The digital economy is a new economic form that has a significant impact on urban land green use efficiency (ULGUE). With the provincial panel data between 2013 and 2021, this paper empirically tests how the digital economy development level (DEDL) promotes the improvement of ULFUE in China. The key findings include the following: (1) There were significant spatial differences for the ULGUE and DEDL of China. For China’s ULGUE, China shows an ascent after an initial decline trend from 2013 to 2017, but a decline trend after 2017. China’s DEDL took on a rising tendency during the research period. In 2021, China’s DEDL increased by 143.8% compared with that in 2013. (2) The digital economy can obviously promote the ULGUE, but the promotion effect is affected by the urbanization level; with improvements in urbanization level, the impact of that may strengthen. (3) Technological innovation demonstrates a complete intermediary effect between the digital economy and ULGUE; the mediation transmission mechanism of technological innovation is evident. These results have been verified by robustness tests, proving their stability and reliability. The research results will provide new insights into the high-quality utilization of urban land resources.

Farmland use transition (FUT) not only reshapes agricultural production systems but also significantly impacts cross-regional carbon sink transfers in the grain trade. However, comprehensive studies exploring connections between FUT and grain carbon sink transfer (GCST) are limited. We constructed an indicator system and transformation framework for FUT by considering dominant and recessive dimensions. Moreover, we estimate GCST based on grain supply–demand balance and fixed carbon coefficients. Fixed effects and threshold models are employed to identify both linear and nonlinear relationships between FUT and GCST. Results show that FUT significantly reshapes carbon sink flows. In terms of dominant FUT indicators, cultivation land rate (CLR) and grain planting area proportion (GPAP) positively drive GCST by expanding the carbon sink supply and exporting ecological services. Regarding recessive FUT indicators, both grain yield per unit area (GYield) and pesticide-fertilizer intensity (PFI) promote GCST, highlighting the role of efficiency and inputs, while rural per capita disposable income (RPCDI) suppresses GCST due to agricultural marginalization. A grain yield threshold of 2.092 t/ha is identified. Below this value, FUT exerts substantial positive effects on GCST. Above it, the effects weaken. This study explains the relationship between FUT and ecosystem carbon sinks, providing a scientific basis for advancing green agriculture in karst mountainous areas.

The black soil region of Northeast China is a key grain-production area where cropland water erosion threatens soil fertility and sustainability. We diagnosed cropland soil loss across six diagnostic years/time slices (2001, 2005, 2010, 2015, 2020, and 2024) using a Revised Universal Soil Loss Equation (RUSLE)-based remote-sensing workflow implemented in Google Earth Engine (GEE). Rainfall erosivity was derived from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily precipitation, soil erodibility from SoilGrids, topography from the Shuttle Radar Topography Mission digital elevation model (SRTM DEM), vegetation cover from the Landsat normalized difference vegetation index (NDVI), and cropland extent from ESA WorldCover; alternative rainfall sources, cropland masks, and P-factor settings were used for sensitivity analyses. Under the slope-graded P-factor scenario, mean annual soil loss ranged from 1.60 to 3.07 t ha⁻¹ yr⁻¹, and the proportion of cropland exceeding T = 2 t ha⁻¹ yr⁻¹ ranged from 25.2% to 52.9%. Soil loss fluctuated among years because rainfall erosivity and cover-management effects partly counteracted each other. Risk was concentrated in sloping piedmont and hilly cropland, whereas broad plains were dominated by very slight and slight erosion. P-factor parameterization represented the largest structural uncertainty. The workflow provides regional screening evidence for field verification and conservation-practice assessment, rather than direct site-specific engineering prescriptions.

Composite environmental risks accumulate unevenly along urban–rural gradients, yet the conditional and nonlinear interaction between built environment quality (BEQ) and urban–rural functional connectivity (URFC) remains poorly quantified at fine resolution. This study aims to determine whether, and under what conditions, BEQ moderates the relationship between URFC and a population-weighted composite risk index (CRI), and to translate the result into spatia targeted green-infrastructure priorities. We use 744,714 grid cells at 100 m resolution over Guangzhou, China. The framework couples entropy-weighted BEQ from satellite and street-view imagery, gravity-model URFC computed on the real road network, and a two-stage population-weighted CRI of heat and air hazards. We apply nested ordinary least squares with incremental F-tests, spatial-lag and spatial-error models, generalised additive models with B-spline bases, gradient-boosted trees with SHAP interaction values, and Baron–Kenny mediation analysis. The main BEQ × URFC estimates are negative across the parametric and machine-learning specifications. The interaction is, however, small: a spatial-lag model on a 10,000-cell subsample returns β = −5.4 × 10⁻⁴, but a scalable generalised-method-of-moments spatial regression on the full grid—where the spatial autoregressive coefficient reaches ρ ≈ 0.99—shows the coefficient to be negative yet not statistically significant, and a five-seed re-estimation confirms that the subsample-based significance is draw-dependent. We therefore interpret the buffering as directionally supported but small and not robustly significant once spatial autocorrelation is fully modelled. The buffering response is nonlinear in the GAM main effects, and BEQ buffers across the entire observed connectivity range rather than switching sign at an interior threshold; URFC functions predominantly as a moderator rather than a mediator. Population-stratified estimation shows that the buffering is exposure-conditional: it is strongest where population exposure is high and weakens or reverses in sparsely populated cells, consistent with the risk = hazard × exposure structure of CRI. Sensitivity tests across values of the distance-decay parameter, 100 entropy perturbations and spatial scales corroborate the buffering direction. The framework provides an evidentiary basis for prioritising green infrastructure in functionally connected, populated but environmentally degraded transition zones.

The transformation of land-border ports from transit channels into regional hubs is increasingly seen as a way to support inclusive growth in frontier regions. Yet port expansion does not automatically improve local livelihoods. Whether port-led development is associated with income gains for rural residents in border counties depends on how cross-jurisdictional public goods are supplied, coordinated, and absorbed. Drawing on collective-action theory and regional public-goods theory, this study develops a two-tier analytical framework that distinguishes regional synergy from county response. Using panel data for seven counties along the China–Vietnam border in Guangxi from 2008 to 2023 and supplementary field research, we apply two-way fixed-effects models, control-function checks, mediation tests, and port-size heterogeneity analysis. Three main findings emerge. First, regional synergy and county response, proxied by Region_BPEDI and Dev_BPEDI, are both positively associated with the logarithm of rural per-capita disposable income in border counties. A one-standard-deviation comparison shows that the estimated association of Region_BPEDI is about 2.5 times that of Dev_BPEDI. Second, industrial-structure upgrading shows the strongest mediating pattern, while infrastructure connectivity and financial development depend more on cross-tier coordination. Third, large ports such as Dongxing and Pingxiang are better positioned to benefit from regional synergy, whereas medium and small ports rely more on niche-based differentiation. The results suggest that hub-oriented border transformation may benefit from multi-level institutional collaboration, place-based industrial matching, and tailored financial instruments. Field evidence also indicates that smart customs clearance, low-carbon logistics, and cross-border environmental coordination are becoming important sustainability dimensions of regional synergy. The study provides a diagnostic framework for evaluating border-port reforms along the Belt and Road and ASEAN economic corridors.