Study on Driving Factors and Spatial Effects of Environmental Pollution in the Pearl River-Xijiang River Economic Belt, China

Research on the Evaluation and Spatial Characteristics of China's Provincial Socioeconomic Development and Pollution Control Based on the Lotka-Volterra Model

AIMS

To evaluate the degree of mutualism between socioeconomic development and industrial and domestic pollution in provinces of China and to analyze the differences in spatial characteristics between their regions.

METHODS

This study used the HDI to measure socioeconomic development and the Lotka-Volterra model to group and estimate the force-on and mutualism degree indexes of industrial and domestic pollution and socioeconomic development in 31 provinces of China, which were then used to them. Then, the study calculated the global and local Moran's I under different space weights matrices to analyze their spatial autocorrelation and heterogeneity.

RESULTS

The research showed that in 2016-2020, compared with 2011-2015, the number of provinces where socioeconomic development and industrial pollution control mutually promoted each other was approximately the same, while the number of provinces that promoted each other's effectiveness with domestic pollution control was reduced. There were many provinces with industrial pollution ranked in the S-level, while most provinces placed a different emphasis on industrial and domestic pollution control. The rank in China tended to be spatially balanced in 2016-2020. There was a negative spatial autocorrelation between the ranks of most provinces and neighboring provinces in 2011-2020. The ranks of some eastern provinces showed a phenomenon of a high-high agglomeration, while the ranks of provinces in the western region were dominated by a high-low agglomeration.

Spatio-Temporal Variation and Decomposition Analysis of Livelihood Resilience of Rural Residents in China

The key to sustainable rural development and coordinated regional development is to properly measure the livelihood resilience of rural residents (LRRR), and investigate its regional differences, distribution characteristics, and evolutionary patterns. This study combined the entropy method, the Dagum Gini coefficient and decomposition, kernel density estimation, and convergence analysis to measure the LRRR in 30 provinces of China from 2006 to 2020, and to analyze its regional differences and sources, dynamic distribution, and characteristics of convergence. The LRRR in China overall declined 2006-2020, with an east-to-west spatial gradient toward lower livelihood resilience. Intra-regional differences in LRRR narrowed in the Eastern and Central Regions, while those in the Western Region widened. Inter-regional differences were the main source of differences in LRRR. The LRRRs in most provinces in China were gradually reaching the same level over time (i.e., σ convergence and β convergence). This research provides a factual reference for policies related to reducing inter-provincial differences in the LRRR in China.