The Sunset Laboratory Carbon Aerosol Analysis Lab Instrument is widely used for thermal-optical analysis (TOA) of ambient particulate matter samples to measure total carbon (TC), organic carbon (OC), and elemental carbon (EC), and often thermal sub-fractions of OC and EC. TOA operating protocols include a series of plateau temperatures at which the thermal sub-fractions evolve. The temperatures have conventionally been measured by a sensor located in the sample oven but away from the filter sample. However, the TOA protocol used by the Interagency Monitoring of Protected Visual Environments (IMPROVE) network and recently adopted by the U.S. Environmental Protection Agency (EPA) Speciation Trends Network (STN) and Chemical Speciation Network (CSN) specify temperatures to be achieved at the filter. Our goal was to develop a simple calibration method to obtain the target filter temperatures in a Sunset Instrument. This method showed good agreement with the IMPROVE/STN/CSN method and has the advantages of not damaging oven components and of providing a direct comparison of sample oven sensor and filter temperatures at the TOA protocol-specified temperatures. Calibrations performed on four Sunset Instruments yielded different sensor/filter temperature relationships. Ambient PM2.5 samples analyzed using IMPROVE_A temperatures at the oven sensor compared to IMPROVE_A temperatures at the filter yielded statistically insignificant differences for TC, OC, and EC but statistically significant differences for the carbon sub-fraction concentrations. Temperature calibrations should be performed on each Sunset Instrument to ensure comparability in the carbon sub-fractions being reported, and a simple method has been provided for performing these calibrations. © 2009 Taylor & Francis Group, LLC.
CITATION STYLE
Phuah, C. H., Peterson, M. R., Richards, M. H., Turner, J. H., Phuah, C. H., & Dillner, A. M. (2009). A temperature calibration procedure for the sunset laboratory carbon aerosol analysis lab instrument. Aerosol Science and Technology, 43(10), 1013–1021. https://doi.org/10.1080/02786820903124698
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