望虞河西岸九里河中四种除草剂的污染现状

基于气相色谱-质谱联用(GC-MS)法结合固相萃取(SPE)前处理技术,建立了水中4种除草剂氯草定、阿特拉津、乙草胺和异丙甲草胺残留的分析方法,于2018年春(4、5月)、秋(9、10月)和冬(1、3月)季对太湖流域望虞河西岸九里河水体中4种除草剂的污染现状进行调查分析。结果表明,4种除草剂的加标回收率为71. 2%～108%,RSD均10%,方法检出限为3. 5～6. 0 ng/L。九里河水体中氯草定、阿特拉津、乙草胺和异丙甲草胺4种除草剂质量浓度分别为未检出～0. 025 7,0. 019 1～1. 19,未检出～0. 026 0和未检出～0. 094 3μg/L。4种除草剂中阿特拉津最高值接近《地表水环境质量标准》(GB 3838—2002)限值,其他3种其值较低,氯草定首次在太湖流域水体中检出。     

Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats,India using water quality indices

Water quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over-drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre-monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca²⁺>Na+>Mg²⁺>K⁺ and the anions HCO₃⁻>Cl⁻>CO₃²⁻ based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.     

珠江口表层水中多环芳烃的分布特征及健康风险评估

分别于2015年2、5、8、11月在珠江八大入海口采集表层水体样品,应用固相萃取富集法对该区域表层水体中16种USEPA优控多环芳烃(PAHs)的时空分布特征进行分析,并利用终生致癌风险增量模型(ILCR)对该区域的饮水健康风险进行评价。结果表明:珠江口4个季度所采集的水样中,∑15PAHs的浓度范围为18.0~50.3 ng/L,含量处于中等水平。其中7种强致癌性∑7PAHs的浓度范围为1.53~3.73 ng/L,占∑15PAHs的5.89%~11.1%,∑15PAHs和∑7PAHs在枯水期(2、11月)样品中明显高于丰水期(5、8月)。就组成特征而言,各采样点PAHs以3、4环为主。珠江口表层水中非致癌类PAHs的危害商数值为0.99×10~(-5)~2.73×10~(-5),远低于USEPA规定的阈值(1);致癌类PAHs产生的健康风险为6.50×10~(-8)~2.37×10~(-7),其中Ba P导致的饮水途径健康风险最高,所有点位致癌类PAHs的健康风险均低于USEPA推荐的对致癌物质最大可接受风险水平(10~(-6)),表明珠江口表层水中PAHs尚不具备严重的致癌风险,但是仍然存在潜在的健康风险,需要重点控制和管理。     

松花江流域水生态环境质量评价研究

采用生物完整性指数(IBI)法评价松花江流域的水生态环境质量。对25个候选生物参数进行敏感度分析、Pearson相关性分析,最终筛选出由总分类单元数、EPT分类单元数、EPT密度、敏感种分类单元比例、敏感物种数量、Hilsenhoff生物指数(HBI)6个核心参数构成的IBI评价指标。采用95%分位数法建立了IBI评价标准,将IBI评价结果划分为5个等级:大于35.84为优,26.88~35.84为良好,17.92~26.88为一般,8.96~17.92为较差,小于8.96为很差。结果表明,建立的IBI评价方法适用于松花江流域水生态环境质量评价,松花江流域各位点30.0%生物状况为优和良好,23.3%为一般;46.7%为较差和很差,说明流域内近一半区域的水生态质量存在不同程度的受损。流域生境质量主要处于一般-良好的状态;水质处于轻度污染。     

汉丹江(陕西段)水质变化特征分析

基于2008—2012年陕西省境内汉江、丹江干流14个断面的水质监测数据,采用单因子评价法、平均综合污染指数法和秩相关系数法等对该段水体的水质变化特征进行研究。结果表明,汉丹江(陕西段)断面水质以Ⅱ类、Ⅲ类为主,水质总体为优;水质综合污染状况呈下降趋势,其中汉江下降趋势显著;水质综合污染状况空间差异和区域分布特征明显,城区段污染大于郊区,各行政区段河流下游污染大于上游。流域水质主要受有机污染和营养盐因子影响,水体污染源主要来自城镇生活源和农业面源,工业源占比不大且排放行业较为集中。     

灌河口表层土壤多环芳烃污染调查

为了解灌河口工业区表层土壤中多环芳烃的污染水平及健康风险。于2017年4月份在灌河口化工园区、火力发电厂和钢铁工业园区采集30个表层土壤样品,利用气相色谱-质谱联用仪(GC-MS)对16种优控ω(PAH)进行了检测。结果表明,30个采样点16种PAH的ω(T-PAHs)总为1 212.8~12 264.5 ng/g,平均值为3 504.8 ng/g。其中单体PAH以Fl为主,平均比例高达19.4%,其次为Pyr(16.7%)和B[a]P(9.6%)。单体PAH相关性分析表明了污染物来源的一致性,主要来源于本地工业区原油、生物质和煤的燃烧过程。根据加拿大土壤环境质量标准,灌河口工业区87%的土壤PAHs污染超过了安全值,存在潜在的生态风险。     

水生态环境质量评价体系研究

流域水生态环境质量评价体系是为流域环境管理提供基础数据,协助管理者开展流域保护措施的重要技术支持。该文深入剖析了发达国家典型水生态环境质量评价体系,归纳分析了其体系框架、构成特点、方法适用性和借鉴意义。结合前期研究基础,对评价体系的技术内容进行了完善和补充,明确了参照点位的选择原则,补充了评价方法选择的技术路线,提出了增设和实施不同监测计划的方案,最终提出生态环境质量评价技术体系框架。     

江苏省太湖流域水生态健康评估的初步实践及展望

阐述了水生态健康的内涵与意义,从江苏省率先在太湖流域开展水生态环境功能分区管理的顶层设计,构建以水生态健康指标为核心的水生态健康评估技术体系,地方对照水生态环境功能区划的水生态分级管控目标开展的应用与实践结果等3个方面,回顾了江苏省太湖流域水生态健康评估工作的主要进展,提出了完善水生态健康评估技术体系和推进流域水生态健康评估工作的建议。     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Exposure assessment of operators to pesticides in Kongou,a sub-watershed of Niger River valley

The use of pesticides in horticultural sector in Niger has become an integral part of modern agriculture. Nevertheless, their inappropriate use can generate negative health effects to operators. A study was carried out among Kongou farmers in order to assess their potential dermal exposure (PDE). The UK-POEM model was used to quantify the PDE during mixing/loading and application according to the local practices. In order to determine which parts of the operator body are subject to most contamination during spraying and to validate the theoretical model used, a patch method was used with a tartrazine dye. The deposits of the tartrazine on patches were measured by colorimetry thanks to the absorbance value determined after their extraction in water and a calibration curve. A total of ten spraying trials (five trials with the hand-held sprayer and five others with the backpack sprayer) were performed by different producers at 0.5 and 1 m height for each trial. The survey shows that 92% of the farmers are illiterate and the most common active substances identified are organophosphate or pyrethroids insecticides. Seventy percent of operators do not use any personal protective equipment (PPE) during mixing/loading or spraying. The predictive systemic exposure levels vary from 0.0027?mg kg^?1 bw per day to 0.7692?mg kg^?1 bw per day for backpack sprayer and from 0.0261?mg kg^?1 bw per day to 0.9788?mg kg^?1 bw per day for hand-held sprayer, several times higher the Acceptable Operator Exposure Level (AOEL) for some actives substances. Theoretical modeling indicates more exposure of operator by a hand-held sprayer than a backpack sprayer. The patch method results show that the deposits of dye increase when the position of sprayer nozzle increases from 0.5 to 1 m for the two sprayers. All parts of the operator body are contaminated but lower body parts and chest are the most exposed. The patch method results also show that hand spraying contaminates operator more than backpack spraying, confirming the results of the theoretical model.