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Biomass burning (BB) is a major source of trace gases and particles in the atmosphere, influencing air quality, radiative balance, and climate. Previous studies have mainly focused on the BB emissions of carbon and nitrogen species with less attention on chlorine. Reactive chlorine chemistry has significant effects on atmospheric chemistry and air quality. However, quantitative information on chlorine emissions from BB, particularly the long-term trend and associated atmospheric impacts, is limited both on regional and global scales. Here, we report a long-term (2001–2018) high-resolution BB emission inventory for the major chlorine-containing compounds (HCl, chloride, and CH3Cl) in Asia based on satellite observations. We estimate an average of 730 Gg yr−1chlorine emitted from BB activity in Asia, with China contributing the largest share at 24.2% (177 Gg yr−1), followed by Myanmar at 18.7% and India at 18.3%. Distinct seasonal patterns and significant spatial and interannual variability are observed, mainly driven by human-mediated changes in agricultural activity. By incorporating the newly developed chlorine emission inventory into a global chemistry-climate model (CAM-Chem), we find that the BB-chlorine emissions lead to elevated levels of HCl and CH3Cl (monthly average up to 2062 and 1421 parts per trillion by volume (pptv), respectively), subsequently resulting in noticeable changes in oxidants (up to 3.1% in O3and 17% in OH radicals). The results demonstrate that BB is not only a significant source of air pollutants but also of oxidants, suggesting a larger role of BB emissions in the atmospheric chemistry and oxidation process than previously appreciated. In light of the projected increase in BB activity toward the end of the century and the extensive control of anthropogenic emissions worldwide, the contribution of BB emissions may become fundamental to air quality composition in the future.Biomass burning releases substantial chlorine-containing species, driving significant long-term and widespread impacts on atmospheric chemistry and oxidation in Asia, revealing a crucial and previously underappreciated role in air quality and climate interactions.

An intercomparison of four regional air quality models is performed in the tropical megacity of São Paulo with the perspective of developing a forecasting system based on a model ensemble. Modeled concentrations of the main regulated pollutants are compared with combined observations in the megacity center, after analyzing the spatial scale of representativeness of air monitoring stations. During three contrasting periods characterized by different types of pollution events, the hourly concentrations of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter (PM2.5and PM10) modeled by the ensemble are in moderate agreement with observations. The median of the ensemble provides the best performance (R≈ 0.7 for CO, 0.7 for NOx, 0.5 for SO2, 0.5 for PM2.5, and 0.4 for PM10) because each model has periods and pollutants for which it has the best agreement. NOx concentration is modeled with a large inter‐model variability, highlighting potential for improvement of anthropogenic emissions. Pollutants transported by biomass burning events strongly affect the air quality in São Paulo and are associated with significant inter‐model variability. Modeled hourly concentration of ozone (O3) is overestimated during the day (≈20 ppb) and underestimated at night (≈10 ppb), while nitrogen dioxide (NO2) is overestimated at night (≈20 ppb). The observed O3concentration is best reproduced by the median of the ensemble (R≈ 0.8), taking advantage of the variable performance of the models. Therefore, an operational air quality forecast system based on a regional model ensemble is promising for São Paulo. Forecasting air quality in megacities is particularly difficult due to the diversity and temporal variability of emission sources. São Paulo is the largest metropolitan area in South America and has no operational air quality forecast. We perform an intercomparison of four regional air quality models with the perspective of developing an air quality forecasting system. During three contrasting periods characterized by different types of pollution events, we analyze the modeled concentrations of the main regulated pollutants (trace gases and aerosols) compared to observations from the São Paulo air quality monitoring network. The modeled concentrations of the main regulated pollutants agree well with the observations range of variation, although we show the potential in improving the treatment of anthropogenic emissions. In addition, the long‐range transport of pollutants due to forest fires strongly affects the air quality in São Paulo and also reduces the performance of the models. The observed hourly ozone concentration is well reproduced by the models, and its median has the best performance, taking advantage of the capabilities of each model. Therefore, an operational air quality forecasting system for the megacity of São Paulo is promising. An ensemble of regional air quality models performs well in the São Paulo megacity for the main regulated pollutants (CO, NOx, O3, SO2, PM2.5, and PM10)Transport of pollutants due to biomass burning events, affecting strongly the air quality of the megacity, is represented with high variability by the ensembleIn the center of the megacity, the median of the regional model ensemble leads to the best performance for these pollutants compared to each model that composes it An ensemble of regional air quality models performs well in the São Paulo megacity for the main regulated pollutants (CO, NOx, O3, SO2, PM2.5, and PM10) Transport of pollutants due to biomass burning events, affecting strongly the air quality of the megacity, is represented with high variability by the ensemble In the center of the megacity, the median of the regional model ensemble leads to the best performance for these pollutants compared to each model that composes it