【作者】 任丽萍；

【导师】 江树人；

【作者基本信息】 中国农业大学 ， 农药学， 2004， 博士

【摘要】 农药残留物是水环境的重要污染源之一，莠去津、毒死蜱、马拉硫磷和丁草胺是我国农业上使用量较大且在环境水体中检出率较高的四种农药。本文研究的目的是建立水体中四种农药的多残留检测方法，研究环境因素对四种农药在水体中降解的影响，建立部分农药水体中降解的数学模型。 建立了环境水体中莠去津、马拉硫磷、毒死蜱和丁草胺等农药的固相萃取—气相色谱分析方法。实验中采用C₁₈固相萃取小柱提取水样中的农药，用GC-NPD对农药进行分析检测。该分析方法的检出限（3σ）对莠去津、马拉硫磷、毒死蜱和丁草胺分别为0.1、0.1、0.2μg·L^-1和0.05μg·L^-1。4种农药的线性范围均为0.10～10 mg·L^-1，在河水、地下水和去离子水中的添加回收率均在70％～112％。利用该方法对河水、地下水和农田沟水等环境水体进行检测，在西北旺农田沟水中检测到丁草胺，在河水中检出了莠去津。 用正交试验设计法，考察了水质、温度和pH等环境因素对四种农药在水体中降解的影响程度。实验结果表明，马拉硫磷在水体中降解的主要途径为水解，pH是影响水解的主要环境因素，水体中的无机矿物质对马拉硫磷降解也有很大的促进作用。影响丁草胺在水体中降解的主要因素是温度，酸性和碱性条件下有利于丁草胺的降解，而水中的无机矿物质对丁草胺的降解没有明显的作用。影响毒死蜱在水体中降解的主要环境因素为温度，pH和水质对毒死蜱降解的影响程度依次降低；水体中的无机物对毒死蜱降解影响不大，微生物对毒死蜱在水体中的降解有一定的贡献，光照和需氧条件有利于毒死蜱在水体中的降解。对水体中莠去津降解影响最大的环境因素是pH，酸性和碱性会促进莠去津的降解；温度、水质、光照对莠去津的降解影响程度较小。 首次用二次回归正交旋转组合设计，建立了水体中马拉硫磷和丁草胺降解的数学模型，并对模型进行了初步的分析和部分验证，分析和验证结果显示，可以用本文建立的模型对环境水体中马拉硫磷和丁草胺的污染程度进行初步的预测。以下是马拉硫磷和丁草胺在水体中降解的数学模型，式中，y-水体中农药残留浓度(μg·L^-1)；x₁-温度（℃）；x₂-时间（day）；x₃-初始浓度(μg·L^-1)。马拉硫磷降解模型:地下水:，，=39.22一2.slx，一2.26x，+0.62x，+0.06xlx:一0.04xlx，+0.06x矛+0.03x全河水:y二33.22一L55x、一2.90x2十0.14x。十0.04x，xZ+0.04x矛一仪02x:x3+0.08x圣池塘水:少=0.48一0.66x，一0.97x2+l.95x，+0.03x:xZ一0.03x，x，一0.02x圣一0·03x了厂草胺的降解模型:池塘水:少=15.73一l.57x:一o.96x2+1.，zx，+o.02x矛+0.“x圣一0.oZxZx，一。，oZx圣更多还原

【Abstract】 Pesticide contamination is considered one of the most contaminated sources of environmental water. Atrazine, Chlorpyrifos, Malathion and Butachlor were applied intensively and more frequently detected in environmental water in China. The objective of this research is to develop a multi-residue analytical method for determination of the above four pesticides and study on the degradation of these pesticides in environmental water.An analytical method for determination of atrazine, chlorpyrifos, malathion and butachlor in environmental water by solid-phase extraction (SPE) and gas-chromatography (GC) with nitrogen-phosphorus detector (NPD) was developed. The detection limits (3a) were 0.1 ug L-1 for atrazine, 0.1 ug L-1 for chlorpyrifos, 0.2 u.g L-1 for malathion and 0.05 ug L-1 for butachlor respectively. Linear range was 0.10 -10 mg L-1 for all four pesticides. The recoveries of four pesticides were between 70%-112% for river water, ground water and deionized water . The proposed method was applied to detect pesticides residue in environmental water. Butachlor was detected in surface water near agriculture field and atrazine was found in riverwater.Effects of pH, source of water and temperature on degradation of four pesticides were examined using orthogonal experimental design. The results showed that: (1) pH was the most important environmental factor of malathion degradation, the influence of water quality and temperature were slighter than pH and inorganic salts may catalyse the degradation of malathion; (2) Temperature was the most important environmental factor of butachlor degradation, H+ and OH- are also known to catalyse the degradation of butachlor, inorganic salts in water has little influence on butachlor degradation; (3) Temperature was the most important factor for chlorpyrifos degradation in water , the influence of pH was lesser than temperature ,and so water quality. Inorganic ions did not influence the degradation of chlorpyrifos, microorganism, irradiation and aerobic condition could promote the degradation of chlorpyrifos in environmental water, and (4) pH was the most important environmental factor of atrazine degradation. Acidic and Alkaline may enhance atrazine degradation. Temperature, water quality and irradiation had been not shown to affect atrazine degradation rates.Rotational regression design was employed to modeling the degradation of malathion and butachlor in water. Analysis and verification of model were conducted partly. The results showed that the established models may be used to predict the pollution of malathion and butachlor in environmental water. Models of malahtion and butachlor in different water are as follows:Malathion:Groundwater y = 39.22 - 2.81x1 - 2.26x2 + 0.62x3 + 0.06x,.x:2 - 0.04x1 x3 + 0.06x12 + 0.03x22River water y = 33.22 -1.55x1 - 2.90x2 + 0.14x3 + 0.04x1x2 + 0.04x12 - 0.02x1, x3 + 0.08x22Pond water y = 0.48 - 0.66x, - 0.97x2 + I.95x3 + 0.03x1x2 - 0.03x1x3 - 0.02x22 - 0.03x32Butachlr:Pond water y = 15.73 - 1.57xx - 0.96x2 + 1.92x3 + 0.02x12 + 0.04x22 - 0.02x2x3 - 0.02x32y, concentration of pesticide residue(ng L-1); x temperature(癈); x2 time(day);x3, concentration of pesticide (ug L-1)更多还原