Research Grants/Fellowships/SBIR

Computer-Aided Hybrid Models for Environmental and Economic Life-Cycle Assessment

EPA Grant Number: R829597
Title: Computer-Aided Hybrid Models for Environmental and Economic Life-Cycle Assessment
Investigators: Horvath, Arpad , Eyerer, Peter , Hendrickson, Chris
Institution: University of California - Berkeley , Carnegie Mellon University , University of Stuttgart
EPA Project Officer: Karn, Barbara
Project Period: January 1, 2002 through December 31, 2004
Project Amount: $325,000
RFA: Technology for a Sustainable Environment (2001) RFA Text |  Recipients Lists
Research Category: Sustainability , Pollution Prevention/Sustainable Development


The proposed research is to develop hybrid models that will overcome the major limitations of the two LCA approaches currently practiced: one based on detailed process model descriptions and corresponding emissions and wastes, and the other based on economic input-output data and publicly available resource consumption and environmental discharge data (EIO-LCA). While both approaches have advantages, both have major limitations as well. We will demonstrate the utility and comprehensiveness of hybrid models combining both LCA approaches by applying them to life-cycle studies from different sectors of the economy. The objectives are (1) to determine which of the three hybrid LCA models lead to more comprehensive and less uncertain results for a given application, or category of products, (2) to find out which hybrid LCA models are useful to what level of decision-making, and (3) to determine the accuracy and comprehensiveness of hybrid LCA models against the stand-alone process-based and EIO-LCA models.


We will integrate the two models such that the hybrid models (1) include detailed process-level environmental data as well as economy-wide (supply chain) environmental impacts ("the best of both worlds"), (2) have environmental and economic information about the major products and processes in the economy, (3) quantify a wide range of environmental data, and (4) provide answers to all decision-making groups (designers, managers, regulatory agencies, consumers, public policy-makers) so that LCA can help inform environmental, design, and business decisions. The project will involve the close collaboration of a team of researchers from UC Berkeley's Consortium on Green Design and Manufacturing, Carnegie Mellon University's Green Design Initiative (home of the EIO-LCA software), and the Institute for Polymer Testing and Polymer Science from the University of Stuttgart, Germany (where the detailed and comprehensive process model-based life-cycle engineering approach called GaBi is developed).

Expected Results:

The hybrid approach would let the user combine models, or choose from several LCA models with more or less detail as the application or time and monetary constraints dictate. At the most detailed level would be the process-level LCA. At the most aggregate end would be the current input-output analysis-based model. Computer interfaces will be developed to facilitate the practical implementation of the hybrid models. Research results will become part of educational efforts at the University of California, Berkeley, and Carnegie Mellon University.

Estimated Improvement:

This research will provide information that will contribute to more informed decisions concerning choices among materials, processes, products and services in order to improve environmental quality and promote sustainable development.

Publications and Presentations:

Publications have been submitted on this project: View all 37 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 15 journal articles for this project

Supplemental Keywords:

life-cycle analysis, pollution prevention, industrial ecology, sustainable development., RFA, Scientific Discipline, Air, Sustainable Industry/Business, Sustainable Environment, climate change, Air Pollution Effects, Economics, Technology for Sustainable Environment, Economics and Business, Environmental Engineering, Atmosphere, computational simulations, environmental monitoring, life cycle analysis, cleaner production, clean technologies, green design, life cycle inventory, computer models, environmental sustainability, computer science, industrial ecology, clean manufacturing, computer generated alternatives, pollution prevention design, life cycle assessment, pollution prevention, environmental cost analysis

Progress and Final Reports:
2002 Progress Report
Final Report