Radiocarbon (14C) Analysis of Carbonaceous Aerosols: Revisiting the Existing Analytical Techniques for Isolation of Black Carbon

Dasari, Sanjeev; Wîdory, David

doi:10.3389/fenvs.2022.907467

Cited by 4 publications

(2 citation statements)

References 66 publications

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“…However, the 14 C intercomparisons of all studies were mainly restricted to ambient filter samples or urban dust (SRM 1649a/b), for which the "true" 14 C of EC is not known. As the literature emphasizes (Dasari et al, 2022), even when methods give similar results, it may still be unclear whether the methods give accurate results. In the worst case, if the methods give different results, then it is impossible to determine which method (if any) gives an accurate value (Zenker et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Technical note: Intercomparison Study of the EC Radiocarbon Analysis Methods Using Synthetic Known Samples

Zhang

Zhu

Liu

et al. 2023

Preprint

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Abstract. The accurate identification of elemental carbon (EC) source in aerosol based on radiocarbon (14C) depends on the method of EC isolation. The lack of aerosol EC reference materials with "true" 14C values makes it impossible to evaluate the accuracy of various methods for the analysis of 14C-EC in aerosols. In this study, EC separation methods were evaluated by using samples of mixed biomass burning, vehicle exhaust and coal-combustion. The results show that 14C-EC was not only related to the separation method but also to the types and proportions of biomass sources in the sample. And the Hydropyrolysis (Hypy) method, which can be used to separate a highly stable portion of ECHypy and avoid charring, is a more effective and stable approach for the matrix-independent 14C quantification of EC in aerosols. The 13C-ECHypy and non-fossil ECHypy values of SRM1649b was 24.9 ‰ and 11 %, respectively.

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Section: Introductionmentioning

confidence: 99%

Technical note: Intercomparison Study of the EC Radiocarbon Analysis Methods Using Synthetic Known Samples

Zhang

Zhu

Liu

et al. 2023

Preprint

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“…CC BY 4.0 License. Huntzicker et al, 1982;Zenker et al, 2017;Dasari and Widory, 2022). Typically, two or more heating steps in an inert (i.e., helium) and in an oxidative atmosphere (i.e., 2 % oxygen in helium) are used to desorb OC and EC, respectively.…”

mentioning

confidence: 99%

An Optimised OC/EC Fraction Separation Method for Radiocarbon Source Apportionment Applied to Low-Loaded Arctic Aerosol Filters

Rauber

Salazar

Yttri

et al. 2022

Preprint

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Abstract. Radiocarbon (14C) analysis of carbonaceous aerosols is used for source apportionment, separating the carbon content into fossil vs. non-fossil origin, and is particularly useful when applied to subfractions of total carbon (TC), i.e., elemental carbon (EC), organic carbon (OC), water-soluble OC (WSOC), and water-insoluble OC (WINSOC). However, this requires an unbiased physical separation of these fractions, which is difficult to achieve. Separation of EC from OC using thermal-optical analysis (TOA) can cause EC loss during the OC removal step and form artificial EC from pyrolysis of OC (i.e., so-called charring), both distorting the 14C analysis of EC. Previous work showed that water extraction reduces charring. Here, we apply a new combination of a WSOC extraction and 14C analysis method with an optimised OC/EC separation that is coupled with a novel approach of thermal-desorption modelling for compensation of EC losses. As water-soluble components promote the formation of pyrolytic carbon, water extraction was used to minimise the charring artefact of EC, and the eluate subjected to chemical wet oxidation to CO2 before direct 14C analysis in a gas-accepting accelerator mass spectrometer (AMS). This approach was applied to 13 aerosol filter samples collected at the Arctic Zeppelin Observatory (Svalbard) in 2017 and 2018, covering all seasons, which bear challenges for a simplified 14C source apportionment due to their low loading and the large portion of pyrolysable species. Our approach provided a mean EC yield of 0.87 ± 0.07 and reduced the charring to 6.5 % of the recovered EC amounts. The mean Fraction Modern (F14C) over all seasons was 0.85 ± 0.17 for TC, 0.61 ± 0.17 and 0.66 ± 0.16 for EC before and after correction with the thermal-desorption model, respectively, and 0.81 ± 0.20 for WSOC.

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Technical note: Intercomparison study of the elemental carbon radiocarbon analysis methods using synthetic known samples

Zhang¹,

Zhu²,

Liu³

et al. 2023

Atmos. Chem. Phys.

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Abstract. The accurate identification of elemental carbon (EC) sources in aerosol based on radiocarbon (14C) depends on the method of EC isolation. The lack of aerosol EC reference materials with “true” 14C values makes it impossible to evaluate the accuracy of various methods for the analysis of 14C-EC in aerosols. In this study, EC isolation methods were evaluated by using samples of mixed biomass burning, vehicle exhaust, and coal combustion. The results show that 14C-EC was not only related to the isolation method but also to the types and proportions of biomass sources in the sample. The hydropyrolysis (Hypy) method, which can be used to isolate a highly stable portion of ECHypy and avoid charring, is a more effective and stable approach for the matrix-independent 14C quantification of EC in aerosols. The 13C-ECHypy and non-fossil ECHypy values of Standard Reference Material (SRM) 1649b were −24.9 ‰ and 11 %, respectively.

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Radiocarbon (14C) Analysis of Carbonaceous Aerosols: Revisiting the Existing Analytical Techniques for Isolation of Black Carbon

Cited by 4 publications

References 66 publications

Technical note: Intercomparison Study of the EC Radiocarbon Analysis Methods Using Synthetic Known Samples

Technical note: Intercomparison Study of the EC Radiocarbon Analysis Methods Using Synthetic Known Samples

An Optimised OC/EC Fraction Separation Method for Radiocarbon Source Apportionment Applied to Low-Loaded Arctic Aerosol Filters

Technical note: Intercomparison study of the elemental carbon radiocarbon analysis methods using synthetic known samples

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