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.

Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas.

Air quality management involves investigating areas where pollutant concentrations are above guideline or standard values to minimize its effect on human health. Particulate matter (PM) is one of the most studied pollutants, and its relationship with health has been widely outlined. To guide the construction and improvement of air quality policies, the impact of PM on the four Brazilian southeast metropolitan areas was investigated. One-year long modeling of PM10 and PM2.5 was performed with the WRF-Chem model for 2015 to quantify daily and annual PM concentrations in 102 cities. Avoidable mortality due to diverse causes and morbidity due to respiratory and circular system diseases were estimated concerning WHO guidelines, which was adopted in Brazil as a final standard to be reached in the future; although there is no deadline set for its implementation yet. Results showed satisfactory representation of meteorology and ambient PM concentrations. An overestimation in PM concentrations for some monitoring stations was observed, mainly in São Paulo metropolitan area. Cities around capitals with high modelled annual PM2.5 concentrations do not monitor this pollutant. The total avoidable deaths estimated for the region, related to PM2.5, were 32,000 ± 5,300 due to all-cause mortality, between 16,000 ± 2,100 and 51,000 ± 3,000 due non-accidental causes, between 7,300 ± 1,300 and 16,700 ± 1,500 due to cardiovascular disease, between 4,750 ± 900 and 10,950 ± 870 due ischemic heart diseases and 1,220 ± 330 avoidable deaths due to lung cancer. Avoidable respiratory hospitalizations were greater for PM2.5 among 'children' age group than for PM10 (all age group) except in São Paulo metropolitan area. For circulatory system diseases, 9,840 ± 3,950 avoidable hospitalizations in the elderly related to a decrease in PM2.5 concentrations were estimated. This study endorses that more restrictive air quality standards, human exposure, and health effects are essential factors to consider in urban air quality management.

Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter.

Emission inventories are one of the most critical inputs for the successful modeling of air quality. The performance of the modeling results is directly affected by the quality of atmospheric emission inventories. Consequently, the development of representative inventories is always required. Due to the lack of regional inventories in Brazil, this study aimed to investigate the use of the particulate matter (PM) emission estimation from the Brazilian top-down vehicle emission inventory (VEI) of 2012 for air quality modeling. Here, we focus on road vehicles since they are usually responsible for significant emissions of PM in urban areas. The total Brazilian emission of PM (63,000 t year-1) from vehicular sources was distributed into the urban areas of 5557 municipalities, with 1-km2 grid spacing, considering two approaches: (i) population and (ii) fleet of each city. A comparison with some local inventories is discussed. The inventory was compiled in the PREP-CHEM-SRC processor tool. One-month modeling (August 2015) was performed with WRF-Chem for the four metropolitan areas of Brazilian Southeast: Belo Horizonte (MABH), Great Vitória (MAGV), Rio de Janeiro (MARJ), and São Paulo (MASP). In addition, modeling with the Emission Database for Global Atmospheric Research (EDGAR) inventory was carried out to compare the results. Overall, EDGAR inventory obtained higher PM emissions than the VEI segregated by population and fleet, which is expected owing to considerations of additional sources of emission (e.g., industrial and residential). This higher emission of EDGAR resulted in higher PM10 and PM2.5 concentrations, overestimating the observations in MASP, while the proposed inventory well represented the ambient concentrations, obtaining better statistics indices. For the other three metropolitan areas, both EDGAR and the VEI inventories obtained consistent results. Therefore, the present work endorses the fact that vehicles are responsible for the more substantial contribution to PM emissions in the studied urban areas. Furthermore, the use of VEI can be representative for modeling air quality in the future.

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.