Updating of the 2013 national emissions inventory for air quality modeling in central Mexico

Abstract

Air pollutant emissions inventories are an essential input parameter for air quality modeling. During its elaboration process, there are uncertainties that cause errors in numerical simulations. The need to continually improve data accuracy or adjust it to the actual conditions being described is indisputable. In this work, the spatial, temporal, and chemical speciation distribution model (DiETE) was applied to the 2013 Mexico National Emissions Inventory in order to obtain a spatially and temporarily disaggregated database, ready for numerical modeling with the Weather Research and Forecasting Model with Chemistry (WRF-Chem) in Central Mexico. Also, the model performance was evaluated for ozone in an environmental contingency episode that took place between May 15 and 21, 2017, based on the comparison with stations observations from Mexico City’s Red Automática de Monitoreo Atmosférico (automatic air quality monitoring network). Statistical metrics showed lower correlation for all variables analyzed and it was decided to update the inventory through a nonparametric methodology based on scale factors. This led us to obtain statistical parameters with larger correlations and model values closer to the observations, which accurately describe the spatial and temporal behavior of the variables. The adjustments made to the inventory were validated through its application to another case of environmental contingency from March 14-17, 2016, with considerable improvements in the performance of the model.