20 resultados para Oil pollution of the sea


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Microbial respiratory reduction of nitrous oxide (N2O) to dinitrogen (N2) via denitrification plays a key role within the global N-cycle since it is the most important process for converting reactive nitrogen back into inert molecular N2. However, due to methodological constraints, we still lack a comprehensive, quantitative understanding of denitrification rates and controlling factors across various ecosystems. We investigated N2, N2O and NO emissions from irrigated cotton fields within the Aral Sera Basin using the He/O2 atmosphere gas flow soil core technique and an incubation assay. NH4NO3 fertilizer, equivalent to 75 kg ha−1 and irrigation water, adjusting the water holding capacity to 70, 100 and 130% were applied to the incubation vessels to assess its influence on gaseous N emissions. Under soil conditions as they are naturally found after concomitant irrigation and fertilization, denitrification was the dominant process and N2 the main end product of denitrification. The mean ratios of N2/N2O emissions increased with increasing soil moisture content. N2 emissions exceeded N2O emissions by a factor of 5 ± 2 at 70% soil water holding capacity (WHC) and a factor of 55 ± 27 at 130% WHC. The mean ratios of N2O/NO emissions varied between 1.5 ± 0.4 (70% WHC) and 644 ± 108 (130% WHC). The magnitude of N2 emissions for irrigated cotton was estimated to be in the range of 24 ± 9 to 175 ± 65 kg-N ha−1season−1, while emissions of NO were only of minor importance (between 0.1 to 0.7 kg-N ha−1 season−1). The findings demonstrate that for irrigated dryland soils in the Aral Sera Basin, denitrification is a major pathway of N-loss and that substantial amounts of N-fertilizer are lost as N2 to the atmosphere for irrigated dryland soils.

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Land use and agricultural practices can result in important contributions to the global source strength of atmospheric nitrous oxide (N2O) and methane (CH4). However, knowledge of gas flux from irrigated agriculture is very limited. From April 2005 to October 2006, a study was conducted in the Aral Sea Basin, Uzbekistan, to quantify and compare emissions of N2O and CH4 in various annual and perennial land-use systems: irrigated cotton, winter wheat and rice crops, a poplar plantation and a natural Tugai (floodplain) forest. In the annual systems, average N2O emissions ranged from 10 to 150 μg N2O-N m−2 h−1 with highest N2O emissions in the cotton fields, covering a similar range of previous studies from irrigated cropping systems. Emission factors (uncorrected for background emission), used to determine the fertilizer-induced N2O emission as a percentage of N fertilizer applied, ranged from 0.2% to 2.6%. Seasonal variations in N2O emissions were principally controlled by fertilization and irrigation management. Pulses of N2O emissions occurred after concomitant N-fertilizer application and irrigation. The unfertilized poplar plantation showed high N2O emissions over the entire study period (30 μg N2O-N m−2 h−1), whereas only negligible fluxes of N2O (<2 μg N2O-N m−2 h−1) occurred in the Tugai. Significant CH4 fluxes only were determined from the flooded rice field: Fluxes were low with mean flux rates of 32 mg CH4 m−2 day−1 and a low seasonal total of 35.2 kg CH4 ha−1. The global warming potential (GWP) of the N2O and CH4 fluxes was highest under rice and cotton, with seasonal changes between 500 and 3000 kg CO2 eq. ha−1. The biennial cotton–wheat–rice crop rotation commonly practiced in the region would average a GWP of 2500 kg CO2 eq. ha−1 yr−1. The analyses point out opportunities for reducing the GWP of these irrigated agricultural systems by (i) optimization of fertilization and irrigation practices and (ii) conversion of annual cropping systems into perennial forest plantations, especially on less profitable, marginal lands.

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A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

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Pollution on electrical insulators is one of the greatest causes of failure of substations subjected to high levels of salinity and environmental pollution. Considering leakage current as the main indicator of pollution on insulators, this paper focus on establishing the effect of the environmental conditions on the risk of failure due to pollution on insulators and determining the significant change in the magnitude of the pollution on the insulators during dry and humid periods. Hierarchical segmentation analysis was used to establish the effect of environmental conditions on the risk of failure due to pollution on insulators. The Kruskal-Wallis test was utilized to determine the significant changes in the magnitude of the pollution due to climate periods. An important result was the discovery that leakage current was more common on insulators during dry periods than humid ones. There was also a higher risk of failure due to pollution during dry periods. During the humid period, various temperatures and wind directions produced a small change in the risk of failure. As a technical result, operators of electrical substations can now identify the cause of an increase in risk of failure due to pollution in the area. The research provides a contribution towards the behaviour of the leakage current under conditions similar to those of the Colombian Caribbean coast and how they affect the risk of failure of the substation due to pollution.