河北省大气污染时空变化特征及其影响因素

doi:10.31497/zrzyxb.20210211

自然资源学报 ›› 2021, Vol. 36 ›› Issue (2): 411-419.doi: 10.31497/zrzyxb.20210211

河北省大气污染时空变化特征及其影响因素

何振芳¹^,²(), 郭庆春¹^,³(), 刘加珍¹, 张莹莹¹, 刘杰¹, 丁航¹

1.聊城大学环境与规划学院,聊城 252000
2.中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京 100085
3.中国科学院地球环境研究所黄土与第四纪地质国家重点实验室,西安 710061

收稿日期:2019-09-12 修回日期:2020-05-09 出版日期:2021-02-28 发布日期:2021-04-28
通讯作者: 郭庆春 E-mail:hezhenfang@lcu.edu.cn;guoqingchun@lcu.edu.cn
作者简介:何振芳（1983- ）,女,山东泰安人,博士,讲师,研究方向为GIS与RS应用。E-mail: hezhenfang@lcu.edu.cn
基金资助:
国家自然科学基金项目(41472162);山东省社科规划研究项目(18CKPJ34);山东省高等学校人文社会科学计划项目(J18RA196);黄土与第四纪地质国家重点实验室开放基金资助项目(SKLLQG1907)

Spatio-temporal variation characteristics of air pollution and influencing factors in Hebei province

HE Zhen-fang¹^,²(), GUO Qing-chun¹^,³(), LIU Jia-zhen¹, ZHANG Ying-ying¹, LIU Jie¹, DING Hang¹

1. School of Environment and Planning, Liaocheng University, Liaocheng 252000, Shandong, China
2. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, CAS, Beijing 100085, China
3. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, CAS, Xi'an 710061, China

Received:2019-09-12 Revised:2020-05-09 Online:2021-02-28 Published:2021-04-28
Contact: GUO Qing-chun E-mail:hezhenfang@lcu.edu.cn;guoqingchun@lcu.edu.cn

摘要/Abstract

摘要：

河北省是中国污染最严重的省份,研究该省大气污染的时空变化与影响因素具有十分重要的意义。利用逐日空气质量指数（AQI）、气象要素观测资料以及社会经济数据,统计分析与空间分析法结合分析了河北省AQI时空变化特征及其与影响因素的定量关系。结果表明：河北省大气污染主要发生在中西部和南部,尤以邯郸、邢台与石家庄等地最为严重,北部地区相对较少。河北省AQI总体呈现逐年减少的趋势,2014—2018年河北省平均AQI线性趋势为-8.845/年,而且与风速、气温、降水、GDP、人口、电力消耗量和第二产业呈现显著负相关关系,而和NO_x与SO₂的排放量呈正相关。气候条件是河北省大气污染的诱导因素,而人为排放是河北省大气重污染的主要因素。随着河北经济的飞速发展,大气污染综合防治经费的投入增加,河北省经济增长与环境污染处于反向阶段,大气污染与经济发展的非线性关系早已过了环境库兹涅兹曲线（EKC）“拐点”。研究结果可为河北省空气污染治理提供理论依据。

关键词: 大气污染, 河北省, 空气质量指数, 气温, 降水, 社会经济

Abstract:

Hebei is the most polluted province in China. It is significant to study the spatio-temporal variation of air pollution and its influencing factors. Based on the daily air quality index (AQI), meteorological data and socio-economic data, the spatial and temporal variation characteristics of air quality index and its relationship with influencing factors in Hebei province were examined by statistical analysis and spatial interpolation. The results show that air pollution mainly occurs in the central and southern parts of the province, especially in Handan, Xingtai and Shijiazhuang, but rarely in the north. The air quality index of the province shows a decreasing trend year by year, with a linear trend of -8.845/year, and it has a good negative correlation with wind speed, temperature, precipitation, gross domestic product (GDP), population, electricity consumption and secondary industry, while it has a positive correlation with sulfur dioxide emissions and nitrogen oxide emissions. Adverse climatic conditions are the inducement of atmospheric pollution, and high emission intensity is the main cause of heavy atmospheric pollution. With the rapid economic development and the increase of money invested in full control of air pollution in Hebei, its economy and pollution are on the right side of the EKC curve of environmental Kuznets. The relationship between air quality and economic development in Hebei has passed the "inflection point" of the environmental Kuznets curve. These results can provide theoretical basis for air pollution control in this province.

Key words: air pollution, Hebei province, air quality index, temperature, precipitation, socio-economy

何振芳, 郭庆春, 刘加珍, 张莹莹, 刘杰, 丁航. 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.

HE Zhen-fang, GUO Qing-chun, LIU Jia-zhen, ZHANG Ying-ying, LIU Jie, DING Hang. Spatio-temporal variation characteristics of air pollution and influencing factors in Hebei province[J]. JOURNAL OF NATURAL RESOURCES, 2021, 36(2): 411-419.

图/表 11

图1

表1

表2

图2

表3

表4

图3

图4

图5

图6

表5

参考文献 22

[1]	HAINES A, AMANN M, BORGFORD N, et al. Short-lived climate pollutant mitigation and the sustainable development goals. Nature Climate Change, 2017,7(12):863-869.
[2]	HUANG R J, ZHANG Y, BOZZETTI C. High secondary aerosol contribution to particulate pollution during haze events in China. Nature, 2014,514(7521):218-222. doi: 10.1038/nature13774 pmid: 25231863
[3]	ZHANG Q, JIANG X, TONG D, et al. Transboundary health impacts of transported global air pollution and international trade. Nature, 2017,543(7647):705-709. doi: 10.1038/nature21712 pmid: 28358094
[4]	尹志聪, 王会军, 袁东敏. 华北黄淮冬季霾年代际增多与东亚冬季风的减弱. 科学通报, 2015,60(15):1395-1401.
	[ YIN Z C, WANG H J, YUAN D M. Interdecadal increase of haze in winter over North China and the Huang-huai Area and the weakening of the East Asia Winter Monsoon. Chinese Science Bulletin, 2015,60(15):1395-1401.]
[5]	梅梅, 朱蓉, 孙朝阳. 京津冀及周边“2+26”城市秋冬季大气重污染气象条件及其气候特征研究. 气候变化研究进展, 2019,15(3):270-281.
	[ MEI M, ZHU R, SUN C Y. Study on meteorological conditions for heavy air pollution and its climatic characteristics in "2+26" cities around Beijing-Tianjin-Hebei region in autumn and winter. Climate Change Research, 2019,15(3):270-281.]
[6]	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.
	[ LIU H M, FANG C L, HUANG J J, 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.]
[7]	周兆媛, 张时煌, 高庆先, 等. 京津冀地区气象要素对空气质量的影响及未来变化趋势分析. 资源科学, 2014,36(1):191-199.
	[ ZHOU Z Y, ZHANG S H, GAO Q X, et al. The Impact of meteorological factors on air quality in the beijing-tianjin-hebei region and trend analysis. Resources Science, 2014,36(1):191-199.]
[8]	魏文秀, 张欣, 田国强. 河北霾分布与地形和风速关系分析. 自然灾害学报, 2010,19(1):49-52.
	[ WEI W X, ZHANG X, TIAN G Q. Analysis of relation between haze distribution and terrain and wind speed in Hebei province. Journal of Natural Disasters, 2010,19(1):49-52.]
[9]	丁一汇, 王会军. 近百年中国气候变化科学问题的新认识. 科学通报, 2016,61(10):1029-1041.
	[ DING Y H, WANG H J. Newly acquired knowledge on the scientific issues related to climate change over the recent 100 years in China. Chinese Science Bulletin, 2016,61(10):1029-1041.]
[10]	王静, 邱粲, 刘焕彬, 等. 山东重点城市空气质量及其与气象要素的关系. 生态环境学报, 2013,22(4):644-649.
	[ WANG J, QIU C, LIU H B, et al. Characteristics of air quality and the correlation between API and meteorological elements in major cities of Shandong province. Ecology and Environmental Sciences, 2013,22(4):644-649.]
[11]	李婷苑, 邓雪娇, 范绍佳, 等. 2010年广州亚运期间空气质量与污染气象条件分析. 环境科学, 2012,33(9):2932-2938.
	[ LI T Y, DENG X J, FAN S J, et al. Study on air quality and pollution meteorology conditions of guangzhou during the 2010 asian games. Environmental Science, 2012,33(9):2932-2938.]
[12]	景瑞环, 麻金继, 汪超. 基于多源数据的PM_2.5反演方法. 大气与环境光学学报, 2015,1:51-62.
	[ JING R H, MA J J, WANG C. Methods of PM_2.5 inversion based on multi-source data. Journal of Atmospheric and Environmental Optics, 2015,1:51-62.]
[13]	丁一汇, 柳艳菊. 近50年我国雾和霾的长期变化特征及其与大气湿度的关系. 中国科学: 地球科学, 2014,44(1):37-48.
	[ DING Y H, LIU Y J. Analysis of long-term variations of fog and haze in China in recent 50 years and their relations with atmospheric humidity. Science China: Earth Sciences, 2014,44(1):37-48.]
[14]	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. 自然资源学报, 2017,32(4):692-703.
	[ KANG H Y, LIU Y L, LI T. 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.]
[15]	PATTON A P, PERKINS J, ZAMORE W, et al. Spatial and temporal differences in traffic-related air pollution in three urban neighborhoods near an interstate highway. Atmospheric Environment, 2014,99:309-321.
[16]	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.
	[ LIN X Q, WANG D. Spatio-temporal variations and socio-economic driving forces of air quality in Chinese cities. Acta Geographica Sinica, 2016,71(8):1357-1371.]
[17]	姚尧, 李江风, 胡涛, 等. 中国城市NO₂浓度的时空分布及社会经济驱动力. 资源科学, 2017,39(7):1383-1393.
	[ YAO Y, LI J F, HU T, et al. Spatiotemporal variation in NO₂ concentrations and socioeconomic driving forces in Chinese cities. Resources Science, 2017,39(7):1383-1393.]
[18]	GANG L, FU J, DONG J, et al. Spatio-temporal variation of PM_2.5 concentrations and their relationship with geographic and socioeconomic factors in China. International Journal of Environmental Research & Public Health, 2014,11(1):173-86. doi: 10.3390/ijerph110100173 pmid: 24362546
[19]	杨昆, 杨玉莲, 朱彦辉, 等. 中国PM_2.5污染与社会经济的空间关系及成因. 地理研究, 2016,35(6):1051-1060.
	[ YANG K, YANG Y L, ZHU Y H, et al. Social and economic drivers of PM_2.5 and their spatial relationship in China. Geographical Research, 2016,35(6):1051-1060.]
[20]	贺灿飞, 张腾, 杨晟朗. 环境规制效果与中国城市空气污染. 自然资源学报, 2013,28(10):1651-1663.
	[ HE C F, ZHANG T, YANG S L. Air pollution in chinese cities: does enforcement of environmental regulations matter?. Journal of Natural Resources, 2013,28(10):1651-1663.]
[21]	徐冬, 黄震方, 黄睿, 等. 中国中东部雾霾污染与入境旅游的时空动态关联分析. 自然资源学报, 2019,34(5):1108-1120.
	[ XU D, HUANG Z F, HUANG R, et al. The spatiotemporal dynamic correlation analysis of haze pollution and inbound tourism in central and eastern China. Journal of Natural Resources, 2019,34(5):1108-1120.]
[22]	王艳华, 苗长虹, 胡志强, 等. 专业化、多样性与中国省域工业污染排放的关系. 自然资源学报, 2019,34(3):586-599.
	[ WANG Y H, MIAO C H, HU Z Q, et al. Specialization, diversity and their impacts on China's provincial industrial pollution emissions. Journal of Natural Resources, 2019,34(3):586-599.]

AQI	等级	状况
0~50	Ⅰ	优
51~100	Ⅱ	良
101~150	Ⅲ	轻度污染
151~200	Ⅳ	中度污染
201~300	Ⅴ	重度污染
>300	Ⅵ	严重污染

城市	PM_2.5	PM₁₀	SO₂	CO	NO₂	O₃
保定	3.5982	2.9698	4.3388	3.9598	2.3788	2.8441
沧州	3.153	2.6298	3.3088	3.1208	2.0205	2.483
承德	3.6425	2.8918	3.3894	2.7278	1.983	2.4802
邯郸	3.3848	2.644	3.8454	3.0217	2.0908	2.7091
衡水	3.2628	2.8221	3.8933	2.9621	2.2107	2.4266
廊坊	4.082	3.1345	4.9266	3.3862	2.1872	2.8967
秦皇岛	3.7035	2.906	3.6954	3.2137	1.8202	2.5462
石家庄	3.8578	3.0932	4.1925	3.649	2.2642	2.9504
唐山	3.3202	2.6416	3.2847	2.7789	1.6204	2.844
邢台	3.5518	2.7978	3.9367	3.0046	1.8408	2.8689
张家口	3.8823	3.2757	4.542	2.6313	2.395	2.0458

城市	优	良	轻度污染	中度污染	重度污染	严重污染
保定	6.85	38.36	33.15	13.42	7.67	0.27
沧州	5.21	47.12	30.68	12.05	3.56	0.55
承德	22.19	55.34	14.52	4.66	0.55	0
邯郸	0.55	43.56	34.25	13.15	5.48	1.92
衡水	2.47	54.25	28.49	9.32	4.56	1.1
廊坊	18.36	50.96	24.38	9.32	2.47	0.27
秦皇岛	18.36	61.92	15.89	2.47	0.82	0
石家庄	1.37	40	32.6	13.42	9.32	1.1
唐山	5.48	50.96	27.4	9.04	3.29	0.55
邢台	2.74	46.85	29.86	11.23	6.58	1.37
张家口	27.95	51.23	15.62	1.64	0.55	0

因素	GDP	人均GDP	人口	电力消费量	SO₂排放量	NO_x排放量
相关系数	-0.9344^**	-0.9274^**	-0.9768^**	-0.3259^**	0.9462^**	0.9780^**
因素	第三产业	第一产业	第二产业	农业	耕地面积	森林面积
相关系数	0.7677^**	0.4897^**	-0.7243^**	-0.6167^**	0.9997^**	-0.9968^**

河北省大气污染时空变化特征及其影响因素

Spatio-temporal variation characteristics of air pollution and influencing factors in Hebei province

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 22

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	薛海, 张帆. 降水量与城市大气环境关系——以113个环保重点城市为例[J]. 自然资源学报, 2020, 35(4): 937-949.
[2]	马伟东, 刘峰贵, 周强, 陈琼, 刘飞, 陈永萍. 1961—2017年青藏高原极端降水特征分析[J]. 自然资源学报, 2020, 35(12): 3039-3050.
[3]	费龙, 邓国荣, 张洪岩, 郭笑怡, 王晓东. 基于降水Z指数的朝鲜降水及旱涝时空特征[J]. 自然资源学报, 2020, 35(12): 3051-3065.
[4]	石育中, 杨新军, 赵雪雁. 气象干旱对甘肃省榆中县乡村社会—生态系统的影响[J]. 自然资源学报, 2019, 34(9): 1987-2000.
[5]	李明, 王贵文, 柴旭荣, 胡炜霞, 张莲芝. 基于空间聚类的中国东北气候分区及其气象干旱时间变化特征[J]. 自然资源学报, 2019, 34(8): 1682-1693.
[6]	汪成博, 李双双, 延军平, 武亚群. 1970-2015年汉江流域多尺度极端降水时空变化特征[J]. 自然资源学报, 2019, 34(6): 1209-1222.
[7]	陈琦, 郭锦荣, 李超, 王翰琨, 吴春生, 邓文平, 刘苑秋, 叶清, 李晓东. 庐山地区大气降水中稳定同位素变化特征[J]. 自然资源学报, 2019, 34(6): 1306-1316.
[8]	孙美平, 张海瑜, 巩宁刚, 闫露霞, 赵琳林. 基于TRMM降水订正数据的祁连山地区最大降水高度带研究[J]. 自然资源学报, 2019, 34(3): 646-657.
[9]	李明, 柴旭荣, 王贵文, 胡炜霞, 张莲芝. 长江中下游地区气象干旱特征[J]. 自然资源学报, 2019, 34(2): 374-384.
[10]	陈洁, 刘玉洁, 潘韬, 吴绍洪, 谭清华, 葛全胜, 刘燕华. 1961-2010年中国降水时空变化特征及对地表干湿状况影响[J]. 自然资源学报, 2019, 34(11): 2440-2453.
[11]	李沛, 黄生志, 黄强, 马岚, 吴洪石, 栾金凯. 大通河流域降水结构的演变特征及其驱动力探究[J]. 自然资源学报, 2018, 33(9): 1588-1598.
[12]	张钦弟, 卫伟, 陈利顶, 杨磊. 黄土高原草地土壤水分和物种多样性沿降水梯度的分布格局[J]. 自然资源学报, 2018, 33(8): 1351-1362.
[13]	孙从建, 李伟, 李新功, 张子宇, 陈若霞, 陈伟. 青藏高原西北部近地表气温直减率时空分布特征[J]. 自然资源学报, 2018, 33(7): 1270-1282.
[14]	张扬, 李宝富, 陈亚宁. 1970—2013年西北干旱区空中水汽含量时空变化与降水量的关系[J]. 自然资源学报, 2018, 33(6): 1043-1055.
[15]	杨勤业, 景可, 徐建辉. 质疑：“红旗河”调水功能的可行性[J]. 自然资源学报, 2018, 33(5): 893-898.