Distribution of organochlorine pesticides in groundwater of industrial parks during the wet season

Objective To characterize the contamination levels of organochlorine pesticides (OCPs) in groundwater from industrial parks in the Jianghan Plain, China.

Methods Five industrial parks were selected using cluster random sampling as survey clusters from all 13 industrial parks in the Jianghan plain, and a total of 43 groundwater samples were collected, and the concentrations of 16 OCPs were determined by solid-phase extraction coupled with gas chromatography-tandem mass spectrometry. Based on concentration statistics and spatial comparison, the pollution distribution of OCPs was characterized. Diagnostic ratios of dichlorodiphenyltrichloroethanes and hexachlorocyclohexanes, hierarchical clustering heatmap, and principal component analysis (PCA) were used for compositional characterization and multivariate analysis. Spearman rank correlation analysis was applied to explore the relationships among OCPs and between OCPs and water quality chemical parameters.

Results Fifteen of the tested OCPs showed a detection frequency higher than 50%. Hexachlorobenzene (HCB) was detected in all samples, while δ-1, 2, 3, 4, 5, 6-hexachlorocyclohexane was not detected. The median concentration of ΣOCPs was 113.15 ng/L (8.38-2 537.35 ng/L). Significant differences in ΣOCPs levels were observed among groundwater samples from different industrial parks (P=0.009), with the highest median concentration found in Park B (278.90 ng/L). HCB and 1, 1, 1-trichloro-2, 2-bis(p-chlorophenyl)ethane were the dominant contributors to OCPs in groundwater across all parks. The overall (dichlorodiphenyldichloroethylene+dichlorodiphenyldichloroethane)/Σdichlorodiphenyltrichloroethanes ratio was relatively low, and the α/γ-hexachlorocyclohexanes ratio was approximately 1. Hierarchical clustering analysis showed that samples from Parks A and B were grouped together, with most OCPs exhibiting relatively high levels, although the characteristic pollutant compositions differed between the two parks. PCA revealed that the first two principal components explained 73.9% of the total variance, effectively reflecting the compositional differences of OCPs among groundwater samples. Significant positive correlations were generally observed among OCPs (r_s=0.46-0.88). The linear correlations between water quality chemical parameters and ΣOCPs were generally weak, and the explanatory power of multiple regression and principal component regression was limited.

Conclusion OCPs were widely detected in groundwater from industrial parks, and localized high-risk hotspots and high-contribution compounds were identified. HCB, 1, 1, 1-trichloro-2, 2-bis(p-chlorophenyl)ethane, and other dominant contributors should be prioritized for routine monitoring and source-oriented control.