Based on field data from 2019 to 2022 in the South Tiaoxi River Watershed in the upper reaches of the Taihu Lake Basin, redundancy analysis (RDA) and non-parametric breakpoint analysis (nCPA) were employed to analyze the relationships between riverine nitrogen (N) concentrations and landscape pattern indices at different buffer scales, and identity the critical landscape threshold ranges affecting the river nitrate (NO₃^--N) concentration. The results showed that the total nitrogen (TN) concentration in the South Tiaoxi River exceeded the Class V surface water quality standard, with NO₃^--N as the predominant N pollutant. During the wet season, the concentrations of TN, dissolved total nitrogen (DTN), NO₃^--N, and dissolved organic nitrogen (DON) were significantly higher than those in the dry season, whereas ammonium nitrogen (NH₄⁺-N) concentrations were lower. N concentrations were lower in the upstream compared to downstream. The landscape pattern indices in the buffer zones of 400m and 200m explained the largest variance in river N concentrations during the wet and dry seasons, respectively (89.49% and 90.97%). Based on the identified key thresholds of landscape pattern indices for significantly reducing the risk of NO₃^--N pollution in the watershed, the following suggestions are provided: the proportion of farmland, construction land, and Shannon diversity index (SDHI)in the buffer zone of 400m should be controlled within 0.25%, 1.75%, and 0.77, respectively; and the proportion of farmland and edge density (ED) in the buffer zone of 200m should be kept within 0.5% and 39m/hm², simultaneously with the proportion of forest area exceeding 91.0%.

Lrovincial panel data from 2011 to 2021 were leveraged in this study to examine the effectiveness and underlying mechanisms of digitalization in promoting the coordinated development of mineral resources and ecological conservation from the perspective of regional development disparities. It was indicated by the findings that, overall, a moderate upward trajectory had been shown in the level of coordinated development of mineral resources and the environment in China. However, significant geographical heterogeneity persisted, with the southeastern coastal regions being outperformed by the central and western areas. This coordinated development was significantly promoted by digitalization, a conclusion that was remained robust even after addressing endogeneity and conducting sensitivity analyses. Furthermore, industrial structure upgrading and improvements in green innovation capabilities were identified as key mediating factors through which coordinated development was facilitated by digitalization. It was also revealed by this study that the impact of digitalization varied across different regions, with China’s southeastern regions being benefited more substantially. Based on this analysis, several recommendations were proposed, including investments in digital infrastructure and technologies being enhanced; the pivotal role of digitalization being reinforced; the green transformation of the industrial structure being advanced; and targeted regional development strategies being developed.

As a common pollutant in water, nitrate has nonnegligible harmful effects on human health and the ecological environment. Faced with an increasingly severe energy crisis, the development of green, clean and sustainable nitrate removal technologies to replace the conventional resource-intensive denitrification process is urgently needed. Photoelectrochemical nitrate reduction powered by sunlight has become a research hotspot at home and abroad. Based on the way photogenerated electrons being transferred from semiconductor to nitrate, this technology can be categorized into photocatalytic reduction, photoelectrocatalytic reduction, and microbial photoelectrotrophic reduction. In this review, the mechanisms of three photoelectrochemical nitrate reduction technologies were discussed. With a focus on improving system performance, the selection and design strategies of photocatalysts, photoelectrodes and microbial photosensitizers were also summarized. Moreover, the technical difficulties of photoelectrochemical nitrate reduction are clarified and the future directions of research are proposed, such as regulating the pathway of microbial absorption and utilization of photogenerated electrons through genetic engineering and other methods. The insights provided will serve as a reference for the development of new nitrate removal and reutilization technologies.

This paper reviewed the occurrence characteristics and abundance of microplastics (MPs) in disinfection processes of water treatment plants both inside and outside China, and analyzed the MPs removal effectiveness of chlorine, ozone and ultraviolet disinfection, followed by an in-depth discussion of the effects of MPs presence on disinfection and its secondary pollution. The results showed significant differences in the abundance of MPs across different water treatment plants, primarily existing in the forms of fibers and fragments, predominantly composed of polyethylene terephthalate (PET), polyethylene (PE), and polypropylene (PP), with most sizes less than 1.0mm and colors mostly black, white, or transparent. The removal rate of the chlorine disinfection unit ranged from 0% to 71.38%; but part of the water treatment plants had seen a rise in MPs abundance after the ozone and ultraviolet disinfection. The removal mechanisms of MPs by disinfection processes remained required further research. Additionally, the trihalomethane formation potential (THMFP) of microplastic-derived dissolved organic matter (MP-DOM) in the chlorine disinfection process could reach as high as 453.3µg/mg, higher than the formation potential of typical aquatic natural organic matter and algae organic matter, pointing to greater health risks.

In this study, the components of dissolved organic matter (DOM) during the anaerobic-anoxic-aerobic (A²O) biological wastewater treatment process was analyzed by using fluorescence emission excitation matrix combined with parallel factor analysis(3D EEMs-PARAFAC), and the generation of nitrous oxide (N₂O) in each unit was also quantified. Additionally, machine learning model was employed to further predict the response relationship between DOM components and N₂O generation. Results showed that DOM in the influent of the wastewater treatment plants (WWTP) was primarily composed of four components, including tryptophan (C1), fulvic acid (C2), humic acid (C3), and tyrosine (C4), while C1 and C4 being the dominant components. The concentration of DOM decreased progressively throughout the treatment process, while the removal efficiency of readily biodegradable DOM (such as C1and C4) were significantly higher than that of C2 and C3. N₂O emission was the major component of direct carbon emissions and showed significant spatial heterogeneity. The N₂O emission amount of each unit ranked from high to low were observed in the following order: oxic tank, secondary sedimentation tank, anoxic tank, anaerobic tank, grille, and primary sedimentation tank. Shapley Additive exPlanation (SHAP) analysis revealed that C1 and C2 would significantly affect the N₂O generation process, while the effects of C3 and C4 were negligible. Specifically, C1would enhance N₂O generation, while C2 had an adverse effect. High-throughput sequencing results indicated that Methylotenera and Terrimonas, which could utilize readily biodegradable organic matter for denitrification, were the dominant bacterial genera in the sludge of WWTP. Overall, this study revealed disparate response between N₂O generation and different DOM components during the A²O process, which would help to improve the current carbon emission accounting method of WWTPs and provide theoretical support for optimizing their low-carbon operation processes.

With the gradual depletion of shallow coal resources in mines and the continuous advancement of structural reforms on the supply side of national energy, the number of abandoned mines has increased, drawing growing attention to the environmental issues left behind in these areas. This study focuses on the abandoned mine in the Wansheng Economic Development Zone, Chongqing City. We collected five types of samples, including water (n=7), sediments (n=4), soil (n=8), coal gangue (n=2), and plants (n=10). The concentrations of the 16priority polycyclic aromatic hydrocarbons (PAHs) identified by the United States Environmental Protection Agency (USEPA) were analyzed using gas chromatography-mass spectrometry (GC-MS). Positive matrix factorization (PMF) and Monte Carlo simulation were employed to analyze the sources of PAH pollution and the carcinogenic risks in various environmental media within the abandoned mine. The results showed that the concentrations of PAHs in river, leachate, sediments, surface soil, coal gangue, and dominant plants were (45.6±12.4), (97.8±89.4)ng/L, (3640±2520), (6400±2650), (18600±1120), and (801±1110)ng/g, respectively. In the river, leachate, coal gangue, and dominant plants, the 2-3 ring PAHs are dominant, accounting for 83%,71%, 39%, and 54%, respectively. In the sediment and surface soil, the 5-6 ring PAHs have a relatively high proportion, accounting for 37% in both. The PMF source apportionment results indicated that diagenetic sources and petroleum source (49%) and traffic sources (32%) were the main contributors to PAHs in water. Traffic sources (48%) and coal combustion sources (35%) were the primary sources of PAHs in surface soil, while traffic sources (46%) and petroleum source and coal combustion sources (38%) were the major sources of PAHs in dominant plants. Monte Carlo simulations revealed potential carcinogenic risks to local residents from soil, coal gangue, and self-cultivated vegetables in the abandoned mine, with adults facing higher health risks than children. Over 96% of the carcinogenic risks were attributed to dermal contact.

A controlled experiment was conducted to investigate temperature-induced alterations in serum biochemical indices and gut microbiota of endemic fish (Procypris rabaudi) in Jinsha River, a cascade hydropower development river in southwest China. Three temperature treatments (16℃, 20℃, 24℃) were established with exposure durations of 24h and 10d. Results showed that compared to the ambient temperature group, the serum antioxidant enzyme activity was promoted in the low temperature group after 24h but inhibited after 10d. The decrease in lysozyme (LZM) activity in the low temperature group of 10d (67.12%) was more significant than that of 24h group (52.04%) relative to the ambient temperature group. And the concentrations of glucose (GLU) and CORTISOL were increased significantly in the low temperature groups both 24h and 10d compared with those in the ambient temperature groups. The Chao1index of the low temperature group at 24h were 23.22% and 26.36% lower than those of the ambient temperature and high temperature groups, respectively. The alpha diversity was found to stabilize in the low temperature group after 10d. Compared to 24h, the difference in gut microbiota community structure under different temperature conditions after 10d was smaller, and the low temperatures significantly affected the community composition of the gut microbiota. Co-occurrence network analysis revealed that microbial interactions were simplified and weakened in the low temperature group (24h), whereas prolonged thermal adaptation (10d) was associated with network stabilization. Significant correlations were established between Proteobacteria, Bacteroidetes, and Firmicutes with antioxidant enzymes and LZM activity.

This study aimed to investigate the mitigating effect and regulatory mechanism of humic acid (HA) on the physicochemical properties and pollutant treatment performance of aerobic granular sludge (AGS) under prolonged stress induced by graphene (G) and oxide graphene (GO). The results demonstrated that the optimal dosage of HA (10mg/L) significantly enhanced the physicochemical characteristics of AGS, and improved the pollutant treatment performance of the AGS reactor (R2 (1.0mg/L G) and R3 (1.0mg/L GO)). At the 75^th day, in R3, there was an obviously increase in average particle size of AGS from 1224.1µm to 1407.5µm, while in R2it increased from 1313.0µm to 1461.3µm. Simultaneously, the enhancement of AGS physicochemical properties led to a respective increase of 2.3% and 7.6% in TN removal efficiency for R2 and R3. The introduction of HA resulted in a significant reduction in the levels of reactive oxygen species (ROS), lactate dehydrogenase activity, catalase activity, and superoxide dismutase activity in R2 and R3. This suggested that HA can effectively bind with accumulated ROS within cells to further mitigate oxidative stress levels induced by G and GO. The addition of HA also effectively alleviated the excessive secretion of extracellular polymeric substances (EPS) in AGS, resulting in a decrease in the content of aromatic proteins and tyrosine-like substances within EPS. Consequently, this led to a more compact and denser AGS particle structure in R2 and R3. Ultimately, the changes in Zeta potential of G and GO (before and after the addition of HA) indicate that the incorporation of HA can enhance the initial potential values of G and GO, thereby augmenting the repulsive effect between G/GO and microorganisms, reducing direct contact between microorganisms and G/GO, thus effectively mitigating the toxic effects exerted by G and GO on microorganisms.

This research addressed the issue of low-carbon development in hydropower, provided a review of the key factors influencing the carbon footprint of hydropower and the regional variations in these footprints. The findings of this research indicated an increasing global focus on research into the carbon footprint of hydropower. Case studies revealed that the primary contributors to the hydropower carbon footprint were the manufacture of construction materials and engineering activities during the construction phase, as well as energy consumption by equipment during the operation and maintenance phase. This research identified key factors affecting hydropower carbon emissions, including the type of hydropower, installed capacity, water storage volume, reservoir area, and life cycle stages. Furthermore, from a geographical perspective, it explored the regional variation in hydropower carbon emissions, highlighting the impact of differences in climate, precipitation, and ecological environment due to geographical location on the hydropower carbon footprint.

A systematic study on antibiotic resistance genes (ARGs) and resistant pathogenic bacteria in the air and corresponding sewage of the sewage treatment plant was conducted. Their enrichment rate in the air and influencing factors were analyzed, and daily respiratory exposure was assessed. A divergence in the distribution of predominant ARGs in ambient air and sewage was revealed, with Sul1 and tetW being identified as the most abundantly detected genetic markers. The taxonomic composition of the dominant pathogenic bacteria was found to be similar across both matrices, with Bacteroides, Klebsiella, and Enterococcus genera being identified as the most prevalent in sequential order. Enrichment of certain ARGs and pathogenic bacteria was observed in the air of wastewater treatment plants, with the highest enrichment rates being attributed to the tetW gene and Megamonas genus, respectively. The transfer process of ARGs and pathogenic bacteria from wastewater to air was influenced by factors such as water quality and aeration processes. Tracing analysis indicated that approximately 73.59%±3.61% of the bacteria in the air of wastewater treatment plants originated from the sewage. Methicillin-resistant Staphylococcus aureus (MRSA) was successfully isolated from both air and sewage samples, with MRSA in the air being observed to exhibit an antibiotic resistance index (0.24) that was significantly higher than that in sewage (0.077±0.045). Furthermore, MRSA's resistance to vancomycin in the air was also found to be greater than that of the corresponding isolates from sewage. The daily inhalation exposure to bacteria for workers at the wastewater treatment plant was estimated to be (1.9±1.5)×10⁵ copies/d, with average exposure to ARGs and mobile genetic elements(MGEs) being calculated as (7.4±7.5)×10⁴ copies/d and (0.8±1.0)×10⁴ copies/d, respectively. The findings of this study were expected to provide scientific data for a comprehensive assessment of health risks associated with air quality in wastewater treatment plants and for the development of corresponding control strategies.