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GREEN CHEMISTRY AND CHEMICAL ENGINEERING

CHEMICALS FROM BIOMASS Integrating Bioprocesses into Chemical Production Complexes for Sustainable Development

DEBALINA SENGUPTA RALPH W. PIKE

CHEMICALS FROM BIOMASS Integrating Bioprocesses into Chemical Production Complexes for Sustainable Development

GREEN CHEMISTRY AND CHEMICAL ENGINEERING Series Editor: Sunggyu Lee Ohio University, Athens, Ohio, USA

Proton Exchange Membrane Fuel Cells: Contamination and Mitigation Strategies Hui Li, Shanna Knights, Zheng Shi, John W. Van Zee, and Jiujun Zhang Proton Exchange Membrane Fuel Cells: Materials Properties and Performance David P. Wilkinson, Jiujun Zhang, Rob Hui, Jeffrey Fergus, and Xianguo Li Solid Oxide Fuel Cells: Materials Properties and Performance Jeffrey Fergus, Rob Hui, Xianguo Li, David P. Wilkinson, and Jiujun Zhang Efficiency and Sustainability in the Energy and Chemical Industries: Scientific Principles and Case Studies, Second Edition Krishnan Sankaranarayanan, Jakob de Swaan Arons, and Hedzer van der Kooi Nuclear Hydrogen Production Handbook Xing L. Yan and Ryutaro Hino Magneto Luminous Chemical Vapor Deposition Hirotsugu Yasuda Carbon-Neutral Fuels and Energy Carriers Nazim Z. Muradov and T. Nejat Vezirogˇ lu Oxide Semiconductors for Solar Energy Conversion: Titanium Dioxide Janusz Nowotny Lithium-Ion Batteries: Advanced Materials and Technologies Xianxia Yuan, Hansan Liu, and Jiujun Zhang Process Integration for Resource Conservation Dominic C. Y. Foo Chemicals from Biomass: Integrating Bioprocesses into Chemical Production Complexes for Sustainable Development Debalina Sengupta and Ralph W. Pike

GREEN CHEMISTRY AND CHEMICAL ENGINEERING

CHEMICALS FROM BIOMASS Integrating Bioprocesses into Chemical Production Complexes for Sustainable Development

DEBALINA SENGUPTA RALPH W. PIKE

CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2013 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Version Date: 20120530 International Standard Book Number-13: 978-1-4398-7815-6 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

Contents Series Preface ..........................................................................................................xi Preface................................................................................................................... xiii Authors ................................................................................................................ xvii 1. Introduction .....................................................................................................1 1.1 Introduction ...........................................................................................1 1.2 Research Vision .....................................................................................3 1.3 New Frontiers ........................................................................................4 1.4 Chemical Industry in the Lower Mississippi River Corridor.........5 1.5 Criteria for the Optimal Configuration of Plants.............................9 1.6 Optimization of Chemical Complex ................................................ 10 1.7 Contributions of This Methodology................................................. 13 1.8 Organization of Chapters .................................................................. 14 1.9 Summary.............................................................................................. 18 2. Biomass as Feedstock................................................................................... 21 2.1 Introduction ......................................................................................... 21 2.2 Biomass Formation ............................................................................. 25 2.2.1 Calvin–Benson Cycle............................................................. 26 2.2.2 C4 Cycle................................................................................... 26 2.2.3 CAM Cycle.............................................................................. 26 2.3 Biomass Classification and Composition ........................................ 27 2.3.1 Saccharides and Polysaccharides ........................................ 27 2.3.2 Starch ....................................................................................... 28 2.3.3 Lignocellulosic Biomass........................................................ 29 2.3.4 Lipids, Fats, and Oils ............................................................. 31 2.3.5 Proteins.................................................................................... 31 2.4 Biomass Conversion Technologies.................................................... 32 2.4.1 Biomass Pretreatment ........................................................... 33 2.4.2 Fermentation........................................................................... 35 2.4.3 Anaerobic Digestion .............................................................. 36 2.4.4 Transesterification.................................................................. 39 2.4.5 Gasification/Pyrolysis...........................................................44 2.5 Biomass Feedstock Availability ........................................................ 46 2.5.1 Forest Resources..................................................................... 48 2.5.1.1 Forestland Base....................................................... 48 2.5.1.2 Types of Forest Resource.......................................48 2.5.1.3 Limiting Factors for Forest Resource Utilization................................................................ 51 2.5.1.4 Summary for Forest Resources ............................ 51 v

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2.5.2

2.6

Agricultural Resources ......................................................... 52 2.5.2.1 Agricultural Land Base ......................................... 52 2.5.2.2 Types of Agricultural Resource ........................... 53 2.5.2.3 Limiting Factors for Agricultural Resource Utilization................................................................ 56 2.5.2.4 Summary for Agricultural Resources................. 58 2.5.3 Aquatic Resources.................................................................. 58 2.5.3.1 Recent Trends in Algae Research......................... 60 2.5.3.2 Algae Species ..........................................................63 Summary..............................................................................................65

3. Chemicals from Biomass............................................................................. 67 3.1 Introduction ......................................................................................... 67 3.2 Chemicals from Nonrenewable Resources ..................................... 68 3.3 Chemicals from Biomass as Feedstock ............................................ 70 3.4 Biomass Conversion Products (Chemicals) ..................................... 73 3.4.1 Single-Carbon Compounds.................................................. 73 3.4.1.1 Methane ................................................................... 73 3.4.1.2 Methanol.................................................................. 74 3.4.2 Two-Carbon Compounds ..................................................... 76 3.4.2.1 Ethanol ..................................................................... 76 3.4.2.2 Acetic Acid .............................................................. 87 3.4.2.3 Ethylene ................................................................... 88 3.4.3 Three-Carbon Compounds .................................................. 91 3.4.3.1 Glycerol .................................................................... 91 3.4.3.2 Lactic Acid............................................................... 93 3.4.3.3 Propylene Glycol..................................................... 93 3.4.3.4 1,3-Propanediol....................................................... 94 3.4.3.5 Acetone .................................................................... 95 3.4.4 Four-Carbon Compounds .................................................... 95 3.4.4.1 Butanol ..................................................................... 95 3.4.4.2 Succinic Acid........................................................... 96 3.4.4.3 Aspartic Acid .......................................................... 98 3.4.5 Five-Carbon Compounds ..................................................... 98 3.4.5.1 Levulinic Acid ........................................................ 98 3.4.5.2 Xylitol/Arabinitol.................................................. 100 3.4.5.3 Itaconic Acid.......................................................... 100 3.4.6 Six-Carbon Compounds...................................................... 102 3.4.6.1 Sorbitol ................................................................... 102 3.4.6.2 2,5-Furandicarboxylic Acid................................. 102 3.5 Biopolymers and Biomaterials ........................................................ 103 3.6 Natural-Oil-Based Polymers and Chemicals ................................ 105 3.7 Summary............................................................................................ 108

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4. Simulation for Bioprocesses..................................................................... 111 4.1 Introduction ....................................................................................... 111 4.2 Ethanol Production from Corn Stover Fermentation................... 115 4.2.1 Process Description for Ethanol Production from Corn Stover Fermentation......................................... 116 4.2.1.1 Pretreatment Section............................................ 119 4.2.1.2 Fermentation Section ........................................... 121 4.2.1.3 Purification Section .............................................. 122 4.2.2 Process Cost Estimation for Ethanol Production from Corn Stover Fermentation......................................... 125 4.2.3 Summary of Ethanol Production from Corn Stover Fermentation......................................................................... 128 4.3 Ethylene Production from Dehydration of Ethanol ..................... 128 4.3.1 Process Description for Ethylene Production from Dehydration of Ethanol ............................................. 129 4.3.2 Process Cost Estimation for Ethylene Production from Dehydration of Ethanol ............................................. 131 4.3.3 Summary of Ethylene Production from Dehydration of Ethanol .............................................................................. 133 4.4 Fatty Acid Methyl Ester and Glycerol from Transesterification of Soybean Oil ........................................ 134 4.4.1 Process Description for Fatty Acid Methyl Ester and Glycerol from Transesterification of Soybean Oil .... 137 4.4.1.1 Transesterification Section .................................. 140 4.4.1.2 Methyl Ester Purification Section ...................... 141 4.4.1.3 Glycerol Recovery and Purification................... 141 4.4.2 Process Cost Estimation for Fatty Acid Methyl Ester and Glycerol from Transesterification of Soybean Oil.....144 4.4.3 Summary of Fatty Acid Methyl Ester and Glycerol from Transesterification of Soybean Oil........................... 146 4.5 Propylene Glycol Production from Hydrogenolysis of Glycerol.... 147 4.5.1 Process Description for Propylene Glycol Production from Hydrogenolysis of Glycerol ...................................... 147 4.5.2 Process Cost Estimation for Propylene Glycol Production from Hydrogenolysis of Glycerol ..... 150 4.5.3 Summary of Propylene Glycol Production from Hydrogenolysis of Glycerol ................................................ 152 4.6 Acetic Acid Production from Corn Stover Anaerobic Digestion.... 152 4.6.1 Process Description for Acetic Acid Production from Corn Stover Anaerobic Digestion ............................ 154 4.6.1.1 Pretreatment Section............................................ 154 4.6.1.2 Anaerobic Digestion Section .............................. 158 4.6.1.3 Purification and Recovery Section..................... 160

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4.6.2

4.7 4.8

Process Cost Estimation for Acetic Acid Production from Corn Stover Anaerobic Digestion ............................ 163 4.6.3 Summary of Acetic Acid Production from Corn Stover Anaerobic Digestion................................................ 165 Ethanol Production from Corn Dry-Grind Fermentation........... 165 Summary............................................................................................ 170

5. Bioprocesses Plant Model Formulation ................................................. 171 5.1 Introduction ....................................................................................... 171 5.2 Ethanol Production from Corn Stover Fermentation................... 174 5.2.1 Pretreatment (Corn Stover)................................................. 175 5.2.2 Fermentation (Corn Stover) ................................................ 180 5.2.3 Purification Section (Corn Stover EtOH).......................... 181 5.3 Ethanol Production from Corn Dry-Grind Fermentation........... 196 5.3.1 Pretreatment (Corn)............................................................. 197 5.3.2 Fermentation (Corn) ............................................................ 201 5.3.3 Purification (Corn EtOH) .................................................... 201 5.4 Ethylene Production from Dehydration of Ethanol ..................... 209 5.5 Acetic Acid Production from Corn Stover Anaerobic Digestion.........................................................................212 5.5.1 Pretreatment (Corn Stover) Anaerobic Digestion............ 216 5.5.2 Anaerobic Digestion ............................................................ 217 5.5.3 Purification (Acetic Acid).................................................... 219 5.6 Fatty Acid Methyl Ester and Glycerol from Transesterification of Natural Oil .........................................225 5.7 Propylene Glycol Production from Hydrogenolysis of Glycerol......................................................................................... 232 5.8 Algae Oil Production........................................................................ 235 5.9 Gasification of Corn Stover .............................................................. 239 5.10 Summary of Bioprocess Model Formulation ................................ 242 5.11 Interconnections for Bioprocesses .................................................. 244 5.12 Summary............................................................................................ 246 6. Formulation and Optimization of the Superstructure ....................... 247 6.1 Introduction ....................................................................................... 247 6.2 Integrated Biochemical and Chemical Production Complex Optimization..................................................................... 247 6.3 Binary Variables and Logical Constraints for MINLP ................ 255 6.4 Constraints for Capacity and Demand .......................................... 257 6.5 Optimization Economic Model—Triple Bottom Line.................. 259 6.6 Optimal Structure............................................................................. 265 6.7 Multiobjective Optimization of the Integrated Biochemical Production Complex .................................................. 274

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6.8

Sensitivity of the Integrated Biochemical Production Complex ...........................................................................................276 6.9 Comparison with Other Results ..................................................... 280 6.10 Summary............................................................................................ 283 7. Case Studies Using Superstructure ........................................................ 285 7.1 Introduction ....................................................................................... 285 7.2 Case Study I—Superstructure without Carbon Dioxide Use..... 286 7.3 Case Study II—Parametric Study of Sustainable Costs and Credits......................................................................................... 292 7.3.1 Carbon Dioxide Costs and Credits.................................... 293 7.3.2 Developing the Case for Sustainability Analysis............ 297 7.3.3 Effect of Sustainable Costs and Credits on the Triple Bottom Line ................................................... 298 7.3.4 Cross-Price Elasticity of Demand for Ammonia.............308 7.4 Case Study III—Parametric Study of Algae Oil Production Costs ...............................................................................309 7.5 Case Study IV—Multicriteria Optimization Using 30%-OilContent Algae and Sustainable Costs/Credits ............................. 317 7.6 Case Study V—Parametric Study for Biomass Feedstock Costs and Number of Corn Ethanol Plants................................... 321 7.6.1 Options Used in the Parametric Study............................. 322 7.6.2 Results of Parametric Study ............................................... 323 7.7 Summary............................................................................................ 327 Appendix A: TCA Methodology and Sustainability Analysis ................ 331 Appendix B: Optimization Theory ................................................................ 365 Appendix C: Prices of Raw Materials and Products in the Complex ..... 375 Appendix D: Supply, Demand, and Price Elasticity................................... 393 Appendix E: Chemical Complex Analysis System ..................................... 407 Appendix F: Detailed Mass and Energy Streams from Simulation Results .................................................................................. 415 Appendix G: Equipment Mapping and Costs from ICARUS ..................433 Appendix H: Molecular Weights .................................................................... 441 Appendix I: Postscript ......................................................................................445

Series Preface

Green Chemistry and Chemical Engineering The subjects and disciplines of chemistry and chemical engineering have encountered a new landmark in the way of thinking about, developing, and designing chemical products and processes. This revolutionary philosophy, termed “green chemistry and chemical engineering,” focuses on the designs of products and processes that are conducive to reducing or eliminating the use and generation of hazardous substances. In dealing with hazardous or potentially hazardous substances, there may be some overlaps and interrelationships between environmental chemistry and green chemistry. While environmental chemistry is the chemistry of the natural environment and the pollutant chemicals in nature, green chemistry proactively aims to reduce and prevent pollution at its very source. In essence, the philosophies of green chemistry and chemical engineering tend to focus more on industrial application and practice rather than academic principles and phenomenological science. However, as both chemistry and chemical engineering philosophy, green chemistry and chemical engineering derives from and builds upon organic chemistry, inorganic chemistry, polymer chemistry, fuel chemistry, biochemistry, analytical chemistry, physical chemistry, environmental chemistry, thermodynamics, chemical reaction engineering, transport phenomena, chemical process design, separation technology, automatic process control, and more. In short, green chemistry and chemical engineering is the rigorous use of chemistry and chemical engineering for pollution prevention and environmental protection. The Pollution Prevention Act of 1990 in the United States established a national policy to prevent or reduce pollution at its source whenever feasible. And adhering to the spirit of this policy, the Environmental Protection Agency (EPA) launched its Green Chemistry Program to promote innovative chemical technologies that reduce or eliminate the use or generation of hazardous substances in the design, manufacture, and use of chemical products. The global efforts in green chemistry and chemical engineering have recently gained a substantial amount of support from the international community of science, engineering, academia, industry, and governments in all phases and aspects. Some of the successful examples and key technological developments include the use of supercritical carbon dioxide as green solvent in separation xi

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technologies; application of supercritical water oxidation for destruction of harmful substances; process integration with carbon dioxide sequestration steps; solvent-free synthesis of chemicals and polymeric materials; exploitation of biologically degradable materials; use of aqueous hydrogen peroxide for efficient oxidation; development of hydrogen proton exchange membrane (PEM) fuel cells for a variety of power generation needs; advanced biofuel production; devulcanization of spent tire rubber; avoidance of the use of chemicals and processes causing generation of volatile organic compounds (VOCs); replacement of traditional petrochemical processes by microorganism-based bioengineering processes; replacement of chlorofluorocarbons (CFCs) with nonhazardous alternatives; advances in the design of energy efficient processes; use of clean, alternative, and renewable energy sources in manufacturing; and much more. This list, even though it is only a partial compilation, is undoubtedly growing exponentially. This book series on green chemistry and chemical engineering by CRC Press/Taylor & Francis Group is designed to meet the new challenges of the twenty-first century in the chemistry and chemical engineering disciplines by publishing books and monographs based on cutting-edge research and development to the effect of reducing adverse impacts on the environment by chemical enterprise. And in achieving this, the series will detail the development of alternative sustainable technologies that will minimize the hazard and maximize the efficiency of any chemical choice. The series aims at delivering the readers in academia and industry with an authoritative information source in the field of green chemistry and chemical engineering. The publisher and its series editor are fully aware of the rapidly evolving nature of the subject and its long-lasting impact on the quality of human life in both the present and future. As such, the team is committed to making this series the most comprehensive and accurate literary source in the field of green chemistry and chemical engineering. Sunggyu Lee

Preface The vision for this book is the development of new plants that are based on renewable resources that supply the needed goods and services for existing petrochemical plants. The vision includes converting existing plants to ones that are based on renewable resources requiring nonrenewable resource supplements. Identifying and designing new chemical processes that use renewable feedstock as raw materials and show how these processes can be integrated into existing chemical production complexes are key to having a sustainable chemical industry. Also, identifying and designing new industrial processes that use carbon dioxide as a raw material are an important option in mitigating the effects of global warming. The existing plants in the chemical production complex in the Lower Mississippi River Corridor produce a wide range of basic and specialty chemicals, monomers, and polymers. They were used as a base case to demonstrate the integration of new, biomass-based plants into an existing infrastructure of plants. Potential bioprocesses were evaluated based on selection criteria, and simulations of these bioprocesses were performed in Aspen HYSYS®. The bioprocesses were then converted to input–output block models. A superstructure of plants was formed, which was optimized to obtain the optimal configuration of existing and new plants (chemical complex optimization). The optimal configuration of plants was based on economic, environmental, and sustainable costs and credits (triple bottom line). The optimal solution to this mixed integer, multicriteria, nonlinear programming problem was obtained using global solvers. Detailed results were provided that showed a triple bottom line increase, raw material cost decrease, utility cost increase, and pure carbon dioxide vented to the atmosphere reduced to zero in the optimal structure. Five case studies were performed demonstrating the versatility of the analysis, and the optimization software, Chemical Complex Analysis System, can be downloaded. A methodology for the optimal integration of bioprocesses in an existing chemical production complex was developed and demonstrated. This methodology can be used to evaluate energy-efficient and environmentally acceptable plants and have new products from greenhouse gases. Based on these results, the methodology could be applied to other chemical complexes for new bioprocesses, reduced emissions, and energy savings. Detailed process designs for fermentation, transesterification, anaerobic digestion, gasification, and algae oil production can be downloaded for modification, as needed, along with optimization programs. This book can serve as a text for a senior or first-year graduate course in bioprocess engineering, since it covers essentially all aspects of this topic.

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These include bioprocess raw materials and products, design of bioprocess, economic and sustainability analysis, optimization of chemical complexes, and applications to existing processes and chemical production complexes. Practicing engineers in the bioprocessing industries will find that this rapidly growing field requires a stand-alone text like this that covers all parts of biomass conversion to products. This book describes the technical and scientific expertise needed to bring the engineer and scientist “up to speed” in this field. The importance and rapid expansion of this field is covered in the Wall Street Journal’s feature article, “Just One Word: Bioplastics,” in the October 18, 2010, issue that describes the “huge potential” of plastics from plant materials. The material is organized into seven chapters, a postscript, and appendices. In Chapter 1, a description of the production of chemicals from renewable resources is given, with the research vision being to develop the methodology for new plants based on renewable resources that supply the needed goods and services for existing plants. The criteria for optimal configuration of plants and optimization theory are introduced in this chapter. In Chapters 2 and 3, detailed literature reviews and analyses are covered for biomass as feedstock and for the production of chemicals from biomass. Conceptual designs of bioprocesses are constructed, as described in Chapter 4, and include detailed information about the bioprocesses. Five processes are developed in Aspen HYSYS® with cost estimations from Aspen ICARUS®. Information from other process simulation software, for example, SuperPro Designer®, is applied for the corn-to-ethanol fermentation process. In Chapter 5, bioprocess plant models are formulated for optimization using input and output streams, equilibrium rate equations, parameters, and thermodynamic information from HYSYS plant models. Two other processes included in this chapter are for the production of algae oil from carbon dioxide and for the production of syngas from corn stover by steam reforming. Then interconnections in the bioprocesses are developed for optimization. In Chapter 6, the superstructure of chemical and biochemical plants was formulated by integrating the bioprocess and carbon dioxide–consuming plants with the base case of existing chemical plants in the Lower Mississippi River Corridor. Carbon dioxide from the integrated chemical complex was utilized for the production of algae and for chemicals from carbon dioxide. The optimal structure was obtained by maximizing the triple bottom line, which included product sales, economic costs (raw material and utility), environmental costs (67% of raw material costs), and sustainable costs and credits. The optimal solution gave the plants that were included in the optimal structure. Comparisons between the base case and optimal structure were given for triple bottom line costs, the pure and impure carbon dioxide emissions, the energy requirements for plants, and the capacity of the plants. Multicriteria optimization was used to determine Pareto optimal solutions for the optimal structure. Monte Carlo simulation was used to determine the

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parameter sensitivity of the optimal solution. Comparisons of results with approaches were included in this chapter. In Chapter 7, optimization was used to evaluate five cases. Case I was a modification to evaluate integration of bioprocesses in the existing base case without carbon dioxide being used for chemicals or algae oil production. The other four cases examine other aspects obtained from the optimization. The postscript gives the conclusions from this methodology and extensions that can be used for future developments. The existing plants used for the base case were developed with industrial colleagues led by Tom A. Hertwig of Mosaic Corporation, and their assistance was invaluable. The assistance of the members of the Total Cost Assessment Users’ Group at the AIChE, and especially Lise Laurin for guidance in using the Total Cost Assessment Methodology, is gratefully acknowledged. MATLAB® is a registered trademark of The Mathworks, Inc. For product information, please contact: The MathWorks, Inc. 3 Apple Hill Drive Natick, MA, 01760-2098 USA Tel: 508-647-7000 Fax: 508-647-7001 E-mail: [email protected] Web: www.mathworks.com

Authors Debalina Sengupta received her bachelor of engineering degree in chemical engineering from Jadavpur University, Calcutta, India, in 2003. She worked as a software engineer in Patni Computer Systems from 2003 to 2004. In 2005, she joined the Department of Chemical Engineering at Louisiana State University, Baton Rouge, Louisiana. She received her doctor of philosophy degree in chemical engineering under the guidance of Professor Ralph W. Pike for her research entitled “Integrating bioprocesses into industrial complexes for sustainable development” in 2010. Her expertise is in optimization of industrial complexes and sustainability analysis using total cost assessment methodology. She is now working as an ORISE postdoctoral fellow at the United States Environmental Protection Agency. Her current research is focused on sustainable supply chain design of biofuels and includes life cycle assessment (LCA) for ethanol as biofuel. Her research interests include model development for ethanol biorefineries for LCA and assessing environmental releases from biorefineries. Ralph W. Pike is the director of the Minerals Processing Research Division and is the Paul M. Horton Professor of Chemical Engineering at Louisiana State University. He received his doctorate and bachelor’s degrees in chemical engineering from Georgia Institute of Technology. He is the author of a textbook entitled Optimization for Engineering Systems and coauthor of four other books on design and modeling of chemical processes. Pike has directed 15 doctoral dissertations and 16 master’s theses in chemical engineering. He is a registered professional engineer in Louisiana and Texas. His research has been sponsored by federal and state agencies and private organizations, with 107 awards totaling $5.6 million, and has resulted in over 200 publications and presentations. His research specialties are optimization theory and applications for the optimal design of engineering systems, online optimization of continuous processes, optimization of chemical production complexes, and related areas of resources management, sustainable development, continuous processes for carbon nanotubes, and chemicals from biomass. Pike is a fellow of the American Institute of Chemical Engineers and is chair of the Environmental Division and past chair of the Fuels and Petrochemicals Division. He is an active member of the Institute for Sustainability and the Safety and Chemical Engineering Education (SACHE) Committee of the Center for Chemical Process Safety. He was the meeting program chairman for the 74th Annual Meeting and has cochaired 66 sessions on optimization, sustainability, transport phenomena, and reaction engineering. He has held all of the positions in the Baton Rouge Section of the AIChE. Pike is also on the editorial boards of Environmental Progress and Renewable Energy and Clean xvii

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Technology and Environmental Policy. He has served as coeditor in chief of Waste Management, an international journal devoted to information on prevention, control, detoxification, and disposition of hazardous, radioactive, and industrial wastes. He is a member of the American Chemical Society and Sigma Xi, the scientific society.

1 Introduction

1.1 Introduction The vision of this book is to demonstrate the development of new plants that are based on renewable resources that supply the needed goods and services of current petrochemical plants. The vision includes converting existing plants to ones that are based on renewable resources requiring nonrenewable resource supplements. This vision is an essential component of sustainable development. It embodies the concepts that sustainability is a path of continuous improvement, wherein the products and services required by society are delivered with progressively less negative impact upon the Earth. It is consistent with the Brundtland Commission report that defines “Sustainable Development” as “development which meets the needs of the present without sacrificing the ability of the future to meet its needs” (United Nations, 1987). Identifying and designing new chemical processes that use renewable feedstock as raw materials and showing how these processes can be integrated into existing chemical production complexes are the keys to having a sustainable chemical industry. Also, identifying and designing new industrial processes that use carbon dioxide as a raw material are an important option in mitigating the effects of global warming. Global warming and biotechnology are on a collision course because new processes for chemicals from biomass are energy intensive and generate carbon dioxide. Global warming is caused by accelerative accumulation of carbon dioxide and other greenhouse gases in the atmosphere. Industrial processes that use carbon dioxide as a raw material are an important option in mitigating the effects of global warming. Approximately, 110 million MT/year of carbon dioxide is used as a raw material for the production of urea, methanol, acetic acid, polycarbonates, cyclic carbonates, and specialty chemicals such as salicylic acid and carbamates in the United States (Arakawa et al., 2001). Other uses include enhanced oil recovery, solvent (supercritical carbon dioxide), refrigeration systems, carbonated beverages, fire extinguishers, and inert gas-purging systems. Recent developments and renewed interest in growing algae as feedstock for bioprocesses provide alternate methods for the utilization of carbon dioxide. 1

Chemicals from Biomass

2

TABLE 1.1 Chemical Complexes in the World Continent North America

South America

Europe

Name and Site Gulf Coast petrochemical complex in Houston area (USA)

Chemical complex in the lower Mississippi River corridor (USA) Petrochemical district of CamacariBahia (Brazil) Petrochemical complex in Bahia Blanca (Argentina) Antwerp port area (Belgium)

BASF in Ludwigshafen (Germany) Asia

Oceania

Africa

The Singapore petrochemical complex in Jurong Island (Singapore) Petrochemical complex of Daqing Oilfield Company Limited (China) SINOPEC Shanghai Petrochemical Co. Ltd. (China) Joint venture of SINOPEC and BP in Shanghai under construction (2005) (China) Jamnagar refinery and petrochemical complex (India) Haldia Petrochemical Complex (India) Sabic company, based in Jubail Industrial City (Saudi Arabia) Petrochemical complex in Yanbu (Saudi Arabia) Equate (Kuwait)

Petrochemical complex at Altona (Australia) Petrochemical complex at Botany (Australia) Petrochemical industries complex at Ras El Anouf (Libya)

Notes Largest petrochemical complex in the world, supplying nearly two-thirds of the nation’s petrochemical needs

Largest petrochemical complex in the Southern Hemisphere

Largest petrochemical complex in Europe and worldwide second only to Houston, Texas Europe’s largest chemical factory complex World’s third largest oil refinery center

Largest petrochemical complex in Asia

World’s largest polyethylene manufacturing site World’s largest and most modern for producing ethylene glycol and polyethylene

One of the largest oil complexes in Africa

Source: Xu, A., Chemical production complex optimization, pollution reduction and sustainable development, PhD dissertation, Louisiana State University, Baton Rouge, LA, 2004.

Introduction

3

After identifying and designing new biochemical processes, these processes were integrated into an existing chemical production complex. In Table 1.1, some of these chemical production complexes in the world are tabulated. The chemical production complex in the lower Mississippi River corridor was used as a base case to demonstrate the integration of these new plants into an existing infrastructure. Potential bioprocesses were evaluated based on selection criteria, and simulations of these bioprocesses were performed in Aspen HYSYS®. The bioprocesses were then converted to input– output block models. A superstructure of plants was formed, which was optimized to obtain the optimal configuration of existing and new plants (chemical complex optimization). Chemical complex optimization is a powerful methodology for plant and design engineers to convert their company’s goals and capital to viable projects that meet economic, environmental, and sustainable requirements. The optimal configuration of plants in a chemical production complex is obtained by solving a mixed-integer, nonlinear programming problem (MINLP). This methodology is applicable to other chemical production complexes in the world, including the ones in the Houston area (largest in the world), Antwerp port area (Belgium), BASF in Ludwigshafen (Germany), petrochemical district of Camacari-Bahia (Brazil), the Singapore petrochemical complex in Jurong Island (Singapore), and Equate (Kuwait), among others.

1.2 Research Vision The research vision leads to the development of new plants that are based on renewable resources. The vision includes converting existing plants to ones that are based on renewable resources that may require nonrenewable resource supplements. An example is ethanol produced from corn that was grown with chemical fertilizers produced from fossil fuels. Ethanol reduces greenhouse gas emissions by 22% compared to gasoline (Bourne, 2007). Another example is a wind farm of turbines producing electricity, where the turbines were built with materials that required energy from fossil fuels. Wind is considered the largest source of renewable energy, and 10,000 MW (megawatts) have been installed in the United States selling for 4–7 cents/kWh, the least expensive source of energy. This vision is a path to sustainable development for the chemical industry, a path of continuous improvement, where products and services required by society are delivered with progressively less negative impact upon the Earth. It leads to development that meets the needs of the present without sacrificing the ability of the future to meet its needs (United Nations, 1987).

4

Chemicals from Biomass

1.3 New Frontiers The world is in a transition not ever experienced in history. An example is the U.S. Gulf Coast region, where losses from natural disasters, plants relocating to other parts of the world, environmental deterioration, and competition from imports have played a major role in shaping the future of the region. Any change for the improvement of the region needs a new vision and direction. This effort is driven by a desire to understand how sustainable industries can evolve from ones based on nonrenewable resources. Chemical plants in the Gulf Coast, which rely exclusively on natural gas as a feedstock, faced closure when natural gas prices reached over $13 per thousand cubic feet. To remain operational, many of these plants must carefully evaluate migration to new feedstocks. The Gulf Coast is uniquely positioned to take advantage of bio-derived feedstocks. There is a strong agricultural industry in the region, and the Mississippi River provides deep-water ports to ensure continuous biofeedstocks throughout the year. Existing natural-gas-intensive processes, such as agricultural chemical production, can be reconfigured as bio-derived chemical plants. For example, the Farmland Industries ammonia plant in Pineville, Louisiana, migrated from ammonia production to biodiesel production from soybean oil. Farmland Industries is one of the 14 companies that has closed 17 ammonia plants with a total capacity of 5.6 million tons/year (Byers, 2006), only to reopen some of these plants when the demand for fertilizer rapidly increased for increased production of corn for biofuels. The Pineville example is both encouraging and discouraging for the Gulf Coast. The Pineville biodiesel facility is in operation but with substantially fewer employees, about 20 employees now compared to over 100 as in an ammonia plant. It is anticipated that new employees will be hired as the facility moves from 100,000 to 200,000 gal of biodiesel fuel per year. This is somewhat encouraging, but there is a net loss in jobs. What was most disturbing for the region was the ultimate use of the remaining sections of the ammonia plant in Pineville. The new biodiesel plant was constructed by modifying the existing water treatment facility in the ammonia plant with some improvements to the control room. However, the majority of the plant, its reactors, separators, distillation columns, etc., were sold to China. This Louisiana facility was disassembled piece by piece and moved to mainland China, where it will be used to produce ammonia (Knopf, 2007). The opportunity existed for this plant to be reconfigured to make valueadded chemicals here in the United States, but this alternative probably was not considered. This work evaluates potential alternatives, including the expertise to help evaluate ethanol and biodiesel as feedstocks for existing chemical plants. However, the profitability of these migrated plants is inextricably linked to energy efficiency. Processing bio-derived chemicals

Introduction

5

requires large steam and electrical demands, which must be met through cogeneration and online optimization. There is virtually no chance for profitable operation if these plants have to purchase generated power. Food security is moving into the hands of major agricultural-chemicalsexporting countries such as Saudi Arabia, Russia, the Ukraine, and Venezuela as high natural gas prices result in the outsourcing of the U.S. agricultural chemical industry. About 40% of U.S. food production comes from commercial fertilizers. Natural gas, the raw material for the production of nitrogen fertilizers, is 93% of the cost of production (Wilson, 2006). Also, imported phosphate from Morocco is shutting down U.S. production (Hertwig, 2006). Mosaic, Incorporated has announced intent to produce ammonia from petroleum coke that is available from processing heavy crude oil from Venezuela (Thrasher, 2006). As the research moved forward, the focus was on scientific and technical questions that form the basis of sustainable industrial development supplemented with nonrenewable resources. Research priorities focused on products and industries for which there is a strong indication of a sustainable development component and for which there is high or increasing impact on the world’s population. Quantifying sustainable costs was a key element in the use of the triple bottom line (economic, environmental, and sustainable costs) to improve all aspects of the region. Sustainable costs are costs to society to repair damage from emissions within environmental regulations as compared to economic and environmental costs borne by the company.

1.4 Chemical Industry in the Lower Mississippi River Corridor The chemical industry in the lower Mississippi River corridor is typical of the chemical production complexes listed in Table 1.1. A map of the plants in the lower Mississippi River corridor is shown in Figure 1.1a. There are about 150 chemical plants producing a wide range of petrochemicals that are used in housing, automobiles, fertilizers, and numerous other consumer products, consuming 1.0 quad (1015 BTUs/year) of energy (Peterson, 2000). The state’s chemical industry is the largest single employer with nearly 26,000 direct employees, a number that does not include the thousands of contract and maintenance employees that work at the plants year round. These jobs generate $5.9 billion in earnings and $125 million in state and local taxes on personal income. Over a billion dollars is spent in Louisiana annually with Louisiana suppliers according to the Louisiana Chemical Association (LCA, 2007). Figure 1.1b shows a chemical production complex that was developed with the assistance of industrial collaborators and published sources (Xu, 2004). It is based on the plants in the agricultural chemical chain and the methanol

FIGURE 1.1 (a) Petrochemical plants in the lower Mississippi River corridor. (From Peterson, R.W., Giants on the River, Homesite Company, Baton Rouge, LA, 2000. With permission.)

Belle Chasse ConocoPhillips (Tosco, BP, Amoco) Alliance Re�nery Chevron Oronite - Lubes

Below New Orleans Domino Sugar – Sugar Re�nery CII Carbon (Kaiser) - Coke Chalmette Re�ning - Oil Re�nery Air Products - Air Separation Murphy Oil Re�nery

New Orleans East Air Products – Air Separation Folgers - Co�ee Michoud – NASA Shuttle

Metairie Shell Petroleum Re�nery

Norco Shell Petroleum Re�nery Shell Chemical - LP, Ole�ns Hexion (RPP) - Epoxies Enterprise Products - Gas Processing Air Liquide - Air Separation Valero (Orion, TransAm.) - Re�nery CII Carbon (Kaiser) - Coke Dow (Union Carbide) – Polypropylene

Garyville/LaPlace Stockhausen (Nalco) - Water Treatment Marathon Petroleum Re�nery Pinnacle Polymers (Epsilon) - Polypropylene DuPont - Elastomers & Specialties Bayou Steel – Structural Steel

Sunshine Bridge & Below DuPont - Sulfuric Acid Air Products – Air Separation Motiva (Star/Texaco) Petroleum Re�nery OxyChem (Convent) - EDC Mosiac (IMC - Agrico, Uncle Sam) - Fertilizers

Gramercy Imperial (Colonial) - Sugar Gramercy Alumina (Kaiser) - Alumina CII Carbon (Kaiser) - Coke

Geismar BCP (Borden) – Acetylene Air Liquide – Air Separation Air Products – Syn Gas, DNT Chemtura (Uniroyal) - EPDM Huntsman (Rubicon) - MDI Hexion (Borden) - Formaldehyde Praxair - Syn Gas BASF - EO, EGA, Urethanes Shell Chemical – Ethylene Derivatives OxyChem (Vulcan) – Chlorine, Organics

Across River from New Orleans Monsanto - Specialty Chemicals Cytec (Am Cyanamid) - Ammonia, Specialty Chemicals

Burnside Ormet – Aluminum Oxide

Geismar Honeywell (Allied Signal) Williams (Union Texas) - Ethylene PCS Nitrogen (Arcadian) - Fertilizers Innophos (Rhodia) - Phosphoric Acid Louis Dreyfus (Gulf Liquids) - Ole�ns Crosstex (El Paco) - Gas Processing

Taft/Hahnville Mosiac (IMC-Agrico) Fertilizer OxyChem (Hooker) – Chlorine Monsanto - Specialty Chemicals Praxair – Syn Gas Air Liquide – Air Separation Chemtura (Witco) - Additives Dow (Union Carbide) – Ethylene & Derivatives

Below Sunshine Bridge Mosaic (IMC-Agrico) Fertilizers ChevronPhillips - Styrene

St Gabriel/Carville Taminco (Air Products) - Amines BCP (Borden) – Ammonia, PVC Syngenta (Novartis & Zeneca) –Ag Chemicals Huntsman (Ciba) - Inks Pioneer (Stau�er) - Chlorine Ineos Fluor (ICI) - Refrigerants Total (Ato�na) – Styrene, PS

Donaldsonville CF Industries - Ammonia Terra (Triad) - Ammonia

Petrochemical plants and re�neries along the lower Mississippi River corridor (a)

Addis/Plaquemine Dow – Chlorine, Ethylene & Derivatives Shintech-PVC Sid Richardson - Carbon Black Poly One (Geon) – Specialty Chemicals Air Liquide - Air Separations Air Products - Air Separations

Plaquemine Georgia Gulf – Chlorine, PVC Shintech – PVC Air Liquide – Air Separations Praxair – Air Separations

Port Allen BASF (Discovery) - Intermediates Criterion (So. Ionics, Alcoa) - Catalysts Placid Petroleum Re�nery ExxonMobil - Lubes Enterprise Products - Propane Splitter

North of Baton Rouge Ferro (Grant) – Specialty Chemicals ExxonMobil Polyole�ns (Allied/Paxon) ExxonMobil-Resin Finishing ExxonMobil BR - Plastics Deltech (Foster Grant) - Styrenes Great Lakes Carbon (Alcoa) - Alumina Clean Harbors (Safety-Kleen) – Hazardous Waste Disposal

Port Hudson Georgia-Paci�c - Paper

Saint Francisville Tembec (Crown) - Paper

Baton Rouge Rhodia (Stau�er) – Sulfuric Acid UOP (LaRoche) - Alumina Lion Copolymer (DSM) - Rubber Albemarle (Ethyl) – R&D Labs Formosa (Allied) - Chlorine, PVC ExxonMobil - Re�nery ExxonMobil - Chemicals Honeywell (Allied Signal) – Refrigerants

6 Chemicals from Biomass

Air

Fuel BFW

Benzene Ethylene Benzene

Natural gas

Air

IP

Sulfur Air BFW H 2O

Steam

Rock slurry Slurry water

Decant water Fines (clay, P2O5) Tailings (sand)

Ethylbenzene

Ammonia plant

Power generation

HP steam

Sulfuric acid plant

Benefici-ation

FIGURE 1.1 (continued) (b) Base case of chemical plants.

(b)

Claus recovery from HC’s

Frasch mines/w ells

Phosphate rock [Ca3(PO4)2...] mine

Reclaim old mines

Clay-settling ponds

Vent

Other use

CO2 Steam

CO2

Rock

Ethylbenzene

LP H2O CO2 Electricity

Others

H2SO4 Vent LP steam Blowdown

Ethylbenzene

H 2O Purge

NH3 CO2

>75 BPL 0) Electric furnace phosphoric acid (Y1) Acetic acid (Y11) New acetic acid (Y12) SO2 recovery from gypsum (Y13) S and SO2 recovery from gypsum (Y14) Methanol (Y16) Haifa process phosphoric acid (Y2) Propylene from CO2 (Y23) Propylene from propane dehydrogenation (Y24) Synthesis gas (Y27) Formic acid (Y29) Wet process phosphoric acid (Y3) Methylamines (Y30) Methanol (Jun et al., 1998) (Y31) Methanol (Bonivardi et al., 1998) (Y32) Methanol (Nerlov and Chorkendorff, 1999) (Y33) Methanol (Ushikoshi et al., 1998) (Y34) New styrene (Y35) Ethanol (Y37) Dimethyl ether (Y38) Graphite (Y39) Styrene (Y40) Ethyl benzene (Y41)

Processes 150 0 0 150 0 0 2 0 107 150 0 147 147 0 150 150 0 0 0 0 0 0 0 0 147 0 3

150 0 0 150 0 0 0 0 0 150 0 150 150 0 150 150 0 0 0 0 0 0 0 0 150 0 0

150 0 0 150 0 0 0 0 0 150 0 150 150 0 150 150 0 0 0 0 0 0 0 0 150 0 0

150 0 0 150 0 0 0 0 0 150 0 150 150 0 150 150 0 0 0 0 0 0 0 0 150 0 0

150 0 0 150 0 0 0 0 0 150 0 150 150 0 150 150 0 0 0 0 0 0 0 0 150 0 0

150 0 0 150 0 0 0 0 0 150 0 150 150 0 150 150 0 0 0 0 0 0 0 0 150 0 0

100 0 0 100 0 0 0 0 0 100 0 100 100 0 100 100 0 0 0 0 0 0 0 0 100 0 0

0.000–0.149 0.150–0.299 0.300–0.449 0.450–0.599 0.600–0.749 0.750–0.900 0.900–1.000

w1

Optimal Structure Changes in Multicriteria Optimization (Number of Times Out of 1000 a Process Is Selected)

TABLE 6.15

1000 0 0 1000 0 0 2 0 107 1000 0 997 997 0 1000 1000 0 0 0 0 0 0 0 0 997 0 3

Total

Formulation and Optimization of the Superstructure 277

Chemicals from Biomass

278

100% Cumulative probability (%)

90%

$2150 million/yr

80% 70% 60% 50% 80%

40% 30% $1650 million/yr 20% 10%

20%

12 0 13 0 00 14 0 15 0 00 16 0 17 0 00 18 0 19 0 0 20 0 0 21 0 00 22 0 23 0 00 24 0 25 0 00 26 0 27 0 00 28 0 29 0 0 30 0 00 31 0 32 0 00

0%

Triple bottom line (million dollars per year) FIGURE 6.7 Cumulative probability distribution for the triple bottom line of the optimal structure.

One of the results from the data analysis was the cumulative probability of the triple bottom line profit, as shown in Figure 6.7. The statistical average triple bottom line profit was $1898 million per year. The standard deviation of the results obtained from Monte Carlo simulations was $312 million per year. The minimum triple bottom line profit was $1251 million per year and the maximum triple bottom line profit was $3134 million per year. From Figure 6.7, it can be said that there is 20% probability of the triple bottom line being less than or equal to $1650 million per year. It can also be inferred that there is 80% probability of the triple bottom line being less than or equal to $2150 million per year. The optimal solution and the statistical average triple bottom line were not the same. The reason for this is a different configuration of plants is selected for a certain price parameter set in each Monte Carlo run. Some of the configurations may be similar while others will differ. The triple bottom line profit function will change accordingly, for inclusion or exclusion of flow rates from plants in the complex. The chemical production complex configurations of Monte Carlo simulation solutions for 1000 samples are shown in Table 6.16. If a process is selected, the binary variable associated with the process is 1, otherwise it is 0. For each process in Table 6.16, the sums of the binary variable values for the corresponding iteration range are shown, along with the total summation of the times the process was selected. The results in Table 6.16 show that the complex was able to curb carbon dioxide emissions for almost all of the case runs (995 out of 1000 times). Corn stover ethanol was selected in 23% of the runs and the corn ethanol process was selected in 77% of the runs. There is 47% probability that the existing

Corn stover ethanol (EP1 > 0) Corn ethanol (EP2 > 0) Ethylbenzene (Y41) Styrene (Y40) Electric furnace phosphoric acid (Y1) Acetic acid anaerobic digestion (Y61) Methanol (Y16) Biomass gasification (Y60) Wet process phosphoric acid (Y3) Pure CO2 emission abatement (S64 = 0) New acetic acid (Y12) Acetic acid (Y11) Propylene from CO2 (Y23) Propylene from propane dehydrogenation (Y24) Synthesis gas (Y27) Formic acid (Y29) Methylamines (Y30) Methanol (Jun et al., 1998) (Y31) Methanol (Bonivardi et al., 1998) (Y32) Methanol (Nerlov and Chorkendorff, 1999) (Y33) Methanol (Ushikoshi et al., 1998) (Y34) New styrene (Y35) Ethanol (Y37) Dimethyl ether (Y38)

Processes 36 114 71 0 0 0 150 122 150 149 48 0 130 148 6 136 44 0 0 0 0 0 15 0

1–150 30 120 79 0 0 0 150 134 150 150 55 0 135 143 9 135 51 0 0 0 0 0 13 0

151–300 33 117 74 0 0 0 150 135 150 150 50 0 135 144 7 132 57 0 0 0 0 0 17 0

301–450 30 120 72 0 0 0 150 131 150 150 54 0 142 147 5 140 51 0 0 0 0 0 20 0

451–600 36 114 76 0 0 0 150 124 150 148 49 0 137 147 6 125 43 0 0 0 0 0 18 0

601–750 37 113 55 0 0 0 150 137 150 149 62 0 140 145 7 142 69 0 0 0 0 0 20 0

751–900 27 73 46 0 0 0 100 81 100 99 37 0 95 99 4 88 37 0 0 0 0 0 8 0

901–1000

Monte Carlo Simulation (Iterations)

Optimal Structure Changes in Monte Carlo Simulation (Number of Times Out of 1000 a Process Is Selected)

TABLE 6.16

229 771 473 0 0 0 1000 864 1000 995 355 0 914 973 44 898 352 0 0 0 0 0 111 0

Total 23 77 47 0 0 0 100 86 100 100 36 0 91 97 4 90 35 0 0 0 0 0 11 0

Probability (%)

Formulation and Optimization of the Superstructure 279

280

Chemicals from Biomass

ethylbenzene process will be selected, but the styrene processes, both existing and proposed, was never selected in the runs. The existing acetic acid process and the new acetic acid process from anaerobic digestion of biomass were never selected, but the new acetic acid process from carbon dioxide consumption was selected in 36% of the runs. The existing methanol process in the base case was always selected, and proposed methanol processes from carbon dioxide consumption could never compete with the existing process. The existing phosphoric acid was always selected and the proposed alternatives for phosphoric acid production could never compete with the existing process. The biomass gasification process was selected in 86% of the case runs, while the new synthesis gas process from carbon dioxide consumption was selected in only 4% of the cases. Among the new plants proposed for carbon dioxide utilization, the graphite process was always selected, propylene from CO2 and formic acid was selected in 90% of the case runs, the methylamines process was selected in 35% of the case runs, ethanol process was selected in 11% of the case runs, and the dimethyl ether process was never selected. Thus, decisions regarding the operation of the plants can be made based on the Monte Carlo sensitivity analysis of the optimal operation of plants.

6.9 Comparison with Other Results The present research studies the chemical complex optimization for integration of bioprocesses into an existing chemical complex infrastructure. Chemical complex optimization has been studied by Xu (2004) for integrating new carbon dioxide processes into the base case of chemical plants in the lower Mississippi River corridor. Indala (2004) developed HYSYS designs for 14 new processes that converted high-purity carbon dioxide to chemicals. The superstructure developed by Xu (2004) integrated these new processes into the base case and obtained the optimal solution. This research acknowledges the work by Xu (2004) and Indala (2004) for the base case of plants and the carbon dioxide processes developed for integration into the base case. There have been no other reports of chemical complex optimization from a macroscale. The comparison of results for the base case and superstructure of plants developed by Xu (2004) is given in this section. The chemical complex analysis system models for the base case and superstructure were obtained from www.mpri.lsu.edu. The parameters for price were changed from 2004 to 2010 values, as given in Table 6.6, and the cases were optimized. The solution for the base case is given in Table 6.17. The optimal solution for the superstructure from Xu (2004) is given in Table 6.18. The base-case flow rates are given in Figure 6.8. From Table 6.17, it is seen that the triple bottom line for the base case increased from $343 million per

Formulation and Optimization of the Superstructure

281

TABLE 6.17 Comparison of Results for Base Case (Million Dollars per Year)

Income from sales Economic costs (Raw materials and utilities) Raw material costs Utility costs Environmental cost (67% of raw material cost) Sustainable credits (+)/costs (−) Triple bottom line

Base Case (Xu, 2004)

Base Case (Present Research)

1277 554

2026 697

542 12 362

685 12 457

−18 343

−18 854

Source: Xu, A., Chemical production complex optimization, pollution reduction and sustainable development, PhD dissertation, Louisiana State University, Baton Rouge, LA, 2004 and present research.

TABLE 6.18 Comparison of Results for Optimal Structure (Million Dollars per Year)

Income from sales Economic costs (raw materials and utilities) Raw material costs Utility costs Environmental cost (67% of raw material cost) Sustainable credits (+)/costs (−) Triple bottom line

Optimal Structure (Xu, 2004)

Optimal Structure (Modified for Cost Parameters)

1508 602

1859 360

577 25 382

334 26 223

−15 506

−14 1262

Source: Xu, A., Chemical production complex optimization, pollution reduction and sustainable development, PhD dissertation, Louisiana State University, Baton Rouge, LA, 2004 and present research.

year to $854 million per year. The income from sales increased from $1277 million per year to $2026 million per year—an increase of 58%. The raw material costs increased from $542 million per year to $685 million per year—an increase of 26%. The optimal structure flow rates for the integration of carbon dioxide processes in the base case are given in Table 6.18. From Table 6.18, it is seen that

Air

Air

Fuel BFW

Benzene Ethylene Benzene

Natural gas

IP

Sulfur Air BFW H2O

0.2986 0.1166 0.0260

Steam 0.5225

0.7200 0.2744

0.0306 0.7336

0.5754

1.1891 7.6792 5.7683 0.7208

Rock slurry slurry water

Decant water Fines (clay, P2O5) Tailings (sand)

Ethylbenzene

Ammonia plant

Power generation

HP steam

Sulfuric acid plant

Beneficiation

0.6124 Vent

Other use 2.8607

0.0938 0.0121

0.6581 0.7529

0.0000

CO2 Steam Natural gas

CO2

Rock

0.4411 Ethylbenzene Ethylbenzene

H2O Purge

NH3 CO2

LP 3.4007 0.7748 H2O 0.0838 CO2 1611 Electricity TJ

3.6781 H2SO4 5.9098 Vent 1.9110 LP steam 0.4154 Blowdown 2.8665 0.0012 Others

>75 BPL 75BPL Fines ponds (clay, P2O5) BeneReclaim old Tailings ficimines (Sand) ation Phosphate plant rock Rock slurry