Atmospheric fine particulate matter (PM2.5), which is mostly formed in the atmosphere from precursor gases, contributes to numerous environmental and health concerns. Quantifying the ambient concentrations of PM2.5 and precursor gases can be challenging. Hence, many scientific questions about the formation, chemical composition, and gas/particle partitioning of PM2.5 remain unanswered. Ambient Ion Monitor - Ion Chromatography (AIM-IC) was characterized and utilized to measure the water-soluble composition of PM2.5 (dominated by pNH4+, pSO42-, and pNO3-) and associated precursor gases (dominated by NH3(g), SO2(g), and HNO3(g)) during two field campaigns. The AIM-IC detection limits for hourly sampling were determined to be 3 - 45 ng m-3. The response time for “sticky” gases was significantly improved with a nylon denuder membrane. A novel inlet configuration for the AIM-IC, which minimizes sampling inlet losses and carryover in sample analyses, was implemented. Measurements from the BAQS-Met 2007 campaign were utilized to assess the accuracy of the AURAMS model and investigate gas/particle partitioning in SW Ontario. Due to high sulphate levels, NH3(g) was the limiting chemical factor in the formation and gas/particle partitioning of PM2.5. The errors in the predictions of relative humidity and free ammonia were responsible for the poor agreement
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between modelled and measured pNO3- values. The AIM-IC measurements from the CalNex 2010 study were compared to the CMAQ model and utilized to investigate the gas/particle partitioning in Bakersfield, CA. Very high NH3(g) concentrations were observed, and the formation and partitioning of PM2.5 was limited by HNO3(g) and H2SO4. Evidence of rapid removal of HNO3(g) by interactions with super-micron dust particles, and possibly with the alkaline surface was found. CMAQ exhibited significant biases in the predicted concentrations of pSO42-, NH3(g) and HNO3(g).
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/32764 |
| Date | 30 August 2012 |
| Creators | Markovic, Milos |
| Contributors | Murphy, Jennifer |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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