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Use of dispersion model and satellite SO_2 retrievals for environmental impact assessment of coal-fired power plants

机译:使用离散模型和卫星SO_2取回评估燃煤电厂的环境影响

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The aim of this study is to investigate the impact of ten proposed plants along with three operating plants in canakkale province of Turkey where the proposed plants are within very close proximity. The province has the highest capacity of the planned plants and the region is also of interest due to its history, tourism and agriculture potential. Current SO2 pollution was assessed using ground observations and satellite retrievals where the impact of plants was better captured by satellite retrievals.Individual and cumulative impact from proposed and operating plants was simulated by CALPUFF for 2014. The study domain was 150 x 150 km(2), with 1 x 1 km2 cell size. The effect of changing meteorological inputs and domain size were investigated with simulations. Three cases were performed using meteorological inputs: from one surface and one radiosonde station (Case 1), 22 surface and one radiosonde station (Case 2), and 22 surface and two radiosonde stations (Case 3).Case 2 and 3 resulted in higher concentrations and showed larger affected regions than case 1 in all simulations. The cumulative impact of proposed plants indicated national annual and daily limit values were exceeded in Case 2 and 3. Hourly limit values were exceeded in all three cases.Simulations for two selected proposed plants were assessed for plant impact area given in environmental impact area reports. Results indicated the plant impact areas cannot be sufficient to determine the maximum SO2 concentrations in some cases and using single meteorology station data cannot represent the study area, especially regions with complex terrain and land-sea interactions such as canakkale province. Cumulative impact can be underestimated clue to small size of plant impact areas not including other plants. Lastly satellite retrievals arc better capturing the pollution than air quality monitoring stations which are strongly affected by meteorology. (C) 2019 Elsevier B.V. All rights reserved.
机译:这项研究的目的是调查土耳其恰纳卡莱省十家拟建工厂和三家运营工厂的影响,这些工厂非常接近。该省的计划植物产能最高,该地区的历史,旅游业和农业潜力也吸引了该地区。目前的SO2污染是通过地面观测和卫星检索评估的,卫星检索可以更好地捕获植物的影响。CALPUFF在2014年模拟了拟建和运营工厂的个体和累积影响。研究范围为150 x 150 km(2) ,其像元大小为1 x 1 km2。通过模拟研究了更改气象输入和域大小的影响。使用气象输入进行了3例:从一个地面和一个探空仪站(案例1),22个地面和一个探空仪站(案例2),以及22个地面和两个探空仪站(案例3),案例2和3导致更高在所有模拟中,浓度都比情况1高,并且显示出更大的受影响区域。拟议工厂的累积影响表明在案例2和3中均超过了国家年度和每日限值。在所有三种情况下均超过了小时限值。对两个选定拟议工厂的模拟对环境影响区域报告中给出的工厂影响区域进行了评估。结果表明,在某些情况下,植物影响区不足以确定最大的SO2浓度,并且使用单一气象站数据无法代表研究区,特别是地形复杂且具有陆海相互作用的区域(如canakkale省)。累积影响可能被低估了,这是因为植物影响区域较小(不包括其他植物)。最后,与受到气象影响严重的空气质量监测站相比,卫星检索可以更好地捕获污染。 (C)2019 Elsevier B.V.保留所有权利。

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