the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An interlaboratory comparison to quantify oxidative potential measurement in aerosol particles: challenges and recommendations for harmonisation
Abstract. This paper presents the findings from a collaborative interlaboratory comparison exercise designed to assess oxidative potential (OP) measurements conducted by 20 laboratories worldwide. This study represents an innovative effort as the first exercise specifically aimed at harmonising this type of OP assay, setting a new benchmark in the field.
Over the last decade, there has been a noticeable increase in OP studies, with numerous research groups investigating the effects of exposure to air pollution particles through the evaluation of OP levels. However, the absence of standardised methods for OP measurements has resulted in variability in results across different groups, rendering meaningful comparisons challenging. To address this issue, this study engages in an international effort to compare OP measurements using a simplified method (with a dithiothreitol (DTT) assay).
Here, we quantify the OP in liquid samples to focus on the protocol measurement itself, while future ILCs should aim to assess the full-chain process, including the sample extraction. We analyse the similarities and discrepancies observed in the results, identifying the critical parameters (such as the instrument used, the use of a simplified protocol, the delivery and analysis time) that could influence OP measurements, and provide recommendations for future studies and interlaboratory comparisons. Even if other crucial aspects, such as sampling PM methods, sample storage, extraction methods and conditions, and the evaluation of other OP assays, still need to be standardised. This collaborative approach enhances the robustness of the OP-DTT assay and paves the way for future studies to build on a unified framework. This pioneering work concludes that interlaboratory comparisons provide essential insights into the OP metric and are crucial to move toward the harmonisation of OP measurements.
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Status: closed
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RC1: 'Comment on amt-2024-107', Anonymous Referee #4, 15 Sep 2024
Please see my comments in the attached .pdf file.
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AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2024-107/amt-2024-107-AC1-supplement.pdf
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AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
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RC2: 'Comment on amt-2024-107', Anonymous Referee #3, 18 Sep 2024
The strength of this manuscript lies in its cross-laboratory comparison of the DTT assay for evaluating the oxidative potential (OP) of particulate matter. The study's objective—assessing the assay's reliability by involving a relatively large number of laboratories and identifying uncertainties—was clear and well-intentioned. However, I found the analysis of the results lacking in solid statistical foundations. Some data treatments appear arbitrary and lack justification, such as the selection of "assigned values" for bias evaluation, which raises questions about key interpretations. The manuscript can provide clearer statistical inferences, and some results, such as the COV and z-score, appear to overlap statistically, adding redundancy rather than clarity. Citations for some statements are vague, imprecise, or insufficient. While the manuscript presents common statistical values from various labs, It is unclear how these observations provide practically beneficial insights into the variation in outcomes and their underlying causes. Some specific comments are given below.
L99: I cannot reference the citation “WHO 2017” in the reference list.
L 102-103: I find it difficult to precisely support the claims from the references- “Huang et al., 2022; Nicholson et al., 2022; Wilker et al.,103 2023; Zare Sakhvidi et al., 2022 “. I did not find evidence from these studies to link PM to mortality. I also recommend increasing the citations' precision- e.g., cite the exact reference to support the oxidative stress and inflammation in the statement.
L 106: I don't find this reference supporting the claimed "unifying mechanism" from “Li et al., 2018”.
L 333: How do the authors determine the number of 20 here ?
L342 - 343: It is unclear to me what “values obtained for the dataset” that is suggested to jeopardize the use of the algorithm.
L348-351: The authors appear to arbitrarily toss the high-variance outcome. How to justify this without compromising the statistical significance ?
L369-373: Describing more details of the statistical method would be beneficial.
Citation: https://doi.org/10.5194/amt-2024-107-RC2 -
AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2024-107/amt-2024-107-AC1-supplement.pdf
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AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
Status: closed
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RC1: 'Comment on amt-2024-107', Anonymous Referee #4, 15 Sep 2024
Please see my comments in the attached .pdf file.
-
AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2024-107/amt-2024-107-AC1-supplement.pdf
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AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
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RC2: 'Comment on amt-2024-107', Anonymous Referee #3, 18 Sep 2024
The strength of this manuscript lies in its cross-laboratory comparison of the DTT assay for evaluating the oxidative potential (OP) of particulate matter. The study's objective—assessing the assay's reliability by involving a relatively large number of laboratories and identifying uncertainties—was clear and well-intentioned. However, I found the analysis of the results lacking in solid statistical foundations. Some data treatments appear arbitrary and lack justification, such as the selection of "assigned values" for bias evaluation, which raises questions about key interpretations. The manuscript can provide clearer statistical inferences, and some results, such as the COV and z-score, appear to overlap statistically, adding redundancy rather than clarity. Citations for some statements are vague, imprecise, or insufficient. While the manuscript presents common statistical values from various labs, It is unclear how these observations provide practically beneficial insights into the variation in outcomes and their underlying causes. Some specific comments are given below.
L99: I cannot reference the citation “WHO 2017” in the reference list.
L 102-103: I find it difficult to precisely support the claims from the references- “Huang et al., 2022; Nicholson et al., 2022; Wilker et al.,103 2023; Zare Sakhvidi et al., 2022 “. I did not find evidence from these studies to link PM to mortality. I also recommend increasing the citations' precision- e.g., cite the exact reference to support the oxidative stress and inflammation in the statement.
L 106: I don't find this reference supporting the claimed "unifying mechanism" from “Li et al., 2018”.
L 333: How do the authors determine the number of 20 here ?
L342 - 343: It is unclear to me what “values obtained for the dataset” that is suggested to jeopardize the use of the algorithm.
L348-351: The authors appear to arbitrarily toss the high-variance outcome. How to justify this without compromising the statistical significance ?
L369-373: Describing more details of the statistical method would be beneficial.
Citation: https://doi.org/10.5194/amt-2024-107-RC2 -
AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2024-107/amt-2024-107-AC1-supplement.pdf
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AC1: 'Reply on RC2', Pamela Dominutti, 21 Oct 2024
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