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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 P; Barrett, William M; Randall, Paul M.
Afiliación
  • Smith RL; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Ruiz-Mercado GJ; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Meyer DE; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Gonzalez MA; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Abraham JP; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Barrett WM; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
  • Randall PM; National Risk Management Research Laboratory, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268, United States.
ACS Sustain Chem Eng ; 5(5): 3786-3794, 2017.
Article en En | MEDLINE | ID: mdl-30245942
A methodology is described for developing a gate-to-gate life cycle inventory (LCI) of a chemical manufacturing process to support the application of life cycle assessment in the design and regulation of sustainable chemicals. The inventories were derived by first applying process design and simulation to develop a process flow diagram describing the energy and basic material flows of the system. Additional techniques developed by the United States Environmental Protection Agency for estimating uncontrolled emissions from chemical processing equipment were then applied to obtain a detailed emission profile for the process. Finally, land use for the process was estimated using a simple sizing model. The methodology was applied to a case study of acetic acid production based on the Cativa process. The results reveal improvements in the qualitative LCI for acetic acid production compared to commonly used databases and top-down methodologies. The modeling techniques improve the quantitative LCI results for inputs and uncontrolled emissions. With provisions for applying appropriate emission controls, the proposed method can provide an estimate of the LCI that can be used for subsequent life cycle assessments.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Aspecto: Patient_preference Idioma: En Revista: ACS Sustain Chem Eng Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Aspecto: Patient_preference Idioma: En Revista: ACS Sustain Chem Eng Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos