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采用 Ti(III) 还原和 NO 激光光谱法对硝酸盐进行自动化快速三重同位素(N、O、O)分析。

Automated rapid triple-isotope (N, O, O) analyses of nitrate by Ti(III) reduction and NO laser spectrometry.

机构信息

WasserCluster Lunz - Biologische Station, Lunz am See, Austria.

International Atomic Energy, Isotope Hydrology Section, Vienna International Centre, Vienna, Austria.

出版信息

Isotopes Environ Health Stud. 2023 Jun;59(3):297-308. doi: 10.1080/10256016.2023.2222222. Epub 2023 Jun 24.

Abstract

The nitrogen and oxygen (N, O, O) stable isotopic compositions of nitrate () are crucial tracers of nutrient N sources and dynamics in aquatic and atmospheric systems. Methods to reduce aqueous to NO gas (microbial or Cd method) before N and O isotope analyses require multi-step conversion or toxic chemicals, and O in NO cannot be disentangled by IRMS due to isobaric interferences. This technical note describes the automation of the stable-isotope analyses of nitrate by coupling the new Ti method with a headspace autosampler and an NO triple-isotope laser analyzer based on off-axis integrated cavity output spectroscopy. The automation yielded accurate and precise results for routine determinations of N, O, and O values for aqueous nitrate in environmental waters. Systematic corrections were required for cavity pressure, NO concentration and water vapour content to obtain the highest precision for all three isotopic ratios. For the first time, an automated laser-based system facilitates routine low-cost triple isotope analyses in studies where high-temporal resolution isotope analyses of NO are required but have been, until now, cost-prohibitive and time-consuming (e.g. atmospheric N pollution).

摘要

氮和氧(N、O、O)稳定同位素组成的硝酸盐()是水生和大气系统中营养 N 源和动态的关键示踪剂。在进行 N 和 O 同位素分析之前,将水合硝酸盐还原为 NO 气体(微生物或 Cd 方法)的方法需要多步转化或有毒化学品,并且由于同位素质谱干扰,IRMS 无法区分 NO 中的 O。本技术说明描述了通过将新的 Ti 方法与顶空自动进样器和基于离轴集成腔输出光谱的 NO 三重同位素激光分析仪相结合,对硝酸盐进行稳定同位素分析的自动化。该自动化系统为环境水中水合硝酸盐的 N、O 和 O 值的常规测定提供了准确和精确的结果。为了获得所有三个同位素比值的最高精度,需要对腔压、NO 浓度和水蒸气含量进行系统校正。该自动化激光系统首次实现了常规的低成本三重同位素分析,这在需要对大气 N 污染等需要高时间分辨率同位素分析但迄今为止成本过高且耗时的研究中非常有用。

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