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珠三角区域PM2.5时空变异特征
引用本文:徐伟嘉,何芳芳,李红霞,钟流举.珠三角区域PM2.5时空变异特征[J].环境科学研究,2014,27(9):951-957.
作者姓名:徐伟嘉  何芳芳  李红霞  钟流举
作者单位:1.中山大学先进技术研究院, 广东 广州 510275 ;东莞中山大学研究院, 广东 东莞 523808
基金项目:广东省自然科学基金项目(S2013040016343);佛山市科技发展专项资金项目(2012AA100741)
摘    要:珠三角区域PM2.5污染严重,以 2012年9月─2013年8月62个大气监测站的PM2.5联网数据为基础,采用地统计学方法定性、定量分析了该区域ρ(PM2.5)的时空变异特征. 定性分析结果表明,基底效应在0.12~0.30之间,相应ρ(PM2.5)变异属于以结构性变异为主的Ⅰ、Ⅱ类,对应的空间自相关程度为强、较强,说明珠三角区域的ρ(PM2.5)分布差异主要由区域结构所致. 定量分析结果表明:①空间自相关距离受气象因素影响,随方向和时间在51~85 km之间变化,东西方向的影响距离(75~85 km)最大. ②ρ(PM2.5)在南北方向的变异幅度指数(0.34~0.70)和变异速度指数〔0.14~0.38 μg/(m3·km)〕在各方向中均为最大;而东北─西南方向的2个指标则均为最小,其中变异幅度指数为0.25~0.42,变异速度指数在0.13~0.34 μg/(m3·km)之间,即南北方向的ρ(PM2.5)变化大于其他方向.③综合异质指数介于0.14~0.54之间,说明ρ(PM2.5)总体保持在中等异质水平. 鉴于珠三角区域ρ(PM2.5)的空间变异特征,在进行监测站布设时,矩形网格相较于方形网格更适合于对该区域地理空间进行划分,其中网格的长为东西方向平均空间自相关距离(78 km)的2倍,宽为南北方向平均空间自相关距离(56 km)的2倍. 

关 键 词:PM2.5    时空变异    变差函数    地统计学    异质性
收稿时间:2013/11/26 0:00:00
修稿时间:2014/5/29 0:00:00

Spatial and Temporal Variations of PM2.5 in the Pearl River Delta
XU Wei-ji,HE Fang-fang,LI Hong-xia and ZHONG Liu-ju.Spatial and Temporal Variations of PM2.5 in the Pearl River Delta[J].Research of Environmental Sciences,2014,27(9):951-957.
Authors:XU Wei-ji  HE Fang-fang  LI Hong-xia and ZHONG Liu-ju
Institution:1.Institute of Advanced Technology, Sun Yat-sen University, Guangzhou 510275, China ;Institute of Dongguan, Sun Yat-sen University, Dongguan 523808, China2.Guangdong Environmental Monitoring Center, Guangzhou 510045, China
Abstract:Fine particulate matter pollution (PM2.5) in the Pearl River Delta is seriously threatening the ecological safety. In order to determine the temporal and spatial variations of the pollution, the geostatistic method was used to analyze concentration data collected from 62 monitoring sites from September 2012 to August 2013. Qualitative analysis showed that:the base effect values ranged from 0.12-0.30; there was a less strong or strong spatial auto-correlation in the region; and, the variation of ρ(PM2.5) was caused by regional structural factors complemented by random factors. Quantitative analysis showed that that the auto-correlation distance ranged from 51 to 85 kilometers along with direction and time influenced by meteorological conditions. The auto-correlation distance in the east-west direction ranged from 75 to 85 kilometers and was wilder than the others. The variation range and speed of ρ(PM2.5) reached maximums (0.34-0.70,0.14-0.38 μg/(m3·km)) in the north-south direction, while the minimums (0.25-0.42,0.13-0.34 μg/(m3·km)) appeared from the northeast to the southwest direction. This indicated that the variation in the north to the south direction was bigger than in other directions. The comprehensive heterogeneity index based on the combination of auto-correlation distance, variation and speed ranges changed from 0.14 to 0.54 with time, but remained at a middle level. Based on the different heterogeneity of each direction of PM2.5 in the Pearl River Delta, a rectangular regional division grid would work better than a square grid for monitoring site arrangement. The length and width of the grid may be twice the auto-correlation distance of the east to the west (78 kilometers) and the south to the north (56 kilometers) directions. 
Keywords:PM2  5  temporal and spatial variation  variogram geostatistics  heterogeneity
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