摘 要:如今，经济与环境的问题引起了人们的高度广泛关注，经济的高速发展必然会带来环境污染问题，环境问题已成为束缚中国经济发展最主要的问题之一。随着全球化进程的加快，发达国家的绿色贸易壁垒越来越制约着发展中国家对外贸易的发展，对我国而言，怎样把握环境保护与经济增长的平衡点是可持续发展的关键。中国作为最大的发展中国家，也是世界上最大的农产品出口国，必然付出了惨痛的代价。农业面源污染作为农业污染中的重点污染，在相当程度上影响了中国的农业出口。因此，分析我国农业环境污染的现状，研究我国贸易发展与农业环境之间的关系，认清农业贸易发展趋势找到平衡点，促使经济增长与环境保护协调一致的发展，对解决中国的农业经济问题具有一定的理论意义和现实意义。本文以江苏省数据为例，利用数据模型，尝试分析农业面源污染与农产品出口贸易之间的关系，探讨如何使中国农业走上现代农业之路。
关键词：农业面源污染；农产品出口贸易；数据分析
ABSTRACT:Nowadays, the economic and environmental problems aroused people's attention.The rapid development of economy brings the problem of environmental pollution.Environmental problems have become one of the main problem in Chinese economic development.With the accelerating process of globalization, more and more green trade barriers of developed countries restrict the development of foreign trade in developing countries.In China,how to grasp the balance of economic growth and environmental protection is the key to sustainable development. China,the largest developing country and also one of the largest exporters of agricultural products,must pay a painful price.Agricultural non-point source pollution as the focus of agricultural pollution,to a considerable extent,affect China's agricultural exports.Therefore, analysising of the current situation of agricultural environmental pollution in China,researching on the relationship between trade development and agricultural environment in China, recognizing the trend of the development of agricultural trade balance and promoting economic growth and environmental protection coordinated, has the certain theory significance and the practical significance to solve the problem of agricultural economy in china.With the data of Jiangsu Province as an example,using the data model,this paper tries to analyze the relationship between the export trade of agricultural non-point source pollution and agricultural products,and discuss how to make Chinese agriculture on the road of modern agriculture.
Keywords: Agricultural non-point source pollution; the export trade of agricultural products; data analysis
