Using meteorological station observations, ERA5-L and reanalysis data, and Landsat remote sensing imagery from 2010 to 2023, we analysed the spatiotemporal characteristics of dust storms in the Ebinur Lake Basin of Xinjiang Uygur Autonomeus Region, northwest China. The generalized grey correlation model was applied to quantitatively assess the influence of surface wind speed, soil moisture, and vegetation coverage on the frequency of dust storm occurrences. The results showed an overall upward trend in dust storm days during 2010~2023 (+0.08d/a). In particular, there was a significant increase from 2010 to 2014 (+0.60d/a), followed by a short decline from 2014 to 2017 (-0.70d/a), and a rise after 2018(+0.31d/a). Spring was identified as the peak season for dust storm occurrences, with a lower frequency observed in summer and autumn, and no recorded events in winter. Spatially, the Jinghe meteorological station emerged as the high-frequency centre over the past 14 years. Compared with the late 20th century, the standard deviation of annual dust storm days across the five meteorological stations decreased by 88.42%, indicating a substantial reduction in regional disparities. It revealed that surface wind speed was the most critical driver of dust storms. Soil moisture was the second most influential factor, showing a distinct seasonal lag effect, while vegetation coverage exerted a comparatively minor influence on dust storm occurrence.

To investigate the variation rules, pollution characteristics, and their regional transport of fine particulate matter (PM_2.5) components in different seasons from Hohhot and Wuhai cities. In this study, the concentration of PM_2.5 and its chemical components, such as water-soluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements, and meteorological data, were obtained from the atmospheric super station in June-August and December of 2022, and January-February of 2023 from Hohhot and Wuhai. The sources and transport paths were also analyzed according to the Positive Definite Matrix Factor Decomposition (PMF) model and the Backward Trajectory (HYSPLIT) model. PM_2.5 mass concentration in winter was higher than that in summer in both cities. PM_2.5 mass concentration in Wuhai was higher than that in Hohhot in the same season. PM_2.5 in both cities is alkaline in winter and summer. The alkalinity of PM_2.5 in Hohhot was stronger than that in Wuhai during summer, and weaker than that in Wuhai during winter. The content of K, Mn, Cu, Ba, Ti, K⁺, and Cl^- in PM_2.5 in winter was higher than that in summer in the two cities. The two cities were more affected by biomass combustion, coal-fired emissions, and motor vehicle emissions in winter. PM_2.5 in Hohhot during summer mainly came from combustion sources, secondary inorganic sources, industrial sources, soil dust sources, and mixed sources motor of vehicle and road dust, while in winter it mainly came from coal combustion sources, biomass combustion sources, secondary inorganic sources, soil dust sources, mixed sources of motor vehicle and road dust, and mechanical wear sources. PM_2.5 in Wuhai during summer mainly came from combustion sources, secondary inorganic sources, industrial sources, soil dust sources, motor vehicle sources, road dust sources, while in winter it mainly came from combustion sources, secondary inorganic sources, industrial sources, soil dust sources, mixed sources of motor vehicle and road dust, and mechanical wear sources. Hohhot city was dominated by secondary sources in both summer and winter. Wuhai city was dominated by the mixture of motor vehicle and road dust in summer, while by secondary inorganic sources in winter. Hohhot City was mainly affected by air currents from southern Shanxi Province, northern Shaanxi Province, and southern Mongolia in summer, with potential source areas being southern Shanxi Province, southern Hebei Province, and northern Henan Province. Wuhai was mainly affected by air currents from eastern Xinjiang, Alxa League, southern Shaanxi Province, and Bayannur City in summer. Hohhot and Wuhai were affected by air currents from Alxa League and southern Mongolia in winter, with the difference that PM_2.5 transport in Wuhai in winter was also affected by air currents from northern Xinjiang. The potential source areas for winter in Hohhot are local, Baotou., Bayannur, Ordos, northeastern Alashan League, and the southern region of Mongolia, while that in Wuhai City during summer and winter were the eastern part of Xinjiang, Hexi Corridor region, Alashan League, Ordos City, Ulanqab City, and Wuhai City. The research results provide data support for the prevention and control of air pollution in typical cities along the Yellow River Basin.

The complex topographical conditions from the eastern Tibetan Plateau to the Chengdu Plain pose significant challenges for traditional boundary layer parameterization schemes, which in turn affects the accuracy of regional air quality models. To better understand these challenges, boundary layer turbulence flux observations were conducted in mountainous regions with substantial elevation variations. Based on these observations, a first-order nonlocal boundary layer scheme was refined for better applicability to local conditions, and its impact on ozone (O₃) simulations was assessed. The results show that the modified scheme improved WRF-Chem's simulation of O₃ advection and chemical processes, reducing the surface O₃ concentration bias from -5.14 ×10^-9 to-2.32×10^-9, demonstrating improved model performance. Moreover, differences in O₃ advection and vertical mixing highlighted distinct transport mechanisms between the mountainous region and the adjacent plains, emphasizing the influence of complex terrain on regional air quality.

In order to clarify the pollution characteristics and potential health risks of bioaerosols during leachate treatment, the concentration and particle size distribution characteristics of culturable microbial aerosols and the microbial community composition of each treatment unit of a typical leachate treatment process (two-stage A/O+MBR membrane treatment+DTRO deep treatment) were investigated and the health risks of aerosols and typical pathogen aerosols released in the leachate treatment process on occupationally exposed personnel were evaluated. The results showed that: During leachate treatment, the overall trend of aerosol concentration of culturable microorganisms showed a decrease in bioaerosol concentration with leachate treatment process (COD concentration decreasing), i.e. regulation tank > biochemical workshop > MBR workshop > DTRO workshop. The bacterial and fungal aerosols with particle sizes of 0.65~2.1μm in the whole plant treatment unit accounted for 26%~57% and 11%~59%, respectively, which had an invasion risk to the lower respiratory tract. With the leachate treatment process, the abundance of Bacillus in the aerosol increased significantly, and the abundance of Pseudomonas decreased significantly. Bacillus was very easy to aerosolize, and it was absolutely advantage in the biochemical workshop, comprehensive pool workshop, etc., and it was mainly distributed in the range of particle sizes from 3.3 to 4.7μm and>7.0μm. Alternaria was the dominant fungal genus, with a relatively uniform distribution in all units, mainly distributed in the particle size of>4.7μm. The aerosol concentration of E. coli at the points involving leachate treatment was significantly higher than that in the office area, and it was mainly distributed in the particle size of 1.1~2.1μm. The aerosol concentration of S. aureus was more variable among different points, but its concentration was overall lower than that of E. coli. The annual infection risk and disease burden of S. aureus aerosol exceeded the baseline values at all sites except the regulation tank, posing a greater threat to the health of plant workers.

Methane (CH₄), as a short-lived and high-warming potential greenhouse gas, understanding its concentration distribution and changes is crucial for China to achieve its "Dual Carbon" goal. This study systematically analyzed the distribution and changing pattern of methane concentration in North China utilizing methane concentration products produced by the Google Earth Engine platform and the University of Bremen, Germany, based on the TROPOMI satellite data, and conducted a comparative analysis of the quality of the two datasets. The results demonstrate that the methane concentrations in North China exhibited an increasing trend from 2019 to 2023. Specifically, the Offline Methane data rose from 1850.25×10^-9 to 1899.15 ×10^-9, representing an increase of 48.90×10^-9, while the Level 2XCH₄ data rose from 1860.13 ×10^-9 to 1909.60 ×10^-9 with an increase of 49.47×10^-9. The methane concentration was relatively high in Tianjin and Hebei Province, while that in the Inner Mongolia Autonomous Region was relatively low. The anomalously high methane concentrations were mainly distributed in Hebei and Shanxi provinces. A strong correlation between the two datasets was observed (r=0.92). Both datasets demonstrated a correlation greater than 0.85 with data from the Xianghe station, indicating that both datasets can effectively reflect the ground-level methane concentration. The Offline Methane data can provide visual downloads and high spatial resolution, but there are many data gaps. In practical applications, data fusion and other interpolation methods can be employed to fill these missing observations. The Level 2XCH₄ data has lower spatial resolution but higher coverage, and can be processed by gridding based on the size of the study area, making it suitable for large-scale research.

Based on the observation data of ozone pollution in the Yangtze River Delta (YRD) region from 2017 to 2023, the self-organized mapping (SOM) typing method and the WRF-CMAQ model were combined to systematically investigate theanomaliesof typical weather patterns and meteorological factor that affected ozone pollution in the region. Six typical weather patterns were identified through SOM modeling: trough front retention (32.65%) was found to be the main pollution pattern in summer, pre-Meiyu rain (21.12%) was concentrated in the alternating period of spring and summer, subtropical high peripheral (18.95%) occurred mostly in fall, and there were also weak low-pressure (12.56%), high-pressure profrontal (9.13%), and anticyclone (5.6%) patterns. The main meteorological factors during the ozone pollution period were characterized by significant anomalies, specifically positive temperature anomalies, negative wind speed and humidity anomalies, and radiation enhancement, all of which contributed to the production and accumulation of ozone. Based on the WRF-CMAQ model simulations with process analysis method, the analysis of the typical pollution processes from 2017 to 2023 revealed that during the cold period from October to April, ozone formation was primarily driven by temperature and radiation anomalies, with photochemical reactions dominating. The contribution of photochemical processes to ozone formation was found to reach 53%. In contrast, during the warm period from May to September, ozone pollution was more influenced by dynamic processes, such as the reduction of wind speed in the boundary layer, leading to a decrease in the contribution of photochemical processes to 38%. Meanwhile, the contribution of horizontal transport significantly increased to 26%. This study clarified the physical and chemical mechanisms between meteorological factors and ozone pollution under different weather patterns, providing scientific support for the refined control of ozone pollution in the YRD region.

As a key precursor to secondary air pollution, the atmospheric oxidation mechanism of volatile organic compounds (VOCs) is very complex, and the current model simulation generally has the problem that the total carbon mass of VOCs conversion process is difficult to close. Aiming for a more comprehensive understanding of the oxidation mechanism of VOCs, this study constructed a Lagrangian simulation system based on the zero-dimensional box model, using 6 widely used atmospheric chemical mechanisms, selecting 4 representative VOCs species and 56 PAMS (Photochemical Assessment Monitoring Station) combined air masses, and systematically carrying out the carbon balance simulation and evaluation of the generational oxidation process. The results showed that there was a significant carbon mass loss phenomenon (7.5%~76%) in the simulation of the six chemical mechanisms, and there were obvious differences between different mechanisms and components. Among them, MCMv3.3.1 had the lowest degree of carbon deletion and the highest OH exposure corresponding to the loss of total carbon mass. In the oxidized carbon balance of a single species, the carbon loss was the most serious during the oxidation of n-pentane, followed by the oxidation process of toluene. The occurrence of total carbon mass loss is mainly related to the chemical consumption of the first generation products and the generation of the second generation products. The results of this study provide an important scientific basis for improving the oxidation mechanism of organic species and improving the integrity of chemical mechanism.

Biogenic volatile organic compounds (BVOCs) are important precursors of ozone (O₃) formation. A rational understanding of the contribution of BVOCs to O₃ pollution is highly significant for regional air quality and environmental management. This study estimated the BVOCs emission intensity and their contribution to O₃ concentration in Shaanxi Province in 2023 based on the MEGANv3.2 and CMAQ models, combined with WRF-simulated meteorological fields and MODIS leaf area index (LAI) data. The results showed that: The WRF model accurately simulated temperature trends and radiation, meeting the requirements for regional meteorological input; but the reliability of wind speed and humidity simulations requires further improvement. The CMAQ-simulated O₃ concentrations exhibited a significant correlation with measured values, though the overall concentrations were underestimated. After applying a regression-derived correction factor of 1.15, the simulated results aligned well with observations. The average BVOCs emission intensity across the province was 3.37t/(km²·a). High-emission areas were primarily distributed in the Qinba Mountains of southern Shaanxi (5.77t/(km²·a)) and the Qiaoshan and Huanglongshan areas of Yan'an (4.74t/(km²·a)), both of which are regions with high natural forest coverage. Low-emission areas were mainly located in the grassland regions of Yulin (0.46t/(km²·a)), the forest-steppe transition zone in northern Yan'an (0.97t/(km²·a)), and the Guanzhong Basin (2.21t/(km²·a)). BVOC emissions exhibited distinct monthly and diurnal variations, peaking in July (0.99t/km²) annually and at 14:00 (local time) daily with a maximum value of 98.65kg/km². Isoprene (ISOP), monoterpenes (TERP), and sesquiterpenes (SESQ) were the main BVOC components, accounting for 37.39%, 28.49%, and 3.56%, respectively, with variation trends similar to total BVOCs. Trees and shrubs were the dominant sources, contributing 51% and 35%, respectively. In July, BVOCs contributed an average of 9.9% to the monthly mean maximum 8-hour O₃ concentration in Shaanxi Province, with ISOP and TERP accounting for 60.5% and 14.8% of this contribution, respectively. In October, the average contribution of BVOCs to the monthly mean maximum 8-hour ozone concentration decreased to 3.1%.

In order to explore the fractionation characteristics and mechanisms of biomass-pyrogenic smoke-derived dissolved organic matter (BSDOM) on ferrihydrite, this study selected BSDOM derived from three biomass sources (fir-wood chips, rice straw, and alfalfa) to investigate its adsorption on ferrihydrite. The organic compositions and molecular variations of BSDOM in the solution before and after fractionation were characterized using ultraviolet-visible (UV-Vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy and three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy. The results indicated that BSDOM primarily consisted of protein-like substances(57%~75%), with cation-π interactions identified as the dominant adsorption mechanism. High molecular weight and highly aromatic compounds exhibited stronger adsorption affinity to ferrihydrite, with polyphenols being preferentially adsorbed. The results demonstrated that acidic conditions enhanced cation-π interactions and ligand exchange between ferrihydrite and BSDOM, thereby promoting adsorption. At high pH(10.0~12.0), the adsorption of polyphenols and short-wave protein-like substances increased, likely due to hydrogen bonding. In contrast, the adsorption of long-wave protein-like substances and humic-like substances decreased, primarily because of increased electrostatic repulsion. This study elucidates the fractionation characteristics of BSDOM on ferrihydrite surfaces at a molecular level, providing insights into the cross-media environmental behavior of BSDOM in surface environments.

Copper-based layered double hydroxides (Cu-LDHs) are layered compounds composed of positively charged lamels and interlayer negative anions. With their excellent ion exchange properties, adjustable interlayer structure, unique memory effect, excellent catalytic activity and good thermal stability, they show great application potential in the field of denitrification. In this paper, the application progress of Cu-LDHs derivative catalysts in denitrification technology was reviewed. The types of SCR catalysts for Cu-LDHs derivatives were systematically classified from the perspectives of metal doping, carrier loading and anion regulation. The reaction mechanism of NH₃, CO and C₃H₆ as reducing agents in SCR system of Cu-LDHs derivatives was investigated. In addition, the strengthening strategy of the Cu-LDHs derivative catalyst in the aspects of sulfur resistance, hydrothermal aging resistance and alkali metal poisoning resistance was described in detail, aiming to enhance the stability and durability of the catalyst by comprehensive means. Finally, the future research direction of Cu-LDHs derivatives is prospectively prospected.

To achieve efficient filtration and enhance the degradation of antibiotics in water, a CoFe₂O₄-modified flat-sheet ceramic membrane was prepared using the impregnation-sintering method. The performance of this ceramic membrane activated by peroxymonosulfate (PMS) for the removal of florfenicol (FLO) and other antibiotics was investigated under dead-end filtration mode. The results indicated that at a pH value of 6 and a PMS dosage of 0.5mmol/L, the removal efficiency of FLO (10mg/L) was achieved at 88% within 30minutes. Furthermore, the system exhibited excellent resistance to interference from coexisting species such as Cl^-, NO₃^-, HCO₃^- and humic acid. After 7 cycles of FLO degradation using the CoFe₂O₄ ceramic membrane/PMS system, the removal rate of FLO remained high at 84%. Mechanistic studies revealed that HO^·, SO₄^·-, O₂^·-, ¹O₂ were identified as the primary reactive species responsible for the catalytic degradation. Treatment results of actual aquaculture wastewater showed that the removal efficiencies for COD and turbidity were 65.4% and 99.3%, respectively. Simultaneously, the removal rates for eight typical antibiotics present in the wastewater exceeded 80%, highlighting its significant potential for practical application.

Natural maghemite (γ-Fe₂O₃) particles were coated with SiO₂ and combined with Bi₂WO₆ to prepare a magnetic photocatalyst γ-Fe₂O₃@SiO₂/Bi₂WO₆. The samples were characterized by multiple means of XRD, FESEM, XPS and VSM. The VSM tests indicated that γ-Fe₂O₃@SiO₂/Bi₂WO₆ possesses magnetic properties, allowing for magnetic recovery and reuse. Compared with Bi₂WO₆, the catalytic performance of γ-Fe₂O₃@SiO₂/Bi₂WO₆ for degrading isobutyl xanthate slightly decreases, but the 5%γ-Fe₂O₃@SiO₂/Bi₂WO₆ can almost completely degrade isobutyl xanthate (60mg/L) within 60min, and the TOC test results showed that the mineralization degree of isobutyl xanthate wastewater was as high as 76.86%. The results of cyclic experiments showed that catalytic activity of γ-Fe₂O₃@SiO₂/Bi₂WO₆ hardly decreased after 5cycles. The degradation efficiency of isobutyl xanthate stabilized over 99% and the recovery rate of 5%γ-Fe₂O₃@SiO₂/Bi₂WO₆ was as high as 82.00%. It proved the stability and recyclability of the prepared γ-Fe₂O₃@SiO₂/Bi₂WO₆ composites. Sacrificial agent experiments and ESR tests indicated that ·O₂^- was the predominant species in the photo-degradation process of isobutyl xanthate. Finally, DFT calculations confirmed that the active sites on the catalyst surface and xanthate were W atom and S atom, respectively.

This study employed H₂S in an ethanol-phase as a sulfidation reagent to synthesize sulfidated nanoscale zero-valent iron (S-nZVI-H₂S-Ethanol) through a liquid-phase chemical reduction approach. A systematic investigation was conducted to examine the effects of sulfidation time duration on the material's surface characteristics, electrochemical properties, hydrogen suppression capability, and dechlorination performance. The results revealed that prolonged sulfidation treatment led to the formation of flake-like iron-sulfur compounds(FeSx) on the particle surfaces, accompanied by a significant increase in specific surface area. XPS analysis demonstrated a non-monotonic relationship between sulfidation time and surface composition: Fe-S content initially increased before decreasing, while Fe-O content exhibited the inverse trend. Electrochemical characterization indentified the S-nZVI-H₂S-Ethanol(S12h) exhibited optimal performance, with the lowest charge transfer impedance and the lowest corrosion potential (-0.923V), suggesting enhanced electron transfer efficiency and reductive capacity. Hydrogen evolution experiments confirmed that sulfidation effectively suppressed the hydrogen evolution reaction, with the hydrogen generation rate decreasing initially before stabilizing with extended treatment time. In TCE dechlorination experiments, both nZVI and S-nZVI-H₂S-Ethanol followed pseudo-first-order kinetics, demonstrating markedly higher apparent rate constants (kb: 1.4/h, 0.81/h, and 0.48/h for S2h, S12h, and S24h, respectively) compared to pristine nZVI (0.025/h). The degradation product distribution of trichloroethylene revealed that the degradation pathways were governed by competing β-elimination and hydrogenation reactions, yielding primarily acetylene, ethylene, ethane, and long-chain hydrocarbons (C₃-C₆). These results collectively demonstrated that ethanol-phase H₂S sulfidation significantly enhances nZVI's degradation performance. The comprehensive examination of S-nZVI-H₂S-Ethanol's surface properties and dechlorination efficiency across varying sulfidation durations provides crucial insights for optimizing material design in environmental remediation applications.

This study systematically explores the performance and mechanisms of zirconium-based gel coagulant (ZXC) synthesized by the sol-gel method in fluoride removal. Through optimizing parameters, examining the impacts of coexisting matrix, and analyzing physicochemical properties, we found that ZXC achieved the best fluoride removal at pH 4.0. ZXC outperformed traditional coagulants like polyaluminum chloride (PAC), polyferric sulfate (PFS), and titanium-based coagulants (TXC), effectively reducing fluoride to below 1.0mg/L with low residual metal concentrations. The fluoride removal by ZXC involves a "concentration-dependent multi-mechanism synergy process," primarily via ligand exchange at low concentrations, and through direct coordination, co-precipitation, and condensation at higher concentrations. Field tests demonstrate that ZXC can reduce fluoride levels in contaminated groundwater, electroplating wastewater, and photovoltaic wastewater to below 1.5mg/L, meeting the first-tier discharge standards. This work offers an efficient and practical solution for industrial fluoride wastewater and high-fluoride groundwater treatment.

The development of photothermal materials derived from coal slime, a solid waste from coal mining, offers a promising approach for the resource utilization of both coal waste and highly mineralized mine water. Coal slime was processed into coal-based carbon material (MC) through calcination and pickling processes. The MC exhibited excellent light absorption (~95.0% in the 200~2500nm) and photothermal performance, with the surface temperature reaching 55.1℃ within 180s of illumination. A spherical evaporator with high-salinity resistance and self-suspension was prepared by incorporating sodium alginate into MC and crosslinking it with calcium chloride, using sodium bicarbonate as a pore-forming agent and polyvinyl alcohol as a foam stabilizer, via the dropwise method. The optimized composite (SA_2/1-MC₂) showed strong photothermal performance, achieving evaporation rates of 0.97kg/(m²·h) for 20.0wt% NaCl solution and 0.99kg/(m²·h) for reverse osmosis concentrated mine water, with stable operation over 10h. These results demonstrate that SA_2/1-MC₂ is an effective material for treating highly mineralized mine water.

In this study, short-term batch experiment was used to investigate the mechanism of thiocyanate (0~500mg/L) addition on the anammox granular sludge system. The results showed that as the concentration of thiocyanate influent increased, nitrogen removal efficiency of Anammox decreased significantly, and the total nitrogen removal efficiency decreased from 88.6% in the control group to 43.3% (500mg/L thiocyanate); The anammox activity (SAA) also showed a rapid decreasing trend. The non-competitive inhibition model determined the 50% inhibitory concentration (IC₅₀) of thiocyanate on Anammox to be 209.5mg/L. The EPS secreted by Anammox cells increased after the addition of thiocyanate. The PN/PS increased with the rise of the concentration of thiocyanate. The relative abundance of Candidatus Brocadia was significantly decreased after the addition of thiocyanate, while the relative abundance of Thiobacillus increased sharply, and The abundance of microbial functional metabolism pathways appeared to be reduced to different degrees. The research results can provide a theoretical basis for the application of Anammox engineering in treating nitrogenous wastewater containing thiocyanate.

In this study, the UV activated periodate (PI, IO₄^-) system (UV/PI) was investigated to degrade PhACs in urine (UV(10W low pressure, peak at 254nm), PI (5mmol/L)), the results demonstrated that the degradation rate of 12 selected Pharmaceutically active compounds (PhACs) exceeded 60% at 10min; based on this, the influence of urine matrix on PhACs degradation was further studied. In fresh urine matrices, urea and citrate reacted with the radicals, inhibiting the degradation of PhACs, with the rate constant k_i decreasing by about 0.0083~0.0129s^-1 compared to the UV/PI system. Meanwhile, Cl^- reacted with the radicals to form lower reactive chlorine species (RCS), which negatively affected the degradation efficiency, with the k_i decreasing by about 0.0015~0.0056s^-1. In hydrolyzed urine matrices, urea and citrate were hydrolyzed into NH₃ and HCO₃^-. Then, NH₃ and HCO₃^- reacted with the radicals to produce reactive nitrogen species (RNS) and CO₃·^-, which further reacted with PhACs. UV/PI system exhibited significant structural selectivity for the degradation of PhACs.

An AnMBR-PN/A system was developed for methylamine wastewater treatment. At optimal HRTs (AnMBR:8h, PN/A:9h), it achieved >95% COD and >86% TN removal, with effluent <5mg/L NH₄⁺-N and <15mg/L TN (meeting Class 1A standards). Net energy potential reached 0.72 with partial recovery, while energy-generating gases provided economic benefits. Versus A²/O, this system reduces operational costs and demonstrates dual advantages in energy conservation and emission reduction.

In this paper, a novel iron-based nanocomposite lignin hydrogel (FeS@LH) was synthesized and applied to the activation of perdisulfate (PDS). Through the characterization of the material, it is found that the unique three-dimensional (3D) structure of the lignin hydrogel is helpful to the dispersion of sulfide nano-zero-valent iron particles (FeS particles) and increase the leakage site of FeS. This three-dimensional structure not only provides more attachment sites for FeS, PDS and pollutants, but also accelerates the electron transfer between FeS and PDS, thus promoting the degradation of pollutants. The experimental results show that FeS@LH has excellent performance in PDS activation. Under the condition of 0.1g/L catalyst and 1mmol/L PDS, 10mg/L IMI (100mL) can be completely degraded in 120minutes. Quenching experiments and electron spin resonance (ESR) spectra show that SO₄·^- and OH· are the main active species for IMI degradation in FeS@LH/PDS system. In addition, FeS@LH can effectively activate PDS to degrade IMI in the presence of inorganic anions and natural organic matter (HA). The degradation products of IMI were identified by liquid chromatography-mass spectrometry (UPLC-MS-MS) system, and two possible degradation pathways were proposed. The toxicity prediction results show that IMI can eventually be converted into a non-toxic product. FeS@LH was able to maintain a certain degradation efficiency after three cycles of testing, while exhibiting low metal leaching characteristics. Study results provide new ideas for the development of efficient degradation of pesticide pollutants.

This study utilizes ascorbic acid under hydrothermal conditions to composite ferric oxide (Fe₃O₄) and molybdenum disulfide (MoS₂), preparing Fe@C-MoS₂ with enhanced electron transfer for catalyzing the degradation of atrazine (ATZ) by peroxymonosulfate (PMS). Under the conditions of an ATZ concentration of 5mg/L, a catalyst dosage of 0.2g/L, and a PMS concentration of 1mmol/L, the removal rate of ATZ reached 84.6% after 35 minutes of reaction. Electrochemical experiments and XPS characterization demonstrated that the excellent catalytic performance of Fe@C-MoS₂ is attributed to the carbon source-induced generation of mixed-phase MoS₂, which effectively improves the conductivity of the catalyst and promotes rapid electron transfer. Additionally, through bio-toxicity tests using locally grown cauliflower as the study subject, the feasibility of using the solution degraded by the Fe@C-MoS₂/PMS system as agricultural irrigation water was evaluated. The results indicate that the post-degradation solution showed negligible effects on both the survival rate of cauliflower seedlings and their growth parameters when compared with conventional water sources.

Given high concentrations of chemical oxygen demand (COD), ammonium nitrogen (NH₄⁺-N), suspended solids (SS), and poor biodegradability of concentrated swine farm wastewater, a combined treatment process of "pretreatment-biochemical treatment-advanced treatment" was employed in this study, specifically designed as "solid-liquid separation → anaerobic fermentation → A/O → MBR." By comparing influent characteristics and pollutant removal efficiency between summer and winter, the energy consumption and greenhouse gas (GHG) emission profiles of the system were systematically analyzed. The average effluent COD and TN in the summer were significantly lower than those in the winter (711.21mg/L and 61.78mg/L, respectively), indicating that low temperature significantly inhibit the treatment efficiency. The A/O unit dominated energy usage, with a consumption of 7.65 (kW·h)/m³, accounting for 56.48% of total energy demand. The annual GHG emissions totaled 1364.41t CO₂-eq, with an emission intensity of 15.53kg CO₂-eq/m³. The emission intensities per unit COD and TN removed were 1.33kg CO₂-eq/kg COD_removed and 10.89kg CO₂-eq/kg TN_removed, respectively. Further analysis revealed that external electricity consumption contributed to 72.98% of total GHG emission, followed by nitrous oxide (N₂O) release (25.99%). Through the regulation of seasonal process parameters, the development of multi-mode operation strategies, and the integration of online monitoring technologies, the precise control of the treatment process is optimized to achieve the goals of energy saving, consumption reduction, and low-carbon operation.

On the basis of investigating the effect of fluoranthene (Flu) on the anaerobic co-digestion of sludge and kitchen waste, the mechanism on anaerobic co-digestion was comprehensively analysed. The results demonstrated that anaerobic methanogenesis was enhanced within the appropriate concentration of Flu (≤50mg/kg TSS). The maximum methane yield of the anaerobic co-digestion system [30.7mL/(gVSS·d)] was achieved at Flu concentration of 50mg/kg TSS, which was 1.61times that of the control group. Mechanistic studies showed that hydrolysis, acidification and acetoclastic methanogenesis were promoted by Flu, as evidenced by the increased activities of acetate kinase (ACK, 1.30-fold) and coenzyme F420 (1.43-fold) relative to the control. Microbial community structure demonstrated that not only Prevotella and Trichococcus, involved in organic matter hydrolysis and acidification, were selectively enriched in the Flu group, but also the relative abundance of the acetoclastic methanogen Methanosarcina was increased. Metagenomics further revealed that the relative abundances of functional genes associated with glycolysis (HK, pfk and PK), volatile fatty acid production (por, ackA and buk) and acetoclastic methanogenesis (pta, ACSS1_2, cdhD and cdhE) were up-regulated, favouring methanogenesis.

With the rapid development of the renewable energy industry, the usage of lithium iron phosphate batteries has soared. Therefore, the recycling of spent batteries has become a social focus. The selective leaching method can effectively extract lithium, reduce impurities, and improve recycling efficiency. This paper systematically reviews various selective lithium leaching techniques, including chemical oxidation, acid-assisted leaching, electrochemistry, high-temperature roasting, mechanochemistry, and so on, which further compares their respective advantages and disadvantages from the aspects of technical economy and environmental benefits. The results indicate that the chemical oxidation method has advantages in cost control and operational flexibility, while the electrochemical method is more and environmentally friendly and green. For the selective recycling of spent lithium iron phosphate batteries, more efficient, environmentally friendly, and economical recycling solutions should be developed in the future. This will provide new ideas for exploring selective recycling strategies for lithium iron phosphate batteries, which can promote comprehensive and coordinated development of the economy, environment, and technology, and thereby build a virtuous cycle system of new quality productivity.

This study conducted X-ray fluorescence (XRF) and X-ray diffraction (XRD) experiments on 10 common types of solid waste. By employing non-parametric tests, the XRF and XRD fingerprint characteristics of solid waste were extracted. A normalized approach was adopted to combine the two fingerprint characteristics to form XRF-XRD coupled spectral fingerprint characteristics. A machine learning classification model was trained using the three fingerprint characteristics as a dataset. It was found that the random forest model exhibited the best classification recognition performance, with classification accuracy, recall rate, and precision rate in the validation set reaching 98.0%, 97.5%, and 97.6%, respectively. This confirmed that the classification performance of coupled spectral fingerprint characteristics was superior to that of single spectral fingerprint characteristics. A method for extracting multi-dimensional fingerprint characteristics of solid waste using XRF-XRD was developed, laying a methodological foundation for the identification of fingerprint characteristics of solid waste.

To investigate the effect of fulvic acid (FA) addition on heavy metal speciation during aerobic composting of sludge-based biomass waste, a 44-day aerobic composting experiment was conducted using sludge, straw, and food waste as raw materials. The effects of FA at 100, 200, and 400mg·kg^-1 on heavy metal transformation dynamics were examined. Results showed that FA addition increased peak temperature, cation exchange capacity (CEC), volatile solids (VS) degradation rate, and germination index (GI). FA notably facilitated the conversion of heavy metals into more stable residual fractions, with residual cobalt (RES-Co), nickel (RES-Ni), and copper (RES-Cu) contents increasing by 11.0%~16.9%, 4.1%~6.8%, and 0.8%~6.0%, respectively, compared to the control. By enhancing the accumulation of aromatic carbon in dissolved organic matter (DOM) and enriching specific microbial taxa (e.g., Proteobacteria and Bacteroidetes), FA accelerated humification and enhanced the immobilization of heavy metals. GI, CEC, pH, and RES-Ni were identified as key factors influencing microbial community shifts. The 400mg/kg FA treatment exhibited the most significant heavy metal passivation effect, primarily by accelerating the humification of dissolved organic matter and optimizing the microbial community structure.

To identify the key extracellular polymeric substance (EPS) fractions and elucidate the microbial mechanisms driving foaming in high solid anaerobic digestion (HSAD) of food waste, organic loading rate (OLR) perturbations were introduced in a semi-continuous anaerobic digestion (AD) reactor to induce the foaming phenomenon. The responses of physicochemical parameters and microbial community structure were systematically investigated. The results indicated that foaming height was positively correlated with hydrophobic proteins in soluble EPS, as well as with hydrophobic humic substances (HU) and hydrophobic proteins (PN) in total EPS. This suggests that these three EPS fractions are potential key contributors associated with foaming. Microbial analyses revealed a significant positive correlation between the abundance of Fastidiosipila, Rikenellaceae_RC9_gut_group, W5053, and W5 genera with foaming height and the concentrations of key EPS fractions (P≤0.05), indicating their role as key microorganisms contributing to AD foaming. Additionally, multivariate statistical analyses of physicochemical and microbial parameters indicated that, the continuous increase in OLR stimulated the accumulation of volatile fatty acids (VFA), which in turn promoted the proliferation of Fastidiosipila, Rikenellaceae_RC9_gut_group, W5053, and W5. These microorganisms subsequently synthesized substantial amounts of key EPS fractions in response to environmental stress. The over-secreted EPS were oriented and arranged on the surface of bubbles, enhancing the mechanical strength of the liquid membrane and slowing down bubble rupture. Unlike other key microorganisms that primarily act in the liquid phase, W5 also migrated with the bubbles to the foam layer, further promoting foam stabilization by secreting hydrophobic HU. This study provides a theoretical basis for developing defoaming strategies for AD systems treating food waste.

Improper export of hazardous waste may cause serious environmental pollution and regulatory risks. To improve the accuracy and scientific nature of export risk warning, this study constructed a hazardous waste export risk warning system based on K-means clustering and particle swarm optimization BP (PSO-BP) neural network. Based on multidimensional indicators of historical data, the export risk of hazardous waste was classified using the K-means clustering algorithm, and the initial parameters of the BP neural network were optimized by the PSO algorithm, thereby improving the accuracy and convergence efficiency of risk prediction. The experimental results showed that the consistency between the risk classification by K-means clustering and expert annotation was 93.2%, proving that the inherent risk structure of the data could be effectively revealed by this method. The prediction accuracy of the PSO-BP neural network reached 92.5%, and the mean square error was reduced to 0.012. Compared with the traditional BP neural network, the prediction accuracy was significantly improved, and the training convergence speed was increased by 40%. Based on the above model, a hazardous waste export risk warning system was developed in this study, through which data collection, risk assessment, model prediction, and warning visualization were achieved. The implementation and application of the model were verified using 30 types of hazardous waste as examples. The results showed that hazardous waste export data could be analyzed in real time, dynamic warnings could be provided based on risk prediction results, and the efficiency of hazardous waste export management could be effectively improved.

This study investigated the impacts of vegetation restoration patch patterns (blank control, checkerboard, horizontal strip, and diagonal strip) and scouring flow rates (3, 4.5, and 6L/min) on slope soil erosion characteristics and vegetation conservation benefits in a mining wasteland of Urat Front Banner. Key findings include: Runoff and sediment yield decreased on vegetation-restored slopes but increased with higher souring flow rates. The horizontal strip pattern slope exhibited the smallest increase in runoff and sediment yield with rising flow rate, achieving the highest overall runoff reduction rate (34.36%) and sediment reduction rate (79.50%), and sediment reduction capacity [35.09g/(min·m²)]. Runoff rates generally increased during scouring, while sediment yield rates varied across patterns. Sediment yield rate within vegetation patches were significantly lower than the slope average and often negative. The horizontal strip slope exhibited stable sediment yield rate, with the lowest patch sediment yield rate [-13.02g/(min·m²)]. Except for the horizontal strip slope, sediment yield rates correlated linearly with runoff rates. Scouring flow rates dominated runoff and runoff rates, contributing 79.37% and 66.21%, respectively. Moreover, vegetation patch patterns exerted stronger effects on erosion than runoff. In conclusion, the horizontal strip pattern is optimal for soil and water conservation in mining wastelands, and drainage design is crucial for erosion control in these areas.

Reclaimed water is an important irrigation source in the agricultural field, but it contains antibiotic resistance genes (ARGs), which are potential pollutants. There have been relatively few reports on the influence of reclaimed water irrigation volume on the level of soil antibiotic resistance. This study constructed a controlled experiment and conducted a comparative analysis of the above issues using metagenomic analysis. The results showed that a total of 442 ARGs belonging to 27 ARG types were identified in the reclaimed water-soil irrigation system. The abundance of ARGs in in reclaimed water irrigation soil increased by 4.04% -28.62%, with the greatest increases in the abundance of colistin, β-lactam, and multidrug resistance genes. During the irrigation process, the abundance, diversity, and risk of soil ARGs, as well as the contribution of reclaimed water, exhibit anoverall fluctuating trend of first increasing and then decreasing. High irrigation volume enhanced the level of soil antibiotic resistance, which was especially evident in the middle stage of irrigation. However, due to soil matrix and recovery capacity, the difference in irrigation volume did not significantly affect the antibiotic resistance of irrigated soil throughout the entire process (variance analysis, P>0.1). Network analysis and variance partitioning analysis (VPA) indicatedthat microbial communities are the main factor affecting the transmission of ARGs in reclaimed water-irrigated soil, while high irrigation volume increased the contribution of mobile genetic elements (MGEs) represented by the integrator intI1, to the transmission of ARGs, resulting in a significant weakening of source characteristics. The research results provide fundamental theoretical support for understanding the spread of antibiotic resistance in reclaimed water and soil, and offer scientific guidance for the risk prevention and control of soil antibiotic resistance and the utilization of reclaimed water.

This study investigated the effects of sugarcane bagasse biochar on the degradation of azoxystrobin and the structural composition of microbial communities in flooded paddy soils from South China using a microcosm system. Results demonstrated that biochar pyrolyzed at 300℃, 500℃, and 700℃ accelerated azoxystrobin degradation during the early incubation phase (10d), achieving degradation rates of 32.42%~34.87%, significantly higher than the 16.48% observed in the control (no biochar). However, it ultimately inhibited complete degradation by the late phase (50d), with final degradation rates of 88.78%~89.76% in biochar-amended soils versus 98.77% in the control, demonstrating an initial stimulation followed by suppression. The inhibitory effect intensified with increasing application rates of 700℃ biochar (BC700). Azoxystrobin acid, a key metabolite, was identified during this process. High-throughput 16S rRNA sequencing revealed that BC700 addition reduced total microbial species richness and Chao1index. Comparative analysis showed that 5% and 10% biochar treatments significantly decreased the relative abundance of Desulfobacterota while increasing Citrifermentans and Bacillus spp. compared to pristine soil and the 3% biochar treatment. Conversely, Clostridium_sensu_stricto_12 abundance declined.

In this study, five treatments (CK: control with no Pb input, Pb₃₀:30mg/kg soil, Pb₆₀:60mg/kg soil, Pb₁₂₀:120mg/kg soil, Pb₂₄₀:240mg/kg soil) were set up by adding PbCl₂ solution withdifferent Pb concentrations to atypical subtropical urban park soil. The indoor incubation experiments were carried out for 28d to investigate the response mechanism of potential N₂O emissions from urban park soilto different exogenous Pb additions. The results showed that the cumulative N₂O emissions from Pb₃₀~Pb₂₄₀ treatments were significantly higher than those from CK, which increased linearly with the increases of exogenous Pb additions and soil Pb contents, during the whole incubation period. After 14d of Pb addition, the activities of nitrite reductase and N₂O reductase increased and decreased with the increasing soil Pb content, respectively, which resulted in significant increases in the potential N₂O emission ratesfrom soil. After 14~28d of Pb addition, soil pH significantly decreased with the increasing soil Pb content, and the combined inhibitory effects of decreasing pH and increasing Pb content on the N₂O reductase activity were significantly enhanced. The combined effects of the above-mentionedprocesses ultimately resulted in significant increases in the potential N₂O cumulative emissionsfrom soilwith increasing Pb additions during the incubation period. This study indicates that the effects of Pb pollutants on nitrogen cycle and denitrification microorganisms should be paid more attention in the future, considering the accumulations of Pb pollutants in urban park soil will increase the risk of potential N₂O emission. This study can provide scientific guidance for management of urban park and formulating measures for the reduction of N₂O emissions from urban park soil.

Based on the investigation of 50 rural black and odorous water remediation projects in Chongqing, this study constructed a "Pressure-State-Response-Benefit" (PSRB) framework model, screened and determined the evaluation index from the four dimensions of Pressure, State, Response and Benefit, and formed an evaluation index system. Based on the investigation of 11 typical cases of black and odorous water specifically ponds, ditches, and rivers that had been remediated for over six months, an evaluation was conducted. Among these, the remediation effect of pond-type black and odorous water was tracked and evaluated in June, August, and October 2023. The results indicate that the weights of the four dimensions Pressure, State, Response and Benefit were 0.27, 0.21, 0.36, and 0.16, respectively. The negative indexes with higher weights (C₁₁, C₁₄, C₂₄, C₃₆) outnumber the positive indexes with higher weights (C₃₁, C₄₁). This suggests that although the remediation of rural black and odorous water has received a positive response, the water that have been remediated still face significant pressure and have limited benefits. Among them, the remediation effect of 10cases was rated as "Effective," while 1case was rated as "Passing." In the Pressure dimension, factors such as "high population load in the water area," "damage to sewage interception and pipe networks," and "residual black and odorous sludge," as well as in the Response dimension, "the investment in water body remediation is relatively high" and "insufficient implementation of operation and maintenance management" were the main adverse influencing factors of the remediation effect.

This study develops an innovative framework for estimating forest carbon stocks in Sanjiangyuan National Nature Reserve through synergistic inversion of multi-source remote sensing data. We pioneer the comprehensive fusion of Sentinel-2red-edge spectral features with Sentinel-1SAR datasets. Comparative analysis of machine learning algorithms-Random Forest (RF), Gradient Boosting Regression Trees (GBRT), and K-Nearest Neighbors (KNN)-was conducted, with Recursive Feature Elimination (RFE) optimizing feature selection. Key findings reveal: The GBRT-RFE integration achieved optimal performance (R²=0.84, RMSE=3.50Mg/hm²). Multi-source fusion significantly enhanced estimation accuracy across forest types (broadleaf: R²=0.88; coniferous: R²=0.92). Red-edge indices (e.g., EVI, CI) demonstrated highest feature importance, while SAR textures effectively compensated for optical data limitations in canopy penetration through structural information. The 30-m resolution carbon stock map generated by the optimized model showed values ranging from 6.06 to 39.73Mg/hm² (mean=20.85Mg/hm²), exhibiting distinct topographic and moisture gradients. Methodological breakthroughs include: A topography-adaptive feature selection framework for alpine regions, improving steep-slope (>25°) estimation accuracy by 18%~22%; First successful integration of Sentinel-2red-edge bands (B5-B7, B8A) with Sentinel-1dual-polarization (VV/VH) textures; Development of a regional-scale high-precision estimation model (validated against 126 field plots, RMSE < 15%). This research delivers robust technical support for carbon sink quantification, with direct applications in carbon trading and ecological compensation programs, advancing China's "Dual Carbon" goals (2030/2060).

To elucidate the sources and driving mechanisms of nitrate pollution in the inflow rivers of northern Fuxian Lake, this study collected water and soil samples from 11sites across four major river catchments (Dufangdagou, Fucheng River, Yaonigou, and Longxigou) in the northern area during both the wet and dry seasons of 2022. An integrated approach combining nitrogen and oxygen isotope tracing, water chemistry analysis, land use assessment, and the MixSIAR model was employed to quantitatively determine the contributions of various nitrogen pollution sources and to identify the key factors influencing nitrate pollution. The results indicated that nitratenitrogen was the predominant nitrogen species, accounting for over 60% of total nitrogen (TN), with an increased proportion during the wet season. Soil nitrogen loss and sewage/manure discharge were identified as the primary sources of nitrate pollution, contributing 31.1%~56.1% and 15.6%~38.9%, respectively, followed by chemical fertilizer application (10.2%~45%) and atmospheric nitrogen deposition (3.3%~16.7%). Notably, the contribution from domestic sewage increased substantially in Fucheng River and Yaonigou catchments during the wet season, likely due to intensified runoff scouring and sewage overflow. In addition, soils under vegetable cultivation exhibited greater nitrate loss compared to those planted with blueberries, wheat, or tobacco, with irrigation during the dry season further exacerbating nitrogen loss. These findings highlight the urgent need for targeted management strategies to mitigate nitrate loss from legacy nitrogen pools in agricultural soils, particularly in vegetable fields.

As an important indicative organism of river ecological health, benthic macroinvertebrates are an ideal choice for constructing the Index of Biological Integrity (IBI). This study is based on data from 41mainstem and tributary monitoring sites in the Ching River Basin, which were collected in November 2021 (autumn) and May 2022 (spring). Using a stepwise selection method, five core parameters were identified for the autumn (total biomass, relative abundance of Ephemeroptera individuals, relative abundance of sensitive taxa, BI, and Simpson's diversity index), and six core parameters were identified for the spring (number of Chironomidae taxonomic units, total biomass, relative abundance of scraper individuals, relative abundance of sensitive taxa, Hilsenhoff Biotic Index, and ASPT index). Health evaluation results showed that among the 41 sampling sites, 15 were classified as healthy, 7 as sub-healthy, 14 as fair, and 5 as poor in the autumn; in the spring, 8 were healthy, 10 were sub-healthy, 15 were fair, and 8 were poor. Spearman's correlation analysis of core parameters and environmental factors showed that, in the autumn, NO₃^--N was significantly negatively correlated with the BI index (P=0.003); in the spring, COD was significantly negatively correlated with total biomass (P=0.007), and pH was significantly positively correlated with the number of Chironomidae taxonomic units (P=0.007). Random forest model analysis of land use types and B-IBI values at different scales indicated that in the autumn, the proportion of grassland had a significant effect on B-IBI in smaller-scale buffers (100~500m), whereas the proportion of cropland and forest had a significant effect in larger-scale buffers (1000~1500m). In the spring, the proportion of cropland significantly affected B-IBI in smaller-scale buffers, and as the buffer scale increased, the proportion of forest had a progressively significant effect, with the most significant effect observed in the 500m buffer. Comprehensive analysis indicates that the combined effects of land use types and environmental factors influence the B-IBI of benthic macroinvertebrates in the Ching River Basin, and that rational land use planning can contribute to the improvement of water ecological health in the basin.

This study takes the Huaihe River Basin as the research area, integrates ecosystem service assessment, biodiversity analysis, and landscape connectivity analysis, and identifies ecological sources by combining nature reserves. Eight key resistance factors were selected, including landscape ecological risk, MSPA (Morphological Spatial Pattern Analysis) landscape types, vegetation coverage, topographic relief, land use types, night-time light index, distance to rivers, and distance to roads. A comprehensive resistance surface was constructed using the entropy weight method. Based on circuit theory, ecological corridors were built and their grades were determined. Furthermore, key areas for ecological restoration were identified by recognizing ecological pinch points and barrier points. The results showed that a total of 24 ecological sources were identified in the Huaihe River Basin, with a total area of 23,590.30km², mainly distributed in cities such as Lu'an and Xinyang. There were 41 ecological corridors, among which 19 were key ecological corridors. A total of 781 ecological pinch points and 142 ecological barrier points were identified. The main land use types of ecological pinch points were cultivated land, water areas, and forest land. Xuzhou City had the largest area of ecological pinch points, while Chuzhou City had the largest number of ecological pinch points. The total area of ecological pinch points requiring priority protection and restoration was 405.76km², and the total area of ecological barrier points was 948.99km². The Huaihe River Basin presents a spatial pattern of "three cores, four belts, and multiple points". Guided by the principle of prioritizing natural ecology and supplementing with artificial measures, this study proposes scientific protection and restoration strategies for key areas of different land types, aiming to enhance the integrity and connectivity of the ecosystem in the Huaihe River Basin. The findings provide a scientific basis and practical guidance for ecological protection and restoration in the Huaihe River Basin and other river basins.

The rapid development of strategic emerging industries has intensified the migration and enrichment of nitrogen-containing heterocyclic compounds (NHCs) in aquatic environments, posing severe threats to ecological functions by disrupting nitrogen cycle homeostasis. This study systematically elucidates the dual effects of NHCs on microalgal nitrogen metabolism. On one hand, NHCs may function as alternative nitrogen sources, with their bioavailability contingent upon bacterial transmembrane transport, ring-opening reactions that liberate nitrogen, and subsequent assimilation processes within algal cells. On the other hand, NHCs act as stressors that perturb nitrogen metabolism by disrupting the photosynthetic electron transport chain, altering the synthesis and stability of photosynthetic pigments, and inducing oxidative stress responses. Building upon these findings, the review further delves into the influence of NHC molecular structures and environmental parameters-particularly light availability-on the mechanisms by which NHCs interfere with algal nitrogen metabolic pathways. In light of existing knowledge gaps, future research should prioritize the development of integrative regulatory models addressing nitrogen metabolism under combined NHC and inorganic nitrogen stress, molecular interactions and targeted regulation in algae-bacteria symbiotic systems, and the exploration of nanomaterial-mediated strategies to enhance electron transport efficiency. Advancements in these areas hold the potential to enable precise manipulation of nitrogen metabolic pathways in aquatic systems and to facilitate the efficient degradation of nitrogenous contaminants.

Scientifically predicting the trade-offs and synergies of ecosystem services under multiple scenarios provides an important basis for the sustainable development of Chinese urban agglomerations. Based on multi-source datasets for 2001, 2010 and 2020, the study employed the PLUS-InVEST modelling framework together with trade-offs and synergies measurement methods to analyze land use change, characterize the spatiotemporal features of ecosystem services, and assess their trade-offs and synergies relationships in Chinese urban agglomerations for 2000, 2010, 2020, and scenarios in 2030. The results showed that between 2000 and 2020, the areas of cropland, forest land, grassland, unused land within Chinese urban agglomerations declined continuously, decreasing by 6.30×10⁴km²、7.49×10³km²、2.88×10⁴km²、1.09×10⁴km², respectively. Scenario simulations indicated that the ecological protection scenario effectively curbed these degradation trends. Overall, the ecosystem service levels of urban agglomerations in southern China were higher than those in the north, and the ecological protection scenario yielded higher levels than the other scenarios. Synergistic relationships consistently existed between ecosystem services in urban agglomerations. The findings contributed to enhancing the effectiveness of ecosystem services in Chinese urban agglomerations and provided support for formulating management measures and policy interventions.

The Yangtze River Basin is an important ecological barrier in China. Understanding the response of the NDVI to climate change during the growing season is important for the effective implementation of ecological and environmental protection strategies. In this study, on the basis of MODIS NDVI data and meteorological data from 2000 to 2020, the response of the NDVI to diurnal temperature and precipitation changes during the growing season was studied through trend analysis, partial correlation analysis and GIS spatial statistical analysis methods. The results revealed the following: from 2000~2020, the growing season NDVI exhibited a fluctuating increasing trend in the Yangtze River Basin, with a growth rate of 0.021/10a. The NDVI exhibited an increasing trend in all subbasins except for Taihu Lake. The overall NDVI exhibited an increasing trend, accounting for 84.19% of the study area, and all subbasins exhibited increasing trends, with the exception of the Taihu Basin, which showed a decreasing trend (60%). (2) During the growing season, Tmax, Tmin and precipitation showed insignificant upward trends, and the increase rate of Tmin was approximately 1.55 times that of Tmax, indicating asymmetric diurnal warming. At the subbasin scale, the change trend was similar to that in the study area except for the Jinsha River Basin. Spatially, Tmax, Tmin and precipitation showed increasing trends, with proportions ranging from 68% to 79%, especially in the Taihu and Wujiang River Basins. The responses of the NDVI to Tmax, Tmin and precipitation during the growing season exhibited spatial heterogeneity, and the range of vegetation growth significantly affected by Tmin and precipitation was greater than that affected by Tmax. The average lag times of the responses of the NDVI to Tmax, Tmin and precipitation during the growing season were 1.6, 1.3 and 1.4 months, respectively. The response characteristics differed across subbasins and vegetation types.

This study focuses on the Chang-Zhu-Tanurban agglomeration as the research area. It integrates the analytical strengths of Morphological Spatial Pattern Analysis (MSPA) in landscape spatial structure with the quantitative assessment capabilities of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for ecosystem service functions to analyze the evolution of the urban agglomeration's ecological network, which holds significant value for safeguarding regional ecological security. Firstly, based on time-series data from three periods (2000, 2010, and 2020), ecological sources within the Chang-Zhu-Tan urban agglomeration were identified. This involved calculating the levels of four key ecosystem service functions-water yield, carbonstorage, soil retention, and habitat quality-and combining these results with MSPA. Subsequently, ecological corridors were extracted using circuit theory to construct the regional ecological network of the Chang-Zhu-Tan urban agglomeration, and its spatiotemporal evolution characteristics were analyzed. The results indicate that:Ecological sources exhibited a continuous expansion trend in scale from 2000 to 2020, with their coverage area increasing from 5855.53km² to 5898.43km². Their spatial distribution density displayed significant heterogeneity, characterized by "high aggregation in the eastern and southern regions and low density in the central region". The number of ecological corridors decreased from 119 in 2000 to 114 in 2020. The total corridor length initially increased from 1604.16km to 1689.22km, then fluctuated and decreased to 1573.28km. Spatially, the corridors exhibited a pattern of "sparser in the center and denser on the periphery". Ecological pinch points (critical areas) and barrier restoration areas were highly concentrated spatially near the corridors. Among these, the number of ecological pinch points showed a trend of initial increase followed by decrease, while ecological barrier points exhibited a continuous expansion trend.

Taking the Beibu gulf urban agglomeration in Guangxi as an example, this paper uses InVEST model evaluation method, afforestation space suitability evaluation method and ArcGIS overlay analysis method to quantitatively analyze the land use type status, habitat quality level and habitat degradation degree of the study area, as well as the scale of suitable afforestation land for planning, and accurately identify the priority area and general area of land greening space according to the classification of habitat quality. The results show that: The main land use types in the study area are forest land and cultivated land, accounting for 87.56% of the total area. In 2020, the average habitat quality index in the study area was 0.3930. The area of medium, good and excellent habitat quality accounted for 44.34%, and the area of poor and poor habitat quality accounted for 55.66%. The average value of habitat degradation index was 0.3199, and the habitat degradation was a more serious grade. The overall status of habitat quality in the study area belongs to the medium deviation level. The number of planning patches suitable for afforestation and greening space use control is 48967, and the planning area is 30091hm². The priority area of ecological construction and land greening in the study area is 24276hm², and the general area is 5815hm². The evaluation and delineation of suitable space for afforestation and greening involves multi-dimensional driving forces such as policies and regulations, ecological needs, scientific and technological support, economic society, international responsibility and public participation, and the comprehensive driving effect is significant. By evaluating and delimiting the space suitable for afforestation and greening land in urban agglomerations and incorporating it into the 'one map' of land and space planning for refined use control, and implementing the integrated comprehensive monitoring of urban and rural greening space 'sky and land', it is helpful to solve the problem of land use for ecological construction projects in urban agglomerations in China and the short board of information management of 'afforestation and greening landing map', so as to provide support for the ecological construction of urban agglomerations to achieve' legal compliance, precise implementation and intelligent management'.

To accurately characterize the impact on DNAPL contaminant migration under the background of groundwater level rise in the coastal areas of North China in recent years, a case study was conducted at a NAPL contaminated site in Tianjin. Utilizing the multiphase flow numerical model TOUGH/TMVOC, a simulation was constructed to analyse the migration characteristics of DNAPL in both homogeneous and layered heterogeneous media under varying groundwater levels. The focus of the study was on the variation of DNAPL movement above and below the water table interface. The key findings were as follows: the NAPL phase was the primary form in which DNAPL migrates in groundwater. In homogeneous saturated media, DNAPL migration exhibited both vertical infiltration and horizontal diffusion. In the unsaturated-saturated aquifer system, a significant increase in DNAPL saturation was observed below the water table interface, with an increase of 47.5% compared to the initial leakage stage. Under water level recovery conditions, the phenomena of sudden increases in DNAPL saturation and vertical migration of contaminants were weakened, with the extension rate decreasing by 1.5~1.8 times compared to low water levels; simultaneously, the phase change of dissolved components to gaseous state was inhibited, resulting in reduced amount of gas phase DNAPL. The dynamic changes in the water table, in conjunction with the layered heterogeneous stratum structure, jointly regulated the DNAPL migration process. Low-permeability layers impeded DNAPL migration. Although DNAPL saturation increased after crossing the water table, its maximum saturation still decreased by 6%~7% compared to the saturated conditions, and the mass of contaminants decreased by 13%~15%. It is recommended to implement contaminant interception when DNAPL reached minimum saturation near the water table to improve remediation efficiency.

In this study, we collected soil samples from the freshwater Phragmites australis marsh at the Minjiang River estuary and constructed wetland soils with different salinities of 0‰, 2.5‰, 11‰, and 22‰ by adding artificial seawater and stabilizing for three months. These salinity values correspond to the ranges of fresh, oligohaline, mesohaline, and polyhaline water zones in estuarine tidal wetlands, respectively. We conducted indoor microcosm anaerobic incubation experiments and meanwhile added ammonium and nitrate to determine role of salinity in the impact of nitrogen additions on CH₄ and CO₂ production in estuarine tidal marsh soils. The results showed that the salinity and nitrogen form had significant effects on the activities of BG, CBH, NAG, PHO, PEO, and mcrA, the addition of ammonium and nitrate significantly increased activities of CBH, NAG, and mcrA in the soils with different salinities. Ammonium addition significantly increased CH₄ production rates in the fresh, oligohaline, and mesohaline water marsh soils by 21.9%, 23.6%, and 40.4%, respectively, but had no significant effect on polyhaline soil. Nitrate addition decreased CH₄production rates in the fresh, oligohaline, and mesohaline soils by 16.56%、15.56% and 19.28%, respectively, although the drop were not significant (P>0.05), nitrate addition significantly reduced CH₄production rates in polyhaline soil by 19.7%. Both ammonium and nitrate addition significantly increased CO₂ production rates in oligohaline and mesohaline soil, while did not significantly change the CO₂ production rates in the fresh and polyhaline soil. Under the nitrogen addition, the production rates of CH₄ and CO₂ were significantly positively correlated with soil pH, extracellular enzyme activities, and mcrA abundance, and significantly negatively correlated with salinity, SOC, Cl^-, and SO₄^2-. The results of random forest model prediction showed that under nitrogen addition scenarios, salinity, NAG, SO₄^2-, and pH had the greatest contribution rates to the production rates of CH₄ and CO₂. Our results indicate that the impact of nitrogen input on CH₄ and CO₂ production rates of estuarine marsh soils varies with salinity. In future, we should consider the influence of salinity gradients when making the strategies and measures to mitigate impact of eutrophication on greenhouse gas emission.

This study attempted to clarify the effects of microbial inoculants combined with sheep manure on species composition, community diversity, and functional structure of soil fungi in a moderately degraded alpine meadow in the source region of "Three Rivers". The changes in plant community and soil fungal community characteristics in the meadow after fertilization with both microbial agents and sheep manure were analyzed using high-throughput sequencing, correlation analysis, and FUNGuild function prediction techniques. The results showed that: Aboveground biomass, underground biomass, coverage and Shannon-Wiener diversity index of the plant community were significantly increased compared with the control (Y0K0). The YK1 (sheep manure: 1500kg/hm², microbial inoculum: 250kg/hm²), Y2K1 (sheep manure: 3000kg/hm²). Microbial agent: 250kg/hm²), and Y3K1treatment (sheep manure: 6000kg/hm², microbial agent: 250kg/hm²) all significantly improved plant diversity and biomass; Compared with the control, the number of OTU, Shannon index, Ace index, Chao1index and Pielou index of the soil fungal community were significantly increased aftr fertilization with both microbial inoculum and sheep manure, with improved fungal network complexity, and a mostly positively correlated network. Ascomycetes, Mortierella and Basidiomycetes were identified as the key species of the rhizosphere fungi community in the degraded alpine meadow; Redundancy analysis revealed a significant correlation between fungal community structure and soil electrical conductivity in all the 12 treatments (P<0.05). The first and second axes achieved an explanatory rate of 33.46% and 7.74% in characterizing the fungal and plant community structure and soil physical and chemical traits, respectively, and SEC was identified as the main factor driving the change of the rhizosphere fungal community in the degraded alpine meadow; Compared with the control (Y0K0), all fertilization treatments increased the abundance of Unkdown fungi, Endophyte-Litter Saprotroph-Soil Saprotroph-Undefined Saprotroph while reducing Undefined Saprotroph, Animal Pathogen-Dung Saprotroph. Endophyte- Epiphyte- Plant Saprotroph-Wood Saprotropl and Animal Pathogen-Undefined Saprotroph. To sum up, all fertilization treatments using both microbial agents and sheep manure promoted the recovery of soil fungi in the degraded alpine meadow and improved soil fungal flora, with the Y2K1treatment (3000kg sheep manure plus 250kg microbial agents per hectare) being the most effective.

In this study, the soils of Larix gmelini forest after fire in the middle recovery period were selected as the research object. Illumina MiSeq technology and phospholipid fatty acid method (PLFAs) were used to determine and analyze the community composition and diversity of soil bacteria and fungi after different intensities of fire. Random forest regression model and partial least squares structural equation modeling were used to screen key microbial species and evaluate the effects of soil physicochemical properties on microorganisms. The results showed that soil microbial biomass carbon (MBC) and total nitrogen (TN) in the middle recovery period after fire were significantly higher than those in the unburned forest (P<0.05), while moisture content (MC) and soil available potassium (AK) content were significantly reduced (P<0.05); the Shannon index of soil bacteria in low and moderate fire disturbance was significantly reduced (P<0.05), the Shannon index of soil fungi in low and high fire disturbance was significantly increased (P<0.05), there was no significant difference in the content of soil bacterial biomass and total microbial biomass in moderate fire disturbance (P>0.05); the relative abundance of dominant bacterial phyla in soil bacteria in the middle recovery period after fire did not change significantly (P>0.05), the relative abundance of Basidiomycota increased significantly (P<0.05), while Ascomycota decreased significantly (P<0.05); PCoA and PLS-SEM results showed that the Beta diversity of soil microorganisms was significantly different (P=0.001). Fire disturbance significantly changed soil organic carbon (SOC) (-1.27), AK (-0.91) and fungal composition (-0.68), MBC significantly changed bacterial composition (0.29), and SOC content significantly changed bacterial composition (0.77), bacterial biomass (0.86), bacterial diversity (-0.98) and fungal composition (-0.68). The study found that after the fire, the diversity, composition and biomass of soil bacteria and fungi in the cold temperate Larix gmelini forest had not recovered to the state before the fire after the recovery of the mid-term, and SOC was the main influencing factor.

Tris(2-chloroisopropyl) phosphate (TCIPP), a widely present organophosphate flame retardant, poses potential ecological risks due to its persistence and bioactivity in environmental media. However, in China, soil safety thresholds for TCIPP have not yet been established, primarily due to limited toxicity data. In this study, standard toxicity tests were conducted on five terrestrial plants (Brassica pekinensis, Brassica rapa var. chinensis, Triticum aestivum, Cucumis sativus, and Solanum lycopersicum) and one invertebrate species (Eisenia fetida), to evaluate the phytotoxic and ecotoxic effects of TCIPP. By combining our results with literature data, the predicted no-effect concentration (PNEC) of TCIPP in soil was derived, and an ecological risk assessment was conducted for TCIPP in Chinese soils. Results showed that B. pekinensis, B. rapa var. chinensis, and S. lycopersicum exhibited the highest sensitivity (root elongation and/or germination rate) to TCIPP with a no-observed-effect concentration (NOEC) of 80mg/kg, while wheat T. aestivum (germination rate) showed the least sensitivity with a NOEC of 320mg/kg. The growth NOEC for E. fetida was determined to be 1mg/kg. Using the species sensitivity distribution (SSD) method, the calculated PNEC value of TCIPP in soil was 0.035mg/kg. Environmental monitoring data revealed that TCIPP concentrations in soils across different regions of China ranged from 0.01 to 444ng/g. Risk quotient (RQ) analysis indicated that TCIPP poses a high ecological risk in industrial areas (maximum RQ = 12.57), whereas agricultural soil showed relatively low risk.

This study evaluated the environmental pollutant reduction and health benefits of new energy vehicle (NEV) promotion in China from 2019 to 2023 through a vehicle life cycle perspective. The emission factor method was employed to quantify pollutant reduction effects, while exposure-response model was used to analyze health impacts from pollutant concentration changes. Health benefits were monetized using the value of statistical life (VSL) method and disease cost method, with uncertainty assessment through the Monte Carlo simulation. The results showed that: In terms of spatial environmental effects, the emission reduction effects of new energy vehicles showed significant heterogeneity, and the emission reduction effects in coastal regions were better than that in inland regions. In terms of time evolution, the emission reduction of CO₂, NO_x, VOCs and SO₂ increased year by year, though NEVs emitted more PM_2.5 than conventional vehicles. Regional disparities emerged with South Central China achieving maximum CO₂ reduction versus minimal reductions in Northwest China, accompanied by significant inter-regional growth rate variations. East China dominated in VOCs and NO_x reduction, while Northeast China exhibited higher annual growth rates. SO₂ reduction displayed polarization, with some regions experiencing emission increases. PM_2.5 dynamics proved complex, showing emission growth in certain regions. Vehicle-type analysis indicated NEV buses outperformed passenger vehicles in reducing PM_2.5, NO_x and SO₂, while passenger vehicles demonstrated advantages in CO₂ and VOCs reduction. Health benefits analysis revealed NEV adoption significantly reduced mortality and morbidity rates, with PM_2.5 mitigation showing particular prominence, and health improvements exhibited annual growth. Monetized health benefits demonstrated sustained growth, with SO₂-related monetary value showing the most significant increase (77.05%) during the study period, though PM_2.5 contributed the largest absolute value. Regional disparities emerged in monetary benefits, with coastal and central regions generating higher economic value compared to western regions.

Based on the 90th percentile of the maximum 8-hour ozone daily sliding average (O₃-8h-90) from 2015 to 2020, exposure risk assessment, health risk assessment, spatial autocorrelation analysis, and correlation analysis methods were used to study the spatialtemporal characteristics of O₃ exposure and health risk in Chinese 337 cities. Moreover, the inequality in provincial exposure and health risk was analyzed using the Gini coefficient, and the two-dimensional partition grade of O₃ exposure-health inequality was established. The results showed that the spatialtemporal characteristics of O₃ exposure risk and premature mortality exhibited similar regional and temporal trends from 2015 to 2020, with hotspot areas highly coincident and primarily concentrated in central and eastern China. The Pearson correlation coefficients between O₃ exposure risk and premature mortality for each year ranged from 0.841 to 0.856, indicating a significant positive correlation, with an increase in exposure risk leading to a rise in premature mortality. The Gini coefficients for O₃ exposure risk (G_e) and health risk (G_h) ranged from 0.1430 to 0.5090 and 0.1020 to 0.5600, respectively, showing a wide range of values, which suggests a significant inequality in the distribution of O₃ exposure and health risks across different regions of the country. The Pearson correlation coefficients between G_e and G_h ranged from 0.563 to 0.728 each year, indicating that inequality in exposure risk significantly exacerbates the uneven distribution of health risk. To further reduce regional disparities in exposure and health risks, the provinces were classified into four categories: "Double Imbalance Zones", "Exposure Dominant Zones", "Health Vulnerable Zones", and "Balanced Development Zones". A zoning governance plan was proposed to provide policy recommendations for precise governance and resource allocation.

This study analyzed agricultural carbon emissions in different cities of Henan Province from 2000 to 2021 by focusing on three indicator categories: land management, grain cultivation, and livestock farming. The analysis of the spatiotemporal evolution trends and patterns of agricultural carbon emissions was conducted using the local Moran I index. Additionally, a random forest model was utilized to determine the primary influencing factors and forecast agricultural carbon emissions in Henan Province across baseline, low-carbon, and high-carbon scenarios. The study findings indicated the following key points: agricultural carbon emissions in Henan Province exhibited a fluctuating trend from 2000 to 2021, reaching a peak of 58.4952million tons in 2006 before declining. By 2021, emissions had decreased by 40.60% compared to the peak year. The spatial distribution of agricultural carbon emissions across cities in the province followed a distinct pattern of being higher in the southeast and lower in the northwest. The primary driving factors positively influencing agricultural carbon emissions in Henan Province were the land plowing area, rural population, administrative area, and total agricultural machinery power. Conversely, the urbanization rate had a negative impact on emissions. Agricultural carbon emissions in Henan Province peaked in 2006 and are projected to continue decreasing from 2022 to 2030 under three scenarios. The anticipated reductions range from 22.4155~24.7073 million tons, 22.4567~24.8222 million tons, and 22.401~24.5974 million tons, respectively, compared to the peak level. These findings offer valuable insights for developing future strategies for reducing agricultural carbon emissions in different cities within Henan Province, thereby contributing to the attainment of the "dual carbon" objectives.

With the rapid growth of global agricultural trade, agriculture has become one of the key sectors of dioxide carbon (CO₂) emission embodied in trade. However, few studies have focused on the transfer of virtual CO₂ emission embodied in global agricultural trade and its driving factors. This study quantitatively estimated CO₂ emissions embodied in agricultural trade for 141 countries and regions worldwide in 2004, 2007, 2011, and 2014, by using the multi-regional input-output (MRIO) model and the GTAP 10 database. The production-based and consumption-based CO₂ emission of the global agricultural sector and virtual CO₂ transfer pathways associated with global agricultural trade were investigated. In addition, the structural decomposition analysis (SDA) method was used to analyze the impact of major driving factors on the CO₂ emissions embodied in global agricultural trade. The results show that the regions with highest production-based CO₂ emissions were the major agricultural producers in the world, including China, the United States, and Latin America. The regions with highest consumption-based CO₂ emissions were the predominantly major agricultural consumers, including China, the United States and the Middle East and North Africa. The meat sector exhibited the largest production-based and consumption-based CO₂ emissions in the six agricultural sectors. The energy sector was the largest contributor to CO₂ emissions due to final demand from the agricultural sector, accounting for more than 40% of total CO₂ emissions induced by agricultural sector. The regions with the net CO₂ outflow embodied in the agricultural trade were the Latin America and the United States, while the Western Europe, China and the Middle East and North Africa were the net CO₂ inflow regions. The input-output structure, final demand structure, and final demand scale are the key drivers that lead to the growth of virtual CO₂ emissions embodied in global agricultural trade, leading to increase of 459.6Mt CO₂ emissions embodied in agricultural trade over the past decade. The final demand scale was the largest driver factors, accounting for 87.8% of total growth of virtual CO₂ emissions. The reduction in global CO₂ emission intensity has served as the predominant inhibiting factor for embodied carbon emissions in agricultural trade, resulting in a decrease of 458.4Mt in CO₂ emissions over the past decade. The results can provide data support and policy recommendations for reducing CO₂ emissions embodied in global agricultural trade from a demand-oriented perspective.

The per capita carbon emissions(PCCE) of energy consumption in 182 county-level districts in Northeast China were measured in this paper. The spatio-temporal change of the PCCE from 2000 to 2020 were analyzed by using kernel density estimation, spatial autocorrelation analysis and Theil index and its influencing factors were discussed by panel data model, which provides a basis for determining carbon emission reduction targets and refining policy design. The results were as follows: The in county-level districts has shown a sustained growth trend since 2000. The growth rate in the first 10 years was faster than that in the second 10 years. Agricultural counties experienced faster growth than forestry counties, whereas urban core districts experienced the slowest growth. A significant spatial positive correlation was observed among county-level districts, exhibiting an overall south-north gradient with higher values in the southern regions and lower values in the northern areas. The relative difference of PCCE among county-level districts gradually decreased, and the differences among prefecture-level districts constituted the main factors behind the reduction in total differences, whereas total differences were mainly manifested as the differences among counties. Economic growth and population quality had significant effects on all types of counties, with economic growth being the primary promoting factor to PCCE. Improving population quality had contributed to PCCE reductions, except in forestry counties. Consumption and population size also had important effects on the regional overall, urban core, and agricultural counties, with consumption contributing to carbon emissions, population shrinkage in the regional overall and in agricultural counties, and population growth in urban core districts suppressing carbon emissions. Urbanization promoted regional carbon emissions overall, but it suppressed emissions in forest counties. Higher technological development and population aging contributed to carbon emissions, albeit to a lesser extent. Environmental regulation had no effect on all county-level districts. To realize carbon emission reduction, it is necessary to strengthen the development of low-carbon industries, enhance the effectiveness of scientific and technological personnel, promote the management of population shrinkage and aging, advocate a low-carbon life and take a county-specific and multi-pronged approach.