Research article Special Issues

The impact of population agglomeration on ecological resilience: Evidence from China

  • Received: 14 June 2023 Revised: 16 July 2023 Accepted: 24 July 2023 Published: 01 August 2023
  • Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.

    Citation: Qingsheng Zhu, Changwen Xie, Jia-Bao Liu. The impact of population agglomeration on ecological resilience: Evidence from China[J]. Mathematical Biosciences and Engineering, 2023, 20(9): 15898-15917. doi: 10.3934/mbe.2023708

    Related Papers:

  • Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.



    加载中


    [1] R. Bhattacharyya, Green finance for energy transition, climate action and sustainable development: overview of concepts, applications, implementation and challenges, Green Finance, 4 (2022), 1–35. https://doi.org/10.3934/GF.2022001 doi: 10.3934/GF.2022001
    [2] L. Khalid, I. Hanif, F. Rasul, How are urbanization, energy consumption and globalization influencing the environmental quality of the G-7, Green Finance, 4 (2022), 231–252. https://doi.org/10.3934/GF.2022011 doi: 10.3934/GF.2022011
    [3] C. S. Holling, Resilience and stability of ecological systems, Annu. Rev. Ecol. Syst., 4 (1973), 1–23. https://doi.org/10.1146/annurev.es.04.110173.000245 doi: 10.1146/annurev.es.04.110173.000245
    [4] F. Brand, Critical natural capital revisited: Ecological resilience and sustainable development, Ecol. Econ., 68 (2009), 605–612. https://doi.org/10.1016/j.ecolecon.2008.09.013 doi: 10.1016/j.ecolecon.2008.09.013
    [5] C. Folke, Resilience: The emergence of a perspective for social-ecological systems analyses, Global Environ. Change, 16 (2006), 253–267. https://doi.org/https://doi.org/10.1016/j.gloenvcha.2006.04.002 doi: 10.1016/j.gloenvcha.2006.04.002
    [6] L. Duo, Y. Li, M. Zhang, Y. Zhao, Z. Wu, D. Zhao, Spatiotemporal pattern evolution of urban ecosystem resilience based on "resistance-adaptation-vitality": A case study of Nanchang City, Front. Earth Sci., 10 (2022), 902444. https://doi.org/10.3389/feart.2022.902444 doi: 10.3389/feart.2022.902444
    [7] C. Shi, X. Zhu, H. Wu, Z. Li, Assessment of urban ecological resilience and its influencing factors: A case study of the Beijing-Tianjin-Hebei Urban Agglomeration of China, Land, 11 (2022), 921. https://doi.org/10.3390/land11060921 doi: 10.3390/land11060921
    [8] R. Zhao, C. Fang, H. Liu, X. Liu, Evaluating urban ecosystem resilience using the DPSIR framework and the ENA model: A case study of 35 cities in China, Sustainable Cities Soc., 72 (2021), 102997. https://doi.org/10.1016/j.scs.2021.102997 doi: 10.1016/j.scs.2021.102997
    [9] Y. Yi, J. Qi, D. Chen, Impact of population agglomeration in big cities on carbon emissions, Environ. Sci. Pollut. Res., 29 (2022), 86692–86706. https://doi.org/10.1007/s11356-022-21722-9 doi: 10.1007/s11356-022-21722-9
    [10] Y. Yan, J. Huang, The role of population agglomeration played in China's carbon intensity: A city-level analysis, Energy Econ., 114 (2022), 106276. https://doi.org/10.1016/j.eneco.2022.106276 doi: 10.1016/j.eneco.2022.106276
    [11] X. Yu, Z. Wu, H. Zheng, M. Li, T. Tan, How urban agglomeration improve the emission efficiency? A spatial econometric analysis of the Yangtze River Delta urban agglomeration in China, J. Environ. Manage., 260 (2020), 110061. https://doi.org/10.1016/j.jenvman.2019.110061 doi: 10.1016/j.jenvman.2019.110061
    [12] T. Huang, Y. Yu, Y. Wei, H. Wang, W. Huang, X. Chen, Spatial-seasonal characteristics and critical impact factors of PM2.5 concentration in the Beijing-Tianjin-Hebei urban agglomeration, PLoS One, 13 (2018), e0201364. https://doi.org/10.1371/journal.pone.0201364 doi: 10.1371/journal.pone.0201364
    [13] S. Malik, A. Iqbal, A. Imran, M. Usman, M. Nadeem, S. Asif, A. Bokhari, Impact of economic capabilities and population agglomeration on PM2.5 emission: empirical evidence from sub-Saharan African countries, Environ. Sci. Pollut. Res., 28 (2021), 34017–34026. https://doi.org/10.1007/s11356-020-10907-9 doi: 10.1007/s11356-020-10907-9
    [14] X. Liu, B. Zou, H. Feng, N. Liu, H. Zhang, Anthropogenic factors of PM2.5 distributions in China's major urban agglomerations: A spatial-temporal analysis, J. Clean. Prod., 264 (2020), 121709. https://doi.org/10.1016/j.jclepro.2020.121709 doi: 10.1016/j.jclepro.2020.121709
    [15] X. Li, M. Zhou, W. Zhang, K. Yu, X. Meng, Study on the mechanism of haze pollution affected by urban population agglomeration, Atmosphere, 13 (2022), 278. https://doi.org/10.3390/atmos13020278 doi: 10.3390/atmos13020278
    [16] H. Zhao, X. Cao, T. Ma, A spatial econometric empirical research on the impact of industrial agglomeration on haze pollution in China, Air Qual. Atmos. Health, 13 (2020) 1305–1312. https://doi.org/10.1007/s11869-020-00884-w doi: 10.1007/s11869-020-00884-w
    [17] R. Ohlan, The impact of population density, energy consumption, economic growth and trade openness on CO2 emissions in India, Nat. Hazards, 79 (2015), 1409–1428. https://doi.org/10.1007/s11069-015-1898-0 doi: 10.1007/s11069-015-1898-0
    [18] C. I. P. Martínez, W. H. A. Piña, S. F. Moreno, Prevention, mitigation and adaptation to climate change from perspectives of urban population in an emerging economy, J. Clean. Prod., 178 (2018), 314–324. https://doi.org/10.1016/j.jclepro.2017.12.246 doi: 10.1016/j.jclepro.2017.12.246
    [19] M. Chen, S. Guo, M. Hu, X. Zhang, The spatiotemporal evolution of population exposure to PM2.5 within the Beijing-Tianjin-Hebei urban agglomeration, China, J. Clean. Prod., 265 (2020), 121708. https://doi.org/10.1016/j.jclepro.2020.121708 doi: 10.1016/j.jclepro.2020.121708
    [20] X. Zeng, H. Xiang, Y. Xue, Y. Su, Y. Tong, Z. Mao, A scenario-based optimization frame to adjust current strategy for population-economy-resource-environment harmony in an urban agglomeration, China, Sustain. Cities Soc., 67 (2021), 102710. https://doi.org/10.1016/j.scs.2021.102710 doi: 10.1016/j.scs.2021.102710
    [21] F. Wang, W. Fan, J. Liu, G. Wang, The effect of urbanization and spatial agglomeration on carbon emissions in urban agglomeration, Environ. Sci. Pollut. Res., 27 (2020), 24329–24341. https://doi.org/10.1007/s11356-020-08597-4 doi: 10.1007/s11356-020-08597-4
    [22] Z. Xiao, H. Li, L. Sun, Does population and industrial agglomeration exacerbate China's pollution, J. Environ. Plann. Man., 65 (2022), 2696–2718. https://doi.org/10.1080/09640568.2021.1978059 doi: 10.1080/09640568.2021.1978059
    [23] X. Guo, M. Deng, X. Wang, X. Yang, Population agglomeration in Chinese cities: is it benefit or damage for the quality of economic development, Environ. Sci. Pollut. Res., 2023 (2023), 1–13. https://doi.org/10.1007/s11356-023-25220-4 doi: 10.1007/s11356-023-25220-4
    [24] M. A. Cole, E. Neumayer, Examining the impact of demographic factors on air pollution, Popul. Environ., 26 (2004), 5–21. https://doi.org/10.1023/B:POEN.0000039950.85422.eb doi: 10.1023/B:POEN.0000039950.85422.eb
    [25] S. Hankey, J. D. Marshall, Impacts of urban form on future US passenger-vehicle greenhouse gas emissions, Energy Policy, 38 (2010), 4880–4887. https://doi.org/10.1016/j.enpol.2009.07.005 doi: 10.1016/j.enpol.2009.07.005
    [26] B. Yang, L. Ding, Y. Tian, The influence of population agglomeration on air pollution: An empirical study based on the mediating effect model, IOP Conf. Ser.: Earth Environ. Sci., 687 (2021), 012014. https://doi.org/10.1088/1755-1315/687/1/012014 doi: 10.1088/1755-1315/687/1/012014
    [27] Y. Hao, S. Zheng, M. Zhao, H. Wu, Y. Guo, Y. Li, Reexamining the relationships among urbanization, industrial structure, and environmental pollution in China—New evidence using the dynamic threshold panel model, Energy Rep., 6 (2020), 28–39. https://doi.org/10.1016/j.egyr.2019.11.029 doi: 10.1016/j.egyr.2019.11.029
    [28] Z. Khan, M. Shahbaz, M. Ahmad, F. Rabbi, S. Yang, Total retail goods consumption, industry structure, urban population growth and pollution intensity: an application of panel data analysis for China, Environ. Sci. Pollut. Res., 26 (2019), 32224–32242. https://doi.org/10.1007/s11356-019-06326-0 doi: 10.1007/s11356-019-06326-0
    [29] Y. Hao, J. Song, Z. Shen, Does industrial agglomeration affect the regional environment? Evidence from Chinese cities, Environ. Sci. Pollut. Res., 29 (2022), 7811–7826. https://doi.org/10.1007/s11356-021-16023-6 doi: 10.1007/s11356-021-16023-6
    [30] K. Khan, C. W. Su, Urbanization and carbon emissions: a panel threshold analysis, Environ. Sci. Pollut. Res., 28 (2021), 26073–26081. https://doi.org/10.1007/s11356-021-12443-6 doi: 10.1007/s11356-021-12443-6
    [31] J. Jiang, X. Zhang, C. Huang, Influence of population agglomeration on urban economic resilience in China, Sustainability, 14 (2022), 10407. https://doi.org/10.3390/su141610407 doi: 10.3390/su141610407
    [32] T. Gan, H. Yang, W. Liang, X. Liao, Do economic development and population agglomeration inevitably aggravate haze pollution in China? New evidence from spatial econometric analysis, Environ. Sci. Pollut. Res., 28 (2021), 5063–5079. https://doi.org/10.1007/s11356-020-10847-4 doi: 10.1007/s11356-020-10847-4
    [33] X. You, Y. Sun, J. Liu, Evolution and analysis of urban resilience and its influencing factors: a case study of Jiangsu Province, China, Nat. Hazards, 113 (2022), 1751–1782. https://doi.org/10.1007/s11069-022-05368-x doi: 10.1007/s11069-022-05368-x
    [34] Y. Chen, M. Zhu, Q. Zhou, Y. Qiao, Research on spatiotemporal differentiation and influence mechanism of urban resilience in China based on MGWR model, Int. J. Environ. Res. Public Health, 18 (2021), 1056. https://doi.org/10.3390/ijerph18031056 doi: 10.3390/ijerph18031056
    [35] Q. Liu, S. Wang, W. Zhang, J. Li, G. Dong, The effect of natural and anthropogenic factors on PM2.5: Empirical evidence from Chinese cities with different income levels, Sci. Total Environ., 653 (2019), 157–167. https://doi.org/10.1016/j.scitotenv.2018.10.367 doi: 10.1016/j.scitotenv.2018.10.367
    [36] Z. Xu, Y. Yin, Regional development quality of Yangtze River Delta: From the perspective of urban population agglomeration and ecological efficiency coordination, Sustainability, 13 (2021), 12818. https://doi.org/10.3390/su132212818 doi: 10.3390/su132212818
    [37] Q. Hu, X. Wang, M. Xu, Are there heterogeneous impacts of social support on subjective well-being, Natl. Account. Rev., 3 (2021), 360–376. https://doi.org/10.3934/NAR.2021019 doi: 10.3934/NAR.2021019
    [38] J. Zhu, Z. Li, Can digital financial inclusion effectively stimulate technological Innovation of agricultural enterprises?—A case study on China, Natl. Account. Rev., 3 (2021), 398–421. https://doi.org/10.3934/NAR.2021021 doi: 10.3934/NAR.2021021
    [39] Y. Yao, D. Hu, C. Yang, Y. Tan, The impact and mechanism of fintech on green total factor productivity, Green Finance, 3 (2021), 198–221. https://doi.org/10.3934/GF.2021011 doi: 10.3934/GF.2021011
    [40] O. Osabuohien-Irabor, I. M. Drapkin, FDI Escapism: the effect of home country risks on outbound investment in the global economy, Quant. Finance Econ., 6 (2022), 113–137. https://doi.org/10.3934/QFE.2022005 doi: 10.3934/QFE.2022005
    [41] F. Morina, S. Grima, The impact of pension fund assets on economic growth in transition countries, emerging economies, and developed countries, Quant. Finance Econ., 6 (2022), 459–504. https://doi.org/10.3934/QFE.2022020 doi: 10.3934/QFE.2022020
    [42] X. Xu, P. Hou, Y. Liu, The impact of heterogeneous environmental regulations on the technology innovation of urban green energy: a study based on the panel threshold model, Green Finance, 4 (2022), 115–136. https://doi.org/10.3934/GF.2022006 doi: 10.3934/GF.2022006
    [43] B. E. Hansen, Threshold effects in non-dynamic panels: Estimation, testing, and inference, J. Econom., 93 (1999), 345–368. https://doi.org/10.1016/S0304-4076(99)00025-1 doi: 10.1016/S0304-4076(99)00025-1
    [44] C. Zhao, B. Wang, How does new-type urbanization affect air pollution? Empirical evidence based on spatial spillover effect and spatial Durbin model, Environ Int., 165 (2022), 107304. https://doi.org/10.1016/j.envint.2022.107304 doi: 10.1016/j.envint.2022.107304
    [45] Y. Chen, S. Shao, M. Fan, Z. Tian, L. Yang, One man's loss is another's gain: does clean energy development reduce CO2 emissions in China? Evidence based on the spatial Durbin model, Energy Econ., 107 (2022), 105852. https://doi.org/10.1016/j.eneco.2022.105852 doi: 10.1016/j.eneco.2022.105852
    [46] L. Gao, Q. Tian, F. Meng, The impact of green finance on industrial reasonability in China: empirical research based on the spatial panel Durbin model, Environ. Sci. Pollut. Res., 30 (2023), 61394–61410. https://doi.org/10.1007/s11356-022-18732-y doi: 10.1007/s11356-022-18732-y
    [47] Q. Zhu, C. Xie, J. B. Liu, On the impact of the digital economy on urban resilience based on a spatial Durbin model, AIMS Math., 8 (2023), 12239–12256. https://doi.org/10.3934/math.2023617 doi: 10.3934/math.2023617
    [48] J. B. Liu, X. B. Peng, J. Zhao, Analyzing the spatial association of household consumption carbon emission structure based on social network, J. Comb. Optim., 45 (2023), 79. https://doi.org/10.1007/s10878-023-01004-x doi: 10.1007/s10878-023-01004-x
  • mbe-20-09-708-supplementary.xlsx
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1617) PDF downloads(209) Cited by(9)

Article outline

Figures and Tables

Figures(3)  /  Tables(13)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog