海盐
气溶胶
盐(化学)
环境科学
无机离子
海盐气溶胶
海水
海洋学
环境化学
离子
化学
地质学
物理化学
有机化学
作者
Ye Tao,Alexander Moravek,Teles C. Furlani,Cameron E. Power,Trevor C. VandenBoer,Rachel Chang,Aldona Wiacek,Cora J. Young
出处
期刊:ACS earth and space chemistry
[American Chemical Society]
日期:2022-04-25
卷期号:6 (5): 1239-1249
被引量:12
标识
DOI:10.1021/acsearthspacechem.1c00367
摘要
Aging of sea-salt aerosol and the corresponding phase partitioning behavior of HCl/Cl– were monitored and studied in the Halifax Fog and Air Quality Study (HaliFAQS) field campaign in Canada in the early summer of 2019. Ionic chemical composition of ambient aerosol from total suspended particles (TSPs) to 10 nm was sampled and measured into 14 size ranges, which showed that aerosol at the sampling location was mainly composed of sea-salt constituents with little influence from anthropogenic emissions of secondary inorganic precursors. The size-resolved pH of aged sea-salt aerosol was calculated by Extended Aerosol Inorganic Model (E-AIM) IV and a newly derived method based on the measurement of NH3/NH4+ and HNO3/NO3– or HCl/Cl– coupled phase partitioning behavior. The latter pH calculation method does not require information about the aerosol liquid water content or complete water-soluble ion measurement, compensating for the role of oxidized organics to influence the proton activity. In comparison, E-AIM calculation requires the input of all major hygroscopic species. The size-resolved pH calculated by E-AIM IV generally agrees with the one calculated by NH3–HCl coupled phase partitioning. The sensitivities of HCl and HNO3 phase partitioning to aerosol pH are studied with both observational data and conceptual modeling, which gives evidence that the phase partitioning of HCl is more sensitive and therefore more reflective of aerosol pH changes than HNO3 in sea-salt dominated atmospheres where particles typically have pH > 3. The higher concentration and more reliable measurement also make HCl a more suitable choice to track pH changes in this study.
科研通智能强力驱动
Strongly Powered by AbleSci AI