Modelling the impacts of emission changes on O3 sensitivity, atmospheric oxidation capacity and pollution transport over the Catalonia region
Abstract. Tropospheric ozone (O3) is an important surface pollutant in urban areas, and it has complex formation mechanisms that depend on the atmospheric chemistry and meteorological factors. The severe reductions observed in anthropogenic emissions during the COVID-19 pandemic can further our understanding of the photochemical mechanisms leading to O3 formation and provide guidance for policies aimed at reducing air pollution. In this study, we use the air quality model WRF-Chem coupled with the urban canopy model BEP-BEM to investigate changes in the ozone chemistry over the Metropolitan Area of Barcelona (AMB) and its atmospheric plume moving northwards, which is responsible for the highest number of hourly O3 exceedances in Spain. The trajectories of the air masses from the AMB to the Pyrenees are studied with the Lagrangian particle dispersion model FLEXPART-WRF. The aim is to investigate the response of ozone chemistry to changes in the precursor emissions. The results show that with the reduction in emissions: 1) the ozone chemistry tends to enter the nitrogen oxide (NOx)-limited or transition regimes; however, highly polluted urban areas are still in the Volatile Organic Compounds (VOC)-limited regime, 2) the reduced O3 production is overwhelmed by reduced nitric oxide (NO) titration, resulting in a net increase in the O3 concentration (up to 20 %) in the evening, 3) the increase in the maximum O3 level (up to 6 %) during the lockdown could be attributable to an enhancement in the atmospheric oxidation capacity (AOC), 4) the daily maximum levels of ozone and odd oxygen species (Ox) generally decreased (4 %) in May with the reduced AOC, indicating an improvement in the air quality, and, 5) ozone precursor concentration changes in the AMB contribute to the pollution plume moving along the S–N valley to the Pyrenees. Our results indicate that O3 abatement strategies cannot rely only on NOx emission control but must include a significant reduction in anthropogenic sources of VOCs (e.g., for power plants and heavy industry). In addition, our results show that mitigation strategies intended to reduce O3 should be designed according to the local meteorology, air transport, particular ozone regimes and AOC of the urban area.
Alba Badia et al.
Status: open (until 22 Apr 2023)
- RC1: 'Comment on egusphere-2023-160', Anonymous Referee #1, 28 Mar 2023 reply
Alba Badia et al.
Alba Badia et al.
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This is a very nice analysis that provides a lot of useful information and insight regarding the production of ozone associated with the reduction of anthropogenic emissions during the COVID-19 pandemic, as well as the changes in the chemical regime associated with it.
Line 22: Add more recent references as Fleming et al (2018), Sillman et al (2021)
Line 70: remove 70
Section 2: some of the discussion belongs to Introduction.
Lines 174-185: the discussion could be part of the supplementary material.
Line 193: Fig 2 is refereed first time after Figs. 3 and 4
Section 3.1: Mar et al (2016), Im et al (2016) showed that RADM2 underestimates the O3 concentration when compared to other chemical mechanisms. A discussion about the choice of chemical mechanism would be beneficial since it looks like the Authors obtained the right answers for the wrong reasons.
Section 3.3: Please check the numbers in the Tables, not always the MB=MM-OM
Lines 301-314: A lot of this information should go to the Figures caption (e.g. “The dots in the lower row represent the land use for each grid cell, which is the key to understanding how industrial, open urban, compact urban, water, agriculture, natural open and forestland uses influenced the O3 regimes”)
Line 315: please specify the land-use categories that belong to “green areas”.
Figures 3-4: Increase the size of the cross and explain what it represents.
Figure 5 Sectors A and G, B and H, as well as the pollutants CO and NOx and NH3 and PM10 have similar colors and it is difficult to distinguish between different lines.
Figures 6-8 As before, we can’t really distinguish the colors. I would suggest using a discrete color scale.
Figures 12-14 There is no reference to these Figures in the text.
Table 1 define F0, F1, F2, F3
Fleming, Z., Doherty, R., Von Schneidemesser, E., Malley, C., Cooper, O., Pinto, J., Colette, A., Xu, X., Simpson, D., Schultz, M., Lefohn, A., Hamad, S., Moolla, R., Solberg, S., and Feng, Z.: Tropospheric Ozone Assessment Report: Present-day ozone distribution and trends relevant to human health, Elementa, 6, 12, https://doi.org/10.1525/elementa.273, 2018
Sillmann, J., Aunan, K., Emberson, L., Büker, P., Van Oort, B., O'Neill, C., Otero, N., Pandey, D., and Brisebois, A.: Combined impacts of climate and air pollution on human health and agricultural productivity, Environ. Res. Lett., 16, 093004, https://doi.org/10.1088/1748-9326/ac1df8, 2021.
Mar, K. A., Ojha, N., Pozzer, A., and Butler, T. M.: Ozone air quality simulations with WRF-Chem (v3.5.1) over Europe: model evaluation and chemical mechanism comparison, Geosci. Model Dev., 9, 3699–3728, https://doi.org/10.5194/gmd-9-3699-2016, 2016.
Im, U., Bianconi, R., Solazzo, E., Kioutsioukis, I., Badia, A., Balzarini, A., Baro, R., Bellasio, R., Brunner, D., Chemel, C., Curci, G., Flemming, J., Forkel, R., Giordano, L., Jimenez-Guerrero, P., Hirtl, M., Hodzic, A., Honzak, L., Jorba, O., Knote, C., Kuenen, J.J.P., Makar, P.A., Manders-Groot, A., Neal, L., Perez, J.L., Pirovano, G., Pouliot, G., San Jose, R., Savage, N., Schroder, W., Sokhi, R.S., Syrakov, D., Torian, A., Tuccella, P., Werhahn, K., Wolke, R., Yahya, K., Zabkar, R., Zhang, Y., Zhang, J., Hogrefe, C., Galmarini, S., 2015. Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone. Atmos. Environ. 115, 404e420.