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751.
Proper disposal and/or recycling of different industrial waste materials have long been recognized as a prime environmental concern throughout the world, and fly ash is major amongst them. In the present study, we tried to assess the feasibilities of possible effective and safe utilization of fly ash as soil amendment in Indian paddy field and its impact on rice plants, especially at growth and yield level. Our results showed that certain doses of fly ash amendments have significantly improved the physico-chemical and mineralogical properties of paddy field soil, and at lower level of amendments, fly ash induced the growth performances of three rice cultivars too. Grain yield and grain quality also responded similarly as per the growth responses. However, differential cultivar response was observed accordingly, and cultivar Sugandha-3 showed higher yield as compared with cultivars Sambha and Saryu-52. Based on the observed results, it was concluded that up to a certain level, fly ash amendments could be beneficial for Indian paddy field and can be utilized as feasible management strategy for the disposal of this major industrial waste.  相似文献   
752.
A rapid, simple, accurate, and sensitive visible spectrophotometric method for the determination of trace amounts of hydrogen peroxide in acidic buffer medium is reported. The proposed method is based on the oxidative coupling of Ampyrone with dibenzazepin hydrochloride by hydrogen peroxide in the buffer medium of pH?4.0 which is catalyzed by ferrous iron. The blue-colored product formed with maximum absorption at 620?nm was found to be stable for 2?h. Beer's law is obeyed for hydrogen peroxide concentration in the range of 0.03-0.42?μg?ml(-1). The optimum reaction conditions and other important optical parameters are reported. The molar absorptive and Sandell's sensitivity are found to be 5.89?×?10(4)?mol(-1)?cm(-1) and 0.57?g/cm(2), respectively. The interference due to diverse ions and complexing agents was studied. The method is successfully applied to the determination of hydrogen peroxide in green plants satisfactorily.  相似文献   
753.
A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.  相似文献   
754.
The particulate matter with an aerodynamic diameter less than or equal to 10 and 2.5 microns respectively (PM10 and PM2.5) constitutes one of the main air pollutants, which is currently regulated in Europe through Directive 2008/50/EC due to its proven harmful effects on human health. In this paper, the airborne PM10 samples collected in Zaragoza city during 2001-2009 were apportioned by statistical tools based on principal component analysis with absolute principal component scores (PCA-APCS). PM10 samples were characterized regarding their concentrations of polycyclic aromatic hydrocarbons (PAH) and water-soluble ions. PAH were analyzed by gas chromatography-mass spectrometry-mass spectrometry detection (GC-MS-MS) and ions were analyzed by ion chromatography. A total of five factors were identified by PCA-APCS corresponding to different anthropogenic and natural sources. This work was focused on analyzing in more detail those samples involving higher negative impact on human health, in particular, PM10 samples exceeding the daily PM10 limit value of 50 μg m(-3) according to Directive 2008/50/EC and samples with concentrations of benzo[a]pyrene (BaP) higher than the upper assessment threshold (BaP > 0.6 ng m(-3)) established by the Directive 2004/107/EC. Most of the exceedances of the daily PM10 limit value were associated with direct and indirect North-African long-range transport. During these exceedances, it was observed that anthropogenic pollution sources slightly decreased with regard to the natural sources. This indicated that episodes of high PM10 could have a natural origin associated with long-range transport from the African continent. On the contrary, those exceedances with regional contribution and samples with BaP concentrations higher than 0.6 ng m(-3) showed an important contribution of anthropogenic pollution sources increasing their negative impact on human health.  相似文献   
755.
Recent studies have reported an increasing trend of mercury concentrations in walleye (Sander vitreus) from the Athabasca River, north eastern Alberta (Canada); these studies were based on three years of comparison and attributed the mercury increase to expanding oil sands developments in the region. In order to conduct a more comprehensive analysis of mercury trends in fish, we compiled an extensive database for walleye, lake whitefish (Coregonus clupeaformis), northern pike (Esox lucius) and lake trout (Salvelinus namaycush) using all available data obtained from provincial, federal, and industry-funded monitoring and other programs. Evidence for increasing trends in mercury concentrations were examined for each species by location and year also considering fish weight and length. In the immediate oil sands area of the Athabasca River, mercury concentrations decreased (p < 0.001) in walleye and lake whitefish over 1984-2011. In western Lake Athabasca and its delta, mercury concentrations decreased (p < 0.0001) in northern pike (1981-2009) although no trend was evident for walleye (1981-2005) and lake trout (1978-2009). Mercury concentrations in lake trout from Namur Lake, a small lake west of the oil sands area, were higher in 2007 than 2000 (p < 0.0001); it is difficult to ascribe this increase to an oil sands impact because similar increases in mercury concentrations have been observed in lake trout from similar sized lakes in the Northwest Territories. While mercury emissions rates have increased with oil sands development and the landscape become more disturbed, mercury concentrations remained low in water and sediments in the Athabasca River and its tributaries and similar to concentrations observed outside the development areas and in earlier decades. Our fish database was assembled from a series of studies that differed in study purpose, design, and analytical methods. Future monitoring programs investigating mercury trends in fish should be more rigorous in their design.  相似文献   
756.
Healthcare settings present a challenging environment for assessing low-level concentrations of specific volatile organic compounds (VOCs) in the presence of high background concentrations of alcohol from the use of hand sanitizers and surface disinfectants. The purposes of this laboratory-based project were to develop and validate a sampling and analysis methodology for quantifying low-level VOC concentrations as well as high-level alcohol concentrations found together in healthcare settings. Sampling was conducted using evacuated canisters lined with fused silica. Gas chromatography/mass spectrometry analysis was performed using preconcentration (for ppb levels) and loop injection (for ppm levels). For a select list of 14 VOCs, bias, precision, and accuracy of both the preconcentration and loop injection methods were evaluated, as was analyte stability in evacuated canisters over 30 days. Using the preconcentration (ppb-level) method, all validation criteria were met for 13 of the 14 target analytes-ethanol, acetone, methylene chloride, hexane, chloroform, benzene, methyl methacrylate, toluene, ethylbenzene, m,p-xylene, o-xylene, alpha-pinene, and limonene. Using the loop injection (ppm-level) method, all validation criteria were met for each analyte. At ppm levels, alpha-pinene and limonene remained stable over 21 days, while the rest of the analytes were stable for 30 days. All analytes remained stable over 30 days at ppb levels. This sampling and analysis approach is a viable (i.e., accurate and stable) methodology that will enable development of VOC profiles for mixed exposures experienced by healthcare workers.  相似文献   
757.
This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.  相似文献   
758.
The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO2 flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO2 fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO2 uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m?2 and for the growth cycle of soybean (154 days) ?231 g C m?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.  相似文献   
759.
The Hawkesbury–Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the ‘bio-geographical’, ‘natural’ and ‘nutrient pollutant’ dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio-temporal scales, taking into account the various effects of nutrient and other pollutant loads from sewerage effluents, agriculture and other point and non-point sources along the river and major tributaries of the HNR. Over the past 26 years, water temperature has significantly increased while suspended solids have significantly decreased (p?<?0.05). The analysis of water quality data through FA, HACA and TA helped to characterise the key sections and cluster the key water quality variables of the HNR system. The insights gained from this study have the potential to improve the effectiveness of river health-monitoring programs in terms of cost, time and effort, particularly in a peri-urban context.  相似文献   
760.
Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (ECe 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.  相似文献   
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