摘要
随着社会经济的发展,固废快速增长,且具有时空多变特性,导致固废管控面临挑战。借助空间统计学方法挖掘分析我国一般工业固废的空间格局及其影响因素。首先,采用GIS可视化制图技术分析固废的空间分布格局及其变化特征。然后,利用莫兰指数分析固废的空间相关性与聚集模式,以及其随时间的变化情况。最后,运用地理探测器分析5个社会经济统计指标对固废空间格局的影响。结果表明:近20 a来,我国一般工业固废的产生量呈现增长态势,且在空间上呈现出东北-西南高、东南-西北低的分布格局,区域间差异逐渐增大,地理重心逐渐向西北方向移动,有明显的正向空间自相关性;社会经济指标对固废空间格局的影响度由高到低依次为能源消费总量、人均GDP、人均工业产值、人口数量和规模以上工业企业数量。研究结果可为固废的减量化、资源化、无害化管理提供辅助决策参考。
With the development of the social economy,solid wastes are increasing rapidly and they change mostly in the spatial and temporal distribution pattern,leading to challenges in solid wastes management and control.The purpose of this study is to excavate and analyze the spatial pattern of the ordinary industrial solid waste(OISW)in China and its influencing factors through spatial statistics,to provide support for the information management of OISW in China.First of all,the statistical data of solid waste in China in 1997,2007,and 2017 were selected as experimental data,and GIS visualization mapping technology was used to analyze the spatial pattern of OISW and its change characteristics.Then,the spatial autocorrelation and aggregation mode of OISW were analyzed by using Moran’s I index.Finally,the geographical detector was used to detect the impact of five socio-economic statistical indexes on the spatial pattern of solid waste.The experimental results show that the production of OISW has increased in China in the past 20 years and it presents a spatial distribution pattern of high density in northeast and southwest,low density in southeast and northwest.Regional differences of OISW gradually increase and the geographic mean centers of OISW move to the northwest.Besides,there is positive obvious spatial autocorrelation among solid wastes.The spatial clustering pattern of OISW is manifested as a high-high cluster,which is mainly distributed in North China and Northeast China,especially in Liaoning,Inner Mongolia,Hebei,Shanxi,Henan,and Shandong provinces.The social and economic indexes of the influence degree on the spatial pattern of solid wastes from high to low are as follows:the total energy consumption,the per capita GDP,the per capita industrial output value,the population,and the number of industrial enterprises above designated size.The research results can provide an auxiliary decision-making reference for the reduction,recycling,and harmless management of solid waste.
作者
黄泽纯
张惠茴
HUANG Ze-chun;ZHANG Hui-hui(Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University,Chengdu 611756,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2022年第2期980-987,共8页
Journal of Safety and Environment
基金
国家重点研发计划项目(2019YFC1905600)。
关键词
环境工程学
一般工业固体废物
莫兰指数
地理探测器
影响因素
空间格局
environmental engineering
ordinary industrial solid waste
Moran index
geographical detector
influencing factors
spatial pattern
