To investigate the dynamic variation patterns of leachate levels within the landfill mound, source leakage, and groundwater contamination plumes, a one-hydrologic-year monitoring was conducted at a landfill site in southern China. The results indicated a significant positive correlation between leachate levels and rainfall. Levels at monitoring points SW1-1, SW1-2, ZS1-2, and ZS1-3 ranged from 4.4m to 5.8m, 6.7m to 11.0m, 4.3m to 6.3m, and 4.0m to 6.8m, respectively, exhibiting annual fluctuations of 1.4m to 4.3m. The estimated source leakage rate of leachate ranged from 9.49m³/d to 10.90m³/d. The areas close to the landfill dam were significantly impacted by leakage. NH₄⁺-N concentrations at the landfill dam shoulder monitoring well QC1-19 increased with rising leachate levels but attenuated rapidly downstream. The spatial extent of the contamination plume exhibited seasonal variability. During wet seasons, plume migration was dominated by source leakage, extending the plume boundary beyond 120m from the landfill dam. Conversely, during dry seasons, natural attenuation mechanisms, such as biodegradation, became dominant, confining the plume boundary near the leakage source. Mn concentrations were generally elevated and demonstrated an inverse relationship with ORP. Conversely, Fe concentrations exhibited no clear discernible trend. NH₄⁺-N concentrations increased with decreasing pH. The relationships between COD_Cr and pH, as well as the dynamic interactions among COD_Cr, NH₄⁺-N, NO₃^-, and ORP, were observed to be complex.

To address the shortcoming of lacking optimization and adjustment methods for long-term monitoring indicators of the groundwater risk control project at contaminated sites, a typical large-scale contaminated site impacted by hazardous waste landfill was focused in the present study. By collecting the existing groundwater monitoring data during the construction, effect evaluation and long-term monitoring periods, a feature dataset regarding exceedances of monitoring wells was constructed for decision-making optimization exploration. Further, the three decision tree models, including Chi-squared Automatic Interaction Detector (CHAID), Exhaustive CHAID(E-CHAID), and Classification and Regression Trees (CART), were employed to identify key monitoring indicators influencing groundwater monitoring well exceedances. The results indicated that it was feasible to use decision tree models to predict groundwater monitoring well exceedances. Based on the all evaluated metrics, including accuracy, precision, recall, and the F₁-score (harmonic mean of precision and recall), the CART model significantly outperformed both the CHAID and E-CHAID models, suggesting that the overall optimization algorithm of the CART model was much suitable for predicting groundwater pollution exceedance events. 1,2,4-Trichlorobenzene and Nickel were identified as the most significant impact factors on the CART model's predictions. Moreover, the Fluoride, Petroleum Hydrocarbons, Trichloromethane, Dichloromethane, Cadmium, and cis-1,2-Dichloroethylene also demonstrated obvious influences. Consequently, it was recommended that the particular attention should be paid to the pollution dynamics of these 8key monitoring indicators during subsequent long-term monitoring of site groundwater.

This study evaluated six inorganic commercial amendments-Ningliang (NL), Tianxiang (TX), Longchang (LC), Wonong (WN), Gefeng (GF), and Baijinhui (BJH) using high-throughput sequencing of 16S rRNA genes to perform rhizosphere metagenomic analysis. We investigated the effects of applying soil amendments on cadmium (Cd) and mercury (Hg) accumulation, translocation characteristics in wheat (Triticum aestivum L.) and the structure of rhizobacterial community in Cd-Hg co-contaminated soil. The field experiment demonstrated that soil amendments significantly reduced the grain Cd enrichment (BCF_Cd) by 20.93%~64.87% and grain Hg enrichment (BCF_Hg) by 13.44%~34.66%, and the proportion of available Cd in soil decreased by 25.06%~39.58%. Notably, the treatments of LC and WN exhibited the optimal performance in immobilizing Cd and inhibiting Cd translocation in wheat, with WN concurrently suppressing Hg translocation. Microbial analysis indicated that amendments changed the rhizobacterial communities by enriching Cd-tolerant bacteria (e.g., Proteobacteria, Gemmatimonadota), thereby reducing the bioavailability of heavy metals (HMs). PICRUSt2 functional prediction indicated that rhizobacteria synergistically mitigated the toxicity of HMs through the enrichment of amino acid metabolism and carbohydrate metabolism. In summary, amendments could block Cd and Hg enrichment in wheat by direct reduction of HMs bioavailability in soil, and indirect enrichment of rhizosphere metal-tolerant bacterial microbiomes.

The influence of Fe-Ca layered double hydroxide-modified corn straw biochar (Fe-Ca LDH-CSB) on nutrient cycling processes in the rhizosphere soil of Bidens pilosa L. was investigated through controlled pot experiments. The application of Fe-Ca LDH-CSB was found to significantly increase the soil C/N ratio and organic matter content by 31.1~45.6% and 3.6~10.3%, respectively (P<0.05). Furthermore, the addition of biochar was observed to markedly upregulate functional genes involved in carbon (C), nitrogen (N), and phosphorus (P) cycling. At a 2% (mass ratio) amendment rate, the relative abundances of genes associated with C fixation (e.g., fbaA, korA, sucC, accD), N cycling (e.g., GDH2, nosZ, nifH, hao), and P cycling (e.g., ppk1, ppa, TC.PIT, pstB) were increased by 1.1~1.4-fold, 1.7~23.5-fold, and 1.1~1.2-fold, respectively, compared with the control. A significant positive correlation between available phosphorus and the abundance of C-, N-, and P-cycling genes (P<0.01) was revealed by Mantel test analysis. Sucrase activity was found to be positively correlated with C- and N-cycling genes (P<0.01) but negatively correlated with P-cycling genes (P<0.05). Partial least squares path modeling indicated that nutrient cycling was indirectly enhanced by Fe-Ca LDH-CSB through alterations in soil physicochemical properties and the reshaping of functional microbial taxa, thereby promoting the expression of nutrient-cycling genes. Taxonomic annotation revealed that Proteobacteria, Actinobacteria, and Chloroflexi were the dominant microbial hosts harboring key C-, N-, and P-cycling genes. Collectively, these findings demonstrated that the application of Fe-Ca LDH-CSB improved rhizosphere soil conditions and microbial community structure, thereby strengthening the biogeochemical cycling of C, N, and P in the rhizosphere of Bidens pilosa L.

sing 200soil As samples collected from suburban Changchun, this study combined the extreme gradient boosting tree (XGBoost) and the GeoShapley algorithm to explore the heterogeneity and nonlinear relationship between As and environmental factors, and to identify the local influencing factors and sources of As. The main conclusions are as follows: ① The XGBoost model had a fitted R² of 0.958, which was better than the geographically weighted regression and multiscale geographically weighted regression models, with fitted and predicted R² values of 0.958 and 0.729, respectively. ② The results of GeoShapley showed that the average contribution rate of manganese content ranked first and was the most significant characteristic variable affecting soil As, while the spatial location characteristic ranked second in importance, confirming the necessity of considering spatial coordinates. ③ The spatial distribution of GeoShapley values of influencing factors revealed that manganese content, alkali-hydrolyzable nitrogen, and sulfur content were the primary influencing factors for local As content at most sampling points, accounting for 99% of the samples. This indicated that parent material and agricultural production are the main sources of As. ④ The nonlinear relationship plots showed that there was a threshold effect between As content and various environmental variables, especially when the manganese content was higher than 2g/kg, the alkali-hydrolyzable nitrogen was higher than 175mg/kg, and the sulfur content was lower than 20mg/kg, As reached the peak, which should be paid special attention to in pollution prevention and control. This paper confirms the superiority of GeoShapley algorithm and the necessity of considering the spatial location, and provides data support for the governmental departments to formulate the policy of localized prevention and control of soil As pollution.

To evaluate the effects of organic fertilizer substitution on rice yield and soil quality under the conditions of equal nutrient substitution, a continuous six-year (2018~2023) field experiment was conducted. Using a no-fertilizer treatment as control (CK), this study examined the effects of chemical fertilizer (CF), 25% organic fertilizer substitution (COF25%), and 50% organic fertilizer substitution (COF50%) under low nitrogen application rates (135kg/hm² in early rice season, 150kg/hm² in late rice season) on rice biomass, yield, and soil properties. Results showed that compared with CK, fertilization promoted rice plant growth, enhanced nitrogen uptake, and increased yield. However, no significant differences (P>0.05) were observed in rice yield, nitrogen use efficiency, or partial factor productivity of nitrogen between CF and COF. Organic fertilizer substitution significantly increased soil organic carbon (SOC) by 8.40%~13.04% compared to CK. Moreover, the extent of SOC improvement increased with higher organic fertilizer substitution rates. All fertilization treatments significantly increased soil total phosphorus (24.30%~33.33%) and available potassium (25.60%~35.20%) contents. COF50% treatment resulted in a 18.18% significant increase in total nitrogen (TN) compared to CK. Analysis using the soil quality index area method revealed that soil quality improved with increasing organic fertilizer substitution rates. The soil quality index area values for COF25% and COF50% treatments were 88.81% and 222.40% higher, respectively, than that of the CF treatment. In conclusion, 25%~50% organic fertilizer substitution ensured normal rice growth and stable yield while enhancing soil quality through increased SOC content.

Lake Daihai remains ice-covered for approximately one-third of the year, forming a multi-media system comprising ice, water, and sediment. To clarify the migration patterns of nutrients at the ice-water-sediment interfaces, a systematic study was conducted on the spatiotemporal distribution, source-sink characteristics, and driving factors of nitrogen nutrients in the three phases (ice, water, sediment) before the freezing period (October) and during the freezing period (January, February). The results revealed significant spatiotemporal heterogeneity of nitrogen nutrients across the media. Total nitrogen (TN) and ammonium nitrogen (NH₄⁺-N) concentrations increased slightly in the ice layer. The TN concentration in the lower ice layer was higher in February than in January, with the lower ice layer exhibiting higher concentrations compared to other layers. From pre-freezing to late freezing periods, TN and nitrate nitrogen (NO₃^--N) concentrations continuously increased in the water and sediment. The NO₃^--N concentration in the water increased by 62.5% between January and February. Spatially, TN and NH₄⁺-N concentrations in the sediment were generally higher in the central area and lower in the eastern part, and overall exceeded those in the under-ice water. During the freezing period, the fractionation coefficients followed the order: NO₃^--N< TN <NH₄⁺-N. At the ice-water interface, NO₃^--N dominated TN migration, with a higher flux observed in January than in February. Sediment acted as a "source" for TN and NH₄⁺-N, but as a "sink" for NO₃^--N. The flux of nitrogen nutrients at the ice-water interface had a greater impact on their concentrations than the sediment-water interface flux. The dynamic changes of nutrients in the water were jointly influenced by the freezing-induced salt rejection effect and endogenous sediment release. Key environmental drivers for the distribution and migration of nitrogen nutrients before and during the freezing period included ice growth rate, dissolved oxygen, salinity, and water temperature.

To investigate the influence of changes in water salinity (composition and concentration) on key nitrate reduction processes in lake wetlands of arid regions, field surveys and salinity-controlled experiments were conducted in Bosten Lake and Xiangsi Lake wetlands located in the arid zone of northwestern China. Field surveys revealed that denitrification rates in Bosten Lake and the surrounding Xiangsi Lake wetland ranged from 7.2 to 131.4 μmol/(kg·h), and salinity was identified as a key environmental factor affecting denitrification. The rates of dissimilatory nitrate reduction to ammonium (DNRA) varied from 2.6 to 19.9μmol/(kg·h), which were primarily influenced by the ratio of dissolved organic carbon to nitrate in the water. In the salinity-controlled experiments, increased salinity (0.2‰~6.6‰) significantly inhibited denitrification rates: with increasing sodium sulfate concentration, denitrification rates declined by 25.7% (Bosten Lake) and 21.0% (Xiangsi Lake), respectively; while increasing sodium chloride concentration led to respective decreases of 36.7% and 31.1% in the two wetlands. Changes in salinity also significantly impacted DNRA rates: DNRA rates first increased and then decreased with rising sodium sulfate concentration in both wetlands, whereas they decreased by 26.1% (Bosten Lake) and 27.8% (Xiangsi Lake) with increasing sodium chloride concentration. Increased salinity exerted a stronger inhibitory effect on denitrificationcompared to DNRA, resulting in an elevated proportion of DNRA in total dissimilatory nitrate reduction. Overall, increased salinity will elevate lake nitrogen concentrations by inhibiting denitrification, while enhancing nitrogen retention potential by increasing the proportion of DNRA, thereby exacerbating the risk of nitrogen pollution in these lakes.

Based on land use, night-time light, POI data, etc., we used the coupling coordination degree and XGBoost-SHAP model, the response characteristics of ecosystem service value (ESV) and the spatial differentiation and driving factors of coupling coordination degree (CCD) under the multi-dimensional urban-rural gradient of Chengdu-Chongqing Economic Circle from 2012 to 2022 were analyzed from the grid scale. It was found that the ESV of the Chengdu-Chongqing Economic Circle showed an increasing trend during the study period, with a total increase of 12.98 billion CNY. In terms of spatial differentiation along the urban-rural gradient, the proportion of suburban space was observed to rise from 0.55% to 0.89%, representing a growth rate of 61.8%, making it the fastest-growing spatial category and indicating a notable trend of suburbanization. The proportion of urban space increased from 0.15% to 0.21%, while that of rural space decreased from 96.67% to 94.25%. A negative correlation between CCD and ESV was identified in the urbanization process of the Chengdu-Chongqing Economic Circle. The CCD was found to be at the preliminary coordination stage and exhibited a slight declining trend. Along the transition from rural to urban areas, ESV was shown to decrease, while CCD demonstrated an increasing trend. Key factors influencing the urban-rural gradient and the CCD of ecosystem service value were identified as population density, normalized difference vegetation index (NDVI), PM_2.5 concentration, and land use change, all of which were revealed to exhibit nonlinear effects.

In order to clarify the transport dynamics and ecological risks of pesticides in ditches and ponds, this paper presenteda pesticide transport model based on a monitoring study on drainage process and pesticide concentrations in field ditches (FD) in a small agricultural watershed in Yangzhou of Jiangsu Province, China. With the proposed model, we analyzed the spatial and temporal variations of chlorpyrifos (CPF) from FD to main ditches (MD) and ponds (PD) under different drainage flow and concentrationconditions, and evaluated the ecological risks of the CPF to aquatic animals. The monitoring results showed that peak drainage flow did not synchronize with peak pesticide concentrations in FD, the pesticide loading process was either with low flow and high concentration or high flow and low concentration. The model predictions of CPF transport process showed that ditches and ponds had a significant buffering effect on pesticide loading pulses, thus reducing peak concentrations of pesticide in drainage discharge. In the low-flow and high-concentration event, the observed peak concentration of CPF was as high as 330μg/L in FD, but reduced to 0.05μg/Lin MD and 0.00002μg/L in PD, resulting in reductions of 99.98% and 100% in MD and PD, respectively. In the high-flow and low-concentration event, the peak concentration of CPF was 2.5μg/L in FD, 0.02μg/L in MD, and 0.0006μg/L in PD, resulting in reductions of 99.2% and 99.98% in MD and PD, respectively. These results showed supportive effect of high-flow process on the output process. Under both types of drainage flow events, CPF concentrations were at low levels in MD (<0.1μg/L) and PD (<0.001μg/L),posing relatively low ecological risks to 16species of aquatic animal species that might be present in the ditches and ponds, except one species with a medium to high risk. Under a hypothetical unfavorable combination of synchronized high flow and high concentration event, the calculated peak concentrations of CPF was 2.55μg/Lin MD and 0.039μg/L in PD, making the number of aquatic animals with high ecological risk rise to 6species, regardless of the great reductions of 99.2% and 99.99% in MD and PD, respectively. Findings from this research may provide a scientific basis for pesticide pollution control and aquatic environmental protection in similar regions.