Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China

Abstract

Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.

Sustainable Development Path of Resource-Based Cities—Taking Datong as an Example

“…For the calculation of the comprehensive capacity (Q) of sustainable development of resource-based cities in the target layer, the calculation method of equal weight is adopted to calculate the arithmetic average of the scores of the five subsystems [31][32][33]. This is consistent with the annual report on the Sustainable Development Goals issued by the United Nations Sustainable Development Solutions Network and the calculation methods indicated for the SDGs.…”

The Spatial and Temporal Evolution of the Coordination Degree in Regard to Farmland Transfer and Cultivated Land Green Utilization Efficiency in China

“…The pollution caused by cultivated land utilization refers mainly to the non-point source pollution during cultivated land use. Non-point source pollution is defined as the environment contamination induced by contaminants through surface runoff and underground infiltration, which is characterized by dispersion and concealment [ 48 ]. This is manifested as nitrogen and phosphorus loss in manure (10,000 tons), insecticide loss (10,000 tons) and agriculture film residue (10,000 tons).…”

“…Comprised of 34 provincial administrative units, China shows significant variations in cultivated land resources, grain yield and the levels of agriculture development between different provinces [ 48 , 56 ]. Given the insufficient data available for Hong Kong, Macau, Taiwan and Tibet, the sample used in the present study relates to 30 provinces in mainland China.…”

Improvement of Agricultural Supply Quality in China: Evidence from Jiangsu Province

“…Experts and scholars pointed out that China's grain production, inventory, and import are increasing, and strengthening the agricultural supply-side reform is proposed [7]. In 2015, the grain output reached 62.1435 million tons, which led to difficulties in domestic grain supply and marketing [3].…”

“…Again, five regional agriculture service centers have been established in Hai'an County since the year 2022 began, and these centers offer precise and focused services to unlock the effective management of agricultural technology services fully [5]. Every year, Jiangsu cultivates 50,000 scientific and technology demonstration entities and supports many eco-friendly, high-quality, and effective technologies [7]. Science and technology make up 70.9% of the province's agricultural advancement, strengthening the province to increase its added value of agriculture, forestry, animal husbandry, and fishing from 340 billion yuan to 507.4 billion yuan [3].…”