City managers need to understand how land use and land cover (LULC) change in an urban landscape can affect future land degradation and conditions for ecosystem services (ESs) supply and demand. Optimal land use and land management requires explicit spatial mapping of ESs supply and demand under alternative land use scenarios. In this study, we applied spatially explicit models to predict changes in ESs supply and demand, and their coupling mechanisms, under one baseline scenario and three stakeholder-defined LULC change scenarios (developed, planning, policy) in Shanghai municipality, China. The results suggest that the policy scenario could significantly increase ESs supply and restore degraded urban areas, but would not guarantee that supply meets demand for four key ESs tested: water retention, particulate matter removal, carbon sequestration, and recreation. However, the policy scenario significantly reduced the shortfalls and spatial mismatches in water retention, particulate matter removal and recreation services, and also greatly restored deficit areas for all four ESs. This is valuable scientific evidence that ESs supply and demand information can be incorporated into urban land management planning in a spatially explicit manner, in order to control or prevent future potential land degradation.

The complex correlation between regions caused by the externality of air pollution increases the difficulty of its governance. Therefore, analysis of the spatio-temporal network of air pollution (STN-AP) holds great significance for the cross-regional coordinated governance of air pollution. Although the spatio-temporal distribution of air pollution has been analyzed, the structural characteristics of the STN-AP still need to be clarified. The STN-AP in the Yangtze River Delta urban agglomeration (YRDUA) is constructed based on the improved gravity model and is visualized by UCINET with data from 2012 to 2019. Then, its overall-individual-clustering characteristics are analyzed through social network analysis (SNA) method. The results show that the STN-AP in the YRDUA was overall stable, and the correlation level gradually improved. The centrality of every individual city is different in the STN-AP, which reveals the different state of their interactive mechanism. The STN-AP could be subdivided into the receptive block, overflow block, bidirectional block and intermediary block. Shanghai, Suzhou, Hangzhou and Wuxi could be key cities with an all above degree centrality, betweenness centrality and closeness centrality and located in the overflow block of the STN-AP. This showed that these cities had a greater impact on the STN-AP and caused a more pronounced air pollution spillovers. The influencing factors of the spatial correlation of air pollution are further determined through the quadratic assignment procedure (QAP) method. Among all factors, geographical proximity has the strongest impact and deserves to be paid attention in order to prevent the cross-regional overflow of air pollution. Furthermore, several suggestions are proposed to promote coordinated governance of air pollution in the YRDUA.