Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of São Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 μg/m3, respectively. In São Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-à-vis health care costs

Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters

Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy

Risk assessment and spatial chemical variability of PM collected at selected bus stations

Abstract: The chemical characterization of particulate matter inside and outside of confined bus shelters has been discerned for the first time. Transit patrons are at risk due to the close vicinity of densely trafficked areas resulting in elevated pollution footprints. Incomplete combustion processes, as well as exhaust and wear and tear emissions from public and personal transportation vehicles, are key contributors to degraded urban air quality and are often implicated as causal to various diseases in humans. Urban planning, therefore, includes efficient public transport systems to mitigate the effect. The bus rapid transit system was inaugurated in Curitiba to ensure dedicated traffic lanes, major bus interchanges and semi-confined bus stops called tube stations. To assess the chemical risk that the passengers are exposed to, an investigation of the aerosol inside and outside five of these tube stations was launched. Electron probe X-ray micro-analysis and X-ray fluorescence were used to determine the elemental composition of individual and of bulk particle samples. An aethalometer quantified the black carbon. Elemental concentrations inside the shelters were in general higher than outside, especially for traffic-related elements. The lead concentration exceeded the NAAS standard at times, although the average was below the guideline. The biogenic, organic and soot clusters showed the highest abundance for the city centre sites. The overall carcinogenic risk could be classed as moderate, and the risk was significant at two sites during one of the sampling campaigns. The non-carcinogenic risk is well below the significant value