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Research On Temporal And Spatial Characteristics And Spatial Effects Of China's Agricultural Carbon Emissions

Posted on:2018-08-20Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2351330515450574Subject:National Economics
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At present,climate change is one of the serious environmental problems in the world.Agricultural carbon emissions are one of the important sources of greenhouse gas emission which is one of the main drivers of climate change.This paper clarified the concepts and theories related to agricultural carbon emissions based on the review of the research literature,analyzed the spatial-temporal evolution characteristics of 31 provinces(municipalities or autonomous region)in China through the calculation of the agricultural carbon emissions,and the decomposition of the affecting factors of agricultural carbon emissions using LMDI model.Furthermore,the spatial spillover effect of agricultural carbon emissions of 31 provinces(municipalities or autonomous region)in China was examined through spatial panel Durbin model by applying 2000-2014 relevant panel data.Some conclusions and policy implications for agricultural carbon emission reduction were obtained based on the above analysis,which are as shown as following:(1)Agricultural carbon emissions in China were on the rising trend overall,with big fluctuation displaying characteristics of “rise slowly-rise rapidly-decline-rise” from year of2000 to 2014;the intensity of agricultural carbon emissions continued to decline with some ups and downs.Carbon emissions caused by farmland using,rice and livestock production were on the rise in the past 15 years.The proportion of carbon emissions caused by agricultural land use increased contrasting to that one caused by the production of rice and livestock.The agricultural carbon emissions of 31 provinces have formed the pattern of “core-periphery”.The provinces with high agricultural carbon emissions are mainly located in Sichuan Basin and east plain region.The traditional agricultural production pattern featured with “high investment”,“high emissions”,“low efficiency” still exists in China.(2)The driving factors and the growth mechanism of agricultural carbon emissions were analyzed by decomposing the affecting factors of agricultural carbon emissions using LMDI model.The results show that the agricultural economic growth and the urbanization level promote the increase of carbon emissions,while the agricultural production efficiency,agricultural industry structure and the labor education level have a significantly positive effect on the carbon emission reduction.(3)The results of the spatial correlation test indicate that there is a spatial dependence among 31 provinces of China.The empirical results from the spatial Durbin model that the economic development level,agricultural economic development level,urbanization level and agricultural disaster degree negatively affect the carbon reduction,while labor education level and agricultural ecological governance degree have effect of reducing the carbon emissions of the region.The economic development,agricultural fixed asset investment degree,urbanization level,agricultural production disaster degree and agricultural ecological governance degree have a positive impact on the agricultural carbon emissions of adjacent provinces,while agricultural economic development can restrain increase of the agricultural carbon emissions of the adjacent provinces.(4)Based on the results,the following policy suggestions were proposed,which include: coordinate the relationship between economic growth and the carbon emissions,change the agricultural production patterns;adjust agricultural industry structure;improve agricultural product efficiency by increasing agricultural asset investment and promoting agricultural science and technology innovation;improve education level of farmers and cultivate the consciousness of low carbon agriculture;construct warning system of agricultural disaster and improve agricultural ecological management;strength farmland resource protection and improve land carbon sink capacity;strength fiscal and taxation support and establish ecological compensation system;establish agriculture carbon trading market and give incentive for carbon emission reduction.
Keywords/Search Tags:agricultural carbon emissions, spatial effect, LMDI models, Spatial Durbin Model
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