Development of β-cyclodextrin crosslinked citric acid encapsulated in polypropylene membrane protected-μ-solid-phase...

Endocrine disruptor compounds (EDCs) such as plasticisers, surfactants, pharmaceutical products, personal care products and pesticides are frequently released into the environmental waters. Therefore, a sensitive and environmentally friendly method is entailed to quantify these compounds at their trace level concentrations. This study encapsulated the β-cyclodextrin crosslinked with citric acid in a polypropylene membrane protected-μ-solid phase extraction (BCD-CA μ-SPE) device for preconcentrating the EDCs (triclosan, triclocarban, 2-phenylphenol, 4-tert-octylphenols and bisphenol A) in real water samples before the analysis by high-performance liquid chromatography. FT-IR and TGA results indicated that BCD-CA was successfully synthesised with the formation of ester linkage (1078.33 cm^-1) and O-H stretching from carboxylic acid (3434.70 cm^-1) with higher thermal stability as compared with native CD with the remaining weight above 72.1% at 500 °C. Several critical parameters such as the sorbent loading, type and amount of salts, extraction time, sample volume, sample pH, type and volume of desorption solvents and desorption time were sequentially optimised and statistically validated. Under the optimum condition, the use of BCD-CA μ-SPE device had manifested good linearity (0.5-500 μg L^-1) with the determination of the coefficient range of 0.9807-0.9979. The p-values for the F-test and t-test (6.60 × 10^-8 - 1.77 × 10^-5) were lesser than 0.05 and low detection limits ranging from 0.27 to 0.84 μg L^-1 for all studied EDCs. The developed technique was also successfully applied for EDC analyses in four distinct real water samples, namely, wastewater, river water, tap water and mineral water, with good EDCs recoveries (80.2%-99.9%), low relative standard deviations (0.1%-3.8%, n = 3) with enrichment factor ranging from 9 to 82 folds. These results signified the potential of the BCD-CA μ-SPE device as an efficient, sensitive, and environmentally friendly approach for analyzing EDCs.