Corn straw biochar (Y-BC) was prepared by high-temperature pyrolysis method and its structure and morphology properties were characterized with a series of analytical techniques. The effects of initial pH and co-existing ions on tetracycline (TC) removal by Y-BC activated two types of persulfates: peroxydisulfate (PDS) and peroxymonosulfate (PMS) were systematically compared. The results showed that Y-BC activated PDS system could effectively remove TC under acidic and neutral conditions (pH=3~7), and TC removal efficiency was between 69.0% to 75.7% in 60min, while alkaline conditions (pH=9~11) TC removal efficiency reduced to 47.8%~48.4%. In contrast, the Y-BC-activated PMS system demonstrated a broad pH range for TC removal, and TC removal efficiency stabilized at 80.9%~86.8% at initial pH 3~11. The Cl^- and NO₃^- anions exhibited negligible effects on both activated persulfate systems. Meanwhile, HCO₃^- showed an inhibitory effect on TC removal by the Y-BC-activated PDS system while promoting the effect by the Y-BC-activated PMS system. TC removal efficiency decreased by 7.6% and increased by 5.1% with Y-BC-activated PDS and PMS, respectively. Combined the results of X-ray photoelectron spectroscopy, quenching experiments, and electron paramagnetic resonance analysis, it was deduced that the primary active sites for Y-BC activated PDS system were defect structures, and TC degradation was mainly through singlet oxygen (¹O₂) generation and electron transfer mechanisms. Conversely, functional groups served as key active sites for the Y-BC-activated PMS system, and TC degradation was primarily via hydroxyl radical (·OH) formation.

This study focuses on the karst depression in Fenghuang Village, Zhongliang Mountain, Chongqing, using the composite fingerprinting technique. An optimal combination of fingerprint properties was selected to quantify the contributions of potential sources to the depression deposits by using multivariate linear mixed model (IsoSource) and Bayesian mixed models (MixSIAR, SIMMR, and SIAR). In addition, the applicability of these models was further assessed by using their root mean square error (RMSE) and in combination with previous reports. Results indicated that the cumulative identification accuracy of the five fingerprint properties, i.e., the total carbon (TC) content, sand content, grain size at 70% frequency (D70), soil organic carbon (SOC) content, and sulfur (S) content, reached 89.5%, and therefore these properties constituted an optimal combination. The RMSE values for the four models were: MixSIAR (2.05), SIMMR (2.05), SIAR (2.07), IsoSource (2.34). Since the RMSEs of the three Bayesian mixed models were lower than that of the IsoSource model, the applicability of the Bayesian mixed models for quantifying the contributions of sediment sources to the depression deposits was higher than that of the multivariate linear mixed model. Among the three Bayesian mixed models, the MixSIAR and SIMMR models had the highest accuracy. Results from the MixSIAR and SIMMR models indicated that arable land was the primary source of the depression deposits, followed by ditch walls, with forest and grassland contributing the least. The composite fingerprinting technique could effectively quantify the sediment sources in the small watersheds in the depression. In this study, the composite fingerprinting technique was employed to unveil the sediment source of depression deposits in a typical karst trough valley in Southwest China, aiming to provide a reference for model selection in similar studies.

Halogenated organic compounds (HOPs), as important industrial chemicals, are extensively released into the environment during their production, transportation, and usage, ultimately accumulating in waste activated sludge (WAS) from wastewater treatment plants. Anaerobic digestion is a crucial approach for resource recovery from WAS, converting organic matter into valuable products such as volatile fatty acids and methane. However, the effects of HOPs on the anaerobic digestion capacity of WAS and their underlying mechanisms have not been systematically elucidated. Through a comprehensive literature review, this study analyzed the impacts of HOPs on methane production efficiency, key processes, and microbial communities during sludge anaerobic digestion. The results revealed that most HOPs inhibit key stages of anaerobic digestion due to their high toxicity, leading to reduced methane yield, while some low-toxicity HOPs exhibit a "hormesis effect" with promotion at low concentrations and inhibition at high concentrations. HOPs primarily regulate anaerobic digestion efficiency by affecting four critical stages: solubilization, hydrolysis, acidogenesis, and methanogenesis, with the most significant impacts on acidogenesis and methanogenesis. HOPs can influence the function of anaerobic microorganisms by altering microbial community structure, inhibiting key enzyme activities, and interfering with metabolic pathways. This study unveils the mechanisms of HOPs’ effects on sludge anaerobic digestion and proposes future research directions addressing current knowledge gaps, providing a theoretical foundation for resource recovery and safe disposal of WAS.

By thoroughly investigating the strategic relationship between the beautiful China initiative and the construction of the economy, politics, culture, society, and ecological civilization, this paper first introduces the concept and connotations of the beautiful China initiative and then summarizes the current state of research on this initiative from five aspects: connotation theory, the target indicators, the path of tasks, practical exploration, and the initiative’s guarantee system. In general, this research has effectively supported the formulation and implementation of the beautiful China initiative strategy. This paper concludes by pointing out the needs and prospects of research on the beautiful China initiative for the construction of an ecological civilization, including deepening research on the ideological connotations and theoretical system of the beautiful China Initiative, as well as strengthening the strategic objectives and indicator system, strategic tasks and implementation paths, and practical integration and guarantee system of the beautiful China initiative. The results provide guidance for the comprehensive promotion of research on the beautiful China initiative.

The active manganese oxide (MnO_x) filter media was found to exhibit efficient catalytic oxidation performance in removing ammonia nitrogen and manganese pollutants from water, but it was lacking in stability for the removal of bisphenol A(BPA), and the interaction mechanism with other inorganic pollutants remained unclear. In this study, sodium persulfate (NPS) was used to enhance the effect of the activated filter material (FM) on the removal of BPA. The experiment revealed that the removal rate could be increased to over 80% with the addition of just 0.1mmol/L of NPS, and the removal efficiency was further improved as the NPS concentration increased, ultimately reaching 100%. The addition of NH₄⁺ and Mn²⁺ was found to increase the production of reactive species by promoting electron transfer and providing electrons, respectively, thus enhancing the removal efficiency of BPA. The cycling experiment demonstrated that, while the FM exhibited good stability, the removal rate dropped to 48% after 11consecutive uses; however, this rate could be maintained above 65% with the addition of NPS. Free radical quenching and EPR experiments, along with X-ray photoelectron spectroscopy (XPS) analysis, confirmed that the primary reactive species in the filter material/NPS system were SO₄^·−, ·OH, and ¹O₂, with Mn(III) playing a crucial role in the catalytic oxidation process for removing BPA. The addition of NPS facilitated the formation of Mn(III), thereby promoting the removal of BPA.

In Momoge Nature Reserve, three distinct water bodies were selected for the investigation of the composition, spectral characteristics, and sources of dissolved organic matter (DOM) utilizing three-dimensional excitation emission matrix spectroscopy in conjunction with parallel factor analysis (PARAFAC). Additionally, two-dimensional correlation spectroscopy combined with structural equation modeling was employed to analyze the variations of DOM components and their relationships with water quality parameters. The results indicated that the DOM in the water bodies originated from both endogenous and exogenous sources, which has obvious humification characteristics. Five components were identified as microbial metabolites (C1), fulvic acid-like (C2 and C4), humic acid-like (C3) and tryptophan-like (C5) through three-dimensional fluorescence coupled with PARAFAC. Of five components, C1content was the highest (41.37%). The changing sequence of DOM components along the direction of water flow was characterized by 2D-COS as follows: C4→C2→C3→C1→C5, with humic-like substances showing greater variation than tryptophan-like substances, and the content of tryptophan-like substances being relatively stable. The humification degree of DOM directly affected the water quality status with influence weight of 46.17%. The water quality was indirectly impacted by DOM components C2 and C3 with a 17.59% influence weight. Insight into the response mechanism of DOM properties to water quality in Momoge Nature Reserve could provide a theoretical basis for the ecological protection of nature reserves.

To explore the effects of two distinct PM_2.5 exposure patterns on alveolar macrophages activation in rats, namely long-term low-concentration continuous exposure and high-concentration intermittent exposure. The rats were divided into three groups: a blank control group, a 4-fold concentrated PM_2.5 continuous exposure group (4FC group) and an 8-fold concentrated PM_2.5 intermittent exposure group (8-FI group). Exposure was facilitated using a whole-body dynamic exposure system over 84 days. The pathological changes in lung tissue were observed using hematoxylin and eosin (HE) staining. The oxidative stress indexes in bronchoalveolar lavage fluid (BALF) were determined by colorimetry. The mRNA levels of M2 polarization markers in lung tissue were measured by RT-qPCR. The protein expression levels related to the PI3K/AKT and JAK1/STAT6 signaling pathways, which are involved in macrophage activation, were assessed by Western blot. The results showed that, compared with the control group, the experimental group showed obvious symptoms of lung injury, accompanied by a significant elevation oxidation index in BALF. The mRNA levels of M2polarization marker and the protein expression of PI3K/AKT and JAK1/STAT6 signaling pathways were significantly upregulated, with the 8FI group showing higher levels than the 4FC group. These findings demonstrate that long-term inhalation of PM_2.5 can promote the activation of alveolar macrophages via the stimulation of the PI3K/AKT and JAK1/STAT6 signaling pathways, ultimately leading to lung injury. And intermittent inhalation of PM_2.5 with high concentration has a more serious effect on alveolar macrophages activation than continuous inhalation to low concentration. At the cellular level, the effect of PM_2.5 on alveolar macrophages activation and related signaling pathways were further verified.

The InVEST-PLUS model was coupled to calculate and analyze the spatiotemporal dynamics of four types of ecosystem services in Guizhou Province from 2000 to 2030 under different scenarios. Based on Spearman’s correlation analysis, the trade-offs/synergies between various service functions were examined, and self-organizing feature mapping networks were utilized to reveal the ecosystem service bundles. The results showed that from 2000 to 2020, the changes in land structure were mainly characterized by the continuous decrease of arable land and the fluctuating changes of forest and grassland, with a significant expansion of construction land. The natural development scenario showed the most significant increase in construction land among the three scenarios, with an increase of 25.39%, while in the ecological protection scenario, the main ecological land such as forest and grassland were protected. The water yield and soil conservation showed a fluctuating trend of first decreasing and then increasing from 2000 to 2020, while habitat quality and carbon storage showed a declining trend. The average value of carbon storage decreased from 234.05t/hm² to 231.70t/hm², and the average value of habitat quality decreased from 0.64 to 0.60. Relatively, in the ecological protection scenario, except for a slight decrease in water yield, other ecological function indicators improved, especially carbon storage and habitat quality, which reached the highest values. The trade-offs (3pairs) and synergies (3pairs) between ecosystem service functions in the study area showed a relatively balanced state. Under the ecological protection scenario, the correlation coefficients between different ecosystem services gradually increased, indicating an overall trend of environmental improvement in the region. Based on the clustering results, four types of ecosystem service bundles (ESB) were identified in Guizhou Province. From 2000 to 2030, the spatial pattern of various ecosystem service clusters in the study area remained basically stable, but there was spatial and temporal heterogeneity among different ESBs.

Based on data from 45 soil cores, 35 lake sediment cores, and 32 sea sediment cores in China, this study found a type of ^239+240Pu peakless distribution cores in soil, lakes, and marine environments, and discussed their causes of ^239+240Pu peakless distribution. The results show that there were two main types of peakless distribution of ^239+240Pu in soil core samples: one that the ^239+240Pu specific activity increased with depth, and the other that the ^239+240Pu specific activity decreased with depth; when using a Convection Dispersion Equation (CDE) model to simulate the migration behavior of ^239+240Pu in soil cores, the apparent convection rate showed a positive correlation with the ^239+240Pu maximum depth (n=45, R²=0.847). There was only one type of peakless distribution of ^239+240Pu in lake and ocean core samples: the ^239+240Pu specific activity decreased with depth. Meanwhile, the sedimentation rate of lake core samples (n=35, R²=0.921) or the maximum apparent convection rate of marine core samples (n=32,R²=0.949) also showed a positive correlation with the ^239+240Pu maximum depth. The maximum apparent convection rate of the exchangeable ^239+240Pu in the peakless distribution core sample was close to the sedimentation rate, and the maximum apparent convection rate didn’t affect the vertical distribution of ^239+240Pu in the core sample.

This study delved into the origins and transformation processes of nitrate in the groundwater of the Datong Basin, utilizing hydrochemical analysis alongside multi-isotope techniques (δ¹⁸O-H₂O, δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-). With the MixSIAR model, we quantitatively assessed the contribution of various pollution sources. Research results are as follows, the mean concentrations of NO₃^--N, NO₂^--N and NH₄⁺-N in groundwater were found to be 32.07,0.96和0.61mg/L, respectively, with NO₃^--N being the most prevalent. Remarkably, the peak concentration of NO₃^--N soared to 538.61mg/L, surpassing the Class III groundwater quality benchmark (20mg/L) by a staggering 27 times, with a 39.13% exceedance rate. The NO₃^--N concentration decreased as groundwater depth increased: shallow groundwater averaged at 34.26mg/L, middle groundwater at 22.05mg/L, and deep groundwater at 13.07mg/L. Nitrogen transformation in groundwater was primarily driven by nitrification, whereas denitrification played a minor role. The primary culprits behind nitrate pollution in groundwater were identified as sewage and manure, soil nitrogen and chemical fertilizers. Their respective average contribution rates were as follows: in shallow groundwater, sewage and manure accounted for 33.6%, followed by soil nitrogen at 33.5% and chemical fertilizers at 21.5%. For middle groundwater, the rates were 43.3% for sewage and manure, 34.4% for soil nitrogen, and 18.1% for chemical fertilizers. In deep groundwater, soil nitrogen led with 54.4%, chemical fertilizers followed at 25.1%, and sewage and manure contributed 18.5%. An uncertainty analysis revealed that the contribution rates of chemical fertilizers and soil nitrogen carried significant uncertainty, indicated by their relatively high UI₉₀values. The research results provide a reference for understanding nitrogen transformation and identifying pollution sources in groundwater.