基于聚丙烯无纺布与耗氧传感器的泄漏乳化油的监测

doi:10.16085/j.issn.1000-6613.2021-0786

摘要/Abstract

摘要：

利用聚丙烯无纺布（polypropylene non-woven fabric，PP NWF）和耗氧传感器结合来构建一个乳化油监测探头。PP NWF是一种超疏水吸油材料，可以快速吸附乳化油污，利用该性能，本监测探头先用PP NWF富集乳化油污，再用探头对材料中的氧含量进行监测，从而达到乳化油监测的目的。本文通过监测不同种类的乳化油（表面活性剂为吐温80的正己烷乳化油、石油醚乳化油、甲苯乳化油及表面活性剂为司班80的正己烷乳化油、石油醚乳化油、甲苯乳化油）来验证其可行性。结果表明：该监测探头可以监测到不同乳化条件下的乳化油，并且能监测到不同种类的乳化油。其中监测甲苯乳化油时响应时间最短，可以在6s内监测到该油污。固定PP NWF时的耗氧传感器探头的最低检测限为1.27g/L，监测效率较未固定PP NWF时提高了近8倍。综上，固定PP NWF的耗氧传感器探头可以作为海洋乳化油监测重要的一个系统，对海洋乳化油泄漏事故进行在线实时监测，可以快速准确提供早期溢油预警。

关键词: 海洋溢油, 聚丙烯无纺布, 耗氧传感器, 在线监测

Abstract:

An on-site marine oil spillage monitoring probe is developed by combining oxygen consumption sensor with polypropylene non-woven (PP NWF). PP NWF is a hydrophobic/oleophilic material which can absorb emulsified oil quickly. To enhance the monitoring efficiency, the spilled emulsified oils were first enriched by PP NWF absorption, then detected by the change of the oxygen content in the porous space of PP NWF. With PP NWF, the probe has shown close to 8 times less Reliable Low Detection Limit (RLDL) in detecting emulsified n-hexane oil spillage. It is demonstrated that the monitoring probe can effectively detect various kinds of emulsified oils, including n-hexane, petroleum ether and toluene, emulsified by different surfactants, such as Tween-80 or Span-80. The impact of surfactants on the response time and sensitivity of the probe in monitoring different types of spilled oils were systematically studied. With the rapid response time and high noise-to-signal ratios, the probe may be used as a key component in marine oil spillage monitoring systems to provide early stage pollution warning.

Key words: emulsified oil spillage, online monitor, polypropylene non-woven, oxygen consumption sensor

中图分类号:

施羽昕, 苌现, 姜斐, 孙志娟, 薛立新. 基于聚丙烯无纺布与耗氧传感器的泄漏乳化油的监测[J]. 化工进展, 2021, 40(S2): 443-450.

SHI Yuxin, CHANG Xian, JIANG Fei, SUN Zhijuan, XUE Lixin. Study on emulsified oil spillage monitoring based on polypropylene non-woven fabric and oxygen consumption sensors[J]. Chemical Industry and Engineering Progress, 2021, 40(S2): 443-450.

图/表 21

参考文献 16

1	赵冬. 基于高/多光谱遥感技术的海表油膜识别方法研究[D]. 武汉: 中国地质大学, 2019.
	ZHAO Dong. Researches on identifying sea surface oil slicks based on hyperspectral and multi-spectral remote sensing technologies[D]. Wuhan: China University of Geosciences, 2019.
2	ANGELA C. Oil pollution in the North Sea: the impact of governance measures on oil pollution over several decades[J]. Hydrobiologia, 2019, 845(1): 109-127.
3	SARBATLY R, KRISHNAIAH D, KAMIN Z. A review of polymer nanofibres by electrospinning and their application in oil-water separation for cleaning up marine oil spills[J]. Marine Pollution Bulletin, 2016, 106(1): 8-16.
4	刘方, 高正松, 缪鑫才. 表面活性剂在石油开采中的应用[J]. 精细化工, 2000, 17(12): 696-699.
	LIU Fang, GAO Zhengsong, Xincai MIU. Application of surfactant in oil exploitation[J]. Fine Chemicals, 2000, 17(12): 696-699.
5	BOARD M B. Oil in the sea: inputs, fates, and effects[J]. Spill science & technology bulletin, 2002, 7(5-6): 1997-1999.
6	CHEN Jinhong, ZHANG Weipan, WAN Zheng, et al. Oil spills from global tankers: status review and future governance[J]. Journal of Cleaner Production, 2019, 227(8): 20-32.
7	WHITE H K, HSING P Y, CHO W, et al. Impact of the deepwater horizon oil spill on a deep-water coral community in the gulf of mexico[J]. Proceedings of the National Academy of Sciences, 2012, 109(50): 20303-20308.
8	KOSTKA J E, PRAKASH O, OVERHOLT W A, et al. Hydrocarbon-degrading bacteria and the bacterial community response in gulf of Mexico beach sands impacted by the deepwater horizon oil spill[J]. Applied and Environmental Microbiology, 2011, 77(22): 7962-7974.
9	吴健，谭娟，黄沈发，等. 溢油污染潮间带大型底栖动物体内总石油烃含量及风险动态[J]. 环境科学学报, 2017, 37(1): 381-387.
	WU Jian, TAN Juan, HUANG Shenfa, et al. Content and risk dynamic of the total petroleum hydrocarbon in the body of benthic invertebrate in the intertidal zone polluted by oil spill[J]. Acta Scientiae Circumstantiae, 2017, 37(1): 381-387.
10	徐进，李博，崔璨，等. 航海雷达溢油监测技术研究[J]. 海洋环境科学, 2018, 37(1): 125-129.
	XU Jin, LI Bo, CUI Can, et al. Research on marine radar oil spill monitoring technology[J]. Marine Environmental Science, 2018, 37(1): 125-129.
11	MENDELSSOHN I A, ANDERSEN G L, BALTZ D M, et al. Oil impacts on coastal wetlands: implications for the mississippi river delta ecosystem after the deepwater horizon oil spill[J]. Bioscience, 2012, 62(6): 562-574.
12	谈爱玲. 水中石油类污染物光纤光谱检测方法的研究[D]. 秦皇岛: 燕山大学, 2012.
	TAN Ailing. Study on fiber optic spectroscopy detecting method for petroleum pollutants in water[D]. Qinhuangdao: Yanshan University, 2012.
13	Al-RUZOUQ R, GIBRIL M B A, SHANABLEH A, et al. Sensors, features, and machine learning for oil spill detection and monitoring: a review[J]. Remote Sensing, 2020, 12(20): 3338.
14	ALTOBELLI S A, CONRADI M S, FUKUSHIMA E, et al. Helicopter-borne NMR for detection of oil under sea-ice[J]. Marine Pollution Bulletin, 2019, 144(7): 160-166.
15	FINGAS M, BROWN C E. A review of oil spill remote sensing[J]. Sensors, 2017, 18(2): 91-108.
16	ZHAO S H, WANG Q, LI Y, et al. An overview of satellite remote sensing technology used in China's environmental protection[J]. Earth Science Informatics, 2017, 10(2): 137-148.

乳化油用量 /g·L^-1	标准偏差
乳化油用量 /g·L^-1	δ₁	δ₂	δ₁₊₂	3δ_1+2/max	油/g·L^-1
1	0.01	0.01	0..02	—	—
3	0.04	0.02	0.06	—	—
5	0.01	0.01	0.02	—	—
10	0.07	0.11	0.18	0.54	1.27
20	0.02	0.02	0.04	—	—

乳化油用量 /g·L^-1	标准偏差
乳化油用量 /g·L^-1	δ₁	δ₂	δ₁₊₂	3δ_1+2/max	油/g·L^-1
1	0.01	0.01	0..02	—	—
3	0.04	0.02	0.06	—	—
5	0.01	0.01	0.02	—	—
10	0.07	0.11	0.18	0.54	1.27
20	0.02	0.02	0.04	—	—

乳化油用量 /g·L^-1	标准偏差
乳化油用量 /g·L^-1	δ₁	δ₂	δ₁₊₂	3δ_1+2/max	油/g·L^-1
1	0.01	0.01	0.02	—	—
3	0.15	0.06	0.32	0.96	9.68
5	0.3	0.02	0.32	0.96	9.68
10	0.26	0.03	0.29	—	—
20	0.17	0.03	0.2	—	—

乳化油用量 /g·L^-1	标准偏差
乳化油用量 /g·L^-1	δ₁	δ₂	δ₁₊₂	3δ_1+2/max	油/g·L^-1
1	0.01	0.01	0.02	—	—
3	0.15	0.06	0.32	0.96	9.68
5	0.3	0.02	0.32	0.96	9.68
10	0.26	0.03	0.29	—	—
20	0.17	0.03	0.2	—	—

乳化油种类	响应时间/s	RSD/%	极性	峰高信噪比/dB
正己烷	18±1	6	0.06	16
石油醚	12±1	8	0.01	18
甲苯	9±1	11	2.4	7