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水质生物毒性检测作为传统理化检测方法的补充,不仅能快速检测出水中是否含有毒性污染物,同时还可反映多种有毒物和污染物的综合毒性[1-2]。目前,用于水质生物毒性检测的生物传感器主要利用有毒物或污染物对不同营养级的指示生物(发光细菌、藻类、溞类、大型无脊椎动物和鱼类等)的呼吸作用、生长发育或运动能力的抑制效应来进行检测[2]。其中较高营养级的指示生物更能反映有毒物或污染物对环境质量的影响程度,但其检测成本较高、耗时也较长且需要专业的生物培养技能与装置,这导致该类群指示生物在实际应用时限制性较大;低营养级的指示生物特别是发光细菌因灵敏度高、响应快且生长周期短已被广泛用于水质生物毒性检测,但发光细菌中应用最多的费氏弧菌(Vibrio fischeri)和明亮发光杆菌(Photobacterium phosphoreum)实为海洋细菌,其生长需在含盐的溶液中,且溶液的浊度和色度会影响检测精度,这也同样限制了其在淡水生境中的广泛应用[3]。因此,寻找一种快速、灵敏、抗干扰能力强且低成本的新型生物毒性传感器成为了现实所需。
近年兴起的微生物燃料电池(microbial fuel cell, MFC)型生物毒性传感器以阳极电活性细菌(Geobacter spp.、Shewanella spp.和Pseudomonas spp.等)为指示生物,当阳极无毒性污染物存在时,电活性细菌通过催化分解有机底物产生电子,电子由胞外电子传递过程转移至阳极,再经电池外电路到达阴极形成稳定电流;当阳极有毒性污染物存在时,电活性细菌的活性或胞外电子传递受到抑制,导致MFC型生物毒性传感器产生的电流降低,通过检测有毒污染物存在时电池产电量的变化则可定量反映水质生物毒性[4-7]。该传感器具有灵敏、抗干扰能力强、无需外加能源、稳定和可自我修复等特点,已被用于检测BOD、COD、挥发性脂肪酸、重金属、氰化物、甲醛和抗生素等[4-7]。然而,目前关于MFC型生物毒性传感器用于检测农药的研究报道较少。KIM等[8]于2007年最早发现,当MFC型生物毒性传感器以1.0 mg·L−1有机磷农药(二嗪磷)为检测物时,所产生的电量降幅高达61%。2012年,王博等[9]利用MFC型生物毒性传感器构建出一套水质生物毒性预警系统,并成功预警了由强降雨导致自来水厂取水区域内农药倒灌引发的饮用水污染事件。2019年,CHOULER等[10]发现,0.3 mg·L−1三嗪类除草剂(莠去津)可使MFC型生物毒性传感器的回路电流下降12%。这些研究结果均表明,MFC型生物毒性传感器可对含农药污水产生毒性响应,但因农药种类多,来源复杂,再加上MFC型生物毒性传感器对不同农药检测的研究匮乏,进而导致MFC型生物毒性传感器检测农药的相关应用极为有限。
为探究MFC型生物毒性传感器对农药污染物的检测性能,本文研究了MFC型生物毒性传感器对溴氰菊酯(菊酯类杀虫剂)、敌百虫(有机磷杀虫剂)、百菌清(有机氯类杀菌剂)、莠去津(三嗪类除草剂)和烟嘧磺隆(磺酰脲类除草剂)5种典型农药检测的剂量-效应关系,评估了MFC型生物毒性传感器中毒后的自我修复能力,并对不同混合农药的生物毒性进行了检测与对比研究。
微生物燃料电池型生物毒性传感器对5种典型农药的毒性检测
Detection of five typical agrichemicals using a microbial fuel cell-based biotoxicity sensor
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摘要: 目前,微生物燃料电池(microbial fuel cell, MFC)型生物毒性传感器被广泛用于检测重金属、氰化物和抗生素等污染物,但将其应用于检测农药的研究极少。为此,探究了MFC型生物毒性传感器对溴氰菊酯、敌百虫、百菌清、莠去津和烟嘧磺隆5种典型农药的检测性能。实验结果表明:这5种典型农药的响应(产电抑制率)均与其浓度的对数呈良好的线性关系,且溴氰菊酯、敌百虫、百菌清、莠去津和烟嘧磺隆使MFC型生物毒性传感器产电抑制率达到10%的质量浓度分别低至0.016、0.070、0.013、0.005和0.033 mg·L−1;中毒后,MFC型生物毒性传感器的恢复时间随农药浓度的增加而延长,但240 min内均可快速恢复稳定;另外,这5种典型农药所配制的不同混合农药的生物毒性均高于单一农药。以上结果表明,MFC型生物毒性传感器对这5种典型农药的响应灵敏,检出限较低且中毒后恢复速度快,具有快速检测和预警水体农药污染的应用潜力。Abstract: At present, microbial fuel cell (MFC)-based biotoxicity sensors were widely attended to detect heavy metals, cyanide and antibiotics in water, while the detection of agrichemicals was rarely discussed. In this paper, five typical agrichemicals including deltamethrin, trichlorfon, chlorothalonil, atrazine, and nicosulfuron were detected using an MFC-based biotoxicity sensor. The results showed that the response (coulombic yield inhibition ratio) of each of these five agrichemicals was in a good linear relationship with the logarithm of its concentration. As low as 0.016 mg·L−1 deltamethrin, 0.070 mg·L−1 trichlorfon, 0.013 mg·L−1 chlorothrin, 0.005 mg·L−1 atrazine or 0.033 mg·L−1 nicotsulfuron could result in a coulombic yield inhibition ratio of 10% for MFC-based biotoxicity sensors. After the biotoxicity detection, the recovery time of MFC-based biotoxicity sensors increased with the increase of agrichemical concentrations, and stable voltage output could be achieved within 240 min for all tested concentrations of these five typical agrichemicals. In addition, compared with the single agrichemical, joint biotoxicities of different mixed agrichemicals prepared by the five typical agrichemicals were apparently higher. This study confirmed that MFC-based biotoxicity sensors possessed sensitive response, low detection limits to these five agrichemicals and robust recovery ability after being poisoned, thus providing an alternative and promising method for fast water quality monitoring and early warning of agrichemical pollutions in water.
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Key words:
- microbial fuel cell /
- biosensor /
- biotoxicity /
- agrichemical /
- recovery time
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