Modelling the impact of energy transitions on air quality and source receptor relations

Abstract

Air pollution is associated with adverse effects on human health through exposure to PM and ozone. To design effective air pollution mitigation strategies it is essential to quantify the effect of pollutant emission reductions on their concentrations as well as health and ecosystem impacts. Within integrated assessment modeling source-receptor relationships (SRRs) are used that are based on chemistry transport modelling. Currently, these SRRs are made using invariant emission time profiles. The LOTOS-EUROS model equipped with a source attribution module was used to test this assumptions for renewable energy scenarios. Renewable energy availability and thereby fossil fuel back up are strongly dependent on meteorological conditions. We have used the spatially and temporally explicit energy model REMix to derive time profiles for backup power generation. These time profiles were used in LOTOS-EUROS to investigate the effect of emission timing on air pollutant concentrations and SRRs. It is found that the effectiveness of emission reduction in the power sector is significantly lower when accounting for the shift in the way emissions are divided over the year and the correlation of emissions with synoptic situations. The source receptor relationships also changed significantly. This effect was found for both primary and secondary pollutants. Our results indicate that emission timing deserves explicit attention when assessing the impacts of system changes on air quality.