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重污染天气下电力行业排放对京津冀地区PM2.5的贡献

杜晓惠 徐峻 刘厚凤 刘俊 何友江 党鸿雁 孟凡

杜晓惠, 徐峻, 刘厚凤, 刘俊, 何友江, 党鸿雁, 孟凡. 重污染天气下电力行业排放对京津冀地区PM2.5的贡献[J]. 环境科学研究, 2016, 29(4): 475-482.
引用本文: 杜晓惠, 徐峻, 刘厚凤, 刘俊, 何友江, 党鸿雁, 孟凡. 重污染天气下电力行业排放对京津冀地区PM2.5的贡献[J]. 环境科学研究, 2016, 29(4): 475-482.
DU Xiaohui, XU Jun, LIU Houfeng, LIU Jun, HE Youjiang, DANG Hongyan, MENG Fan. Contribution of Power Plant Emissions to PM2.5 over Beijing-Tianjin-Hebei Area during Heavy Pollution Periods[J]. Research of Environmental Sciences, 2016, 29(4): 475-482.
Citation: DU Xiaohui, XU Jun, LIU Houfeng, LIU Jun, HE Youjiang, DANG Hongyan, MENG Fan. Contribution of Power Plant Emissions to PM2.5 over Beijing-Tianjin-Hebei Area during Heavy Pollution Periods[J]. Research of Environmental Sciences, 2016, 29(4): 475-482.

重污染天气下电力行业排放对京津冀地区PM2.5的贡献

基金项目: 国家科技支撑计划项目(2014BAC06B05);国家电网公司科技项目(SGHAJYOOGHJS1500029)

Contribution of Power Plant Emissions to PM2.5 over Beijing-Tianjin-Hebei Area during Heavy Pollution Periods

  • 摘要: 利用CAMx(区域空气质量模型)中的PSAT(颗粒物源示踪技术),分析了重污染天气下分区域、分行业的污染物排放对京津冀地区PM2.5的贡献,设计了分行业排放的环境影响效率系数(EESCR)计算方法,并对“电能替代”(以电力行业产能替代民用能源消耗)情景方案下的排放进行模拟分析. 结果表明:在重污染天气背景下,电力行业排放对京津冀地区ρ(PM2.5)的贡献率较低,各地均低于10%,并且区域排放的贡献次序为京津冀以外地区>京津冀其他城市>当地,这与电力行业高架源排放的特征有关,而工业和民用行业对区域排放的贡献次序相反. PM2.5主要组分和前体物的分行业EESCR计算结果表明,电力行业ESSCR值均在y=1/2x趋势线之下,远低于其他行业,因此优先控制其他行业排放才是改善京津冀地区空气质量的关键.电能替代的情景模拟结果表明,电能替代是有效降低京津冀地区ρ(PM2.5)的可行方式. 研究显示,充分利用电力行业高架源排放的特点和便于集中处理的行业优势,尽力降低因产能增长带来的排放增量,实施电能替代可成为改善区域空气质量的有效途径之一.

     

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出版历程
  • 收稿日期:  2015-10-12
  • 修回日期:  2015-12-21
  • 刊出日期:  2016-04-25

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