Predicting global scale exposure of humans to PCB 153 from historical emissions
Abstract
Predicting human exposure to an environmental contaminant based on its emissions is one of the great challenges of environmental chemistry. It has been done successfully on a local or regional scale for some persistent organic pollutants. Here we assess whether it can be done at a global scale, using PCB 153 as a test chemical. The global multimedia fate model BETR Global and the human exposure model ACC-HUMAN were employed to predict the concentration of PCB 153 in human milk for 56 countries around the world from a global historical emissions scenario. The modeled concentrations were compared with measurements in pooled human milk samples from the UNEP/WHO Global Monitoring Plan. The modeled and measured concentrations were highly correlated (r = 0.76, p < 0.0001), and the concentrations were predicted within a factor of 4 for 49 of 78 observations. Modeled concentrations of PCB 153 in human milk were higher than measurements for some European countries, which may reflect weaknesses in the assumptions made for food sourcing and an underestimation of the rate of decrease of concentrations in air during the last decades. Conversely, modeled concentrations were lower than measurements in West African countries, and more work is needed to characterize exposure vectors in this region.
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BibTeX
@article{mclachlan2026predicting,
title = {{Predicting global scale exposure of humans to PCB 153 from historical emissions}},
author = {Michael Mclachlan and Emma Undeman and Fangyuan Zhao and Matthew Macleod},
journal = {Environmental Science: Processes \& Impacts},
year = {2026},
month = nov,
doi = {10.1039/c8em00023a},
url = {https://univ-rennes.hal.science/hal-05855193v1},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Predicting global scale exposure of humans to PCB 153 from historical emissions
AU - Michael Mclachlan
AU - Emma Undeman
AU - Fangyuan Zhao
AU - Matthew Macleod
PY - 2026
DA - 2026/11/06
JO - Environmental Science: Processes & Impacts
DO - 10.1039/c8em00023a
UR - https://univ-rennes.hal.science/hal-05855193v1
AB - Predicting human exposure to an environmental contaminant based on its emissions is one of the great challenges of environmental chemistry. It has been done successfully on a local or regional scale for some persistent organic pollutants. Here we assess whether it can be done at a global scale, using PCB 153 as a test chemical. The global multimedia fate model BETR Global and the human exposure model ACC-HUMAN were employed to predict the concentration of PCB 153 in human milk for 56 countries around the world from a global historical emissions scenario. The modeled concentrations were compared with measurements in pooled human milk samples from the UNEP/WHO Global Monitoring Plan. The modeled and measured concentrations were highly correlated (r = 0.76, p < 0.0001), and the concentrations were predicted within a factor of 4 for 49 of 78 observations. Modeled concentrations of PCB 153 in human milk were higher than measurements for some European countries, which may reflect weaknesses in the assumptions made for food sourcing and an underestimation of the rate of decrease of concentrations in air during the last decades. Conversely, modeled concentrations were lower than measurements in West African countries, and more work is needed to characterize exposure vectors in this region.
SN - 2050-7887
ER -