城市污水处理厂不同工艺段中有机氯农药残留

建立了基于HLB固相萃取柱和气相色谱 /电子捕获 (GC/ECD)分析城市污水中有机氯农药的分析方法 ,同时分析了北京市高碑店和北小河两个污水处理厂中 4个不同工艺段水体中有机氯农药的浓度。在两个污水处理厂的水体中共检出了 6种有机氯类农药 ,分别是α 六六六、β 六六六、γ 六六六、δ 六六六、艾氏剂和 4 ,4’ 滴滴滴 ,浓度在 1 89—6 9 6ng/L之间。结果表明 ,曝气活性污泥法对六六六类有机氯农药的去除效果较好。     

有机磷农药残留检测技术研究进展

综述了近年来有机磷农药残留检测技术的研究进展,其检测方法主要有色谱法、降解酶法、化学发光技术和生物传感技术.详细介绍了几种生物传感器(如酶传感器、微生物传感器、免疫传感器、压电传感器、纳米传感器和液晶型化学传感器)在有机磷农药检测中的应用,并展望了这一领域的发展趋势.     

固相萃取毛细管气相色谱法分析水中有机磷农药残留

探索了采用固相萃取对样品进行提取富集，以及配备氮磷检测器的毛细管气相色谱(CGC)法分析水中有机磷农药痕量残留的方法。结果表明：敌敌畏、内吸磷、乐果、甲基对硫磷、马拉硫磷和对硫磷等6种农药在20min内有较好的分离；3个不同浓度的标准添加，其回收率范围为52．1％～93．7％，最低检出限范围为1．11～5．21ng／L；同时利用该方法分析太湖梅梁湾水源地和长江沿岸水厂取水口水质，6种有机磷农药均有一定程度检出，但仍未超出集中水源地供水标准。     

蔬菜上低残留农药的选择及其安全使用

经试验示范,筛选出供蔬菜上使用的32种高效、低毒、低残留农药,并制定了30种农药的安全间隔期。     

Au@Ag致密单层膜的组装及对农药残留的SERS检测

采用聚合物溶液组装法构筑致密Au@Ag核壳单层膜结构,用作SERS基底检测有机磷农药具有高灵敏性和重现性。Au@Ag核壳纳米立方体首先通过种子生长法合成,然后用功能化的配体聚乙二醇巯基（mPEG–SH）进行修饰获得有序的致密单层膜结构。该结构的形成归因于适量mPEG–SH的加入可以精确调节颗粒间以及颗粒与基底间的相互作用力,使得基底表面的纳米粒子重新排列。这种有序的单层膜结构用作SERS基底具有稳定和高重现的SERS信号,用于检测乙基对氧磷农药残留时检测限低至10-8 mol·L-1（2.75 μg·mL-1）。该聚合物组装方法为构建高灵敏和高重现性的SERS基底提供了一个有效的途径,为SERS技术在农药残留检测领域的推广应用打下了基础。     

多壁碳纳米管固相萃取—高效液相色谱法测定水中7种三唑类农药残留

应用多壁碳纳米管自制固相萃取柱富集、净化,以乙腈-水为流动相,用乙酸乙酯洗脱,高效液相色谱进行分析检测,建立了环境水样中7种三唑类农药残留分析的方法。结果表明,在0.05~10.00mg/L线性范围内,方法检出限为0.000 9~0.047 7mg/L;农药的加标水平在0.25~1.00mg/L时,加标回收率为72.28%~106.60%,相对标准偏差为1.12%~9.73%。该方法操作简单,定性、定量准确,是对水样中三唑类农药残留液相色谱分析较理想的一种方法。     

城市污水处理厂不同工艺段中有机氯农药残留

建立了基于HLB固相萃取柱和气相色谱／电子捕获(IGC／ECD)分析城市污水中有机氯农药的分析方法，同时分析了北京市高碑店和北小河两个污水处理厂中4个不同工艺段水体中有机氯农药的浓度。在两个污水处理厂的水体中共检出了6种有机氯类农药，分别是α—六六六、β—六六六、γ—六六六、δ—六六六、艾氏剂和4，4′—滴滴滴，浓度在1．89—69．6ng／L之间。结果表明，曝气活性污泥法对六六六类有机氯农药的去除效果较好。     

固相萃取-毛细管气相色谱法测定蔬菜、土壤和水中的毒死蜱残留量

采用固相萃取技术提取蔬菜、土壤和水体中毒死蜱,建立了蔬菜、土壤和水体中毒死蜱的固相萃取-气相色谱测定方法,并与传统方法进行了比较。添加浓度为0.1、1、10 mg·L-1,两种方法的水样平均回收率分别在93.7%~102.7%和96.2%~100.2%,变异系数分别在2.2%~7.7%和3.3%~5.1%;土壤平均回收率分别在91.3%~100.7%和92.0%~104.8%,变异系数分别在1.4%~7.0%和0.3%~5.2%;蔬菜平均回收率分别在89.4%~101.4%和92.5%~101.8%,变异系数分别在5.2%~7.1%和3.1%~6.0%。试验结果表明,固相萃取法与传统方法的回收率和变异系数相当,但前者更加省时、省力和省溶剂。     

水环境中磺胺类抗生素固相萃取-液质联用检测方法的建立及效果评估

为快速、同步检测分析磺胺类抗生素,有效削减并控制水体中磺胺类上抗生素含量,基于已有检测仪器和分析测试方法,建立了一种用于同时测定水体中8种磺胺类抗生素(磺胺氯哒嗪、磺胺间二甲氧嘧啶、磺胺二甲基嘧啶、磺胺甲恶唑、磺胺喹恶啉、磺胺甲氧哒嗪、磺胺甲噻二唑、磺胺吡啶)残留的固相萃取-液相色谱-三重四极杆串联质谱检测方法;在检测过程中,调节水样的pH为3,用HLB固相萃取柱进行净化、富集,在40 ℃条件下用氮吹浓缩吹干,用超纯水复溶至1 mL;以0.1%甲酸水溶液和0.1%甲酸乙腈溶液作为流动相,使用Phenomenex Kinetex F5 色谱柱(50 mm×3.0 mm, 2.6 μm)进行分离,在多反应监测模式(MRM)下对样品进行定量、定性分析。结果表明：8种磺胺类抗生素线性关系良好,且拟合度均大于0.999 0;检出限为0.1~0.5 μg·L⁻¹,定量限为0.5~2.0 μg·L⁻¹;质量浓度为1、5、50 μg·L⁻¹的混标溶液的加标回收率分别为78.85%~127.96%、76.69%~114.38%和73.55%~125.92%, 相对标准偏差均在15%以内。该方法快捷、高效、灵敏,能够满足水中磺胺类抗生素的定性、定量检测,可为我国检测方法标准体系的建设提供参考。     

有机改性剂对水中有机氯农药提取效率的影响研究

通过有机改性剂在液液萃取和固相萃取条件下水中有机氯农药的提取效率比对分析,首次探讨了有机改性剂对水中有机氯农药提取效率的影响。结果表明,（1）液液萃取前处理水样中不加有机改性剂、固相萃取前处理水样中添加一定量有机改性剂时,水中有机氯农药的提取效率较高;（2）采用正交实验优化水中有机氯农药固相萃取的提取效率实验表明,有机改性剂添加量对其影响大于有机改性剂种类对其影响;最佳优化方案为水样中添加1%甲醇时,提取效率最高。     

Validation of a QuEChERS-based gas chromatographic method for analysis of pesticide residues in Cassia angustifolia (senna)

A simple multi-residue method based on modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) approach was established for the determination of 17 organochlorine (OC), 15 organophosphorous (OP) and 7 synthetic pyrethroid (SP) pesticides in an economically important medicinal plant of India, Senna (Cassia angustifolia), by gas chromatography coupled to electron capture and flame thermionic detectors (GC/ECD/FTD) and confirmation of residues was done on gas chromatograph coupled with mass spectrometry (GC-MS). The developed method was validated by testing the following parameters: linearity, limit of detection (LOD), limit of quantification (LOQ), matrix effect, accuracy–precision and measurement uncertainty; the validation study clearly demonstrated the suitability of the method for its intended application. All pesticides showed good linearity in the range 0.01–1.0 μg mL^?1 for OCs and OPs and 0.05–2.5 μg mL^?1 for SPs with correlation coefficients higher than 0.98. The method gave good recoveries for most of the pesticides (70–120%) with intra-day and inter-day precision < 20% in most of the cases. The limits of detection varied from 0.003 to 0.03 mg kg^?1, and the LOQs were determined as 0.01-0.049 mg kg^?1. The expanded uncertainties were <30%, which was distinctively less than a maximum default value of ±50%. The proposed method was successfully applied to determine pesticide residues in 12 commercial market samples obtained from different locations in India.     

Nature of the field-to-field distribution of pesticide residues

The supervised trial datasets (1950), consisting of a minimum of five residue values and selected by the experts of FAO/WHO Joint Meeting on Pesticide Residues for recommending maximum residue levels between 1997 and 2011, were evaluated to obtain information on the typical spread of residue values in individual datasets. The typical relative standard deviation, CV, of field-to-field variation of pesticide residues was about 80%. The spread of residues in datasets is independent from the chemical structure of pesticides, residue level, pre-harvest interval and number of values in the datasets. The CV ranges within the Codex commodity groups and between groups overlapped and their difference were not statistically significant. The number of residues below the limit of quantification (LOQ) affects the CV at various extents depending on the ratio of LOQ/R _mean. The combined uncertainty of the highest residue in a dataset significantly affects the CV of the dataset. The lowest and intermediate ones have less influence. The residues in different fields receiving the same treatment vary within large range: 55%, 72%, 78%, 86% and 89% of the 25,766 residues values were, respectively, within 3, 4, 5, 6 and 7 times the median value of the corresponding dataset.     

Determination of pesticide residues in IPM and non-IPM samples of mango (Mangifera indica)

Studies were conducted to analyze the residue of commonly used pesticides viz. methyl parathion, chloropyrifos, endosulfan, cypermethrin, fenvalerate, carbendazim, imidacloprid and carbaryl in mango, Dashehari variety, integrated pest management (IPM) and non-IPM samples were collected from the IPM and non-IPM orchards, Lucknow, India. We also present a method for the simultaneous determination of these pesticides in mango samples. Residues of methyl parathion, chloropyriphos, endosulfan, cypermethrin, fenvalerate were extracted from the samples with acetone: cyclohexane: ethyl acetate in the ratio 2:1:1 followed by cleanup using neutral alumina. Analysis was performed by gas chromatography-electron capture detector (GC-ECD) with a megabore column (OV-1). Residues of carbendazim, imidacloprid and carbaryl were extracted with acetone and after cleanup, analysis was performed by high performance liquid chromatography (HPLC) using photo diode array (PDA) detector. Recoveries of all the pesticides ranged between 72.7 – 110.6%, at 0.1 and 1.0 μg g^{? 1} level of fortification. The residues detected in non-IPM samples of mango were found to be below the prescribed limits of maximum residue limit (MRL) while IPM samples were free from pesticide residues.     

Distribution of pesticide residues in soil and uncertainty of sampling

Pesticide residues were determined in about 120 soil cores taken randomly from the top 15 cm layer of two sunflower fields about 30 days after preemergence herbicide treatments. Samples were extracted with acetone-ethyl acetate mixture and the residues were determined with GC-TSD. Residues of dimethenamid, pendimethalin, and prometryn ranged from 0.005 to 2.97 mg/kg. Their relative standard deviations (CV) were between 0.66 and 1.13. The relative frequency distributions of residues in soil cores were very similar to those observed in root and tuber vegetables grown in pesticide treated soils. Based on all available information, a typical CV of 1.00 was estimated for pesticide residues in primary soil samples (soil cores). The corresponding expectable relative uncertainty of sampling is 20% when composite samples of size 25 are taken. To obtain a reliable estimate of the average residues in the top 15 cm layer of soil of a field up to 8 independent replicate random samples should be taken. To obtain better estimate of the actual residue level of the sampled filed would be marginal if larger number of samples were taken.     

Characterization of distribution of pesticide residues in crop units

The characteristic features of distribution of pesticide residues in crop units and single sample increments were studied based on more than 19,000 residue concentrations measured in root vegetables, leafy vegetables, small-, medium- and large-size fruits representing 20 different crops and 46 pesticides. Log-normal, gamma and Weibull distributions were found to provide the best fit for the relative frequency distributions of individual residue data sets. The overall best fit was provided by lognormal distribution. The relative standard deviation of residues (CV) in various crops ranged from 15–170%. The 100–120 residue values being in one data set was too small to identify potential effects of various factors such as the chemical and physical properties of pesticides and the nature of crops. Therefore, the average of CV values, obtained from individual data sets, were calculated and considered to be the best estimate for the likely variability of unit crop residues for treated field (CV = 0.8) and market samples (CV = 1.1), respectively. The larger variation of residues in market samples was attributed to the potential mixing of lots and varying proportion of non-detects. The expectable average variability of residues in composited samples can be calculated from the typical values taking into account the sample size.     

Estimation of uncertainty of sampling for analysis of pesticide residues

Abstract

A computer model was used to take random samples from primary sample populations obtained from field trials to simulate the uncertainty of sampling for residue analysis of plant commodities and soil. The results indicate about 40%, 30% and 20% relative uncertainty when random samples of size 5, 10 and 25 are taken respectively, from a single lot. Therefore the sample size should be the same for establishing and enforcing legal limits.     

Human milk contamination by nine organochlorine pesticide residues (OCPs)

Abstract

Organochlorine pesticides (OCPs) are widely used around the world as insecticides, herbicides, fungicides, nematicides, and rodenticides. Despite banned in Brazil, the usage remains occurring in many countries. The persistence and extreme mobility of OCPs contribute to the contamination of the environment and the human body. The OCPs bioaccumulation in adipose tissue triggers the excretion into human milk during breastfeeding. Hence, the present study determined eighteen OCPs residues in the breast milk of mothers from the Western Region of Bahia State, Brazil. Nine different residue species were found, including beta-Hexachlorocyclohexane (9.24?±?0.00?ng g^?1 fat), delta- Hexachlorocyclohexane (22.15?±?10.48?ng g^?1 fat), Heptachlor (58.08?±?74.13?ng g^?1 fat), Aldrin (142.65?±?50.65?ng g^?1 fat), Dieldrin (774.62?±?472.68?ng g^?1 fat), Endosulfan I (408.44?±?245.51?ng g^?1 fat), Dichloro-diphenyl-dichloro-ethylene (29.17?±?22.42?ng g^?1 fat), Dichloro-diphenyl-trichloro-ethane (28.87?±?0.00?ng g^?1 fat) and Methoxychlor (1699.67?±?797.43?ng g^?1 fat). The Methoxychlor presence in all samples may reveal a recent exposure, while Dieldrin and Endosulfan I analyses can point to distant past exposure.     

Monitoring of pesticide residues in a cotton crop soil

Abstract

This paper reports on the residues of methyl parathion (O,O‐dimethyl O‐4‐nitrophenyl phosphorothioate), trifluralin (α, α, α‐trifluoro‐2, 6‐dinitro‐N, N‐dipropyl‐p‐toluidine), endosulfan [(1, 4, 5, 6, 7, 7‐hexachloro‐8, 9, 10‐trinorborn‐5‐en‐2, 3‐ylenebismethylene) sulfite] and dimethoate (O, O‐dimethyl S‐methylcarbamoylmethyl phosphorodithioate) in a cotton crop soil. Soil samples (0–15 cm) were collected at different periods from the cotton crop farm and subjected to Soxhlet extraction. The extracted material was analysed after clean‐up by a HP5890 II gas Chromatograph equipped with a ⁶³Ni electron‐capture detector (ECD‐⁶³Ni) and fitted with a 25m x 0,2mm i.d. fused silica capillary column [Ultra‐2 (5% phenylmethyl polysiloxane)]. The recoveries of the pesticide residues from the spiked control soil were determined after Soxhlet extraction and C₁₈ cartridges clean‐up by using radiotracer techniques with the corresponding ¹⁴C‐pesticides. The results show that in the cotton crop soil the pesticide residues under study were present in the range of 0.1 to 0.4 mg ? kg^‐1. Endosulfan was found to be rapidly degraded in the soil and formed a sulfate metabolite.     

Estimation of sampling uncertainty for determination of pesticide residues in plant commodities

In order to provide residue data for refining the estimated sampling uncertainty, a coordinated research program was initiated for performing field studies on residues in individual items of leafy vegetables, small and large crops. The trials were carried out in 13 countries with 3 small fruits, 5 large crops, 2 medium/large crops and 3 leafy vegetables. The 25 pesticide active ingredients applied represented the dicarboximide (3), organophosphorus (8), synthetic pyrethroids (5), phthalimides (2), organochlorine (1) and other types of pesticides (6). In addition, 11 supervised field trials were performed in grapes and lettuce by the pesticide manufacturers, and their results were provided for evaluation. The studies represented actual agriculture practice around the world, and provide reliable data for estimation of sampling uncertainty. Based on the 12346 residue data, the best estimate for the relative sampling uncertainty for composite samples, assuming sample size of 10 for small crops and leafy vegetables and 5 for large crops, with 95% confidence limits in brackets are: small commodities: 0.25 (0.20–0.29); Brassica leafy vegetables: 0.20 (0.16–0.24); large commodities: 0.33 (0.29–0.38).