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Environmental impact evaluation model for industrial processes.

C P Li1, I K Hui

  • 1Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Kowloon.

Environmental Management
|May 4, 2001
PubMed
Summary
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This study introduces a new model for assessing manufacturing environmental impacts. It uses hazard scores to identify the most eco-friendly processes, aiding decision-making for sustainable production.

Area of Science:

  • Environmental Science
  • Industrial Ecology
  • Risk Assessment

Background:

  • Manufacturing processes pose significant environmental and human health risks.
  • Existing evaluation methods may lack a comprehensive, unified scoring system.
  • Quantifying diverse environmental impacts is crucial for sustainable industrial practices.

Purpose of the Study:

  • To propose a novel model for evaluating the environmental impact of manufacturing.
  • To develop a single-score system for comparing process environmental friendliness.
  • To provide a decision-making tool for selecting sustainable manufacturing options.

Main Methods:

  • Utilized the potency factor approach to categorize environmental impacts.
  • Classified impacts into five ecological and seven human health groups based on toxicological and physical effects.

Related Experiment Videos

  • Determined hazard scores for ecological and human health impacts.
  • Developed the Environmental Impact Evaluation System (EIES) software.

    • Main Results:

    • The model successfully classifies and scores environmental impacts.
    • A single score effectively represents the overall environmental burden of a process.
    • Demonstrated application using paper bag manufacturing processes.

    Conclusions:

    • The proposed model offers a robust method for evaluating manufacturing environmental impacts.
    • The single-score system facilitates the identification of the most environmentally friendly processes.
    • The EIES software serves as a valuable tool for industrial environmental performance assessment and decision-making.