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Research On Spatial-temporal Differences,influence Factors And Prediction Of Carbon Emission In Agriculture And Animal Husbandry In China

Posted on:2019-07-05Degree:MasterType:Thesis
Country:ChinaCandidate:Q WeiFull Text:PDF
GTID:2321330569489770Subject:Physical geography
Abstract/Summary:PDF Full Text Request
In order to explore the carbon emissions of agriculture and animal husbandry in China,This paper based on the relevant statistics to calculate the carbon emissions of agricultural and animal husbandry in China from 1997 to 2015.The carbon emissions including:?1?CH4 and N2O emissions from rice and other crops in the planting process,?2?CH4 and N2O produced by intestinal fermentation and fecal management during the feeding perio,?3?Carbon emissions from the use of chemical fertilizers,pesticides and others.Based on the visual description of the spatial and temporal differences of carbon emissions in China,the paper makes a spatial visualization analysis of carbon emissions from agriculture,animal husbandry,agriculture and animal husbandry,and it also built gravity model to analyze the dynamic trajectory of carbon emission.In the aspect of influence factors and Prediction,the fixed effect model is used to analyze the carbon emissions of agriculture and animal husbandry,and the grey prediction model GM?1.1?and ARIMA model are also used to predict the future carbon emissions in China.The results are as follows:?1?The trend of carbon emissions in agriculture and animal husbandry in China is characterized by the three stages of"rising-down-rising".The carbon emission intensity of agriculture and animal husbandry showed a downward trend.In terms of carbon emissions from agriculture and animal husbandry,carbon emissions from agriculture are higher than those from animal husbandry,and overall changes is increasing.The trend of carbon emissions from animal husbandry is also shown the characteristics of"rising,falling and rising".Among all types of carbon sources,carbon emissions from agricultural land use have grown most rapidly,and their carbon emissions have surpassed livestock husbandry in 2008-2015,and becoming the highest carbon emissions.?2?Henan province has become the most carbon emission province since 1998,the average annual growth rate of carbon emissions of Ningxia is the largest in the country,which is 3.46%.According to spatial visualization analysis,the high carbon emission areas of agriculture and animal husbandry,agriculture,animal husbandry are mainly distributed in China's main grain production area and animal husbandry area.the focus of carbon emission in agriculture and animal husbandry,agriculture,animal husbandry are in the central region.?3?According to the regression analysis of factors affecting carbon emissions in agriculture and animal husbandry,the output value of agriculture and animal husbandry,crop areas has significant positive effect on carbon emissions,and crop areas has the greatest positive impact on the carbon emissions.the structure of output value about agriculture and animal husbandry,level of urbanization and the consumption level of residents has a significant negative effect on carbon emissions.The greatest positive factors of carbon emissions from agriculture and animal husbandry are crop areas and rural population respectively.?4?by comparing the accuracy,this paper selects the ARIMA model to predict carbon emissions from agriculture,animal husbandry,agriculture and animal husbandry in China from 2016—2023.The prediction results indicate that the carbon emissions of agriculture,animal husbandry,agriculture and animal husbandry increased to 29542.59104t?22594.18 104t?10530.13 104t in 2023.Compared with 2015,it increased by 1.72%,14.79%and 12.50%respectively.Finally,based on the findings,the study put forward policy suggestions from the aspects of reducing the carbon emissions from agricultural land use,treatment of livestock excreta,adjustment of the structure of agricultural industries and other aspects.
Keywords/Search Tags:Agricultural and animal husbandry carbon emission, regression analysis, GM(1,1) model, ARIMA model
PDF Full Text Request
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