{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T05:01:25Z","timestamp":1784782885764,"version":"3.55.0"},"reference-count":38,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["No. 2024YFC3906403"],"award-info":[{"award-number":["No. 2024YFC3906403"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Toxics"],"abstract":"<jats:p>Long-term open-air storage of coal gangue (CG) can generate leachates containing oxidizable components contributing to chemical oxygen demand (COD), together with sulfate (SO42\u2212) and fluoride (F\u2212), yet their source-term behavior remains poorly understood. In this study, batch and column leaching tests were conducted on multi-source CG samples and combined with ToF-SIMS (surface compositional mapping), solid-phase TOC gradient leaching, and PHREEQC-XGBoost-SHAP modeling (coupled geochemical\u2013machine learning analysis). Batch-leachate COD levels ranged from 4.6 to 68.0 mg\/L, while SO42\u2212 and F\u2212 concentrations reached maxima of approximately 317 and 1.29 mg\/L, respectively. During column leaching, COD levels and SO42\u2212 concentrations were highest at low liquid-to-solid ratios (L\/S) and subsequently decreased, with maximum initial values of 186.6 and 3074 mg\/L, respectively, whereas F\u2212 exhibited delayed and persistent release at approximately 0.3\u20132.3 mg\/L. Solid-phase TOC did not directly predict the COD response, and ToF-SIMS revealed aliphatic organic fragments associated with aluminosilicate surfaces that weakened or were redistributed after leaching. The COD\u2013DOC discrepancy further indicated that dissolved organic matter alone could not fully explain the COD response, although the possible contribution of inorganic reducing species requires direct verification. Within the modeled framework, the sulfate source-term coefficient accounted for 69.4\u201376.9% of the modeled influence at L\/S = 0.5\u20132.0 L\/kg, while the influence of the HFO surface complexation increased during later leaching. In contrast, the F\u2212 source-term coefficient remained dominant over L\/S = 0.5\u201310.0 L\/kg, accounting for 97.0\u201397.9% of the modeled influence. These findings support parameter- and stage-specific monitoring and pollution control at CG disposal sites.<\/jats:p>","DOI":"10.3390\/toxics14070635","type":"journal-article","created":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T15:17:52Z","timestamp":1784647072000},"page":"635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Source-Term Release Behavior and Mechanisms of Non-Metallic Leaching Parameters from Coal Gangue: COD, Sulfate, and Fluoride"],"prefix":"10.3390","volume":"14","author":[{"given":"Siqi","family":"Xu","sequence":"first","affiliation":[{"name":"College of Water Science, Beijing Normal University, Beijing 100085, China"},{"name":"State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"},{"name":"State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyong","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"},{"name":"State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yufei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"},{"name":"State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qifei","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Water Science, Beijing Normal University, Beijing 100085, China"},{"name":"State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"},{"name":"State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingqi","family":"Die","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"},{"name":"State Environmental Protection Key Laboratory of Hazardous Waste Identification and Risk Control, Chinese Research Academy of Environmental Sciences, Beijing 100012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,21]]},"reference":[{"key":"ref_1","unstructured":"International Energy Agency Statistics (2024). 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