Functional Group Composition of Organic Aerosols in the IMPROVE Network

ANN DILLNER, Dominique Young, Sean Raffuse, University of California, Davis

     Abstract Number: 133
     Working Group: Remote and Regional Atmospheric Aerosol

Abstract
The Interagency Monitoring of Protected Visual Environments (IMPROVE) is a long-term ambient particulate matter (PM) monitoring network of approximately 160 sites. IMPROVE sites are located throughout the US at primarily pristine locations such as National Parks and Wilderness Areas. PTFE filter samples are collected for 24-hours on small (25 mm) filters with a high (22.8 lpm) flowrate which provides a larger areal density than more common sampling techniques which use 16.7 lpm and 47 mm filters. Carbonaceous aerosols are characterized in IMPROVE as organic carbon (OC) and elemental carbon (EC). Thermal fractions of OC obtained while measuring OC and EC provide operationally-defined partitioning of OA but there is uncertainty in their relationship to atmospheric constituents. In addition, heteroatoms such oxygen (O), hydrogen (H) and others that are associated with the carbon are not measured. Therefore organic aerosol (OA) or organic matter (OM) is not measured directly but is estimated as 1.8 * OC.

One measure of atmospheric constituents of OM is organic functional groups, that is carbon bonded to O, H and other atoms. Other methods measure individual compounds or classify OM composition based on volatility. In this work, we measure organic functional groups and OA across the IMPROVE network using Fourier Transform Infrared (FT-IR) spectrometry measurements. Organic functional groups include aliphatic CH, alcohol OH, carboxylic acid (COOH) groups and non-acid carbonyls (CO) and are measured at all IMPROVE sites from the beginning of 2015 to the middle of 2018. Most of the data is above minimum detection limit due to the high areal density of IMPROVE samples. OM or OA is the sum of the functional groups. We will begin by presenting our quality assurance efforts and will highlight notable trends across regions, seasons, and years.