Zhang Na, Sun Fang-Cheng, Hu Yu-Ling, Tang Jing
Research Center for Economy of Upper Reaches of the Yangtze River, Chongqing Technology and Business University, Chongqing 400067, China.
School of Economics, Lanzhou University, Lanzhou 730000, China.
Huan Jing Ke Xue. 2024 Aug 8;45(8):4656-4669. doi: 10.13227/j.hjkx.202309059.
It is of great significance to explore the regional differences of land use carbon emission (LUCE) in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt (Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration) from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that: ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute convergence and also had conditional convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.
探索长江经济带土地利用碳排放(LUCE)的区域差异及区域可持续发展的协同减排路径具有重要意义。基于LUCE估算方法,本研究科学计算了2010—2020年长江经济带三大城市群(长江三角洲、长江中游和成渝城市群)的LUCE。运用核密度估计和空间收敛模型研究LUCE的动态演变、区域差异和收敛特征。结果表明:① 与耕地和建设用地的碳排放相比,林地、水域、草地和未利用地的碳吸收量相对较小。建设用地碳排放逐渐增加,而四个碳汇的碳吸收量在研究期内波动较小。② 不同城市群的核密度曲线呈现出不同的分布格局、扩展性和极化特征,但总体趋于平衡。③ 2010—2020年,长江经济带整体LUCE呈现先增加后减少、东高西低的时空特征。三大城市群中心城市的LUCE一直处于最高水平,经济发展水平与生态环境之间尚未建立稳定的耦合机制。④ 长江经济带三大城市群的LUCE均存在绝对收敛,在经济发展水平、城市化水平、产业结构、人口密度和环境规制等模型控制变量下也存在条件收敛,且各区域的条件收敛速度大于绝对收敛速度。长江三角洲城市群的收敛速度最慢。上述结论为长江经济带三大城市群的协同减排路径提供了支撑,也有利于积极稳步推进碳达峰、碳中和目标的实现。