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.

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.

This study established 4treatments, straw degradation microbial agent (MC), organic fertilizer (OF), MC+OF, and control check (CK), and conducted a 120 days straw returning experiment to analyze the impact of different treatments on straw decomposition rate, soil nutrients, and soil microecology. The results demonstrated that the MC+OF treatment significantly improved the straw returning rate, especially enhanced the lignin degradation of stubborn components in the straw. After 120 days, the MC+OF group showed significantly higher rates of hemicellulose, cellulose, lignin degradation, and strawweight loss compared with other treatments, with increases ranging from 2.87% to 11.78%, 3.20% to 10.59%, 6.00% to 32.97%, and 9.49% to 26.77% respectively (P<0.05). The total amount of humus reached 70.39g/kg, a 24.87% increase compared with the CK; additionally, soil organic carbon and dissolved organic carbon increased by 33.39% and 62.00%, respectively, from their initial levels, while soil total nutrients(nitrogen, phosphorus, potassium) increased relatively by 134.21mg/kg. The combination of microbial and organic fertilizers also enhanced the activity of invertase, urease, and neutral phosphatase in the soil. Moreover, microorganisms such as Aspergillus in the MC treatment became dominant genera during the straw returning process, induced a significant enrichment of indigenous microorganisms with lignocellulose degradation functions like Alcaligenes, Ensifer, and Brevundimonas. The combination of microbial and organic fertilizers decreased the total amount of pathogenic saprophytic fungi in the soil and improved soil quality. These results indicate the immense potential of MC+OF in accelerating the recycling and utilization of straw resources.

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.

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.

In the paper, the NRC and PRC columnar denitration catalysts were prepared using aluminum sol binders (nano-alumina and pseudo-boehmite) through the extrusion molding method. Their denitration performance was studied. It was shown that, compared to the original tailings, the denitration activity of the columnar catalysts was significantly improved. Compared to PRC, the denitration efficiency of NRC was found to be higher, reaching 67%. With the increase in the addition of the two binders, the mechanical strength was found to be improved to a certain extent. A more uniform surface distribution was observed in PRC, which allowed the catalyst to have a larger specific surface area and more surface acid sites. It was shown by H₂-TPR experiments that the area of the reduction peaks of PRC was decreased, the number of reduction peaks was reduced, and the redox ability was weakened, which was identified as the reason for its relatively smaller improvement in denitration performance. Both the E-R mechanism and L-H mechanism were observed on the surfaces of rare earth tailings and NRC, and the E-R mechanism of NRC was found to play a stronger role.

In this research, BPS and BPF with sublethal dose were selected to compare the difference and combined toxicity of neurodevelopmental toxicity in zebrafish from four aspects: developmental phenotype, motor behavior, vascular development and neurotoxicity. The results showed that both BPS and BPF of LC5 induced apparent deformities in zebrafish, such as inhibiting the development of swimming sac and yolk sac. Exposure to BPS and BPF can affect the early motor behavior of zebrafish, which is potentially associated with damage to the cardiovascular system and nervous central system. BPS and BPF caused abnormal cardiovascular development and shortened caudal vein (CV) width in zebrafish. The abnormal transmission of DA, AChE and NO neurotransmitters leads to the impaired development of zebrafish neurons, which has a direct impact on the function of the lateral nervous system, and then leads to the impaired early motor behavior of zebrafish. BPS and BPF show different toxicity differences in specific indicators. BPF exposure is more likely to induce tissue and organ toxicity in zebrafish, while the direct toxicity of BPS is less than that of BPF, which is more manifested at the molecular level, indicating that there is a certain degree of difference in the mode of action of the two. In addition, combined with the analysis of the combined action of concentration addition model, the addition action between BPS and BPF is mainly. The results of this study provide a reference for health risk assessment and risk warning after exposure to BPS, BPF and their mixtures.

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.

To understand nitrogen pollution and sources of Laizhou Bay, nitrogen sources and transformation processes in the coastal rivers entering the sea of Laizhou Bay were studied. Water quality parameters, nitrogen content, and stable isotopes were used to clarify the sources and key processes in river estuary. The results indicate strong temporal and spatial consistency between δD and δ¹⁸O of water, EC, and salinity, suggesting significant seawater mixing effects in the estuary, which was significantly weakened upstream of the river. NO₃^--N was found to be the dominant form to inorganic nitrogen in most reaches of the river during high flow and low flow seasons, ranging from 37.2% to 81.7% and 29.5% to 95.9%, respectively, except for a few sites. Furthermore, extreme values of ρ(TN) and ρ(NH₄⁺-N) values were observed at some sample sites during low flow season, which were significantly higher than those during the high flow season. Some water samples had ρ(NH₄⁺-N) values exceeding 2mg/L, resulting in an inferior Category V water quality. The long-term variation of ρ(NO₃^--N) from 2005 to 2023 showed an initial increase followed by a decrease in rivers entering Laizhou Bay. The δ¹⁵N-NO₃^- varied from +5.7‰ to +18.6‰ and from +4.5‰ to +20.0‰ during the high flow and low flow seasons, respectively, while the δ¹⁸O-NO₃^- varied from +4.2‰ to +13.8‰ and from -0.5‰ to +20.1‰, with no obvious seasonal variations. The nitrate isotope results showed that nitrification was major process affecting riverine nitrogen entering Lanzhou Bay, and that some river samples were also influenced by denitrification. During low flow season, NO₃^--N at the low salinity sampling sites was mainly sourced from manure and sewage, while most estuary sites during the high flow season were affected by the salty tide backflow, and agricultural fertilization impacted most river sections. This study provides insights into the emission characteristics of nitrogen pollution sources and spatial and temporal variability in Laizhou Bay’s coastal zone estuaries, offering valuable research demonstrations and data references for future prevention, control, and management efforts for nitrogen pollution in rivers entering the sea around the Bohai Sea.

Hasuhai Lake was selected as the research object, where surface sediment samples were collected from 19 sampling points during three water periods: April 2023 (dry season), July 2023 (wet season), and September 2023 (normal season). The concentrations of seven heavy metals (As, Cr, Cd, Cu, Pb, Zn, and Hg) were determined, with all metals except Cr being detected. Subsequently, their pollution levels and spatial distribution characteristics were analyzed. The geo-accumulation index (I_geo) and potential ecological risk index (RI) were used to assess the potential ecological risks of six heavy metals, respectively. The correlation analysis (CA), principal component analysis (PCA) and positive matrix factorization (PMF) models were utilized to analyze the sources and relative contributions of heavy metals in surface sediments. The results indicated that the average contents of six heavy metals in both dry and wet season exceeded the background values of Inner Mongolia stream sediments, and the average contents of five heavy metals except As in normal season exceeded the background values of Inner Mongolia stream sediments. The average contents of Cd and Hg exceeded the background values of Chinese stream sediments in the three water periods. Spatially, the distribution of heavy metals content in surface sediments of each water period is significantly different. The high value of heavy metals content in the dry season is concentrated in the east and west of the lake area, the wet season is mainly concentrated in the north and south of the lake area, and the normal season is mainly concentrated in the middle of the lake area. The results of the geo-accumulation index method and the potential ecological risk index method revealed that Cd and Hg were the main heavy metals elements causing ecological risks in the three water periods, and the mean values of RI in each water period were 590.42, 503.73 and 570.07 respectively, indicating a strong potential ecological risk. The sum of the contribution rates of Cd and Hg to RI values in the three water periods exceeded 90%. The main sources of heavy metals in surface sediments were identified as agricultural production activities and transportation (32.5%), industrial activities (22.7%), natural sources (20.1%), and mining activities (24.7%).