the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Sep 2025
PAMS-Constrained Top-Down Calibration of VOC-Speciated CMAQ Simulations
Abstract. Accurate simulation of volatile organic compound (VOC) emissions and their role in ozone (O3) formation remains a persistent challenge in chemical transport models (CTMs). Most models rely on lumped surrogate species, limiting their ability to represent speciated VOCs and directly compare with observations. In this study, we develop an enhanced version of the Community Multiscale Air Quality model, termed CMAQ-PAMS, which explicitly incorporates 54 VOC species targeted by the Photochemical Assessment Monitoring Stations (PAMS) network in Taiwan.
We evaluate model performance during a representative high-ozone event in fall 2021 and apply a top-down calibration approach using hourly VOC data from 12 PAMS sites. The original simulation (OrigSIM) significantly misrepresents key species, largely due to reliance on U.S.-based speciation profiles. After adjustment, the modified simulation (ModSIM) shows substantial improvements in both individual species concentrations and group-level composition (e.g., alkanes, aromatics). Notably, acetylene, a key tracer of incomplete combustion, was underestimated in OrigSIM but successfully recovered in ModSIM.
Despite accounting for only ~32 % of total VOC emissions, PAMS species contribute up to 52 % of modeled domestic O3 formation, highlighting their disproportionate impact in VOC-limited regimes. Additionally, the CMAQ-PAMS framework enables the use of diagnostic ratios (e.g., propylene/acetylene) to identify emission sources and assess air mass aging. These findings underscore the importance of localized VOC profiling and demonstrate that the PAMS-constrained CMAQ-PAMS model provides a more chemically detailed and observationally anchored platform for ozone modeling and regulatory applications.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4664', Anonymous Referee #1, 30 Oct 2025
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RC2: 'Comment on egusphere-2025-4664', Anonymous Referee #2, 05 Nov 2025
General Comments
In this study, the authors have incorporated speciated VOC measurements from Taiwan’s PAMS network into the CMAQ model, addressing the limitations of conventional lumped-species chemical mechanisms. The revised model is now capable of explicitly simulating 54 PAMS-targeted species, more direct and comparable evaluation against observed VOC data. This work is timely and valuable, however, there exists some issues which need to be addressed before publishing. Therefore, it requires substantial revisions to improve its clarity and presentation. I recommend a major revision. The specific suggestions are as follows:
Specific Comments
1. Lines 25–30: Could the authors clarify which substances are included under the term “most primary pollutants”?
2. Lines 35–40: While “grouping chemically similar VOCs into lumped surrogate species” is a common approach, it is not the only method used. I suggest the authors provide a more comprehensive overview of chemical mechanisms employed in chemical transport models (CTMs).
3. Lines 70–75: The Introduction lacks sufficient context regarding the significance and necessity of developing CMAQ-PAMS.
4. Lines 80–85: Please provide detailed information on the 54 PAMS species and their corresponding mappings in the CB05e51 and CB6r3 mechanisms directly.
5. Lines 85–90: The reference to (Knote et al.) appears to be incomplete.
6. line100: The additional chemical reaction pathways should be presented as supplementary.
7. lines 119-121: The processes of converting VOC concentrations into emission rates and spatially allocating these emissions within a gridded inventory remain unclear.
8. Lines 145–150: The statement “the transboundary influence for the PAMS species
is limited” represents a rather bold assumption. What evidence supports this claim? It also appears to be inconsistent with the results discussed in Section 5.3.
9. Line 164, figure S2: Is it showing the O3 vertical profile? What does the left axis stand for? How were the vertical winds observed?
10. Section 3.3: What is the rationale for comparing the computational times of the new (cb6rpams_ae6) and the old (cb6r3_ae6) chemical mechanisms in this study?
11. It is strongly recommended that Sections 2, 3, and 4 be combined into a single “Materials and Methods” section to enhance the overall readability of the paper.
12. Figure 3. Why are only the results for the W-site presented? How do the results from other types of sites compare, and what are the key similarities or differences among them?
13. Lines 365–370: What exactly is meant by “local circulation” in this manuscript? In what ways does it affect the spatial distribution of pollutants?
14. Figure 6: The title, figure number, content, and caption should remain together rather than separated. Furthermore, to enable a more straightforward comparison, the units (kg/hr and ppbC) should be converted and the time zones harmonized.
15. It is recommended to provide relevant evidence to demonstrate that Taiwan is in a “VOC-limited regime”.
Technical Corrections
1. The citations in the manuscript are not properly formatted. For example, in lines 50-60, “Yang et al. (Yang et al., 2005) analyzed …” should be “Yang et al. (2005) analyzed …”. In lines 70-75, “(Chen et al., 2010; Ying and Li, 2011; Chen et al., 2014a; Chen et al., 2015; Su et al., 2016). (Ge et al., 2024; Rowlinson et al., 2024)” should be “(Chen et al., 2010, 2014a, 2015; Ge et al., 2024; Rowlinson et al., 2024; Su et al., 2016; Ying and Li, 2011)”.
2. The manuscript uses both “ozone” and “O3” in different places; it is recommended to use a consistent notation throughout.
3. Lines 95: Change to “Figure 1. The CMAQ modeling framework revised for
CMAQ-PAMS (red parts).”
4. A few spelling and grammatical errors in the manuscript need to be corrected.
Citation: https://doi.org/10.5194/egusphere-2025-4664-RC2
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- 1
This manuscript by Chen et al. modified the chemical mechanism of the CMAQ model to incorporate 54 VOC species included in PAMS. Furthermore, the anthropogenic VOC emissions in the emission inventory were adjusted under the constraint of PAMS observation data from Taiwan, resulting in modeled VOC concentration results that are close to the observed levels. This study conducts model evaluation for individual PAMS VOC species.
Main comments:
1. The authors appear to frame the inclusion of PAMS species as a key feature of this study. Based on current research in this field, lumped mechanisms are widely recognized as a reliable method for improving model operational efficiency—specifically by grouping species with similar photochemical reaction behaviors. Different gas-phase chemical mechanisms may treat certain species (deemed important) as individual components, whether in the context of emissions or chemical reaction mechanisms. More notably, the explicit Master Chemical Mechanism (MCM) includes no fewer than 6,000 explicit species. Therefore, the novelty of developing the CMAQ-PAMS modeling system needs to be discussed in Introduction and Discussion section.
2. Although Figure 1 is provided to introduce the CMAQ-PAMS modeling system, it only shows where modifications were made to the model. The process of inventory adjustment and model modification are needed. For instance, how to generate emissions of PAMS species into the CB mechanism via SPECIATE. Mabe it is necessary to include at least one table in the appendices that presents the proportion of each PAMS species within lumped species, preferably disaggregated by emission source.
3. There is no doubt that using VOC observation data to constrain emissions is an effective method for improving VOC simulation performance. However, details are needed for the approach used to adjust emissions:
4. Lines 90–91: Adjustments to PAMS emissions would likely have a significant impact on O3 formation—insights that could help us better understand the role of VOC emissions in pollutant simulation. What are the results of O3?
Minor comments:
1. There are multiple instances of inconsistent subscript formatting for O3 and NOx throughout the manuscript, such as in Line 9, Line 29, Line 35, and Line 37. Please standardize subscript formats; as inconsistencies may be interpreted as evidence of AI-generated content.
2. Lines 34–39: This section summarizes the research status of VOCs in air quality models, but every sentence lacks supporting literature citations.
3. There are numerous issues with the reference citation format in the manuscript. For example: Line 50: Cardelino and Chameides (Cardelino and Chameides, 1990)→Cardelino and Chameides (1990); Line 87: (Knote et al.) → (Knote et al., 2015). Please standardize all reference citations to comply with the journal’s formatting requirements.
4. Sections 2–4 can be merged into a single chapter titled "Materials and Methods".
5. Lines 142–144: For the 2021 simulation, the 2010 emission inventory used in the manuscript appears outdated. Although the simulation performance of NOₓ and O₃ shown in Figure S3 seems acceptable, statistical parameters (e.g., R2, NMB, NME) should be added to verify the simulation accuracy.
6. Improve the standardization of figures and tables. This encompasses, but is not limited to, Figure 3, Table 3, Figure 5, Figure 6, Figure 8, and most figures in the supplementary information. Specifically: Use a consistent Arial font across all figures; Standardize axis scales and labels; Ensure no single figure spans multiple pages. These adjustments are necessary to meet the journal’s formatting standards.
7. Lines 350–356: Does Table 2 present the average values of adjustment coefficients? If so, this should be clearly indicated in the table title to avoid ambiguity for readers.
8. Line 375: The manuscript mentions that the improved simulation includes explicit ISOP compared to previous mechanisms. However, many current research already considered and analyzed ISOP as an individual species. The authors should clarify: What distinguishes your results from these prior studies?