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Since air pollution compromise the respiratory system and COVID-19 disease is caused by a respiratory virus, it is expected that air pollution plays an important role in the current COVID-19 pandemic. Exploratory studies have observed positive associations between air pollution and COVID-19 cases, deaths, fatality, and mortality rate. However, no study focused on Brazil, one of the most affected countries by the pandemic. Thus, this study aimed to understand how long-term exposure to PM 10 , PM 2.5 , and NO 2 contributed to COVID-19 fatality and mortality rates in São Paulo state in 2020. Air quality data between 2015 and 2019 in 64 monitoring stations within 36 municipalities were considered. The COVID-19 fatality was calculated considering cases and deaths from the government’s official data and the mortality rate was calculated considering the 2020 population. Linear regression models were well-fitted for PM 2.5 concentration and fatality ( R 2 = 0.416; p = 0.003), NO 2 concentration and fatality ( R 2 = 0.232; p = 0.005), and NO 2 concentration and mortality ( R 2 = 0.273; p = 0.002). This study corroborates other authors’ findings and enriches the discussion for having considered a longer time series to represent long-term exposure to the pollutants and for having considered one of the regions with the highest incidence of COVID-19 in the world. Thus, it reinforces measures to reduce the concentration of air pollutants which are essential for public health and will increase the chance to survive in future respiratory disease epidemics.

O estado de São Paulo apresenta a maior produção industrial do Brasil, formando o maior Produto Interno Bruto (PIB) do país. Como consequência da atividade industrial, diversos municípios têm apresentado elevados índices de poluição atmosférica. O objetivo desta pesquisa foi estimar a mortalidade pordoenças cardiorrespiratórias atribuíveis à poluição do ar em municípios com elevada industrialização do estado de São Paulo entre os anos 2008 e 2016. Selecionaram-se 11 municípios para análise com base no consumo de energia elétrica pelo setor industrial e pela existência de estação de monitoramentoda qualidade do ar. Com base em modelo recomendado pela Organização Mundial da Saúde (OMS), estimou-se o número de óbitos por problemas cardiorrespiratórios que puderam ser atribuídos à concentração de material particulado (MP2,5) em cada município ao longo dos anos. Baseando-se no valor estatístico de uma vida, realizou-se valoração econômica do impacto em saúde. Cinco dos 11 municípios analisados pertencem à Região Metropolitana de São Paulo (RMSP). O município cuja população é mais afetada pelapoluição é Cubatão. No entanto, em razão do grande número de habitantes, São Paulo é o município cujo maior número de óbitos pode ser atribuído à exposição ao poluente MP2,5. Considerando os resultados encontrados para os 11 municípios, 43.512 óbitos puderam ser atribuídos à poluição atmosféricano período, o que representa prejuízo superior a US$ 48,3 bi. Esses resultados embasam a necessidade de pesquisas e de implementação de tecnologias mais limpas no parque industrial do estado de São Paulo.

One of the policies adopted to reduce vehicular emissions is subway network expansion. This work fitted interrupted regression models to investigate the effects of the inauguration of subway stations on the mean, trend, and seasonality of the NO, NO2, NOx, and PM10 local concentrations. The regions investigated in the city of São Paulo (Brazil) were Pinheiros, Butantã, and St. Amaro. In Pinheiros, after the inauguration of the subway station, there were downward trends for all pollutants. However, these trends were not significantly different from the trends observed before. In Butantã, only regarding NO, there was a significant reduction and seasonal change after the subway station’s inauguration. In St. Amaro, no trend in the PM10 concentration was noted. The absence of other transportation and land use policies in an integrative way to the subway network expansion may be responsible for the low air quality improvement. This study highlights that the expansion of the subway network must be integrated with other policies to improve local air quality.

Traditionally, studies that associate air pollution with health effects relate individual pollutants to outcomes such as mortality or hospital admissions. However, models capable of analyzing the effects resulting from the atmosphere mixture are demanded. In this study, multilayer perceptron neural networks were evaluated to associate PM10, NO2, and SO2 concentrations, temperature, wind speed, and relative air humidity with cardiorespiratory mortality among the elderly in São Paulo, Brazil. Daily data from 2007 to 2019 were considered and different numbers of neurons on the hidden layer, algorithms, and a combination of activation functions were tested. The best-fitted artificial neural network (ANN) resulted in a MAPE equal to 13.46%. When individual season data were analyzed, the MAPE decreased to 11%. The most influential variables in cardiorespiratory mortality among the elderly were PM10 and NO2 concentrations. The relative humidity variable is more important during the dry season, and temperature is more important during the rainy season. The models were not subjected to the multicollinearity issue as with classical regression models. The use of ANNs to relate air quality to health outcomes is still very incipient, and this work highlights that it is a powerful tool that should be further explored.