Evaluation of Bayesian approaches to identify DDT source contributions to soils in Southeast China

•A novel method based on Bayesian probability was developed for DDT source apportionment in soils.•The spatial distribution of source contributions were mapped with different methods.•Historical DDT was still an important pollution source to soils in Fujian, Southeast China.•Both DDX level and dicofol contribution in non-agricultural soils were higher than that in agricultural soils.

Dicofol application may be an important source to elevate the dichlorodiphenyltrichloroethane (DDT) residues to soils in Fujian, Southeast China, after the technical DDT was banned, which left DDT residues from the historical application. The DDT residues varied geographically, corresponding to the varied potential sources of DDT. In this study, a novel approach based on the Bayesian method (BM) was developed to identify the source contributions of DDT to soils, composed with both historical DDT and dicofol. The Naive Bayesian classifier was used basing on the subset of the samples, which were determined by chemical analysis independent of the Bayesian approach. The results show that BM (95%) was higher than that using the ratio of o, p′-/p, p′-DDT (84%) to identify DDT source contributions. High detection rate (97%) of dicofol (p, p′-OH-DDT) was observed in the subset, showing dicofol application influenced the DDX levels in soils in Fujian. However, the contribution from historical technical DDT source was greater than that from dicofol in Fujian, indicating historical technical DDT was still an important pollution source to soils. In addition, both the DDX (DDT isomers and derivatives) level and dicofol contribution in non-agricultural soils were higher than other agricultural land uses, especially in hilly regions, the potential cause may be the atmospheric transport of dicofol type DDT, after spraying during daytime, or regional difference on production and application.