The Aethalometer calibration and determination of iron concentration in dust aerosols

Fialho, Paulo; Freitas, Maria do Carmo Duarte; Barata, Filipe Themudo; Vieira, Bruno; Hansen, A. D. A.; Honrath, R. E.

doi:10.1016/j.jaerosci.2006.03.002

Cited by 52 publications

(43 citation statements)

References 19 publications

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“…generalizable because it is sensitive to details of the environment and measurement framework. To begin with, the total iron content obtained from XRF (IMPROVE) or Neutron Activation (Fialho et al 2006) analyses is an imperfect indicator of the specific minerals that absorb. Absorption is sensitive to iron's oxidation state and other distinctions seldom analyzed in PM 2.5 samples (Lafon et al 2006), and to the physical dispersal of the absorbing minerals in the rest of the dust matrix (Sokolik and Toon 1999).…”

Section: Discussionmentioning

confidence: 99%

“…The PTFE sample filter is analyzed for absorption by HIPS as described above, as well as for mass by weighing and elemental composition by X-ray fluorescence (XRF). The XRF element most relevant to our analysis is iron (Fe), which is reliably measured (Hyslop et al 2012(Hyslop et al , 2015 and serves as a tracer both for mineral dusts in general (Hand et al 2016) and for absorbing dusts in particular (Fialho et al 2006;Moosmuller et al 2012). The total Fe measured by XRF is not limited to the (hydr)oxides believed responsible for absorption (Lafon et al 2006;Journet et al 2014;Utry et al 2015), but includes structural Fe in nonabsorbing clays.…”

Section: Datamentioning

confidence: 99%

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A critical review of filter transmittance measurements for aerosol light absorption, and de novo calibration for a decade of monitoring on PTFE membranes

White

Trzepla

Hyslop

et al. 2016

Aerosol Science and Technology

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Section: Discussionmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

A critical review of filter transmittance measurements for aerosol light absorption, and de novo calibration for a decade of monitoring on PTFE membranes

White

Trzepla

Hyslop

et al. 2016

Aerosol Science and Technology

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“…In contrast with other optical measurement techniques such as nephelometry (Anderson et al 1996;Varma et al 2003;AbuRahmah et al 2006;Bond et al 2009;Massoli et al 2009) aethalometry (Hansen et al 1984;Weingartner et al 2003;Fialho et al 2006;Lack et al 2008) and photoacoustic spectroscopy (Arnott et al 1999Raspet et al 2003), there have been few studies of the instrumental limitations that can compromise the accuracy of aerosol optical properties retrieved by A-CRDS. Baynard and co-workers (2007) determined an absolute uncertainty in the measured aerosol extinction coefficient of <1% when including factors such as aerosol transmission efficiency, gas-phase interference, evaporation of volatile compounds and determination of aerosol sample volume.…”

Section: Introductionmentioning

confidence: 99%

Sources of Error and Uncertainty in the Use of Cavity Ring Down Spectroscopy to Measure Aerosol Optical Properties

Miles

Rudić

Orr-Ewing

et al. 2011

Aerosol Science and Technology

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The use of cavity ring down spectroscopy to retrieve aerosol complex refractive index from optical property measurements has seen increasing popularity over the past few years. However, few studies have looked at the limit which sources of error and uncertainty inherent in the cavity ring down method place on the accuracy with which the refractive index can be retrieved. In this paper, we consider both experimental sources of error and those which compromise the theoretical models against which measurements are compared, both reviewing previously published work and presenting new data. Our results show that for absolute measurements made using single-cavity instruments, factors such as uncertainty in the length of the ring down cavity occupied by aerosol and the counting efficiency of the CPC can introduce an error of ∼2.5% into the real part of the refractive index retrieved from experiment. This is significantly higher than the typical 1% error quoted in previously published work. We note that due to the dependence of particle extinction efficiency on diameter, the effect of a given error on measurements for different particle sizes is not constant.

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“…For instance, Fialho et al (2005) differentiated the absorption spectral dependence of dust and BC measured by an aethalometer. In a subsequent study, Fialho et al (2006) calibrated these measurements with Fe on the filters, and derived empirical calibration constants for the determination of the iron concentration from the aethalometer observations. Koven and Fung (2006) employed a similar concept of absorption spectral dependence for the characterization of dust composition; however, they studied sun/sky radiometer measurements through the whole atmospheric column (AERONET) and incorporated the mineralogical effects by using different modeled relative fractions of hematite, silicate and BC.…”

Section: Introductionmentioning

confidence: 99%

The role of iron and black carbon in aerosol light absorption

et al. 2008

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Abstract. Iron is a major component of atmospheric aerosols, influencing the light absorption ability of mineral dust, and an important micronutrient that affects oceanic biogeochemistry. The regional distribution of the iron concentration in dust is important for climate studies; however, this is difficult to obtain since it requires in-situ aerosol sampling or simulation of complex natural processes. Simultaneous studies of aerosol chemical composition and radiometric measurements of aerosol optical properties, which were performed in the Negev desert of Israel continuously for about eight years, suggest a potential for deriving a relationship between chemical composition and light absorption properties, in particular the spectral single-scattering albedo.The two main data sets of the present study were obtained by a sun/sky radiometer and a stacked filter unit sampler that collects particles in coarse and fine size fractions. Analysis of chemical and optical data showed the presence of mixed dust and pollution aerosol in the study area, although their sources appear to be different. Spectral SSA showed an evident response to increased concentrations of iron, black carbon equivalent matter, and their mixing state. A relationship that relates the spectral SSA, the percentage of iron in total particulate mass, and the pollution components was derived. Results calculated, using this relationship, were compared with measurements from dust episodes in several locations around the globe. The comparison showed reasonable agreeCorrespondence to: Y. Derimian (derimian@loa.univ-lille1.fr) ment between the calculated and the observed iron concentrations, and supported the validity of the suggested approach for the estimation of iron concentrations in mineral dust.

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The Aethalometer calibration and determination of iron concentration in dust aerosols

Cited by 52 publications

References 19 publications

A critical review of filter transmittance measurements for aerosol light absorption, and de novo calibration for a decade of monitoring on PTFE membranes

A critical review of filter transmittance measurements for aerosol light absorption, and de novo calibration for a decade of monitoring on PTFE membranes

Sources of Error and Uncertainty in the Use of Cavity Ring Down Spectroscopy to Measure Aerosol Optical Properties

The role of iron and black carbon in aerosol light absorption

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