Oil spills occurring either in oceans or inland waterways may cause serious economic losses and ecological damage. Previous studies pertaining to oil spills and their consequences are primarily based on marine environments, whereas few have focused on oil spills occurring in inland waterways characterised by pronounced flow advection transport effects, which differ from the marine environment. A generalised flume experiment is performed to investigate the spread and transport of oil spills, and the relationships between the area and thickness of oil slick over time are analysed parametrically. An oil spill model combined with a depth–integrated two–dimensional non–uniform flow model, which is suitable for modelling inland waterways based on the Lagrangian method, is established; it is calibrated and verified using measured data from the flume experiment. The model is applied to three scenarios on the Luoqi reach of the Yangtze River, and spilled oil drifting trajectory maps are obtained and analysed considering the field wind parameters. The results show that the drift distance of the oil slick in the inland waterway is primarily controlled by the flow velocity with effects of advection transport; however, the oil spill trajectory spreads toward the wind direction when the flow velocity is relatively small compared with the wind speed. The results of this study serve as a reference for predicting the spread and transport of oil spills in inland waterways.

Gaining insight into the response of surface ozone (O₃) formation to its precursors plays an important role in the policy-making of O₃ pollution control. However, the real atmosphere is an open and dissipative system, and its complexity poses a great challenge to the study of nonlinear relations between O₃ and its precursors. At present, model-based methods based on reductionism try to restore the real atmospheric photochemical system, by coupling meteorological model and chemical transport model in temporal and spatial resolution completely. Nevertheless, large inconsistencies between predictions and true values still exist, due to the great uncertainty originated from emission inventory, photochemical reaction mechanism and meteorological factors. Recently, based on field observations, some nonlinear methods have successfully revealed the complex emergent properties (long-term persistence, multi-fractal, etc) in coupling correlation between O₃ and its precursors at different time scales. The emergent properties are closely associated with the intrinsic dynamics of atmospheric photochemical system. Taking them into account when building O₃ prediction model, is helpful to reduce the uncertainty in the results. Nonlinear methods (fractal, chaos, etc) based on holism can give new insights into the nonlinear relations between O₃ and its precursors. Changes of thinking models in methodology are expected to improve the precision of forecasting O₃ concentration. This paper has reviewed the advances of different methods for studying the sensitivity of O₃ formation to its precursors during the past few decades. This review highlights that it is necessary to incorporate the emergent properties obtained by nonlinear methods into the modern models, for assessing O₃ formation under combined air pollution environment more accurately. Moreover, the scaling property of coupling correlation detected in the real observations of O₃ and its precursors could be used to test and improve the simulation performance of modern models.

Research on the environmental fate and behavior of novel brominated flame retardants (NBFRs) remains limited, especially in the remote alpine regions. In this study, the concentrations and distributions of NBFRs were investigated in soils and mosses collected from two slopes of Shergyla in the southeast of the Tibetan Plateau (TP), to unravel the environmental behaviors of NBFRs in this background area. The total NBFR concentrations (∑₇NBFRs) ranged from 34.2 to 879 pg/g dw in soil and from 72.8 to 2505 pg/g dw in moss. ∑₇NBFRs in soil samples collected in 2019 were significantly higher than those in 2012 (p < 0.05). Decabromodiphenyl ethane (DBDPE) was the predominant NBFR, accounting for 90% of ∑₇NBFRs on average. The ratio of the concentrations in moss and soil showed significantly positive correlations with LogKOA except for DBDPE (p < 0.05), indicating that the role of mosses as accumulators compared to soils are more pronounced for more volatile NBFRs. In addition, the concentrations of NBFRs generally decreased with increasing altitude on the south-facing slope, whereas on the north-facing slope some NBFRs exhibited different trends, suggesting concurrent local and long-range transport sources. Normalization based on total organic carbon/lipid concentrations strengthened the correlation with altitude, implying that the altitude gradient of the mountain slope and forest cover could jointly affect the distribution of NBFRs in the TP. Furthermore, principal components analysis (PCA) with multiple linear regression analysis (MLRA) showed that the average contribution of the mountain cold trapping effect (MCTE) accounted for the major (77%) contribution and forest filter effect (FFE) has only a modest contribution to the deposition of NBFRs in soil.

Recent studies suggested that long-term exposure to fine particulate matter (PM₂.₅) was related to a higher risk of dementia incidence or hospitalizations in western populations, but the evidence is limited in Asian cities. Here we explored the link between long-term PM₂.₅ exposure and dementia incidence in the Hong Kong population and whether it varied by population sub-group. We utilized a Hong Kong Chinese cohort of 66,820 people aged ≥65 years who were voluntarily enrolled during 1998–2001 and were followed up to 2011. Prevalent dementia cases were excluded based on the face-to-face interview at baseline. We ascertained the first occurrence of hospitalization for all-cause dementia and major subtypes during the follow-up period. We assessed PM₂.₅ concentrations using a satellite data-based model with a 1 × 1 km² resolution on the residential address. Cox proportional hazards models were adopted to estimate associations of annual mean PM₂.₅ exposure with dementia incidence, adjusting for potential confounders. We identified 1183 incident cases of all-cause dementia during the follow-up period, of which 655 (55.4%) were cases of Alzheimer’s disease, and 334 (28.2%) were those of vascular dementia. We found a positive association between annual mean PM₂.₅ exposure and all-cause dementia incidence in the fully adjusted model. The estimated hazard ratio was 1.06 (95% confidence interval (CI): 1.00, 1.13) per every 3.8 μg/m³ increase in annual mean PM₂.₅ exposure. And the estimated HRs for Alzheimer’s disease and vascular dementia were 1.03 (95% CI: 0.94, 1.12) and 1.09 (95% CI: 0.98, 1.22), respectively. We did not find effect modifications by age, sex, BMI, hypertension, diabetes, or heart disease on the associations. Results suggest that long-term exposure to PM₂.₅ is associated with a higher risk of dementia incidence in the Asian population.

Land use regression model (LUR) is a widespread method for predicting air pollution exposure. Few studies have explored the performance of independently developed daytime/nighttime LUR models. In this study, fine particulate matter (PM₂.₅), inhalable particulate matter (PM₁₀), and nitrogen dioxide (NO₂) concentrations were measured by mobile monitoring during non-heating and heating seasons in Taiyuan. Pollutant concentrations were higher in the nighttime than the daytime, and higher in the heating season than the non-heating season. Daytime/nighttime and full-day LUR models were developed and validated for each pollutant to examine variations in model performance. Adjusted coefficients of determination (adjusted R²) for the LUR models ranged from 0.53–0.87 (PM₂.₅), 0.53–0.85 (PM₁₀), and 0.33–0.67 (NO₂). The performance of the daytime/nighttime LUR models for PM₂.₅ and PM₁₀ was better than that of the full-day models according to the results of model adjusted R² and validation R². Consistent results were confirmed in the non-heating and heating seasons. Effectiveness of developing independent daytime/nighttime models for NO₂ to improve performance was limited. Surfaces based on the daytime/nighttime models revealed variations in concentrations and spatial distribution. In conclusion, the independent development of daytime/nighttime LUR models for PM₂.₅/PM₁₀ has the potential to replace full-day models for better model performance. The modeling strategy is consistent with the residential activity patterns and contributes to achieving reliable exposure predictions for PM₂.₅ and PM₁₀. Nighttime could be a critical exposure period, due to high pollutant concentrations.

Nitrogen (N) pollution and the resulting eutrophication can have deleterious consequences on estuaries, such as hypoxia, fish kills, and loss of biotic diversity. An understanding of N sources and cycling in estuaries is fundamental to determining how to effectively manage these ecologically and commercially important areas. We applied a multiple-isotopic approach to examine the transformations and sources of the N pools in the Pearl River Estuary (PRE) during winter. The surface water in the West PRE was characterized by low salinity and high NO₃⁻, while that in the east had high salinity and low NO₃⁻. The NO₃⁻ in the West PRE was largely regulated by a conservative mixing process. In contrast, assimilation and nitrification dominated in the East PRE, which was attributed to the long water-residence time. For the first time, the source contributions of NO₃⁻ and NH₄⁺ were estimated by isotope mixing models. Our results suggest that river discharge and nitrification contributed 81% and 12% to the NO₃⁻ pool, respectively. A major portion (68%) of the NH₄⁺ was from river discharge, with the remainder likely from sewage and the aquitard-aquifer system. Our study demonstrates that internal nitrification can potentially be of pivotal importance in determining the NO₃⁻ level in an estuary and its export to coastal waters.

Enormous wastewater discharges have significantly impeded the sustainable development. As several economic belt has been formed in China, systematic analysis of multi-regional wastewater metabolic system is required for advancing wastewater mitigation effectively and efficiently. In this study, a distributive environmental input-output model (DEIO) is developed for the Yangtze River Economic Belt (YREB) to provide bases for supporting sustainable development from inter-regional and inter-sectoral perspectives. The discharges and flows of wastewater and related pollutants (i.e., chemical oxygen demand (COD) and ammonia nitrogen (AN)) among sectors and regions are analyzed to providing solid bases for wastewater management within the YREB. The results show that the industrial wastewater mitigation in YREB is desired urgently. The industrial wastewater discharges in Jiangsu and Zhejiang provinces are numerous, while Hunan and Yunnan provinces are more inclined to suffer from serious COD and AN pollution. In addition, the manufacture of food, tobacco, chemical materials, and pharmaceutical are the typical sectors with a large amount of direct wastewater discharge, and the tertiary industry is ranked at the first in indirect wastewater discharge. According to the analysis, the implementation of the “Supply-side Structure Reform” and the “Replace Subsidies with Rewards” policy can benefit the wastewater mitigation in the YREB.

Supplemental activated biochar pellet fertilizers (ABPFs) were evaluated as a method to sequester carbon and reduce greenhouse gas (GHG) emissions, and improve rice production. The evaluated treatments were a control (standard cultivation method, no additives applied), activated rice hull biochar pellets with 40% of N (ARHBP-40%), and activated palm biochar pellets with 40% of N (APBP-40%). The N supplied by the ARHBP-40% and APBP-40% treatments reduced the need for supplemental inorganic nitrogen (N) fertilizer by 60 percent. The ARHBP-40% treatment sequestered as much as 1.23 tonne ha⁻¹ compared to 0.89 tonne ha⁻¹ in the control during the rice-growing season. In terms of greenhouse gas (GHG) emissions, CH₄ emissions were not significantly different (p > 0.05) between the control and the ARHBP-40%, while the lowest N₂O emissions (0.002 kg ha⁻¹) were observed in the ARHBP-40% during the crop season. Additionally, GHG (CO₂-equiv.) emissions from the ARHBP-40% application were reduced by 10 kg ha⁻¹ compared to the control. Plant height in the control was relatively high compared to others, but grain yield was not significantly different among the treatments. The application of the ARHBP-40% can mitigate greenhouse gas emissions and enhance carbon sequestration in crop fields, and ABPFs can increase N use efficiency and contribute to sustainable agriculture.

Rising of temperature in conjunction with acidification due to the anthropogenic climates has tremendously affected all aquatic life. Small changes in the surrounding environment could lead to physiological constraint in the individual. Therefore, this study was designed to investigate the effects of warm water temperature (32 °C) and low pH (pH 6) on physiological responses and growth of hybrid grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) juveniles for 25 days. Growth performance was significantly affected under warm water temperature and low-pH conditions. Surprisingly, the positive effect on growth was observed under the interactive effects of warm water and low pH exposure. Hybrid grouper exposed to the interactive stressor of warm temperature and low pH exhibited higher living cost, where HSI content was greatly depleted to about 2.3-folds than in normal circumstances. Overall, challenge to warm temperature and low pH induced protein mobilization as an energy source followed by glycogen and lipid to support basal metabolic needs.

The presence of phenols, such as nonylphenol (NP), bisphenol (BPA), and octylphenol (OP), in the environment have been receiving increased attention due to their potential risks to human health and environment. The use of reclaimed water for irrigation may be one of the sources of these phenols in the agricultural system. A field experiment was conducted to assess the effects of reclaimed water irrigation on phenol contamination of agricultural topsoil and products in the North China Plain between 2015 and 2016. Three irrigation treatments were applied to all crops: reclaimed water irrigation, groundwater irrigation and alternative irrigation with reclaimed water and groundwater (1:1, v/v). The results showed that the concentrations of NP, BPA, and OP in the topsoil were 0.02–0.54, 0.004–0.06, and ND–9.9 × 10⁻³ mg/kg, respectively; the corresponding values in agricultural products were 0.007–0.70, 0.004–0.24, and ND–1.08 mg/kg, respectively. The concentration of NP in the topsoil and agricultural products and that of BPA in the agricultural products were all less than the recommended limits. The yields of wheat, maize, vegetables were 4.35–7.08, 1.03–6.46, and 10.9–67.0 t/ha, respectively. The bioaccumulation factors (BCFs) of OP, NP, and BPA for cereals were 0.7–4.77, 0.16–4.59, and 1.3–23.9, respectively; the corresponding values in vegetables were 0.0–4.53 (except cucumber and eggplant), 0.38–12.6, and 0.57–24.3, respectively. No significant differences in phenol concentrations, BCFs, or yields of wheat and vegetables were observed among the three irrigation treatments. In conclusion, compared with groundwater irrigation, reclaimed water irrigation in this experiment did not significantly affect phenol concentrations in the topsoil and agricultural products as well as BCFs and yields of wheat and vegetables. However, because the quality of reclaimed water may vary across collected areas, additional experiments are warranted to analyze the effects of reclaimed water irrigation on the risk of phenol contamination.