aPredicting 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 ¼ 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.
Environmental signicanceThis work shows that mathematical models can be used to predict the environmental fate and exposure of a persistent organic pollutant along the whole journey from emissions to human tissues on a global scale with reasonable accuracy. This increases our condence in our knowledge of the key processes governing the environmental chemistry of such contaminants and our ability to synthesize this knowledge in models. In addition, the work identies several areas where further work is needed: food sourcing patterns in regions with strong gradients in environmental contamination, exposure pathways to PCBs in Africa, and evaluation of the ability of the models to predict long term time trends.