Techniques for surfactant detection from wastewater: a review

ABSTRACT

The COVID-19 pandemic has led to an extensive use of surfactants in the form of disinfectants, surface cleaners, sanitisers and shower gels for hygiene. Considering their environmental impact, it becomes essential to keep track of the surfactants emitted by cleansers, cosmetics, and hygiene products. Linear alkyl benzenes (LABs) are discharged substantially into the environment as a by-product of hazardous linear alkyl benzene sulphonate (LAS), an anionic surfactant widely used in detergent manufacture. Many signals linked to the characteristic fragments of LABs, C₇H₇⁺ (mass 91.05) have been identified by high-resolution orbitrap mass spectroscopy. Precise qualitative and quantitative predictions can only facilitate the correct remedial methods to be applied for surfactant eradication. Thus, it is crucial to detect surfactants qualitatively and quantitatively in the water reservoirs. The current review focuses on various analytical approaches used for detecting surfactants in surrounding water reservoirs, which have been explored mainly for wastewater treatment plants (WWTPs). Based on recent developments, techniques like Spectroscopy, Chromatography, Potentiometry, Titrimetry, and Electrophoresis have been discussed. This manuscript highlights specific methods regularly employed for surfactant analysis, including their advantages, disadvantages, and the problems associated with the various detection techniques of surfactants. This article emphasises on the need for automated yet simple methods for surfactant analysis aiding in choosing the correct detection method.

KEYWORDS:

• Wastewater
• surfactants
• sample extraction
• pre-treatment
• spectroscopy
• chromatography

Disclosure statement

No potential conflict of interest was reported by the author(s).

Authors’ contributions

Deepali Kulkarni: Literature survey, study concept, data interpretation, drafting;

Dipika Jaspal: Critical revision, Guiding, Proofreading supervision.

All authors read and approved the final manuscript.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/03067319.2023.2285372.

Additional information

Funding

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.