Estimation of chronic personal exposure to airborne polycyclic aromatic hydrocarbons

Background: Polycyclic aromatic hydrocarbons (PAH) exposure from solid fuel burning represents an important public health issue for the majority of the global population. Yet, understanding of individual-level exposures remains limited.

Objectives: To develop regionally adaptable chronic personal exposure model to pro-carcinogenic PAH (c-PAH) for the population in Kraków, Poland.

Methods: We checked the assumption of spatial uniformity in eight c-PAH using the coefficients of divergence (COD), a marker of absolute concentration differences. Upon successful validation, we developed personal exposure models for eight pro-carcinogenic PAH by integrating individual-level data with area-level meteorological or pollutant data. We checked the resulting model for accuracy and precision against home outdoor monitoring data.

Results: During winter, COD of 0.1 for Kraków suggest overall spatial uniformity in the ambient concentration of the eight c-PAH. The three models that we developed were associated with index of agreement approximately equal to 0.9, root mean square error < 2.6 ng/m3, and 90th percentile of absolute difference ≤ 4 ng/m3 for the predicted and the observed concentrations for eight pro-carcinogenic PAH.

Conclusions: Inexpensive and logistically feasible information could be used to estimate chronic personal exposure to PAH profiles, in lieu of costly and labor-intensive personal air monitoring at wide scale. At the same time, thorough validation through direct personal monitoring and assumption checking are critical for successful model development.

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