Physiologically based pharmacokinetic/toxicokinetic (PBPK/PBTK) models are designed to elucidate the mechanism of chemical compound action in organisms based on the physiological, biochemical, anatomical, and thermodynamic properties of organisms. After nearly a century of research and practice, good results have been achieved in the fields of medicine, environmental science, and ecology. However, there is currently a lack of a more systematic review of progress in the main research directions of PBPK models, especially a more comprehensive understanding of the application in aquatic environmental research. In this review, a total of 3974 articles related to PBPK models from 1996 to 24 March 2024 were collected. Then, the main research areas of the PBPK model were categorized based on the keyword co-occurrence maps and cluster maps obtained by CiteSpace. The results showed that research related to medicine is the main application area of PBPK. Four major research directions included in the medical field were “drug assessment”, “cross-species prediction”, “drug–drug interactions”, and “pediatrics and pregnancy drug development”, in which “drug assessment” accounted for 55% of the total publication volume. In addition, bibliometric analyses indicated a rapid growth trend in the application in the field of environmental research, especially in predicting the residual levels in organisms and revealing the relationship between internal and external exposure. Despite facing the limitation of insufficient species-specific parameters, the PBPK model is still an effective tool for improving the understanding of chemical–biological effectiveness and will provide a theoretical basis for accurately assessing potential risks to ecosystems and human health. The combination with the quantitative structure–activity relationship model, Bayesian method, and machine learning technology are potential solutions to the previous research gaps.

Smoking prevalence stays high among adults in China, which also makes children exposed to secondhand smoke (SHS) in their households. This study aimed to investigate the status of SHS exposure among Chinese children, identify the influencing factors, and determine “co-exposure” to tobacco and other smokes in households. A total of 41,439 children aged 6–17 years were recruited from 30 provinces in Mainland China through the first Chinese Environmental Exposure-Related Human Activity Model Survey for Children (CEERHAPS-C). Information regarding children’s demographics, socioeconomic status, and exposures to SHS and solid fuel smoke (SFS) in households was collected using a comprehensive questionnaire. Factors that affected exposures to household smokes were identified using multivariable logistic regressions. The overall prevalence of household SHS exposure was 41.7%, and the average duration was 14.7 ± 14.6 min/day among the exposed participants. Prevalence of household SHS exposure increased among children in older age groups and with parents in lower education levels. Among SHS-exposed children, 34% had co-exposure to SFS, and they had a significantly higher risk of co-exposure than non-SHS exposed children (odds ratio = 1.12, 95% confidence interval: 1.061, 1.162). The prevalence of household SHS exposure remains high among school-age children, suggesting the need to develop and implement smoking-free home programs.

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.

Benzene, toluene, ethylbenzene and xylene isomers (BTEX) have raised increasing concern due to their adverse effects on human health. In this study, a coking factory and four communities nearby were selected as the research area. Atmospheric BTEX samples were collected and determined by a preconcentrator GC–MS method. Four biomarkers in the morning urine samples of 174 participants from the communities were measured by LC–MS. The health risks of BTEX exposure via inhalation were estimated. This study aimed to investigate the influence of external BTEX exposure on the internal biomarker levels and quantitatively evaluate the health risk of populations near the coking industry. The results showed that the average total BTEX concentration in residential area was 7.17 ± 7.24 μg m⁻³. Trans,trans-muconic acid (T,T-MA) was the urinary biomarker with the greatest average level (127 ± 285 μg g⁻¹ crt). Similar spatial trends can be observed between atmospheric benzene concentration and internal biomarker levels. The mean values of the LCR for male and female residents were 2.15 × 10⁻⁵ and 2.05 × 10⁻⁵, respectively. The results of the risk assessment indicated that special attention was required for the non-occupational residents around the area.