Kai Chen

As a primary energy consumer and carbon emitter, the construction industry (CI) faces a growing conflict between traditional energy-intensive growth models and global sustainable development goals. To promote the sustainable development of the CI, this study establishes a sequential analytical framework following the logic of “coupling evaluation–driving force identification–causal inference” across 30 developed economies (DE) from 2000 to 2022. Initially, the coupling coordination degree (CCD) between the economic and environmental systems of the CI was evaluated, utilizing the Environmental Kuznets Curve (EKC) to characterize the transition from relative to absolute decoupling. The results show that the economy and the environment in the construction industry (CEECI) for DE is generally high (0.70–0.90). Subsequently, based on Green Innovation Growth (GIG) theory, Panel Data Analysis (PDA) is employed to identify the key drivers of the coupling between the economy and CEECI. The results show that for every 1% increase in per capita GDP, CEECI increases by approximately 0.035; for every 1% increase in science and technology investment (ST Inv), CEECI increases by 0.045; and for every 1 unit increase in building energy use (BEU), CEECI decreases by 0.008. Furthermore, Granger causality analysis (GCA) was used to examine the bidirectional predictive relationship. Furthermore, there is a two-way correlation between GDP and CEECI, and a one-way correlation between CEECI and ST Inv. Overall, our results show that further decoupling requires innovation, not just economic growth; therefore, the CI should optimize its industrial structure, prioritize technological innovation, strengthen lifecycle energy management, and promote coordinated global CI improvement.

Green infrastructure (GI) effectively mitigates health effects associated with PM _2.5 and urban heat. However, the impact of GI's morphological characteristics on compound exposure remains unclear. With a large urban population, Chinese cities face significant compound exposure risks, yet national‐scale GI planning strategies addressing this issue are lacking. This study incorporates 374 Chinese cities, quantifying and mapping the spatial distribution and changes of four spatial morphological structures of GI, seasonal PM _2.5 pollution, and summer daytime and nighttime land surface temperature over the past 20 years. Results indicate that core areas are larger and have expanded significantly, failing to effectively mitigate compound exposure risks. Although connectors represent a smaller scale of GI, they play a significant and positive role in mitigating compound exposure risk, especially when their proportion exceeds 2% of urban space. We suggest that urban planners prioritize connectivity‐oriented GI strategies to effectively mitigate compound exposure risks.

Urban green infrastructure (UGI) is critical for mitigating fine particulate matter (PM _2.5 ) pollution, a major obstacle to sustainable urban development. However, the morphological spatial patterns of UGI and their impact on PM _2.5 remain largely unexplored, as most related studies have focused solely on case studies. This study employed morphological spatial pattern analysis to document the national scale spatial distribution of seven UGI morphology space patterns (MSPs) across 288 Chinese cities. It verified the disparities of each MSP under varying geographic conditions and scalar categories. Using advanced interpretable machine learning methods that account for aggregated contribution of location features, the study confirmed the positive role of UGI proportion in mitigating PM _2.5 levels. Significantly, the findings revealed that smaller non‐core UGI areas, such as perforation and islet, exert a more pronounced positive impact on reducing PM _2.5 . Furthermore, the study explored the potential PM _2.5 risks facing Chinese cities due to temporal changes of UGI. The study results not only fill the gap in UGI research, but also contributes a feasible urban planning method and provide a basis for reducing PM _2.5 to promote sustainable urban development.