Issue 29, 2022

Optimization and validation of ultrasound application with a low-temperature method to analyze organochlorine pesticides in smuggled cigarette tobacco

Abstract

This work presents the optimization and validation of a method to quantify organochlorine pesticides in tobacco samples from smuggled cigarettes using ultrasound application and low-temperature extraction. The combined approach was validated for 20 organochlorine pesticides, achieving recoveries between 73% and 116%, and a relative standard deviation of less than 20%. The method minimized the matrix effect in 65% of the organochlorine pesticides. The limits of detection and quantification varied from 2 to 60 ng g−1 and 120 to 190 ng g−1, respectively. The method was applied to the analysis of 18 brands of smuggled cigarettes. The organochlorine pesticides found in the samples were cis-chlordane (89%), p,p′-dichlorodiphenyldichloroethylene (DDD) and methoxychlor (78%), endosulfan sulfate (67%), heptachlor epoxide, and endosulfan II (61%). The concentrations of the organochlorine pesticides in this study were higher than those in a similar survey on cigarettes marketed in China. The ultrasound application and low-temperature extraction may be an efficient alternative to analyzing tobacco samples since it uses only one extraction solvent, requires low-cost equipment, does not require an additional clean-up step, reduces the environmental impact through minimal waste generation, and can detect low analyte concentrations.

Graphical abstract: Optimization and validation of ultrasound application with a low-temperature method to analyze organochlorine pesticides in smuggled cigarette tobacco

Article information

Article type
Paper
Submitted
31 Mar 2022
Accepted
05 Jul 2022
First published
05 Jul 2022

Anal. Methods, 2022,14, 2857-2865

Optimization and validation of ultrasound application with a low-temperature method to analyze organochlorine pesticides in smuggled cigarette tobacco

C. E. Domingues, J. Kordiak, C. R. Pedroso, T. R. de Oliveira Stremel, J. Beber de Souza, C. M. de Sousa Vidal and S. X. de Campos, Anal. Methods, 2022, 14, 2857 DOI: 10.1039/D2AY00544A

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