...
首页> 外文期刊>Atmospheric environment >Unit-based emission inventory and uncertainty assessment of coal-fired power plants
【24h】

Unit-based emission inventory and uncertainty assessment of coal-fired power plants

机译:燃煤电厂的单位排放清单和不确定性评估

获取原文
获取原文并翻译 | 示例
           

摘要

A unit-based emission inventory of coal-fired power plants in China was developed which contains unit capacity, coal consumption, emission control technology and geographical location. Estimated total emissions of SO_2, NO_x, particulate matter (PM) and PM_(2.5) in 2011 were 7251 kt, 8067 kt, 1433 kt and 622 kt, respectively. Units larger than 300 MW consumed 75% coal, while emitting 46% SO_2,58% NO_x, 55% PM and 63.2% PM_(2.5). Emission comparisons between key regions such as the Yangtze River Delta, the Pearl River Delta and Shandong Province showed a general downward trend from 2005 to 2011, mainly because of the growing application ratio of desulphurisation, LNBs, denitration and dust-removal facilities. The uncertainties at unit level of SO_2, NO_x, PM and PM25 were estimated to be -10.1% ~ +5.4%, -2.1% ~ +4.6%, -5.7% ~ +6.9% and -4.3% ~ +6.5%, respectively. Meanwhile sector-based Monte Carlo simulation was conducted for better understanding of the uncertainties. Unit-based simulation yielded narrowed estimates of uncertainties, possibly caused by the neglected diversity of emission characteristics in sector-based simulation. The large number of plants narrowed unit-based uncertainties as large uncertainties were found in provinces with a small number of power plants, such as Qinghai. However, sector-based uncertainty analysis well depends on detailed source classification, because small NO_x uncertainties were found in Shandong due to the detailed classification of NO_x emission factors. The main uncertainty sources are discussed in the sensitivity analysis, which identifies specific needs in data investigation and field measures to improve them. Though unit-based Monte Carlo greatly narrowed uncertainties, the possibility of underestimated uncertainties at unit level cannot be ignored as the correlation of emission factors between units in the same source category was neglected.
机译:编制了中国燃煤电厂的单位排放清单,其中包含单位容量,煤炭消耗,排放控制技术和地理位置。 2011年,SO_2,NO_x,颗粒物(PM)和PM_(2.5)的估计总排放量分别为7251 kt,8067 kt,1433 kt和622 kt。大于300兆瓦的机组消耗了75%的煤炭,同时排放了46%的SO_2、58%的NO_x,55%的PM和63.2%的PM_(2.5)。从2005年到2011年,长江三角洲,珠江三角洲和山东省等重点区域的排放比较显示总体下降趋势,这主要是由于脱硫,LNB,脱硝和除尘设施的应用比例不断增加。 SO_2,NO_x,PM和PM25的单位水平不确定度分别估计为-10.1%〜+5.4%,-2.1%〜+ 4.6%,-5.7%〜+ 6.9%和-4.3%〜+ 6.5%。 。同时进行了基于扇区的蒙特卡洛模拟,以更好地了解不确定性。基于单元的模拟得出的不确定性的估计范围变窄,这可能是由于基于扇区的模拟中排放特征的被忽略的多样性所致。大量的发电厂缩小了单位不确定性,因为在青海等发电厂较少的省份发现了较大的不确定性。但是,基于部门的不确定性分析完全取决于详细的源分类,因为在山东,由于对NO_x排放因子的详细分类,发现了较小的NO_x不确定性。敏感性分析中讨论了主要的不确定性来源,该不确定性来源确定了数据调查和改进中的现场措施的特定需求。尽管基于单元的蒙特卡洛极大地缩小了不确定性的范围,但是由于忽略了同一排放源类别中单元之间的排放因子之间的相关性,因此不能忽略单元水平上被低估的不确定性的可能性。

著录项

  • 来源
    《Atmospheric environment》 |2014年第12期|527-535|共9页
  • 作者单位

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

    State Key Laboratory of Clean Energy Utilisation, Zhejiang University, Hangzhou 310027, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Unit-based emission inventory; Uncertainty assessment; Coal-fired power plant; SO_2; NO_x; PM_(2.5); China;

    机译:基于单位的排放清单;不确定度评估;燃煤电厂;SO_2;NO_x;PM_(2.5);中国;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号