Abstract

Abstract. We use a three-dimensional regional chemical transport model (PMCAMx) with high grid resolution and high-resolution emissions (4 × 4 km2) over the Paris greater area to simulate the formation of carbonaceous aerosol during a summer (July 2009) and a winter (January/February 2010) period as part of the MEGAPOLI (megacities: emissions, urban, regional, and global atmospheric pollution and climate effects, and Integrated tools for assessment and mitigation) campaigns. Model predictions of carbonaceous aerosol are compared against Aerodyne aerosol mass spectrometer and black carbon (BC) high time resolution measurements from three ground sites. PMCAMx predicts BC concentrations reasonably well reproducing the majority (70 %) of the hourly data within a factor of two during both periods. The agreement for the summertime secondary organic aerosol (OA) concentrations is also encouraging (mean bias = 0.1 µg m−3) during a photochemically intense period. The model tends to underpredict the summertime primary OA concentrations in the Paris greater area (by approximately 0.8 µg m−3) mainly due to missing primary OA emissions from cooking activities. The total cooking emissions are estimated to be approximately 80 mg d−1 per capita and have a distinct diurnal profile in which 50 % of the daily cooking OA is emitted during lunch time (12:00–14:00 LT) and 20 % during dinner time (20:00–22:00 LT). Results also show a large underestimation of secondary OA in the Paris greater area during wintertime (mean bias = −2.3 µg m−3) pointing towards a secondary OA formation process during low photochemical activity periods that is not simulated in the model.

Highlights

  • Megacities are major sources of gas and particulate pollutants affecting public health, regional ecosystems, and climate

  • Freutel et al (2013) analyzed aerosol mass spectrometer (AMS) measurements from three stationary sites in the Paris area during July 2009. They found that the origin of air masses had a large influence on secondary organic aerosol (OOA) concentrations with elevated values observed during periods when the site was affected by transport from continental Europe and lower concentrations (1–3 μg m−3) when air masses were originating from the Atlantic

  • HOA, BBOA, COA, OOA1, OOA2 HOA, BBOA, COA, OOA HOA, BBOA, OOA1, OOA2 for 36 % of total dry PM1 mass concentration at ground level averaged over the Paris greater area domain during summer, followed by nitrate (20 %), sulfate (16 %) and ammonium (12 %) with the remaining 16 % comprised of crustal material, sea salt and metal oxides

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Summary

Introduction

Megacities (cities with more than 10 million inhabitants) are major sources of gas and particulate pollutants affecting public health, regional ecosystems, and climate. Freutel et al (2013) analyzed aerosol mass spectrometer (AMS) measurements from three stationary sites in the Paris area during July 2009 They found that the origin of air masses had a large influence on secondary (oxygenated) organic aerosol (OOA) concentrations with elevated values (up to 7 μg m−3) observed during periods when the site was affected by transport from continental Europe and lower concentrations (1–3 μg m−3) when air masses were originating from the Atlantic. Skyllakou et al (2014), using the particulate matter source apportionment technology (PSAT) together with PMCAMx, showed that approximately 50 % of the predicted fresh POA originated from local sources and another 45 % from areas 100–500 km away from the receptor region during summer in Paris They found that more than 45 % of OOA was due to the oxidation of volatile organic compounds (VOCs) that were emitted 100–500 km away from the center of Paris. Emission and meteorological errors affecting the predicted BC concentrations and discuss missing or inadequate processes forming OA in the model

Model description
Model application
Measurements
Model predictions over the Paris greater area
Primary organic aerosol levels and sources
Oxygenated organic aerosol
Black carbon
Estimation of cooking OA emissions
Conclusions
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