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FTIR Measurements of Tropospheric Species in the High Arctic to Investigate Pollution Events from Fires
Future climate change may cause significant air quality reduction by changing the outflow of pollutants as well as the strength of emissions from the biosphere, fires and dust. The sign and magnitude of these effects are highly uncertain and will vary regionally. The Arctic is a sensitive area, which has been warming rapidly over the past century with an accentuated heating in the past decades. It is a major receptor for mid-latitude pollution and changes in chemistry and influx of pollution may disrupt this sensitive system. Several studies have identified pollution transport to the Arctic based on model simulations and meteorological analyses, but our ability to verify these pathways through chemical observations has been limited.
In this study, we investigate the atmospheric concentrations and variability of tropospheric trace gases (such as carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C2H6), and acetylene (C2H2)) using ground-based Fourier Transform Infrared (FTIR) solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 80°05'N, 86°42'W) and at Thule (Greenland, 76°53'N, -68°74'W) from 2008 to 2013. The target species are all emitted by biomass burning and can be transported from mid-latitudes to the Arctic.
Fire events are identified by detecting, within a time-series, simultaneous enhancements of the three main biomass burning tracers, which are HCN, CO and C2H6. Analyses of back-trajectories coupled with MODIS hot spot and other evidence of fires are used to attribute the burning source regions and the travel time durations of the plumes. One significant case study is shown for August 2010, when simultaneous enhancements of aerosol optical depth and total columns of CO, HCN, and C2H6 were observed as a result of an intense boreal fire event occurring in Russia. We estimate emission ratios, which are key parameters required to improve the simulation of fire emissions in chemical transport models, and add new observations to the sparse dataset of emission factors that have been reported and compiled in the literature.