Energy Recovery

ENERGY RECOVERY

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ENERGY RECOVERY

EDGARD DUBOIS AND

ARTHUR MERCIER EDITORS

Nova Science Publishers, Inc. New York

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA DuBois, Edgard. Energy recovery / Edgard DuBois and Arthur Mercier. p. cm. Includes index. ISBN 978-1-61728-402-1 (E-Book) 1. Waste products as fuel. I. Mercier, Arthur. II. Title. TP360.D82 2009 662'.87--dc22 2009024627

Published by Nova Science Publishers, Inc.    New York

CONTENTS Preface

vii

Chapter 1

Biogas Recovery from Landfills Sherien A. Elagroudy and Mostafa A. Warith

Chapter 2

Landfill Gas: Generation Models and Energy Recovery Lidia Lombardi

Chapter 3

Energy and Material Recovery from Biomass: The Biorefinery Approach. Concept Overview and Environmental Evaluation Francesco Cherubini and Gerfried Jungmeier

Chapter 4

Pinch Technology for Waste Heat Recovery Applications in Oil Industry Mahmoud Bahy Noureldin

1 69

97

141

Chapter 5

Treatment of Secondary Sludge for Energy Recovery Chunbao (Charles) Xu and Jody Lancaster

Chapter 6

Energy Recovery from Waste: Comparison of different Technology Combinations Lidia Lombardi and Andrea Corti

213

Energy Recovery from Waste Incineration: Linking the Systems of Energy and Waste Management Kristina Holmgren

229

Chapter 7

Chapter 8

Experimental Analysis of a Combined Recovery System R. Herrero Martín

Chapter 9

Energy Recovery Systems from Industrial Plant Waste: Planning of an Industrial Park Located in the South of Italy Silvana Kühtz, Francesca Intini, Sara Bellini and Giovanna Matarrese

Index

187

253

289

311

PREFACE Energy recovery occurs when the energy that is released from a resource recovery process (i.e., pyrolysis/gasification) is used for another purpose such as to generate steam, fuel or electricity generation. This book examines the energy recovery technologies which use landfill gas to produce energy directly. An overview of a variety of secondary sludge post treatment methods for energy recovery is given, including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. The several routes that energy recovery can follow from waste are looked at as well, of which the most common is waste direct combustion associated with conventional energy recovery in a steam turbine cycle. Energy recovery in air conditioning systems to promote energy saving and improve environmental quality is also explored in this book. Chapter 1 - Disposal of municipal wastes can produce emissions of most of the important greenhouse gases (GHG). Solid wastes can be disposed of through landfilling, recycling, incineration or waste-to-energy. This chapter will deal with emissions resulting from landfilling of solid waste. The most important gas produced in this source category is methane (CH4). Approximately 5-20 per cent (IPCC 1992) of annual global anthropogenic CH4 produced and released into the atmosphere is a by-product of the anaerobic decomposition of waste. A major source of this type of CH4 production is solid waste disposal to land. In landfills, methanogenic bacteria break down organic matter in the waste to produce CH4. In addition to CH4, solid waste disposal sites can also produce substantial amounts of carbon dioxide (CO2) and non-methane volatile organic compounds (NMVOC). The gases produced in solid waste disposal sites, particularly CH4, can be a local environmental hazard if precautions are not taken to prevent uncontrolled emissions or migration into surrounding land. Landfill gas is known to be produced both in managed “landfill” and “open dump” sites. Both are considered here as solid waste disposal sites (SWDSs). Gas can migrate from SWDSs either laterally or by venting to atmosphere, causing vegetation damage and unpleasant odors at low concentrations, while at concentrations of 515 per cent in air, the gas may form explosive mixtures. With the recognition of the formation of landfill gas and its associated hazards, and the potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and

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a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site. This chapter will describe the processes that result in gas generation from SWDSs and the factors which affect the amount of CH4 produced. It will then describe two methodologies for estimating CH4 emissions from SWDSs. One of these methods is a default base method which all countries can use to estimate CH4 emissions from different types of SWDSs. It is recommended that countries which have adequate data also estimate their emissions using the second method presented. Finally, this section discusses sources of uncertainty associated with any estimates of CH4 emissions from SWDSs, in particular the availability and quality of data required. Chapter 2 - In this chapter different landfill gas production mathematical models have been analysed, implemented and compared among themselves and with data collected from existing landfills. These models will be presented in the chapter. One of these models has been selected for application to some study cases. The selected model is based on first-order decay equation and considers as basic inputs the years of landfill operation, the amount of municipal solid waste landfilled per year, the municipal solid waste component characterisation and biodegradability. Three different behaviours, in reference to biodegradation rate, have been considered dividing the material categories into rapidly, moderately and slowly biodegradable. The model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system. In particular, reciprocating engines were considered for energy recovery purposes. The landfill gas energy recovery by means of reciprocating engines is a quite widespread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue. For this reason, the selection of an appropriate combination of engines has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions. Further, in order to investigate the management possibilities to enhance energy recovery, the behaviour of a landfill where leachate is recirculated was observed, recording a more concentrated landfill gas production in a shorter time than in conventional landfills - and reproduced by means of adapting the landfill gas production model. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission. Chapter 3 - A great fraction of worldwide energy carriers and material products come from fossil fuel refinery. Because of the on-going price increase of fossil resources, the uncertain availability, the environmental concerns and the fact that they are not a renewable resource, the feasibility of their exploitation is predicted to decrease in the near future. Therefore, alternative solutions able to reduce the consumption of fossil fuels should be promoted. Electricity and heat can be provided by a variety of renewable alternatives (wind,

Preface

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sun, water, biomass), while the fossil resource alternative for production of fuels and chemicals can be just biomass, the only C-rich material source available on the Earth, besides fossils. The replacement of oil with biomass as raw material for fuel and chemical production leads to the development of “biorefinery”, a relatively young concept in the scientific literature. In biorefinery, almost all the types of biomass feedstock can be converted to different classes of biofuels and chemicals through jointly applied conversion technologies. This chapter describes the emerging biorefinery concept and provides an overview of the most important biomass sources, conversion technologies and platforms (or intermediates). The advantages of biorefinery systems over conventional fossil systems are outlined by means of Life Cycle Assessment (LCA): in the second half of this chapter, a LCA of a biorefinery system based on a lignocellulosic feedstock (e.g. wood industrial residues) and producing bioethanol and methyltetrahydrofuran (MTHF) as transportation biofuels, furan resins, fumaric acid and oxygen as chemicals and hydrogen, biomethane, electricity and heat as further energy carriers, is reported. The biorefinery system is compared with a reference system based on fossil sources. Results focus on greenhouse gas (GHG) and energy balances and estimate the possible GHG and fossil energy savings. System performances are also investigated with calculations of product yields and mass, energy, exergy and C conversion efficiencies. Since the biorefinery system co-produces many high value products, an allocation issue must be addressed. Different allocation procedures (substitution method, and energy, exergy, economic allocation) are therefore used and final results compared. The evaluation of the environmental performances reveals that relevant environmental benefits can be gained with a shift from oil refinery to biorefinery: almost 89% of GHG emissions and 96% of fossil energy demand can be saved. Chapter 4 - This chapter addresses the problem of waste heat recovery via presenting an introduction to the pinch technology and two industrial applications of heat integration for waste heat recovery in oil and gas business. Pinch technology, after almost three decades of its emanation in the late seventies for a reason or another, is still the most widely used method for energy integration in oil industry. The chapter comes into two parts; the first part introduces some aspects of Pinch technology in brief. Pinch technology is now well documented in several literatures and the refernces 1 to 4 at the end of this chapter are only few main examples. In this part, authors will show how authors can use pinch technology for energy utility targeting, selection of utility mix and heat exchanger network synthesis using pinch design method [1, 2, 3 and 4]. The second part introduces two important applications for heat integration in oil industry [5]. The first application is showing the effect of heat integration on both energy consumption and GHG emission reduction in an oil-gas separation facility, and in the second application an evolutionary approach to crude distillation pre-heat train design is introduced. Chapter 5 - Primary and secondary sludges are produced as a result of primary and secondary wastewater treatment in municipal wastewater plant or pulp and paper mills. Sludge disposal has become a worldwide problem for many reasons including rapidly shrinking landfill space, increased environmental awareness, more stringent environmental standards governing the disposal of sludge, and dewatering challenges. Unlike the primary sludge, the secondary sludge as byproduct of the biological treatment is far more difficult to dewater and to be disposed. Secondary sludge waste management issues are a continuing challenge. This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. In this chapter, authors have overviewed a variety of secondary sludge post treatment methods for energy recovery,

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including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. A critical comparison between these methods is presented with respect to their net energy efficiencies. The advantages and drawbacks of each treatment option are also highlighted in this chapter. Chapter 6 - Energy recovery from waste can follow several routes. The most common one is waste direct combustion associated with conventional energy recovery in a steam turbine cycle. The combustion can be applied directly to Municipal Solid Waste or can be applied to a stream of selected waste obtained by means of mechanical sorting of Municipal Solid Waste, using several technologies for the combustion, the most common of which is mobile grate combustor. Besides the direct combustion of waste, alternative possibilities for thermal treatment are gasification and pyrolysis. These processes require being fed by a homogeneous combustible fraction obtained by mechanical sorting and supply as output one or more combustible streams, available for energy recovery. When Municipal Solid Waste mechanical sorting is applied, besides the combustible fraction stream, a humid fraction is also obtained, characterised by a high presence of organic biodegradable fraction. At present the fate for this stream is biological aerobic stabilisation, but another option, to push energy recovery also from this stream, is biological anaerobic digestion, which can be applied through different technologies (wet and dry digestion). Through this process a biogas with elevated content of methane can be produced and supplied to engines for energy recovery. The above-mentioned technologies can be combined in several schemes to optimise the overall energy recovery. The combination of schemes will be analysed in this chapter in reference to a study case characterised by an average waste material composition. The comparison will be carried out using some indicators of the overall energy recovery for each scheme. Chapter 7 - Energy recovery from waste incineration has a double function as a waste treatment method and a supplier of electricity and/or heat. Waste incineration thereby links the systems of waste management and energy. This chapter addresses the importance of taking this into consideration when e.g. making investment decisions or designing policy instruments. The design of two policy instruments will be described as examples of the conflicting goals in the two systems. A conflict is also that increased waste incineration can decrease production of combined heat and power in the district heating systems. Since policy instruments in Sweden are dependent on the common legislation of the European Union this will be addressed, together with trading in waste and electricity and how this impacts waste incineration in Sweden. Conflicts between the internal market in the European Union and waste management goals are shown. When making investment decisions, various models are often used as decision support tools. Some models for assessing waste incineration/ management are therefore described together with strengths and weaknesses when dealing with the dual function of waste incineration. Chapter 8 - The present work is found in the field of energy recovery in air conditioning systems to promote energy saving and improve environmental quality. Experimental research has been carried out whose aim is the characterization of combined recovery equipment, consisting of a ceramic semi-indirect evaporative cooler and a heat pipe device to recover energy at low temperature in air conditioning systems. For characterization purposes, a design of experiment (DOE) and an analysis of variance (ANOVA) were applied with the aim of

Preface

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better understanding the energy behaviour of the combined device. The combined system built allows a feasible energy exchange between the supply airstream and the return one, improving the operation in air-conditioning systems. It is a new alternative device for use as a recovery system. The configuration chosen (crossed flow) is the most adequate from an operational point of view. The characterization of the system was carried out by employing experimental design methodology. A factorial design was performed by analysing how the factors used affect the characteristics analyzed. The contributions of the single factors and their interactions were presented by carrying out a variance analysis. The superiority of the evaporative cooling device under the operating conditions was clearly shown. An estimation of the energy saved by the combined system was carried out, showing the possibilities of implementing this solution to save energy and also to improve the indoor air quality by means of increasing the ventilation rates. Chapter 9 - In this chapter, authors compare environmental and technological aspects of some innovative energy recovery systems from industrial waste. The authors present the results of a research study that authors are conducting on an Italian firm that produces polyethylene terephthalate (PET) supports for waterproof membranes from plastic bottles. For this firm (and all of the firms in the same industrial park), the waste represents only an undesired cost rather than a potential energy source. The authors first compared a traditional thermal waste treatment with a molecular dissociator and then with a specific gasifier. All three technologies can be fed with basically every type of waste, and can produce electric and/or thermal energy. In particular, the latter two produce syngas that can be burned after depuration to produce energy. A cost-benefit analysis is then carried out to plan how the whole industrial park can use the industrial waste to produce the energy it needs, with economic and environmental benefits for all.

In: Energy Recovery Editors: Edgard DuBois and Arthur Mercier

ISBN: 978-1-60741-065-2 © 2009 Nova Science Publishers, Inc.

Chapter 1

BIOGAS RECOVERY FROM LANDFILLS 1

Sherien A. Elagroudy and 2Mostafa A. Warith*

1

Civil Engineering Department, Ain Shams University Univeristy, 13 El-Makreezy Street, Manshiett Elbakry, Heliopolis, Cairo, Egypt, 11341 2 Ryerson Polytechnic University, Civil Engineering Department, 350 Victoria Street, Toronto, ON, Canada, M5B 2K3,

ABSTRACT Disposal of municipal wastes can produce emissions of most of the important greenhouse gases (GHG). Solid wastes can be disposed of through landfilling, recycling, incineration or waste-to-energy. This chapter will deal with emissions resulting from landfilling of solid waste. The most important gas produced in this source category is methane (CH4). Approximately 5-20 per cent (IPCC 1992) of annual global anthropogenic CH4 produced and released into the atmosphere is a by-product of the anaerobic decomposition of waste. A major source of this type of CH4 production is solid waste disposal to land. In landfills, methanogenic bacteria break down organic matter in the waste to produce CH4. In addition to CH4, solid waste disposal sites can also produce substantial amounts of carbon dioxide (CO2) and non-methane volatile organic compounds (NMVOC). The gases produced in solid waste disposal sites, particularly CH4, can be a local environmental hazard if precautions are not taken to prevent uncontrolled emissions or migration into surrounding land. Landfill gas is known to be produced both in managed “landfill” and “open dump” sites. Both are considered here as solid waste disposal sites (SWDSs). Gas can migrate from SWDSs either laterally or by venting to atmosphere, causing vegetation damage and unpleasant odors at low concentrations, while at concentrations of 5-15 per cent in air, the gas may form explosive mixtures. With the recognition of the formation of landfill gas and its associated hazards, and the potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the *

J. Patrick A. Hettiaratchi, PhD, PEng, Professor of Environmental Engineering, Associate Head of Undergraduate Studies, Department of Civil Engineering, and Center for Environmental Engineering Research & Education (CEERE), University of Calgary, Calgary, Alberta, Canada, Tel. 403-220-5503; Fax. 403-282-7026, [email protected]

2

Sherien A. Elagroudy and Mostafa A. Warith landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site. This chapter will describe the processes that result in gas generation from SWDSs and the factors which affect the amount of CH4 produced. It will then describe two methodologies for estimating CH4 emissions from SWDSs. One of these methods is a default base method which all countries can use to estimate CH4 emissions from different types of SWDSs. It is recommended that countries which have adequate data also estimate their emissions using the second method presented. Finally, this section discusses sources of uncertainty associated with any estimates of CH4 emissions from SWDSs, in particular the availability and quality of data required.

I. INTRODUCTION Throughout Europe and the United States, there is a strong reliance on disposing of waste in landfills. Furthermore, in many developing countries, conditions for waste disposal are still rudimentary. In 1997, for instance, 99% (around 90,000 tons per day) of Brazil's collected waste was being landfilled or simply dumped. Each person in the United Staes generates about 4.5 pounds of waste per day, which is nearly 1 ton per year. Again, most of this waste is deposited in municipal solid waste (MSW) landfills. As MSW decomposes, it produces a blend of several gases, including methane (about 50%). Landfilling is the oldest and most widely practiced waste disposal option. Modern landfill sites have developed from uncontrolled dumping sites to be an advanced treatment and disposal option designed and managed as engineering projects. In addition, modern purposebuilt landfill sites normally incorporate a system for the extraction of landfill gas (arising from the decomposition of biodegradable wastes), from which energy can be recovered. The types of wastes suitable for landfilling include biodegradable wastes, aqueous liquids in limited amounts, inert wastes, and certain special wastes that would not pose toxic threats. Wastes that are generally considered unsuitable for landfilling include volatile liquids or solvents, wastes that would introduce unacceptable contamination into the leachate, and wastes that would interfere with the biological processes in a landfill site. More recently, increasing attention has focused on the role of CH4 in global atmospheric change. Methane from SWDSs contributes a significant proportion of annual global CH4 emissions, although the estimation is subject to a great deal of uncertainty. Estimates of global CH4 emissions from SWDSs range from less than 20 to 70 Tg/yr (Bingemer and Crutzen 1987; US EPA 1994), or about 5 per cent to 20 per cent of the total estimated emissions of 375 Tg/yr (IPCC 1996) from anthropogenic sources globally. There are eight sections in this chapter. Section 2 discusses environmental regulations as they pertain to landfill gas emissions. Regulations addressed in this section include the European Landfill Directive [1999/31/EC], Resource Conservation and Recovery Act (RCRA) solid and hazardous waste management requirements, Clean Air Act (CAA) requirements, and Clean Water Act (CWA) requirements associated with landfill emissions. An overview of the different types of bioreactor landfills as a development to sanitary landfills is provided in Section 3 along with bioreactor features and advantages. Section 4

Biogas Recovery from Landfills

3

provides a broad overview on Landfill gas (LFG) characteristics, composition, LFG production and methods of enhancement, and gas yield. It also discusses gas-generation mechanisms and gas-transport mechanisms and factors affecting both mechanisms. Gases generated in the landfill will move throughout the mass of waste in addition to movement or migration out of the site. Section 5 focuses on LFG movement and generation and LFG monitoring programs. Landfill gas may form an explosive mixture when it combines with air in certain proportions, LFG hazards including explosion, asphyxiation hazards and odor are also discussed in this section. Section 6 discusses LFG generation models. Several models are available for estimating the LFG generation rate using site-specific input parameters. These models vary widely, not only in the assumptions that they make, but also in their complexity, and in the amount of data they require. The LandGEM model is one of these models and was developed by the US Environmental Protection Agency to estimate landfill gas emissions and to determine regulatory applicability to CAA requirements. There are other LFG emission models in use by industry that also work very well. The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of CH4 emissions from the landfills is based on First-Order decay (FOD) method. These 2 models are explained in details in this section. LFG regression models using sitespecific data are also discussed in this section along with mathematical models. Section 7 provides an overview of landfill gas energy recovery system. The energy recovery technology is based around the gas collection system and the pre-treatment and power generation technology. Each of those three systems is explained separately in details in this section. Section 8 covers the Calgary biocell as a full-scale case study that is constructed in Calgary, Canada. It is a unique facility where the three processes, anaerobic bioreactor, aerobic bioreactor and mining are sequentially applied in one cell. The stages of operation of the cell and the LFG data collected over 2 years from the cell are provided in this section. Anaerobic decomposition of organic solid waste in the landfill environment produces landfill gas (LFG). LFG mainly consists of methane and carbon dioxide, both of which are odorless. Trace constituents of other volatiles, often malodorous or toxic gases, are also found in LFG. LFG can migrate through soil into structures located on or near landfills. Since methane presents a fire or explosive threat, LFG must be controlled to protect property, and public health and safety. Also, many jurisdictions require landfill owners/operators to reduce reactive organic gas emissions to improve regional air quality. Thus, engineered solutions are needed to efficiently and safely monitor, collect, and process landfill gas. As noted, a positive side to LFG control is energy recovery. Today's technology allows a landfill owner/operator to recovery the energy in LFG while reducing gas emissions. Revenue from the sale of LFG or electricity generated using LFG as a fuel can offset costs for landfill environmental compliance and/or closure.

II. REGULATORY CONSIDERATIONS This section discusses environmental regulations as they pertain to landfill gas emissions. Regulations addressed in this section include the European Landfill Directive [1999/31/EC], Resource Conservation and Recovery Act (RCRA) solid and hazardous waste management requirements, Clean Air Act (CAA) requirements, and Clean Water Act (CWA) requirements

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associated with landfill emissions. Many of the regulations discussed below apply to currently operating or recently closed landfills and may not be appropriate for landfills that stopped receiving wastes prior to 1987. It is important that personnel know the regulatory framework under which the LFG control is being done (e.g., Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) remediation, RCRA Corrective Action, etc.) in order to determine which, if any of the following requirements must be met. The discussion of applicable regulations and legal requirements in this section is only meant to make the reader aware of some of the many requirements that may potentially apply to landfill gas emissions and disposal of condensate. This chapter is not intended to stand in place of any applicable law, regulation, or standard and may not reflect the current standards embodied in law and regulation. Statutes and regulations are the controlling rule of law and should always be consulted to determine how they apply to a particular set of circumstances to assure compliance before action is taken. Regulations affecting LFG management are addressed under various legislations including: • • • •

Landfill Directive 1999/31/EC The RCRA which regulates solid and hazardous waste management such as the landfill itself. The CAA which regulates air emissions. The CWA which regulates discharges of water such as LFG condensate and storm water runoff.

A brief summary of these regulations applicable is presented in the following section.

A. U Landfill Directive 1999/31/EC The EU Landfill Directive [1999/31/EC] became law on 16 July 1999 after a protracted drafting process. It was published in the Official Journal of the European Communities on the 16th July 1999. Member States were required to bring into force the laws, regulations and administrative provisions necessary to comply with the Landfill Directive not later than two years after its entry into force i.e. the 16th July 2001. The aim of the Directive is "by way of stringent operational and technical requirements on the waste and landfills, to provide for measures, procedures and guidance to prevent, or reduce as far as possible, negative effects on the environment, in particular the pollution of surface water, groundwater, soil and air, and on the global environment, including the greenhouse effect, as well as any resulting risk to human health, from landfilling of waste, during the whole life-cycle of the landfill." (Waste Landfill Directive, 1999) The Landfill Directive sets requirements for the authorization, design, operation, closure and aftercare of landfills. The reduction of the biodegradable fraction of municipal waste going for landfill disposal is given specific targets in the Landfill Directive. Some wastes may no longer be accepted in landfills and only wastes that fulfill certain acceptance criteria may be disposed of in the appropriate class of landfill. In addition to the Landfill Directive, the

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Council Decision 2003/33/EC established the criteria and procedures for the acceptance of waste in landfills (commonly referred to as Waste Acceptance Criteria (WAC)). The Directive encompasses the requirements of Articles 3 and 4 of 75/442/EEC (The Framework Directive). It also covers the technical requirements for landfills covered by the IPPC Directive (Council Directive 96/61/EC). The Directive has 19 Articles and 3 Annexes covering General Requirements, WAC, and Control and Monitoring. Central to the Directive is the requirement (Article 5) that all Member States shall introduce measures to reduce the quantities of biodegradable material going to landfill, to 35% of 1995 levels by 2016. Up to 4 years' derogation from this is possible for countries currently landfilling more than 80% of wastes. The Directive also requires Member States to set up a national strategy for the implementation of these targets.

B. RCRA Regulations Under RCRA, if LFG is emitted or condensate is treated and/or disposed of, RCRA requirements may have to be met. Primary RCRA requirements pertaining to LFG emission and condensate disposal are found in the following regulations: • • • •

40 CFR Part 258 [regulations for LFG emissions from MSW (non-hazardous) landfills] 40 CFR Parts 260-261 [regulations for characterization and disposal of condensate] 40 CFR Part 262 [regulations pertaining to generator requirements] 40 CFR Part 268 [regulations for land disposal restrictions]

C. CAA Regulations Since passage of the Federal CAA in 1970, many rules and regulations have been adopted that could potentially affect LFG operations. The applicability of these rules and regulations are governed by specific factors such as the implementation schedule of the rule, size of the facility, the equipment and type of operations conducted at the site, and the emissions from these operations. Personnel need to be familiar with the specific requirements of each regulation prior to deciding whether or not the requirements apply to their project. Potentially applicable CAA regulations include: • • • •

New Source Performance Standards (NSPS) found at 40 CFR Part 60 National Emission Standards for Hazardous Air Pollutants found at 40 CFR 63 Title V Operating Permits found at 40 CFR Part 70 State and local air quality regulations

The Environmental Protection Agency (EPA) designed the Title V operating permit program as a central mechanism to regulate emissions, monitoring data needs, compliance schedules, fee payments, and other conditions associated with the issuance, compliance and enforcement of operating permits. Personnel involved in designing LFG control systems

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should ensure that the customer is made aware of calculated LFG emissions and what control devices will be used to control them. This information is important to the customer who is ultimately responsible for determining the need to obtain a Title V operating permit or to revise an existing permit. Any questions regarding the need to obtain an operating permit for the LFG control system should be discussed with the customer and the project team.

D. CWA Regulations Under the CWA, if LFG condensate is disposed of by treatment and effluent discharge to Waters of the United States, discharge permits may be required and effluent concentrations/limits may be required to meet a state's water quality standards. Effluent analyses required for all discharge permits can include: • • • • • • • •

Biochemical Oxygen Demand (BOD) Chemical Oxygen Demand (COD) Total Organic Carbon (TOC) Total Suspended Solids (TSS) Ammonia Temperature pH Flow

Response actions taken under CERCLA are not required to obtain discharge permits. However, substantive requirements such as numerical discharge limits may still have to be established and met at these sites, especially when condensate is discharged via a point source to Waters of the U.S. Other analyses may be required if other pollutants are expected to be present. If the condensate is disposed of by indirect discharge through a publicly owned treatment works (POTW), sewer effluent conditions will be imposed by the local POTW as regulated by local ordinances or federal requirements.

III. SANITARY AND BIOREACTOR LANDFILLS A. Development of Sanitary Landfills In the past, a landfill often represented little more than an open hole or mash where refuse was dumped. The refuse was often not covered properly, sometimes it was burned for volume reduction, and there was little effort to control storm water runoff and downward migration of water that had come into contact with the refuse (Barlaz 1997). With the implementation of increasingly stringent regulations, landfills have become highly engineered facilities with sophisticated containment systems, environmental monitoring, and improved operational practices.

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As a generality, a typical dry landfill has an impermeable bottom liner, the wastes are delivered to the landfill, spread out, compacted and covered at the end of the day with a thin layer of soil, until a planned depth is reached, then the waste is covered with an impermeable cap. The environmental barriers such as landfill liners and covers exclude moisture that is essential to waste biodegradation. Consequently, wastes are contained in a “dry tomb” and remain intact for long periods of time ranging from 30 to 200 years, possibly in excess of the life of the landfill barriers and covers. Liner failure could happen in conventional dry landfill sometime in future, which can cause serious groundwater and surface water contamination (Warith 2003). Nowadays, siting new landfills has been very difficult and costly not only because landfills can threaten the environment, but also because the public opposition, this often called the NIMBY, or not in my back yard, syndrome. Therefore, the condition appeals to investigators to make efforts to make landfills more economically sound and environmentally friendly (Stessel and Murphy 1992). Today, the “bioreactor landfill” is one idea that has gained significant attention. A bioreactor landfill is a sanitary landfill that uses enhanced microbiological processes to transform and stabilize the readily and moderately decomposable organic waste constituents within 5 to 10 years of bioreactor process implementation. The bioreactor landfill significantly increases the extent of organic waste decomposition, conversion rates and process effectiveness over what would otherwise occur within the landfill (Pacey et al. 1999). The “bioreactor landfill” provides control and process optimization, primarily through the addition of leachate or other liquid amendments, the addition of sewage sludge or other amendments, temperature control, and nutrient supplementation (Reinhart et al. 2002). Beyond that, bioreactor landfill operation may involve the addition of air. Based on waste biodegradation mechanisms, different kinds of “bioreactor landfills” including anaerobic bioreactors, aerobic bioreactors, and aerobic-anaerobic (hybrid) bioreactors have been constructed and operated worldwide. According to the survey conducted by the Solid Waste Association of North America (SWANA) in 1997, there were over 130 leachate recirculation landfills in USA (Gou and Guzzone 1997; Reinhart et al. 2002). Generally, there are four advantages for employing bioreactor landfill technology comparing to conventional dry landfills: (1) contain and treat leachate, (2) rapidly recover air space, (3) accelerate waste stabilization and avoid long-term monitoring and maintenance and delay siting of a new landfill, and (4) make more potential benefits from increased methane generation in anaerobic bioreactor landfill. For aerobic bioreactor landfill, there are three other advantages: (1) significant increase in the biodegradation rate of the MSW over anaerobic processes, (2) a reduction in the volume of leachate, and (3) significantly reduced methane generation and “anaerobic” odors. However, Costs for continuous supply of air are excessively high for municipal solid waste treatment (Hanashima, 1999).

B. Bioreactor Landfills There are three types of bioreactor technology: 1. Anaerobic Bioreactor Landfills 2. Aerobic Bioreactor Landfills 3. Aerobic-Anaerobic Bioreactor Landfills

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1. Anaerobic bioreactor landfills The Anaerobic Bioreactor seeks to accelerate the degradation of waste by optimizing conditions for anaerobic bacteria. In landfills, consortia of anaerobic bacteria are responsible for the conversion of organic wastes into organic acids and ultimately into methane and carbon dioxide. Anaerobic conditions develop naturally in nearly all landfills without any intervention. The waste in typical landfills contains between 10 and 25 percent water. It is generally accepted that to optimize anaerobic degradation moisture conditions at or near field capacity, or about 35 to 45 percent moisture, are required. Moisture is typically added in the form of leachate through a variety of delivery systems. However, the amount of leachate produced at many sites is insufficient to achieve optimal moisture conditions in the waste. Additional sources of moisture such as sewage sludge, storm water, and other non-hazardous liquid wastes may therefore be necessary to augment the leachate available for recirculation. As the moisture content of the waste approaches optimal levels, the rate of waste degradation increases, this in turn leads to an increase in the amount of landfill gas produced. Also observed is an increase in the density of the waste. While the rate of gas production in an anaerobic bioreactor can be twice as high as a normal landfill, the duration of gas production is significantly shorter. Because of this accelerated production, gas collection systems at bioreactor landfills must be capable of handling a higher peak volume but need do so for a shorter period of time. The anaerobic biodegradation of MSW follows three sequenced biochemical reactions involving three different groups of anaerobic bacteria which are: (1) Fermentative and hydrolystic bacteria, (2) Acidogenic bacteria and (3) Methanogenic bacteria. In the anaerobic stage, there are four steps involved in the bacteria groups to convert waste into biogas (CH4, CO2) as end products, and organic acids as intermediate products. The four steps are hydrolysis, acidogenesis, acetogenesis and methanogenesis (Jin, 2005). Figure 1 shows a cut-away view of an anaerobic bioreactor with elevated levels of ammonium in the leachate. Leachate is removed via pipes from the bottom of the landfill and piped to an on-site biological leachate treatment facility. The treated leachate and other liquids are then reinjected into the landfill. At the same time, gas generated by the decomposing waste rises through the landfill, and is collected by pipes within the waste and on top of the landfill. The landfill gas that is collected is used to generate energy. Groundwater monitoring occurs at monitoring wells situated around the perimeter of the landfill (U.S EPA 2004).

2. Aerobic bioreactor landfills The Aerobic Bioreactor seeks to accelerate waste degradation by optimizing conditions for aerobes. Aerobes are organisms that require oxygen for cellular respiration. In aerobic respiration, energy is derived from organic molecules in a process that consumes oxygen and produces carbon dioxide. Aerobes require sufficient water to function just as anaerobes do. However, aerobic organisms can grow more quickly than anaerobes because aerobic respiration is more efficient at generating energy than anaerobic respiration. One consequence of this is that aerobic degradation can proceed faster than anaerobic degradation. Another consequence is that aerobic respiration can generate large amounts of metabolic heat, which requires significant quantities of water. In landfills aerobic activity is promoted through

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injection of air or oxygen into the waste mass. It is also possible to apply a vacuum to the waste mass and pull air in through a permeable cap. Liquids are typically added through leachate recirculation, with the need for additional sources of moisture even more acute than for anaerobic reactors. The aerobic process does not generate methane. Figure 2 shows a cut-away view of an aerobic bioreactor. Leachate is removed from the bottom layer of the landfill and piped to a liquids storage tank. From the tank, the leachate is piped across the top layer, where it is released to filter down through the landfill to be collected again. A blower forces air into the waste mass through vertical or horizontal wells located in the top layer of the landfill. Groundwater monitoring occurs at wells situated around the perimeter of the landfill (U.S EPA 2004).

Figure 1. Anaerobic Bioreactor Landfill (U.S EPA 2004)

Figure 2. Aerobic Bioreactor Landfill (U.S EPA 2004)

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3. Aerobic-anaerobic bioreactor landfills The Aerobic-Anaerobic Bioreactor is designed to accelerate waste degradation by combining attributes of the aerobic and anaerobic bioreactors. The objective of the sequential aerobic-anaerobic treatment is to cause the rapid biodegradation of food and other easily degradable waste in the aerobic stage in order to reduce the production of organic acids in the anaerobic stage resulting in the earlier onset of methanogenesis. In this system the uppermost lift or layer of waste is aerated, while the lift immediately below it receives liquids. Landfill gas is extracted from each lift below the lift receiving liquids. Horizontal wells that are installed in each lift during landfill construction are used convey the air, liquids, and landfill gas. Figure 3 shows a cut-away view of an aerobicanaerobic bioreactor. The principle advantage of the hybrid approach is that it combines the operational simplicity of the anaerobic process with the treatment efficiency of the aerobic process. Added benefits include an expanded potential for destruction of volatile organic compounds in the waste mass.

C. Features Unique to Bioreactor Landfills The bioreactor accelerates the decomposition and stabilization of waste. At a minimum, leachate is injected into the bioreactor to stimulate the natural biodegradation process. Bioreactors often need other liquids such as stormwater, wastewater, and wastewater treatment plant sludge to supplement leachate to enhance the microbiological process by purposeful control of the moisture content and differs from a landfill that simple recirculates leachate for liquids management. Landfills that simply recirculate leachate may not necessarily operate as optimized bioreactors.

Figure 3. Aerobic-Anaerobic Bioreactor Landfill (U.S EPA 2004)

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Moisture content is the single most important factor that promotes the accelerated decomposition. The bioreactor technology relies on maintaining optimal moisture content near field capacity (approximately 35 to 65%) and adds liquids when it is necessary to maintain that percentage. The moisture content, combined with the biological action of naturally occurring microbes decomposes the waste. The microbes can be either aerobic or anaerobic. A side effect of the bioreactor is that it produces landfill gas (LFG) such as methane in an anaerobic unit at an earlier stage in the landfill’s life and at an overall much higher rate of generation than traditional landfills.

D. Potential Advantages of Bioreactor Landfills Decomposition and biological stabilization of the waste in a bioreactor landfill can occur in a much shorter time frame than occurs in a traditional “dry tomb” landfill providing a potential decrease in long-term environmental risks and landfill operating and post-closure costs. Potential advantages of bioreactors include: • • • • • •

Decomposition and biological stabilization in years vs. decades in “dry tombs” Lower waste toxicity and mobility due to both aerobic and anaerobic conditions Reduced leachate disposal costs A 15 to 30 percent gain in landfill space due to an increase in density of waste mass Significant increased LFG generation that, when captured, can be used for energy use onsite or sold Reduced post-closure care

Research has shown that municipal solid waste can be rapidly degraded and made less hazardous (due to degradation of organics and the sequestration of inorganics) by enhancing and controlling the moisture within the landfill under aerobic and/or anaerobic conditions. Leachate quality in a bioreactor rapidly improves which leads to reduced leachate disposal costs. Landfill volume may also decrease with the recovered airspace offering landfill operators an extension for the operating life of the landfill. LFG emitted by a bioreactor landfill consists primarily of methane and carbon dioxide plus lesser amounts of volatile organic chemicals and/or hazardous air pollutants. Research indicates that the operation of a bioreactor may generate LFG earlier in the process and at a higher rate than the traditional landfill. The bioreactor LFG is also generated over a shorter period of time because the LFG emissions decline as the accelerated decomposition process depletes the source waste faster than in a traditional landfill. The net result appears to be that the bioreactor produces more LFG overall than the traditional landfill does. Some studies indicate that the bioreactor increases the feasibility for cost effective LFG recovery, which in turn would reduce fugitive emissions. This presents an opportunity for beneficial reuse of bioreactor LFG in energy recovery projects. Currently, the use of LFG (in traditional and bioreactor landfills) for energy applications is only about 10 percent of its potential use. The US Department of Energy estimates that if the controlled bioreactor technology were applied to 50 percent of the waste currently being landfilled, it could provide over 270 billion cubic feet of methane a year, which is equivalent to one percent of US electrical needs.

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IV. LANDFILL GAS (LFG) This section covers LFG characteristics, composition, LFG production, and gas yield. It also discusses gas-generation mechanisms and gas-transport mechanisms and factors affecting both mechanisms.

A. Landfill Gas Characteristics Landfill gas is typically a combination of methane, carbon dioxide, and nonmethanogenic organic compounds. Table 1 shows characteristics of some of the typical components of landfill gas.

1. Density and viscosity The density of LFG depends on the proportion of gas components present. For example, a mixture of 10 percent hydrogen and 90 percent carbon dioxide, such as might be produced in the first stage of anaerobic decomposition, will be heavier than air, while a mixture of 60 percent methane and 40 percent carbon dioxide, such as might be produced during the methanogenic phase of decomposition, will be slightly lighter than air. Some typical values for density and viscosity at 00C and atmospheric pressure are given in Table 2. Table 1. Landfill Gas Characteristics Constituent

Relative Specific Gravity

Concentration in Landfill Gas

Air

1

NA

Methane

0.554

40-70%

Carbon Dioxide

1.529

30-60%

Hydrogen Sulfide

1.19

800 ppm

Water Vapor

0.62

100% Saturated

Benzene

2.8

30 ppm

Toluene

3.1

300 ppm

Organic Acids Organosulphur Compounds

GT 2

Traces

Forms explosive mixture with methane Explosive; LEL 5% in air; UEL 15% in air Forms weak acid; Asphyxiant Forms strong acid Toxic: PEL = 10 STEL = 15 Forms acids with hydrogen sulfide and carbon dioxide Flammable Toxic: PEL 1.0 ppm STEL 5 ppm Toxic: PEL 100 ppm STEL 150 ppm Odorous

GT 1.5

50 ppm

Odorous

Notes

Source: US Army Corps of Engineers (2008) LEL = lower explosive limit; UEL = upper explosive limit; STEL = short-term-exposure limit; PEL = permissible exposure limit.

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Table 2. Typical Values for Gas Density and Viscosity at (00C) Gas Air Methane Carbon Dioxide 50% CH4+ 50% CO2 60% CH4+ 40% CO2

Density (kg/m3) 1.29 0.72 1.9 1.35 1.19

Viscosity (Pa*s) 1.71 × 10–5 1.03 × 10–5 1.39 × 10–5 1.21 × 10–5 1.17 × 10–5

Source: US Army Corps of Engineers (2008)

2. Heat value content During the methanogenic stage, LFG can be expected to have a heating value of 18.6 MJ/m3 under good conditions. This value is about half that of natural gas. The actual heating value of the gas from a landfill is a function of the type age of the waste, the type of landfill cover, and many other factors.

3. Non-methane organic compounds If a landfill contains a significant amount of municipal solid waste, the gas produced will consist of approximately 50 percent methane, 50 percent carbon dioxide, and trace amounts of non-methane organic compounds (NMOC). The concentration of NMOC can range from 200 to 15,000 ppm according to research from the EPA. In the EPA study, ethane, toluene, and methylene chloride were found at the highest concentrations in landfill gas with average reported values of 143, 52, and 20 ppm, respectively. The most frequently detected compounds reported were trichloroethene, benzene, and vinyl chloride. During the design phase of a landfill closure, historical records or word of mouth information should be obtained as to the type of wastes that were placed in the landfill and the potential for these wastes to create off-gas emissions.

4. Water vapor Gas created during the decomposition of organic compounds typically includes between 4 and 7 percent by volume water vapor. The actual water vapor content of LFG will depend on the temperature and pressure within the landfill. Temperatures are typically elevated over ambient during biological decomposition, increasing the evaporation of water into the LFG.

5. Others Hydrogen is produced during waste decomposition, particularly during the initial anaerobic conversion of mixed organic acids to acetic acid. Significant amounts of hydrogen are later consumed in the formation of CH4. Hydrogen is flammable between 4 and 74 percent, by volume, in air. The presence of CO2 affects these ranges although little significant change occurs near the lower limit of the range

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B. Landfill Gas Composition LFG is the product of microbiological decomposition of land-filled garbage. The microorganisms turn complex organic compounds in garbage into methane, carbon dioxide, and trace amounts of other compounds. The composition of landfill gas depends on the activity of the bacteria involved, the available substrate and other factors. Landfill gases can be classified into three groups: (1) major components which consist of methane and carbon dioxide; (2) minor components which consist of ammonia, hydrogen, hydrogen sulfide, nitrogen, and carbon monoxide; and (3) trace compounds known as ‘trace gases’, mainly volatile organic compounds (VOC) (Tchobanouglous et al. 1977). Table 3 shows the composition of major and minor compounds in landfill gases, whereas Table 4 shows the concentration of various VOC in landfill gases (Tchobanouglous et al. 1993). Methane comprises about 50- 55% of LFG, while 40-45% of LFG is carbon dioxide. Methane is the most reduced organic molecule. In other words, no further conversions to simpler organic molecules are possible once methane has been produced. It is produced as an end product of anaerobic metabolism. Methane is a short-lived GHG with an atmospheric lifetime of approximately 12 years compared to over 100 years for carbon dioxide. It is 21 times more potent as a GHG, kilogram for kilogram, than carbon dioxide. The balance of the input rate and the removal rate determines atmospheric concentrations of GHG. There will be a greater impact by concentrating on methane in the medium-term because it is short lived in the atmosphere and has a high global warming potential (GWP). Some 60 percent of methane emissions come from anthropogenic sources, with around 40 percent from natural sources. Over 550 trace gases have been identified to date, and doubtless more will yet be discovered. The trace components have chemical or physical properties that differ significantly from the bulk gases. Also, it is known that some of these trace components, when present above threshold concentrations, cause physiological effects and thus have potential health impacts. Just sixty two landfill gas trace substances were then more recently identified within the landfill gas source-term as those from the list of 500, being likely to be present at a significant concentration and to be worthy of further consideration. Table 3. Typical Composition of Landfill Gas Component Methane Carbon dioxide Nitrogen Oxygen Sulfides Ammonia Hydrogen Carbon monoxide Trace constituents (Source: Tchobanouglous et al., 1993)

Percent (volume basis) 45 – 65 40 – 60 2–5 –1 0–1 –1 0 – 0.2 0 – 0.2 0.01 – 0.6

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C. Landfill Gas Yield Methane yield is defined as the total amount of methane generated per unit weight (dry or wet) of MSW (El-Fadel et al. 1996a). The methane yield is a function of waste composition. Eleazer et al. (1997) found that the methane yield increased as cellulose and hemicelluose content increased. The methane yield was reviewed by El-Fadel et al. (1996a). There are two approaches for estimating this yield: theoretical and experimental The Theoretical approach uses the stoichiometric and biodegradability methods to estimate the gas yield. The stoichiometric method is based on several assumptions, such as whether or not complete degradation of waste has occurred; the degradation product only includes CH4 and CO2; the balance of substrates and nutrients is available at all times in all places in the landfill, and no portion of the degraded matter is utilized into cell growth (Ham 1979). The following equation is commonly used to estimate the theoretical landfill gas yield: .

b c 3d e ⎞ ⎛ ⎛ a b c 3d e ⎞ + ⎟ H 2O ⇒ ⎜ + − − − ⎟ CH 4 + C a H b Oc N d S e + ⎜ a − − + 4 2 4 2⎠ ⎝ ⎝2 8 4 8 4⎠ [1] ⎛ a b c 3d e ⎞ + ⎟ CO2 + d NH 3 + e H 2 S ⎜ − + + ⎝ 2 8 4 8 4⎠ Table 4. Typical Concentrations of VOCs Compounds in Landfills Gases Concentration, ppbV (Part per billion per volume) Median Mean Maximum Acetone 0 6,838 240000 Benzene 932 2057 39000 Chlorobenzene 0 82 1640 Chloroform 0 245 12000 1,1-Dichloroethane 0 2801 36000 Dichloromethane 1150 25694 620000 1,1-Dichloroethene 0 130 4000 Diethylene chloride 0 2835 20000 trans-1,2-Dichloroethane 0 36 850 Ethylene dichloride 0 59 2100 Ethyl benzene 0 7334 87500 Methyl ethyl ketone 0 3092 130000 1, 1, 1-Trichloroethane 0 615 14500 Trichloroethylene 0 2079 32000 Toluene 8125 34907 280000 1, 1, 2, 2-Tetrachloroethane 0 246 16000 Tetrachloroethylene 260 5244 180000 Vinyl chloride 1150 3508 32000 Styrenes 0 1517 87000 Vinyl acetate 0 5663 240000 Xylenes 0 2651 38000 (Source: Tchobanouglous et al., 1993) Compound

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Sherien A. Elagroudy and Mostafa A. Warith Table 5. Methane Yield Based on the Stoichiometric Method

Sources Barlaz et al. (1989) Ham et al. (1989) El-Fadel et al. (1996) Peer et al. (1993)

Methane (L/kg dry waste) 373 carbohydrate 274 protein 270 220-270 230-270

(Source: El-Fadel et al. 1997)

Using this method, the estimated yield of the landfill gas is 440 L/kg wet waste with a composition of 53% methane and 46% CO2 (Ham 1979). El-Fadel et al. (1997) reported, based on the stoichiometric method that the estimated methane yield is in the range of 220270 L/kg dry waste after complete decomposition. Table 5 summarizes the estimated methane yield based on this method. In the experimental approach, the landfill gas yield can be obtained from laboratory scale studies. The amount of biogas produced by biodegradation of MSW can be measured in the laboratory. The biodegradation of MSW can be controlled and enhanced by manipulating environmental factors such as pH, temperature, moisture, nutrients, etc. The range of methane yield from lab scale studies varies from no generation to 107 L CH4/kg dry waste.

D. LFG Emission LFG emissions are governed by gas-generation mechanisms and gas-transport mechanisms. The following paragraphs describe these mechanisms and the major factors influencing gas generation and transport.

1. LFG Generation 1.1. LFG generation mechanisms The three primary causes of LFG generation are volatilization, biological decomposition, and chemical reactions. Volatilization Volatilization is due to the change of chemical phase equilibrium that exists within the landfill. Organic compounds in the landfill volatilize until the equilibrium vapor concentration is reached. This process is accelerated when biological activity increases the temperature of the waste mass. The rate at which compounds volatilize depends on their physical and chemical properties. Biological decomposition The rate and composition of landfill gas vary according to the stabilization stages of MSW. Five main stages of degradation of biodegradable wastes have been identified (Kjeldsen et al 2002; Waste Management Paper 26B, 1995; McBean et al 1995). Figure 4

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shows the decomposition pathways of the major organic and inorganic components of biodegradable wastes, and Figure 5 shows the process in more detail (Waste Management Paper 26B, 1995). Throughout the process of degradation, because of the heterogeneous nature of waste, all the different stages may be progressing simultaneously until all the waste has reached stage five and stabilization of the landfill has been reached.

Figure 4. Major stages of waste degradation in landfills. Source: Waste Management Paper 26B, 1995.

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Figure 5. Details of the stages of waste degradation in landfills. Source: Waste Management Paper 26B, 1995.

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Stage I. Hydrolysis/aerobic degradation The hydrolysis/aerobic degradation stage occurs under aerobic (in the presence of oxygen) conditions. This occurs during the emplacement of the waste and for a period thereafter which depends on the availability of oxygen in the trapped air within the waste. The micro-organisms are of the aerobic type, that is, they require oxygen and they metabolise the available oxygen and a proportion of the organic fraction of the waste to produce simpler hydrocarbons, carbon dioxide, water and heat. The heat generated from the exothermic degradation reaction can raise the temperature of the waste to up to 70–90 °C (McBean et al. 1995; Waste Management Paper 26B 1995). However, compacted waste achieves lower temperatures due to the lower availability of oxygen. Water and carbon dioxide are the main products, with carbon dioxide released as gas or absorbed into water to form carbonic acid, which gives acidity to the leachate. The aerobic stage lasts for only a matter of days or weeks depending on the availability of oxygen for the process, which in turn depends on the amount of air trapped in the waste, the degree of waste compaction and how quickly the waste is covered. Stage II. Hydrolysis and fermentation Stage I processes result in a depletion of oxygen in the mass of waste and a change to anaerobic conditions. Different micro-organisms, and the facultative anaerobes, which can tolerate reduced oxygen conditions, become dominant. Carbohydrates, proteins and lipids are hydrolysed to sugars which are then further decomposed to carbon dioxide, hydrogen, ammonia and organic acids. Proteins decompose via deaminisation to form ammonia and also carboxylic acids and carbon dioxide. The ammonia is derived largely from the deaminisation of proteins, which also form carboxylic acids and carbon dioxide. The derived leachate contains ammoniacal nitrogen in high concentration. The organic acids are mainly acetic acid, but also propionic, butyric, lactic and formic acids and acid derivative products, and their formation depends on the composition of the initial waste material. The temperatures in the landfill drop to between 30 and 50 °C during this stage. Gas concentrations in the waste undergoing stage II decomposition may rise to levels of up to 80% carbon dioxide and 20% hydrogen (Waste Management Paper 26, 1986; Waste Management Paper 26B, 1995). Stage III. Acetogenesis The organic acids formed in Stage II are converted by acetogen micro-organisms to acetic acid, acetic acid derivatives, carbon dioxide and hydrogen under anaerobic conditions. Other organisms convert carbohydrates directly to acetic acid in the presence of carbon dioxide and hydrogen. Hydrogen and carbon dioxide levels begin to decrease throughout Stage III. Low hydrogen levels promote the methane-generating micro-organisms, the methanogens, which generate methane and carbon dioxide from the organic acids and their derivatives generated in the earlier stages. The acidic conditions of the acetogenic stage increase the solubility of metal ions and thus increase their concentration in the leachate. In addition, organic acids, chloride ions, ammonium ions and phosphate ions, all in high concentration in the leachate, readily form complexes with metal ions, causing further increases in solubiliation of metal ions. Hydrogen sulphide may also be produced throughout the anaerobic stages as the sulphate compounds in the waste are reduced to hydrogen sulphide by sulphate-reducing micro-organisms (Christensen et al 1996). Metal sulphides may be a

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reaction product of the hydrogen sulphide and metal ions in solution. The presence of the organic acids generates a very acidic solution which can have a pH level of 4 or even less (Moss 1997). Stage IV. Methanogenesis The methanogenesis stage is the main landfill gas generation stage, with the gas composition of typical landfill gas generated at approximately 60% methane and 40% carbon dioxide. The reactions are relatively slow and take many years for completion. The conditions maintain the anaerobic, oxygen-depleted environment of Stages II and III. Low levels of hydrogen are required to promote organisms, the methanogens, which generate carbon dioxide and methane from the organic acids, and their derivatives such as acetates and formates, generated in the earlier stages. Methane may also form from the direct microorganism conversion of hydrogen and carbon dioxide to form methane and water. Hydrogen concentrations produced during Stages II and III therefore fall to low levels during this fourth stage. There are two classes of microorganisms which are active in the methanogenic stage, the mesophilic bacteria which are active in the temperature range 30–35 °C and the thermophilic bacteria active in the range 45–65 °C. Therefore, landfill gas can be generated during the methanogenic stage over a temperature range of 30–65 °C, with an optimum temperature range of gas generation between 30 and 45 °C. In fact, most landfill sites fall within this temperature range with an average range for UK landfill sites of between 30 and 35 °C. Where temperatures in the mass of waste drop significantly, for example, to below 15 °C in cold weather in shallow sites, then the rate of biological degradation falls off. The organic acids formed during Stages II and III are degraded by the methanogenic microorganisms, and as the acid concentration becomes depleted, the pH rises to about pH 7–8 during the methanogenesis stage. Ideal conditions for the methanogenic micro-organisms are a pH range from 6.8 to 7.5, but there is some activity between pH 5 and pH 9. Stage IV is the longest stage of waste degradation, but may not commence until 6 months to several years after the waste is placed in the landfill, depending on the level of water content and water circulation. Significant concentrations of methane are generated after between 3 and 12 months, depending on the development of the anaerobic micro-organisms and waste degradation products. Landfill gas will continue to be generated for periods of between 15 years and 30 years after final deposition of the waste, depending on waste and site characteristics (Landfill Gas Development Guidelines 1996). However, low levels of landfill gas may be generated up to 100 years after waste emplacement. Stage V. Oxidation The final stage of waste degradation results from the end of the degradation reactions, as the acids are used up in the production of the landfill gas methane and carbon dioxide. New aerobic micro-organisms slowly replace the anaerobic forms and re-establish aerobic conditions. Aerobic micro-organisms which convert residual methane to carbon dioxide and water may become established. Figure 6 shows the changes in composition of landfill gas and leachate as the five stages of waste degradation progress with time. Initial formation of hydrogen and carbon dioxide in the hydrolysis/aerobic degradation, hydrolysis and fermentation and acetogenesis stages is followed by the main landfill gas generation stage, the methanogenesis stage. The characteristic landfill gas composition is methane and carbon dioxide with other minor

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components and water vapor. The final stages mark the end of the reaction and a return to aerobic conditions. Hydrogen sulphide gas may also form, derived from sulphate-reducing micro-organisms, in wastes with a high concentration of sulphate.

Figure 6. Changes in composition of LFG and leachate during stages of waste decomposition (modified from Pohland and Harper, 1986)

1.2. Factors affecting LFG generation Solid waste disposal sites are by nature heterogeneous. Microbiological investigations into site characteristics have shown that there are considerable differences between different SWDSs and even different regions within the same SWDS. This makes it very difficult to extrapolate from observations on single SWDSs to predictions of global CH4 emissions. Nevertheless, a better understanding of the factors thought to most significantly influence the generation of CH4 from land disposal of solid waste can reduce the uncertainty associated with emissions estimates.

1. Site characteristics Landfill sites with waste depths exceeding 5m tend to develop anaerobic conditions and greater quantities of landfill gas. Shallower sites allow air interchange and lower anaerobic activity, and consequently lower landfill gas production. However, if the site is well capped, anaerobic conditions will be created. Similarly, rapid covering of the waste will reduce the aerobic phase, and since this is the increasing temperature phase, this will tend to keep waste temperatures down. Also, rapid covering of the waste will reduce the chance of rainfall increasing the moisture content of the waste, which in turn reduces the initial rate of biodegradation. 2. Waste characteristics The major components of municipal solid waste include the biodegradable fraction, that is, the paper and board, food and garden waste, and non-biodegradable components, plastics, glass and textiles. The amount of gas produced will vary depending on the proportion of biodegradable components in the waste. This fraction has been shown to vary depending on a number of factors, for example, higher concentrations of garden waste are produced in spring and autumn, and more industrially developed countries produce more paper. In addition, the bacteria that break down the waste require small amounts of certain minerals such as calcium,

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potassium and magnesium and other micronutrients. If these are present the bacteria thrive and gas is produced rapidly. If they are lacking or if substances that inhibit bacterial growth are present, gas production will proceed more slowly and in extreme circumstances may stall completely. In addition, the composition of the organic components, that is, the proportion of cellulose, proteins and lipids, will similarly influence the degradation pathway. The rate at which gas is produced depends on the proportions of each type present in the waste. Shredding or pulverisation of the waste prior to landfilling results in increased available surface area and consequent increased homogeneity and increased rates of biological degradation. The density or degree of compaction of the waste in the landfill will increase the amount of biodegradable material available for degradation and therefore increase the production of landfill gas per unit volume of void space in the landfill. Too high a degree of compaction, however, may limit the percolation of water through the site, which is necessary for the free flow of nutrients for the micro-organisms.

3. Age of the waste Landfill gas production begins as soon as waste has been deposited, but anaerobic methane production only occurs when all of the available oxygen has been absorbed. Peak landfill gas production generally occurs about a year after deposit and thereafter gradually declines. Significant gas production is generally completed within about 20 years of deposition, but every site is different. Where gas production is slow, the period of significant gas production may extend for 40 or 50 years. Also, older landfill sites have been shown to contain lower proportions of biodegradable waste than modern sites due to the changing nature of waste over the last few decades. The pattern of gas production for an entire site is the sum of the performance of all of the individual components of waste. Some will be rapidly enter the gas generation stage, others will be slower, particularly where the period over which waste has been deposited, has been many years. Similarly, the period of significant gas production will vary, and for an entire site most often extends over several decades. Figure 7 below shows an idealised and fairly typical sequence of LFG production, although actual durations will vary greatly site by site.

Figure 7. Variations in Rate of Landfill Gas Production with Time Source: UK Department of Energy (1992)

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4. Temperature Similar to other microbial processes, the biodegradation rate of microorganisms involved in the MSW decomposition is highly affected by temperature. Methane production increases with an increase in temperature. The optimum temperature for methane production in mesophilic waste decomposition is in the range of 30 to 40ºC, whereas 60 is the optimum temperature for thermophilic waste decomposition (Ham et al. 1989; Barlaz et al. 1990). Hartz et al. (1982) recommended that the optimum temperature for methane generation is in the range of 36 to 41˚C. Ham and Barlaz (1989) concluded that gas production rates at 30, 35, and 40˚C are much higher than rates at 20 and 25˚C. Anaerobic bacteria produce only small amounts of heat and may not be able to maintain the temperature of a shallow landfill when external temperatures fall so landfill gas generation may show pronounced diurnal or seasonal variations. Likewise, waterlogged landfills may not attain optimum temperatures because the bacteria do not generate sufficient heat to raise the temperature of the excess water. Higher temperatures promote volatilisation and chemical reactions within the waste so the trace gas component of landfill gas tends to increase with higher landfill temperatures. Chaiampo et al. (1996) have monitored the temperature changes with depth throughout a 20 m deep municipal solid waste landfill in Italy. They showed that the first 1–2m were in the temperature range of 10–15 °C, but the temperature increased to 35–40 °C at the 3–5m depth and to 45–65 °C in the 5–20 m depth region. They equated the temperature regions with the mesophilic bacteria in the 1–5m range and thermophilic bacteria in the deeper layers. 5. Pressure Atmospheric pressure can have a minor affect on the rate at which landfill gas is released to the atmosphere. It can also influence the operation of gas extraction systems. A decrease in barometric pressure results in a temporary increase in LFG flow and an increase in barometric pressure will cause LFG flow to temporarily decrease. This is because the pressure within the landfill changes at a slower rate than the atmosphere and a pressure gradient temporarily develops between the inside and outside of the landfill until these pressures equalize. 6. Moisture content and movement Moisture is essential for the activity of all microorganisms in the landfill. The moisture content therefore is one of the most critical factors controlling the biodegradation of MSW. Many researches have shown that the methane production rate increases by increasing the moisture content of the MSW. Rees (1980) found from existing literature that by increasing the water content from 25% to 60% (wt), the rate of gas production and the percentage of methane in the gas are increased. Baldwin et al. (1998) studied the moisture content in three landfills over 1-6 years and found that wastes with high moisture content are more quickly decomposed. The increase in moisture content affects the limitation of oxygen diffusion from the atmosphere into the landfill, the exchange of substrate, nutrients and microorganisms, and the dilution of inhibitors and improved distribution of enzymes and microorganisms within the landfill (Klink et al. 1982; Christensen et al. 1996). Furthermore, Klink et al. (1982) concluded that moisture movement through the MSW increased the methane production rate from 25% to 50%, compared to no movement of moisture at the same moisture content levels. Compaction of the waste and the presence of layers of poorly permeable material such as clay used for covering

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will tend to reduce gas production because they obstruct the passage of moisture. Leachate recirculation back into the waste tends to increase the rate of gas production.

7. Atmospheric conditions Atmospheric conditions affect the temperature, pressure, and moisture content within a landfill. Landfill covers and liners help to isolate waste from atmospheric conditions by limiting oxygen intrusion, limiting infiltration of precipitation, and buffering the effects of temperature changes. 8. Oxygen concentration The activity of anaerobic microorganisms is affected by the presence of oxygen. Thus, the absence of free oxygen concentration in the landfill is required in order to grow and degrade the MSW into methane and CO2. In reality, the oxygen that diffuses from the atmosphere into the landfill is consumed by aerobic bacteria in the top layers of the landfill (aerobic zone) (Warith 2003). If oxygen is present, aerobic biodegradation will proceed rapidly and the resulting gas will comprise mostly carbon dioxide. A few modern engineered landfills are designed to function aerobically. However, in a typical engineered landfill where waste is quickly compacted and covered, aerobic degradation only occurs until the entrained oxygen is used up in newly deposited waste. Where oxygen is not available, the waste is broken down by anaerobic bacteria that produce a “classic” landfill gas, containing roughly equal amounts of methane and carbon dioxide. In uncontrolled “dumps”, where waste is left loose and uncovered, breakdown of the waste may be almost entirely aerobic, and in such cases no methane will be produced. 9. Hydrogen concentration The fermentative and acidogenic bacteria produce hydrogen during the biodegradation of MSW, while the methanogenic bacteria use the hydrogen as a substrate to produce methane. Low partial pressure of hydrogen is required for the acidogenic processes (hydrogen producing bacteria) and methanogenesis processes. An increase in the partial pressure of hydrogen causes the generation of propionic and butyric acids with no further conversion, resulting in an accumulation of volatile organic acids which reduce the pH and inhibit the methanogenic bacteria. The conversion of propionic acid requires a hydrogen pressure lower than 9x10-5 atmospheres (Christensen et al. 1989). 10. Precipitation Precipitation dramatically affects the gas generation process by supplying water to the process and by carrying dissolved O2 into the waste with the water. High rates of precipitation may also flood sections of the landfill, which will obstruct gas flow. The amount of precipitation that reaches the waste is highly dependent on the type of landfill cover system. 11. Density of the waste The density of waste fills is highly variable. An estimate of waste density is often required for estimating landfill gas generation rates. Several researchers reported density values; Stecker, (1989) reported that MSW density values range from 474 to 711 Kg/m3,

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Emcon Associates (1980) stated that MSW density is about 650 Kg/m3, a wider MSW density range of 387 to 1662 Kg/m3 was suggested by Landva et al. (1990).

12. Nutrients and trace metals Microorganisms in the landfill require various nutrients for their activity, such as nitrogen and phosphorous, as well as traces of heavy metals like zinc, iron, copper, potassium, calcium, cobalt and molybdenite. Rees (1980) and Christensen et al. (1996) found from existing literature that all the necessary nutrients and traces of heavy metals are available in most landfills, but heterogeneous insufficient mixing of the wastes may result in nutrient limited environments. The optimal ratios needed in order to enhance the biodegradation are 100:0.44:0.08 for organic matter expressed as chemical oxygen demand (COD), nitrogen and phosphorous (McCarty 1964). 13. Acidity The acidity of the landfill site influences the activity of the various microorganisms and therefore determines the rate of biodegradation. The pH of leachate produced from a landfill can have a significant effect on the stabilization of methane production. The pH of a typical landfill site would initially be neutral, followed by acidic phases, Stages II and III, where organic acids are produced from waste degradation by the acetogenic micro-organisms, and the pH falls to as low as 4. The resultant organic acids provide the nutrients for the methanogenic bacteria and as the acids are consumed, the pH rises. The fermentative and acetogenic microorganisms have a wider range of pH compared to methanogenic bacteria. The ideal methanogenic bacteria activity occurs in environmental conditions within a pH range of 6.8 to 8.0 (Warith 2003). Any drop in the pH value below 6.8 will slow down the activity and growth of methanogenic microorganisms. In a well-established methanogenic media, if the methanogenic activity is inhibited by other factors [O2, H2, etc.], the conversion of acetic acid to methane and CO2 decreases and leads to an accumulation of the acids, thereby decreasing the pH which in turn may stop the generation of methane (Christensen et al. 1996). 14. Inhibitors There are a number of elements or compounds that can inhibit the biodegradation of MSW (methane production) besides O2, H2, pH (acidity) and high concentrations of heavy metals. These inhibitors are carbon dioxide, sulphate, and high concentrations of cations such as sodium, potassium, calcium, magnesium, and ammonium. The CO2 acts as an inhibitor by raising the redox potential which has an effect on the acetic acid conversion to methane (Christensen et al. 1996). Rees (1980) reported that high sulphate concentrations inhibit the methanogenic bacteria for two reasons: reduction of SO42- to S2-, which is toxic; and competition for common substrate between methanogenic and sulphate reducing bacteria. These cations in low concentrations are required for biodegradation, but in high concentrations they inhibit the methanogenic bacteria. To the author’s knowledge, there have been no studies to evaluate the impact of Chloride on the degradation of MSW.

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2. LFG Transport 2.1. LFG transport mechanisms Transport of landfill gas occurs by the two principal mechanisms of diffusion and advection. Transport conditions both within the landfill and for the subsurface surrounding the landfill must be considered. These transport mechanisms are discussed in the following paragraphs. Diffusion Molecular diffusion occurs in a system when a concentration difference exists between two different locations. Diffusive flow of gas is in the direction in which its concentration decreases. The concentration of a volatile constituent in the LFG will almost always be higher than that of the surrounding atmosphere, so the constituent will tend to migrate to the atmosphere. Wind often serves to keep the surface concentration at or near zero, which renews the concentration gradient between the surface and the interior of the landfill and thus promotes the migration of vapors to the surface. Geomembranes in landfill covers will significantly reduce diffusion because the geomembrane prevents gases from diffusing to the atmosphere. Specific compounds exhibit different diffusion coefficients. Diffusion coefficients are the rate constants for this mode of transport and quantify how fast a particular compound will diffuse. Published diffusion coefficients have been calculated using open paths between one vapor region (concentration) and another. This type of test is not very representative of the conditions found in a landfill. In landfills, gases must travel a tortuous path around all the solids and liquids in its path; thus, the published diffusion coefficients must be used with care. Advection. Advective flow occurs where a pressure gradient exists. The rate of gas movement is generally orders of magnitude faster for advection than for diffusion. Gas will flow from higher pressure to lower pressure regions. In a landfill, advective forces result from the production of vapors from biodegradation processes, chemical reactions, compaction, or an active LFG extraction system. Variations in water table elevations can create small pressure gradients that either push gases out (rising tide) or draw gases in (falling tide). Changes in barometric pressure at the surface can also have an impact on the advective flow of gas.

2.2. Factors affecting LFG transport mechanisms LFG transport is affected by the following factors: Permeability. The permeability of waste has a large influence on gas flow rates and gas recovery rates. Coarse-grain wastes exhibit large values of gas permeability and more uniform gas flow patterns. By contrast, fine-grained and heterogeneous wastes are characterized by small values of gas permeability and gas flow patterns that are not uniform throughout the waste mass. Permeability of refuse is often reported in Darcys. One Darcy = 9.85×10–9 cm2. Reported values for the apparent permeability of municipal solid waste are in the range of 13 to 20 Darcys. Water competes with air to occupy pore space within the solid matrix and ultimately reduces the effective porosity and ability of vapors to migrate through

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the landfill due to a reduction in available air pathways. This reduction will also reduce the rate of gas flow and decrease gas recovery rates. Geologic Conditions. Geologic conditions must be determined to estimate the potential for off-site migration of gas. Permeable strata such as sands, gravels, and weathered bedrock provide a potential pathway for off-site migration, especially if these layers are overlain by a layer of low permeability soil. Geologic investigations must be performed to determine the potential for off-site migration. Additional attention must be given to areas where houses and other structures are present to ensure off-site migration will not impact these structures. Depth to Ground Water. The water table surface acts as a no-flow boundary for gas. As a result, it is generally used to help estimate the thickness of the zone through which gas can travel. A consistently high ground water table will significantly reduce the potential for offsite migration of gas. The depth to groundwater (as well as seasonal variations) also needs to be evaluated during the design process to evaluate well construction requirements and the potential for water table upwelling (i.e., the upward rise of the water table toward a vacuum well screened in the unsaturated zone). Man-Made Features. In some instances, underground utilities such as storm and sanitary sewers or the backfill that surrounds these features may produce short-circuiting of airflow associated with an active landfill gas collection system. As a result, airflow may be concentrated along these features rather than within the landfill. Man-made features also provide a potential pathway for the off-site migration of landfill gas. Landfill Cover and Liner Systems. The components of many hazardous and solid waste landfill cover systems consist of a vegetated surface component, a drainage layer, and a low permeability layer composed of one or more of the following: geomembrane, geosynthetic clay liner (GCL), or compacted clay. A geomembrane in the cover system will prevent the intrusion of air into the waste. Therefore, a higher operating vacuum can be applied to the gas collection system without the danger of overdrawing. Thus, the effective radius of influence of each well is increased. Overdrawing occurs when oxygen from the atmosphere is pulled into the landfills interior during the anaerobic phase. Landfill liner systems consist of various combinations of low permeability layers and leachate collection layers. The low permeability layers are created using natural low permeability geologic formations, compacted clay, geomembranes, and geosynthetic clay liners. Liner systems prevent the migration of LFG to the surrounding areas. Liner systems also prevent gases in the surrounding geologic formations from being pulled into the LFG collection system. Barometric Pressure. The amount of gas escaping from a landfill’s surface changes as barometric pressure changes. Gas generation within a landfill will result in a positive pressure gradient from the inside to the outside of the landfill. For a passive LFG collection system, increases in atmospheric pressure will cause a decrease in gas flow from a landfill because the pressure differential between the inside and the outside has decreased. For an active gas collection system, there is a higher probability of atmospheric air intrusion through the landfill cover during periods when the barometric pressure is rising. The amount of air

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intrusion will be greatly affected by the type of cover on the landfill. A landfill with a low permeability (geomembrane) cover will be more resistant to air intrusion than a landfill with a soil cover.

E. LFG Production Enhancement Methods The biodegradation of MSW and LFG production in bioreactor landfills can be enhanced through different methods. In all cases, the purpose is to control and manipulate the influencing factors in a positive manner in order to accelerate the biodegradation of MSW and increase the amount of LFG produced. There are many advantages to enhancing the biodegradation of MSW, including more rapid waste stabilization and increased gas production; lower leachate treatment costs through recirculation to the landfill; reduced length and cost of post closure activities; and greater landfill airspace availability due to increased settlement during the operation rather than the post closure stage, as is the case in conventional landfills (Reinhart et al., 2002). The technologies used to enhance the biodegradation of MSW are studied by San et al. (2001), Laquidara et al. (1986), Chan et al. (2002), Chiemchaisri et al. (2002), Warith (2003), Bae et al. (1998), Pacey (1989), Klink et al. (1982), Stegmann (1983), and reviewed by Barlaz et al. (1990), Warith et al. (1998), Komilis et al. (1999a), Christensen et al. (1992), Stegmann et al. (1996). These technologies are leachate recycle, pH buffering, sludge addition, temperature control, reduced waste particle size, improved cell design, daily cover and waste compaction, and pre-treatment of MSW. They will all be discussed in the following sections.

1. Leachate recirculation Leachate recirculation is the process by which the leachate collected at the base of the landfill is recycled or reintroduced in the landfill in order to control the moisture content. The advantages and impacts of leachate recirculation on the degradation of MSW were covered by Barlaz et al. (1996), San et al. (2001), Ham et al. (1982, 1989), Baldwin et al. (1998), Warith et al. (1998, 2002, 2003), Reinhart et al. (1996, 2002), and Sponza et al. (2004). The advantages of leachate recirculation lay both in the rapid reduction of the organic content present in the leachate itself which reduces the cost of treatment; and the potential transformation of waste into energy, as it increases the rate of methane production. Leachate recirculation provides optimum conditions for enhancing biodegradation by increasing the moisture content and movement, and by distributing the nutrients throughout the landfill. Both moisture content and moisture movement are necessary settings for bacteria growth and the establishment of methanogenic conditions. They also provide better contact between insoluble substrates, soluble nutrients and microorganisms (Klink et al., 1982). Ham et al. (1982) and Baldwin et al. (1998) studied the effect of moisture content on the biodegradation of MSW and concluded that moisture content has a positive effect on gas production. Also, leachate recirculation treats the leachate through the landfill (in situ treatment) because the organic compounds in the leachate are reduced with the recirculation due to the biological activity within the landfill (Sponza et al., 2004).

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Klink et al. (1982) found that the reactor with leachate recycle had 25-50% higher methane production as compared to reactors having the same moisture content but without leachate recirculation.

2. pH buffering The methanogenic bacteria are sensitive to pH and could be inhibited by acidic conditions. This understanding has led to adding buffer to the leachate prior to recycling it back to the bioreactor landfill. Leachate recirculation with a buffering system to control the pH causes a shorter acidogenic stage compared to leachate recirculation without a buffering system (Komilis et al., 1999a). In a study conducted by Warith (2002), the reactor with buffered and nutrients amended recycled leachate resulted in the greatest reduction of COD concentration over time. Also, a study by San et al. (2001) found that the highest degree of stabilization occurred in a reactor with a four-time per week recirculation and pH control by addition of buffer. Ağdağ et al. (2005) studied the effect of alkalinity addition to leachate recycle on the degradation of MSW in an anaerobic bioreactor. It was observed that lower COD, VFA concentrations and BOD5/COD ratios were obtained in the bioreactors with alkalinity addition in comparison to the bioreactor (control) without alkalinity addition. Lab scale experiment results recommend the addition of buffer to leachate recycle, especially in the acid generation phase, to maintain the pH at a neutral level. This helps to establish a methanogenic condition. 3. Sludge addition The effect of sludge addition on the MSW degradation is covered by Pacey (1989), Leuschner (1982) and Warith (2002). They concluded that the addition of sewage sludge has both a positive and a negative effect on the MSW biodegradation and methane generation. The positive effect of sludge addition occurs if the methanogenic bacteria are already established or the landfill environment is optimum (pH neutral) for methanogenic bacteria (Christensen et al., 1992). This positive effect can be attributed to the following factors: 1) sludge can be a source of nutrients and active methanogenic bacteria, and; 2) sludge increases the moisture content. The negative effect of sludge addition to fresh waste is attributed to the acid accumulation that is associated with it which decreases the pH and inhibits the methanogenic bacteria (Barlaz et al., 1990). Rees (1980) and Leuschner (1982) found that the anaerobic digested sewage sludge is an excellent source of microbial inoculum, whereas the septic tank sludge is a poor one. Also, Komilis et al. (1999a) concluded that adding anaerobic digested sludge to MSW produces three times more methane than adding primary sludge. It appears that the addition of anaerobic digested sludge with buffering enhanced the biodegradation and increased methane generation. Buffering controls the pH of the landfill around neutral, allowing the methanogenic bacteria in the anaerobic sludge to acclimatize to the landfill environment faster than without buffer addition. The addition of old waste or ashes to new waste could improve biodegradation by diluting the acids produced during the acidogenic stage, thereby enhancing the methane formation stage. The percentage of ash should not exceed 10% in weight (Komilis et al., 1999a).

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4. Temperature control The direct effect of temperature on bacteria activity could be manipulated to optimize the decomposition of MSW in the bioreactor landfill. Thus, it is necessary to realize the temperature constraints on individual microorganisms in order to control the activity of bacteria and enhance waste stabilization. Baldwin et al. (1998) investigated the effect of temperature on a large scale using two different landfills, one located in Florida and the other in Wisconsin. The Florida landfill (30˚C) had a more rapid decomposition compared to the Wisconsin landfill (22˚C). Kasali et al. (1989) found that by increasing the temperature of MSW with a 60% w/w moisture content from 18.7 to 30˚C caused a 2.6 times increase in the methanogenic rate, while a 7.8 times increase when the temperature rose from 18.7 to 40˚C. The methanogenic rate is inhibited when the temperature is increased to 55˚C. Based on the experimental work, the optimum temperature for enhancing the MSW biodegradation is in the range of 30-40˚C. 5. Reduced waste particle size Shredding or reducing the particle size of MSW has several advantages, such as providing more landfill space and greater MSW stabilization. The arguments for shredding are: 1) it increases homogeneity and distribution of waste within the landfill, 2) it improves the contact surface area of the waste, 3) it promotes better contact between the organic matter and microorganisms (Christensen et al., 1992). Ham et al. (1982) found that the shredding of waste increases the rate of decomposition and methane production. Some authors (Buivid et al., 1981) concluded that refuse with 2.5 to 3.5 cm particle sizes produced 32% more methane than refuse with 1 to 1.5 cm particle sizes in a period of 90 days. This is due to the fact that the smaller particle size increases the rate of hydrolysis and acid formation which in turn decreases the pH and postpones the production of methane. Based on that, if the negative effect of smaller particle sizes in the initial stage of biodegradation can be controlled (by adding buffer or pre-composting), shredding may enhance the biodegradation process, since the hydrolysis is the rate-limiting step (Yildiz et al., 2004; El-Fadel et al., 1996b; Pareek et al., 1999; Naranjo et al., 2004). Sponza et al. (2005) reported that the shredding of MSW has a positive effect on the rate of biological degradation in anaerobic bioreactors with leachate recycle. They compared three types of reactors. The first reactor was loaded with raw waste, the second with shredded waste, and the third with compacted waste. At the end of the experiments (57 days later), they found that the reactor with waste shredding had the lowest COD and VFA concentrations and the highest methane percentage. 6. Cell design, daily cover and compaction of waste The enhancement of waste biodegradation in the landfill is also affected by the cell thickness, daily cover and compaction of waste. The cell thickness has an adverse effect on the biodegradation of waste. Ham et al. (1982) found that the cell with a 2m deep lift produced higher leachate concentrations and took a longer time to stabilize than the cell with a 1.2m deep lift. By doubling the cell depth from 1.2 to 2.4 m, the concentration of leachate and the stabilization time are doubled as well.

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Similarly, the daily cover has a negative effect on the biodegradation of waste because it decreases the O2 diffusion into the waste which in turn diminishes the composting rate. If a low permeability soil is used as a daily cover, it could create a barrier and may impact leachate distribution and landfill gas flow into the collection system. A soil cover more permeable than the waste can direct leachate to the sides. Use of alternative covers that do not create such barriers can reduce these effects. On the other hand, positive effects of daily cover soil may be expected if the soil supplies buffer to the landfill (e.g. contain lime) (Christensen et al., 1992). The cell with soil cover has a higher leachate concentration than the cell without it. Initially, the cell without cover produced a high leachate concentration, but it was followed by a rapid decrease (Ham et al., 1982). It appears that the lack of daily cover enhances the aerobic activity and prevents a long acidogenic stage. The short acidogenic period leads to the rapid establishment of the methanogenic stage. The landfill should utilize thin lifts and the daily cover should not be used immediately. Likewise, waste compaction has an adverse effect on the biodegradation of waste in the landfill. Ehring et al. (1980) found that cells with low-density waste have shorter periods of high leachate concentration. This means that there is an enhancement in the acidogenic stage. Rees et al. (1982) concluded that by increasing the waste density from 0.2 to 0.47 t/m3, there was a decrease in gas production due to acid accumulation, which in turn decreased the pH and inhibited the methanogenic bacteria. Waste compaction causes sudden decrease in the void space of the waste which in turn decreases the moisture content dramatically. On the other side, the effect of load caused from subsequent waste layers, which is examined in this thesis, causes a gradual decrease in waste voids in a way that does not affect waste biodegradation.

7. Pre-treatment The objective of the pre-treatment of MSW is to enhance the acidogenic stage and decrease the accumulation of organic acids. This method is based on the stabilization of part of the waste through aerobic processes which will dilute the organic acids and cause a balance between the acidic phase and the methanogenic bacteria. This method was studied by Ham et al. (1982); Beker (1987); and Stegmann (1983) and was reviewed by Komilis et al. (1999b). Ham et al. (1982), Beker (1987) and Stegmann (1983) found that by placing fresh waste on top of the composted waste layer caused a shorter acidogenic stage and enhanced the methanogenic stage. This is due to the fact that the composted layer acts as an anaerobic filter which has the ability to treat leachate as it passes through. The composted bottom layer can be prepared by the following procedure: a layer (1.5m-2m) of waste is placed without compaction, so that the easy degradable material can be decomposed aerobically with leachate recycle. The leachate concentration and the temperature of the waste can be used as indicators for the progress of the aerobic process. After one year of the placement, the waste layer is compacted and an additional layer of fresh waste can be added on top (Stegmann, 1983). The author suggested that efforts should be made to reduce the time required for aerobic decomposition of the first layer by injecting air through perforated pipes.

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V. LANDFILL GAS BEHAVIOUR A. LFG Movement and Migration Gases generated in the landfill will move throughout the mass of waste in addition to movement or migration out of the site. The mechanism of gas movement is via gaseous diffusion and advection or pressure gradient. That is, the gas moves from high to low gas concentration regions or from high to low gas pressure regions (Kjeldsen et al 2002). Movement of gas within the mass of waste is governed by the permeability of the waste, overlying daily or intermittent cover, and the degree of compaction of the waste. Lateral movement of the gases is caused by overlying low permeability layers such as the daily cover and surface and sub-surface accumulations of water. Vertical movement of gas may occur through natural settlement of the waste, between bales of waste if a baling system is used to compact and bale the waste, or through layers of low permeability inert wastes such as construction waste rubble. Where landfill gas extraction is practised to recover the gas for energy use, the gas is collected in gas wells, and piped to the surface (Waste Management Paper 27, 1994). Fully contained landfill sites where, after completion, the landfill is capped with an impermeable synthetic and natural containment system to prevent migration of landfill gas out of the site and which have gas recovery systems in place, have low gas emission levels (Mosher et al 1999). The capping liner system is also designed to prevent ingress of precipitation. For landfill sites, where landfilling is still in operation and where the waste is only partially covered by an impermeable layer, there are higher emissions of landfill gas. Waste landfills are a source of volatile organic hydrocarbons, both to the site workers and to the surrounding neighbourhood. The contribution of a range of chemicals identified in landfill gas has been shown to be significant contributors to the toxic air pollutants in local neighborhoods adjacent to landfill sites (Scheff et al 2001). Certain chemicals, including chlorinated hydrocarbons, have been identified as being derived from landfill as the major source. Additionally, other work has shown that chlorinated hydrocarbons are found in landfill gas at concentrations which exceed occupational exposure levels (Allen et al 1997). However, it is unlikely that long exposure to such levels would be experienced by landfill site workers and even less likely for members of the public (Allen et al 1997). Sub-surface gas migration out of the mass of waste into the surrounding environment may occur from older sites, where containment was not practised, or through containment sites, where significant leakage has occurred. In addition, leachate movement out of such sites may cause later degradation to landfill gas. Migration of gas outside the site requires migration pathways such as high-permeability geological strata, through caves, cavities, cracks in the overlying capping layer and through man-made shafts, such as mine shafts and service ducts, etc. Gas may migrate considerable distances from the boundaries of the site through these possible pathways. It has been reported that changes in the major and trace components of landfill gas occur during subsurface migration (Ward et al 1996). For example, reduction in methane concentration occurs due to oxidation, and some alteration of trace landfill gases occurs due to adsorption onto soil particles, oxidation, degradation, condensation and dissolution.

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B. Monitoring of LFG The monitoring program for landfill gas at waste landfill sites is recommended to determine whether landfill gas is causing a hazard to human health or the environment. Monitoring takes place throughout the operation of the plant and for many years during the post-closure period, until emission levels of methane and carbon dioxide are at environmentally insignificant levels, typically below 1.0% by volume of methane and 1.5% by volume of carbon dioxide. Monitoring takes place within the landfill and outside the site boundary. The monitoring program, including the frequency of monitoring, will be dependent on the age of the site, the type of waste and the gas collection and control measures installed. Frequency between measurements will vary from weekly, monthly or even quarterly, depending on site-specific characteristics. More frequent monitoring may be required where migration of gas is suspected. Monitoring techniques for landfill gas include, for example, surface monitoring, sub-surface probes, gas monitoring wells, and boreholes. Surface monitoring with portable instruments is mainly used to detect the presence of gas leaks throughout the site. Sub-surface monitoring using gas probes is used to monitor gas production and migration at depths of between 1 and 10m in the mass of waste and in the surrounding environment. The probes may be left for long periods of time to monitor and map the production of gas from the site throughout site operation and post-closure. The probes are constructed of steel and plastic pipe, consisting of a porous lower section and a gas transfer pipe which transfers the gas to the surface, where the gas sample is taken for analysis. Gas monitoring well and boreholes consist of a porous plastic casing in direct contact with the waste or geological strata. Probes or tubes may be permanently installed. They are installed within the mass of waste and in the surrounding environment. Gas sample analysis may take the form of portable instruments for gas analysis or laboratory-based analysis. Portable analyzers may be simple devices, such as gas indicator tubes, which produce a color change to indicate a concentration of a particular gas in a sample. The gas is drawn through the tube on-site and an immediate indication of gas concentration is obtained. The method is, however, subject to error. More sophisticated instruments are available, such as infra-red gas analyzers and flame ionization detectors, which would normally be housed in a portable laboratory or at the analytical laboratory. The gas sample is piped directly to the analyzer or else a sample of the gas is taken in suitable sealable containers, such as ‘Teflon’ bags or glass sample tubes and the sample is then transferred to the instrument for analysis. The most accurate and reliable technique for gas analysis is gas chromatography. A sample of the gas is taken in a suitable container to the laboratory for analysis. The gas chromatograph can separate out individual gas components and provide an accurate analysis, even at trace concentrations.

C. LFG Hazards 1. LFG explosion hazard Landfill gas may form an explosive mixture when it combines with air in certain proportions. The following conditions must be met for landfill gas to pose an explosion hazard:

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•

Gas production. A landfill must be producing gas, and this gas must contain chemicals that are present at explosive levels. Gas migration. The gas must be able to migrate from the landfill. Underground pipes or natural subsurface geology may provide migration pathways for landfill gas. Gas collection and treatment systems reduce the amount of gas that is able to escape from the landfill. Gas collection in a confined space. The gas must collect in a confined space to a concentration at which it could potentially explode. A confined space might be a manhole, a subsurface space, a utility room in a home, or a basement. The concentration at which a gas has the potential to explode is defined in terms of its lower and upper explosive limits (LEL and UEL). The concentration level at which gas has the potential to explode is called the explosive limit. The LEL and UEL are measures of the percent of a gas in the air by volume. At concentrations below its LEL and above its UEL, a gas is not explosive. However, an explosion hazard may exist if a gas is present in the air between the LEL and UEL and an ignition source is present.

Methane is the constituent of landfill gas that is likely to pose the greatest explosion hazard. Methane is explosive between its LEL of 5% by volume and its UEL of 15% by volume. Because methane concentrations within the landfill are typically 50% (much higher than its UEL), methane is unlikely to explode within the landfill boundaries. As methane migrates and is diluted, however, the methane gas mixture may be at explosive levels. Table 6. Potential Explosion Hazards from Common Landfill Gas Components Component

Methane

Carbon dioxide Nitrogen dioxide Oxygen Ammonia

NMOC

Hydrogen sulfide

Potential to pose an explosion hazard Methane is highly explosive when mixed with air at a volume between its LEL of 5% and its UEL of 15%. At concentrations below 5% and above 15%, methane is not explosive. At some landfills, methane can be produced at sufficient quantities to collect in the landfill or nearby structures at explosive levels. Carbon dioxide is not flammable or explosive. Nitrogen dioxide is not flammable or explosive. Oxygen is not flammable, but is necessary to support explosions. Ammonia is flammable. Its LEL is 15% and its UEL is 28%. However, ammonia is unlikely to collect at a concentration high enough to pose an explosion hazard. Potential explosion hazards vary by chemical. For example, the LEL of benzene is 1.2% and its UEL is 7.8%. However, benzene and other NMOC alone are unlikely to collect at concentrations high enough to pose explosion hazards. Hydrogen sulfide is flammable. Its LEL is 4% and its UEL is 44%. However, in most landfills, hydrogen sulfide is unlikely to collect at a concentration high Enough to pose an explosion hazard.

Source: Cheremisinoff 2003

Also, oxygen is a key component for creating an explosion, but the biological processes that produce methane require an anaerobic, or oxygen-depleted, environment. At the surface of the landfill, enough oxygen is present to support an explosion, but the methane gas usually

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35

diffuses into the ambient air to concentrations below the 5% LEL. In order to pose an explosion hazard, methane must migrate from the landfill and be present between its LEL and UEL. Other landfill gas constituents (e.g., ammonia, hydrogen sulfide, and NMOC) are flammable. However, because they are unlikely to be present at concentrations above their LELs, they rarely pose explosion hazards as individual gases. For example, benzene (an NMOC that may be found in landfill gas) is explosive between its LEL of 1.2% and UEL of 7.8%. However, benzene concentrations in landfill gas are very unlikely to reach these levels. If benzene were detected in landfill gas at a concentration of 2 ppb (or 0.0000002% of the air by volume), then benzene would have to collect in a closed space at a concentration 6 million times greater than the concentration found in the landfill gas to cause an explosion hazard. Table 6 provides a summary of the potential explosion hazards posed by the important constituents of landfill gas. Methane is the most likely landfill gas constituent to pose an explosion hazard. Other flammable landfill gas constituents are unlikely to be present at concentrations high enough to pose an explosion hazard. However, the flammable NMOC do contribute to total explosive hazard when combined with methane in a confined space.

2. LFG asphyxiation hazard Landfill gas poses an asphyxiation hazard only if it collects in an enclosed space (e.g., a basement or utility corridor) at concentrations high enough to displace existing air and create an oxygen-deficient environment. The Occupational Safety and Health Administration (OSHA) defines an oxygen-deficient environment as one that has less than 19.5% oxygen by volume. Ambient air contains approximately 21% oxygen by volume. Health effects associated with oxygen deficient environments are described in Table 7. Any of the gases that make up landfill gas can, either individually or in combination, create an asphyxiation hazard if they are present at levels sufficient to create an oxygen-deficient environment. Table 7. Health Effects from Oxygen-Deficient Environments Oxygen Concentration 21% 17%

14 to 16% 6 to 10% Less than 6%

Health Effects Normal ambient air oxygen concentration Deteriorated night vision (not noticeable until a normal oxygen concentration is restored), increased breathing volume, and accelerated heartbeat Increased breathing volume, accelerated heartbeat, very poor muscular coordination, rapid fatigue, and intermittent respiration Nausea, vomiting, inability to perform, and unconsciousness Spasmatic breathing, convulsive movements, and death in minutes

Source: Cheremisinoff 2003

Carbon dioxide, which comprises 40% to 60% of landfill gas, may pose specific asphyxiation hazard concerns. Because it is denser than air, carbon dioxide that has escaped from a landfill and collected in a confined space, such as a basement or an underground utility corridor, may remain in the area for hours or days after the area has been opened to the air

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Sherien A. Elagroudy and Mostafa A. Warith

(e.g., after a manhole cover has been removed or a basement door opened). Carbon dioxide is colorless and odorless and therefore not readily detectable. Carbon dioxide concentrations of 10% or more can cause unconsciousness or death. Lower concentrations may cause headache, sweating, rapid breathing, and increased heartbeat, shortness of breath, dizziness, mental depression, visual disturbances, and shaking. The seriousness of these symptoms depends on the concentration and duration of exposure. The response to carbon dioxide inhalation varies greatly even in healthy normal individuals. In assessing the public health issues of migrating landfill gas, environmental health professionals should investigate the presence of buried utility lines and storm sewers on or adjacent to the landfill. These structures not only provide a pathway for migrating gases, but also pose a special asphyxiation problem for utility workers who fail to follow confined space entry procedures prescribed by OSHA. On-site or adjacent residences and commercial buildings with basements or insulated (or sealed) crawl spaces should also be investigated for potential asphyxiation hazards.

3. Landfill odors Landfill odors often prompt complaints from community members. People may also have concerns about health effects associated with these odors and other emissions coming from the landfill. People in communities near landfills are often concerned about odors emitted from landfills. They say that these odors are a source of undesirable health effects or symptoms, such as headaches and nausea. At low-level concentrations—typically associated with landfill gas— it is unclear whether it is the constituent itself or its odors that trigger a response. Typically, these effects fade when the odor can no longer be detected. Landfill gas odors are produced by bacterial or chemical processes and can emanate from both active and closed landfills. These odors can migrate to the surrounding community. Potential sources of landfill odors include sulfides, ammonia, and certain NMOC, if present at concentrations that are high enough. Landfill odors may also be produced by the disposal of certain types of wastes, such as manures and fermented grains. The following are major landfill gases generated: Sulfides. Hydrogen sulfide, dimethyl sulfide, and mercaptans are the three most common sulfides responsible for landfill odors. These gases produce a very strong rotten-egg smell— even at very low concentrations. Of these three sulfides, hydrogen sulfide is emitted from landfills at the highest rates and concentrations. Humans are extremely sensitive to hydrogen sulfide odors and can smell such odors at concentrations as low as 0.5 to 1 part per billion (ppb). At levels approaching 50 ppb, people can find the odor offensive. Average concentrations in ambient air range from 0.11 to 0.33 ppb. According to information collected by the Connecticut Department of Health, the concentration of hydrogen sulfide in ambient air around a landfill is usually close to 15 ppb. Ammonia. Ammonia is another odorous landfill gas that is produced by the decomposition of organic matter in the landfill. Ammonia is common in the environment and an important compound for maintaining plant and animal life. People are exposed daily to low levels of ammonia in the environment from the natural breakdown of manure and dead plants and animals. Because ammonia is commonly used as a household cleaner, most people are familiar with its distinct smell. Humans are much less sensitive to the odor of ammonia

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37

than they are to sulfide odors. The odor threshold for ammonia is between 28,000 and 50,000 ppb. Landfill gas has been reported to contain between 1,000,000 and 10,000,000 ppb of ammonia, or 0.1% to 1% ammonia by volume. Concentrations in ambient air at or near the landfill site are expected to be much lower. NMOC. Some NMOC, such as vinyl chloride and hydrocarbons, may also cause odors. In general, however, NMOC are emitted at very low (trace) concentrations and are unlikely to pose a severe odor problem. Odor control technologies prevent odor-causing gases from leaving the landfill. Installing a landfill cover will prevent odors from newly deposited waste or from gases produced during bacterial decomposition. Covering a landfill daily with soil can help reduce odors from newly deposited wastes. More extensive covers are installed at landfill closure to prevent moisture from infiltrating the refuse and encouraging bacterial growth and decomposition. Vegetative growth on the landfill cover also reduces odors. Flaring is another technique that can eliminate landfill gas odors by thermally destroying the odor-causing gases. Venting landfill gas through a filter is another technology used to reduce odors. Landfill gas is collected and vented through a filter of bacterial slime. As long as oxygen is present, bacteria will decompose landfill gas under aerobic conditions, producing carbon dioxide and water.

VI. MODELING OF METHANE GAS GENERATION AND EMISSION FROM LANDFILLS A. General Several models are available for estimating the LFG generation rate using site-specific input parameters. These models vary widely, not only in the assumptions that they make, but also in their complexity, and in the amount of data they require. The LandGEM model is one of these models and was developed by the US Environmental Protection Agency to estimate landfill gas emissions and to determine regulatory applicability to CAA requirements. There are other LFG emission models in use by industry that also work very well. The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of CH4 emissions from the landfills is based on First-Order decay (FOD) method. Regardless of what model is used, the accuracy of the inputs drives the results and given the level of uncertainty, it makes estimating landfill emissions very difficult. Estimates of the amount of landfill gas generated throughout the lifetime of the landfill site are highly variable with estimates of between 39 to 500 m3/tonne (McBean et al 1995). For the estimation of landfill gas throughout the lifetime of a site for the assessment of energy recovery from landfill gas utilization, values of between 150 and 250m3/tonne are typically used (Loening 2003). Annual rates of gas production have been estimated for a typical municipal solid waste landfill at between 6 and 8m3/tonne/year but much higher rates of over 25m3/tonne/year have been recorded (Characterization of 100 UK landfill sites 1995). This allows the potential amount of energy which could be generated from the site, knowing that undiluted landfill gas can have a calorific value of between 15 and 21 MJ/m3, compared to the calorific value of natural gas at about 37 MJ/m3 (Waste Management Paper 27, 1994). The

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calorific value of the gas depends on the percentage composition of combustible gases such as methane, and non-combustible gases such as carbon dioxide. The presence of carbon dioxide results in reduced flame temperatures and burning rates, a narrower range of flame stability and thus lower combustion efficiency (Qin et al 2001). The carbon dioxide is also regarded as ‘inert’, in that it does not combust and therefore does not contribute to the energy content of the landfill gas.

B. U.S.E.P.A. Model - Landgem 1. Model description The landfill gas emission model (LandGEM) developed by US EPA provides an automated estimation tool for estimation of landfill gas emissions from municipal solid waste MSW landfills (http://www.epa.gov/ttn/catc/products.htmlsoftware). The model is based on a first order decomposition rate equation to estimate annual emissions over a specified time period, described as follows: 1 n ⎛ M ⎞ − kt QCH 4 = ∑ ∑ kLo ⎜ i ⎟e ij ⎝ 10 ⎠ i =1 j = 0.1

(1)

Where,

QCH 4

=

Annual Methane generation in the year of the calculation (m3/year)

Mi

=

Mass of waste accepted in the year I (Mg)

L0 k j i n

=

Potential methane generation capacity of the waste (m3/Mg)

=

Methane generation rate (per year)

=

Waste type category (index)

= =

1Year (year of the calculation)- (initial year of waste acceptance) Age of the jth section of waste mass M i accepted in the ith year (decimal

tij

=

years, e.g., 3.2 years)

1.1. Input Parameters Main Input parameters required for LandGEM are as follows: • • •

Annual Waste acceptance rate during the operation of the landfill (tons/year) Start year and end year of the landfill operations Assumed values of methane generation rate ( k ) and methane generation potential ( L0 )

•

NMOC concentration and methane content in landfill gas

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39

LandGEM is considered a screening tool – the better the input data, the better the estimates. The Input parameters in the model are described below in more details:

Methane generation potential (L0) The methane generation potential is the total amount of methane that a unit mass of refuse will produce given enough time. It depends upon the composition of the waste. Values of Lo can vary widely and are difficult to estimate for a particular landfill. As per IPCC (1996), the values of Lo may range from less than 100 to over 200m3/Mg. Methane generation rate (k) The k value is indicative of the fraction of the waste which undergoes decomposition in the given year to produce methane. The k value for the given mass is actually related to its half life time period of decay:

k = ln 2

t1/ 2

(2)

Where, half life is the time taken by the degradable organic carbon in the waste to decay to half of its initial mass. This value is affected by a number of factors including the waste composition, climatic conditions at the site, characteristics of the disposal site, waste disposal practices etc. The most rapid rates (k = 0.2) are associated with high moisture conditions and rapidly degradable material such as food waste. The slower decay rates (k = 0.02) are associated with dry site conditions and slowly degradable waste such as wood or paper. IPCC (2006) has provided default k values as dry and wet values for various types of waste depending upon the climatic conditions. There are two options to use the value of k for estimation of gas potential: Bulk waste option in which single value of k is chosen for the entire waste and Waste composition option in which k value for each component of waste stream is considered for calculations. LandGEM has bulk waste option for k.

C. IPCC-First Order Decay (FOD) Model 1. Model description The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of CH4 emissions from the landfills is based on FOD method. This method assumes that the degradable organic carbon (DOC) in the waste decays slowly throughout a few decades, during which CH4 and CO2 are formed. If conditions are constant, the rate of CH4 formation depends solely on the amount of carbon remaining in the waste. Therefore, the CH4 emissions from the waste deposited in a landfill are highest in the first few years after closure and then gradually start reducing. The FOD model developed by IPCC (2006) has been widely adapted for calculation of methane emissions from the landfills. Same model has been used by United Nations Framework Convention on Climate Change (UNFCCC) in its “Tool to determine methane

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Sherien A. Elagroudy and Mostafa A. Warith

emissions avoided from dumping waste at a solid waste disposal site” to award Clean Development Mechanism (CDM) benefits to a particular landfill closure project. As per the tool, the amount of methane that is generated each year ( BECH 4, SWDS , y ), (t CO2e) is calculated for each year y, using the following equation: BECH 4,SWDS , y = j ×(1 - f ) ×GWPCH 4 ×(1 - OX ) y

MCF ×å

å W j, x ×DOC j ×(1 - e

- kj

) ×e

16 ×F ×DOC f 12

(3)

- k j ×( y - x )

x =1 j

Where:

BECH 4,SWDS , y

=

φ

Methane emissions avoided during the year y from preventing waste disposal at the solid waste disposal site (SWDS) during the period from the start of the project activity to the end of the year y (tCO2e)

=

Model correction factor to account for model uncertainties

f

=

GWPCH 4

=

OX

=

F DOC f

= =

Fraction of methane captured at the SWDS and flared, combusted or used in another manner Global Warming Potential (GWP) of methane, valid for the relevant commitment period Oxidation factor (reflecting the amount of methane from SWDS that is oxidised in the soil or other material covering the waste Fraction of methane in the SWDS gas (volume fraction) Fraction of degradable organic carbon (DOC) that can decompose Methane correction factor Amount of organic waste type j prevented from disposal in the SWDS in the year x (tons) Fraction of degradable organic carbon (by weight) in the waste type j

MCF W j ,x

=

DOC j

=

kj

=

Decay rate for the waste type j

j

=

x

=

y

=

Waste type category (index) Year during the crediting period: x runs from the first year of the first crediting period (x = 1) to the year y for which avoided emissions are calculated (x = y) Year for which methane emissions are calculated

=

1.1. Input Parameters The input parameters used in the FOD model are more or less similar to the LandGEM model except that IPCC has attempted to make the projections for methane emissions more realistic by incorporating various correction factors to the equation.

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The values for correction factors used in the model are mostly default values suggested by IPCC, as mentioned below:

Degradable Organic Carbon ( DOC j ) Degradable organic carbon is the fraction of the organic carbon present in the waste that will degrade under anaerobic conditions. However, only fraction of the DOC is decomposable in nature ( DOC f ). Hence, decomposable degradable organic carbon by mass ( DDOCm ) is:

DDOCm = W ∗ DOC ∗ DOC f ∗ MCF

(4)

Where, W is the mass of the waste deposited in the landfill in the given year and MCF is the methane correction factor for aerobic decomposition of waste. The relationship between Methane generation potential ( L0 ) used in LandGEM and

DDOCm , as described in IPCC (2006), is:

L0 = DDOC m ∗ F ∗

16 12

(5)

Where, F = CH4 concentration in LFG and 16/12 is the ratio of molecular weight of CH4 and Carbon. MSW contains different types of waste namely food waste, garden waste, paper, wood, textiles, plastics etc. Different waste types contain different amount of degradable organic carbon (DOC). As per IPCC FOD model, waste composition of MSW is classified into six categories as shown in Table 8.

Decay rate/methane generation rate ( k j ) As already mentioned in the previous section, IPCC has mentioned two alternatives to use the value of k for estimation of gas potential. In this model, the waste composition option is used where degradation of different types of waste is assumed to be independent of each other. IPCC 2006 has recommended default k values for different waste categories dependent upon the location of the landfill site and its climatic conditions as shown in Table 9. Table 8. IPCC Default DOC Value (In Fraction) For Different Waste Type Type of Waste Wood and wood products, A Pulp, paper and cardboard, B Food, food waste, beverages and tobacco, C Textiles, D Garden, yard and park waste, E Glass, plastic, metal other inert, F Source: IPCC, 2006

DOCj 0.430 0.400 0.150 0.240 0.200 0

42

Sherien A. Elagroudy and Mostafa A. Warith Table 9. IPCC Default of K Used in IPCC in IPCC FOD Modeling

Type of Waste Wood and wood products, A Pulp, paper and cardboard, B Food, food waste, beverages and tobacco, C Textiles, D Garden, yard and park waste, E Glass, plastic, metal other inert, F

K 0.035 0.07 0.40 0.07 0.17 0

Source: IPCC, 2006

D. Regression Models The EPA Air and Energy Engineering Research Laboratory (AEERL) began a research program in 1990 with the goal of improving global landfill methane emission estimates. Part of this program was a field study to gather information that was used to develop an empirical model of methane emissions. Twenty-one US landfills with gas recovery systems were included in the study. Site-specific information included average methane recovery rate, landfill size, refuse mass, average age of the refuse, and climate. A correlation analysis showed that refuse mass was positively linearly correlated with landfill depth, volume, area, and well depth. Regression analysis of the methane recovery rate on depth, refuse mass, and volume was significant, but depth was the best predictive variable (R2 = 0.53). Refuse mass was nearly as good (R2 = 0.5). None of the climate variables (precipitation, average temperature, dew point) correlated well with the methane recovery rate. Much of the variability in methane recovery remains unexplained, and is likely due to between-site differences in landfill construction, operation, and refuse composition. A model for global landfill emissions estimation was proposed based on this data. A simple model correlating refuse mass to methane recovery with a zero intercept was developed:

Qmethane = 4.52 w

(6)

Where; 3

Qmethane = Methane flow rate (m /min)

w = mass of refuse (Mg) E- Theoretical Models The theoretical CH4 generation capacity ( L0 ) can be determined by a stoichiometric method that is based on a gross empirical formula representing the chemical composition of the waste. If a waste contains carbon, hydrogen, oxygen, nitrogen and sulfur (represented by CaHbOcNdSe), its decomposition to gas is shown as:

Ca H b Oc N d Se ® vCH 4 + wCO2 + xN 2 + yNH 3 + zH 2 S + humus

(7)

Biogas Recovery from Landfills

43

However, this type of model is of limited use because it provides an estimate of the total amount of gas generated and does not provide information on the rate of generation. It also requires knowledge of the chemical composition of the waste.

F. Other Models El-Fadel et al. (1996b) developed a mathematical model to simulate the biodegradation of solid waste and biogas generation in a sanitary landfill. The model was based on bio-kinetic equations describing the microbial processes, time dependent transport and generation of gas and heat. The biodegradation process occurred in three stages: hydrolysis, acidogenesis and methanogenesis. They assumed hydrolysis to be the rate limiting step in the biodegradation process and was represented by first order kinetics. Monod kinetics were used to simulate the growth rate of acidogenic and methanogenic biomass. The effect of pH inhibition on the methanogenic growth rate was also included. In El-Fadel et al. (1997) several runs were performed to assess the model sensitivity to the hydrolysis rate constant, the kinetics constant of acidogenic and methanogenic biomass (µ, kd, ks) and initial carbon concentrations (solid, aqueous, acetic acid, acidogenic and methanogenic). They concluded that the hydrolysis rate is the most important parameter in gas generation in landfills. Gas generation showed greater sensitivity to the methanogenic kinetics than to the acidogenic kinetics, and the initial concentrations of acetic acid and methanogenic biomass had a more important impact on gas generation than aqueous and acidogenic biomass. In El-Fadel et al. (1996c) the model was used to simulate data from the Mountain View controlled landfill. The results of the model showed good agreement with the field data. They concluded that the model could be used to predict the rate and total production of biogases in landfills. Al-Yousfi et al. (1998) developed a numerical (PITTLEACH) model to predict the leachate quality and quantity and biogas generation from municipal solid waste, for both single pass and leachate recirculation. The model consisted of four phases. In the first phase, the water budget method was used to estimate the net percolation rate of water flow into the waste layer. In the second phase, leachate generation and transport rates were estimated by using the theory of moisture flow through unsaturated porous media. The third step was to simulate the anaerobic process involved in landfill stabilization, including hydrolysis, acid formation and methane fermentation. In the fourth phase, the effect of acids on the pH was modeled. The model was calibrated with experiments done by Pohland et al. (1992) and Yari (1986). The model results were close to the experimental results for both scenarios (single pass and leachate recirculation). Pareek et al. (1999) developed a mathematical model to predict the methane and carbon dioxide production from landfill reactors operated under sulfate reducing and methane producing conditions. The model was based on biochemical processes responsible for the degradation of solid waste in landfills. These processes were hydrolysis, acidogenesis, methanogenesis and sulfidogenesis. Hydrolysis was assumed to be the rate limiting step in the process and followed first order reaction, whereas the Monod kinetics were applied for the growth of acidogenic and methanogenic bacteria. A multiplicative model was applied to estimate the growth rate of the sulfidogenic bacteria. The values of kinetics required were taken from the literature. The model was calibrated with four experiments run for 700 days.

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Sherien A. Elagroudy and Mostafa A. Warith

The simulated methane production was in good agreement with the measured values in all reactors, but the carbon dioxide production was not so accurate in the sulfate reducing reactors for the first 100 days. They concluded that the moisture factor and initial concentration of biomass and acetate were important factors in controlling the microbial growth rates and methane production. Suk et al. (2000) proposed a numerical model to predict the change in leachate concentration and gas production by microbial activity in landfills. The model included gas and water flows, interphase mass transfer of solids and water phase solutes, microbial growth and death, and aerobic and anaerobic biodegradation. The model was applied to measure gas composition and leachate qualities of the experiments done by Lee (1997). The results of the model matched the experimental data. Haarstick et al. (2001) developed a mathematical model to simulate the biodegradation of organic wastes (easily and slowly degraded), biogas generation and heat release. The model was based on physical, chemical, thermodynamic and microbial processes occurring in landfills. The biodegradation of organic waste was assumed to follow three biochemical reactions: hydrolysis, acidogenesis and methanogenesis in which Monod kinetics were used for all of them. The specific growth rate was considered to be effected by inhibition terms included substrate limiting, inhibitory substrate, temperature, and pH.

μ max ⋅ f 1 (s ) ⋅ f 2 ( s ) ⋅ f 3 (T ) ⋅ f 4 ( pH )

(8)

Where;

si : Inhibition term for substrate limiting K si + si K Ii : Inhibition term for inhibitory substrate f 2 ( s) = K si + si f 3 (T ) = exp− (k (T − Topt )) : Inhibition term for influence of temperature f1 ( s ) =

f 4 ( pH ) =

K pH K pH + I pH

: Inhibition term for influence of pH

The temperature effect is taken into account in the hydrolysis rate constant, and in the acidogenic and methanogenic bacteria kinetics. The effect of pH on the biodegradation rate is also taken into account by including an inhibition term in the maximum growth rate and expressed as non competitive inhibition. The kinetics required for the model were obtained from the literature. The model was not calibrated with real data. Naranjo et al. (2004) modified the model of Haarstrick et al. (2001) by assuming the hydrolysis followed first order kinetics. The model was calibrated with experiments. They used the model to simulate the effect of temperature and water content on acetate and methane production. The model showed results similar to the experiments. They concluded that temperature had an impact on the growth and activity of bacteria and that an increase in water content enhanced methane production.

Biogas Recovery from Landfills

45

Zacharof et al. (2004) developed a mathematical model to simulate the hydrological and biochemical processes taking place in solid waste landfills. They used a statistical velocity model to represent the water flow through the waste. The waste biodegradation was assumed to follow three steps: hydrolysis, acidogenesis and methanogenesis; and employed a simplified methodology for the rate of biodegradation to reduce the parameter required. The model was used to simulate case studies. Sensitive analysis showed uncertain results. They found the model was sensitive to depth of waste, infiltration rate, waste heterogeneity and biodegradation rate constants. In the end, they concluded that the model could be used as a tool for modeling landfill processes and that further improvements were required to assess the model’s performance. Yildiz et al. (2004) proposed a mathematical model to simulate the landfill leachate behavior, distribution of moisture through the landfill, and methane production. They assumed that landfills consisted of cells and that each cell consisted of several layers. Also, they considered each layer as a completely mixed reactor having uniformly distributed solid wastes, moisture, gases and microorganisms. The model was based on the governing equations that describe leachate production, solubilization of inorganic and organic matter, degradation of soluble organic matter, the growth of acidogenic and methanogenic microorganisms, and their inhibition by acetic acid, and change in pH over time. The solubilization of inorganic solid waste was assumed to have followed zero order kinetics, whereas the solubilization of organic solid waste was assumed to be a function of the concentration difference in leachate and microbial activity. The growth rate of acidogenic and methanogenic microorganisms were described by the Monod model, and it included an inhibition terms for acetic acid and pH. The model was solved by the fourth order RungeKulta method and calibrated with real landfill data from the Keele Valley landfill. The values of the kinetics required for the model were determined by using a trial and error procedure with the data obtained from the landfill. These values were then compared with the literature. There was good agreement between the predicted and observed results from the Keele Valley landfill. They concluded that the model had the potential to be used during the design of the landfills to estimate the quality and quantity of leachate and methane production for different operation conditions. White et al. (2003, 2004) developed a mathematical model to simulate solid waste biodegradation and gas generation in landfills. The model included biochemical degradation of solid waste, and transport of leachate and gas. The biodegradation part was based on the model proposed by Young (1989) and El-Fadel et al. (1996a) and occurred in three stages: hydrolysis, acidogenesis and methanogenesis. The Monod kinetics were used to simulate the growth rate of biomass in all stages. The moisture content and effect of pH inhibition on the biomass growth rates were included in the model. The required kinetics for the model were obtained from the literature. The model was used to simulate case studies but was not calibrated with real data. They concluded that it could be used for laboratory and field tests to investigate the geotechnical and hydrogeological properties of biodegrading solid waste.

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Sherien A. Elagroudy and Mostafa A. Warith

VII. LANDFILL GAS ENERGY SYSTEMS With the recognition of the formation of landfill gas and its associated hazards, and the potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site. Figure 8 shows a schematic diagram of a landfill gas energy recovery project. The energy recovery technology is based around the gas collection system and the pre-treatment and power generation technology. Each of those three systems is explained separately in details.

Figure 8. Schematic diagram of a landfill gas energy recovery scheme. Source: Brown and Maunder 1994.

A. LFG Collection System Once gases are produced under the landfill surface, they generally move away from the landfill. Gases tend to expand and fill the available space, so that they move, or "migrate," through the limited pore spaces within the refuse and soils covering the landfill. The natural tendency of landfill gases that are lighter than air, such as methane, is to move upward, usually through the landfill surface. Upward movement of landfill gas can be inhibited by densely compacted waste or landfill cover material (e.g., by daily soil cover and caps). When upward movement is inhibited, the gas tends to migrate horizontally to other areas within the landfill or to areas outside the landfill, where it can resume its upward path. Basically, the gases follow the path of least resistance. Some gases, such as carbon dioxide, are denser than air and will collect in subsurface areas, such as utility corridors. Three main factors influence

Biogas Recovery from Landfills

47

the migration of landfill gases: diffusion (concentration), pressure, and permeability. Gases can travel off-site and into neighboring buildings, posing indoor air quality threats such as odors or exposures to inhalation hazards, or even fire and explosion. For these reasons gas control is needed. There are three types of systems used to control landfill gas migration (Tchobanoglous and O’Leary 1994; McBean et al 1995; Pescod 1991–93; Waste Management Paper 26B, 1995; Waste Management Paper 27, 1994): passive venting; physical barriers; pumping extraction systems.

Passive venting Passive systems use existing variations in landfill pressure and gas concentrations to vent landfill gas into the atmosphere or a control system. Passive venting systems are only recommended for old sites in the late stages of gas generation where gas generation rates are low, or where inert wastes are landfilled and similarly low or negligible rates of gas generation are found. The passive venting pit consists of a highly permeable vent of gravel material encased in a geotextile fabric to prevent ingress of fine material and reduction of permeability. The gases flow up the highly permeable layer, and vent passively into the atmosphere through a permeable capping layer of sand and granular soil or crushed stone. The vent may also be constructed of granular material but with a central perforated plastic pipe, the pipe venting directly to the atmosphere. Construction of the passive venting system may be as emplacement of the waste proceeds or afterwards by drilling or excavation into the mass of waste. Typically the vents are placed at intervals of between 20 and 50 m and to depths ranging from 50% to 90% of the waste thickness. If groundwater is encountered within the waste, wells end at the groundwater table. Other designs of passive gas venting systems include trenches, which are excavated into or at the boundary of the waste. The trench is lined at the outer edge with a low-permeability barrier and the trench is filled with highpermeability gravel, or perforated pipes are used to vent the migrating gas to the surface (Waste Management Paper 26B, 1995; Waste Management Paper 27, 1994). Physical barriers Physical barriers use low-permeability barriers of, for example, flexible polymeric geomembranes, bentonite cement or clay, to contain and restrict the gas migration. Whilst these barriers might form part of a leachate containment system, they are less effective in containing gas. Coefficients of permeability for gas containment are required to be lower than 10−9 m/s. Efficiencies of barriers are improved if they are combined with a means of removing the gas by either passive venting or pumped extraction. Pumping extraction systems Pumping extraction systems pump the gas out of the landfill. The gas migrates to gas pits or wells, within the waste, which consist of highly permeable gravel, stones or rubble with a central perforated plastic pipe. The gases pass through the high-permeability vent to a plain imperforated pipe which draws the gases through to the pump. Leachate vapor may also be pumped out with the gas, which has high moisture content, and therefore a leachate condensation trap is required. Figure 9 shows a typical pumping extraction well. The gas pumped to the surface is either flared by self-sustaining combustion or the use of a support

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fuel, utilized in an energy recovery system, or if the gas concentrations are sufficiently low, discharged to the atmosphere.

Figure 9. Typical combined leachate and landfill gas collection well. Source: Waste Management Paper 26B, 1995.

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B. LFG Pretreatment System A condensate removal system is required, since the gas is at temperatures above ambient and is saturated with water vapour and organic vapours. As the gas cools the water vapour condenses to form water in the pipe, which reduces the efficiency of gas collection and transport. The condensate system used to remove the water vapour consists of baffled or expansion chambers which cool and condense the water. Condensate systems both below and above ground may be required to de-water the gas. A filter would also be included to remove fine particulate material from the gas flow. The gas is then compressed and possibly passed to a pre-treatment section if a greater degree of clean-up is required, for example, to remove corrosive trace gases and vapor from the gas stream. Such possible pre-treatments may include further filtration, gas chilling to condense certain constituents, absorption and adsorption systems to scrub the gases, and other gas clean-up systems such as membranes and molecular sieves to remove trace contaminants. A large proportion of the landfill gas consists of carbon dioxide which is non-combustible and therefore reduces the overall calorific value of the gas. Therefore, for utilization systems requiring a high specification gas or a high calorific value, then clean-up systems to remove carbon dioxide may be required. Such systems include water scrubbing, absorption on zeolites and membrane separation and are expensive to install and maintain (Brown and Maunder 1994; Stegmann 1996).

C. LFG Utilization System 1. Combustion technologies (Flaring Practices) LFG flaring Combustion is the most common technique for controlling and treating landfill gas. Combustion technologies such as flares, incinerators, boilers, gas turbines, and internal combustion engines thermally destroy the compounds in landfill gas. Over 98% destruction of organic compounds is typically achieved. Methane is converted to carbon dioxide, resulting in a large greenhouse gas impact reduction. Combustion or flaring is most efficient when the landfill gas contains at least 20% methane by volume. At this methane concentration, the landfill gas will readily form a combustible mixture with ambient air, so that only an ignition source is needed for operation. At landfills with less than 20% methane by volume, supplemental fuel (e.g., natural gas) is required to operate flares, greatly increasing operating costs. When combustion is used, two different types of flares can be chosen: open or enclosed flares. 1.1. Open flame flares Open flame flares (e.g., candle or pipe flares), the simplest flaring technology, consist of a pipe through which the gas is pumped, a pilot light to spark the gas, and a means to regulate the gas flow. The simplicity of the design and operation of an open flame flare is an advantage of this technology. Disadvantages include inefficient combustion, aesthetic complaints, and monitoring difficulties. Sometimes, open flame flares are partially covered to hide the flame from view and improve monitoring accuracy.

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1.2. Enclosed flame flares Enclosed flame flares are more complex and expensive than open flame flares. Nevertheless, most flares designed today are enclosed, because this design eliminates some of the disadvantages associated with open flame flares. Enclosed flame flares consist of multiple burners enclosed within fire- resistant walls that extend above the flame. Unlike open flame flares, the amount of gas and air entering an enclosed flame flare can be controlled, making combustion more reliable and more efficient. 1.3. Other enclosed combustion technologies Other enclosed combustion technologies such as boilers, process heaters, gas turbines, and internal combustion engines can be used not only to efficiently destroy organic compounds in landfill gas, but also to generate useful energy or electricity, as described later in this chapter. In addition to flaring, the other options for dealing with landfill gas (once collected) are as follows: • • • • •

boilers for making thermal energy Internal combustion engine for generating electricity Gas turbine for generating electricity Fuel cell for generating electricity Conversion of the methane to methyl alcohol

There are limited data comparing emissions from landfill gas flares to energy producing combustion devices (which includes boilers, turbines and internal combustion engines). According to very limited data in a USEPA 1995 report, carbon monoxide and NOx emissions are highest from internal combustion engines and lowest from boilers. Flares and gas turbines are somewhere in the middle. Flaring of landfill gas is done either in a candle flare or a shrouded flare. A candle flare is an open air flame. With such, there is no reliable means to monitor for dioxins or other toxic emissions. Shrouded flares involve enclosing the flame in an insulated cylindrical shroud which can be anywhere from 5 to 18 m tall. While dioxins can be tested for in such flares, it is possible that enclosing the flare will keep the post combustion temperature in dioxinformation range, resulting in increased dioxin emissions. Essentially, this is a loose-loose situation. Most shrouded landfill gas flares have exit temperatures of around 7600C, well above the dioxin formation range (which end around 4000C). In such cases, dioxins will be formed in midair as the exhaust hits the cooler background air after leaving the stack. Dioxin emissions data are also very sparse. Flares are known to generate more dioxin than internal combustion engines or boiler mufflers. There is high variability in dioxin emissions from landfill gas burners (based on composition of waste dumped and also on the combustion technology - internal combustion engines are much more variable). Burning landfill gas is dirtier than burning natural gas. Whether using an internal combustion engine or a gas turbine, burning landfill gas to produce energy emits more pollution per kilowatt hour than natural gas does. Some public concerns have been raised about whether the combustion of landfill gas may create toxic chemicals. Combustion can create acid gases such as SO2 and NOx. The generation of dioxins has also been questioned. EPA investigated the issue of dioxin formation and

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concluded that the existing data from several landfills did not provide evidence showing significant dioxin formation during landfill gas combustion. Because of the potential imminent health threat from other components of landfill gas, landfill gas destruction in a properly designed and operated control device, such as a flare or energy recovery unit, is preferable to uncontrolled release of landfill gas. Scientists continue to review new information on byproduct emissions from landfill gas control devices as it becomes available. • Boilers Boilers are among the cheapest options. They produce thermal energy or heat, not electricity. Boilers are generally less sensitive to landfill gas contaminants and therefore require fewer cleanups than other alternatives. Boilers have the lowest NOx and carbon monoxide emissions of the combustion technologies. Landfill gas use in boilers brings in the issue of piping the gas to local industries. While boilers themselves may not require much cleanup of the gas, the pipelines do require some cleanup, since corrosive compounds in the gas (particularly the acids and hydrogen sulfide -- H2S) can damage the pipelines. Among the concerns with this option are the integrity of the pipeline, liability issues, and the economic support of neighboring polluting industries which might use the gas. • Internal Combustion Engines Internal combustion engines are the dirtiest technology for burning landfill gas. They emit the most carbon monoxide and NOx and they may be the largest dioxin source of the available technologies. • Gas Turbines Gas turbines are somewhere in the middle in terms of carbon monoxide and NOx emissions. There isn't enough data on dioxin emissions from landfill gas turbines to provide an extensive comparison. • Fuel Cells Fuel cells are the most expensive technology, and they are still largely experimental. EPA describes fuel cells as "potentially one of the cleanest energy conversion technologies available." In order not to poison the fuel cells, halogenated contaminants must first be removed and destroyed, for example by pyrolysis. • Conversion of Methane to Methyl Alchol One option is to convert the methane recovered from landfills into methyl alcohol or methanol. Other novel ideas include converting the carbon dioxide in landfill gas to dry ice for sale to industry.

2. Non-combustion technologies Non-combustion technologies were developed in the 1990s as an alternative to combustion, which produces compounds that contribute to smog, including nitrogen oxides, sulfur oxides, carbon monoxide, and particulate matter. Non combustion technologies fall into two groups: energy recovery technologies and gas-to-product conversion technologies. Regardless of which non combustion technology is used, the landfill gas must first undergo

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pretreatment to remove impurities such as water, NMOC, and carbon dioxide. Numerous pretreatment methods are available to address the impurities of concern for a specific landfill. After pretreatment, the purified landfill gas is treated by non combustion technology options.

Figure 10. Schematic diagram of the Calgary Biocell

2.1. Energy recovery technologies Energy recovery technologies use landfill gas to produce energy directly. Currently, the phosphoric acid fuel cell (PAFC) is the only commercially available non-combustion energy recovery technology. Other types of fuel cells (molten carbonate, solid oxide, and solid polymer) are still under development. The PAFC system consists of landfill gas collection and pretreatment, a fuel cell processing system, fuel cell stacks, and a power conditioning system. Several chemical reactions occur within this system to create water, electricity, heat, and waste gases. The waste gases are destroyed in a flare. 2.2. Gas to product conversion technologies Gas-to-product conversion technologies focus on converting landfill gas into commercial products, such as compressed natural gas, methanol, purified carbon dioxide and methane, or liquefied natural gas. The processes used to produce each of these products vary, but each includes landfill gas collection, pretreatment and chemical reactions and/ or purification techniques. Some of the processes use flares to destroy gaseous wastes. Non-combustion energy recovery systems are not used as widely as combustion based systems. Fuel cells are a promising new technology for producing energy from landfill gas that does not involve combustion. This technology has been demonstrated and in the future may become more economically competitive with other options. One option that does not involve combustion of landfill gas at or near the landfill is purifying the landfill gas to remove constituents other than methane, producing a high British thermal unit (Btu) gas that can be sold as pipeline quality natural gas. Although the high-Btu gas is eventually combusted, it

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would not contribute to any emissions near the landfill. Another option is using compressed landfill gas as a vehicle fuel. Both combustion and non-combustion energy recovery systems have three basic components: (1) a gas collection system; (2) a gas processing, treatment, and conversion system; and (3) a means to transport the gas or final product to the user. Gas is collected from the landfill by the use of active vents. It is then transported to a central point for processing. Processing requirements vary, depending on the gas composition and the intended use, but typically include a series of chemical reactions or filters to remove impurities. For direct use of landfill gas in boilers, minimal treatment is required. For landfill gas injection into a natural gas pipeline, extensive treatment is necessary to remove carbon dioxide. At a minimum, the gas is filtered to remove any particles and water that may be suspended in the gas stream.

VIII. CASE STUDY: CALGARY BIOCELL PROJECT A. Introduction Although landfill disposal is an integral part of waste management, most people identify sanitary landfills as a key factor in the mis-management of finite resources and as a source of greenhouse gas emissions. This situation arose because modem landfills have evolved from open dumping of solid waste. Since 1960s, engineers and scientists have attempted to rectify the problems with “open dumps”, targeting groundwater contamination by landfill leachate and waste related aesthetic issues. More recently, attempts have been made to address the landfill gas issues, including the contribution of landfills towards the global carbon budget and potentially global warming. The reactive approach followed by landfill engineers has created collateral problems. For example, the current traditional approach of waste landfilling, namely the dry-tomb landfilling approach, solves the problem of groundwater contamination but is counterproductive because of the slow production and atmospheric release of methane (CH4), and loss of resources (e.g. material and space). So far, the general approach towards solving the solid waste problem has been mostly piece meal and reactive. Landfills are considered a liability requiring solutions for individual landfill problems. This reactive approach has ignored the positive aspects of solid waste including the inherent resource value of the waste. The pessimistic view of waste is “waste is a liability and requires high level of resources to manage” but the optimistic view of waste is “waste is a resource in the wrong place and wrong time”. Recent advances in sanitary landfill technology research have indicated that the operation of landfills as bioreactors (Reinhart and Townsend, 1998) could be viable. Waste entombment in a conventional landfill slows down the process of biodegradation by minimizing moisture entry, whereas, bioreactors speed up the biodegradation process by controlled input of moisture (i.e., by leachate recirculation) and increased cycling of nutrients and bacterial populations (Reinhart and Townsend, 1998). The operation of traditional “entombed” landfills for the sole purpose of controlling groundwater contamination is not sustainable, and could be counterproductive because of the slow production and atmospheric release of CH4 and loss of resources (e.g. material and space).

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The biocell concept involves the operation of a landfill cell as an anaerobic bioreactor with leachate recirculation to recover the full energy potential of biomass waste. In a second stage, the biocell is operated in the aerobic mode to produce stable organic material, that can be used as low-quality compost or refuse derived fuel (RDF). The input of air and operation of the cell as an aerobic bioreactor (Stessel and Murphy, 1992) enhances waste decomposition to a level where it could be mined in a third stage for compost/RDF and space recovery, thus making the landfill operation sustainable. Instead of operating the “entombed” waste cell as a “long-term storage facility”, the biocell converts the cell into a waste processing facility. The biocell is a novel and holistic approach; with energy recovery, landfill gas emission control, groundwater contamination control, and resource/space recovery as direct benefits. This approach has the potential to revolutionize management of waste in Canada, and in other countries, both developed and developing.

B. The Calgary Biocell: Background and Construction Phase In dry-tomb type sanitary landfills, the preferred landfilling option in the United States, the underlying principle has been to prevent saturation of the waste in order to reduce the potential for leachate generation and leaking into the sub-surface and groundwater aquifers. In a bioreactor landfill, leachate is re-circulated to maintain high waste moisture content. Data compiled by Rees and Grainger (1982) from lysimeter studies suggest the rate of gas production increases exponentially as the water content of the waste is increased. At the Brogborough landfill in the United Kingdom, addition of water to test cells containing 15,000 tonnes of waste was found to increase the rate of gas production by 8 m3/tonne/yr than that of a control cell (Knox and Gronow, 1995). There are three different types of bioreactor landfills corresponding to the operational processes involved, aerobic, anaerobic, and hybrid (aerobic-anaerobic) as discussed in Section 2. The primary difference between the aerobic and anaerobic is that, in anaerobic bioreactors, a key objective is to enhance the generation of landfill gas, containing methane and carbon dioxide, under anaerobic conditions, by minimizing oxygen infiltration, whereas, in aerobic bioreactors, the objective is to maintain aerobic conditions by introducing oxygen into the waste mass. The Calgary biocell is a unique facility where the three processes, anaerobic bioreactor, aerobic bioreactor and mining are sequentially applied in one cell. The Calgary biocell is a full-scale facility, which covers an area of 100 m x 100 m with a waste footprint of 85 m x 85 m and a maximum height of 18 m. The schematic diagram of the biocell is presented in Figure 10. The base of the biocell is 50m x 50m, and it extends 10 m below the ground surface. The shape of the biocell is a pyramidal square frustum increasing sectional area with side slope of 3H : 1V up to ground level. The bottom liner/leachate collection systems are used to minimize groundwater contamination and maximize recovery of leachate. The biocell received 43,000 tonnes of residential (high in organics) and selected commercial wastes, with the resulting feedstock placed in three lifts of 5-6 m each. Collected leachate is re-circulated after ensuring the quality is acceptable. A pipe system was added to re-circulate the collected leachate. Re-circulation of leachate adds the much needed moisture and transfer bacteria from well-inoculated waste to freshly deposited waste, thus accelerating the establishment of microbial community. The biocell is instrumented to gather moisture, temperature and

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settlement data. The leachate composition is analyzed on a regular basis. A gas collection system is installed for landfill gas collection and emission control. The produced biogas is collected using this gas collection system comprised of a combination of vertical wells and horizontal trenches. The collected bio-gas is used to produce electrical energy. This gas collection system will also be used to pump air into the waste matrix during the second stage aerobic operation to accelerate biological degradation. A low permeable final biocover was installed to prevent gas escape from the top surface prior to extraction of biogas. Gas/energy recovery has commenced after filling and construction of the final cover. CO2 emissions

CH4 & CO2 emissions

Commercial recovery

Oxidation in landfill bio-cover (Methanotrophs)

Final bio-cover CH4 & CO2 Solid waste-3rd lift (8 m)

generation GL

GL

2nd Intermediate thin biocover (30 cm) Solid waste-2nd lift (5 m)

CH4 & CO2 generation

1st Intermediate thin biocover (30 cm) Solid waste-1st lift (5m)

CH4 & CO2 generation

Figure 10. Schematic diagram of the Calgary Biocell

The biocell is located at the Shepard landfill owned and operated by the City of Calgary, Canada. Construction of the biocell started in the summer of 2004. The biocell started receiving domestic municipal solid waste in April 2005. The 1st intermediate cover consisted of a mixture of partly stabilized leaf compost and soil (6:4 wet weight) and was placed in July 2005 over the 1st lift, with a depth of 5 m. Similarly, a 2nd intermediate cover of tree branch mulch was placed in December 2005 over the 2nd lift which was also 5 m in depth. A mixture of stabilized compost and tree mulch (9:1 wet weight) was placed in an area of 10m x 10m in the northwest quadrant. The thickness of both intermediate covers ranged from 30 to 40 cm. The placement of the third and final lift of waste commenced during the third week of January 2006. The materials for the landfill final cover and leachate collection system were selected to facilitate convenient excavation, and to recover, and to reuse all components of the biocell. The biocell reached its final design elevations by April 2006 and was capped initially with a 0.5 m biocover, a granular medium to support methanotrophic bacteria that oxidize methane to carbon dioxoide without producing harmful by-products. The construction was completed in summer 2006 and operation started in September 2006 with gas recovery. The Calgary biocell pilot project used real-time instrumentation to measure settlement during the

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construction phase of the biocell. The field data during construction stage was presented in Hunte et al, 2007. According to Hunte et al. (2007) the settlement trend follows the waste filling operation. In addition, based on the load cell data, Hunte et al. (2007) back calculated the average unit weight of waste and also the compression index, two useful parameters of settlement models and found to be consistent with values reported in literature.

C. Operation of the Calgary Biocell The biocell operational plan is illustrated in Figure 11. The operation of each stage is described below.

Stage of Landfill Stage I: Anaerobic Bio-Reactor Stage II: Enhanced Aerobic Reactor Stage III: Mining, Recycling, and Recovery Total Expected Life Span of the Biocell

Timeline 5 to 7 years 1 to 2 years ½ to 1 year 6 to 12 years

Figure 11. Operational Plan of the Calgary Biocell

1. Biocell stage 1: Anaerobic decomposition with gas extraction In a waste cell, the biodegradation rate and landfill gas production depends on temperature, moisture content, nutrient and organic content in the waste. The higher the organic content, higher will be the gas production. In a conventional dry-tomb sanitary landfill, it may take as long as 50 to 100 years to degrade the majority of biodegradable organics (Crawford and Smith, 1985). In the biocell, such degradation will occur within a ten year time period. Although the concept of bioreactor landfilling is relatively new, a number of demonstration anaerobic bioreactors are underway in Northern America and Europe (Hettiaratchi, 2006). Crow Wing County Landfill (CWC) located in north central Minnesota was started in 1998 and accepted 50,000 tonnes of waste annually in an area of 5.7 hectares (14.1 acres). Four million gallons of treated and untreated leachate were injected to waste via

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horizontal laterals, working face spray; and spray on yard waste composting over intermediate cover (USEPA, 2007). Burlington County bioreactor in northwest New Jersey had full scale leachate and liquid recirculation from 2002 to 2005 in a 4 hectare (10 acre) area accepting about one million tonnes of MSW. The New River Regional bioreactor was a “research” bioreactor in Union County, north central Florida. It had about one million tonnes of waste in-place in an existing 5.07 hectare (10-acre) area. Leachate was re-circulated into an existing interim capped landfill with an exposed membrane cover. Volume of leachate re-circulated was about 24,600 m3 (6.5 million gallons) to date (USEPA, 2007). Salem County bioreactor in southwest New Jersey is another anaerobic bioreactor with about 2 hectare (5-acre) area. Leachate re-circulated from storage tank and force main to subsurface horizontal injection trenches has been performed since 2000. The rate of moisture addition is about 0.167 m3/tonne (44 gallons/tonne) waste (USEPA, 2007). Indicators of waste stabilization in these bioreactor landfills include settlement and gas production. The airspace at CWC landfill had been monitored using airspace factor (AUF) calculations. The cell was constructed in 1991 and recirculation began in 1998. Accordingly, the pre- and post-recirculation AUF was 595 kg/m3 (1004 lb/yd3) and 795 kg/m3 (1,341 lb/yd3) respectively. In addition, CWC installed four settlement plates in 2000 and 2001 at the waste level of two of the horizontal laterals. Data indicates that about 20% settlement has occurred within 5 years (USEPA, 2007). Burlington County landfill bioreactor measures quarterly settlement surveys with settlement plates and annual air photography surveys for topographic comparisons. Substantial settlement over the last 4 years of operation was observed increasing the effective density from 500 kg/ m3 (840 lb/yd3) to over 720 kg/ m3 (1,200 lb/yd3) (USEPA, 2007). The New River Regional Landfill measured the settlement with GPS coordinates on the landfill surface with settlement of each nested vertical injection well. The depth of settlement was the greatest at the injection well and declined with radial distance from the well up to 15 m (50 ft) away and then leveled off. The data also showed a distinct linear relationship between total settlement and the amount of moisture added (USEPA 2007). The Salem County bioreactor showed a settlement rate of about 1.5 m (5 ft) per year, which was greater than the rate observed before leachate re-circulation commenced (USEPA 2007). Landfill gas was passively vented at Crow Wing County Landfill and concentrations of methane had been as high as 60%. At the Calgary biocell, the end of stage 1 will be determined using a combination of settlement and gas generation readings. The gas production rate from October 2006 to September 2008 is shown on Figure 12. The initial gas production rate was low, indicating the microorganism acclimation stage. After leachate recirculation was initiated, the gas production rate increased four-fold to 254 m3/h (150 cfm). Thereafter, the gas production rate decreased gradually and reached a steady state flow rate of 170 m3/h (100 cfm) throughout the winter months. The Calgary Biocell received 43,000 tonnes of waste over a period of about one year. The methane generation potential, calculated from waste composition data, is 120 m3/tonne of solid waste. Hence, in October 2006 the theoretical gas generation rate at the Biocell should be approximately 282 m3/h (166cfm) which is very close to the field measured value of 254 m3/h (150cfm) reported in Figure 12.

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900,000

Methane generated (m3/month)

800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 0 Oct-06

Jan-07

Apr-07

Aug-07

Monthly methane Generation

Nov-07

Feb-08

Cumulative methane

Jun-08

Sep-08

Scholl Canyon

Figure 12. Comparison of Gas Production Data at the Biocell and a Conventional Landfill

For comparison purposes, the Figure 12 includes the cumulative methane generation curve for a landfill cell containing 43,000 tonnes of waste and operated as a dry-tomb sanitary landfill. The Scholl Canyon model was used to generate this curve using the parameter values; k = 0.023 yr-1 and Lo = 116.7 m3/tonne. The parameter values are those proposed by Environment Canada for a typical sanitary landfill in the province of Alberta. Evidently, the gas production at the biocell is more than 400% higher than that of a dry tomb type sanitary landfill of similar size and configuration located in Calgary, Alberta.

2. Biocell stage 2: Aerobic decomposition Once methane production decreases to a critical level, the next stage of biocell will initiate, that is to use aerobic degradation to rapidly decompose the remaining organic waste. Since aerobic degradation occurs at a high rate, this stage may take only a year or two to complete. To convert from anaerobic to aerobic conditions, air has to be introduced to the biocell and maintained to enhance the rate of waste decomposition (Stessel and Murphy, 1992; Hettiaratchi, 2006). The aerobic bioreactor concept was first proposed by Merz and Stone (1962) and there are more than 20 operating aerobic bioreactors in North America. The gas extraction system used during the anaerobic stage will be used to pump air into the landfill to create aerobic conditions, which accelerates and completes biological degradation or organic waste. The recirculation of appropriately adjusted leachate for aerobic degradation is also required for the same reason stated in the first stage of operation. Towards the end of aerobic decomposition, periodic testing of waste from boreholes and the analysis of the leachate would ensure complete biodegradation. The Calgary biocell is not the first to propose the use of aerobic treatment of waste in a waste cell. Williamson County bioreactor in central Tennessee is one of the existing aerobic

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bioreactors. This bioreactor landfill contains about 70,000 tonnes of waste in a cell of area 2.85 hectares (7 acres). Leachate, storm water, and air were injected into vertical risers with force main and header from storage tank that were retro-fitted for the closed landfill. The operation started in June 2000 and approximately 3,785 m3 (one million gallons) of leachate has been re-circulated (USEPA 2007). Two other aerobic landfills are in operation in Georgia (the Columbia County landfill) and in Atlanta (a privately operated bioreactor). For each aerobic landfill system, the air injection comprises of air compressor and piping connected to vertical air injection wells. Leachate collected in holding tanks at each site was pumped back into each aerobic system through a leachate recirculation system installed on top of the intermediate cap. The air injection rates were 56 m3/min and 100 m3/min for the Columbia County Landfill and Atlanta Landfill, respectively (Hudgings and Harper, 1999). Monthly topographic surveys of Williamson County Landfill bioreactor surface were performed to detect settlement across the site. An initial survey of the landfill bioreactor surface was conducted in January 2000, several months prior to the start-up of the landfill bioreactor as a baseline. Results of settlement as of April 2005 show a 0.53-meter to 1.2meter drop in the surface elevations since the landfill bioreactor operations began. The comparisons of the April 2005 elevations with the original survey in January 2000 show a 5.1% to 10.7% decrease in waste height over a 59-month period of operation (USEPA 2007). The study conducted in Georgia is interesting since it was conducted after landfills went through anaerobic process first. It was observed that the average settlement was 4.5% and the greatest settlement was 9% at Columbia County Landfill and 10% at Atlanta Landfill. The methane generation was reduced to 50% for the Columbia County Landfill and 50 to 90% for the Atlanta Landfill after aeration started. The operation of each system was also a dynamic process. It was observed in some areas that the decay process would revert back to anaerobic once temperatures decreased and that the air would make its way to other nearby areas, thereby repeating the process. Also, if too much leachate was applied in the aerobic areas, there would be an insufficient amount of oxygen for the bacteria and reverted the decay process back to anaerobic. Conversely, if too little leachate was applied, waste mass temperatures would tend to rise into the thermophillic range (40 to 700C). In several cases, it was also observed that air could provide a cooling effect on the waste mass temperatures above 600C or increase temperatures that were below 200C, provided sufficient moisture was applied (Hudgins, 1998; Hudgins and Harper, 1999). Partially degraded waste has produced difficulties in post mining attempts. Therefore, before moving to the mining step, it is essential to ensure that most of the organic waste is decomposed before mining commences.

3. Biocell stage 3: Mining for recovery of useful/recyclable products Mining will ensure recovery of space and various products (Murphy, 1993; Zee et al., 2003). Recycling a biocell involves a series of activities that includes excavation of cell, separating, sorting, and processing of recyclables. Separation of waste based on size can be performed through the use of various types of screens (trammel, vibrating, rotating, and disc). Once recovered, the recyclables can be crushed, bailed or shredded for the convenience of transportation. Usually, the excavated waste is stockpiled and fed to a shaker with sieves to separate the leftover organic waste. The organics that passes through 1 cm – 5 cm sieve size can be used as compost in agricultural applications or as refuse derived fuel (RDF). The collected non-

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biodegradable fraction will be sent to an automatic sorting unit through a feeding belt with a magnetic drum installed on the belt to remove the ferrous metals. The automatic sorting unit will sort through air flotation the light materials such as plastic, and non-degraded packaging wastes from heavier materials such as glass and aluminum based on weight difference. The mixed plastic waste could be shredded into small pieces for further processing. The majority of the compost-like product resulting from biodegradation is expected to be used as soil conditioner with various agricultural applications. Thermoplastics, such as PETE, PVC, and HDPE, soften when heated and can be recycled and remolded. Cullet, the industrial term for the furnace-ready scrap glass, is one of the most important ingredients of the glass manufacturing process. Cullet requires less energy to melt compared to sand since it already contains additives and can reduce furnace temperature. Recycled paper has many applications in newspaper industry and packaging. Other than these versatile uses, recyclables can be used as feedstock for a number of products, such as plastic lumber park benches or decks made from plastic milk jugs or soda bottles. Also, cardboard containers such as juice boxes and plastics have been used to produce construction materials (El Hagger, 2005). Even with enhanced biodegradation and recycling processes described above, there will be some residual waste which are non-recoverable, but with high calorific value. These wastes may include plastics, textiles, rubber, waste wood, and a number of other organic waste types. These can be used to produce refuse derived fuel (RDF) and co-incinerated in cement kilns.

D. Summary and Conclusions There are four main problems with landfill operation, namely aesthetic issues, ground/surface water contamination with leachate, emission of landfill gases, and extensive space requirements. Over the last three decades, the design and operation of sanitary landfills have managed to solve, to a large extent, the first three problems. However, the fourth problem has not been adequately addressed. The biocell is a concept proposed to solve all four problems at the same time. The biocell approach involves sequential operation of a landfill cell to produce methane gas during the first stage of anaerobic degradation, in-situ composting within the cell footprint during aerobic degradation in the second stage and landfill mining for resources and space recovery in a third stage. The resources that can be recovered include compost-like material and recyclables such as plastics, metal, and glass. Non-recovered waste but with high energy content can be used as refuse derived fuel. The practice of this approach will no longer require the need to allocate valuable land for new landfills on an on-going basis and hence will revolutionize the management of municipal solid waste.

REFERENCES Ağdağ, O. N. & Sponza, D. T. (2005). Effect of alkalinity on the performance of a simulated landfill bioreactor digesting organic solid wastes. Chemosphere, 59(6), 871-879. Allen, R., Matthew, Braithwaite, Alan, & Hills, C. Chris, (1997). Trace organic compounds in landfill gas at seven U.K. waste disposal sites Environ. Sci. Technol., 31(4), 1054-1061.

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Al-Yousfi, B. & Pohland, F. (1998). Strategies for simulation, design and management of solid wastes disposal sites as landfill bioreactors. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 2(1), 13- 21. Bae, J. H., Cho, K. W., Lee, S. J., Bum, B. S. & Yoon, B. H. (1998). Effects of leachate recycle and anaerobic digester sludge recycle on the methane production from solid wastes. Water Science and Technology, 38(2), 159-168. Baldwin, T., Stinson, J. & Ham, R. K. (1998). Decomposition of specific materials buried within sanitary landfills. Journal of Environmental Engineering, 124(12), 1193-1202. Barlaz, M. A. (1997). Microbial studies of landfills and anaerobic refuse decomposition. In Manual of Environmental Microbiology, 541-557, C. J. Hurst, (ed), American Society for Microbiology, Washington, D.C. Barlaz, M. A., Bonner, B. A. & Calvert, P. P. (1996). Evaluation of the Anaerobic Biodegradability of Radiolabeled Test Materials in a Laboratory-Scale Simulated Landfill, Institute for Scientific Research, ASTM, Phil. PA. Barlaz, M. A., Ham, R. K. & Schaefer, D. M. (1990). Methane production from municipal refuse - a review of enhancement techniques and microbial dynamics. Critical Reviews in Environmental Control, 19(6), 557-584. Beker, I. D. (1987). Control of acid degradation. In: Christensen, T.H., Cossu, R. and Stegmann, R. (eds). Proceeding Sardinia 87’, First International landfill Symposium. Vol. 2, Cagliari, Italy: CISA. 1-22. Cited in Komilis et al., (1999a) Brown, K. A. & Maunder, D. H. (1994). Exploitation of landfill gas: A UK perspective, Water Science and Technology, 30, 143–151. Buivid, M. et al. (1981). Fuel gas enhancement by controlled landfilling of municipal solid waste. Resour. Recovery Conserv., 6, 3. Cited in Barlaz et al., (1990) Chaiampo, F., Conti, R. & Cometto, D. (1996). Morphological characterization of MSW landfills, Resources, Conservation and Recycling, 17, 37–45. Chan, G. Y. S., Chu, L. M. & Wong, M. H. (2002). Effects of leachate recirculation on biogas production from landfill co-disposal of municipal solid waste, sewage sludge and marine sediment. Environmental Pollution, 118(3), 393-399. Cheremisinoff, N. P. (2003). Handbook of solid waste management and waste minimization technologies. Butterworth-Heinemann, USA. Chiemchaisri, C., Chiemchaisri, W., Nonthapund, U. & Sittichoktam, S. (2002). Acceleration of solid waste biodegradation in tropical landfill using bioreactor landfill, concept, 5th Asian Symposium on Academic Activities for Waste Management, Sep. 2002 Kuala Lumpur. Christensen, T. H. & Kjeldsen, P. (1989). Basic biochemical process in landfills. Sanitary landfilling: Process, Technology and Environmental Impact, Eds. Christensen, T.H., Cossu, R. and Stegmann, R., Academic press, London UK, 29-49. Christensen, T. H., Kjeldsen, P. & Stegmann, R. (1992) . Effects of landfill management procedures on landfill stabilization and leachate and gas quality. Landfilling of waste: Leachate edited by Christensen, T.H., Cossu, R. and Stegmann, R, Elsevier Applied Science, 6, London and New York, 119-137. Christensen, T. H., Kjeldsen, P. & Lindhardt, B. (1996). Gas generating processes in landfills. In, Landfilling of Waste: Biogas, Christensen, T. H., Cossu, R., & Stegman, R. (Eds.), E & FN Spon, London.

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Hudgins, M. & Harper, S. (1999). Operational characteristics of two aerobic landfill systems. Proceedings of the 7th International Waste Management and Landfill Symposium in Sardinia, Italy. Hunte, C., Hettiaratchi, P., Meegoda, N. J. & Hettiarachchi, C. H., (2007). Settlement of bioreactor landfills during filling operation. ASCE Geotechnical Special Publication #152, GeoDenver2007, ISBN # 0784408971 Jin, H. (2005). Decomposition of high organic and moisture content municipal solid waste in bioreactor landfills. M.Sc. Thesis, Ryerson Polytechnic University, Ontario, Canada. Kjeldsen, P., Barlaz, M. A., Rooker A. P., Baun, A., Ledin, A. & Christensen, T. H. (2002). Critical Reviews in Environmental Science and Technology, 32, 297–336. Klink, R. E. & Ham, R. K. (1982). Effects of moisture movement on methane production in solid-waste landfill samples. Resources and Conservation, 8(1), 29-41. Knox, K. & Gronow, J. R. (1995). Pilot scale study of denitrification and contaminant flushing during prolonged leachate recirculation. Proceedings Sardinia '95, Fifth International Landfill Symposium, S.Margherita di Pula, Cagliari, Italy. Komilis, D. P., Ham, R. K. & Stegmann, R. (1999a). The effect of landfill design and operation practices on waste degradation behavior: A review. Waste Management & Research, 17(1), 20-26. Komilis, D. P., Ham, R. K. & Stegmann, R. (1999b). The effect of municipal solid waste pretreatment on landfill behavior: A literature review. Waste Management & Research, 17(1), 10-19. Landfill Gas Development Guidelines. (1996). Energy technology support unit. Department of Trade and Industry, HMSO, London. Landva, Arvid O. & Clark, Jack I., (1990). Geotechnics of Waste Fill. Geotechnics of Waste Fill – Theory and Practice, ASTM STP 1070, ASTM, Philadelphia, PA Laquidara, M. J., Leuschner, A. P. & Wise, D. L. (1986). Procedure for determining potential gas quantities in an existing sanitary-landfill. Water Science and Technology, 18(12), 151-162. Lee, N. H. (1997). Development of landfill gas control and utilization technologies. Rep. No. EPA/ 9-3-4, Seoul. Leuschner A. (1982). Enhancement of degradation: Laboratory-scale experiments. In sanitary landfilling process, Technology and Environmental Impact, Christensen, T.H., Cossu R. and Stegmann R. eds, Academic Press, London, UK, 83- 102. Loening A. (2003). Predictions and projections; looking at the power generation potential of landfill gas, Waste Management World. International Solid Waste Association, Copenhagen, November– December. McBean E. A., Rovers F. A. & Farquhar, G. J. (1995). Solid waste landfill engineering and design. Prentice-Hall, New Jersey. McCarty, P. L. (1964). Anaerobic waste treatment fundamentals. Parts 1, 2, 3 and 4. Public works, 95 (9), 107-12, (10), 123-6, (11), 91-4, (12), 95-9. Cited in Christensen et al., (1989). Merz, R. C. & Stone, R. (1962). Landfill settlement rates. Public Works, 93(9), 103-106, 210212 Mora-Naranjo, N., Meima, J. A., Haarstrick, A. & Hempel, D. C. (2004). Modelling and experimental investigation of environmental influences on the acetate and methane formation in solid waste. Waste Management, 24(8), 763-773.

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Mosher, B. W., Czepiel, P. M., Harriss, R. C., Shorter, J. H., Kolb, C. E., McManus, J. B., Allwine, E. & Lamb, B. K. (1999). Methane emissions at nine landfill sites in the northeastern United States. Environ. Sci. Technol., 33(12), 2088–2094. Moss, H. (1997). Dynamotive Technologies. UK Ltd, Bedford. Murphy, R. J. (1993). Optimization of landfill mining, Technical Report, Center for Solid and Hazardous Waste Management and the Collier County Government of Naples, Florida. Pacey, J. (1989). Enhancement of degradation: large-scale experiments, In sanitary landfilling process, technology and environmental impact, Christensen, T.H., Cossu R. and Stegmann R. eds, Academic Press, London, UK, 103- 119. Pacey, J., Augenstein, D., Mork, R., Reinhart, D. & Yazdani, R. (1999). The bioreactor landfill: an innovation in solid waste management. SWANA, Silver Springs, Maryland. Pareek, S., Matsui, S., Kim, S. K. & Shimizu, Y. (1999). Mathematical modeling and simulation of methane gas production in simulated landfill column reactors under sulfidogenic and methanogenic environments. Water Science and Technology, 39(7), 235-242. Pescod, M. B. (Ed.) 1991–93. Urban Solid Waste Management. World Health Organization, Copenhagen. Pohland, F. G. (1992). Assessment of solid waste and remaining stabilization potential after exposure to leachate recirculation at a municipal landfill. Prepared for Post, Buckley, Schuh & Jernigan, Inc. Project No. 07-584.18. Cited in Al-Yousfi et al. (1998). Qin, W., Egolfopoulos, F. N. & Tsotsis, T. T. (2001). Fundamental and environmental aspects of landfill gas utilization for power generation. Chemical Engineering Journal, 82, 157–172. Rees, J. F. (1980). The fate of carbon-compounds in the landfill disposal of organic-matter. Journal of Chemical Technology and Biotechnology, 30(4), 161-175. Rees, J. F. & Grainger, J. M. (1982). Rubbish dump or fermenter? Prospects for the control of refuse fermentation to methane in landfills. Process Biochemistry, 17(6), 41-44, 1982 Reinhart, D. R. & AlYousfi, A. B. (1996). The impact of leachate recirculation on municipal solid waste landfill operating characteristics. Waste Management & Research, 14(4), 337-346. Reinhart, D. R. & Townsend, T. G. (1998). Landfill bioreactor design and operation, Lewis Publisher, New York Reinhart, D. R., McCreanor, P. T. & Townsend, T. (2002). The bioreactor landfill: Its status and future. Waste Management & Research, 20(2), 172-186. San, I. & Onay, T. T. (2001). Impact of various leachate recirculation regimes on municipal solid waste degradation. Journal of Hazardous Materials, 87(1-3), 259-271. Scheff, P., Casten, C., Ruesch, P. & Friedl, M. (2001). In, Environmental Health Risk, Fajzieva D. and Brebbie C.A. (Eds.), WIT Press, Southampton UK. Sponza, D. T. & Agdag, O. N. (2004). Impact of leachate recirculation and recirculation volume on stabilization of municipal solid wastes in simulated anaerobic bioreactors. Process Biochemistry, 39(12), 2157-2165. Sponza, D. T. & Agdag, O. N. (2005). Effects of shredding of wastes on the treatment of municipal solid wastes (MSWs) in simulated anaerobic recycled reactors. Enzyme and Microbial Technology, 36(1), 25-33. Stecker, P. (1989). Active landfill gas recovery systems. University of Wisconsin Sanitary Landfill Leachate and Gas Management Seminar, Madison, WI, December 4-7, 1989.

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NOTATIONS The following symbols are used in this chapter: (AEERL):

BECH 4,SWDS , y :

Air and Energy Engineering Research Laboratory Methane emissions avoided during the year y from preventing waste

DOC f :

disposal at the solid waste disposal site during the period from the start of the project activity to the end of the year y (tCO2e) Biochemical Oxygen Demand Clean Air Act Clean Development Mechanism Comprehensive Environmental Response, Compensation, and Liability Act Methane Carbon dioxide Chemical Oxygen Demand Clean Water Act Crow Wing County Landfill Degradable Organic Carbon Fraction of degradable organic carbon (DOC) that can decompose

(EPA): (EU): f:

Environmental Protection Agency European Union Fraction of methane captured and flared, combusted or used in

(BOD): (CAA): (CDM): (CERCLA): (CH4): (CO2): (COD): (CWA): (CWC): (DOC):

GWPCH 4 :

another manner Fraction of methane in the SWDS gas (volume fraction) First Order Decay GreenHouse Gases Global Warming Potential Global Warming Potential (GWP) of methane, valid for the relevant

(HDPE): (H2S):

commitment period High Density Polyethylene Hydrogen Sulfide

F: (FOD): (GHG): (GWP):

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(IPCC): k:

1Year Intergovernmental Panel on Climate Change Methane generation rate (per year)

kj:

Decay rate for the waste type j

j:

Waste type category (index)

L0 :

Potential methane generation capacity of the waste (m3/Mg)

(LFG): Mi :

Landfill Gas Mass of waste accepted in the year I (Mg)

MCF: (MSW): n: (NIMBY): (NMOC): (NMVOC): (NSPS): (OSHA): OX: (PAFC): (POTW): QCH 4 :

Methane correction factor for aerobic decomposition of waste Municipal Solid Waste (year of the calculation)- (initial year of waste acceptance) Not in My Back Yard Non-Methane Organic Compounds Non-Methane Volatile Organic Compounds. New Source Performance Standards Occupational Safety and Health Administration Oxidation factor (reflecting the amount of methane that is oxidized in the soil or other material covering the waste Phosphoric Acid Fuel Cell Publicly Owned Treatment Works Annual Methane generation in the year of the calculation (m3/year)

Qmethane :

Methane flow rate (m3/min)

(RCRA): (RDF): (SWANA): (SWDSs): tij :

Resource Conservation and Recovery Act Refuse Derived Fuel Solid Waste Association of North America Solid Waste Disposal Sites Age of the jth section of waste mass M i accepted in the ith year

(TOC): (TSS): (UNFCC): (VOC): w: W: (WAC): x:

y:

Total Organic Carbon Total Suspended Solids United Nations Framework Convention on Climate Change Volatile Organic Compounds Mass of refuse (Mg) Mass of the waste deposited in the landfill Waste Acceptance Criteria Year during the crediting period: x runs from the first year of the first crediting period (x = 1) to the year y for which avoided emissions are calculated (x = y) Year for which methane emissions are calculated

φ:

Model correction factor to account for model uncertainties

In: Energy Recovery Editors: Edgard DuBois and Arthur Mercier

ISBN: 978-1-60741-065-2 © 2009 Nova Science Publishers, Inc.

Chapter 2

LANDFILL GAS: GENERATION MODELS AND ENERGY RECOVERY Lidia Lombardi∗ Dipartimento di Energetica “Sergio Stecco” Università degli Studi di Firenze Via Santa Marta, 3, 50139 Firenze, Italy

ABSTRACT In this chapter different landfill gas production mathematical models have been analysed, implemented and compared among themselves and with data collected from existing landfills. These models will be presented in the chapter. One of these models has been selected for application to some study cases. The selected model is based on firstorder decay equation and considers as basic inputs the years of landfill operation, the amount of municipal solid waste landfilled per year, the municipal solid waste component characterisation and biodegradability. Three different behaviours, in reference to biodegradation rate, have been considered dividing the material categories into rapidly, moderately and slowly biodegradable. The model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system. In particular, reciprocating engines were considered for energy recovery purposes. The landfill gas energy recovery by means of reciprocating engines is a quite widespread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue. For this reason, the selection of an appropriate combination of engines has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions. Further, in order to investigate the management possibilities to enhance energy recovery, the behaviour of a landfill where leachate is recirculated was observed, recording a more concentrated landfill gas production in a shorter time than in ∗

Tel. +39 055 4796349; Fax +39 055 4796342; [email protected]

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Lidia Lombardi conventional landfills - and reproduced by means of adapting the landfill gas production model. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission.

1. INTRODUCTION Energy recovery from landfill gas (LFG) is strongly recommended as a means to reduce the environmental impact, in terms of Greenhouse Effect (GHE), arising from landfills containing biodegradable wastes (Lombardi et al., 2006). As a matter of fact, biodegradable organic matter contained in Municipal Solid Wastes (MSW) is degraded by anaerobic biological processes in landfills giving place to a LFG, which is approximately composed of 50% methane and 50% carbon dioxide. Hence the LFG has two main features: it is composed of two of the main Greenhouse gases and it has a not negligible heating value (approximately 16.000-17.000 kJ/Nm3). Simple flare combustion of LFG allows reducing landfill GHE contribution converting methane to carbon dioxide, since Global Warming Potential (GWP) of methane is twenty-one times larger (on mass basis) than GWP of carbon dioxide. When LFG is combusted with energy recovery, both thermal and electric energy can be delivered and landfill GHE is further reduced, considering the avoided emissions from conventional sources of energy, in place of which LFG is exploited. The proper design of LFG collection and energy recovery system needs to be based on an adequate LFG production estimation during the landfill operation and post-closure phases, this can be done through LFG production modelling.

2. LANDFILL GAS CHARACTERISTICS AND GENERATION MECHANISMS LFG is composed of a number of gases that are present in large amounts (the principal gases) and a number of gases that are present in very small amounts (the trace gases). The principal gases are produced from the decomposition of the organic fraction of municipal solid waste (OFMSW) and they include mainly carbon dioxide (CO2) and methane (CH4), but also ammonia (NH3), carbon monoxide (CO), hydrogen (H2) and oxygen (O2) can be present. Trace constituents mainly belong to the VOCs family. The typical percentage composition of LFG is reported in Table 1. The generation of LFG takes place in different steps. At the beginning, as OFMSW is placed in the landfill, it undergoes microbial decomposition in aerobic conditions, because certain amount of air is trapped within the waste (phase I). When oxygen is depleted, anaerobic conditions begin to develop and after a transition phase (phase II), during which the oxidation/reduction potential decreases, the acid phase (phase III) starts, consisting in

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hydrolysis of higher molecular mass compounds into compounds suitable for use by microorganisms as a source of energy and cell carbon, followed by the acidogenesis of the previous formed compounds to produce lower-molecular mass intermediate compounds, as typified mainly by acetic acid (CH3COOH). Carbon dioxide is the principal gas generated in this phase. Small amounts of hydrogen gas will also be produced. Table 1. Typical composition of LFG (Tchobanoglous et al., 1993) Component Methane Carbon dioxide Nitrogen Oxygen Carbon monoxide

Percent (dry volume basis) 45-60 40-60 2-5 0,1-1,0 0-0,2

Component Sulfides, disulfides, mercaptans, etc. Ammonia Hydrogen Trace constituents

Percent (dry volume basis) 0-1,0 0,1-1,0 0-0,2 0,01-0,6

The microorganisms involved in this conversion, described collectively as nonmethanogenic, consist of facultative and obligate anaerobic bacteria. In the following phase – the methane fermentation phase (phase IV) a second group of microorganisms, which convert the acetic acid and the hydrogen to methane and carbon dioxide, becomes more predominant. The microorganisms responsible for this phase are strict anaerobes and are called methanogenic. In this phase both methane and acid formation proceed simultaneously, although the rate of acid formation is considerably reduced. Finally the last phase – the maturation phase (phase V) occurs when almost all the readily available biodegradable organic material has been converted. The rate of LFG generation decreases significantly because most of the available nutrients have been previously removed and the remaining substrates are slowly biodegradable. The duration of the individual phases in the production of LFG will vary depending on the distribution of the organic components in the landfill, the availability of nutrients, the moisture content of waste, moisture routing through the landfill and the degree of initial compaction.

Figure 1. Generalised phases in the generation of LFG (Tchobanoglous et al., 1993).

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3. MATHEMATICAL MODELS FOR LANDFILL GAS PRODUCTION PREDICTION Mathematical models for LFG production prediction are tools used to estimate, along the time, gas or methane production from a given amount of waste starting from some input data supplied by the model user. In technical literature several models have been proposed (EMCON, 1980) (Boyle, 1976) (Ham, 1979) (Halvadakis, 1983) (Findikakis, 1988) (Christensen et al., 1996) (Swarbrick and Lethlean, 1995) (Young, 1995) (Bonori et al., 2001) in order to both estimate the potential amount of LFG that can be produced from a given amount of waste and forecasting the temporal evolution of LFG production. The models proposed in literature can be classified into: empirical models, stoichiometric models, biochemical models and ecological models. Empirical models are based on black box approach, correlating input, related to typology of landfilled waste, and output related to LFG production, in reference to collected data from existing landfills and experimental data. These kind of models are very site and data specific. Stoichiometric models are based on a global stoichiometric reaction, in which the reactant is waste, represented by an empirical chemical formula, and the products include methane and carbon dioxide. Stoichiometric models differ in the selected stoichiometric reaction, in waste components considered and whether they include or not cellular growth. Obtainable results are generally overestimated, since actual biodegradation efficiency is not taken into account. Biochemical models are based on biodegradable substrate removal equations, using more or less complex kinetics, considering more or less substrates and including or not the parameters influencing the degradation (temperature, moisture, compaction, etc). Ecological models describes the dynamic coexistence of the different bacterial populations which compete in the waste degradation. Actually these are the only models which are able to highlight nutrients imbalances and substrate characteristics, but their application is quite complex due to the non homogeneous characteristics of landfills and moreover it is too onerous in the frame of LFG collection and recovery. However, quite often the proposed models are a mixing of different elements, mainly using a stoichiometric sub-model which uses waste composition as input, supplying the amount of biodegradable compounds as output, and a biochemical-kinetic sub-model which supplies the evolution during the time of LFG from biodegradable compounds, on the basis of some parameters as temperature, moisture, etc. In this chapter the attention is focused on four previously proposed models which are: the Triangular model (Tchobanoglous et al., 1993; Bonori et al., 2001); the Scholl Canyon equation model (Department of the Army U.S., 1995); the LandGEM model (EPA, 2005) and a modified version of first order decay model (Van Zanten and Scheepers 1995).

The Triangular Model In the triangular model, a linear growth of the LFG production rate is assumed until it reaches a peak after which a linear decrement starts (Tchobanoglous et al., 1993), as shown in

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Figure 2. In the original version, LFG production is assumed to start at the end of the first year of full landfill operation and to finish after a finite time tend. The area under the triangle is equal to one half the base (which represents the time during which LFG production lasts) times the altitude (which represents the peak rate of LFG production), therefore, the total amount of LFG produced from an amount Ri of waste placed in landfill at year i is equal to:

Ri L0 =

1 (tend ,i − t0,i ) ⋅ QLFG ,max,i 2

(1)

LFG production rate [m3 /year]

where: L0 = waste potential gas production [m3/t] tend,i = time during which gas production takes place [year] t0,i = time at which LFG production starts for waste placed at year i [year] QLFG,i,max = maximum gas production rate [m3/(t · year)] Ri = amount of waste placed in landfill at year i [t]

Q LFG smax year

t end - t 0 Figure 2. Triangular distribution of LFG production rate.

The triangular model, in the original version (Tchobanoglous et al. 1993), considers two different behaviours in biodegradation rate, distinguishing waste components in rapidly biodegradable, which are degraded within five years or less, and slowly biodegradable, which require up to fifty years for degradation. For each of the two categories a triangular LFG production distribution is assumed, characterised by a different peak rate time. The total rate of LFG production from a landfill operated for a given time is obtained graphically – as shown in Figure 3 - by summing the LFG produced from the rapidly and slowly biodegradable portions of waste deposited each year. In the present chapter, as it will be described later, the Triangular model has been applied considering three different behaviours in biodegradation rate, distinguishing waste components in rapidly, moderately and slowly biodegradable.

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Figure 3.. Graphical representation of LFG production over a five-year period from the rapidly and slowly decomposable organic materials in landfill (Tchobanoglous et al., 1993).

Analytically, the LFG production rate in the Triangular model can be described as a function of time as it follows:

QLFG ,t ,i = 0, t i ≤ t 0,i growing phase : QLFG ,t ,i = QLFG ,max,i

t i − t 0 ,i t max,i − t 0,i

decreasing phase : QLFG ,t ,i = QLFG ,max,i

, t 0,i ≤ t i ≤ t max,i

t max,i − t i t end ,i − t max,i

, t max,i ≤ t i ≤ t end ,i

(2)

QLFG ,t ,i = 0, t i ≥ t end ,i where: QLFG,t,i = LFG production rate at year t for waste placed at year i [m3/(t · year)] tmax,i = time at which LFG production reaches the peak for waste placed at year i [year] In order to estimate the current emissions from waste placed in all years, Equation 1 and Equation 2 can be solved for all values of Ri and the results summed:

QLFG ,t =

t

∑Q

LFG ,t ,i i =initial year

(3)

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First Order Decay Model: The Scholl Canyon Equation The Scholl Canyon Model is a model which assumes that LFG generation is a function of first-order kinetics. This model ignores the first two stages of bacterial activity and is simply based on the observed characteristics of substrate-limited bacterial growth. The LFG production rate is assumed to be at its peak upon initial placement after a negligible lag time – in the original version - during which anaerobic conditions are established and decreases exponentially (first-order decay) as the organic content of the waste is consumed (Department of the Army U.S., 1995). Average annual placement rates are used, and the time measurements are in years. The model equation takes the form: (4)

QLFG = Ravg ⋅ L0 ⋅ (e − kc − e − kT ) where: QLFG= LFG generation rate at time T [m3/year] L0= waste potential LFG generation capacity [m3/t] Ravg = average annual acceptance rate of waste [t/year] k = LFG generation rate constant [1/year] c = time since landfill closure [year] (c = 0 for active landfills) T = time since initial waste placement [year]

To allow for variances in annual acceptance rates, the derivative of Equation 4 with respect to the time can be used to estimate LFG generation from waste landfilled in a single year (Ri) (IPCC, 1996). In this equation, the variable T is replaced with t-i, which represents the number of years the waste has been in the landfill. The resulting equation thus becomes: (5)

QLFG ,t ,i = L0 ⋅ k ⋅ Ri ⋅ e− k ( t − i ) QLFG,t,i = the amount of LFG generated in the current year (t) by the waste Ri [m3/year] Ri = amount of waste disposed in year i [t/year] i = the year of waste placement [year] t = current year [year]

In order to estimate the current emissions from waste placed in all years, Equation 5 can be solved for all values of Ri and the results summed:

QLFG ,t =

t

∑

i = initial year

QLFG ,t ,i =

t

∑R ⋅L

i i = initial year

0

⋅ k ⋅ e − k (t −i )

(6)

Lag time due to the establishment of anaerobic conditions could also be incorporated into the model by replacing “t” by “t + lag time”. The lag time before which anaerobic conditions are established may range from two-hundred days to several years (Department of the Army U.S., 1995):

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QLFG , t , i = Ri ⋅ L0 ⋅ k ⋅ e − k ( t − i − lag )

(7)

lag = time to reach anaerobic conditions [year]

Software Application of First Order Decay Model: Landgem U.S. EPA developed LandGEM (Landfill Gas Emissions Model), which is a software for quantifying LFG emissions, based on the application of Scholl Canyon model in the form of equation (6) (EPA, 2005). The required inputs for estimating the amount of generated LFG are: design capacity of the landfill; amount of waste in place or the annual acceptance rate; the LFG generation rate constant k and LFG generation potential L0; the number of years of waste acceptance. Default values for k and L0 can be used or site-specific values can be introduced. The software can be operated under the Windows environment. Graphs and reports of estimated gas emissions can be produced.

Modified First Order Model A modified version of the first order decay model assumes that LFG generation is initially low and then rises to a maximum before declining exponentially. The equation of this model is represented by Equation 8 (Van Zanten and Scheepers, 1995):

QLFG ,t ,i = Ri ⋅ Lo

k+s (1 − e −s ( t −i−lag ) )k ⋅ e −k ( t −i−lag ) s

(8)

where s = rise phase LFG generation rate constant [1/year]

4. THE ESTIMATION OF K AND L0 IN THE MODELS The tricky parameters for the first order models are the gas generation rate constant (k) and the waste potential LFG generation capacity (L0). The potential for LFG generation capacity, usually expressed as the volume of gas per mass of waste, can be estimated based on theoretical prediction, laboratory experiments or actual gas production data. At present, there is no method for determining gas potential that is without fault (Reinhart and Faour, 2005). Experimental procedure to evaluate the gas potential has been developed (biochemical methane potential - ASTM Method E1196-92), which determines the methane yield of an organic material during its anaerobic decomposition by a mixed microbial flora in a defined medium. Such a procedure has been modified for solid waste (Owens and Chynoweth, 1992), so biochemical methane potential values are available for various waste fractions. Hence on

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the basis of waste component characterization, L0 can be calculated as weighted average of biochemical methane potential values. Actual gas production data have been collected from lysimeters, pilot-scale cells, and full-scale landfills. However, the drawback of utilizing these data is that they reflect gas recovered, not gas generated. Gas recovery efficiency is believed to be far less than 100% and depends on many factors such as the presence and integrity of a cover and the type and quality of the gas collection system. The presence of cracks and fissures will reduce collection efficiency. In addition, these studies rarely last sufficiently long to actually reach the point of total gas production. Further, other data necessary, such as waste mass and actual dates of placement, for determining methane potential may not be available (Reinhart and Faour, 2005). Theoretical predictions are based on the chemical composition of the waste and would give absolute maximum gas potential. In reality, gas generation would never reach this potential due to the inaccessibility of some waste, the inability to biodegrade all organic wastes, and the likely production of other non-methane carbon compounds other than carbon dioxide. Consequently, theoretical gas potential must be adjusted by a biodegradability factor, also based on various assumptions (Reinhart and Faour, 2005). The first-order rate constant, k, controls the rate of decline of the first-order model and, consequently, the period of LFG generation predicted by the model. As the value of k increases, the duration of LFG production declines. It would be expected that as conditions within a landfill are optimized with respect to waste degradation (i.e., moisture content, temperature, biodegradability of the waste, etc.), k would increase, assuming that L0 remains the same (Reinhart and Faour, 2005). In the present chapter both L0 and k have been estimated on theoretical basis, in reference to a component characterization of the waste, specific for the analysed site and reported in Table 2, using a stoichiometric based approach. For each material component the chemical composition, the moisture and the biodegradability coefficients reported in Table 2 have been assumed (Tchobanoglous,1993). On the basis of component characterisation of waste, chemical composition of each component and biodegradability of each component it is possible to describe the biodegradable fraction, with reference to the unit mass of waste, by the generic formula CaHbOcNdSe. In calculating the biodegradable fraction, it was also considered that not all the biodegradable fraction is available for being converted to LFG according to an efficiency depending on the landfill body temperature as it follows (Tabasaran, 1982): Biodegradable fraction availability = 0,014 Temp + 0,28

(9)

where Temp is the landfill body temperature expressed in °C. Assuming a landfill body temperature of 35°C the biodegradable fraction availability results 0,77. The biodegradation process of the organic biodegradable fraction to form the LFG can be described by the global stoichiometric reaction (Tchobanoglous,1993):

C a H b Oc N d S e + w ⋅ H 2 O → x ⋅ CH 4 + y ⋅ CO2 + z ⋅ NH 3 + k ⋅ H 2 S (10)

Table 2. Waste component characterisation for the study case site and assumed values for chemical composition, moisture and biodegradability

Organic fraction Paper and cardboard Plastics Textile Pruning scrap Wood Glass and inert Metals Sewage sludge

Component characterization % 17,53% 32,20% 16,83% 6,20% 2,46% 6,31% 10,61% 3,86% 4,00%

C %SS 28,70% 44,40% 70,50% 39,60% 45,50% 49,50% 0,50% 0,50% 47,07%

H %SS 3,10% 4,40% 11,50% 6,50% 8,70% 6,00% 0,10% 0,60% 6,74%

O %SS 29,20% 40,90% 11,30% 25,30% 20,10% 42,70% 0,40% 4,30% 26,43%

N %SS 1,90% 0,10% 0,90% 5,60% 1,80% 0,20% 0,10% 0,10% 5,97%

S %SS 0,60% 0,30% 0,90% 0,70% 0,20% 0,10% 0,00% 0,00% 2,24%

Inert %SS 36,50% 9,90% 4,90% 22,30% 23,70% 1,50% 98,90% 94,50% 11,54%

Moisture % 70,00% 5,50% 2,00% 10,00% 60,00% 20,00% 2,00% 3,00% 70%

Biodegradability % 82% 50% 0% 54% 60% 72% 0% 0% 57,5%

Table 3. Values assumed for gas generation rate constant, rise phase gas generation rate constant (for modified first order model), potential gas generation capacity and lag time of materials with different biodegradation velocity k [1/year] k [1/year] Rapidly biodegradable fractions Moderately biodegradable fractions

Organic fraction Pruning scrap

Paper and cardboard Textile Slowly biodegradable fractions Wood Sewage sludge * input to LandGEM

0,36 0,15 0,07

L0 [Nm3/t]

13,44 Calculated as weighted 29,54 average* 0,139 29,69

L0 [Nm3/t] Calculated as weighted average* 24,59

Lag Time [year]

s [1/year]

0,3

1,155

2

0,346

5

0,231

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Applying the stoichiometric balance to the reaction above it is possible to obtain the stoichiometric coefficients w, x, y, z and k as a function of a, b, c, d, e: ⎛ 4a − b − 2c + 3d + 2e ⎞ C a H bOc N d S e + ⎜ ⎟ ⋅ H 2O → 4 ⎝ ⎠ ⎛ 4a + b − 2c − 3d − 2e ⎞ ⎛ 4a − b + 2c + 3d + 2e ⎞ →⎜ ⎟ ⋅ CH 4 + ⎜ ⎟ ⋅ CO2 + dNH 3 + eH 2 S 8 8 ⎝ ⎠ ⎝ ⎠

(11) Hence, total number of dry kilomoles of LFG will be: LFG kmol ,dry = x + y + z + k =

4a + b − 2c − 3d − 2e 4a − b + 2c + 3d + 2e + + d + e = a + d + e [kmol 8 8

(12) In order to consider the presence of water vapour in the LFG it has been assumed that the gas is saturated with water vapour. From the total number of kilomoles it is then possible to calculate the potential gas generation capacity (L0):

L0 [ Nm

3

3

] = LFGmol [kmol ] ⋅ 22,414[ Nm ] t t kmol

(13)

Actually, the different components of waste undergo biodegradation according to different degradation rates. The different behaviours have been considered distinguishing the materials in rapidly, moderately and slowly biodegradable, according to (EMCON, 1980). After a literature review (Nutting, 2001) (US-EPA, 1995) (IGES, 2000) (Metcalf and Eddy (1991) (Baldwin et al., 1998) (Hartz et al., 1982) (Warith and Sharma, 1998) (Lifshits and Galueva, 1997) (McBean et al., 2005) (Christensen et al., 1996), different values for LFG generation rate constant have been assumed for each class of materials with different biodegradation velocity, as reported in Table 3. Also the potential LFG generation capacities (L0) for each class of material with different biodegradation velocity were calculated separately (calculated values are reported in Table 3) in order to apply the models – when this is allowed by the model itself – in order to proceed with separate calculations and adding up the three contributions of LFG production. From Equation 11 it is, also, possible to calculate LFG composition, which, in this case, results: CH4 48,23%; CO2 47,95%; NH3 3,39%; H2S 0,42 %. The composition is assumed not to change during the time.

5. APPLICATION OF THE MODELS TO A STUDY CASE The above described models – with the exception of LandGEM – have been implemented using a calculation worksheet. In reference to Scholl Canyon model, LandGEM and modified first order model the input data consisted in: amount of waste landfilled yearly; potential LFG

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generation capacity; LFG generation rate constant. In the case of Scholl Canyon model and modified first order model, calculation have been performed separately for group of waste components with different biodegradation velocity, using values for potential LFG generation capacity and LFG generation rate constant reported in Table 3. Also, for these two models, a lag time was considered, as reported in Table 3. Concerning the modified first order model, assumed values for the rise phase gas generation rate constant (s) are reported in Table 3 (Youcai et al., 2002). The LandGEM model does not offer the possibility of considering different velocities of biodegradation for different materials, hence single average values were introduced for potential gas generation capacity and gas generation rate constant, as reported in Table 3. It is not possible to introduce lag time in the software. The amount of waste landfilled yearly is reported in Table 4. The analysed site is a landfill for non-hazardous waste with an overall capacity of about 3.700.000 m3 located in central Italy. Values until seventh year are real data collected on-site, while values between after eighth year are assumed according to the hypothesis of filling up the site authorised capacity within the ninth year (last year of operation). Table 4. Amount of waste landfilled yearly in the analysed site Year

Waste [t]

Year

Waste [t]

1 2 3 4 5 6

171.929 263.606 260.453 315.214 246.159 259.896

7 8 9 10 11

278.634 240.000 240.000 240.000 240.000

The triangular model requires as inputs: amount of waste landfilled yearly; maximum gas production rate (QLFG,max); time at which gas production starts (t0); time at which the peak rate of gas production occurs (tmax); time at which gas production finishes (tend). The maximum gas production rate (QLFG,max) was obtained from the total amount of produced LFG i.e. potential gas generation capacity (L0) used for the other models, from equation (1) according to:

QLFG ,max =

2 L0

t end − t 0

(14)

Also in this model calculations have been performed separately for group of waste components with different biodegradation velocity, adding up the results to obtain overall LFG production. Assumed values for start time, peak rate time, end time and maximum LFG production rate for each group of waste components with different biodegradation velocity, are summarised in Table 5. The results obtained applying the different models, according to the assumed inputs, are shown in Figures 4, 5, 6 and 7. Figure 8 shows the comparison of results obtained from the different applied models.

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Table 5. Assumed input parameters for Triangular model Rapidly biodegradable fractions 0 1,92 9,63 2,78

t0 [year] tmax [year] tend [year] QLFG,max [Nm3/t]

Moderately biodegradable fractions 0 4,62 23,10 2,55

Slowly biodegradable fractions 0 9,90 49,51 1,19

1,2E+07

1,0E+07

Nm3

8,0E+06

6,0E+06

4,0E+06

2,0E+06

0,0E+00 1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

Year

Rapidly biodegradable fractions Slowly biodegradable fractions

Moderately biodegradable fractions

Figure 4. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of Scholl Canyon model.

Results obtained from the different models have been compared with the data of collected LFG at the landfill site during three years of operation, which are reported in Table 6. For the analysed landfill site, the estimation escaped LFG from the landfill surface, is available from a measuring campaign previously carried out, by means of the accumulation chamber method (Cardellini et al., 2003) (Börjesson et al., 2000) (Raco et al., 2005) during the sixth year of operation. The specific carbon dioxide emission resulting from those previous measurements is 350 g/(m2 · day). Assuming a composition of LFG of 50% CH4 and 50% CO2 and an overall landfill surface of about 90.000 m2 (at sixth year), the amount escaped LFG is about 11.713.862 Nm3 in the sixth year. This allows the estimation of the LFG collection efficiency, as shown in Table 6. Table 6. Collected LFG data, estimated escaped LFG at the studied landfill site and estimated collection efficiency Year 5 6 7

Collected LFG [Nm3] 7.500.000 7.707.818 11.500.000

Escaped LFG [Nm3] 11.713.862 -

Estimated collection efficiency [%] 40 -

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1,0E+07

Nm3

8,0E+06

6,0E+06

4,0E+06

2,0E+06

0,0E+00 1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

Year

Slowly biodegradable fractions Rapidly biodegradable fractions

Moderately biodegradable fractions

Figure 5. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of modified first order model. 1,20E+07

1,00E+07

Nm3

8,00E+06

6,00E+06

4,00E+06

2,00E+06

0,00E+00 1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

Year

Figure 6. Results of overall LFG production, obtained by the application of LandGEM model.

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1,20E+07

1,00E+07

Nm3

8,00E+06

6,00E+06

4,00E+06

2,00E+06

0,00E+00 1

6

11

16

21

26

31

36

41

Year

46

Rapidly biodegradable fractions Slowly biodegradable fractions

51

56

61

66

71

76

81

Moderately biodegradable fractions

Figure 7. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of Triangular model. 2,50E+07

2,00E+07

Nm3

1,50E+07

1,00E+07

5,00E+06

0,00E+00 1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

Year

Scholl Canyon

Modified first order

Triangular

LandGEM

Figure 8. Comparison of results obtained from the different applied models.

Applying the estimated collection efficiency to the model results, it is possible to estimate the collected LFG from the model results and compare it with the collected LFG measured data available for the fifth, sixth and seventh year, as shown in Figure 9. From a first look at Figure 9, it is evident that the model which fits better the measured data, at least in the years for which data are available, is the Scholl Canyon one. For these reasons the selected model is the Scholl Canyon one.

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2,00E+07

Nm3

1,50E+07

1,00E+07

5,00E+06

0,00E+00 5

6

7

Year

Measured collected landfill gas Triangular - collected LandGEM - collected

Scholl Canyon - collected Modified first order - collected

Figure 9. Comparison of results obtained from the different applied models with the data of collected LFG.

6. ENERGY RECOVERY The selected Scholl Canyon model has been used to predict the LFG production for the case-study landfill in order to properly size the energy recovery system along the time. In particular, reciprocating engines were considered for energy recovery purpose. The LFG energy recovery by means of reciprocating engines is a quite wide spread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue. For this reason, the selection of the engine configuration along the time has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy. It has been assumed that no LFG collection takes place until the fifth year included, then the assumed collection efficiency coefficient is equal to 40% for the sixth and seventh years, and 60% for the following years (on the basis of the designed improved collection network in the specific plant). Several sizes of engine have been considered with reference to existing Jenbacher engines (kWe 143, kWe 330, kWe 511, kWe 625, kWe 836, kWe 1048, kWe 1413, kWe 1698). The amount of potential electric energy has been calculated according to:

EE = η el ⋅ LHV LFG ⋅ VLFG where: EE = electric energy [kW] ηel = engine electric energy conversion efficiency VLFG = LFG flow rate [Nm3/h] LHVLFG = LFG low heating value [kWh/Nm3]

(12)

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The values of engine maximum LFG flow rate and energy conversion efficiency were retrieved from Jenbacher engine technical forms. Energy conversion efficiency was considered dependant on the engine load (i.e. decreasing when load decreases) according to the indications on Jenbacher engine technical forms. On the basis of the LFG collected yearly, obtained from the Scholl Canyon model, it is possible to estimate the appropriate size and number of reciprocating engines required every year for the LFG exploitation, considering as constraints the maximum load (i.e. maximum LFG flow rate) for each engine and 90.000 hours as maximum amount of operating hours for each engine (about ten years). As a matter of fact, during the energy recovery time, different combinations of engine sizes and numbers can be adopted to exploit the LFG: the selection of the final combination, was carried out with the aim of maximising the profits coming from the balance of energy system investment and maintenance costs and electric energy selling earnings. Assuming the energy recovery to start at the sixth year of landfill operation and to finish in year thirty-eight, a combination of engines which maximises the profit was found, based on the use of one 143 kWe engine, three 625 kWe engines and two 1413 kWe engines, distributed as shown in Figure 10. 3,00E+07

625 kWe 625 kWe 625 kWe 1413 kWe 1413 kWe

2,50E+07

143 kWe 143 kWe

2,00E+07

1,50E+07

1,00E+07

5,00E+06

0,00E+00 1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

Year Recovered EE [kWh]

Produced LFG [Nm3]

Collected LFG [Nm3]

Figure 10. Results of produced LFG, collected LFG and recovered electric energy, with the indication of the time during which engines have been used.

The economic evaluation was carried out considering the depreciation annual cost for the engine investment (considering 6,5% interest rate and 10 years investment time), the maintenance costs (assumed 0,03 €/kWh for programmed maintenance plus 3% for non programmed maintenance), the earnings for electric energy (EE) selling assuming a selling price equal to 0,13 €/kWh (considering an engine availability of 88%). Table 7 reports the engine costs. Results in terms of produced EE, overall costs and earnings are reported in Table 8.

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The obtained configuration for energy recovery was evaluated also from an environmental point of view, estimating the overall GHE produced, considering the contribution due to the presence of both carbon dioxide and methane in the escaped LFG and considering the contribution due to carbon dioxide (originally present in LFG and obtained from methane combustion) in collected and combusted LFG. Moreover, it is possible to consider that the amount of electric energy produced by the engines fed with LFG, is no more produced by conventional energy system, this term can be considered as an avoided effect of GHE emissions and then subtracted from the overall balance. Being the specific emission of about 0,551 kg of equivalent CO2/kWh for electric energy production (with reference to the Italian situation (ENEL, 1999)) the overall avoided effect can be calculated. Table 9 summarises the above mentioned contributions. Table 7. Investment costs and depreciation cost for the selected engines

Engine size kWe 143 kWe 625 kWe 1413

Engine cost [€] 252.000 377.000 689.300

Additional cost [€] 282.500 282.500 282.500

Total investment cost [€] 534.500 659.500 971.800

Depreciation [€/year] 74.351 91.740 135.182

Table 8. Costs and earnings for the LFG energy recovery system

Produced EE [kWh] Total produced EE [kWh] EE selling earnings [€] Engine costs + maintenance costs [€] Net profit [€] Total net profit [€]

kWe143 6.513.868 188.678.178 846.803 751.249 95.553 17.997.791

kWe625 42.315.774

kWe1413 139.652.646

5.501.051 2.927.351 2.573.700

18.154.844 2.826.306 15.328.538

Table 9. Contributions to GHE during the landfill life time GHE from escaped LFG [tCO2eq] GHE from collected LFG [tCO2eq] Total produced GHE [tCO2eq] Avoided GHE form EE production [tCO2eq] Net produced GHE [tCO2eq]

1.221.175 234.839 1.456.014 - 103.962 1.352.052

The simple collection and combustion of LFG (for example by means of flaring) offers the possibility of reducing GHE with respect to uncontrolled emission of all LFG to atmosphere (in that case the GHE production would be 2.199.035 tCO2eq and the reduction by means of collection and combustion is about 34%). When EE is produced the contribution of avoided GHE allows a further decrease of about 7%. From an energetic point of view, it is possible to calculate an overall energy conversion efficiency, dividing the amount of generated electric energy (Table 8) by the energy content of the LFG (considering the

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calculated content of methane) generated in the landfill life time (both collected and non). The value of the overall energy conversion efficiency results about 15%. In order to highlight the contribution to natural resources conservation, and in particular to saved conventional fossil fuels, the EE production from this renewable source allows to save about 40.599 TEP (ton of equivalent petrol) (assuming an average energy conversion efficiency of 37% for conventional plants).

7. MANAGEMENT OPTION TO IMPROVE ENERGY RECOVERY The Scholl Canyon equation based model has been applied to a second study case in order to evaluate the possibility of improving energy recovery from LFG by means of leachate recirculation (Corti et al., 2005). The practice of leachate recirculation has been studied in several laboratory cells, pilot cells and real landfills highlighting its beneficial effects on the waste biodegradation process (Reinhart and Townsend, 1998). In the present chapter, the aim is to highlight the behaviour differences between a landfill where leachate recirculation takes place and a conventional landfill, by means of adapting the Scholl Canyon equation based model previously described. In order to define the different parameters to be used to describe a conventional landfill and a landfill where leachate is recirculated, the above described model has been applied to simulate the behaviour of an existing reference landfill, where MSW are deposited, in the two periods in which it was operated without leachate recirculation and with leachate recirculation. In order to do this, measured data from a landfill where leachate recirculation takes place were considered and the Scholl Canyon equation based model was built around data and inputs –referred to the analysed landfill - reported in Table 10 and Table 11. Table 10. Chemical composition of waste component fractions and their humidity, biodegradability and biodegradation rate category

Material Organic matter Paper and cardboard Plastics Textiles Pruning scrap Wood Glass and inert Metals

C

H

O

N

S

Inert

Humidity

Biode Grada bility

Biode Gradation rate

28,70%

3,10%

29,20%

1,90%

0,60%

36,50%

70,00%

82%

Rapid

44,40%

4,40%

40,90%

0,10%

0,30%

9,90%

5,50%

50%

Moderate

70,50% 39,60%

11,50% 6,50%

11,30% 25,30%

0,90% 5,60%

0,90% 0,70%

4,90% 22,30%

2,00% 10,00%

0% 54%

Slow

45,50%

8,70%

20,10%

1,80%

0,20%

23,70%

60,00%

60%

Rapid

49,50%

6,00%

42,70%

0,20%

0,10%

1,50%

20,00%

72%

Slow

0,50%

0,10%

0,40%

0,10%

0,00%

98,90%

2,00%

0%

-

0,50%

0,60%

4,30%

0,10%

0,00%

94,50%

3,00%

0%

-

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Lidia Lombardi Table 11. Waste component characterisation, input parameters for Scholl Canyon model and amount of MSW landfilled yearly in the analysed site Material Organic matter Paper and cardboard Plastics Textiles Pruning scrap Wood Glass and inert Metals

Mass composition [%] 15,97 20,47 19,54 23,05 4,37 4,38 9,53 2,69

Lag time [year] 0,3 1 5 0,3 5 -

K[1/year] 0,69 0,14 0,05 0,69 0,05 -

Year 1 2 3 4 5 6 7 8

MWS [t] 9.883 94.308 80.600 47.311 49.598 36.544 25.020 28.413

The application of the previously described Scholl Canyon equation based model, applying a LFG collection efficiency of 0,75, supplied the results shown in Figure 11, which are compared with the real data collected at the existing reference landfill. As a matter of fact the model fits the real data properly in the period before starting the leachate recirculation (the third year), but it fails after leachate recirculation starts. So, in order to fit the real data after the third year, it is necessary to introduce a proportional coefficient β between reaction rate for a conventional landfill and a landfill with leachate recirculation, defined as reported in Equation 13. It has been assumed that the LFG generation potential remains the same in the case of presence or absence of leachate recirculation.

k CV = k LR

β

where, kCV = LFG generation rate constant for the conventional landfill [1/year] kLR = LFG generation rate constant for the landfill with leachate recirculation [1/year]

Figure 11. Comparison of model results and collected data for the existing reference landfill.

(13)

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With a value of β in the range of 2-2,5, it is possible to obtain quite good accordance between real data, after the recirculation beginning, and model results, as shown in Figure 12.

Figure 12. Model results applying different β coefficients.

Further, the modified model has been applied to a hypothetical study case - characterised by the waste component characterisation and amount of MSW yearly landfilled reported in Table 12 - in order to understand the behaviour differences between a conventional landfill and a landfill with leachate recirculation. Table 12. Waste component characterisation and yearly landfilled amount for the hypothetical study case Material Organic matter Paper and cardboard Plastics Textiles Pruning scrap Wood Glass and inert Metals

Mass composition [%] 36,3 21,4 12,0 5,9 3,5 3,5 11,0 6,4

Year 1 2 3 4 5 6 7

MSW [t] 113.873 111.163 107.655 104.538 101.775 99.521 98.865

The model results, in terms of produced LFG, are plotted in Figure 13. It is quite important to note that in the case of landfill with leachate recirculation the 95% of LFG is produced ten years before than in the conventional landfill case. This feature allows the concentration of energy recovery during a smaller period of time.

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Lidia Lombardi 1,40E+07 Conventional landfill

1,20E+07

Landfill with leachate recirculation

Nm3

1,00E+07 8,00E+06 6,00E+06 4,00E+06 2,00E+06 0,00E+00 1

6

11

16

21

26

31

36

41

46

51

56

Year

Figure 13. Comparison of model results – LFG production - for landfill with leachate recirculation and conventional landfill.

The accelerated biological degradation also strongly contributes to the volume reduction of the landfilled waste. In order to evaluate the overall waste volume reduction it is necessary to account for both the increasing density of the waste, due to the weight of the upper layers, and the accelerated biodegradation. Assuming that waste density passes from 0,6 to 1 t/m3 in thirty years and then it keeps constant, both in a conventional landfill and landfill with leachate recirculation, and combining this effect with the material loss in LFG, it is possible to estimate the overall volume reduction in the two cases. It was calculated that at the end of the seventh year (last year of operation) in both plants the volume reduction allows further landfilling, but while in the conventional landfill the recovered volume can host about 55.000 t, in the landfill with leachate recirculation about 80.000 t of waste can still be placed. This possibility of higher recovered volumes and higher capacity has been accounted in the following considering as input to the landfill with leachate recirculation the higher amount of waste. In order to understand the benefits that can derive from leachate recirculation, the two hypothetical plants have been compared from an economic, environmental and energetic point of view. From an economic point of view, the considered investment costs included: bottom impermeabilisation cost, LFG and leachate collection system costs and capping (Table 13). In the case of landfill with leachate recirculation a horizontal piping system for both LFG collection and leachate recirculation has been assumed (with a LFG collection efficiency of about 70%), while for the conventional landfill a vertical LFG collection system (with a LFG collection efficiency of about 60%) and a separate conventional leachate draining system were considered. In order to properly calculate the annual instalment connected to the investments relative to bottom impermebilisation, collection system, capping and flaring it is necessary to consider

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the effective utilisation time of the equipment. Table 14 summarises the construction phases and the depreciation times assumed. The interest rate used is 6,5%. On the basis of the LFG collected yearly in the two considered cases, it is possible to estimate the appropriate size and number of reciprocating engines required every year to use the LFG energy content, assuming to apply LFG collection and energy recovery until about 95% of total LFG is produced. Considering a reciprocating engine average life of ten years, it is possible to calculate the overall number and combination of engines required. The engine selection has been based on existing models (Jenbacher), using relative large size engine in the high LFG production period and small size engines in the final LFG production. Table 15 summarises the engine number used for each of the considered case. Table 13. Investment and operation costs for the different considered plants Equipment

Landfill with leachate recirculation

Bottom impermeabilisation [€] Collection system (leachate and LFG) [€] Capping [€]

4.957.803 750.000 1.816.809

Conventional landfill with vertical collection system 4.957.803 460.000 1.816.809

Table 14. Assumed construction phases and the depreciation times Equipment Construction phases Depreciation time [years] Bottom impermeabilisation All placed at the beginning 8 Capping All placed at the closing time 1 Flare Life time of 1 flare 10 Landfill with leachate recirculation Collection system Collection/recirculation system is placed at three different moments At the beginning 8 After 2 year 6 After 5 years 3 At the beginning 8 After 2 year 6 After 5 years 3 Conventional landfill with vertical collection system Collection system Collection system is placed at Landfill operation time = 8 the beginning years

From the electric energy conversion efficiency of the considered engines (143 kW – 34,3%; 625 kW – 38,7; 836 kW – 38,8) it is possible to evaluate the electricity production and assuming an electric energy selling price of about 0,13 €/kWh, it is possible to estimate the gain from electricity sell. The estimation of electricity production also took into account the energy conversion efficiency lowering when energy input is less than nominal size.

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Table 15. Number, size and overall investment cost of the reciprocating engines and energy production for each considered case in the operating and post-closure phases

Considered configurations Investment cost [€] Produced electric energy [GWh]

Landfill with leachate recirculation 4 x 625 kW engines + 1 x 143 kW engines 2.246.740 131

Conventional landfill with vertical collection system 3 x 625 kW engines + 3 x 143 kW engines 2.469.720 105

Table 16 summarises operation costs, grouping together the costs that last for the same number of years. Operation cost have been assumed equal for the two different plants considered. Table 16. Summary of the operation costs Operation costs Personnel, covering soils Leachate disposal, electricity, water, etc Mechanical machines, fuels and lubricating oil, machine maintenance Leachate disposal, environmental and topographic analysis, general maintenance, assurance Vigilance

[year] 8 9

[€/year] 380.000 630.000

10

275.000

49

460.000

58

25.000

From an energy point of view, it is possible to calculate an overall energy conversion efficiency, dividing the amount of generated electric energy (Table 15) by the energy content of the LFG generated in the landfill life time (assuming an average low heating value of 16.000 kJ/Nm3). From an environmental point of view, it is possible to calculate the specific GHE production for the different considered cases. Contributions to GHE during operation and post-closure phases come from collected LFG combustion and from uncollected LFG directly emitted to the atmosphere; while after the end of the post-closure phase the residual LFG is all emitted to the atmosphere contributing as well to GHE. These contributions have been calculated for the two cases (landfill with leachate recirculation and conventional landfill). Further, considering that the amount of electric energy produced by the engines fed with LFG, is no more produced by conventional energy system, this term can be considered as an avoided effect of GHE emissions and then subtracted from the overall balance. Being the specific emission of about 0,551 kg of equivalent CO2/kWh for electric energy production (with reference to the Italian situation (ENEL, 1999) the overall avoided effect can be calculated. Table 17 shows the results in terms of specific disposal cost for disposing one ton of MSW, in the two cases of landfill with leachate recirculation and conventional landfill. From the economical point of view, it appears that applying the leachate recirculation, even if a slightly higher investment cost for the collection/recirculation system is required, a lower specific disposal cost can be reached in comparison to a conventional landfill. The lower cost is mainly due to the shorter time during which the LFG production exhausts with a

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more concentrated energy recovery using a lower number of engines (lower investment), but also to the possibility of higher landfill volume recovery due to the accelerated biodegradation process with a consequent higher amount of disposed waste that corresponds to a higher amount of LFG production. Table 17. Specific disposal cost for MSW, overall energy conversion efficiency and specific CO2 emission Landfill with leachate recirculation 817.390 32.980.512 40,35

Disposed MSW [t] Total cost [€] Specific disposal cost [€/tMSW] Overall energy efficiency and environmental impact Overall energy conversion efficiency [%] 25 GHE [kgCO2/tMSW] without avoided effects 528 GHE [kgCO2/tMSW] with avoided effects 439

Conventional landfill with vertical collection system 792.518 37.679.930 46,28 20 644 571

From the results concerned with overall energy conversion efficiency, a higher value was obtained for the landfill with leachate recirculation with respect to the conventional landfill. Concerning GHE production the landfill with leachate recirculation allows the reduction of specific CO2 equivalent emitted per each ton of landfilled waste, thanks to the less LFG emitted directly to the atmosphere after the post-closure phase (without any collection and combustion). When considering avoided effects, since in the landfill with leachate recirculation case a higher energy recovery is possible, a further decrease in CO2 equivalent specific emission is registered.

CONCLUSION Different landfill gas production mathematical models have been analysed, implemented and compared among themselves and with data collected from existing landfills, selecting one of them for application to some study cases. The use of landfill gas production models is definitely useful in order to properly design landfill gas collection and energy recovery systems since it supplies an estimation of landfill gas amount during the landfill operation and post-closure phases. The accuracy of the landfill gas production estimation depends in part on the complexity of the model and mainly on the accuracy and specificity of the input data. The selected model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system, with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions. Energy recovery offers the possibility of decreasing the contribution to Greenhouse Effect, with respect to

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simple landfill gas flaring, and the chance to save conventional fuels being a renewable source of energy. The same selected model was, then, applied to another case-study landfill in order to investigate a management option to enhance energy recovery, consisting in leachate recirculation. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission.

REFERENCES Baldwin T.D., Stinson J. and Ham R.K. (1998), “Decomposition of specific materials buried within sanitary landfills.” J. Env. Eng. 124(12): 1193-1202. Bonori B., Pasquali G., Bergonzoni M. (2001), “Landfill gas production valued with a mathematical method” in Sardinia 2001 Eighth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. Börjesson G., Danielsson A., Svensson B. H., (2000), "Methane Fluxes from a Swedish Landfill Determined by Geostatistical Treatment of Static Chamber Measurements", in Environmental Science Technology, vol. 34, pp. 4044-4050. Boyle W.C. (1976), “ Energy recovery from sanitary landfills: a review”. Microbial energy conversion, Schlegel H.G. and Barnes J. Eds. Cardellini C., Chiodini G., Frondini F., Granieri D., Lewicki J. and Peruzzi L. (2003), “Accumulation chamber measurements of methane fluxes: application to volcanicgeothermal areas and landfills”. Applied Geochemistry, Volume 18, Issue 1, January 2003, Pages 45-54. Corti A., Lombardi L., Puglierin L. (2005), “Landfill gas production and energy recovery in bioreactor landfill”, Proceedings of SARDINIA 2005, Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. Department of the Army U.S. Army Corps of Engineers Washington (1995). Engineering and Design - Landfill Off-Gas Collection and Treatment Systems, da Environmental Technical Letter, ETL 1110-1-160. EMCON Associates (1980). “Methane generation and recovery from landfills”. Ann Arbour Science Publisher Inc., Ann Arbour, USA. ENEL “Rapporto Ambientale 1999” (in Italian). EPA (2005), Landfill Gas Emissions Model (LandGEM) Version 3.02 User's Guide, EPA/600/R-05/047. Findikakis A.N. et al. (1988), “Modelling gas production in managed sanitary landfills”. Waste Management and Research, vol. 6, No. 2, pagg 115-124. Halvadakis C.P. (1983), “Methanogenesis in solid waste landfill bioreactors”. PhD Thesys. Stanford University

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Ham R.K. (1979), “Predicting gas generation from landfills”. Waste Age, 11, 50. Hartz K.E., Ham R.K. (1982), “Gas generation rates of landfill samples”. Conservation and Recycling, 5, 2/3, 133-147. Hartz K.E., Klink R.E., Ham R.K. (1982), “Temperature Effects: Methane generation from landfill samples.” J. Env. Eng. 108: 629-638. IGES (2000), “Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories, Institute for Global Environmental Strategies (IGES). IPCC (1996), “Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories”. Workbook (Volume 2). Lifshits A.and Galueva T. (1997), “Gas production modelling based on the field gas emissions measurements”, in Sardinia 1997, Sixth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. Lombardi L., Carnevale E., Corti A. (2006) Greenhouse effect reduction and energy recovery from waste landfill”, Energy, Vol. 31, Pag. 3208-3219, Elsevier Science Limited, Oxford (UK). McBean E., Ritchie S. and Gidda T. (2005), “Landfill gas collection for greenhouse gas credits: an Argentinian case study”, Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. Metcalf and Eddy (1991), “Wastewater engineering: Treatment, disposal, and reuse”. Third Ed. McGraw-Hill, Inc. New York. Nutting L. (2001), “Evaluating Landfill Gas Potential” Proceedings Training Workshop Sao Paulo, Brazil Owens. J.M.; and Chynoweth, D.P., 1992. “Biochemical Methane Potential of MSW Components,” International Symposium on Anaerobic Digestion of Solid Waste, Venice, Italy. April 15–17. Raco B., Scozzari A., Guidi M., Lelli M. and Lippo G., (2005). Comparison of two non invasive methodologies to monitor diffuse biogas emissions from MSW landfills soil: a case study. Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. Reinhart D., Faour A. (2005), First-Order Knetic Gas Generation Model Parameters for Wet Landfills, EPA-600/R-05/072. Reinhart, D.R., Townsend, T.G., (1998), “Landfill Biorector Design and Operation”, Lewis Publisher. Swarbrick, G.E. and Lethlean, J.J. (1995), “Physical and bio-chemical modelling of landfill degradation” in Sardinia 1995, Fifth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy. T.H. Christensen, R. Cossu, R. Stegmann (1996) “Landfilling of waste: Biogas”, Th. Christensen, E and FN SPON, 237-268. Tchobanoglous G., Theisen H., Vigil S., (1993), Integrated solid waste management – Engineering principles and management issues. McGraw-Hill, Inc. US-EPA (1995), “Compilation of Air Pollutant Emission Factors - AP-42”, Fifth Edition, Volume I: Stationary Point and Area Sources. US-EPA, EPA Method 2E, in Code of Federal Regulations, Title 40, Charter I, Part 60, Appendix A

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Van Zanten, B., Scheepers, M.J.J. (1995) “Modeling of Landfill Gas Potentials.” in Proceedings of SWANA 18th Annual Landfill Gas Symposium, New Orleans, LA. Warith M.A. and Sharma R. (1998), “Technical review of methods to enhance biological degradation in sanitary landfills.” Water Qual. Res. J. Canada. 33(3): 417-437. Young A. (1995), “Mathematical modelling of the methanogenic ecosystem”. Microbiology of Landfill sites, ed. E. Senior, Lewis Publishers, Ann Arbor, pp. 67-89. Zhao Youcai, Wang Luochun, Hua Renhua, Xu Dimin and Gu Guowei, (2002), A comparison of refuse attenuation in laboratory and field scale lysimeters, Waste Management, Volume 22, Issue 1, 2002, Pages 29-35.

In: Energy Recovery Editors: Edgard DuBois and Arthur Mercier

ISBN: 978-1-60741-065-2 © 2009 Nova Science Publishers, Inc.

Chapter 3

ENERGY AND MATERIAL RECOVERY FROM BIOMASS: THE BIOREFINERY APPROACH. CONCEPT OVERVIEW AND ENVIRONMENTAL EVALUATION Francesco Cherubini∗ and Gerfried Jungmeier Joanneum Research, Institute of Energy Research, Elisabethstraße 5, 8010 Graz, Austria

ABSTRACT A great fraction of worldwide energy carriers and material products come from fossil fuel refinery. Because of the on-going price increase of fossil resources, the uncertain availability, the environmental concerns and the fact that they are not a renewable resource, the feasibility of their exploitation is predicted to decrease in the near future. Therefore, alternative solutions able to reduce the consumption of fossil fuels should be promoted. Electricity and heat can be provided by a variety of renewable alternatives (wind, sun, water, biomass), while the fossil resource alternative for production of fuels and chemicals can be just biomass, the only C-rich material source available on the Earth, besides fossils. The replacement of oil with biomass as raw material for fuel and chemical production leads to the development of “biorefinery”, a relatively young concept in the scientific literature. In biorefinery, almost all the types of biomass feedstock can be converted to different classes of biofuels and chemicals through jointly applied conversion technologies. This chapter describes the emerging biorefinery concept and provides an overview of the most important biomass sources, conversion technologies and platforms (or intermediates). The advantages of biorefinery systems over conventional fossil systems are outlined by means of Life Cycle Assessment (LCA): in the second half of this chapter, a LCA of a biorefinery system based on a lignocellulosic feedstock (e.g. wood industrial residues) and producing bioethanol and methyltetrahydrofuran (MTHF) as transportation biofuels, furan resins, fumaric acid and oxygen as chemicals and hydrogen, biomethane, electricity and heat as further energy carriers, is reported. The biorefinery system is compared with a reference system based on fossil sources. Results focus on greenhouse gas (GHG) and energy balances and estimate the possible GHG and fossil energy savings. System performances are also ∗

Corresponding author; tel. +433168761327; fax: +433168761330; e-mail: [email protected]

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Francesco Cherubini and Gerfried Jungmeier investigated with calculations of product yields and mass, energy, exergy and C conversion efficiencies. Since the biorefinery system co-produces many high value products, an allocation issue must be addressed. Different allocation procedures (substitution method, and energy, exergy, economic allocation) are therefore used and final results compared. The evaluation of the environmental performances reveals that relevant environmental benefits can be gained with a shift from oil refinery to biorefinery: almost 89% of GHG emissions and 96% of fossil energy demand can be saved.

1. INTRODUCTION Our strong dependence on fossil fuels results on the intensive use and consumption of petroleum derivatives which, combined with diminishing petroleum resources, causes environmental and political concerns. As a consequence, new renewable sources of energy and chemicals are object of research and development activities. Electricity and heat can be provided by a variety of renewable alternatives (wind, sun, water, biomass and so on), while the fossil resource alternative for production of transportation fuels and chemicals is biomass, the only C-rich material source available on the Earth, besides fossils. The term “biorefinery” is raising importance in the scientific community and the concept embraces a wide range of technologies able to separate biomass resources (wood, grasses, corn…) into their building blocks (carbohydrates, proteins, fats…) which can be converted to value added products, biofuels and chemicals (see Figure 1). A biorefinery is a facility that integrates biomass conversion processes and equipment to produce transportation biofuels, power, and chemicals from biomass. The biorefinery concept is analogous to today's petroleum refinery, which produces multiple fuels and products from petroleum. The replacement of oil with biomass as raw material will require some changes from the today’s production of goods and service: biological and chemical sciences will play a leading role in the generation of future industries and new synergies of biological, physical, chemical and technical sciences must be elaborated (Kamm et al., 2006a). A first generation of transportation biofuels and chemicals is today produced from sugars, starches and vegetable oils, giving rise to several issues: these raw materials compete with food for their feedstock and fertile land, their potential availability is limited by soil fertility and per hectare yields and the effective savings of CO2 emissions and fossil energy consumption are limited by the high energy input required for crop cultivation and conversion (Lange, 2007). Biomaterials

Biomass

Pretreatment

Biomass components

Conversion technologies

Bioenergy

Biochemicals

Figure 1. Simplified scheme of biorefinery: conversion of biomass into bioproducts.

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These limitations can be partly overcome by the utilization of lignocellulosic materials, such as residues from agriculture, forestry, industry and dedicated crops (Cherubini et al., 2009). The importance of recovering transportation biofuels and chemicals from lignocellulosic biomass feedstocks is evident: they are the most abundant biomass source in the Earth, they can be recovered from residue streams in different sectors, they can be grown in combination with food (e.g. straw and corn stover) or in non-agricultural lands and they have high potential for converting their main components (cellulose, hemicellulose and lignin) into a wide spectrum of biofuels and chemical products (Kamm et al., 2006b; Katzen and Schell, 2006). Since this is a relatively new concept in the scientific literature, few published papers on environmental performances of biorefinery systems are currently available. This work addresses this aspect: after a definition of the biorefinery concept, a Life Cycle Assessment (LCA) of a biorefinery system based on wood residues is reported. The chapter starts with a formal definition of biorefinery and a list of criteria that a bioenergy/biomass system has to meet to be a real “biorefinery”. Afterwards, the most important biomass feedstocks, processes and platforms, related to the biorefinery concept, are depicted and a comparison between biomass and oil as raw materials is presented. In order to investigate all the environmental aspects of biorefinery systems, a case study is evaluated by means of Life Cycle Assessment (LCA). The biorefinery system produces bioethanol, furfural derivates, electricity, heat, biomethane, hydrogen and oxygen from wood industrial residues. The biorefinery is compared with a reference system producing the same products from fossil sources. Information concerning product yields and mass, energy, exergy and carbon conversion efficiencies are also reported. Several allocation methods are used to share the environmental burdens of the biorefinery among the co-products and the final results are compared.

2. APPROACHING BIOREFINERY: DEFINITION, CRITERIA AND CHARACTERISTICS 2.1. Background and Current Status Among the several definition of biorefinery, the most exhaustive was recently performed by the IEA Bioenergy Task 42 on biorefineries (IEA 2008) (Figure 2):

“Biorefining: the sustainable processing of biomass into a spectrum of marketable products and energy”. One of the main driving factors for the future development of biorefinery can be seen in the efficient production of transportation liquid biofuels. The transportation sector is growing steadily and in the same way grows the demand for renewable (bio-)fuels, which can only be provided from biomass. Numerous countries have targets for improving the shares of biofuels in the national transport sector.

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Figure 2. Biorefinery recovers energy and materials from biomass sources.

For instance, Europe aims at a share of 5.75% in 2010 and 10% in 2020 of biofuels, according to the draft directive for renewable energy, while IEA and IPCC expect a significant contribution of biofuels on transportation market in 2030 (10 – 20%) (EBS 2007). The main challenge for biorefinery development is therefore the efficient and cost effective production of transportation biofuels, whereas for the coproduced biomaterials and biochemicals additional economic and environmental benefits might be gained. The most common biofuels produced today in the world are bioethanol, biodiesel and biogas (or biomethane). Bioethanol production from sugar or corn starch was more than 17 Mtoe in 2005; United States (from corn starch) and Brazil (from sugar cane) are the largest producers (GBEP 2007). Biodiesel, made by combining vegetable oil (from rapeseed, soybean, sunflowers, canola and others) or animal fat with an alcohol and a catalyst through a reaction known as transesterification, is mainly produced in European countries and its total production in 2005 was about 2.5 Mtoe (GBEP 2007). The production of biogas is diffused in all the countries, and in the last few years it has been strong implemented in countries with high feed in tariffs for electricity generation from biogas (especially European countries). In some countries (such as Germany and Sweden), biogas is also used as transportation biofuel, after upgrading to biomethane. For instance, Sweden currently leads the world in automotive biogas production, with a total fleet of approximately 4500 vehicles with 45 % of its fuel supplied by biomethane (Jönsson and Persson, 2003). Already commercially available biobased products include adhesives, cleaning compounds, detergents, dielectric fluids, dyes, hydraulic fluids, inks, lubricants, packaging materials, paints and coatings, paper and box board, plastic fillers, polymers, solvents, and sorbents. However, most of these biofuels and biochemicals are produced in single production chains and not with a biorefinery approach, and have raw materials in competition with the food and feed industry. Their exploitation is thereby limited. An alternative can be represented by lignocellulosic materials. In fact, lignocellulosic feedstocks can be supplied either from dedicated crops or as residues from agricultural, forestry and wood industry. This feedstock is made of 3 main components (cellulose, hemicellulose and lignin) which can be refined into different final products using a set of jointly applied technological processes. There is not anymore a competition with the food and feed industry since lignocellulosic biomass can be grown on land which is not suitable for agricultural crops. Moreover, in comparison with conventional starch and oilseed crops that can contribute only with a small fraction (grains and seeds) of the above standing biomass to bioenergy and biochemical

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production, biorefineries based on lignocellulosic feedstocks can rely on bigger biomass per hectare yields, since the whole crop is available as feedstock. Therefore, lignocellulosic raw materials are the most suitable biomass source for providing a large and constant feedstock supply to biorefineries, on condition that sustainable practices and managements are followed. Over the next 10 to 15 years, it is expected that lower cost residue and waste sources of lignocellulosic biomass will provide the first influx of next-generation feedstocks, with cellulosic energy crops expected to begin supplying feedstocks for bioenergy production towards the end of this time frame, then expanding substantially in the years beyond (Worldwatch Institute, 2006).

2.2. Criteria for Biorefinery System In addition to the definition, biorefinery systems should also follow some requisites which act as guidelines for the future deployment of biorefinery concepts. The criteria which a biomass or bioenergy system has to follow to be named biorefinery are the following: 1. Biomass Refining: a biorefinery, similarly to the upgrading of crude oil that occurs in oil refinery, is based on feedstock upgrading processes, where raw materials are continuously upgraded and refined. This means that a biorefinery should separate all the biomass feedstock components in order to be individually exploited, leading through a chain of several processes to a high concentration of pure chemical molecules (e.g. ethanol) or a high concentration of molecules having similar functions (e.g. the mixture of C alkanes in FT-fuels). 2. Combustion of residues: a feedstock can not be directly combusted without any previous treatment, since the aim of a biorefinery is to increase the value of the different biomass components as material and energy source. Therefore, the most desirable option is to send combustion for heat and electricity production only the residues and leftovers of the several technological treatments and conversion processes. 3. Value chemicals/materials: a biorefinery should produce at least one value chemical/material product, besides the low-grade and high-volume animal feed and fertilizers, according to the specifications of the first criterion. 4. Fuel-Energy products: as a direct consequence of the second criteria, a biorefinery should produce at least one energy product besides heat and electricity. Therefore, the production of at least one biofuel (liquid, solid or gaseous) is required. 5. Fossil fuel replacement: the products of a biorefinery must be able to replace fossil fuel based products coming from oil refinery, both chemicals and energy carriers. Concerning the chemicals, this objective can be met by producing the same chemical molecule from biomass instead of from fossils (e.g. phenols), or producing a molecule having a different structure but an equivalent function (e.g. succinic acid from biomass vs. maleic anhydride from fossils) or new biobased products able to replace petroleum based products (e.g. synthetic biodegradable plastics from starch). Concerning the fuels, a biorefinery must replace conventional fossil fuels (mainly gasoline, diesel, heavy oil, coal and natural gas) with the production of biofuels coming from biomass upgrading, both liquid (e.g. bioethanol, biodiesel, FT-fuels), gaseous (e.g. synthetic natural gas, hydrogen) and solid (e.g. lignin, charcoal, residues).

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6. Energy self-sufficiency: a biorefinery plant should have the aim to run in a sustainable way: all the energy requirements of the several biomass conversion processes should be internally supplied by the production of heat and electricity from combustion of residues. For instance, in a lignocellulosic ethanol plant, lignin, after separation from cellulose and hemicellulose, can be burnt to provide the heat and electricity required by the plant. However, direct external fossil energy inputs are allowed if they ensure economic benefits to the system and do not unduly burden the overall GHG and energy balances. 7. Waste minimization: solid, liquid and gaseous wastes released by a biorefinery should be minimized. This target can be achieved in two ways: using the different biomass components for producing a wide spectrum of multiple products, or setting up “bioclusters”, where material flow exchanges among different plants are promoted in order to transform a downstream residue of a plant into an upstream raw material for another plant.

2.3. Fossils vs. Biomass as Raw Materials The structure of biorefinery raw materials is totally different from that on which the current oil refinery is based. Crude oil is a mixture of many different organic hydrocarbon compounds (based on C and H) while biomass is made of different compounds (with a large abundance of O and ashes). The first step of oil refinery is to remove water and impurities, then distill the crude oil into its various fractions as gasoline, diesel fuel, kerosene, lubricating oils and asphalts. Then, these fractions can be chemically changed further into various industrial chemicals and final products. Unlike petroleum, biomass composition is not homogeneous, because the biomass feedstocks might be made of grains, wood, grasses, biological wastes and so on, and the elemental composition is a mixture of C, H and O (plus other minor components such as N, S and other mineral compounds). This biomass compositional variety is both an advantage and a disadvantage. An advantage is that biorefineries can make more classes of products that can petroleum refineries and can rely on a wider range of raw materials. A disadvantage is that a relatively larger range of processing technologies is needed, and most of these technologies are still at a pre-commercial stage (Dale and Kim, 2006). In order to be used for production of biofuels and chemicals, biomass needs to be depolymerized and deoxygenated. Deoxygenation is required because the presence of O in biofuels reduces the heat content of molecules and usually gives them high polarity, which hinders blending with existing fossil fuels (Lange, 2007). Chemical applications may require much less deoxygenation, since the presence of O often provides valuable physical and chemical properties to the product. The main benefits which can be related to an extensive deployment of biorefinery in replace of oil refinery are based on the supply of renewable biomass. In fact, if this is managed with sustainable practices, biomass has a closed carbon cycle: its use release to the atmosphere almost the same amount of CO2 that was captured during the photosynthetic process. Furthermore, unlike fossil resources, biomass resources are locally available for many countries and their provision, together with an implementation and development of biorefinery industries, will create a large number of jobs, especially in rural areas. Therefore, biorefinery technologies should be compact and suitable for local installations.

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Another important point concerning biorefinery processing is the fact that environmental impacts and consumption of non renewable resources should be minimized, while complete and efficient biomass use maximized. This ecological perspective requires: analyses of three important agricultural and forestry cycles as carbon (respiration, photosynthesis, and organic matter decomposition), water (precipitation, evaporation, infiltration, and runoff) and nitrogen (N fixation, mineralization, denitrification) and their interdependencies (Gravitis and Suzuki, 1999); system performance evaluations and environmental impact estimations carried out by means of Life Cycle Assessment (Cherubini et al., 2007). Especially soil degradation minimization and biodiversity conservation seems to be two dominating factors to consider in the assessment of biorefinery systems. With all this, biorefinery represents a change from the traditional refinery based on large exploitation of natural resources and large waste production towards integrated systems in which all resources are used. An example of how the biorefinery of the future will evolve can be found in the history of the existing corn wet-milling industry (Lasure and Min, 2004). Initially the corn wet milling industry produced starch as the major product. As technology developed and the need for higher value products drove the growth of the industry, the product portfolio expanded from various starch derivatives such as glucose and maltose syrups to high fructose corn syrup. Later, fermentation products derived from the starch and glucose such as citric acid, gluconic acid, lactic acid, lysine, threonine and ethanol were added. Many other by-products, such as corn gluten, corn oil, corn fiber and animal feed are now being produced. The final vision is then the development of the technical, commercial and political infrastructure for a biomass refinery (biorefinery), which will be similar to the current oil refinery concept.

3. OVERVIEW OF BIOREFINERY FEEDSTOCKS, PROCESSES AND PLATFORMS 3.1. Biorefinery Feedstocks The term of feedstock refers to raw materials used in biorefinery, from which biofuels and biochemicals are produced and recovered by means of a set of jointly applied technological processes. The biomass of the world is synthesized via the photosynthetic process that converts atmospheric carbon dioxide to sugar. Plants use the sugar to synthesize the complex materials that are biomass. Renewable carbon-based raw materials are produced in agriculture, silviculture and microbial systems. Although a tremendous variety of biomass resources is available, only four basic chemical structures are of significance for production of biofuels and biochemicals: carbohydrates (sugar, starch, cellulose, hemicellulose), lignin (polyphenols), triglycerides (lipids, vegetable oils and animal fats) and proteins (vegetable and animal polymers made up of amino-acids). The average composition of synthesized biomass in the world is 75% carbohydrates, 20% lignin and 5% other compounds (oils, proteins and so on) (Lichtenthaler, 2006). As a consequence, the main attention of research and development activities should first be focused on efficient access to carbohydrates, and their subsequent conversion to chemical intermediates and corresponding final products.

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All the existing types of biomass feedstocks can be divided in five groups: sugar crops, starch crops, oil based materials, grasses, lignocellulosic materials and organic residues and others. In the next sections, each of this group is depicted.

3.1.1. Sugar crops Concerning sugar crops, they provide sugars in a simple form, i.e. mono- or disaccharides, which can be readily used in conversion processes. Six-carbon, singlemolecule “monosaccharide” sugars (C6H12O6) include glucose, galactose and mannose, while the most common 5-carbon sugars (C5H10O5) are xylose and arabinose. The two most important sugar crops are sugar cane and sugar beet which, together with corn (a starch crop), supply almost all the bioethanol that is produced today (Rajagopal and Zilberman, 2007). The drawback of this type of feedstock is that requires dedicated hectares for the production and can compete with the food industry. Chemical structures of glucose and xylose are reported in Figure 3.

Figure 3. Chemical structures of glucose and xylose.

3.1.2. Starch crops Starch crops provide grains containing starch. Starch (C6H10O5)n is a very large polymer molecule composed of many hundreds or thousands of glucose molecules (polysaccharides), which must be broken down into one or two molecule pieces prior to be fermented to bioethanol or biochemicals. The most widespread starch crops are wheat and corn (Tuck et al., 2006; Wright, 2006). The major drawback of the use of these crops in biorefinery is that they are also used in the food and feed industry and their provision as biorefinery feedstock can have adverse impacts on food supply, soil carbon content (if straws and corn stovers are removed) and land pressure. The chemical structure of starch is illustrated in Figure 4.

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Figure 4. Chemical structure of starch (segment).

3.1.3. Oil based materials Oil based materials are made of triglycerides which typically consist of glycerin and saturated and unsaturated fatty acids (the chain length ranges between C8 and C20). The sources of oils and fats are a variety of vegetable and animal raw materials. Soybean, palm, rapeseed and sunflower oil are the most important in the terms of world wide production (Demibras, 2003; Hill, 2006; Sheehan et al., 2000). Vegetable oils are nowadays used for production of biodiesel by reacting with an alcohol, usually methanol. However, they can also be used as a substrate for chemical reactions thanks to two chemically reactive sites: the double bond in the unsaturated fatty acid chain and the acid group of the fatty acid chain (Biermann et al., 2001). Like sugar and starch crops, oilseed crops are characterized by low yield, high use of agrochemical inputs and competition with food market. In the future, nonedible crops like Jatropha curcas and Pongamia pinnata, which require lower inputs and are suited to marginal lands, may become the most widespread oil crops, especially in dry and semiarid regions (Achten et al., 2007; Rajagopal and Zimermann, 2007). Other sources of oil provision are the food industry, where waste edible oil is mainly generated from commercial services and food processing plants such as restaurants, fast food chains and households (Tsai et al., 2007), and the micro-algae, microscopic single cell aquatic plants with the potential to produce large quantities of lipids. The latter seems to have promising advantages over conventional oil crops because of the possibility to be grown in arid and semi-arid regions with poor soil quality, with a per hectare yield estimated to be many times greater than that of even tropical oilseeds. Moreover, algae can also grow in saline or polluted water, which has few competing uses in agriculture, forestry and industry (Chisti, 2007; Sheehan et al., 1998). A chemical structure of a saturated triglyceride is illustrated in Figure 5.

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Figure 5. Chemical structure of triglycerides.

3.1.4. Grasses Grasses are the raw materials for the so-called green biorefinery. This group includes the large family of green plant materials (green grass from meadows, willow and other natural resources), alfalfa, clover grass, grass silage, immature cereals and plant shoots (Kromus et al., 2006). The main components of green plant materials are carbohydrates, proteins, fibers, fats, amino acids and others. This composition allows to the green biorefinery to produce biogas, lactic acid, amino acids and fibers. An important green raw material source is the green harvesting residue material from agricultural cultivated crops, mainly the green foliage from sugar beet leaves, hemp scrape and leaves. 3.1.5. Lignocellulosic materials Lignocellulosic materials include dedicated energy crops (such as switchgrass and miscanthus), agricultural residues, forestry wastes, agroindustrial wastes, and other industrial wastes. The importance of lignocellulosic biomass as feedstock for biorefinery is evident: their use allows either the production of valuable biofuels and chemicals able to replace fossil derived products, and the utilization of a wide range of residues of domestic, agricultural and industrial activities. Among the potential large scale industrial biorefineries, the biorefinery systems based on lignocellulosic feedstocks will most probably achieve the greatest success in terms of market penetrations and product volumes. On the one side the raw material situation is optimum (widespread and easily available), on the other side conversion product have a good position on both the traditional petrochemical and future biobased product market. All kinds of lignocellulosic biomass are made of three main components: cellulose, hemicellulose and lignin. Cellulose (see Figure 6) has a strong molecular structure made by long chains of glucose molecules (C6 sugars) and is one of the most important raw materials for a variety of industries. Currently, major uses of cellulose are in pulp and paper industry, in medicine and in pharmacy (Kamm et al., 2006b).

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Figure 6. Cellulose structure.

In the biorefinery concept, the first treatment which cellulose undergoes is usually acid or enzymatic hydrolysis to glucose, if the feedstock is not pyrolysed or gasified. This sugar monomer is a key chemical that can mainly follow two routes: fermentation or chemical synthesis (Schiweck et al., 1991). The second main component of lignocellulosic biomass is hemicellulose (see Figure 7), which is relatively easier to breakdown to sugar monomers with chemicals and/or heat than cellulose. It contains a mix of C6 sugars (galactose and mannose) and C5 sugars (xylose and arabinose), which represent a great potential for the production of biofuels or chemicals. Xylose, the most representative sugar in hemicellulose, can mainly undergo three different pathways: hydrogenation to xylitol, acid treatment to furfural and fermentation to bioethanol together with C6 sugars (Kamm et al., 2006b).

Figure 7. Hemicellulose structure.

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Figure 8. Fragment of lignin structure.

The third component of lignocellulosic feedstock is lignin, made of phenolic polymers (see Figure 8). Even if lignin cannot be hydrolyzed to sugars and then fermented, it is useful for other purposes. For instance, it can be used in its polymeric forms as adhesives for wood materials, cement additive and so on, or can be fractionated into low molecular mass compounds (e.g. phenols), completely degraded to gas or liquid bio-oil through gasification or pyrolysis, or burnt as a solid fuel to generate heat and electricity. Table 1 reports the composition of some lignocellulosic biomass which can constitute the raw materials for biorefinery systems. The abundance of the three main components can vary significantly among the feedstocks. For instance, lignin ranges from 17% in wheat straw up to 28% in softwood.

3.1.6. Organic residues and others This group refers to the other biomass raw material sources that do not fall into the other categories, i.e. the organic fraction of Municipal Solid Waste (MSW), manure, wild fruits and crops and residues from the food production chain (such as fresh fruit and vegetable). The physical and chemical characteristics of this wide spectrum of biomass resources vary largely. Certain streams such as sewage sludge, manure from dairy and swine farms and residues from food processing are very wet, with moisture contents over 70%. Therefore, these feedstocks are more suited for an anaerobic digestion process to generate biogas, rather than other biofuels or chemicals (Berglund and Börjesson, 2006). Other streams, such as organic MSW, may be more or less contaminated with heavy metals or other elements (Faaij et al., 1997). Clearly, the different properties and characteristic of the biomass wastes require the application of different conversion technologies.

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Table 1. Composition of some lignocellulosic feedstocks. Parameter Water LHV Cellulose Glucan (C6) Hemicellulose Xylan (C5) Arabinan (C5) Galactan (C6) Mannan (C6) Lignin Acids Extractives Ash C H O N S

Unit (dry) % MJ/kg % % % % % % % % % % % % % % % %

Softwood

Switchgrass

Corn stover

Wheat straw

15 19.6 44.55 44.55 21.9 6.3 1.6 2.56 11.43 27.67 2.67 2.88 0.32 50.26 5.98 42.14 0.03 0.01

15 18.6 35.39 35.39 26.52 22.44 2.73 0.96 0.39 18.17 2.15 11.46 4.28 46.9 5.54 41.96 0.62 0.7

15 18.51 38.12 38.12 25.29 20.25 2.03 0.74 0.41 20.24 4.84 4.78 8.59 46.75 5.49 38.4 0.67 0.1

15 17.56 32.64 32.64 22.63 19.22 2.35 0.75 0.31 16.85 2.24 12.95 10.22 43.88 5.26 38.75 0.63 0.16

Sources: softwood Hammelinck et al., 2005; swithgrass EERE 2008 (biomass sample type: Switchgrass Alamo Whole Plant #94); corn stover EERE 2008 (biomass sample type: Corn Stover Zea Mays Stalks and Leaves w/o cobs #55); wheat straw EERE 2008 (biomass sample type: Wheat Straw (Triticum Aestivum) Thunderbird Whole Plant #154).

3.2. Technological Processes Biomass must be chemically converted for production of biofuels and biochemicals. Obviously, changes are necessary to convert biomass from a solid to a liquid state. As discussed in the previous section, fundamental is the biomass feedstock composition: it generally has too little hydrogen (which must be added), too much oxygen (which must be rejected), and other undesirable elements (such as nitrogen and sulphur) which also must be rejected (Cherubini and Jungmeier, 2008). The aim of each technological process which acts on raw biomass can be summarized in depolymerising and deoxygenating the biomass components. Especially for producing fuels, deoxygenation is particularly important as the presence of oxygen reduces the heat content of the molecules, while some chemical products may require much less deoxygenation, because the presence of oxygen often provides valuable physical and chemical properties to the compound (Lange, 2007). In order to convert biomass feedstock into valuable products within a biorefinery approach, several technological processes must be jointly applied in multiple steps. These

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technologies can be grouped in 4 main categories: thermochemical, biochemical, mechanical / physical and chemical processes.

3.2.1. Thermochemical processes There are two main thermochemical processes for converting biomass into energy and chemical products. The first is gasification, which consists in keeping biomass at high temperature (> 700°C) with low oxygen levels to produce syngas, a mixture of H2, CO, CO2 and CH4 (Paisley et al., 1998; Spath and Dayton, 2003). Syngas can be used directly as a fuel or can be a chemical intermediate (platform) for production of fuels (FT-fuels, Dimethyl ether, ethanol, isobutene…) or chemicals (alcohols, organic acids, ammonia, methanol and so on). The second most common thermochemical pathway is pyrolysis, which uses high temperatures (300 – 600°C) in absence of oxygen to convert the feedstock into a liquid pyrolytic oil (or bio-oil), solid charcoal and light gases similar to syngas (Bridgwater and Peacocke, 2000; Guo et al., 2001). Their yields vary with process conditions and for biorefinery purposes the treatment which maximizes the production of liquid bio-oil is the most desirable (flash pyrolysis). The application of bio-oil as a transportation fuel is problematic (see following section) and its use as a chemical source of phenols or levoglucosan is still under development (Helle et al., 2007; Meister, 2002; Zhuang et al., 2001). Together with charcoal, it is generally best suited as a fuel for stationary electric power or thermal energy plants. In addition to gasification and pyrolysis, direct combustion is also included among the thermochemical processes (Gani and Naruse, 2007; Senneca, 2007). This is the most common and oldest form of biomass conversion that involves burning biomass in an oxygen-rich environment mainly for the production of heat. Another less widespread thermochemical process is the biomass hydrothermal upgrading (HTU), which can be conducted at different conditions of temperature and pressure and with or without a catalytic mean (Karagöz et al., 2005; Zhang et al., 2002). The purpose of the HTU process is to convert biomass into the so-called “biocrude”, a liquid fuel with an energy density approaching that of fossil fuels which requires additional treatment before to be used as a transportation biofuel. This technology is still at a research and development stage. 3.2.2. Biochemical processes Unlike thermochemical processes, biochemical processes occur at lower temperatures and have lower reaction rates. The most common types of biochemical processes are fermentation and anaerobic digestion. The fermentation uses microorganisms and/or enzymes to convert a fermentable substrate into ethanol, the most common fermentation product, but the production of many other chemical compounds (e.g. hydrogen, methanol, succinic acid, among others) is nowadays object of many activities of research and development. Hexoses, mainly glucose, are the most frequent fermentation substrates, while pentoses (sugars from hemicellulose), glycerol and other hydrocarbons have required the development of customized fermentation organisms to enable their conversion to ethanol (Hamelinck et al., 2005; Lynd, 1996). Anaerobic digestion involves bacterial breakdown of biodegradable organic material in the absence of oxygen over a temperature range of about 30 – 65 °C. The main end product of this process is biogas (a gas mixture made of methane, CO2 and other impurities), which can be upgraded up to > 97% methane and used as a surrogate of natural gas (Berglund and Börjesson, 2006; Romano and Zhang, 2008).

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3.2.3. Mechanical/physical processes Mechanical/physical processes are processes which do not change the state or the composition of biomass, but only perform a size reduction or a separation of feedstock components. In a biorefinery pathway, they are usually applied first, because the following biomass utilization requires reduction of the material size within specific ranges, depending on feedstock specie, handling and further conversion processes. Biomass size reduction is a mechanical treatment process that significantly refers to either cutting or commuting processes that significantly change the particles size, shape and bulk density of biomass. Separation processes involve the separation of the substrate into its components, while with extraction methods valuable compounds are extracted and concentrated from a bulk and inhomogeneous substrates (Huang et al., 2008). Lignocellulosic pre-treatment methods, (e.g. the split of lignocellusic biomass into cellulose, hemicellulose and lignin) fall within this category, even if some hemicelluse is also hydrolized to single sugars (Cadoche and Lopez, 1989; Lasser et al., 2002, Sung and Cheng, 2002). 3.2.4. Chemical processes Chemical processes are those processes which carry a change in the chemical structure of the molecule by reacting with other substances. The most common chemical processes in biomass conversion are hydrolysis and transesterification, but this group also includes the wide class of chemical reactions where a change in the molecular formula occurs. Hydrolysis uses acids, alkalis or enzymes to depolymerise polysaccharides and proteins into their component sugars (e.g. glucose from cellulose) or derivate chemicals (e.g. levulinic acid from glucose) (Lynd, 1996; Sung and Cheng, 2002). Transesterification is the most common method to produce biodiesel today and is a chemical process by which vegetable oils can be converted to methyl or ethyl esters of fatty acids, also called biodiesel. This process implicates the coproduction of glycerine, a chemical compound with diverse commercial uses (Crabbe et al., 2001; Demirabas, 2003; Marchetti et al., 2007). Other important chemical reactions in biorefining are Fisher-Tropsch synthesis, methanisation, steam reforming, catalytic synthesis or reactions, hydrogenation, oxygenation and so on.

3.3. Platforms In biorefinery, the platforms are the intermediates which constitute the link between feedstock and final products. This concept is similar to the petrochemical industry, where the refinery starts with a massive distillation to separate the crude oil into a large number of intermediates that are further manipulated into the desired products. Among the several possible alternatives, the chemicals (or mix of chemicals) which are individuated as the most important biorefinery platforms are the following: biogas, syngas, hydrogen, C6 sugars, C5 sugars, levulinic acid, furfural, pyrolytic oil, oil and organic juice.

3.3.1. Biogas Biogas is a biomass derived gas made of mainly CH4 and CO2. It can be produced either by anaerobic digestion of biological materials or by methanisation of the syngas coming out from gasification. Biogas can be used as such for electricity and heat generation or can be

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upgraded to biomethane by removing CO2 and other undesired elements, like H2S (Mozaffarian et al., 2004a; Mozaffarian et al., 2004b). Biomethane can be used as a transportation biofuel, as a stationary biofuel for electricity and heat generation or can be transported through the existing gas infrastructure and substituting natural gas in all its existing applications.

3.3.2. Syngas Syngas is the product of the gasification process. It is mainly made of CO, H2, CH4 and CO2, but it may also contain different contaminants such as nitrogen, particulates, condensable tars, alkali compounds, H2S, HCl, NH3, HCN and COS. Since these contaminants can lower activity in the FT or other chemical synthesis due to catalyst poisoning, the syngas undergo a cleaning process in which the contaminats are removed and its main components can be tailored to the needs of the following conversion processes, by means of methane reforming (which converts CH4 with steam to CO and H2), water gas shift reaction (adjusts the H2/CO ratio by converting CO with steam to H2 and CO2) and CO2 removal (with an amine). The main products that can be obtained from syngas are: ethanol, methanol, hydrogen, ammonia, FT-fuels, acetic acid, formaldehyde and others (Dybkjaer and Christensen, 2001; Hamelinck et al., 2004; Spath and Dayton, 2003). 3.3.3. Hydrogen Hydrogen can be produced by syngas after a water shift reaction process (CO + H2O → H2 + CO2), by methane after a steam reforming process (CH4 + H2O → 3 H2 + CO), by alkaline water electrolysis (H2O → H2 + ½ O2) or by fermentation of suitable substrates and microorganisms (Spath and Mann, 2001; Spath and Mann, 2004; Stojic et al., 2003). Hydrogen can be used either as a fuel or as a chemical reducing agent. 3.3.4. C6 sugars C6 sugars are the most abundant renewable resource available. Glucose is the most important C6 sugar and, in Nature, is present in cellulose, starch or as a free monomer. Other C6 sugars, present in hemicellulose, are arabinose and galactose. Glucose may be used as substrate for producing energy and material product through mainly 3 pathways: a) hydrogenation, leading to sorbitol and 1,2-propylene glycol, b) acid treatment, leading to 5Hydroxymethylfurfural, levulinic acid and their derivates, c) fermentation, leading to ethanol, other alcohols and organic acids (such as lactic acid, acetic acid, citric acid and others) (Kamm et al., 2006b). 3.3.5. C5 sugars The most common C5 sugars in biomass feedstocks are xylose and mannose (with xylose having a dominant position). They can be found in the hemicellulose fraction of lignocellulosic raw materials or as free monomers. As in the previous case, there are three main chemical conversion pathways for producing fuels or chemicals from xylose: (a) hydrogenation, producing xylitol, (b) acid treatment producing furfural and its derivates, (c) fermentation, producing bioethanol and other chemicals (Kamm et al., 2006b).

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3.3.6. Levulinic acid Levulinic acid (C5H8O3) is formed by acid hydrolysis of C6 sugars and can be easily converted to chemical derivates, thanks to its high reactivity: since it has both a ketone carbonyl group and an acidic carboxyl group, it can react as a ketone and as a fatty acid.

Figure 9. A possible reaction mechanism of levulinic acid from C6 sugars via HMF (Hayes et al., 2006; Timokhin et al., 1999).

A possible reaction mechanism for the production of levulinic acid from C6 sugars is illustrated in Figure 9. Firstly, cellulose is hydrolyzed to C6 sugars and then levulinic acid is obtained through hydroxymethylfuran (HMF) with an efficiency of 50% (Hayes et al., 2006). Its main derivates are: methyltetrahydrofuran (MTHF, a fuel which can be obtained by dehydratation and hydrogentation), δ-aminolevulinic acid (DALA, a herbicide which can be produced after a chemical synthesis process), diphenolic acids (DA, a polymer constituent coming out from the reaction of levulinic acid with phenols), ethyl levulinate (EL, a fuel produced by the reaction with ethanol) and others (Bozell et al., 2000; Hayes et al., 2006).

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3.3.7. Furfural Since there is no synthetic route available for furfural production, this chemical compound is exclusively produced from lignocellulosic biomass by dehydrating C5 sugars (mainly xylose) which are present in the hemicellulose fraction (see Figure 10). Furfural (C5H4O2), together with its derivates, is an important chemical because is a selective solvent for separating compounds in petroleum refining, gas, oil and diesel fuel. The main furfural derivate is furfuryl alcohol, a basic component for furan resins, but a wide range of products can also be produced through different chemical reactions, such as methylfuran (MF, a pharmaceutical compound), methyltetrahydrofuran (MTHF, a fuel additive), maleic acid (MA, a commodity chemical) and Nylon 6.6 (a polyamide), among others (Kamm et al., 2006b; Vazquez et al., 2007).

- 3 H2O

Furfural Xylose

Figure 10. Production of xylose from dehydratation of xylose.

3.3.8. Pyrolytic liquid Pyrolytic liquid is the product of the pyrolysis process applied to biomass feedstocks; in the case of flash pyrolysis, the yield of pyrolytic oil is about 75%. Pyrolytic liquid (or biooils) is a multi-component mixture of different size molecules derived from depolymerization and fragmentation of the feedstock. Therefore, the elemental composition of bio-oil and petroleum derived fuel is different, and they cannot be mixed. Pyrolytic liquid has a water content of 20-30%, and an oxygen content of 35-40% (but if only lignin is pyrolysed this value can decrease to 20%); it is highly corrosive and with a lower heating value of 20 MJ/kg (Bridgwater and Peacocke, 2000; Spilae et al., 1998). The 99.7% (dry weight) of pyrolytic oil, is composed of acids, alcohols, aldehydes, esters, ketones, sugars, phenols, guaiacols, syringols, furans, lignin derived phenols and extractible terpene with multi-functional groups. Many of these substances can be extracted, such as phenols, volatile organic acids, levoglucosan and others, but the utilization of pyrolytic oil as a fuel for stationary generation of steam and power remains, to date, the most suitable alternative (Zhang et al., 2007). 3.3.9. Vegetable oil Vegetable oil can be extracted from nearly any oilseed crop for potential use as biofuels or as a chemical substrate. They are made of triglycerides which typically consist of glycerin and saturated and unsaturated fatty acids. Triglycerides have two chemically reactive sites and thanks to this reactivity, a wide range of products can be produced, such as: biodiesel (giving glycerin as a co-product), dicarboxylic acid (by bio-oxydation), polyamides and polyurethanes (i.e. bio-plastics), among others (Hill, 2006).

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3.3.10. Organic juice Organic juice refers to the liquid phase which can be obtained after pressing of fresh biomass feedstock such as grasses, vegetables, fruits and others. This organic fraction is extremely reach of chemical compounds dispersed in an aqueous solution, mainly organic acids of different size and proteins, which can be extracted and concentrated in order to become value added products.

4. LIFE CYCLE ASSESSMENT OF BIOREFINERY SYSTEMS: A CASE STUDY 4.1. Introduction to LCA In order to investigate all the environmental aspects of biorefinery systems, an evaluation by means of Life Cycle Assessment (LCA) of the full production chain, from supply of raw materials to final use of products, is required. A Life Cycle Assessment study is a tool for evaluating environmental impacts associated with a product, process, or service by identifying energy and materials used and emissions released to the environment; moreover it also allows an identification of opportunities for environmental improvements (Consoli et al., 1993; Lindfors et al., 1995). A typical LCA study consists of the following stages: 1. Goal and scope definition (ISO 14041); 2. Life cycle inventory (LCI) analysis, with compilation of data both about energy and material flows and on emissions to the environment, throughout the life cycle of the case study (ISO 14041); 3. Assessment of the potential impacts (Life Cycle Impact Assessment, LCIA) associated with the identified forms of resource use and environmental emissions (ISO 14042); 4. Interpretation of the results from the previous phases of the study in relation to the objectives of the study (ISO 14043).

4.2. Goal and Scope Definition The goal and scope definition is the first part of an LCA, where the purpose, the scope, the functional unit and the system boundary of the assessment are described. The aim of this work is to analyze a biorefinery system by means of LCA. The investigated biorefinery is a system where several conversion technologies are jointly applied to produce transportation biofuels, bioenergy and material products. The products of the biorefinery are the following: 1. Transportation biofuels: bioethanol and methyltetrahydrofuran (MTHF); 2. Bioenergy carriers: biomethane, hydrogen, electricity and heat; 3. Biomaterials: furan resins, fumaric acid (FUMA) and oxygen.

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Wood industrial residues are used as raw materials and are delivered to the plant in the form of pellets (chemical and elemental composition in Table 1). The results of the biorefinery systems are shown in comparison with a fossil reference system providing the same amount of energy and chemical products from fossil sources. The software tool Gemis is used to model LCA calculations and as database source (Gemis, 2008). Environmental concerns are focused on energy and greenhouse gas (GHG) balances of biorefinery and fossil reference systems, because reduction of GHG emissions and decrease of fossil fuel consumption are two driving forces of biomass utilization strategies. As a direct consequence of the definition, a biorefinery is characterized by multiple useful outputs (both energy and material products). This fact gives rise to an allocation issue, which was addressed using different allocation methods. Finally, biorefinery system performances are investigated by means of several indices and indicators such as conversion yields and mass, energy, exergy and C efficiencies.

4.2.1. Biorefinery: scope and system boundaries Wood industrial residues are the raw materials for this biorefinery system. The feedstock is assumed to be collected from industries, transported to a pellet facility (20 km), where it is dried and pelletized, and transported to the biorefinery plant (100 km). The GHG emissions estimated for collecting, processing and delivery of raw materials to biorefinery gates are equal to 1.94 g CO2-eq./MJpellets, while the primary fossil energy consumption is 8.47 kJ/MJpellets (Gemis, 2008). MTHF H2

C5 sugars

Pretreatment

Feedstock

C6 sugars

Acid treatment

Furfural

Chemical reactions

Furan resins O2

FUMA

Hydrolysis

Fermentation

CO2

Distillation

Bioethanol

Fertilizer Wastewater

Legend Feedstock

Intermediate

Energy Product

Anaerobic digestion Biogas

Process

Output not exploited

Lignin & residues

Combustion

Material Product

Electricity Heat

Upgrading

Alkaline water electrolysis

Biomethane

Hydrogen Oxygen

Figure 11. Process scheme of the investigated biorefinery.

This biorefinery produces bioethanol from fermentation of C6 sugars, furfural from hydrolysis of C5 sugars (which is then chemically converted to fuel additive and other chemicals), electricity and heat from combustion of lignin and residues, hydrogen and oxygen through alkaline water electrolysis and biomethane and fertilizer via anaerobic digestion of wastewaters (Figure 11).

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The lignocellulosic feedstock (530 ktonnes/a) is pretreated through an acid catalyzed hydrolysis step which splits the raw material in 2 flows: a solid flow containing cellulose and lignin and a liquid flow containing the hydrolyzed C5 sugars. The pretreatment occurs at temperatures higher than 160°C and with a reaction time of 2-10 minutes (Sun and Cheng, 2002). The liquid flow is made of C5 sugars (xylose and arabinose monomers coming from hemicellulose hydrolysis with an efficiency of 95%) which are treated with a dilute sulfuric acid solution at low temperature for a short period of time. The product output is furfural, obtained with an efficiency of 90% by the following reaction: C5H10O5 → C5H4O2 + 3H2O (Kaylen et al., 2000). Furfural is then converted to the following products (Kamm et al., 2006b; Vazquez et al., 2007):

Figure 12. Conversion of furfural to MTHF via methylfuran.

•

• •

70% to the fuel additive methyltetrahydrofuran (MTHF) by reduction with H2 via the intermediate methyl furan, as illustrated in Figure 12 (1st reaction: C5H4O2 + 2H2 → C5H6O + H2O, molar efficiency 80%; 2nd reaction: C5H6O + 2H2 → C5H10O, molar efficiency 95%; both reactions needs a Ni catalyst; overall yield 76%); 15% to furan resins, made by polymerization of furfural, furfuryl alcohol or other compounds containing a furan ring; 15% to fumaric acid (FUMA) by oxidation (followed by opening of the furan ring) in presence of a V2O5 catalyst (C5H4O2 + 2O2 → C4H4O4 + CO2) (Figure 13).

Figure 13. Conversion of furfural to FUMA via oxidation.

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The reactants H2 and O2 are internally produced in the biorefinery system by alkaline water electrolysis; 89% and 22% of the generated H2 and O2 are required in the production of MTHF and FUMA. The solid fraction coming out from pretreatment step is subjected to a further hydrolysis to hydrolyze the remaining cellulose and other C6 polymers and separate lignin. The conversion efficiencies are the following (Hamelinck et al., 2005): • • •

from cellulose to glucose 90%, from galactan to galactose 82%, from mannan to mannose 89%.

About 2% of cellulose is lost during acid recycle activities, while 9% is set aside for bacteria cultivation; all the C6 sugar monomers are then fermented to bioethanol with the following efficiencies (Hamelinck et al., 2005): • •

glucose to ethanol 93%, galactose and mannose to ethanol 90%.

Bioethanol is finally recovered via distillation. Lignin (lower heating value 22.9 MJ/kg) and the unconverted cellulose and hemicelluse (lower heating value15.63 MJ/kg) are combusted to produce electricity and heat with an efficiency of 26% and 44%, respectively (De Feber and Gielen, 2000). Ashes are delivered to landfill. Since H2 and O2 are required for the chemical conversion of furfural to its derivates, 20% of the total electricity output is destined to water electrolysis, which generates H2 with an energy efficiency of 77% and O2 at a rate of 7.92 g/gH2 (Gemis, 2008). Wastewaters coming from xylose conversion to furfural and C6 sugar fermentation are anaerobically digested to produce biogas. These wastewaters have a total dry matter content of 54.4 ktdry and generate biogas at a rate of 6 GJ/tdry (Berglund and Börjesson, 2006). The produced biogas has a heating value of 24 MJ/m3 and methane content of 60% (Alzate and Toro, 2006). Undesired methane emissions to the atmosphere during digestion and biogas treatments are estimated to be 3.47 mg/MJ and the upgrading of biogas to biomethane (CH4 content greater than 97%), by removing impurities and CO2, needs 5% of the energy content of the biogas (Gemis, 2008). Fossil energy consumption and GHG emissions related to the supply of auxiliary materials (such as sulphuric acid, lime, urea, sodium hydroxide, potassium chloride, phosphporic acid and sodium sulfite) are calculated using the software tool Gemis, while the quantities come from (Kaylen et al., 2000). Other releases of GHG emissions are the following (Gemis, 2008): • • •

Emissions from lignin (and biomass residue) combustion in turbine, estimated to be 1.59 g CO2-eq./MJ of heat set free from combustion; Emissions from combustion of bioethanol in a passenger car, assumed to be 3 g CO2eq./km (with a specific consumption of 2.45 MJ/km); Emissions from combustion of biomethane in its final use (0.67 g CO2-eq./MJ).

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Because of a lack in available data, the GHG emissions from MTHF combustion and its specific consumption in cars are assumed to be equal to bioethanol. Since the combustion of these biofuels (e.g. lignin and biomass residues, bioethanol, biomethane and MTHF) releases CO2 which has a biological origin, it is not accounted for as a GHG and the above emission factors are mainly due to N2O and CH4. This biorefinery plant requires 0.16 MWh of electricity and 0.60 MWh of heat per ton of feedstock for producing bioethanol and furfural (Kaylen et al., 2000), while 7.5 kJ of heat per g water are needed to distil the water required by the electrolysis process (Gemis, 2008). The anaerobic digestion step and following biogas upgrading requires 0.65 GJ of electricity and 0.1 GJ of heat per tonne of dry matter in wastewaters (Berglund and Börjesson, 2006).

4.2.2. Biorefinery material products All the products produced by biorefinery systems can be grouped in two broad categories: material products and energy products. Energy products are those products which are used for their energy content, providing electricity, heat or transportation service. On the other hand, material products are not used for an energy generation purpose but for their chemical or physical properties. The chemical structure of energy and material products of the investigated biorefinery system are reported in Figure 14. The market share of products produced from biomass is expected to rise from the current level of 5% to 20% in the short run (Sauer et al., 2007). In fact, these products are favourable from a chemical point of view. Functional groups that must be introduced by costly oxidative process steps into oil are already available in plant materials. It is noteworthy that for many biomass derived chemicals the actual market is small, but an economical production process will create new markets by providing new opportunities for the chemical industry. For example, succinic acid and formic acid could replace the petroleum-derived commodity chemical maleic anhydride. The market for maleic anhydride is huge, whereas the current market for the organic acids mentioned is small. The material products of the analyzed biorefinery system are fumaric acid, furan resins, O2 and fertilizers. Fumaric acid (HO2CCH=CHCO2H) is a carboxylic acid currently produced from the oxygenation of the fossil derived product benzene. It is mainly used in medicine, in food industry as a food acidulent, in chemical industry and in the manufacture of polyester resins and polyhydric alcohols. Fumaric acid has an annual production of 12 ktonnes but a projected market volume of more than 200 ktonnes (Sauer et al., 2007). The uses are the following: 35% as paper size resins, 22% as food acidulant, 15% in unsaturated polyester resins, 6% in alkyd resins, 5% as plasticizers and 17% miscellaneous (including lubricating oils and oil field fluids, esters, inks, lacquers, carboxylating agent for styrenebutadiene rubber) (CMR, 2008). Furan resins are made by polymerization or polycondensation of furfural, furfuryl alcohol or other compounds containing a furan ring, or by reaction of these furan compounds with other molecules (not over 50%). The major uses of furan resins are as foundry binders and their production in biorefinery is assumed to play a major role in chemical conversions of furfural. Another chemical product is oxygen in its diatomic form (O2), which can be used in a lot of chemical applications like oxidizing agent. Fertilizers are the residues of the anaerobic digestion step which can partly replace the use of synthetic fertilizers. However, due to a lack of data on its use and fossil fertilizers replacement rate, no benefits from this material output are considered in LCA calculation.

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Figure 14. Chemical structures of the bioproducts from the biorefinery: bioethanol, biomethane, MTHF, furfural and fumaric acid

4.2.3. Biorefinery energy products The energy products of the biorefinery are bioethanol, MTHF, biomethane, hydrogen, electricity and heat. The production of large quantities of biofuels or fuel additives via renewable feedstocks offers perhaps the greatest potential for mass-market penetration of biorefineries. Bioethanol is one of the most common transportation biofuels currently produced in the world and can replace gasoline in vehicles. Biomethane is obtained from upgrading of biogas by removing CO2 and other undesired elements, like H2S. Biomethane can be used as a transportation biofuel or can be transported through the existing gas infrastructure and substituting natural gas in all its existing applications. Methyltetrahydrofuran (MTHF) is produced from furfural by reduction to methyl furan, which is then reduced to MTHF (both reductions occur with H2). MTHF is a very important compound because it can be added to gasoline (to be blended at the refinery rather than later in the distribution process) or bioethanol up to 30% by volume without effects on performances and engine modification. Using MTHF as a fuel additive increases the oxygenate level in gasoline without adversely affecting engine performance. MTHF also boasts a high octane rating (87) and a low vapour pressure, thereby reducing fuel evaporation and improving air quality. Although it has a lower LHV than gasoline, it has a higher specific gravity and hence mileage is competitive. Properties of MTHF as fuel are reported in Table 2. Hydrogen is produced via alkaline water electrolysis and is used as a reducing agent for conversion of furfural to MTHF at the biorefinery plant site. This can be seen as an innovative way to safely store H2 in a transportation biofuel. The remaining H2 fraction is delivered to the market.

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Table 2. Selected properties of MTHF as a transportation biofuel. Property Boiling point (102 mmHg) Boiling point (Atm.) Flash point Reid vapour pressure Lower heating value Specific gravity Octane rating

Unit °C °C °C psig MJ/kg

MTHF 20 80 11 5.7 32 0.813 80

Electricity and heat are produced by combustion of lignin and process residues. Part of this electricity and heat production is used to meet the plant energy demand and the rest is delivered to the public grid.

4.2.4. Fossil reference system LCA environmental performances of the analyzed biorefinery system are compared with those of a fossil reference system based on oil refinery, producing the same amount of energy and chemical products. A comparison between the two systems is illustrated in Figure 15. ReferenceSystem

Biorefinery Collection Wood residues

Transport

Natural decomposition

Natural gas

Oil

Extraction & Conveyance

Extraction & Conveyance

Transport

Transport

Power plant

Refinery

Processing Air Steam reforming

Biorefinery plant

Processing Distribution Electric net

Distribution

Distribution

Heavy oil

Gasoline

Distribution

Heating plant

Distribution

Heating network

Gasoline vehicles

Distribution

O

2

H2

Biofuel vehicles

Heating Chemicals Electric net network andH2

Chemicals

Productsandservices (transportation, chemicals, electricity, heat, H2, methane)

Figure 15. Comparison between production chains: biorefinery system vs. fossil reference system.

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The biorefinery chain starts at the top with carbon fixation from the atmosphere via photosynthesis, or, as it occurs in this case study, biomass C taken as biomass waste from the forest sector. At the end of the biorefinery chain a certain amount of useful energy and products are supplied. Along the whole process chain, all the energy and material inputs and emissions occurring for planting and harvesting the crop (or collect the raw materials), processing the feedstock into fuels and products, transporting and storing of the feedstock, distributing and final use of the products must be accounted for in a life cycle perspective (Schlamadinger et al., 1997). Particular importance should be given to the numerous co-products which a biorefinery may produce, because they can have relevant implications in the assessment of the overall system. The fossil reference system is dealt with in a similar way, considering all the material and energy inputs and emissions associated with its life cycle stages: production of the raw fossil fuel, refining, storage, distribution and combustion. If compared in this manner, the differences between the two systems producing the same product/service can be presented. Table 3 reports the bioproducts produced by the investigated biorefinery and the fossil conventional counterparts that they replace. In the right part of the table the environmental impacts, in terms of GHG emissions and total energy demand, of the fossil derived products are listed: these are the GHG emissions and energy consumption saved by the biofuels and biochemicals of the biorefinery. These values, reported in the right part of the table, have been calculated by means of the LCA software tool Gemis (Gemis, 2008). Table 3. Table reporting the conventional alternatives of the different products of the biorefinery and their specific factors for GHG emissions and fossil energy consumptions.

a

Biorefinery Bioproducts Bioethanol Electricity Heat Biomethane MTHF

Fossil reference system Conventional alternative Unit g CO2-eq./unit Gasoline km 189 b Electricity from natural gas MJ 120 c Heat from oil MJ 106 Conventional methaned MJ 76 Gasoline km 189

H2 Furan resins Fumaric acid

H2 from natural gas Epoxy resins Conventional fumaric acid

MJ g g

72 6.07 1.29

1.24 0.13 0.05

O2 Fertilizer

Conventional O2 (from air) No benefits

g

0.07

0.001

MJtot./unita 2.36 1.96 1.32 1.31 2.36

Mainly fossil energy (> 98%) Large scale gas-fired combined-cycle (CC) power plant with efficiency of 57% and low NOx burner; it is assumed that 1/3 of the electric capacity comes from the steam turbine. c Heavy oil boiler for industrial process heat, efficiency 85%. d Including emissions from combustion in natural gas boiler (66.15 g CO2-eq./MJ), efficiency 85%. b

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The transportation biofuels bioethanol and MTHF replace conventional gasoline as a liquid transportation fuel in passenger cars. It is assumed that the electricity and heat produced by the biorefinery substitute, respectively, electricity produced from natural gas turbine and heat generated from a heavy oil boiler. Regarding the two remaining biofuels, biomethane (fed to the national grid) replaces conventional natural gas in its applications as a stationary fuel while bio-H2 replaces conventional hydrogen production from steam reforming of natural gas. Concerning the chemicals, their GHG emissions and fossil energy requirements were been estimated considering their production chains in the current oil refinery. It is assumed that furan resins replace epoxy resins. Epoxy resins are polymers originated from polymerization of epoxy monomers, and are produced by reaction of epichlorohydrin and bisphenol-A. Epichlorohydrin is a highly reactive epoxide and polymerizes upon treatment with acid or strong base; bisphenol A, commonly abbreviated as BPA, is an organic compound with two phenol functional groups and constitutes a building block of several important polymers and polymer additives. Epoxy resins are used as adhesives (they are one of the few adhesives that can be used on metals), as protective coatings, as materials in electronic circuit boards and for patching holes in concrete pavement. In Figure 16, the chemical structures of BPA, epichlorohydrin and the reaction mechanism leading to epoxy resins, are illustrated.

Figure 16. Reaction between BPA and epichlorohydrin and formation of epoxy resins.

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Conventional fumaric acid is currently produced from oxygenation of benzene (C6H6 + 4O2 → C4H4O4 + 2 CO2H2). The chemical properties of fumaric acid can be anticipated from its component functional groups. This weak acid forms a diester, it undergoes additions across the double bond, and it is an excellent dienophile. The O2 produced by the biorefinery plant (via alkaline water electrolysis) replaces the molecular oxygen (O2) that is currently produced from processing of air, from which O2 is separated. About 100 million tonnes of O2 are extracted from air for industrial uses annually. The most common method to recover O2 is to fractionally-distill liquefied air into its various components, with nitrogen N2 distilling as a vapor while oxygen O2 is left as a liquid (Emsley, 2001).

4.2.5. Functional unit The functional unit is the foundation of biorefinery systems LCA: it sets the scale for comparison of different technological routes which a biomass feedstock can undergo in order to be converted to biofuels and chemicals. One of the main purposes of the functional unit is to provide a reference to which the input and output data are normalized and the basis by which the final results are shown. For instance, the results of a bioenergy system from dedicated biomass crops should be expressed on a per hectare basis, since the available area for the production of biomass raw materials is the biggest bottleneck for the production of biofuels (Schlamadinger et al., 2005). However, in order to be comparable, biorefinery results have the need to be independent from the kind of biomass feedstock (dedicated crops or residues) and from the conversion processes which act on the biomass raw materials. As a consequence, they cannot be expressed per hectare basis or per unit of output. The most suitable functional unit is then the unit of biomass input which, in this study, is the amount of biomass treated per year by the biorefinery: 530 ktonnes/a. Therefore, all the input flows reported in the following inventory list and the final results of GHG emissions and cumulated primary energy demand are referred to this amount of biomass input. 4.2.6 Allocation Allocation in LCA is carried out to attribute shares of the total environmental impact to the different products of a system. This concept is extremely important for biorefinery systems, where multiple energy and material products are produced. The question of the most suitable allocation procedure is still an open issue. Scientific LCA publications show benefits and disadvantages of several allocation methods (Curran 2007; Ekval and Finnveden, 2001; Frischknecht 2000; Wang et al., 2004). The ISO standards suggest to avoid allocation by expanding system boundaries, when possible. This method relies on the expansion of the product system to include the additional functions related to the co-products. This procedure (also called substitution method) has the advantage to avoid allocation issues while has the disadvantage to make the system too complex, especially if multiple co-products are present (like in biorefineries). In fact, this method relies on identification of a main product and the environmental benefits of coproducts are assumed as credits, which are subtracted to the total GHG emissions and the remaining emissions are completely assigned to the main product. Furthermore, the identification of one of the output as main product is an arbitrary choice and can be a difficult decision in biorefinery systems, where multiple useful and valuable outputs are produced. Therefore, system expansion is not recommended when an elevated number of high quality outputs is produced; this situation can even lead to a negative value (i.e. below zero) of the

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burdens allocated to the main product. Where system expansion cannot be applied and the allocation cannot be avoided, ISO norms suggest that the inputs and outputs of the system should be partitioned between its different products or functions in a way which reflects the underlying physical relationships between them (physical allocation); i.e. they shall reflect the way in which the inputs and outputs are changed by quantitative changes in the products or functions delivered by the system (Curran 2007). Where physical relationship alone cannot be established or used as the basis for allocation, the inputs should be allocated between the products and functions in a way which reflects other relationships between them. If system expansion cannot be applied, input and output data might be allocated between co-products in proportion to thermodynamics parameters (such as energy or exergy content of outputs) or to the economic value of products. Allocation based on energy content of products can be easily carried out but its application is inconsistent (i.e. lacking of a correct logical relation) and results in misleading conclusions if there are some products which are not used as energy carriers (e.g. chemicals). Allocation based on exergy overcomes this inconsistency but can be problematic to be applied because of the difficulties for estimating the exergy content of substances (especially new bio-based products). Allocation based on economic values focuses on external characteristics of the products and has the disadvantages that do not take into account the environmental perspective and the physical properties of the products, because is based on their “value” in human societies; in addition, market values of products can fluctuate consistently according to the reference year, production chain and geographical location (Ekvall, 2001; Pierru 2007). In order to do not disregard these issues and provide a sensitivity analysis on how the different allocation procedures affect the final results, all the above mentioned allocation methods are applied to the biorefinery system assessed in this chapter. Concerning system expansion, the main product is assumed to be bioethanol and the environmental benefits of co-products are assumed as credits, calculated thanks to the fossil reference systems. These credits (i.e. the GHG and fossil energy saved by the co-products) are then subtracted to the total GHG emissions and energy consumption of the whole system; the resulting environmental burdens are completely assigned to the main product. Allocation methods based on thermodynamics parameters (energy and exergy content) and economic values of the products share the environmental burdens among the different outputs, without identifying a main product. Concerning allocation based on energy content, for biofuels the following heating values are considered: bioethanol 27 MJ/kg, MTHF 32 MJ/kg, biomethane 34.75 MJ/kg, hydrogen 114 MJ/kg. The energy content of the material products has been estimated by means of the Dulong’s formula (furan resins 21.22 MJ/kg, FUMA 9.08 MJ/kg). Oxygen does not have a heating value. Exergy content of products are collected from a specific database (Ayres et al., 1996).

4.3. Life Cycle Impact Assessment Life Cycle Impact Assessment (LCIA) stage deals with the evaluation of environmental impacts of the biorefinery system and fossil reference system over their whole life cycle. The results focus on two types of impact categories: greenhouse gas (GHG) emissions and cumulative primary energy demand.

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Unit

Transportation (bioethanol)

Price

$/kg

1.34

Transportation (MTHF)a

$/kg

1.31

Furan resinsb

$/ton

3555

$/ton

1278

$/GJ

27.78

$/GJ

9.29

FUMA

c d

Electricity e

Heat

f

Biomethane

$/GJ

9.29

g

$/GJ

35.09

f

$/kg

8.93

H2 a

a

O2

Calculated on the basis of gasoline price in the US (1.06 $/L) b New chemical commodity, price in market not available. Estimate on the basis of the price of epoxy resins c The price is referred to low grade fumaric acid d Average electricity price for households in the US e Price based on energy content of replaced natural gas f Average price natural gas for households in the US g Average estimated price of H2 in future markets (Ducharme et al., 2005) f Average O2 price for laboratories

The first impact category refers to all the GHG emissions released for feedstock production, transport, conversion processes, provision of auxiliary materials and final use of the products. These emissions are accounted for and converted to g CO2-eq. with equivalency factors. The analysis considers three long lived GHGs released by human activities: CO2, CH4 and N2O. Their effect on global warming can be assessed by an index called Global Warming Potential (GWP), which is a measure of how much a given mass of GHG contributes to global warming relative to a reference gas (usually CO2) for which GWP is set to 1. For a 100-year time horizon, GWPs of CO2, CH4 and N2O are, respectively, 1, 25 and 298 g CO2-eq./gemission (IPCC, 2007). Using this index, one can calculate the equivalent CO2 emission by multiplying the emission of a GHG by its GWP. Similarly, the cumulative primary energy demand accounts for all the life cycle stages, from feedstock provision to final use of products. The primary energy demand is divided into fossil, renewable and other energy demand. The same impact categories are evaluated for the fossil reference system as well, with the intent to make comparisons and quantify savings. In order to gain information concerning performances and conversion efficiencies of the biorefinery system, the mass, energy, exergy and carbon efficiencies are carried out through the whole biorefinery conversion chain. The C content of the different feedstock components and final products are estimated and the C balance of the system calculated according to the methodology depicted in (Cherubini and Jungmeier, 2008), while the exergy contents of the molecules are derived from (Ayres et al., 1996).

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4.3.1. Results and interpretation The final quantities of products produced are reported in Table 6 (upper part), where the results of the biorefinery and fossil reference systems are also shown. The biorefinery releases about 36.8 kt CO2-eq./a and requires 10858 TJ/a of primary energy, of which 208 TJ/a fossil energy. On the other hand, the fossil reference system releases 336 kt CO2-eq./a and requires 4772 TJ/a, of which 4736 TJ/a fossil energy. Table 6. Quantities of final products, GHG emissions and primary energy demand of biorefinery system and fossil reference system. Birefinery System Product/service: Transportation (bioethanol) 1,082 Transportation (MTHF) 122 Furan resins 2.91 FUMA 3.34 Electricity 333 Heat 224 Biomethane 261 H2 13.7 O2 7.07 Fertilizer (no benefit) 36.9 Environmental impacts: Total GHG emissions 36.8 CO2 27.0 N2O 9.22 CH4 0.61 Primary energy demand 10,858 Fossil 208 Renewable (biomass) 10,495 Others 16 GHG and energy savings With heat credits GHG emissions saved 300 0.66 Fossil energy saved 4,527 10.05 Excluding heat credits GHG emissions saved 276 0.61 Fossil energy saved 4,231 9.39

Mio km Mio km kt kt TJ TJ TJ TJ kt ktd ry

Fossil Reference System Product/service: Transportation (gasoline) 1,204 Mio km Epoxy resins (from fossil) FUMA (from fossil) Electricity (from natural gas) Heat (from oil) Natural gas H 2 (from natural gas) O2 (conventional, from air)

2.91 3.34 333 224 261 13.7 7.07

kt kt TJ TJ TJ TJ kt

Environmental impacts (including heat): Total GHG emissions 336 CO2 322 N 2O 7.27 CH4 7.69

kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO 2-eq./a

TJ/a TJ/a TJ/a TJ/a

Primary energy demand Fossil Renewable Others

TJ/a TJ/a TJ/a TJ/a

kt CO 2-eq./a t CO2-eq./tdrywo od TJ/a GJ/tdrywood

Environmental impacts (excluding heat): Total GHG emissions 313 CO 2 299 N 2O 6.76 CH 4 7.15

kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO 2-eq./a

kt CO 2-eq./a t CO2-eq./tdrywo od TJ/a GJ/tdrywood

Primary energy demand Fossil Renewable Others

TJ/a TJ/a TJ/a TJ/a

kt kt kt kt

CO 2-eq./a CO 2-eq./a CO2-eq./a CO 2-eq./a

4,772 4,736 7 25

4,474 4,440 6 24

This means that the biorefinery system is able to save 89% of GHG emission and 95.6% of fossil energy in respect with its fossil reference system, providing the same quantities of products and services. In Figure 17, the GHG emissions of the biorefinery and fossil reference system are compared. Biorefinery shows a relevant decrease of total GHG, CO2 and CH4 emissions, while it has a slight increase in N2O emissions, because of the biomass (lignin, residues, biofuels) combustion steps.

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336

350

322

300

kt CO2-eq./a

250 Total GHG 200

CO2 N2O

150

CH4

100 50

37

27

9

-

0.61

Biorefinery

7

8

Fossil reference system

Figure 17. Comparison between GHGs of biorefinery and fossil reference system.

Going into details, about 33 kt CO2-eq./a are released by feedstock production and biorefinery plant activities, with the following shares: • • •

61% of these emissions comes from feedstock provision (e.g. collection of wood residue, pelleting and transport), 16% from lignin and process residue combustion for CHP production (i.e. emissions of CH4 and N2O), 23% from manufacturing of auxiliary materials such as urea (9%), sulfuric acid, phosphoric acid (5.7%), sodium hydroxide (5%) and others.

In addition to these emissions, distribution and final use of products are responsible for an emission of 3.8 kt CO2-eq./a (coming from combustion of transportation biofuels in passenger cars (95%) andfrom combustion of biomethane in its final application (5%)). Table 7. GHG emissions of the fossil reference system. Fossil reference system Product/service

kt CO2-eq./a

%

Transportation (gasoline)

227

67.6%

FUMA (from fossil)

4.31

1.3%

Epoxy resins (from fossil)

17.7

5.2%

Electricity (from natural gas)

39.8

11.8%

Heat (from oil)

23.8

7.1%

Natural gas

21.9

6.5%

H2 (from natural gas)

987

0.3%

O2 (conventional)

509

0.2%

336

100.00%

Total GHG emissions

Biorefinery Concept: Energy and Material Recovery from Biomass…

Biomethane combustion Biofuel combustion 0.5% in cars 10%

129

Other 0.5%

Manufacture of auxiliary materials 20% Feedstock provision 55% Residue combustion 14% Figure 18. Contributions to the total GHG emissions of the biorefinery system. “Other” includes wastewater treatment, waste disposal (mainly ashes) and uncontrolled CH4 emissions from anaerobic digestion.

Contributions from all the stages to the total GHG emissions of the biorefinery system are illustrated in Figure 18. More than half of the GHG emissions are due to feedstock provision, i.e. collection, processing and delivery of wood residue pellets. Concerning the fossil reference system, the total GHG emissions are mainly due to gasoline (68%), followed by electricity (12%) and then other products. Detailed information concerning the contributors to the total GHG emissions of the fossil reference system are reported in Table 7. The primary energy demand of biorefinery system and fossil reference system has similar contributions than those of GHG emissions. Results highlight both the importance of generating high quantities of electricity and the benefits deriving from an utilization of the process heat produced for achieving high GHG emission and fossil energy savings. Concerning electricity, the lower the share of electricity sent to alkaline water electrolysis, the higher the savings. In the determination of the magnitude of these savings, a fundamental role is played by the fossil reference system considered. It is assumed that the fossil reference system produces electricity from natural gas but the savings would be larger if, for instance, electricity from coal or oil is displaced. Regarding the heat, fundamental is the possibility to use it in an application located in the surrounded of the biorefinery, maximizing the environmental benefits which can be gained. In the fossil reference system, heat is assumed to be produced from oil and even in this case, environmental savings would be larger if coal-derived heat is replaced. The differences between biorefinery systems with and without process heat utilization are reported in the

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lower part of Table 6: GHG and fossil energy savings are about 8% lower if heat is not used to substitute oil-derived heat. Comparison of the biorefinery with its fossil reference system shows that the biorefinery can reduce GHG emissions of about 299.6 kt CO2-eq./a (0.66 t CO2-eq./tdry wood) and save 4527 TJ/a of fossil energy (10.05 GJ/tdry wood). Even if the biorefinery system requires more than twice the primary energy demand of the fossil reference system, it is mainly constituted (97%) by renewable energy, i.e. the energy content of biomass feedstock, and the savings of fossil energy are relevant (almost 96%). As a consequence, the provision of biomass with sustainable practices is a crucial point to ensure a renewable energy supply to biorefineries. Table 8. Conversion yields and mass, carbon, energy and exergy efficiencies of the biorefinery system. Ethanol yield per t of feedstock (dry) 0.22 Ethanol yield per ton of cellulose 0.49 C conversion efficiency from wood to EtOH 22.45% C conversion efficiency from cellulose to EtOH 56.98% Furfural yield per t of feedstock (dry) 0.04 Furfural yield per ton of xylan 0.68 C conversion efficiency from wood to furfural 5.35% C conversion efficiency from hemicellulose to furfural 74.86% a Material products per t of feedstock (tprod/tdry wood) 2.96% Energy products (net) per GJ of feedstock (GJprod/GJwood)b: with heat 37.28% without heat 35.12% C conversion efficiency (from feedstock to products) 29.15% Exergy conversion efficiency: with heat 44.38% without heat 42.95% a Only material products included (e.g. furan resins, FUMA, and O2) b Energy feedbacks to the plant subtracted (i.e. only final energy outputs included)

t/tdry t/tcell

t/tdry t/txylan

Biorefinery system performances in terms of product yields and mass, energy, exergy and C conversion efficiencies are reported in Table 8. Bioethanol and furfural yields are respectively 0.22 and 0.04 t per tonne of dry feedstock, but the yields increase up to 0.49 t of bioethanol per tonne of cellulose and 0.78 t of furfural per tonne of xylan. The overall C conversion efficiency of the plant from feedstock to products is 29.15% and the exergy conversion efficiency is 44.38%. The material products of the biorefinery (i.e. furan resins, FUMA and O2) constitute 2.96% of the total mass of the dry feedstock, while final net energy products (bioethanol, MTHF, H2, biomethane, electricity and heat) store about 37% of the raw material energy content. Without heat, this energy efficiency decreases to 35%. A comparison can be done with other biomass conversion systems, which have energy efficiencies higher than biorefinery. In fact, production of heat from wood combustion can reach efficiencies higher than 85%, while in CHP application the overall energy efficiency is around 80%. The reason is that a biorefinery system is made of several conversion steps and biomass undergo chemical reactions and changes of state, while the aforementioned

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131

conventional biomass system mainly involve one step (biomass combustion). In particular, energy and C conversion efficiencies of the biorefinery are lowered by the fermentation step, where C6 sugars are converted to bioethanol: C efficiency from cellulose to bioethanol is about 57% while from hemicellulose to furfural (a chemical pathway, without microorganisms) is about 75%. During fermentation almost half of the C in C6 sugars is converted to the useless product CO2, thus lowering the overall efficiency of the process.

4.3.2. Allocation results The allocation procedures previously described are applied in order to share the environmental burdens of the biorefinery among the different products. The allocation criteria are based on energy content, exergy content and economic value of products. An attempt to avoid allocation through system expansion was also done. Results are reported in Table 9, where the GHG emissions of the biorefinery system are allocated. Concerning the cumulated primary energy demand, allocation can be performed considering the same shares of the total GHG emissions of Table 9. Table 9. Allocation of the GHG emissions to the biorefinery products using different allocation methods. Allocation method Unit Transportation (bioethanol) Transportation (MTHF) Furan resins FUMA Electricity Heat Biomethane H2 O2

Energy

Exergy

Economic value

System expansion main -97.6 produc t

kt CO2-eq./a

25.1

68.3%

25.7

69.8%

25.4

68.9%

kt CO2-eq./a

2.82

7.68%

2.98

8.09%

2.36

6.41%

25.6

credits

kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a kt CO2-eq./a

0.59 0.29 3.18 2.14 2.49 0.13 -

1.60% 0.79% 8.64% 5.83% 6.78% 0.36% 0.00%

0.62 0.33 2.60 1.05 3.22 0.11 0.01

1.69% 0.90% 7.07% 2.86% 8.75% 0.30% 0.02%

2.02 0.83 1.80 0.41 0.47 0.09 3.45

5.48% 2.26% 4.90% 1.11% 1.29% 0.25% 9.38%

4.31 17.6 39.8 23.8 21.8 0.99 0.51

credits credits credits credits credits credits credits

In Figure 19, the influence of the allocation methods on GHG emissions allocated to biorefinery products is shown. It can be noticed that, besides system expansion which uses a different approach, all the allocation criteria lead to similar results, especially concerning transportation biofuels (bioethanol and MTHF). Allocation based on energy and exergy content of products show similar results also for the other energy products and chemicals, while allocation based on economic values increases the shares of chemical products, such as furan resins, FUMA and mainly oxygen, while decreasing the environmental burdens assigned to electricity, heat and biomethane. The specific GHG emission factors for each product according to the allocation procedure are listed in Table 10. In this table, GHG emissions per unit of product, i.e. km driven for biofuels, GJ for electricity and heat, g for chemicals and gaseous biofuels, are reported. For instance, these factors can be applied in a LCA if these products are used as auxiliary materials in a future biobased society. Results of these biomass derived products and services can be compared with those derived from oil refinery (reported in Table 3). For

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instance, driving a car fuelled with bioethanol produced from biorefinery (23.23 g CO2eq./km, energy allocation) instead of gasoline from oil refinery (189 g CO2-eq./km), saves approximately 88% of CO2-eq. emissions .

25

k t C O 2 - e q ./a

20 15 10 5

O2

H2

B io m e th a n e

H eat

E le c tr ic ity

FU M A

F u r a n r e s in s

T r a n sp o r ta tio n (M T H F)

T r a n sp o r ta tio n ( b io e th a n o l)

-

Energy allocation Exergy allocation Economic allocation Figure 19. mparison among the different allocation methods (data from Table 9).

Table 10. Specific factors of GHG emissions of biorefinery products according to the different allocation methods used. Unit

Energy

Exergy

Economic

Transportation (bioethanol)

g CO2-eq./km

23.23

23.74

23.43

-90.20

System expansion main product

Transportation (MTHF)

g CO2-eq./km

23.23

24.47

19.38

210.23

credits

Furan resins

g CO2-eq./g

0.18

0.21

0.69

1.48

credits

FUMA

g CO2-eq./g

0.09

0.10

0.25

5.29

credits

Electricity

kg CO2-eq./GJ

9.56

7.82

5.42

119.60

credits

Heat

kg CO2-eq./GJ

9.56

4.69

1.81

106.00

credits

Biomethane

g CO2-eq./g

0.33

0.43

0.06

2.91

credits

H2

g CO2-eq./g

1.09

0.92

0.78

8.23

credits

O2

g CO2-eq./g

-

0.001

0.49

0.07

credits

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133

5. CONCLUSION The use of biomass as raw materials for bioenergy and biochemical production is encouraged by the need for a secure energy supply, a reduction of fossil CO2 emissions and a revitalization of rural areas. Biomass energy and material recovery is maximized if a biorefinery approach is considered, where many technological processes are jointly applied to different kinds of biomass feedstock for producing a wide range of bioproducts. A lot of biorefinery pathways, from feedstock to products, can then be established, according to the different types of feedstock, conversion technologies and products. Biorefinery concept is analogous to today's petroleum refinery, which produces multiple fuels and products from petroleum. Among the different biomass resources, lignocellulosic materials have great potentials for production of bioenergy and biochemicals in biorefinery, replacing fossil derived products and services. The LCA depicted in this chapter shows that significant GHG and fossil energy savings are achievable if a biorefinery system is compared with a fossil reference system. The investigated biorefinery produces transportation biofuels (bioethanol, MTHF), gaseous biofuels (biomethane and H2), chemicals (furan resins, FUMA and O2), electricity and heat from softwood forest residues, while the fossil reference system produces gasoline as transportation fuel, natural gas, H2 from natural gas, conventional O2 from air processing, conventional FUMA and epoxy resins from oil refinery, electricity from natural gas and heat from heavy oil. The biorefinery releases 36.8 kt CO2-eq./a and requires 10858 TJ/a of primary energy, of which 208 TJ/a fossil energy, while the fossil reference system releases 336 kt CO2-eq./a and requires 4772 TJ/a, of which 4736 TJ/a fossil energy. Therefore, 89% of GHG emissions and 96% of fossil energy can be saved. Even if the biorefinery has higher primary energy demand than the fossil reference system, it is mainly based on renewable energy (i.e. the energy content of the processed feedstock): the provision of biomass with sustainable practices is then a crucial point to ensure a renewable energy supply to biorefineries. Furthermore, more than half of the total GHG emissions of the biorefinery are originated from feedstock provision (collection, processing and delivery), followed by manufacture of auxiliary materials and biomass combustion. Results also show biorefinery system performances in terms of product yields and mass, energy, exergy and C conversion efficiencies. Energy and C efficiencies result affected by the fermentation step, where almost half of the C of the feedstock is loss in the formation of the useless product CO2. In order to share the environmental impacts of the biorefinery among the different coproducts, several allocation procedures were applied. An attempt to avoid allocation through system expansion was developed and then allocations based on energy content, exergy content and economic value of outputs have been carried out. All the findings are finally compared and the specific GHG emission factors (g CO2-eq./unit) of each product are reported. These factors can be applied in LCA studies of a future biobased society, when biorefinery products will be widely used by customers and as auxiliary materials in production processes.

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Paisley, M. A., Farris, M. C., Black, J., Irving, J. M. & Overend, R. P. (1998). Commercial demonstration of the Battelle/FERCO Biomass gasification process: startup and initial operating experience, In: Overend RP and Chornet E, Proceedings of Fourth Biomass Conference of the Americas, Elsevier Science, Oxford, UK, Oakland, USA, 1061-1066. Pierru, A. (2007). Allocating the CO2 emissions of an oil refinery with Aumann-Shapley prices, Energy Economics, vol. 29, Issue 3, pp. 563-577. Rajagopal, D. & Zilberman, D. (2007). Review of environmental, economic and policy aspects of biofuels, Policy research working paper of the World Bank development research group, September 2007. Romano, R. T. & Zhang, R. (2008). Co-digestion of onion juice and wastewater sludge using an anaerobic mixed biofilm reactor, Bioresource Technology, vol. 99, Issue 3, 631-637. Sauer, M., Porro, D., Mattanovich, D. & Branduardi, P. (2007). Microbial production of organic acids: expanding the markets, Trends in Biotechnology, vol. 26. N. 2, 100-108. Schiweck, H., Munir, M., Rapp, K. M., Scheider, B. & Vogel, M. (1991). New developments in the use of sucrose as an industrial bulk chemical – 5-hydroxymethilfurfural (HMF), In: Carbohydrates as Organic Raw Materials, F.W. Lichtenthaler (ed.), VCH, Weinheim New York Basel Cambridge Tokyo, 1991, 78-94. Schlamadinger, B., M. J. A., Bohlin, F., Gustavsson, L., Jungmeier, G., Marland, G., Pingoud, K. & Savolainen, I. (1997). Towards a standard methodology for greenhouse gas balances of bioenergy systems in comparison with fossil energy systems, Biomass and Bioenergy; 13: 359-375. Schlamadinger, B., Edwards, R., Byrne, K. A., Cowie, A., Faaij, A., Green, C., Fijan-Parlov, S., Gustavsson, L., Hatton, N., Heding, K., Kwant, K., Pingoud, M., Ringer, K., Robertson, B., Solberg, S., Soimakallio, & Woess-Gallasch, S. (2005). Optimizing the GHG benefits of bioenergy systems, 14th European Biomass Conference, 17-21 October 2005, Paris, France. Senneca, O. (2007). Kinetics of pyrolysis, combustion and gasification of three biomass fuels, Fuel Processing Technology, vol. 88, Issue 1, Pages 87-97. Sheehan, J., Dunahay, T., Benemann, J. & Roesller, P. (1998). A look back the US department of Energy’s acquatic species program: biodiesel from algae, NREL/TP-58024190, Golden, CO, NREL. Sheehan, J., Camobreco, V., Duffield, J., Graboski, M. & Shapouri, H. (2000). An Overview of Biodiesel and Petroleum Diesel Life Cycles, Report No. NREL/TP-580-24772, National Renewable Energy Laboratory, Golden, Colorado, 2000. Sipilae, K., Kuoppala, E., Fagernae’s, L., et al. (1998). Characterization of biomass–based flash pyrolysis oils, Biomass Bioenergy, 14 (2): 103–13. Spath, P. L. & Dayton, D. C. (2003). Preliminary Screening – Technical and Economic Assessment of Synthesis Gas to Fuels and Chemicals with Emphasis on the Potential for Biomass-Derived Syngas, NREL Task N° BBB3.4210, NREL, Co USA. Spath, P. L. & Mann, M. K. (2001). Life Cycle Assessment of Hydrogen Production via Natural Gas Steam Reforming, NREL/TP-570-27637, NREL, Co USA. Spath, P. L. & Mann, M. K. (2004). Life Cycle Assessment of Renewable Hydrogen Production via Wind/Electrolysis, NREL/MP-560-35404, NREL, Co, USA. Stojic, D. L., Marceta, M. P., Sovilj, S. P. & Miljanic, S. S. (2003). Hydrogen generation from water electrolysis – possibilities of energy saving, Journal of Power Sources, 118: 315-319.

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Sun, Y. & Cheng, J. (2002). Hydrolysis of lignocellulosic materials for ethanol production: a review, Bioresource Technology, 83 (1): 1-11. Timokhin, B. V., Baransky, V. A., Eliseeva, G. D. (1999). Levulinic acid in organic synthesis, Russian Chemical Reviews, 68(1): 73-84. Tsai, W. T., Lin, C. C., Yeh, C. W. (2007). An analysis of biodiesel fuel from waste edible oil in Taiwan, Renewable and Sustainable Energy Reviews, 11, 838–857. Tuck, G., Glendining, M. J., Smith, P., House, J. I., Wattenbach, M. (2006). The potential distribution of bioenergy crops in Europe under present and future climate, Biomass and Bioenergy, vol. 30, Issue 3, March 2006, Pages 183-197. Vazquez, M., Oliva, M., Tellez-Luis, S. J. & Ramırez, J. A. (2007). Hydrolysis of sorghum straw using phosphoric acid: Evaluation of furfural production, Bioresource Technology, 98: 3053–3060. Wang, M., Lee, H. & Molburg, J., (2004). Allocation of energy use in petroleum refineries to petroleum products, International Journal of LCA, 9 (1), 34-44. Worldwatch Institute (2006), Biofuel for transport: global potential and implications for energy and agriculture, Prepared by Worldwatch Institute for the German Ministry of Food, Agriculture and Consumer Protection (BMELV) in coordination with the German Agency for Technical Cooperation (GTZ) and the German Agency of Renewable Resources (FNR), published by Earthscan, London. Wright, L. (2006), Worldwide commercial development of bioenergy with a focus on energy crop-based projects Biomass and Bioenergy, vol. 30, Issues 8-9, August-September 2006, Pages 706-714. Zhang, C., Peters, C. J. & de Swaan Arons, J. (2002). Thermodynamic modeling of biomass conversion processes, Fluid Phase Equilibria, 194-197, 805-815. Zhang, Q., Chang, J., Wang, T. & Xu, Y. (2007). Review of biomass pyrolysis oil properties and upgrading research, Energy Conversion and Management, 48; 87-92. Zhuang, X. L., Zhang, H. X. & Thang, J. J. (2001). Levoglucosan kinase involved in citric acid fermentation by Aspergillus niger CBX -209 using levoglucosan as sole carbon and energy source, Biomass and Bioenergy 21: 53-60.

In: Energy Recovery Editors: Edgard DuBois and Arthur Mercier

ISBN: 978-1-60741-065-2 © 2009 Nova Science Publishers, Inc.

Chapter 4

PINCH TECHNOLOGY FOR WASTE HEAT RECOVERY APPLICATIONS IN OIL INDUSTRY *

Mahmoud Bahy Noureldin

Consulting Services Department, Saudi Aramco, Dhahran, Saudi Arabia.

Part I: Pinch Technology for Energy Utilities Targeting and HEN Design Constructing the Composite Curves for Energy Utilties Targeting Targeting using Algebraic and Mathematical Programming Methods Constructing the Grand Composite Curve (GCC) Utility Selection Using Grand Composite Curve (GCC) Understanding and Applying Grand Composite Curve Heat Exchanger Network Synthesis using Pinch Design Method Part II: Heat Integration Applications in Oil Industry Oil and Gas Separation Process Crude Atmospheric Distillation Unit

INTRODUCTION In process industries the main source of waste heat is associated with hot utilities; that include furnaces, steam boilers, gas turbines and diesel engines. Energy efficiency optimization not only keeps operating cost under control and conserve depleted resources but also reduces GHG emissions. Oil and gas industry consists of very energy intensive processes. Oil and gas separation; crude atmospheric and vacuum distillation; Naphtha and Diesel hydro-treating and gas oil and Naphtha reforming, are only some examples. In the oil and gas business, energy cost is a major element in any facility operating cost. It usually comes before maintenance cost and sometimes even labor cost. Implementation of a

*

[email protected] Tel: 9663-873-6045, Fax 9663-873-0766

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decent level of energy integration in any industrial facility, most of the time, needs capital investment. This chapter addresses the problem of waste heat recovery via presenting an introduction to the pinch technology and two industrial applications of heat integration for waste heat recovery in oil and gas business. Pinch technology, after almost three decades of its emanation in the late seventies for a reason or another, is still the most widely used method for energy integration in oil industry. The chapter comes into two parts; the first part introduces some aspects of Pinch technology in brief. Pinch technology is now well documented in several literatures and the references 1 to 4 at the end of this chapter are only few main examples. In this part, I will show how we can use pinch technology for energy utility targeting, selection of utility mix and heat exchanger network synthesis using pinch design method [1, 2, 3 and 4]. The second part introduces two important applications for heat integration in oil industry [5]. The first application is showing the effect of heat integration on both energy consumption and GHG emission reduction in an oil-gas separation facility, and in the second application an evolutionary approach to crude distillation pre-heat train design is introduced.

TARGETING USING GRAPHICAL METHOD Any heat exchanger can be represented as a hot stream that is cooled by a cold stream and/or cold utility and a cold stream that is heated by a hot stream and/or hot utility with a specified minimum temperature approach between the hot and the cold called ∆Tmin. The process exhibited below in the graph shows the situation when the two streams do not have a chance of overlap that produce heat integration between the hot and the cold.

Figure 1. Two Non-Overlapping Streams

Pinch Technology for Waste Heat Recovery Applications in Oil Industry Feed

120

H

C

PROCESS

143

Product

HOT UTILITY

T

100

HEAT RECOVERY

80

Pinch

60

(MAT) 40

20

0

COLD UTILITY

0

10

20

30

40

50

60

H

Figure 2. Heat Integration between Hot and Cold

Moving the cold stream to the left on the enthalpy axis without changing its supply and target temperatures until we have a desired small vertical distance between the hot stream and the cold stream we obtain some overlap between the two streams that result in heat integration between the hot and the cold and less hot and cold utilities. As seen depicted in the graph below with shrinkage in the red and blue lines span. Now we want to represent all the hot streams in the process by one long hot stream and we will call this line the hot composite curve. We will also do the same thing with all the cold streams in the process. The next step will be drawing the two composite curves/lines on the same page in a Temperature (T)-Enthalpy diagram with two conditions: 1. The cold composite curve should be completely below the hot composite curve, and 2. The vertical distance between the two lines/curves in terms of temperature should be greater than or equal to a selected minimum approach temperature called global ∆Tmin The resulting graph is depicted below and known as thermal pinch diagram. Net Heat Sink Above the Pinch

Opportunity for heat recovery Net Heat Source Below the Pinch

Figure 3. Composite Curves

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Constructing the Composite Curves 1. Draw the hot composite curve and the cold composite curve via developing the following tables. 2. These tables list all the hot and cold streams temperatures in an ascending order with the cumulative enthalpy corresponding to the lowest hot temperature and lowest cold temperature respectively equal to zero. 3. In every temperature interval the cumulative hot load is calculated using the following formula H= FCp * (Tsupply – Ttarget) 4. In every temperature interval the cumulative cold load is calculated using the following formula H= FCp * (Ttarget – Tsupply) Hot streams temperature list T0=30 T1=70 T2=120 T3=170

Cumulative Enthalpy (H) H0=0.0 H1=800 H2=2300 H3=2800

Cold streams temperature list T0=20 T1=50 T2=90 T3=110

Cumulative Enthalpy (H) H0=0.0 H1=450 H2=2650 H3=3450

As we mentioned before the cold composite curve shall lie completely below the hot composite curve and this can be done via dragging the cold composite curve to the right on the enthalpy axis (H). This process shall stop at a vertical distance between the cold and the hot composite curve for a temperature equal to the minimum temperature approach selected earlier. Table 1. Data for Constructing Composite Curves Supply Temp (º C) 170 120 50 20

Target Temp. (º C) 70 30 90 110

FCp (kW/ ºC) 10 20 40 15

Pinch Technology for Waste Heat Recovery Applications in Oil Industry

Temperature (T)- Enthalpy (H) Diagram

T

Hot composite curve

Cold composite curve

30 20 Cold composite curve is not completely below the hot composite curve

H

Figure 4. Temperature (T) Enthalpy (H) Diagram 1

Temperature (T) - Enthalpy (H) Diagram Minimum Heating Utility T

Qh=300 kW

Hot composite curve

Cold composite curve

Minimum Temperature Approach 30 20 Qc=150 kW Minimum Cooling Utility

H

Figure 5. Temperature (T) Enthalpy (H) Diagram 2

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TARGETING USING ALGEBRAIC METHOD Information needed Given a unit with a list of hot streams to be cooled and cold streams to be heated

FCp (kW/ ºC) 10 5 10 5

Table 2. Data for Algebraic Method Supply Temp Target Temp. (º C) (º C) 520 330 380 300 300 550 320 380

1. Constructing Temperature Iinterval Diagram 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 1.8. 1.9.

Draw two temperature scales one for the hot streams and another for the cold streams Select a reasonable minimum temperature approach between the hot streams and the cold stream, (for instance, 10 ºC) Draw all the hot streams (in the table hot section) to be cooled according to the hot steam scale as arrows that start at the supply temperatures and end at the target temperatures Repeat step 1.3 for all cold streams in the cold section of the table Start at the highest temperature of any hot stream in the hot section and draw a horizontal line that spans across the two sections of the table, the hot and the cold. Draw horizontal lines again at the start and the end of any arrow representing the hot streams in the hot section of the table Repeat step 1.6 for any arrow representing cold stream in the cold section (at the start and the end of any arrow) Count the number of segments generated and number them starting at the highest temperature (they are called temperature intervals) Make sure that each temperature interval has now temperature value on both the hot temperature scale and cold temperature scale. The difference is the desired minimum temperature approach (for instance the 10 ºC used in this example) These procedures are depicted in the figure below

Note: This structure means that within any temperature interval it is thermodynamically feasible to transfer heat from the hot streams to cold streams. It is also feasible to transfer heat from a hot stream in an interval “x” to any cold stream which lies in an interval below. Note: The temperature symbol T* ‘(Figure 6) is the interval inlet temperature used later on constructing what is know as grand composite curve for selecting the suitable energy utility mix. To calculate T* we take the average interval inlet temperature of the hot and cold temperature scale.

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∆ T minimum = 10 K

T* 555 515

Interval

1

Hot Streams 560 H1

T

t

Cold Streams 550

520

510

390

380

2 385 3

H2

380

370

4

330

320

305

5

310

300

295

6

300

290

375 310

Hot Streams:H1; F1Cp1= 10 kW/K H2; F2Cp2= 5 kW/K

C2 C1

Cold Streams:C1; F1Cp1= 10 kW/K C2; F2Cp2= 5 kW/K

Figure 6. The Temperature Interval Diagram

2. Constructing Tables of Exchangeable Heat Loads and Cooling Capacities 2.1. Determining individual heating loads and cooling capacities of all process streams for all temperature intervals using this formula: Qnm = F1Cp1* (Ts-Te) in energy units (kW) Ts is the interval start temperature and Te is the interval end temperature “n” is stream number and “m” is the interval number Example 1: Interval # 1 in the hot section: The interval start temperature is 560 K The interval end temperature is 520 K Q11 (Q for stream #1 in interval #1)= F1Cp1*(560-520) Since there is no H1 stream in this interval, hence, F1Cp1=0.0 Q stream # 1(exchangeable load) in this interval = 0.0*(560-520) = zero Example 2: Interval # 2 in the hot section: The interval start temperature is 520 K The interval end temperature is 390 K The flow specific heat F1Cp1= 10 kW/K Then, Q stream #1(exchangeable load) in interval #1= 10*(520-390) = 1300 kW

148

Mahmoud Bahy Noureldin Example 3: Interval # 1 in the cold section: The interval start temperature is 550 K The interval end temperature is 520 K The flow specific heat of this cold stream is F1Cp1= 10 kW/K Then, Q stream #1(cooling capacity) in interval #1= 10*(560-520) = 400 kW Upon the completion of this step, 2.2 We can now obtain the collective loads (capacities) of the hot (cold) process streams. These collective loads (capacities) are calculated by summing up the individual loads of the hot process streams that pass through that interval and the collective cooling capacity of the cold streams within the same interval These calculations for the above problem is shown in the following tables Table 3. Exchangeable Loads for Process Hot Streams Intervals

Interval 1

Load of H1, kW

Load of H2, kW

0.0*(560-520)= 0.0

0.0*(560-520)= 0.0

Total Load, kW 0.0+0.0= 0.0

2

10*(520-390)= 1300 0.0*(520-390)= 0.0

1300+0.0= 1300

3

10*(390-380)= 100

0.0*(390-380)= 0.0

100+0.0= 100

4

10*(380-350)= 500

5*(380-330)= 250

500+250= 750

5

0.0*(330-310)= 0.0

5*(330-310)= 100

0.0+ 100= 100

6

0.0*(310-300)= 0.0

5*(310-300)= 50

0.0+50= 50

Table 4.Cooling Capacities for Process Cold Stream Intervals Interval 1

Capacity of C1, kW Capacity of C2, kW 10*(550-510)= 400

0.0*(550-510)= 0.0

Total Load, kW 400+0.0= 400

2

10*(510-380)= 1300 0.0*(510-380)= 0.0

1300+0= 1300

3

10*(380-370)= 100

100+50= 150

4

10*(370-320)=500

5*(370-320)= 250

500+250= 750

5

10*(320-300)= 200

0.0*(320-300)= 0.0

200+ 0.0= 200

6

0.0*(300-290)= 0.0

5*(380-370)= 50

0.0*(300-290)= 0.0

0.0+0.0= 0

Pinch Technology for Waste Heat Recovery Applications in Oil Industry Hot Load From Utility Source “Top Input”

Hot Load From Process Source “Left Input”

Cooling Capacity From Process Source

1

“ Right Output”

Residual Hot to Subsequent Interval “Bottom Output” from first interval

Heat Balance Top Input+ Left Input- Right Output = Bottom Output Figure 7. First Interval Heat Balance

Numerical Example of First Interval Heat Balance Hot Load From Utility Source “Top Input ”= 0.0 kW

Cooling Capacity From Process Source

Hot Load From Process Source “Left Input ”= 0.0 kW

1

“ Right Output ”=400 kW

Residual Hot to Subsequent Interval “Bottom Output ” from first interval

Heat Balance Top Input+ Left Input - Right Output = Bottom Output 0.0 + 0.0 - 400 = - 400 kW Figure 8. Numerical Example of First Interval Heat Balance

= - 400 kW

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Mahmoud Bahy Noureldin Subsequent Intervals Heat Balance

Hot Load From Above Interval “Top Input”

Hot Load From Process Source “Left Input”

Cooling Capacity From Process Source

N

“ Right Output”

Residual Hot to Subsequent Interval “Bottom Output”

Heat Balance Top Input+ Left Input- Right Output = Bottom Output Figure 9. Subsequent Intervals Heat Balance

Numerical Example for Subsequent Intervals Heat Balance For instance; Interval # 3 Hot Load From Above Interval “Top Input” = - 400

Hot Load From Process Source “Left Input”= 100

Cooling Capacity From Process Source “ Right Output”= 150

3

Residual Hot to Subsequent Interval “Bottom Output” = - 450

Heat Balance Top Input+ Left Input- Right Output = Bottom Output - 400 + 100 -150 = - 450 Figure 10. Numerical Example for Subsequent Heat Balance

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151

Constructing Thermal Cascade Diagrams This diagram is constructed using the total hot loads and cooling capacities obtained in the previous step for each temperature intervals.[1,2,3] The temperature intervals are drawn as “rectangular” with two inlets and two outlets. The inlet from the left is the total hot load available in this interval (for instance, 1300 kW in case of interval # 2) The inlet from above is the utility input load, in case of the first interval, or the input from interval above in case of second, third,……,N intervals. The output from the right is the total cooling capacity of this interval ( for instance, 1300 kW in case of interval #2). The output from the bottom is the difference between the total inputs and the cooling capacity of the interval The heat balance around each interval will be conducted as above.

The reader is encouraged to do the calaculation for interval number 2 and see that in interval number 2 the hot side input is equal to the cold side output and hence the final output of the interval will be the same as interval number one ,-400 energy unit. Upon the completion of the heat balance around each interval the following energy deficiency diagram will be produced.

Thermal Cascade Diagram (Un-Balanced) Note: During this step the input from Hot Utility to the first interval is equal to zero 0.0 0.0 1300 100 750

400

1 -400

2 - 400 3

1300 150

- 450 750

4 -450

100 50

200

5 - 550

0

6 - 500

Figure 11. Thermal Cascade Diagram (Un-Balanced)

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The maximum difference between the available hot loads and cooling capacities from the heat balances of these intervals is – 550 kW. This deficiency in heat will be supplied via an outside hot utility. This value will be the input (from the top of the first interval) and the same heat balance calculation conducted above will be repeated to produce the energy balanced thermal cascade diagram below. Balanced Thermal Cascade Diagram Minimum Heating Utility = 550 units

0.0 1300

400

1 150

2

1300

150

100 750

150

3 100

750

4 100

100 Pinch Point

50

200

5 0.0

0

6

Minimum Cooling Utility = 50 units

Figure 12. Thermal Cascade Diagram (Balanced)

With the completion of this step, the minimum heating utility and minimum cooling utility required are 550 kW and 50 kW respectively.

TARGETING USING MATHEMATICAL PROGRAMMING METHOD The algebraic method mentioned above can be generalized using optimization techniques. A very famous approach is the “transshipment model formulation as we mentioned in the first module. Mathematical programming at a Glance: Let us consider the following constrained problem; Min f(x) s.t. h(x) =0.0 g(x) ≤ 0.0 n

xє R Where: f(x) is the objective function h(x) = 0.0 is the set of (m) equations in variables x g(x) ≤ 0.0 is the set of r inequality constraints.

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In general the number of variables, n, will be greater than the number of equations, m, and the difference between (n-m) is commonly denoted as the number of degrees of freedom of the optimization problem. Any optimization problem can be represented in the above form. If we want to maximize a function this is equivalent to minimizing the negative of that function. Now for the heating and cooling utilities minimization problem, let us go back to our small problem solved algebraically before using pinch technology and use FCP for cold streams of 19 and 2 kW/ºC resepctively. The new problem can be easily solved using mathematical programming model. We write our objective function not only including heating and cooling utiltities loads but also including heating and colling utilitie costs in dollar value; formulate our model/constraints using the cascade approach; and then solving the optimization problem using any commercial software. •

Objective function Minimize (5* 10

−6

min −6 min Qheating + 9* 10 Qcooling )*3600*8000

•

Define the loads of heating and cooling utilities in each temperature interval and the surplus from each interval as we did before in the algebraic method through the development of temperature interval diagram, tables of exchangeable loads and un-balanced thermal cascade diagram. The model formulation is a heat balance around each temperature interval in the graph below as follows: min Q heating

0.0

1

760

r1

1300

2

2470

r2

100

3

210

r3

750

4

1050

r4

100

5

380

r5

50

6

0.0

min Q cooling

Figure 13. Thermal Cascade diagram for LP model min Qheating + 0.0-760 = r1

r1+1300-2470 = r2

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r2+100-210 = r3 r3+750-1050 = r4 r4+100-380 = r5 min

r5+50-0.0 = Qcooling Now using any optimization software: Model: Min = (3* 10

−6

min −6 min Qheating + 5* 10 Qcooling )*3600*8760; min

r1- Qheating = -760; r2-r1= -1170; r3-r2= -110; r4-r3= -300; r5-r4= -280; min Qcooling -r5= 50; min Qheating ≥ 0.0; min Qcooling ≥0.0;

r1≥0.0; r2≥0.0; r3≥0.0; r4≥0.0; r5≥0.0; The targets obtained graphically or algebraically or using mathematical programming, give an idea about the potential utility needs of any industrial facility. To get a better idea in terms of utility types needed, we need to construct a diagram known as the grand composite curve (GCC) and use it for defining the kind of utilities we need and how much we need. We can then utilize these findings to compare the current

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facility needs with the minimum utility needs calculated before to define the gap needed to be tackled. This step will help us evaluate potential savings upon the heat integration for certain process area.

CONSTRUCTING THE GRAND COMPOSITE CURVE (G.C.C) This curve will be drawn between T* calculated before during the temperature interval diagram construction which is the average temperature of hot and cold side each interval boundary and the corresponding surplus heat/enthalpy from each interval. These data are shown below for a generic balanced cascade diagram that can be developed for any application as shown before:

Data Required To Construct The G.C.C

T* (K)

Enthalpy ( kW) 2620 kW

555 T* (K)

515

1 1860 kW 2 690 kW

385 3

580 kW

375 4

280 kW

310 305

5

0.0 kW

Thermal Pinch

6 295

50 kW Enthalpy ( kW)

Figure 14. Data required to drawing Grand Composite Curve (G.C.C.)

Drawing these data as T* versus Enthalpy results in the following diagram that can be used to define different levels of utilities mix that can be used to satisfy the process heating utility requirement for instance, as shown below.

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Mahmoud Bahy Noureldin Grande Composite Curve (G.C.C) Should Be Drawn To Scale

Total hot utility required is equal to 2620 kW

T* (K) 600

Hu3 Hu2

500 Hu1 400

300

200

Enthalpy ( kW) 700

1400

2100

2800

Figure 15. Grand Composite Curve

Multiple Utility Targeting/Selection using Grand Composite Curve (GCC) Upon maximizing heat recovery in the heat exchanger network, those heating duties and cooling duties not serviced by heat recovery must be provided by external utilities. The most common utility is steam. It is usually available at several levels. High temperature heating duties require furnace flue gas or a hot oil circuit. Cold utilities might be refrigeration, cooling water, air cooling, furnace air preheating, boiler feed water preheating, or even steam generation at higher temperatures. Although the composite curves can be used to set energy targets, they are not a suitable tool for the selection of utilities. The grand composite curve drawn above is a more appropriate tool for understanding the interface between the process and the utility system. The GCC is obtained via drawing the problem table cascade as we shown earlier. The graph shown above is a typical GCC. It shows the heat flow through the process against temperature. It should be noted that the temperature plotted here is the shifted temperature T* and not the actual temperature. Hot streams are represented by ∆Tmin/2 colder and the cold streams ∆Tmin/2 hotter than they are in the streams problem definition. This method means that an allowance of ∆Tmin is already built into the graph between the hot and the cold for both process and utility streams. In other words, the actual hot utility

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temperature will be {T*(obtained from graph)+(∆Tmin/2)} and the actual cold utility temperature will be {T*(obtained from graph)-(∆Tmin/2)} The point of “zero” heat flow in the GCC is the pinch point. The open “jaws” at the top and the bottom represent QHmin and QCmin respectively. The grand composite curve (GCC) provides a convenient tool for setting the targets for the multiple utility levels of heating utilities as illustrated above. The graphs below further illustrate such capability for both heating and cooling utilities.

Figure 16. Grand Composite Curve for Utility Selection-1

The above figure 16(a) shows a situation where HP steam is used for heating and refrigeration is used for cooling the process. In order to reduce utilities cost, intermediate utilities MP steam and cooling water (CW) can be introduced. The second graph (b) shows the targets for all the utilities. The target for the MP steam is set via simply drawing a horizontal line at the MP steam temperature level starting from the vertical axis until it touches the GCC. The remaining heat duty required is then satisfied by the HP steam. This maximizes the MP steam consumption prior to the remaining heating duty be fulfilled by the HP steam and therefore minimizes the total utilities cost. Similar logic is followed below the pinch to maximize the use of the cooling water prior the use of the refrigeration. The points where the MP steam and CW levels touch the GCC are called utility pinches since these are caused by utility levels. The graph, 17(C) below, shows a different possibility of utility levels where furnace heating is used instead of HP steam. Considering that furnace

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heating is more expensive than MP steam, the use of the MP steam is first maximized. In the temperature range above the MP steam level, the heating duty has to be supplied by the furnace flue gas. The flue gas flowrate is set as shown in the graph via drawing a sloping line starting from the MP steam to theoretical flame temperature Ttft. If the process pinch temperature is above the flue gas corrosion temperature, the heat available from the flue gas between the MP steam and pinch temperature can be used for process heating. This will reduce the MP steam consumption. In summary the GCC is one of the basic tools used in pinch technology for the selection of appropriate utility levels and for targeting for a given set of multiple utility levels. The targeting involves setting appropriate loads for the various utility levels by maximizing cheaper utility loads and minimizing the loads on expensive utilities. Normally, we have a choice of many hot and cold utilities. Using the entropy balance equation for an open system we can conclude and generally recommend to use hot utilities at the lowest possible temperature while we generate it at the highest possible temperature to generate work. And for the cold utilities it is recommended to use it at the highest possible temperature. These recommendations are best explained using the grand composite curve.

(C)

T-tft

T*

MP

CW

Refrigeration

H Figure 17. Grand Composite Curve for Utility Selection-2

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Understanding and Applying the Grand Composite Curve The graph below shows that utility pinches are formed according to the number of utilities used. Each time a utility is used a “utility pinch” is created. It also shows that the GCC right noses, sometimes known as “pockets”, are areas of heat integration/energy recovery and hence does not need any external utilities. These right noses/pockets represent another possibility of heat integration among hot and cold process streams at a minimum approach temperature ∆T higher than that of the ∆Tmin. In such cases an ooprtunity for lost work recovery can exist on the expense of process to process heat integration. The GCC curve can be used by engineers to select the best match between the utility profile and process combined heat and power requirements profile. For instance, the steam system shown below in figure 19 needs to be integrated with the process demands to minimize low pressure steam flaring and high or medium pressures steam let downs. In addition, GCC can also helps in selecting steam header pressure levels and loads.

Figure 18. Understanding the Grand Composite Curve

Before closing this part of GCC and its use in selecting process requirements of utilities mix, I need to mention one important fact here about a rule in pinch technology that is generally accepted by many people in the industrial community. This rule says that: “do not use cold utility above the pinch” to avoid buying extra heating and cooling utiltities. This rule is absolutely true when we talk only about cost of heating

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utilities. However, in some situation we can have a trade off between heating utilities cost and benefits obtained from reducing power import or exporting power to the grid. With the aid of GCC we might find situations in which it is better from work generation point of view to use cold water above the pinch to produce steam and generate electricity, then using steam turbines exhaust for process heating than literally doing process to process integration using minimum approach temperature ∆T among hot and cold process streams much higher than the originally selected minimum approach temperature ∆T_min.

HP Boiler

HP Proc. #1

HP Process Condensate

Proc. #2

chemicals

MP Boiler

MP Vent Proc. #4

MP Process Condensate

Proc. #1 Vent

Deaerator

BFW Raw water Make-up Treatment Plant

LP Effluent Proc. #1 Process Condensate

Proc. #3

LP Process Condensate

Figure 19. Combined Heat and Power System Example

In summary, the Grand Composite Curve can be utilized to help optimize combined heat and power systems (CHP) shown in figure 19, select the load and return temperature of hot oil circuits, best integration between process and furnaces exhaust and process refrigeration levels as well as the synthesis of the multiple-cycle refrigeration systems [1,3].

HEAT EXCHANGERS NETWORK (HEN) SYNTHESIS Upon deciding on process reaction-separation system design, the optimization of major design variables such as reactor conversion, selectivity, recycle inert concentration, etc., minimization of process waste, minimization of utility waste via heat integration, process modifications for the sake of more heat integration has been explored and the plant utility system is configured, the material and energy balance can now be more or less fixed and hence the hot and cold streams which contribute to the heat exchanger network can be

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identified. The task is then becomes to design the heat exchanger network. In a little elaboration define the HEN streams matching, duty of each heat exchanger, inlet and outlet temperatures of each heat exchanger and with given overall heat transfer coeffiecients calculate the surface area of each heat exchanger. In the section below we will be defining the topology, duty and temperatures information of the HEN.

The Pinch Design Method The best design for an energy efficient heat exchange network will often result in a tradeoff between the equipment and operating cost. This is dependent on the choice of the DTmin for the process. The lower the DTmin chosen, the lower the energy costs, but conversely the higher the heat exchanger capital costs, as lower temperature driving forces in the network will result in the need for greater area. A large DTmin on the other hand will mean increased energy costs due to less overall heat recovery, but the required capital cost will be less. This is true most of the time but not all of the time. Designers may find that a very large DTmin might lead to high levels of heat duties available to be handled by process to process heat exchangers and process to utiltities ones resulting in high surface area needs and consequently both capital cost and energy cost will be increased. Any way early in this chapter we introduced how to set energy and area targets for the process before considering the HEN design because in the early days of pinch technology this technique was important to help make the trade-off between the HEN capital cost and operating cost quickly and without any heavy calculations. However, nowadays lot of software is available to make a preliminary synthesis of any large size HEN and estimate its capital cost directly and then automatically make the trade-off between the operating cost and the capital cost for the HEN in order to determine the optimal Dtmin for the HEN to be designed. Now let us first estimate the minimum number of units in a HEN (Nunits ) using the following formula:[1]

Nunits = S – 1 Where, S = number of streams (hot and cold) including utilities It is important to keep in mind that using the above formula for HEN minimum number of units calculation will only be giving an estimate and in some cases designers can come up with designs which exhibit less number of units due to some perfect matches in temperature range and load among hot and cold process streams. Having calculated an estimate to HEN minimum number of units we can then use the composite curves again used before to determine the energy targets for a given value of DTmin to determine another estimate to the minimum heat transfer area required to achieve the desired energy targets ahead of HEN design.

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To calculate the HEN estimated surface area from the composite curves, utility streams must be included with the process streams in the composite curves to obtain the balanced composite curves. The resulting balanced composite curves should have no residual demand for utilities. Then the balanced composite curves are divided into vertical enthalpy intervals to calculate the total minimum area targets assuming constant overall heat transfer coefficient and pure vertical counter current heat transfer using the famous formual in heat transfer Q=U*A*T_L.M.T.D [4]. Nowadays due to widespread use of computer programs for HEN automated design such area targeting calculation is not very beneficial any more in industry. Now we will start the design of the HEN using the well known pinch design method. A good initialization of this design is to assume that no individual heat exchanger will have a temperature difference smaller than ∆Tmin calculated from the targeting phase and there must be no heat transfer across the pinch by process to process heat transfer or/and inappropriate use of utilities. These rules are important for the HEN design to achieve the energy target, given that no individual exchanger should have a temperature difference smaller than ∆Tmin. To comply with these two guidelines the design problem needs to be divided at the pinch and using the grid diagram as shown in figure 20.

HEN DESIGN METHOD Four Streams Problem Example The graph below shows the stream data of a very simple HEN problem drawn on a grid diagram [1,2,3], where the pinch temperature is shown on both the hot and the cold sides using a minimum approach temperature, ∆T_min=10 ºC The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

330 ºC

H1=10

380 ºC 550 ºC 380 ºC

300 ºC 300 ºC

C1=20

320 ºC

C2=2 300 ºC

Figure 20. Grid Diagram for HEN Design

H2=5

QC_min = 50 kW

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The example given in this chapter for the illustration of the pinch design method for heat exchangers network design is very simple. Before going through the design of the network for this simple example in a step-by-step manner, some important rules in pinch design method need to be mentioned to enable the reader solve more complicated problems.

Start at the Pinch The pinch is the most constrained region of the problem. At the pinch, ∆Tmin exists between all the hot and cold streams. As a result, the number of feasible matches in this region is severely restricted. Quite often there are essential matches to be made. If such matches are not made, the result will be either using a temperature differences smaller than ∆Tmin or we have to buy more utilities due to heat transfer across the pinch. Since the pinch point divides the problem into two subproblems we are going to solve first the above pinch subproblem. We need to start at the pinch. There are some rules for matches to be both feasible and efficienct for the designated ∆T_min. With feasible we mean that the hot stream shall always have a ∆T_min over the matched cold stream. We will be elaborating more about feasibility later in this section. With efficienct we mean that a hot stream shall be matched above the pinch at the pinch in a way that he/she reaches its target temperature at the pinch. Hence, we reach the target heating utility calculated beforehand. Otherwise we will be needing to buy cold utility above the pinch!! Resulting in more heating and cooling utilities than the ones originally calculated during the energy targeting step. In order to be able to achive this requirement, during matching above the pinch we have to have enough number of cold streams above the pinch at the pinch to enable each hot stream above the pinch at the pinch reaches its pinch temperature via matching with a cold process stream. Otherwise we end up using cold utility above the pinch. If the number of hot stream above the pinch at the pinch is less than the number of cold streams in such situation we can consider splitting cold streams to enable us keep the following two rules intact above the pinch at the pinch. These rules of the inch design method will be further elaborated in this section. But for now we need to keep in mind the following two rules for streams matching above the pinch at the pinch: 1. Number of hot streams above the pinch at the pinch shall be less than or equal to number of cold streams; and 2. Upon matching hot and cold streams, hot stream CP(FCp) should be less than or equal to the cold stream matched with it (lighter in load) to avoid infeasiibilty in matching at some point and again to avoid using cold utility above the pinch at the pinch that results in consuming more than originally calculated energy target For streams matching below the pinch at the pinch the reverse is true: 3. Number of cold streams at the pinch shall be less than or equal to number of hot streams; and 4. Upon matching hot and cold streams, cold stream CP(FCp) should be less than or equal to the hot stream matched with it (lighter in load) to avoid infeasiibilty in

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Mahmoud Bahy Noureldin matching at some point and again to avoid using hot utility below the pinch at the pinch that results in consuming more than originally needed energy target

The CP(FCp) inequality for individual matches In summary for hot and cold streams matching above the pinch at the pinch; if a hot steam with CP(FCp) greater than a CP(FCp) of a cold stream, moving away from the pinch, the temperature difference must increase. At the pinch the match starts with a temperature difference equal to selected ∆Tmin. The relative slopes (1/FCp) of the temperature-enthalpy profiles of the two streams mean that the temperature differences become smaller while we are moving away from the pinch, which is infeasible. Hence we should not consider such match. On the other hand if we match this hot stream with another cold stream having a greater CP(FCp), in such case the relative slopes (1/FCp) of the temperature-enthalpy profiles now cause the temperature differences to become larger moving away from the pinch, which is feasible. Thus starting with ∆Tmin at the pinch, for temperature difference to increase while moving away from the pinch, we have to have this inequality achieved. CPH(FCpH) is less than or equal to CPC(FCpC) (Above the pinch for streams at the pinch) So a very simple explaination for you to remember: Above the pinch at the pinch the CP (FCp) of the hot stream shall be less than (lighter in load) or equal the cold stream matched with to enable it reach its pinch target tempetraturte without aid of cold utility above the pinch. Otherwise; the matching will be infeasible and to avoid such infeasibility we have to use cold utility above the pinch to enable the hot stream reach its pinch target temperature. Below the pinch at the pinch the rules are the opposite. If a cold stream is matched with a hot that has a smaller CP(FCp), in such case steeper slope(1/FCp) will result, then the temperature differences away from the pinch will become smaller which is infeasible. If the same cold stream is matched with a hot stream with a larger CP(FCp) different situation will arise. A less steep slope(1/FCp) will be obtained resulting in temperature differences that become larger away of the pinch which is feasible. Thus starting with ∆Tmin at the pinch, for temperature difference to increase while we are moving away from the pinch we have to have the following inequality achieved CPH(FCpH) is greater than or equal to CPC(FCpC) ( below the pinch for streams at the pinch) Again a very simple words for you to remember, below the pinch at the pinch the CP (FCp) of the cold stream shall be less than (lighter in load) or equal to the hot stream matched with to enable it reach its pinch target tempetraturte without aid of hot utility below the pinch. Otherwise; the matching will be infeasible and to avoid infeasibility we have to use hot utility below the pinch to enable the cold stream reach its pinch target temperature that results in both heating and cooling utilities increase than originally obtained in the energy targeting step.

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The CP(FCp) table Identification of the essential matches in the pinch region can be clarified using what we call CP(FCp) table [1,2,3]. In a CP(FCp) table as is shown in the graphs below, the CP(FCp) values of the hot and the cold streams at the pinch are listed in descending order. It is important to note here that the CP(FCp) inequality constraint applies only when a match is made between two streams that are both at the pinch. Away from the pinch, temperature differences increase and it is no longer essential to obey the CP(FCp) inequalities. In conclusion there are some essential matches at the pinch or the region of minimum choice (ROMC) that need to be made around the pinch or the ROMC. The next task is to design a network that exhibit minimum number of units. In other words we need to decide the matched heat loads which minimize the HEN number of units. The “tick-off” heuristic Once the matches around the pinch have been chosen to satisfy the criteria for minimum energy, the design should be continued in such a way to keep capital cost to a minimum. One important criterion in the capital cost is the number of units since more heat exchangers mean more skids; instrumentation, control; space; concrete and so on. Keeping the number of units at a minimum can be achieved using the “tick-off” heuristic [1,2,3]. To tick off a stream, individual units are made as large as possible. In other words the smaller of the two heat duties on the streams being matched shall be taken completely. Cooling water must not be used above the pinch to avoid unwarranted excessive use of utilities, therefore if there are hot streams above the pinch where the duties are not specified by pinch matches, additional process-to-process matches for more heat recovery shall be explored; even if it leads to more number of units in the network than the estimated minimum. Same logic is correct for heating utilities application below the pinch. Hot utilitites must not be used below the pinch to avoid unwarranted excessive use of utilities; both heating and cooling. Therefore if there are cold streams below the pinch where the duties are not specified by pinch matches, additional process-to-process matches for more heat recovery shall be identified; even if it leads to more number of units in the network than the estimated minimum.

Streams Splitting Stream splitting is sometimes necessary to overcome the CP(FCp) constraints mentioned above and/or to avoid using cold utility above the pinch or hot utility below the pinch. Cooling utilities should not be used above the pinch. It means that all hot streams must be cooled to pinch temperature by heat recovery. If we have a number of hot streams greater than the number of cold streams (Three hot streams and two cold streams for instance) a problem will then arise. Since regardless of the CP(FCp) values of the streams, there will be one of the hot streams that will not be cooled to pinch temperature without some violation of the ∆Tmin constraint. This problem can only be resolved by splitting a cold stream into two

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parallel branches. Thus in addition to the CP(FCp) criterion, there is a stream number criterion above the pinch such that Sh is less than or equal to Sc (above the pinch) Where: Sh = number of hot streams at the pinch Sc = number of cold streams at the pinch If there had been more cold streams than hot streams in the design above the pinch, this would not have created a problem, since hot utility can be used above the pinch. Let us now consider the sub-problem below the pinch. Here hot utility must not be used below the pinch. That’ means that all cold streams must be heated to pinch temperature by heat recovery. Again, for below the pinch, if we have the number of cold streams greater than the number of hot streams (3 cold streams and two hot streams, for instance) regardless of the CP(FCp) values, one of the cold streams can not be heated to pinch temperature without some violation of the ∆Tmin constraint. The problem can be solved by splitting a hot stream into two parallel branches. In such a case, each cold stream at the pinch will have a partner with which to match and be capable of heating it to pinch temperature. Thus there is also a stream number criterion below the pinch such that Sh is greater than or equal to Sc (below pinch) If we have more hot streams than cold streams below the pinch, this would not be a problem, since cold utility can be used below the pinch. It is instructive to mention here that it is not only the stream number that creates the need to split streams at the pinch but also the streams CP(FCp) inequality. Sometimes the CP(FCp) inequality criteria for the streams above the pinch “at the pinch” and below the pinch “at the pinch” can not be met at the pinch without a stream split. It is important to emphasize here the need to satisfy both criteria; the stream population and the CP(FCp) inequality. The number of hot streams above the pinch at the pinch needs to be less than or equal to the number of cold streams above the pinch at the pinch. If this is not the case then we need to split a cold stream to achieve this guideline. At the same time, the CP(FCp) of the hot stream above the pinch at the pinch shall be less than or equal to the CP(FCp) of the cold stream above the pinch at the pinch in order to be able to match them in a heat exchanger. If this is not the case the cold stream needs to be split into two.

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On the other hand, the number of cold streams below the pinch at the pinch needs to be smaller than or equal to the number of hot streams below the pinch at the pinch. If this is not the case then we need to split a hot stream to achieve this guideline. At the same time, the CP(FCp) of the hot stream below the pinch at the pinch shall be greater than or equal to the CP(FCp) of the cold stream below the pinch at the pinch in order to be able to match them in a heat exchanger. If this is not the case the cold stream needs to be split into two lighter loads cold streams. Before closing the pinch design method (PDM) general description with its rules and heuristics let us summarize the methodology in a step-by-step fasion. Briefly, the design procedure known as the pinch design method can be lumped as follows: • • •

• •

Divide the problem at the pinch into two separate sub-problems The design for the separate sub-problems is started at the region of minimum choice known as the pinch point and then moving away Temperature feasibility requires constraints on the CP(FCp) values to be satisfied for matches between streams “at the pinch” for the two problems above the pinch and below the pinch The loads on individual heat exchangers are determined using the tick-off heuristic to minimize the number of units Away from the pinch there is usually more freedom in the choice of matches. In this case the designer can choose on the basis of his/her process knowledge

Having described the pinch design methodology, let us solve the numerical example mentioned above. The pinch point has divided the problem into two sub-problems one above the pinch and another below the pinch. The division lies at 310 ºC on the hot streams side and 300 ºC on the cold streams side. The problem minimum approach temperature used is ∆T_min=10 ºC, and the minimum heating and cooling utiltities are 2876 kW and 50 kW, respectively. Using the minimum number of units formula mentioned before we can estimate that the network minum number of units shall be 5 units. Now we will synthesize a feasible HEN that realizes these two design objectives; minimum utiltities consumtion and minimum number of units. In such situations two pinch points will be arised and three sub-problems will be produced. One sub-problem above the 330 ºC-320 ºC near pinch point; one sub-problem below the 310 ºC-300 ºC pinch point and a third sub-problem in between the two pinch points. Handling situations like that is not difficult but less systematic than one pinch point situation [1]. The impact of such situation in the systematic design of the HEN is generating a HEN design that exhbits more number of units than the estimated minimum number of units HEN originally calculated without considering the near pinch point.

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It is instructive to mention here that the hot stream H1 and the cold stream C2 can be called “near” pinch streams and in some commercial software another near pinch vertical line will be drawn at 330 ºC-320 ºC as shown in figure 21 below. The Grid Diagram for the Step -By-Step HEN Design Near Pinch

Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

330 ºC

H1=10

380 ºC 550 ºC 380 ºC

300 ºC 300ºC

H2=5 C1=20

320 ºC

C2=2 300 ºC

QC_min = 50 kW

Figure 21. Grid Diagram with near pinch representation

We will start now the design above the pinch at the pinch. Since we have only one possibility for hot stream matching with cold stream at the pinch, we will check the CP(FCp) matching rule. Since stream H2 has CP(FCp) equal to 5 while the cold stream C1 has a CP(FCp) equal to 20, the CP(FCp) matching rule here rule is satisfied, we do not need to make any split and we can match the hot stream H2 and the cold stream C1 as shown in the graph below, figure 21. Upon matching H2-C1 in a heat exchanger uint we need to tick-off one of the streams to minimize the number of heat exchangers, hence we let the stream with lower heat load ticked-off. In this example it is the hot stream H2. The heat exchganger heat duty/load can now be calculated by simply using Q= FCp (Ts-Tt) formula. This load (Q) in this example is equal to 350 kW. The hot stream H2 has now been cooled down to its pinch target temperature of 310 ºC and the cold stream C1 has been heated up from its pinch temperature at 300 ºC to 317.5 ºC as shown in figure 22. It is also important to note here that in the pinch design method, away from the pinch there is no systematic technique to complete the HEN. The designer can use his/her common sense to complete the design to reach feasible network rendering the exact minimum utilities requirements with minimum number of units. It is clear in figure 22 above that the hot stream H1 and the cold stream C2 can also have a good match since hot stream H1 can be ticked-off completely, upon such matching with C2 resulting in a HEN with the desired estimated minimum number of units calculated earlier for the this example (5 units). The minimum approach temperature between the two streams is still not violated, greater than or equal to the specified ∆T_min=10 ºC, and is equal to 12.5 ºC.

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Pinch Technology for Waste Heat Recovery Applications in Oil Industry The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW 330 ºC

520 ºC

H1=10

Q= 350 kW

380 ºC 550 ºC

H2=5

300 ºC

317.5 ºC

380 ºC

300 ºC

C1=20

320 ºC

C2=2 300 ºC

QC_min = 50 kW

Figure 22. Grid Diagram for H2-C1 matching above the pinch at the pinch

The hot stream H1 has a heat load of 1900 kW and hence the process to process heat exchange between H1-C1 match shall be 1900 kW which is now the duty of this heat exchanger as shown in figure 23 below. The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

Q= 1900 kW

380 ºC 550 ºC 380 ºC

412.5 ºC

330 ºC

H1=10

Q= 350 kW

317.5 ºC

300 ºC

300 ºC

H2=5 C1=20

320 ºC

C2=2 300 ºC

QC_min = 50 kW

Figure 23. Grid Diagram for H1-C1 matching away from the pinch

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Now to calculate the cold stream C1 outlet temperature from H1-C1 heat exchanger we divide the load/duty of this hea exchanger, 1900 kW, on cold steam C1 CP(FCp) to get the raise in temperature of this stream upon matching it with the hot stream H1. Adding this raise in temperature to the the cold stream C1 inlet temperature to H1-C1 heat exchanger renders the cold stream C1 outlet temperature equal to 412.5 ºC. Upon the completion of defining the matches for the two hot streams H1 and H2 at the pinch cold stream C1, we need now to decide the amount of hot utility needed to allow the cold stream C1 reaches its target temperature, 550 ºC. The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

Q= 1900 kW

380 ºC Q= 2750 kW 550 ºC 412.5 ºC

380 ºC

330 ºC

H1=10

Q= 350 kW

317.5 ºC

300 ºC

H2=5

300 ºC

C1=20

320 ºC

C2=2 300 ºC

QC_min = 50 kW

Figure 24. Grid Diagram for C1 matching with hot utility away from the pinch Figure 24 above shows that; the hot utility unit has a heating load/duty of 2750 kW. Bear in mind that in order to reach the minimum heating utiltity target the cold stream C2 should not require more than 2870-2750 kW of heating utility. Otherwise, the network streams matching to realize the minimum heating utility target will not be adequate. To enable the cold stream C2 reaches its target temperature we need a hot utility heater with duty equal to 120 kW as shown in figure 25 below. Counting the number of units and adding the duties of the two utilities units, we see that the estimated minimum number of units, above the pinch, and minimum heating utiltity requirements are both satisfied. Before we move to the network design below the pinch, it is instructive to note that same result obtained in figure 25 above for the estimated minimum number of units and minimum heating utility equal to 2870 kW, may be obtained again using different HEN structure and process engineers are always encouraged to explore; synthesize and generate more than one HEN structure to study other process objectives satisfaction

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The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

Q= 1900 kW

330 ºC Q= 350 kW

380 ºC Q= 2750 kW 550 ºC 412.5 ºC

380 ºC

H1=10

317.5 ºC

Q= 120 kW

300 ºC

H2=5

300 ºC

C1=20

320 ºC

C2=2 QC_min = 50 kW

300 ºC

Figure 25. Grid Diagram for C2 matching with hot utility away from the pinch The Grid Diagram for the Step -By-Step HEN Design Pinch

CP (kW/ ºC)

310 ºC

QH_min = 2870 kW

520 ºC

Q= 1900 kW

380 ºC Q= 2750 kW 550 ºC 412.5 ºC

380 ºC

Q= 120 kW

330 ºC

H1=10 Q= 50 kW

Q= 350 kW

317.5 ºC

300 ºC

300 ºC

H2=5 C1=20

320 ºC

C2=2 300 ºC

QC_min = 50 kW

Figure 26. Grid Diagram for H2 matching with cold utility below the pinch Now after we completed the network above the pinch we go below the pinch. In this simple example we have only one hot steam H2 below the pinch. The hot stream H2 needs to be cooled down from 310 ºC to 300 ºC. The amount of load needed to be removed from this stream is equal to 50 kW. Therfore the amount of cooling utility required using cooler will be 50 kW, which is exactly the cooling utility target obtained earlier during the utilities targeting step. Combining the design above the pinch and below the pinch gives us the complete design of the heat exchanger network that satisfy our two objectives of minmum number of units and minimum utitilties consumption at ∆T_min equal to 10 ºC.

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Figure 26 above is showing such complete heat exchanger network that achieves the desired heat recovery level exhibited in minimum heating utility equal to 2870 kW and minimum cooling utility equal to 50 kW. It also consists of the estimated minimum number of units that equal to 5 units, two process to process heat exchangers and three utiltity service units (two heaters and one cooler). Having introduced the fundamentals of energy integration using pinch techniques, the second part will discuss two industrial applications. In these two application pinch technology has been used for targeting and utility selection. However, because of capital cost and end user preference its strict application has been sacrificed for the sake of easy to operate networks and less capital investment.

PART II. HEAT INTEGRATION APPLICATIONS IN OIL INDUSTRY Environmentally, there are essentially four phenomena associated with atmospheric emissions. They are urban smog, acid rain, ozone layer destruction and the greenhouse effect or global warming. The greenhouse gas effect or global warming phenomenon problem arises mainly from the burning of fossil fuels, and its main constituents are carbon dioxide and methane, of which methane has more than ten times the effect of carbon dioxide. The result is that global temperatures increase, leading to melting of the polar ice caps and thus rising sea levels, increased weather disruptions and changes to ocean currents. Atmospheric emissions are mainly formed as by-products of combustion processes. Such combustion processes, to date, remain to be the main source used for energy generation in our societies. In process industries, the essential sources of energy waste are associated with hot utilities. If the process industries require a furnace or a boiler to provide hot utility, then any excessive use of the hot utility will automatically produce excessive utility waste and consequently excessive generation of atmospheric emissions. Therefore, energy conservation is one important way of not only saving money and natural resources, but also protecting the environment via minimizing energy-based GHG emissions. Until late last century the preferred method of dealing with the atmospheric emissions were known to be taking the end-of-pipe approach. This approach is myopic view and usually an expensive one. This view does not tackle the problem at the source where solving could and indeed has proved in many cases to be easier and more cost effective. Nowadays, energy efficiency optimization techniques have become a major tool in NOx, SOx, CO and CO2 emissions minimization from combustion-based processes. Systematic methods and tools have been developed and are currently utilized to conserve energy; protect energy-based natural resources and last but not least to minimize energybased emissions and reduce the impact on the environment. A major concept in the energy efficiency optimization techniques is the concept of “Heat Integration” applied in Pinch Technology and others to enhance waste energy recovery in industrial processes. One way of using this concept is to look first in our plants to satisfy some of their thermal energy needs through letting the hot streams (sources) that are to be

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cooled help the cold streams (sinks) that are to be heated to enable both hot and cold process streams reach their heating and cooling targets. This approach of “Integration” of heat sources and sinks in industrial facilities reduces the need for external hot thermal energy utility that mostly come from fossil materials combustion processes. This methodology in turn attacks, at the source, the main contributor to the atmospheric emissions problem by reducing the heating utility requirement. In this paper a step-by-step modifications are applied to an actual oil and gas separation plant to minimize its environment-footprint via GHG emissions reduction using heat integration. The approach give the process owner the facility to select scheme based upon not only capital but also energy resources sustainability and environmental impact on the world.

Oil and Gas Separation Plant Process Description The un-stabilized crude oil is pumped to the stabilizer unit through a pipeline. The stabilizer is fed after removing some light ends. These light ends are combined with overheads from the column to the compression system. Light end gases from other stabilizers and low pressure and high pressure production traps, not shown in this graphs but by arrows only, are also directed to the gas compression section. The fractionation capability provides a well defined split between the light ends and the crude oil. This tight split ensures maximization of stabilized crude and minimization of crude oil quality loss (API Gravity). Heat input to the stabilizer bottom is provided through reboilers utilizing a heating oil media in a closed loop circulation system. A furnace is used to heat up the return cold heating oil. Light ends from the stabilizer overhead system is used as fuel for the heating oil furnace; flare pilot and purge gas process blanketing. Net light gases are then compressed, condensed and pumped to the natural gas liquid pipeline. The stabilized crude flowing from the bottom of the stabilizer column is cooled before going to its final destination partially by heat exchange with the stabilizer bottoms and completely in a final cooling stage using air coolers.

Heat Integration Application in Oil and Gas Separation Facility Pinch Analysis techniques have been applied taking into consideration legitimate process constraints such as safety and operability to evaluate the possibility of improving heat recovery in the process and consequently reducing energy-based GHG emissions. Major streams in the process have been listed below with its supply temperatures. In this chapter Pinch technology has been used for targeting purposes and HEN synthesis. However the problem solved in this chapter is considering HEN sophistication as the primary dominant objective and energy cost and/or GHG emissions reduction as the secondary one.

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Figure 1. Typical Oil and Gas Separation Process Flow Diagram

The design shown above is used as a base case to make comparisons among other design options regarding energy consumption, capital investment, expressed in terms of number of heat exchangers and its surface area, and the GHG emissions reductions. Heat integration role is not only to save energy consumption and its environmental impact but also it can save some capital investment. Table 1. Stream 1 2 3 4 5 6 7 8

Name De-gassing Tank Feed Desalter Feed Stabilizer Feed Stabilizer Btms to Reb Stb Btm Product Atm Comp 1st stg HP Comp 1st stg HP Comp 2nd stg

TS [F] 90.0 109.8 157.5 165.0 195.3 265.2 191.0 210.9

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In the early days of its application in process plants; people were triggered with its capability in such direction, hence many plants have been reporting successful applications. In many other cases realizing all possible potential in energy consumption collided with excessive needs for capital investment. In case of the oil and gas separation presented in this paper, Figure 2 below shows that for hot and cold streams minimum approach temperature of 17 ºF, the one used in the base case design, minimum heating and minimum cooling utilities consumption due to heat integration are 615 and 24 MM Btu/h respectively. Heating oil media is used to render the desired heating and air is used for the desired cooling. Realizing such results needs significant capital investment and the decision makers are always looking for scenarios to select among it, where they get highest possible impact on energy consumption and GHG emissions reduction with minimum capital investment. A furnace with about 90 percent efficiency is used to heat up the return hot oil and electricity is taken from the grid to supply for air coolers and others. This furnace will produce about 300 kg of CO2 per hour for each megawatt of heat delivered to the heating oil media used in the process [1]. It is important to note here that even though the hot oil system used in the process can better match the process requirements for heating purposes compared with steam due to the slope of the heat deficit curve, as per the shown grand composite curve in Figure 3.In early design stages it might be much better to consider cogeneration application. Considering a CHP combined heat and power system in oil and gas separation processes can produce the desired electricity for the plant and the low pressure steam produced as a by-product of the cogeneration system in process heating purposes. In this chapter the HEN design is only considered and not the whole utilities system. According to pinch technology heuristics for defining the minimum number of units, we have 8 streams above the pinch and 3 streams below the pinch, eleven heat exchangers will be required. This number can increase and form a very complex network in order to satisfy the desired energy targets for the oil and gas separation system while the base case design network is using only seven heat exchangers. Enabling the process owners to exercise their best budget allocation in reducing energy consumption and GHG emissions by a little defined increase in the capital investment is shown in the graphs below. In figure 4 below only one heat exchanger has been added to the base case design to integrate the discharge of the first stage compressor with a branch from the crude stream before the desalter. In addition to the relocation of the stabilizer bottoms feed heat exchanger to make the matching happens before the desalter instead of having it after the desalter. This change requires an increase in the reboiler duty from the base case design of 197 MM Btu/h to 272 MM Btu/h Such modifications in the base case design due to better integration results in about 85.8 MM Btu/h savings in heating oil duty and about 180 T/d reductions in GHG emissions and of-course savings air cooling duties savings too. The capital investment is exhibited in the extra heat exchangers surface area increase shown in graph below.

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Figure 2. Oil and Gas Separation Utilities Targeting

Figure 3. Oil and Gas Separation GCC

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Figure 4. Oil and Gas Separation Design Option # 1

Pushing the envelope for more reduction in both energy consumption and GHG emissions lead us to design option # 2 shown in figure 5 below. In this design option two heat exchangers have been added to the base case design to integrate the discharge of the first and third stage compressors with a branch from the crude stream before the desalter. Again the relocation of the stabilizer bottoms feed heat exchanger has been also implemented and extra duty for the reboiler has been added. In this design option more waste heat has been recovered and consequently more GHG emissions have been reduced as follows; about 124 MM Btu/h savings in heating oil duty and about 260 T/d reductions in GHG emissions and of-course again more savings in air cooling duties. Further push towards more reduction in heating oil duty and GHG emissions through design modification produces design options three, four and five shown in Figures 6, 7 and 8. In these three new design options, three heat exchangers have been added to the base case design but with different surface area requirements as shown in the three figures below. The reduction in heating oil duties are 128.6 MM Btu/h, 139.4 MM Btu/h and 142.9 MM Btu/h; respectively and the reduction in GHG emissions due to such reduction in heating oil duties are 270 t/d, 292 t/d and 300 t/d; respectively too. It is instructive to note here that the reduction in both heating oil duties and GHG emissions with the increase in number of heat exchanger and associated surface area is happening with steeper change. About 60 % of the reduction in GHG emissions can be attained with 50 % of extra heat exchangers surface area.

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Figure 5. Oil and Gas Separation Design Option # 2

Figure 6. Oil and Gas Separation Design Option # 3

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Figure 7. Oil and Gas Separation Design Option # 4

Figure 8. Oil and Gas Separation Design Option # 5

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Heat Integration in Crude Atmospheric Distillation Unit In crude atmospheric distillation units, feed get separated to different cuts according to difference in boiling points. Crude feed get heated up from the ambient temperature to the desalting temperature, normally between 126 and 140 ºC. After desalting operation that reduces the crude temperature between 3 to 6 ºC, crude is fed to the pre-flash drum or sometimes even tower to remove some of the light hydrocarbons before the crude goes to the crude furnace. Petroleum Gas & Light Naphtha Distillation tower

~40°C

~25-175°C

~150-260°C Fired heater

~235-360°C ~350370°C

Heavy Naphtha

Crude oil feed

Kerosene

Light Gas Oil (LGO)

~330-380°C Heavy Gas Oil (HGO)

Atmospheric residue Preheated Crude oil ~250-280°C

Figure 9. Crude Atmospheric Distillation Unit

As shown in the generic crude atmospheric distillation; Figure 9 above the products from the crude tower and circulating pump-around that are used as tower inter-coolers are used to aid the products in heating the incoming crude. The incoming crude then is fed to the heater to raise its temperature to the desired flash zone temperature in the atmospheric distillation column. It is always of high importance in the design of this unit to integrate the cold stream represented by the crude feed stream and products as well as pump-arounds to reduce the heat load the crude heater as much as possible. In this chapter, a real industrial application is introduced and discussed. Table 2 below, shows data extracted from plant process flow diagrams for the crude as a cold stream and other hot streams. The cold stream is segmented into several streams using its simulation heating curve to avoid in-accuracy for assuming constant specific heat along long temperature range. The same is also practiced for some hot streams as shown in the table, using its simulation cooling curves.

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Table 2.

Stream Name PreDesalter PreFlash AfterFlash TPA Kero LDO Prod IPA HDO Prod BPA RCO

TS

TT

[C] 37.46 84.16 90.42 125 158.9 188 225.1 265 160.5 185.1 105 61 241.2 103.3 253.9 318.2 198.4 327.5 346.4 259.7 169.9

[C] 84.16 90.42 126.7 158.9 193 225.1 265 378 75 105 61 40 103.3 60 138 198.4 60 225 259.7 169.9 80

DH [MM kCal/hr] 16.02 2.27 13.74 13.4833 14.216 14.8257 16.64 64.52 16.02 2.27 1.12 0.5 13.74 3.68 13.43 4.06 3.89 10.35 16.65 15.52 13.23

CP [MM kCal/C] 0.343041 0.36262 0.378721 0.397738 0.41689 0.399614 0.417043 0.570974 0.187369 2.83E-02 2.55E-02 2.38E-02 9.96E-02 8.50E-02 0.115876 3.39E-02 2.81E-02 0.100976 0.192042 0.172829 0.147164

The first step in applying pinch technology is to find for a reasonable minimum approach temperature the minimum heating utility and minimum cooling utilities required for this crude unit. These targets are shown in Figure 10. The heating utility which is our main focus in this application is about 48 MM Kcal/h Using pinch design method (PDM) to synthesis the crude pre-heat train, to reach desired level of waste heat recovery and to minimize the heating load of the crude heater results in the network below in Figure 11. The network exhibits three splits in the cold crude stream. First split happens before the crude desalter, the second after the desalter and before the flash drum and the third after the flash drum up to the crude heater. As you notice both heating and cooling utilities are considered being of the same important. In most cases in oil refining heating utility is more expensive than cooling water. Therefore, many designer put more emphasis on saving in heating utility since it also reduce emissions than saving on the cold side. Another very important objective in designing new pre-heat train in crude distillation unit is the number of units of the heat exchangers, less sophisticated configuration and the easiness of heat exchanger network operation and maintenance. This need pushes the plant designers to the extreme in considering the easiness of operation to the extent that they design networks that do not give enough attention to decent level of waste heat recovery and GHG emissions reduction compared with their emphasis on capital investment, maintenance and operation of the network.

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Figure 10. Crude Atmospheric Distillation Unit Utilities Targeting

This approach is demonstrated here in the schematic pre-heat train design shown below in Figure 12 for the same industrial application in hand. The schematic network shown is only used for topology comparision. The design exhibits less number of units, no split at all, but much less crude temperature ,265 ºC before the crude heater. This design means that the approach advocating the easiness of operation and minimum number of units results in more energy consumption in the crude heater and consequently more GHG emissions. It is important to note here that maintenance and easiness of operation of heat exchanger networks in crude oil refining facilities are very legitimate issues. However, it needs to be handled with care and at the end a balanced picture and right trade-off based upon economic should prevail over the argument of we did not do designs like this before, or our operators are not trained to operate such sophisticated network or even we do prefer this one since it has no splits and less potential for fouling and cleaning.

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Pinch Technology for Waste Heat Recovery Applications in Oil Industry RCO 150.7 C TPA 160.5

37.5 C

IPA 157.9

To Tower

LDO 150.9 C

0.3

133.4 C

0.46

133.8 C 133.9 C

Desalter

136.8 C

0.24

0.38

207 C

0.3

204.2 C

205.5 C

134.5 C

RCO Prod. 80 C

LDO Prod. 60 C

150.7 C

205.1 C HDO 217.9 C

To Colm. 75 C

HDO 217 C

HDO Prod. 60 C

LOD Prod. 241.2 C

IPA 217.4 C

0.4

199.2 C

Flash

0.32

322.8 C

0.2 308.8 C 0.08

378 C

292.8 C

292.2 C 238.5 C

0.32 HDO 327.5 C

HDO 318.2 C

RCO 346.4 C

IPA 253.9 C

Figure 11. Crude Atmospheric Distillation Unit HEN (I)

TPA 141.2C

Toairandwatercoolers

160.5C

138.8C

137.1C

169.9C

159C

198.4C

196C

206C

BPA

RCO

. . E-5 37.5C

84.5C

90.8C

E-6

253.9C E-1

E-2

185.1C

KERO

327.5C

E-7

127.0C

E-3

V04-V6 \Desalter

E-4

241.2C

259.9C

199.6C

318.2C

E-8 IPA-b

346.4C

225.5C E-9

HDO-2 225.7C

253.9C

265.4C

LDO

IPA

Figure 12. Crude Atmospheric Distillation Unit HEN (II)

378C

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Kero

TPA 160.5C

241.2C

185.1C

IPA-a 253.9C

84.5C

37.45C

127C

90.8C

E-1

E-2

75C

75C

138.8C

E-3

E-4

103.3C

105C

137.1C

134.2C

60C

Desalter 61C

40C

FlashVap IPA-b 253.9C 193.8C E-5 137.1C

145C

BPA

199.4C HDO

141.2C 80C

378C

276.6C

FlashDrum E-8

200C E-6

327.5C

318.2C

183.9C E-7

193.7C

RCO 225.7C

186.3C 60C

E-9

346.4C

275.4C

275.8C

Furnace

220C RCO

Figure 13. Crude Atmospheric Distillation Unit HEN (III)

The third network shown in figure 13 set the right compromise to some facilities. It is designed differently than the first network since it does not use the pinch design method. However, some sense of systematic technique has been also used here. This network design evolves from the simplest design desired by most of the process owners and plant operators. It has less number of units, no splits, less possibility of fouling and frequent cleaning needs, easy to operate and more importantly less area and capital cost. The pre-heat train in Figure 13 kept the simple design before the desalter almost as it is and focused only on the heating utility minimization. It tried to push the temperature before the crude heater from 265 ºC in the simple design to about 276 ºC in the new design via better heat recovery in the area after the pre-flash drum only. A systematic technique can be used for that purpose via enumerating all matches possibilities between the crude stream, after the pre-flash drum, and all hot streams available at temperatures higher than its supply temperature. Simulating these possibilities only and then ranking them based upon the impact on the heating utilities requirement but with only one split in the crude stream after the preflash drum to avoid increasing fouling, will conclude this step and move the approach to the second step. The second step is to reconcile the selection of the new matches after the preflash drum with that before it. The possibilities that can arise can also be ranked based upon the level of simplicity in it. The point that we are trying to make here in this crude unit pre-heat train design approach is that instead of designing the heat exchanger network using pinch design method to get the best possible waste heat recovery scheme and try an ad hoc approach to simplify the network,

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we can start from the simplest possible straight line network shown in this chapter and evolve from it systematically to reach to better networks from waste heat recovery point of view and of-course GHG emissions reduction while keeping the easy to operate, clean to maintain and capital cost objectives satisfied. The details of this new approach and its step-by-step implementation will be published latter elsewhere.

CONCLUSION Pinch technology as a new systematic method for advanced waste heat recovery and heat integration in industrial facilities emanated in the early seventies during the first oil crisis is still nowadays the most widely used technique for energy integration in oil industry. It has been successfully used to systematically address the problems of energy efficiency optimization and the reduction of energy-based un-desired emissions. Systematic waste heat recovery in oil and gas industry is very beneficial to plant operating cost reduction. Aggressive waste heat recovery is an essential approach for inprocess GHG emissions avoidance. GHG and other energy-based undesired by-products atmospheric emissions, produced during oil and gas separation processes and crude oil distillation can be reduced significantly through proper application of heat integration concepts. Every megawatt of heating utilities obtained from process boilers and/or furnaces that can be saved through efficient waste heat recovery system design and operation means less greenhouse gas and other harmful NOx and Sox emissions. Improved heat recovery systems designs while can be attained systematically using Pinch Technology, it is important to consider it in a step-by-step approach especially for the heat exchangers network grassroots design modifications and existing plants retrofit to enable the decision makers selects the right scenario that best fit his/her capital investment budget.

REFERENCES Douglas, J. (1985). Conceptual Design of Chemical Processes, McGraw-Hill, Inc. EL-Halwagi, M. (1996). Pollution Prevention Process Integration, Academic Press, Linnhoff, B. (1993). Pinch Analysis-a state-of-the-art, Trans. IChemE, 71(A5), 503-522 Noureldin, M. B. & Hasan, A. K. (2006). Global energy targets and optimal operating conditions for waste energy recovery in Bisphenol-A plant, Applied Thermal Engineering 26, 374-381. Noureldin, M. B. & Swan, J. E. (2004). Computer-Aided design software for energy optimization through interval constraint logic propagation, Proceeding of MDP-8, Cairo University Conference on Mechanical Design and Production, Cairo, Egypt, January. Noureldin, M. B. (2003). TEM_icons™ 1.2 User’s manual, Report, Department of Materials and Process Engineering, University of Waikato, Hamilton, New Zealand. Noureldin, M. B., Aseeri, A. S. & Al Qahtani, A. H. (2006). Systematic in-Process Modification Approach for Enhanced Waste Energy Recovery in Gas Plants, AIChE Spring Meeting Orlando, Florida, April 23-27.Smith, R. (1996). Chemical Process Design , McGraw-Hill, Inc.

In: Energy Recovery Editors: Edgard DuBois and Arthur Mercier

ISBN: 978-1-60741-065-2 © 2009 Nova Science Publishers, Inc.

Chapter 5

TREATMENT OF SECONDARY SLUDGE FOR ENERGY RECOVERY Chunbao (Charles) Xu* and Jody Lancaster Department of Chemical Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, Ont., Canada P7B 5E1

ABSTRACT Primary and secondary sludges are produced as a result of primary and secondary wastewater treatment in municipal wastewater plant or pulp and paper mills. Sludge disposal has become a worldwide problem for many reasons including rapidly shrinking landfill space, increased environmental awareness, more stringent environmental standards governing the disposal of sludge, and dewatering challenges. Unlike the primary sludge, the secondary sludge as byproduct of the biological treatment is far more difficult to dewater and to be disposed. Secondary sludge waste management issues are a continuing challenge. This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. In this chapter, we have overviewed a variety of secondary sludge post treatment methods for energy recovery, including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. A critical comparison between these methods is presented with respect to their net energy efficiencies. The advantages and drawbacks of each treatment option are also highlighted in this chapter.

1. INTRODUCTION Primary and secondary sludges are produced as a result of primary and secondary wastewater treatment in municipal or industrial wastewater plants, e.g., pulp and paper mills. For instance, about 40-50 kg of sludge (dry)is generated in the production of 1 tonne of paper at a paper mill in North America (Joyce et al., 1979), and of that approximately 70%is primary sludge and 30% secondary sludge (Elliot and Mahmood, 2007). The primary sludge *

E-mail: [email protected]

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can be relatively easily dewatered for disposal. The secondary sludge consists predominantly of excess biomass produced during the biological process (Ramalho, 1983), and about half of the incoming organic pollution load is converted into secondary sludge, containing 0.5 to 2% solids (Winkler, 1993). Compared with the primary sludge, the secondary sludge is far more difficult to dewater. The management of municipal and industrial wastewater sludges has been a long-standing challenge for many utilities. For example, Canadian municipalities spend $12–15 billion annually for sewage sludge treatment (Buberoglu and Duguay, 2004). Normally, sludges are disposed by landfilling and incineration (Reid, 1998), which have, however, suffered from their inherent drawback of poor economics due to many reasons including (1) the high cost associated with dewatering the sludge to 20-40% solids or higher so as to meet the requirements of landfilling or incineration, and (2) the significant energy loss in evaporating the sludgecontaining water in incineration or combustion of the sludges in a recovery boiler. The sludge disposal/management costs can be as high as 60% of the total wastewater treatment plant operating costs (Canales et al., 1994). In recent years, due to rapidly shrinking landfill space and the secondary pollution issues associated with the conventional sludge disposal approaches as well as the increasingly stringent environmental regulations, the disposal of sludges continues to be one of the major challenges for the municipal wastewater plants and most pulp and paper mills (Mahmood and Elliott, 2006). This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. For instance, the percentage of pulp/paper sludges disposed by landfills has constantly decreased in Europe in recent years, as shown in Fig. 1, dropping 40% in 1990 to 20% in 2002. In the meantime, the percentage of pulp/paper sludge used as a raw material in other industries and other applications (e.g., agriculture as soil improvers, in road construction, land reconstruction) and for energy recovery has steadily increased.

Figure 1. Disposal methods for the pulp and paper residues in Europe (adapted from Monte et al., 2008 and CEPI, 2004)

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Comparing with other typical industrial sludges containing 16-35% of total dry solids (Oral et al., 2005; Rato Nunes, et al., 2008), the original secondary sludges from municipal wastewater treatment plant or a pulp and paper mill usually contains a much higher ratio of water (98-99%). A comparison of municipal and pulp and paper secondary sludge characteristics is presented in Table 1. Similarities exist between municipal and pulp and paper waste activated sludge, which would suggest that technologies used in the municipal wastewater sector could be transferred into the pulp and paper industry. General processes and technologies of sludge reduction technologies through process changes (e.g. operational control, and return activated sludge treatment) or through post-treatment (e.g., incineration, carbonization gasification, pyrolysis, supercritical water oxidation (SCWO) and aerobic/anaerobic digestion, etc.) have been recently reviewed by Mahmood & Elliot (2006). While changing/optimizing the sludge producing process would certainly reduce the amount of secondary sludge generation and thus alleviate the issues of sludge waste management, secondary sludge post-treatment technologies and in particular those aimed at energy recovery are the focus of this chapter. Table 1. Comparison of municipal and pulp and paper activated sludge (modified from Elliott and Mahmood, 2007)

Total dry solids (TS) (%) Volatile solids (%TS) N (%TS) P (%TS) Fe (g/kg_TS) PH Heating value (MJ/kg_TS)

Municipal 0.8-1.2 59-68 2.4-5.0 0.5-0.7 0 6.5-8.0 19-23

Pulp/Paper 1.0-2.0 65-97 3.3-7.7 0.5-2.8 0.33-2.2 6.0-7.6 22-25

To evaluate different post-treatment options and in order to provide a means of comparison, it is advantageous to compare the energy efficiency for each option if possible. A definition of net energy efficiency may be outlined as follows (Xu and Lancaster, 2008). The net energy efficiency or “Energy Output/Input Ratio” can be defined as the ratio of energy content of the objective products to the energy input to produce it, as show in Eq. (1). For simplification of the discussion, several assumptions may be adopted: (1) Since the feedstock used is waste biomass or waste sludge, it can be considered as the feed of “ZERO” energy value, (2) the heat loss of the reactor or process is negligibly small assuming well insulation and (3) the energy consumption by other auxiliary operations (e.g., feedstock preparation and feeding, products separation and recovery, etc.) may be neglected. From the above assumptions, for many hydrothermal treatment processes for the treatment of sludge, the energy input may be approximated by the energy required to dewater/thicken the sludge from its original TS content (e.g. 1-2% for secondary pulp/paper sludge) to a suitable TS content for the process use (e.g 25% TS or above), and to heat the dewatered sludge from room temperature (Trm) to the specified reaction temperature (T).

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Energy Output/Input Ratio =

∑ (HHV of the product) × (mass of the product) (Energy Input)

(1)

The approximate energy efficiency of each process can be estimated by the equation above, while depending on different requirements and characteristics of each process, the energy input calculation may differ method to method and may be difficult to determine due to shortage of experimental data reported. The objective of this chapter is to provide an overview of different types of posttreatment methods of secondary sludge, i.e., waste activated sludge (WAS), for energy recovery. Emphasis is put on the discussion on the energy efficiency for each process, while advantages and disadvantages of each process are also highlighted. An outline of the many post-treatment options and their primary energy products can be summarized in Figure 2. A description of each treatment method including incineration, gasification, pyrolysis, direct liquefaction, super critical water oxidation and anaerobic digestion follows.

Figure 2. Outline of treatment options of secondary sludge for energy production

2. SECONDARY SLUDGE TREATMENT METHODS Secondary sludge can be treated by employing a variety of post-treatment technologies such as heat treatment, chemical oxidation and sludge digestion whose processes have been overviewed recently by Mahmood & Elliot (2006).

2.1. Incineration Incineration technology is the controlled combustion of waste with the recovery of heat to produce steam that in turn produces power through steam turbines (Kumar, 2000). A general flow diagram of the incineration process is depicted in Figure 3. It shows that the sludge is fed into the boiler, which could be rotary kiln, fixed bed furnace or, common in the

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paper industry, a fluidized-bed incinerator (Latva-Somppi et al., 1997). The incinerator yields products of steam and byproducts of ash and flue gas. Ash can be disposed directly into the nearest landfill or it can be used as the raw materials of light-weight aggregate and constructional brick in the building industry (Liaw et al., 1998; Monte et al., 2008). The flue gas requires treatment through air pollution control before discharge through the stack. However, specifically designed fluidized-bed combustors produce fewer pollutants through the flue gas (Kumar, 2000). For power generation the steam is directed through steam turbines, which work to produce power through the electric generator. Alternatively steam can be used locally for process steam reducing the mill’s dependence on costly fossil fuels for steam production (Monte et al., 2008). Typical fluidized bed operating temperature is between 700-900oC (Latva-Somppi et al., 1997). While depending on specific waste regulations in Europe 850oC must be achieved for at least 2 seconds, and if hazardous waste with a content of more than 1% of halogenated organic substances, the temperature is raised to 1100oC for 2 seconds in order to reduce the formation of the toxic compounds such as polychlorinated dibenzodioxins (PCDDs) (Monte et al., 2008). Efficient heat and mass transfer in the fluidized bed enables the endothermic fuel drying and devolatilization to occur simultaneously with exothermic combustion of char and volatiles (Latva-Somppi et al., 1997). Incineration of residues (both rejects and sludge), combined with power and steam generation, is one of the most commonly applied disposal methods in Europe (Monte et al., 2008). Sludge incineration is widely practiced on a full-scale basis in many highly populated urban areas such as in Japan and Germany (Stark et al., 2006). A recent review by Monte et al. (2008) cited eleven European pulp mills which burn some portion of pulp sludge in combination with other biomass. Oral et al. (2005a/b) described a three-stage retrofit of an incinerator in the Czech Republic and concluded that the thermal treatment through incineration of sludge for energy recovery is favorable both economically and environmentally.

Figure 3. General flow diagram of incineration (modified from Kumar, 2000)

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In a sludge incineration process, water in the sludge is completely evaporated and the organic matter in the sludge is effectively oxidized at high temperatures to CO2 and H2O, as shown in the following two reactions: Evaporation: Oxidation and combustion:

H2O (l) → H2O (g) sludge solids/organics + O2 → CO2 + H2O + ash + heat

Since the water evaporation reaction is highly endothermic, in order to sustain the combustion for sludge with a low TS content, dewatering of the original sludge must be conducted or additional fuels (bark, wood waste and oil, etc.) shall be added (Monte et al., 2008). Monte et al. (2008) illustrated that self-supporting incineration (combustion) can be attained for feedstock containing approximately > 25% combustible/organic content and an ash content of 0-60%, where additional fuels are not necessary. Evaporation, oxidation and combustion occur simultaneously. The energy required for evaporation can be estimated using an equation from Kim and Parker (2008):

Qdrying = Mws ×W × [(Cp,water × ΔT) + ΔHvap] + [Mws × (1-W)] × Cp,sludge × ΔT

(2)

Where Mws is unit mass of wet sludge using a basis of 1kg, W is the water fraction in sludge, ΔHvap is latent heat for vaporization of water (2090 kJ/kg), Cp,water is heat capacity of water (4.186 kJ/kg/oC), Cp,sludge is heat capacity of solids in sludge (1.95 kJ/kg/oC) and ΔT is temperature difference between initial temperature of 25oC and the temperature of drying of 105oC. This results in an approximate energy input for drying of 2198 kJ/kg. Further energy input is required to raise the temperature of the sludge from drying temperature of 105oC to an average reactor temperature of 800oC. The further energy input can be estimated at 2753 kJ per kg of the sludge with 10% total solids (TS). An estimated energy consumption of the evaporation energy input plus the energy required for heating the feedstock to the reactor temperature is thus approximately 5000 kJ/kg. Approximately 30% of the solids remain in the ash (Fytili and Zabaniotou, 2008), therefore 70% is combusted. Energy output of the incinerator may be estimated given the steam generation data for the incinerator.

2.2. Pyrolysis Pyrolysis is a thermal decomposition process in the absent of oxygen to convert biomass or waste materials into solid charcoal, water, water-soluble organics (pyroligneous acids, including methanol and acetic acid); water-insoluble organics grouped under the term of “tar” or “bio-oil”, and non-condensable gases (H2, CH4, CO, CO2). The chemistry of pyrolysis mainly associates with degradation of carbohydrate polymers (cellulose and hemi-cellulose) and conversion of carbohydrate components, which may be illustrated in Figure 4. When heated at a temperature higher than 300°C, the carbohydrate polymers depolymerize into short chains of sugars, accompanied by slow dehydration and subsequent reactions to form unsaturated polymer intermediates that may be eventually condensed to form char (Lomax et al., 1991). When heated at a higher heating rate to a higher temperature, the de-polymerization reactions will liberate volatile products as oil or tar. Cleavage of C-C

Treatment of Secondary Sludge for Energy Recovery

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bond will occur at a high temperature, leading to formation of gas products (mainly CO, CO2, H2 and CH4). Accordingly, pyrolysis process can be tuned to produce char, oil and/or gas by properly selection of the operating conditions of temperature, heating rate and reaction time. If the purpose is to maximize the oil yield then a high heating rate and short gas residence time would be required, while for high char production, a low temperature and low heating rate would be preferred. High yield of bio-oil up to about 70-75% (Agblevor et al., 1995) can be produced in fast pyrolysis processes (with very short residence time and elevated reactor temperature of ~500°C or higher). The commonly used reactors for fast pyrolysis include bubbling fluidized bed, circulating fluidized bed, ablative, entrained flow, rotating cone reactors, and vacuum reactors (Mohan et al., 2006). A significant amount of char and equal amounts of oil and gas products can be obtained in slow pyrolysis processes (operating at a low temperature for a long residence time). The char produced typically has a higher heating value of ~ 30 MJ/kg, which can be used as a valuable fuel for generating heat and electricity, or can be turned into activated carbon by activation. Pyrolysis oils are normally composed of a variety of organic oxygenates and polymeric carbohydrate and lignin fragments derived from the thermal cracking of cellulose, hemi-cellulose and lignin components of the biomass (Mohan et al., 2006; Tsai et al., 2007). The physical properties of wood fast-pyrolysis oil are compared with those of a petroleum-based heavy fuel oil in Table 2 (Czernik and Bridgewater, 2004). As shown in this Table, pyrolysis oil contains a high concentration of water (15-30%), and is highly acidic (corrosive) and unstable liquid with a lower caloric value of 16-19 MJ/kg compared with 40 MJ/kg for the petroleum-based heavy oil. Pyrolysis oil is a potential liquid fuel for turbines and boilers, or it can also be applied to produce chemicals directly, or be upgraded to high-quality fuels by hydro-cracking or catalytic cracking (Vitolo et al., 1999).

Figure 4. Chemistry of biomass pyrolysis (Lange, 2007)

Pyrolysis has long been recognised more advantageous over conventional incineration processes for the treatment of sewage-sludge with respect to fuel economy, energy recovery, and the control of heavy-metal emissions (Lewis, 1975). However, process efficiency is affected by sludge moisture content, such that co-pyrolysis with other wastes has been recommended in order to increase the dry-solids content of the sludge (Olexseyr, 1975). The process normally needs additional treatment to remove excess water. Higher water content feedstocks cause increases in the production of hydrogen and methane, but these do not compensate for the losses of carbon monoxide and thermal efficiency (Carre, et al., 1989). Water reduction is accomplished by dewatering to about 25% DS followed by thermal drying to 95% DS.

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Chunbao (Charles) Xu and Jody Lancaster Table 2. Typical properties of pyrolysis bio-oil and of a petroleum-based heavy fuel oil (Czernik and Bridgewater, 2004). Physical property

Bio-oil

Heavy fuel oil

Moisture content (wt %)

15-30

0.1

pH

2.5

-

Specific gravity

1.2

0.94

C

54-58

85

H

5.5-7.0

11

O

35-40

1.0

N

0-0.2

0.3

ash

0-0.2

0.1

HHV (MJ/kg)

16-19

40

Viscosity (at 50 oC, cP)

40-100

180

Elemental composition (wt %)

Low temperature pyrolysis with reactor temperature