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Measuring The Cultivated Land Use Efficiency Of The Main Grain-Producing Areas In China Under The Constraints Of Carbon Emissions And Agricultural Nonpoint Source Pollution

Posted on:2021-02-23Degree:MasterType:Thesis
Country:ChinaCandidate:Y W ZhangFull Text:PDF
GTID:2381330623981185Subject:Land Resource Management
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Food security plays a key role in safeguarding national security,achieving social stability and promoting economic development.The total grain produced in the main grain producing areas accounts for about 80%of the national total.It can be seen that the 13 major grain producing provinces bear the important responsibility of China’s food security.However,along with the continuous advancement of urbanization and industrialization,problems have arisen in different provinces of major grain producing areas,such as accelerated non-agriculturalization of agricultural land,insufficient food production,and increased environmental pollution.Therefore,how to improve the utilization level of cultivated land in China’s major grain-producing areas and prevent the degradation of cultivated land to ensure national food security and improve the living standards of farmers has become the focus of academic circles in China.As an important indicator to measure the economic benefits of cultivated land,cultivated land use efficiency has been widely concerned by many scholars around the world.However,traditional cultivated land use efficiency assessments do not incorporate resource and environmental factors into the evaluation system.This not only overestimates the true performance of cultivated land use efficiency,but also has a continuous negative impact on the welfare level of farmers.Therefore,it is very important and urgent to re-evaluate the level of cultivated land use efficiency in China’s major grain producing areas under environmental constraints.In view of this,the carbon emissions and agricultural nonpoint source pollution constraints were incorporated into the input-output index system,and the epsilon-based measure(EBM)super efficiency model and global Malmquist-Luenberger(GML)index were used to measure the cultivated land use efficiency and changes in the total factor productivity(TFP)of cultivated land use in the main grain-producing areas in China from 1993-2016.The total factor productivity of cultivated land was decomposed into GPTC,GSEC,GPEC and GSTC,and the convergence analysis of the change of cultivated land use efficiency value was carried out.Finally,using the comprehensive FGLS model to analyze the influencing factors of cultivated land use efficiency,the results show that:(1)From 1993 to 2016,the cultivated land use efficiency in the main grain-producing areas in China showed a tendency to fluctuate and increase,with obvious stage characteristics;however,the overall level was not high.(2)There is a significant difference in the cultivated land use efficiency under the constraints of carbon emissions and nonpoint source pollution in the main grain-producing areas in the different provinces,and low-efficiency provinces have higher input redundancy and undesired output redundancy than high-efficiency provinces.It can be observed that input redundancy and undesired output redundancy have a significant negative effect on cultivated land use efficiency.(3)The TFP of cultivated land use under the constraints of carbon emissions and nonpoint source pollution in China’s main grain-producing areas is estimated by the GML index.The results show that the TFP of cultivated land use in the main provinces in the main grain-producing regions is greater than 1,indicating that the productivity levels of all the provinces in China’s main grain-producing areas are increasing.From the perspective of the power sources in each province,global pure technological change(GPTC)and global scale technological change(GSTC)are the main driving forces for the TFP of cultivated land use,while global pure efficiency change(GPEC)and global scale efficiency change(GSEC)are the bottlenecks for increasing the TFP of cultivated land use.(4)From the convergence analysis,although the cultivated land use efficiency under the constraints of carbon emissions and non-point source pollution in China’s maj or grain producing areas in the past 24 years has converged,the convergence rate is slow.And in 2009-2016,the cultivated land use efficiency of China’s major grain producing areas has a tendency to divergence.(5)This paper uses the panel data from 1993 to 2016 to explore the main influencing factors of cultivated land use efficiency in China’s major grain producing areas.The results show that the multiple cropping index,total freight volume,agricultural tax exemption and per capita net income of farmers have a positive impact on the improvement of cultivated land use efficiency.The economic development and the proportion of disaster-affected disasters have a negative impact on the improvement of arable land use efficiency.Based on the above analysis,this paper finally proposes policy recommendations to improve the efficiency of cultivated land use in China’s major grain producing areas.It mainly includes:strengthening the monitoring and evaluation of cultivated land pollution;reforming the agricultural technology extension system;establishing a reasonable compensation and relief mechanism for cultivated land environmental protection;realizing the planned production of cultivated land through land transfer and land remediation,giving full play to the potential of agricultural science and technology.increasing capital investment in agricultural production,increasing the scale and total amount of transportation infrastructure,establishing a sound agricultural natural disaster early warning mechanism and disaster prevention system Finally,the realization of clean production of cultivated land will help the use of cultivated land in China’s major grain-producing areas to embark on a strong sustainable development path.
Keywords/Search Tags:cultivated land use efficiency, input-output redundancy analysis, environmental constraints, EBM super efficiency model, China
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