Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies
AbstractA decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.
HighlightsA modelling framework for evaluating UK air quality policies has been developed.The framework combines decision analysis, air pollution and impact modelling.Multi-criteria decision analysis is used for comparative evaluation of policies.The framework is used to evaluate idealized UK air quality policies.
Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies
AbstractA decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.
HighlightsA modelling framework for evaluating UK air quality policies has been developed.The framework combines decision analysis, air pollution and impact modelling.Multi-criteria decision analysis is used for comparative evaluation of policies.The framework is used to evaluate idealized UK air quality policies.
Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies
Chalabi, Zaid (Autor:in) / Milojevic, Ai (Autor:in) / Doherty, Ruth M. (Autor:in) / Stevenson, David S. (Autor:in) / MacKenzie, Ian A. (Autor:in) / Milner, James (Autor:in) / Vieno, Massimo (Autor:in) / Williams, Martin (Autor:in) / Wilkinson, Paul (Autor:in)
Atmospheric Environment ; 167 ; 466-475
22.08.2017
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Utilizing Multi-Criteria Decision Making to Evaluate the Quality of Healthcare Services
| DOAJ | 2022
| British Library Online Contents | 2013
| DOAJ | 2023
Applying multi-criteria decision analysis to select WSUD and LID technologies
| Online Contents | 2012