18 resultados para Microplastic pollution
Resumo:
The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirão Preto, São Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.
Resumo:
Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.
Resumo:
The study of organic pollution in estuaries is very relevant as they are transitional zones, which control the fluxes of water, nutrients, particles and organisms from and to the continental margins, rivers and oceans. The aims of this study are:(1) to evaluate organic pollution in coastal sediments of Montevideo, Río de la Plata Estuary by a multi-biomarker approach, (2) to identify major sources of organic pollutants through qualitative analysis using molecular indices, (3) to assess the relative contribution of different sources of hydrocarbons through quantitative source apportionment employing (PCA/MLR) as chemometric technique. Sampling surveys were carried out in July 2009, January 2010 and March 2011 in 37 stations along the middle portion of the Río de la Plata Estuary across the coast of Montevideo. In each station surface (0–2 cm depth) sediment samples were taken with a 0.05 m2 van Veen grab. The Soxhlet extracted organic compounds included aliphatic hydrocarbons (AHs) and steroids, analysed by gas chromatograph with flame ionization detector (GC-FID), linear alkylbenzenes (LABs) and polycyclic aromatic hydrocarbons (PAHs) quantified by gas chromatograph with mass spectrometer (GC/MS). All biomarkers presented the highest concentrations in the stations of Montevideo Bay indicating high levels of organic pollution. The combination of molecular indices and the chemometric technique showed that major sources of AHs and PAHs are petroleum inputs and combustion, due to oil transport and refinement, harbour activities and vehicular emissions.Major sources of LABs and steroids are urban and domestic sewage. Identification, quantification and source assignment of those organic compounds are very important to assess pollution and to give tools to help minimize the inputs into the environment