基于时空分布特征的霾与区域经济关联性分析
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摘要
霾与经济相关性研究较多,这些研究假定霾处于污染状态作为不变的量。事实上霾是可以流动的,时刻处于动态变化中。对霾的时空格局变化过程进行动态分析,更有利于界定霾与区域经济的相关性。根据霾日数时空格局分布将所研究区域划分为四类,分别为:Ⅰ类长期性霾污染状态、Ⅱ类间歇性霾污染状态、Ⅲ类新出现霾污染状态和Ⅳ类无霾状态。分别针对这四类区域的霾次数、霾日数和GDP进一步进行对比分析和相关性分析。结果显示经济发展是霾污染的因素之一,但不是唯一因素,因此不同区域要采取不同的治霾措施。明确各区域霾污染产生的各种影响因素,采用多种手段,从多个方向入手,实现精准治霾。
There are many studies on the correlation between haze and economy. The studies assume that haze is a constant quantity. In fact, haze can flow and keep in a dynamic change. The change of haze is analyzed dynamically. Four typical states have been gotten by the characteristics of temporal and spatial distribution. Ⅰis long-term haze state. Ⅱ is intermittent haze pollution state. Ⅲ is haze appeared from a certain year. Ⅳ is no haze state. Different regions have different states. In every region, the relation of time number, day number and GDP were analyzed by comparison and correlation. The results show the change trend of haze and GDP is not the similarity and the relevance of the haze and GDP is different among four types. The advice is different areas should adopt different measures to reduce haze.
There are many studies on the correlation between haze and economy. The studies assume that haze is a constant quantity. In fact, haze can flow and keep in a dynamic change. The change of haze is analyzed dynamically. Four typical states have been gotten by the characteristics of temporal and spatial distribution. Ⅰis long-term haze state. Ⅱ is intermittent haze pollution state. Ⅲ is haze appeared from a certain year. Ⅳ is no haze state. Different regions have different states. In every region, the relation of time number, day number and GDP were analyzed by comparison and correlation. The results show the change trend of haze and GDP is not the similarity and the relevance of the haze and GDP is different among four types. The advice is different areas should adopt different measures to reduce haze.
引文
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[9] 石庆玲,郭峰,陈涛一.雾露治理中的“政治性蓝天”——来自中国地方“两会”的证据[J].中国工业经济,2016.5:40-56.
[10] 吴春燕,王雪峰.叶面滞尘量对大叶黄杨反射光谱的影响[J].林业科学,2015,51(3):49-56.
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[12] 王桂芝,顾赛菊,陈纪波.基于投入产出模型的北京市霾间接经济损失评估[J].环境工程,2016,34(1):121-125.
[13] 姜绵峰, 叶春明, 盛真真,等. 上海市雾霾健康经济损失风险评估[J]. 生态科学, 2017, 36(3):90-97.
[2] Goldberg M S, Burnett R T, Brook J R, et al. Identifying subgroups of the general population that may be susceptible to short-term increases in particulate air pollution: a time-series study in Montreal, Quebec[J]. Research Report, 2000, 97(97):7.
[3] 王勇,郝振航,任栋,等.中国大陆地区GNSS对流层延迟与PM2.5浓度的相关性研究[J].灾害学,2017,32(4):6-10.
[4] Yan R, Yu S, Zhang Q, et al. A heavy haze episode in Beijing in February of 2014: Characteristics, origins and implications[J]. Atmospheric Pollution Research, 2015, 6(5):867-876.
[5] 郭俊华, 刘奕玮. 我国城市雾霾天气治理的产业结构调整[J]. 西北大学学报(哲学社会科学版), 2014, 44(2):85-89.
[6] 茹少峰,雷振宇.我国城市雾霾天气治理中的经济发展方式转变[J].西北大学学报(哲学社会科学版),2014,44(2):90-93.
[7] 吴振磊,朱楠.我国雾霾天气治理的城市化方式的转变[J].西北大学学报(哲学社会科学版), 2014,44(2):98-102.
[8] 马国顺, 赵倩. 雾霾现象产生及治理的演化博弈分析[J]. 生态经济, 2014, 30(8):169-172.
[9] 石庆玲,郭峰,陈涛一.雾露治理中的“政治性蓝天”——来自中国地方“两会”的证据[J].中国工业经济,2016.5:40-56.
[10] 吴春燕,王雪峰.叶面滞尘量对大叶黄杨反射光谱的影响[J].林业科学,2015,51(3):49-56.
[11] 刘星河.公共压力、产权性质与企业融资行为——基于“PM2.5爆表”事件的研究[J].经济科学,2016(02):67-80.
[12] 王桂芝,顾赛菊,陈纪波.基于投入产出模型的北京市霾间接经济损失评估[J].环境工程,2016,34(1):121-125.
[13] 姜绵峰, 叶春明, 盛真真,等. 上海市雾霾健康经济损失风险评估[J]. 生态科学, 2017, 36(3):90-97.