Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

Abstract

The urban agglomerations in the middle reaches of the Yangtze River (MYR-UA) are facing a severe challenge in reducing carbon emissions while maintaining stable economic growth and prioritizing ecological protection. The energy consumption related to land urbanization makes an important contribution to the increase in carbon emissions. In this study, an IPAT/Kaya identity model is used to understand how land urbanization affected carbon emissions in Wuhan, Changsha, and Nanchang, the three major cities in the middle reaches of the Yangtze River, from 2000 to 2017. Following the core idea of the Kaya identity model, sources of carbon emissions are decomposed into eight factors: urban expansion, economic level, industrialization, population structure, land use, population density, energy intensity, and carbon emission intensity. Furthermore, using the Logarithmic Mean Divisia Index (LMDI), we analyze how the different time periods and time series driving forces, especially land urbanization, affect regional carbon emissions. The results indicate that the total area of construction land and the total carbon emissions increased from 2000 to 2017, whereas the growth in carbon emissions decreased later in the period. Energy intensity is the biggest factor in restraining carbon emissions, followed by population density. Urban expansion is more significant than economic growth in promoting carbon emissions, especially in Nanchang. In contrast, the carbon emission intensity has little influence on carbon emissions. Changes in population structure, industrial level, and land use vary regionally and temporally over the different time period.

The Impact of Rationalization and Upgrading of Industrial Structure on Carbon Emissions in the Beijing-Tianjin-Hebei Urban Agglomeration

“…The rationalization of industrial structure refers to the aggregation quality between industries, reflects the coordination degree and sufficient utilization degree of resources between industries, and measures the coupling degree of factor input structure and output structure. This paper refers to the research results of Gan (2011) and Zhang (2018), who used the Theil index to calculate the industry rationalization index [30,31]. Theil index represents regional economic disparity, and the value is proportional to the degree of distinction.…”

Evaluation of the Effects of Urbanization on Carbon Emissions: The Transformative Role of Government Effectiveness

“…For instance, Zhou et al (2019) suggested a Kuznets curve relationship between economic urbanization and carbon emissions, and they also claimed that energy consumption related to land urbanization greatly contributes to the increase in carbon emissions. Besides, urban expansion is more significant than economic growth in promoting carbon emissions (Zhang et al, 2021). Population and gross regional domestic product (GRDP) are positively correlated with carbon emissions, and the entire built-up and urban road areas are positively correlated with carbon emissions (Pu et al, 2020;Zhang et al, 2022).…”

Impact of technological innovation and industrial‐structure upgrades on ecological efficiency in China in terms of spatial spillover and the threshold effect

“…The leading and emerging industries with high‐tech as the core will further improve resource utilization efficiency, thus changing the overall structure of social resource use. An improved resource utilization rate and an emerging environmental pollution control technology will further reduce the environmental impact and thus improve ecological efficiency (Zhang and Cui 2018). The rationalization of industrial structure refers to the process of pursuing moderate industrial scale and a balanced growth rate.…”