Ponente
Descripción
In order for an air quality model to better emulate and represent the atmospheric pollution in a region, its performance has to be evaluated to both identify uncertainties and reproduce ambient observations.
An air quality modeling system has been implemented at UNAM’s Institute of Atmospheric Sciences and Climate Change with the main objective of generating air quality forecasts for the area of Central Mexico. This region encompasses a megalopolis that includes 5 states surrounding the Mexico Megacity. Central Mexico is chosen as a case study because of the interest in criteria pollutant emissions, evaluation of emissions inventories and greenhouse gases in the region.
The modeling system has been applied in studies related to improving emissions inventories and to evaluate mitigation scenarios. Part of the products have been used to support key decision-making processes both at a regional and national level. In order to better identify the uncertainties and improve the model performance, a verification system based on the NCEP Unified Post Processing System (UPP), Model Evaluation Tools (MET), Fortran codes, grads, R and bash scripts, has been implemented. The system aims to address the following questions: 1) at which monitoring stations does the model perform best? 2) Are there chemical/meteorological regimes impacting the model performance? 3) Is the forecast capturing the meteorology natural variability correctly? 4) What is the best way to present the results to the public?
A description of the observational dataset used for validation will be presented. It includes data from several platforms: surface air quality network, satellite products for CO and CO2 and additional surface meteorological observations. In addition, a comparison between model results and satellite products will be presented.
