电镀企业排放及周边水环境中典型全氟及多氟烷基化合物的环境风险评估

ENVIRONMENTAL RISK ASSESSMENT OF TYPICAL PER- AND POLYFLUOROALKYL SUBSTANCES IN ELECTROPLATING FACTORIES DISCHARGE WASTEWATER AND SURROUNDING AQUAIC ENVIRONMENT

齐观景

11849066

硕士

环境科学与工程

史江红

2020-05-28

2020-07-10

哈尔滨工业大学

深圳

全氟及多氟烷基化合物（PFASs）是一类高度氟化的脂肪族化合物，具有持久性和生物蓄积性，对水环境构成了潜在威胁。电镀行业是水环境中PFASs的重要来源之一，因此掌握电镀企业PFASs排放特征并评估其在周边水环境中的风险，对电镀行业PFASs的污染防控具有重要意义。本研究通过对电镀企业及周边水环境实地采样分析和文献调研，掌握企业排放和周边水环境中PFASs的种类和分布特征，结合定量构效关系（QSAR）、种间关系预测（ICE）、物种敏感度分布（SSD）模型，推断了典型PFASs的预测无效应浓度（PNEC），最后基于商值法定量评估了企业排放和周边水环境中PFASs的环境风险。具体研究内容和结果如下：（1）获取了电镀企业排放及周边水环境中PFASs的种类和浓度。建立了水环境中19种PFASs的分析方法，方法检出限为0.1~2.0 ng/L，回收率为81%~122%；分析了深圳市某电镀园区企业排放及周边水环境中PFASs的浓度特征，分别检测到了13种、15种，其中分别以全氟辛烷磺酸（PFOS，16.9 ng/L）和全氟丁烷磺酸（PFBS，132 ng/L）含量最高；通过文献调研获取了广州市某电镀企业周边水环境中11种PFASs的浓度数据。基于实地采样分析和文献调研，确定全氟丁烷羧酸（PFBA）、全氟辛烷羧酸（PFOA）、PFBS、全氟己烷磺酸（PFHxS）、PFOS和6:2 氯-全氟醚磺酸（6:2 Cl-PFESA）等6种PFASs为电镀企业排放和周边水环境中的特征PFASs，开展环境风险评估。（2）通过QSAR模型补充了PFASs对羊角月牙藻、小球藻、斑马鱼、大型溞等4个物种的急性毒性数据。基于MOPAC，EPI Suite等软件计算的分子描述符，建立了4个物种预测PFASs急性毒性与亲脂性、极化和电子受体等性质相关的QSAR模型（R2>0.370）。使用非交叉验证和留一法交叉验证对模型进行评价，四个模型均表现出较高的预测能力和一定的统计学意义。（3）通过ICE模型构建了替代物种与预测物种的种间结构毒性关系，进一步完善了本地物种的急性毒性数据。利用34个ICE模型，结合QSAR和实验所得急性毒性数据，分别补充了PFBA、PFOA、PFBS、PFHxS、PFOS、6:2 Cl-PFESA的13个、34个、17个、13个、14个、13个急性毒性数据。（4）通过SSD模型推算了PNEC。综合文献收集、QSAR预测、ICE补充的急性毒性数据，建立了QSAR-ICE-SSD毒性效应推算方法。针对六种PFASs，通过拟合的正态分布曲线获得了生态系统5%的物种受影响的浓度值（HC5），除以评估因子5，得到6种PFASs的PNEC推算值，分别为804 μg/L（PFBA）、6.27×103 μg/L（PFOA）、1.01×4 μg/L（PFBS）、1.29×4 μg/L（PFHxS）、2.09×103 μg/L（PFOS）、254 μg/L（6:2 Cl-PFESA）。对毒性数据详实的PFOA和PFOS，通过毒性实验数据构建SSD模型，以此推算PNEC。结果表明该推算值分别是QSAR-ICE-SSD方法推算值的1.16倍（PFOA）和1.20倍（PFOS），建立的QSAR-ICE-SSD毒性效应推算方法可靠，可用于PFASs的PNEC推算。（5）根据PFASs的暴露浓度和PNEC推算值，采用商值法评估了PFASs的环境风险。结果表明，深圳市某电镀园区企业排放和周边水环境中6种PFASs的环境风险均较低（风险商范围0~1.21×10-4），风险最高的为PFOS（风险商为1.21×10-4）。

Per- and polyfluoroalkyl substances (PFASs) refer to a class of highly fluorinated aliphatics. PFASs are threatening to aquatic environment as they are persistent and bio-accumulative. The electroplating factories are important source of PFASs in aquatic environment. To figure out PFASs emission characteristic of electroplating factories and risk in surrounding aquatic environment is significant. PFASs concentration was got from field sampling analysis and paper searching. PNEC values of target PFASs were calculated by quantitative structure activity relationship (QSAR) model, interspecies relationship prediction (ICE) model, and species sensitivity distribution (SSD) model. The environmental risk was evaluated by risk quotients.1) Different kinds of PFASs were detected in the wastewater of electroplating factories and surrounding aquatic environment. The analysis method of 19 PFASs in water samples was established. The limit of detection was between 0.1 and 2.0 ng/L, and the recovery rates were between 81% and 122%. Concentrations of PFASs in wastewater of electroplating factories in Shenzhen were analyzed. Perfluorooctane sulfonate (PFOS, 16.9 ng/L) and perfluorobutane sulfonate (PFBS, 132 ng/L) were the main PFASs in wastewater and surrounding aquatic environment. Concentrations of 11 PFASs in aquatic environment surrounding other electroplating factories were obtained through literature searching. Perfluorobutane carboxylic acid (PFBA), perfluorooctanoic acid (PFOA), PFBS, perfluorohexane sulfonic acid (PFHxS), PFOS and 6:2 Cl-perfluoroalkyl ether sulfonate acid (6:2 Cl-PFESA) were chosen as target PFASs in the wastewater and surrounding aquatic environment to evaluate the environmental risk based on field sampling analysis and literature searching.2) Acute toxicity data of PFASs to Pseudokirchneriella subcapitata, Chlorella vulgaris, Danio rerio and Daphnia magna were supplemented by QSAR models. QSAR models (R2>0.370) to predict acute toxicity of PFASs to the mentioned species were established based on the molecular descriptor calculated using MOPAC 2016 and EPI Suit. The models were evaluated using non-cross-validation and leave-one-out cross-validation. All models showed high predictive ability and certain statistical significance. It was found that the acute toxicity of PFASs was related to the lipophilicity, polarization and electron acceptor properties.3) The ICE models were used to construct the interspecies toxicity relationship between the substitute species and the predicted species, which further supplemented acute toxicity data of local species. We used ICE models to supplement the acute toxicity data of PFBA (13 pieces), PFOA (34 pieces), PFBS (17 pieces), PFHxS (13 pieces), PFOS (14 pieces), 6:2 Cl-PFESA (13 pieces).4) The PNEC values were calculated through the SSD model. QSAR-ICE-SSD method was established based on QSAR models, ICE models and experimental toxicity data. The concentration values affecting 5% species in the ecosystem (HC5) were obtained using the fitted normal distribution curve. HC5 is divided by evaluation factor 5 to obtain PNEC values, namely 804 μg/L (PFBA), 6.27×103 μg/L (PFOA), 1.01×104 μg/L (PFBS), 1.29×104 μg/L (PFHxS), 2.09×103 μg/L (PFOS), 254 μg/L (6:2 Cl-PFESA). Based on the PFOA and PFOS toxicity data from published papers, local species SSD models were constructed to estimate PNEC values. The results showed that it was 1.16 times (PFOA) and 1.20 times (PFOS) more than PNEC values from QSAR-ICE-SSD method. It indicted that the QSAR-ICE-SSD method established in this study was reliable to calculate toxicity effect and could be used for PNEC calculation of PFASs.6) The environmental risk of the six PFASs in factory’s discharge and surrounding aquatic environment was evaluated based on the ratio of exposure concentration and PNEC values. The environmental risk of target PFASs in the factory’s discharge and surrounding aquatic environment was low (0~1.21×10-4) and the highest risk quotient value (1.21×10-4) was from PFOS exposure.

电镀企业 全氟及多氟烷基化合物 环境风险评估 定量构效关系模型 种间关系预测模型 物种敏感度分布模型

electroplate industry per- and polyfluoroalkyl substances environmental risk assessment quantitative structure activity relationship model interspecies correlation estimation model species sensitivity distribution model

中文

联合培养

南方科技大学

齐观景. 电镀企业排放及周边水环境中典型全氟及多氟烷基化合物的环境风险评估[D]. 深圳. 哈尔滨工业大学,2020.