Multi-modal Chemical Characterization of Brown Carbon in Atmosphere and Snowpack from the Colorado Rockies

STEVEN SHARPE, Kyla Siemens, Felipe Rivera-Adorno, Jay Tomlin, Nurun Nahar Lata, Zezhen Cheng, Erik Hulm, Matthew Fraund, Ryan Moffet, Swarup China, Alexander Laskin, Purdue University

     Abstract Number: 496
     Working Group: Remote and Regional Atmospheric Aerosol

Abstract
Snowpack in the Colorado Rockies is a crucial source of fresh water, which also provides terrestrial transport of nutrients and carbon for the arid Southwest United States. The lifetime and evolution of alpine snowpack is influenced by the deposition of light absorbing particles (LAPs), principally black carbon (BC), brown carbon (BrC), and mineral dust (MD). Deposition of LAPs decreases snow albedo and accelerates snowmelt. We have employed multi-modal chemical imaging (CI) and molecular characterization (MC) techniques for comprehensive analysis of airborne particles and snow pollutants collected at Gothic, CO as part of the Surface-Atmosphere Integrated Field Laboratory (SAIL) campaign. In this study, we characterize aerosol regimes, quantify optical and chemical properties of LAPs within snowpack, and use optical and chemical properties of LAPs to inform modeling estimates of the radiative forcing attributed to atmospheric and surface-deposited LAPs. Specific tasks of our study included: 1) deployment of an aethalometer and a time-resolved aerosol collector to provide real-time monitoring and sampling of light-absorbing aerosols. 2) Aethalometer filters were analyzed with Direct Analysis in Real Time (DART) high resolution mass spectrometry aided with temperature programed desorption to assess gas-condensed phase partitioning of aerosol components. 3) Analysis of snow-deposited LAPs using CI and MC techniques. 4) multi-modal high-resolution microscopy analysis of airborne LAPs sampled by a tethered balloon system deployed at Gothic to investigate differences in individual aerosol composition and morphology at various altitudes. Comprehensive data sets from this study will inform particle-resolved models that account for individual particle complexity and modeling of snow spectral albedo under different contamination scenarios in Colorado.