Measurement Of Agricultural Ecological Efficiency In China Based On Carbon Emissions And Sinks And Analysis Of Its Influencing Factors

The rapid development of agricultural economy has brought a series of ecological and environmental problems,such as resource shortage,declining cultivated land quality and environmental pollution,which seriously threaten the sustainable development of agriculture.Based on the current situation,the China Municipal Government has placed the environmental problems of agricultural development in a prominent position in national governance,put forward new requirements for green agricultural development,and made accelerating the establishment of a green and low-carbon circular agricultural industrial system as the major strategic decision-making focus of implementing the central peak carbon dioxide emissions and carbon neutrality in the agricultural field.In view of the strong demand of reducing emissions and increasing foreign exchange in agriculture and the special functional characteristics of agriculture,it is of great significance to take agricultural carbon sink as expected ecological output and agricultural carbon emission as unexpected output into the accounting system of agricultural ecological efficiency,consider the dual effects of agricultural production on the environment,and truly and accurately understand the current level of agricultural green development in China,so as to realize the low-carbon,green and sustainable development of China’s agricultural economy.Based on the provincial macro data of agricultural production in China from 2000 to 2020,this paper analyzes the agricultural ecological efficiency and its influencing factors.Firstly,the related research literature at home and abroad is sorted out,and the concept of agricultural ecological efficiency is defined and related theories are sorted out.Secondly,the current agricultural carbon emissions and carbon sinks in China’s provinces are calculated and analyzed in time and space to understand the current ecological environment of agricultural production in China.Then,the global super-efficiency EBM model is used to measure the agricultural ecological efficiency and its decomposition efficiency,and the evolution trend of its temporal and spatial characteristics is analyzed.At the same time,the spatial correlation of agricultural ecological efficiency is analyzed by spatial autocorrelation to explore its global and local spatial distribution characteristics.Finally,Tobit model is used to explore the influencing factors of regional agricultural ecological efficiency,and seven key variables are selected according to resource endowment,natural environment and economic development level,and a model is constructed to test the influencing factors.The main conclusions of this paper are as follows:(1)The total agricultural carbon emissions fluctuated and then decreased,reaching the peak in 2015;The total amount of agricultural carbon sinks shows a steady increase;The regional ranking of agricultural carbon emissions is not consistent with that of agricultural carbon sinks,and the areas with carbon emissions lower than that of carbon sinks are mostly concentrated in major grain producing areas and a few areas with excellent ecological environment.(2)The agricultural ecological efficiency with carbon sink effect is higher than that without carbon sink effect,and the power source of agricultural ecological efficiency mainly comes from pure technical efficiency.The development trend of the two kinds of agricultural ecological efficiency shows a downwardsteadily increasing trend,and the efficiency distribution has obvious spatial differences.The areas where the agricultural ecological efficiency with carbon sink effect is lower than that without carbon sink effect are mainly concentrated in some major grain producing areas and some areas with poor natural environment conditions,which shows that the carbon sink effect in these areas has less effect on improving agricultural ecological efficiency than the areas with rising ranking.(3)The spatial correlation test of agricultural eco-efficiency shows that the spatial correlation of agricultural eco-efficiency without carbon sink is stronger than that with carbon sink,and the spatial agglomeration characteristics all show the development trend of "weak agglomeration-weak dispersion",and the number of local spatial agglomeration distribution of agricultural eco-efficiency is relatively small and changes irregularly.(4)The influencing factors of agricultural ecological efficiency have obvious regional heterogeneity.The impact of agricultural materials load index on agricultural ecological efficiency is negatively correlated in Northeast China,North China,East China and Southwest China,and positively correlated in Central China and Northwest China.The disaster rate has a significant negative correlation with the agricultural ecological efficiency in Northeast China,North China,East China,Southwest China and Northwest China.The average planting scale of labor is positively correlated with agricultural ecological efficiency in North China,South China and Northwest China.The development level of secondary and tertiary industries has a significant negative correlation with agricultural ecological efficiency in Northeast China and South China,and a significant positive correlation with agricultural ecological efficiency in East China.Farmers’ income level has a significant positive correlation with agricultural ecological efficiency in Northeast China,North China,Central China,East China,South China and Southwest China.The influence of irrigation index on agricultural ecological efficiency in Northeast China,North China,Central China and Southwest China is negatively correlated.The level of machinery input has a significant positive correlation with the agricultural ecological efficiency in the northwest,and a significant negative correlation with the agricultural ecological efficiency in the southwest.Finally,according to the conclusion of this paper,some suggestions are put forward to promote the development of agricultural green production.