重金属-纳米颗粒联合毒性评价模型研究进展

李雪玲; 盖鑫磊; 陈敏东; 毋赟

doi:10.7524/j.issn.0254-6108.2022031502

重金属-纳米颗粒联合毒性评价模型研究进展

江苏省大气环境监测与污染控制高技术重点实验室，江苏省大气环境与装备技术协同创新中心，南京信息工程大学环境科学与工程学院，南京，210044

通讯作者: Tel：025-58731394, E-mail：wuyun@nuist.edu.cn

基金项目:
国家自然科学基金（32171617，22176100）资助.

Toxicity prediction models for heavy metal and nanoparticle mixtures

Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (AEET), School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing , 210044, China

Corresponding author: WU Yun, wuyun@nuist.edu.cn

Fund Project: the National Natural Science Foundation of China (32171617, 22176100).

摘要: 基于单一污染物的毒性研究无法准确评估真实环境中多污染物共存的生态与健康风险，因此大量研究开始关注混合物联合毒性这一更具挑战性和现实性的课题. 本文围绕当前毒理学领域的主要研究对象——重金属、纳米材料，综述了重金属混合物、纳米颗粒混合物、以及两者混合物的联合作用评价方法，包括基于重金属间无相互作用或相互作用可忽略的浓度加和（concentration addition，CA）模型、独立作用（independent action，IA）模型及其改进模型，基于生物生理过程的生物配体模型（biotic ligand model，BLM）、毒代-毒效动力学模型（toxicokinetictoxicodynamic，TK-TD）、动态能量平衡（dynamic energy budget，DEB）理论，基于颗粒物结构性质的定量纳米结构-活性关系（quantitative nanostructure-activity relationships，QNAR，或nano-QSAR）模型等，介绍了各类模型的基本原理、适用条件和应用情况. 最后对重金属-纳米颗粒联合毒性的未来研究方向进行了展望.
- 重金属 /
- 纳米颗粒 /
- 联合作用 /
- 毒性预测模型.
Abstract: Toxicity studies based on single pollutant can not exactly evaluate the ecological and health risks of multiple pollutants in environment, a large number of studies have focused on the joint toxicity of mixtures, a more challenging and realistic topic. Heavy metal and nanomaterial are two of the most notable pollutants in the field of toxicology, thus this paper summarizes the evaluation methods of heavy metal mixtures, nanoparticle mixtures and their combined effects, including models based on no interaction or negligible interaction between pollutants (e.g., the concentration addition model, CA; independent action model, IA; and their derived models), models based on physiological process (e.g., biological ligand model, BLM; toxicokinetictoxicodynamic, TK-TD; dynamic energy budget theory, DEB), models based on the structural properties of particles (quantitative nanostructure activity relationships, QNAR or nano QSAR), etc. The basic principles of these models and their applicable conditions are introduced first, and then perspectives for future research in combined toxicity of heavy metals and nanoparticles are discussed in the end.
- heavy metal /
- nanoparticle /
- joint toxicity /
- toxicity prediction model.

随着工业水平的不断进步，人类社会的发展对能源的需求量越来越高，但是化石燃料仍为主要的能源来源^[1]. 到2040年，全球能源需求量将增长30%左右，表明CO₂排放量将继续增长. 因此，有效利用CO₂并开发新能源是本世纪面临的艰巨挑战. 通过直接利用可持续的太阳能，将CO₂和H₂O光催化还原为有用的太阳能燃料，是解决碳排放和能源短缺的一种极具前景的策略.

水滑石（LDH）具有高比表面积、结构可调性、酸碱可调性、记忆效应、热稳定性、无毒、价格低廉、光稳定性等优点，受到研究者的广泛关注. 研究表明，LDH的表面羟基还可以与价带空穴反应生成羟基自由基（HO•），这可作为关键的中间物种参与氧化过程^[2-3]. 此外，含Ti的LDH具有丰富的Ti–O表面缺陷，这些缺陷可作为光生载流子的有效捕获位点，促进了电子和空穴的分离^[4-6]，进而提高Ti基水滑石（Ti-LDH）的光催化性能. 近几年来，ZnTi-LDH在光催化领域展现出令人瞩目的潜能，被广泛应用于光催化领域. 例如，Xia等^[7]合成了具有良好晶体结构的Fe₃O₄/ZnTi-LDH、CeO₂/ZnTi-LDH和SnO₂/ZnTi-LDH等3种复合材料，并将它们用于光催化降解酸性红14 （AR14），展现出较高的高催化活性. 但是，ZnTi-LDH可见光活性偏低，仍需对其做进一步的改性.

硫化处理是一种简单常用的改性方法，可对半导体的带隙宽度和电子和空穴的分离效率进行调控，有效的改善半导体的光催化性能. 例如，Du等^[8]通过水热法合成了MoS₂-CdS-TiO₂催化剂用于光催化水分解. Zou等^[9]采用湿法硫化制备了C/ZnS/ZnO空心球，用于光催化四环素的降解. 与C/ZnO相比，硫化后的C/ZnS/ZnO空心球光生电子和空穴的分离效率和可见光吸收性能显著提升. Ren等^[10]以In金属有机框架作为前驱体制备了CdS/In₂O₃复合材料，其中CdS和In₂O₃纳米分子之间紧密相连形成异质结结构，促进了光生载流子的分离，进而提高其光催化水分解制氢效率. Yang等^[11]采用水热法制备了核壳结构的In₂S₃/In₂O₃纳米材料，通过在In₂O₃进行硫化，可有效缩短其禁带宽度并提高其可见光利用率，进而有效提高其光催化水分解效率. 此外，硫化时间对催化剂的光催化活性也有较大的影响，当硫化30  min时，C/ZnS/ZnO样品在可见光下具有最佳的光降解活性. 但截至到目前为止，对LDH进行硫化处理后用于光催化H₂O还原CO₂的研究还未见报道.

为此，本文首先通过水热法制备了ZnTi-LDH，然后利用Na₂S溶液对其进行硫化处理，并借助XRD、SEM、TEM、UV-Vis以及电化学工作站等对其晶体结构、形貌、光电性能等进行表征，探究硫化时间对光催化CO₂还原性能的影响.

1. 实验部分（Experimental section）

1.1 实验药品

本文所用实验药品如表1所示.

表 1 原料试剂一览表

Table 1. The list of materials and reagents

试剂 Reagent	规格 Specifications	生产厂家 Manufacturer
硝酸锌（Zn(NO₃)₂·6H₂O）	分析纯	天津市大茂化学试剂厂
硫化钠（Na₂S·9H₂O）	分析纯	天津市风船化学试剂科技有限公司
尿素	分析纯	上海阿拉丁生化科技股份有限公司
四氯化钛（TiCl₄）	分析纯	上海阿拉丁生化科技股份有限公司
二氧化碳（CO₂）	≥99.999%	天津联博化工股份有限公司
氩气（Ar）	≥99.999%	天津东祥特种气体有限公司

| Show Table

DownLoad: CSV

1.2 催化剂的制备

1.2.1 ZnTi-LDH的制备

采用水热法制备了ZnTi-LDH光催化剂，其步骤如下：将2.38 g Zn(NO₃)₂·6H₂O和3.0 g尿素溶于70 mL去离子水中，随后将0.44 mL的TiCl₄快速加入到上述混合溶液中，室温下剧烈搅拌30 min后将其置于100 mL水热釜中，在130 ℃下水热48 h. 最后，离心收集所得到的沉淀，去离子水洗涤4次后置于烘箱中50 ℃下干燥24 h.

1.2.2 ZnTi-LDH的硫化

称取200 mg制备的ZnTi-LDH样品，加入装有40 mL 0.1 mol·L⁻¹ Na₂S溶液的烧杯中，于60 ℃下分别硫化1 h、2 h和3 h后，得到所需样品. 将它们分别命名为ZnS/TiO₂/S-1 h、ZnS/TiO₂/S-2 h和ZnS/TiO₂/S-3 h.

1.2.3 催化剂/陶瓷基板的制备

在光催化活性评价过程中，将催化剂负载于陶瓷基板上，其制备方法如下：首先将硅溶胶与拟薄水铝石粉按3∶1 （体积（mL）∶质量（g））的配比在烧杯中均匀混合，然后将其倒入长、宽、高分别为5.0、2.5、0.5 cm的矩形模具中，在室温下干燥24 h后置于马弗炉中700 ℃下煅烧4 h.

将50 mg催化剂样品在1 mL去离子水中超声分散1 h，然后用胶头滴管将所得悬浮液均匀滴于陶瓷基板表面，并在60 ℃下干燥2 h.

1.3 催化剂的表征

1.3.1 结构形貌表征

采用Bruker公司（德国）生产的D8-Focus X射线衍射仪（XRD）对催化剂的物相组成和结构进行分析，测试条件为：石墨单色化的铜靶，Cu Kα射线辐射波长0.15418 nm，管电压40 kV，管电流40 mA，扫描速度8 °·min⁻¹，扫描范围2θ=20°—80°.

采用日立公司（日本）生产的加速电压为5 kV的S-4800 场发射扫描电子显微镜（SEM）测试催化剂的尺寸和表面形貌.

采用电子公司（日本）生产的加速电压为300 kV 的JEM-2100F 场发射透射电子显微镜（TEM）观察测量催化剂晶粒的形貌和晶格间距. 制备方法如下：将催化剂充分研磨后，称取适量粉末放于0.5 mL样品管中，加入无水乙醇，超声处理至样品分散均匀，随后用胶头滴管取少许悬浮液滴于超薄碳膜上，待其自然晾干.

1.3.2 光电性能表征

采用Perkin Elmer公司生产的紫外-可见分光光度计（Lambda 750型）对催化剂的吸光性能进行测试. 以BaSO₄作为背景板，波长范围为200—800 nm.

采用上海辰华公司生产的CHI-660型电化学工作站对催化剂的光电性能进行表征. 测试条件：三电极系统，电解质溶液为0.1 mol·L⁻¹的Na₂SO₄，工作电极为涂覆催化剂样品的ITO玻璃，对电极为铂电极，参比电极为Ag/AgCl电极. 工作电极的制备如下：称取0.4 mg样品放于离心管中，向其中滴加0.2 mL乙醇、0.2 mL水和20 μL萘酚，超声处理至样品分散均匀，随后用胶头滴管将悬浮液滴涂在ITO玻璃上，室温下自然晾干.

1.4 光催化活性测试

CO₂光催化还原活性测试在总体积为300 mL的石英玻璃管循环体系中进行^[12].

如图1所示，气体在进入反应体系之前需经净化，去除掉可能存在的微量CO，三通阀14接入管路3，经出气口15抽气进行检验. 当三通阀3和14接入管路01时为吹扫系统，接入管路01和02时为循环系统. 具体操作过程如下，将催化剂/陶瓷基板垂直放置在装有石英砂的石英反应器底部，通过CO₂鼓泡将水带入反应器中参与反应. 光照之前，用CO₂吹扫反应器1 h，去除反应器中的空气和催化剂表面可能吸附的有机物，随后将气路切换到循环系统，打开蠕动泵和氙灯，模拟光源采用装有AM 1.5 G滤光片的300 W氙灯（PLS-SXE 300c氙灯） . 反应结束后，用注射器从13号取样口抽取0.1 mL气体，借助热导检测器进行气相色谱分析.

图 1 反应装置示意图

Figure 1. Schematic diagram of experimental set-up for photocatalytic reduction of CO₂

1.CO₂钢瓶；2.气体净化器；3,14.三通阀；4.二通阀；5.加热炉；6.鼓泡管；7.反应器；8.陶瓷片； 9.石英砂；10.通光孔；11.氙灯光源；12.蠕动泵；13,15.取样口

1.CO₂ cylinder; 2.Gas purifier; 3,14.Three-way valve; 4.Two-way valve; 5.The heating furnace ;6.Water bubbler; 7.Photoreactor; 8.Ceramic chip; 9.Quartz sand; 10.The optical aperture;11.Xenon lamp light source; 12.Peristaltic pump; 13,15.Sampling port

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2. 结果与讨论（Results and discussion）

2.1 XRD结构分析

借助XRD对未硫化和硫化的ZnTi-LDH的晶体结构进行表征，结果如图2所示. 从图2可观察到，归属于ZnTi-LDH （003）、（006）、（009）、（100）、（101）、（012）、（110）和（113）晶面的尖锐特征衍射峰^[13]，表明合成了结晶度较高的ZnTi-LDH. 此外，还可观察到归属于锐钛矿相TiO₂ （101）、（004）和（211）晶面的衍射峰. 借助0.1 mol·L⁻¹的Na₂S 对ZnTi-LDH进行硫化处理后，ZnTi-LDH的特征峰消失，并可观察到归属于立方相ZnS （0010）、（110）和（1110）晶面的特征峰.

图 2 硫化前后 ZnTi-LDH样品的XRD谱图

Figure 2. XRD patterns of ZnTi-LDH which was sulfated and unsulfated

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2.2 形貌分析

借助SEM和TEM对未硫化和硫化后的ZnTi-LDH的形貌、组成、尺寸大小等进行了研究，结果如图3所示. 由图3（a）中的SEM照片和图3（c）中的TEM照片可以看出，所合成的ZnTi-LDH具有由二维纳米薄片堆叠而成的片层结构. 借助Na₂S对其进行硫化后，可观察到生成的ZnS/TiO₂由纳米颗粒组成，且随着硫化时间的增加，纳米颗粒之间堆叠更加紧密（图3（d-f））. 这可能是由于硫化时间越长，生成的硫化物也越多，当硫化处理超过一定时间后，硫化物在相互作用下发生团聚或堆积. 为了进一步探究ZnS/TiO₂的结构组成，借助高倍透射电镜（HRTEM）对其进一步探究. 从图3（g）可以清楚的观察到ZnS和TiO₂的存在，其中晶格间距约为0.352 nm、0和0.239 nm的晶格条纹可分别归属于金红石相TiO2（101）面和ZnS（110）面. 此外，HRTEM图像还显示ZnS和TiO₂之间存在紧密的界面接触，上述结果表明ZnTi-LDH硫化之后复合材料已成功制备.

图 3 SEM照片（a） ZnTi-LDH, （c） ZnS/TiO₂/S-1h; TEM 照片（b） ZnTi-LDH, （d） ZnS/TiO₂ /S-1h, （e） ZnS/TiO₂/S-2h, （f） ZnS/TiO₂/S-3h; HRTEM 照片（g） ZnS/TiO₂ /S-1h

Figure 3. SEM images of （a） ZnTi-LDH and （b） ZnS/TiO₂/S-1h; TEM images of （c） ZnS/TiO₂ and （d） ZnS/TiO₂/S-1h, （e） ZnS/TiO₂/S-2h, （f） ZnS/TiO₂/S-3h; HRTEM image of （g） ZnS/TiO₂/S-1h

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2.3 光电性能表征

图4（a）所示为未硫化和硫化的ZnTi-LDH紫外-可见漫反射光谱（UV-vis DRS）. 从图4可看出，ZnTi-LDH样品只对波长小于400 nm处的光具有吸收带，这是由于在Zn原子、Ti原子及其配体形成的MO₆八面体中发生了配体-金属之间的电荷转移（LMCT）^[14]. ZnTi-LDH经Na₂S硫化后，其吸收带边明显发生了红移，在400—500 nm范围内产生了明显的光吸收，并且随着硫化时间的延长，ZnS/TiO₂可见光吸收性能均逐渐增强. 这可归因于硫化后生成的ZnS和TiO₂之间相互作用，减小了带隙宽度，降低了电子跃迁需要的能量，进而促进了配体-金属和金属-金属之间的电荷转移. 为了得到准确的禁带宽度，利用Kubelka-Munk公式^[15]计算了未硫化和硫化的ZnTi-LDH的带隙宽度，（αhv）² 与hv的关系曲线如图4 （b）所示. 从图4（b）和表2可以看出，ZnTi-LDH及ZnS/TiO₂/S-1 h、ZnS/TiO₂/S-2 h和ZnS/TiO₂/S-3 h样品的带隙宽度分别为3.42、3.38、3.35、3.32 eV，表明硫化处理得到的ZnS/TiO₂样品的带隙变窄. 且硫化时间越长，带隙宽度越窄，因此催化剂样品的光吸收性能越好. 但同时带隙变窄可能对电子和空穴的分离产生不利影响. 因此，需要做进一步的研究，以寻求最为合适的硫化时间.

图 4 硫化前后ZnTi-LDH样品的（a） UV-vis DRS, （b） Kubelka-Munk函数变换图

Figure 4. （a） UV-vis DRS and （b） Photo energy plots transformed by Kubelka–Munk function of ZnTi-LDH which was sulfated and unsulfated

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表 2 未硫化和硫化处理的ZnTi-LDH的禁带宽度和导价带位置

Table 2. The band gap and the positions of the conduction band and valence band of ZnTi-LDH which was sulfated and unsulfated

催化剂 Catalysts	禁带宽度/eV Band gap	E_FB/（V vs. NHE）	E_CB/（V vs. NHE）	E_VB/（V vs. NHE）
ZnTi-LDH	3.42	−0.25	−0.45	2.97
ZnS/TiO₂/S-1h	3.38	−0.77	−0.97	2.41
ZnS/TiO₂/S-2h	3.35	−0.71	−0.91	2.44
ZnS/TiO₂/S-3h	3.32	−0.47	−0.67	2.65

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采用电化学工作站对未硫化和硫化的ZnTi-LDH的光电化学性能做进一步的探究，结果如图5所示. 从瞬态光电流响应测试结果（图5（a））可以发现，对ZnTi-LDH水滑石进行硫化处理后，光电流密度有所增加，这是由于硫化后带隙变窄，使得电子跃迁所需的能量降低，从而产生更多的光生电子和空穴. 但是，ZnTi-LDH在硫化1 h后具有最高的光电流密度，进一步增加硫化时间，光电流密度反而下降，这可归因于硫化时间变长后，带隙较窄，促进了光生电子和空穴的复合. 通过电化学阻抗谱图研究了未硫化和硫化处理的ZnTi-LDH与电解液之间的界面电荷转移电阻和分离效率，其结果如图5（b）所示. 由图5可知，ZnTi-LDH在未经硫化处理时，Nyquist曲线均呈现出较大曲率半径的圆弧，意味着较大的阻抗. 硫化处理后，圆弧的曲率半径有所降低，其中，ZnS/TiO₂/S-1 h具有最小的阻抗，也即具备着最好的界面电荷传输速率与光生电子-空穴分离效率，这一结果与瞬态光电流响应结果相吻合.

图 5 硫化前后ZnTi-LDH样品的光电流响应图（a）、电化学阻抗图（b）和莫特肖特基曲线（c）

Figure 5. （a） Photocurrent response, （b） EIS Nyquist and （c） Mott-Schottky plots of ZnTi-LDH which was sulfated and unsulfated

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为了进一步研究硫化对能带结构、载流子浓度和半导体类型的影响，利用Mott-Schottky曲线计算频率为10 kHz时的平带电势（E_FB）（式1）.

$1/C=（2/{\varepsilon} _{r}{\varepsilon} _{0}eN_{d}A^{2}）[（E-E_{FB}）-k_{b}T/e]$

$(1)$

$E（{\rm{NHE}}）=E（{\rm{Ag}}/{\rm{AgCl}}）+0.197$

$(2)$

$E_{{\rm{VB}}}=E_{{\rm{CB}}}+E_{{\rm{g}}}$

$(3)$

其中，C为比容量，ε₀是真空的介电常数，ε_r是半导体的介电常数，e是基本电荷，A是电极的有效面积，N_d是样品的电子载流子密度，E是外加电位，k_b是玻尔兹曼常数，T是绝对温度. 图5（c）所示表明，未硫化和硫化处理的ZnTi-LDH的莫特肖特基曲线斜率均为正，表明ZnTi-LDH为n型半导体，且硫化并未改变其半导体类型. 借助公式（2）将电极电势转换为标准氢电极（NHE）电势，计算可得，ZnTi-LDH、ZnS/TiO₂ /S-1 h、ZnS/TiO₂ /S-2 h 和ZnS/TiO₂ /S-3 h的E_FB分别为−0.25、−0.77、−0.71、−0.47 eV.

众所周知，n型半导体的导带电势（E_CB）比其平带势（E_FB）负0.1或0.2 V，在本文中，取−0.2 V来计算硫化前后ZnTi-LDH样品的E_CB值，结合带隙值，通过公式（3）计算出它们的价带电势（E_VB），所有计算结果列于表2. 由表2可知，硫化处理可以明显的提高导带底的电子能级，从而有利于提高光生电子的还原能力.

2.4 光催化活性测试

在200 ℃、模拟太阳光照射下以H₂O为还原剂测试了未硫化和硫化处理的ZnTi-LDH光催化还原CO₂的性能，结果如图6所示. 从图6可看出，纯的ZnTi-LDH光催化CO₂还原为CO的产率仅为5.70 μmol·（g·h）⁻¹，具有较低的光催化活性. 硫化处理得到的ZnS/TiO₂光催化性能得到很大的提升，且其活性随硫化时间呈规律性变化，其中，ZnS/TiO₂/S-1 h的光催化CO产率最高，为25.35 μmol·（g·h）⁻¹，是纯ZnTi-LDH的4.4倍. 此外，对其副产物H₂进行了检测. 结果显示，ZnS/TiO₂/S-1 h的氢气产率最高，为15.54 μmol·（g·h）⁻¹，是纯ZnTi-LDH的1.5倍.

图 6 硫化前后ZnTi-LDH样品的CO和H₂的光催化产率

Figure 6. CO and H₂ photocatalytic yield of of ZnTi-LDH which was sulfated and unsulfated

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为了进一步测试硫化处理的ZnTi-LDH的稳定性，以具有最高催化活性的ZnS/TiO₂/S-1 h样品进行5次光催化稳定性测试，结果如图7所示. 图7结果显示，ZnS/TiO₂/S-1 h在5次循环之后活性下降了18.2%，表明ZnS/TiO₂/S-1 h具有相对较高的稳定性.

图 7 ZnS/TiO₂/S-1 h样品的稳定性测试

Figure 7. The stability test of ZnS/TiO₂/S-1 h

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3. 结论（Conclusion）

通过水热法制备了具有二维纳米片层结构的ZnTi-LDH，然后利用硫化钠溶液对其进行了硫化处理. 研究结果表明，硫化后的样品片层结构部分被破坏，形成了二维纳米片负载小颗粒的形貌，为光催化反应提供了更多的活性位点. 硫化后的样品，对可见光的吸收性能增强，光生载流子的分离效率提高，导带电子的还原能力增加. 活性测试结果证明，所有硫化后的样品的CO₂还原活性均有所提升，而ZnS/TiO₂/S-1 h样品具有最高的光催化活性，其CO和H₂的产率分别为25.35 μmol·(g·h)⁻¹和15.54 μmol·(g·h)⁻¹，分别是ZnTi-LDH的4.4倍和1.5倍.

图 1 纳米颗粒的细胞毒性机制

Figure 1. Cytotoxic mechanism of nanoparticles

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图 2 重金属-纳米颗粒之间的相互作用

Figure 2. Possible interactions between heavy metals and nanoparticles

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表 1 联合毒性评价方法在重金属混合物研究中的应用

Table 1. Application of joint toxicity assessment methods for heavy metal mixtures

测试金属Test metal	受试生物Test organism	评价方法Evaluation method	模型评价效果Result of model evaluation	参考文献Reference
Ni、Zn、Cr、Cd四元混合物	V. fischeri （费氏弧菌）	CA、IA	CA和IA模拟效果基本一致，对四元重金属混合物拟合效果较好	[20]
Zn、Ni、Pb、Cr、As、Cu二元混合物	Scenedesmus obliquus（斜生栅藻）	CI	CI方法可以较为准确地表示出污染物联合毒性随组分和比例变化时联合作用的转变	[24]
Fe、Mn、Zn、Cu、Pb、Cr多元混合物	Human lung epithelial cells（A549）	CA、IA、IAM、IAI模型	CA、IA、IAM模型的预测结果与实验值存在偏差，IAI模型模拟效果最好	[25]
Ni、Fe、Cr、Cd二元混合物	Chlorella pyrenoidosa（蛋白核小球藻）、Selenastrum capricornutum（羊角月牙藻）	CA、IA、PCR-IAM	CA和IA会高估或低估混合毒性，PCR-IAM可准确评估二元混合物的联合作用	[26]
Cu、Zn、Cr、Cd二元混合物	Caenorhabditis elegans	CA、IA	相较于IA模型，CA的预测能力更好	[27]
Ni、Cu、Mn二元混合物	Paronychiuruskimi （Collembola）	TU	对于低效应区评价结果较为可靠	[28]
Ni、Zn、Cu、Cd、Pb二元混合物	Daphnia magna、Ceriodaphnia dubia、Hordeum vulgare	CA、IA	IA评价结果更为准确，CA结果比较保守. 在低效应水平下，CA高估了对Daphnids和H. vulgare的混合毒性	[29]
Cd、Cu、Ni、Pb、Zn二元混合物	Phaeocystis antarctica、Cryothecomonas armigera	CA、IA	适合重金属对这两种受试生物的毒性预测	[30]
Ni、Cu、Cd三元混合物	Lemna minor	CA	基于内剂量的CA可以在一定范围内准确评估毒性	[31]
Cd、Cu、Ni、Zn三元混合物	Daphnia magna	CA、IA	CA模型预测Cd、Cu、Ni三元混合物的死亡率优于IA模型，总体预测结果表明CA预测较好	[32]
Cd、Ni、Cr二元混合物	Chlorella pyrenoidosa、Selenastrum capricornutum	CA、CI	CA可描述混合物毒性作用. CI可定量表征二元混合物毒性效应大小，且能比较置信区间内任一效应水平下混合物的联合作用强度	[33]
Y、La、Ce二元混合物	Triticum aestivum L.	CA、IA	CA与IA模型预测结果的准确性相当	[34]
Ag、Cd、Cu、Ni、Pb、Zn二元混合物	Lymnaea stagnalis	CA、IA	与CA相比，IA的预测偏差相对更小	[35]
Hg、Cu、Ni二元混合物	Tetrahymena thermophila（嗜热四膜虫）	MTI	可判断1﹕1浓度比和1﹕1毒性比下金属混合物的联合毒性作用	[36]

测试金属Test metal	受试生物Test organism	评价方法Evaluation method	模型评价效果Result of model evaluation	参考文献Reference
Ni、Zn、Cr、Cd四元混合物	V. fischeri （费氏弧菌）	CA、IA	CA和IA模拟效果基本一致，对四元重金属混合物拟合效果较好	[20]
Zn、Ni、Pb、Cr、As、Cu二元混合物	Scenedesmus obliquus（斜生栅藻）	CI	CI方法可以较为准确地表示出污染物联合毒性随组分和比例变化时联合作用的转变	[24]
Fe、Mn、Zn、Cu、Pb、Cr多元混合物	Human lung epithelial cells（A549）	CA、IA、IAM、IAI模型	CA、IA、IAM模型的预测结果与实验值存在偏差，IAI模型模拟效果最好	[25]
Ni、Fe、Cr、Cd二元混合物	Chlorella pyrenoidosa（蛋白核小球藻）、Selenastrum capricornutum（羊角月牙藻）	CA、IA、PCR-IAM	CA和IA会高估或低估混合毒性，PCR-IAM可准确评估二元混合物的联合作用	[26]
Cu、Zn、Cr、Cd二元混合物	Caenorhabditis elegans	CA、IA	相较于IA模型，CA的预测能力更好	[27]
Ni、Cu、Mn二元混合物	Paronychiuruskimi （Collembola）	TU	对于低效应区评价结果较为可靠	[28]
Ni、Zn、Cu、Cd、Pb二元混合物	Daphnia magna、Ceriodaphnia dubia、Hordeum vulgare	CA、IA	IA评价结果更为准确，CA结果比较保守. 在低效应水平下，CA高估了对Daphnids和H. vulgare的混合毒性	[29]
Cd、Cu、Ni、Pb、Zn二元混合物	Phaeocystis antarctica、Cryothecomonas armigera	CA、IA	适合重金属对这两种受试生物的毒性预测	[30]
Ni、Cu、Cd三元混合物	Lemna minor	CA	基于内剂量的CA可以在一定范围内准确评估毒性	[31]
Cd、Cu、Ni、Zn三元混合物	Daphnia magna	CA、IA	CA模型预测Cd、Cu、Ni三元混合物的死亡率优于IA模型，总体预测结果表明CA预测较好	[32]
Cd、Ni、Cr二元混合物	Chlorella pyrenoidosa、Selenastrum capricornutum	CA、CI	CA可描述混合物毒性作用. CI可定量表征二元混合物毒性效应大小，且能比较置信区间内任一效应水平下混合物的联合作用强度	[33]
Y、La、Ce二元混合物	Triticum aestivum L.	CA、IA	CA与IA模型预测结果的准确性相当	[34]
Ag、Cd、Cu、Ni、Pb、Zn二元混合物	Lymnaea stagnalis	CA、IA	与CA相比，IA的预测偏差相对更小	[35]
Hg、Cu、Ni二元混合物	Tetrahymena thermophila（嗜热四膜虫）	MTI	可判断1﹕1浓度比和1﹕1毒性比下金属混合物的联合毒性作用	[36]

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表 2 联合毒性评价方法在纳米颗粒混合物研究中的应用

Table 2. Application of joint toxicity assessment methods for nanoparticles

纳米颗粒Nanoparticle	受试生物Test organism	评价方法Evaluation method	模型评价效果Result of model evaluation	参考文献Reference
ZnO NPs和CuO NPs二元混合物	Scenedesmus obliquus	CA、IA	CA比IA模型更精确	[76]
Cu NPs和ZnO NPs二元混合物	Lactuca sativa L	CA、IA	IA模型更适合评估Cu NPs和ZnO NPs混合物的毒性	[77]
TiO₂纳米球和TiO₂纳米管二元混合物	Scenedesmus obliquusChlorella pyrenoidosa	TU、CA、IA	TU评估表明TiO₂ NPs和TiO₂ NTs混合物对藻类产生相加作用. CA和IA模型能分别有效的预测混合物对 S. obliquus 和 C. pyrenoidosa的联合毒性	[78]
ZnO NPs和Ag NPs二元混合物	Daphnia magna	CA、IA	CA对二元纳米混合物的毒性预测偏差较IA小	[79]
Zn NPs、Cu NPs、ZnO NPs、CuO NPs二元混合物	V. fischeri	IA	IA模型预测结果存在较大偏差	[80]
ZnO NPs、NiO NPs、CuO NPs、TiO₂ NPs、 Fe₂O₃ NPs的二元混合物	Chlorella vulgaris	CA、IA	CA比IA模型更精确	[81]

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1. 实验部分（Experimental section）
1.1 实验药品
1.2 催化剂的制备
1.3 催化剂的表征
1.4 光催化活性测试
2. 结果与讨论（Results and discussion）
2.1 XRD结构分析
2.2 形貌分析
2.3 光电性能表征
2.4 光催化活性测试
3. 结论（Conclusion）

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随着工业的发展以及人类消耗的激增，经各种途径排放进入环境中的重金属和纳米材料大为增加^[1-2]. 其中土壤和水体是重要的汇^[3]. 同时使用纳米颗粒减少作物中重金属累积、去除水中重金属污染等的发展^[4-6]，也导致了环境中重金属和纳米颗粒的共存问题. 重金属可在不同营养级生物体内发生生物积累，还可影响生物的代谢活动和免疫能力，改变生物生理生化状态，诱发动物和人类多种疾病产生^[7-8]. 纳米颗粒由于尺寸微小，相较于大颗粒更易进入生物体内且进入后更难清除. 另外，纳米颗粒可诱导DNA突变，损伤线粒体结构，产生氧化应激、炎症反应，破坏细胞和器官的正常功能^[9-10]. 传统污染物Cd、Pb、Cu、As等金属和类金属元素，以及新型污染物金属和非金属纳米材料，都是当前毒理学的重要研究对象.

实际环境中，生物往往暴露于多种污染物，产生不同于单一污染物暴露的毒性效应. 首先，一种金属的存在可影响其他金属的生物效应. 如Cu可增强海洋浮游硅藻对Zn的吸收^[11]，而Zn与Ni对小麦毒性存在拮抗作用^[12]. 其次，一种纳米颗粒可通过干扰其他纳米颗粒的分散稳定性、表面性质以及离子释放等^[13]，进而影响其生物效应. 最后，重金属与纳米颗粒之间也存在相互作用. 一方面，纳米颗粒可改变金属的生物吸收，如叶面喷洒TiO₂纳米颗粒可减少玉米幼苗对Cd的吸收^[14]；另一方面，重金属的存在会影响纳米颗粒的团聚行为，同时重金属对生物生理（如细胞膜通透性、氧化损伤等）的影响也会改变纳米颗粒的生物转运与毒性^[15]. 当有其它因素存在时，纳米颗粒与重金属的联合效应更为复杂，如TiO₂ NPs与Cd的联合效应与水中Ca的浓度密切相关^[16].

显然，研究污染物的联合毒性比研究单一污染物对生物的毒性效应更具实际意义. 然而由于污染物的联合毒性取决于其组成，对环境中各种污染物组成混合物的联合毒性均采用实验研究又不切实际^[17-18]，因此需要根据各种污染物的混合体系采用适合的数学模型进行毒性评价. 对于多元混合物的毒性评估经历了从定性到定量的发展阶段，出现了多种模型预测方法. 但由于环境中污染物种类多、性质差异大，对于不同类型污染物的评估方法差异较大. 鉴于重金属和纳米颗粒对生态环境和人类健康的不利作用，本文概述了重金属、纳米颗粒以及两者共存的联合毒性评价模型，总结了各评价方法的优缺点及其应用，旨在为这些混合物毒性的精确评估提供方法参考.

1. 重金属联合毒性评价方法（Joint toxicity evaluation method for heavy metals）

2. 纳米颗粒联合毒性评价方法（Joint toxicity evaluation method for nanoparticles）

3. 重金属-纳米颗粒联合毒性评价方法（Evaluation methods for joint toxicity of heavy metals and nanoparticles）

4. 总结与展望（Summary and prospect）

随着新型纳米材料的广泛使用以及人们对于单一污染物毒性剂量、作用机理的了解深入，越来越多的研究开始关注它们的联合毒性这一更具挑战性和现实性的问题：

（1）对于重金属联合毒性的评价，目前使用较多的仍是基于重金属间无相互作用或相互作用可忽略的CA、IA模型及其改进模型. 考虑到重金属生物累积过程中的相互作用，一些基于生物生理过程的概念模型，如BLM、TK-TD、DEB等，已开始应用于重金属的混合物研究，它们是揭示污染物相互作用机理、提高模型预测准确性的新型尝试和发展方向.

（2）对于纳米颗粒联合毒性的预测，目前的研究还处于起步阶段，通常使用CA、IA等模型判别颗粒物之间的联合作用类型，但这些模型对纳米颗粒联合毒性的预测还存在一定的不确定性，其适用性与纳米颗粒的种类有关. 鉴于颗粒物的结构性质对效应的决定作用，构建适用于颗粒混合物的QNAR模型可能是一个研究方向，但需要大量实验表征混合后颗粒物的结构性质.

（3）关于重金属-纳米颗粒混合物的联合毒性评价，现有研究也是主要使用CA、IA等模型定性定量判别混合物的联合作用，但是金属离子与颗粒物之间的相互作用限制了模型预测的准确性，今后需要进一步明确它们的相互作用机制. 近来，QNAR也开始被用于预测纳米颗粒与重金属混合物的联合作用，但这种模型的普适性、混合物描述符的建立、运算法则的选取等，都需要更多的数据验证.

随着新型纳米材料的不断研发，大数据与人工智能时代的机器学习技术在评价纳米材料及其混合物的毒性与安全方面表现出巨大优势，相较传统方法能够大幅节省人力、物力和财力. 但目前机器学习主要针对单种纳米颗粒，缺少混合物数据及其生理意义解释. 也有研究建议将机器学习与组学相结合，从而实现基于机理的高通量分析.

参考文献 (121)

重金属-纳米颗粒联合毒性评价模型研究进展

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