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991.
Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.  相似文献   
992.
Environmental Science and Pollution Research - We studied the possible metal offloading onto the progeny of three pregnant female ragged-tooth sharks (Carcharias taurus) (C. taurus). The presences...  相似文献   
993.
994.
This study aims to estimate the emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitric oxide (NO) for coal combustion in thermal power plants in India using plant-specific emission factors during the period of 2001/02 to 2009/10. The mass emission factors have been theoretically calculated using the basic principles of combustion under representative prevailing operating conditions in the plants and fuel composition. The results show that from 2001/02 to 2009/10 period, total CO2 emissions have increased from 324 to 499 Mt/year; SO2 emissions have increased from 2,519 to 3,840 kt/year; and NO emissions have increased from 948 to 1,539 kt/year from the Indian coal-fired power plants. National average emissions per unit of electricity from the power plants do not show a noticeable improvement during this period. Emission efficiencies for new plants that use improved technology are found to be better than those of old plants. As per these estimates, the national average of CO2 emissions per unit of electricity varies between 0.91 and 0.95 kg/kWh while SO2 and NO emissions vary in the range of 6.9 to 7.3 and 2.8 to 2.9 g/kWh, respectively. Yamunagar plant in Haryana state showed the highest emission efficiencies with CO2 emissions as 0.58 kg/kWh, SO2 emissions as 3.87 g/kWh, and NO emissions as 1.78 g/kWh, while the Faridabad plant has the lowest emission efficiencies with CO2 emissions as 1.5 kg/kWh, SO2 emissions as 10.56 g/kWh, and NO emissions as 4.85 g/kWh. Emission values at other plants vary between the values of these two plants.  相似文献   
995.
In countries like India where multiple risks interact with socio-economic differences to create and sustain vulnerability, assessing the vulnerability of people, places, and systems to climate change is a critical tool to prioritise adaptation. In India, several vulnerability assessment tools have been designed spanning multiple disciplines, by multiple actors, and at multiple scales. However, their conceptual, methodological, and disciplinary underpinnings, and resulting implications on who is identified as vulnerable, have not been interrogated. Addressing this gap, we systematically review peer-reviewed publications (n = 78) and grey literature (n = 42) to characterise how vulnerability to climate change is assessed in India. We frame our enquiry against four questions: (1) How is vulnerability conceptualised (vulnerability of whom/what, vulnerability to what), (2) who assesses vulnerability, (3) how is vulnerability assessed (methodology, scale), and (4) what are the implications of methodology on outcomes of the assessment. Our findings emphasise that methods to assess vulnerability to climate change are embedded in the disciplinary traditions, methodological approaches, and often-unstated motivations of those designing the assessment. Further, while most assessments acknowledge the importance of scalar and temporal aspects of vulnerability, we find few examples of it being integrated in methodology. Such methodological myopia potentially overlooks how social differentiation, ecological shifts, and institutional dynamics construct and perpetuate vulnerability. Finally, we synthesise the strengths and weaknesses of current vulnerability assessment methods in India and identify a predominance of research in rural landscapes with a relatively lower coverage in urban and peri-urban settlements, which are key interfaces of transitions.  相似文献   
996.
Environmental Science and Pollution Research - Though globalization, industrialization, and urbanization have escalated the economic growth of nations, these activities have played foul on the...  相似文献   
997.
Environmental Science and Pollution Research - Food materials are consumed for nutritional purposes in the form of fruits, vegetables, plants, and meat. These contain proteins, carbohydrates, and...  相似文献   
998.
Environmental Science and Pollution Research - Regional averages of radon, thoron, and associated decay product concentration are reported to be higher than their respective global averages in...  相似文献   
999.
Environmental Science and Pollution Research - Bioaugmented zero water exchange aquaculture production systems (ZWEAPS) maintained with minimal or no water exchange prevent the ammonia accumulation...  相似文献   
1000.
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