the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Mar 2024
Process Analysis of Elevated Concentrations of Organic Acids at Whiteface Mountain, New York
Abstract. Organic acids represent an important class of compounds in the atmosphere but there are many uncertainties in understanding their formation; in particular, few investigations have been carried out as to their sources in the Northeast U.S. Associated with a heat wave and pollution event on 1–2 July, 2018, unusually high concentrations of formic (HCOOH), acetic (CH3COOH), and oxalic (OxAc) acid in cloud water were measured at the summit of Whiteface Mountain (WFM) in upstate New York. To investigate the gas phase production of organic acids for this pollution event, this work uses a combination of the regional transport model WRF-Chem which gives information on transport and environmental factors affecting air parcels reaching WFM, the Lagrangian chemical box model BOXMOX, which allows analysis analysi of chemistry with different chemical mechanisms. Two chemical mechanisms are used in BOXMOX: 1) the Model for Ozone and Related chemical Tracers (MOZART T1), and 2) the Master Chemical Mechanism version 3.3.1 (MCM). The WRF-Chem results show that air parcels sampled during the pollution event at WFM originated in central Missouri, which has strong biogenic emissions of isoprene. Many air parcels were influenced by emissions of nitrogen oxides (NOx) from the Chicago Metropolitan Area. Ozonolysis of isoprene and related oxidation products were the major sources of HCOOH in both mechanisms. CH3COOH was produced from acetyl peroxy radical (CH3CO3) reacting with the hydroperoxy (HO2) radical, with MCM producing up to 40 % more CH3COOH under conditions of high isoprene and low NOx compared to MOZART T1. Both mechanisms underpredicted HCOOH and and CH3COOH by an order of magnitude compared to measurements at WFM. A simple gas+aqueous box model was used to determine if cloud water chemistry could have had an appreciable impact on organic acid formation. Aqueous chemistry exacerbated the discrepancies of HCOOH by leading to a net depletion within cloud water. There were large disagreements in the production of glyoxal (a key precursor of OxAc) between the two gas-phase mechanisms, with MOZART T1 showing stronger daytime production under high NOx conditions, while MCM showed strong nocturnal production via ozonolysis chemistry. The gas + aqueous model exhibited strong production of OxAc within cloud droplets, with glyoxal serving as an important precursor. The substantial differences between chemical mechanisms and between observations and models indicates that further studies are required to better constrain gas and aqueous production of low molecular weight organic acids.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Review of “Process Analysis of Elevated Concentrations of Organic Acids at Whiteface Mountain, New York” by Lawrence et al.', Anonymous Referee #1, 01 Apr 2024
Review of “Process Analysis of Elevated Concentrations of Organic Acids at Whiteface Mountain, New York” by Lawrence et al.
This manuscript describes a comprehensive modeling and cloud sampling project to understand organic acid concentrations present in cloud water collected at Whiteface Mountain (WFM) – a lone massif with complex micrometeorology. The authors employ HYSPLIT back trajectories to understand where air masses encountered at WFM are derived from. They employ WRF-Chem to understand gas-phase mixing ratios of water-soluble organic gases likely to be present. They model gas phase chemistry with two different mechanisms and explore differences in predicted concentrations of water-soluble gases, with a focus on glyoxal. They compare these predictions to measurements from aqueous cloud samples.
This work is sufficiently novel and important that it warrants publication. However, there are several items that need to be addressed before final acceptance.
In the Abstract the authors state, “aqueous chemistry exacerbated the discrepancies of HCOOH leading to a net depletion”. Which discrepancies – between models or in relation to measurements at WFM? The cloud samples are collected in bulk at 12 hour intervals. Can nighttime vs. daytime differences in the cloud samples be teased out to understand potential accuracy of model differences in their prediction of the predominance of glyoxal production pathway (i.e., nighttime from the ozonolysis of an isoprene hydroperoxy aldehyde vs. daytime oxidation of the lumped peroxy radical XO2 reaction with NO)? Perhaps the NOx emission timing and concentrations are too uncertain.
The authors assume gas-to-droplet partitioning and do not consider aqueous phase production and then find that the gas-phase predictions are an order of magnitude lower than WFM cloud water measurements. Is there any understanding from Barth et al., (2021) cited in the manuscript as to which process produces more of the carboxylic acids in cloud water? Is it gas-to-droplet partitioning or in-cloud production?
In this paper, the description of model performance is generally subjective and colloquial. Phrases such as “strong agreement”, “fairly substantial disagreement” etc. are common. It would be better to provide quantitative assessment. For example, tarting on Line 154, the authors state, “There is reasonable agreement of surface O3 and PM2.5 …” Typically models are evaluated with a quantitative description of statistics such as normalized mean bias. Can the authors provide this assessment for PM2.5 and O3 in this simulation and provide context for model performance? I find it is difficult to tell in some areas (e.g., near Lake Michigan) what “reasonable agreement” is. Also, how is the bias/error in the general vicinity of the HYSPLIT trajectory ‘upstream’ of WFM, specifically?
Detailed comments:
Line 51: I think these are all modeling studies with the exception of Blando and Turpin, 2000 which is a literature review of plausibility. It would be good to cite as evidence a glyoxal–OxAc-cloud SOA reference that is experimental (lab or field).
Line 94: “a manuscript regarding organic acid measurements is forthcoming” I find it difficult to assess some of the quantitative description in the absence of constraints on measurement uncertainty.
Line 196: are these gas-phase or aqueous-phase photolysis rates? How were the different?
The authors focus on a high-pressure stagnation event and seek to make associations with NOx. Electricity sector emissions increase during meteorological events like one studied here. Such events are often referred to high electricity demand events and there is increased reliance on peak load units. This may help the authors make their connections to NOx.
Incorporating information used to Figure 8 into Figure 10 that directly compared concentrations from the observation-based estimates to the model predictions would be helpful.
Line 390: I think it is more precise to start this sentence with “*Model predictions suggest* strong isoprene emissions …”
Editorial:
Line 155: “PM 2.5” has a space and the number is not subscript
Starting at line 172: “The complex geography of the Adirondack Mountains are likely not properly captured with a 12kmx12 km horizontal grid resolution …” “geography” is singular and “are” is plural. Also, I am sure there must be a paper describing the complex micrometeorology of WFM. Why not describe is more precisely?
Many of the References are formatted incorrectly: Herckes et al., seems to have a personal note. Sometimes Atmos. Phys. Chem. references have “publisher: Copernicus GmbH”, sometimes they do not.
Citation: https://doi.org/10.5194/egusphere-2024-715-RC1 - AC1: 'Reply on RC1', Christopher Lawrence, 18 Jun 2024
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RC2: 'Comment on egusphere-2024-715', Anonymous Referee #2, 16 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-715/egusphere-2024-715-RC2-supplement.pdf
- AC2: 'Reply on RC2', Christopher Lawrence, 18 Jun 2024
Interactive discussion
Status: closed
-
RC1: 'Review of “Process Analysis of Elevated Concentrations of Organic Acids at Whiteface Mountain, New York” by Lawrence et al.', Anonymous Referee #1, 01 Apr 2024
Review of “Process Analysis of Elevated Concentrations of Organic Acids at Whiteface Mountain, New York” by Lawrence et al.
This manuscript describes a comprehensive modeling and cloud sampling project to understand organic acid concentrations present in cloud water collected at Whiteface Mountain (WFM) – a lone massif with complex micrometeorology. The authors employ HYSPLIT back trajectories to understand where air masses encountered at WFM are derived from. They employ WRF-Chem to understand gas-phase mixing ratios of water-soluble organic gases likely to be present. They model gas phase chemistry with two different mechanisms and explore differences in predicted concentrations of water-soluble gases, with a focus on glyoxal. They compare these predictions to measurements from aqueous cloud samples.
This work is sufficiently novel and important that it warrants publication. However, there are several items that need to be addressed before final acceptance.
In the Abstract the authors state, “aqueous chemistry exacerbated the discrepancies of HCOOH leading to a net depletion”. Which discrepancies – between models or in relation to measurements at WFM? The cloud samples are collected in bulk at 12 hour intervals. Can nighttime vs. daytime differences in the cloud samples be teased out to understand potential accuracy of model differences in their prediction of the predominance of glyoxal production pathway (i.e., nighttime from the ozonolysis of an isoprene hydroperoxy aldehyde vs. daytime oxidation of the lumped peroxy radical XO2 reaction with NO)? Perhaps the NOx emission timing and concentrations are too uncertain.
The authors assume gas-to-droplet partitioning and do not consider aqueous phase production and then find that the gas-phase predictions are an order of magnitude lower than WFM cloud water measurements. Is there any understanding from Barth et al., (2021) cited in the manuscript as to which process produces more of the carboxylic acids in cloud water? Is it gas-to-droplet partitioning or in-cloud production?
In this paper, the description of model performance is generally subjective and colloquial. Phrases such as “strong agreement”, “fairly substantial disagreement” etc. are common. It would be better to provide quantitative assessment. For example, tarting on Line 154, the authors state, “There is reasonable agreement of surface O3 and PM2.5 …” Typically models are evaluated with a quantitative description of statistics such as normalized mean bias. Can the authors provide this assessment for PM2.5 and O3 in this simulation and provide context for model performance? I find it is difficult to tell in some areas (e.g., near Lake Michigan) what “reasonable agreement” is. Also, how is the bias/error in the general vicinity of the HYSPLIT trajectory ‘upstream’ of WFM, specifically?
Detailed comments:
Line 51: I think these are all modeling studies with the exception of Blando and Turpin, 2000 which is a literature review of plausibility. It would be good to cite as evidence a glyoxal–OxAc-cloud SOA reference that is experimental (lab or field).
Line 94: “a manuscript regarding organic acid measurements is forthcoming” I find it difficult to assess some of the quantitative description in the absence of constraints on measurement uncertainty.
Line 196: are these gas-phase or aqueous-phase photolysis rates? How were the different?
The authors focus on a high-pressure stagnation event and seek to make associations with NOx. Electricity sector emissions increase during meteorological events like one studied here. Such events are often referred to high electricity demand events and there is increased reliance on peak load units. This may help the authors make their connections to NOx.
Incorporating information used to Figure 8 into Figure 10 that directly compared concentrations from the observation-based estimates to the model predictions would be helpful.
Line 390: I think it is more precise to start this sentence with “*Model predictions suggest* strong isoprene emissions …”
Editorial:
Line 155: “PM 2.5” has a space and the number is not subscript
Starting at line 172: “The complex geography of the Adirondack Mountains are likely not properly captured with a 12kmx12 km horizontal grid resolution …” “geography” is singular and “are” is plural. Also, I am sure there must be a paper describing the complex micrometeorology of WFM. Why not describe is more precisely?
Many of the References are formatted incorrectly: Herckes et al., seems to have a personal note. Sometimes Atmos. Phys. Chem. references have “publisher: Copernicus GmbH”, sometimes they do not.
Citation: https://doi.org/10.5194/egusphere-2024-715-RC1 - AC1: 'Reply on RC1', Christopher Lawrence, 18 Jun 2024
-
RC2: 'Comment on egusphere-2024-715', Anonymous Referee #2, 16 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-715/egusphere-2024-715-RC2-supplement.pdf
- AC2: 'Reply on RC2', Christopher Lawrence, 18 Jun 2024
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Christopher Lawrence
Mary Barth
John Orlando
Paul Casson
Richard Brandt
Daniel Kelting
Elizabeth Yerger
Sara Lance
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(10451 KB) - Metadata XML
-
Supplement
(9175 KB) - BibTeX
- EndNote
- Final revised paper