Clean-soil Air Water最新文献

Green Adsorption Approach: Competitive Adsorption of Cu(II), Pb(II), and Cd(II) Using Cabbage Waste 绿色吸附方法：利用白菜垃圾竞争吸附Cu（II）、Pb（II）和Cd（II）

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-09-05 DOI: 10.1002/clen.70036

Elif Öztekin, Gülçin Demirel Bayık, Sinem Çolak

{"title":"Green Adsorption Approach: Competitive Adsorption of Cu(II), Pb(II), and Cd(II) Using Cabbage Waste","authors":"Elif Öztekin, Gülçin Demirel Bayık, Sinem Çolak","doi":"10.1002/clen.70036","DOIUrl":"https://doi.org/10.1002/clen.70036","url":null,"abstract":"<div>\u0000 \u0000 This study investigates the potential of cabbage (Brassica oleracea var. capitata f. alba) leaves as a low-cost, eco-friendly adsorbent for the removal of heavy metals—Cu(II), Pb(II), and Cd(II)—from aqueous solutions. The research aims to evaluate single, binary, and ternary metal systems under experimental conditions with initial metal concentrations (20–200 mg/L) and contact time (10–180 min). Adsorption efficiency increased with initial metal concentration, reaching saturation at 40 ppm for Cu and Pb. In competitive binary and ternary systems, Cu exhibited the highest adsorption capacity, followed by Pb and Cd (Cu > Pb > Cd), likely due to differences in ionic radius and hydration energy. The adsorption mechanism predominantly followed chemisorption, as indicated by the pseudo-second-order kinetic model. Kinetic studies revealed that the adsorption process follows the pseudo-second-order model more closely, whereas equilibrium data fitted well with the Langmuir isotherm, indicating monolayer adsorption. The maximum adsorption capacities (q_max) for Cu(II), Pb(II), and Cd(II) were found to be 42.5, 56.8, and 33.2 mg/g, respectively. The results demonstrate the effectiveness of cabbage leaves in treating heavy metal contaminated water and highlight their potential application in sustainable wastewater treatment technologies.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of Atrazine Residue in Drinking Water, Soil, Cassava Tuber, and Associated Health Risks From Three Rural and Neglected Farm Settlements in Ogun State, Nigeria 尼日利亚奥贡州三个农村和被忽视农场住区饮用水、土壤、木薯块状物中阿特拉津残留及相关健康风险评估

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-09-04 DOI: 10.1002/clen.70037

Folarin Owagboriaye, Olusolape Ilusanya, Abdulwahab Osibogun, Kehinde Olasehinde, Marvelous Ariyibi, Opeyemi Ogunbiyi, Titilayo Adesetan, Gabriel Dedeke

{"title":"Assessment of Atrazine Residue in Drinking Water, Soil, Cassava Tuber, and Associated Health Risks From Three Rural and Neglected Farm Settlements in Ogun State, Nigeria","authors":"Folarin Owagboriaye, Olusolape Ilusanya, Abdulwahab Osibogun, Kehinde Olasehinde, Marvelous Ariyibi, Opeyemi Ogunbiyi, Titilayo Adesetan, Gabriel Dedeke","doi":"10.1002/clen.70037","DOIUrl":"https://doi.org/10.1002/clen.70037","url":null,"abstract":"<div>\u0000 \u0000 Studies on risks associated with atrazine have largely focused on a single exposure pathway, paying less attention to potential integrated risks from multiple avenues. Health risks associated with exposure to atrazine residues in drinking water, soil, and cassava from three farm settlements in Ago-Iwoye, Nigeria, were evaluated. Drinking water, soil, and cassava tubers collected from each farm settlement were analyzed for atrazine residues using a standard method. The mean values of atrazine obtained were used to evaluate carcinogenic and non-carcinogenic risks associated with its exposure in adults and children. Atrazine in soil ranged from 0.120 to 0.310 mg/kg. Stream and well water recorded a range of 0.020–0.070 mg/L, but cassava recorded a range of 0.003–0.005 mg/kg. The hazard index for children and adults exposed to water and soil was below the risk limit. Although the incremental lifetime cancer risk for soil was below the threshold risk limit in adults and children, it was slightly above the limit for water. The human risk index associated with cassava consumption was below the threshold values for adults (0.35), but not for children (1.65). Water or cassava exposure, excluding soil, from the farm settlements may pose high risks, especially to children.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterization and Implications of Water Chemistry and Heavy Metal Pollution in the Sixi River, Hunan, China 湖南四溪河水体化学与重金属污染特征及意义

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-09-03 DOI: 10.1002/clen.70038

Lan Wang, Jianfeng Li, Feng Pan

{"title":"Characterization and Implications of Water Chemistry and Heavy Metal Pollution in the Sixi River, Hunan, China","authors":"Lan Wang, Jianfeng Li, Feng Pan","doi":"10.1002/clen.70038","DOIUrl":"https://doi.org/10.1002/clen.70038","url":null,"abstract":"<div>\u0000 \u0000 Situated within the metallogenically critical Nanling metallogenic belt of Hunan Province, the Sixi River basin exemplifies subtropical watersheds experiencing compounded anthropogenic pressures from historic tin mining and intensive agriculture. This hydrogeochemical investigation examines heavy metal contamination dynamics across aquatic matrices in this Pearl River tributary. Field analyses reveal severe Hg (20× WHO guidelines) and As exceedances with distinct spatial stratification: contamination frequencies follow tailings dams (87.61%) > ponds (81.86%) > rivers (67.64%) > wells (71.76%), posing significant neurotoxic and carcinogenic risks. Dominant HCO3–Ca·Mg hydrochemical facies reflect carbonate-granite weathering regimes, with ionic concentrations declining from tailings (12.01 mg/L) to wells (7.40 mg/L). Pollution indices demonstrate pH-dependent metal mobility, where alkaline conditions (pH > 8.5) exacerbate Hg/As dissolution in lotic systems. Principal component analysis delineates dual pollution pathways: PC1 (33.3% variance, As–Hg–Cu) traces agricultural inputs in alluvial plains, whereas PC2 (19.9%, Tl–Pb–Sn–Mn) aligns with fault-controlled sulfide mineralization in the Bailashui tin belt. Critically, anthropogenic loading from fertilizer-enriched runoff exerts greater influence on basin-wide degradation than mining effluents, underscoring the lithogenic–anthropogenic interface in subtropical mining watersheds.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144930051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment and Prediction of Soil Fertility in Urban Areas of the Loess Plateau Based on Machine Learning Methods 基于机器学习方法的黄土高原城市土壤肥力评价与预测

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-09-01 DOI: 10.1002/clen.70039

Xiaoyu Shen, Haoran Huang, Yuyao Ma, Jianqun Liao, Mingwei Wang, Xinfeng Li, Zi Ye, Ke Liu, Yan Li

{"title":"Assessment and Prediction of Soil Fertility in Urban Areas of the Loess Plateau Based on Machine Learning Methods","authors":"Xiaoyu Shen, Haoran Huang, Yuyao Ma, Jianqun Liao, Mingwei Wang, Xinfeng Li, Zi Ye, Ke Liu, Yan Li","doi":"10.1002/clen.70039","DOIUrl":"https://doi.org/10.1002/clen.70039","url":null,"abstract":"<div>\u0000 \u0000 The Loess Plateau, a vital ecological region in China, suffers from severe soil pollution and erosion. The soil fertility index (SFI) is a key indicator for assessing soil conditions, and understanding its spatial distribution and influencing factors is crucial for effective soil management. Machine learning methods, capable of analyzing complex and high-dimensional data, offer potential for large-scale SFI prediction. This study focuses on Lanzhou, a representative city on the Loess Plateau, using soil samples and the data of five key factors screened from environmental big data to train three machine learning models (random forest [RF], LightGBM, and XGBoost) for SFI prediction. The results show that all models effectively matched reference data trend, with XGBoost achieving the highest performance (R2 > 0.81). Notably, normalized difference vegetation index (NDVI) and soil organic carbon density (SOCD) emerged as the dominant predictors, collectively contributing over 80% to SFI prediction accuracy. Predicted SFI values in Lanzhou ranged from 0.09 to 0.91, with medium and lower quality soils predominantly located in central and north-central regions, highlighting the need for soil quality improvement. This study provides a theoretical basis and scientific support for large-scale SFI prediction.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Issue Information: Clean Soil Air Water. 9/2025 发行信息：清洁土壤空气水。9/2025

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-09-01 DOI: 10.1002/clen.70040

引用次数: 0

Application of Fenton and UV–Fenton Reaction for Resin Wastewater Treatment Detection of Residual H2O2 Fenton和UV-Fenton反应在树脂废水处理中残留H2O2检测中的应用

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-08-24 DOI: 10.1002/clen.70035

Zeynep Özcan, Gamze Sönmez, Mustafa Işık

{"title":"Application of Fenton and UV–Fenton Reaction for Resin Wastewater Treatment Detection of Residual H2O2","authors":"Zeynep Özcan, Gamze Sönmez, Mustafa Işık","doi":"10.1002/clen.70035","DOIUrl":"https://doi.org/10.1002/clen.70035","url":null,"abstract":"<div>\u0000 \u0000 The Fenton and UV–Fenton procedures were utilized in this study to eliminate total organic carbon (TOC) from wastewater generated during actual resin manufacturing. Optimal operating parameter values influencing removal efficiency were identified, including initial H2O2 and Fe2+ concentrations and total reaction time (t). The residual H2O2 concentration was measured using the metavanadate method in all processes. The results indicated that the Fenton process achieved a TOC removal rate of 32.0% at concentrations of 500 mg L−1 for H2O2 and 100 mg L−1 for Fe2+, with a constant pH of 3.78 and a reaction time of 6 h. In the UV–Fenton process, H2O2 concentrations of 500 and 1000 mg L−1 were examined, resulting in 14% and 15% TOC removal efficiencies, respectively. The effect of gradually adding H2O2 on the removal efficiency was also investigated in this study. To do this, the Fenton process started with an initial H2O2 concentration of 250 mg L−1. Once approximately 80% of this amount was consumed, 250 mg L−1 H2O2 was added, and the process continued. A maximum TOC removal of about 71% was achieved by gradually adding H2O2 at a 4000 mg L−1 concentration. On the basis of these findings, the gradual addition of H2O2, as opposed to an initial dose, proved to be a significant and practical method for removing organic matter from wastewater in the Fenton process.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D Pattern Characterization of Rainfall Trends and Change Point Detection in an Indian River Basin, Using Variable-Size Cluster Analysis 基于变大小聚类分析的印度河流流域降雨趋势的三维模式特征和变化点检测

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-08-22 DOI: 10.1002/clen.70032

Pradeep Kumar Mahato, Kesheo Prasad, P. R. Maiti

{"title":"3D Pattern Characterization of Rainfall Trends and Change Point Detection in an Indian River Basin, Using Variable-Size Cluster Analysis","authors":"Pradeep Kumar Mahato, Kesheo Prasad, P. R. Maiti","doi":"10.1002/clen.70032","DOIUrl":"https://doi.org/10.1002/clen.70032","url":null,"abstract":"<div>\u0000 \u0000 Floods and droughts are significantly impacted by rainfall, a vital component of the hydrological cycle. This study evaluates long-term rainfall trends using variable-size cluster analysis (VSCA) to examine trends and change points over eight synoptic stations of the Damodar River Basin from 1922 to 2021. The Mann–Kendall (MK) test with Sen's slope estimator reveals monotonic trends and magnitudes, and VSCA analyzes rainfall patterns and change points. Changing climate statistics were summarized using a modified Pettitt–Mann–Whitney test version. Rainfall patterns that changed over time were shown graphically using 3D representations for 100 years of data with a minimum cluster size of 10. VSCA analysis showed a declining trend in rainfall beginning about 1990, with notable variations in 1970–1980 for Bardhaman, Dhanbad, Giridih, and Hazaribag. On the other hand, Koderma and Purulia had rising patterns starting in 1970 and lasting roughly from 1960 to 1980. Most of the time, West-Medinipur showed both declining and no-trend conditions. The MK test and Sen's slope technique revealed a significant negative trend in rainfall, with magnitudes of −1.28, −1.03, −1.67, −0.61, −2.54, and −1.92 mm/year for Bardhaman, Dhanbad, Giridih, Hazaribag, Ramgarh, and West-Medinipur, respectively. Purulia and Koderma displayed rising trends with magnitudes of 0.84. This research enhances our understanding and provides valuable insights for managing water resources.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation and Future Projections of Monthly Groundwater Levels in the Lower Godavari River Basin of India Using Artificial Intelligence Models 利用人工智能模型对印度戈达瓦里河下游流域每月地下水位的模拟和未来预测

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-08-22 DOI: 10.1002/clen.70031

Niharika Patel, Madhava Rao V., Prakash C. Swain

{"title":"Simulation and Future Projections of Monthly Groundwater Levels in the Lower Godavari River Basin of India Using Artificial Intelligence Models","authors":"Niharika Patel, Madhava Rao V., Prakash C. Swain","doi":"10.1002/clen.70031","DOIUrl":"https://doi.org/10.1002/clen.70031","url":null,"abstract":"<div>\u0000 \u0000 Groundwater, the largest global source of freshwater, is under increasing stress due to over-extraction, leading to a significant decline in groundwater levels (GWLs) in many regions around the world. This global groundwater crisis, driven by consistent overdraft, seriously threatens water security and requires immediate action for sustainable management strategies. This study aims to predict and forecast monthly GWLs at three critical observation wells, such as Ramachandrapuram, Palakollu, and Jangareddigudem, located in the Lower Godavari River Basin, India, to support sustainable groundwater management. Univariate artificial intelligence (AI) models, namely, random forest (RF), least-squares support vector machine (LS-SVM), and radial basis function SVM (RBF SVM), were utilized for GWL simulation and prediction. The time-series features were extracted from historical groundwater data (January 1998–December 2012) to develop prediction models for training (January 1998–June 2008) and testing (July 2008–December 2012) periods. The models were then applied to project the monthly GWLs from January 2013 to December 2018. RF outperformed LS-SVM and RBF SVM models, achieving R2 values of 0.89, 0.86, and 0.82 for Jangareddigudem, Ramachandrapuram, and Palakollu during testing phase. The superior performance of the RF model demonstrates its robustness in modeling GWLs with high predictive accuracy. This data-driven approach, leveraging AI techniques for time-series prediction, presents a novel methodology for GWL estimation in data-sparse regions. The developed models provide valuable insights for sustainable groundwater management and inform policy decisions to mitigate impacts of groundwater overdrafts and ensure long-term water security in vulnerable regions.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dye Manufacturing Wastewater Treatment by Adsorption and Fenton Processes: Performance Evaluation and Cost Analysis 吸附法和Fenton法处理染料生产废水：性能评价和成本分析

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-08-22 DOI: 10.1002/clen.70034

Yasemin Kayhan, Deniz İzlen Çifçi, Elçin Güneş, Yalçın Güneş

{"title":"Dye Manufacturing Wastewater Treatment by Adsorption and Fenton Processes: Performance Evaluation and Cost Analysis","authors":"Yasemin Kayhan, Deniz İzlen Çifçi, Elçin Güneş, Yalçın Güneş","doi":"10.1002/clen.70034","DOIUrl":"https://doi.org/10.1002/clen.70034","url":null,"abstract":"<div>\u0000 \u0000 The dye manufacturing industry generates substantial volumes of wastewater that contains color, metals, and various toxic chemicals depending on the specific dyes produced. Effective treatment of this complex wastewater is of great importance to ensure compliance with discharge regulations and protect aquatic ecosystems. In this study, the treatability of wastewater samples taken from the dye manufacturing industry at two different times was investigated using adsorption and Fenton oxidation processes. Treatment performance and cost-effectiveness were assessed by using different pH values and activated carbon dosages in the adsorption process, and different Fe2+ and H2O2 dosages in the Fenton process. The optimum removal of chemical oxygen demand (COD) and color in the adsorption process was achieved at pH 5, and at 20 g L−1 activated carbon, COD and color removal were achieved at above 64.2% and 95%, respectively. In Fenton oxidation studies, a COD removal rate of 56.6% was achieved for wastewater 1 at 3000 mg L−1 Fe2+ and 6000 mg L−1 H2O2. Similarly, a 60.3% COD removal rate was achieved at 4000 mg L−1 Fe2+ and 6000 mg L−1 H2O2 in wastewater 2. In the Fenton process, the color removal rate for both wastewaters approached approximately 98%–99%. The cost of wastewater treatment for dye manufacturing wastewater was calculated to be $10.58–15.53 m−3 in the adsorption process and $20.57–22.89 m−3 in the Fenton oxidation process. Overall, the findings indicate that both adsorption and Fenton processes are effective treatment alternatives for dye manufacturing wastewater, providing significant reductions in COD and color.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decomposition of Uranium-Containing Plant Residues and Impact on the Surrounding Environment 含铀植物残体的分解及其对周围环境的影响

IF 1.4 4区环境科学与生态学

Clean-soil Air Water Pub Date : 2025-08-22 DOI: 10.1002/clen.70030

Haojie Zhang, Tianhao Zhou, Yuxiang Chen, Jinlong Tan, Jiangyue Han, Chengyu Liu, Qinwen Deng

{"title":"Decomposition of Uranium-Containing Plant Residues and Impact on the Surrounding Environment","authors":"Haojie Zhang, Tianhao Zhou, Yuxiang Chen, Jinlong Tan, Jiangyue Han, Chengyu Liu, Qinwen Deng","doi":"10.1002/clen.70030","DOIUrl":"https://doi.org/10.1002/clen.70030","url":null,"abstract":"<div>\u0000 \u0000 As plants gradually age and die, uranium-rich plant residues are at risk of migration and diffusion of accumulated uranium to the surrounding environment under the action of monsoon and rainfall. In this study, we collected roots and stems of Macleaya cordata from restored uranium-rich soils to simulate the decomposition of M. cordata residues under rainfall drenching. We analyzed the characteristics of uranium release, microbial community composition, and functional group changes during the decomposition of residues. The results showed that after 36 days of decomposition, the stems of the plant residues decomposed faster than the roots, whereas the uranium release rate from the stems (65.09%) was greater than that from the roots (59.09%). On the basis of microbial community analysis and infrared spectroscopy, our results show that Galactomyces, Proteobacteria, and Firmicutes (Ascomycota phylum) play critical roles in the degradation of cellulose, hemicellulose, and lignin in M. cordata residues. These results suggest that after the uranium-rich plant residues migrate and disperse with the monsoon, the uranium in the plant is released into the water body under the action of rain, and migrates and disperses with the water body, causing pollution to the surrounding environment.\u0000 </div>","PeriodicalId":10306,"journal":{"name":"Clean-soil Air Water","volume":"53 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0