Compositional Analysis of Fine Particulate Matter in Fairbanks, Alaska

Abstract:

Fairbanks, AK experiences extreme pollution episodes that result in winter violations of the fine particulate matter (PM_2.5) National Ambient Air Quality Standards. This poses a significant health risk for the inhabitants of the area. These high levels result from trapping of pollution in a very shallow boundary layer due to local meteorology, but the role of primary (direct emission) of particulate matter versus secondary production (in the atmosphere) of particulate matter is not understood. Analysis of the PM_2.5 composition is being conducted to provide insight into sources, trends, and chemistry. Methods are developed to convert carbon data from IMPROVE (post-2009 analysis method) to NIOSH (pre-2009 method) utilizing blank subtraction, sampler bias adjustment, and inter-method correlations from co-located samples. By converting all carbon measurements to a consistent basis, long-term trends can be analyzed. The approach shows excellent mass closure between PM_2.5 mass reconstructed from constituents and gravimetric-analyzed mass. This approach could be utilized in other US locations where the carbon analysis methods also changed. Results include organic and inorganic fractional mass percentages, analyzed over an eight-year period for two testing sites in Fairbanks and two in the nearby city of North Pole. We focus on the wintertime (Nov—Feb) period when most air quality violations occur and find that the particles consist primarily of organic carbon, with smaller percentages of sulfate, elemental carbon, ammonium, and nitrate. The Fairbanks area PM_2.5 organic carbon / elemental carbon partitioning matches the source profile of wood smoke. North Pole and Fairbanks PM_2.5 have significant compositional differences, with North Pole having a larger percentage of organic matter. Mass loadings in SO₄^2-, NO₃^-, and total PM_2.5 mass correlate with temperature. Multi-year temporal trends show little if any change with a strong effect from temperature. Insights from this study regarding primary versus possible secondary PM_2.5 production processes can help in identifying effective PM_2.5 control strategies.