基于PM2.5形成贡献的广东省2020年火电环保空间测算

doi:10.11930/j.issn.1004-9649.2016.10.136.06

摘要/Abstract

摘要： 以PM2.5为典型细粒子代表的雾霾污染问题已广受关注，作为经济快速发展的珠三角地区，复合型区域大气污染特征日益明显。火电厂是电力行业的主要排放源，其排放对大气环境有不可忽视的作用。通过分析历史年份火电厂一次排放情况及火电厂对污染物的排放贡献，在《大气污染防治行动计划》等相关政策的控制约束下，预测广东省2020年火电厂及全省污染物排放趋势。利用CAMｘ（ＰＳＡＴ）模型模拟得到火电厂对细颗粒污染物的贡献。通过假设火电厂在维持2012年贡献率水平且PM2.5均值浓度不超过国家环境空气质量标准的基础上，在现役及规划电源厂址上，构建火电厂对PM2.5形成贡献率的变化与装机容量变化的关系，测算出2020年广东省可新建火电装机容量。

关键词: 火电厂, 大气污染物, PM2.5, 环保空间测算, 装机容量

Abstract: Haze pollution caused by airborne fine particulates, typically PM2.5, has received lots of attention. In the Pearl River Delta area where the economy is growing very fast, the regional and complex air pollution characteristics are becoming increasingly evident. As the major emission source of electric power industry, the discharges from the thermal power plants have great impacts on the atmospheric environment. By analyzing the historic emission conditions and contributions of thermal power plants, under the constraints of the related policy control, the pollutant emission trends are predicted for not only thermal power plants but also the entire province of Guangdong in 2020. The contribution to fine particle pollution of thermal power plants is obtained by virtue of simulations based on CAMX (PSAT) model. Assuming that the contribution percentage is at the same level as that in 2012, and the average PM2.5 concentration complies to the national ambient air quality standard, the relationship between contribution percentage and generation capacity changes is established in consideration of the in-service and the planned power plant locations, thus the feasible installed capacity for new thermal power plant can be calculated for year 2020.

Key words: thermal power plant, atmospheric pollutant, PM2.5, environmental protection space estimation

中图分类号:

X513
TM621

覃芸，郑秀波，朱文波，林勇，郑君瑜，王延纬. 基于PM2.5形成贡献的广东省2020年火电环保空间测算[J]. 中国电力, 2016, 49(10): 136-141.

QIN Yun, ZHENG Xiubo, ZHU Wenbo, LIN Yong, ZHENG Junyu, WANG Yanwei. Estimation of Environmental Protection Space Based on PM2.5 Contributions for Guangdong Thermal Power Generation in 2020[J]. Electric Power, 2016, 49(10): 136-141.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.2016.10.136.06

https://www.electricpower.com.cn/CN/Y2016/V49/I10/136

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