This paper shows the results of an approximation and transformation made on the Sao Paulo Metropolitan Region (SPMR) pollutant emission inventory, required to be used as input data on the WRF/Chem model ("Weather Research This paper shows the results of an approximation and transformation made on the Sao Paulo Metropolitan Region (SPMR) pollutant emission inventory, required to be used as input data on the WRF/Chem model ("Weather Research and Forecasting / CHEMistry"). Therefore, the purpose is to evaluate the efficiency of the WRF/Chem model to simulate photochemical pollutants on the SPMR, using as parameters the inclusion of the emission inventory and measurements of carbon monoxide (CO) and tropospheric ozone (O3) concentrations. The WRF/Chem is a forecast, weather climate and air quality model, which solves simultaneously the meteorology and chemistry modules. SPMR is considered one of the largest cities in the world, and like other big cities suffer with atmospheric pollution. Researches made in SPMR show that vehicles are the main sources of Carbon monoxide (CO), Hydrocarbon (HC) and Nitrogen oxide (NOx). When it comes to Sulphur oxides (SOx) and inhalable particles (PM10) the main sources of emission fundamentally are industries and vehicles. Another crucial factor is the resuspension of particles from the ground (soil) and the formation of secondary aerosols. A 2006 Companhia Ambiental do Estado de São Paulo (CETESB) inventory of emissions will be used as input data to the WRF/CHEM model. Since the annual CETESB inventory of emissions integrates the whole SPMR some approximation is required to match the model input data format. It was proposed some approximation methods in which the inventory of annual emissions was representatively distributed in time and space as required by the model. The results show that these methods improved the forecasting of the ozone (O3) and of CO concentration by approximately 25%, reaching a correlation coefficients of 0,79% for the ozone and 0,49% for carbon monoxide, when comparing simulations and observations.
Air Pollution; Emissions; Air Quality Models
