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Challenges to social, economic, and environmental sustainability are global in scale, yet sustainable development policies must be implemented locally. There has been a tendency for sustainable urbanism projects to engage in the conspicuous sustainability of spatially bounded and highly visible sustainability achievements, rather than spatially expansive, long-term achievements. China's complex system of multilevel governance encourages policy experimentation, but it is also frequently productive of entrepreneurial urbanism and intercity competition. This paper analyses spatial planning documents concerning Hengqin (Zhuhai Municipality, Guangdong Province), an island adjacent to Macao SAR, to show how the ambitions for a new-build district's contributions to sustainable development have become more spatially expansive and ambitious over time. This has occurred alongside changes in project leadership (from city, to provincial, to central government leadership) as well as a deepening awareness of the Greater Bay Area as a region for crossborder policymaking. The paper argues that crossborder perspectives are vital for genuine sustainable development but face certain obstacles in relation to the sites at which policy decisions are made. • Policymakers often prefer conspicuous sustainability to long-term achievements. • Innovative urban entrepreneurialism is common in China's multilevel governance. • Hengqin's spatial planning initially prioritised immediate, localised results. • Centralised leadership and regional awareness can raise sustainability ambitions. • Crossborder perspectives better reflect sustainable development needs. [ABSTRACT FROM AUTHOR]

Carbon lock-in has become a major obstacle to green development in all countries, and carbon unlocking (CUL) is of great significance in accelerating the process of carbon neutrality worldwide. Based on the panel data of 292 prefecture-level cities in China from 2006 to 2020, this paper constructs a PSM-DID model based on machine learning to empirically test the impact of LCCP policy on urban CUL. The regression result shows that the low carbon city pilot (LCCP) policy significantly increases the level of CUL by 1.25 % in the pilot cities, which is still valid after range of robustness tests, and the mechanism analysis shows that green innovation and green habits are important ways for the policy to affect CUL. Based on the generalized random forest (GRF) algorithm, we further find that the policy can increase the CUL level by 0.6 %, and the average treatment effect (ATE) of the sample is concentrated between 0.004 and 0.006, which exhibits obvious heterogeneity. This paper chooses population quality, openness level and industrial structure as heterogeneous factors, which are finally found to have a U-shaped or inverted U-shaped relationship with ATE. This study provides useful insights for China and other countries to break the carbon lock-in and realize green development. • Low-carbon city pilot policy can effectively promote urban carbon unlocking. • Causal forest model is used for causal inference based on generalized random forests algorithm. • The propensity score is calculated by machine learning. • Generalized random forest is used for heterogeneity analysis. • Low-carbon city pilot policy transmits policy effects through green innovation and green habits. [ABSTRACT FROM AUTHOR]