| 华北平原地下水砷异常识别-成因-预警关键技术 |
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| 关键词:arsenic groundwater on-site rapid detection genetic mechanism early risk warning |
| 基金项目:本文由河北省中央引导地方科技发展资金项目(编号: 246Z3601G)、国家自然科学基金地质联合基金项目(编号: U2444218)、国家重点研发计划项目课题(编号: 2022YFC3703701)、国家自然科学基金项目(编号: 42477093)和中国地质科学院基本科研业务费专项(编号: SK202530)联合资助。 |
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| Key Technologies for the Identification, Genesis, and Early Warning of Groundwater Arsenic Anomalies in the North China Plain |
| The widespread occurrence of arsenic anomalies in groundwater in the North China Plain poses a serious threat to regional water supply security and sustainable agricultural development. Currently, in terms of the on-site rapid screening of regional high-arsenic groundwater, the analysis of its complex formation mechanisms, and high-precision risk warning, a series of prominent challenges still remain. This study aims to establish a systematic solution for high-arsenic groundwater in the North China Plain by addressing the core bottlenecks in the entire chain of “identification-mechanism analysis-early warning” and has achieved a series of key technological breakthroughs. For rapid identification, the molybdenum blue method for arsenic detection was optimized by extending the storage time of the reducing agent (>7 days), reducing the sulfuric acid concentration in the chromogenic reagent, and shortening the chromogenic reaction time to 6 min. When combined with a self-developed portable three-channel arsenic speciation colorimeter, simultaneous rapid field detection of phosphate, inorganic arsenate (iAs(V)), and inorganic arsenite (iAs(III)) in groundwater samples was achieved, significantly improving the efficiency of regional groundwater arsenic investigations. Regarding mechanism analysis, a multi-factor control framework of “sediment dominance–human activity stress–climate change driving” was proposed. A paleochannel migration intensity index was constructed to predict arsenic distribution, elucidate the fundamental controlling role of the Yellow River paleochannel sedimentary environment in regional arsenic enrichment, and quantify the contributions of groundwater overexploitation and meteorological factors to arsenic enrichment. For early risk warning, a dual-driven numerical model for groundwater arsenic risk in North China was developed. Compared with conventional data-driven models, simulation and prediction accuracy improved by more than 20%, effectively enhancing the precision and generalizability of arsenic risk prediction under large-scale, small-sample, and heterogeneous distribution conditions. This study establishes a fully integrated technological system that integrates theory, methodology, and practical application. Promising results have been achieved in multiple provinces across the North China Plain, including Hebei and Inner Mongolia. This study holds significant scientific value and application potential for enhancing China’s groundwater investigation and assessment capabilities and for supporting the national “Healthy China” strategy. |
| CAO Wengeng,GUO Huaming,ZHENG Yan,XIE Xianjun,LI Xiangzhi,DUAN Yanhua,WANG Yanyan,REN Yu,TUO Xiaobao,HAO Guizhen,FENG Chuangye,SONG Le,YE Mingxia,NAN Tian,LU Chongsheng,LI Xiaofeng,XUE Ru,DONG Yueyong.2026.Key Technologies for the Identification, Genesis, and Early Warning of Groundwater Arsenic Anomalies in the North China Plain[J].Acta Geoscientica Sinica,47(3):443-453. |
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