Impact of the intensive use of urban construction land on carbon emission efficiency: evidence from the urban agglomeration in the middle reaches of the Yangtze River.

Urban construction land, as the main carrier of socioeconomic activities, is also a land type that is associated with large carbon emissions. This study uses statistical data of the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) from 2006 to 2020 to examine the mechanism of the intensive use of urban construction land (IUUCL) on carbon emission efficiency (CEE) from the perspective of urban land resource utilization. The study shows that the capital-intensive and technology-intensive use of urban construction land can significantly increase CEE, while increased labor and energy intensification inhibits CEE. In addition, there is regional heterogeneity in the effect of the IUUCL on CEE. The external control factor industrial structure has the most obvious inhibiting effect on the CEE of the Wuhan urban circle, the intensive use of energy has become the crucial constraint on the carbon emission reduction of the city cluster around Poyang Lake, and the intensive use of science and technology is the key factor in realizing the green and low-carbon development of the Chang-Zhu-Tan city cluster. This study innovatively constructs a theoretical framework of IUUCL versus CEE and conducts a heterogeneous study on the CEE of intensive use of construction land from the perspective of urban agglomerations. By providing a better understanding of the intrinsic influence mechanism of both these processes, this study provides a new perspective for reducing carbon emissions.

Spatiotemporal heterogeneity and decoupling decomposition of industrial carbon emissions in the Yangtze River Delta urban agglomeration of China.

The objective of this study is to identify the spatiotemporal change law and the leading factors of industrial carbon emission decoupling. Based on the industrial carbon emission level of the Yangtze River Delta urban agglomeration (YRDUA) from 2006 to 2020, the spatiotemporal heterogeneity was explored with the help of the spatial Markov chain, the Tapio decoupling model was used to analyze its decoupling state from the industrial economy, and its driving factors were decomposed using the Kaya identity and logarithmic mean Divisia index (LMDI) model. The results show that (1) in 51.9% of the YRDUA's cities, the industrial carbon emission situation was stable, the emission reduction observation area (medium carbon) occupied a dominant position, and the emission reduction key area (relatively high carbon) gradually decreased. (2) Industrial carbon emissions had spatial overflow and path dependency characteristics, and the probability of carbon emission type transfer maintaining the original state reached 80.0%. From 2006 to 2011, the average probability of the downward migration of high-carbon cities was 5.0%. From 2011 to 2020, the average probability of the upward transfer of low-carbon cities was 9.4%. (3) The negative decoupling rate of carbon emissions in the YRDUA experienced a transition from 3.7% to 44.4% and then back to 7.4%, showing spatial imbalance. Unsatisfactory decoupling cities were concentrated along the Yangtze River and in coastal areas. (4) The promoting efficiency of energy intensity, carbon emission coefficient, and employment structure was gradually strengthened, and the carbon-increasing effect of labor input was gradually weakened. (5) The decoupling mode of heavy difficult cities is dominated by the three-factor balanced type, which is jointly affected by industrial production, labor input, and carbon emission coefficient. The findings in this study can provide inspiration for industrial carbon emission reduction in megalopolises.

Spatiotemporal dynamics and decoupling mechanism of economic growth and carbon emissions in an urban agglomeration of China.

Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan's single-core to Wuhan and Changsha's dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010-2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow.