Measure And Warning Of Carbon Emissions From China’s Agricultural Exports

Since entering the twenty-first Century,the economic development has made remarkable achievements in China,but at the same time,environmental problems are becoming increasingly serious.As global temperatures gradually increase,the area of glaciers is decreasing and climate is changing,and the carbon emissions has become an important indicator of environmental pollution.Agricultural production is closely related to greenhouse gas emissions and it is an important source of carbon emissions.The main development mode of agriculture is "chemical agriculture" in China.During the growth of crops,a lot of pesticides,agricultural films,fertilizers and various kinds of petroleum energy will be consumed,which will cause massive carbon emissions and damage the environment.When exported to other countries,agricultural will increase China’s carbon emissions.However,crop also brings about some carbon sink in the process of growth.From this point of view,the export of agricultural products will also increase domestic carbon sinks.So this forewarning study mainly focuses on net carbon emissions from agricultural products export trade.Not only it has enriched the research direction of carbon emissions to a certain extent,but also made more accurate forewarning of carbon emissions from agricultural products export trade.In this paper,forewarning research is carried out and get the warning level,to arouse the attention of relevant departments and optimize the export trade structure of our agricultural products and promote technological progress gradually.And then,we can achieve the coordinated development of carbon emission reduction and export trade in agricultural production.By analyzing the research status of carbon emissions at home and abroad,this paper summarizes the relevant theories of forewarning models for agricultural products export trade in China.Taking the data of 15 years in 2002-2016 years as the research sample,the paper analyses the present situation of agricultural products export trade objectively and truthful.Secondly,in order to predict carbon emissions accurately,this paper uses input-output method from the industry level to measure the total carbon emissions in the export trade of agricultural products in China and calculates the carbon sequestration of these 15 years based on the crop estimation method,then the net carbon emission is obtained.The next,the BP neural network forewarning model based on the genetic algorithm is established,meanwhile,according to the principle of index selection and correlation analysis,the forewarning index system of net carbon emissions of agricultural products export trade was selected and identified.Finally,the paper uses the GA-BP neural network forewarning model to conduct an empirical analysis,and it carries out a forewarning study on the net carbon emissions of China’s agricultural products export trade.The result shows that the forewarning model is very accurate,and it forecasts the warning degree in 2017.The empirical results show that the forewarning model has a significant effect.It can predict the net carbon emissions in the export trade of agricultural products effectively and accurately in China,and it has a good warning effect on the net carbon emissions of export trade.This study provides a reference for strengthening the management of the carbon emissions of agricultural products export trade in China.Meanwhile,it is also of great significance to further optimize the export structure of China’s agricultural products.