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Application of LEFC-2006 in Thallium Monitoring of Water Quality |
LIN Hai-lan1, HUANG Zhong-ting1*, CHEN Yang2, YU Tao1, YANG Yun-bo2, BI Jun-ping1, LIU Pei1 |
1. Hunan Province Environmental Monitoring Center, State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, Changsha 410019, China
2. Lihe Technology (Hunan) Co., Ltd., Changsha 410205, China
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Abstract Thallium, as a highly toxic heavy metal element, has strong accumulation, latency and mobility. The mining of thallium-containing deposits and the massive discharge of industrial three wastes can lead thallium to enter the surface environment, participate in the material cycle of the soil sphere, hydrosphere, atmosphere and biosphere, gradually enrich soil and water, and destroy the ecological environment. It will eventually endanger human health through the food chain. In recent years, thallium pollution emergencies in water quality have occurred from time to time. The analysis technology of thallium in the water environment has also become the research hotspot of thallium analysis technology. However, most of them focus on improving laboratory analysis methods, and there is little research on on-site monitoring of thallium in water quality. However, the laboratory analysis methods inevitably have pollution and loss in the process of transportation and preservation; It also leads to a certain lag in data timeliness, which is difficult to be applied to the emergency monitoring of thallium in water, which affects the analysis and disposal of pollution accidents and becomes the biggest bottleneck in the disposal of pollution accidents. In order to quickly and accurately respond to the on-site monitoring of thallium in water quality, the research on on-line monitoring technology in water quality has important application significance for thallium monitoring, which can realize the monitoring and early warning of thallium pollution in water and effectively reduce the risk of thallium poisoning caused by thallium pollution. A new monitoring technique of thallium in water quality based on the principle of the three electrode method is established in this paper. The instrument used in this method is small, portable and low-cost. It can be used not only for on-site monitoring of thallium pollution accidents but also for monitoring pollution sources and surface water risk. In this paper, the detection limit, accuracy, precision, method comparison and field application of the instrument are verified. The experimental results show that the detection limit of the method for the determination of thallium in water is 0.02 μg·L-1, which is consistent with the detection limit of the ICP-MS instrument; The relative error range of thallium standard solution is -5.5%~2.9%, and the range of relative standard deviation is 0.60%~6.2%, and the recovery of standard addition is 101%~127%. When the water sample content is above 0.08 μg·L-1, the method is comparable with laboratory ICP-MS in the field emergency monitoring and comparison, which shows that the technique is very applicable.
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Received: 2021-09-15
Accepted: 2022-03-23
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Corresponding Authors:
HUANG Zhong-ting
E-mail: 13643860@qq.com
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[1] CHEN Yong-heng, ZHANG Ping, WU Ying-juan, et al(陈永亨,张 平,吴颖娟,等). Journal of Guangzhou University·Natural Science Edition(广州大学学报·自然科学版),2013,12(4):26.
[2] ZHENG Ying-cong(郑颖聪). Science and Technology & Innovation(科技与创新),2014,(20):158.
[3] ZHANG Hou-mei(张厚美). China Environment Supervision(中国环境监察),2017,(6):53.
[4] YU Lei, LIU Li-bin, ZHU Rui-rui, et al(于 磊,刘荔彬,朱瑞瑞,等). Environmental and Development(环境与发展),2020,(9):138.
[5] QI Jian-ying, LI Xiang-ping, LIU Juan, et al(齐剑英,李祥平,刘 娟,等). Bulletin of Mineralogy, Petrology and Geochemistry(矿物岩石地球化学通报),2008,27(1):81.
[6] LIANG Yong-jin, DU Shao-xian, ZHANG Yin, et al(梁永津,杜韶娴,张 荧,等). Chemical Reagents(化学试剂),2014,36(8):734.
[7] The National Standard of the People’s Republic of China(中华人民共和国国家标准). GB 3838—2002 Environmental Quality Standards for Surface Water(地表水环境质量标准).
[8] MA Chao, KANG Xiao-feng, LÜ Tian-feng, et al(马 超,康晓风,吕天峰,等). Physical Testing and Chemical Analysis Part B: Chemical Analysis(理化检测: 化学分测),2020,56(2):232.
[9] National Environmental Protection Standards of the People’s Republic of China(中华人民共和国国家环境保护标准). HJ 168—2020 Technical Guideline for the Development of Environmental Monitoring Analytical Method Standards(环境监测分析方法标准制修订技术导则). Beijing:Ministry of Ecology and Environment of the People’s Republic of China(北京:生态环境部),2020.
[10] National Environmental Protection Standards of the People’s Republic of China(中华人民共和国国家环境保护标准). HJ 700—2014 Water Quality-Determination of 65 Elements-Inductively Coupled Plasma-Mass Spectrometry(水质65种元素的测定 电感耦合等离子体质谱法). Beijing:Ministry of Ecology and Environment of the People’s Republic of China(北京:生态环境部),2014.
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