Integration of land ecological consolidation and ecosystem product value realization: A case from the Yangtze riverside industrial park in Changzhou, China.

Traditional industries and industrialization have led to widespread environmental pollution and ecosystem degradation in major river basins globally. Strategies centered on ecological restoration and ecological economy are emerging as essential tools for effective environmental governance. This study aims to investigate how a multifaceted framework for land ecological consolidation, with various developmental goals, can effectively support ecological restoration and sustainability. Through quantitative analysis and in-depth interviews, we investigated the case of Yangtze riverside chemical industrial park in Changzhou. This park pursues ecological and economic sustainability through chemical industry transformation, ecological restoration and protection, ecological management, and ecological industry development. The results show that this practice established a multi-objective action framework rooted in urban renewal, land consolidation, ecological restoration, industrial transformation, and rural revitalization. Through multiplanning integration, integrated implementation and full-cycle profit distribution, the aim of ecological protection has been initially achieved, offering a crucial guarantee for sustainable development. A total of 96.47 ha ecological space expanded, which can generate ecological product worth CNY 7.283 billion, alongside a net economic benefit of CNY 978 million over three decades. The top-down ecological responsibilities, coupled with local developmental demands, have stimulated collaborations within a bottom-up endogenous network comprising government, enterprises, and residents.

[Application of the LUR Model in the Prediction of Spatial Distributions of Soil Heavy Metals].

Using the Jintan District of Changzhou City, Jiangsu Province as an example, the LUR model was used to study the spatial distribution of heavy metals and to simulate the spatial distribution of heavy metals in the study area. Compared with the traditional LUR model and the ordinary Kriging interpolation model, the following conclusions were obtained. ① The soil heavy metal content in the study area was highly and significantly correlated with land factors, with the main factor of land use and influencing factors of heavy metals in the soil environment (P<0.01). In terms of influencing factors, the soil Cu and Zn contents were significantly correlated with the area related to traffic in a 2000 m buffer area and 2000 m buffer zone, respectively. The soil Cr, Cu, and Zn contents were significantly correlated with OM, Corg, TC, and TN (P<0.01). ② The R2 of the LUR-S models of the spatial distribution of the heavy metals, Pb, Cr, Cu, and Zn, in the study area were improved by 0.041, 0.406, 0.102, and 0.501, respectively, compared with the traditional LUR model. The accuracy test R2 values were improved by 0.1477, 0.0116, 0.2310, and 0.081, respectively; and the RMSE was reduced by 2.413, 0.631, 1.112, and 2.138, respectively. It was shown that the LUR-S model, which considered the source-sink relationship, had a higher accuracy than the traditional LUR model and ordinary Kriging interpolation model. ③ The LUR-S model was more suitable for the prediction of the spatial distribution of heavy metals with lower pollution and smaller variations, while results for the prediction of the heavy metals with higher pollution and larger variations were worse.