Robustness of PM2.5 Source Allocation to Meteorological Variability—Evidence from 150 European Cities

Ambient fine particulate matter (PM2.5) poses a significant health risk in Europe, where many cities are exposed to levels exceeding WHO and EU guidelines. Reducing population exposure, therefore, calls for targeted and effective mitigation strategies. To support the implementation of optimal PM2.5 reduction policies, high-resolution air quality modeling is necessary. In this context, source allocation studies aim to link the pollution at a specific location to different emitters, typically expressing the contribution of each in terms of concentration differences. An alternative approach is the use of relative potentials, defined as the share of PM2.5 concentration reduced at a given receptor resulting from the reduction in the emissions from a given source. To calculate relative potentials, Source-Receptor Relationships (SRRs) can be used to mimic Chemical Transport Models, saving significant computation time when simulating emission reduction scenarios. However, while the relative potential indicator is increasingly used to guide source allocation analyses, its robustness with respect to meteorological variability has not been systematically evaluated. Given that meteorology can be a major driver of PM2.5 inter-annual variability, assessing this robustness is a prerequisite for the optimal use of SRRs in air quality planning. To address this gap, we use the SRR model SHERPA, based on the Chemical Transport Model EMEP, to evaluate the robustness of relative potentials of 150 European cities across four contrasting meteorological years (2015, 2017, 2019, and 2021). The contributions of four spatial reduction scales, six emission sectors and five emission precursors are analyzed. Our results show that relative potentials vary little with meteorology for most cities, with low inter-annual ranges for most spatial scales, precursors and sectors. These trends are consistent with EMEP simulations. They establish the robustness of the relative potential indicator and of SRR-based source allocations with respect to meteorological variability, supporting their use in guiding targeted air quality policies in Europe.

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Publication Details

Journal
Atmosphere
Published
2026-06-29
DOI
https://doi.org/10.3390/atmos17070641
Primary Topic
Air Quality and Health Impacts
Type
article
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article

Robustness of PM2.5 Source Allocation to Meteorological Variability—Evidence from 150 European Cities

Alexander de Meij, Enrico Pisoni, Anthony Rey-Pommier, Stefano Zauli-Sajani et al.
Atmosphere
Air Quality and Health Impacts
article

Robustness of PM2.5 Source Allocation to Meteorological Variability—Evidence from 150 European Cities

Alexander de Meij, Enrico Pisoni, Anthony Rey-Pommier, Stefano Zauli-Sajani, Philippe Thunis
article en

Abstract

Ambient fine particulate matter (PM2.5) poses a significant health risk in Europe, where many cities are exposed to levels exceeding WHO and EU guidelines. Reducing population exposure, therefore, calls for targeted and effective mitigation strategies. To support the implementation of optimal PM2.5 reduction policies, high-resolution air quality modeling is necessary. In this context, source allocation studies aim to link the pollution at a specific location to different emitters, typically expressing the contribution of each in terms of concentration differences. An alternative approach is the use of relative potentials, defined as the share of PM2.5 concentration reduced at a given receptor resulting from the reduction in the emissions from a given source. To calculate relative potentials, Source-Receptor Relationships (SRRs) can be used to mimic Chemical Transport Models, saving significant computation time when simulating emission reduction scenarios. However, while the relative potential indicator is increasingly used to guide source allocation analyses, its robustness with respect to meteorological variability has not been systematically evaluated. Given that meteorology can be a major driver of PM2.5 inter-annual variability, assessing this robustness is a prerequisite for the optimal use of SRRs in air quality planning. To address this gap, we use the SRR model SHERPA, based on the Chemical Transport Model EMEP, to evaluate the robustness of relative potentials of 150 European cities across four contrasting meteorological years (2015, 2017, 2019, and 2021). The contributions of four spatial reduction scales, six emission sectors and five emission precursors are analyzed. Our results show that relative potentials vary little with meteorology for most cities, with low inter-annual ranges for most spatial scales, precursors and sectors. These trends are consistent with EMEP simulations. They establish the robustness of the relative potential indicator and of SRR-based source allocations with respect to meteorological variability, supporting their use in guiding targeted air quality policies in Europe.

AtmosphereVol. 17(7)
Joint Research Centre (IT)
Sustainable cities and communities
Openalex Percentile: Top 9%
Air Quality and Health Impacts
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