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运用多同位素方法和同位素混合模型追踪和量化中国西南部沱江的磷源

Using a Multi-isotope Approach and Isotope Mixing Models to Trace and Quantify Phosphorus Sources in the Tuojiang River, Southwest China.

作者信息

Liu Dandan, Li Xueying, Zhang Yue, Qiao Qi, Bai Lu

机构信息

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

SEPA Key Laboratory of Eco-Industry, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

出版信息

Environ Sci Technol. 2023 May 16;57(19):7328-7335. doi: 10.1021/acs.est.2c07216. Epub 2023 Mar 15.

DOI:10.1021/acs.est.2c07216
PMID:36920429
Abstract

Identifying phosphorus (P) sources is critical for solving eutrophication and controlling P in aquatic environments. Phosphate oxygen isotopes (δO) have been used to trace P sources. However, the application of this method has been greatly restricted due to δO values from the potential source having wide and overlapping ranges. In this research, P sources were traced by combining δO with multiple stable isotopes of nitrogen (δN), hydrogen (δD), and dissolved inorganic carbon (δC). Then, a Bayesian-based Stable Isotope Analysis in R (SIAR) model and IsoSource model were used to estimate the proportional contributions of the potential sources in the Tuojiang River. δO was not in equilibrium with ambient water, and statistically significant differences in the δO values were found between the potential sources, indicating that δO can be used to trace the P sources. δN, δD, and δC could assist δO in identifying the main sources of P. The SIAR and IsoSource models suggested that industrial and domestic sewage was the largest contributor, followed by phosphate rock and phosphogypsum and agricultural sewage. The uncertainty of the calculation results of the SIAR model was lower than that of the IsoSource model. These findings provide new insights into tracing P sources using multiple stable isotopes in watersheds.

摘要

识别磷(P)源对于解决富营养化问题和控制水生环境中的磷至关重要。磷酸盐氧同位素(δO)已被用于追踪磷源。然而,由于潜在源的δO值范围广泛且重叠,该方法的应用受到了极大限制。在本研究中,通过将δO与氮(δN)、氢(δD)和溶解无机碳(δC)的多种稳定同位素相结合来追踪磷源。然后,使用基于贝叶斯的R语言稳定同位素分析(SIAR)模型和IsoSource模型来估计沱江潜在源的比例贡献。δO与周围水体未达到平衡,且在潜在源之间发现了δO值的统计学显著差异,这表明δO可用于追踪磷源。δN、δD和δC可以协助δO识别磷的主要来源。SIAR和IsoSource模型表明,工业和生活污水是最大的贡献者,其次是磷矿石、磷石膏和农业污水。SIAR模型计算结果的不确定性低于IsoSource模型。这些发现为在流域中使用多种稳定同位素追踪磷源提供了新的见解。

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