European NOx emissions in WRF-Chem derived from OMI: impacts on summertime surface ozone

• Published in: Atmospheric chemistry and physics 2019-09, Vol.19 (18), p.11821-11841
• Main Authors: Visser, Auke J, K Folkert Boersma, Ganzeveld, Laurens N, Krol, Maarten C
• Format: Article
• Language: English
• Subjects: Agricultural land; Air pollution; Air quality; Air quality models; Atmospheric chemistry; Bias; Chemistry; Computer simulation; Daytime; Dependence; Distribution; Ecosystems; Emission; Emission standards; Emissions; Environmental changes; Environmental impact; Gases; Mass balance; Meteorology; Monitoring instruments; Nitrogen compounds; Nitrogen dioxide; Nitrogen oxides; Nitrogen oxides emissions; Organic chemistry; Outdoor air quality; Oxidants; Oxides; Oxidizing agents; Ozone; Ozone concentration; Ozone formation; Ozone monitoring; Performance evaluation; Photochemicals; Pollutants; Pollution monitoring; Precursors; Production increases; Regions; Satellite observation; Satellites; Simulation; Soil; Soils; Spatial distribution; Summer; Trends; VOCs; Volatile organic compounds; Weather forecasting
• ISSN: 1680-7316; 1680-7324
• DOI: 10.5194/acp-19-11821-2019

Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx=NO+NO2) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8 h ozone concentration (MDA8 O3) is underestimated (mean bias error of −14.2 µg m−3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50 Tg N (for July 2015), which is 0.18 Tg N higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1 Tg N, much higher than the bottom-up 0.02 Tg N natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slope =0.98, r2=0.84) and reduces the low bias against independent surface NO2 measurements by 1.1 µg m−3 (−56 %). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0 µg m−3, and increases of >10 µg m−3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4 µg m−3 (48 %). Overall, our results highlight the dependence of surface ozone on its p