In this study, nighttime light intensity was adopted as a proxy for economic activity, and a random forest model was constructed to integrate both anthropogenic and meteorological factors for O₃ concentration prediction. Panel data from the Beijing-Tianjin-Hebei region and surrounding areas (the "2+26" cities) during 2014~2022 were employed to empirically examine the differential contributions of economic activity intensity across various temporal scales, spatial regions, and pollutant types. The findings showed that:①economic activity intensity consistently exhibited significant predictive power across different temporal scales. On the annual scale, its importance reached 0.7053, surpassing all meteorological variables and becoming the dominant predictor. In contrast, on the daily scale, temperature and other meteorological factors were found to be more influential, with the contribution of economic activity reduced to 0.0869. ②Marked spatial heterogeneity was observed between high- and low- O₃ concentration areas. Temperature and economic activity had stronger impacts in high- O₃ regions, while low-concentration regions displayed irregular and spatially discontinuous patterns of predictor relevance. ③ Over long time horizons, economic activity was identified as a decisive factor in explaining both PM_2.5 and O₃ concentrations. However, on shorter time scales, although economic activity was the second most important factor for PM_2.5 prediction after temperature, its contribution to O₃ prediction remained relatively limited.

This study investigates the relative contributions of anthropogenic and meteorological factors to ozone (O₃) variations in major cities on the northern slope of the Tianshan Mountains (Urumqi, Changji, Shihezi, Wujiaqu) from 2018 to 2023 using a stepwise multiple linear regression (MLR) model. Based on OMI satellite data (HCHO and NO₂ tropospheric column concentrations) and ground-based observation data (O₃ and NO₂), the fractional nucleation rate (FNR) threshold for the northern slope of the Tianshan Mountains was determined. The study highlights regional differences, seasonal patterns, and variations in the sensitivity of precursor substances. The results indicate that O₃ on the northern slope of the Tianshan Mountains generally exhibited a fluctuating upward trend, with an annual average concentration of 86.97μg/m³, and the O₃ concentration in the warm season (107.63μg/m³) was higher than that in the cold season (66.31μg/m³). The O₃ concentration decreased to its lowest level (86.71μg/m³) in 2020 attributed to the decreased emissions resulting from the pandemic. The annual growth rates varied significantly among the cities, with Changji at 3.87μg/(m³·a) and Shihezi at 1.51μg/(m³·a). Meteorological factors have a significant impact on O₃ concentration variations, with temperature and humidity as key factors. The contribution rates of meteorological factors in Urumqi and Wujiaqu were higher (50% and 60%, respectively), while those in Changji and Shihezi were lower (29% and 44%, respectively). The NO₂ column concentration showed a downward trend (annual decrease rate of 0.22 × 10¹⁵ molec/(cm²·a)), while the HCHO column concentration remained relatively stable, indicating that VOCs emissions may have increased. FNR analysis indicates that the ozone formation sensitivity (OFS) threshold was as follows: when FNR < 1.75, ozone formation was controlled by VOCs; when FNR > 3.67, ozone formation was controlled by NO_x; and when 1.75 < FNR < 3.67, it is in a transitional state. During the warm season (April to September), the sensitivity of O₃ photochemical production was mainly controlled by NO_x. This study reveals the spatiotemporal variation characteristics of O₃ formation and precursor sensitivities in the northern slope area of the Tianshan Mountains, providing scientific guidance for the development of more precise O₃ pollution control strategies.

This study investigated the characteristics of O₃ and its precursors in Dongguan during the autumns of 2018 and 2022. By integrating observational data, backward trajectory analysis, and box model simulations, we examined the changes in O₃ and precursor concentrations, O₃ formation pathways, and the evolution of control regimes during both polluted and clean periods, which provided insights into ozone pollution mitigation. The average O₃ concentration in Dongguan was higher in autumn 2022 than in 2018, whereas both the average concentrations of nitrogen oxides (NO_x) and volatile organic compounds (VOCs) decreased in 2022. Alkanes accounted for the largest proportion of total VOCs (TVOCs) in both autumn periods, while aromatics and alkenes contributed the most to ozone formation potential (OFP). Notably, the contribution of biogenic VOCs (specifically isoprene) to OFP increased from 6.0% in 2018 to 12.1% in 2022. Comparative studies between polluted and clean periods revealed that TVOC concentrations during polluted periods in 2018 (73.7×10^-9) and their growth rates (148.5%) were significantly higher than those in 2022 (26.1×10^-9 and 67.0%), driven primarily by alkanes and aromatics. In 2018, the OFP growth rate of alkanes was highest during the polluted periods, whereas aromatics dominated in 2022. Box model simulations revealed that the enhancement of O₃ formation rates (16.6×10^-9/h) was notably higher in the polluted periods of 2018 than in 2022 (1.8×10^-9/h), mainly due to increased production of RO₂ and HO₂ radicals from high concentrations of alkanes and aromatics. Additionally, the marked decline in TVOC concentrations during the polluted periods of 2022 suggests a shift in O₃ formation from a VOC-limited regime to a transitional regime, highlighting the need for joint control of TVOCs and NO_x. The results of VOCs emission reduction indicated that O₃ was most sensitive to reductions in the top 10 OFP-contributing species, with relative incremental reactivities (RIR) of 0.85%/% in 2018 and 0.81%/% in 2022, which was more effective than reducing alkenes (0.74%/% in 2018 and 0.37%/% in 2022), aromatics (0.44%/% in 2018and 0.49%/% in 2022), and the top 10species with the highest concentrations (0.20%/% in 2018and 0.37%/% in 2022).

To investigate the causes of ozone (O₃) pollution in the Pearl River Delta (PRD) region under non-high-temperature conditions, this study analyzed differences in O₃ pollution characteristics between high-temperature days (daily maximum temperature ≥28℃) and non-high-temperature days (daily maximum temperature <28℃) using air quality and meteorological data from 2015 to 2023. The key findings are as follows: O₃ pollution in the PRD primarily occurred on high-temperature days, yet 17.2% of total polluted cities were observed during non-high-temperature days. High-temperature pollution was concentrated in central and southwestern PRD, while non-high-temperature pollution predominantly occurred in the southwest. Non-high-temperature O₃ pollution typically occurred under conditions of daily maximum temperature (25.0~27.2℃), relative humidity (44.9%~56.8%), and sunshine duration (7.7~9.8h). Compared to high-temperature pollution days, non-high-temperature pollution days exhibited 6.0% lower relative humidity and a more concentrated distribution of sunshine duration in higher intervals. The SHAP method demonstrated that relative humidity is the most influential meteorological factor affecting O₃ concentrations. On high-temperature days and non-high-temperature days, the contribution of relative humidity to the O₃_8h concentration can reach up to 30 and 60μg/m³, respectively. Low relative humidity (<65%) paired with prolonged sunshine duration synergistically promoted O₃ formation, whereas high relative humidity (>65%) combined with reduced sunshine suppressed it. Additionally, the pronounced impact of sunshine duration under non-high-temperature conditions highlights sufficient solar radiation as a prerequisite for O₃ generation. Under non-high-temperature conditions, NO₂ exerts a weaker influence on O₃ concentrations compared to high-temperature days, with its contribution to O₃ concentration variations quantified at approximately 15 μg/m³.

Taking a region in the Hangzhou Bay area of China as an example, this study refined the local anthropogenic emission inventory and incorporated it into the regional air quality model WRF-CMAQ. The source contributions to ozone pollution during a typical month were quantitatively analyzed using the Integrated Source Apportionment Method (ISAM) and the Integrated Reaction Rate (IRR) method within CMAQ. The results showed that ozone pollution in this area was mainly attributed to contributions from outside the region, accounting for 73.3%, while local contributions accounted for 26.7%. However, on pollution days, the local contribution was found to increase to 35.6%. Furthermore, the contributions of different local emission sectors were analyzed, and industrial and transportation emissions were identified as the major anthropogenic sources of local ozone formation, contributing 38.3% and 35.4%, respectively. Based on the source apportionment results and considering the region's actual control policies and reduction potential, a refined emission reduction strategy was designed for 40subcategories of anthropogenic sources. This strategy was implemented as an emission control scenario in the CMAQ model to assess its effectiveness. The results indicated that the refined reduction plan significantly reduced locally formed ozone on pollution days, with a maximum reduction of up to 26.44μg/m³ and an average reduction of 3.5μg/m³, representing 7.1% of the locally produced ozone concentration during the pollution period.

This study utilized a rotor UAV equipped with multi-pollutant sensors to conduct vertical observations of multiple parameters in the Daya Bay District of Huizhou City, Guangdong Province, from October 12 to 18, 2023, during the morning (9:00), afternoon (15:00), and evening (21:00) each day. The results showed that temperature generally decreased with increasing altitude, with temperature inversion observed at 350 meters during certain periods. Relative humidity exhibited an overall increasing trend with height. NO₂ concentrations typically increased with altitude, with significant peaks around 350 meters at specific times. SO₂ concentrations exhibited a general decreasing trend, but significant elevations were also observed around 350meters at certain times, suggesting potential NO₂ and SO₂ pollution transport processes at this altitude. CO concentrations were relatively high at ground level and decreased rapidly with altitude, showing minimal variation above 200meters, indicating that high-altitude CO concentrations were primarily influenced by near-surface emissions and diffusion, with no significant pollution transport processes. PM₁₀ and PM_2.5 concentrations were generally low, with slight variations across altitudes. They tended to be higher in the morning and lower in the afternoon and evening, likely due to residual layer accumulation or overnight particle emissions. Backward trajectory analysis revealed that air masses at 0, 300, and 500meters all passed over the Daya Bay Petrochemical Industrial Park. Air masses at 300meters and 500meters originated from northeastern counties and cities of Guangdong Province from October 12 to 14, and from coastal areas of Guangdong and Fujian Provinces from October 16 to 18, indicating that emissions from the Daya Bay Petrochemical Industrial Park and upwind regions contributed to high-altitude pollutant levels in the Daya Bay area. WRF-CAMx model simulations further identified high-concentration zones of NO₂ and SO₂ upwind of Daya Bay, confirming the existence of high-altitude pollutant transport pathways. The vertical profile characteristics obtained from UAV observations provide valuable insights into the transport patterns of atmospheric pollutants at high altitudes, offering support for regional air quality impact studies.

To investigate the pollution characteristics and driving mechanisms of atmospheric gaseous nitric acid (HNO₃) in Shenzhen, this study conducted HNO₃ measurements during summer 2023 and winter 2024 using iodide ion chemical ionization time-of-flight mass spectrometry (I-CIMS), combined with machine learning for mechanism analysis. The results revealed significantly higher HNO₃ concentrations in winter (0.72±0.19×10^-9) compared to summer (0.09±0.05×10^-9), with distinct diurnal patterns showing daytime peaks. The model demonstrated good performance (R²=0.91), with SHAP analysis identifying temperature as the primary driver governing HNO₃ variation through gas-particle partitioning. Seasonal differences emerged: temperature dominated summer dynamics through thermodynamic control, while chemical processes prevailed in winter. Notably, chloride salts suppressed HNO₃ formation through nitrate displacement, revealing the complex role of chloride depletion in nitrogen cycling. Our findings highlight the priority of NH₃ emission control, which concurrently inhibits total nitrate formation and reduces HNO₃ particle-phase conversion. Special attention should be given to coastal urban nitrogen cycling complexities induced by chloride depletion, providing scientific basis for nitrate pollution mitigation in the Pearl River Delta region.

Based on the observation of particulate matter concentration in Shenzhen from October to December 2022, the characteristics and influencing factors of New Particle Formation (NPF) events in autumn and winter in Shenzhen were explored. During the observation period, the average particulate matter concentration on non-NPF days was measured as 1.09×10⁴ #/cm³, and on NPF days, it was measured as 1.57×10⁴ #/cm³. The overall particulate matter concentration on non-NPF days was found to be lower than that on NPF days. The Shenzhen NPF event was characterized by low particle formation rate, low growth rate, and low condensation sink, which were consistent with clean and coastal areas both domestically and internationally. By using the standard of whether the mean condensation concentration during the time before dawn to early morning period was greater than 0.02s^-1, NPF days were further classified into clean and polluted backgrounds. It was observed that the significant increase in boundary layer uplift and wind speed during the daytime created favorable conditions for NPF under polluted backgrounds. Under polluted backgrounds, NPF days were associated with stronger solar radiation compared to clean backgrounds. It was concluded that active photochemical reactions were the main driving force of the autumn and winter NPF events in Shenzhen. High temperatures, strong solar radiation, and low humidity were identified as factors controlling the formation of new particles, while high condensation and low wind speeds were found to control the loss of new particles.

Proposing a novel algorithm for identifying atmospheric pollutant transport pathways by coupling optical flow vectors with movement distance constraints—Farneback-Distance Transmission Path Recognition Algorithm (FBD-TPRA). Based on high spatiotemporal-resolution (2km spatial resolution, 1h temporal resolution) PM_2.5 concentration satellite remote sensing inversion data generated via a one-dimensional deep convolutional neural network (1D-CNN), this algorithm extracts inter-frame motion features of polluted air masses using optical flow and incorporates movement distance constraints to achieve continuous and refined reconstruction of pollutant transport pathways. Validation experiments conducted during three typical air pollution events in Changsha, Hunan Province (January 14, October 12, and October 27, 2024) demonstrate that the transport paths identified by the FBD-TPRA algorithm can reasonably explain the temporal relationships of urban concentration variations (Xiantao-Jingzhou-Yueyang-Changsha, Yueyang-Changde-Yiyang-Changsha, and Yueyang-Yiyang-Changsha). Compared with the widely used HYSPLIT model, the FBD-TPRA achieves strong consistency in net displacement direction(cosine similarity up to 0.99), but differ in path morphology, as reflected by dynamic time warping (DTW) values of 2.99°, 9.58°, and 3.69°, respectively. The study indicates that the FBD-TPRA algorithm enhances the characterization of pollutant transport processes by integrating high-resolution spatiotemporal pollutant concentration data and movement distance constraints, providing a new technical approach for identifying atmospheric pollution transport pathways.

This study systematically analyzed the evolution of winter air quality and pollutant emissions in Lanzhou through integrated multi-source data, including ground-based ambient monitoring, nighttime light observations, and emission inventories. Utilizing radiosonde data from Yuzhong Station, surface meteorological measurements, and ERA5reanalysis, we quantified changes in upper-atmospheric and surface wind fields alongside atmospheric stability via linear trend analysis and Mann-Kendall tests to identify drivers of the post-pandemic pollution rebound. Significant reductions were observed in SO₂, PM_2.5, and PM₁0 concentrations over the past 15 winters, with post-pandemic (2022~2023) levels rebounding by 6.59% (PM_2.5) and 21.14% (PM₁₀) relative to 2019 baselines. Notable declines in primary pollutant emissions since 2000 were documented, demonstrating effective mitigation measures. Deteriorating meteorological dispersion conditions were characterized by a 20-year trend of declining surface wind speed and increasing inversion frequency, with winter valley cold pool intensity in 2022~2023 reaching 1.2 times the historical average. The synergistic effect of weakened near-surface ventilation and enhanced atmospheric stability was identified as the dominant mechanism driving the post-pandemic particulate matter rebound.

This study examined the feasibility of using dispersion model back-calculation to estimate VOCs emissions from storage tanks by monitoring concentrations at breathing vents and downwind locations in an oilfield storage area. Area source and volume source dispersion models were used to back-calculate tank VOCs emissions and compared with flow rate method and petrochemical industry formula calculations. Results showed VOCs concentrations at breathing vents fluctuated significantly (10³~10⁵mg/m³) with high variability. The volume source dispersion model better accounted for microscale flow field characteristics influenced by tank structures, yielding results closer to those from flow rate and petrochemical formula methods. This demonstrates the volume source dispersion model back-calculation method has high applicability and validity for estimating storage tank VOCs emissions.

Based on observational data of carbonaceous aerosols collected in Chengdu from June 15, 2020 to April 15, 2022, this study analyzed the temporal variation characteristics of their concentrations and optical properties, and explored the influence of different pollution processes on carbonaceous aerosol levels. The results show that the diurnal variations of carbonaceous aerosol components exhibited distinct bimodal patterns, primarily influenced by traffic rush hours and the development of the planetary boundary layer. The mass concentrations of total carbon (m_TC), elemental carbon (m_EC), and organic carbon (m_OC) peaked in winter, with average values of 8.8 ± 6.4, 2.8 ± 2.1, and 6.0 ± 4.5 μg/m³, respectively, and were lowest in summer. During winter, the mean values of the mass ratio of OC to EC (m_OC/m_EC:2.8 ± 0.9), the absorption Ångström exponent (α:1.5), and the contribution of brown carbon (BrC) to total absorption at 370nm (P_ErC:34 ± 19%) all reached their seasonal maxima. Statistical analysis of the relationship between carbonaceous aerosol components and pollution levels indicates that air pollution in Chengdu is mainly driven by the accumulation and aging of primary emissions under stagnant meteorological conditions. As pollution becomes more severe, the proportion of primary components in carbonaceous aerosols increases. Firework emissions during the Spring Festival were found to increase the contribution of BrC, while emissions and accumulation from motor vehicles led to an increased contribution of black carbon (BC). The relative contribution of BC can serve as an indicator of primary emission accumulation and subsequent aging processes during pollution events. This study provides valuable data support for expanding the carbonaceous aerosol database in Chengdu and for understanding the formation mechanism of wintertime compound pollution in the region.

Based on the environmental statistics data and departmental survey data of Shaanxi Province in 2022, the emission inventory of atmospheric pollutants and CO₂ of Shaanxi Province in 2022 was established by a combination method of bottom-up and top-down. The results indicate that the total emissions of SO₂, NO_x, CO, VOCs, NH₃, PM₁₀, PM_2.5, BC, OC and CO₂ were 64.0×10³, 31.2×10⁴, 19.3×10⁵, 21.5×10⁴, 34.0×10⁴, 67.9×10⁴, 20.8×10⁴, 11.7×10³, 24.0×10³, 33.1×10⁷ tons, respectively. The primary source of SO₂ was electricity generation and heating supply; the primary source of NO_x and BC was diesel vehicles; the primary source of CO was the iron and steel industry; the primary source of VOCs was the coking industry; the primary source of NH₃ was livestock and poultry farming; the primary source of PM₁₀ and PM_2.5 was the road dust; and the primary source of OC was biomass stoves. Yulin, Xi'an and Weinan were the major cities with SO₂ and PM₁₀ emissions; Yulin, Xi'an and Hancheng were the major cities with PM_2.5 emissions; Xi'an, Yulin and Xianyang were the major cities with NO_x emissions; Xi'an, Yulin and Yan'an were the major cities with VOCs emissions; Hancheng, Yulin and Xi'an were the major cities with CO emissions; Yulin, Weinan and Baoji were the major cities with NH₃ emissions; Yulin, Xi'an and Xianyang were the major cities with BC emissions; Yulin, Xi'an and Weinan were the major cities with OC emissions. On this basis, the pollution and carbon reduction effects of air pollutants and CO₂ emission reduction measures were analyzed, and it was found that the cleanification of civil energy, the electricity generation of cleaner power energyin power plants and the renovation of coal-fired boilers all have pollution and carbon reduction effects,while the electricity generation of cleaner power energyin power plants have the highest synergistic effect.

Taking the well-structured rod-like SBA-15 as support, Pd₁Co_x/SBA-15 bimetallic catalysts with different palladium(Pd) and cobalt(Co) molar ratios were prepared by adjusting the Co content for acetone (C₃H₆O) catalytic oxidation. Among these, the Pd₁Co₁/SBA-15 catalyst was found to exhibit superior performance for the low-temperature oxidation of C₃H₆O, achieving 90% conversion at 220℃, along with high CO₂ selectivity and thermal stability. Characterization by SEM, XRD, FT-IR, and N₂ adsorption-desorption was conducted, and it was revealed that Pd₁Co₁/SBA-15 possessed the optimal Pd/Co ratio and a higher specific surface area, which were crucial for the stabilization and exposure of active sites. Further investigations using H₂-TPR, O₂-TPD, and XPS indicated that the primary active oxygen species in Pd₁Co_0.5/SBA-15 and Pd₁Co₃/SBA-15 were chemisorbed oxygen, while surface lattice oxygen was predominantly present in Pd₁Co₁/SBA-15. Moreover, the transformation of abundant active oxygen species in Pd₁Co₁/SBA-15 was significantly promoted. The reaction mechanism of acetone oxidation over Pd₁Co₁/SBA-15 was elucidated by in-situ infrared spectroscopy. The decomposition path of acetone molecules over Pd₁Co₁/SBA-15 catalyst was determined as C₃H₆O→CH₃CH₂OH→CH₃COO^-→COO^-→CO₂, which further indicated that enhanced surface lattice oxygen can significantly accelerate activation and cleavage during the acetone oxidation process.

This study investigated the advection and diffusion patterns of hydrogen sulfide (H₂S) in a prototype sewer network of a residential area in Xi'an, using Ventsim to simulate both natural and forced ventilation conditions. The results show that the simulated and measured values are within 10% difference, which confirms the reliability of the Ventsim simulation method. Forced ventilation increased the air velocity in sewer pipes by 8.8% compared to natural ventilation conditions. It was further found that utilizing only an intake or exhaust fan required 108s and 105s, respectively to completely expel hazardous gases from the sewage network. Simultaneous operation of both intake and exhaust fans significantly enhanced the migration rate of harmful gases, reducing the expulsion time to 55s. Nevertheless, using only an intake fan may cause H₂S to escape through small openings on manhole covers. These findings provide technical support for predicting and controlling hazardous gases within sanitary sewer networks, contributing to infrastructure safety and operational maintenance.

Cr (VI) typically exists as a negatively charged anion, whereas Cr (III) is positively charged as a cation. The positively charged Cr (III) obtained through the reduction of Cr (VI) can further adsorb Cr (VI), thereby enabling cyclic adsorption and enrichment of chromium species. In this study, polypyrrole (PPy) was dispersed in chitosan/polyethyleneimine (CS/PEI) hydrogel network to prepare a composite aerogel named CS/PPy/PEI. The composition and structure of CS/PPy/PEI were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), Zeta potential and UV-vis-NIR spectroscopy. Based on the valence transformation of Cr (VI)/Cr (III), the cyclic enrichment process of Cr (VI) adsorption-photoreduction-immobilization-re-adsorption is established in CS/PPy/PEI aerogel. The results showed that the introduction of ascorbic acid as a co-catalyst during the photocatalytic reduction process could further enhance the enrichment of chromium by CS/PPy/PEI, and the adsorption capacity of CS/PPy/PEI could reach 279.69mg/g after 6cycles of enrichment. Since CS/PPy/PEI aerogels do not contain any other metals, high-purity chromium can be effectively recovered through simple calcination.

This study addresses challenges in conventional advanced oxidation processes (AOPs), including mass transfer limitations of endogenous mediators, and reliance on energy-intensive/sacrificial agents' consumption to maintain the catalytic activity, by proposing an innovative strategy that employs trace H₂O₂ to micro-regulate dual-reaction center (DRC) catalysts for enhanced water self-purification. DRC catalyst (FZSO) with surface electron-polarized distribution can effectively enhance interactions between naturally dissolved oxygen and pollutants, thereby overcomes mass transfer limitations and obviously enhances water self-purification. This process radically changes the role of H₂O₂—innovatively repurposed from the sacrificial agent in AOPs to the precision micro-regulator in DRC system, largely reducing consumption in water treatment. Experimental results demonstrate that under micro-regulation with only 1mmol/L H₂O₂, the FZSO-DRC system achieved complete ciprofloxacin removal within 15min, with less than 10% H₂O₂ consumption. FZSO system also exhibits strong adaptability and stability for complex water matrices (pH or salinity ions). This study proposes a breakthrough in energy-efficient water purification by amplifying natural water self-purification capacity through the FZSO-DRC system, providing new technical perspective for developing high-efficiency, low-consumption water treatment processes.

To efficiently remove Cd (II) from water, this study prepared a novel adsorbent by compositing hydrochloric acid-activated attapulgite with hydrochar and in-situ loading iron-manganese bimetallic oxides. The material was characterized by SEM-EDS, XPS, XRD, FTIR, and BET, revealing the synergistic chemisorption of Cd (II) by iron-manganese oxides and functional groups such as hydroxyl and carboxyl groups. The optimally proportioned adsorbent exhibited a maximum Cd (II) adsorption capacity of 66.8mg/g. The adsorption process followed pseudo-second-order kinetics and the Langmuir model, indicating predominantly monolayer chemisorption. After five adsorption-desorption cycles, the material retained approximately 75% of its initial adsorption capacity, demonstrating excellent regeneration performance. These experimental results provide a reliable technical basis for low-cost, highly efficient, and reusable remediation of heavy metals in water bodies.

This study investigated the removal effectiveness and mechanism of mixed surfactant solutions composed of sodium dodecyl sulfate (SDS) and polyethylene glycol octylphenyl ether (TX100) on trichloroethylene (TCE) contamination through column and three-dimensional sand tank experiments, combined with electrical resistivity tomography (ERT). The column experiments revealed a significant synergistic effect of surfactant concentration and mixing ratio on TCE removal. When the mixing ratio α was 0.9, all tested concentrations exhibited optimal removal performance, with the 3.0g/L solution showing the highest resistivity change percentage (91.37%), followed by 1.5g/L (87.07%) and 0.5g/L (81.25%). Resistivity monitoring indicated that most TCE removal occurred during the first pore volume (pv) of surfactant injection, after which the resistivity stabilized, suggesting the completion of the removal process. In the sand tank experiments, the resistivity difference in the TCE-contaminated region increased from an initial value of approximately 60 Ω·m to 120~140 Ω·m during TCE injection, reflecting the accumulation of contaminants. After water injection, the resistivity difference decreased to 30~60 Ω·m with a localized rebound to 80~140 Ω·m, indicating dilution and redistribution of the contaminant. Following the injection of the mixed surfactant solution (3.0g/L, α = 0.9), the resistivity difference in the contaminated area significantly decreased to the initial range (approximately 20~60 Ω·m), demonstrating a remarkable removal effect. ERT effectively visualized the contaminant removal process in real time, revealing spatial distribution changes of TCE across different depths and cross-sections. This non-invasive, real-time, and three-dimensional monitoring approach highlights the unique advantages of ERT in tracking and evaluating contaminant remediation processes.

This study addresses the challenge of low-temperature nitrogen removal in the anaerobic ammonium oxidation (ANAMMOX) process. By using cold shock, the nitrogen removal performance of immobilized ANAMMOX particles (R3) at various low temperatures was successfully improved. The results showed that, at the low temperatures ranging from 23℃ to 6℃, the nitrogen removal efficiency of R3 particles was significantly higher than that of non-cold-shocked immobilized particles (R2) and non-immobilized ANAMMOX sludge (R1), with the advantage being especially pronounced at 12 and 6℃. The higher specific ANAMMOX activity (SAA) and biomass concentration (MLVSS) of R3 particles were key factors in maintaining efficient nitrogen removal at low temperatures. At 12 and 6℃, the SAA of R3 was 20~22 times higher than that of R1 and 12~14 times higher than R2; the MLVSS of R3 reached as high as 6059~4732mg/L. This was attributed to the fact that cold shock improved the metabolic proliferation of functional bacteria, extracellular polymeric substance (EPS) regulation, and the secondary structure of proteins (PN) in EPS. Notably, the relative abundance of Candidatus Brocadia in R3 was significantly increased, enabling it to maintain activity at extremely low temperatures. Additionally, the increase in the abundance of ANAMMOX genera and cold-tolerant bacterial genera within the particles facilitated the regulation of EPS secretion and improved bioaggregation. This study provides an effective approach for promoting the low-temperature application of the ANAMMOX process.

This study employed a partial denitrification-Anammox biofilm system (PDA-Bf) to treat simulated municipal wastewater, with a focus on exploring its nitrogen removal performance under mesophilic conditions (34℃). After 317 days of operation, the results indicated that under an influent carbon-to-nitrogen ratio (C/N) of 2.1, the total nitrogen (TN) concentration in the effluent was reduced to 10.94mg/L, with an average TN removal rate of 82.6%. Moreover, the contribution of the Anammox pathway to TN removal significantly increased over time. The study found that the abundances of the denitrifying genus Thauera and the anammox genus Candidatus Brocadia in the biofilm significantly increased with operation time. Thauera increased from 0.37% on day 250 to 4.11% on day 305, and Ca. Brocadia rose from 0.27% to 3.51%. The two genera worked well in synergy. The outer layer of the biofilm had a high abundance of genes encoding nitrate reduction, such as narG (55152hits), narH (35866hits), and narI (16506hits), indicating that this area was suitable for the growth of denitrifying bacteria and provided nitrite for the Anammox reaction. In contrast, the inner layer of the biofilm had a higher abundance of the Anammox-related hdh gene (1174hits), and lower abundances of nitrite reduction genes nirK (13400hits) and nirS (3954hits), maintaining a higher nitrite concentration and creating a suitable environment for Anammox bacteria (AnAOB). This stratified microbial community structure suggests that the outer and inner layers of the biofilm are respectively suitable for the growth of Thauera and Ca. Brocadia, jointly promoting the efficient nitrogen removal performance of the system.

There is the potential for nitrate contamination in the northern karst area. Systematically investigating the spatiotemporal pattern of surface water nitrate and the sources of pollution is extremely important for the timely recognition of the pollution hazard and the accurate location of the sources of pollution. Based on the representative watershed in the northern karst area, the Wuhushan Reservoir Basin, this study carried out evenly distributed sampling on the three main rivers of Jinyangchuan, Jinyunchuan, and Jinxiuchuan. A total of 54surface water samples from 18points along the major streams and primary tributaries were collected in the dry season, normal season, and wet season. By combining hydrochemical analysis, redundancy analysis (RDA), nitrogen and oxygen isotope methods, and the Bayesian isotope mixing model (SIAR), the study outlined the spatiotemporal pattern characteristics of nitrate in the basin's intricately interconnected surface water system and quantitatively estimated the contribution rates of different sources of pollution. The results showed that: ① The hydrochemical conditions in the research area were favorable for nitrification, with low ammonium and nitrite nitrogen contents persistently throughout the three seasons. Average nitrate contents in the dry season were greater than the normal season and wet season. Nitrate contents remained low in the upper reaches of Jinxiuchuan throughout the periods, while the downstream segments (S7-S9) had much higher nitrate contents in the dry season and normal season. Spatial differences in nitrate contents in the wet season narrowed, with relatively high contents at stations X2 and X3 in Jinyangchuan, Y2 and Y3 in Jinyunchuan. ② During the entire course of the three seasonal periods, assimilation and denitrification did not play a dominant role in the nitrate transport and transformation process, with the prevalence of nitrification. ③ During the wet season, nitrate in surface water in the study area came mainly from non-point source pollution, of which soil organic nitrogen was 62.81%. Pollution sources in the normal season were richer in composition, with soil and manure/sanitary sewerage supplying 48.85% and 21.96%, respectively. Sewage from household discharge was the major source in the dry season, which contributed to the surface water nitrate to the extent of 68.03%. These discoveries provide scientific support for the prevention of nitrate pollution and environmental protection of surface water in the northern karst area in China.

Polydimethylsiloxane (PDMS) is widely applied in daily-use products, medical treatment and power industry. In order to achieve its harmless disposal, the microbial green degradation approach was explored, and the pyrolysis characteristics, composition, production mechanism and surface hydrophobicity (CSH) of microbial cell membrane during the degradation process were analyzed. Results demonstrated that CGMCC 0452 strain exhibited strong tolerance to high-viscosity PDMS when polydimethylsiloxane (PDMS) was treated with Pseudomonas aeruginosa strain (CGMCC 0452). With the extension of degradation days, the CSH increased to 16%, and the CO stretching vibration of the carbonyl group in the chemical structure of the rhamnolipid chain was detected at 1712 cm^-1 by Fourier transform infrared spectroscopy. Gel permeation chromatography analysis revealed that the weight-average molecular weight and number-average molecular weight of PDMS decreased by 29130 Da and 21701 Da, respectively. Based on the above results, combined with comprehensive analysis of gas chromatography-mass spectrometry, it was determined that the long chain of polysiloxane was mainly degraded into cyclosiloxane oligomers (D5, D6, D8, D9), and the degradation products did not appear toxic and harmful substances. Finally, the CSH enhancement mechanism (rhamnolipid adsorption and cell membrane lipopolysaccharide loss) and cyclosiloxane oligomer formation mechanism were revealed from the micro level. This paper provides a novel research idea for the efficient and harmless treatment of polysiloxane, and offers a valuable reference for investigating the biodegradation mechanism of polymers.

This study addresses the limitations of traditional landfill groundwater pollution risk prediction methods by integrating high-performance simulation with uncertainty analysis to more accurately capture the effects of concealed leakage. The limitations of high computational load and low efficiency were addressed by combining a Particle Swarm Optimization (PSO) algorithm with an Extreme Gradient Boosting (XGBoost) model. By learning from multiple samples generated by detailed simulation models, a surrogate model was established to improve prediction efficiency. Additionally, an improved sampling method was proposed to reduce the reliance of PSO-XGBoost on sample size. The results indicate that the machine learning surrogate model developed in this study better captures the impact of parameter uncertainty compared to traditional analytical-Monte Carlo methods such as Landsim. The predicted pollution concentration range is 1.36 times greater than that of conventional models. The PSO-XGBoost surrogate model, combined with the improved sampling method, outperforms other machine learning models in prediction accuracy (R²= 0.99) and stability, while reducing the computational time for model training by 70%, significantly improving the efficiency of uncertainty analysis. The application research based on this model shows that the probability of the characteristic pollutant COD exceeding the standard in the 10th year reaches 56.43%, and the possible distance of exceeding the standard is 54meters, indicating that there is a certain pollution risk in the study area. These findings provide an efficient and precise scientific method for analyzing landfill leakage risks and uncertainties and offer valuable references for further related research.

The primary parent material of tropical coral islands was coral sand, which was characterized by significant deficiencies in nitrogen retention capacity, particularly in terms of nitrate nitrogen (NO₃^--N) immobilization efficiency. This limitation was not only jeopardizes the sustainability of freshwater resources on these islands but also compromises the stability of coastal ecosystems. To promote the synergistic development of island-marine ecosystems, this study selected biochar (C), iron-modified biochar (FeC), and magnesium-modified biochar (MgC) were selected as soil amendments. These were combined with the native pioneer plant Ipomoea pes-caprae (P) to establish a collaborative remediation system. Experimental results demonstrated that MgC exhibited optimal NO₃^--N adsorption performance when applied individually, with its adsorption capacity and surface area-based adsorption capacity (SAC) exceeding those of FeC and C by 12.3%~28.6%. However, in plant-combined systems, a more sustained synergistic effect was demonstrated by the FeC-P combination, which maintained over 85% NO₃^--N retention rate throughout the experimental period. In contrast, performance decline was exhibited by the MgC-P system in later stages. Specifically, an 88.7% retention rate was achieved by the FeC-P group on day 40, which was 1.96-fold of the A-P group, 1.17-fold of the C-P group and 1.10-fold of the MgC-P group, respectively. Mechanistic analysis revealed that the electrical conductivity of coral sand was significantly increased by FeC (33.7%), and the proliferation of Patescibacteria was promoted (a 1.8-fold increase in relative abundance was observed), thereby strengthening the system's nitrogen transformation function. This physicochemical-biological synergistic optimization mechanism facilitated beneficial interactions between FeC and Ipomoea pes-caprae. Ultimately, a sustained enhancement of nitrogen retention capacity in coral sand was achieved. A novel technical pathway for the ecological restoration of coral islands was provided by the research outcomes.

Thorough mixing of contaminated soil and stabilizer is essential for effective ex-situ stabilization for heavy metals-contaminated soils. Field tests of ex-situ soil stabilization was conducted, and the total elements, moisture content, and leaching concentrations of target heavy metals (including arsenic(As) and antimony(Sb)) in the stabilized soils were measured. The influence of mixing equipment type, and soil-stabilizer mixing frequency on the ex-situ stabilization efficiency was evaluated. Based on the measured total elemental content and moisture content, a concept termed 'mixing uniformity' was proposed. The results showed the multi-function mixing equipment performed better than screening crushing bucket in controlling the uniformity of stabilizers in the contaminated soil. In contrast, the screening crush bucket significantly improved the uniformity of total As and Sb in the soil, with a larger mixing range. The mixing uniformities of total element content, moisture content, and As and Sb leaching concentrations increased with the number of mixing using the screening crushing bucket. When the number of mixing exceeded three, As and Sb leaching concentrations fell below remediation target values. Additionally, the uniformity of As and Sb leaching concentrations showed a good correlation with the uniformity of total contents. Based on the results, it is recommended that on-site rapid testing of total heavy metal content, combined with uniformity analysis, can be used to evaluate the mixing uniformity of contaminated soil and stabilizers during stabilization processes.

In view of the characteristics of Ultisols (red soils) in southern China, this study developed two types of rice-specific biochar-based fertilizers (BBOF: bio-organic-inorganic biochar-based fertilizer; BBF: inorganic biochar-based fertilizer) using rice straw biochar as the base and coating technology. Pot and field experiments were conducted to evaluate their effects on soil chemical properties, microbial communities and rice yield under different pH value, nutrient statuses, and cadmium (Cd) pollution levels. Conventional fertilizer (CF) was used as the control, with three carbon treatments for experiments: direct biochar application (BC), BBOF, and BBF. The results showed that both BBF and BC improved rice yield under field conditions, with BBF enhancing the three key yield components; however, BBF had limited effects on soil improvement. BBOF and BC significantly increased soil pH and soil organic carbon contents(SOC) in the weakly acidic (WA) soil and the strongly acidic soil (SA) with Cd pollution(P<0.05), demonstrating effective acid regulation and carbon sequestration, but had limited effects in low-nutrient acidic (LN) soils. The impact of carbon treatments on soil nutrients varied with soil type: in WA soils, all three treatments significantly increased available phosphorus (AP), available potassium (AK), and dissolved organic carbon (P<0.05); in SA soil, AK was significantly reduced (P<0.05); and in LN soil, ammonium nitrogen(NH₄⁺-N) and nitrate nitrogen levels were notably altered, with BC also significantly increasing AK content (P<0.05). Other soil properties showed no significant response to biochar treatments. Compared with BC, biochar-based fertilizers reduced the amount of exogenous biochar applied and thereby decreased soil Cd input, indicating higher environmental safety. Microbial community analysis revealed that none of the biochar treatments had significant effects on fungal communities (P>0.05), but all affected bacterial communities, with an impact intensity order of BC>BBOF>BBF and a soil bacterial communities response order of LN>SA>WA. Both BC and BBOF regulated bacterial communities in a similar way by significantly increasing the relative abundances of key phyla (Myxococcota, Methylomirabilota, and Acidobacteria) and important functional families (Rokubacteriales_unclassified, Anaeromyxobacteraceae, Bradyrhizobiaceae, and Nitrospiraceae), while significantly decreasing the relative abundances of Planctomycetota (phyla level) and Subgroup_7_unclassified and Isosphaeraceae (family level) (P<0.05). Correlation and redundancy analyses indicated that shifts in soil bacterial communities were closely related to changes in soil chemical properties, with different driving factors identified across soils: AP in WA, SOC in SA, and NH₄⁺-N in LN. This suggests that the regulatory effects of carbon treatments are highly soil-dependent. In conclusion, the bio-organic-inorganic biochar-based fertilizer demonstrated advantages in improving soil environmental conditions and regulating microbial communities in rice-growing red soils, showing potential to replace direct application of biochar. However, its yield enhancement effects and application strategies require further study and optimization.

Pyrolysis is an important process for efficient remediation of petroleum-contaminated soil (PCS), but how to reuse the obtained carbonized soil (RCS) has not received enough attention. In this study, RCS was treated by ball milling to activate its environmental catalytic components, and the obtained carbonized soil (RBCS) was used to activate peroxymonosulfate (PMS) oxidation to treat organic wastewater. The results showed that when the dosage of RBCS was 2g/L and the dosage of PMS was 1.5g/L, the removal rate of aniline (AN, 100mg/L) reached 99.9 %. Compared with RCS, ball milling treatment significantly improved the activation performance of RBCS for PMS oxidation. Quenching experiments and EPR tests showed that 、·OH、¹O₂ and environmental permanent free radicals (EPFRs) existed in the RBCS/PMS system. Electrochemical experiments show that there is also an electron transfer mechanism in the RBCS/PMS system. Ball milling exposes more metal oxides, amorphous carbon and oxygen-containing groups on the surface of carbonized soil. Metal oxides and oxygen-containing groups can activate PMS to produce reactive oxygen species to attack AN, while graphitized carbon and EPFRs may promote PMS oxidation by accelerating direct electron transfer to degrade AN. This study provides an environmentally friendly, value-added transformation strategy and treatment method for RCS, which is expected to have a good application prospect.

Representative Sb tailings from the northwest and southwest regions were selected to investigate the migration characteristics of Sb and arsenic (As), as well as changes in microbial community under both covered and exposed conditions. The results showed that the total concentrations of Sb-As in the Qinglong tailings were significantly higher than those in the Xihe soil-covered tailings, with Sb levels being 21.90~29.35 times higher and As levels 20.23~39.26 times higher. The index of Geo-accumulation (I_geo) and the Ratio of secondary phase to primary phase (RSP) indicated that the Qinglong tailings Sb-As contamination index was greater than 3, which belongs to severe contamination, the exposure of Sb-As thus poses a considerable threat to the soil environment. In contrast, the I_geo index for Sb-As in the Xihe soil-covered tailings were both <3, and RSP values was <2, indicating a relatively low level of contamination. Using the Wenzel sequential extraction method, the distribution of Sb-As fractions was found to follow the order: amorphous iron-aluminum oxide-bound fraction (F3)>residual fraction (F5)>crystalline iron-aluminum oxide-bound fraction (F4)>specifically adsorbed fraction (F2)>non-specifically adsorbed fraction (F1). F3 accounted for 36.91% and 37.00% of the total Sb-As contents, respectively. The bioavailable forms of Sb [Sb(Bio)] and As [As (Bio)] were significantly higher in the Qinglong tailings than in the Xihe soil-covered tailings. In Qinglong, Sb-As primarily occurred in the F3fraction, whereas in Xihe, they were mainly associated with the F5fraction. Principal coordinates analysis(PCoA) revealed that bacterial community structure varied across different environmental media. The dominant bacterial phyla in the Qinglong tailings were Chloroflexi and Firmicutes, with Kaistobacter, Pseudomonas, and Rhodoplanes as the predominant genera. In the Xihe soil-covered tailings, Gemmatimonadetes and Bacteroidetes were significant components, and Thiobacillus, Kaistobacter, and Sphingomonas were the dominant genera. Thiobacillus, Pseudomonas, Bacillus, Geobacter, and Sphingomonas were identified as key bacterial taxa enriched in long-term Sb-As contaminated environments, indicating their potential for application in in-situ ecological restoration of Sb tailings. The functional prediction using PICRUSt2 and Partial least squares discriminant analysis(PLS-DA)suggested that bacterial functional changes were primarily characterized by the enrichment of specific metabolic functions, accounting for approximately 40.66% of the total predicted functions. Spearman correlation analysis, Redundancy analysis (RDA), and Random forest (RF) analysis revealed that pH, soil organic matter (SOM), and water content (WAF) were the main drivers of bacterial community changes in the Xihe soil- covered tailings, while Sb-As concentrations and their chemical fractions were the main drivers of bacterial community structure and functional variation in the Qinglong tailings.

This study used Festuca arundinacea (tall fescue) as a pioneer plant for vegetation establishment on tungsten tailings to restore the tailings' soil multifunctionality index (SMF). The results showed that the application of chicken manure and biochar increased the available nitrogen (61.15%~61.48% and 23.55%~24.82%), available phosphorus (116.07%~143.50%), and organic matter content (55.46%~59.80% and 255.36%~263.27%) in the tailings. Chicken manure also increased the activities of urease (95.97%~117.03%), β-glucosidase (97.28%~112.59%), and phosphatase (31.11%~49.35%) in the tailings. These changes led to an increase in the SMF of the tailings, and the SMF was significantly correlated with the planting time of F. arundinacea (R² = 0.4260, P< 0.05). The amendments altered the bacterial community structure, with the community dissimilarity index between treatments increasing from 0.5437 to 0.7696 and then decreasing to 0.3496. The development of the bacterial community in the tailings showed convergence, attributed to the increase in the SMF. Co-occurrence network analysis of OUTs (operational taxonomic units) revealed that after the amendment treatments, the proportion of positively correlated edges decreased from 65.39% to 56.96%~61.85%, which enhanced the competitive relationships between bacteria and increased the complexity and sensitivity of the bacterial network. The structural equation model explained 89.1% of the changes in soil multifunctionality, with the direct effect of the amendments being 0.502. Additionally, indirect effects were generated through their impact on the fresh weight of F. arundinacea, bacterial diversity, and the co-occurrence network of OUTs.

In September 2023, a study was conducted in the Northeastern South China Sea to investigate the concentration distribution and mole composition of total dissolved amino acids (TDAA) in the seawater, as well as the sources and degradation status of dissolved organic matter (DOM). The results showed that the concentration of TDAA ranged from 0.37 to 2.59μmol/L, with an average value of (0.78±0.41) μmol/L. The horizontal distribution of TDAA exhibited a pattern of higher concentrations near the coast and lower concentrations in offshore, while the vertical distribution showed a gradual decrease from the surface to the bottom layer. Using D-alanine (D-Ala) as a biomarker, the contribution of bacterial organic matter to DOM (Bacterial-C%) was quantified. The Bacterial-C% in seawater ranged from 9.6% to 46.2%, with an average value of (23.3±8.1)%, demonstrating an overall trend of lower values near the coast and higher values in offshore areas. Additionally, the mean value of degradation index (DI) in surface seawater was (0.5 ± 1.0), while the average DI values for middle and bottom layers were (-1.2±0.6) and (-1.3±0.6), respectively. This indicates that the DOM in surface seawater was less degraded compared to those in the middle and bottom layers. This study elucidates the sources and degradation status of DOM in the Northeastern South China Sea, providing important scientific insights and data support for a deeper understanding of biogeochemical cycling processes in marginal seas.

Nitrogen and phosphorus concentrations in lakes are indicative indicators of water eutrophication. To explore the impact of nitrogen and phosphorus release from sediments in Hengshui Lake on the evolution of water environment quality, a hydrodynamics-water quality-sediment model of Hengshui Lake was constructed based on the EFDC model. The "source" and "sink" transformation processes of nutrients such as nitrogen and phosphorus at the sediment-water interface and the magnitude of nutrient fluxes were analyzed. Through scenario simulation analysis, the impact of internal nutrient release in Hengshui Lake on lake water quality was evaluated, and the regulatory capacity of lake sediments on water quality under the conditions of large input of external pollutants or implementation of dredging projects was discussed. The results showed that the release fluxes of ammonia nitrogen, nitrate nitrogen and phosphate in the sediments of Hengshui Lake exhibited obvious temporal and spatial variations. During water replenishment, the annual net fluxes of ammonia nitrogen, nitrate nitrogen and phosphate in the Wangkou Gate area increased by 48%, 86% and 75% respectively compared with the average values in the central part of the lake. In the plant area, the annual net deposition flux of ammonia nitrogen was 2.7 times higher than that in the non-plant area in the central part of the lake, and the annual net release flux of phosphate was 3.75 times higher. In the scenario simulation settings, the TN concentration in the water body decreased by 10%~25% when sediments were present compared with when there were no sediments, while the TP concentration increased by 4%~33%, which revealed the risk of internal TP release in Hengshui Lake. When the input of external nutrients increased sharply, a large amount of nutrients were caused to settle into the sediments at the bottom of the lake, and the nutrient content in the sediments tended to reach a new equilibrium state after about 2 years. When dredging was excessive, it took about 3 years for the lake sediments to recover to the dynamic equilibrium state of the lake.

The water environmental capacity of alpine fragile rivers, constrained by hydrological-biogeochemical coupling processes, has long lacked robust quantitative investigations. Herein, we selected specific reaches of the Taohe River as the study area, leveraging the SWAT (Soil and Water Assessment Tool) model to simulate watershed runoff dynamics, and integrating the WASP (Water Analysis Simulation Program) model for analyzing riverine water quality indicators. A coupled SWAT-WASP water quality model was thereby constructed, accompanied by the establishment of a quantitative calculation framework for water environmental capacity, to assess the spatiotemporal patterns of water environmental capacity in the alpine watershed at the northeastern margin of the Qinghai-Tibet Plateau. Model simulations exhibited strong concordance with measured data, with correlation coefficients exceeding 0.6 for water discharge and runoff depth. Under Class Ⅰ water quality standards, the annual water environmental capacities for BOD, TP, and DO were 157.6, 2.067, and 221.8 tons, respectively; in contrast, TN required relaxation to Class Ⅳ standards, yielding an annual capacity of 50.38 tons. Spatially, the water environmental capacities of BOD, TP, and DO in the upstream section accounted for 9.9%~10.3% of those in the downstream, while temporally, their capacities in January (dry season) represented 10.1%~34.2% of those in July (wet season). These findings underscore the dominant roles of hydrodynamic conditions and seasonal hydrological drivers in alpine fragile watersheds, defining the sustainable development thresholds for such systems. With TN identified as the priority control factor, a spatiotemporally coordinated allocation strategy is proposed, offering a scientific foundation for adaptive water quality management in alpine fragile water source regions.

Based on hydrodynamic, water quality, and aquatic ecology models, the ecological flow requirements needed to meet water quality standards, suppress algal blooms, and support fish spawning in the middle and lower Hanjiang River were quantified, and temporally and spatially coupled ecological flow regimes by period, type, and region were proposed. The spatiotemporal coupling indicated that ecological flows at the Huangjiagang, Xiangyang, Huangzhuang, Shayang, and Xiantao sections ranged from 330~904m³/s, 366~1135m³/s, 514~1160m³/s, 632~1236m³/s, and 486~1013m³/s, respectively. From February to April of the subsequent year, ecological flow was governed by algal bloom control requirements; from June to September, it was driven by water quality compliance; and from October to November, it was dictated by fish spawning needs. During the dry season, ecological flow in the midstream region was determined by algal bloom prevention and control, whereas in the downstream section it was determined by fish spawning requirements. During the flood season, ecological flow across the entire middle and lower Hanjiang River was governed by the attainment of water quality standards. This work provided a new perspective for the systematic study of ecological flow in rivers and offered scientific evidence and a theoretical foundation for river ecosystem improvement and related engineering applications.

To explore the status of net anthropogenic phosphorus input (NAPI) and its influencing factors in the Beijing-Tianjin-Hebei region, this study took 13 prefecture-level cities as research units, collected relevant statistical data and NAPI model parameters from 1990 to 2022, analyzed the spatiotemporal characteristics of NAPI and the variation trends of its components over the 33 years, and used redundancy analysis (RDA) to quantitatively reveal the impacts of different types of factors on NAPI and its components. The results showed that:(1) The overall NAPI in the Beijing-Tianjin-Hebei region showed a fluctuating upward trend, with a significant increase from 1990 to 2006 and a slight decrease from 2006 to 2022. The annual average value was 1906kg/(km²·a), which was 5.6times the national level. Phosphorus input from chemical fertilizers was the most important source, with an average annual contribution rate of 54.90%, followed by phosphorus input from food and feed, with an average annual contribution rate of 41.18%. Affected by terrain, the spatial distribution of NAPI showed a trend of gradually decreasing from south to north. Handan City had the highest NAPI value, accounting for 15.76% of the entire study area, while Chengde City had the lowest NAPI value, accounting for 1.52%. The average uncertainty range of NAPI from 2018 to 2022 was -14.81% to 14.56%. (2) The order of influence of different factors on NAPI and its components was: land use factors > economic factors > social factors, and the combined explanatory rate of the three types of factors was 81.77%. Among them, NAPI and its components were only negatively correlated with the proportion of forest and grassland areas, and positively correlated with other influencing factors. Among the indicators, the proportion of construction land area had the highest individual explanatory rate of 45.70%, and had the strongest positive correlation with food/feed phosphorus and non-food phosphorus, making it the most critical factor affecting NAPI and its components. The increase in the proportion of construction land area is often accompanied by intense human activities, such as the increase in food consumption and detergent use. Therefore, the positive impact of the proportion of construction land on food/feed phosphorus and non-food phosphorus leads to its highest individual explanatory rate.

This study conducted field research in the summer and autumn seasons of 2023 and 2024 at a typical drainage ditch in the Yihe Canal, Hetao Irrigation District. Water quality samples (TN, TP, EC, pH) and UAV multispectral reflectance data were collected to build an inversion model based on statistical regression (SR) and extreme gradient boosting (XGBoost), exploring the correlation between water quality parameters and spectral indices for high-precision inversion. The results indicate that the SR-XGBoost model achieved average R² values of 0.872 and 0.880 in the training and validation sets, respectively, with RRMSE values of 3.46% and 3.23%, significantly outperforming single-band and other combined models. The autumn model exhibited better fitting performance than the summer model, with an average R² increase of 11.50% and an average RRMSE reduction of 1.76%. Spatial distribution results show that pollutant concentrations are higher upstream of the drainage ditch than downstream, with higher concentrations in summer than in autumn and more significant distribution differences. This study reveals the correlation between water quality parameters and spectral indices, validates the high accuracy and stability of the SR-XGBoost model, and provides scientific evidence for applying multispectral remote sensing technology in water quality monitoring.

Based on the Biome-BGC ecological process model, the spatial and temporal dynamics of carbon and water flux, water use efficiency (WUE), and its driving factors in the past 24 years were simulated and analyzed, and the soil moisture vegetation carrying capacity of different stands was estimated. The carbon and water fluxes increased year by year, and the average annual growth rates of GPP and ET were 6.42g C/m² and 5.45kg H₂O/m², respectively. WUE decreased by 0.006g C/kg H₂O, showing a trend of carbon efficiency and water consumption imbalance. Interspecific competition significantly affected the dynamic stability of WUE. The shrub pure forest showed stronger adaptability in the carbon and water regulation relationship. The increase of CO₂ concentration was the main driving factor leading to the decrease of WUE, and had a significant indirect effect through temperature (indirect path coefficient 0.435) and NDVI (indirect path coefficient 0.808). Moderate regulation of stand structure and surface vegetation coverage can effectively improve regional WUE. The results of soil moisture vegetation carrying capacity showed that there was still room for improvement in the current planting density of arbor forest, shrub forest and shrub-shrub mixed forest, which could be increased by 15.07%, 3.78% and 16.72%, respectively. The study is helpful to clarify the water use mechanism of different vegetation types in arid and semi-arid areas, define the ecological limits of vegetation restoration projects under the constraints of water resources, and provide theoretical support and decision-making basis for regional 'planting by water' policy formulation and sustainable management of sandy ecosystem.

Trichloroethylene (TCE), a common chlorinated hydrocarbon and volatile organic compound (VOC), poses significant risks to environmental and human health. Its volatilization and diffusion in fractured porous media are complex and difficult to characterize. The volatilization behavior of TCE at the air-soil interface of complex dual media remains poorly understood experimentally. Simulation experiments of NAPL-phase TCE leakage in dual-media systems, combined with finite difference numerical technique, were used to qualitatively assess the influences of fracture and pore structure geometry on TCE volatilization and diffusion. The diffusional fluxes of TCE volatizedfrom the aqueous phase, calculated using effective diffusion coefficients (D_e) obtained from four empiricalandsemi-empirical models, werecompared. In addition, the contribution of volatilization fluxes of TCE from the non-aqueous phase liquid (NAPL)was also analyzed. We find the volatilization flux of TCE at the air-soil interface of the complex structure P5F3 constructed with permeable blocks made of 3~5mm gravel (P5) and a 3mm-aperture vertical fracture (F3) was lower than thatof structure P3F1. Comparison the TCE diffusional flux volatilized from the aqueous phase at the air-soil interface over the upstream-source, source, and downstream-source regions, thehighest vapor flux was estimated overfracture region, followed by the downstream-source region, with the upstream-source region showing the lowest flux. TCE vapor diffusional flux from aqueous phaseoverfracture region accounts for 3% and 5% of the total fluxover entire regionwhenthe ratio of fracture width to permeable block length is 1:150 and 1:50, respectively. The interface diffusional fluxbased on D_e from the Bartelt-Hunt model is the largest, while that from the Currie model is the smallest. The amount of vapor TCE volatized from Napl-phaseis significantly greater than that fromaqueous phase, the former may account for more than 78% of total gas-phase TCE, based on the discrepancy between the gas-phase TCE concentration measured under the sealed air chamber in the lab and the value estimated numerically from the aqueous phase alone.

To assess the habitat quality of wild Chinese giant salamanders (Andrias davidianus) and promote the conservation of their conservation, a survey on the community structure and driving factors of macroinvertebrates was conducted in May 2023 in the Guangdong Liannan Giant Salamander Provincial Nature Reserve. The results indicated that streams in the reserve maintained a high level of benthic macroinvertebrate biodiversity, with 180 species, belonging to six phyla, seven classes, 16orders, 71 families, and 167 genera recorded across 32 sampling sites. Among them, aquatic insects accounted for 94.6% (172species) of the total species richness. The dominant species included Cheumatopsyche sp. (12.1%), Hydropsyche sp. (11.6%), Togoperla sp. (6.7%), Baetis sp. (6.0%), and Stenopsyche sp. (5.5%), which all belong to the orders Ephemeroptera, Plecoptera, and Trichoptera (EPT). A comparison of sampling sites in three regions—Wankeng River, Sanjiachong River (upstream, located in the core area), and Paiduhou River (downstream, in the experimental area)—revealed no significant differences in benthic invertebrate species richness, density, Simpson index, Shannon index, and Pielou's evenness index. The community composition was also similar across the three regions, with EPT and Diptera (sensitive taxa) being the dominant groups. The nMDS ordination plot showed substantial overlap among the three regions. Redundancy analysis (RDA) indicated that key environmental factors influencing the benthic community included altitude, dissolved oxygen, and substrate type, while key spatial factors included 12PCNM variables representing large- (PCNM axes 1, 3, 4, 6~8), medium- (10, 12, 13, 15), and small-scale (23, 28) spatial patterns. Variation partitioning analysis (VPA) showed that environmental factors alone explained 4.7% of the community variation, spatial factors alone explained 5.0%, and their combined effect explained 8.4%, indicating that environmental and spatial factors contributed similarly to the variation in benthic communities. Overall, the stream habitats in both the core and experimental zones of the Liannan giant salamander reserve were in excellent condition, with clean water and high benthic diversity, although the habitat quality in the experimental zone was slightly inferior to that of the core zone. The high-quality stream habitats and rich benthic biodiversity provide favorable conditions for the survival and reproduction of the giant salamander. In the future, long-term monitoring and management of the stream ecosystems in the reserve should be strengthened to continuously improve the habitat quality for wild giant salamanders and provide scientific support for the stability and recovery of their populations.

A strain of polycyclic aromatic hydrocarbons (PAHs) degrading bacteria, QYQ-1, was isolated from the sediments of the Jialing River bed. Through 16S rRNA sequence alignment, calculation of average nucleotide identity, and whole-genome phylogenetic analysis, it was identified as Pseudomonas jessenii. The strain QYQ-1 exhibits a wide adaptive range for temperature (15~40℃) and pH (5~9), excellent salt tolerance (0.5%~5%), and good heavy metal resistance (Cu²⁺, Zn²⁺, Co²⁺, Mn²⁺, Cd²⁺). It has a unique advantage in withstanding low temperatures (15℃), high salinity (5%), and heavy metals. The optimal degradation conditions are at a temperature of 35℃ and a pH of 7, achieving a degradation rate of 97.7% for 100mg/L naphthalene within 48hours. Additionally, it can efficiently degrade aromatic compounds such as benzoic acid and phenol. Genomic analysis indicates that the strain QYQ-1 possesses various key genes involved in the degradation of multiple PAHs, including a complete pathway for benzoate degradation and a meta-cleavage pathway for catechol. It also contains critical genes related to PAHs degradation, such as salicylate hydroxylase, cytochrome P450, and protocatechuate 3,4-dioxygenase. Additionally, it carries a significant number of resistance genes for heavy metals such as copper, zinc, cobalt, manganese, and cadmium. Furthermore, strain QYQ-1 has a robust iron uptake system. This expands the application range of strain QYQ-1, making it suitable not only for environmental remediation of PAHs-contaminated sites but also for potential use in environments contaminated with both heavy metals and PAHs.

A heterotrophic nitrifying-aerobic denitrifying bacterium, identified as Thauera butanivorans SVT, was isolated from spice wastewater. Genomic DNA of the isolate was extracted for whole-genome sequencing to analyze and predict nitrogen metabolic pathways. The nitrogen metabolism characteristics were investigated using 100mg/L NH₄⁺-N, NO₃^--N, or NO₂^--N as sole nitrogen sources. The effects of different carbon sources (sodium acetate anhydrous, sodium citrate, sodium succinate, sucrose, and glucose), C/N ratios (1, 5, 10, 15, 30), temperatures (10℃, 20℃, 30℃, 40℃, 50℃), and pH levels (4.0, 6.5, 7.5, 8.5, 10.0) on its heterotrophic nitrification-aerobic denitrification performance were systematically investigated. Results showed total nitrogen removal rates of (86.96±1.03)%, (60.52±4.70)%, and (64.32±1.40)% within 48hours when using NH₄⁺-N, NO₃^--N, and NO₂^--N as sole nitrogen sources, respectively. Strain SVT demonstrated growth and nitrogen removal capabilities under all tested conditions, with optimal performance achieved using sodium acetate anhydrous as carbon source at 30℃, C/N=10, and pH 7.5. Genomic analysis identified six nitrogen metabolism-related functional enzyme genes (napAB, nxrAB, nirBD, nirS, norBC, and nosZ). Combined with KEGG database alignment and single nitrogen source metabolism results, the proposed nitrogen metabolic pathways include: ammonium assimilation (NH₄⁺-N→L-glutamate→L-glutamine), nitrification (NH₄⁺-N→NO₂^--N→NO₃^--N), denitrification (NO₃^--N→NO₂^--N→NO→N₂O→N₂), and DNRA pathway (NO₃^--N→NO₂^--N→NH₄⁺-N). This study demonstrates that strain SVT exhibits efficient heterotrophic nitrification-aerobic denitrification capabilities, showing promising potential for wastewater treatment applications.

To explore the sedimentary history, sources, and ecological risks of emerging contaminants in global alpine lake sediments, 2,026 monitoring data points from 42 published studies were systematically integrated. Unit standardization and concentration normalization were applied, and temporal sequences with 5-year intervals were constructed for trend analysis. The results showed that persistent organic pollutants (POPs) in global alpine lake sediments stayed at generally low levels, with concentrations of 0.160~2140, 0.001~12.9, 1.30~372, 0.001~12.9, and 0.119~2.50 ng/g for PAHs, DDTs, HCHs, PCBs, and PBDEs, respectively. Concentrations of PAHs showed a continuous rising trend, whereas concentrations of DDTs and HCHs exhibited two peaks in the 1980s and early 2000s, reflecting "primary source" emissions from human activities and "secondary source" releases driven by global warming. Microplastic abundance (19~2640 items/kg) remained relatively low overall but displayed an increasing trend, also related to human activities and climate change. The toxic equivalents of PAHs continues to rise, leading to increasing ecological risks; while microplastics exhibit relatively low abundance but high proportion of hazardous polymers, indicating non-negligible ecological threats. However, current research on microplastic chronological sequence in alpine lake sediments remains scarce; studies of non-extractable residues (NER) of emerging contaminants in alpine lake sediments are relatively limited; and reports on endocrine-disrupting compounds and antibiotics are extremely rare. Investigations on emerging contaminants in data-scarce regions such as the African plateau and research on multiple categories of emerging contaminants especially co-migrating substances are both needed in the future.

The fugacity model is a widely used multimedia environmental fate model for organic pollutants. Multimedia environmental fate of typical antibiotics including ofloxacin and roxithromycin in Liangshui River using reclaimed water was simulated and researched based on level IV fugacity model, and the reliability of model was verified in this study. For another, transfer flux and the main transport process were analysed and identified. Meanwhile, the model key parameters were conducted by sensitivity analysis and uncertainty analysis. The results showed that the simulated concentrations were in good agreement with the measured concentrations, which indicated the simulation effectiveness of the model in the study area. When the environmental system reached equilibrium in the study area, the water advection outflow was identified as the primary export process for target antibiotics in water, while the interfacial exchange process with water phase was the major process for sediment. Sediment was the main reservoir of two antibiotics in the study area because of the mass fraction of ofloxacin and roxithromycin in water and sediment, respectively, were 8.73% and 91.27%, 27.46% and 72.54% at equilibrium. Henry's Law constant (H) significantly influenced the two-phase migration behavior. This study provides theoretical basis and decision-making support for environmental prediction and pollution control of antibiotics in rivers using reclaimed water.

In this study, we investigated the transformation of sulfamethoxazole (SMX) by various reactive nitrogen intermediates (RNIs) (NO, NH₂OH, and free nitrous acid (FNA)), as well as the effect of FNA on the removal of SMX (1~5mg/L) by ammonia-oxidizing bacteria (AOB) under weak acidic conditions. The results demonstrated that FNA significantly enhanced the removal of SMX, with pH identified being the most influential factor. Under weak acidic conditions(pH=6~7), FNA-coupled AOB cometabolism achieved a SMX removal efficiency of 80.0% without significantly affecting ammonia oxidation efficiency. During the process, the content of extracellular polymers (EPS) exhibited an initial increase followed by a decrease. The content of ammonia monooxygenase (AMO) was slightly inhibited, while the levels of hydroxylamine oxidoreductase (HAO) initially decreased and then increased. Additionally, the abundance of the AOB genus Nitrosomonas decreased sharply from 56.4% to 0.7% before recovering to 14.7%. In contrast, the abundance of Comamonas and Thermomonas increased significantly, which helped maintain ammonia oxidation performance and SMX removal efficiency.

A sulfur packed-bed reactor was employed, with lime mud-an industrial by-product, serving as an alkalinity source. The concentration of Sulfamethoxazole (SMM) was gradually increased to investigate the microscopic response mechanisms of sulfur autotrophic denitrifying (SADN) microbial communities under SMM stress. The results indicated that the SADN microbial communities could utilize the alkalinity provided by lime mud to achieve efficient nitrogen removal. Under low-concentration SMM stress, the system remained stable, Thiobacillus was enriched with removal efficiencies of nitrate (NO₃^--N) and SMM exceeding 99%. Under the impact of high-concentration SMM, the abundance of Thiobacillus in the system decreased, and the nitrogen removal performance fluctuated. However, the dominant bacteria in the system regulated the synthesis of hydrophobic amino acids glutamic acid (Glu) and proline (Pro) by increasing the secretion of C6-HSL, promoted the synthesis of tightly bound protein (TB-PN) in extracellular polymer (EPS), maintained the tight secondary structure of the protein, and thus promoted the aggregation of floc sludge. Under this regulation, the denitrification performance was recovered, and the SMM removal rate reached 60%. Additionally, under high-concentration SMM stress, unclassified_f__Rhodocyclaceae utilized the carbon sources secreted by apoptotic autotrophic bacteria and EPS to synergize with Ferritrophicum and Thiobacillus for efficient nitrogen removal.

Jianhu Lake, a small plateau lake in Yunnan Province, was selected as the study area. The spatio-temporal distributions of microplastics in water of Jianhu Lake were studied, and the microplastic fluxes from the influent and effluent rivers were explored through field sample collection and laboratory experiment. Then, the source or sink effects of small plateau lakes on microplastics were revealed. The results showed that the average abundances of microplastics in water of Jianhu Lake were (4.80±2.85) and (12.61±8.00) n/m³ in wet and dry seasons, respectively. The average monthly fluxes into the lake were (55.59×10⁶) and (3.82×10⁶) n, respectively. The monthly fluxes out of the lake were (13.70×10⁶) and (9.80×10⁶) n, respectively. The rayon (RY), polyethylene terephthalate (PET), and low density styrene-butadiene-styrene (SBS) were the main polymers types in water of Jianhu Lake. The degree of microplastic pollution in water of Jianhu Lake was higher in the dry season than that in the wet season. The microplastics from influent rivers had a significant contribution to the accumulation of microplastics in water of Jianhu Lake. Generally, Jianhu Lake was the sink of microplastics, while the "source" and "sink" roles of lakes on microplastics were the dynamic process under the different conditions.

The effect of polyethylene (PE) microplastics with varying particle sizes and addition levels on nutrient cycling in the rhizosphere soil of pakchoi (Brassica campestris L.) was investigated through pot experiments. The total carbon content in the soil was found to be significantly increased by PE addition (P<0.05), with increases of 73.9% and 56.3% observed under treatments with PE particle sizes of 1.0μm and addition levels of 0.5% (w/w) and 1.0% (w/w), respectively. Moreover, soil enzyme activity was influenced by PE addition, and significant increases in cellulase, invertase, amylase, urease, protease, and phosphatase activities were recorded under treatments with a PE particle size of 0.5μm and an addition level of 1.0% (w/w) (P<0.05). A highly significant impact of PE particle size, addition level, and their interaction on the levels of nitrate nitrogen and available phosphorus, as well as the activities of cellulase, invertase, and phosphatase in the rhizosphere soil of pakchoi, was revealed by two-way ANOVA (P<0.001). Furthermore, the abundance of microbial functional genes associated with the reduction of citrate cycles and incomplete citrate cycles during carbon cycling was enhanced by PE addition, thereby partially increasing the carbon fixation potential of the microbiome in the rhizosphere soil of pakchoi. Significant positive correlations between cellulase activity and changes in carbon and nitrogen cycling functional genes (P<0.05), as well as significant negative correlations with changes in phosphorus cycling functional genes (P<0.05), were demonstrated by Mantel test results. Changes in nitrogen and phosphorus cycling functional genes were found to be positively correlated with total carbon content (P<0.05). Actinobacteria, Proteobacteria, and Acidobacteria were identified as the primary hosts of key functional genes involved in carbon, nitrogen, and phosphorus cycling in the rhizosphere soil of pakchoi. The physicochemical properties of the rhizosphere soil were altered, the microbial community structure was modified, and the expression of functional genes linked to carbon, nitrogen, and phosphorus cycling was modulated by PE addition, thereby influencing nutrient cycling processes within the rhizosphere soil of pakchoi.

Microplastics (MPs) pollution, as a global environmental problem, has been recognized as a serious threat to aquatic ecosystems and the health of wild fish. The characteristics and influencing factors of microplastic pollution were analyzed in 11species of wild fish from Baiyangdian. The results indicated that the detection rate of MPs in these 11species was 100%, with an average abundance of (26.54±3.69) MPs per individual. The majority of the detected MPs were identified as transparent and black fibrous particles, with sizes predominantly less than 0.5mm, and their polymer composition was found to be diverse. The accumulation of MPs in Baiyangdian fish was influenced by multiple factors: the biological characteristics of the fish (body length and weight) were shown to determine the probability of MPs intake; the trophic level was observed to affect the biomagnification effect; feeding habits were found to regulate exposure probability; and habitat characteristics (such as the vertical distribution of MPs in the water column) were demonstrated to constrain exposure levels. The interaction of these factors resulted in significant variations in MPs accumulation among different fish individuals, revealing the complex mechanisms underlying MPs bioaccumulation. The findings of this study are expected to provide valuable data support for assessing the status and risks of MPs pollution in Baiyangdian fish populations.

Accurate measurement of internal exposure to metal(loid) mixtures is crucial for early identification of disease risk. In this study, a multi-element analytical method based on inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was developed and optimized for the quantification of 35metals and metalloids in whole blood. The method demonstrated excellent linearity (R²>0.998), high sensitivity (limits of detection as low as 2.0ng/L), good precision (coefficient of variation < 15%), and acceptable accuracy (spike recovery rates ranging from 76.2% to 124%). The performance of this method was further validated by its application to whole blood samples collected from 211middle-aged and elderly residents living near a non-ferrous metal smelting area in China. Moreover, this application facilitated an assessment of population-level exposure characteristics of 35target elements. Elevated concentrations of toxic elements such as Pb and Cd—associated with smelting activities—were observed, while statistically significant variations across sex and age groups suggested potential demographic determinants of exposure heterogeneity(P < 0.05). This high-throughput quantitative approach to whole-blood metallomics holds great potential for elucidating the biological roles of multiple elements, and provides a robust analytical foundation for exposure assessment, environmental risk evaluation, and the development of health interventions in populations affected by industrial activities. The established protocol could be further expanded to encompass a broader range of target elements in future studies.

Atmospheric inversion is a key method to estimate urban carbon dioxide emissions for monitoring and assessment purpose. The inversion skills determine not only the assessment accuracy and efficiency, but also whether they can fulfill the demands of carbon managements for the cities to achieve carbon peak and carbon neutrality (dual carbon pledge). However, despite the recent advances in urban carbon inversions, it is still not well examined in depth and details the current status of the inversion skills and their roles in urban dual carbon managements, taking into account multiple factors including monitoring networks, emission inventories, atmospheric transport and inversion methods. Here, we review the advances of urban carbon inversions and examine inversion performance, highlighting that the improvement of the inversion performance requires coordinated optimization of monitoring networks, prior inventories, and transport models. High-performance inversion systems can provide timely and accurate estimates of urban emissions and identify short-term emission variations, supporting policy assessment and carbon management at urban scale. We further discuss the challenges and possible solutions for improving inversion performance in several Chinese cities, with the aim of providing atmospheric environmental monitoring support for these cities to achieve dual carbon targets.

This article used the window EBM super-efficiency DEA model to calculate the synergistic level of carbon reduction, pollution reduction, green expansion and economic growth (CPGE) of crop production in China from 2009 to 2022, and identified the key driving factors and nonlinear response relationships of carbon reduction, pollution reduction, green expansion and economic growth synergy through the GBDT model. The results showed that: (1) During the inspection period, the overall synergy of CPGE of crop production in China showed an upward trend, rising from 0.67 in 2009 to 0.95 in 2022, with an average annual growth rate of 2.65%. Taking 2016 as the dividing point, the growth rate generally showed a "downward-upward" trend. (2) The regional differences in synergistic effects of CPGE of crop production in China were significant. In terms of temporal characteristics, the synergy between grain main production areas, grain main sales areas, and production and sales balance areas has been improved, with average annual growth rates of 2.85%, 3.68%, and 1.84%, respectively. In terms of spatial distribution, the pattern of synergistic effects has shifted from "high in the north and low in the south" to "high in the south and low in the north", gradually converging towards high-quality level, reducing regional differences, and ultimately presenting a spatial clustering feature of "cold in the east and hot in the west". (3) The key driving factors that affected synergistic effects included grain yield per hectare and agricultural mechanization level. Grain yield per hectare, individual technological level and urban-rural income gap factors had complex nonlinear characteristics. Technological innovation level factor had a significant promoting effect, while other factors had fluctuating negative impacts. From the perspective of time effects, grain yield per hectare has gradually become a core factor. From the perspective of regional effects, there were significant spatial differences in driving factors.

This study adopts a life cycle assessment (LCA) framework to define the system boundary for greenhouse gas (GHG) emission accounting across the entire food waste collection, transportation, and treatment process. Emission sources and gas types were identified to establish a comprehensive emission inventory, upon which a modular and decomposable GHG emission accounting model was developed based on the emission factor method. The results indicate that the full-process system boundary encompasses nine accounting units and seven major categories of GHG emission sources. Compared to conventional models, the proposed model demonstrates distinct advantages in accounting accuracy, modularity, flexibility, and scenario adaptability. A case study was conducted for the Chaoyang District of Beijing to validate the model. The findings show that GHG emissions are particularly significant at the waste disposal sites and during vehicle transportation, with emission rates of 1.38 and 1.32 tCO₂e/d, respectively. Fossil fuel combustion was identified as the dominant emission source, contributing 24.4% of total emissions. In the treatment and disposal phase, wastewater treatment exhibited the highest emissions, reaching 4.05tCO₂e/d, or 32.3% of the total. Carbon offsetting efforts achieved a reduction of 53.2tCO₂e/d. Sensitivity analysis revealed that food waste generation volume and biogas yield have the most significant impact on total GHG emissions, while the influence of total vehicle kilometers traveled and electricity emission factors was comparatively minor.

A power system flexibility optimization model, NEMO-China-Flexibility, was constructed in this study, integrating power system flexibility enhancement into a carbon-neutral framework for China's regional power grids. Based on regional economic development levels, energy demand intensity, renewable resource development potential, and flexibility enhancement, four distinct scenarios were designed: baseline scenario, high-penetration variable renewable energy scenario, flexibility enhancement scenario, and comprehensive scenario. The effects of flexibility enhancement were analyzed through scenario comparison. The results showed that integrated source-grid-load-storage flexibility enhancement could significantly enhance the power system's capability to address supply-demand fluctuations and improve renewable energy consumption. Among various flexibility resources, coal power was the foundational flexibility resource, while energy storage exhibited the greatest development potential. Additionally, flexibility enhancement delivered co-benefits such as reducing carbon emissions and lowering power system operational costs.