Chronic toxicity of copper (Cu) at sublethal levels is associated with ionoregulatory disturbance and oxidative stress. These factors were considered in a toxicokinetic-toxicodynamic model in the present study. The ionoregulatory disturbance was evaluated by the activity of the Na⁺/K⁺-ATPase enzyme (NKA), while oxidative stress was presented by lipid peroxidation (LPO) and glutathione-S-transferase (GST) activity. NKA activity was related to the binding of Cu²⁺ and Na ⁺ to NKA. LPO and GST activity were linked with the simulated concentration of unbound Cu. The model was calibrated using previously reported data and empirical data generated when zebra mussels were exposed to Cu. The model clearly demonstrated that Cu might inhibit NKA activity by reducing the number of functional pump sites and the limited Cu-bound NKA turnover rate. An ordinary differential equation was used to describe the relationship between the simulated concentration of unbound Cu and LPO/GST activity. Although this method could not explain the fluctuations in these biomarkers during the experiment, the measurements were within the confidence interval of estimations. Model simulation consistently shows non-significant differences in LPO and GST activity at two exposure levels, similar to the empirical observation.

The Sichuan Basin (SCB) in southwestern China is largely affected by air pollution. Understanding the responses of air pollutant concentrations to emission changes is critical for designing and evaluating effective control strategies. Thus, this study used the Community Multi-scale Air Quality (CMAQ) model to simulate PM₂.₅ (i.e., particulate matter with an aerodynamic diameter ≤ 2.5 μm) in winter (January 2015) and ozone (O₃) in summer (July 2015) under nine emission reduction scenarios. For each scenario, the anthropogenic emissions of each air pollutant in each SCB grid cell were reduced by the same percentage, ranging from 10% to 90%. We found that approximately 30–70% emission reductions are required to reduce the January mean PM₂.₅ concentrations in all the SCB urban centers to a value that is less than the Chinese standard for daily mean PM₂.₅ (24-h PM₂.₅: 75 μg m⁻³). However, the January mean PM₂.₅ concentrations under 90% emission reduction still exceeded the World Health Organization (WHO) guideline (25 μg m⁻³) in 16 SCB urban centers. Moreover, reducing both SCB and non-SCB emissions were critical for achieving the PM₂.₅ level recommended by WHO. An 80% emission reduction was required to prevent the occurrence of 8-h O₃ (i.e., daily maximum 8-h mean O₃) non-attainment days in all SCB urban centers. Under 90% emission reduction, July mean 8-h O₃ concentrations still exceeded the WHO guideline of 47 ppb in approximately 35% of the SCB areas. In conclusion, this study suggests that (1) compared with the governmental emission reduction targets for 2015–2020 (2–27%), more significant emission reductions are required to meet the Chinese and WHO pollution standards; and (2) both SCB and non-SCB emissions must significantly reduce to achieve the desired pollution targets.

With the implementation of clean air strategies, PM₂.₅ pollution abatement has been observed in the “2 + 26” cities in the Beijing-Tianjin-Hebei (BTH) region (referred to as the BTH2+26) and their surrounding areas. To identify the drivers for PM₂.₅ concentration decreases in the BTH2+26 cites from the 2016/17 heating season (HS1617) to the 2017/18 heating season (HS1718), we investigated the contributions of meteorological conditions and emission-reduction measures by Community Multi-Scale Air Quality (CMAQ) model simulations. The source apportionments of five sector sources (i.e., agriculture, industry, power plants, traffic and residential), and regional sources (i.e., local, within-BTH: other cities within the BTH2+26 cities, outside-BTH, and boundary conditions (BCON)) to the PM₂.₅ decreases in the BTH2+26 cities were estimated with the Integrated Source Apportionment Method (ISAM). Mean PM₂.₅ concentrations in the BTH2+26 cities substantially decreased from 77.4 to 152.5 μg m⁻³ in HS1617 to 52.9–101.9 μg m⁻³ in HS1718, with the numbers of heavy haze (daily PM₂.₅ ≥150 μg m⁻³) days decreasing from 17-77 to 5–30 days. The model simulation results indicated that the PM₂.₅ concentration decreases in most of the BTH2+26 cities were attributed to emission reductions (0.4–55.0 μg m⁻³, 2.3–81.6% of total), but the favorable meteorological conditions also played important roles (1.9–25.4 μg m⁻³, 18.4–97.7%). Residential sources dominated the PM₂.₅ reductions, leading to decreases in average PM₂.₅ concentrations by more than 30 μg m⁻³ in severely polluted cities (i.e., Shijiazhuang, Baoding, Xingtai, and Beijing). Regional source analyses showed that both local and within-BTH sources were significant contributors to PM₂.₅ concentrations for most cities. Emission controls in local and within-BTH sources in HS1718 decreased the average PM₂.₅ concentrations by 0.1–47.2 μg m⁻³ and 0.3–22.1 μg m⁻³, respectively, relative to those in HS1617. Here we demonstrate that a combination of favorable meteorological conditions and anthropogenic emission reductions contributed to the improvement of air quality from HS1617 to HS1718 in the BTH2+26 cities.

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.

A two-dimensional hydrodynamic model that couples hydrology and water quality processes was developed to simulate the concentrations of PAH in water phase and sedimentation rates of PAHs in marine environment. The kinetic processes of the model included atmospheric exchange, transportation, deposition, etc. Taking Liaodong Bay as an example, the pollution level, spatial distribution of PAHs in sediments were analyzed and the transport, transformation and sedimentation processes of PAHs were simulated. The results show that PAHs concentrations in sediments are at a “moderate risk” level, and the distribution has a conspicuous spatial variation. According to the results of simulation, the PAHs in sediments are easily accumulated with weak hydrodynamic conditions. Thus, hydrodynamic is one of the important factors affecting the spatial distribution characteristics of PAHs in the sediments. The PAHs numerical calculation model established in this paper and its evaluation results have important research value for PAHs pollution prevention and control.

The high levels of parabens (including methyl-, ethyl- and propyl congeners), triclocarban (TCC) and triclosan (TCS) used every year in China might be a problem to the typical wastewater treatment plant (WWTP). This study addresses measurements of parabens, TCC and TCS Northern China WWTP and a modelling assessment on the occurrence, fate and removal pathways in WWTP. Per-capita emissions of the three parabens, TCC and TCS to the WWTP were estimated as 0.41, 0.11 and 0.07 mg/d. After the wastewater treatment processes, 94, 92 and 87% of parabens, TCC and TCS were removed. The major removal pathway of parabens was biodegradation while that of TCC and TCS were sorption to sludge. Computer simulations on the fate processes of parabens, TCC and TCS in the WWTP using the SimpleTreat 4.0 model suggested the model could generally reproduce the measurements with root mean squared errors (RMSEs) of less than 10 ng/L. However, the model underestimated the removal of TCC and TCS from water to sludge in the primary tank. These discrepancies were attributed to the uncertainty of the predicted organic carbon-water partition coefficients (Kₒc) to which the modelling results are highly sensitive. The model predictions using updated Kₒc became more accurate and RMSEs of TCC and TCS were reduced by 40 and 80%, respectively. The modelling assessment suggests that the SimpleTreat, as a generic model to simulate chemical fate processes in WWTPs, has the potential to be applied to other similar WWTPs in China for estimating environmental releases of parabens, TCC and TCS at a larger spatial scale.

The double glass cover analysis of a solar box cooker has been implemented in an internal heat transfer using MoS₂–Fe₂O₃–Cr₂O₃ nanomaterials. A nanocomposite material’s essential role is its higher surface/volume ratio which agrees in small area size of a high ductility without strength loss and an enhanced optical property. The nanocomposite materials have an average particle size of 0.2 - 0.5 μm. Compared to the overall thermal energy efficiency of the solar cookers used, the samples with and without this study’s modification are 56.21–31.77% and 33.90–24.90%. The design used nanomaterials’ performance with and without coating materials achieved by the bar plate temperature of about 163.74 °C and 113.34 °C below solar radiation of 1037W/m². The simulation model is conducted on the fuzzy intelligent logic and Cramer’s rules. It agreed with the experimental results by 91%.

Spatial planning is crucial for sponge city (SC) construction; however, prioritizing SC sites at the watershed scale has not been fully explored. In this study, a multi-criteria decision model, considering demand and suitability of SC construction, was established by monitoring, model simulation, and index calculation. This new model was then tested in a rapidly urbanizing watershed, Beijing, China, and the priority of SC construction at both grid scale (1km×1km) and subwatershed scale was ranked. The results showed that the highest priority was found in emerging regions where urbanization is ongoing and followed by urban core areas. In addition, six indexes were identified by clustering heatmaps as key factors affecting the priority of SC planning, including topographic index, water pollution index, pollution rate based on the state standard of surface water environment quality, urbanization planning, urban levels, and vegetation index, which could guide SC planning in data-lacking regions. The approach and findings in this study cannot only provide helpful references for watershed managers and urban planners but also can be easily used in other regions.

Developing countries are enthusiastically on the road to economic progress and economic openness, which is proved to be a silver bullet for them. However, it has put their environmental quality at stake. This study examines whether economic openness and electricity consumption matter for environmental deterioration by controlling for the influence of economic progress. For this, we have used time series frequency data of Pakistan from 1971 to 2016 and employed the state-of-the-art dynamic autoregressive distributed lag (ARDL) simulation model. The model has the advantage over traditional ARDL in determining the positive and negative environmental deterioration variations induced by economic openness, electricity consumption, and economic progress. The main findings are as follows: Firstly, electricity consumption in both long and short run positively and significantly influenced CO₂ emissions, while long-run influence exceeded that of short run. Secondly, economic progress validated an environmental Kuznets curve hypothesis and thus limited the environmental degradation. Thirdly, economic openness showed an insignificant influence on CO₂ emissions both in the long and short run. Based on research findings, it is suggested that economic progress and economic openness are not the direct culprits to deteriorate a developing country’s environmental condition like Pakistan; rather, electricity consumption remained the key role player. Therefore, the transition from fossil-based electricity consumption to renewable energy consumption would provide a sustainable pathway towards achieving sustainable economic openness in the future.

Seawater intrusion not only causes fresh water shortages in coastal areas, but also has a negative impact on regional economic and social development. Global climate change will affect precipitation, sea level, and many other factors, which will in turn affect the simulation and prediction results for seawater intrusion. By combining groundwater numerical simulation technology, an atmospheric circulation model, artificial intelligence methods, and simulation optimization methods, this study coupled a numerical simulation model of seawater intrusion with an optimization model to optimize the groundwater exploitation scheme in the study area under the condition of climate change. As a result, a groundwater exploitation scheme was obtained for a typical study area, which provided a scientific basis and a reference for the rational development of effective groundwater resource solutions. The results of this study can be described as follows. (1) By introducing the theory and method of deep learning from artificial intelligence, the problem of complex nonlinear mapping between the inputs and outputs of a three-dimensional variable-density seawater intrusion numerical simulation model under the condition of limited number of training samples is effectively solved, and the approximation accuracy of the surrogate model with respect to the simulation model is improved. (2) By solving the optimization model, a reasonable groundwater exploitation scheme was obtained, which provided a scientific basis for the rational development and efficient use of groundwater resources in the study area.