The ambient ion monitor-ion chromatography (AIM-IC) system, which provides hourly measurements of the main chemical components of PM2.5 (particulate matter with an aerodynamic diameter<2.5 μm) and its precursor gases, was evaluated and deployed from May to July 2011 and April to December 2013 in the Athabasca Oil Sands Region (AOSR) of northeastern Alberta, Canada. The collection efficiencies for the gas-phase SO2 and HNO3 using the cellulose membrane were 96% and 100%, respectively, and the collection efficiency of NH3 using the nylon membrane was 100%. The AIM-IC was compared with a collocated annular denuder sampling system (ADSS) and a Federal Reference Method (FRM) Partisol PM2.5 sampler. The correlation coefficients of SO4(2-) concentrations between the AIM-IC and ADSS and between the AIM-IC and the Partisol PM2.5 sampler were 0.98 and 0.95, respectively. The comparisons also showed no statistically significant difference between the measurement sets, suggesting that the AIM-IC measurements of the PM2.5 chemical composition are comparable to the ADSS and Partisol PM2.5 methods. NH3 concentration in the summer (mean±standard deviation, 1.9±0.7 µg m(-3)) was higher than in the winter (1.3±0.9 µg m(-3)). HNO3 and NO3- concentrations were generally low in the AOSR, and especially in the winter months. NH4+ (0.94±0.96 µg m(-3)) and SO4(2-) (0.58±0.93 µg m(-3)) were the major ionic species of PM2.5. Direct SO2 emissions from oil sands processing operations influenced ambient particulate NH4+ and SO4(2-) values, with hourly concentrations of NH4+ and SO4(2-) measured downwind (~30 km away from the stack) at 10 and 28 µg m(-3). During the regional forest fire event in 2011, high concentrations of NO3-, NH4+, HNO3, NH3, and PM2.5 were observed and the corresponding maximum hourly concentrations were 31, 15, 9.6, 89, and >450 (the upper limit of PM2.5 measurement) µg m(-3), suggesting the formation of NH4NO3.
Implications: The AOSR in Canada is one of the most scrutinized industrial regions in the developed world due to the extent of oil extraction activities. Because of this, it is important to accurately assess the effect of these operations on regional air quality. In this study, we compare a new analytical approach, AIM-IC, with more standard analytical approaches to understand how local anthropogenic and nonanthropogenic sources (e.g., forest fires) impact regional air quality. With this approach, we also better characterize PM2.5 composition and its precursor gases to understand secondary aerosol formation mechanisms and to better identify possible control techniques if needed.