Log in

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China

  • Research
  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (France)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

Data can be made available from the corresponding author on reasonable request.

References

  • Anselin, L. (1988). Lagrange multiplier test diagnostics for spatial dependence and spatial heterogeneity. Geographical Analysis, 20(1), 1–17.

    Article  Google Scholar 

  • Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.

    Article  Google Scholar 

  • Cai, M., Gu, X., & Zhao, Z. Y. (2023). Characteristics of ozone concentration and relationships with meteorological factors in Yuncheng City from 2016 to 2021. Acta Scientiae Circumstantiae, 43(9), 229–243.

    CAS  Google Scholar 

  • Cao, T., Wang, H., Li, L., et al. (2024). Fast spreading of surface ozone in both temporal and spatial scale in Pearl River Delta. Journal of Environmental Sciences, 137, 540–552.

    Article  CAS  Google Scholar 

  • Carvalho, R. B., Marmett, B., Dorneles, G. P., da Silva, I. M., Romão, P. R. T., da Silva Júnior, F. M. R., & Rhoden, C. R. (2022). O3 concentration and duration of exposure are factors influencing the environmental health risk of exercising in Rio Grande, Brazil. Environmental Geochemistry and Health, 44(8), 2733–2742.

    Article  CAS  Google Scholar 

  • Chen, G., Liu, T., Chen, J., Xu, L., Hu, B., Yang, C., & Zhang, F. (2024). Atmospheric oxidation capacity and O3 formation in a coastal city of southeast China: Results from simulation based on four-season observation. Journal of Environmental Sciences, 136, 68–80.

    Article  CAS  Google Scholar 

  • Chen, J., Sun, L., Jia, H., Li, C., Ai, X., & Zang, S. (2022). Effects of seasonal variation on spatial and temporal distributions of ozone in Northeast China. International Journal of Environmental Research and Public Health, 19(23), 15862.

    Article  CAS  Google Scholar 

  • Chen, Z., Zhuang, Y., **e, X., Chen, D., Cheng, N., Yang, L., & Li, R. (2019). Understanding long-term variations of meteorological influences on ground ozone concentrations in Bei**g During 2006–2016. Environmental Pollution, 245, 29–37.

    Article  CAS  Google Scholar 

  • Cheng, Y., Dai, H., Zhang, Y., Qiao, L., Ma, Y., An, J., & Huang, C. (2023). Spatial and temporal distribution characteristic of ozone concentration and population health benefits in the Yangtze River Delta Region from 2017 to 2020. Environmental Science, 44(2), 719–729.

    Google Scholar 

  • Diao, B., Ding, L., Su, P., & Cheng, J. (2018). The spatial-temporal characteristics and influential factors of NOx emissions in China: A spatial econometric analysis. International Journal of Environmental Research and Public Health, 15(7), 1405.

    Article  Google Scholar 

  • Ding, L., & Fang, X. (2022). Spatial–temporal distribution of air-pollution-intensive industries and its social-economic driving mechanism in Zhejiang Province, China: A framework of spatial econometric analysis. Environment. Development and Sustainability, 24(2), 1681–1712.

    Article  Google Scholar 

  • Ding, Y., Zhang, M., Chen, S., Wang, W., & Nie, R. (2019). The environmental Kuznets curve for PM2.5 pollution in Bei**g-Tian**g-Hebei region of China: A spatial panel data approach. Journal of Cleaner Production, 220, 984–994.

    Article  CAS  Google Scholar 

  • Elhorst, J. P. (2014). Matlab software for spatial panels. International Regional Science Review, 37(3), 389–405.

    Article  Google Scholar 

  • Fabregat, A., Vázquez, L., & Vernet, A. (2021). Using machine learning to estimate the impact of ports and cruise ship traffic on urban air quality: The case of Barcelona. Environmental Modelling & Software, 139, 104995.

    Article  Google Scholar 

  • Gao, S., Bai, Z., Liang, S., Yu, H., Chen, L., Sun, Y., & Zhao, H. (2021a). Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model. Atmospheric Environment, 261, 118599.

    Article  CAS  Google Scholar 

  • Gao, Y., Wang, Z., Li, C. Y., Zheng, T., & Peng, Z. R. (2021b). Assessing neighborhood variations in ozone and PM2.5 concentrations using decision tree method. Building and Environment, 188, 107479.

    Article  Google Scholar 

  • Gauthier-Manuel, H., Bernard, N., Boilleaut, M., Giraudoux, P., Pujol, S., & Mauny, F. (2023). Spatialized temporal dynamics of daily ozone concentrations: Identification of the main spatial differences. Environment International, 173, 107859.

    Article  CAS  Google Scholar 

  • Gong, S., Liu, Y., He, J., Zhang, L., Lu, S., & Zhang, X. (2022a). Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 1: Synoptic circulation patterns and pollution. Science of The Total Environment, 815, 152770.

    Article  CAS  Google Scholar 

  • Gong, S., Zhang, L., Liu, C., Lu, S., Pan, W., & Zhang, Y. (2022b). Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 2. Key weather elements and emissions. Science of The Total Environment, 824, 153847.

    Article  CAS  Google Scholar 

  • Hu, J., Zhao, T., Liu, J., Cao, L., Wang, C., Li, Y., & Li, J. (2022). Exploring the ozone pollution over the western Sichuan Basin, Southwest China: The impact of diurnal change in mountain-plains solenoid. Science of the Total Environment, 839, 156264.

    Article  CAS  Google Scholar 

  • Iyke, B. N. (2024). Climate change, energy security risk, and clean energy investment. Energy Economics, 129, 107225.

    Article  Google Scholar 

  • **g, Q., Sheng, L., Zhang, W., & An, X. (2023). Characteristics of PM2.5 and O3 pollution and related meteorological impacts in ‘2+26’ cities of Bei**g-Tian**-Hebei and its surrounding areas from 2018 to 2021. Research of Environmental Sciences, 36(5), 875–886.

    CAS  Google Scholar 

  • Jung, M. C., Yost, M. G., Dannenberg, A. L., Dyson, K., & Alberti, M. (2024). Legacies of redlining lead to unequal cooling effects of urban tree canopy. Landscape and Urban Planning, 246, 105028.

    Article  Google Scholar 

  • Kang, Y., Choi, H., Im, J., Park, S., Shin, M., Song, C. K., & Kim, S. (2021). Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia. Environmental Pollution, 288, 117711.

    Article  CAS  Google Scholar 

  • LeSage, J. P., & Pace, R. K. (2009). Spatial econometric models. In Handbook of applied spatial analysis: Software tools, methods and applications (pp. 355–376). Berlin, Heidelberg: Springer Berlin Heidelberg.

  • Li, L., Wang, L., Liu, X., et al. (2020). Temporal and spatial distribution characteristics of ozone and its relationship with meteorological factors in Harbin. China Environmental Science, 40(5), 1991–1999.

    Google Scholar 

  • Li, W., Liu, W., & Lu, C. (2023). Analysis of spatial distribution and drivers of gaseous energy combustion pollution in China based on SDM. Environmental Geochemistry and Health, 45(11), 8565–8583.

    Article  CAS  Google Scholar 

  • Liu, H., Liu, S., Xue, B., Lv, Z., et al. (2018). Ground-level ozone pollution and its health impacts in China. Atmospheric Environment, 173, 223–230.

    Article  CAS  Google Scholar 

  • Liu, P., Song, H., Wang, T., Wang, F., Li, X., Miao, C., & Zhao, H. (2020). Effects of meteorological conditions and anthropogenic precursors on ground-level ozone concentrations in Chinese cities. Environmental Pollution, 262, 114366.

    Article  CAS  Google Scholar 

  • Livesley, S. J., McPherson, E. G., & Calfapietra, C. (2016). The urban forest and ecosystem services: Impacts on urban water, heat, and pollution cycles at the tree, street, and city scale. Journal of Environmental Quality, 45(1), 119–124.

    Article  CAS  Google Scholar 

  • Lu, K., Zhang, Y., Su, H., Shao, M., Zeng, L., Zhong, L., & Wahner, A. (2010). Regional ozone pollution and key controlling factors of photochemical ozone production in Pearl River Delta during summer time. Science China Chemistry, 53, 651–663.

    Article  CAS  Google Scholar 

  • Ma, P., Mao, H., Zhang, J., Yang, X., Zhao, S., Wang, Z., & Chen, C. (2022). Satellite monitoring of stratospheric ozone intrusion exceptional events—A typical case of China in 2019. Atmospheric Pollution Research, 13(2), 101297.

    Article  CAS  Google Scholar 

  • Malinović-Milićević, S., Vyklyuk, Y., Stanojević, G., Radovanović, M. M., Doljak, D., & Ćurčić, N. B. (2021). Prediction of tropospheric ozone concentration using artificial neural networks at traffic and background urban locations in Novi Sad, Serbia. Environmental Monitoring and Assessment, 193, 1–13.

    Article  Google Scholar 

  • Oancea, B., & Pirjol, D. (2019). Extremal properties of the Theil and Gini measures of inequality. Quality & Quantity, 53, 859–869.

    Article  Google Scholar 

  • Pan, W., Gong, S., Lu, K., Zhang, L., **e, S., Liu, Y., & Zhang, Y. (2023). Multi-scale analysis of the impacts of meteorology and emissions on PM2.5 and O3 trends at various regions in China from 2013 to 2020 3. Mechanism assessment of O3 trends by a model. Science of The Total Environment, 857, 159592.

    Article  CAS  Google Scholar 

  • Qi, G., Che, J., & Wang, Z. (2023). Differential effects of urbanization on air pollution: Evidences from six air pollutants in mainland China. Ecological Indicators, 146, 109924.

    Article  CAS  Google Scholar 

  • Qu, X., & Lee, L. F. (2015). Estimating a spatial autoregressive model with an endogenous spatial weight matrix. Journal of Econometrics, 184(2), 209–232.

    Article  Google Scholar 

  • Shan, W., Yin, Y., Zhang, J., Ji, X., & Deng, X. (2009). Surface ozone and meteorological condition in a single year at an urban site in central–eastern China. Environmental Monitoring and Assessment, 151, 127–141.

    Article  CAS  Google Scholar 

  • 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(10), 6476–6494.

    Article  Google Scholar 

  • Shao, S., Zhang, K., & Dou, J. (2019). Effects of economic agglomeration on energy saving and emission reduction: Theory and empirical evidence from China. Management World, 35(1), 36-60+226.

    Google Scholar 

  • Tang, X., Gao, X., Li, C., Zhou, Q., Ren, C., & Feng, Z. (2020). Study on spatiotemporal distribution of airborne ozone pollution in subtropical region considering socioeconomic driving impacts: A case study in Guangzhou, China. Sustainable Cities and Society, 54, 101989.

    Article  Google Scholar 

  • Theil, H. (1967). Economics and information theory. North Holland Publishing Co.

    Google Scholar 

  • Theil, H. (1972). Statistical decomposition analysis. North Holland Publishing Co.

    Google Scholar 

  • Vu, T. V., Shi, Z., Cheng, J., Zhang, Q., He, K., Wang, S., & Harrison, R. M. (2019). Assessing the impact of clean air action on air quality trends in Bei**g using a machine learning technique. Atmospheric Chemistry and Physics, 19(17), 11303–11314.

    Article  CAS  Google Scholar 

  • Wang, P., Guo, H., Hu, J., Kota, S. H., Ying, Q., & Zhang, H. (2019). Responses of PM2.5 and O3 concentrations to changes of meteorology and emissions in China. Science of the Total Environment, 662, 297–306.

    Article  CAS  Google Scholar 

  • Wang, X., Zhao, W., Li, L., Yang, X., Jiang, J., & Sun, S. (2020a). Characteristics of spatiotemporal distribution of O3 in China and impact analysis of socio-economic factors. Earth and Environment, 48(1), 66–75.

    CAS  Google Scholar 

  • Wang, Z. B., Li, J. X., & Liang, L. W. (2020b). Spatio-temporal evolution of ozone pollution and its influencing factors in the Bei**g-Tian**-Hebei urban agglomeration. Environmental Pollution, 256, 113419.

    Article  CAS  Google Scholar 

  • Wise, E. K., & Comrie, A. C. (2005). Extending the Kolmogorov-Zurbenko filter: Application to ozone, particulate matter, and meteorological trends. Journal of the Air & Waste Management Association, 55(8), 1208–1216.

    Article  CAS  Google Scholar 

  • **ng, J., Zheng, S., Ding, D., Kelly, J. T., Wang, S., Li, S., & Hao, J. (2020). Deep learning for prediction of the air quality response to emission changes. Environmental science & technology, 54(14), 8589–8600.

    Article  CAS  Google Scholar 

  • Yang, Z., Yang, J., Li, M., Chen, J., and Ou, C. Q. (2021). Nonlinear and lagged meteorological effects on daily levels of ambient PM2.5 and O3: Evidence from 284 Chinese cities. Journal of Cleaner Production, 278, 123931.

    Article  CAS  Google Scholar 

  • Yi, R., Wang, Y. L., Zhang, Y. J., Shi, Y., & Li, M. S. (2015). Pollution characteristics and influence factors of ozone in Yangtze River Delta. Acta Sci. Circumstantiae, 35(8), 2370–2377.

    CAS  Google Scholar 

  • York, R., Rosa, E. A., & Dietz, T. (2003). STIRPAT, IPAT and ImPACT: Analytic tools for unpacking the driving forces of environmental impacts. Ecological Economics, 46(3), 351–365.

    Article  Google Scholar 

  • Zhang, H. Y., Chen, J., & Wang, Z. (2021a). Spatial heterogeneity in spillover effect of air pollution on housing prices: Evidence from China. Cities, 113, 103145.

    Article  Google Scholar 

  • Zhang, J., Lei, R., Cui, S., et al. (2022). Spatiotemporal trends and impact factors of PM2.5 and O3 pollution in major cities in China during 2015–2020. Chinese Science Bulletin, 67, 2029–2042.

    Article  Google Scholar 

  • Zhang, Q., Ye, S., Ma, T., Fang, X., Shen, Y., and Ding, L. (2023). Influencing factors and trend prediction of PM2.5 concentration based on STRIPAT-scenario analysis in Zhejiang Province, China. Environment, Development and Sustainability, 25(12), 14411–14435.

    Article  Google Scholar 

  • Zhang, X., Yan, B., Du, C., Cheng, C., & Zhao, H. (2021b). Quantifying the interactive effects of meteorological, socioeconomic, and pollutant factors on summertime ozone pollution in China during the implementation of two important policies. Atmospheric Pollution Research, 12(12), 101248.

    Article  CAS  Google Scholar 

  • Zhang, Y. N., **ang, Y. R., Chan, L. Y., Chan, C. Y., Sang, X. F., Wang, R., & Fu, H. X. (2011). Procuring the regional urbanization and industrialization effect on ozone pollution in Pearl River Delta of Guangdong. China. Atmospheric Environment, 45(28), 4898–4906.

    Article  CAS  Google Scholar 

  • Zhao, C., & Wang, B. (2022). How does new-type urbanization affect air pollution? Empirical evidence based on spatial spillover effect and spatial Durbin model. Environment International, 165, 107304.

    Article  CAS  Google Scholar 

  • Zhou, M. W., Kang, P., Wang, K. K., Zhang, X. L., & Hu, C. Y. (2020). The spatio-temporal aggregation pattern of ozone concentration in China from 2016 to 2018. China Environmental Science, 40(5), 963–1974.

    Google Scholar 

  • Zhou, X., Zhang, X., Wang, Y., Chen, W., & Li, Q. (2023). Spatio-temporal variations and socio-economic drivers of air pollution: Evidence from 332 Chinese prefecture-level cities. Atmospheric Pollution Research, 14(6), 101782.

    Article  CAS  Google Scholar 

Download references

Funding

This work was supported by Soft Science Project of Zhejiang Science and Technology Department (2024C35096), 2023 Zhejiang College Domestic Visiting Engineer Program (Leader: Lei Ding), and the Major Humanities and Social Science Research Projects in Zhejiang Higher Education Institutions (Grant Number 2021GH047).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization and writing—original draft: Lei Ding, Lihong Wang, and Xuejuan Fang. Data collection, formal analysis, and investigation: Huihui **a, Beidi Diao, and Yidi Hua. Writing—review and editing: Qiong Zhang and Xuejuan Fang. Resources and supervision: Xuejuan Fang. Lei Ding and Lihong Wang contributed equally to this work. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Xuejuan Fang.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

All authors consent to participate in this research.

Consent for publication

All authors consent to publish this research.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 22.6 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, L., Wang, L., Fang, X. et al. Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China. Environ Monit Assess 196, 603 (2024). https://doi.org/10.1007/s10661-024-12762-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-024-12762-4

Keywords

Navigation