Combining a Multi-Objective Approach and Multi-Criteria Decision Analysis to Include the Socio-Economic Dimension in an Air Quality Management Problem

Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary P M 10 fractions ar...

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Bibliographic Details
Published inAtmosphere Vol. 10; no. 7; p. 381
Main Authors Turrini, Enrico, Vlachokostas, Christos, Volta, Marialuisa
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2019
Subjects
Air pollution
Air quality
Air quality management
Airborne particulates
Analysis
Costs
Decision analysis
Decision making
decision support systems
Economic analysis
Economics
Environmental law
environmental modelling
Experts
integrated assessment modelling
Methods
multi-criteria decision analysis
multi-objective approach
Multiple criterion
Multiple objective analysis
Neural networks
Objective analysis
Particulate emissions
Particulate matter
Planning
Pollutants
Quality management
Social factors
Socioeconomic aspects
Sociology
Subjectivity
Suspended particulate matter
Greece
France
Italy
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Summary:Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary P M 10 fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA.
ISSN:2073-4433
2073-4433
DOI:10.3390/atmos10070381