含水层
冲积层
有机质
铵
冲积土
环境化学
环境科学
地质学
冲积平原
水文学(农业)
地球化学
地下水
化学
地貌学
生态学
生物
岩土工程
古生物学
有机化学
标识
DOI:10.5194/egusphere-egu24-3292
摘要
Elevated concentration levels of geogenic ammonium in groundwater arise from the mineralization of nitrogen-containing natural organic matter in various geological settings worldwide, especially in alluvial-lacustrine and coastal environments. However, the difference in enrichment mechanisms of geogenic ammonium between these two types of aquifers remains poorly understood. To address this knowledge gap, we investigated two representative aquifer systems in central Yangtze (Dongting Lake Plain, DTP) and southern China (Pearl River Delta, PRD) with contrasting geogenic ammonium contents. The use of optical and molecular characterization of DOM combined with hydrochemistry and stable carbon isotopes has revealed differences in DOM between the two types of aquifer systems and revealed contrasting controls of DOM on ammonium enrichment. The results indicated higher humification and degradation of DOM in DTP groundwater, characterized by abundant highly unsaturated compounds. The degradation of DOM and nitrogen-containing DOM was dominated by highly unsaturated compounds and CHO+N molecular formulas in highly unsaturated compounds, respectively. In contrast, the DOM in PRD groundwater was more biogenic, less degraded, and contained more aliphatic compounds in addition to highly unsaturated compounds. The degradation of DOM and nitrogen-containing DOM was dominated by aliphatic compounds and polyphenols and CHO+N molecular formulas in highly unsaturated compounds and polyphenols, respectively. As DOM degraded, the ammonium production efficiency of DOM decreased, contributing to lower ammonium concentrations in DTP groundwater. In addition, the CHO+N(SP) molecular formulas were mainly of microbial-derived and gradually accumulated with DOM degradation. In this study, we conducted the first comprehensive investigation into the patterns of groundwater ammonium enrichment based on DOM differences in various geological settings.
科研通智能强力驱动
Strongly Powered by AbleSci AI