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1、摘 要随着人口的增加、社会经济的发展和农业集约化水平的提高，人们对自然干预和土地索取的增强导致“农业污染”日益严重，给土地可持续发展带来了巨大的压力，严重危害人体健康。乱用农药，不仅会造成环境污染，杀伤病虫害天敌，增强病、虫的抗药性，给病虫害防治工作带来新困难，破坏生态环境，并且会对人体健康产生急性中毒、慢性危害和“三致”危害。近年辽宁省农药使用总量增长迅速，单位面积用药量上升较快。本研究以辽宁省81个农业县区为研究区域，基于“压力-状态-响应”（PSR）模型，选取自然条件、国民经济、农业生产、教育科技、环境保护等评价指标，通过主成分分析，研究土壤环境在压力所对应的环境状态，评估土壤环境的承载
2、程度，分析不同地区影响土壤环境承载力的因素。采用ArcGIS的Kriging插值法，绘制土壤环境承载力得分分布图，识别低承载力地区，并提供应对策略。以土壤环境承载力为核心，通过主成分分析，选取与生态风险、致癌风险、非致癌风险和土壤农药残留浓度的平均相关性系数绝对值大于0.120的指标。为了指标体系的完整性，增加年平均气温、年日照时数、良种播种面积、大豆年产量、水果年产量和农业技术人员6个因素，最后扩展为56项二级指标。遵循科学性原则的基础上，将其分为有利和不利指标，进行极差标准化处理。通过主成分分析，识别影响2013-2015年辽宁省农药使用土壤环境承载力的8个主成分（PC），整体土壤环境承载
3、力呈下降趋势。土壤环境承载力较低的地区主要分布在沈阳市、锦州市、鞍山市和盘锦市以及西部朝阳市和阜新市，抚顺市、本溪市、丹东市东部和大连市南部土壤环境承载力较高。之后对沈阳市（2003-2015，不含2006年）和大连市（2002-2015年）15个县区的土壤环境承载力进行年际变化分析，并预测5年后土壤环境承载力得分。对总得分和原始数据进行多元一次线性拟合，通过敏感性分析，找出对总得分影响较大的14个可控指标。结合国家和辽宁省农业相关政策，对全省和的得分最低的昌图县、新民市给出提高土壤环境承载力的应对策略。为了进一步探究农药使用和土壤环境承载力的关系，分别针对总农药、在用农药和禁用农药，对辽宁省
4、2015年农药使用及残留的土壤环境承载力进行主成分分析，识别出10个PC。通过土壤环境承载力得分比较，发现辽宁省中部的沈阳市、辽阳市和阜新市的总农药土壤环境承载力最差，大连市甘井子区、金州区、旅顺口区得分较高。总的来说，辽宁省不同时间的不同地区土壤环境承载力差异较大，且整体呈逐年下降趋势，部分地区如大连市金州区土壤环境承载力有所改善。主成分分析的结果解释了土壤环境承载力变化的原因，敏感性分析确定对总得分影响较大的14个可控指标，研究结果为管理者制定相关管理措施，保障人类健康和生态环境安全提供科学依据。关键词：土壤环境承载力；PSR模型；主成分分析；农药使用- I -Evaluation of
5、Soil Environmental Carrying Capacity of Pesticide Use in Liaoning and Its CountermeasuresAbstract With the increase of population, the development of social economy and the intensification of agricultural intensification, the increase of natural intervention and land acquisition has led to the incre
6、asing agricultural pollution, which has brought great pressure to the sustainable development of land and seriously harmed the human body health. Indiscriminate use of pesticides, not only will cause environmental pollution, kill insect pests natural enemies, enhance disease, insect resistance, to p
7、est control work to bring new difficulties, destruction of the ecological environment, and human health will be acute poisoning, chronic hazards and three harm. In recent years, the total amount of pesticide use in Liaoning Province has been increasing rapidly, and the dosage per unit area has incre
8、ased rapidly. Based on the pressure-state-response (PSR) model, the evaluation index of natural condition, national economy, agricultural production, educational science and technology, environmental protection and so on was analyzed by principal component analysis (PCA) , The soil environment in th
9、e soil environment in the corresponding state of the environment to assess the soil environment carrying capacity, analysis of different areas affect the soil environmental carrying capacity factors. Using Kriging interpolation method of ArcGIS, the soil environmental carrying capacity score map is
10、drawn, the low bearing capacity area is identified, and the coping strategy is provided.Taking the soil environmental carrying capacity as the core, the average correlation coefficient of the average correlation coefficient with ecological risk, carcinogenic risk, non - carcinogenic risk and soil pe
11、sticide residue concentration was more than 0.120 by principal component analysis. In order to improve the integrity of the index system, increase the annual average temperature, annual sunshine hours, seed sown area, annual output of soybean, fruit annual output and agricultural technical personnel
12、 6 factors, and finally expanded to 56 secondary indicators. Follow the scientific principles on the basis of its divided into favorable and unfavorable indicators, the implementation of extreme standardization.Through the analysis of principal component analysis, the eight main components (PC) affe
13、cting the soil environmental carrying capacity of pesticides in Liaoning Province from 2013 to 2015 were observed, and the overall soil environmental carrying capacity decreased. The areas with low soil carrying capacity are mainly distributed in Shenyang, Jinzhou City, Anshan City and Panjin City,
14、and the western part of Chaoyang City and Fuxin City, Fushun City, Benxi City, Dandong City and Dalian City. The soil environmental carrying capacity of 15 counties in Dalian (2003-2015, excluding 2006) and Dalian (2002 - 2015) was analyzed and the soil environmental carrying capacity was predicted
15、after 5 years. The total score and the original data were subjected to multiple linear fitting. By means of sensitivity analysis, 14 controllable indexes with large influence on the total score were found out. Combined with the national and Liaoning provincial agriculture-related policies, the provi
16、nce and the lowest score of Changtu County, Xinmin City, to improve the soil environmental carrying capacity of the coping strategies.In order to further explore the relationship between pesticide use and soil environmental carrying capacity, the main constituents were analyzed for the total pesticide, pesticide and pesticide were used to analyze the soil environmental carrying capacity of pesticide use and residues in Liaoning Province in 2015, a
