To evaluate pesticide regulatory standards in agricultural crops, we introduced a regulatory modeling framework that can flexibly evaluate a population’s aggregate exposure risk via maximum residue levels (MRLs) under good agricultural practice (GAP). Based on the structure of the aggregate exposure model and the nature of variable distributions, we optimized the framework to achieve a simplified mathematical expression based on lognormal variables including the lognormal sum approximation and lognormal product theorem. The proposed model was validated using Monte Carlo simulation, which demonstrates a good match for both head and tail ends of the distribution (e.g., the maximum error = 2.01% at the 99th percentile). In comparison with the point estimate approach (i.e., theoretical maximum daily intake, TMDI), the proposed model produced higher simulated daily intake (SDI) values based on empirical and precautionary assumptions. For example, the values at the 75th percentile of the SDI distributions simulated from the European Union (EU) MRLs of 13 common pesticides in 12 common crops were equal to the estimated TMDI values, and the SDI values at the 99th percentile were over 1.6-times the corresponding TMDI values. Furthermore, the model was refined by incorporating the lognormal distributions of biometric variables (i.e., food intake rate, processing factor, and body weight) and varying the unit-to-unit variability factor (VF) of the pesticide residues in crops. This ensures that our proposed model is flexible across a broad spectrum of pesticide residues. Overall, our results show that the SDI is significantly reduced, which may better reflect reality. In addition, using a point estimate or lognormal PF distribution is effective as risk assessments typically focus on the upper end of the distribution.

Chinese children have been exposed to high level of lead due to polluted air, dust, contaminated foods and water, etc. In this research, we investigated published blood lead levels (BLLs) reflecting 1,057,832 Chinese children aged at 0–12 and teenagers aged at 13–18 in the past 30 years (1991–2020). The data mining and estimation were performed innovatively by Monte Carlo simulation to remedy the skewed distribution-induced bias. The temporal trend of Chinese children’s BLLs showed an obvious decrease in the past decades from 88.74 μg/L (Geometric SD = 4.09) during 1991–1995 to 27.32 μg/L (Geometric SD = 4.18) during 2016–2020. This study also indicated that children’s BLLs of Yunnan, Guizhou, Shanxi were at relatively high levels and most provinces showed a downward trend. Chinese boys aged at 1–18 years old had higher BLLs (GM: 44.03 μg/L) compared to girls (GM: 41.32 μg/L) (p < 0.001). At different age groups, Chinese children’s BLLs were 42.04 μg/L (1–3 years old), 52.88 μg/L (4–6 years old), 50.49 μg/L (7 and above years old), respectively. Although the BLLs of Chinese children exhibited a continuous declined trend in the past 30 years, it was still higher than that in developed countries, which indicated that more efforts are needed in children’s BLLs control.

This study performs an environmental risk assessment (ERA) of the anthelmintic medicine albendazole (ABZ) in the eastern African region. A systematic literature search strategy was applied to obtain quantitative information on the physicochemical characteristics, the metabolization-fate, the ecotoxicity and the environmental occurrence in different countries worldwide serving as model regions. In addition, insilico tools were employed to obtain data on physicochemical characteristics and toxic hazards of ABZ and its metabolites. Moreover, ERA models were used to predict environmental concentrations in different compartments and compare them with the measured environmental concentrations. Finally, the environmental risk of ABZ in the eastern Africa was estimated by calculating the risk quotient (RQ), and its uncertainty estimated by Monte Carlo simulation. The predicted environmental concentrations of ABZ in surface water in the model region based on consumption (1.6–267 ng/L) were within the range of values obtained from the measured environmental concentrations of the same region (0.05–101,000 ng/L). Using these models with adapted input variables for eastern Africa, the predicted surface water concentration in that region was 19,600 ± 150 ng/L (95% CI). The calculated soil concentrations of ABZ in the model regions and the eastern Africa were found to be 0.057 ± 0.0 μg/kg and 0.022 ± 0.0 μg/kg, respectively. The environmental risk expressed as risk quotient of ABZ in eastern Africa estimated for the aquatic compartment (146 ± 1) indicated a significant environmental risk calling on appropriate actions from the competent authorities to reduce this risk in this region.

Nanoscale zero-valent iron (nZVI) is the main nanomaterial used in environmental remediation processes. The present study aims to evaluate the life cycle sustainability of nZVI production methods applied in environmental remediation. Three production methods of nZVI were selected for analysis: milling, liquid reduction with sodium borohydride, and chemical reduction with hydrogen gas (in two approaches: considering the goethite and hematite synthesis and after using in nZVI production and, using goethite and hematite particles already synthesized for nZVI production). The life cycle sustainability assessment was carried out based on a multi-criteria and multi-attribute analysis. The multi-criteria analysis was used to determine impact category preferences of different specialists in sustainability and remediation, and calculate the sustainability score through a linear additive model. Finally, a Monte Carlo simulation was used to quantify the results uncertainty. The functional unit considered was 1.00 kg of nZVI produced. The milling method and the hydrogen gas method in approach considering the use goethite and hematite particles already synthesized were the most sustainable. Moreover, the sustainability index was found to be influenced by the considered location scenarios as well as the perspectives of the different specialists, which was essential in producing a more accurate and comprehensive evaluation of the aforementioned sustainability methods. Overall, this study significantly contributed to applications of the state-of-the-art life cycle sustainability assessment in studies regarding nanomaterials, employing a simple methodology that included an analysis of different specialists. In addition, this is the first article that uses life cycle sustainability assessment in nanomaterials.

The accuracy of the nitrogen (N) budget is of great importance for evidence-based decision-making to address both food security and environmental protection challenges. This study attempts to advance understanding of uncertainties in China's N budget using the Coupled Human And Natural Systems (CHANS) model and Monte Carlo simulation from 1980 to 2018. Results show that the spatial and temporal variations in agricultural and industrial activities and insufficient knowledge on N cycling parameterization are the two dominant causes of uncertainties in the N budget in China. Uncertainties of N inputs generally are <10%, while they are <30% for N outputs and >30% for N accumulations. Uncertainty of nitrogen oxides emission is more sensitive to energy consumption due to the large contributions from industry and transportation. While the uncertainty of ammonia emission is predominantly affected by agricultural activity. Combining surface measurements, satellite observations, and atmospheric simulation models enables cross-check of N fluxes in multiple systems and reduces uncertainties of N budget.

Polycyclic aromatic hydrocarbons (PAHs) and certain ingredients in personal care products, such as parabens, bisphenols, triclosan and phthalate metabolites, have become ubiquitous in the world. Concerns of human exposure to these pollutants have increased during recent years because of various adverse health effects of these chemicals. Multiple compounds including parabens, bisphenols, triclosan, phthalate metabolites (mPAEs) and hydroxyl PAHs (OH-PAHs) in urine samples from Guangzhou were determined simultaneously to identify the human exposure pathways without external exposure data combined with data analysis, and the toxicants posed the highest risk to human health were screened in the present study. The detection frequencies for the chemicals exceeded 90%. Among the contaminants, mPAEs showed the highest concentrations, followed by OH-PAHs, with triclosan present at the lowest concentrations. Mono-n-butyl phthalate, methylparaben, bisphenol A, and hydroxynaphthalene represented the most abundant mPAE, parabens, bisphenol, and OH-PAH compounds, respectively. The present PAHs are mainly exposed to human through inhalation, while the chemicals added to personal care products are mainly exposed to human through oral intake and dermal contact. The urine samples from suburban subjects showed significantly higher OH-PAH levels than the urine samples from urban subjects, and females had lower OH-PAH levels than males. Urinary concentrations of the analyzed contaminants were significantly correlated with age, body mass index, residence time, as well as the frequencies of alcohol consumption and swimming. Risk assessments based on Monte Carlo simulation indicated that approximately 30% of the subjects suffered non-carcinogenic risks from mPAEs and OH-PAHs, with mPAEs accounting for 89% of the total risk.

Identification of pollution point source in rivers is strenuous due to accidental chemical spills or unmanaged wastewater discharges. It is crucial to take physical characteristics into account in the estimation of pollution sources. In this study, an integrated inverse modeling framework is developed to identify a point source of accidental water pollution based on the contaminant concentrations observed at monitoring sites in time series. The modeling approach includes a Markov chain Monte Carlo method based on Bayesian inference (Bayesian-MCMC) inverse model and a genetic algorithm (GA) inverse model. Both inverse models can estimate the pollution sources, including the emission mass quantity, release time, and release position in an accidental river pollution event. The developed model is first tested for a hypothetical case with field river conditions. The results show that the source parameters identified by the Bayesian-MCMC inverse model are very close to the true values with relative errors of 0.02% or less; the GA inverse model also works with relative errors in the range of 2%–7%. Additionally, the uncertainties associated with model parameters are analyzed based on global sensitive analysis (GSA) in this study. It is also found that the emission mass of pollution source positively correlates with the dispersion coefficient and the river cross-sectional area, whereas the flow velocity significantly affects release position and release time. A real case study in the Fen River is further conducted to test the applicability of the developed inverse modeling approach. Results confirm that the Bayesian-MCMC model performs better than the GA model in terms of accuracy and stability for the field application. The findings of this study would support decision-making during emergency responses to river pollution incidents.

Squids are globally distributed. Hg-contaminated squids may have high risks on humans. With abundant Se (antagonistic effect on Hg), the risks can be reduced. We collected squids around the world (Northwest Pacific Ocean, Southeast Pacific Ocean and Indian Ocean). Concentrations of Hg and Se were region-based and tissue-based. The higher content of Se were, the lower relative Hg levels were. The correlation between Se:Hg and Se was the strongest in the digestive gland. The values of Se:Hg and THQ all confirm that the health risk was lower in samples with higher concentrations of Se. Despite the risk assessment by Se:Hg, BRV and THQ analysis showed no risk when consumed in moderation, the maximum daily intake is provided based on Monte Carlo simulation. In future, when evaluating the risks cause by Hg exposure and providing the recommended daily amount, it may need to concurrent consideration of Se levels.

Hg and ²¹⁰Po were measured in the muscle tissue of commercially important fish species collected in the main coastal cities of the Djiboutian coast (Tadjoura Gulf) to evaluate the potential risk associated with their consumption. The levels of Hg among the different species ranged from 0.02 to 1.69 mg/kg w.w and exceeded tolerable limits as reported by the national regulation (2000-0727/PR/MAEM) and the Codex Alimentarius. The probabilistic distributions of health hazard were evaluated through Monte-Carlo simulation, which confirmed the carcinogenic risk from Hg. The levels of ²¹⁰Po ranged from 4.1 to 134.5 Bq/kg w.w among muscle tissues of the eight commercially important species. The carcinogenic risk was in an unacceptable range and simulation revealed that children were the most vulnerable population. The results obtained confirms that the health impact is reduced when consuming two servings per week.

This article presents the results of studies of the activity of radionuclides in peat-bog profiles of the European subarctic of Russia. Two peat profiles were collected in different areas of the Arkhangelsk region. The peat cores were used to determine ²¹⁰Pb, ¹³⁷Cs, ²⁴¹Am, ²³⁹Pu, ²⁴⁰Pu, ²³⁸U, and ²³⁴U content. To estimate the relationship between radionuclide activity and physicochemical parameters of peat, the content of organic matter, water-soluble salts, carbonates and ash, and the pH of aqueous and salt extracts were studied. Radionuclide activity concentrations in peat samples were measured using inductively coupled plasma mass spectrometry (ICP-MS), low-background semiconductor gamma spectrometry with a high-purity germanium (HPGe) detector, and alpha spectrometry. The ²¹⁰Pb chronology of peat cores was studied using a constant flow model based on the Monte Carlo simulation method. Comparison of ²¹⁰Pb dating data showed that the position of the maximum activity peaks of anthropogenic radionuclides shifted along the peat profile. This is probably due to the relative mobility of different radionuclides in the peat massif. Measurement of the atomic ratio ²⁴⁰Pu/²³⁹Pu showed that the main sources of pollution in the peatlands of the European subarctic of Russia are global fallout from atmospheric tests from the 1950s through 1980 and fallout from the Chernobyl nuclear accident in 1986. This study shows that a complex of radioactive isotopes in peat deposits can provide valuable information on the environmental pollution loads of subarctic territories.