We have evaluated the spread of SARS-CoV-2 through Latin America and the Caribbean (LAC) region by means of a correlation between climate and air pollution indicators, namely, average temperature, minimum temperature, maximum temperature, rainfall, average relative humidity, wind speed, and air pollution indicators PM 10 , PM 2.5 , and NO 2 with the COVID-19 daily new cases and deaths. The study focuses in the following LAC cities: Mexico City (Mexico), Santo Domingo (Dominican Republic), San Juan (Puerto Rico), Bogotá (Colombia), Guayaquil (Ecuador), Manaus (Brazil), Lima (Perú), Santiago (Chile), São Paulo (Brazil) and Buenos Aires (Argentina). The results show that average temperature, minimum temperature, and air quality were significantly associated with the spread of COVID-19 in LAC. Additionally, humidity, wind speed and rainfall showed a significant relationship with daily cases, total cases and mortality for various cities. Income inequality and poverty levels were also considered as a variable for qualitative analysis. Our findings suggest that and income inequality and poverty levels in the cities analyzed were related to the spread of COVID-19 positive and negative, respectively. These results might help decision-makers to design future strategies to tackle the spread of COVID-19 in LAC and around the world.

Southeastern Brazil, the most populous and developed region of the country, faces various environmental problems associated with the growth of its population in urban areas. It is the most industrialized area in the country, comprising the metropolitan areas of São Paulo, Rio de Janeiro, Belo Horizonte, and other major cities. Air quality is a major concern, because the reported concentrations of certain regulated pollutants, typically ozone and fine particulate, have exceeded national standards. Due to the difficulty in taking measurements over many different areas, air quality modeling is a useful tool to estimate air pollutant concentrations. For southeastern Brazil, air quality modeling has been performed mostly with the Brazilian Regional Atmospheric Modeling System with Simplified Photochemical Module and the Weather Research and Forecast with Chemistry models. One of the main objectives was to study the evolution of air quality associated with improved vehicle emission factors in urban areas, the impact of climate change on air quality, and the relationship between pollutant concentrations and health. Knowledge of mobile source emission factors has been continuously expanded by in-tunnel measurements and dynamometer protocols, which provide accurate data as inputs to photochemical air quality models. The spatial distribution of the mobile source emissions was constructed based on open access data related to the streets and traffic distribution. The mobile emission module was combined to the chemistry modeling and this implementation can be an example to be applied to other places that do not have a spatial distribution of this source. Forecasts of pollutant concentrations can inform public policies, including those addressing the effects of pollutants on health of the general population, and studies of the impacts of using different fuels and implementation of emissions regulations programs.

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