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A. V. M. Subba Rao Arun K. Shanker V. U. M. Rao V. Narsimha Rao A. K. Singh Pragyan Kumari C. B. Singh Praveen Kumar Verma P. Vijaya Kumar B. Bapuji Rao Rajkumar Dhakar M. A. Sarath Chandran C. V. Naidu J. L. Chaudhary Ch. Srinivasa Rao B. Venkateshwarlu 《Environmental Modeling and Assessment》2016,21(1):17-30
966.
L. Schultz P. Shah E. Giandomenico B. Chiera 《Environmental Modeling and Assessment》2016,21(2):169-179
Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality. 相似文献
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Steven?J.?CookeEmail authorView authors OrcID profile Eduardo?G.?Martins Daniel?P.?Struthers Lee?F.?G.?Gutowsky Michael?Power Susan?E.?Doka John?M.?Dettmers David?A.?Crook Martyn?C.?Lucas Christopher?M.?Holbrook Charles?C.?Krueger 《Environmental monitoring and assessment》2016,188(4):239
Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions. 相似文献
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Ahmed F Bibi MH Asaeda T Mitchell CP Ishiga H Fukushima T 《Environmental monitoring and assessment》2012,184(7):4383-4396
Bottom sediments from Lake Jinzai in southwest Japan were analyzed to determine their chemical compositions and to assess the potential for ecological harm by comparison with sediment quality guidelines. The pollution status of lake sediments was evaluated by employing contamination factor (CF), pollution load index (PLI), and geoaccumulation index (I(geo)), focusing on a suite of elements in lakebed and core sediments. Elevated concentrations of As, Pb, Zn, Cu, TOC, N, and P were present in several layers of the upper core and other surface sediments. The elevated metal concentrations are likely related to the fine-grained nature of the sediments, reducing bottom conditions produced by abundant organic matter, and possibly minor non-point anthropogenic sources. Moreover, correlations between the concentrations of trace metals and organic carbon, nitrogen, phosphorus, and iron, suggest that these elements play a role in controlling abundances. Calculated CF, PLI, and I(geo) indicate that the sediments are strongly polluted with respect to As, moderately to strongly polluted with Zn, and moderately polluted with Pb and Cu. Metal concentrations exceed the New York State Department of Environmental Conservation (NYSDEC) lowest effect level and the Canadian Council of Ministers of the Environment (CCME) interim sediment quality guidelines that indicate moderate impact on aquatic organisms in the study area. 相似文献
970.
The presence of the anesthetic lidocaine (LDC), the analgesic tramadol (TRA), the antidepressant venlafaxine (VEN) and the metabolites O-desmethyltramadol (ODT) and O-desmethylvenlafaxine (ODV) was investigated in wastewater treatment plant (WWTP) effluents, in surface waters and in groundwater. The analytes were detected in all effluent samples and in only 64% of the surface water samples. The mean concentrations of the analytes in effluent samples from WWTPs with wastewater from only households and hospitals were 107 (LDC), 757 (TRA), 122 (ODT), 160 (VEN) and 637 ng L(-1) (ODV), while the mean concentrations in effluents from WWTPs treating additionally wastewater from pharmaceutical industries as indirect dischargers were for some pharmaceuticals clearly higher. WWTP effluents were identified as important sources of the analyzed pharmaceuticals and their metabolites in surface waters. The concentrations of the compounds found in surface waters ranged from 相似文献