Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust
<p>The determination of mineral dust and elemental carbon in snow samples is of great interest, since both compounds are known to be light-absorbing snow impurities. Different analytical methods have to be used to quantify both compounds. The occurrence of mineral dust, which contains hematite...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-09-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/15/5207/2022/amt-15-5207-2022.pdf |
| _version_ | 1798033004727107584 |
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| author | D. Kau M. Greilinger B. Kirchsteiger A. Göndör C. Herzig A. Limbeck E. Eitenberger A. Kasper-Giebl |
| author_facet | D. Kau M. Greilinger B. Kirchsteiger A. Göndör C. Herzig A. Limbeck E. Eitenberger A. Kasper-Giebl |
| author_sort | D. Kau |
| collection | DOAJ |
| description | <p>The determination of mineral dust and elemental carbon in
snow samples is of great interest, since both compounds are known to be light-absorbing snow impurities. Different analytical methods have to be used to
quantify both compounds. The occurrence of mineral dust, which
contains hematite, leads to a bias in the quantification of elemental carbon and organic carbon via thermal–optical analysis. Here we present an approach
which utilizes this interference to determine the concentration of iron via
thermal–optical analysis using a Lab OC <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="1b4178c77ca0d4bfee6c9ddd864f3a43"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-15-5207-2022-ie00001.svg" width="8pt" height="14pt" src="amt-15-5207-2022-ie00001.png"/></svg:svg></span></span> EC Aerosol Analyzer (Sunset
Laboratory Inc.) and the EUSAAR2 protocol. For this, the temperature
dependency of the transmittance signal determined during the calibration
phase, i.e., when all carbonaceous compounds are already removed, is
evaluated. Converting the transmittance signal into an attenuation, a linear relationship between this attenuation and the iron loading is obtained for loadings ranging from 10 to 100 <span class="inline-formula">µ</span>g Fe cm<span class="inline-formula"><sup>−2</sup></span>.
Furthermore, evaluation of the transmittance signal during the
calibration phase allows to identify samples which need to be re-evaluated,
since the analysis of elemental carbon and organic carbon is biased by
constituents of mineral dust. The method, which was initially designed for snow
samples, can also be used to evaluate particulate matter samples collected
within the same high alpine environment. When applying the method to a new
set of samples it is crucial to check whether the composition of iron
compounds and the sample matrix remain comparable. If other sources than
mineral dust determine the iron concentration in particulate matter, these
samples cannot be evaluated with thermal–optical analysis. This is shown
exemplarily with data from particulate matter samples collected in a railway
tunnel.</p> |
| first_indexed | 2024-04-11T20:23:15Z |
| format | Article |
| id | doaj.art-f47f8d0b18b34050947d62f703029d66 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-04-11T20:23:15Z |
| publishDate | 2022-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-f47f8d0b18b34050947d62f703029d662022-12-22T04:04:46ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482022-09-01155207521710.5194/amt-15-5207-2022Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dustD. Kau0M. Greilinger1B. Kirchsteiger2A. Göndör3C. Herzig4A. Limbeck5E. Eitenberger6A. Kasper-Giebl7Institute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaSection Climate Monitoring and Cryosphere, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, 1190, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, AustriaInstitute of Technologies and Analytics, TU Wien, Vienna, 1060, Austria<p>The determination of mineral dust and elemental carbon in snow samples is of great interest, since both compounds are known to be light-absorbing snow impurities. Different analytical methods have to be used to quantify both compounds. The occurrence of mineral dust, which contains hematite, leads to a bias in the quantification of elemental carbon and organic carbon via thermal–optical analysis. Here we present an approach which utilizes this interference to determine the concentration of iron via thermal–optical analysis using a Lab OC <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mo>/</mo></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="8pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="1b4178c77ca0d4bfee6c9ddd864f3a43"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="amt-15-5207-2022-ie00001.svg" width="8pt" height="14pt" src="amt-15-5207-2022-ie00001.png"/></svg:svg></span></span> EC Aerosol Analyzer (Sunset Laboratory Inc.) and the EUSAAR2 protocol. For this, the temperature dependency of the transmittance signal determined during the calibration phase, i.e., when all carbonaceous compounds are already removed, is evaluated. Converting the transmittance signal into an attenuation, a linear relationship between this attenuation and the iron loading is obtained for loadings ranging from 10 to 100 <span class="inline-formula">µ</span>g Fe cm<span class="inline-formula"><sup>−2</sup></span>. Furthermore, evaluation of the transmittance signal during the calibration phase allows to identify samples which need to be re-evaluated, since the analysis of elemental carbon and organic carbon is biased by constituents of mineral dust. The method, which was initially designed for snow samples, can also be used to evaluate particulate matter samples collected within the same high alpine environment. When applying the method to a new set of samples it is crucial to check whether the composition of iron compounds and the sample matrix remain comparable. If other sources than mineral dust determine the iron concentration in particulate matter, these samples cannot be evaluated with thermal–optical analysis. This is shown exemplarily with data from particulate matter samples collected in a railway tunnel.</p>https://amt.copernicus.org/articles/15/5207/2022/amt-15-5207-2022.pdf |
| spellingShingle | D. Kau M. Greilinger B. Kirchsteiger A. Göndör C. Herzig A. Limbeck E. Eitenberger A. Kasper-Giebl Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust Atmospheric Measurement Techniques |
| title | Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust |
| title_full | Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust |
| title_fullStr | Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust |
| title_full_unstemmed | Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust |
| title_short | Thermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dust |
| title_sort | thermal optical analysis of quartz fiber filters loaded with snow samples determination of iron based on interferences caused by mineral dust |
| url | https://amt.copernicus.org/articles/15/5207/2022/amt-15-5207-2022.pdf |
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