Does emission trading system improve the urban land green use efficiency? Empirical evidence from Chinese cities
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature..
Maximizing socioeconomic and environmental benefits with minimal investment in urban land resources is a key concern for sustainable urban development. The emission trading system is an important strategy of the Chinese government to control environmental pollution and promote green development, but whether it improves urban land green use efficiency is still unclear. Combining the concept of green development with urban land use efficiency, this paper uses the super-efficiency slack-based measure (SBM) model with undesirable outputs to measure the land green use efficiency of 261 prefecture-level cities in China from 2003 to 2017. In addition, the propensity score matching difference-in-differences (PSM-DID) method and the mediating effect model were used to test the impact of the China's emission trading system on urban land green use efficiency and behind the mechanism. According to the findings, China's emission trading system has significantly improved urban land green use efficiency, compared with that in nonpilot cities, urban land green use efficiency in pilot cities has increased by 10.40%. Moreover, the policy effect of the emission trading system is more significant in resource-based cities and cities with a high intensity of environmental regulations. Further mechanism analysis reveals that green technology innovation and industrial structure upgrading are effective transmission mechanisms for China's emissions trading policy to improve urban land green use efficiency. The findings provide policy implications for promoting the sustainable use of urban land resources and advancing the coordinated development of urban socioeconomic and ecological environments.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
Environmental science and pollution research international - 30(2023), 58 vom: 26. Dez., Seite 121666-121683 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wen, Limin [VerfasserIn] |
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| Links: |
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| Themen: |
7440-44-0 |
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Date Completed 21.12.2023 Date Revised 27.12.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1007/s11356-023-30678-3 |
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| 520 | |a Maximizing socioeconomic and environmental benefits with minimal investment in urban land resources is a key concern for sustainable urban development. The emission trading system is an important strategy of the Chinese government to control environmental pollution and promote green development, but whether it improves urban land green use efficiency is still unclear. Combining the concept of green development with urban land use efficiency, this paper uses the super-efficiency slack-based measure (SBM) model with undesirable outputs to measure the land green use efficiency of 261 prefecture-level cities in China from 2003 to 2017. In addition, the propensity score matching difference-in-differences (PSM-DID) method and the mediating effect model were used to test the impact of the China's emission trading system on urban land green use efficiency and behind the mechanism. According to the findings, China's emission trading system has significantly improved urban land green use efficiency, compared with that in nonpilot cities, urban land green use efficiency in pilot cities has increased by 10.40%. Moreover, the policy effect of the emission trading system is more significant in resource-based cities and cities with a high intensity of environmental regulations. Further mechanism analysis reveals that green technology innovation and industrial structure upgrading are effective transmission mechanisms for China's emissions trading policy to improve urban land green use efficiency. The findings provide policy implications for promoting the sustainable use of urban land resources and advancing the coordinated development of urban socioeconomic and ecological environments | ||
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