Abstract
Addressing global uneven urban development and the urgent need to reduce carbon emissions (CE), this study presents a new method for calculating urban socioeconomic development indexes using a variety of data sources. Using the Yangtze River Delta as an example, we categorize urban areas into core, transitional, and peripheral cities. With the help of extended Kaya-index decomposition models, we evaluate the effects of regional industrial growth, consumer markets, and spatial expansion on urban CE. The research explores differences in CE drivers across and within these city categories. Our findings reveal that in core cities, 31.5 % of CE is due to the industrial structure and 14.9 % due to population density. In transitional cities, CE increases by 60.22 % primarily due to industrial structure and consumer consumption. Peripheral cities, on the other hand, have a complex set of causes for CE, with per capita living, spatial expansion, population size, urbanization, and consumption limitation contributing to 91.97 %, 10.73 %, 14.2 %, 9.34 %, and 24.92 % of CE respectively. Varied factors influence CE intensity differences within each city group. Cleaner production technologies and potential carbon reductions in consumption and industry are identified as key strategies for compensating CE reduction. We propose the adoption of carbon function zoning in urban clusters to leverage the role of carbon function in each area. Territorial spatial planning should ensure a balanced layout of production, living, and ecological functions. Residents' consumption, being the key factor driving CE, must transition toward green, low-carbon consumption, reinforced by societal norms and responsibilities. This research provides valuable theoretical and practical insights into urban classification and CE reduction strategies.
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