Mathematical model developed for environmental samples: prediction of GC/MS dioxin TEQ from XDS-CALUX bioassay data

Abstract

Remediation of hazardous waste sites requires efficient and cost-effective methods to assess the extent of contamination by toxic substances including dioxin-like chemicals. Traditionally, dioxin-like contamination has been assessed by gas chromatography/high-resolution mass spectrometry (GC/MS) analysis for specific polychlorinated dibenzo-p-dioxins, dibenzofurans, and biphenyl congeners. Toxic equivalency factors for these congeners are then used to estimate the overall dioxin toxic equivalency (TEQ) of complex mixtures found in samples. The XDS-CALUX bioassay estimates contamination by dioxin-like chemicals in a sample extract by measuring expression of a sensitive reporter gene in genetically engineered cells. The output of the XDS-CALUX assay is a CALUX-TEQ value, calibrated based on TCDD standards. Soil samples taken from a variety of hazardous waste sites were measured using the XDS-CALUX bioassay and GC/MS. TEQ and CALUX-TEQ from these methods were compared, and a mathematical model was developed describing the relationship between these two data sets: log(TEQ) = 0.654 x log(CALUX-TEQ) + 0.058-(log(CALUX-TEQ))2. Applying this equation to these samples showed that predicted and GC/MS measured TEQ values strongly correlate (R2 = 0.876) and that TEQ values predicted from CALUX-TEQ were on average nearly identical to the GC/MS-TEQ. The ability of XDS-CALUX bioassay data to predict GC/MS-derived TEQ data should make this procedure useful in risk assessment and management decisions.

FIGURE 1

Comparison of GC/MS-TEQ and CALUX-TEQ for SITE samples. TEQ was determined by GC/MS, CALUX-TEQ was determined by XDS-CALUX as described, and the average results for each quadruplicate analysis of 42 soil and sediment samples are graphed. Solid line is the data trend line; for comparison, the dashed line represents y = x(slope = 1 and intercept = 0). The regression line equation for the data is y = 3.356x^1.0067.

FIGURE 2

Modeling the relationship between predicted GC/MS-TEQ and GC/MS-TEQ. The TEQ was predicted from CALUX-TEQ values for SITE samples using eq 1. Solid line is the data trend line; for comparison, the dashed line represents y = x(slope = 1 and intercept = 0). The regression line equation for the data is y = 1.7789x^0.9384.

FIGURE 3

Comparison of GC/MS-TEQ and CALUX-TEQ for SW846 samples. TEQ was determined by GC/MS, and CALUX-TEQ was determined by XDS-CALUX as described. Solid line is the data trend line; for comparison, the dashed line represents y = x(slope = 1 and intercept = 0). Sample matrix was ash (■) or soil (△).

FIGURE 4

Predicting GC/MS-TEQ from CALUX-TEQ for SW846 samples. TEQ was predicted from CALUX-TEQ determinations using eq 1. Solid line is the data trend line; for comparison, the dashed line represents y = x(slope = 1 and intercept = 0). Sample matrix was ash (■) or soil (△). The regression line equation for ash is y = 6.49x^0.82 and for soil is y = 5.86x^0.97.

FIGURE 5

Predicted CALUX-TEQ by TEF/REP conversion comparison with GC/MS TEQ. TEQ was calculated from XDS-CALUX data using TEF REP conversion factors as described previously (ref ; also see Tables 1 and 3). Solid line is the data trend line; for comparison, the dashed line represents y = x(slope = 1 and intercept = 0). Sample matrix was ash (■) or soil (△). The regression line for ash is y = 4.49x^0.82 and for soil is y = 3.88x^0.97.