AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
Predicting Ambient Aerosol Thermal Optical Reflectance (TOR) OC and EC in the Chemical Speciation Network (CSN) and the PM2.5 Federal Reference Method Network (FRM)
ANN DILLNER, Mohammed Kamruzzaman, Andrew Weakley, Satoshi Takahama, University of California, Davis
Abstract Number: 131 Working Group: Carbonaceous Aerosols in the Atmosphere
Abstract The two large particulate matter speciation networks in the United States, the Interagency Monitoring of Protected Visual Environments (IMPROVE) network in pristine areas and the Chemical Speciation Network (CSN) in urban areas use thermal optical reflectance (TOR) to quantify organic (OC) and elemental carbon (EC) (Solomon et al., 2014). Previously we showed that infrared spectra of PTFE filter samples and partial least squares (PLS) regression can be used to predict TOR OC and EC (Dillner and Takahama, 2015a, 2015b) in the IMPROVE network inexpensively and without damaging the samples. The objective of this work is to extend the method to the CSN and Federal Reference Method (FRM) networks, which pose additional considerations given the diversity in site types and aerosol composition. The FRM network is used for assessing compliance with the PM2.5 National Ambient Air Quality Standard and has approximately 900 sites compared to fewer than 200 sites each for CSN and IMPROVE. However, the FRM network does not routinely obtain speciated data. Using sites with collocated CSN and FRM samplers, TOR analysis of quartz filter samples collected in the CSN network are used to calibrate infrared spectra of PTFE filter samples from CSN and FRM network. We discuss the feasibility of using FT-IR and PLS to predict TOR OC and EC in the CSN and FRM networks and provide guidance on developing the calibration models.
Dillner, A. M., Takahama, S., Predicting Ambient Aerosol Thermal Optical Reflectance (TOR) Measurements from Infrared Spectra: Organic Carbon. Atmospheric Measurement Techniques, 8, 1097-1109, 2015a.
Dillner, A. M., Takahama, S., Predicting Ambient Aerosol Thermal Optical Reflectance (TOR) Measurements from Infrared Spectra: Elemental Carbon. Atmospheric Measurement Techniques, submitted, 2015b.
Solomon P. A., Crumpler, D., Flanagan, J. B., Jayanty, R.K.M., Rickman, E. E., McDade, C. E., U.S. National PM2.5 Chemical Speciation Monitoring Networks—CSN and IMPROVE: Description of networks, Journal of the Air & Waste Management Association 64:12, 1410-1438, 2014.