Spatiotemporal Divergence And Driving Factors Of The Low-Carbon Performance Of Cropland Use In China

In response to the increasingly global warming,countries around the world are actively promoting low-carbon transformation.Cropland use possesses dual effects of carbon emission and sequestration.On the one hand,it contributes to 13% of the global carbon dioxide emissions,44% of methane,and 82% of nitrogen oxide emissions,playing an important role in the carbon cycle.On the other hand,as a significant carbon sink,crops absorb carbon dioxide through photosynthesis,which is a powerful weapon against global warming.Different from the single target of emission reduction in other production activities,cropland use exhibits unique significance in the process of both carbon peaking and carbon neutralization.By reducing the emission intensity in agriculture and promoting the carbon sequestration of crops,it contributes to the ’double carbon’ goal of China by dual paths.In addition to the key role in the carbon cycle,cropland is the base for food security.From 2000 to 2021,the grain output increased from 462 million t to 685 million t in China.This remarkable achievement stemmed from the increasing mechanization and chemicalization during agricultural production,which was accompanied by the increasing carbon emissions.Consequently,the relationship between input-driven agricultural production,food security,and low-carbon transformation of cropland use requires coordinating.For the low-carbon transformation of cropland use,existing studies have measured the carbon emissions and sequestration of cropland use at different scales.Several approaches,such as field experiments,model simulations,and inventory-based accounting,have been applied,which helps to recognize the gross quantity of carbon sequestered or emitted by cropland use system.However,different geographical conditions and cropland endowments result in diverse agricultural production in places.Carbon accounting only offers a general reference,which can hardly reflect the reasonable level of carbon emissions and sequestration corresponding to the provincial production characteristics.To balance the economy and the environment,it is necessary to consider how to minimize carbon emissions and improve desirable output under the given input combination.This study attempts to define the low-carbon performance of cropland use.At given inputs and technology,the performance is the comprehensive ratio of the actual outputs to the optimal level of the cropland use system.Notably,the outputs include three dimensions,namely,agricultural output,carbon emissions,and crop sequestration.With technological progress,demand upgrades,and policy changes,cropland use differs over time,and the low-carbon performance of cropland use will gradually evolve temporally.Meanwhile,the cropland conditions and the agricultural development vary widely in different provinces,and the performance will also show distinct spatial differentiation.The spatiotemporal divergence of the performance contradicts the overall cropland protection and the fairness of carbon emission mitigation.Therefore,the question that needs to be further solved is: What is the temporal evolution of the performance? What is the spatial pattern? What are the driving factors of the spatiotemporal divergence? By answering the above questions,it is possible to understand the low-carbon transformation of provinces’ cropland use systems corresponding to their own producing characteristics and cropland conditions.Further,it helps to implement policies for the realization of the coordination of low-carbon transformation of cropland use across the country.In view of this,focusing on the low-carbon performance of cropland use,this study takes30 provinces in China from 2000 to 2019 as the research area.Then,the definition,analytical framework,and measurement of the low-carbon performance of cropland use are demonstrated,with its spatiotemporal divergence and driving factors explored.The study is organized as 1)The first part illustrates the study origin,the theoretical basis,and the analytical framework,covering Chapters 1 and 2.This part aims to introduce the background,significance,related literature,analytical ideas,approach,and possible innovations of this study.With the core concepts clarified,the theoretical framework of both the performance and its driving factors are analyzed based on the related classical theories.2)The second part examines the low-carbon transformation of cropland in China from three perspectives,which are absolute,relative,and comprehensive,involving Chapters 3 and 4.First,the carbon accounting list is constructed based on the carbon cycle of cropland use,with which the carbon emissions and sequestration of provincial cropland use are estimated.This provides a quantitative reference of the scale of China’s cropland-use carbon source/sink from the absolute low-carbon perspective.Then,the relationship between the economic output and carbon output of the cropland use is discussed,which offers an understanding from the relatively low-carbon perspective.Finally,from the comprehensive low-carbon perspective,carbon emission and sequestration are introduced into the framework of the cropland use system as environmental cost and ecological output,respectively.The GB-US-S-SBM model is employed to measure the low-carbon performance of cropland use in 30 provinces of China from 2000 to 2019.3)The third part analyzes the spatiotemporal divergence of the low-carbon performance of cropland use,further explores the driving factors,consisting of Chapters 5,6,and 7.First,the temporal changes of performance are classified into stages according to their characteristics,and their dynamic evolution and convergence are portrayed.Then,the spatial pattern of the performance is described from both national and regional levels,the spatial correlation is examined with the agglomeration centers portrayed,and the structure of regional differences is discovered.Finally,a spatial econometric model is applied to explore the driving factors of the spatiotemporal divergence.4)The last part,Chapter 8,gives the conclusions and develops a feasible path for low-carbon transformation of cropland use in China based on global,regional,and provincial levels.Also,the main outcomes are compared with the related literature,where the differences are discussed and the shortcomings of this study are pointed out,with the future directions are prospected.The main conclusions are as follows:(1)The cropland use system in China acted as a carbon sink,and the relationship between net carbon sequestration and economic output tended to be coordinated.The total carbon emissions from cropland use averaged to be 232.79 million t in China,with an annual growth rate of 1.15%.In the emission structure,the average proportion of carbon sources decreased in the order of agricultural materials(33.7%),rice fields(26.7%),straw burning(26.6%),and soil(13.0%).According to the development of each source,it was judged that the carbon emission of cropland use in China had reached a peak in 2015.The total carbon sequestration of cropland use in China was 661.23 million t,showing a fluctuating upward trend,with an annual growth rate of 2.20%.Grain contributed more to the carbon sequestration structure.The cropland use system had always exhibited to be net carbon sequestration,with an annual amount of 428.43 million t.The relationship with economic development has improved from a global imbalance to partial coordination.The type of provincial coupling has evolved from multiple types to an economy-led type,showing that the relationship between economic output and carbon output is gradually optimized.(2)The overall low-carbon performance of cropland use was 0.650 in China,indicating that the cropland use was transiting from a stage of high carbon to that of low carbon.A significant gap existed among provinces,with the performance ranging from 0.274 to 1.149.The performance of seven provinces,such as Chongqing and Hunan,were quite stable,that of five provinces,such as Guizhou and Sichuan,showed negative growth,and the performance of other 18 provinces,such as Qinghai and Hebei,increased with different speed.The reasons for the inherent loss of performance varied from provinces.Most non-effective provinces displayed low efficiency on several input factors,and some even exhibited the coexistence of the lack of desirable output and excess of undesired output.(3)The low-carbon performance of cropland use nationwide had gone through four stages:violent fluctuation(2000-2003),slow rise(2004-2008),fluctuation(2009-2011),and highspeed growth(2012-2019),showing an upward trend overall.According to the initial performance and the annual change rate,30 provinces could be divided into five types,including low-performance and high-potential type(fifteen provinces such as Beijing and Tianjin),low-performance and stable type(four provinces such as Jiangsu and Anhui),highperformance and stable type(three provinces such as Chongqing and Xinjiang),highperformance and low-potential type(three provinces such as Hubei and Sichuan),and highperformance and high-potential type(five provinces such as Jilin and Heilongjiang).There was no σ convergence in the performance of the whole country,eastern or central regions,while the performance in the northeastern and western regions strictly followed the σ convergence.Besides,a β convergence was testified in the performance of the whole country and all regions,suggesting that the performance of each region would converge to their steady-state level over time.(4)The low-carbon performance of cropland use agglomerated geographically in China.In the early stage,the high-performance provinces were mainly located in the southwest,with the low-performance ones agglomerating in the northwest.At the end of the study period,the provinces of high performance were mostly situated in the northeast and northwest,and those of low performance were clustered in the middle reaches of the Yangtze River.The spatial correlation was discovered to exist in the performance of close provinces,and the degree of correlation weakened early but strengthened later.The Theil index showed that the regional disparities in the performance almost originated from within regions early,the overall disparities were composed of intra-regional and inter-regional differences later.(5)At the national level,for a province,agricultural structure adjustment and urbanization could promote the low-carbon performance of cropland use,while the effectiveness of irrigation and the disaster showed a negative impact.Owing to the agricultural competitiveness and the wide coverage of disasters,the performance of a province would be affected by the agricultural structure and disaster in its nearby provinces.Besides,due to the radiation of technology,the performance of a province would be facilitated by the urbanization in the nearby provinces.The driving factors varied in four regions.The cropland scale and disaster played a key role in the performance in the eastern region.The northeastern region should pay attention to multiple cropping,disaster,and urbanization.Cropland scale,agricultural investment,technicians,and disaster significantly affected the performance in the central region.Besides,four indicators,cropping structure,the effectiveness of irrigation,disaster,and financial support,exhibited significant influence in the performance of the western region.To accelerate the low-carbon transformation of cropland use in China,it is suggested that:from the national level,attention should be paid to the main carbon sources.Emissions are supposed to be mitigated in the whole process of cropland use.A reasonable carbon compensation mechanism may be explored for regional cropland use.The labor surplus and agricultural materials redundancy in the cropland use system needs to be targeted,which requires improving the allocation of production factors and alleviating the resource waste.A focus on the agricultural structure,disaster,and other key driving factors of the spatiotemporal divergence is urgently required.From a regional perspective,it’s necessary to respect the cropland conditions and production characteristics in different regions,and four provinces,Hubei,Hunan,Jiangxi,and Anhui,should be chosen as key areas to support because of their low-performance agglomeration.Meanwhile,encouraging the provinces of high-performance agglomeration,such as Heilongjiang,Jilin,and Liaoning,to share the initiatives of low-carbon cropland use with nearby provinces may act as additional beneficial methods.Breaking through geographical restrictions and strengthening inter-provincial cooperation is recommended,which facilitates the regional chain effects to mitigate the performance gaps.At the provincial level,it is suggested that emissions in provinces be mitigated according to the local carbon structure.Optimizing the allocation of the input according to the province’s redundant characteristics can potentially help to achieve low-carbon cropland use.The possible innovations of this paper are as follows:(1)Providing a theoretical framework for assessing the low-carbon performance of cropland use.Applying the concept of the low-carbon performance to the field of cropland use,this paper constructs an input-output system of cropland use under low-carbon targets,where carbon sequestration and emissions act as ecological benefits and environmental burdens,respectively.Measuring the performance helps to achieve the low-carbon transformation of cropland use in China while ensuring food security,which also provides ideas for further research on the environmental performance of cropland use.(2)Constructing a comprehensive inventory for measuring the carbon emissions and sequestration of cropland use.Different from the existing literature that merely considers six conventional carbon factors of agricultural materials like fertilizer and pesticide,this paper sorts out the carbon effects of the cropland use system as comprehensively as possible.To ensure the reliability of carbon accounting,the coefficients mainly referred to inventories published by the Chinese government and widely referenced literature.Then,a more comprehensive inventory is developed concerning agricultural materials,rice fields,soil,and straw burning,which is an extension of the existing literature.(3)The spatial econometric model is applied to explore the driving factors of the spatiotemporal divergence of the performance.Provinces that are geographically close to each other may have many similar characteristics,such as geographic environment,resource endowment,cropping structure,and technology level.The similarities ease the mobility of production factors,the diffusion of low-carbon technology,and the reference of advanced policies.This interaction is known as spatial spillover and therefore,the geographical location needs to be included in the analysis.If not,it will lead to a misspecification of the model set.Therefore,this paper introduces geographic factors into the analytical framework.On the one hand,it verifies the driving factors in a relatively robust and reliable manner.On the other hand,it puts the low-carbon transformation of cropland use in a broader spatial perspective.