Air Quality Monitoring Studies Point Chongqing City Environment

All efforts of environmental monitoring work are to realize the monitoring data’srepresentation, comparability, accuracy, precision and integrity, and the most basicnature is representative. Other nature will become meaningless without therepresentation. At present, many methods was used in the ambient air monitoring pointarrangement, such as functional area grid optimization method, mathematical statisticsmethod, nonlinear methods, the matter element analysis method, simulation analysisand comprehensive evaluation method to optimize atmospheric monitoring points. Theexisting data show that, the arrangement method and standard of ambient air qualitymonitoring point mainly from the characteristics of the majority of plain city. The cityfunction distribution, population density and position conditions were more detailedprovisions.Chongqing is located in the Western China, the upper reaches of the Yangtze Riverand the hinterland of the Three Gorges Reservoir area, in the landscape, the most typicalcharacteristic is many mountain and river. Along the river terrain, mountains and downs,this formed from the North-South tilt to the Yangtze River Valley landscape, dominatedby mountainous, hilly terrain. This text with the thought of "people-oriented", the use ofpassive diffusion sampling methods for sampling, Air monitoring point arrangement ofthe data grid monitoring selection of cluster analysis, We use CALPUFF model to verifythe results of the analysis and the optimize air quality monitoring sites. Mainly thefollowing results are obtained:1. Using clustering analysis method to analyze passive diffusion experiment ofChongqing urban area, we make the59monitoring points of passive diffusionexperiment into12categories. Compared with average concentration of SO₂and NO₂of the optimum monitoring points for city representative point andeach type of all points in the city, it result that relative deviations are2.4%and2.4%.this accord with The ambient air quality monitoring standard （tryout）"（<10%）.it account for that The concentration level optimization level canrepresent the level of the whole city. the correlation coefficient （R2） of SO₂and NO₂of the optimum point for city representative point and each type ofall points in the city respectively are0.987and0.9361. Results showed thatthe optimum threshold concentration with the group’s average concentrationdeviation in the acceptable range, and the optimum points are representative. 2. Through the input of Chongqing urban area of geographic data, meteorologicaldata and sources of data, using center of each network and passive diffusionexperiment point as CALPUFF receptor levels of the model, we useCALPUFF simulation model of air quality to test and verify the optimummonitoring points. The results show that the correlation of SO₂and NO₂simulation and monitoring values respectively are0.773and0.667. Therefore,it is feasible that CALPUFF simulation model of air quality to test theoptimum monitoring points.3. According to the location of Chongqing urban area, we screened out mainsimulation network in the simulation area, including259km2x2kmsimulation cell. According to the distribution of geographical space group, wesubdivided into three regions （I, II and III）. The average concentration of SO₂and NO₂from CALPUFF test and verify the optimum monitoring points. Theresults show that the optimum monitoring points is representative. Theaverage relative deviation of SO₂and NO₂respectively are-3.1%and0.8%.Due to large area SO₂spatial heterogeneity, so the average relative deviationof SO₂is larger. Similarly, according to the regional continuity in divided intothree section, Statistical analysis was carried out on that therepresentativeness of the monitoring points （I>II>III）. This is due to thenumber of monitoring points is the most large in I. Overall, the monitoringpoints in each area are able to better reflect the average.