基于多尺度的中国环境污染事件时空分布及其影响因素

doi:10.13249/j.cnki.sgs.2019.09.001

摘要/Abstract

摘要：

环境污染事件已成为人类社会发展面临的严峻挑战,严重制约着人类社会的可持续发展,当前急需厘清环境污染事件的时空特征及影响因素,为制定有效的环保政策提供借鉴。利用Theil指数、变异系数、ESDA等方法,分析了2006~2016年中国环境污染事件的时空分布特征,并借助地理探测器识别了不同尺度环境污染事件的影响因素。结果表明：① 2006~2016年省级尺度环境污染事件发生总频次与不同等级环境污染事件发生频次均呈波动下降趋势,其发生频次和区域差异呈“东-中-西”洼地型格局;② 地级市尺度环境污染事件发生频次随城市规模减小有所降低,随经济发展水平降低呈倒U型,同时,环保重点城市污染事件发生频次高于普通城市的特征;而环境污染事件的差异性表现为随城市规模减小有所降低,随经济发展水平降低而递减,及环保重点城市高于普通城市的特征。③ “胡焕庸线”以东地区环境污染事件多发且类型多样,以西地区污染事件少发且类型单一,不同等级环境污染事件的空间分布差异较大;④ 环境污染事件的影响因素存在差异,且随尺度增大,影响因素与环境污染事件的关联性趋于增强。其中,经济发展和环境监管水平对不同尺度环境污染事件均有显著影响,环境监管水平与其他因素的交互作用对不同尺度环境污染事件的解释力较高。

关键词: 环境污染事件, 区域差异, 地理探测器, 中国

Abstract:

Environmental pollution incidents have become a major challenge for human social development, seriously restrict the sustainable development. Therefore, it is urgently necessary to clarify the temporal and spatial characteristics of pollution incidents and its influencing factors, in order to provide references for the formulation of effective environmental protection policies. In this paper, used the Theil index, coefficient of variation, ESDA and other methods to analyze the spatial distribution characteristics of pollution incidents from 2006 to 2016 in China, and the GeoDetector to identify the influencing factors at different scales. The results showed that: 1) At the provincial scales, the occurrence frequencies of environmental pollution incidents and the occurrence of environmental pollution incidents at different levels both showed fluctuating downward trends, and their frequency and regional differences all showed 'East-Central-West' low-lying land patterns. 2)At the prefecture-level cities scale, the frequency of environmental pollution incidents is reduced as the decreases of city scale, and the U-shaped change occurs with the decrease of economic development level, the frequency of pollution incidents in key environmental protection cities is higher than ordinary cities, difference of environmental pollution incidents is reduced as the decreases of city scale and economic development level, and the environmental protection key cities are higher than ordinary cities. 3) The environmental pollution incidents in east of the 'Hu Line' are frequent and diverse, and the western pollution incidents are rare and single, and the spatial distribution of different levels of environmental pollution incidents were quite different. 4) There existed differences in impacting factors at different scales, and as the scale increased, the correlation between impacting factors and environmental pollution incidents also increased. Among them, the level of economic development and the level of environmental supervision all had vital impacts on environmental pollution incidents. The interaction between environmental supervision and other factors had the significant impacts to the environmental pollution incidents.

Key words: environmental pollution incidents, regional differences, GeoDector, China

中图分类号:

X507

赵雪雁, 王蓉, 王晓琪, 刘江华. 基于多尺度的中国环境污染事件时空分布及其影响因素[J]. 地理科学, 2019, 39(9): 1361-1370.

Zhao Xueyan, Wang Rong, Wang Xiaoqi, Liu Jianghua. Spatio-temporal Distribution and Influencing Factors of Environmental Pollution Incidents Based on Multi-scales in China[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(9): 1361-1370.

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差异性	城市规模				城市经济发展水平				环保城市和普通城市
差异性	特大城市	大城市	中等城市	小城市	发达城市	较发达城市	欠发达城市	不发达城市	环保重点城市	普通城市
污染事件比重（%）	29.71	25.88	19.41	25.00	28.82	30.29	32.35	8.53	56.76	43.24
变异系数	3.44	1.69	1.08	1.56	2.72	2.28	1.35	1.18	2.64	1.25
Theil指数	0.50	0.26	0.13	0.27	0.42	0.38	0.27	0.08	0.82	0.34

探测指标	省级			地级市
探测指标	2006年	2011年	2016年	2016年
年末人口数（x₁）	0.59^***	0.35	0.32	0.09^**
GDP（x₂）	0.38^*	0.46^**	0.55^**	0.13^***
城镇化率（x₃）	0.20	0.28	0.17	0.06
工业增加值占GDP比重（x₄）	0.40^*	0.11	0.41	0.02
工业企业数（x₅）	0.50^**	0.23	0.28	0.06
环保人员数（x₆）	0.40^*	0.60^***	0.46^*	0.08^*
环保机构数（x₇）	0.35	0.32	0.37	0.09^**
环境污染治理投资占GDP比重（x₈）	0.21	0.38^**	0.07	0.02

2006年		2011年		2016年
交互因子	作用值	交互因子	作用值	交互因子	作用值
x₁∩x₂	0.86	x₁∩x₃	0.90	x₁∩x₂	0.83
x₂∩x₃	0.73	x₂∩x₃	0.87	x₂∩x₃	0.89
x₁∩x₄	0.86	x₃∩x₄	0.89	x₃∩x₅	0.62
x₂∩x₄	0.80	x₃∩x₅	0.80	x₄∩x₂	0.93
x₃∩x₄	0.83	x₆∩x₂	0.86	x₄∩x₃	0.85
x₃∩x₅	0.90	x₆∩x₃	0.86	x₅∩x₁	0.84
x₆∩x₄	0.88	x₆∩x₄	0.87	x₅∩x₂	0.94
x₆∩x₅	0.88	x₆∩x₇	0.84	x₆∩x₄	0.80
x₇∩x₁	0.89	x₇∩x₈	0.83	x₇∩x₄	0.87
x₇∩x₂	0.98	x₈∩x₂	0.86	x₇∩x₅	0.85
x₇∩x₃	0.85	x₈∩x₃	0.85	x₈∩x₄	0.89
x₇∩x₄	0.88	x₈∩x₅	0.83	x₈∩x₅	0.91
x₈∩x₆	0.76	x₈∩x₆	0.94	x₈∩x₆	0.89

	x₁	x₂	x₃	x₄	x₅	x₆	x₇
x₂	0.26
x₃	0.33	0.31
x₄	0.26	0.30	0.33
x₅	0.26	0.24	0.23	0.28
x₆	0.16	0.29	0.36	0.24	0.23
x₇	0.17	0.29	0.31	0.30	0.25	0.23
x₈	0.28	0.31	0.26	0.20	0.30	0.29	0.36