Simulação da poluição atmosférica em regiões urbanas costeiras utilizando o modelo WRF-Chem

Abstract

Air pollution is a critical factor that harms biodiversity, ecosystems, and human health. The increase in pollutant concentrations due to the growth of urban and industrial areas has led to increased scientific discussions on this topic, and computational modeling is an important management tool for decision-making. In this sense, the main objective of this work is to evaluate the performance of the air quality model WRF-Chem (Weather Research and Forecasting with Chemistry) to determine the concentration field of the pollutants O3 (ozone), NOx (nitrogen oxides) and PM (particulate matter) in the metro politan region of Salvador (RMS), particularly analyzing the influence of the sea breeze on the dispersion of these pollutants. However, for this purpose, a consistent source in ventory is important, and simulations were first performed using the WRF-Chem and WRF-CMAQ model systems to assess PM dispersion in the Vitoria metropolitan region (RMV), where a well-documented inventory exists. Additionally, in the RMS, an evalua tion of the evolution of the measured pollutants over time and their relationship with four climatic variables (solar irradiance, air temperature, relative humidity and wind speed) was performed using the DFA (Detrended Fluctuation Analysis) and ρDCCA (Detrended Cross-Correlation Coefficient Analysis). The results show that the WRF-Chem model simulates more satisfactorily the PM concentration field in the RMV, where the WRF CMAQ system tends to underestimate the concentration. In the RMS, when the breeze enters, the pollutants are transported over large distances, although the highest concen tration remains in regions close to the main sources. The concentrations in the RMS, when compared with the local measured data, present underestimated values, which sug gests that the inventory of sources is still incipient. The use of DFA and ρDCCA techniques indicate that pollutants in the MSR tend to increase over time, impairing air quality and affecting human health. The results show a cross-correlation between air pollution and climate variables that persisted for a certain period, with higher correlation between O3 concentration and wind, especially temperature, and negative correlation with humidity for all monitoring stations. In addition, unlike O3 and PM10, NOx concentrations always had a persistent behavior in the study region throughout the analyzed period.