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• W4308702932 endingPage "135122" @default.
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• W4308702932 abstract "In recent years, low-carbon sustainable development has attracted increasing attention worldwide. However, the spatiotemporal evolution of carbon balance and the impact of various urban development indicators are still uncertain, especially in the current scenario of climate change, rapid urbanization, and ecosystem degradation. This study proposes a flexible framework for analyzing the carbon balance and the factors that drive it. This framework is used to investigate the dynamics and heterogeneity of the regional carbon balance from the perspective of land use. New-type urbanization is introduced to explore the impacts of population, economic, spatial, and ecological urbanization on carbon emission using the PLS–STIRPAT model. The proposed method is applied to analyze the urban carbon balance in the Middle Reaches of the Yangtze River Urban Agglomeration (MRYRUA) in China. The results show that the MRYRUA was in a state of carbon deficit between 2000 and 2020, while the growth rate decreased significantly during 2005–2020. The urban carbon balance model can classify into five categories: the high carbon emissions–high carbon balance index (CBI), the high carbon emissions–low CBI, the medium carbon emissions–high CBI, the low carbon emissions–high CBI, and the low carbon emissions–low CBI. In addition, the indicators of ecological urbanization, population density, and road density in new-type urbanization were found to have a positive effect on curbing the growth in carbon emissions. In conclusion, this study provides appropriate guidelines for carbon reduction policies for cities and is valuable for achieving sustainable development goals." @default.
• W4308702932 created "2022-11-14" @default.
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• W4308702932 date "2022-12-01" @default.
• W4308702932 modified "2023-10-03" @default.
• W4308702932 title "Spatiotemporal evolution of urban carbon balance and its response to new-type urbanization: A case of the middle reaches of the Yangtze River Urban Agglomerations, China" @default.
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• W4308702932 doi "https://doi.org/10.1016/j.jclepro.2022.135122" @default.
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