To explore the influence of trace elements and change in environmental conditions at low temperature on the nitrification performance of biofilm reactor, a simulated wastewater containing NH₄⁺-N was treated. The effects of trace elements, low temperature, aeration rate and flow rate on nitrification performance of the biofilm reactor were studied. The microbial community structure was analyzed by 16S rRNA high-throughput sequencing technique. The results showed that trace elements significantly affected the nitrification performance (P<0.0001). After adding trace elements to the influent, the removal load of NH₄⁺-N increased from 0.93kg/(m³·d) to 1.63kg/(m³·d) and the generation load of NO₃^--N increased from 0.23kg/(m³·d) to 1.21kg/(m³·d). Low temperature can affect nitrifying bacteria. Nitrite oxidizing bacteria (NOB) are sensitive to low temperature shock, while ammonia oxidizing bacteria (AOB) are resistant to it. The decrease in aeration rate led to a lack of dissolved oxygen (DO) in the reactor, which further affected the nitrification performance. The change in flow rate had no significant effect on the nitrification performance. Analysis of the microbial community structure at low temperatures showed that the nitrobacteria of Nitrosomonas and Nitrospira were enriched during operation, which ensured that the reactor can still have stable nitrification performance. The research provides experimental evidence and theoretical guidance for improving the nitrification performance and enhancing the low-temperature resistance of biofilm reactor in wastewater nitrification treatment practice.

Sulfate radical (SO₄^•−)-based advanced oxidation processes (SR-AOPs) are characterized by in situ generation of SO₄^•− with strong oxidation capacity, which can effectively degrade a variety of organic pollutants. However, SO₄^•− can transform nitrite (NO₂⁻) and bromide (Br⁻) into toxic nitrated byproducts and halogenated byproducts, respectively. In this study, the mechanisms underlying the formation of nitrated and brominated byproducts on the reaction system in which NO₂⁻ and Br⁻ coexist were systematically investigated. Results showed that three nitrated byproducts, including 2-nitrophenol, 4-nitrophenol, and 2,4-dinitrophenol were produced during the heat-activated persulfate nitrification process. It was observed that nitrophenols accounted for approximately 34.5% of the phenol transformed under reaction conditions of [phenol]= 50µmol/L, [NO₂⁻]=100µmol/L,[PDS]=2mmol/L and temperature of 60℃ C. Once NO₂⁻ was co-present, the formation rate of nitrophenol was significantly accelerated. The conversion rate increased to 46.0% under the same conditions. Br⁻ can be oxidized by SO₄^•− to form reactive bromine species, which rapidly react with NO₂⁻ to form a strong oxidizing agent, nitryl halide. Then nitryl halide reacts with the phenol and plays a key role in promoting the formation of nitrophenol. Note that, Br⁻ is eventually released and acts as a catalyst equivalent. Meanwhile, the presence of NO₂⁻ results in an inhibition of the rate of formation of brominated byproducts, such as dibromoacetic acid. Therefore, the transformation mechanisms of NO₂⁻ and Br⁻ influence each other in SR-AOPs. When they coexist, promote the formation of nitrophenol byproducts but inhibit brominated byproducts.

Based on water quality indicators, climate indicators, and wetland operation parameters, data from previous studies were collected to predict the effluent concentrations of ammonia nitrogen (NH₄⁺-N), COD, sulfamethoxazole (SMX), and some heavy metals in constructed wetlands using three machine learning models. The results showed that the Random Forest model slightly outperformed XGBoost and LightGBM in overall performance, demonstrating more stable R² and RMSE values. In particular, it achieved higher accuracy in predicting NH₄⁺-N and SMX concentrations, with R² values of 0.93, 0.89, and 0.87, respectively, for NH₄⁺-N. In contrast, the models performed relatively weaker in COD predictions, with R² values of 0.71, 0.61, and 0.64, respectively. By incorporating the SMOTE data augmentation technique, the prediction performance and accuracy of the models were significantly enhanced, especially for COD, where improvements ranged from 7.04% to 26.23%. This study combines scientific data analysis with machine learning algorithms, providing a feasible approach for practical engineering applications.

To investigate the relative importance of the bottom-up versus top-down on phytoplankton biomass in the estuary and its adjacent waters of the Yellow River during the water and sediment regulation scheme (WSRS), the study utilized R2V software to extract historical data (2011~2020) on chlorophyll a (Chl a) concentration, environmental factors, and zooplankton abundance in the estuary and its adjacent waters of the Yellow River from the literature. The spatial distribution and interannual variation of Chl a concentration was analyzed, and regression tree models Chl a with environmental and biological factors at different stages of WSRS were developed to explore the controlling factors. The results showed that Chl a concentrations in the estuary and its adjacent waters of the Yellow River generally decreased from the estuary towards offshore areas from 2011 to 2020. As WSRS progressed, the high-value areas gradually shifted to the nearshore northwest of the estuary. Regions with significant interannual variations in Chl a concentrations largely overlapped with high-value areas at each stage. The regression tree model indicated that, with the progression of water and sediment regulation, there was a notable shift in the dominant effects on Chl a concentration. Before WSRS, the top-down effect of zooplankton grazing was the primary driver of Chl a spatial variability. During the water and sediment regulation period, Chl a concentration was mainly controlled by bottom-up effects. In the early WSRS, temperature was the primary driving factor, while in the later stage of WSRS, dissolved inorganic phosphorus (DIP) became the main driving factor. The changes in salinity fronts caused by freshwater flow during WSRS may be an important factor inducing changes in the dominant effects on Chl a concentration.

Packed column experiments and numerical simulations were conducted to investigate the co-transport behavior of nanoscale iron supported on biochar (nFe/BC) pyrolyzed at 500℃ and 800℃, respectively, with arsenic (As) in contaminated soil. The results showed that the mobility of nFe/BC (nFe/BC500 and nFe/BC800) in As-contaminated soil was obviously lower than that of pristine biochars (BC500 and BC800), decreasing by about 57.8% and 45.5% in As-contaminated soil, respectively. This is likely because zeta potentials of nFe/BC became less negative due to the adherence of positively charged Fe onto the BC. Therefore, electrostatic repulsion between nFe/BC and soil grain was weakened, resulting in a lower mobility of nFe/BC. Also the mobility of nFe/BC was reduced with an increase in pyrolysis temperature. This is likely because that the surface charge of nFe/BC produced at high temperature was less negative, due to the lower density of O-containing functional groups. Therefore, the total repulsive interaction energies between nFe/BC and soil grain were reduced. A two-site kinetic retention model was successfully employed to simulate the transport of nFe/BC in soils, further illustrating the co-transport characteristics of nFe/BC. Additionally, pristine BCs facilitated the transport of As due to the competition between BCs and As for the available sorption sites on the soil surface. However, nFe/BC first inhibited the transport of As, and then promoted it. The main reason could be because the iron substance or Fe₃O₄ on the surface of nFe/BC reacted with As, and then fixed it in soil. Once the reaction between nFe/BC and As was completed, nFe/BC lost its original inhibitory effect, and instead acted as a carrier to promote As transport in soil. This could cause potential risks of As to the groundwater environment.

This study involved the collection and analysis of bacteria and fungi samples in water and sediment from ten typical sub-lakes of Poyang Lake. A hydrological connectivity index system for sub-lakes was established to quantitatively assess the effect of hydrological connectivity on microbial community structure. The results indicate significant differences in the α-diversity of water bacteria, sediment bacteria, and fungal communities during different stages of the dry season, sediment bacteria and fungi showed higher α-diversity during the mid-dry season. The difference in β diversity of water bacterial community was more obvious in different periods, and the β diversity of sediment bacterial and fungal communities showed spatial differences. With the increase of hydrological connectivity, the similarity of sediment bacterial and fungal communities was lower. The water area ratio (WSP) and water depth (WD) were the main hydrological connectivity variables affecting the water bacterial community structure. Lake basin elevation (LE) and WD were the main hydrological connectivity variables affecting sediment bacteria and fungi community structure. Hydrological connectivity explained less variation in water bacterial community structure (7.6%) compared to sediment bacteria (33.3%) and fungal (29.7%) community structures. The co-interpretation rate of hydrological connectivity and physicochemical factors on bacterial community structure in water was only 2.4%, and the co-interpretation rates of bacterial and fungal community structure in sediments were 9.7% and 6.2%, respectively. Sediment bacterial and fungal communities were predominantly shaped by stochastic and deterministic processes, respectively, while both processes jointly influenced water bacterial communities. Under moderate hydrological connectivity, water bacterial communities showed stronger stochastic processes, whereas as connectivity increased, stochastic processes in sediment bacteria and fungi weakened.

This study investigated the effects of raw water turbidity variation on the stable flux, pollutants removal, and bio-cake layer of gravity flow ultrafiltration (GDM) system. The results showed that the increase of raw water turbidity led to a significant decrease in the flux of GDM system, but a new stable flux can be achieved in 17~30 days. Compared to control GDM with low influent turbidity (1.8~3.7NTU), the increase of raw water turbidity to 10, 50 and 100 NTU reduced the stable flux of GDM system by 15%, 36% and 61%, respectively. The macromolecular organic matter carried by particles was degraded by microorganisms in the bio-cake layer to low molecular weight organic matter, which passed through the membrane and resulted in increase of dissolved organic matter in the effluent with the increase of raw water turbidity. The ammonia removal rate of GDM system reached more than 80% after 9days of start-up, and the temporary decrease in ammonia nitrogen removal capacity occurred due to the increase of raw water turbidity. However, it recovered after 7~11days of adaptation period. With the increase of raw water turbidity, the thickness of bio-cake layer increased by 1.8 to 7.9 times and the microbial extracellular polymeric substances increased by 37 to 98%. Meanwhile, the microbial community structure underwent certain changes. This study shows that GDM system has certain adaptability to increase of raw water turbidity.

In view of the typically unsatisfactory antibiotics removal performances that were observed in the traditional 'three ponds and two dams' combination process, a new composite packing filter dam was developed. Through the synergetic combination of composite packing balls with a specially designed filter dam structure, highly efficient and broad-spectrum removal of antibiotics was achieved. Results showed that the removal rates of antibiotics (in terms of total mass concentrations) in perch, eel, raw fish and shrimp culture pond water were maintained at more than 80% by the composite packing filter dam. Quinolones, sulphonamides, tetracyclines and chloramphenicol were removed to different extents, among which the best removal effects were observed for quinolones and sulphonamides. The composite filler consisting of iron filings, ceramsites and polybutylene succinate (PBS) was found to significantly improve the removal of quinolones and sulfonamides. Ceramsites were demonstrated to play an adsorption role through which quinolone and sulfonamide antibiotics were removed via pore filling and π-π electron donor-acceptor interactions, which was identified as the main antibiotic removal pathway. Iron filings were shown to remove tetracycline and chloramphenicol through adsorption and reduction processes, and were suggested to have accelerated the direct electron transfer process that promoted antibiotic degradation. PBS was involved in the removal of antibiotics through co-metabolic denitrification. Both iron filings and PBS were proven to enhance the metabolic activity of functional microorganisms, thereby accelerating antibiotic removal. The synergistic effect between these components was confirmed to help achieve efficient and broad-spectrum antibiotic removal.

The distribution characteristics of benzene, toluene, ethylbenzene and xylene (BTEX) concentrations in seawater and the atmosphere in the East China Sea in October 2020 were investigated, the sea-air exchange fluxes were evaluated, and the ecological risks and environmental effects were analyzed. The results showed the average concentrations of benzene, toluene, ethylbenzene, m/p-xylene and o-xylene were (136.8±76.8), (321.3±279.0), (530.3±530.0), (336.2±453.6) and (493.7±814.7) pmol/L in the surface seawater, respectively, and were (122.3±84.2), (217.1±162.4), (423.8±399.0), (236.8±215.1) and (344.3±288.5) pmol/L in the bottom seawater. The high values were found in the nearshore and the eastern part of the investigated sea area, of which the high values in the nearshore indicated they were influenced by land-based inputs, and the high values in the eastern part might be related to the petroleum extraction activities. The average atmospheric concentrations of benzene, toluene, ethylbenzene, m-/p-xylene and o-xylene were (110.5±45.3),(410.1±384.4), (139.5±108.8), (128.3±123.9) and (108.9±97.6) ×10^-12, and the backward trajectories showed they were affected by the input from land-based sources. The mean sea-air fluxes of benzene, toluene, ethylbenzene, m-/p-xylene and o-xylene were (25.6±13.1),(73.1±78.2), (179.9±194.5), (146.3±185.4), and (216.3±358.7) g/(km²⋅d), indicating that the investigated sea area is an important source of atmospheric. In terms of ecological risk, the concentrations of BTEX in seawater were far below the acute toxicity median effect concentration (EC50) and the half-lethal concentration (LC50) for marine organisms, indicating that BTEX posed relatively low direct harm to segmental marine life. In the atmosphere, the calculated carcinogenicity risk value (R), the non-carcinogenicity risk hazard quotient (HQ), and the non-carcinogenicity risk index (HI) were much lower than the reference values, indicating that the direct threat of atmospheric BTEX to human health was low. The analysis of O₃ and SOA generation potentials revealed that toluene and xylene were the key active components of BTEX and had the most significant impact on environmental effects.

This study takes the Wujing Road Tunnel in Tianjin as an example to explore the emission characteristics of benzothiazoles (BTs) in particulate, gaseous pollutants, and road dust. The results show that the concentrations of particulate matter, gaseous pollutants, and BTs in road dust exhibit regular patterns, especially the concentration changes of 2-hydroxybenzothiazole (2-OH-BT) and benzothiazole (BT). Since BTs in the enclosed tunnel environment mainly originate from tire wear particles of motor vehicles, 2-OH-BT and BT can serve as important tracers for identifying non-exhaust emissions from motor vehicles. During the tunnel experiment, the daily traffic volume ranged from 11,972 to 16, 157 vehicles per day, the total carbon (TC) concentration was between 10.85and 15.75μg/m³, and the BTs concentration was between 3.33 and 8.41ng/m³. The gas-particle ratio values of 2-mercaptobenzothiazole (MBT), 2-OH-BT, and BT in the tunnel were generally higher than those in the receptor environment, and 2-OH-BT and BT were the dominant gaseous BTs components. This indicates that most MBT, 2-OH-BT, and BT generated from tire wear sources of motor vehicles are released in the gaseous phase, so the gaseous BTs should not be overlooked. For the calculation of motor vehicle emission factors, the average emission factors of organic carbon (OC), elemental carbon (EC), and PM_2.5 in the Wujing Road Tunnel were 2.80, 1.60, and 13.77mg/(km⋅vehicle), respectively. In the health risk assessment model, the daily exposure to BTs through ingestion was the highest. The daily intake for children and adults was 12.03 and 1.29ng/(kg⋅d), respectively. The total daily exposure for children was more than nine times that of adults, indicating that children may face a greater health threat from traffic pollution than adults.