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Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework
Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24 June 15-18, 2014, Budapest, Hungary. Copyright © 2014 Elsevier B.V. All rights reserved.
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework Carina L. Gargalo,a,b Ana Carvalho,c Henrique A. Matos,a* Rafiqul Gani,b a CPQ/DEQ, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal b CAPEC, Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark c CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001 Lisboa, Portugal [email protected]
Abstract Nowadays, companies are looking for new sustainable design alternatives that improve their original processes. To assess the best design alternative, economic aspects have been the preferred indicators. However, environmental and social concerns should also be included in the decision process so that truly sustainable design alternatives can be found. This work proposes a framework, called ‘Techno-Economic Sustainability Environmental Impact Diagnosis’ (TESED) that allows users to assess chemical/biochemical processes in a product oriented analysis. TESED is a systematic and generic approach that can be applied to any product/processes combination. Bioethanol production was the case-study selected to highlight the TESED framework. Two production processes using two different feedstocks, hardwood chips and cassava rhizome, have been analysed. Keywords: TESED; Bioethanol; Retrofit; Sustainability
1. Techno-Economic Sustainability Environmental Impact Diagnosis Framework (TESED) TESED is a generic and systematic framework to select the most sustainable process design of a target product. This framework employs a multi-level approach, where at the first level a set of possible processes, available to produce the target product, are analysed and more sustainable alternatives are generated for each process. At the end of this level, the new design alternatives, identified for each process, are assessed and the most sustainable is selected. At the second-level the most sustainable design alternatives defined in the first level are evaluated through a multi-criteria analysis, to determine the most sustainable process to produce the target product. The TESED framework is illustrated in Figure 1 and described in the text below. 1.1. Step 1 – Problem Definition In the first step of the framework the problem should be described and identified. The target product should be selected for the framework analysis. Then a set of processes available to produce the target product should be selected. These processes are classified as the Base Case design, which are the designs already available in the market to produce the target product.
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1.2. Step 2 – Data Collection In this step the data required to classify all Base Case designs is collected. This data can be collected from the literature or from the actual plant. The data collection process is divided into two sub-steps: 2.1 Product data collection (chemical compounds properties such as density, enthalpy of vaporization, thermal capacity, etc.) and 2.2 Process data collection (reactions, published process simulation, stream composition, operating conditions). 1.3. Step 3 – Process Simulation A rigorous simulation of the BaseCase design for each process is made in this step. Commercial simulators such as ASPEN or PRO II are used to simulate the Base Case designs. Through process simulation the remaining process data (mass and energy balances) required to perform the subsequent steps of the framework are obtained. 1.4. Step 4 – BaseCase Detailed Analysis At this stage, a complete analysis of all Base Case designs, with respect to process bottlenecks and sustainability metrics (step 4.1), economic factors (step 4.2) and environmental impact (step 4.3) is performed. The sustainability analysis (step 4.1) is performed through SustainPro (Carvalho et al., 2013) software. SustainPro is a software tool, which employs a retrofit methodology to propose new sustainable design alternatives for a Base Case design, based on sustainability metrics. Moreover, this tool is also used to assess the proposed new design alternatives. Step 4.2 employs another computer-aided tool, ECON, (Carvalho et al., 2013) to perform a full economic evaluation. Two of the most important parameters obtained through this software are the operational and capital costs. The potential environmental impact of a certain chemical/biochemical plant design is also estimated following step 4.3, where LCSoft (a third computer aided tool) is applied (Carvalho et al., 2013). Several environmental impact categories are estimated based on a cradle-to-gate analysis (potential environmental impacts and carbon footprint). From this step the first analysis of the Base Case designs is obtained and a set of indicators and metrics are available to classify them. 1.5. Step 5 – Bottleneck Identification Steps 1-4 provide a complete analysis on the Base Case design processes generating a good understanding of the process critical points with respect to sustainability issues, economic issues and environmental impacts. Through SustainPro and its systematic approach, the critical points of the process in terms of external dependence and natural resources consumption are identified. Next, based on the set of indicators obtained from SustainPro the bottlenecks with high potential for process improvements are identified. These critical points (step 4.1), are then verified through ECON (step 4.2) and LCSoft (step 4.3). The aforementioned tools are used as a cross-sectional approach integrating the current main areas of concern and identifying the set of indicators that represent the bottleneck. The bottlenecks that have the best chance for improvement are targeted for further study. In this way, the probability of achieving the desired (targeted) improvements in the sustainability, economics and environmental impacts of the process is increased.
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework
1023
No
Feedstock
Yes
Are there more feedstock to analyze?
Step1 – Problem & Fobj Definition
ICAS, Published Data
Step 2 – Data Collection
Step 7.2 – Final Comparison among Alternatives (TESED)
Best Alternative Step 5 Bottleneck Identification Step 6
ASPEN/ PROII
Step 3 - Process Simulation
Step 4
ECON
Step 4.1 Sustainability Analysis
SustainPro
Step 4.2 Economic Analysis
LCSoft
Step 4.3 – Life Cycle Assessment
Tool Information
Step 6.1 S Generation of New Design alternatives
ASPEN/ PROII
Step 6.2 Screening Alternatives
Sustainability Metrics & Objective Function
Step 7.1 Comparison to the BaseCase Scenario (TESED)
SustainPro ECON LCSoft
Best Design Alternative (for a specific feedstock)
Figure 1. Flow-diagram of TESED framework.
1.6. Step 6 – Generation & Evaluation of new design alternatives Step 6 is divided into two sub-steps: Step 6.1: here, a new design alternative to the Base Case design of a certain feedstock is generated, based on the bottlenecks identified in the previous step; Step 6.2: the New Design alternatives are compared and screened in terms of their sustainability metrics. It is important to note that after any change made in each Base Case design, for instance by either heat, mass or water integration, a new design alternative is generated. Therefore, the new design alternatives must be simulated again to allow comparison and screening of alternatives (Step 6.2). The most sustainable alternative is selected in Step 6.2 from all generated alternatives for a specific feedstock BaseCase design. The selection is performed through the application of sustainability metrics and the objective function introduced in step 1. The alternative that has the best values with respect to the design targets is selected for further analysis in the next step.
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1.7. Step 7 – Comparison of different design alternatives and Final Decision TESED proposes an option to compare several processes that produce a target product. Therefore, Step 7 is divided into two sub-steps: 7.1 and 7.2. In Step 7.1, the different best feasible alternatives from the step 6.2 are compared to Base Case design from each feedstock using SustainPro, ECON and LCSoft. In Step 7.2, the best alternative from Step 7.1 is selected, determining the most sustainable process design to produce the target product.
2. Case Study In this paper the bioethanol production process is studied in detail. The main results obtained by employing the framework are presented. 2.1. Step 1 The assessment of different process designs to produce Bioethanol was identified as the objective of the study. Bioethanol was selected as the target product. The selected Base Case designs for the production of bioethanol are based on two feedstocks: hardwood chips and cassava rhizome. 2.2. Step 2 & Step 3 Data for the two Base Case designs (Alvarado-Morales et al., 2009; Mangnimit, 2013) were collected. Based on the data of the BaseCase designs (processes using hardwood chips and cassava rhizome) the two processes were simulated using PROII. The flowsheet of bioethanol produced from hardwood chips and cassava rhizome were built considering 99.95 % purity of the bioethanol product. The most important data needed for process assessment are schematically shown in Table 1 & 2. 2.3. Step 4.1 SustainPro has been applied and a list containing the most critical indicators in terms of mass, water and energy consumption was obtained. For the hardwood chips process, the identified critical points are: 1) The excess of fresh water added to the system in the pre-treatment stage; 2) The excess of energy wasted in the output stream, since it has high energy content that can be integrated with a cold stream. For the cassava rhizome process, the two main critical points were identified: Table 1. Mass balance of the bioethanol production BaseCase from hardwood chips
Table 2. Mass balance of the bioethanol production BaseCase from cassava rhizome.
Hardwood Chips
Cassava rhizome
In
ton/day
Out
ton/day
Feedstock water
3819
419
NH3 Acid
31.8
Ethanol Waste gases residue Waste water
Z. mobilis Enzyme Lime Total in
5152 1183 7.44 106 18 10317
Total out
1223 32.3 8642
10317
In
ton/day
Out
ton/day
Feedstock HP+LP steam NH3
807
121
0.08
Acid
6
Enzyme Corn steep Liquor Lime
1.1
Ethanol Waste gases residue Waste water CaSO4
Total in
915
Total out
915
93
126 113 546 9
3.6 4.4
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework
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1) The fresh water that is being added to the process in the pre-treatment stage and then released as waste water; 2) The amount of solid residue that is being discarded as waste(mostly lignin), since it has economic value and it could be burned. 2.4. Step 4.2 A number of economic metrics were employed as criteria for comparison and were estimated using ECON. However, due to the limit of 6-pages per paper, only a few are presented here. Regarding bioethanol production from hardwood chips, the operational cost obtained was calculated as 0.520 $/kg of Ethanol and the process Internal Rate of Return (IRR) was 5 %. With respect to bioethanol production from cassava rhizome, the calculated operational cost was 0.258 $/kg of Ethanol and IRR was 25 %. 2.5. Step 4.3 Several environmental impact categories were predicted through LCSoft; nevertheless, due to the limit of space, only carbon footprint results are presented. Bioethanol produced from hardwood chips registered 5.91 kg CO2 eq./kg of Ethanol and from cassava rhizome was found to be 5.92 kg CO2 eq./kg of Ethanol. 2.6. Step 5 The critical points already identified by SustainPro were confirmed by the data obtained through ECON and LCSoft. To improve the identified process critical points and to increase the overall process sustainability, the major target was to decrease the amount of fresh water added to the system and the net energy input. 2.7. Step 6 For bioethanol production from hardwood chips, three different retrofit design alternatives were generated in order to overcome the identified bottlenecks (step 6.1) through heat integration (HC-A), water integration (HC-B) and a combination of heat and water integration (HC-C) were separately analyzed. For bioethanol production from cassava rhizome only the conjugated effect of water, energy co-production were tested (CR-A) (see Table 3). After screening (step 6.2), HC-C and CR-A were the retrofit options chosen with respect to bioethanol production from hardwood chips and cassava rhizome, respectively. 2.8. Step 7.1 In this step, both Base Cases were compared against the most sustainable alternative selected in step 6.2, and from that two designs come out.. Table 4 gives the performance criteria used for comparison of the two best alternatives: design-alternative HC-C for bioethanol production from hardwood chips and design-alternative CR-A for bioethanol production from cassava rhizome. 2.9. Step 7.2 According to Table 4, the best option with respect to the defined objectives of this study is bioethanol produced from cassava rhizome. Bioethanol production from cassava rhizome has improved water, raw materials and energy consumptions and the better economic factors, as well as larger operating profit. Likewise, with respect to environmental impact, the total carbon footprint of the processing plant has better values. Table 3. Retrofit options generated Hardwood chips
Cassava rhizome
HC-A
HC-B
HC-C
CR-A
heat integration
water integration
heat + water integration
Water recycle + energy co-production (steam/electricity by a turbo-generator)
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Table 4. Summary of the most relevant comparison metrics obtained in Step 7.1. Alternative selected in Step 7.2 Raw Material usage (kg RM/kg EtOH) Total Energy usage (GJ/kg of EtOH) Net Fresh Water added(kg/kg of EtOH) Total Utility Cost ($/kg of EtOH) Operating Cost($/kg of EtOH) Capital Cost ($/kg of EtOH) Operating Profit ($/kg of EtOH) Net Present Value Internal Rate of Return (IRR) Ethanol minimum selling Price ($/kg) Total Carbon Footprint (kg CO2/kg of EtOH) Ozone Depletion Potential(CFC-11eq.)
HARDWOOD CHIPS HC-C 8.96 0.12 6.14 0.221 0.48 0.69 0.19 230 8% 0.51 5 6.31E-07
CASSAVA RHIZOME CR-A 3.103 0.013 1.45 0.007 0.111 0.65 0.46 157 45% 0.14 4 1.26E-10
3. Conclusion A framework, which assesses the Techno-Economic, Sustainability and Environmental Impact Diagnosis (TESED) of chemical/biochemical processes for a target product production has been presented. TESED is not only a systematic way of generating more sustainable, economic and environmentally feasible options, but it also provides options to perform multi-criteria comparison of alternatives. Thereby enabling, the simultaneous comparison of different processes producing the same product. Currently TESED was used to test the production from different feedstock. Bioethanol produced from hardwood chips and cassava rhizome was the case study selected to highlight the application of the framework. Bioethanol produced from cassava rhizome was found to be a better option with respect to the multi-criteria set of metrics that were employed.
References M. Alvarado-Morales, J. Terra, K. V. Gernaey, J. M. Woodley, R. Gani, 2009, Biorefining: Computer aided tools for sustainable design and analysis of bioethanol production, Chemical Engineering Research and Design, 87, 9, 1171–1183. A. Carvalho, H. A. Matos, R. Gani, 2013, SustainPro—A tool for systematic process analysis, generation and evaluation of sustainable design alternatives, Computers and Chemical Engineering, 50, 8–27. S. Mangnimit, P. Malakul, R. Gani, 2013, Sustainable process design of biofuels: bioethanol production from cassava rhizome, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA), Kuala Lumpur.
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework Carina L. Gargalo,a,b Ana Carvalho,c Henrique A. Matos,a* Rafiqul Gani,b a CPQ/DEQ, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal b CAPEC, Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Lyngby, Denmark c CEG-IST, Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001 Lisboa, Portugal [email protected]
Abstract Nowadays, companies are looking for new sustainable design alternatives that improve their original processes. To assess the best design alternative, economic aspects have been the preferred indicators. However, environmental and social concerns should also be included in the decision process so that truly sustainable design alternatives can be found. This work proposes a framework, called ‘Techno-Economic Sustainability Environmental Impact Diagnosis’ (TESED) that allows users to assess chemical/biochemical processes in a product oriented analysis. TESED is a systematic and generic approach that can be applied to any product/processes combination. Bioethanol production was the case-study selected to highlight the TESED framework. Two production processes using two different feedstocks, hardwood chips and cassava rhizome, have been analysed. Keywords: TESED; Bioethanol; Retrofit; Sustainability
1. Techno-Economic Sustainability Environmental Impact Diagnosis Framework (TESED) TESED is a generic and systematic framework to select the most sustainable process design of a target product. This framework employs a multi-level approach, where at the first level a set of possible processes, available to produce the target product, are analysed and more sustainable alternatives are generated for each process. At the end of this level, the new design alternatives, identified for each process, are assessed and the most sustainable is selected. At the second-level the most sustainable design alternatives defined in the first level are evaluated through a multi-criteria analysis, to determine the most sustainable process to produce the target product. The TESED framework is illustrated in Figure 1 and described in the text below. 1.1. Step 1 – Problem Definition In the first step of the framework the problem should be described and identified. The target product should be selected for the framework analysis. Then a set of processes available to produce the target product should be selected. These processes are classified as the Base Case design, which are the designs already available in the market to produce the target product.
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1.2. Step 2 – Data Collection In this step the data required to classify all Base Case designs is collected. This data can be collected from the literature or from the actual plant. The data collection process is divided into two sub-steps: 2.1 Product data collection (chemical compounds properties such as density, enthalpy of vaporization, thermal capacity, etc.) and 2.2 Process data collection (reactions, published process simulation, stream composition, operating conditions). 1.3. Step 3 – Process Simulation A rigorous simulation of the BaseCase design for each process is made in this step. Commercial simulators such as ASPEN or PRO II are used to simulate the Base Case designs. Through process simulation the remaining process data (mass and energy balances) required to perform the subsequent steps of the framework are obtained. 1.4. Step 4 – BaseCase Detailed Analysis At this stage, a complete analysis of all Base Case designs, with respect to process bottlenecks and sustainability metrics (step 4.1), economic factors (step 4.2) and environmental impact (step 4.3) is performed. The sustainability analysis (step 4.1) is performed through SustainPro (Carvalho et al., 2013) software. SustainPro is a software tool, which employs a retrofit methodology to propose new sustainable design alternatives for a Base Case design, based on sustainability metrics. Moreover, this tool is also used to assess the proposed new design alternatives. Step 4.2 employs another computer-aided tool, ECON, (Carvalho et al., 2013) to perform a full economic evaluation. Two of the most important parameters obtained through this software are the operational and capital costs. The potential environmental impact of a certain chemical/biochemical plant design is also estimated following step 4.3, where LCSoft (a third computer aided tool) is applied (Carvalho et al., 2013). Several environmental impact categories are estimated based on a cradle-to-gate analysis (potential environmental impacts and carbon footprint). From this step the first analysis of the Base Case designs is obtained and a set of indicators and metrics are available to classify them. 1.5. Step 5 – Bottleneck Identification Steps 1-4 provide a complete analysis on the Base Case design processes generating a good understanding of the process critical points with respect to sustainability issues, economic issues and environmental impacts. Through SustainPro and its systematic approach, the critical points of the process in terms of external dependence and natural resources consumption are identified. Next, based on the set of indicators obtained from SustainPro the bottlenecks with high potential for process improvements are identified. These critical points (step 4.1), are then verified through ECON (step 4.2) and LCSoft (step 4.3). The aforementioned tools are used as a cross-sectional approach integrating the current main areas of concern and identifying the set of indicators that represent the bottleneck. The bottlenecks that have the best chance for improvement are targeted for further study. In this way, the probability of achieving the desired (targeted) improvements in the sustainability, economics and environmental impacts of the process is increased.
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework
1023
No
Feedstock
Yes
Are there more feedstock to analyze?
Step1 – Problem & Fobj Definition
ICAS, Published Data
Step 2 – Data Collection
Step 7.2 – Final Comparison among Alternatives (TESED)
Best Alternative Step 5 Bottleneck Identification Step 6
ASPEN/ PROII
Step 3 - Process Simulation
Step 4
ECON
Step 4.1 Sustainability Analysis
SustainPro
Step 4.2 Economic Analysis
LCSoft
Step 4.3 – Life Cycle Assessment
Tool Information
Step 6.1 S Generation of New Design alternatives
ASPEN/ PROII
Step 6.2 Screening Alternatives
Sustainability Metrics & Objective Function
Step 7.1 Comparison to the BaseCase Scenario (TESED)
SustainPro ECON LCSoft
Best Design Alternative (for a specific feedstock)
Figure 1. Flow-diagram of TESED framework.
1.6. Step 6 – Generation & Evaluation of new design alternatives Step 6 is divided into two sub-steps: Step 6.1: here, a new design alternative to the Base Case design of a certain feedstock is generated, based on the bottlenecks identified in the previous step; Step 6.2: the New Design alternatives are compared and screened in terms of their sustainability metrics. It is important to note that after any change made in each Base Case design, for instance by either heat, mass or water integration, a new design alternative is generated. Therefore, the new design alternatives must be simulated again to allow comparison and screening of alternatives (Step 6.2). The most sustainable alternative is selected in Step 6.2 from all generated alternatives for a specific feedstock BaseCase design. The selection is performed through the application of sustainability metrics and the objective function introduced in step 1. The alternative that has the best values with respect to the design targets is selected for further analysis in the next step.
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1.7. Step 7 – Comparison of different design alternatives and Final Decision TESED proposes an option to compare several processes that produce a target product. Therefore, Step 7 is divided into two sub-steps: 7.1 and 7.2. In Step 7.1, the different best feasible alternatives from the step 6.2 are compared to Base Case design from each feedstock using SustainPro, ECON and LCSoft. In Step 7.2, the best alternative from Step 7.1 is selected, determining the most sustainable process design to produce the target product.
2. Case Study In this paper the bioethanol production process is studied in detail. The main results obtained by employing the framework are presented. 2.1. Step 1 The assessment of different process designs to produce Bioethanol was identified as the objective of the study. Bioethanol was selected as the target product. The selected Base Case designs for the production of bioethanol are based on two feedstocks: hardwood chips and cassava rhizome. 2.2. Step 2 & Step 3 Data for the two Base Case designs (Alvarado-Morales et al., 2009; Mangnimit, 2013) were collected. Based on the data of the BaseCase designs (processes using hardwood chips and cassava rhizome) the two processes were simulated using PROII. The flowsheet of bioethanol produced from hardwood chips and cassava rhizome were built considering 99.95 % purity of the bioethanol product. The most important data needed for process assessment are schematically shown in Table 1 & 2. 2.3. Step 4.1 SustainPro has been applied and a list containing the most critical indicators in terms of mass, water and energy consumption was obtained. For the hardwood chips process, the identified critical points are: 1) The excess of fresh water added to the system in the pre-treatment stage; 2) The excess of energy wasted in the output stream, since it has high energy content that can be integrated with a cold stream. For the cassava rhizome process, the two main critical points were identified: Table 1. Mass balance of the bioethanol production BaseCase from hardwood chips
Table 2. Mass balance of the bioethanol production BaseCase from cassava rhizome.
Hardwood Chips
Cassava rhizome
In
ton/day
Out
ton/day
Feedstock water
3819
419
NH3 Acid
31.8
Ethanol Waste gases residue Waste water
Z. mobilis Enzyme Lime Total in
5152 1183 7.44 106 18 10317
Total out
1223 32.3 8642
10317
In
ton/day
Out
ton/day
Feedstock HP+LP steam NH3
807
121
0.08
Acid
6
Enzyme Corn steep Liquor Lime
1.1
Ethanol Waste gases residue Waste water CaSO4
Total in
915
Total out
915
93
126 113 546 9
3.6 4.4
Techno-Economic, Sustainability & Environmental Impact Diagnosis (TESED) Framework
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1) The fresh water that is being added to the process in the pre-treatment stage and then released as waste water; 2) The amount of solid residue that is being discarded as waste(mostly lignin), since it has economic value and it could be burned. 2.4. Step 4.2 A number of economic metrics were employed as criteria for comparison and were estimated using ECON. However, due to the limit of 6-pages per paper, only a few are presented here. Regarding bioethanol production from hardwood chips, the operational cost obtained was calculated as 0.520 $/kg of Ethanol and the process Internal Rate of Return (IRR) was 5 %. With respect to bioethanol production from cassava rhizome, the calculated operational cost was 0.258 $/kg of Ethanol and IRR was 25 %. 2.5. Step 4.3 Several environmental impact categories were predicted through LCSoft; nevertheless, due to the limit of space, only carbon footprint results are presented. Bioethanol produced from hardwood chips registered 5.91 kg CO2 eq./kg of Ethanol and from cassava rhizome was found to be 5.92 kg CO2 eq./kg of Ethanol. 2.6. Step 5 The critical points already identified by SustainPro were confirmed by the data obtained through ECON and LCSoft. To improve the identified process critical points and to increase the overall process sustainability, the major target was to decrease the amount of fresh water added to the system and the net energy input. 2.7. Step 6 For bioethanol production from hardwood chips, three different retrofit design alternatives were generated in order to overcome the identified bottlenecks (step 6.1) through heat integration (HC-A), water integration (HC-B) and a combination of heat and water integration (HC-C) were separately analyzed. For bioethanol production from cassava rhizome only the conjugated effect of water, energy co-production were tested (CR-A) (see Table 3). After screening (step 6.2), HC-C and CR-A were the retrofit options chosen with respect to bioethanol production from hardwood chips and cassava rhizome, respectively. 2.8. Step 7.1 In this step, both Base Cases were compared against the most sustainable alternative selected in step 6.2, and from that two designs come out.. Table 4 gives the performance criteria used for comparison of the two best alternatives: design-alternative HC-C for bioethanol production from hardwood chips and design-alternative CR-A for bioethanol production from cassava rhizome. 2.9. Step 7.2 According to Table 4, the best option with respect to the defined objectives of this study is bioethanol produced from cassava rhizome. Bioethanol production from cassava rhizome has improved water, raw materials and energy consumptions and the better economic factors, as well as larger operating profit. Likewise, with respect to environmental impact, the total carbon footprint of the processing plant has better values. Table 3. Retrofit options generated Hardwood chips
Cassava rhizome
HC-A
HC-B
HC-C
CR-A
heat integration
water integration
heat + water integration
Water recycle + energy co-production (steam/electricity by a turbo-generator)
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Table 4. Summary of the most relevant comparison metrics obtained in Step 7.1. Alternative selected in Step 7.2 Raw Material usage (kg RM/kg EtOH) Total Energy usage (GJ/kg of EtOH) Net Fresh Water added(kg/kg of EtOH) Total Utility Cost ($/kg of EtOH) Operating Cost($/kg of EtOH) Capital Cost ($/kg of EtOH) Operating Profit ($/kg of EtOH) Net Present Value Internal Rate of Return (IRR) Ethanol minimum selling Price ($/kg) Total Carbon Footprint (kg CO2/kg of EtOH) Ozone Depletion Potential(CFC-11eq.)
HARDWOOD CHIPS HC-C 8.96 0.12 6.14 0.221 0.48 0.69 0.19 230 8% 0.51 5 6.31E-07
CASSAVA RHIZOME CR-A 3.103 0.013 1.45 0.007 0.111 0.65 0.46 157 45% 0.14 4 1.26E-10
3. Conclusion A framework, which assesses the Techno-Economic, Sustainability and Environmental Impact Diagnosis (TESED) of chemical/biochemical processes for a target product production has been presented. TESED is not only a systematic way of generating more sustainable, economic and environmentally feasible options, but it also provides options to perform multi-criteria comparison of alternatives. Thereby enabling, the simultaneous comparison of different processes producing the same product. Currently TESED was used to test the production from different feedstock. Bioethanol produced from hardwood chips and cassava rhizome was the case study selected to highlight the application of the framework. Bioethanol produced from cassava rhizome was found to be a better option with respect to the multi-criteria set of metrics that were employed.
References M. Alvarado-Morales, J. Terra, K. V. Gernaey, J. M. Woodley, R. Gani, 2009, Biorefining: Computer aided tools for sustainable design and analysis of bioethanol production, Chemical Engineering Research and Design, 87, 9, 1171–1183. A. Carvalho, H. A. Matos, R. Gani, 2013, SustainPro—A tool for systematic process analysis, generation and evaluation of sustainable design alternatives, Computers and Chemical Engineering, 50, 8–27. S. Mangnimit, P. Malakul, R. Gani, 2013, Sustainable process design of biofuels: bioethanol production from cassava rhizome, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA), Kuala Lumpur.