The distribution of heavy metal pollution in cultivated land is closely related to the quality of the cultivated land. In this study, 533 soil samples were collected from cultivated land in the Yangtze River delta region in China for Cd, Pb, and Hg analyses. Spatial statistical analysis was used to study the heavy metal pollution in the cultivated land, and the driving forces of heavy metal distribution in different cultivated land quality subdivisions were analyzed with GeogDetector. The conclusions are as follows: (1) Among the three heavy metals in the study area, the coefficient of variation of Cd is the largest, and that of Pb is the smallest. The proportion of Cd and Hg exceeding the standard value (the standard of level two in GB 15618—2018) is relatively large, both of which are 5%; (2) From the perspective of the spatial distribution of soil heavy metal pollution, only four counties (CX, HN, WY, and LH) were free of heavy metal pollution. Soil heavy metal pollution in AJ, SY, QJ, and DS counties is relatively serious, and the pollution may come from agricultural activities, manufacturing, and prevalent coastal shipping industries in these counties; (3) The heavy metal pollution levels of cultivated land with different quality levels are different. The high-quality cultivated land has no high contamination, while the medium and the general cultivated land both have high contamination. High contamination is related to Cd for medium and general cultivated lands, and to Hg in only general cultivated land; (4) The main driving factors of heavy metal concentration in cultivated soil were GDP, followed by soil organic matter, and pH. These results indicate that the spatial distribution of heavy metal concentration in cultivated soil was affected by the level of economic development, followed by the ecological environment, indicating that human activities had a critical impact on the ecological environment of cultivated land.

This paper attempts to reveal the impact and mechanisms of digital inclusive finance (DIF) on agricultural carbon emission performance (ACEP). Specifically, based on the provincial panel data in China from 2011 to 2020, a super slacks-based measure (Super SBM) model is applied to measure ACEP. The panel regression model and spatial regression model are used to empirically analyze the impact of DIF on ACEP and its mechanism. The results show that: (1) during the study period, China’s ACEP exhibited a continuous growth trend, and began to accelerate after 2017. The high-value agglomeration areas of ACEP shifted from the Huang-Huai-Hai plain and the Pearl River Delta to the coastal regions and the Yellow River basin, the provincial differences displayed an increasing trend from 2011 to 2020. (2) DIF was found to have a significant positive impact on ACEP. The main manifestation is that the development of the coverage breadth and depth of use of DIF helps to improve the ACEP. (3) The positive impact of DIF on ACEP had a significant spatial spillover effect, that is, it had a positive effect on the improvement of ACEP in the surrounding provinces. These empirical results can help policymakers better understand the contribution of DIF to low-carbon agriculture, and provide them with valuable information for the formulation of supportive policies.

Exploring the spatial heterogeneity of urban multi-dimensional networks and influencing factors are of great significance for the integrated development of metropolitan circle. This study took Hangzhou metropolitan circle as an example, using multi-source geospatial big data to obtain urban population, transportation, goods, capital, and information flow information among sub-cities. Then, spatial visualization analysis, social network analysis, and geographical detector were applied to analyze the differences in spatial structure of multiple urban networks and influencing factors in Hangzhou metropolitan circle, respectively. The results showed that (1) the network connections of population, traffic, goods, and capital flows transcended geographical proximity except that of information flow, and population and traffic flow networks were found to be more flattened in Hangzhou metropolitan circle than in other urban networks; (2) the comprehensive urban network of Hangzhou metropolitan circle was imbalanced across sub-cities, presenting hierarchical and unipolar characteristics; and (3) the influence of traffic distance on the network spatial structure of Hangzhou metropolitan was stronger than the geographical distance, and the interactions between traffic distance and socioeconomic factors would further enhance the regional differentiation of the network spatial structure. This study could provide scientific reference for constructing a coordinated and integrated development pattern in a metropolitan circle.