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. Future scenarios about vehicle emission inventory to define public policies were also proposed and analyzed for Belo Horizonte (BH), a Brazilian State capital, with the third-largest metropolitan region in the country. The Normal-Neighborhood Model (i.e., the mixed effect model with random effect in the neighborhood, radar type, and in the regional area) was used to calculate traffic flow in each urban street. Results showed average reductions in CO (4.5%), NMHC (3.0%), NOx (3.0%) and PM2.5 (6.2%) emissions even with an increase in fleet composition (25% in average). The decrease is a result of the implementation of emission control programs by the government, improvements vehicles technologies, and the quality of fuels. Prediction of traffic data from radar databases has proven to be useful for avoiding the high costs of performing origin-destination surveys and traffic modeling using commercial software. Radar databases can provide many potential benefits for research and analysis in environmental and transportation planning. These findings can be incorporated in future investigations to implement public policies on vehicular emission reduction in urban areas and to advance environmental health effects research and human health risk assessment.

Avoiding hospital admissions for respiratory system diseases by complying to the final Brazilian air quality standard: an estimate for Brazilian southeast capitals.

According to the World Health Organization (WHO), in 2016, 91% of the global population was living in places where guidelines on air quality were not met, which results in an estimated figure of seven million deaths annually. The new Brazilian air quality standards, CONAMA 491/2018, was the first revision in over two decades and has as final target the WHO guidelines for air quality, although no deadline has been established for implementation. The goal of this work was to quantify public health gains of this new policy based on hospitalizations due to respiratory diseases, the most studied outcome in Brazilian time series studies, in four Brazilian Southeast capitals: São Paulo (SP), Rio de Janeiro (RJ), Belo Horizonte (MG), and Vitória (ES) for PM10, PM2,5, SO2, CO, and O3. Population and hospitalizations data for all respiratory diseases for people under 5 years old, over 64 years old, most vulnerable populations, and all ages were analyzed. The air quality monitoring data was analyzed in two different periods: 2016 to 2018 for São Paulo and Vitória; and between 2015 and 2017 for Belo Horizonte and Rio de Janeiro, according to available monitoring data. A literature review was carried out to determine the appropriate relative risk to be used in the estimations, and the public health gains were calculated based on the selected relative risks for each city. The highest estimate was for São Paulo, with 3454 avoidable respiratory hospital admissions (all ages). In total, the four cities accounted for 4148 avoidable hospitalizations, which was associated to $1.1 million public health gains. Results considering the day of exposure (lag 0) were superior to those with the 5-day moving average (lag 5). The results highlighted the importance of adopting more restrictive standards and called for public policies, the necessity of expanding the air quality monitoring network, mapping emission sources, and improve the knowledge about the interaction between air pollution and health outcomes beyond respiratory disease for the region.

Analysis of PM2.5 concentrations under pollutant emission control strategies in the metropolitan area of São Paulo, Brazil.

Great efforts have been made over the years to assess the effectiveness of air pollution controls in place in the metropolitan area of São Paulo (MASP), Brazil. In this work, the community multiscale air quality (CMAQ) model was used to evaluate the efficacy of emission control strategies in MASP, considering the spatial and temporal variability of fine particle concentration. Seven different emission scenarios were modeled to assess the relationship between the emission of precursors and ambient aerosol concentration, including a baseline emission inventory, and six sensitivity scenarios with emission reductions in relation to the baseline inventory: a 50% reduction in SO2 emissions; no SO2 emissions; a 50% reduction in SO2, NOx, and NH3 emissions; no sulfate (PSO4) particle emissions; no PSO4 and nitrate (PNO3) particle emissions; and no PNO3 emissions. Results show that ambient PM2.5 behavior is not linearly dependent on the emission of precursors. Variation levels in PM2.5 concentrations did not correspond to the reduction ratios applied to precursor emissions, mainly due to the contribution of organic and elemental carbon, and other secondary organic aerosol species. Reductions in SO2 emissions are less likely to be effective at reducing PM2.5 concentrations at the expected rate in many locations of the MASP. The largest reduction in ambient PM2.5 was obtained with the scenario that considered a reduction in 50% of SO2, NOx, and NH3 emissions (1 to 2 µg/m3 on average). It highlights the importance of considering the role of secondary organic aerosols and black carbon in the design of effective policies for ambient PM2.5 concentration control.

Avaliação da influência das condições meteorológicas na concentração de material particulado fino (MP2,5) em Belo Horizonte, MG / Evaluation of meteorological conditions influence on fine particulate matter (PM 2.5 ) concentration in Belo Horizonte, MG, Brazil

RESUMO O agravamento da poluição atmosférica nos centros urbanos devido ao crescimento das instalações industriais e da frota veicular é um problema que causa danos ambientais, afetando também a saúde humana, principalmente pela inalação de material particulado fino (MP2,5). O objetivo deste estudo foi avaliar a influência das condições meteorológicas na concentração de MP2,5 em Belo Horizonte, utilizando dados amostrados entre o inverno de 2007 e o outono de 2008. Além disso, foram avaliadas as diferenças dos dados meteorológicos e da concentração do MP2,5 entre as estações do ano nesse período. Para tanto, foram realizados testes estatísticos de correlação entre os dados meteorológicos e a concentração de MP2,5, além de análises de significância para avaliação das diferenças entre esses dois parâmetros nos períodos seco e chuvoso, característicos da área de estudo. Foi observada diferença significativa entre a concentração do MP2,5 nos períodos seco e chuvoso. Foram também observadas diferenças significativas entre os parâmetros meteorológicos (umidade relativa; temperatura mínima, média e máxima; e direção do vento) para esses períodos. Por meio da análise de correlação de Spearman, observou-se correlação significativa entre a concentração do MP2,5 e os parâmetros meteorológicos precipitação e umidade relativa do ar.

ABSTRACT The increase of air pollution in urban centres due to the growth of industrial facilities and vehicular fleet is a problem that causes environmental damage and affects human health, mainly due to the inhalation of fine particulate matter (PM2.5). For this reason, the aim of this study was to evaluate the influence of meteorological conditions on PM2.5 concentration in Belo Horizonte, using data sampled from the winter of 2007 to the autumn of 2008. In addition, the differences in meteorological data and PM2.5 concentration between the seasons of the year in this study's period were also assessed. For this, correlation statistical tests were performed for meteorological data and PM2.5 concentration, as well as significance analysis to evaluate the differences between these two parameters in the dry and wet periods, characteristic of the study area. It was observed a significant difference between PM2.5 concentration in dry and wet periods. Significant differences were also observed between meteorological parameters (relative humidity, minimum, mean and maximum temperature and wind direction) for these periods. Spearman's correlation analysis showed a significant correlation between PM2.5 concentration and the meteorological parameters precipitation and relative humidity.