Environmental exposure to 4-nonylphenol (4-NP) is extensive, and studies related to human risk assessment must continue. Especially, prediction of toxicodynamics (TDs) related to reproductive toxicity in males is very important in risk-level assessment and management of 4-NP. This study aimed to develop a physiologically-based-toxicokinetic-toxicodynamic (PBTK-TD) model that added a TD prostate model to the previously reported 4-n-nonylphenol (4-n-NP) physiologically-based-pharmacokinetic (PBPK) model. Modeling was performed under the assumption of similar TKs between 4-n-NP and 4-NP because TK experiments on 4-NP, a random-mixture, are practically difficult. This study was very important to quantitatively predict the TKs and TDs of 4-NP by age at exposure using an advanced PBTK-TD model that reflected physiological-changes according to age. TD-modeling was performed based on the reported toxic effects of 4-NP on RWPE-1 cells, a human-prostate-epithelial-cell-line. Through a meta-analysis of reported human physiological data, body weight, tissue volume, and blood flow rate patterns according to age were mathematically modeled. These relationships were reflected in the PBTK-TD model for 4-NP so that the 4-NP TK and TD changes according to age and their differences could be confirmed. Differences in TK and TD parameters of 4-NP at various ages were not large, within 3.61-fold. Point-of-departure (POD) and reference-doses for each age estimated using the model varied as 426.37–795.24 and 42.64–79.52 μg/kg/day, but the differences (in POD or reference doses between ages) were not large, at less than 1.87-times. The PBTK-TD model simulation predicted that even a 100-fold 4-NP PODₘₐₙ dose would not have large toxicity to the prostate. With a focus on TDs, the predicted maximum possible exposure of 4-NP was as high as 6.06–23.60 mg/kg/day. Several toxicity-related values estimated by the dose-response curve were higher than those calculated, depending upon the PK or TK, which would be useful as a new exposure limit for prostate toxicity of 4-NP.

South Korea has experienced a rapid increase in ozone concentrations in surface air together with China for decades. Here we use a 3-D global chemical transport model, GEOS-Chem nested over East Asia (110 E - 140 E, 20 N–50 N) at 0.25° × 0.3125° resolution, to examine locally controllable (domestic anthropogenic) versus uncontrollable (background) contributions to ozone air quality at the national scale for 2016. We conducted model simulations for representative months of each season: January, April, July, and October for winter, spring, summer, and fall and performed extensive model evaluation by comparing simulated ozone with observations from satellite and surface networks. The model appears to reproduce observed spatial and temporal ozone variations, showing correlation coefficients (0.40–0.87) against each observation dataset. Seasonal mean ozone concentrations in the model are the highest in spring (39.3 ± 10.3 ppb), followed by summer (38.3 ± 14.4 ppb), fall (31.2 ± 9.8 ppb), and winter (24.5 ± 7.9 ppb), which is consistent with that of surface observations. Background ozone concentrations obtained from a sensitivity model simulation with no domestic anthropogenic emissions show a different seasonal variation in South Korea, showing the highest value in spring (46.9 ± 3.4 ppb) followed by fall (38.2 ± 3.7 ppb), winter (33.0 ± 1.9 ppb), and summer (32.1 ± 6.7 ppb). Except for summer, when the photochemical formation is dominant, the background ozone concentrations are higher than the seasonal ozone concentrations in the model, indicating that the domestic anthropogenic emissions play a role as ozone loss via NOₓ titration throughout the year. Ozone air quality in South Korea is determined mainly by year-round regional background contributions (peak in spring) with summertime domestic ozone formation by increased biogenic VOCs emissions with persistent NOₓ emissions throughout the year. The domestic NOₓ emissions reduce MDA8 ozone around large cities (Seoul and Busan) and hardly increase MDA8 in other regions in spring, but it increases MDA8 across the country in summer. Therefore, NOₓ reduction can be effective in control of MDA8 ozone in summer, but it can have rather countereffect in spring.

A better understanding of the spatiotemporal dynamics and influencing factors of sulfonamide antibiotic resistance genes (ARGs) distribution in subsurface flow constructed wetlands is essential to improve the ARGs removal efficiency. The spatiotemporal dynamics of sulfonamide ARGs were explored in the vertical upflow subsurface flow constructed wetland (VUSFCW). The results showed that the absolute abundance of ARGs presented a trend of bottom layer > middle layer > top layer. The relative abundance of ARGs decreased significantly from the bottom layer to the middle layer, but increased in the top layer. The bottom layer was the main stage to remove ARGs. The absolute abundance of ARGs at each point in summer was significantly higher than that in winter. Based on the spatiotemporal distribution of ARGs, the internal mechanism of ARGs dynamic change was explored by the partial least square path analysis model. The results showed that physical-chemical factors, microorganisms and antibiotics indirectly affected the spatiotemporal distribution of ARGs mainly through mobile genetic elements. The indirect influence coefficients of physical-chemical factors, microorganisms and antibiotics on the spatiotemporal distribution of ARGs were 0.505, 0.221 and 0.98 respectively. The direct influence coefficient of MGEs on the spatiotemporal distribution of ARGs was 0.895. The results of network analysis showed that the potential host species of ARGs in summer were more abundant than those in winter. The selection mode of sulfonamide ARGs to potential hosts was nonspecific. There is a risk of sulfonamide ARGs infecting pathogens in VUSFCW. Fortunately, VUSFCW has proven effective in reducing the absolute abundance of ARGs and the potential risk of pathogens carrying ARGs. These findings provide a model simulation and theoretical basis for effectively reducing the threat of ARGs.

We apply a tracer model linked with a 3D circulation model to simulate transport and fate of water-soluble persistent substances in the Black Sea that do not bioaccumulate to a considerable extent. The model uses specified degradation time and identical concentrations in the rivers to build a correlation between average concentration in the basin and half-life (DT50). The average concentration in certain sub-regions of the Black Sea can be estimated using an exponential dependence of DT50, if DT50 and concentration in rivers are known. Averaging is performed on the simulations from 2000 to 2019 with real atmospheric forcing and river runoff. A well-defined seasonal cycle is evident for the average shelf concentration, while the average concentration in the deep region does not show a pronounced seasonal cycle or inter-annual variations. With the help of the existing observational data, we estimate DT50 and concentration in the rivers for carbamazepine, sulfamethoxazole and terbuthylazine. Atrazine and simazine are believed to have accumulated in the basin for a long time due to their widespread use in the past and the slow rate of degradation in the marine environment.

Contribution of liquid water content (LWC) to the levels of the carcinogenic particulate nitro(so) compounds and the chemistry affecting LWC were investigated based on the observation of seven nitrosamines and two nitramines in rural (Seosan) and urban (Seoul) area in South Korea during October 2019 and a model simulation. The concentrations of both the total nitrosamines and nitramines were higher in Seosan (12.48 ± 16.12 ng/m³ and 0.65 ± 0.71 ng/m³, respectively) than Seoul (7.41 ± 13.59 ng/m³ and 0.24 ± 0.15 ng/m³, respectively). The estimated LWC using a thermodynamic model in Seosan (12.92 ± 9.77 μg/m³) was higher than that in Seoul (6.20 ± 5.35 μg/m³) mainly due to higher relative humidity (75 ± 9% (Seosan); 62 ± 10% (Seoul)) and higher concentrations of free ammonia (0.13 ± 0.09 μmol/m³ (Seosan); 0.08 ± 0.01 μmol/m³ (Seoul)) and total nitric acid (0.09 ± 0.07 μmol/m³ (Seosan); 0.04 ± 0.02 μmol/m³ (Seoul)) in Seosan while neither fog nor rain occurred during the sampling period. The relatively high concentrations of the particulate nitrosamines (>30 ng/m³) only observed probably due to the higher LWC (>10 μg/m³) in Seosan. It implies that aqueous phase reactions involving NO₂ and/or uptake from the gas phase enhanced by LWC could be promoted in Seosan. Strong correlation between the concentrations of nitrosodi-methylamine (NDMA), an example of nitrosamines, simulated by a kinetic box model including the aqueous phase reactions and the measured concentration of NDMA in Seosan (R = 0.77; 0.37 (Seoul)) indicates that the aqueous phase reactions dominantly enhanced the NDMA concentrations in Seosan. On the other hand, it is estimated that the formation of nitrosamines by aqueous phase reaction was not significant due to the relatively lower LWC in Seoul compared to that in Seosan. Furthermore, it is presumed that nitramines are mostly emitted from the primary emission sources. This study implies that the concentration of the particulate nitrosamines can be promoted by aqueous phase reaction enhanced by LWC.

While polychlorinated biphenyl (PCB)-related risks have been reported at the cellular, organ, and individual levels in some marine mammals, studies quantifying the PCB-associated population-level effects are limited. Here, we combined chemical analysis and individual-based model simulation to investigate the impact of PCBs on the Indo-Pacific humpback dolphin (sub)population from the Pearl River Estuary (PRE). An annual PCB accumulation rate of 0.29 ± 0.07 mg/kg lipid per year was estimated based on the measured age-specific male data as males continue to accumulate PCBs throughout their lifetime, without depurating contaminant loads. Using the Taiwan Strait dolphin population with low PCBs as a baseline, we compare our model simulations in PRE population to estimate relative population impacts of PCBs and other stressors. When using the current vital rates of the PRE dolphins which have been affected by PCBs and other stressors (e.g., underwater noise, prey limitation, etc.), our simulations revealed a substantial decline (8.1%) in the annual population growth rate (λ) of PRE metapopulation compared to baseline over the next 100 years. At the estimated PCB accumulation rate, the PCB-mediated effects on calf survival and immunity would cause a slight decline (0.9%) in λ relative to baseline. Our findings suggest a relatively limited impact of PCBs on the long-term survival of PRE dolphins among all stressors. However, it should be noted that even under model simulations where dietary PCBs were eliminated, humpback dolphins would still need a long time to reduce their PCB burdens to a relatively “safe” level through biological cycling. Considering that the baseline vital rates might also have been affected by PCBs and other stressors, our results are considered relative rather than absolute. This study provides a starting point for quantifying population-level consequences of contaminant exposure on humpback dolphins, although more efforts are needed to perfect this type of analysis.

Simulation model is very essential for predicting the environmental fate and the potential environmental consequences of chemical pollutants including those from accidental chemical spills. However very few of such simulation model is seen related to Chinese costal water body. As the first step toward our final goal to develop a simulation model for the prediction and the risk assessment of chemical pollutants in Chinese coastal water, this study developed a three-dimensional (3D) hydrodynamic model of Xiamen Bay (XMB). This hydrodynamic model was externally derived by meteorological data, river discharge and boundary conditions of XMB. We used the model to calculate the physical factors, especially water temperature, salinity and flow field, from June to September 2016 in XMB. The results demonstrated a good match between observations and simulations, which underscores the feasibility of this model in predicting the spatial-temporal concentration of chemical pollutants in the coastal water of XMB. Longitudinal salinity distributions and the mixing profile of river-sea interactions are discussed, including the obvious gradation of salinity from the river towards sea sites shown by the model. We further assumed that 1000 kg and 1000 mg/L of a virtual chemical pollutant leaked out from Jiulong River (JR) estuary (point source) and whole XMB (non-point source), respectively. The model illustrates that it takes three months for XMB to become purified when point source pollution occurs in the estuary, while half a year to be required in the case of non-point source pollution across the entire bay. Moreover, the model indicated that pollutants can easily accumulate in the western coastal zone and narrow waters like Maluan Bay, which can guide environmental protection strategies.

Soils, especially permafrost in the Arctic and the Tibetan Plateau, are one of the largest reservoirs of mercury (Hg) in the global environment. The Hg concentration in the grassland soils over the Tibetan Plateau and its driving factors have been less studied. This study analyzes soil total mercury (STHg) concentrations and its vertical distribution in grassland soil samples collected from the Tibetan Plateau. We adopt a nested-grid high-resolution GEOS-Chem model to simulate atmospheric Hg deposition. The relationship between STHg and soil organic carbon (SOC), as well as atmospheric deposition, are explored. Our results show that the STHg concentrations in the Tibetan Plateau are 19.8 ± 12.2 ng/g. The concentrations are higher in the south and lower in the north in the Tibetan Plateau, consistent with the previous results. Our model shows that the average deposition flux of Hg is 3.3 μg m⁻² yr⁻¹, with 57% contributed by dry deposition of elemental mercury (Hg⁰), followed by dry (19%) and wet (24%) deposition of divalent mercury. We calculate the Hg to carbon ratio (RHg:C) as 5.6 ± 6.5 μg Hg/g C, and the estimated STHg is 86.6 ± 101.2 Gg in alpine grasslands in the Tibetan Plateau. We find a positive relationship between STHg and SOC in the Tibetan Plateau (r² = 0.36) and a similar positive relationship between STHg and atmospheric total Hg deposition (r² = 0.24). A multiple linear regression involving both variables better model the observed STHg (r² = 0.42). We conclude that SOC and atmospheric deposition influence STHg simultaneously in this region. The data provides information to quantify the size of the soil Hg pool in the Tibetan Plateau further, which has important implications for the Hg cycles in the permafrost regions as well as on the global scale.

Peroxyacetyl nitrate (PAN) is an important reservoir of atmospheric nitrogen, modulating reactive nitrogen cycle and ozone (O3) formation. To understand the origins of PAN, a field measurement was conducted at Tung Chung site (TC) in suburban Hong Kong from October to November 2016. The average level of PAN was 0.63 ± 0.05 ppbv, with a maximum of 7.30 ppbv. Higher PAN/O3 ratio (0.043–0.058) was captured on episodes, i.e. when hourly maximum O3 exceeded 80 ppbv, than on non-episodes (0.01), since O3 production was less efficient than PAN when there was an elevation of precursors (i.e. volatile organic compounds (VOCs) and nitrogen oxide (NOx)). Model simulations revealed that oxidations of acetaldehyde (65.3 ± 2.3%), methylglyoxal (MGLY, 12.7 ± 1.2%) and other oxygenated VOCs (OVOCs) (8.0 ± 0.6%), and radical cycling (12.2 ± 0.8%) were the major production pathways of peroxyacetyl (PA) radical, while local PAN formation was controlled by both VOCs and nitrogen dioxide (NO2). Among all VOC species, carbonyls made the highest contribution (59%) to PAN formation, followed by aromatics (26%) and biogenic VOCs (BVOCs) (10%) through direct oxidation/decomposition. Besides, active VOCs (i.e. carbonyls, aromatics, BVOCs and alkenes/alkynes) could stimulate hydroxyl (OH) production, thus indirectly facilitating the PAN formation. Apart from primary emissions, carbonyls were also generated from oxidation of first-generation precursors, i.e., hydrocarbons, of which xylenes contributed the most to PAN production. Furthermore, PAN formation suppressed local O3 formation at a rate of 2.84 ppbv/ppbv, when NO2, OH and hydroperoxy (HO2) levels decreased and nitrogen monoxide (NO) value enhanced. Namely, O3 was reduced by 2.84 ppbv per ppbv PAN formation. Net O3 production rate was weakened (∼36%) due to PAN photochemistry, so as each individual production and loss pathway. The findings advanced our knowledge of atmospheric PAN and its impact on O3 production.