中国城市群空气质量时空演化及收敛趋势

doi:10.13249/j.cnki.sgs.2022.11.009

Abstract

Abstract:

Based on the real-time monitoring data of China’s urban air quality from 2015 to 2020, the paper quantitatively analyzed the air quality differences in urban agglomerations and their sources and convergence mechanisms, using methods such as Dagum Gini coefficient, coefficient of variation and convergence model. The results show that: 1) Since 2015, the air quality of China’s 20 urban agglomerations has not shown an ideal trend of improvement year by year, but the air quality of most urban agglomerations tends to improve in the process of fluctuation, and O₃ has begun to replace PM_2.5 as the most important primary pollutant in part of urban agglomerations. 2) The spatial differentiation characteristics of air quality in China’s urban agglomerations are obvious, but the spatial differences have been reduced during the study period, and the differences between urban agglomerations are much larger than those within urban agglomeration. 3) The air quality of China’s urban agglomerations not only has a trend of σ convergence, but also a trend of absolute and conditional β convergence. Whether or not other heterogeneous influencing factors other than the initial air quality are considered, the urban air quality within each urban agglomeration is moving towards steady-state level.

Key words: air quality, convergence trend, spatial Durbin model, urban agglomeration

CLC Number:

Wan Qing, Luo Xiang, Pan Fangjie, Jin Gui. Spatial-temporal Evolution and Convergence Trend of Air Quality in China’s Urban Agglomerations[J].SCIENTIA GEOGRAPHICA SINICA, 2022, 42(11): 1943-1953.

Figures/Tables 7

Table 1

Fig. 1

Table 2

Fig. 2

Table 3

Table 4

Table 5

References 37

[1]	许昕, 赵媛, 张新林, 等. 中国县域高龄人口地域分异特征及环境成因[J]. 地理科学, 2018, 38(9): 1449-1457
	Xu Xin, Zhao Yuan, Zhang Xinlin et al. Regional differentiation characteristics and environmental causes of elderly population in China based on county scale. Scientia Geographica Sinica, 2018, 38(9): 1449-1457
[2]	孙鸿鹄, 甄峰. 居民活动视角的城市雾霾灾害韧性评估——以南京市主城区为例[J]. 地理科学, 2019, 39(5): 788-796
	Sun Honghu, Zhen Feng. Evaluation of urban haze disaster resilience from the perspective of residents’ activity: A case study of the main urban area of Nanjing City. Scientia Geographica Sinica, 2019, 39(5): 788-796
[3]	顾康康, 朱鹏祥, 宁杨, 等. 基于绿色出行理念的合肥市区空气污染分区调控研究[J]. 地理科学, 2019, 39(8): 1312-1320 doi: 10.13249/j.cnki.sgs.2019.08.013
	Gu Kangkang, Zhu Pengxiang, Ning Yang et al. Zoning and regulation of air pollution in Hefei City based on the concept of green travel. Scientia Geographica Sinica, 2019, 39(8): 1312-1320 doi: 10.13249/j.cnki.sgs.2019.08.013
[4]	王振波, 方创琳, 许光, 等. 2014年中国城市PM_2.5浓度的时空变化规律 [J]. 地理学报, 2015, 70(11): 1720-1734 doi: 10.11821/dlxb201511003
	Wang Zhenbo, Fang Chuanglin, Xu Guang et al. Spatial-temporal characteristics of the PM_2.5 in China in 2014. Acta Geographica Sinica, 2015, 70(11): 1720-1734 doi: 10.11821/dlxb201511003
[5]	韩立建. 城市化与PM_2.5时空格局演变及其影响因素的研究进展 [J]. 地理科学进展, 2018, 37(8): 1011-1021 doi: 10.18306/dlkxjz.2018.08.001
	Han Lijian. Relationship between urbanization and urban air quality: An insight on fine particulate dynamics in China. Progress in Geography, 2018, 37(8): 1011-1021 doi: 10.18306/dlkxjz.2018.08.001
[6]	曹广忠, 刘嘉杰, 刘涛. 空气质量对中国人口迁移的影响[J]. 地理研究, 2021, 40(1): 199-212 doi: 10.11821/dlyj020190892
	Cao Guangzhong, Liu Jiajie, Liu Tao. Examining the role of air quality in shaping the landscape of China’s internal migration: Phase characteristics, push and pull effects. Geographical Research, 2021, 40(1): 199-212 doi: 10.11821/dlyj020190892
[7]	程钰, 徐成龙, 刘雷, 等. 1991—2011年山东省工业经济增长的大气污染效应及其时空格局——以SO₂和粉尘为例 [J]. 地理科学进展, 2013, 32(11): 1703-1711 doi: 10.11820/dlkxjz.2013.11.013
	Cheng Yu, Xu Chenglong, Liu Lei et al. Effect of industrial growth on atmospheric pollution and its spatio-temporal pattern in Shandong Province during 1991-2011: Taking SO₂ and dust emissions as example. Progress in Geography, 2013, 32(11): 1703-1711 doi: 10.11820/dlkxjz.2013.11.013
[8]	滕堂伟, 谌丹华, 胡森林. 黄河流域空气污染的空间格局演化及影响因素[J]. 地理科学, 2021, 41(10): 1852-1861
	Teng Tangwei, Chen Danhua, Hu Senlin. Spatial evolution and influencing factors of spatial agglomeration pattern of air pollution in the Yellow River Basin. Scientia Geographica Sinica, 2021, 41(10): 1852-1861
[9]	李名升, 张建辉, 张殷俊, 等. 近10年中国大气PM₁₀污染时空格局演变 [J]. 地理学报, 2013, 68(11): 1504-1512 doi: 10.11821/dlxb201311006
	Li Mingsheng, Zhang Jianhui, Zhang Yinjun et al. Spatio-temporal pattern changes of ambient air PM₁₀ pollution in China from 2002 to 2012 . Acta Geographica Sinica, 2013, 68(11): 1504-1512 doi: 10.11821/dlxb201311006
[10]	王振波, 梁龙武, 王旭静. 中国城市群地区PM_2.5时空演变格局及其影响因素 [J]. 地理学报, 2019, 74(12): 2614-2630 doi: 10.11821/dlxb201912014
	Wang Zhenbo, Liang Longwu, Wang Xujing. Spatio-temporal evolution patterns and influencing factors of PM_2.5 in Chinese urban agglomerations . Acta Geographica Sinica, 2019, 74(12): 2614-2630 doi: 10.11821/dlxb201912014
[11]	Shen Y, Zhang L, Fang X et al. Spatiotemporal patterns of recent PM_2.5 concentrations over typical urban agglomerations in China [J]. Science of the Total Environment, 2019, 655: 13-26 doi: 10.1016/j.scitotenv.2018.11.105
[12]	Huang C, Liu K, Zhou L. Spatio-temporal trends and influencing factors of PM_2.5 concentrations in urban agglomerations in China between 2000 and 2016 [J]. Environmental Science and Pollution Research, 2021, 28(9): 10988-11000 doi: 10.1007/s11356-020-11357-z
[13]	刘晟东, 史君楠, 程勇, 等. 中国典型城市群PM_2.5污染特征研究进展 [J]. 环境科学研究, 2020, 33(2): 243-251
	Liu Shengdong, Shi Junnan, Cheng Yong et al. Review of pollution characteristics of PM_2.5 in Chinese representative megacities . Research of Environmental Sciences, 2020, 33(2): 243-251
[14]	Liu X, Zou B, Feng H et al. Anthropogenic factors of PM_2.5 distributions in China’s major urban agglomerations: A spatial-temporal analysis [J]. Journal of Cleaner Production, 2020, 264: 121709 doi: 10.1016/j.jclepro.2020.121709
[15]	Yan D, Kong Y, Ye B et al. Spatio-temporal variation and daily prediction of PM_2.5 concentration in world-class urban agglomerations of China [J]. Environmental Geochemistry and Health, 2021, 43: 301-316 doi: 10.1007/s10653-020-00708-x
[16]	王兴杰, 谢高地, 岳书平. 经济增长和人口集聚对城市环境空气质量的影响及区域分异——以第一阶段实施新空气质量标准的74个城市为例[J]. 经济地理, 2015, 35(2): 71-76
	Wang Xingjie, Xie Gaodi, Yue Shuping. Impact of economic growth and population aggregation on urban environmental quality and its regional differentiation: A case study of 74 cities implemented the new standard for air quality during the first stage. Economic Geography, 2015, 35(2): 71-76
[17]	刘满凤, 谢晗进. 基于空气质量指数AQI的污染集聚空间异质性分析[J]. 经济地理, 2016, 36(8): 166-175 doi: 10.15957/j.cnki.jjdl.2016.08.024
	Liu Manfeng, Xie Hanjin. The spatial heterogeneity analysis of pollution agglomeration based on the AQI air quality index. Economic Geography, 2016, 36(8): 166-175 doi: 10.15957/j.cnki.jjdl.2016.08.024
[18]	张向敏, 罗燊, 李星明, 等. 中国空气质量时空变化特征[J]. 地理科学, 2020, 40(2): 190-199 doi: 10.13249/j.cnki.sgs.2020.02.004
	Zhang Xiangmin, Luo Shen, Li Xingming et al. Spatio-temporal variation features of air quality in China. Scientia Geographica Sinica, 2020, 40(2): 190-199 doi: 10.13249/j.cnki.sgs.2020.02.004
[19]	Xu L J, Zhou J X, Guo Y et al. Spatiotemporal pattern of air quality index and its associated factors in 31 Chinese provincial capital cities[J]. Air Quality, Atmosphere & Health, 2017, 10(5): 601-609
[20]	Pu H, Luo K, Wang P et al. Spatial variation of air quality index and urban driving factors linkages: Evidence from Chinese cities[J]. Environmental Science and Pollution Research, 2017, 24(5): 4457-4468 doi: 10.1007/s11356-016-8181-0
[21]	姜磊, 周海峰, 柏玲. 外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数(AQI)为例[J]. 地理科学, 2018, 38(3): 351-360
	Jiang Lei, Zhou Haifeng, Bai Ling. Spatial heterogeneity analysis of impacts of foreign direct investment on air pollution: Empirical evidence from 150 cities in China based on AQI. Scientia Geographica Sinica, 2018, 38(3): 351-360
[22]	Ye W, Ma Z, Ha X et al. Spatiotemporal patterns and spatial clustering characteristics of air quality in China: A city level analysis[J]. Ecological Indicators, 2018, 91: 523-530 doi: 10.1016/j.ecolind.2018.04.007
[23]	Wang J, Qu W, Li C et al. Spatial distribution of wintertime air pollution in major cities over eastern China: Relationship with the evolution of trough, ridge and synoptic system over East Asia[J]. Atmospheric Research, 2018, 212: 186-201 doi: 10.1016/j.atmosres.2018.05.013
[24]	Han X, Fang W, Li H et al. Heterogeneity of influential factors across the entire air quality spectrum in Chinese cities: A spatial quantile regression analysis[J]. Environmental Pollution, 2020, 262: 114259 doi: 10.1016/j.envpol.2020.114259
[25]	肖嘉玉, 何超, 慕航, 等. 中国城市空气污染时空分布格局和人口暴露风险[J]. 地理科学进展, 2021, 40(10): 1650-1663 doi: 10.18306/dlkxjz.2021.10.004
	Xiao Jiayu, He Chao, Mu Hang et al. Spatiotemporal pattern and population exposure risks of air pollution in Chinese urban areas. Progress in Geography, 2021, 40(10): 1650-1663 doi: 10.18306/dlkxjz.2021.10.004
[26]	何振芳, 郭庆春, 刘加珍, 等. 河北省大气污染时空变化特征及其影响因素[J]. 自然资源学报, 2021, 36(2): 411-419 doi: 10.31497/zrzyxb.20210211
	He Zhenfang, Guo Qingchun, Liu Jiazhen et al. Spatio-temporal variation characteristics of air pollution and influencing factors in Hebei Province. Journal of Natural Resources, 2021, 36(2): 411-419 doi: 10.31497/zrzyxb.20210211
[27]	Zhang X, Gong Z. Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants[J]. Journal of Geographical Sciences, 2018, 28(5): 563-578 doi: 10.1007/s11442-018-1491-z
[28]	杜国祥. 基于AQI指数的城市空气质量变化趋势及空间差异——以京津冀城市群为代表[J]. 城市发展研究, 2017, 24(8): 49-56
	Du Guoxiang. Research on variation trends and space difference based on AQI of Beijing-Tianjin-Hebei Urban Agglomeration. Urban Development Studies, 2017, 24(8): 49-56
[29]	柏玲, 姜磊, 周海峰, 等. 长江经济带空气质量指数的时空特征及驱动因素分析——基于贝叶斯空间计量模型的实证[J]. 地理科学, 2018, 38(12): 2100-2108 doi: 10.13249/j.cnki.sgs.2018.12.019
	Bai Ling, Jiang Lei, Zhou Haifeng et al. Spatio-temporal characteristics of air quality index and its driving factors in the Yangtze River Economic Belt: An empirical study based on bayesian spatial econometric model. Scientia Geographica Sinica, 2018, 38(12): 2100-2108 doi: 10.13249/j.cnki.sgs.2018.12.019
[30]	黄莘绒, 管卫华, 陈明星, 等. 长三角城市群城镇化与生态环境质量优化研究[J]. 地理科学, 2021, 41(1): 64-73
	Huang Xinrong, Guan Weihua, Chen Mingxing et al. Urbanization and optimization of the Yangtze River Delta Urban Agglomeration. Scientia Geographica Sinica, 2021, 41(1): 64-73
[31]	康恒元, 刘玉莲, 李涛. 黑龙江省重点城市AQI指数特征及其与气象要素之关系[J]. 自然资源学报, 2017, 32(4): 692-703 doi: 10.11849/zrzyxb.20160451
	Kang Hengyuan, Liu Yulian, Li Tao. Characteristics of air quality index and its relationship with meteorological factors in key cities of Heilongjiang Province. Journal of Natural Resources, 2017, 32(4): 692-703 doi: 10.11849/zrzyxb.20160451
[32]	姜磊, 周海峰, 柏玲, 等. 中国城市空气质量指数(AQI)的动态变化特征[J]. 经济地理, 2018, 38(9): 87-95
	Jiang Lei, Zhou Haifeng, Bai Ling et al. The spatio-temporal variation of air quality index of cities in China. Economic Geography, 2018, 38(9): 87-95
[33]	蔺雪芹, 王岱. 中国城市空气质量时空演化特征及社会经济驱动力[J]. 地理学报, 2016, 71(8): 1357-1371 doi: 10.11821/dlxb201608006
	Lin Xueqin, Wang Dai. Spatio-temporal variations and socio-economic driving forces of air quality in Chinese cities. Acta Geographica Sinica, 2016, 71(8): 1357-1371 doi: 10.11821/dlxb201608006
[34]	方创琳. 中国城市群地图集[M]. 北京: 科学出版社, 2020.
	Fang Chuanglin. The atlas of China urban agglomerations. Beijing: Science Press, 2020.
[35]	国家统计局. 中国城市统计年鉴2020[M]. 北京: 中国统计出版社, 2021.
	National Bureau of Statistics. China city statistical yearbook 2020. Beijing: China Statistics Press, 2021.
[36]	中华人民共和国住房和城乡建设部. 中国城市建设统计年鉴2019[M]. 北京: 中国统计出版社, 2019
	Housing and urban-rural development of the People's Republic of China. China urban construction statistical yearbook 2019. Beijing: China Statistics Press, 2019.
[37]	于伟, 张鹏, 姬志恒. 中国城市群生态效率的区域差异、分布动态和收敛性研究[J]. 数量经济技术经济研究, 2021, 38(1): 23-42
	Yu Wei, Zhang Peng, Ji Zhiheng. Study on regional difference, distribution dynamics and convergence of eco-efficiency of urban clusters in China. The Journal of Quantitative & Technical Economics, 2021, 38(1): 23-42

年份	总体	群内	贡献率/%	群间	贡献率/%	超变密度	贡献率/%
2015	0.130	0.005	3.8	0.101	77.2	0.025	19.0
2016	0.128	0.004	3.2	0.105	81.9	0.019	14.8
2017	0.121	0.004	3.1	0.099	82.2	0.018	14.7
2018	0.123	0.004	3.3	0.103	83.7	0.016	13.0
2019	0.122	0.004	3.3	0.101	83.0	0.017	13.7
2020	0.118	0.004	3.1	0.099	84.2	0.015	12.7

城市群	2015年	2016年	2017年	2018年	2019年	2020年
总体	0.235	0.229	0.216	0.218	0.216	0.209
京津冀城市群	0.207	0.186	0.184	0.144	0.163	0.141
长三角城市群	0.101	0.113	0.106	0.140	0.124	0.097
珠三角城市群	0.112	0.101	0.120	0.104	0.106	0.113
长江中游城市群	0.180	0.119	0.093	0.127	0.139	0.117
成渝城市群	0.119	0.097	0.104	0.087	0.084	0.093
辽中南城市群	0.098	0.087	0.109	0.108	0.086	0.093
山东半岛城市群	0.205	0.192	0.164	0.166	0.132	0.144
海峡西岸城市群	0.129	0.100	0.085	0.073	0.053	0.052
哈长城市群	0.169	0.124	0.132	0.101	0.104	0.114
中原城市群	0.079	0.055	0.054	0.030	0.039	0.046
江淮城市群	0.119	0.059	0.077	0.092	0.078	0.098
关中城市群	0.084	0.203	0.226	0.201	0.199	0.178
北部湾城市群	0.097	0.072	0.059	0.063	0.040	0.052
天山北坡城市群	0.219	0.216	0.183	0.184	0.171	0.172
晋中城市群	0.035	0.060	0.080	0.088	0.086	0.065
呼包鄂榆城市群	0.083	0.092	0.070	0.072	0.069	0.105
滇中城市群	0.147	0.134	0.084	0.059	0.058	0.068
黔中城市群	0.090	0.115	0.056	0.066	0.064	0.072
兰西城市群	0.055	0.115	0.079	0.081	0.084	0.074
宁夏沿黄城市群	0.058	0.043	0.042	0.022	0.041	0.048

	绝对β收敛		条件β收敛
	传统收敛模型	空间杜宾模型	传统收敛模型	空间杜宾模型
注：括号中的值为估计系数的t统计量或z统计量，^***表示估计系数在1%统计水平上显著，空白为无此项。
β	−0.837^*** （−29.70）	−0.802^*** （−31.97）	−0.855^*** （−30.31）	−0.825^*** （−32.74）
ρ		0.593^*** （24.54）		0.573^*** （21.38）
γ		0.444^*** （12.25）		0.437^*** （11.03）
控制变量	否	否	是	是
空间固定效应	是	是	是	是
时间固定效应	是	是	是	是
R²	0.63	0.20	0.67	0.50
样本数	975	975	945	945

Spatial-temporal Evolution and Convergence Trend of Air Quality in China’s Urban Agglomerations

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 37

Related Articles 15

Metrics

Comments

Recommended 0

城市群名称	2015年			2020年
城市群名称	PM_2.5	O₃	PM₁₀	PM_2.5	O₃	PM₁₀
京津冀城市群	139	86	94	77	136	70
长三角城市群	152	114	42	51	142	22
珠三角城市群	81	86	23	21	113	17
长江中游城市群	204	38	80	102	87	32
成渝城市群	199	39	66	99	99	31
辽中南城市群	149	106	62	104	105	72
山东半岛城市群	171	91	94	93	150	82
海峡西岸城市群	43	24	79	25	121	29
哈长城市群	148	45	69	104	52	35
中原城市群	223	33	87	124	143	72
江淮城市群	235	0	82	89	144	31
关中城市群	97	64	177	91	106	93
北部湾城市群	106	33	57	50	40	53
天山北坡城市群	85	20	213	95	127	94
晋中城市群	159	35	115	96	153	83
呼包鄂榆城市群	66	124	137	55	136	91
滇中城市群	29	32	85	12	104	7
黔中城市群	84	27	64	36	51	7
兰西城市群	72	54	215	66	110	133
宁夏沿黄城市群	82	62	191	68	119	142

[1]	Hu Nanlin, Ren Zhibin, Dong Yulin, Fu Yao, Guo Yujie, Mao Zhixia, Chang Xinyue. Spatio-temporal Evolution of Heat Island Effect and Its Driving Factors in Urban Agglomerations of China [J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(9): 1534-1545.
[2]	Jia Zhuo, Zhao Jinyao, Yang Yongchun, Chen Xingpeng. Spatial Pattern and Spatial Convergence of Environmental Regulation Efficiency of Lanzhou-Xining Urban Agglomeration in the Yellow River Basin [J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(4): 568-578.
[3]	Zhang Zhonghao, Nie Tiantian, Gao Yang, Tan Shenghui, Gao Jun. Ecological Security Assessment and Spatio-temporal Transition Characteristics in the Yangtze River Delta Urban Agglomeration [J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(11): 1923-1931.
[4]	Fang Yelin, Cheng Xuelan, Su Xueqing, Bao Jie. The Spatial Spillover Effect of Integration Progress on Tourism Economy: A Case Study of the Yangtze River Delta Urban Agglomeration [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(9): 1546-1555.
[5]	Li Yuanjun, Wu Qitao, Zhang Yuling, Wu Kangmin, Zhang Hongou, Jin Shuangquan. Spatial Structure and Formation Mechanism of E-commerce Express Logistics Network in the Three Major Urban Agglomerations of China [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(8): 1398-1408.
[6]	Tang Jianxiong, Ma Mengyao. Spatial Layout and Linkage Mode of Industrial Tourism in Changsha-Zhuzhou-Xiangtan Urban Agglomeration from a Multi-scale Perspective [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(8): 1428-1436.
[7]	Duan Dezhong, Xia Qifan, Zhang Yang, Gao Xin. Evolution Pattern and Impact Factors of Environmental Innovation in the Yangtze River Economic Belt [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(7): 1158-1167.
[8]	Zhou Jianping, Liu Chengjun, Xu Weixiang, Li Lu, Zhou Mengyao. Research on the Spatial Adaptability of China’s New Urbanization and Urban Medical Resources [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(7): 1168-1177.
[9]	Qi Xin, Wang Lijun, Zhang Jiaxing, Wang Feiyue. Spatial Association of Urban Agglomeration and Its Economic Growth Effect Under the Influence of High-speed Railway [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(3): 416-427.
[10]	Zhang Guojun, Wang Yunzhe, Wang Juehan, Cao Yongwang, Zhou Chunshan. The Spatio-temporal Evolution and Mechanism of the Coordination Between Quality and Quantity of Economic Growth in Chinese Urban Agglomerations [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(12): 2075-2086.
[11]	Li Linshan, Zhao Hongbo, Guo Fuyou, Wang Yu. High-quality Development Spatio-temporal Evolution of Industry in Urban Agglomeration of the Yellow River Basin [J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(10): 1751-1762.
[12]	Wang Fuxi. Study on the Quality Measurement and Coordinated Development of Population-land Urbanization in Shandong Peninsula Urban Agglomeration [J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(8): 1345-1354.
[13]	Zhao Ruyu, Xu Jun. Spatial Agglomeration and Unbalanced Development of Elements in Northeast China [J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(7): 1104-1113.
[14]	Peng Wenying, Wang Ruijuan, Liu Dandan. Inter-regional Ecological Contribution and Ecological Compensation in Urban Agglomeration [J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(6): 980-988.
[15]	Zhang Xiangmin, Luo Shen, Li Xingming, Li Zhuofan, Fan Yong, Sun Jianwu. Spatio-temporal Variation Features of Air Quality in China [J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(2): 190-199.