Are the intensity of energy use, land agglomeration, CO2emissions, and economic progress dynamically interlinked across development levels?

Although urban agglomerations have introduced substantial contributions to the economies around the globe, it has also led to the serious environmental challenges. However, this situation may vary across the development levels. The existing knowledge offers a gap in terms of both theoretical and empirical grounds. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) is previously not known to incorporate land agglomeration and the intensity of energy use. Besides, the investigation of linkages among the variables of interest across the development levels within a country is not known to be considered by the existing knowledge. This study systematically investigates the heterogeneous dynamic causality among the intensity of energy use, land agglomeration, carbon dioxide emissions (CO2), and economic progress across the development levels in the Chinese economy, considering 29 provinces for the period 2000 to 2018. To this end, a long-term co-integration association is tested and found existent among the variables of interest. A dynamiccommon correlated effects mean group approachis applied for impact analysis. The key findings include: The impacts of economic progress and land agglomeration on CO(2)are found positive and significant in the country panel and western zone of China (WZC). It turned to be neutral in the case of the central zone of China (CZC) and significantly negative in the eastern zone of China (EZC). To this end, economic progress presented a 'development ladder-based CO(2)mitigation effect,' while the land agglomeration exposed the 'land agglomeration ladder-based CO(2)mitigation effect'. Further, the causalities extracted are: first, economic progress is found in positive bilateral linkages with the intensity of energy use and land agglomeration for all the panels. Second, a positive and unilateral causal bridge is found operating from land agglomeration to the intensity of energy use and from the intensity of energy use to CO2. Third, a unilateral linkage of mixed nature is exposed to exist from land agglomeration to CO2, with positive causal links for country panel and WZC, negative causal links for EZC, while a neutral linkage is found for CZC. Fourth, a bidirectional link with mixed causalities appeared in the country panel and WZC. Economic progress increased CO(2)in WZC. Next, a negative bilateral link is observed between the two variables in EZC. Additionally, this link remained neutral in CZC. Based on empirics, it is revealed that the development level matters in determining the links among the variables of interest.