利用水、碱萃取物(WEOM和AEOM)荧光光谱和紫外光谱特征识别浅湖沉积物中溶解有机质来源

IF 7.3 2区 环境科学与生态学 Q1 ECOLOGY Ecological Informatics Pub Date : 2025-05-01 Epub Date: 2025-01-22 DOI:10.1016/j.ecoinf.2025.103043
Jun Cao , Tianyu Chen , Jipeng Sun , Jun Zhong , Biao Mu , Xin Wang , Chunyan Wang , Massimiliano Materazzi , Hualun Zhu
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引用次数: 0

摘要

本研究探讨了溶解有机质(DOM)荧光特征在浅水湖泊沉积物有机质(OM)来源识别中的潜力。对太湖沉积物中水、碱萃取有机质(WEOM和AEOM)进行了光谱分析。湖泊被划分为7个明显的区域:R1和R2受入流河流的强烈影响,R3和R4以淹没植物为主,R5-R7以蓝藻华为主。调查结果表明,水碱可萃取有机碳(WEOC和AEOC)在R4区最高。其中,西北地区腐殖化指数(HIX)持续大于2.0,东南大部分地区主要小于1.0。此外,在R5、R6和R7区域,WEOM的荧光指数(FI)达到2.10,明显高于其他区域。AEOM的4个光谱指数的水平分布与WEOM的分布模式有部分相似。虽然WEOM含量略微落后于AEOM,但在坡度比(SR)、HIX和FI 3个指标上,WEOM与AEOM之间存在显著的相关性。来源鉴定表明,R1和R2区沉积物有机质来源于陆源,R3和R4区主要来源于沉水植物,R5-R7区主要受蓝藻源有机质的影响。值得注意的是,鉴定结果与太湖入流河流、蓝藻华和淹没植物覆盖的分布完全一致,强调了溶解有机质光谱特征在沉积物有机质来源分析中的潜在应用。摘要本研究通过荧光特征来确定太湖沉积物中有机质的不同来源和空间分布,以突出陆地输入、淹没植物和蓝藻华的影响。
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Identifying sources of dissolved organic matter in sediments of a shallow lake by fluorescence and ultraviolet spectral characteristics of water and alkali extractable organic matter (WEOM and AEOM)
This study investigates the potential of fluorescence characteristics of dissolved organic matter (DOM) to identify sediment organic matter (OM) sources in shallow lakes. Spectral analyses were performed on water and alkali extractable organic matter (WEOM and AEOM) from Lake Taihu sediments. The lake was divided into seven distinct regions: R1 and R2 strongly influenced by inflowing rivers, R3 and R4 were characterized by submerged macrophytes, and R5-R7 were dominated by cyanobacterial blooms. The investigation illustrated that the highest values of water and alkali extractable organic carbon (WEOC and AEOC) were found in region R4. Specifically, the Humification Index (HIX) values consistently exceeded 2.0 in the northwest regions, contrasting with values predominantly below 1.0 in most southeastern regions. Moreover, the Fluorescence Index (FI) of WEOM in regions R5, R6 and R7 reached 2.10, markedly higher than the values observed in other regions. The horizontal distribution of the four spectrographic indices of AEOM exhibited partial similarity to the distribution pattern of WEOM. Although the WEOC content marginally trailed AEOC, there was a significant correlation between WEOM and AEOM in three indices including slope ratio (SR), HIX and FI. The identification of sources implied that organic matter in sediments of regions R1 and R2 originated from terrestrial sources, while regions R3 and R4 were largely derived from submerged macrophyte and the regions R5-R7 were notably impacted by cyanobacteria-derived organic matters. Notably, the identification results aligned perfectly with the distribution of inflowing rivers, cyanobacterial blooms and submerged macrophyte coverage within Taihu Lake, underscoring the potential use of dissolved organic matter's spectral characteristics for organic matter source analysis within sediments.

Synopsis

This study identifies distinct sources and spatial distributions of organic matter in Lake Taihu's sediments, using fluorescence characteristics to highlight influences from terrestrial input, submerged macrophytes, and cyanobacterial blooms.
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来源期刊
Ecological Informatics
Ecological Informatics 环境科学-生态学
CiteScore
8.30
自引率
11.80%
发文量
346
审稿时长
46 days
期刊介绍: The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.
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