| The trend of global warming caused by greenhouse gas emissions is getting more and more intense.Green and low-carbon development has become a common problem.As an important developing country in the world,China has been strictly implementing the policies and guidelines of energy conservation,emission reduction and environmental protection since it initiated low-carbon environmental protection.The report to the 19 th National Congress of the Communist Party of China(CPC)further emphasized the concept of "promoting green development and promoting harmonious coexistence between man and nature" and "upholding the principle that clear waters and green mountains are gold and silver mountains".However,while taking responsibility for environmental protection and green development,China is still a large agricultural country,and agricultural ecological efficiency and agricultural development quality are important factors affecting the realization of carbon emission reduction targets.However,the development of agriculture in China is accompanied by high pollution emissions,especially due to excessive and inappropriate use of pesticides and fertilizers and other environmental pollution problems.In view of this,this paper uses the SBM-ESDA model to measure China’s agricultural ecoefficiency from the perspective of low carbon,and dynamically analyzes the variation trend and spatial differentiation law of agricultural eco-efficiency in various regions,which is not only helpful to provide reference for the formulation of agro-environmental policies,but also helpful to promote the green transformation and high-quality development of China’s agriculture.This paper focuses on agricultural eco-efficiency under the constraint of agricultural carbon emissions,and explores the spatiotemporal variation of agricultural eco-efficiency in China’s provinces(municipalities and autonomous regions)from 1998 to 2018 from a lowcarbon perspective.Firstly,the researches on this in the world are reviewed,and the main research methods and themes of this paper are quoted.Secondly,through the SBMUndesirable model,we tested the robustness of the model based on different constraints of the model to measure the inter-provincial agricultural eco-efficiency in China during 1998-2018,and analyzed the redundancy(shortage)in the input-output index of the provinces that did not achieve the efficiency state from 1998 to 2018.Thirdly,exploratory spatial data analysis(ESDA)was used to investigate the temporal and spatial differentiation of agricultural eco-efficiency among provinces in China,and to describe the temporal and spatial characteristics of agricultural eco-efficiency among provinces in China from 1998 to2018.The main conclusions of this paper are as follows: the eastern region had the highest average both in a single year and in the whole period in most cases;after analyzing the slack situation of input-output index of all provinces,some provinces have insufficient agricultural output,and most provinces have input redundancy.According to the results of spatial correlation analysis,the spatial correlation of agricultural eco-efficiency at provincial level in China is very significant.According to the cold and hot spot tool analysis,there are 9provinces(cities)in the hot spot region,and one province in the cold spot region is Xinjiang Uygur Autonomous Region.From the perspective of changes in the center of gravity,the center of gravity of China’s agricultural ecological efficiency from 1998 to 2018 is located in the central and western regions of Henan Province,and the center of gravity changes are generally relatively stable.From the perspective of spatial change trend,the east-west change is intense,while the north-south change is simple.From the perspective of overall change trend,the value of agricultural eco-efficiency in China is gradually increasing,and the regional differences are gradually decreasing. |
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