Unraveling the complexity of atmospheric brown carbon produced by smoldering boreal peat using size-exclusion chromatography with selective mobile phases

ENVIRONMENTAL SCIENCE-ATMOSPHERES(2021)

引用 1|浏览0
暂无评分
摘要
Boreal wildfires are a significant source of atmospheric brown carbon (BrC), a complex mixture of thousands of light-absorbing organic compounds that contributes to the warming effects of combustion particulate matter. Here, we use size-exclusion chromatography (SEC) coupled with photodiode array detection to characterize BrC collected from the controlled combustion of boreal peat. Importantly, rather than attempting to estimate the molecular weight of BrC chromophores through the minimization and correction of secondary interactions, we instead exploit these interactions to systematically explore BrC hydrophobicity, lability, and size-dependent light absorption properties. Using this new approach, which we corroborate using independent asymmetric flow field-flow fractionation (AF4) analysis, we show that the components of fresh wildfire BrC span a wide range of sizes, polarities, and light absorption characteristics. Unlike atmospherically aged wildfire BrC, which has previously been shown to resemble terrestrial humic substances in both its absorption profile and its retention behaviour, the fresh BrC sample studied here contains both higher-MW chromophores with "humic-like" featureless absorption and smaller-MW chromophores with structured absorption, and is more susceptible to hydrophobic interactions with the column matrix. Interestingly, we find that the contribution of the low-MW fraction to overall BrC absorption increases with increasing mobile phase acetonitrile content, which suggests that the high-MW fraction consists of metastable aggregates held together by easily disrupted intermolecular forces. Together, these results highlight the compositional diversity of atmospheric BrC and the challenge and potential of SEC for the characterization of complex, and poorly defined, environmental matrices.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要