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基于Model-3/CMAQ模式的本溪市大气细颗粒物数值模拟
引用本文:秦思达,惠秀娟,夏广锋,王淑兰.基于Model-3/CMAQ模式的本溪市大气细颗粒物数值模拟[J].环境科学研究,2018,31(1):53-60.
作者姓名:秦思达  惠秀娟  夏广锋  王淑兰
作者单位:1.辽宁大学环境学院, 辽宁 沈阳 110036
基金项目:国家重点研发计划重点专项(2017YFC212500);辽宁省中央引导地方科技发展专项;辽宁省环境保护厅委托项目(辽宁省中部城市群雾霾分析及对策研究)
摘    要:为探究北方山区城市大气细颗粒物污染特征,应用气象模式WRF耦合空气质量模式CMAQ对本溪市2016年PM2.5空间分布特征、化学组分特征及主要污染源贡献情况进行分析.本溪市SO2、NOx、TSP的工业排放量分别达到5.2×104、4.1×104、16.1×104 t.结果表明,模拟值与监测值变化趋势基本一致,模拟效果较好. 1月ρ(PM2.5)明显高于7月,空间分布均呈现"西高东低"态势,高值区出现在人口稠密的市区附近. 1月ρ(PM2.5)本地源贡献率表现为钢铁(35.7%)>供暖(12.5%)>居民(7.5%)>移动(5.2%)>秸秆(2.0%)>电力(0.4%);7月为钢铁(48.6%)>移动(9.2%)>建材(3.5%)>居民(2.8%)>电力(1.5%).受气候、地貌及大气污染物排放特征影响,1月区域传输特征明显,外来源贡献为24%,高于7月的14%.另外,1月和7月本溪市PM2.5组分中二次粒子(SO42-、NO3-、NH4+)占比分别为29%和32%,碳组分(OC、EC)占比分别为43%和37%,碳气溶胶污染严重.研究显示,本溪市大气细颗粒物污染具有明显的季节性变化特征,1月部分区域浓度超标主要是由于以钢铁行业为主的工业排放造成,加之本溪市1月以西北风为主且风力较大,市区位于西部低海拔地区,来自中部城市群的污染物在向东南方向传输过程中受到高海拔山区阻隔,从而形成污染物积聚效应. 

关 键 词:CMAQ    PM2.5    源解析    辽宁省中部城市群
收稿时间:2017/6/19 0:00:00
修稿时间:2017/9/20 0:00:00

A Numerical Study of PM2.5 Pollution in Benxi City based on Model-3/CMAQ
QIN Sid,HUI Xiujuan,XIA Guangfeng and WANG Shulan.A Numerical Study of PM2.5 Pollution in Benxi City based on Model-3/CMAQ[J].Research of Environmental Sciences,2018,31(1):53-60.
Authors:QIN Sid  HUI Xiujuan  XIA Guangfeng and WANG Shulan
Institution:1.Environmental Sciences, Liaoning University, Shenyang 110036, China2.Liaoning Academy of Environmental Sciences, Shenyang 110161, China3.Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Abstract:To investigate the pollution characteristics of fine particulate matter in the northern mountain cities, the research adopts Weather Research and Forecasting Model (WRF) in combination with Congestion Mitigation and Air Quality Model (CMAQ) to analyze the spatial distribution characteristics, chemical constituent and the main contributed pollutant sources of PM2.5 in Benxi City for the year 2016. The industrial pollution of SO2, NOx, and TSP in Benxi City are 5.2×104, 4.1×104, and 16.1×104 tons respectively. According to the result, the simulation value and the monitoring value change trend are basically consistent. Therefore the simulation results are reliable. PM2.5 concentration of Benxi City in January is obviously higher than that in July; the spatial distribution of PM2.5 in west area is higher than that in east area. The high-concentration area occurs in populated main city. The main contribution of PM2.5 concentration in January is Steel (35.7%)>Heating (12.5%)>Resident (7.5%)>Mobile (5.2%)>Straw (2.0%)>Electricity (0.4%); On the other hand, Steel (48.6%)>Mobile (9.2%)>Concrete (3.5%)>Resident (2.8%)>Electricity (1.5%) in July. Affected by climate, landscape and characteristics of pollutant distribution, transmission is obvious in January, external source contribution is 24%, which is higher than that in July (14%). Besides, the secondary particles of PM2.5 (SO42-, NO3-, NH4+) in Benxi City occupy 29% and 32% in January and July, carbon components(OC, EC) occupy 43% and 37%, Carbon aerosols pollution is heavy. PM2.5 air pollution in Benxi City illustrates obvious seasonal variation. Concentration in partial region of January exceeds the standard mainly due to industrial emissions (especially steel industry).In addition, the city of Benxi was dominated by the northwest wind and the wind was strong in January. The city is located in the low-altitude area of the west. The pollutants from the central urban agglomeration are blocked by high altitude in the south-eastern direction, that lead to the pollutant concentration increase. 
Keywords:CMAQ  PM2  5  source apportionment  urban agglomeration of central Liaoning Province
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