Abstract
Abstract. Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, organic carbon is measured from a quartz fiber filter that has been exposed to a volume of ambient air and analyzed using thermal methods such as thermal-optical reflectance (TOR). Here, methods are presented that show the feasibility of using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters to accurately predict TOR OC. This work marks an initial step in proposing a method that can reduce the operating costs of large air quality monitoring networks with an inexpensive, non-destructive analysis technique using routinely collected PTFE filter samples which, in addition to OC concentrations, can concurrently provide information regarding the composition of organic aerosol. This feasibility study suggests that the minimum detection limit and errors (or uncertainty) of FT-IR predictions are on par with TOR OC such that evaluation of long-term trends and epidemiological studies would not be significantly impacted. To develop and test the method, FT-IR absorbance spectra are obtained from 794 samples from seven Interagency Monitoring of PROtected Visual Environment (IMPROVE) sites collected during 2011. Partial least-squares regression is used to calibrate sample FT-IR absorbance spectra to TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date. The calibration produces precise and accurate TOR OC predictions of the test set samples by FT-IR as indicated by high coefficient of variation (R2; 0.96), low bias (0.02 μg m−3, the nominal IMPROVE sample volume is 32.8 m3), low error (0.08 μg m−3) and low normalized error (11%). These performance metrics can be achieved with various degrees of spectral pretreatment (e.g., including or excluding substrate contributions to the absorbances) and are comparable in precision to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC ratio, which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; these divisions also leads to precise and accurate OC predictions. Low OC concentrations have higher bias and normalized error due to TOR analytical errors and artifact-correction errors, not due to the range of OC mass of the samples in the calibration set. However, samples with low OC mass can be used to predict samples with high OC mass, indicating that the calibration is linear. Using samples in the calibration set that have different OM / OC or ammonium / OC distributions than the test set leads to only a modest increase in bias and normalized error in the predicted samples. We conclude that FT-IR analysis with partial least-squares regression is a robust method for accurately predicting TOR OC in IMPROVE network samples – providing complementary information to the organic functional group composition and organic aerosol mass estimated previously from the same set of sample spectra (Ruthenburg et al., 2014).
Highlights
Particulate matter (PM) has been implicated in increased morbidity and mortality (Anderson et al, 2012), climate change (Yu et al, 2006) and reduced visibility (Watson, 2002)
The analysis shows that the accuracy of Fourier transform infrared (FT-IR) organic carbon (OC) predictions with respect to thermal-optical reflectance (TOR) OC values is comparable to the precision of collocated TOR measurements
Using the lowest one-third of OC samples in the calibration set may improve the prediction for some samples near the MDL, but this modification to the calibration does not improve the overall performance of the calibration
Summary
Particulate matter (PM) has been implicated in increased morbidity and mortality (Anderson et al, 2012), climate change (Yu et al, 2006) and reduced visibility (Watson, 2002). Organic carbon (OC) and elemental carbon (EC) concentrations are measured on quartz filters using thermal-optical reflectance (TOR; Chow et al, 2007), NIOSH 5040 (Birch and Cary, 1996), European Supersites for Atmospheric Aerosol Research protocol (EUSAAR-2; Cavalli et al, 2010) or similar methods. Charring of organic material during heating is corrected for by using laser reflectance or transmittance (Cavalli et al, 2010; Chow et al, 2007). The measurement artifact caused by gas phase adsorption of organic material on the quartz filter may be corrected for by using blank or back-up quartz filters (Chow et al, 2010; Maimone et al, 2011; Turpin et al, 1994). Organic matter (OM) is estimated by multiplying the reported OC by an assumed OM / OC factor (Pitchford et al, 2007; Turpin and Lim, 2001)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
