基于GIS的唐山地区大气污染物时空分布研究

应用数据统计和ArcGIS对北方重工业城市唐山地区2014年14个县(区)18个空气自动监测站的数据进行时空分布特征分析,监测的污染物为PM_(10)、SO_2、NO_2、PM_(2.5)、O_3、CO共6项。利用ArcGIS对各个自动监测站污染物数据建立网格模型,采用反距离权重法分别对年均、采暖期、非采暖期的环境空气质量综合指数和6项污染因子浓度的空间分布进行估算,直观比较了污染物在不同时期内的空间分布状况。结果表明,空气质量时间分布较为明显,非采暖期明显好于采暖期。同时,计算出每个网格单元污染指数的标准偏差,结合气象气候、地形地势、工业发展等情况,分析得出北部山区、市中心区附近区域空气质量波动较大。为区域大气污染有针对性的综合防治、联防联控及污染物区域削减计划打下数据基础。

Research on the Temporal and Spatial Distribution of Air Pollutants in Tangshan Based on GIS

In this paper, data statistics and ArcGIS were adapted to analyze the temporal and spatial distribution of air pollutants in a heavy industry northern city of Tangshan, with the data from 18 automatic air quality monitoring stations of 14 counties in 2014, The following six pollutants were monitored:PM₁₀, SO₂, NO₂, PM_2.5, O₃, CO. By using the geographic information system (ArcGIS), grid model was established on the basis of various automatic monitoring station pollutant data. By using the inverse distance weighting method, the spatial distribution of comprehensive pollution index and concentration of six pollutants during the whole year, heating period and non-heating period was estimated, respectively. The spatial distribution status of pollutants in different periods were being compared directly. It came to a conclusion that the air quality varied due to different time. In other words, it is obvious that the air quality is much better in non-heating period than the heating period. Meanwhile the standard deviation of each grid cell pollution index was calculated. Combining the climate, terrain, industrial development, etc., it concluded that the air quality had a larger fluctuation in northern mountainous area and the downtown neighboring area. These could lay the data foundation for the targeted control, joint defense and pollutants district-cutting plans on districts air pollution.