Abstract
The phenomenon of urban shrinkage is currently occurring worldwide; however, the “growth-oriented” planning paradigm is not suitable for these shrinking cities. Reconsidering the relationship between urban form and PM2.5 concentrations from the perspective of urban shrinkage can help provide a research reference for controlling air pollution and optimizing the spatial layout of shrinking cities. This study takes shrinking areas in China as the research subject, which are divided into four research groups according to their shrinkage degree. The empirical results indicate that the average PM2.5 concentrations decrease with the aggravation of urban shrinkage. In terms of the effect of urban form on PM2.5 concentrations, the urban size is always positively related to PM2.5 concentrations, while the impact of urban fragmentation on PM2.5 concentrations is negligible. Further, urban shape positively affects PM2.5 concentrations only in moderately and severely shrinking cities. Cities with sprawling urban forms have higher PM2.5 concentrations, except for those facing severe shrinking trends. This study suggests that governments in shrinking cities should reasonably adjust both the urban form and land use to improve air quality based on the degree of urban shrinkage.
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This work was supported by the Fundamental Research Funds for the Central Universities (Grant No. 2020CDJSK03ZH05) and the Graduate Research and Innovation Foundation of Chongqing, China (Grant No. CYB22039).
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Jianing Sun: conceptualization, methodology, data curation, software, validation, visualization, and writing—original draft.
Tao Zhou: conceptualization; formal analysis; writing—review and editing; and supervision.
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Appendix
Appendix
Appendix 1. Descriptive statistics
Metrics and units | Slightly shrinking group (n = 379) | Mildly shrinking group (n = 340) | |||||||
Mean | St. dev | Min | Max | Mean | St. dev | Min | Max | ||
Dependent variable | PM2.5 (μg·m–3) | 34.0 | 16.0 | 1.9 | 68.0 | 33.4 | 15.4 | 2.7 | 67.2 |
Independent variables | PLAND | 4.424 | 12.577 | 0.008 | 100 | 4.976 | 17.552 | 0.003 | 100.000 |
NP | 2.541 | 2.391 | 1 | 19 | 2.476 | 2.592 | 1 | 23 | |
LSI | 1.868 | 0.682 | 1.000 | 4.904 | 1.763 | 0.673 | 1.000 | 4.737 | |
CONTAG | 46.167 | 12.336 | 0.000 | 77.152 | 46.681 | 13.567 | 0.000 | 84.997 | |
Control variables | GDP (million yuan) | 287.961 | 548.193 | 9.859 | 7369.100 | 220.738 | 227.032 | 6.646 | 1847.760 |
POPD (people·km2) | 848.949 | 2522.337 | 0.331 | 23,858.000 | 1182.705 | 4517.659 | 1.411 | 32,105.330 | |
TEMP (℃) | 15.4 | 4.7 | 1.6 | 25.4 | 15.0 | 4.6 | 1.7 | 25.4 | |
WIND (m·s–1) | 2.5 | 0.4 | 1.6 | 3.8 | 2.5 | 0.4 | 1.6 | 3.6 | |
Moderately shrinking group (n = 470) | Severely shrinking group (n = 241) | ||||||||
Mean | St. dev | Min | Max | Mean | St. dev | Min | Max | ||
Dependent variable | PM2.5 (μg·m–3) | 30.3 | 13.2 | 4.2 | 72.5 | 24.3 | 12.8 | 3.1 | 61.1 |
Independent variables | PLAND | 3.174 | 12.603 | 0.005 | 100.000 | 3.504 | 12.989 | 0.0078 | 100.000 |
NP | 2.456 | 2.265 | 1 | 18 | 2.680 | 2.116 | 1 | 13 | |
LSI | 1.743 | 0.626 | 1.000 | 4.429 | 1.903 | 0.692 | 1.000 | 4.556 | |
CONTAG | 45.980 | 12.610 | 0.000 | 79.067 | 50.361 | 14.091 | 0.000 | 83.739 | |
Control variables | GDP (million yuan) | 187.300 | 302.518 | 3.725 | 4692.300 | 128.693 | 206.143 | 6.800 | 2727.100 |
POPD (people·km2) | 824.386 | 3982.138 | 0.429 | 45,087.890 | 592.689 | 2727.146 | 1.901 | 28,052.160 | |
TEMP (℃) | 13.5 | 4.9 | − 1.1 | 24.0 | 8.9 | 5.4 | − 2.5 | 22.2 | |
WIND (m·s–1) | 2.5 | 0.4 | 1.1 | 4.9 | 2.7 | 0.4 | 1.7 | 3.5 | |
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Sun, J., Zhou, T. Reconsidering the effects of urban form on PM2.5 concentrations: an urban shrinkage perspective. Environ Sci Pollut Res 30, 38550–38565 (2023). https://doi.org/10.1007/s11356-022-25044-8
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DOI: https://doi.org/10.1007/s11356-022-25044-8