Abstract
An urban agglomeration (UA), similar to a megalopolis or a metropolitan area, is a region where cities and people are concentrated, and where air pollution has adversely impacted on sustainable and high quality development. Studies on the spatio-temporal trends and the factors which influence PM2.5 concentrations may be used as a reference to support air pollution control policy for major UAs throughout the world. Nineteen UAs in China covering the years 2000–2016 were chosen as the research object, the PM2.5 concentrations being used to reflect air pollution and being estimated from analysis of remote sensing images. The Exploratory Spatial Data Analysis method was used to study the spatio-temporal trends for PM2.5 concentrations, and the Geodetector method was used to examine the factors influencing the PM2.5 concentrations. The results revealed that (i) the temporal trend for the average values of the PM2.5 concentrations in the UAs followed an inverted U-shaped curve and the inflection points of the curve occurred in 2007. (ii) The PM2.5 concentrations in the UAs exhibited significant global spatial autocorrelation with the high–high type and the low–low type being the main categories. (iii) The rate of land urbanization and the structure of energy consumption were the main factors which influenced the PM2.5 concentrations in the UAs.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
All data generated or analyzed during this study are included in this article.
References
Bai K, Ma M, Chang N, Gao W (2019) Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM2.5 data. J Environ Manag 233:530–542. https://doi.org/10.1016/j.jenvman.2018.12.071
Delfino R, Sioutas C, Malik S (2005) Potential role of ultrafine particles in associations between airborne particle mass and cardiovascular health. Environ Health Perspect 113(8):934–946. https://doi.org/10.1289/ehp.7938
Deng X, Yu Y, Liu Y (2015) Effect of construction land expansion on energy-related carbon emissions: empirical analysis of China and its provinces from 2001 to 2011. Energies 8(6):5516–5537. https://doi.org/10.3390/en8065516
Du Y, Wan Q, Liu H, Liu H, Kapsar K, Peng J (2019) How does urbanization influence PM2.5 concentrations? Perspective of spillover effect of multi-dimensional urbanization impact. J Clean Prod 220:974–983. https://doi.org/10.1016/j.jclepro.2019.02.222
Fan Q, Yang S, Liu S (2019) Asymmetrically spatial effects of urban scale and agglomeration on haze pollution in China. Int J Environ Res Public Health 16(24):1–18. https://doi.org/10.3390/ijerph16244936
Fang C, Liu H, Li G, Sun D, Miao Z (2015) Estimating the impact of urbanization on air quality in China using spatial regression models. Sustainability 7(11):15570–15592. https://doi.org/10.3390/su71115570
Fang C, Wang Z, Ma H (2018a) The theoretical cognition of the development law of China’s urban agglomeration and academic contribution. Acta Geograph Sin 73(4):651–665. https://doi.org/10.11821/dlxb201804005
Fang C, Yang J, Fang J, Huang X, Zhou Y (2018b) Optimization transmission theory and technical pathways that describe multiscale urban agglomeration spaces. Chin Geogr Sci 28(4):543–554. https://doi.org/10.1007/s11769-018-0974-2
Fu W, Chen Z, Zhu Z, Liu Q, van den Bosch CCK, Qi J, Wang M, Dang E, Dong J (2018) Spatial and temporal variations of six criteria air pollutants in Fujian Province, China. Int J Environ Res Public Health 15(12):2846. https://doi.org/10.3390/ijerph15122846
Gottmann J (1957) Megalopolis or the urbanization of the northeastern seaboard. Econ Geogr 33:189–200. https://doi.org/10.2307/142307
Grossman G, Krueger A (1995) Economic growth and the environment. Q J Econ 110:353–377. https://doi.org/10.2307/2118443
Han L, Zhou W, Li W, Li L (2014) Impact of urbanization level on urban air quality: A case of fine particles (PM2.5) in Chinese cities. Environ Pollut 194:163–170. https://doi.org/10.1016/j.envpol.2014.07.022
Han L, Zhou W, Pickett S, Li W, Qian Y (2019) Risks and causes of population exposure to cumulative fine particulate (PM2.5) pollution in China. Earth’s Future 7:615–622. https://doi.org/10.1029/2019EF001182
He J (2006) Pollution haven hypothesis and environmental impacts of foreign direct investment: the case of industrial emission of Sulfur Dioxide (SO2) in Chinese provinces. Ecol Econ 14(4):228–245. https://doi.org/10.1016/j.ecolecon.2005.12.008
Hixson M, Mahmud A, Hu JL, Kleeman M (2012) Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley, USA. J Air Waste Manage Assoc 62(5):566–575. https://doi.org/10.1080/10962247.2012.663325
Huang M, Lin S (2013) Pollution damage, environmental management, and sustainable economic growth: Based on the analysis of five-department endogenous growth model. Econ Res J 12:30–41
Huang X, Zhao J, Cao J, Xin W (2019) Evolution of the distribution of PM2.5 concentration in Yangtze River Economic Belt and its influencing factors. Environ Sci 40:1–15. https://doi.org/10.13227/j.hjkx.201906158
Jin G, Chen K, Wang P, Guo B, Dong Y, Yang J (2019) Trade-offs in land-use competition and sustainable land development in the North China Plain. Technol Forecast Soc Chang 141:36–46. https://doi.org/10.1016/j.techfore.2019.01.004
Laden F, Neas L, Dockery D, Schwartz J (2000) Association of fine particulate matter from different sources with daily mortality in six US cities. Environ Health Perspect 108(10):941–947. https://doi.org/10.1289/ehp.00108941
Laden F, Schwartz J, Speizer F, Dockery D (2006) Reduction in fine particulate air pollution and mortality: extended follow-up of the Harvard six cities study. Am J Respir Crit Care Med 173(6):667–672. https://doi.org/10.1164/rccm.200503-443OC
Li T (2018) 40 Years of Chinese urbanization: key findings and future options. Popul Res 42(6):15–24
Li Y, Zhu K, Wang S (2019) Polycentric and dispersed population distribution increases PM2.5 concentrations: evidence from 286 Chinese cities, 2001-2016. J Clean Prod 248:1–11. https://doi.org/10.1016/j.jclepro.2019.119202
Lin X, Wang D (2016) Spatiotemporal evolution of urban air quality and socioeconomic driving forces in China. J Geogr Sci 26(11):1533–1549. https://doi.org/10.1007/s11442-016-1342-8
Lin B, Wang Y (2020) Does energy poverty really exist in China? From the perspective of residential electricity consumption. Energy Policy 143:1–10. https://doi.org/10.1016/j.enpol.2020.111557
Lin Y, Yuan X, Zhai T, Wang J (2019) Effects of land-use patterns on PM2.5 in China’s developed coastal region: exploration and solutions. Sci Total Environ 703:1–10. https://doi.org/10.1016/j.scitotenv.2019.135602
Liu M, Hao W (2020) Spatial distribution and its influencing factors of national A-level tourist attractions in Shanxi Province. Acta Geograph Sin 75(4):878–888. https://doi.org/10.11821/dlxb202004015
Liu H, Fang C, Zhang X, Wang Z, Bao C, Li F (2017) The effect of natural and anthropogenic factors on haze pollution in Chinese cities: a spatial econometrics approach. J Clean Prod 165:323–333. https://doi.org/10.1016/j.jclepro.2017.07.127
Liu H, Fang C, Huang X, Zhu X, Zhou Y, Wang Z, Zhang Q (2018a) The spatial-temporal characteristics and influencing factors of air pollution in Beijing-Tianjin-Hebei urban agglomeration. Acta Geograph Sin 73(1):177–191. https://doi.org/10.11821/dlxb201801015
Liu H, Fang C, Miao Y, Ma H, Zhang Q, Zhou Q (2018b) Spatio-temporal evolution of population and urbanization in the countries along the Belt and Road 1950-2050. J Geogr Sci 28(7):919–936. https://doi.org/10.1007/s11442-018-1513-x
Lu D (2015) Function orientation and coordinating development of subregions within the Jing-Jin-Ji Urban Agglomeration. Prog Geogr 34(3):265–270. https://doi.org/10.11820/dlkxjz.2015.03.001
Meijers E, Burger M (2010) Spatial structure and productivity in US metropolitan areas. Environ Plan A 42:1383–1402. https://doi.org/10.1068/a42151
National Bureau of Statistics of China (2001-2017a) China statistical yearbook. China Statistics Press, Beijing
National Bureau of Statistics of China (2001-2017b) China urban statistical yearbook. China Statistics Press, Beijing
National Bureau of Statistics of China (2001-2017c) China Energy Statistical Yearbook. China Statistics Press, Beijing
Parrish D, Zhu T (2009) Clean air for megacities. Science 326(5953):674–675. https://doi.org/10.1126/science.1176064
Peng J, Chen S, Lü H, Liu Y, Wu J (2016) Spatiotemporal patterns of remotely sensed PM2.5 concentration in China from 1999 to 2011. Remote Sens Environ 174:109–121. https://doi.org/10.1016/j.rse.2015.12.008
Perry S (2013) Do urbanization and industrialization affect energy intensity in developing countries. Energy Econ 37:52–59. https://doi.org/10.1016/j.eneco.2013.01.009
Samet J, Chung Y (2018) Air quality, atmosphere, and health: the 10-year anniversary. Air Qual Atmos Health 11(1):1–2. https://doi.org/10.1007/s11869-017-0541-5
Samet J, Dominici F, Curriero F, Coursac I, Zeger S (2000) Fine particulate air pollution and mortality in 20 U.S. cities, 1987-1994. N Engl J Med 343(24):1742–1749. https://doi.org/10.1056/NEJM200012143432401
Shao S, Yang L, Yu M, Yu M (2011) Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009. Energy Policy 39:6476–6494. https://doi.org/10.1016/j.enpol.2011.07.049
Shao S, Zhang K, Dou J (2019) Effects of economic agglomeration on energy saving and emission reduction: theory and empirical evidence from China. Manag World (1):36–60. https://doi.org/10.19744/j.cnki.11-1235/f.2019.0005
Wagner U, Timmins C (2009) Agglomeration effects in foreign direct investment and the pollution haven hypothesis. Environ Resour Econ 43(2):231–256. https://doi.org/10.1007/s10640-008-9236-6
Wan Q, Chen Z, Wang Y, Feng B (2019) Spatio-temporal evolution of PM2.5 in the Yangtze River Economic Belt during 1998-2016 by multiscale analysis. Resour Environ Yangtze Basin 28(10):2504–2512. https://doi.org/10.11870/cjlyzyyhj201910022
Wang J, Xu C (2017) Geodetector: principle and prospective. Acta Geograph Sin 72(1):116–134. https://doi.org/10.11821/dlxb201701010
Wang D, Yang Q (2018) Rationality diagnosis and evolution characteristics of urban agglomeration scale structure in China. China Popul Resour Environ 28(9):123–132. https://doi.org/10.12062/cpre.20180415
Wang J, Li X, Christakos G, Liao Y, Zhang T, Gu X, Zheng X (2010) Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun region, China. Int J Geogr Inf Sci 24(1):107–127. https://doi.org/10.1080/13658810802443457
Wang H, Dwyer-Lindgren L, Lofgren K, Rajaratnam J, Marcus J, Levin-Rector A, Levitz C, Lopez A, Murray C (2012) Age specific and sex-specific mortality in 187 countries, 1970-2010: a systematic analysis for the global burden of disease study 2010. Lancet 380(9859):2071–2094. https://doi.org/10.1016/S0140-6736(12)61719-X
Wang Y, Ying Q, Hu J, Zhang H (2014) Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014. Environ Int 73:413–422. https://doi.org/10.1016/j.envint.2014.08.016
Wang Z, Liang L, Wang X (2019) Spatio-temporal evolution patterns and influencing factors of PM2.5 in Chinese urban agglomerations. Acta Geograph Sin 74(12):2614–2630. https://doi.org/10.11821/dlxb201912014
Xue M, Wang C, Zhao J, Li M (2020) Spatial differentiation pattern and influencing factors of tourism economy in the Yellow River Basin. Econ Geogr 40(4):19–27. https://doi.org/10.15957/j.cnki.jjdl.2020.04.003
Yuan X, Mu R, Zuo J (2015) Economic development, energy consumption, and air pollution: a critical assessment in China. Hum Ecol Risk Assess Int J 21(3):781–798. https://doi.org/10.1080/10807039.2014.932204
Zhang K, Wang D (2014) The interaction and spatial spillover between agglomeration and pollution. China Ind Econ (6):70–82. https://doi.org/10.19581/j.cnki.ciejournal.2014.06.007
Zheng B, Liang L, Li M (2019) Analysis of temporal and spatial patterns of PM2.5 in prefecture-level cities of China from 1998 to 2016. China Environ Sci 39(5):1909–1919. https://doi.org/10.19674/j.cnki.issn1000-6923.2019.0226
Zhou L, Zhou C, Yang F, Che L, Wang B, Sun D (2019) Spatio-temporal evolution and the influencing factors of PM2.5 in China between 2000 and 2015. J Geogr Sci 29(2):253–270. https://doi.org/10.1007/s11442-019-1595-0
Funding
This study was supported by National Natural Science Foundation of China (72004124) and the Key Projects of Social Science Planning in Shandong Province, China (20BJJJ06).
Author information
Authors and Affiliations
Contributions
Caihong Huang analyzed the influencing factors of PM2.5 concentrations. Kai Liu conceived and designed the research and was a major contributor in writing the manuscript. Liang Zhou analyzed and interpreted the data for PM2.5. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Clinical trial registration
Not applicable.
Additional information
Responsible Editor: Gerhard Lammel
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Highlights
• Spatio-temporal trends for PM2.5 concentrations were studied using the Exploratory Spatial Data Analysis method.
• Factors which influenced PM2.5 concentrations were examined using the Geodetector method.
• Temporal trends for the average PM2.5 concentrations followed an inverted U-shaped curve.
• PM2.5 concentrations exhibited significant global spatial autocorrelation, the main categories being the high–high and the low–low type categories.
• Main factors which influenced PM2.5 concentrations were the rate of land urbanization and the structure of energy consumption.
Supplementary Information
ESM 1
(DOCX 4963 kb)
Rights and permissions
About this article
Cite this article
Huang, C., Liu, K. & Zhou, L. Spatio-temporal trends and influencing factors of PM2.5 concentrations in urban agglomerations in China between 2000 and 2016. Environ Sci Pollut Res 28, 10988–11000 (2021). https://doi.org/10.1007/s11356-020-11357-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-020-11357-z