Although huge interspecies differences in the response to dioxins have been acknowledged, toxic equivalency factors derived from rodent studies are often used to assess human health risk. To determine interspecies differences, we first developed a toxicokinetic model in humans by measuring dioxin concentrations in environmental and biomonitoring samples from Southern China. Significant positive correlations between dioxin concentrations in blood and age were observed for seven dioxin congeners, indicating an age-dependent elimination rate. Based on toxicokinetic models in humans, the half-lives of 15 dioxin congeners were estimated to be 1.60–28.55 years. In consideration that the highest contribution to total toxic equivalency in blood samples was by 12378-polychlorinated dibenzo-p-dioxin (P₅CDD), this study developed a physiologically based pharmacokinetic (PBPK) model of 12378-P₅CDD levels in the liver, kidney, and fat of C57/6J mice exposed to a single oral dose, and the half-life was estimated to be 26.1 days. Based on estimated half-lives in humans and mice, we determined that the interspecies difference of 12378-P₅CDD was 71, much higher than the default usually used in risk assessment. These results could reduce the uncertainty human risk assessment of 12378-P₅CDD, and our approach could be used to estimate the interspecies differences of other dioxin congeners.

Antibiotics in the environment usually co-exist with their transformation products with retained toxicity, raising concerns about environmental risks of their combined exposure. Herein, we reported a novel predictive approach for evaluating the individual and combined toxicity for photodegradation products of fluoroquinolone antibiotics (FQs). Quantitative structure-activity relationship (QSAR) models with promising predictive performance were constructed and validated using experimental data obtained with 13 FQs and 78 mixtures towards E. coli. A structural descriptor reflecting the interaction among FQ molecules and the target protein was employed in the QSAR models, which was obtained through molecular docking and thus provided a rational mechanistic explanation for these models. The predicted results indicated that the degradation products displayed varying degrees of changes compared to the parent FQs, while the combined toxicity of FQs and their degradation products was mostly additive. Furthermore, following UV irradiation the degradation products displayed elevated capacity of inducing resistance mutations in E. coli, though their overall toxicity was reduced. This result highlights the implications of antibiotic degradation products on resistance development in bacteria and stresses the importance of considering such impacts during environmental risk assessments of antibiotics.

A comprehensive modelling approach has been developed to predict population exposure to the ambient air PM₂.₅ concentrations in different microenvironments in London. The modelling approach integrates air pollution dispersion and exposure assessment, including treatment of the locations and time activity of the population in three microenvironments, namely, residential, work and transport, based on national demographic information. The approach also includes differences between urban centre and suburban areas of London by taking account of the population movements and the infiltration of PM₂.₅ from outdoor to indoor. The approach is tested comprehensively by modelling ambient air concentrations of PM₂.₅ at street scale for the year 2008, including both regional and urban contributions. Model analysis of the exposure in the three microenvironments shows that most of the total exposure, 85%, occurred at home and work microenvironments and 15% in the transport microenvironment. However, the annual population weighted mean (PWM) concentrations of PM₂.₅ for London in transport microenvironments were almost twice as high (corresponding to 13–20 μg/m³) as those for home and work environments (7–12 μg/m³). Analysis has shown that the PWM PM₂.₅ concentrations in central London were almost 20% higher than in the surrounding suburban areas. Moreover, the population exposure in the central London per unit area was almost three times higher than that in suburban regions. The exposure resulting from all activities, including outdoor to indoor infiltration, was about 20% higher, when compared with the corresponding value obtained assuming inside home exposure for all times. The exposure assessment methodology used in this study predicted approximately over one quarter (−28%) lower population exposure, compared with using simply outdoor concentrations at residential locations. An important implication of this study is that for estimating population exposure, one needs to consider the population movements, and the infiltration of pollution from outdoors to indoors.

In recent years, implementation of aggressive and strict clean air policies has resulted in significant decline in observed PM₂.₅ concentration in the Beijing–Tianjin–Hebei (BTH) region and its surrounding areas (i.e., the “2 + 26” region). To eliminate the effects of interannual and seasonal meteorological variation, and to evaluate the effectiveness of emission abatement policies, we applied a boosted regression tree model to remove confounding meteorological factors. Results showed that the annual average PM2.5 concentration normalized by meteorology for the “2 + 26” region declined by 38% during 2014–2019 (i.e., from 96 to 60 μg/m³); however, the BTH region exhibited the most remarkable decrease in PM₂.₅ concentration (i.e., a 60% reduction). Certain seasonal trend in normalized PM₂.₅ level remained for four target subregions owing to the effects of anthropogenic emissions in autumn and winter. Although strong interannual variations of meteorological conditions were unfavorable for pollutant dispersion during the heating seasons of 2016–2018, the aggressive abatement policies were estimated to have contributed to reductions in normalized PM₂.₅ concentration of 19%, 10%, 19%, and 17% in the BTH, Henan, Shandong, and Shanxi subregions, respectively. Our study eliminated the meteorological contribution to concentration variation and confirmed the effectiveness of the implemented clean air policies.

In predicting palm oil mill effluent (POME) degradation efficiency, previous developed quadratic model quantitatively evaluated the effects of O2 flowrate, TiO2 loadings and initial concentration of POME in labscale photocatalytic system, which however suffered from low generalization due to the overfitting behaviour. Evidently, high RMSE (131.61) and low R₂ (−630.49) obtained indicates its insufficiency in describing POME degradation at unseen factor ranges, hence verified the fact of poor generalization. To overcome this issue, several models were developed via machine learning-assisted techniques, namely Gaussian Process Regression (GPR), Linear Regression (LR), Decision Tree (DT), Supported Vector Machine (SVM) and Regression Tree Ensemble (RTE), subsequently being assessed systematically. To achieve high generalization, all models were subjected to ‘train-all-test-all’ strategy, 5-fold and 10-fold cross validation. Specifically, GPR model was furnished with high accuracy in ‘train-all-test-all’ strategy, judging from its low RMSE (1.0394) and high R₂ (0.9962), which however menaced by the risk of overfitting. In contrast, despite relatively poorer RMSE and R₂ (1.7964 and 0.9886) obtained in 5-fold cross validation, GPR model was rendered with highest generalization, while sufficiently preserving its accuracy in development process. Besides, SVM and RTE models were also demonstrated promising R₂ (0.9372 and 0.9208), which however shadowed by their high RMSEs (4.2174 and 4.7366). Furthermore, the extraordinary generalization of GPR model was coincidentally verified in 10-fold cross validation. The lowest RMSE (2.1624) and highest R₂ (0.9835) obtained with feature number of 36 asserted its sufficiency in both generalization and accuracy prospect. Other models were all rendered with slight lower R₂ (> 0.9), plausibly due to the higher RMSE (> 4.0). According to GPR model, optimized POME degradation (52.52%) can be obtained at 70 mL/min of O₂, 70.0 g/L of TiO₂ and 250 ppm of POME concentration, with only ∼3% error as compared to the actual data.

Both air pollution and dyslipidemias contributed to large number of deaths and disability-adjusted life lost years. Long-term air pollution exposure was related to changed blood lipids and risk of dyslipidemias. This study was designed to evaluate relationships between air pollutants, blood lipids and prevalence of dyslipidemias in a Chinese rural population exposed to high-level air pollution based on baseline data of The Henan Rural Cohort study. An amount of 39,057 participants from rural areas in China were included. The 3-year average exposure of air pollutants (PM2.5, PM10, NO2) was estimated by a spatiotemporal model. Logistic and linear regression models were employed to explore relationships between air pollutants, blood lipids (TC, TG, HDL-C and LDL-C) and prevalence of dyslipidemias. The three-year concentration of PM2.5, PM10 and NO2 was 72.8 ± 2.3 μg/m3, 131.5 ± 5.7 μg/m3and 39.1 ± 3.1 μg/m3, respectively. Overall, increased air pollution exposure was related to increased TC and LDL-C, while decreased TG and HDL-C. Each 1-μg/m3 increment of PM2.5 was related to 0.10% (0.07%–0.19%) increase in TC, 0.63% (0.50%–0.77%) increase in LDL-C, 2.93% (2.70%–3.16%) decrease in TG, 0.49% (0.38%–0.60%) decrease in HDL-C; and 5.7% (95%CI: 3.7%–7.6%), 4.0% (95%CI: 2.1%–6.0%) and 3.8% (95%CI: 2.5%–5.1%) increase in odds for hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia, respectively. Stronger associations were found in male and older participants. Findings suggest that air pollutants were associated with changed blood lipid levels and higher risk of dyslipidemias among rural population. Male and elder people should pay more attention to personal safety protection.

Polybrominated diphenyl ethers (PBDEs) are a series of highly persistent organic pollutants (POPs) ubiquitously distributed in marine environments. As key primary producers, microalgae are the start of PBDEs bioaccumulations and vulnerable to their toxicities. In order to deeply investigate the toxic mechanism of PBDEs on microalgal cells, the occurrence of programmed cell death (PCD) in a model diatom Thalassiosira pseudonana and its possible mediating mechanism were studied. The results indicated: cell death of T. pseudonana happened under the stress of BDE-47, which was proved to be PCD based on the correlations with three biochemical markers (DNA fragmentation, phosphatidylserine externalization and caspase activity) and three molecular markers [Metacaspase 2 gene (TpMC2), Death-associated protein gene (DAP3) and Death-specific protein 1 gene (TpDSP1)]; Furthermore, the changes of cellular ROS levels were correlated with the PCD markers and the dead cell rates, and the cell membrane and the chloroplast were identified as the major ROS production sites. Therefore, we concluded that PCD might be an important toxic mechanism of PBDEs on microalgal cells, and that chloroplast- and cell membrane-produced ROS was an important signaling molecule to mediate the PCD activation process. Our research firstly indicated microalgal PCD could be induced by PBDEs, and increased our knowledge of the toxic mechanisms by which POPs affect microalgal cells.

Large amounts of wastewater discharge have emerged as a burden in the process of industrialization and urbanization. In this study, a dynamic wastewater-induced input-output model is developed to systematically analyze the related situation. The developed model is applied to Guangdong Province, China to analyze its prominent characteristics from 2002 to 2015. Combining input-output analysis, ecological network analysis and structural decomposition analysis, the developed model reveals issues of direct and indirect discharges, relationships among various discharges, and driving forces of wastewater discharges. It is uncovered that Primary Manufacturing and Advanced Manufacturing dominate the system because of significant temporal and spatial variations in wastewater discharge. In addition, Manufacturing of paper, computer and machinery and Services are the key industries responsible for large amounts of wastewater discharge and unhealthy source-discharge relationships. The largest wastewater discharge occurred in 2005 and indirect wastewater discharge is the main form. Furthermore, final demand is found to be the biggest driving force of wastewater discharge. Finally, a three-phase policy implementation system implemented in stages proposes solutions to wastewater problems.

The desorption rate is an important factor determining cadmium (Cd) ecotoxicity and pollution remediation in soils. The pedotransfer functions (PTFs) of desorption rate coefficients of fresh Cd in soils have been developed in literature. We hypothesized that the aging of Cd pollution would alter Cd desorption process. Taking historically polluted soils as the object, this study aimed at testing the hypothesis and developing new PTFs of desorption rate coefficients for historical Cd. 15 d batch extraction experiments and 13 kinetic models were employed to define Cd desorption rate coefficients in 27 historically polluted soil samples. Compared with fresh Cd, the desorption rate coefficients of historical Cd were lower, and the break time of biphasic desorption processes was retarded to 3 d (4320 min). Different with the usual models for fresh Cd desorption (e.g. parabolic diffusion and two constant rate models), the best models to mimic the historical Cd desorption processes were the pseudo first order, logarithmic, Elovich, and simple Elovich models. The rate-limiting step controlling Cd desorption was changed from the intraparticle diffusion to the interface reaction with aging of pollution. New PTFs of desorption rate coefficients of historical Cd were established (R² ≥ 0.71). Cd desorption rate coefficients increased with organic matter and clay contents, but decreased with oxalate extractable Fe content, solution pH, cation exchange capacity, and silt content. The key soil properties influencing desorption rate coefficients were not altered by the aging of pollution. The developed PTFs could guide us to adjusting the ecotoxicity and pollution remediation of Cd in historically polluted field soils.

Multiple types of persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs), polychlorinated naphthalenes (PCNs), and hexachlorobenzene (HCB), can be unintentionally released from combustion or thermal industrial processes, which are speculated to be the main sources of these contaminants, as they were banned on production and use since several decades ago. In this study, concentrations and sources of 40 PCBs, 39 PCNs, and HCB were analyzed in air samples collected during the period 2012–2015 at a background site in east China. ΣPCBs, ΣPCNs, and HCB were in the range of 9–341 pg/m³, 6–143 pg/m³, and 14–522 pg/m³, respectively. Seasonal characteristics with high levels in winter and low levels in summer were observed for PCNs and HCB. PCBs also exhibited slightly higher levels in winter. Source apportionment was conducted, using polycyclic aromatic hydrocarbons (PAHs) as combustion sources indicator, combined with principal component analysis (PCA) and positive matrix factorization (PMF) model. The results indicated that the legacy of past produced and used commercial PCBs was the dominant contributor (∼56%) to the selected PCBs in the atmosphere in east China. PCNs were mainly emitted from combustion sources (∼64%), whereas HCB almost entirely originated from combustion process (>90%).