the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Oct 2023
Summertime tropospheric ozone source apportionment study in Madrid (Spain)
David de la Paz
Juan Manuel de Andrés
Luis Miguel Tovar
Golam Sarwar
Sergey L. Napelenok
Abstract. The design of emission abatement measures to effectivly reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditons and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQv5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.
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David de la Paz et al.
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RC1: 'Comment on egusphere-2023-2056', Anonymous Referee #1, 01 Nov 2023
The manuscript “summertime tropospheric ozone source apportionment study in Madrid (Spain) by de la Paz et al. presents a ozone source apportionment study using ISAM in the CMAQ model over the Madrid region for July 2016.
While the topic of the paper is very interesting and fits into the scope of ACP, the manuscript lacks many important information and the results are discussed in an insufficient way. Therefore, I recommend to reject the manuscript. Please find below a more detailed review given some major and minor comments the authors should consider before the plan to resubmit the publication.
Reading the paper I had several major concerns which needs to be clarified.
1) The authors apply a new version of ISAM in CMAQ 5.3.2 which (to my knowledge) has not been used in similar publications before. According to the authors this new version attributes ozone to all involved precursors and NOT to the limiting precursor (e.g. NOx or VOC). Sadly, the manuscript is lacking any details on the new method. I guess the method is somehow similar to the method presented by Grewe et al., 2017? The results presented in the manuscript heavily depend on this method. Therefore, the method either needs to be presented before in a scientific publication (e.g. an update of Kwok et al., 2015 and not a youtube video) which is cited by the authors or the manuscripts needs to include a detailed presentation/discussion of the revised method.
2) Given the new method, I am missing a detailed discussion of the method and the results in comparison to previous publications ( see for example Butler et al., 2018 for a detailed discussion of many ozone tagging methods). Moreover, I am missing a critical discussion of the model results. As example, Fig.4 shows a contributions of more than 14 % of SNAP6 (solvents) to ozone over the mountain range north of Madrid. Given my understanding of the method and results of similar methods I wonder about this high contribution. How can this be explained? Moreover, I wonder about the small contribution of biogenic emissions, even though they account for a large fraction of the VOC emissions. If the method attributed ozone to all precursors, they should account for a larger fraction (?) Please clarify. In addition, the manuscript is lacking an overview of the definition of the different source attribution sectors (e.g. as table etc). From Fig 11 it seems that 12 different source sectors are considered.
3) I am missing any new results. The large importance of boundary conditions to ozone levels over the Iberian Peninsula have been reported by e.g. Pay et al., 2019. Also the larger importance of regional emissions to high ozone values have been presented in previous publications (maybe not focusing on Madrid). I like the detailed investigation of source attribution results for specific weather patterns, however, for a scientific publication in ACP more detailed analyses are needed in my opinion and the author need to highlight new findings in more detail.
4) The authors mix the physical quantities “concentration” and “mixing ratio”. They use the term concentration and use the unit ppb which suggest a (volume) mixing ratio. Please clarify the used physical quantity. Similarly, Fig. 2 does not give any physical quantities for the emissions. In addition, please clarify what emissions of NOx and VOC are. Are they given in amount of N, NO, NO2 and C or NMHC?
5) Parts of the manuscript are confusing and missing a proper proof-reading. As example, on P5l197 the authors write that Fig. 4 shows “average contributions”. The description of Fig.4, however, indicates that contribution to the 90th percentile of ozone are given. Moreover, I find it very confusing, that the authors only show contributions to ozone attributed to anthropogenic origin. I suggest to always show contributions with respect to total ozone. Otherwise results are very hard to compare to other studies and readers might be confused.
6) In the last subsections the authors present a comparison with measurements. This comparison shows an underestimation of ozone simulated by the model under accumulation conditions during 13 -19 UTC, however the authors do not discuss this model bias. How does it affect the source apportionment results? It seems that the model underestimated local ozone production under this stagnant conditions. To my opinion, the manuscript should start with a model evaluation and discuss the source attribution results critically with respect to the model performance.
7) Given the importance of emissions from the previous day for ozone formation I wonder why the authors attribute them to “IC”. Wouldn’t it be better to account them also sectorwise?
8) Some of the reference seems to be not adequate. As an example, P3l118 cites Borgee et al., 2022 (https://doi.org/10.1016/j.scitotenv.2013.07.093), but I can’t find “tagging” nor “ISAM” in the whole paper. Maybe I misunderstood something, but the authors should check the manuscript carefully.
Some minor comments:
- Introduction: I am missing a discussion of similar source attribution studies (globally, for Europe) and a discussion of comparable source attribution methods.
- Fig 2: COVs instead of VOC
-p5l183 I wonder why the contribution of biogenic emissions is so small (see also major comments above).
- P3l109 What is the temporal resolution of the boundary conditions?
- p2l45 You mean STE is projected to increase? Please clarify.
- P2l47ff I am missing a discussion of the role of the non linearity of the ozone chemistry which lead to an increase of the ozone production efficiency when emissions are reduced. The authors should consider to add this point including a discussion of the relevant literature.
- p2l58 Please fix, should be Paoletti et. al, 2014
- p5l160 How is soil-NOx handled?
- p5l185 But Pay et al, 2019 applies the “old” ISAM tagging, right? So I would expect a difference with the new approach? Please discuss.
References:
Butler, T., Lupascu, A., Coates, J., and Zhu, S.: TOAST 1.0: Tropospheric Ozone Attribution of Sources with Tagging for CESM 1.2.2, Geosci. Model Dev., 11, 2825–2840, https://doi.org/10.5194/gmd-11-2825-2018, 2018
Grewe, V., Tsati, E., Mertens, M., Frömming, C., and Jöckel, P.: Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52), Geosci. Model Dev., 10, 2615–2633, https://doi.org/10.5194/gmd-10-2615-2017, 2017.
Citation: https://doi.org/10.5194/egusphere-2023-2056-RC1 -
CC1: 'Comment on egusphere-2023-2056', Johana Romero Alvarez, 02 Nov 2023
Review article: Summertime tropospheric ozone source apportionment study in Madrid (Spain)
The paper describes a modeling study that investigates the source of summertime surface ozone (O3) in Madrid, Spain, using an integrated source apportionment method within the Community Multiscale Air Quality model (CMAQv5.3.2). The paper highlights the importance of local sources (road traffic) in the build-up of O3 during peak events, which tends to happen during anticyclonic stagnation conditions in summertime. Suggesting that local measurements aim to reduce O3 precursors could have a positive effect during such periods. In general, the findings are valuable for the understanding of the O3 build-up mechanism in the region and, consequently, for policy decision-making.
The narrative in the abstract suggests that the study focused on the source contributions to urban O3 pollution. However, the results include the contribution to O3 in different chemical environments (urban, suburban, and rural); therefore, I believe that the scope needs to be clearly stated in the document. Also, I feel that the source apportionment method is loosely defined in the methods session. Expanding the description of the method with an example of the mechanics would strengthen the paper. It also feels that the discussion of the model evaluation has been skipped, and something is missing in the paper to convince the reader of the model's capabilities to reproduce the meteorology and chemical environment of the period study. It would be helpful to show a time series of O3 at some representative sites (urban, regional, and suburban) to show the diurnal and day-to-day variability (e.g., hourly ozone) and the model performance. This is important as it gives the reader a general idea of the O3 evolution and the pollution episodes, which are investigated throughout the study. Once these issues have been addressed, along with the points below, the manuscript will be suitable for publication.
General Comments
When you say that the contribution from biogenic emissions is relatively small and therefore excluded from the analysis, are you referring to the contribution to regional scale O3? Could you consider including an evaluation of biogenic VOCs, e.g., a time series comparison of isoprene or a statement regarding the performance of the MEGAN model? Biogenic VOCs, in particular isoprene, are important contributors to O3 formation during photochemical O3 episodes, particularly in rural areas but also in urban environments (Dunker et al., 2016), due to their reactivity and abundance. You concluded that biogenic sources are responsible for 42.4% of the total VOCs domain-wide, so an important impact from this source should be expected.
Evaluation of the model is reported in the supplemental material and loosely mentioned in the manuscript. Please adjust section 3 and provide a quantitative statement of the model performance for meteorology and chemistry (especially O3) for the model domains, along with some plots. This could be a spatial contour plot showing the model and observed mean or P95 of O3 or time series of O3 at some representative sites.
Specific Comments
Line 32:33: ‘These measures, however, have failed to significantly improve ozone (O3) ambient concentration levels’. I feel this is a strong affirmation that needs to be re-phrased, taking into account the nonlinearity nature of O3 formation and the different aspects related to the concentrations observed in different chemical environments (e.g., urban, rural, and suburban) as well as the effects of emissions reductions such as the urban decrement.
Line 140: It would be helpful to have a paragraph describing how experiments were designed, for instance, how the chemical cycling is performed and how often the meteorology is restarted.
Line 249: The link provided does not work
Line 360: The link provided does not work
Dunker et al., 2016.https://doi.org/10.1016/j.atmosenv.2016.09.048
Citation: https://doi.org/10.5194/egusphere-2023-2056-CC1 - RC2: 'Comment on egusphere-2023-2056', Anonymous Referee #2, 23 Nov 2023
David de la Paz et al.
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