990 resultados para Diesel Particulate Matter


Relevância:

80.00% 80.00%

Publicador:

Resumo:

Air pollution is an environmental issue worldwide and frequently cause negative effects on population health and ecosystems on cities. The relationship between climate and atmospheric pollution can be used as a surrogate to the intensity of air pollution. The present and quantity of some gases can be used as indicators to air quality: particulate matter (PM), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). Among those gases, CO has its major source within the cities, where automobiles are the main emitter. But measure pollutant concentration are challenging, sometimes because the lack of good equipments due to high costs and of the large variability of models that varies in precision, way of measure and distribution of sellers. Modeling are useful when there are an intend to evaluate air pollution, its sources and evaluate scenarios. This work aims to use CAL3QHCR model developed by the U.S Environmental Protection Agency (EPA) to generate predictive surfaces of CO concentration distribution on a site within Campinas city, located in São Paulo state, Brazil. CAL3QHCR model use data urban automobile circulation to generate spatial results for CO distribution. We observed that the pollution concentration was lower on our modeling than the concentrations measured by Companhia Ambiental do Estado de São Paulo (CETESB), the main environmental company on the São Paulo state. Also the correlation between average estimates of our model and the measure by CETESB was weak, indicating that the model used on this study need to be or better parameterized, or the scale we measured of CO emissions need to be rescaled. Although the model failed to correlate to CETESB data, maybe one that explore the estimated emissions distributed within the sites to understand spatial distributions of CO on the regions. Also, the generated information can also be used to other studies, and come to be useful to explain heat island

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Mecânica - FEG

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Pós-graduação em Geociências e Meio Ambiente - IGCE

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Pós-graduação em Engenharia Mecânica - FEG

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Polycyclic aromatic hydrocarbons (PAHs) and non-aromatic hydrocarbons (NAHs), including n-alkanes, isoprenoids and petroleum biomarkers (terpanes, hopanes, steranes and diasteranes), were quantified by gas chromatography with flame ionization and mass spectrometer detectors in sediment samples collected from the Sao Sebastiao Channel (SSC), Brazil, where the largest Brazilian maritime petroleum terminal is located The concentrations of total PAHs. total n-alkanes and petroleum biomarkers ranged from below the detection limits to 370 ng g(-1,) 28 mu g g(-1), 2200 ng g(-1) (dry weight), respectively. The analysis of PAN distribution suggested combustion sources of PAHs as the main input for these compounds with smaller amount from petroleum contamination The distribution of petroleum biomarkers undoubtedly demonstrated petroleum as a source of anthropogenic contamination throughout the region. The assessment of petrogenic sources of contamination in marine sediment is more challenging if only PAH analysis were carried out, which demonstrates that more stable hydrocarbons such as petroleum biomarkers are useful for investigating potential presence of petroleum (C) 2009 Elsevier Ltd. All rights reserved.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Background: The Amazon represents an area of 61% of Brazilian territory and is undergoing major changes resulting from disorderly economic development, especially the advance of agribusiness. Composition of the atmosphere is controlled by several natural and anthropogenic processes, and emission from biomass burning is one with the major impact on human health. The aim of this study was to evaluate genotoxic potential of air pollutants generated by biomass burning through micronucleus assay in exfoliated buccal cells of schoolchildren in the Brazilian Amazon region. Methods: The study was conducted during the dry seasons in two regions of the Brazilian Amazon. The assay was carried out on buccal epithelial cells of 574 schoolchildren between 6-16 years old. Results: The results show a significant difference between micronucleus frequencies in children exposed to biomass burning compared to those in a control area. Conclusions: The present study demonstrated that in situ biomonitoring using a sensitive and low cost assay (buccal micronucleus assay) may be an important tool for monitoring air quality in remote regions. It is difficult to attribute the increase in micronuclei frequency observed in our study to any specific toxic element integrated in the particulate matters. However, the contribution of the present study lies in the evidence that increased exposure to fine particulate matter generates an increased micronuclei frequency in oral epithelial cells of schoolchildren.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

Objective: To investigate the lag structure effects from exposure to atmospheric pollution in acute outbursts in hospital admissions of paediatric rheumatic diseases (PRDs). Methods: Morbidity data were obtained from the Brazilian Hospital Information System in seven consecutive years, including admissions due to seven PRDs (juvenile idiopathic arthritis, systemic lupus erythematosus, dermatomyositis, Henoch-Schonlein purpura, polyarteritis nodosa, systemic sclerosis and ankylosing spondylitis). Cases with secondary diagnosis of respiratory diseases were excluded. Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2) nitrogen dioxide (NO2), ozone (O-3) and carbon monoxide (CO) were evaluated. Generalized linear Poisson regression models controlling for short-term trend, seasonality, holidays, temperature and humidity were used. Lag structures and magnitude of air pollutants' effects were adopted to estimate restricted polynomial distributed lag models. Results: The total number of admissions due to acute outbursts PRD was 1,821. The SO2 interquartile range (7.79 mu g/m(3)) was associated with an increase of 1.98% (confidence interval 0.25-3.69) in the number of hospital admissions due to outcome studied after 14 days of exposure. This effect was maintained until day 17. Of note, the other pollutants, with the exception of O-3, showed an increase in the number of hospital admissions from the second week. Conclusion: This study is the first to demonstrate a delayed association between SO2 and PRD outburst, suggesting that oxidative stress reaction could trigger the inflammation of these diseases. Lupus (2012) 21, 526-533.

Relevância:

80.00% 80.00%

Publicador:

Resumo:

The objective of this study was to determine the size and composition of atmospheric aerosols in the downtown area of the city of So Paulo, Brazil, for a polluted and an unpolluted period. Aerosols were sampled with a portable air sampler (PAS), Micro-Orifice Uniform Deposit Impactor (MOUDI), and Scanning Mobility Particle Sizer. At the study site, air quality is poor, especially during the winter, high concentrations of pollutants being emitted primarily by the light- and heavy-duty vehicle fleet. We analyzed mass, black carbon (BC), Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sn, Zr, and Pb. During the polluted period, diurnal PM(10) was higher than nocturnal PM(10), whereas the inverse was true during the unpolluted period. The FPM was rich in BC, S, and Pb, whereas CPM was rich in Al, Si, Ca, Ti, and Fe. Mass balance was performed by category: ammonium sulfate, sodium chloride, crustal material, BC, and other. The PAS-determined FPM was mainly BC. The MOUDI-determined FPM crustal material explained more mass than did ammonium sulfate and BC during the polluted period, whereas ammonium sulfate had the largest mass during the unpolluted period. Crustal material was the major CPM component, followed by ammonium sulfate and BC. During the unpolluted period, FPM concentrations were lower, whereas those of ammonium sulfate were relatively higher, especially at night, and particle number was inversely proportional to particle size. Aerosol growth was more intense during the polluted period.