Towards Sustainable Chemical Processes: Applications of Sustainability Assessment and Analysis, Design and Optimization, and Hybridization and Modularization

Towards Sustainable Chemical Processes describes a comprehensive framework for sustainability assessment, design and the processes optimization of chemical engineering. Beginning with the analysis and assessment in the early stage of chemical products’ initiating, this book focuses on the combination of science sustainability and process system engineering, involving mathematical models, industrial ecology, circular economy, energy planning, process integration and sustainability engineering.

All chapters throughout answered two fundamental questions in depth: (1) what tools and models are available to be used to assess and design sustainable chemical processes, (2) what the core theories and concepts are to get into the sustainable chemical process fields. Therefore, Towards Sustainable Chemical Processes is an indispensable guide for chemical engineers, researchers, students, practitioners and consultants in sustainability related area.

• Provides innovative, novel and comprehensive methods and models for sustainability assessment, design and optimization, and synthesis and integration of chemical engineering processes
• Combines sustainability science with process system engineering
• Integrates mathematical models, industrial ecology, circular economy, energy planning, process integration and sustainability engineering
• Includes new case studies related to renewable energy, resource management, process synthesis and process integration

• Language: English
• Publisher: Elsevier Science
• Release date: Jun 30, 2020
• ISBN: 9780128189344

Book preview

Towards Sustainable Chemical Processes

Applications of Sustainability Assessment and Analysis, Design and Optimization, and Hybridization and Modularization

First Edition

Jingzheng Ren

The Hong Kong Polytechnic University, Department of Industrial and Systems Engineering, Center for Sustainability Science, Hong Kong, China

Yufei Wang

Associate professor, State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, China

Chang He

School of Materials Science and Engineering, Sun Yat-sen University, Guangzhou, China

Table of Contents

Cover image

Title page

Copyright

Contributors

Part 1: Sustainability assessment and analysis

1: Sustainability assessment for chemical product and process design during early design stages

Abstract

1 Introduction

2 Framework for the sustainability assessment of chemical products and processes at early design stages

3 Application of the methodology to the case studies

4 Conclusions

2: Optimization and decision-making methods in realization of tri-generation systems

Abstract

1 Introduction

2 Design methods

3 Evaluation criteria

4 Optimization methods

5 Decision-making methods

3: Techno-economic assessment of an integrated bio-oil steam reforming and hydrodeoxygenation system for polygeneration of hydrogen, chemicals, and combined heat and power production

Abstract

Acknowledgments

1 Introduction

2 Methodology

3 Process modeling and integration of the BOSR-HDO system

4 Discussion

5 Conclusions

4: Risk and resilience analysis of integrated biorefineries using input-output modeling

Abstract

Acknowledgment

1 Introduction

2 Problem statement

3 Methodology

4 Case study: IBR

5 Conclusions

5: Advanced integrated systems for hydrogen production and storage from low-rank fuels

Abstract

1 Introduction

2 Hydrogen: Properties and characteristics

3 Hydrogen production from low-rank fuels

4 Hydrogen storage

5 Conclusion

Part 2: Sustainability design and optimization

6: Energy system optimization under uncertainties: A comprehensive review

Abstract

1 Introduction

2 Literature review

3 Energy system optimization methodologies under uncertainties

4 Optimization of different energy systems under uncertainty

5 Conclusion

7: Sustainable utilization of low-grade heat: Modeling and case study

Abstract

1 Introduction

2 Absorption refrigeration cycle

3 Organic Rankine cycles and Kalina cycles

4 Conclusions

8: Sustainable design of industrial complex: Industrial area-wide layout optimization

Abstract

1 Introduction

2 Methodology

3 Case studies

4 Results and discussion

5 Conclusion

9: Sustainable design of cooling water system

Abstract

1 Introduction

2 Problem statement

3 Model formulation

4 Objective function and solution technique

5 Case studies: Without air cooler

6 Case study: With air coolers

7 Conclusion

10: Pinch analysis for sustainable process design and integration

Abstract

1 Introduction

2 Pinch analysis

3 Water pinch analysis

4 Carbon emission pinch analysis

5 Other applications of pinch analysis

6 Conclusions

11: Model-based synthesis and Monte Carlo simulation of biochar-based carbon management networks

Abstract

Acknowledgment

1 Introduction

2 Methodology for assessing the robustness of BCMNs

3 Illustrative case study

4 Conclusion

Part 3: Sustainable manufacturing via hybridization and modularization

12: Frontiers of sustainable manufacturing: Hybridization and modularization

Abstract

1 Introduction

2 Hybrid energy processes

3 Modular chemical production processes

4 Conventional evaluation and optimization methods

5 Model-based simulation and optimization

6 Sustainability assessment and optimization

7 Future challenges and opportunities

13: Hybrid processes for sustainable liquids production from lignite, natural gas, and biomass

Abstract

1 Introduction

2 Lignite conversion and hybridization opportunity

3 Hybrid processes description

4 Life cycle multiindicator optimization

5 Illustrative example

6 Conclusions

14: Hybrid processes for sustainable chemicals production from shale gas and ethanol

Abstract

1 Introduction

2 Shale gas conversion and hybridization opportunity

3 Hybrid process description

4 Life cycle bi-objective optimization

5 Illustrative example

6 Conclusions

15: Modular fuels/chemical production from shale gas

Abstract

Acknowledgment

1 Introduction

2 Technologies for modular fuels/chemicals production from shale gas

3 Modeling, analysis, and optimization of modular fuels/chemicals production systems

4 Pros and cons of modular production

5 Discussion and future directions

6 Conclusion

Author Index

Subject Index

Copyright

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Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

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Contributors

Muhammad W. Ajiwibowo     Universitas Indonesia, Depok, Indonesia

Houssein Al Moussawi     Lebanese International University, LIU, Beirut, Lebanon

Muhammad Aziz     Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

Beatriz A. Belmonte     Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines

Michael Francis D. Benjamin     Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines

Mauricio Camargo     Equipe de Recherche des Processus Innovatifs, ERPI-ENSGSI, Université de Lorraine, Nancy, France

Arif Darmawan     Tokyo Institute of Technology, Tokyo, Japan

Farouk Fardoun     Faculty of Technology, Department GIM, Lebanese University, Saida, Lebanon

Xiao Feng     School of Chemical Engineering & Technology, Xi’an Jiaotong University, Xi’an, People’s Republic of China

Chang He     School of Materials Science and Engineering, Guangdong Engineering Centre for Petrochemical Energy Conservation, Sun Yat-sen University, Guangzhou, People's Republic of China

Xiaoping Jia     School of Environment and Safety Engineering, Qingdao University of Science and Technology, Qingdao, China

Zhiwei Li     School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg, South Africa

Bo Liu     State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, People's Republic of China

Hasna Louahlia     Normandie Univ, UNICAN, LUSAC, Saint Lo, France

Jiaze Ma     State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, People's Republic of China

Lei Ma     School of Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, China

Elias Martinez-Hernandez     Biomass Conversion Department, The Mexican Institute of Petroleum, Mexico City, Mexico

Paulo César Narváez Rincón     Departamento de Ingeniería Química y Ambiental, Grupo de Procesos Químicos y Bioquímicos, Facultad de Ingeniería, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia

Kok Siew Ng     Department of Engineering Science, University of Oxford, Oxford, United Kingdom

Álvaro Orjuela     Departamento de Ingeniería Química y Ambiental, Grupo de Procesos Químicos y Bioquímicos, Facultad de Ingeniería, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia

Luis F. Razon     Chemical Engineering Department, De La Salle University, Manila, Philippines

Jingzheng Ren     Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, People's Republic of China

Juliana Serna     Departamento de Ingeniería Química y Ambiental, Grupo de Procesos Químicos y Bioquímicos, Facultad de Ingeniería, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia

Raymond R. Tan     Chemical Engineering Department, De La Salle University, Manila, Philippines

Ruiqi Wang     State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, People's Republic of China

Yufei Wang     State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, People's Republic of China

Yan Wu     State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing, People's Republic of China

Minbo Yang     School of Chemical Engineering & Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China

Part 1

Sustainability assessment and analysis

1

Sustainability assessment for chemical product and process design during early design stages

Paulo César Narváez Rincóna; Juliana Sernaa; Álvaro Orjuelaa; Mauricio Camargob    a Departamento de Ingeniería Química y Ambiental, Grupo de Procesos Químicos y Bioquímicos, Facultad de Ingeniería, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia

b Equipe de Recherche des Processus Innovatifs, ERPI-ENSGSI, Université de Lorraine, Nancy, France

Abstract

Nowadays, the importance of reaching sustainable production and consumption is broadly and globally recognized. Considering the chemical sector, a major challenge to incorporate a sustainability approach for product/process design is its inherent complexity. This is more difficult at early design stages when information is scarce, uncertainty is high, and the effects of decisions are huge. Considering this, the chapter presents a decision-making methodology applicable to the sustainable design of chemical products and processes at early design stages. The methodology proposes the use of indicators to assess the design alternatives on the three sustainability dimensions. Most of the proposed indicators were calculated based upon the H statements of the Globally Harmonized System of Classification and Labelling of Chemicals, which are available and easy to calculate. The incorporation of assessments is done based on Multicriteria Decision Analysis methods. The proposed methodology can become a rapid conceptual design tool for systematic decision-making at the early stages of product/process synthesis. The following sections explain the steps of the decision methodology, which are (1) problem definition, (2) assessment of alternatives, (3) integration of assessments and (4) final decision. Additionally, the methodology is exemplified through two case studies: the selection of a chemical route to produce glyceryl monostearate, and the selection of a formulation for a cosmetic application.

Keywords

Sustainability assessment; Chemical product and process design; Early design stages; Multicriteria decision analysis; Sustainability indicators; Globally harmonized system of classification and labelling of chemicals (GHS)

1 Introduction

Nowadays, the importance of reaching sustainable production and consumption is broadly and globally recognized. This is reflected in the United Nations’ statement on the Sustainable Development Goals (SDGs) for the year 2030 (2015a). In view of this, the World Business Council for Sustainable Development (WBCSD) has published a specific roadmap to help the chemical sector undertake actions to contribute to the SDG agenda (WBCSD, 2018). Many chemical industry organizations have also manifested their active support for fulfilling the SDGs. For example, the International Council of Chemical Associations (ICCA) has presented a report of efforts being made in their sector to achieve the SDGs (ICCA, 2017). Also, the European Chemical Industry Council (CEFIC) has published a sustainability report within its new framework, ChemistryCan, created to boost cooperation between CEFIC members toward sustainable development (CEFIC, 2017). Similarly, the American Chemical Society (ACS) has published a policy statement focused on sustainability, recommending government actions that can promote the SDGs (ACS, 2017). Additionally, several big chemical industries, such as Dow, BASF, and Akzo Nobel, have aligned their goals to this purpose (Axon and James, 2017).

In spite of the awareness that actions are needed for sustainable development, there is still a long way to go to achieve the SDGs (United Nations, 2018). Considering the chemical sector, a major challenge to incorporating a sustainability approach into product/process design is its inherent complexity. Sustainable design involves:

•A multidimensional perspective, because by definition it incorporates at least three dimensions: economic, environmental, and social. These dimensions are usually referred to as the triple bottom line (TBL) (Hacking and Guthrie, 2008; Govindan et al., 2013). Moreover, in recent approaches, additional dimensions, including political and technological, are also taken into account (Bautista et al., 2016).

•A multiscale view, because decisions made at the molecular, phenomenological, process, and supplier chain scales may have effects at the ecosystem and planet scales (Martinez-Hernandez, 2017; Hanes and Bakshi, 2015).

•A multiactor problem, because decisions must be made considering different stakeholders with diverse and even contradictory interests that may be affected or benefited by the product/process to be devised (Azapagic et al., 2016). Stakeholders to be considered include investors, organizations, governments, individuals, communities, and workers.

The complex nature of sustainability means more effort is required for its implementation. Nevertheless, it is also an opportunity for broadening the scope of chemical engineering design beyond the chemical plant. Sustainability can be evaluated using indicators related to each dimension, and the appropriate indicators must be selected according to the design stage under evaluation and the available information. A sustainable design must consider simultaneously all TBL dimensions throughout the entire design process, i.e., from the early design stages when the product is devised, components are selected and/or a chemical route is defined, all the way to the production stage when the plant is in operation and administrative and manufacturing decisions are made. Thus, the implementation of sustainability assessment can be more demanding during the early design stages when information is scarce and the impact of decisions is high and difficult to correct at later stages (Serna et al., 2016; Argoti et al., 2019). In this context, appropriate assessment methods for each dimension and decision-making tools involving multiple objectives are needed.

Several sustainability assessment approaches applicable to early design stages have been proposed. Examples are the indicator-based methodology proposed by Srinivasan and Nhan (2008), the environmental hazard index (EHI) (Cave and Edwards, 1997), and the waste reduction (WAR) algorithm (Young et al., 2000), among many others. The social dimension is difficult to assess at the early design stages due to a lack of models and information (Argoti et al., 2019). Some methods apply a surrogate approach using safety and health indicators. Examples of safety assessment approaches are the inherent safety index (ISI and ISI2) (Adu et al., 2008) and the prototype inherent safety index (PIIS) (Edwards and Lawrence, 1993). Examples of occupational health indicators are the Inherent Occupational Health Index (Hassim and Edwards, 2006) and the Globally Harmonized System of Classification and Labelling of Chemicals (GHS). The latter is global standard for hazardous material categorization that has been widely implemented worldwide (United Nations, 2015b). It can also be used to assess the environmental and health hazards of substances (Suarez and Narváez, 2017). However, more investigation is required to generate a more comprehensive assessment of the social dimension at early and advanced stages of the product and process design.

For the specific case of sustainability assessments during product design, there are different methodologies in which sustainability indicators have been incorporated to a greater or lesser degree. For example, in addition to cost, Conte et al. (2011) and Mattei et al. (2013) considered flammability and toxicity as criteria for selecting safe and economic product components. Heintz et al. (2014) proposed a framework for substituting possible toxic ingredients with more sustainable options, considering their lethal dose (LD50) and bioconcentration factor (BCF). Similarly, a framework integrating computer-aided molecular design and a complete evaluation of occupational health and safety criteria was presented by Ten et al. (2016). In that proposal, seven indices related to the safety and health characteristics of chemical molecules were selected and implemented when generating molecular products. These indices are flammability and explosiveness for safety; and viscosity, material phase, volatility, and exposure limit for occupational health.

In addition to the selection of suitable indicators, two aspects must be considered when carrying out an integrated sustainability assessment: (1) to normalize the indicators to make them comparable, (2) to present the indicators simultaneously so that decision-makers can identify eventual compromises between alternatives (Serna et al., 2016). When incorporating multiple dimensions into the assessments, all stakeholder preferences have to be included. This can be done by implementing a multicriteria decision analysis (MCDA) (Govindan et al., 2013; Serna et al., 2016; Azapagic et al., 2016), and multiactor decision-making (MADM) methods (Ren et al., 2013). According to the problem and the availability of models and information, design alternatives can be identified by experience, literature search, or by modeling and optimization. In the latter case, when complete problem modeling is possible, optimization can be done before or after incorporating assessments with MCDA or MADM (Azapagic et al., 2016). In the first option, the Pareto front is identified by applying a multiobjective optimization method, and the assessments are integrated subsequently, and the best alternative is defined. In the second option, the criteria are first integrated into a single objective, and subsequently an easier mono-objective optimization is performed. The advantage of the first option is a clear identification of all the best alternatives (Pareto front) and possible trade-offs.

Taking the above into account, this chapter presents a decision-making methodology applicable to the sustainable design of chemical products and processes at early design stages. It is based on a previously presented methodology that uses indicators to assess the process design alternatives and MCDA methods to integrate the assessment (Serna et al., 2016). The contribution of this chapter is that it extends the application of the methodology to product design and presents new indicators based on the GHS that require little information and can be easily applied at early design stages. Additionally, the here-presented methodology uses the MCDA methods such as the analytic hierarchy process (AHP) and the preference ranking organization method for enrichment of evaluations (PROMETHEE). The latter is a noncompensatory decision method that enables a clear comparison of alternatives and the identification of synergies and compromises. The following section explains the steps of decision methodology, which is exemplified in Section 3 through two case studies: the selection of a chemical route to produce glyceryl monostearate, and the selection of a formulation for cosmetic application.

2 Framework for the sustainability assessment of chemical products and processes at early design stages

Fig. 1.1 presents the steps involved in the multicriteria analyzes-based framework proposed in this chapter. The steps are based on the previously presented methodology (Serna et al., 2016), but in this proposal a new set of indicators applicable to both products and processes is presented, and a different MCDA method is used for the integration of assessments. The framework has four steps:

1.Problem definition. This includes the substeps of the objective statement, knowledge of the product, identification of alternatives, and information gathering.

2.Assessment of alternatives. This comprises the selection of appropriate indicators applicable at the early stages of product and process design, calculation of indicators for each alternative, and normalization of indicators.

3.Integration of assessments. This step involves the calculation of weights for the indicators, calculation of a global sustainability index, and the exploration of the relationship between indicators through a sensitivity analysis. In this study, for the assessment of alternatives, indicators applicable to early design stages of product and process design are presented. For the integration of assessments, the MCDA method is used.

4.Final decision

Fig. 1.1 Multicriteria analyses-based framework to assess product/process alternatives under sustainability criteria at early design stages. Adapted from Serna, J., Díaz, E., Narváez, P., Camargo, M., Gálvez, D., Orjuela, Á., 2016. Multi-criteria decision analysis for the selection of sustainable chemical process routes during early design stages. Chem. Eng. Res. Des. https://doi.org/10.1016/j.cherd.2016.07.001.

2.1 Problem definition

In this step, the scope of the design is defined and the product is thoroughly characterized (properties, specifications, prices, legal framework, etc.). If the product is not a formulation but the result of a reaction and a separation process, it is necessary to identify and study the possible chemical process routes and raw materials for its generation. If the product is a formulation, it is necessary to gather information about the possible ingredients to be used. In both cases, this information includes economic, safety, occupational health, and environmental properties of the substances, and operating conditions of the processes. Among others, sources for this information include:

•scientific papers

•safety data sheet of ingredients

•suppliers’ documentation

•reports from governmental and intergovernmental agencies and organizations (e.g., European Chemicals Agency (ECHA), the Organization for Economic Co-operation and Development (OECD), and the U.S. Environmental Protection Agency (EPA))

•scientific databases (e.g., PubChem, eChemPortal)

•ECHA dossier of chemicals

•group contribution methods to calculate some safety and occupational health indices for molecules (e.g., Ten et al., 2016)

•software that incorporates property estimation tools (e.g., EPI Suite from EPA)

2.2 Assessment of alternatives

During this stage, the performance of each alternative is assessed within the TBL dimensions through suitable indicators. Because the methodology is applicable to early design stages, when information on the social dimension is very scarce at this point, this dimension was indirectly assessed via health and safety indicators, as shown in Fig. 1.2.

Fig. 1.2 Sustainability indicators to assess product/process alternatives at early design stages.

2.2.1 Selection of indicators

A set of indicators is used to calculate the sustainability performance of different chemical process routes and formulations at the early design stages. Most of them are defined based on the GHS (United Nations, 2015b). The indicators can be calculated using the properties of the substances, which are normalized using their definition according to GHS Hazard statements (H statements). An H statement is assigned to a substance to indicate a hazard class (e.g., acute toxicity, eye irritation, flammability, etc.) and a hazard category (i.e., division of a hazard class that specifies its severity) (United Nations, 2015b). Alternatively, indicators can be defined directly from the H statements, which can be found in the safety information on substances. This approach was used because the GHS information was constructed on current scientific principles, is globally accepted, and is available for almost any commercial substance.

To complete the assessment, additional indicators outside the GHS are proposed. Most of them have been previously included in the WAR algorithm (Young and Cabezas, 1999) and the inherent safety index (ISI) approach (Heikkil, 1999). Some additional indicators are also proposed, and the complete list is presented in Table 1.1. It is not always necessary to use all the listed indicators; some of them can be disregarded or additional ones can be included. Decision-makers have to select the most suitable indicators according to product characteristics, the specific context of selection problem, and the availability of information.

Table 1.1