Partitioning, Translocation Pathways and Environmental Risk Evaluation of Selected Polychlorinated Biphenyls and Pestici
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		    Partitioning, Translocation Pathways and Environmental Risk Evaluation of Selected Polychlorinated Biphenyls and Pesticides Olatunde Stephen Olatunji
 
 Received: 19 February 2020 / Accepted: 13 July 2020 # Springer Nature Switzerland AG 2020
 
 Abstract Degradation-resistant chemical contaminants of health concern such as dichlorodiphenyltrichloroethane (DDT) pesticides and polychlorinated biphenyls (PCBs) in the environment are redistributed between different environmental compartments, where they partition between biotic heterotrophic routes and abiotic features (water and immobile soil components). Their fate and the potential risk they pose is a function of translocation, interaction, environmental behavior, and bio-translation/activities. In this study, the partitioning, translocation, bio-translation pathways of 3-DDT and 6PCB congeners in dosed soils cultured root and leaf vegetables were investigated to predict their soil– vegetable mobility, depuration, and exposure risk. Results showed that PCB_110 and PCB_180 were the least and highest PCBs concentrated in both the leaf and root vegetables. The variations in the 3-DDT and 6-PCB concentrations in the leaf and root vegetables may be attributed to differences in their solubility and partitioning. Total residual mass fraction 3-DDT taken up by the leaf and root vegetables indicated timedependent preferentiality in pesticide-type vascular tissue translocation to the vegetables. Mann–Whitney nonparametric test showed evidence of spatial variations in
 
 Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11270-020-04771-z) contains supplementary material, which is available to authorized users. O. S. Olatunji (*) School of Chemistry and Physics, University of KwaZulu-Natal, Westville, Durban 4000, South Africa e-mail: [email protected]
 
 levels of the 3-DDT and 6-PCBs across the farmland; however, the variations in the distribution were not significant (PFML1–FML6 0.75,
 
 Water Air Soil Pollut
 
 (2020) 231:407
 
 Page 9 of 18 407
 
 Table 4 Retention time and qualifying and quantifying ion characteristics of 3-DDT and 6-PCB congeners Compound
 
 Sensitivity Quantifying Retention ion time (min)
 
 4,4′-DDE
 
 Qualify ion (Q1) 4,4′-DDD Qualify ion (Q1) 4,4′-DDT Qualify ion (Q1) 4,4′-DDT_d8 Qualify ion (Q1) PCB_110 Qualify ion (Q1) PCB_118 Qualify ion (Q1) PCB_138 Qualify ion (Q1) PCB_149 Qualify ion (Q1) PCB_153 Qualify ion (Q1) PCB_180 Qualify ion (Q1)
 
 MRM MRM Collision parent product energy mass mass
 
 Standard Slope deviation (σ)
 
 18.61
 
 316
 
 246
 
 20
 
 1.09
 
 19.29
 
 235
 
 165
 
 22
 
 3.42
 
 111,684
 
 19.46
 
 235
 
 165
 
 22
 
 3.28
 
 111,684
 
 19.41
 
 243
 
 173
 
 25
 
 18.75
 
 324
 
 254
 
 24
 
 19.30
 
 324
 
 254
 
 19.15
 
 360
 
 19.65
 
 Linearity
 
 LOD LOQ Coefficient of (μg/L) (μg/L) regression (R2)
 
 0.084
 
 0.9943
 
 0.052
 
 0.156
 
 0.9990
 
 0.016
 
 0.048
 
 0.9943
 
 5.52
 
 24,427.4 0.075
 
 0.225
 
 0.9943
 
 26
 
 1.37
 
 24,427.4 0.018
 
 0.054
 
 0.9943
 
 290
 
 18
 
 2.50
 
 24,427.4 0.034
 
 0.102
 
 0.9943
 
 358
 
 288
 
 20
 
 1.65
 
 24,427.4 0.022
 
 0.066
 
 0.9943
 
 20.09
 
 358
 
 288
 
 22
 
 1.64
 
 24,4		
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