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Team TFS
Team TFS

103122 Pesticides in soil.jpg

 

Organochlorine pesticides (OCPs) are semi-volatile chlorinated hydrocarbons that were used extensively in the middle of the 20th century to protect crops, livestock, and buildings from insect damage. However, since the 1970s, OCPs have been banned or restricted in the United States, Europe and other countries, as their persistent presence in the environment and food pose a threat to health. To ensure safe levels of OCPs in accordance with these restrictions, laboratories require robust, high-throughput methods for determining these compounds in a wide range of samples.

 

Determination of OCPs in soil using gas chromatography

 

Determination of OCPs in food, environmental and biological samples is typically achieved using gas chromatography (GC) coupled with various detection techniques. United States Environmental Protection Agency (US EPA) Method 8270 provides procedures for the detection and measurement of semi-volatile organic compounds — including OCPs in water, solid and air samples — using gas chromatography-mass spectrometry (GC-MS). Additionally, US EPA Method 8081 details validated procedures for determination of 28 OCPs using electron capture detection (ECD), which can be coupled with gas chromatography for sensitive detection.

 

Accurately determining concentrations of OCPs in samples requires robust and reliable methods for extracting these compounds from solid samples, including soils, sludges and wastes. Methods such as Soxhlet, sonication and microwave extraction are commonly used for this purpose; however, these techniques are highly labor-intensive and require large quantities of solvent, which contribute to additional costs and must be correctly disposed of.

 

Fully automated accelerated solvent extraction

 

Accelerated solvent extraction was developed to overcome the limitations of conventional extraction techniques, and uses high temperatures and pressures to quickly and efficiently remove unwanted matrix components from solid samples for GC analysis. The combined effect of temperature and pressure greatly increases the efficiency of the extraction process, significantly reducing the amount of time and solvent required for extraction compared to traditional Soxhlet and sonication.

 

Advanced, automated solutions for accelerated solvent extraction can be used to further improve the efficiency of this approach. The Thermo Scientific™ EXTREVA™ ASE™ accelerated solvent extractor is a new, fully automated system based on gas-assisted solvent delivery and parallel accelerated solvent extraction technologies. By combining two sample preparation instruments in one, the system performs both extraction and evaporation of organic compounds in a single seamless operation.

 

The EXTREVA ASE system is capable of extraction and concentration of up to 16 solid and semi-solid samples in a single workflow, using up to six different extraction solvents (or mixtures thereof) to extract up to four cells in parallel. Offering the convenience of automation and an easy ”load-and-go” start process, the EXTREVA ASE system enables unattended operations and minimizes solvent usage to save time, reduce errors and significantly increase analytical throughput.

 

Determining OCPs in soils using accelerated solvent extraction and GC-ECD

 

To evaluate the effectiveness of the fully automated extraction technique for environmental analysis of semi-volatiles, we used the EXTREVA ASE system and Thermo Scientific™ TRACE™ 1310 gas chromatograph system with Thermo Scientific™ iConnect™ electron capture detector to determine 20 OCPs in soil samples.

 

Recoveries for all OCPs extracted from the spiked soil samples (25 µg/kg) ranged between 80 and 115%, within the recommended acceptance criteria of the US EPA and other global regulations (Figure 1). The relative standard deviation (RSD) was below 8% for all compounds, demonstrating good channel-to-channel and run-to-run reproducibility for both extraction and evaporation.

 

To assess the impact of carryover between runs using the system, a heavily fortified soil sample (250 µg/kg) was extracted and concentrated prior to a second identical analysis of an Ottawa sand sample. Each flow path channel was rinsed with 10 mL of solvent between the two extractions. Carryover between consecutive runs was less than 0.5% for all analytes after solvent rinse, demonstrating that the rinsing step was effective for minimizing cross-contamination between extractions.

 

A final test was performed to evaluate the impact of analyte thermal degradation on measurement results. As the soil samples were typically extracted at high temperatures, thermally labile analytes may partially degrade during the extraction. Of the 20 OCPs analyzed in this study, endrin and 4,4’-dichlorodiphenyltrichloroethane (DDT) were the least thermally stable. Thermal degradation of both compounds under typical extraction conditions (100 and 150 °C) were low (less than 4%) and fell below the 15% criteria suggested by the US EPA, highlighting the suitability and robustness of the extraction process. The low thermal degradation (less than 4%) was attributed to the 3.1% breakdown that occurred in the GC injection port, thus, the thermal degradation during extraction was negligible.

 

Automated accelerated solvent extraction: efficient, reliable performance

 

New, fully automated accelerated solvent extraction systems are supporting efficient, robust, high-throughput performance in pesticide analysis. By applying these technologies for the determination of OCPs in soil, laboratories can save time and reduce solvent usage, while achieving reliable results.

 

Read more about this accelerated solvent extraction-based GC-ECD method for determining OCPs in soils here.

 

Figure 1. Average OCP recovery rates for the 25 µg/kg spiked samples fell between the 80 and 120% limits recommended by the US EPA.Figure 1. Average OCP recovery rates for the 25 µg/kg spiked samples fell between the 80 and 120% limits recommended by the US EPA.

 

Fabrizio Galbiati, Anzi Wang, Changling Qiu, Mingfang Wang and Yan Liu contributed to this blog post.

 

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