Avaliação da influência das emissões biogênicas na qualidade do ar: estudo de caso para uma região tropical urbanizada

Abstract

The sources of atmospheric pollution can be classified as anthropogenic and biogenic; the latter being composed of emissions from vegetation, soil, oceans, among others. In this context, vegetation has significant relevance because it emits a variety of pollutants, and the biogenic volatile organic compounds (BVOCs) stand out, because these species play an important role in atmospheric chemistry, as they contribute to the formation of secondary pollutants, such as ozone (O3 ) and secondary organic aerosol (SOA). Thus, this study aims to evaluate the influence of biogenic emissions on air quality, using MEGAN model (Model of Emissions of Gases and Aerosols from Nature) together with the WRF-SMOKE-CMAQ system. The present work was developed for the Greater Vitória Region (RGV), for the period of August 2010. This study also developed a computational tool that allows the use of Plant Functional Types and Leaf Area Index data available in meteorological model results as input to run MEGAN model, granting the use of the same surface database in all modeling stages. The evaluation of air quality and the influence of BVOCs emissions was carried out through simulations with the CMAQ air quality model for 3 conditions: base case, without biogenic emissions, and without anthropogenic emissions. The results of the WRF meteorological model indicated a good correlation with the values measured at 3 stations in the region. The MEGAN model indicated that the BVOCs emissions with the highest percentage contribution are isoprene and terpenes, with 74% and 25% of total emissions, respectively. Air quality modeling was the basis for assessing the formation of O3 and AOS. The results indicated that, for RGV, O3 concentrations are lower in regions of high NOX concentration, which occurs due to the participation of these compounds in the O3 formation and destruction reactions. In addition, the estimated hourly O3 concentration was compared with observed data, in which it was found that the simulation underestimates O3 peak concentrations for most of the time. The results for SOA indicated that, in RGV, the contribution of biogenic emissions in its formation is higher by up to an order of magnitude compared to anthropogenic emissions participation. The present work emphasizes the importance of including the estimation of COVBs in all air quality simulations, including for RGV.