Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)

Abstract

The temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.