摘要
目前,中国大气污染问题愈发严峻,由大气污染所导致的公共健康风险及经济损失日益突出,探询污染的形成原因、影响因素是制定治理政策的重要依据。本文针对大气污染的主要污染物PM10进行研究,特别探讨中国31个省市自治区本地与异地之间PM10交互影响的问题及产业结构影响。首先,分析全局空间相关性,发现地区间PM10存在着空间自相关,且逐年增强;其次分析局域相关性,发现中国北方部分地区出现高-高类型的集聚,主要集中于北京、天津、河北、山西、山东、河南、黑龙江、吉林和辽宁等9个省份;南方部分地区出现低-低类型的集聚,主要集中于广东、海南、广西、贵州以及云南等5个省份。虽出现个别年份的波动,但从长期看,各集聚区均处于较稳定状态;第三,建立空间计量模型对PM10进行比较全面的模型数据分析,包括经济社会、经济结构以及气候等因素对PM10的影响,以较为新颖的视角刻画PM10的形成,发现地区间PM10的交互影响存在着"负效应",分析表明这种"负效应"具有短期性,而且"负效应"与"溢出效应"可能存在联系。此外,重点分析工业中对PM10贡献较大的典型行业,以及以典型行业为代表的工业结构对我国东、中、西部地区PM10的影响特点,与劣质煤进口量逐年增大的事实相结合,阐述了降低PM10的困难所在。最后,基于实证分析结果论证影响不同地区PM10的主导因素,空间因素对PM10的影响,长期看在部分地区通过产业转移的方式降低PM10的不可行性;论证中,以北京地区为主要分析案例,发现交通拥堵程度以及空间因素是其出现高雾霾的重要原因。根治雾霾,区域间的联合治理势在必行。
Air pollution in China has become more and more serious, which has brought about public health risk increasingly and a huge economic loss. Consequently, it is of great importance to look into the reasons for pollution and its influencing factors, which could be served as basis for policy-making. This article is to study the regional spatial effect of PM10, a main pollutant, especially the interaction between local PMl0 concentration values and that of its adjacent provinces and the impact of industrial structure. The author conducted spatial autocorrelation analysis at national level as well as provincial level. The result showed that, firstly, at national level, PM10 concentration values of different provinces were correlated, and this relation strengthens every year. Secondly, at provincial level, PMI0 concentration values of in northern China, including Beijing, Tianjin, Hebei, Shanxi, Shandong, Henan, Heilongjiang, Jilin and Liaoning are ＇high-high＇ related. On the contrary, those in southern China, including Guangdong, Guangxi, Hainan, Guizhou and Yunnan, are ＇low-low＇ related. Thirdly, a spatial regression model was established according to economic, social and natural influencing factors of PMI0 etc. Analysis of the model revealed a ＇negative effects＇ , between local PMI0 concentration values and that of its adjacent provinces and its short-term nature, and there might be linkage between ＇ spillover effects＇ and ＇ negative effects＇. In addition, influence of industrial structure on PM10 concentration values in east, central and west regions of China was given special attention. Together with the fact of increasing inferior coal import, the author looked into the difficulty of controlling PM10 concentration values. In conclusion, the author pointed out that industrial transfer is impractical in some areas to reduce PM10 concentration values in the long term. And Beijing was taken as a typical case, which was found that traffic congestion and spatial factors may be the main reasons for it
出处
《中国人口·资源与环境》
CSSCI
北大核心
2014年第7期157-164,共8页
China Population,Resources and Environment
基金
国家社会科学基金项目"跨区域碳减排的技术经济优化路径及政策研究"(编号:13CJY009)
中国社会科学院数量经济与技术经济研究所重点课题"跨区域碳减排的技术经济优化路径及政策研究"
关键词
PM10
空间效应
空间计量模型
工业结构
产业转移
PM10
spatial effects
spatial econometrics model
industrial structure
industry transfer
