Monte Carlo simulation (MCS) is a computational technique widely used in exposure and risk assessment. However, the result of traditional health risk assessment based on the MCS method has always been questioned due to the uncertainty introduced in parameter estimation and the difficulty in result validation. Herein, data from a large-scale investigation of individual polycyclic aromatic hydrocarbon (PAH) exposure was used to explore the key factors for improving the MCS method. Research participants were selected using a statistical sampling method in a typical PAH polluted city. Atmospheric PAH concentrations from 25 sampling sites in the area were detected by GC-MS and exposure parameters of participants were collected by field measurement. The incremental lifetime cancer risk (ILCR) of participants was calculated based on the measured data and considered to be the actual carcinogenic risk of the population. Predicted risks were evaluated by traditional assessment method based on MCS and three improved models including concentration-adjusted, age-stratified, and correlated-parameter-adjusted Monte Carlo methods. The goodness of fit of the models was evaluated quantitatively by comparing with the actual risk. The results showed that the average risk derived by traditional and age-stratified Monte Carlo simulation was 2.6 times higher, and the standard deviation was 3.7 times higher than the actual values. In contrast, the predicted risks of concentration- and correlated-parameter-adjusted models were in good agreement with the actual ILCR. The results of the comparison suggested that accurate simulation of exposure concentration and adjustment of correlated parameters could greatly improve the MCS. The research also reveals that the social factors related to exposure and potential relationship between variables are important issues affecting risk assessment, which require full consideration in assessment and further study in future research.

Polycyclic aromatic hydrocarbon (PAH) emissions from the combustion of household solid coal for cooking and heating cause great harm to public health in China, especially in less developed areas. Children are one of the most susceptible population groups at risk of indoor air pollutants due to their immature respiratory and immune systems. However, information on PAH exposure of children is limited due to limited monitoring data. In this study, we aimed to assess the seasonal differences of PAHs in classrooms, analyze the pollutant sources, and calculate the incremental lifetime cancer risk attributable to PAHs in Shanxi Provence. A typical school using household coal combustion in Shanxi Province was selected. Fine particulate matter (PM_2.5)samples were collected by both individual samplers and fixed middle-flow samplers during the heating and non-heating seasons in December 2018 and April 2019. The PAH concentrations in PM_2.5 samples were analyzed by a gas chromatograph coupled to a mass spectrometer. The results showed that PAH concentrations in PM_2.5 varied between 89.1 ng/m³ in the heating season and 1.75 ng/m³ in the non-heating season. The mean concentrations of benzo[a]pyrene (BaP), a carcinogenic marker of PAHs, were 10.3 and 0.05 ng/m³ in the heating and non-heating seasons, respectively. Source allocation analysis of individual portable and passive samplers revealed that the main contributors during heating and non-heating seasons were coal combustion and gasoline sources, respectively. According to the results of a Monte Carlo simulation, the incremental lifetime cancer risk values from the inhalation of PAHs in the heating and non-heating seasons were 3.1 × 10⁻⁶ and 5.7 × 10⁻⁸, respectively. The significant increase in PAHs and the incremental lifetime cancer risk in the heating season indicates that children are more exposed to health threats in winter. Further PAH exposure control strategies, including reducing coal usage and promoting clean fuel applications, need to be developed to reduce the risk of PAH-induced cancer.