Trade-offs among productive-living-ecological lands for facilitating low-carbon and efficient cities: evidences in 30 major Chinese cities from 2015 to 2020

ABSTRACT

Low-carbon and efficient city, a sustainable city development mode, requires the land to carry more people and economy, but cause no ecological damage, which is essentially a trade-off among diverse land functional zones (LFZs), e.g. living, productive, and ecological lands, from a land system perspective. Unfortunately, there is little knowledge about how to trade off LFZs for building low-carbon and efficient cities. To fill the gap, the study first proposes a fine-grained LFZ mapping method to sort the land into seven kinds of LFZs based on multimodal geographic data; then, the study defines carbon efficiency (CE) as a reference to evaluate efficient cities considering their economics, society, and ecology; finally, the study presents a cross lasso regression method to explore how LFZ patterns as well as their temporal changes influence CE, based on which LFZ features are optimized at both national and city levels for improving CE and facilitating efficient cities. The proposed methods are verified in 30 major Chinese cities from 2015 to 2020. The experimental results indicate that the 30 cities have different LFZ patterns in area proportion, morphology, and temporal change, where LFZ proportions are master control factors to CE; and LFZ feature trade-off at national level works better than per city, as it can improve CE by 58.5% compared to that in 2020, which increases population carrying capacity by 88.5% and economy producing capacity by 81.0% with no change in carbon emission, or reduces carbon emission by 55.2% by keeping population and economy constant. These findings directly contribute to low-carbon and efficient city planning, and facilitating sustainable city development.

KEYWORDS:

• Land functional zone
• trade-off
• carbon efficiency
• low-carbon and efficient cities

Acknowledgments

The work presented in this paper is funded by the National Key Research and Development Program of China (No. 2022YFF1301102) and the National Natural Science Foundation of China (No. 42001327 and 42271469).

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

Data openly available in a public repository that does not issue DOIs. The data that support the findings of this study are openly available at http://geoscape.pku.edu.cn/en.html.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [42271469]; National Key Research and Development Program of China [2022YFF1301102]; National Natural Science Foundation of China [42001327].