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PMF、CMB、FA等大气颗粒物源解析模型对比研究

Comparative Study on PMF、CMB and FA Models of Sources Apportionment of Atmospheric Particulates

【作者】 陈分定

【导师】 房春生;

【作者基本信息】 吉林大学 , 环境科学, 2011, 硕士

【摘要】 由国家环境保护部发布的《中国环境质量状况报告》可知,我国环境空气质量总体状况良好,但部分城市污染仍较重,特别是一些经济发展较快的大中城市。受气候、地形、城市布局等因素的影响,环境空气污染治理难度较大。由于大气颗粒物具有组成复杂、危害较大并可以作为其他具有危害性的物质的承载物的特点,大气颗粒物及其治理越来越受到人们的关注。对大气颗粒物进行源解析研究,不仅可以定性了解大气颗粒物的污染特征,还可以定量计算出各种有贡献的排放源对大气环境颗粒物的贡献情况。源解析研究结果可以作为相关部门进行环境空气颗粒物污染治理的科学依据,对不同的排放源采取不同的治理措施。龙岩市地处福建省西部。龙岩市的山谷走向为东南走向,东部山坡较高,山谷地形严重影响了市区低层大气的流动,使得龙岩市低层大气污染更加严重。而冬季逆温的出现,导致空气中PM10污染物无法稀释及向外部扩散,极易在市区内部堆积,从而使得冬季污染物浓度高于其它季节。根据在代表不同功能区的四个监测点(龙岩师专、龙岩学院、龙岩市监测站和闽西大学)采集的受体样品,对龙岩市大气颗粒物时空分布特征进行研究得知,龙岩市不同功能区大气颗粒物样品中的元素浓度存在较明显的空间分布特征,工业企业和机械制造业多的区域(龙岩师专和闽西大学)高于商业区和居民生活区(市监测站);元素Mg、Al、K、Ca、Fe、Zn和Ni含量季节变化较大,且变化规律不一致,其他元素季节变化不是很明显。目前,龙岩市大气颗粒物污染严重,采用CMB、FA、PMF三种模型对龙岩市大气颗粒物PM10进行来源解析研究,有助于更有效地治理颗粒物污染,提高环境空气质量。CMB模型解析结果表明:第一次采样,对龙岩市PM10贡献较大的源类为城市综合扬尘和道路尘;第二次采样,城市综合扬尘和机动车尾气尘对龙岩市PM10的贡献最大;第三次采样,龙岩市PM10的主要来源是城市综合扬尘、土壤风沙尘和机动车尾气尘;全年样品,龙岩市全年大气颗粒物PM10的主要来源是:燃煤尘、土壤风沙尘、城市综合扬尘和道路尘。FA模型解析结果表明:第一次采样,龙岩市PM10主要源于土壤风沙尘和城市综合扬尘的贡献;第二次采样,土壤风沙尘和城市综合扬尘、交通道路尘对龙岩市PM10贡献最大;第三次采样,龙岩市PM10的主要来源为土壤风沙尘和交通道路尘、燃煤尘及城市综合扬尘;全年样品,龙岩市全年大气颗粒物PM1o的主要来源是:土壤风沙尘和城市综合扬尘、机动车尾气尘和道路尘。PMF模型解析结果表明:第一次采样,龙岩市PM1o的主要来源是建筑水泥尘和燃煤尘;第二次采样,燃煤尘、机动车尾气尘、建筑水泥尘和土壤风沙尘对龙岩市PM1o贡献最大;第三次采样,龙岩市PM10的主要来源为土壤风沙尘、生物质和废弃物燃烧尘及城市综合扬尘;全年样品,龙岩市大气颗粒物PM1o的主要来源是:燃煤尘、建筑水泥尘、机动车尾气尘和钢铁厂除尘器集尘。运用Visual Basic 6.0开发语言设计的PMF源解析程序也能满足计算的需要,结果与实际相符。CMB模型较FA模型和PMF模型成熟,应用也较后两者广泛,在已知受体成分谱和源成分谱的情况下解析结果更有效;FA模型在已知受体成分谱而源成分谱未知的情况下,根据受体成分谱之间的相关性,结合源的特征元素知识,推断出排放源的类型及其方差贡献率;PMF模型与FA模型相似,都是在已知受体成分谱而源成分谱未知的情况下,结合运算结果、EV值和源的标识元素知识,推断排放源的类型。PMF模型优于FA模型的显著特点是可以得到非负的源成分谱和源贡献率,解析结果更有意义、更符合实际情况。根据龙岩市大气颗粒物PM1o样品监测结果及源解析结果,建立的基于GIS的大气颗粒物源解析结果展示系统可直观地展现龙岩市大气颗粒物PMlo的分布规律、污染物来源、污染程度等信息,方便地生成污染物分布图、各项指标专题图以及等值线图层,对这些图层有选择、有次序地叠加,在一张图上可以显示不同图层的综合信息。同时,还可以对比显示不同源解析方法对不同时期大气颗粒物源的解析结果。

【Abstract】 According to the China Environmental Quality Status Report issued by the State Environmental Protection Ministry, environment air quality of our country is good on the whole, but the pollution of some cities is still heavier, especially some provinces and cities with faster economic development. Because of the influence of such factors as climate, topography, urban layout, it’s very difficult to deal with environment air pollution. Atmospheric particulates and its control have attracted more and more attention, because it is complex, harmful and can be the carrier of other dangerous substances. The source apportionment of atmospheric particulates cannot only qualitatively understand pollution characteristics of the atmospheric particulates, but can also quantitatively calculate the contributions of various emission sources to the atmospheric particulates. The result of source apportionment study can be taken as the scientific basis of treating environmental air particulates pollution. And different measures are adopted to manage different emission sources.Longyan city is located in the west of Fujian province. The valley slope of Longyan city is from south to east. The east valley is higher. The valley terrain seriously impacts the flow of the lower atmosphere in the urban area, making the pollution in the lower atmosphere of Longyan city more serious. The air contaminant PM10 cannot be diluted and diffused because of the temperature inversion in winter, which results in PMio accumulated easily in urban areas. As a result, the concentration of pollutant in winter is higher than that in other seasons. According to receptor samples collected in four monitoring spots which represent different functional areas (Longyan Teachers College, Longyan college, Environment Monitoring Station of Longyan and University of Western Fujian), and the study of the distributive characters of atmospheric particulates in time and space in Longyan city, the elements concentration of atmospheric particulates samples collected in different functional areas is obviously different in different places. Industrial and mechanical manufacturing areas (Longyan Teachers College and University of Western Fujian) are higher in the quantity of particulates than downtown and living areas (Environment Monitoring Station of Longyan). The concentration of elements such as Mg, Al, K, Ca, Fe, Zn and Ni varies greatly from season according to different tendencies, while the amount of other elements does not change very much.At present, atmospheric particulate pollution of Longyan city is serious. The study on source apportionment to atmospheric particulates PM10 of Longyan city adopts the CMB, FA and PMF models, which is helpful for effectively controlling particulate pollution and improving the air quality. The results by CMB model show that:for the first samples, the sources with bigger contribution to PM10 sample of Longyan city are urban fugitive dust and road dust; for the second, urban comprehensive fugitive dust and motor vehicle exhaust dust are the major contribution to PM10; for the third, the main sources of PM10 sampled in Longyan city are urban comprehensive fugitive dust, soil dust and motor vehicle exhaust dust; for annual samples, the main sources of atmospheric particulates PM10 are coal-burnt dust, soil dust, urban comprehensive fugitive dust and road dust. The results by FA model show that:for the first samples, PM10 of Longyan city mainly comes from soil dust and urban comprehensive fugitive dust; for the second, soil dust, urban comprehensive fugitive dust and road dust are the largest contribution to PM10 of Longyan city; for the third, the main sources of PM10 of Longyan city are soil dust, road dust, coal-burnt dust and urban comprehensive fugitive dust; for the annual samples, the main sources of atmospheric particulates PM10 are:soil dust, urban comprehensive fugitive dust, road dust and motor vehicle exhaust dust. The results by PMF model show that:for the first samples, the main sources of PM10 of Longyan city are construction cement dust and coal-burnt dust; for the second, coal-burnt dust, motor vehicle exhaust dust, construction cement dust and soil dust are the largest contribution to PM10; for the third samples, the main sources of PM10 are soil dust, biomass-burnt and waste-burnt dust, and urban comprehensive fugitive dust; for annual samples, the main sources of atmospheric particulates PM10 of Longyan city are:coal-burnt dust, construction cement dust, motor vehicle exhaust dust, iron and steel industry dust. The PMF sources apportionment program designed via Visual Basic 6.0 can satisfy the need of calculation, and the calculation result is consistent with the reality. The CMB model is more mature and more widely used than PMF model and FA model. With both receptor component spectrums and source component spectrum known, the source apportionment result by CMB model is more efficient. According to the correlation between the receptor components and the characteristics of source components, the source types and contribution rate can be deduced by the FA model, even though the receptor profile is known and the source profile is unknown. The PMF model is similar to the FA model. The type of emissions sources is inferred by PMF, when the receptor profile is known but the source profile unknown, combined with calculation result, the EV and the characteristics of source components. The advantage of PMF model to FA model is that nonnegative source profile and contribution rate can be obtained by PMF model. And the results of source apportionment are more meaningful and more consistent with the actual situation.According to the PM10 monitoring results and source apportionment results of Longyan city, the author has designed a results-displaying system based on GIS. This system can visually show distribution rule, pollution, pollutants sources of PM10 of Longyan city, and conveniently generate the map of contaminant distribution, special charts of each index and isoline layers. Stacking these layers selectively and orderly, the comprehensive information of different layers can be displayed in one map. Meanwhile, the sources apportionment results calculated by different sources apportionment methods to the samples collected during different sampling period are showed comparatively.

  • 【网络出版投稿人】 吉林大学
  • 【网络出版年期】2011年 09期
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