Sources of NH4+ in PM2.5 and Their Seasonal Variations in Urban Tianjin China: New Insights From the Seasonal δ15N Values of NH3 Source

季节性 氮气 稳定同位素比值 环境化学 化学 分析化学(期刊) 物理 生态学 生物 有机化学 量子力学
作者
Hao Xiao,Shiyuan Ding,Xiaodong Li
出处
期刊:Journal Of Geophysical Research: Atmospheres [Wiley]
卷期号:129 (9) 被引量:5
标识
DOI:10.1029/2023jd040169
摘要

Abstract The stable nitrogen isotopic composition (δ 15 N) has been widely used to quantify sources of ammonium (NH 4 + ) in PM 2.5 . However, the overlap and uncertainty in δ 15 N values from different NH 3 sources, coupled with their seasonal variability, hinder accurate identification of NH 4 + source. Here, the δ 15 N values of various NH 3 source samples collected by the active sampler were determined. Subsequently, we measured the δ 15 N values of NH 4 + in PM 2.5 , which were collected seasonally in Tianjin. We found that the combustion‐related NH 3 (c‐NH 3 ) exhibiting higher δ 15 N values compared to volatile NH 3 (v‐NH 3 ), but all δ 15 N values was fell within the range reported by previous studies. Furthermore, inconsistent seasonal variations were observed in the δ 15 N‐NH 3 values originating from emissions of agricultural soil and human excreta. The application of the Bayesian isotope mixing model (MixSIAR model) revealed a significant increase in the contribution of v‐NH 3 to NH 4 + when incorporating current source data, as opposed to previous data, for δ 15 N of NH 3 source. Notably, the contribution of v‐NH 3 (53.1%) to NH 4 + was almost equivalent to that of c‐NH 3 (46.9%) when considering the seasonal δ 15 N signatures of NH 3 source. Additionally, the estimated contribution of v‐NH 3 to NH 4 + exhibited significant seasonal variability, which is more reasonable than in the non‐seasonal scenario. This study demonstrated that v‐NH 3 and c‐NH 3 contributed to NH 4 + in PM 2.5 in Tianjin almost equally, and it is highlighted that the seasonal δ 15 N values of NH 3 sources should be considered when estimating the contributions of different NH 3 sources to NH 4 + in PM 2.5 by the MixSIAR model.
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