2020, Vol. 41
作为一类新兴污染物, 药物活性化合物(pharmaceutical active compounds, PhACs)主要用来预防、诊断和治疗人类和动物的许多疾病[1].据估计, 全球每年人均药物消费量约为15 g, 工业化国家则在50~150 g之间[2].大多数PhACs分子结构复杂, 不易挥发, 生物活性高, 大量使用导致PhACs在自然环境中大量赋存[3], 其生态健康风险引起人们的广泛关注[4~6].PhACs能通过固体垃圾、工业废水、生活污水、水产养殖、牲畜粪便和农业生产等多途径进入自然水体[7], 污水处理厂尾水排放被认为是PhACs进入自然水体的主要途径之一[8].前期研究发现, 在污水厂尾水排放口下游水体中PhACs的检出浓度明显要高于上游水体[9].Liu等[8]在对污水处理厂尾水受纳水体中PhACs检测发现：ETM等10种单体PhACs的赋存浓度为67.0~107.6 ng ·L-1, 总检出浓度在15.4~384.5 ng ·L-1之间[10].西班牙当地污水厂尾水受纳水体中78种PhACs的最高检出浓度达到23 μg ·L-1 [11].虽然PhACs检出浓度多在ng ·L-1~μg ·L-1范围, 但其长期暴露对生态系统安全甚至人类健康造成的不利影响不容忽视[12].Liu等[10]在对8种亲脂性PhACs的生物累积研究中发现, PhACs能在鱼的肝脏、肌肉、脑等组织中累积, 布洛芬(IPF)对鱼类产生高的慢性生态风险, 而ETM对绿藻产生高的急性和慢性生态风险.大型溞的慢性暴露实验结果表明：IPF和CFI等PhACs能影响大型溞正常生殖、生长状况, 随着PhACs暴露浓度的增加大型溞的死亡率逐渐上升(CFI暴露浓度为44.5 mg ·L-1时大型溞死亡率达到100%), 体长逐渐减小, 首胎产卵时间逐渐延长[13].天然水体中PhACs数量众多, 其联合毒理效应研究尚少, 在认知PhACs环境赋存的基础上, 应进一步加强其复合污染生态风险研究.
大型溞作为一种标准的模式生物, 具有生活周期短、繁殖快、经济、方便易得、培养简单、对毒物敏感和测试指标丰富等优点.大型溞属于浮游动物, 其健康与否, 将进一步影响水体中初级生产者和高级消费者的种群动态.本文以南京污水厂尾水受纳水体为研究区域, 分析水体中8种典型PhACs赋存现状, 即红霉素(ETM)、罗红霉素(ROX)、布洛芬(IPF)、酮康唑(KTC)、舍曲林(SER)、阿替洛尔(ATL)、氯贝酸(CA)和咖啡因(CFI)；结合PhACs环境赋存状况, 评价水体中典型PhACs的生态风险及其对大型溞的慢性毒理效应.
1 材料与方法 1.1 试剂与仪器CFI、ROX、IPF、ATL、CA和ETM购自于TCI Development Co., Ltd (Shanghai, China), 其纯度大于98%；KTC、SER购自于Dr.Ehrenstorfer (Augsburg, Germany), 其纯度大于98%；甲醇(色谱纯)购自于德国Merck公司.甲醇作溶剂配制1 mg ·L-1的储备液置于-20℃冰箱备用.超纯水由MF-A10超纯水机(美国Millpore公司)制备.
1.2 实验方法 1.2.1 样品采集本文选取了南京江宁污水厂尾水受纳水体为研究对象, 在污水厂尾水排放口下游1、2和3 km处各设置一个采样断面, 在2018年7月(夏季)和12月(冬季)进行了两次采样.利用水质采样器在水面下0.5 m处采集1 L水样放入棕色玻璃瓶中, 加入适量甲醇(5‰)以抑制细菌的生长, 所有点位的样品一式3份.样品瓶用泡沫塑料包裹, 放入含有干冰的样品储存箱中保存并迅速运回实验室.
1.2.2 水样的预处理水样用0.45 μm的玻璃纤维滤膜进行过滤.用5 mL甲醇、5 mL超纯水和5 mL二氯甲烷活化Waters HLB固相萃取柱.以3~5 mL ·min-1的流速对过滤后的水样进行富集.过完水样的柱子用10 mL超纯水进行淋洗, 并用氮气干燥.然后依次分别用3 mL甲醇、3 mL甲醇:二氯甲烷混合液(体积比=1 :1)和3 mL氨水:乙腈混合液(体积比=4.5% :95.5%)溶液洗脱, 洗脱液氮吹至干, 用甲醇定容至1 mL, 收集在1.5 mL棕色进样瓶中待测.
1.3 仪器检测与质量控制 1.3.1 仪器检测利用Waters Xevo TQ三重四级杆质谱仪(电喷雾离子源)对8种PhACs进行了定性定量分析, 配备ACQUITY BEH C18色谱柱, (2.1 mm×100 mm, 1.7 μm, 美国Waters公司)；柱温40℃.运用梯度洗脱的方法对目标药物进行洗脱, 正离子模式(ESI+)流动相包括A[水:甲醇(体积分数98% :2%)+0.05%甲酸]和B(甲醇+0.05%甲酸), 负离子模式(ESI－)流动相为A[水:甲醇混合液(体积分数98% :2%)+5 mmol ·L-1乙酸铵]和B(100%乙腈), 进样体积为5 μL, 流速为0.4 mL ·min-1.正离子模式流动相A梯度为0~0.25 min维持在90%, 0.3~1.0 min降到40%, 1.0~5.0 min降到0%, 5.0~6.0 min恢复到90%.负离子模式流动相A梯度为0~0.25 min维持在90%, 0.3~4.0 min降到10%, 4.0~5.0 min维持在10%, 5.0~6.0 min恢复到90%.
质谱条件：毛细管电压3.0 kV, 碰撞气体流速0.15 L ·min-1, 离子源温度：150℃；锥孔反吹气流量：50 L ·h-1；脱溶剂气温度：500℃；脱溶剂气流量：900 L ·h-1；采用多重反应监测模式(MRM)对目标化合物进行定性和定量.ATL、ETM、CFI、KTC、ROX和SER以正离子模式检测, 而CA和IPF用负离子模式检测.
1.3.2 质量控制与保证整个实验过程均进行严格的质量控制, 每批样品设置一个溶剂空白、一个野外空白和一个基质加标, 保证样品前处理技术的稳定.样品中污染物均使用外标法计算, 标准曲线由7个不同浓度梯度的混合标准溶液进行确定. 8种PhACs的检测限为0.04~0.16 μg ·L-1, 定量限为0.13~1.00 μg ·L-1, 回收率为71.2% ~92.6%, 相对标准偏差低于20%.溶剂空白和野外空白中未检出目标化合物.
1.4 大型溞毒性实验 1.4.1 受试生物大型溞(Daphnia magna)由中国科学院武汉水生生物研究所提供.实验开始前, 大型溞在实验室驯化14 d, 驯化介质为曝气24 h的纯净水；温度：(21±1)℃；光暗周期：16 h :8 h；光照强度：1 000 lx.每天定时喂食纯种斜生栅藻(Scenedesmus obliquus).
1.4.2 实验方法大型溞21 d慢性生殖毒性实验参照OECD方法进行[14].本实验设置清水对照组、溶剂对照组(0.1%甲醇)、环境浓度组和100倍环境浓度组, PhACs实验暴露组见表 1, 真实浓度与理论浓度相比, 偏差低于15%.随机选择一只6~24 h大型溞幼体放入含有50 mL暴露溶液的100 mL烧杯中, 每个实验组设置20个平行.所有的实验烧杯用透明薄膜封好以尽可能减少水分的蒸发, 同时在薄膜上开数个小孔以满足大型溞的生长需求, 然后将烧杯置于智能光照培养箱中, 光暗比为16 h : 8 h, 温度为(21±1)℃.大型溞暴露周期为21 d, 实验期间每隔2 d换一次暴露溶液并清洗烧杯, 同时每天用新鲜的斜生栅藻(90 000 cells ·L-1)喂养大型溞.每隔24 h观察记录大型溞的存活以及产卵情况. 21 d暴露结束后, 进行大型溞体长(包括尾刺)、心率、胸肢跳动数和游速等指标测定.
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表 1 混合暴露组中8种PhACs浓度设置/ng ·L-1 Table 1 Concentrations of eight PhACs in mixture exposure groups/ng ·L-1 |
1.4.3 测定项目
心率和胸肢跳动：将暴露21 d后存活的(以15 s内大型溞包括触角能够活动为准)大型溞放置于显微镜下观察, 用秒表计数统计心率和胸肢跳动(次·min-1)[15].
体长：在显微镜下用目微尺测量母溞体长, 母溞身体与刻度尺平行, 记录其对应的刻度(包括尾刺)[15].
游速：将大型溞放入培养皿, 加入刚好没过大型溞身体的水量, 使其只能水平游动, 录制其游动的视频, 再将视频导入tracker软件测量游泳轨迹、速度和加速度[15].
1.5 数据统计方法 1.5.1 风险评估方法风险熵值法(RQ法)是基于实验室毒理数据从化学响应角度对污染物的生态毒性及风险水平进行评估.RQ是污染物实际检出浓度(MEC)和预测无影响浓度(PNEC)的比值, RQ的计算公式见式(1)和(2).自然环境中污染物并不是单独存在的, 他们共同存在形成复合污染风险熵(MRQ), 计算公式见式(3)[16]：
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(1) |
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(2) |
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(3) |
式中, EC50：半数效应浓度, LC50：半致死浓度, AF：评估因子；RQ的分类标准：0.01≤RQ＜0.1为低风险；0.1≤RQ＜1中等风险；RQ≥1高风险.
1.5.2 数据分析所有数据都进行同方差性检验, 并以平均值±标准偏差的形式表示.采用One-Way ANOVA方差分析方法进行组间统计学分析, 并用Dunnett's t检验法进行显著性水平分析.评估结果线性分析采用Origin软件进行处理, 其他数据分析在SPSS上完成, P < 0.05表示具有显著性差异.
2 结果与讨论 2.1 PhACs在水体中的赋存特征目标物在本研究区域和世界其他区域的赋存状况见表 2, 8种PhACs均被检出, 单体平均浓度范围在1.0~75.9 ng ·L-1之间, 总浓度范围在27.6~368.8 ng ·L-1之间.抗生素类(ETM和ROX)、消炎类(IPF)、降血脂类(CA)、β阻滞类(ATL)、抗抑郁类(SER)、抗真菌类(KTC)和兴奋剂类(CFI)药物浓度范围分别为0.9~40.8、3.3~89.2、3.6~59.2、0.2~8.0、ND~8.6、ND~5.8、0.3~31.4和16.2~125.8 ng ·L-1. 8种PhACs中, ETM、ROX、CFI和IPF检出浓度相对较高, 分别达到了40.8、89.2、125.8和59.2 ng ·L-1.ETM和ROX都属于大环内酯类抗生素, 这是一类具有复杂大分子结构的化合物, 具有抗菌活性强、不易产生耐药性等优点, 广泛应用于人类及畜禽类的疾病治疗.Liu等10]对南京5个污水厂尾水受纳水体中PhACs检测发现：ETM和ROX的浓度范围为0.7~85.3 ng ·L-1和0.3~66.5 ng ·L-1, 与本文研究结果较为接近. CFI作为一种重要的兴奋剂和止痛剂被大量使用, 由于在自然水体中被广泛检出, 被视为污水厂尾水排放的重要标记物质[17].本研究中CFI的平均浓度范围为16.2~125.8 ng ·L-1, 低于中国厦门市7个污水厂中CFI的赋存水平(2.42~686 ng ·L-1)[18].IPF是一种非甾体抗炎药, 既可以用于风湿类关节炎的治疗, 也可以用于减轻中轻度的发热、头痛等[19].我国是IPF的生产和使用大国, 在我国自然水体中一直广泛检出.IPF在本研究中的检出浓度范围是3.6~59.2 ng ·L-1, 高于韩国污水处理厂中的赋存水平(ND~0.31 ng ·L-1)[20], 前期研究中发现现有污水处理工艺对IPF的去除率在77% ~99%之间[21, 22].
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表 2 8种PhACs在研究区域水体以及其他流域中的赋存1)/ng ·L-1 Table 2 Occurrence of eight PhACs in the receiving water of the study area and other watershed/ng ·L-1 |
从时间分布来看, PhACs夏季的检出浓度普遍低于冬季, 其中KTC、ETM、ROX、IPF季节变化较为明显, 4种PhACs冬季的平均检出浓度比夏季分别高出243%、356%、92.7%和45%, 该趋势与Jing等[25]的研究结果吻合.相较于冬季, 夏季河流水量充沛, 微生物生物群落丰富度高, 水流的稀释作用和生物降解可能导致了药物含量偏低, 而冬季气温较低, 微生物活性受到抑制, 药物降解速率降低且水量偏低, 再加上冬季用药量偏高, 这可能是冬季药物浓度偏高的主要原因.
2.2 PhACs的生态风险评价生态风险是人类活动或自然变化而引起的生态系统的结构组织的改变而导致整个生态系统功能损失的可能性大小.生态风险评价是通过定量分析来预测自然界中各种风险源对生态系统造成的风险及预测生态系统可接受该风险的程度, 是生态风险决策与管理的重要依据[26].定量风险表征方法是近年来使用比较普遍的评价方法, 包括风险因子法、生态系统风险表征、熵值法等.其中, 风险熵值法(RQ)应用比较广泛.
根据PhACs在水体中的最高检出浓度和目标物对水生生物的急慢性毒理数据(表 3), 本文利用熵值法风险评估模型对目标化合物生态风险进行了评估, 结果如图 1所示.从化合物风险特征来看, 在冬季ETM和KTC对绿藻产生了高生态风险, 在夏季对绿藻产生中等生态风险.前人研究发现, ETM等抗生素对多种水生生物具有慢性生态风险, 其中藻类对ETM最为敏感, 生长抑制半数效应浓度为20 μg ·L-1 [28].浮萍的生长抑制实验中发现KTC能够显著缩短浮萍的根长并减少其叶片数和干重, 其EC50为80~160 μg ·L-1[40], 藻类对抗生素等药物的敏感度远高于浮萍[41]. IPF和ATL在夏、冬两季均对鱼类产生高风险, IPF风险值在夏、冬两季分别达到5.61和5.92.研究发现IPF能诱导鱼体内抗氧化酶活性, 造成鱼体内雌性激素失调, 生殖能力降低, 死亡率提高[31, 42].Winter等[43]在对黑头鲦鱼(Pimephales promelas)的慢性暴露中发现, ATL长期暴露会影响黑头鲦鱼的生殖能力和胚胎发育.除此之外, ETM和KTC还分别对溞类和鱼类产生中等生态风险.大型溞暴露于浓度179 μg ·L-1的ETM 21 d, 其存活率、产卵次数、每胎产卵数都受到显著抑制[44].黑头鲦鱼21 d慢性暴露中发现KTC能够影响黑头鲦鱼类固醇的合成并降低其繁殖成功率[45].
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表 3 8种PhACs对藻类、蚤类和鱼类的慢性毒性数据 Table 3 Chronic toxicity data of eight PhACs for algae, daphnia, and fish |
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图 1 8种PhACs对绿藻、溞类和鱼类的风险熵及其贡献率 Fig. 1 Risk quotient and contribution rate of eight PhACs to algae, daphnia, and fish |
从混合风险来看, 冬季藻类对目标PhACs较为敏感, 混合风险达到8.34, 其次是鱼类(6.45)和溞类(MRQ=0.22)；夏季鱼类对目标PhACs最为敏感, 混合风险达到5.68, 其次是藻类(1.51)和溞类(0.08).整体来看, 冬季PhACs生态风险明显高于夏季.从单一药物风险贡献率来看, ETM和KTC是藻类MRQ的主要贡献者, 二者贡献率之和达到99%；同时ETM还是溞类MRQ的主要贡献者, 贡献率达到85%以上；而鱼类MRQ的主要贡献者为IPF, 贡献率达到92%以上.在江汉平原、珠江三角洲和黄河三角洲也发现相似的现象, ETM的混合风险贡献率达到60%以上[46], 这说明混合风险MRQ值的大小与污染物的总浓度没有必然联系, 总体风险熵值可能由一小部分高风险污染物来主导.
2.3 混合PhACs对大型溞的生长、生殖影响8种PhACs混合暴露对大型溞生殖、生长和发育影响见表 4.整个暴露期间所有暴露组大型溞死亡率低于10%, 清水对照组与溶剂对照组无明显差异, 下文讨论中以溶剂对照组作为参照.
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表 4 混合PhACs对大型溞生殖和生长指标的影响1) Table 4 Influence of mixed PhACs on reproductive and development index of Daphnia magna |
生殖能力作为测试污染物对生物损伤程度的一个指标, 已经逐渐在各项研究中得到应用[47].本文通过对大型溞性成熟时间和生殖能力等生殖特征的研究, 分析混合PhACs对大型溞生殖健康的影响.表 4显示, EC-PhACs和100 EC-PhACs两个实验组21 d暴露并未对大型溞的首胎产卵时间产生显著性影响(P>0.05), 有研究表明IPF在14 d慢性暴露下会延缓大型溞的首胎产卵时间, EC50为13.4 mg ·L-1[30].从生殖能力来看, EC-PhACs和100 EC-PhACs两个实验组都显著提高了每胎平均产卵数和21 d产卵总数(P < 0.05).但相对于环境浓度组EC-PhACs, 100倍环境浓度PhACs对大型溞生殖能力的诱导作用显著降低, 呈现低浓度刺激效应.前人研究结果表明, 由于大型溞低浓度药物暴露压力下的过度补偿机制, 36 μg ·L-1氟西汀能显著诱导大型溞的繁殖能力, 而与CA、ETM等药物的联合作用更加复杂, 无法用单一污染物作用机制预测[48].IPF对大型溞14 d的慢性暴露实验中, 当暴露浓度达到20 mg ·L-1时, 大型溞的产卵总数显著下降, 达到80 mg ·L-1时不再产卵[30].本文的暴露浓度在ng ·L-1~μg ·L-1的范围内, 接近环境浓度, 在这种低剂量暴露下可能引起大型溞对环境压力的过度补偿, 造成繁殖力增强.Fuertes等[49]的研究发现卡马西平、安定和普萘洛尔等药物在环境浓度下能显著提升大型溞生殖能力, 且三者混合暴露呈现浓度相加效应.
大型溞的游泳行为的变化受到其生理、感知、神经和肌肉系统等多方面的影响[47, 50], 监测大型溞的游泳速度、加速度等生态行为是评价污染物生态毒理效应的有效手段.表 4显示, EC-PhACs和100 EC-PhACs两个暴露组都显著提高了大型溞的游泳速度(P < 0.05), EC-PhACs显著提高了大型溞的游泳加速度(P < 0.05).现有研究表明, 污染物能够改变大型溞游泳活性, 污染物单独暴露多抑制大型溞活动能力, 而混合暴露造成的抑制率往往偏低.部分污染物也能诱导大型溞游泳速度加快, 如氨基甲酸酯、三氯蔗糖和兴奋剂等[50].CFI是一种神经系统兴奋剂, 它通过增加神经递质多巴胺的产生和释放提高大型溞的心率[51], 而心率的增加可能会刺激大型溞的神经、肌肉, 导致游泳活性的变化.
大型溞的心率、胸枝活动等生理指标被证实与生物的摄食、呼吸和代谢速率密切相关[50], 在各项研究中经常使用这两项指标来评价各类污染物对大型溞的不利影响[52].从表 4可以看出100 EC-PhACs暴露组显著抑制了大型溞的胸枝跳动和心脏跳动频次.急慢性毒理学研究表明β-阻滞剂(阿替洛尔、美托洛尔和普萘洛尔)对大型溞的心率和胸枝跳动都有明显的抑制作用, 且药物浓度越高, 抑制越明显[52].心率和胸肢跳动降低会造成血液流动减缓、摄食不足, 从而进一步影响大型溞营养物质和气体交换[15].
3 结论(1) 8种PhACs均有检出, 其中ETM、ROX、IPF和CFI这4种药物检出浓度相对较高, 分别在0.9~40.8、3.3~89.2、3.6~59.2和16.2~125.8 ng ·L-1范围内.
(2) 从混合风险来看, 冬季PhACs生态风险明显高于夏季, 冬季水生生物对PhACs的敏感度从高到低依次是藻类>鱼类>溞类, 而夏季为鱼类>藻类>溞类；混合风险贡献率较高的3种PhACs为ETM、KTC和IPF, KTC、ETM和IPF对藻类、溞类和鱼类的混合风险贡献率分别达到49%、85%和92%以上.
(3) 8种PhACs混合暴露能够改变大型溞的生殖、生理指标, 显著提高了大型溞生殖能力和游泳活性, 降低心率和胸肢跳动.
| [1] | Gurung K, Ncibi M C, Thangaraj S K, et al. Removal of pharmaceutically active compounds (PhACs) from real membrane bioreactor (MBR) effluents by photocatalytic degradation using composite Ag2O/P-25 photocatalyst[J]. Separation and Purification Technology, 2019, 215: 317-328. DOI:10.1016/j.seppur.2018.12.069 |
| [2] | Zhang Y J, Geißen S U, Gal C. Carbamazepine and diclofenac:removal in wastewater treatment plants and occurrence in water bodies[J]. Chemosphere, 2008, 73(8): 1151-1161. DOI:10.1016/j.chemosphere.2008.07.086 |
| [3] | Gimeno O, García-araya J F, Beltrán F J, et al. Removal of emerging contaminants from a primary effluent of municipal wastewater by means of sequential biological degradation-solar photocatalytic oxidation processes[J]. Chemical Engineering Journal, 2016, 290: 12-20. DOI:10.1016/j.cej.2016.01.022 |
| [4] | Omar T F T, Aris A Z, Yusoff F M, et al. Risk assessment of pharmaceutically active compounds (PhACs) in the Klang River estuary, Malaysia[J]. Environmental Geochemistry and Health, 2019, 41(1): 211-223. DOI:10.1007/s10653-018-0157-1 |
| [5] |
封梦娟, 张芹, 宋宁慧, 等. 长江南京段水源水中抗生素的赋存特征与风险评估[J]. 环境科学, 2019, 40(12): 5286-5293. Feng M J, Zhang Q, Song N H, et al. Occurrence characteristics and risk assessment of antibiotics in source water of the Nanjing reach of the Yangtze River[J]. Environmental Science, 2019, 40(12): 5286-5293. |
| [6] |
武旭跃, 邹华, 朱荣, 等. 太湖贡湖湾水域抗生素污染特征分析与生态风险评价[J]. 环境科学, 2016, 37(12): 4596-4604. Wu X Y, Zou H, Zhu R, et al. Occurrence, distribution and ecological risk of antibiotics in surface water of the Gonghu Bay, Taihu Lake[J]. Environmental Science, 2016, 37(12): 4596-4604. |
| [7] | Kleywegt S, Payne M, Ng F, et al. Environmental loadings of active pharmaceutical ingredients from manufacturing facilities in Canada[J]. Science of the Total Environment, 2019, 646: 257-264. DOI:10.1016/j.scitotenv.2018.07.240 |
| [8] | Liu J C, Dan X X, Lu G H, et al. Investigation of pharmaceutically active compounds in an urban receiving water:Occurrence, fate and environmental risk assessment[J]. Ecotoxicology and Environmental Safety, 2018, 154: 214-220. DOI:10.1016/j.ecoenv.2018.02.052 |
| [9] | Liu J C, Lu G H, Zhang Z H, et al. Biological effects and bioaccumulation of pharmaceutically active compounds in crucian carp caged near the outfall of a sewage treatment plant[J]. Environmental Science:Processes & Impacts, 2015, 17(1): 54-61. |
| [10] | Liu J C, Lu G H, Xie Z X, et al. Occurrence, bioaccumulation and risk assessment of lipophilic pharmaceutically active compounds in the downstream rivers of sewage treatment plants[J]. Science of the Total Environment, 2015, 511: 54-62. DOI:10.1016/j.scitotenv.2014.12.033 |
| [11] | Biel-Maeso M, Baena-Nogueras R M, Corada-Fernández C, et al. Occurrence, distribution and environmental risk of pharmaceutically active compounds (PhACs) in coastal and ocean waters from the Gulf of Cadiz (SW Spain)[J]. Science of the Total Environment, 2018, 612: 649-659. DOI:10.1016/j.scitotenv.2017.08.279 |
| [12] | Costa F, Lago A, Rocha V, et al. A review on biological processes for pharmaceuticals wastes abatement-a growing threat to modern society[J]. Environmental Science & Technology, 2019, 53(13): 7185-7202. |
| [13] | Bang S H, Ahn J Y, Hong N H, et al. Acute and chronic toxicity assessment and the gene expression of Dhb, Vtg, Arnt, CYP4, and CYP314 in Daphnia magna exposed to pharmaceuticals[J]. Molecular & Cellular Toxicology, 2015, 11(2): 153-160. |
| [14] | OECD. Test No. 211. Daphnia magna reproduction test[A]. In: OECD(Ed.). Guidelines for the Testing of Chemicals, Section 2[M]. Population, Paris: Organization for Economic Cooperration and Development, 2012. 202. |
| [15] | Liu J C, Shen J, Lu G H, et al. Multilevel ecotoxicity assessment of environmentally relevant bisphenol F concentrations in Daphnia magna[J]. Chemosphere, 2020, 240: 124917. DOI:10.1016/j.chemosphere.2019.124917 |
| [16] | Riva F, Zuccato E, Davoli E, et al. Risk assessment of a mixture of emerging contaminants in surface water in a highly urbanized area in Italy[J]. Journal of Hazardous Materials, 2019, 361: 103-110. DOI:10.1016/j.jhazmat.2018.07.099 |
| [17] | Caldas S S, Arias J L O, Rombaldi C, et al. Occurrence of pesticides and PPCPs in surface and drinking water in Southern Brazil:data on 4-Year Monitoring[J]. Journal of the Brazilian Chemical Society, 2019, 30(1): 71-80. |
| [18] | Wang Y W, Li Y, Hu A Y, et al. Monitoring, mass balance and fate of pharmaceuticals and personal care products in seven wastewater treatment plants in Xiamen City, China[J]. Journal of Hazardous Materials, 2018, 354: 81-90. DOI:10.1016/j.jhazmat.2018.04.064 |
| [19] | Davarnejad R, Soofi B, Farghadani F, et al. Ibuprofen removal from a medicinal effluent:A review on the various techniques for medicinal effluents treatment[J]. Environmental Technology & Innovation, 2018, 11: 308-320. |
| [20] | Han G H, Hur H G, Kim S D. Ecotoxicological risk of pharmaceuticals from wastewater treatment plants in Korea:occurrence and toxicity to Daphnia magna[J]. Environmental Toxicology and Chemistry, 2006, 25(1): 265-271. |
| [21] | Clara M, Strenn B, Gans O, et al. Removal of selected pharmaceuticals, fragrances and endocrine disrupting compounds in a membrane bioreactor and conventional wastewater treatment plants[J]. Water Research, 2005, 39(19): 4797-4807. DOI:10.1016/j.watres.2005.09.015 |
| [22] | Castiglioni S, Bagnati R, Fanelli R, et al. Removal of pharmaceuticals in sewage treatment plants in Italy[J]. Environmental Science & Technology, 2006, 40(1): 357-363. |
| [23] | Sharma B M, Be Dč anová J, Scheringer M, et al. Health and ecological risk assessment of emerging contaminants (pharmaceuticals, personal care products, and artificial sweeteners) in surface and groundwater (drinking water) in the Ganges River Basin, India[J]. Science of the Total Environment, 2019, 646: 1459-1467. DOI:10.1016/j.scitotenv.2018.07.235 |
| [24] | Subedi B, Balakrishna K, Sinha R K, et al. Mass loading and removal of pharmaceuticals and personal care products, including psychoactive and illicit drugs and artificial sweeteners, in five sewage treatment plants in India[J]. Journal of Environmental Chemical Engineering, 2015, 3(4): 2882-2891. DOI:10.1016/j.jece.2015.09.031 |
| [25] | Jiang L, Hu X L, Yin D Q, et al. Occurrence, distribution and seasonal variation of antibiotics in the Huangpu River, Shanghai, China[J]. Chemosphere, 2011, 82(6): 822-828. DOI:10.1016/j.chemosphere.2010.11.028 |
| [26] | Zhao X M, Yao L A, Ma Q L, et al. Distribution and ecological risk assessment of cadmium in water and sediment in Longjiang River, China:Implication on water quality management after pollution accident[J]. Chemosphere, 2018, 194: 107-116. DOI:10.1016/j.chemosphere.2017.11.127 |
| [27] | Ji K, Kim S, Han S, et al. Risk assessment of chlortetracycline, oxytetracycline, sulfamethazine, sulfathiazole, and erythromycin in aquatic environment:are the current environmental concentrations safe?[J]. Ecotoxicology, 2012, 21(7): 2031-2050. DOI:10.1007/s10646-012-0956-6 |
| [28] | Isidori M, Lavorgna M, Nardelli A, et al. Toxic and genotoxic evaluation of six antibiotics on non-target organisms[J]. Science of the Total Environment, 2005, 346(1-3): 87-98. DOI:10.1016/j.scitotenv.2004.11.017 |
| [29] | Lee Y J, Lee S E, Lee D S, et al. Risk assessment of human antibiotics in Korean aquatic environment[J]. Environmental Toxicology and Pharmacology, 2008, 26(2): 216-221. |
| [30] | Heckmann L H, Callaghan A, Hooper H L, et al. Chronic toxicity of ibuprofen to Daphnia magna:effects on life history traits and population dynamics[J]. Toxicology Letters, 2007, 172(3): 137-145. DOI:10.1016/j.toxlet.2007.06.001 |
| [31] | Han S, Choi K, Kim J, et al. Endocrine disruption and consequences of chronic exposure to ibuprofen in Japanese medaka (Oryzias latipes) and freshwater cladocerans Daphnia magna and Moina macrocopa[J]. Aquatic Toxicology, 2010, 98(3): 256-264. DOI:10.1016/j.aquatox.2010.02.013 |
| [32] | Geiger E, Hornek-Gausterer R, Sacan M T. Single and mixture toxicity of pharmaceuticals and chlorophenols to freshwater algae Chlorella vulgaris[J]. Ecotoxicology and Environmental Safety, 2016, 129: 189-198. DOI:10.1016/j.ecoenv.2016.03.032 |
| [33] | Vestel J, Caldwell D J, Constantine L, et al. Use of acute and chronic ecotoxicity data in environmental risk assessment of pharmaceuticals[J]. Environmental Toxicology and Chemistry, 2016, 35(5): 1201-1212. DOI:10.1002/etc.3260 |
| [34] | Henschel K P, Wenzel A, Diedrich M, et al. Environmental hazard assessment of pharmaceuticals[J]. Regulatory Toxicology and Pharmacology, 1997, 25(3): 220-225. DOI:10.1006/rtph.1997.1102 |
| [35] | Moore M T, Greenway S L, Farris J L, et al. Assessing caffeine as an emerging environmental concern using conventional approaches[J]. Archives of Environmental Contamination and Toxicology, 2008, 54(1): 31-35. DOI:10.1007/s00244-007-9059-4 |
| [36] | Zarrelli A, DellaGreca M, Iesce M R, et al. Ecotoxicological evaluation of caffeine and its derivatives from a simulated chlorination step[J]. Science of the Total Environment, 2014, 470-471: 453-458. DOI:10.1016/j.scitotenv.2013.10.005 |
| [37] | Johnson D J, Sanderson H, Brain R A, et al. Toxicity and hazard of selective serotonin reuptake inhibitor antidepressants fluoxetine, fluvoxamine, and sertraline to algae[J]. Ecotoxicology and Environmental Safety, 2007, 67(1): 128-139. DOI:10.1016/j.ecoenv.2006.03.016 |
| [38] | Santos L H M L M, Araújo A N, Fachini A, et al. Ecotoxicological aspects related to the presence of pharmaceuticals in the aquatic environment[J]. Journal of Hazardous Materials, 2010, 175(1-3): 45-95. DOI:10.1016/j.jhazmat.2009.10.100 |
| [39] | Furberg A. Environmental risk assessment of pharmaceutical exposure to fish in the swedish göta Älv River[D]. Göteborg, Sweden: Chalmers University of Technology, 2014. 9. |
| [40] | Haeba M, Bláha L. Comparison of different endpoints responses in aquatic plant Lemna minor exposed to ketoconazole[J]. Egyptian Journal of Natural Toxins, 2011, 8(1-2): 49-57. |
| [41] | Tripathi R D, Chandra P. Chromium uptake by Spirodela polyrrhiza (L.) schleiden in relation to metal chelators and pH[J]. Bulletin of Environmental Contamination and Toxicology, 1991, 47(5): 764-769. DOI:10.1007/BF01701147 |
| [42] | Bartoskova M, Dobsikova R, Stancova V, et al. Evaluation of ibuprofen toxicity for zebrafish (Danio rerio) targeting on selected biomarkers of oxidative stress[J]. Neuro Endocrinology Letters, 2013, 34(S2): 102-108. |
| [43] | Winter M J, Lillicrap A D, Caunter J E, et al. Defining the chronic impacts of atenolol on embryo-larval development and reproduction in the fathead minnow (Pimephales promelas)[J]. Aquatic Toxicology, 2008, 86(3): 361-369. |
| [44] | Meinertz J R, Schreier T M, Bernardy J A. Chronic toxicity of erythromycin thiocyanate to Daphnia magna in a flow-through, continuous exposure test system[J]. Bulletin of Environmental Contamination and Toxicology, 2011, 87(6): 621-625. DOI:10.1007/s00128-011-0415-8 |
| [45] | Ankley G T, Jensen K M, Kahl M D, et al. Ketoconazole in the fathead minnow (Pimephales promelas):reproductive toxicity and biological compensation[J]. Environmental Toxicology and Chemistry, 2007, 26(6): 1214-1223. DOI:10.1897/06-428R.1 |
| [46] |
刘昔, 王智, 王学雷, 等. 我国典型区域地表水环境中抗生素污染现状及其生态风险评价[J]. 环境科学, 2019, 40(5): 2094-2100. Liu X, Wang Z, Wang X L, et al. Status of antibiotic contamination and ecological risks assessment of several typical Chinese surface-water environments[J]. Environmental Science, 2019, 40(5): 2094-2100. |
| [47] | Liu Y H, Yan Z Y, Zhang L, et al. Food up-take and reproduction performance of Daphnia magna under the exposure of Bisphenols[J]. Ecotoxicology and Environmental Safety, 2019, 170: 47-54. DOI:10.1016/j.ecoenv.2018.11.106 |
| [48] | Flaherty C M, Dodson S I. Effects of pharmaceuticals on Daphnia survival, growth, and reproduction[J]. Chemosphere, 2005, 61(2): 200-207. DOI:10.1016/j.chemosphere.2005.02.016 |
| [49] | Fuertes I, Campos B, Rivetti C, et al. Effects of single and combined low concentrations of neuroactive drugs on Daphnia magna reproduction and transcriptomic responses[J]. Environmental Science & Technology, 2019, 53(20): 11979-11987. |
| [50] | Bownik A. Daphnia swimming behaviour as a biomarker in toxicity assessment:a review[J]. Science of the Total Environment, 2017, 601-602: 194-205. DOI:10.1016/j.scitotenv.2017.05.199 |
| [51] | Jeong T Y, Yoon D, Kim S, et al. Mode of action characterization for adverse effect of propranolol in Daphnia magna based on behavior and physiology monitoring and metabolite profiling[J]. Environmental Pollution, 2018, 233: 99-108. DOI:10.1016/j.envpol.2017.10.043 |
| [52] | Dzialowski E M, Turner P K, Brooks B W. Physiological and reproductive effects of beta adrenergic receptor antagonists in Daphnia magna[J]. Archives of Environmental Contamination and Toxicology, 2006, 50(4): 503-510. DOI:10.1007/s00244-005-0121-9 |