Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil.

Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM), ozone (O), relative humidity, temperature and delayed exposure between 4 and 21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM), ozone (O), accounting for relative humidity, temperature and mobility.

Simulation of O and NO in São Paulo street urban canyons with VEIN (v0.2.2) and MUNICH (v1.0).

We evaluate the performance of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) in simulating ozone (O) and nitrogen oxides (NO) concentrations within the urban street canyons in the São Paulo metropolitan area (SPMA). The MUNICH simulations are performed inside the Pinheiros neighborhood (a residential area) and Paulista Avenue (an economic hub), which are representative urban canyons in the SPMA. Both zones have air quality stations maintained by the São Paulo Environmental Agency (CETESB), providing data (both pollutant concentrations and meteorological) for model evaluation.

Evolution of Vehicle Emission Factors in a Megacity Affected by Extensive Biofuel Use: Results of Tunnel Measurements in São Paulo, Brazil.

Since 2001, four emission measurement campaigns have been conducted in multiple traffic tunnels in the megacity of São Paulo, Brazil, an area with a fleet of more than 7 million vehicles running on fuels with high biofuel contents: gasoline + ethanol for light-duty vehicles (LDVs) and diesel + biodiesel for heavy-duty vehicles (HDVs). Emission factors for LDVs and HDVs were calculated using a carbon balance method, the pollutants considered including nitrogen oxides (NO), carbon monoxide (CO), and sulfur dioxide, as well as carbon dioxide and ethanol. From 2001 to 2018, fleet-average emission factors for LDVs and HDVs, respectively, were found to decrease by 4.

Coupled models using radar network database to assess vehicular emissions in current and future scenarios.

Vehicles are one of the most significant sources of air pollutant emissions in urban areas, and their real contribution always needs to be updated to predict impacts on air quality. Radar databases and traffic counts using statistical modeling is an alternative and low-cost approach to produce traffic activities data in each urban street to be used as input to predict vehicular emissions. In this work, we carried out a spatial statistical analysis of local radar data and calculated traffic flow using local radar data combined with different statistical models.

Spread of SARS-CoV-2 through Latin America and the Caribbean region: A look from its economic conditions, climate and air pollution indicators.

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, PM, and NO 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.

Generating traffic flow and speed regional model data using internet GPS vehicle records.

Nowadays, many smart-phones and vehicles are equipped with Global Position System (GPS) for tracking and navigation purposes, providing an opportunity to derive highly representative local vehicular flow and estimate vehicular emissions information. Here, we report and discuss methods used to handle large volumes of such activity data, namely 124 million GPS recordings from the web page Maplink.com.

A two decades study on ozone variability and trend over the main urban areas of the São Paulo state, Brazil.

In this paper, we analyze the variability of the ozone concentration over São Paulo Macrometropolis, as well the factors, which determined the tendency observed in the last two decades. Time series of hourly ozone concentrations measured at 16 automated stations from an air quality network from 1996 to 2017 were analyzed. The temporal variability of ozone concentrations exhibits well-defined daily and seasonal patterns.