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  • Original Article
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An accurate filter loading correction is essential for assessing personal exposure to black carbon using an Aethalometer

Abstract

The AE51 micro-Aethalometer (microAeth) is a popular and useful tool for assessing personal exposure to particulate black carbon (BC). However, few users of the AE51 are aware that its measurements are biased low (by up to 70%) due to the accumulation of BC on the filter substrate over time; previous studies of personal black carbon exposure are likely to have suffered from this bias. Although methods to correct for bias in micro-Aethalometer measurements of particulate black carbon have been proposed, these methods have not been verified in the context of personal exposure assessment. Here, five Aethalometer loading correction equations based on published methods were evaluated. Laboratory-generated aerosols of varying black carbon content (ammonium sulfate, Aquadag and NIST diesel particulate matter) were used to assess the performance of these methods. Filters from a personal exposure assessment study were also analyzed to determine how the correction methods performed for real-world samples. Standard correction equations produced correction factors with root mean square errors of 0.10 to 0.13 and mean bias within ±0.10. An optimized correction equation is also presented, along with sampling recommendations for minimizing bias when assessing personal exposure to BC using the AE51 micro-Aethalometer.

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References

  1. US EPA. Integrated Science Assessment for Particulate Matter, EPA/600/R-08/139F 2009.

  2. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2224–2260.

    Article  Google Scholar 

  3. Kim JJ, Smorodinsky S, Lipsett M, Singer BC, Hodgson AT, Ostro B . Traffic-related air pollution near busy roads: the East Bay Children’s Respiratory Health Study. Am J Respir Crit Care Med 2004; 170: 520–526.

    Article  Google Scholar 

  4. Adams HS, Nieuwenhuijsen MJ, Colvile RN, Older MJ, Kendall M . Assessment of road users' elemental carbon personal exposure levels, London, UK. Atmos Environ 2002; 36: 5335–5342.

    Article  CAS  Google Scholar 

  5. Dons E, Int Panis L, Van Poppel M, Theunis J, Willems H, Torfs R et al. Impact of time–activity patterns on personal exposure to black carbon. Atmos Environ 2011; 45: 3594–3602.

    Article  CAS  Google Scholar 

  6. Hansen ADA, Rosen H, Novakov T . The Aethalometer - an instrument for the real-time measurement of optical-absorption by aerosol-particles. Sci Total Environ 1984; 36 (Jun): 191–196.

    Article  CAS  Google Scholar 

  7. Cai J, Yan B, Ross J, Zhang D, Kinney PL, Perzanowski MS et al. Validation of microaeth(R) as a black carbon monitor for fixed-site measurement and optimization for personal exposure characterization. Aerosol Air Qual Res 2014; 14: 1–9.

    Article  CAS  Google Scholar 

  8. Cheng Y-H . Real-time performance of the microAeth® AE51 and the effects of aerosol loading on its measurement results at a traffic site. Aerosol Air Qual Res 2013; 13: 1853–1863.

    Article  Google Scholar 

  9. Weingartner E, Saathoff H, Schnaiter M, Streit N, Bitnar B, Baltensperger U . Absorption of light by soot particles: determination of the absorption coefficient by means of aethalometers. J Aerosol Sci 2003; 34: 1445–1463.

    Article  CAS  Google Scholar 

  10. Liousse C, Cachier H, Jennings SG . Optical and thermal measurements of black carbon aerosol content in different environments: variation of the specific attenuation cross-section, sigma (σ). Atmos Environ 1993; 27A.

  11. Petzold A, Kopp C, Niessner R . The dependence of the specific attenuation cross-section on black carbon mass fraction and particle size. Atmos Environ 1997; 31: 661–672.

    Article  CAS  Google Scholar 

  12. Bond TC, Anderson TL, Campbell D . Calibration and intercomparison of filter-based measurements of visible light absorption by aerosols. Aerosol Sci Technol 1999; 30: 582–600.

    Article  CAS  Google Scholar 

  13. Virkkula A, Mäkelä T, Hillamo R, Yli-Tuomi T, Hirsikko A, Hämeri K et al. A Simple procedure for correcting loading effects of aethalometer data. J Air Waste Manage Assoc 2007; 57: 1214–1222.

    Article  Google Scholar 

  14. Buonanno G, Stabile L, Morawska L, Russi A . Children exposure assessment to ultrafine particles and black carbon: The role of transport and cooking activities. Atmos Environ 2013; 79: 53–58.

    Article  CAS  Google Scholar 

  15. Dons E, Panis LI, Van Poppel M, Theunis J, Willems H, Torfs R et al. Impact of time–activity patterns on personal exposure to black carbon. Atmos Environ 2011; 45: 3594–3602.

    Article  CAS  Google Scholar 

  16. Nwokoro C, Ewin C, Harrison C, Ibrahim M, Dundas I, Dickson I et al. Cycling to work in London and inhaled dose of black carbon. Eur Respir J 2012; 40: 1091–1097.

    Article  CAS  Google Scholar 

  17. Delgado-Saborit JM . Use of real-time sensors to characterise human exposures to combustion related pollutants. J Environ Monit 2012; 14: 1824–1837.

    Article  CAS  Google Scholar 

  18. Hatzopoulou M, Weichenthal S, Dugum H, Pickett G, Miranda-Moreno L, Kulka R et al. The impact of traffic volume, composition, and road geometry on personal air pollution exposures among cyclists in Montreal, Canada. J Expo Sci Environ Epidemiol 2013; 23: 46–51.

    Article  CAS  Google Scholar 

  19. Hong ESA, Bae CHC . Exposure of bicyclists to air pollution in Seattle, Washington hybrid analysis using personal monitoring and land use regression. Transp Res Rec 2012; 2270: 59–66.

    Article  Google Scholar 

  20. Wu H, Reis S, Lin C, Beverland IJ, Heal MR . Identifying drivers for the intra-urban spatial variability of airborne particulate matter components and their interrelationships. Atmos Environ 2015; 112: 306–316.

    Article  CAS  Google Scholar 

  21. Klompmaker JO, Montagne DR, Meliefste K, Hoek G, Brunekreef B . Spatial variation of ultrafine particles and black carbon in two cities: results from a short-term measurement campaign. Sci Total Environ 2015; 508: 266–275.

    Article  CAS  Google Scholar 

  22. Louwies T, Nawrot T, Cox B, Dons E, Penders J, Provost E et al. Blood pressure changes in association with black carbon exposure in a panel of healthy adults are independent of retinal microcirculation. Environ Int 2015; 75: 81–86.

    Article  CAS  Google Scholar 

  23. Ruths M, von Bismarck-Osten C, Weber S . Measuring and modelling the local-scale spatio-temporal variation of urban particle number size distributions and black carbon. Atmos Environ 2014; 96: 37–49.

    Article  CAS  Google Scholar 

  24. MacNaughton P, Melly S, Vallarino J, Adamkiewicz G, Spengler JD . Impact of bicycle route type on exposure to traffic-related air pollution. Sci Total Environ 2014; 490: 37–43.

    Article  CAS  Google Scholar 

  25. Rivas I, Donaire-Gonzalez D, Bouso L, Esnaola M, Pandolfi M, de Castro M et al. Spatiotemporally resolved black carbon concentration, school children's exposure and dose in Barcelona. Indoor Air 2016; 26: 391–402.

    Article  CAS  Google Scholar 

  26. Weichenthal S, Kulka R, Dubeau A, Martin C, Wang D, Dales R . Traffic-related air pollution and acute changes in heart rate variability and respiratory function in urban cyclists. Environ Health Perspect 2011; 119: 1373–1378.

    Article  CAS  Google Scholar 

  27. Collaud Coen M, Weingartner E, Apituley A, Ceburnis D, Fierz-Schmidhauser R, Flentje H et al. Minimizing light absorption measurement artifacts of the Aethalometer: evaluation of five correction algorithms. Atmos Meas Tech 2010; 3: 457–474.

    Article  Google Scholar 

  28. de Nazelle A, Fruin S, Westerdahl D, Martinez D, Ripoll A, Kubesch N et al. A travel mode comparison of commuters' exposures to air pollutants in Barcelona. Atmos Environ 2012; 59: 151–159.

    Article  CAS  Google Scholar 

  29. Peters J, Van den Bossche J, Reggente M, Van Poppel M, De Baets B, Theunis J . Cyclist exposure to UFP and BC on urban routes in Antwerp, Belgium. Atmos Environ 2014; 92: 31–43.

    Article  CAS  Google Scholar 

  30. Li B, Lei XN, Xiu GL, Gao CY, Gao S, Qian NS . Personal exposure to black carbon during commuting in peak and off-peak hours in Shanghai. Sci Total Environ 2015; 524-525: 237–245.

    Article  CAS  Google Scholar 

  31. Dekoninck L, Botteldooren D, Panis LI, Hankey S, Jain G, S Karthik et al. Applicability of a noise-based model to estimate in-traffic exposure to black carbon and particle number concentrations in different cultures. Environ Int 2015; 74: 89–98.

    Article  CAS  Google Scholar 

  32. Apte JS, Kirchstetter TW, Reich AH, Deshpande SJ, Kaushik G, Chel A et al. Concentrations of fine, ultrafine, and black carbon particles in auto-rickshaws in New Delhi, India. Atmos Environ 2011; 45: 4470–4480.

    Article  CAS  Google Scholar 

  33. McMeeking GR, Good N, Petters MD, McFiggans G, Coe H . Influences on the fraction of hydrophobic and hydrophilic black carbon in the atmosphere. Atmos Chem Phys 2011; 11: 5099–5112.

    Article  CAS  Google Scholar 

  34. Nakayama T, Suzuki H, Kagamitani S, Ikeda Y, Uchiyama A, Matsumi Y . Characterization of a three wavelength photoacoustic soot spectrometer (PASS-3) and a photoacoustic extinctiometer (PAX). J Meteorol Soc Jpn Ser II 2015; 93: 285–308.

    Article  Google Scholar 

  35. Good N, Mölter A, Ackerson C, Bachand A, Carpenter T, Clark ML et al. The Fort Collins Commuter Study: impact of route type and transport mode on personal exposure to multiple air pollutants. J Expo Sci Environ Epidemiol 2016; 26: 397–404.

    Article  CAS  Google Scholar 

  36. Gysel M, Laborde M, Olfert JS, Subramanian R, Gröhn AJ . Effective density of Aquadag and fullerene soot black carbon reference materials used for SP2 calibration. Atmos Meas Tech 2011; 4: 2851–2858.

    Article  CAS  Google Scholar 

  37. Moteki N, Kondo Y . Dependence of laser-induced incandescence on physical properties of black carbon aerosols: measurements and theoretical interpretation. Aerosol Sci Technol 2010; 44: 663–675.

    Article  CAS  Google Scholar 

  38. Moteki N, Kondo Y, Takegawa N, Nakamura S-I . Directional dependence of thermal emission from nonspherical carbon particles. J Aerosol Sci 2009; 40: 790–801.

    Article  CAS  Google Scholar 

  39. Bond TC, Bergstrom RW . Light absorption by carbonaceous particles: an investigative review. Aerosol Sci Technol 2006; 40: 27–67.

    Article  CAS  Google Scholar 

  40. Drinovec L, Mocnik G, Zotter P, Prevot ASH, Ruckstuhl C, Coz E et al. The "dual-spot" Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation. Atmos Meas Tech 2015; 8: 1965–1979.

    Article  CAS  Google Scholar 

  41. Kirchstetter TW, Novakov T . Controlled generation of black carbon particles from a diffusion flame and applications in evaluating black carbon measurement methods. Atmos Environ 2007; 41: 1874–1888.

    Article  CAS  Google Scholar 

  42. Igor Pro 6. Wavemetrics Inc.: OR, USA.

  43. R version 3.2.2. The R Foundation for Statistical Computing: Austria.

  44. RStudio 0.99.473. RStudio Inc.: Boston, MA, USA.

  45. Royston P, Altman DG . Regression using fractional polynomials of continuous covariates - parsimonious parametric modeling. Appl Stat 1994; 43: 429–467.

    Article  Google Scholar 

  46. Sauerbrei W, Royston P . Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials. J R Stat Soc A Stat 1999; 162: 71–94.

    Article  Google Scholar 

  47. Saathoff H, Moehler O, Schurath U, Kamm S, Dippel B, Mihelcic D . The AIDA soot aerosol characterisation campaign 1999. J Aerosol Sci 2003; 34: 1277–1296.

    Article  CAS  Google Scholar 

  48. Armstrong BG . Effect of measurement error on epidemiological studies of environmental and occupational exposures. Occup Environ Med 1998; 55: 651–656.

    Article  CAS  Google Scholar 

  49. Hagler GSW. . Post-processing method to reduce noise while preserving high time resolution in aethalometer real-time black carbon data. Aerosol Air Qual Res 2011; 11: 539–546.

    Article  Google Scholar 

  50. Dons E, Int Panis L, Van Poppel M, Theunis J, Wets G . Personal exposure to Black Carbon in transport microenvironments. Atmos Environ 2012; 55: 392–398.

    Article  CAS  Google Scholar 

  51. Koehler KA, Good N, Moore B, L'Orange C, Clark ML, Kayne A et al. "A holistic approach to microenvironmental exposure assessment: home, work, and commute personal exposures to particulate air pollution." Abstract #O-1-10-05. ISEE/ISES Joint International Conference on Environment and Health. Basel, Switzerland. 2013. http://ehp.niehs.nih.gov/isee/wp-content/uploads/2013/09/EHB13-Abstracts.pdf. Accessed online 6 December 2016.

  52. Van Poppel M, Peters J, Bleux N . Methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments. Environ Pollut. 2013; 183: 224–233.

    Article  CAS  Google Scholar 

  53. Jarjour S, Jerrett M, Westerdahl D, de Nazelle A, Hanning C, Daly L et al. Cyclist route choice, traffic-related air pollution, and lung function: a scripted exposure study. Environ Health 2013; 12: 14.

    Article  Google Scholar 

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Acknowledgements

This work was funded by the United States Department of Health and Human Services (HHS), National Institute of Health (NIH), National Institute of Environmental Health Sciences (NIEHS) under grant R01ES020017. The content of this article is solely the authors’ responsibility and does not necessarily represent official views of the HHS, NIH or NIEHS.

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Correspondence to John Volckens.

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Good, N., Mölter, A., Peel, J. et al. An accurate filter loading correction is essential for assessing personal exposure to black carbon using an Aethalometer. J Expo Sci Environ Epidemiol 27, 409–416 (2017). https://doi.org/10.1038/jes.2016.71

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