Understanding the relationship between land use/cover pattern and water quality could provide guidelines for non-point source pollution and facilitate sustainable development. The previous studies mainly relate the land use/cover of the entire region to the water quality at the monitoring sites, but the water quality at monitoring sites did not totally reflect the water environment of the entire basin. In this study, the land use/cover was monitored on Google Earth Engine in Tang-Pu Reservoir basin, China. In order to reflect the water quality of the whole study area, the spatial distribution of the determinants for water quality there, i.e., the total nitrogen and total phosphorus (TN&TP), were simulated by the Soil and Water Assessment Tool (SWAT). The redundancy analysis explored the correlations between land use/cover pattern and simulated TN&TP. The results showed that: (1) From 2009 to 2019, forest was the dominant land cover, and there was little land use/cover change. The landscape fragmentation increased, and the connectivity decreased. (2) About 25% TP concentrations and nearly all the TN concentrations at the monitoring points did not reach drinking water standard, which means nitrogen and phosphorus pollution were the most serious problems. The highest output per unit TN&TP simulated by SWAT were 44.50 kg/hm² and 9.51 kg/hm² and occurred in areas with highly fragile landscape patterns. (3) TN&TP correlated positively with cultivated and construction land but negatively with forest. The correlation between forest and TN&TP summited at 500–700-m buffer and construction land at 100-m buffer. As the buffer size increased, the correlation between the cultivated land, and the TN weakened, while the correlation with the TP increased. TN&TP correlated positively with the Shannon’s Diversity Index and negatively with the Contagion Index. This study provides a new perspective for exporting the impact of land use/cover pattern on water quality.

The extensive pattern of economic growth has an inestimable negative impact on the ecological environment, which causes the soil pollution problem to become increasingly prominent. In order to improve the effectiveness and rationality of prevention and control of heavy metal pollution in regional soil, it is necessary to understand the current situation of pollution, identify pollution sources and clarify future pollution risks. In this paper, an industrially developed city in eastern China was taken as the study region. The positive matrix factorization model (PMF) model and Unmix model was applied to identify and apportion the pollution sources of soil potential toxic elements after evaluating the ecological risk of soil potential toxic elements. The PMF model identified six factors, including single source and composite source. The Unmix model also identified six sources, including sources of nature, industrial discharge and traffic emissions. The comparison between the two models showed that Hg and Ni pollution, as well as Cr enrichment in the study region, were related to the industrial discharge from enterprises and factories. Cd pollution was related to traffic emission sources. Cu and Zn pollution were related to the multiple sources mixed with soil parent material, traffic emissions and industrial discharge from electronic enterprises. Pb pollution was related to natural sources (e.g., soil pH) but also to industrial sources (e.g., industrial wastes discharge). Enrichment was related to soil parent material and agricultural inputs. Our study also implies that soil heavy metal pollution or enrichment in the study region was mainly from anthropogenic sources and supplemented by natural sources.

The three-dimensional (3D) built environment encodes critical information about urban form intensity, environmental exposure, and resource consumption. However, previous studies have often overlooked the integration of long-term analyses of both horizontal expansion and vertical growth. This study aims to identify the spatial differentiation, morphology types, and vertical growth trajectories of major Chinese megacities over the past three decades. Using high-resolution GABLE building data and time-series GAIA impervious surface data, we examine the evolution of urban 3D morphology across six major Chinese megacities from 1991 to 2023 through a retrospective analysis of building construction years combined with spatial gradient analysis. The results reveal that although the megacities exhibit distinct differences in vertical structure, shape complexity, and spatial compactness, they share a consistent center-to-periphery gradient across most 3D indicators. The most active volumetric growth was concentrated in a zone 8–14 km from city centers, which accounted for 23.6% of total new development, whereas the inner core within 6 km contributed less than 2.68%. In terms of temporal dynamics, Beijing, Shanghai and Guangzhou follow an inverted-V-shaped 3D expansion trajectory driven by mid-rise construction; Tianjin and Hangzhou show accelerated growth with a higher proportion of high-rise clusters; while Shenzhen demonstrates an early peak and a decelerated growth rate, accompanied by a pronounced polycentric pattern. While recent global-scale studies have suggested a shift from outward urban sprawl to vertical development, our findings indicate that horizontal expansion still dominates in the selected Chinese megacities, with outward sprawl exceeding vertical densification during the study period. The integrated approach provides a robust framework for mapping 3D urbanization and offers practical insights for policymakers seeking to manage horizontal expansion, guide vertical intensification, and optimize land-use efficiency in rapidly urbanizing megacities.