Optimization framework of sediment phosphate oxygen isotope pretreatment method based on large-scale application: A case study of Fuyang River basin.

Jing Yang,Chengyu Du,Xin Jin, Hengtong Lu, Qingqing Chan, Jiaxuan Zhang, Hailong Ma, Huiying Zeng,Simin Li

Heliyon(2023)

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摘要
Phosphate oxygen isotope (δO) technique is an effective tool to identify the source and transformation process of phosphorus. The poor applicability of existing δO pretreatment methods for sediments hindered the large-scale application of δO technology. This paper presents an optimization framework for the pretreatment of sediment δO samples based on large-scale applications, using the Fuyang River Basin as a case study. The typical channel landscape outflow lake, South Lake, was selected as the most favorable point for assessing the applicability and optimizing the mainstream δO pretreatment method, which was achieved by clarifying the sediment environmental characteristics of South Lake. To evaluate the suitability of the Blake and McLaughlin methods in South Lake, a comparative study was carried out based on five dimensions: phosphorus recovery rate, removal efficiency of organic matter, removal efficiency of extraction liquid impurity ion, experimental time, and reagent consumption cost. The findings demonstrated that the Blake method outperformed the McLaughlin method across all five dimensions. Based on the environmental characteristics of the sediments of South Lake, the Blake method was optimized from two perspectives, namely the substitution of reagents and adjustment and optimization of experimental procedures. This resulted in an enhancement of phosphorus recovery and organic matter removal efficiency, while also reducing the experimental time required. The optimized method also yielded satisfactory results when applied to the entire watershed. This research paper can thus offer valuable technical support for the widespread application of sediment δO technology.
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关键词
phosphate oxygen isotope, Pretreatment method, Watershed, Sediments, Method optimization framework, Large-scale application
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