Multi-level policies for air quality: implications of national and sub-national emission reductions on population exposure

Emanuela Peduzzi,Alain Clappier,Enrico Pisoni,Philippe Thunis

doi:10.1007/s11869-018-0613-1

Abstract

Poor air quality and related health impacts are still an issue in many cities and regions worldwide. Integrated assessment models (IAMs) can support the design of measures to reduce the emissions of precursors affecting air pollution. In this study, we apply the SHERPA (screening for high emission reduction potentials for air quality) model to compare spatial and sectoral emission reductions, given country-scale emission targets. Different approaches are tested: (a) country ”uniform” emission reductions, (b) emission reductions targeting urban areas, (c) emission reductions targeting preferential sectors. As a case study, we apply the approaches to the implementation of the National Emission Ceiling Directive. Results are evaluated in terms of the reduction in average population exposure to PM2.5 overall in a country and in its main cities. Results indicate that the reduction of population exposure to PM2.5 highly depends on the way emission reductions are implemented. This work also shows the usefulness of the SHERPA model to support national authorities implementing national emission reduction targets while, at the same time, addressing their local air quality issues.

Highlights

Integrated assessment models (IAMs) are increasingly used to support the development of air quality (AQ) policies (Thunis et al 2016b)
Several surrogate modelling approaches applied to AQ are reviewed by Clappier et al (2015)
The number and type of simulations performed within this set and the type of surrogate model will determine the range of application and the flexibility of the surrogate model to address specific issues

Summary

Introduction

Integrated assessment models (IAMs) are increasingly used to support the development of air quality (AQ) policies (Thunis et al 2016b). They provide a simplification of reality that allows users to simulate and connect complex phenomena. They can be used to evaluate, for example, policy scenarios and their consequent emission reductions in terms of pollutant concentrations changes and environmental, health and economic impacts. The surrogate model is normally a simplification of complex chemical transport models (CTMs) that allows the user to rapidly evaluate the pollutant concentration changes (by cell, sector, region or country). The challenge is to cover the widest range of applicability for the lowest number of full CTM simulations (which are time-consuming)

Objectives

Findings

Discussion

Conclusion