地理学报 ›› 2021, Vol. 76 ›› Issue (11): 2814-2829.doi: 10.11821/dlxb202111015
赵艳艳1(), 张晓平1(
), 陈明星1,2, 高珊珊1, 李润奎1
收稿日期:
2020-09-07
修回日期:
2021-04-20
出版日期:
2021-11-25
发布日期:
2022-01-25
通讯作者:
张晓平(1972-), 女, 河南南阳人, 博士, 副教授, 硕士生导师, 主要从事经济地理学相关领域的教学与科研。E-mail: zhangxp@ucas.ac.cn作者简介:
赵艳艳(1995-), 女, 河北邢台人, 硕士生, 专业方向为产业与区域可持续发展。E-mail: zhaoyanyan18@mails.ucas.ac.cn
基金资助:
ZHAO Yanyan1(), ZHANG Xiaoping1(
), CHEN Mingxing1,2, GAO Shanshan1, LI Runkui1
Received:
2020-09-07
Revised:
2021-04-20
Published:
2021-11-25
Online:
2022-01-25
Supported by:
摘要:
开展城市空气质量时空格局演变特征及其影响因素的研究,对于深入认识城市环境与社会经济系统的互馈机理、制定高效的环境治理措施、提升城市发展质量具有重要的理论与实践意义。本文以中国全面实施《大气污染防治行动计划》的2014年为起点,刻画了2014—2019年286个地级以上城市6种空气污染物浓度(CO、NO2、O3、PM10、PM2.5、SO2)的时空演变特征,并基于面板回归模型分析各污染物浓度之间的相互作用关系;进而利用随机森林模型对城市6种空气污染物浓度与13个自然和社会经济影响因子的关联强度进行探究,从中梳理出关键影响因子。结果显示:① 研究期内,O3污染加剧,其余污染物年均浓度逐年下降,其中SO2浓度降幅最大。虽然典型的重污染区范围有所减小,但京津冀、山东半岛、山西、河南等地区的城市空气污染物浓度仍相对较高。② 城市6种空气污染物浓度之间存在显著的相互影响关系,城市空气复合污染特征明显。③ 自然因素和社会经济因素对不同种类空气污染物浓度的影响差异较大,且与污染物浓度之间呈非线性响应关系。自然因素中,城市年均气温与空气污染物浓度的关联强度最大,其次是植被指数。社会经济影响因素中,土地城市化水平和二产比重是主导影响因子,其次是电力消耗总量和交通因子。偏依赖分析进一步刻画了不同污染物浓度对主导影响因子的响应突变阈值。鉴于人类对于自然环境和气象条件的控制能力有限,建议继续通过优化城市密度、控制人为排放源及严格的空气污染防控措施以进一步有效提高城市空气质量。
赵艳艳, 张晓平, 陈明星, 高珊珊, 李润奎. 中国城市空气质量的区域差异及归因分析[J]. 地理学报, 2021, 76(11): 2814-2829.
ZHAO Yanyan, ZHANG Xiaoping, CHEN Mingxing, GAO Shanshan, LI Runkui. Regional variation of urban air quality in China and its dominant factors[J]. Acta Geographica Sinica, 2021, 76(11): 2814-2829.
表2
城市6种空气污染物之间相互影响关系的面板回归模型结果
变量 | CO | NO2 | O3_8h | PM10 | PM2.5 | SO2 |
---|---|---|---|---|---|---|
CO | - | 2.397*** | -11.662*** | 3.228*** | 0.808 | 15.944*** |
NO2 | 0.00470*** | - | 0.636*** | 0.320*** | 0.0787** | 0.150*** |
O3_8h | -0.00305*** | 0.0848*** | - | 0.0586*** | -0.0373*** | -0.171*** |
PM10 | 0.000197*** | 0.0997*** | 0.137*** | - | 0.489*** | 0.0458 |
PM2.5 | 0.00124 | 0.0616** | -0.219*** | 1.229*** | - | 0.349*** |
SO2 | 0.0100*** | 0.0482*** | -0.412*** | 0.0473 | 0.144*** | - |
Constant | 0.681*** | 8.467*** | 89.084*** | 5.296** | 3.576** | -4.619** |
Observations | 1430 | 1430 | 1430 | 1430 | 1430 | 1430 |
R2 | 0.861 | 0.935 | 0.741 | 0.972 | 0.965 | 0.878 |
变量个数(个) | 286 | 286 | 286 | 286 | 286 | 286 |
表3
2019年相较于2015年城市6种空气污染物浓度变化量(按城市分类)
污染物浓度 | CO (mg/m3) | NO2 (μg/m3) | O3_8h (μg/m3) | PM10 (μg/m3) | PM2.5 (μg/m3) | SO2 (μg/m3) | |
---|---|---|---|---|---|---|---|
变化量 | 环保重点城市 | -0.278 | -3.624 | 10.228 | -23.512 | -14.384 | -16.140 |
非环保重点城市 | -0.269 | -1.926 | 9.457 | -18.305 | -12.302 | -13.277 | |
变化率 (%) | 环保重点城市 | -25.29 | -10.3 | 12.13 | -25.18 | -26.56 | -58.38 |
非环保重点城市 | -25.92 | -7.10 | 11.54 | -21.84 | -24.84 | -54.19 |
[1] | Xu Qingli, Li Hao. Study on the pollution characteristics and correlation of PM2.5 and NO2 in the urban area of Chenzhou City. China Population, Resources and Environment, 2016, 26(Suppl.2):80-82. |
[徐庆利, 李濠. 关于郴州市城区PM2.5和NO2的污染特征及相关性的探讨. 中国人口·资源与环境, 2016, 26(Suppl.2):80-82.] | |
[2] | Li Kai, Liu Min, Mei Rubo. Pollution characteristics and sensitivity analysis of atmospheric ozone in Taian city. Environmental Science, 2020, 41(8):3539-3546. |
[李凯, 刘敏, 梅如波. 泰安市大气臭氧污染特征及敏感性分析. 环境科学, 2020, 41(8):3539-3546.] | |
[3] | Liu Huajun, Du Guangjie. Spatial pattern and distributional dynamics of urban air pollution in China: An empirical study based on AQI and six sub-pollutants of 161 cities. Economic Geography, 2016, 36(10):33-38. |
[刘华军, 杜广杰. 中国城市大气污染的空间格局与分布动态演进: 基于161个城市AQI及6种分项污染物的实证. 经济地理, 2016, 36(10):33-38.] | |
[4] | Deng Xiajun, Liao Liangqing, Hu Guiping. Air pollution index and their correlation with meteorological data in major cities of China during the last decade. Environmental Science & Technology, 2013, 36(9):70-75, 80. |
[邓霞君, 廖良清, 胡桂萍. 近10年中国主要城市空气API及与气象因子相关性分析. 环境科学与技术, 2013, 36(9):70-75, 80.] | |
[5] |
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 |
[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. 地理学报, 2016, 71(8):1357-1371.] | |
[6] |
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 |
[张向敏, 罗燊, 李星明, 等. 中国空气质量时空变化特征. 地理科学, 2020, 40(2):190-199.] | |
[7] |
Chen W, Tang H Z, Zhao H M. Diurnal, weekly and monthly spatial variations of air pollutants and air quality of Beijing. Atmospheric Environment, 2015, 119:21-34.
doi: 10.1016/j.atmosenv.2015.08.040 |
[8] |
Dai F, Chen M, Yang B. Spatiotemporal variations of PM2.5 concentration at the neighborhood level in five Chinese megacities. Atmospheric Pollution Research, 2020, 11(6):190-202.
doi: 10.1016/j.apr.2020.03.010 |
[9] |
Wang Zhenbo, Liang Longwu, Wang Xujing. Spatio-temporal evolution patterns and influencing factors of PM2.5 in Chinese urban agglomerations. Acta Geographica Sinica, 2019, 74(12):2614-2630.
doi: 10.11821/dlxb201912014 |
[王振波, 梁龙武, 王旭静. 中国城市群地区PM2.5时空演变格局及其影响因素. 地理学报, 2019, 74(12):2614-2630.] | |
[10] | Guo Yiming, Lin Xueqin, Bian Yu. The spatial-temporal characteristics and influencing factors of air quality in China's urban agglomerations. Ecological Economy, 2019, 35(11):167-175. |
[郭一鸣, 蔺雪芹, 边宇. 中国城市群空气质量时空演化特征及其影响因素. 生态经济, 2019, 35(11):167-175.] | |
[11] |
Cheng Yu, Liu Tingting, Zhao Yunlu, et al. Spatiotemporal evolution and socioeconomic driving mechanism of air quality in Beijing-Tianjin-Hebei and surrounding areas ("2+26" cities). Economic Geography, 2019, 39(10):183-192.
doi: 10.2307/142511 |
[程钰, 刘婷婷, 赵云璐, 等. 京津冀及周边地区“2+26”城市空气质量时空演变与经济社会驱动机理. 经济地理, 2019, 39(10):183-192.] | |
[12] |
Chen T, Deng S L, Gao Y, et al. Characterization of air pollution in urban areas of Yangtze River Delta, China. Chinese Geographical Science, 2017, 27(5):836-846.
doi: 10.1007/s11769-017-0900-z |
[13] |
Li H J, Qi Y J, Li C, et al. Routes and clustering features of PM2.5 spillover within the Jing-Jin-Ji region at multiple timescales identified using complex network-based methods. Journal of Cleaner Production, 2019, 209:1195-1205.
doi: 10.1016/j.jclepro.2018.10.284 |
[14] | Liao Qianyi, Luo Bin, Du Yunsong, et al. Effects and characteristics of floating dust weather on air quality in Sichuan Basin. Environmental Monitoring in China, 2016, 32(5):51-55. |
[廖乾邑, 罗彬, 杜云松, 等. 北方沙尘对四川盆地环境空气质量影响和特征分析. 中国环境监测, 2016, 32(5):51-55.] | |
[15] | Yu Caixia, Deng Xueliang, Shi Chun'e, et al. The scavenging effect of precipitation and wind on PM2.5 and PM10. Acta Scientiae Circumstantiae, 2018, 38(12):4620-4629. |
[于彩霞, 邓学良, 石春娥, 等. 降水和风对大气PM2.5、PM10的清除作用分析. 环境科学学报, 2018, 38(12):4620-4629.] | |
[16] | Yang Qian, Gao Yanghua, Chen Guichuan. Influence analysis of the precipitation on atmospheric pollutant concentration in Chongqing. Meteorological and Environmental Sciences, 2019, 42(2):68-73. |
[杨茜, 高阳华, 陈贵川. 降水对重庆市大气污染物浓度的影响分析. 气象与环境科学, 2019, 42(2):68-73.] | |
[17] | Wang Yidi, Wang Zhenxiang. Characteristics of PM2.5 concentration variability and its meteorological factors in Shanghai. Arid Land Geography, 2018, 41(5):1088-1096. |
[王祎頔, 王真祥. 上海市PM2.5浓度变化特征及其气象因子分析. 干旱区地理, 2018, 41(5):1088-1096.] | |
[18] | Long X, Tie X X, Cao J J, et al. Impact of crop field burning and mountains on heavy haze in the North China Plain: A case study. Atmospheric Chemistry and Physics, 2016, 16(15):9675-9691. |
[19] |
Liu H M, Fang C L, Zhang X L, et al. The effect of natural and anthropogenic factors on haze pollution in Chinese cities: A spatial econometrics approach. Journal of Cleaner Production, 2017, 165:323-333.
doi: 10.1016/j.jclepro.2017.07.127 |
[20] | Liu Yaqing, Ma Yixiang, Wu Zhenxin. The impact of industrial structure upgrade in Beijing-Tainjin-Heibei region on air pollution. Urban Problems, 2017(12):65-71. |
[刘亚清, 马艺翔, 吴振信. 京津冀地区产业结构升级对大气污染的影响. 城市问题, 2017(12):65-71.] | |
[21] | Jiang Lei, Zhou Haifeng, Bai Ling. Impact of urbanization on urban air quality based on spatial econometric models. Tropical Geography, 2019, 39(3):461-471. |
[姜磊, 周海峰, 柏玲. 基于空间计量模型的中国城市化发展与城市空气质量关系. 热带地理, 2019, 39(3):461-471.] | |
[22] | Wang Fayuan, Zheng Jun, Wang Zongshun. Analysis of the influence of urbanization and industrialization level on air quality: Based on the space-time model of data from 16 cities in Hubei Province in 2005-2017. Resources and Environment in the Yangtze Basin, 2019, 28(6):1411-1421. |
[汪发元, 郑军, 汪宗顺. 城市化水平、工业化水平对空气质量的影响分析: 基于湖北省16城市2005—2017年数据的时空模型. 长江流域资源与环境, 2019, 28(6):1411-1421.] | |
[23] | Xu Shan, Zou Bin, Pu Qiang, et al. Impact analysis of land use/cover on air pollution. Journal of Geo-Information Science, 2015, 17(3):290-299. |
[许珊, 邹滨, 蒲强, 等. 土地利用/覆盖的空气污染效应分析. 地球信息科学学报, 2015, 17(3):290-299.] | |
[24] |
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.
doi: 10.13249/j.cnki.sgs.2018.03.004 |
[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. 地理科学, 2018, 38(3):351-360.] | |
[25] | Liu Huajun, Sun Yanan, Chen Minghua. Dynamic correlation and causes of urban haze pollution. China Population, Resources and Environment, 2017, 27(3):74-81. |
[刘华军, 孙亚男, 陈明华. 雾霾污染的城市间动态关联及其成因研究. 中国人口·资源与环境, 2017, 27(3):74-81.] | |
[26] |
Liu Haimeng, Fang Chuanglin, Huang Jiejun, et al. The spatial-temporal characteristics and influencing factors of air pollution in Beijing-Tianjin-Hebei urban agglomeration. Acta Geographica Sinica, 2018, 73(1):177-191.
doi: 10.11821/dlxb201801015 |
[刘海猛, 方创琳, 黄解军, 等. 京津冀城市群大气污染的时空特征与影响因素解析. 地理学报, 2018, 73(1):177-191.] | |
[27] |
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 |
[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. 地理科学, 2018, 38(12):2100-2108.] | |
[28] | Bai Ling, Jiang Lei, Zhou Haifeng, et al. Spatiotemporal heterogeneity of air quality index and its socio-economic factors in the Yangtze River economic belt. Research of Soil and Water Conservation, 2019, 26(2):312-319. |
[柏玲, 姜磊, 周海峰, 等. 长江经济带空气质量指数时空异质性及社会经济影响因素分析. 水土保持研究, 2019, 26(2):312-319.] | |
[29] |
Zhang X P, Gong Z Z. Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants. Journal of Geographical Sciences, 2018, 28(5):563-578.
doi: 10.1007/s11442-018-1491-z |
[30] |
Chen Mingxing. Research progress and scientific issues in the field of urbanization. Geographical Research, 2015, 34(4):614-630.
doi: 10.11821/dlyj201504002 |
[陈明星. 城市化领域的研究进展和科学问题. 地理研究, 2015, 34(4):614-630.] | |
[31] |
Liu Weidong, Tang Zhipeng, Xia Yan, et al. Identifying the key factors influencing Chinese carbon intensity using machine learning, the random forest algorithm, and evolutionary analysis. Acta Geographica Sinica, 2019, 74(12):2592-2603.
doi: 10.11821/dlxb201912012 |
[刘卫东, 唐志鹏, 夏炎, 等. 中国碳强度关键影响因子的机器学习识别及其演进. 地理学报, 2019, 74(12):2592-2603.] | |
[32] | Chen Danling, Lu Xinhai, Kuang Bing. Dynamic evolution and spatial convergence of urban land use efficiency in the middle reaches of the Yangtze River. China Population, Resources and Environment, 2018, 28(12):106-114. |
[陈丹玲, 卢新海, 匡兵. 长江中游城市群城市土地利用效率的动态演进及空间收敛. 中国人口·资源与环境, 2018, 28(12):106-114.] | |
[33] | Ministry of Environmental Protection of the People's Republic of China. Ambient Air Quality Standards. National Environmental Protection Standards of the People's Republic of China (GB3095-2012), 2012-02-29. |
[国家环境保护部. 环境空气质量标准. 中华人民共和国国家环境保护标准(GB3095-2012), 2012-02-29.] | |
[34] | Cheng Linjun, Wang Shuai, Gong Zhengyu, et al. Pollution trends of ozone and its characteristics of temporal and spatial distribution in Beijing-Tianjin-Hebei region. Environmental Monitoring in China, 2017, 33(1):14-21. |
[程麟钧, 王帅, 宫正宇, 等. 京津冀区域臭氧污染趋势及时空分布特征. 中国环境监测, 2017, 33(1):14-21.] | |
[35] | Su Yongxian, Chen Xiuzhi, Ye Yuyao, et al. The characteristics and mechanisms of carbon emissions from energy consumption in China: Using DMSP/OLS night light imageries. Acta Geographica Sinica, 2013, 68(11):1513-1526. |
[苏泳娴, 陈修治, 叶玉瑶, 等. 基于夜间灯光数据的中国能源消费碳排放特征及机理. 地理学报, 2013, 68(11):1513-1526.] | |
[36] |
Xiao H W, Ma Z Y, Mi Z F, et al. Spatio-temporal simulation of energy consumption in China's provinces based on satellite night-time light data. Applied Energy, 2018, 231:1070-1078.
doi: 10.1016/j.apenergy.2018.09.200 |
[37] |
Wu Jiansheng, Niu Yan, Peng Jian, et al. Research on energy consumption dynamic among prefecture-level cities in China based on DMSP/OLS nighttime light. Geographical Research, 2014, 33(4):625-634.
doi: 10.11821/dlyj201404003 |
[吴健生, 牛妍, 彭建, 等. 基于DMSP/OLS夜间灯光数据的1995—2009年中国地级市能源消费动态. 地理研究, 2014, 33(4):625-634.] | |
[38] | Bai Caiquan, Wang Xiumei, Xie Yueqing, et al. Evolutionary tendency and income gap of county residents in Yangtze River Delta: Based on kernel density estimation method. Acta Agriculturae Zhejiangensis, 2015, 27(3):498-503. |
[白彩全, 王秀梅, 谢悦青, 等. 长三角县域居民收入差距演变趋势: 基于核密度估计的分析. 浙江农业学报, 2015, 27(3):498-503.] | |
[39] |
Breiman L. Random forests. Machine Learning, 2001, 45(1):5-32.
doi: 10.1023/A:1010933404324 |
[40] | Xia Xiaosheng, Chen Jingjing, Wang Jiajia, et al. PM2.5 concentration influencing factors in China based on the random forest model. Environmental Science, 2020, 41(5):2057-2065. |
[夏晓圣, 陈菁菁, 王佳佳, 等. 基于随机森林模型的中国PM2.5浓度影响因素分析. 环境科学, 2020, 41(5):2057-2065.] | |
[41] | Wang Jiajia, Xia Xiaosheng, Cheng Xianfu, et al. Temporal and spatial distribution characteristics and influencing factors of PM2.5 concentration in Hefei city. Resources and Environment in the Yangtze Basin, 2020, 29(6):1413-1421. |
[王佳佳, 夏晓圣, 程先富, 等. 合肥市PM2.5浓度时空分布特征及影响因素分析. 长江流域资源与环境, 2020, 29(6):1413-1421.] | |
[42] |
Wang Chao, Kan Aike, Zeng Yelong, et al. Population distribution pattern and influencing factors in Tibet based on random forest model. Acta Geographica Sinica, 2019, 74(4):664-680.
doi: 10.11821/dlxb201904004 |
[王超, 阚瑷珂, 曾业隆, 等. 基于随机森林模型的西藏人口分布格局及影响因素. 地理学报, 2019, 74(4):664-680.] | |
[43] | Wang Wei. Characteristics of negative air ion concentration and its relationships with environmental factors. Ecology and Environmental Sciences, 2014, 23(6):979-984. |
[王薇. 空气负离子浓度分布特征及其与环境因子的关系. 生态环境学报, 2014, 23(6):979-984.] | |
[44] |
Wang Hua, Lu Shaowei, Li Shaoning, et al. Inhalable particulate matter and fine particulate matter: Their basic characteristics, monitoring methods, and forest regulation functions. Chinese Journal of Applied Ecology, 2013, 24(3):869-877.
pmid: 23755507 |
[王华, 鲁绍伟, 李少宁, 等. 可吸入颗粒物和细颗粒物基本特征、监测方法及森林调控功能. 应用生态学报, 2013, 24(3):869-877.]
pmid: 23755507 |
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