基于GIS的大气污染源项分类体系及臭氧浓度相关性分析

近年来,中国城市的急速发展伴生了严峻的空气污染问题,其中,臭氧污染问题亦十分突出.量化分析各类污染源对空气污染的影响程度是制定相关政策及有效解决空气污染问题的关键.但大气污染源种类繁复,要对所有源项进行细致排查难以实现,随着GIS和地图产品的丰富,地理信息大数据为更便捷详尽地掌握地面源项信息提供了可能.本文以成都为例,对地理信息数据进行分类并建立其与各类源项的表征关系,基于统计分析探讨各类源项与臭氧浓度的相关性,并分析评价各种源项对成都市臭氧问题的影响.结果表明,成都市近年来臭氧问题的加剧与人类活动密切相关,其中,工业源与臭氧浓度相关性最大,机动车服务源的溶剂使用与臭氧浓度也呈正相关.交通源由于NO_x和VOC之间的相互作用会在一定程度上抑制臭氧生成,从而与臭氧浓度的相关性显著水平较低.这些结果的发现对于精细化空气质量管理和污染防治具有非常重要的意义.

A GIS-based approach for air pollutants source classifications and its correlational analysis with ozone concentration

With the rapid development of economy in China in recent years, air pollution has become increasingly prominent, especially in the urban area. It is imperative to quantify the contributions of different sources to air pollution for air quality management and improvement. However, air pollution contributing sources exist almost everywhere in the city, which has posed significant challenges in identifying and quantifying these sources. Fortunately, the wide application of Geographic Information System (GIS) has made these sources geocoded in a variety of mapping-related products, from which sources information can be retrieved. This research uses Chengdu as an example to regroup geocoded data from mapping-related products as surrogates to represent various sources. Several buffers with different distances surrounding seven environmental monitoring stations were defined. For each of the buffers, the total numbers of surrogates which represent different sources were counted. Correlation coefficients between ozone concentrations of the seven monitoring stations and the numbers of surrogates for each source within each buffer size were estimated. The results showed that ozone concentrations in Chengdu have positive correlations with VOC emitting sources such as manufacturing industries, solvent uses for vehicle services, and others with the former being the most correlated one. Although nitrogen oxides (NO_x) is one of the ozone formation precursors and mainly come from mobile vehicles, the correlation coefficient between mobile source and ozone concentration is relatively small. This may be due to the complex atmospheric chemical reactions for ozone formation when both NO_x and VOC exist. The developed method for air pollution sources identification and quantification using geocoded information can be used for improving the accuracy of emission inventory development.