Application of high-performance liquid chromatography in atmospheric chemistry.

摘要

Identification and quantification of atmospheric trace species, such as reactive and reduced nitrogen-containing compounds, carbonyl compounds and aliphatic alcohols are important in understanding several key issues in the atmospheric chemistry, such as free radical and oxidant production, particulate matter formation, and aerosol chemistry. Sensitive measurement techniques with short time resolution are required to gain information on their temporal and spatial distribution, in order to fully understand their formation mechanisms, fates, and roles in the atmospheric chemistry. In this research, highly sensitive measurement techniques were developed for some of the highly soluble atmospheric species, based on aqueous scrubbing by a coil sampler or bubble sampler, followed by high-performance liquid chromatography (HPLC) analysis with pre-column derivatization. Four groups of compounds were examined: (1) nitrous acid (HONO), nitric acid (HNO₃) and pernitric acid (HO₂NO ₂), (2) hydroxyacetone and other multi-oxygenated carbonyl compounds, (3) low-molecular-weight aliphatic alcohols, and (4) ammonia and low-molecular-weight aliphatic amines. The derivatization technique and sensitive HPLC analysis method specific to each group of compounds have been fully studied and analytical parameters were optimized. For field measurements, key factors such as the sample collection, analytical interferences were investigated. On-line derivatization and automated measurement system were designed to allow continuous and sensitive ambient measurement with the time resolution ranging from 5 min to 30 min, depending on the type of measured compounds. To validate the analytical methods and obtain information regarding the cycling of compounds in the atmosphere, techniques were deployed in several field campaigns in urban and rural environments. The importance and implications of these species in the atmospheric environment were evaluated based on their ambient levels, temporal distribution, and correlation with other physical, chemical and meteorological parameters.