摘要
通过采用GIS空间分析方法,以第二次全国污染源普查(简称“二污普”) SO2、NOX、COD、NH3-N的排放总量和排放强度为测度指标,对云南省县域尺度的污染物排放量及排放强度地理聚集特征进行分析。结果表明,(1) SO2、NOX排放总量和强度空间差异明显, COD、NH3-N排放总量和强度区域差异不明显。(2) 按Moran指数分析,云南省污染物排放的空间相关性显著,各类污染物的排放总量空间集聚显著性特征SO2 】COD 】NH3-N 】NOX,排放强度的聚集显著性特征为SO2 】NOX 】COD 】NH3-N。(3) SO2、NOX排放总量的热点区与冷点区的分布区域与排放量强度的分布规律总体一致,但昆明、玉溪、红河大部分区域由排放量的热点区变为排放强度的冷点区;COD、NH3-N排放总量和强度形成了多个热点片区,排放总量和排放强度空间分布格局出现明显倒置,昆明、曲靖、玉溪、红河绝大多数热点区域变为了冷点区,普洱、临沧、德宏由冷点区变为热点区。(4) 四类污染物排放总量和强度均主要呈低–低聚集状态,高–高状态的区域污染物排放的绝对差异大,同时存在一定比例的低–高,高–低区域。
By using the method of GIS spatial analysis, taking the total pollution amount and pollution inten-sity of SO2, NOX, COD and NH3-N in the Second China Pollution Source Census (The Second CPSC) as the measurement index, the geographical aggregation characteristics of the pollutant emissions and emission intensity at the county level in Yunnan Province were analyzed. The results show that: (1) The spatial difference of total amount and intensity of SO2 and NOX emission from waste gas is obvious, while the regional difference of total amount and intensity of COD and NH3-N emission from waste water is not obvious. (2) According to the Moran index analysis results, the spatial correlation of pollutant emission in Yunnan province is significant, the spatial aggregation significance of the total emission of various pollutants is SO2 >COD >NH3-N >NOX, and the aggregation significance characteristic of the emission intensity is SO2 >NOX >COD >NH3-N. (3) The hot-spot and cold-spot areas of the total emission of SO2 and NOX are generally consistent with the distribution of emission intensity, but most areas of Kunming, Yuxi and Honghe are changed from hot-spot areas to cold-spot areas. The total amount and intensity of wastewater COD and NH3-N emissions have formed multiple hot-spot areas, and the spatial distribution pattern of total discharge and intensity has obviously inverted, and most of the hot-spot areas in Kunming, Qujing, Yuxi, and Honghe have become cold-spot areas. Pu’er, Lincang and Dehong changed from cold-spots to hot-spots. (4) The total amount and intensity of the four types of pollutants are mainly in the low-low aggregation state, and the high-high state areas have great absolute differences in pollutant emissions, and there is a cer-tain proportion of low-high, high-low areas.
出处
《低碳经济》
2020年第3期159-168,共10页
Journal of Low Carbon Economy
关键词
第二次全国污染源普查
空间聚集
空间自相关性
热点分析
The Second China Pollution Source Census
Spatial Aggregation
Spatial Autocorrelation
Hot Spot Analysis
