4.7 Article

How does the marginal abatement cost of CO2 emissions evolve in Chinese cities? An analysis fromthe perspective of urban agglomerations

Journal

SUSTAINABLE PRODUCTION AND CONSUMPTION
Volume 32, Issue -, Pages 147-159

Publisher

ELSEVIER
DOI: 10.1016/j.spc.2022.04.013

Keywords

CO2 emissions; Marginal abatement cost; Urban agglomerations; Dagum Gini coefficient; Convergence trend

Funding

  1. Chinese National Funding of Social Sciences [19ZDA082]

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Reducing the cost of carbon emissions reduction is crucial for the low-carbon development of urban agglomerations. This study investigates the dynamic characteristics of the marginal abatement cost (MAC) of CO2 emissions in China's major urban agglomerations. The results show a U-shaped relationship between carbon emission intensity and MAC, with narrowing differences in MAC within most urban agglomerations. The study suggests exploring technology spillover and scale effect to lower the costs of emissions reduction and promote low-carbon development.
Lowering the cost of reducing carbon emissions is of great significance for the low-carbon development of urban agglomerations. This study aims to investigate the dynamic characteristics of the marginal abatement cost (MAC) of CO2 emissions (measured by its shadow price) in China's eight major urban agglomerations. Based on the data from 135 cities from 2003 to 2018, this study uses a dual model of nonparametric linear programming to calculate the shadow price of CO2 emissions, which is used to measure the MAC and estimate the marginal abatement cost curve (MACC). Subsequently, it uses the Dagum Gini coefficient to examine the regional differences in the MAC and corresponding sources and uses the spatial convergence model to examine the convergence trend of the MAC within and between urban agglomerations. The results reveal a U-shaped relationship between carbon emission intensity and the MAC, and the MAC increases gradually with the decrease in carbon intensity. Barring the Beijing-Tianjin-Hebei region, differences in the MAC within other urban agglomerations are narrowing, and the regional difference is the main source of the overall difference. The convergence analysis suggests that the MACs of the eight urban agglomerations as a whole and within each urban agglomeration are changing toward their respective steady-state levels, and spatial correlation is one of the reasons for the convergence within some urban agglomerations. Finally, it is recommended that the technology spillover and scale effect of the agglomeration economy should be explored fully to lower the costs of emissions reduction and promote the low-carbon development of urban agglomerations. (C) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

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