Refining δ15N isotopic fingerprints of local NO for accurate source identification of nitrate in PM2.5

氮氧化物 环境科学 燃烧 δ15N 硝酸盐 同位素特征 同位素分析 采样(信号处理) 稳定同位素比值 环境化学 化学 δ13C 滤波器(信号处理) 地质学 工程类 量子力学 海洋学 电气工程 物理 有机化学
作者
Hao Xiao,Qinkai Li,Shiyuan Ding,Wenjing Dai,Gaoyang Cui,Xiaodong Li
出处
期刊:Environment International [Elsevier BV]
卷期号:196: 109317-109317
标识
DOI:10.1016/j.envint.2025.109317
摘要

Stable nitrogen isotopic composition (δ15N) has proven to be a valuable tool for identifying sources of nitrates (NO3-) in PM2.5. However, the absence of a systematic study on the δ15N values of domestic NOx sources hinders accurate identification of NO3- sources in China. Here, we systematically determined and refined δ15N values for six categories of NOx sources in Tianjin using an active sampling method. Moreover, the δ15N values of NO3- in PM2.5 were measured during pre-heating, mid-heating and late-heating periods, which are the most heavily polluted in Tianjin. The results indicate that the isotopic fingerprints of the six types of NOx sources in Tianjin are indicative of the regional characteristics of China, particularly the North China Plain. The Bayesian isotope mixing (MixSIAR) model demonstrated that coal combustion, biomass burning, and vehicle exhaust collectively contributed more than 60 %, dominating the sources of NO3- during sampling periods in Tianjin. However, failure to consider the isotopic signatures of local NOx sources could result in an overestimation of the contribution from natural gas combustion. Additionally, the absence of industrial sources, an uncharacterized source in previous studies, may directly result in the contribution fraction of other sources being overestimated by the model more than 10 %. Notably, as the number of sources input to the model increased, the contribution of various NOx sources was becoming more stable, and the inter-influence between various sources significantly reduced. This study demonstrated that the refined isotopic fingerprint in China could more effectively distinguish source of NO3-, thereby providing valuable insights for controlling NO3- pollution.

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