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Title: Multi-Attribute Decision Theory methodology for pollution control measure analysis

Conference ·
OSTI ID:6728107
;  [1]; ;  [2]
  1. Instituto Mexicano de Petroleo, Mexico City (Mexico)
  2. Los Alamos National Lab., NM (United States)

A methodology based in Multi-Attribute Decision Theory was developed to prioritize air pollution control measures and strategies (a set of measures) for Mexico City Metropolitan Area (MCMA). We have developed a framework that takes into account economic, technical feasibility, environmental, social, political, and institutional factors to evaluate pollution mitigation measures and strategies utilizing a decision analysis process. In a series of meetings with a panel of experts in air pollution from different offices of the mexican government we have developed General and Specific criteria for a decision analysis tree. With these tools the measures or strategies can be graded and a figure of merit can be assigned to each of them, so they can be ranked. Two pollution mitigation measures were analyzed to test the methodology, the results are presented. This methodology was developed specifically for Mexico City, though the experience gained in this work can be used to develop similar methodologies for other metropolitan areas throughout the world.

Research Organization:
Los Alamos National Lab., NM (United States)
Sponsoring Organization:
USDOE; USDOE, Washington, DC (United States)
DOE Contract Number:
W-7405-ENG-36
OSTI ID:
6728107
Report Number(s):
LA-UR-92-4063; CONF-930208-2; ON: DE93005444
Resource Relation:
Conference: International symposium on air pollution, Monterrey (Mexico), 16-25 Feb 1993
Country of Publication:
United States
Language:
English