Spatial-temporal variation and driving forces of the synergy of “pollution reduction, carbon reduction, green expansion and economic growth”: evidence from 243 cities in China - Hu, Chiqun; Ma, Xiaoyu; Yang, Lan; Chang, Xiaona; Li, Qiangyi (Frontiers in Ecology and Evolution, 2023)
Introduction Pollution reduction, carbon reduction, green expansion and economic growth—the synergistic effects of the four—have become essential in maintaining urban ecological security and promoting a green and low-carbon transition. And it is inherently consistent with the globally accepted concept of sustainable development. Methods Based on the evaluation index system and the coupling mechanism of the four, we adopt the entropy method and the coupling coordination model to measure the synergistic level of “pollution reduction, carbon reduction, green expansion and economic growth” in 243 cities above prefecture level in China from 2005 to 2020. Furthermore, the study examined the temporal and spatial evolution and regional differences by utilizing the center of gravity-standard deviation ellipse, Dagum Gini coefficient method, Kernel density estimation, and Markov chain. In addition, the spatial econometric model was used to analyze the driving factors affecting the synergistic development. Results The results show that the overall synergistic level is rising, the spatial distribution characteristics of “high in the east and low in the west.” The standard deviation ellipse shows a “northeast–southwest” pattern, and the center of gravity moves in a “southeast–northwest–southwest” migration trend. Regional differences are mainly rooted in inter-regional differences. The intra-regional differences are East > West > Central, with the most prominent East–West inter-regional differences. Without considering the spatial factor, the synergistic level shows a steady increase and has continuity. Under the spatial condition, the synergistic level has a positive spatial correlation. However, the positive spatial correlation decreases significantly as the years go by. Also, the probability of “rank locking” of synergistic development has been reduced, and there is a leapfrog shift. In terms of driving factors, the innovation level, level of external openness, population size, and industrial structure positively drive synergistic development. While government intervention negatively affects synergistic development. Discussions Based on the above findings,policy recommendations are proposed to strengthen the top-level design and build a policy system, play the radiation linkage, apply precise policies according to local conditions, and optimize the industrial structure fully. Which is of great significance for improving the urban ecological resilience and helping to achieve the “double carbon” target.