the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Source Attribution of Ozone and Precursors in the Northeast U.S. Using Multiple Photochemical Model Based Approaches (CMAQ v5.3.2 and CAMx v7.10)
- U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
- U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
Abstract. The Integrated Source Apportionment Method (ISAM) has been revised in the Community Multiscale Air Quality (CMAQ) model. This work updates ISAM to maximize its flexibility, particularly for ozone (O3) modeling, by providing multiple attribution options, including products inheriting attribution fully from nitrogen oxide reactants, fully from volatile organic compound (VOC) reactants, equally to all reactants, or dynamically to NOx or VOC reactants based on the indicator gross production ratio of hydrogen peroxide (H2O2) to nitric acid (HNO3). This study's primary objective is to document these ISAM updates and demonstrate their impacts on source apportionment results for O3 and its precursors. Additionally, the ISAM results are compared with the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx) and the brute force method (BF). All comparisons are performed for a 4 km horizontal grid resolution application over the northeast U.S. for a selected two-day summer case study (August 9th and 10th, 2018). General similarities among ISAM, OSAT, and BF results add credibility to the new ISAM algorithms. However, some discrepancies in magnitude or relative proportions among tracked sources illustrate the distinct features of each approach while others may be related to differences in model formulation of chemical and physical processes. Despite these differences, OSAT and ISAM still provide useful apportionment data by identifying the geographical and temporal contributions of O3 and its precursors. Both OSAT and ISAM attribute the majority of O3 and NOx contributions to boundary, mobile, and biogenic sources, whereas the top three contributors to VOCs are found to be biogenic, boundary, and area sources.
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Qian Shu et al.
Status: final response (author comments only)
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RC1: 'Comment on gmd-2022-273', Anonymous Referee #1, 28 Dec 2022
General comments
The focus of this manuscript is a comparison of 5 versions of the Integrated Source Apportionment Method (ISAM) in the Community Multiscale Air Quality Model (CMAQ), the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx), and the brute force method in CMAQ. This is a subject of interest to the audience of Geoscientific Model Development. To compare the source apportionment methods, the authors chose the model configurations to be as close as possible, with one exception, and picked days when the MDA8 O3 predictions of the models agreed well. There are numerous results in the manuscript and the supplement. The manuscript is reasonably well written, with some exceptions. A minor exception is that the reference list needs attention; some citations in the text are not in the list and vice versa.
I have two major issues with the manuscript. One is that Section 2 does not adequately describe the new/updated versions of ISAM in enough detail to be understood, nor does this section compare the ISAM versions to OSAT in detail so that the reader can understand the differences between all the methods. The authors should take 2 or 3 reactions of different types and explain, using equations, how the products are allocated to sources and how the allocations propagate to allocation of O3 formation if O3 is not a direct product of the reactions. Given that the authors have submitted the manuscript to Geoscientific Model Development, the readers should be informed of the details of the source allocation methods, to the point that someone could implement such methods in other models. That is a major value of this journal.
My other major issue is that the authors used a different chemical mechanism for the ISAM and OSAT simulations. Because source apportionments depend on the chemistry used, this is a significant limitation of the work and reduces its value to readers. As the authors note, differences in the source apportionments could be due to differences between ISAM and OSAT or due to differences in the chemical mechanisms in the two models or both. Some of the differences in the source apportionments are puzzling, suggesting that the difference in the chemistry could be important. Because the chemistry is different between CMAQ and CAMx, the conclusions of the manuscript are rather vague, e.g., lines 19-23. Consequently, the authors provide little guidance on which ISAM methods should be used and for what purpose.
Specific comments
Line 59. NOx (as NO2) also removes OH to HNO3, and this is usually a greater impact on the O3 formation than the titration of O3. Titration produces NO2, which can quickly photolyze and produce O3 again, but OH loss slows O3 formation for an extended time period.
Line 95. Are the updates just changes to flexibility in application or do they also include more substantial changes that affect how O3 is apportioned to sources?
Lines 150-152. Unclear. How is ISAM-OP3 different from ISAM-OP1?
Lines 154-158. Is ISAM-OP5 the same as OSAT3? If not, what are the differences?
Lines 155-158. This seems in conflict with Table S3. For OP5, Table S3 indicates that the PH2O2/PHNO3 ratio affects whether or not O3 is allocated to VOCs but that O3 is allocated to NOx species whether the ratio is above or below the 0.35 threshold.
Line 160, Table 1, ISAM-OP1. Is the source attribution based on the reaction products or the reactants? Lines 115-125 suggest it is the reactants. Also, for ISAM-OP5, the Table mentions ISAM-OP3 but lines 155-156 mention ISAM-OP2 and ISAM OP4. Confusing and unclear.
What is the total number of tracers used in the different versions of ISAM and in OSAT3?
Are any of the ISAM versions close to or the same as OSAT3? What are the differences between ISAM-OP5 and OSAT3?
Lines 178-185. The authors did a good job of making most configuration options as similar as possible between the models and picking days when the MDA8 O3 predictions of the models agreed well. However, CMAQ used CB6r3 and CAMx used CB6r4. The chemistry is a key driver of the source apportionments, and thus the apportionments will depend on the chemical mechanism. The CMAQ and CAMx simulations should have been done using the same chemical mechanism to eliminate the differences in chemistry as a possible explanation for the differences in the source apportionments. To make this paper useful to the modeling community, one set of simulations should be redone with the chemical mechanism used for the other set of simulations.
Lines 194-215. The description of OSAT3 should be in Section 2, after the description of ISAM. Pick the same 2 or 3 reactions used to give the details of ISAM and give the corresponding details of OSAT3.
Lines 225-235. It is unclear what was done with the OTHR category. Line 226 states that there was a tracer for OTHR but lines 226-227 imply that OTHR was not tagged. Also, why cannot a BF simulation be done removing just the OTHR emissions? Lastly, the OTHR emissions should be included in Table 3 to show how large they are compared to everything else.
Line 240-241. “… ISAM tracks all individual oxidized nitrogen and VOC species, …”. But the footnotes to Table 4 state that ISAM does not track INO3, OPAN and CRON. This seems to be a contradiction. Please revise or provide an explanation why this isn’t a contradiction.
Lines 243-244. “…the two models have distinct species representation.” CB6r3 and CB6r4 have different species? ISAM and OSAT use different species? Please clarify and give examples.
Line 259. Correlation of O3 concentrations? Correlation of all species concentrations?
Line 278. “ …inconsistent predicted concentrations.” Please explain further.
Lines 295-296. The MB and NMB differences diminish for MDA8 O3 but increase for hourly O3.
Line 350. “typically negative.” Typically smaller?
Lines 355-356. “Except for …all sectors.” This sentence is redundant with the following sentence.
Lines 365-376. The results in Figure 5 raise the question of why there is such a large difference between ISAM and OSAT for the BULK VOC results (which are reflected in differences in the BIO VOC, BCON VOC and AREA VOC results), when there is much better agreement in Figures 3 and 4 for BULK O3 and BULK RNOx. The difference for BULK VOC needs further investigation and explanation because it suggests some important difference(s) in the formulation or implementation of ISAM and OSAT. An alternative explanation is that the difference is due to differences in the chemical mechanisms, which should be remedied by using the same mechanism in both models. Because the BULK O3 and BULK RNOx agree reasonably well, other explanations seem unlikely.
Line 391. What is this 5 ppbv? The total (BULK) offshore O3 concentration is clearly above 5 ppbv.
Line 392. “ and gaseous chemical mechanism configuration between the two parent models”. The same mechanism should be used in both models to avoid this ambiguity.
Line 400. “For most sources, OSAT paradoxically shows lower contributions over the ocean.” However, CAMx BULK O3 is larger than CMAQ BULK O3 over the ocean. Assuming that OSAT BULK O3 is the sum of the contributions from the individual source categories, there must be enough increased marine O3 from some sources (e.g., BCON and EGU) that there is no inconsistency/paradox in the OSAT results. The increased O3 is from a few sources, not distributed across all sources, which may be a consequence of the OSAT procedure for allocating O3.
Lines 411-415. The BCON results using OP1, OP4 and OP5 are strange. The authors’ conclusion that the OP1, OP4, and OP5 results are due to VOC or oxidants transported from the boundary is not at all obvious. This is especially true because the OSAT and BF results show little impact of BCON, and the only impact is very near the west boundary. Again, without an understanding of how the products are allocated in ISAM and the impact of the chemistry differences between CB6r3 and CB6r4, it is not possible to understand these BCON results. In addition, the OP1, OP4 and OP5 results for BCON raise the question of whether these versions of ISAM are useful.
Line 416. “Higher VOC concentrations from CAMx already shown in Figure 6 …”. Figure 6 shows O3, not VOC. Should the reference be to Figure 5?
Lines 417-419. “…may result from other differences between two models, like chemistry or deposition, …”. Again, using different chemistry in the two models significantly limits the conclusions that can be obtained with these results, making the paper less valuable to readers and to regulatory officials. The differences between OSAT and ISAM for Bulk VOC and BIO VOC need better explanation.
Lines 419-421. It is surprising that the VOC contribution depends very little on the ISAM version for most source categories, but OP2 gives a significantly greater VOC contribution for CMV, EGU, and RAIL than do the other methods. CMV, EGU, and RAIL are sources with small VOC emissions (Table 3). The results suggest that OP2 is not valuable for source apportionment for sources with small VOC emissions, certainly not to apportion VOC emissions to them.
Lines 455-456. If the CMAQ-BF time is equal to the quantity in parentheses, 60 mins/day X 15, the total should be 900 mins/day.
Lines 476-480. Why does OSAT, which the authors expect to be most similar to OP5 (lines 485-487), give such a smaller contribution of BCON to RNOx than OP5 (and OP1 and OP4) in Figure 7? Does OSAT retain the emitted source identity through fast NOx cycling? The fact that OP1, OP4, and OP5 assign so much RNOx to BCON compared to the BF RNOx results suggest that these ISAM versions are not very accurate for RNOx.
Lines 485-489. There are also significant differences between OSAT and OP5 for O3 apportionment to EGU, NONROAD, and ONROAD sources. These are sources for which it is important to estimate their O3 contributions accurately. Again, the authors need to describe in detail how the source apportionments are done in OP1 - OP5 and contrast those procedures with how the apportionment is done in OSAT so that the reader has some understanding of why these differences occur. Just stating that the procedures differ is not very helpful.
Line 496. OILGAS appears to be about as large as AREA in contribution to VOC (Figures 5 and 8).
Technical corrections
Line 38. Lefohn et al., 1998 citation is not in the reference list.
Line 77. Sillman, 1996 citation is not in the reference list.
Line 90. 2016a should be 2016.
Line 93. Baker and Kelly, 2014 and Baker and Woody, 2017 are not in the reference list.
Line 121. Pierce et al. 1999 is not in the reference list.
Line 171. Henderson et al., 2014 is not in the reference list.
Line 176. Bash et al., 2016 is not in the reference list.
Line 360-361. Burr and Zhang, 2011 is not in the reference list. Jiminez and Baldano,2004 is Jiminez, 2004?
Lines 580-581. There are strings of symbols here that are unintelligible.
Lines 650-653. There are two U.S. EPA (2021) references. These should be labeled 2021a and 2021b and cited as such.
Line 660. 1967 or 1984?
The following publications are in the reference list but I did not find them cited in the text: Baker and Timin (2008); Oltmans et al. (1998); Sarwar et al. (2011)
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RC2: 'Comment on gmd-2022-273', Anonymous Referee #2, 03 Jan 2023
The ISAM is a powerful tool for source apportionment of O3 and PM2.5 in CMAQ. The authors have updated ISAM with more attribution options and compared the results with different options to those using OSAT or the brute force method. Generally, the manuscript is well written, and the work is worthy of publication. There are a few questions that need to be addressed:
- It is not quite clear in what cases or on what purpose is each of the option the best one? For example, is ISAM-OP2 more suitable for RNOx attribution? The authors could elaborate more.
- The CB6R3 and CB6R4 were used in CMAQ and CAMx, respectively. What are the impacts of using different chemical mechanisms?
- Some mistakes in the manuscript. For example, lines 76-77: “when the ratio (PH2O2/PHNO3) is below 0.35, the formation is classified as NOx-limited…”; lines 199-200: “when the ratio of PH2O2/PHNO3 exceeds 0.35, the produced O3 is attributed to VOC emissions…”
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CEC1: 'Comment on gmd-2022-273', Astrid Kerkweg, 06 Jan 2023
Dear authors,
this manuscript is definitely not of the type "methods of model assessment paper" as which it was submitted. It is either of type "development and technical paper" or a "model evaluation" paper.
For a "model evaluation paper", the new ISAM must have been per-reviewed published. This is, as far as I can see, not the case, as the only documentations which are cited in the manuscript are US EPA, 2021 (2 different documents / archives) and US EPA 2022, which all are not per-reviewed literature.
For a "development and technical paper" the details on the new scheme need to be provided within the article. Which seems to me to be not the case by now.
Anyhow, the detailed documentation of the new scheme cited in the article is US EPA 2021 . This relates to https://www.epa.gov/air-emissions-modeling/2016-version-1-technical-support-document . This is a web site which could change its content any time and this is in any case not sufficient as documentation for a GMD publication. The content of this web site needs either to be archived permanently as well (in form of a document with DOI) or as supplement to this article or you have to include all the for ISAM relevant information into your article to meet the requirements of a "development and technical paper".
I will write to the copernicus office to change the type of the paper to "development and technical paper" , please include the required documentation into your manuscript.
Furthermore, the modified code needs to be archived permanently. An "available on request statement" for your codes updates and scripts is not sufficient for publication in GMD
Best regards, Astrid Kerkweg (GMD Executive Editor)
Qian Shu et al.
Qian Shu et al.
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