广东省火电污染物排放特征及其对大气环境的影响

采用物料衡算及排放因子法建立了2012年广东省火电大气污染物排放(下称火电排放)清单,并运用WRF/SMOKE/CAMx模型分析火电排放对大气环境质量的影响. 结果表明:SO₂、NO_x、CO、PM₁₀、PM_2.5、VOCs和NH₃排放量分别为269 408、539 565、301 257、135 920、65 050、18 790、1 949 t. 300 MW以上的机组对火电排放的贡献较大,但125 MW以下的机组单位煤耗污染物排放较高. 春季、夏季、秋季、冬季火电排放所占比例分别为27.1%、25.4%、24.0%和23.5%,24 h排放呈“三峰三谷”特征；排放量较大的城市为广州、佛山、东莞、江门、汕头、潮州和梅州,不同区域火电排放贡献率顺序为珠三角 (46.2%~52.3%)>广东省东部(26.9%~34.3%)>广东省西部(11.9%~14.4%)>广东省北部(5.5%~10.0%). 8月火电排放对珠三角城市ρ(SO₂)、ρ(NO₂)月均值的贡献率较高,分别为17.0%、11.1%,其次为10月、4月、1月,其影响集中于火电厂所在城市及下风向区域,对不同城市的贡献差异性较大,具有局地特征；火电排放10月对ρ(PM₁₀)、ρ(PM_2.5)月均值贡献率(9.1%、10.6%)较高,其次为8月、4月和1月,影响区域更广,对不同城市的贡献差异较小,呈现区域性特征. 

Emission Characteristics of Thermal Power in Guangdong Province and Influence on Atmospheric Environment

Abstract: Using the material balance and emission factor methods, an air pollutant emissions inventory from thermal power in Guangdong Province in the year 2012 was estimated. The results show that emissions of SO₂, NO_x, CO, PM₁₀, PM_2.5, VOCs and NH₃ were 269,8, 539,5, 301,7, 135,0, 65,0, 18,0 and 1,9 tons, respectively. Class units above 300 MW made the main contribution to total emission, while those below 125 MW emitted more air pollutants per unit of coal consumption. In terms of the seasonal emissions, spring accounted for 27.1%, followed by summer (25.4%), fall (24.0%) and winter (23.5%). Three peaks and three valleys were found in the hourly emission distribution. Considering spatial distributions, emissions were mainly distributed in Guangzhou, Foshan, Dongguan, Jiangmen, Shantou, Chaozhou and Meizhou. With regards to the sub-category areas in Guangdong Province, about half of the emissions were concentrated in the Pearl River Delta region, with the percentage of 46.2%-52.3%, followed by the eastern (26.9%-34.3%), western (11.9%-14.4%) and northern areas (5.5%-10.0%). The impacts of thermal power emissions on the air quality in PRD were also estimated using WRF/SMOKE/CAMx. The results show that the influences on ambient SO₂ and NO₂ in the PRD cities were highest in August (17.0% and 11.1%), followed by October, April and January. The influences were commonly more noticeable in the downwind areas of power plant. When it comes to ambient PM₁₀ and PM_2.5, the influences were highest in October (9.1% and 10.6%), followed by August, April and January. Compared with SO₂ and NO₂, the area of influences on particulate matter was wider and showed less spatial variations.