Technical note: sensitivity of the CAMS regional air quality modelling system to anthropogenic emission temporal variability

Abstract. An accurate characterization of the temporal distribution in primary emissions is essential for air quality modeling. This study evaluates the impact of replacing the default temporal profiles in the Copernicus Atmosphere Monitoring Service (CAMS) European air quality multi-model ensemble with an updated dataset (CAMS-REG-TEMPO). The sensitivity of 11 regional models and the ensemble to these changes is assessed by comparing modeled and observed monthly, weekly, and diurnal cycles of nitrogen dioxide (NO2), ozone (O3), coarse particulate matter (PM10), and fine particulate matter (PM2.5) across Europe. NO2 shows the greatest improvement, with weekly cycle correlations increasing up to +0.17 due to better road transport emissions representation. PM10 correlations improve in winter (up to +0.13 weekly and +0.07 diurnal) due to refined residential wood combustion emissions. PM2.5 correlations remain largely unchanged, except for diurnal cycles, which improve in winter (+0.18) but slightly degrade in spring and summer (−0.02). O3 is the least affected, as correlations were already high with default profiles (0.9–0.95). For some species and timescales (e.g., NO2 diurnal cycles), results vary across models, highlighting the complex interactions between emission timing and atmospheric processes. CAMS-REG-TEMPO has little effect on annual RMSE and bias, aside from slight improvements in high PM10 concentrations. Overall, the findings support implementing CAMS-REG-TEMPO in the operational CAMS multi-model ensemble.

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Publication Details

Journal
Atmospheric chemistry and physics
Published
2025-10-21
DOI
https://doi.org/10.5194/acp-25-13245-2025
Citations
1
Primary Topic
Atmospheric chemistry and aerosols
Type
article
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1.30
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Technical note: sensitivity of the CAMS regional air quality modelling system to anthropogenic emission temporal variability

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Technical note: sensitivity of the CAMS regional air quality modelling system to anthropogenic emission temporal variability

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article en
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Abstract

Abstract. An accurate characterization of the temporal distribution in primary emissions is essential for air quality modeling. This study evaluates the impact of replacing the default temporal profiles in the Copernicus Atmosphere Monitoring Service (CAMS) European air quality multi-model ensemble with an updated dataset (CAMS-REG-TEMPO). The sensitivity of 11 regional models and the ensemble to these changes is assessed by comparing modeled and observed monthly, weekly, and diurnal cycles of nitrogen dioxide (NO2), ozone (O3), coarse particulate matter (PM10), and fine particulate matter (PM2.5) across Europe. NO2 shows the greatest improvement, with weekly cycle correlations increasing up to +0.17 due to better road transport emissions representation. PM10 correlations improve in winter (up to +0.13 weekly and +0.07 diurnal) due to refined residential wood combustion emissions. PM2.5 correlations remain largely unchanged, except for diurnal cycles, which improve in winter (+0.18) but slightly degrade in spring and summer (−0.02). O3 is the least affected, as correlations were already high with default profiles (0.9–0.95). For some species and timescales (e.g., NO2 diurnal cycles), results vary across models, highlighting the complex interactions between emission timing and atmospheric processes. CAMS-REG-TEMPO has little effect on annual RMSE and bias, aside from slight improvements in high PM10 concentrations. Overall, the findings support implementing CAMS-REG-TEMPO in the operational CAMS multi-model ensemble.

Atmospheric chemistry and physicsVol. 25(20)
Roskilde University (DK), Institució Catalana de Recerca i Estudis Avançats (ES), Finnish Meteorological Institute (FI), Swedish Meteorological and Hydrological Institute (SE), Royal Netherlands Meteorological Institute (NL), Norwegian Meteorological Institute (NO), Netherlands Organisation for Applied Scientific Research (NL), Forschungszentrum Jülich (DE), Aarhus University (DK), Roskilde Sygehus (DK), Barcelona Supercomputing Center (ES), Météo-France (FR), Institute of Environmental Protection (PL), Institut national de l'environnement industriel et des risques (FR), National Agency for New Technologies Energy and Sustainable Economic Development (GB), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 17%
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