Post-processing Method to Reduce Noise while Preserving High Time Resolution in Aethalometer Real-time Black Carbon Data

Gayle S.W.  Hagler; Tiffany L.B.  Yelverton; Ram  Vedantham; Anthony D.A.  Hansen; Jay R. Turner

doi:10.4209/aaqr.2011.05.0055

Post-processing Method to Reduce Noise while Preserving High Time Resolution in Aethalometer Real-time Black Carbon Data

Gayle S.W. Hagler ¹, Tiffany L.B. Yelverton¹, Ram Vedantham², Anthony D.A. Hansen³, Jay R. Turner⁴

¹US EPA, Office of Research and Development, National Risk Management Research Laboratory, Research Triangle Park, NC, USA
²US EPA, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC, USA
³Magee Scientific, Berkeley, CA, USA
⁴Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO, USA

Received: May 4, 2011
Revised: June 20, 2011
Accepted: June 20, 2011
Download Citation: ||https://doi.org/10.4209/aaqr.2011.05.0055

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Cite this article:
Hagler, G.S., Yelverton, T.L., Vedantham, R., Hansen, A.D. and Turner, J.R. (2011). Post-processing Method to Reduce Noise while Preserving High Time Resolution in Aethalometer Real-time Black Carbon Data. Aerosol Air Qual. Res. 11: 539-546. https://doi.org/10.4209/aaqr.2011.05.0055

ABSTRACT

Real-time aerosol black carbon (BC) data, presented at time resolutions on the order of seconds to minutes, is desirable in field and source characterization studies measuring rapidly varying concentrations of BC. The Optimized Noise-reduction Averaging (ONA) algorithm has been developed to post-process data from the Aethalometer, one of the widely used real-time BC instruments. The ONA program conducts adaptive time-averaging of the BC data, with the incremental light attenuation (∆ATN) through the instrument’s internal filter determining the time window of averaging. Analysis of instrument noise and the algorithm performance was conducted using Aethalometer 1-second data from a soot generation experiment, where input BC concentrations were maintained constant and an optimal ∆ATNmin value was defined. The ONA procedure was applied to four additional data sets (1 s to 5 min data), including cookstove emissions tests, mobile monitoring, continuous near-road measurements, and indoor air sampling. For these data, the algorithm reduces the occurrence of negative values to virtually zero while preserving the significant dynamic trends in the time series.

Keywords: Aerosol; Soot; Aethalometer; Smoothing; Carbonaceous