Coupling Computer-Aided Process Simulation and Estimations of Emissions and Land Use for Rapid Life Cycle Inventory Modeling

Smith, Raymond L.; Ruiz-Mercado, Gerardo J.; Meyer, David E.; Gonzalez, Michael A.; Abraham, John; Barrett, William M.; Randall, Paul M.

doi:10.1021/acssuschemeng.6b02724

Cited by 44 publications

(50 citation statements)

References 24 publications

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“…More recent approaches are based on advanced process calculations (65,66) and data mining (67). Parvatker & Eckelman (44) compared these prediction methods for LCI.…”

Section: Data Sources For Background Systemsmentioning

confidence: 99%

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

Kleinekorte

Fleitmann

Bachmann

et al. 2020

Annu. Rev. Chem. Biomol. Eng.

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Design in the chemical industry increasingly aims not only at economic but also at environmental targets. Environmental targets are usually best quantified using the standardized, holistic method of life cycle assessment (LCA). The resulting life cycle perspective poses a major challenge to chemical engineering design because the design scope is expanded to include process, product, and supply chain. Here, we first provide a brief tutorial highlighting key elements of LCA. Methods to fill data gaps in LCA are discussed, as capturing the full life cycle is data intensive. On this basis, we review recent methods for integrating LCA into the design of chemical processes, products, and supply chains. Whereas adding LCA as a posteriori tool for decision support can be regarded as established, the integration of LCA into the design process is an active field of research. We present recent advances and derive future challenges for LCA-based design. 203 Annu. Rev. Chem. Biomol. Eng. 2020.11:203-233. Downloaded from www.annualreviews.org Access provided by 44.224.250.200 on 07/08/20. For personal use only.

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“…More recent approaches are based on advanced process calculations (65,66) and data mining (67). Parvatker & Eckelman (44) compared these prediction methods for LCI.…”

Section: Data Sources For Background Systemsmentioning

confidence: 99%

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

Kleinekorte

Fleitmann

Bachmann

et al. 2020

Annu. Rev. Chem. Biomol. Eng.

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“…Where necessary, end-of-pipe treatment needs to be applied to such streams. 56 Smith et al 51 showed how simulations can be improved with vent, storage, and fugitive emission models. This work provides spreadsheet tools for storage and fugitive emission calculations and on-site utility generation.…”

Section: Methodsmentioning

confidence: 99%

Applying Environmental Release Inventories and Indicators to the Evaluation of Chemical Manufacturing Processes in Early Stage Development

Smith

Tan

Ruiz-Mercado

2019

ACS Sustainable Chem. Eng.

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As manufacturing processes are developed through the early stages of technology readiness, various assessments can be used to evaluate their performance. Performance indicators describe processes by transforming attributes into scores that represent desirable objectives. One type of assessment is obtained by determining the life cycle inventories of inputs and outputs for processes. For a functional unit of product, the user finds the resources used and the releases to the environment, which can be compared to results for similar processes and/or combined with other processes in the life cycle. In this work, an expanded range of process inputs and releases is modeled, including forklift/loader, fugitive, storage, boiler, and cooling tower emissions. A generic scenario approach for the cooling tower releases provides a first approximation of emission and wastewater flows. These inventory values are used in performance indicators that can be placed on a scale between fixed best-and worst-case limits with the GREENSCOPE methodology, thus allowing comparisons across various technologies. The processes of interest are two conversion pathways for producing cellulosic ethanol from biomass via thermochemical and biochemical routes. The results can be used in risk assessments, decision making, evaluation of research, and in spurring future technology development.

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“…This work is interesting because the authors developed methods to model ancillary energy processes (Jiménez‐González, 2000b) separate from the chemical of interest (Jiménez‐González et al., 2000a). Numerous other examples of using process design in LCI modeling have followed (Alvarado et al., 2019; Geisler, Hofstetter, & Hungerbühler, 2004; Parvatker et al., 2019; Simon et al., 2019; Yao, 2018), with this approach eventually expanding to include full process simulation (Liao, Kelley, & Yao, 2020; Smith et al., 2017). Although effective, process design and simulation often require detailed process knowledge and chemical engineering expertise that may not be practical or readily available (Meyer et al., 2019; Parvatker, 2018).…”

Section: Introductionmentioning

confidence: 99%

Improving the reliability of chemical manufacturing life cycle inventory constructed using secondary data

Meyer

Cashman

Gaglione

2020

J of Industrial Ecology

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This study proposes methods to improve data mining workflows for modeling chemical manufacturing life cycle inventory. Secondary data sources can provide valuable information about environmental releases during chemical manufacturing. However, the often facility‐level nature of the data challenges their utility for modeling specific processes and can impact the quality of the resulting inventory. First, a thorough data source analysis is performed to establish data quality scoring and create filtering rules to resolve data selection issues when source and species overlaps arise. A method is then introduced to develop context‐based filter rules that leverage process metadata within data sources to improve how facility air releases are attributed to specific processes and increase the technological correlation and completeness of the inventory. Finally, a sanitization method is demonstrated to improve data quality by minimizing the exclusion of confidential business information (CBI). The viability of the methods is explored using case studies of cumene and sodium hydroxide production in the United States. The attribution of air releases using process context enables more sophisticated filtering to remove unnecessary flows from the inventory. The ability to sanitize and incorporate CBI is promising because it increases the sample size, and therefore representativeness, when constructing geographically averaged inventories. Future work will focus on expanding the application of context‐based data filtering to other types and sources of environmental data.

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Coupling Computer-Aided Process Simulation and Estimations of Emissions and Land Use for Rapid Life Cycle Inventory Modeling

Cited by 44 publications

References 24 publications

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

Life Cycle Assessment for the Design of Chemical Processes, Products, and Supply Chains

Applying Environmental Release Inventories and Indicators to the Evaluation of Chemical Manufacturing Processes in Early Stage Development

Improving the reliability of chemical manufacturing life cycle inventory constructed using secondary data

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