Articles | Volume 24, issue 23
https://doi.org/10.5194/acp-24-13541-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-13541-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2024
Research article |
| 10 Dec 2024
| 10 Dec 2024
The long-term impact of biogenic volatile organic compound emissions on urban ozone patterns over central Europe: contributions from urban and rural vegetation
Marina Liaskoni
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Lukáš Bartík
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Alvaro Patricio Prieto Perez
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Jan Karlický
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Kateřina Šindelářová
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000 Prague 8, Czechia
Related authors
Marina Liaskoni, Peter Huszar, Lukáš Bartík, Alvaro Patricio Prieto Perez, Jan Karlický, and Ondřej Vlček
Atmos. Chem. Phys., 23, 3629–3654, https://doi.org/10.5194/acp-23-3629-2023, https://doi.org/10.5194/acp-23-3629-2023, 2023
Short summary
Short summary
Wind-blown dust (WBD) emissions emitted from European soils are estimated for the 2007–2016 period, and their impact on the total particulate matter (PM) concentration is calculated. We found a considerable increase in PM concentrations due to such emissions, especially on selected days (rather than on a seasonal average). We also found that WBD emissions are strongest over western Europe, and the highest impacts on PM are calculated for this region.
Jan Karlický, Jáchym Bareš, and Peter Huszár
EGUsphere, https://doi.org/10.5194/egusphere-2025-388, https://doi.org/10.5194/egusphere-2025-388, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Our study includes results of WRF model simulations focused to evaluate sensitivity of local climate in cities on urban surface characteristics. Summer urban heat island is mostly impacted by changes in vegetation cover in city, albedo of roofs and irrigated green roofs. Results are usable also to reveal suitable mitigation strategies for reduction of negative aspects of local climate in cities.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Lukáš Bartík, Peter Huszár, Jan Karlický, Ondřej Vlček, and Kryštof Eben
Atmos. Chem. Phys., 24, 4347–4387, https://doi.org/10.5194/acp-24-4347-2024, https://doi.org/10.5194/acp-24-4347-2024, 2024
Short summary
Short summary
The presented study deals with the attribution of fine particulate matter (PM2.5) concentrations to anthropogenic emissions over Central Europe using regional-scale models. It calculates the present-day contributions of different emissions sectors to concentrations of PM2.5 and its secondary components. Moreover, the study investigates the effect of chemical nonlinearities by using multiple source attribution methods and secondary organic aerosol calculation methods.
Peter Huszar, Alvaro Patricio Prieto Perez, Lukáš Bartík, Jan Karlický, and Anahi Villalba-Pradas
Atmos. Chem. Phys., 24, 397–425, https://doi.org/10.5194/acp-24-397-2024, https://doi.org/10.5194/acp-24-397-2024, 2024
Short summary
Short summary
Urbanization transforms rural land into artificial land, while due to human activities, it also introduces a great quantity of emissions. We quantify the impact of urbanization on the final particulate matter pollutant levels by looking not only at these emissions, but also at the way urban land cover influences meteorological conditions, how the removal of pollutants changes due to urban land cover, and how biogenic emissions from vegetation change due to less vegetation in urban areas.
Marina Liaskoni, Peter Huszar, Lukáš Bartík, Alvaro Patricio Prieto Perez, Jan Karlický, and Ondřej Vlček
Atmos. Chem. Phys., 23, 3629–3654, https://doi.org/10.5194/acp-23-3629-2023, https://doi.org/10.5194/acp-23-3629-2023, 2023
Short summary
Short summary
Wind-blown dust (WBD) emissions emitted from European soils are estimated for the 2007–2016 period, and their impact on the total particulate matter (PM) concentration is calculated. We found a considerable increase in PM concentrations due to such emissions, especially on selected days (rather than on a seasonal average). We also found that WBD emissions are strongest over western Europe, and the highest impacts on PM are calculated for this region.
Peter Huszar, Jan Karlický, Lukáš Bartík, Marina Liaskoni, Alvaro Patricio Prieto Perez, and Kateřina Šindelářová
Atmos. Chem. Phys., 22, 12647–12674, https://doi.org/10.5194/acp-22-12647-2022, https://doi.org/10.5194/acp-22-12647-2022, 2022
Short summary
Short summary
Urbanization turns rural land cover into artificial land cover, while due to human activities, it introduces a great quantity of emissions. We attempt to quantify the impact of urbanization on the final air pollutant levels by looking not only at these emissions, but also the way urban land cover influences meteorological conditions, how the removal of pollutants changes due to urban land cover, and how biogenic emissions from vegetation change due to less vegetation in urban areas.
Katerina Sindelarova, Jana Markova, David Simpson, Peter Huszar, Jan Karlicky, Sabine Darras, and Claire Granier
Earth Syst. Sci. Data, 14, 251–270, https://doi.org/10.5194/essd-14-251-2022, https://doi.org/10.5194/essd-14-251-2022, 2022
Short summary
Short summary
Three new datasets of global emissions of biogenic volatile organic compounds (BVOCs) emitted into the atmosphere from terrestrial vegetation were developed for air quality modelling using the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) driven by European Centre for Medium-Range Weather Forecasts meteorological reanalyses for the years 2000–2019. The datasets include updates of the isoprene emission factors in Europe and study the impact of land cover change on emissions.
Peter Huszar, Jan Karlický, Jana Marková, Tereza Nováková, Marina Liaskoni, and Lukáš Bartík
Atmos. Chem. Phys., 21, 14309–14332, https://doi.org/10.5194/acp-21-14309-2021, https://doi.org/10.5194/acp-21-14309-2021, 2021
Short summary
Short summary
Urban areas are strong hot spots of emissions influencing local and regional air quality. Cities furthermore influence the meteorological conditions due to their characteristic surface properties and geometry. We found that if these latter effects are not included in the quantification of the impact of urban emissions on regional air quality, this impact will be overestimated, and this overestimation is mainly due to the enhanced turbulence that is present in cities compared to rural areas.
Jaroslav Resler, Kryštof Eben, Jan Geletič, Pavel Krč, Martin Rosecký, Matthias Sühring, Michal Belda, Vladimír Fuka, Tomáš Halenka, Peter Huszár, Jan Karlický, Nina Benešová, Jana Ďoubalová, Kateřina Honzáková, Josef Keder, Šárka Nápravníková, and Ondřej Vlček
Geosci. Model Dev., 14, 4797–4842, https://doi.org/10.5194/gmd-14-4797-2021, https://doi.org/10.5194/gmd-14-4797-2021, 2021
Short summary
Short summary
We describe validation of the PALM model v6.0 against measurements collected during two observational campaigns in Dejvice, Prague. The study focuses on the evaluation of the newly developed or improved radiative and energy balance modules in PALM related to urban modelling. In addition to the energy-related quantities, it also evaluates air flow and air quality under street canyon conditions.
Jan Karlický, Peter Huszár, Tereza Nováková, Michal Belda, Filip Švábik, Jana Ďoubalová, and Tomáš Halenka
Atmos. Chem. Phys., 20, 15061–15077, https://doi.org/10.5194/acp-20-15061-2020, https://doi.org/10.5194/acp-20-15061-2020, 2020
Short summary
Short summary
Cities are characterized by their impact on various meteorological variables. Our study aims to generalize these modifications into a single phenomenon – the urban meteorology island (UMI). A wide ensemble of Weather Research and Forecasting (WRF) and Regional Climate Model (RegCM) simulations investigated urban-induced modifications as individual UMI components. Significant changes are found in most of the discussed meteorological variables with a strong impact of specific model simulations.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Tereza Nováková, Kateřina Šindelářová, Filip Švábik, Michal Belda, Tomáš Halenka, and Michal Žák
Atmos. Chem. Phys., 20, 11655–11681, https://doi.org/10.5194/acp-20-11655-2020, https://doi.org/10.5194/acp-20-11655-2020, 2020
Short summary
Short summary
The paper shows how extreme meteorological conditions change due to the urban land-cover forcing and how this translates to the impact on the extreme air pollution over central European cities. It focuses on ozone, nitrogen dioxide, and particulate matter with a diameter of less than 2.5 μm and shows that, while for the extreme daily maximum 8 h ozone, changes are same as for the mean ones, much larger modifications are calculated for extreme NO2 and PM2.5 compared to their mean changes.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Kateřina Šindelářová, Tereza Nováková, Michal Belda, Tomáš Halenka, Michal Žák, and Petr Pišoft
Atmos. Chem. Phys., 20, 1977–2016, https://doi.org/10.5194/acp-20-1977-2020, https://doi.org/10.5194/acp-20-1977-2020, 2020
Short summary
Short summary
Urban surfaces alter meteorological conditions which consequently alter air pollution due to modified transport and chemical reactions. Here, we focus on a major component of this influence, enhanced vertical eddy diffusion. Using a regional climate model coupled to a chemistry transport model, we investigate how different representations of turbulent transport translate to urban canopy impact on ozone and PM2.5 concentrations and whether turbulence remains the most important component.
Peter Huszar, Michal Belda, Jan Karlický, Tatsiana Bardachova, Tomas Halenka, and Petr Pisoft
Atmos. Chem. Phys., 18, 14059–14078, https://doi.org/10.5194/acp-18-14059-2018, https://doi.org/10.5194/acp-18-14059-2018, 2018
Short summary
Short summary
The impact of meteorological changes introduced by urbanization on aerosol concentration using a regional climate model and a chemistry transport model over central Europe is investigated. We found a strong increase of temperature and turbulence and a decrease of humidity and wind speed due to urban surfaces. This resulted in a clear decrease of aerosol concentrations near the surface: PM2.5 concentrations were reduced by 3 μg/m3. The dominating effect is the increased turbulent transport.
Jan Karlický, Peter Huszár, Tomáš Halenka, Michal Belda, Michal Žák, Petr Pišoft, and Jiří Mikšovský
Atmos. Chem. Phys., 18, 10655–10674, https://doi.org/10.5194/acp-18-10655-2018, https://doi.org/10.5194/acp-18-10655-2018, 2018
Short summary
Short summary
Our work presents a comparison of modelled and observed urban-induced meteorological changes in long-term perspective using 10-year simulations. It contains an evaluation of models' urban parameterizations, investigations of the benefits of more sophisticated urban parameterizations with respect to simple approaches and evaluation of urban-induced meteorological changes from the perspective of pollutant dispersion.
Petr Pisoft, Petr Sacha, Jiri Miksovsky, Peter Huszar, Barbara Scherllin-Pirscher, and Ulrich Foelsche
Atmos. Meas. Tech., 11, 515–527, https://doi.org/10.5194/amt-11-515-2018, https://doi.org/10.5194/amt-11-515-2018, 2018
Short summary
Short summary
We revise selected findings regarding utilization of Global Positioning System radio occultation density profiles for analysis of internal gravity waves. The results show that previously published results are valid only for one specific data version only. Using radiosonde profiles, we also analyze a nonhydrostatic component in temperature profiles. The last part presents detailed study on the utilization of density profiles for characterization of the wave field stability.
Jan Karlický, Peter Huszár, and Tomáš Halenka
Adv. Sci. Res., 14, 181–186, https://doi.org/10.5194/asr-14-181-2017, https://doi.org/10.5194/asr-14-181-2017, 2017
Short summary
Short summary
The article describes ability of the numerical atmospheric model WRF-Chem to predict concentrations of main gas pollutants over Europe. Model experiments showed that daily and annual cycles of ozone are well captured, but the model concentrations of nitride dioxide and sulfur dioxide are significantly lower than measured values. The differences between two chemical modules are significant in term of ozone daily cycle, not in the total amount of nitride and sulfur dioxide.
Peter Huszár, Michal Belda, Jan Karlický, Petr Pišoft, and Tomáš Halenka
Atmos. Chem. Phys., 16, 12993–13013, https://doi.org/10.5194/acp-16-12993-2016, https://doi.org/10.5194/acp-16-12993-2016, 2016
Short summary
Short summary
Using an online coupled system of a regional climate model and chemistry transport model we investigated the radiative/climate impact of short-lived pollutants directly emitted by urban areas and those secondarily formed, focusing on the area of central Europe. We found that the direct/indirect effects of aerosols dominate, causing small but statistically significant cooling in summer and winter (up to −0.04 K). The radiative impact of ozone changes remains negligible.
P. Huszar, M. Belda, and T. Halenka
Atmos. Chem. Phys., 16, 1331–1352, https://doi.org/10.5194/acp-16-1331-2016, https://doi.org/10.5194/acp-16-1331-2016, 2016
Short summary
Short summary
The study is dealing with the present day air quality impacts of the urban emissions, focusing on central Europe. Using a coupled regional climate/chemistry model we showed that urban centers impact largely (by up to 10–20 %) the regional air quality but the urban air quality itself is affected by local emission by only 50 % and the rural (non-urban) emissions and long-range transport play an important role in urban air pollution. This has to be taken into account in air quality control measures.
P. Huszar, T. Halenka, M. Belda, M. Zak, K. Sindelarova, and J. Miksovsky
Atmos. Chem. Phys., 14, 12393–12413, https://doi.org/10.5194/acp-14-12393-2014, https://doi.org/10.5194/acp-14-12393-2014, 2014
Short summary
Short summary
The impact of cities and urban surfaces on climate of central Europe is examined using a regional climate model coupled to a single-layer urban canopy model. Results show a significant impact on temperature (up to 1.5K increase in summer), the boundary layer height, surface wind with a winter decrease and precipitation (a summer decrease). Applying the urban canopy model, the regional climate model exhibits a decreased model bias when compared to observations.
P. Ricaud, B. Sič, L. El Amraoui, J.-L. Attié, R. Zbinden, P. Huszar, S. Szopa, J. Parmentier, N. Jaidan, M. Michou, R. Abida, F. Carminati, D. Hauglustaine, T. August, J. Warner, R. Imasu, N. Saitoh, and V.-H. Peuch
Atmos. Chem. Phys., 14, 11427–11446, https://doi.org/10.5194/acp-14-11427-2014, https://doi.org/10.5194/acp-14-11427-2014, 2014
P. Huszar, H. Teyssèdre, M. Michou, A. Voldoire, D. J. L. Olivié, D. Saint-Martin, D. Cariolle, S. Senesi, D. Salas Y Melia, A. Alias, F. Karcher, P. Ricaud, and T. Halenka
Atmos. Chem. Phys., 13, 10027–10048, https://doi.org/10.5194/acp-13-10027-2013, https://doi.org/10.5194/acp-13-10027-2013, 2013
Related subject area
Subject: Climate and Earth System | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Opinion: Understanding the impacts of agriculture and food systems on atmospheric chemistry is instrumental to achieving multiple Sustainable Development Goals
Examining ENSO-related variability in tropical tropospheric ozone in the RAQMS-Aura chemical reanalysis
Global assessment of climatic responses to ozone–vegetation interactions
Recommendations on benchmarks for chemical transport model applications in China – Part 2: Ozone and Uncertainty Analysis
Impacts of irrigation on ozone and fine particulate matter (PM2.5) air quality: Implications for emission control strategies for intensively irrigated regions in China
Opinion: A research roadmap for exploring atmospheric methane removal via iron salt aerosol
An inverse model to correct for the effects of post-depositional processing on ice-core nitrate and its isotopes: model framework and applications at Summit, Greenland, and Dome C, Antarctica
The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS)
Amos P. K. Tai, Lina Luo, and Biao Luo
Atmos. Chem. Phys., 25, 923–941, https://doi.org/10.5194/acp-25-923-2025, https://doi.org/10.5194/acp-25-923-2025, 2025
Short summary
Short summary
We discuss our current understanding of and knowledge gaps in how agriculture and food systems affect air quality and how agricultural emissions can be mitigated. We argue that scientists need to address these gaps, especially as the importance of fossil fuel emissions is fading. This will help guide food-system transformation in economically viable, socially inclusive, and environmentally responsible ways and is essential to help society achieve sustainable development.
Maggie Bruckner, R. Bradley Pierce, and Allen Lenzen
Atmos. Chem. Phys., 24, 10921–10945, https://doi.org/10.5194/acp-24-10921-2024, https://doi.org/10.5194/acp-24-10921-2024, 2024
Short summary
Short summary
We analyze interannual variability in tropical tropospheric ozone by applying composite analysis, empirical orthogonal function (EOF) analysis, and multiple linear regression to the Real-time Air Quality Modeling System (RAQMS) Aura chemical reanalysis. We find that variability in biomass burning emissions contributes to El Niño–Southern Oscillation (ENSO) variability in tropical tropospheric ozone, though the dominant driver is convection.
Xinyi Zhou, Xu Yue, Chenguang Tian, and Xiaofei Lu
Atmos. Chem. Phys., 24, 9923–9937, https://doi.org/10.5194/acp-24-9923-2024, https://doi.org/10.5194/acp-24-9923-2024, 2024
Short summary
Short summary
With a climate–vegetation–chemistry coupled model, we explore global climatic responses to the ozone–vegetation interactions of the present day. We find strong warming and drying effects due to the ozone-induced inhibition on plant stomatal conductance, especially over polluted regions such as the eastern US and China. These climatic perturbations further enhance surface ozone by decreasing dry deposition but reduce aerosol optical depth by increasing cloudiness and the drought tendency.
Ling Huang, Xinxin Zhang, Chris Emery, Qing Mu, Greg Yarwood, Hehe Zhai, Zhixu Sun, Shuhui Xue, Yangjun Wang, Joshua S. Fu, and Li Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-2199, https://doi.org/10.5194/egusphere-2024-2199, 2024
Short summary
Short summary
Serious air pollution problems have occurred in many regions of China for the past decade and chemical transport models (CTMs) are being applied more frequently to address diverse scientific and regulatory compliance associated with deteriorated air quality in China. We provided benchmarks for model performance evaluation of CTM applications in China to demonstrate model robustness.
Tiangang Yuan, Amos P. K. Tai, Tzung-May Fu, Aoxing Zhang, David H. Y. Yung, Jin Wu, and Sien Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-1557, https://doi.org/10.5194/egusphere-2024-1557, 2024
Short summary
Short summary
This study utilizes a regional climate-air quality coupled model to first investigate the complex interaction between irrigation, climate, and air quality in China. We found that large-scale irrigation practices reducing summertime surface ozone while raising second inorganic aerosol concentration via complicated physical and chemical processes. Our results emphasize the importance to make a tradeoff between air pollution control and sustainable agricultural development.
Katrine A. Gorham, Sam Abernethy, Tyler R. Jones, Peter Hess, Natalie M. Mahowald, Daphne Meidan, Matthew S. Johnson, Maarten M. J. W. van Herpen, Yangyang Xu, Alfonso Saiz-Lopez, Thomas Röckmann, Chloe A. Brashear, Erika Reinhardt, and David Mann
Atmos. Chem. Phys., 24, 5659–5670, https://doi.org/10.5194/acp-24-5659-2024, https://doi.org/10.5194/acp-24-5659-2024, 2024
Short summary
Short summary
Rapid reduction in atmospheric methane is needed to slow the rate of global warming. Reducing anthropogenic methane emissions is a top priority. However, atmospheric methane is also impacted by rising natural emissions and changing sinks. Studies of possible atmospheric methane removal approaches, such as iron salt aerosols to increase the chlorine radical sink, benefit from a roadmapped approach to understand if there may be viable and socially acceptable ways to decrease future risk.
Zhuang Jiang, Becky Alexander, Joel Savarino, and Lei Geng
Atmos. Chem. Phys., 24, 4895–4914, https://doi.org/10.5194/acp-24-4895-2024, https://doi.org/10.5194/acp-24-4895-2024, 2024
Short summary
Short summary
Ice-core nitrate could track the past atmospheric NOx and oxidant level, but its interpretation is hampered by the post-depositional processing. In this work, an inverse model was developed and tested against two polar sites and was shown to well reproduce the observed nitrate signals in snow and atmosphere, suggesting that the model can properly correct for the effect of post-depositional processing. This model offers a very useful tool for future studies on ice-core nitrate records.
Xingxia Kou, Zhen Peng, Meigen Zhang, Fei Hu, Xiao Han, Ziming Li, and Lili Lei
Atmos. Chem. Phys., 23, 6719–6741, https://doi.org/10.5194/acp-23-6719-2023, https://doi.org/10.5194/acp-23-6719-2023, 2023
Short summary
Short summary
A CMAQ EnSRF-based regional inversion system was extended to resolve satellite retrievals into biogenic source–sink changes. The size of the assimilated biosphere sink in China inferred from GOSAT was −0.47 Pg C yr−1. The biosphere flux at the provincial scale was re-estimated following the refined description in the regional inversion.
Cited articles
Aksoyoglu, S., Ciarelli, G., El-Haddad, I., Baltensperger, U., and Prévôt, A. S. H.: Secondary inorganic aerosols in Europe: sources and the significant influence of biogenic VOC emissions, especially on ammonium nitrate, Atmos. Chem. Phys., 17, 7757–7773, https://doi.org/10.5194/acp-17-7757-2017, 2017. a
Archibald, A. T., Cooke, M. C., Utembe, S. R., Shallcross, D. E., Derwent, R. G., and Jenkin, M. E.: Impacts of mechanistic changes on HOx formation and recycling in the oxidation of isoprene, Atmos. Chem. Phys., 10, 8097–8118, https://doi.org/10.5194/acp-10-8097-2010, 2010. a, b
Bartík, L., Huszár, P., Karlický, J., Vlček, O., and Eben, K.: Modeling the drivers of fine PM pollution over Central Europe: impacts and contributions of emissions from different sources, Atmos. Chem. Phys., 24, 4347–4387, https://doi.org/10.5194/acp-24-4347-2024, 2024. a, b
Bastien, L. A. J., Brown, N. J., and Harley, R. A.: Contributions to local- and regional-scale formaldehyde concentrations, Atmos. Chem. Phys., 19, 8363–8381, https://doi.org/10.5194/acp-19-8363-2019, 2019. a
Bates, K. H. and Jacob, D. J.: A new model mechanism for atmospheric oxidation of isoprene: global effects on oxidants, nitrogen oxides, organic products, and secondary organic aerosol, Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, 2019. a, b
Belda, M., Krč, P., Resler, J., Huszár, P., Benešová, N., Karlický, J., and Juruš, P.: FUME-dev/fume: Official 2.0 release (2.0), Zenodo [code], https://doi.org/10.5281/zenodo.10142912, 2023. a
Belda, M., Benešová, N., Resler, J., Huszár, P., Vlček, O., Krč, P., Karlický, J., Juruš, P., and Eben, K.: FUME 2.0 – Flexible Universal processor for Modeling Emissions, Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, 2024. a
Benešová, N., Belda, M., Eben, K., Geletič, J., Huszár, P., Juruš, P., Krč, P., Resler, J., and Vlček, O.: New open source emission processor for air quality models, in: Proceedings of Abstracts 11th International Conference on Air Quality Science and Application, edited by: Sokhi, R., Tiwari, P. R., Gállego, M. J., Craviotto Arnau, J. M., Castells Guiu, C., and Singh, V., 11th International Conference on Air Quality Science and Application, Barcelona, Spain, 12–16 March 2018, University of Hertfordshire, 27 pp., https://doi.org/10.18745/PB.19829, 2018. a
Bonn, B., von Schneidemesser, E., Butler, T., Churkina, G., Ehlers, C., Grote, R., Klemp, D., Nothard, R., Schäfer, K., von Stülpnagel, A., and Kerschbaumer, A.: Impact of vegetative emissions on urban ozone and biogenic secondary organic aerosol: Box model study for Berlin, Germany, J. Clean. Prod., 176, 827–841, https://doi.org/10.1016/j.jclepro.2017.12.164, 2018. a
Bougeault, P. and Lacarrère, P.: Parameterization of orography-induced turbulence in a meso-beta-scale model, Mon. Weather Rev., 117, 1872–1890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2, 1989. a
Buchholz, R. R., Emmons, L. K., Tilmes, S., and The CESM2 Development Team: CESM2.1/CAM-chem Instantaneous Output for Boundary Conditions, UCAR/NCAR – Atmospheric Chemistry Observations and Modeling Laboratory, Subset used Lat: 10 to 80, Lon: −20 to 50, December 2014–January 2017, https://doi.org/10.5065/NMP7-EP60, 2019. a
Byun, D. W., and Ching, J. K. S.: Science Algorithms of the EPA Model-3 Community Multiscale Air Quality (CMAQ) Modeling System, Office of Research and Development, U.S. EPA, North Carolina, EPA/600/R-99/030, 1999. a
Calfapietra, C., Fares, S., Manes, F., Morani, A., Sgrigna, G., and Loreto, F.: Role of Biogenic Volatile Organic Compounds (BVOC) emitted by urban trees on ozone concentration in cities: A review, Environ. Pollut., 183, 71–80, https://doi.org/10.1016/j.envpol.2013.03.012, 2013. a, b
CAMx: Comprehensive Air Quality Model With Extensions version 7.20 code, Ramboll US Corporation, Novato, CA 94945, USA [code], https://www.camx.com/download/source/ (last access: 15 May 2024), 2022. a
Cao, L., Li, S., and Sun, L.: Study of different Carbon Bond 6 (CB6) mechanisms by using a concentration sensitivity analysis, Atmos. Chem. Phys., 21, 12687–12714, https://doi.org/10.5194/acp-21-12687-2021, 2021. a
Carter, W. P. L.: Documentation Of The SAPRC-99 Chemical Mechanism For VOC Reactivity Assessment, Final Report to California Air Resources Board, Contract 92-329 and Contract 95-308, 00-AP-RT17-001-FR, University of California, Riverside, California 92521, 2000. a
Castell, N., Stein, A. F., Salvador, R., Mantilla, E., and Millán, M.: The impact of biogenic VOC emissions on photochemical ozone formation during a high ozone pollution episode in the Iberian Peninsula in the 2003 summer season, Adv. Sci. Res., 2, 9–15, https://doi.org/10.5194/asr-2-9-2008, 2008. a, b
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface Hydrology Model with the Penn State-NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity, Mon. Weather Rev., 129, 569–585, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a
Chen, S. and Sun, W.: A one-dimensional time dependent cloud model, J. Meteorol. Soc. Jpn., 80, 99–118, https://doi.org/10.2151/jmsj.80.99, 2002. a
Chen, Y., Liu, C., Su, W., Hu, Q., Zhang, C., Liu, H., and Yin, H.: Identification of volatile organic compound emissions from anthropogenic and biogenic sources based on satellite observation of formaldehyde and glyoxal, Sci. Total Environ., 859, 159997, https://doi.org/10.1016/j.scitotenv.2022.159997, 2023. a
Churkina, G., Kuik, F., Bonn, B., Lauer, A., Grote, R., Tomiak, K., and Butler, T. M.: Effect of VOC Emissions from Vegetation on Air Quality in Berlin during a Heatwave, Environ. Sci. Technol., 51, 6120–6130, https://doi.org/10.1021/acs.est.6b06514, 2017. a
Coates, J., Mar, K. A., Ojha, N., and Butler, T. M.: The influence of temperature on ozone production under varying NOx conditions – a modelling study, Atmos. Chem. Phys., 16, 11601–11615, https://doi.org/10.5194/acp-16-11601-2016, 2016. a
CORINE: CORINE Land Cover, European Union, Copernicus Land Monitoring Service 2012, European Environment Agency (EEA), https://land.copernicus.eu/pan-european/corine-land-cover (last access: 9 December 2024.), 2012. a
Curci, G., Beekmann, M., Vautard, R., Smiatek, G., Steinbrecher, R., Theloke, J., and Friedrich, R.: Modelling study of the impact of isoprene and terpene biogenic emissions on European ozone levels, Atmos. Environ., 43, 1444–1455, https://doi.org/10.1016/j.atmosenv.2008.02.070, 2009. a, b
Curci, G., Palmer, P. I., Kurosu, T. P., Chance, K., and Visconti, G.: Estimating European volatile organic compound emissions using satellite observations of formaldehyde from the Ozone Monitoring Instrument, Atmos. Chem. Phys., 10, 11501–11517, https://doi.org/10.5194/acp-10-11501-2010, 2010. a
de la Paz, D., Borge, R., de Andrés, J. M., Tovar, L., Sarwar, G., and Napelenok, S. L.: Summertime tropospheric ozone source apportionment study in the Madrid region (Spain), Atmos. Chem. Phys., 24, 4949–4972, https://doi.org/10.5194/acp-24-4949-2024, 2024. a
Duan, C., Liao, H., Wang, K., Ren, Y.: The research hotspots and trends of volatile organic compound emissions from anthropogenic and natural sources: A systematic quantitative review, Environ. Res., 216, 114386, https://doi.org/10.1016/j.envres.2022.114386, 2023. a
Dufour, G., Wittrock, F., Camredon, M., Beekmann, M., Richter, A., Aumont, B., and Burrows, J. P.: SCIAMACHY formaldehyde observations: constraint for isoprene emission estimates over Europe?, Atmos. Chem. Phys., 9, 1647–1664, https://doi.org/10.5194/acp-9-1647-2009, 2009. a
EEA: Europe's air quality status 2022, European Environmental Agency, Briefing no. 04/2022, https://doi.org/10.2800/049755, 2022. a
EEA: Air Quality e-Reporting products on EEA data service: E1a and E2a data sets, European Environment Agency, Copenhagen, Denmark [data set], https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm (last access: 15 May 2024), 2023. a
Emery, C., Baker, K., Wilson, G., Yarwood, G.: Comprehensive Air Quality Model with Extensions: Formulation and Evaluation for Ozone and Particulate Matter over the US, Atmosphere, 15, 1158, https://doi.org/10.3390/atmos15101158, 2024. a
Emmons, L. K., Schwantes, R. H., Orlando, J. J., Tyndall, G., Kinnison, D., Lamarque, J.-F., Marsh, D., Mills, M. J., Tilmes, S., Bardeen, Ch., Buchholz, R. R., Conley, A., Gettelman, A., Garcia, R., Simpson, I., Blake, D. R., Meinardi, S., and Pétron, G.: The Chemistry Mechanism in the Community Earth System Model version 2 (CESM2), J. Adv. Model. Earth Sys., 12, e2019MS001882, https://doi.org/10.1029/2019MS001882, 2020. a
EUROSTAT: Farms and farmland in the European Union – statistics, European Commission – Eurostat, L-2920 Luxembourg, https://ec.europa.eu/eurostat/statistics-explained/SEPDF/cache/73319.pdf (last acces: 25 September 2024), 2020. a
Fitzky, A. C., Sandén, H., Karl, T., Fares, S., Calfapietra, C., Grote, R., Saunier, A., and Rewald, B.: The Interplay Between Ozone and Urban Vegetation – BVOC Emissions, Ozone Deposition, and Tree Ecophysiology, Frontiers in Forests and Global Change, 2, 50, https://doi.org/10.3389/ffgc.2019.00050, 2019. a, b
Fitzky, A. C., Kaser, L., Peron, A., Karl, T., Graus, M., Tholen, D., Halbwirth, H., Trimmel, H., Pesendorfer, M., Rewald, B., and Sandén, H.: Same, same, but different: Drought and salinity affect BVOC emission rate and alter blend composition of urban trees, Urban For. Urban Gree., 80, 127842, https://doi.org/10.1016/j.ufug.2023.127842, 2023. a
FOREST EUROPE: State of Europe's Forests 2020, Ministerial Conference on the Protection of Forests in Europe – FOREST EUROPE, Liaison Unit Bratislava, https://foresteurope.org/wp-content/uploads/2016/08/SoEF_2020.pdf (last access: 25 September 2024), 2020. a
Gao, Y., Ma, M., Yan, F., Su, H., Wang, S., Liao, H., Zhao, B., Wang, X., Sun, Y., Hopkins, J. R., and Chen, Q.: Impacts of biogenic emissions from urban landscapes on summer ozone and secondary organic aerosol formation in megacities, Sci. Total Environ., 814, 152654, https://doi.org/10.1016/j.scitotenv.2021.152654 2022a. a, b
Gao, Y., Yan, F., Ma, M., Ding, A., Liao, H., Wang, S., Wang, X., Zhao, B., Cai, W., Su, H., and Yao, X.: Unveiling the dipole synergic effect of biogenic and anthropogenic emissions on ozone concentrations, Sci. Total Environ., 818, 151722, https://doi.org/10.1016/j.scitotenv.2021.151722, 2022b. a
Gao, Y., Pan, H., Cao, L., Lu, C., Yang, Q., Lu, X., and Zhao, T.: Effects of anthropogenic emissions and meteorological conditions on diurnal variation of formaldehyde (HCHO) in the Yangtze River Delta, China, Atmos. Pollut. Res., 14, 101779, https://doi.org/10.1016/j.apr.2023.101779, 2023. a
Ghirardo, A., Xie, J., Zheng, X., Wang, Y., Grote, R., Block, K., Wildt, J., Mentel, T., Kiendler-Scharr, A., Hallquist, M., Butterbach-Bahl, K., and Schnitzler, J.-P.: Urban stress-induced biogenic VOC emissions and SOA-forming potentials in Beijing, Atmos. Chem. Phys., 16, 2901–2920, https://doi.org/10.5194/acp-16-2901-2016, 2016. a
Grell, G.: Prognostic evaluation of assumptions used by cumulus parameterizations, Mon. Weather Rev., 121, 764–787, https://doi.org/10.1175/1520-0493(1993)121<0764:PEOAUB>2.0.CO;2, 1993. a
Grote, R., Monson, R. K., and Niinemets, Ü.: Leaf-Level Models of Constitutive and Stress-Driven Volatile Organic Compound Emissions, in: Biology, Controls and Models of Tree Volatile Organic Compound Emissions, Tree Physiology, edited by: Niinemets, Ü. and Monson, R., Springer, Dordrecht, vol. 5, https://doi.org/10.1007/978-94-007-6606-8_12, 2013. a
Gu, S., Guenther, A., and Faiola, C.: Effects of Anthropogenic and Biogenic Volatile Organic Compounds on Los Angeles Air Quality, Environ. Sci. Technol., 5, 12191–12201, https://doi.org/10.1021/acs.est.1c01481, 2021. a, b
Guenther, A., Jiang, X., and Duhl, T.: MEGAN version 2.10, National Center for Atmospheric Research, Boulder, CO, USA [code], https://bai.ess.uci.edu/megan/data-and-code/megan21 (last access: 15 May 2024), 2014. a
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012. a, b, c
Guidolotti, G., Pallozzi, E., Gavrichkova, O., Scartazza, A., Mattioni, M., and Calfapietra, C.: Emission of constitutive isoprene, induced monoterpenes, and other volatiles under high temperatures in Eucalyptus camaldulensis: A 13C labelling study, Plant Cell Environ., 42, 1929–1938, https://doi.org/10.1111/pce.13521, 2019. a
Harrison, R. M., Yin, J., Tilling, R. M., Cai, X., Seakins, P. W., Hopkins, J. R., Lansley, D. L., Lewis, A. C., Hunter, M. C., Heard, D. E., Carpenter, L. J., Creasey, D. J., Lee, J. D., Pilling, M. J., Carslaw, N., Emmerson, K. M., Redington, A., Derwent, R. G., Ryall, D., Mills, G., and Penkett, S. A.: Measurement and modelling of air pollution and atmospheric chemistry in the U.K. West Midlands conurbation: Overview of the PUMA Consortium project, Sci. Total Environ., 360, 5–25, https://doi.org/10.1016/j.scitotenv.2005.08.053, 2006. a
Hodnebrog, Ø., Solberg, S., Stordal, F., Svendby, T. M., Simpson, D., Gauss, M., Hilboll, A., Pfister, G. G., Turquety, S., Richter, A., Burrows, J. P., and Denier van der Gon, H. A. C.: Impact of forest fires, biogenic emissions and high temperatures on the elevated Eastern Mediterranean ozone levels during the hot summer of 2007, Atmos. Chem. Phys., 12, 8727–8750, https://doi.org/10.5194/acp-12-8727-2012, 2012. a, b
Huszar, P.: CAMx simulations on BVOC impact over central Europe, Czech National Repository [data set], https://doi.org/10.48700/datst.b6as3-v2y27, 2024. a
Huszár, P., Karlický, J., Belda, M., Halenka, T., and Pišoft, P.: The impact of urban canopy meteorological forcing on summer photochemistry, Atmos. Environ., 176, 209–228, https://doi.org/10.1016/j.atmosenv.2017.12.037, 2018. a, b
Huszar, P., Karlický, J., Ďoubalová, J., Šindelářová, K., Nováková, T., Belda, M., Halenka, T., Žák, M., and Pišoft, P.: Urban canopy meteorological forcing and its impact on ozone and PM2.5: role of vertical turbulent transport, Atmos. Chem. Phys., 20, 1977–2016, https://doi.org/10.5194/acp-20-1977-2020, 2020a. a, b, c
Huszar, P., Karlický, J., Ďoubalová, J., Nováková, T., Šindelářová, K., Švábik, F., Belda, M., Halenka, T., and Žák, M.: The impact of urban land-surface on extreme air pollution over central Europe, Atmos. Chem. Phys., 20, 11655–11681, https://doi.org/10.5194/acp-20-11655-2020, 2020b. a
Huszar, P., Karlický, J., Bartík, L., Liaskoni, M., Prieto Perez, A. P., and Šindelářová, K.: Impact of urbanization on gas-phase pollutant concentrations: a regional-scale, model-based analysis of the contributing factors, Atmos. Chem. Phys., 22, 12647–12674, https://doi.org/10.5194/acp-22-12647-2022, 2022. a
Huszar, P., Prieto Perez, A. P., Bartík, L., Karlický, J., and Villalba-Pradas, A.: Impact of urbanization on fine particulate matter concentrations over central Europe, Atmos. Chem. Phys., 24, 397–425, https://doi.org/10.5194/acp-24-397-2024, 2024. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the aer radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008. a
Im, U., Poupkou, A., Incecik, S., Markakis, K., Kindap, T., Unal, A., Melas, D., Yenigun, O., Topcu, S., Odman, M. T., Tayanc, M., and Guler, M.: The impact of anthropogenic and biogenic emissions on surface ozone concentrations in Istanbul, Sci. Total Environ., 409, 1255–1265, https://doi.org/10.1016/j.scitotenv.2010.12.026, 2011. a
Im, U., Bianconi, R., Solazzo, E., Kioutsioukis, I., Badia, A., Balzarini, A., Baró, R., Bellasio, R., Brunner, D., Chemel, C., Curci, G., Flemming, J., Forkel, R., Giordano, L., Jiménez-Guerrero, P., Hirtl, M., Hodzic, A., Honzak, L., Jorba, O., Knote, C., Kuenen, J. J., Makar, P. A., Manders-Groot, A., Neal, L., Pérez, J. L., Pirovano, G., Pouliot, G., San Jose, R., Savage, N., Schroder, W., Sokhi, R. S., Syrakov, D., Torian, A., Tuccella, P., Werhahn, J., Wolke, R., Yahya, K., Zabkar, R., Zhang, Y., Zhang, J., Hogrefe, C., and Galmarini, S.: Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone, Atmos. Environ., 115, 404–420, https://doi.org/10.1016/j.atmosenv.2014.09.042, 2015. a
Jiang, J., Aksoyoglu, S., Ciarelli, G., Oikonomakis, E., El-Haddad, I., Canonaco, F., O'Dowd, C., Ovadnevaite, J., Minguillón, M. C., Baltensperger, U., and Prévôt, A. S. H.: Effects of two different biogenic emission models on modelled ozone and aerosol concentrations in Europe, Atmos. Chem. Phys., 19, 3747–3768, https://doi.org/10.5194/acp-19-3747-2019, 2019. a
Johnson, D. and Marston, G.: The gas-phase ozonolysis of unsaturated volatile organic compounds in the troposphere, Chem. Soc. Rev., 37, 699–716, https://doi.org/10.1039/B704260B, 2008. a
Kaiser, J., Wolfe, G. M., Min, K. E., Brown, S. S., Miller, C. C., Jacob, D. J., deGouw, J. A., Graus, M., Hanisco, T. F., Holloway, J., Peischl, J., Pollack, I. B., Ryerson, T. B., Warneke, C., Washenfelder, R. A., and Keutsch, F. N.: Reassessing the ratio of glyoxal to formaldehyde as an indicator of hydrocarbon precursor speciation, Atmos. Chem. Phys., 15, 7571–7583, https://doi.org/10.5194/acp-15-7571-2015, 2015. a
Karamchandani, P., Long, Y., Pirovano, G., Balzarini, A., and Yarwood, G.: Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data, Atmos. Chem. Phys., 17, 5643–5664, https://doi.org/10.5194/acp-17-5643-2017, 2017. a
Karlický, J., Huszár, P., and Halenka, T.: Validation of gas phase chemistry in the WRF-Chem model over Europe, Adv. Sci. Res., 14, 181–186, https://doi.org/10.5194/asr-14-181-2017, 2017. a
Karlický, J., Huszár, P., Halenka, T., Belda, M., Žák, M., Pišoft, P., and Mikšovský, J.: Multi-model comparison of urban heat island modelling approaches, Atmos. Chem. Phys., 18, 10655–10674, https://doi.org/10.5194/acp-18-10655-2018, 2018. a, b, c
Karlický, J., Huszár, P., Nováková, T., Belda, M., Švábik, F., Ďoubalová, J., and Halenka, T.: The “urban meteorology island”: a multi-model ensemble analysis, Atmos. Chem. Phys., 20, 15061–15077, https://doi.org/10.5194/acp-20-15061-2020, 2020. a, b
Karlický, J., Rieder, H. E., Huszár, P., Peiker, J., and Sukhodolov, T.: A cautious note advocating the use of ensembles of models and driving data in modeling of regional ozone burdens, Air. Qual. Atmos. Health, 17, 1415–1424, https://doi.org/10.1007/s11869-024-01516-3, 2024. a
Kelly, J. M., Doherty, R. M., O'Connor, F. M., and Mann, G. W.: The impact of biogenic, anthropogenic, and biomass burning volatile organic compound emissions on regional and seasonal variations in secondary organic aerosol, Atmos. Chem. Phys., 18, 7393–7422, https://doi.org/10.5194/acp-18-7393-2018, 2018. a
Kesselmeier, J. and Staudt, M.: Biogenic Volatile Organic Compounds (VOC): An Overview on Emission, Physiology and Ecology, J. Atmos. Chem., 33, 23–88, https://doi.org/10.1023/A:1006127516791, 1999. a
Khan, M. A. H., Schlich, B. L., Jenkin, M. E., Cooke, M. C., Derwent, R. G., Neu, J. L., Percival, C. J., and Shallcross, D. E.: Changes to simulated global atmospheric composition resulting from recent revisions to isoprene oxidation chemistry, Atmos. Environ., 244, 117914, https://doi.org/10.1016/j.atmosenv.2020.117914, 2021. a
Kim, S. Y., Jiang, X., Lee, M., Turnipseed, A., Guenther, A., Kim, J. C., Lee, S. J., and Kim, S.: Impact of biogenic volatile organic compounds on ozone production at the Taehwa Research Forest near Seoul, South Korea, Atmos. Environ., 70, 447–453, https://doi.org/10.1016/j.atmosenv.2012.11.005, 2013. a
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, 2014. a
Kusaka, H., Kondo, K., Kikegawa, Y., and Kimura, F.: A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models, Bound.-Lay. Meteorol., 101, 329–358, https://doi.org/10.1023/A:1019207923078, 2001. a
Lam, Y. F., Fu, J. S., Wu, S., and Mickley, L. J.: Impacts of future climate change and effects of biogenic emissions on surface ozone and particulate matter concentrations in the United States, Atmos. Chem. Phys., 11, 4789–4806, https://doi.org/10.5194/acp-11-4789-2011, 2011. a
Lawrence, P. J. and Chase, T. N.: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0), J. Geophys. Res.-Biogeo., 112, G01023, https://doi.org/10.1029/2006JG000168, 2007. a
Lee, K. Y., Kwak, K. H., Ryu, Y. H., Lee, S. H., and Baik, J. J.: Impacts of biogenic isoprene emission on ozone air quality in the Seoul metropolitan area, Atmos. Environ., 96, 209–219, https://doi.org/10.1016/j.atmosenv.2014.07.036, 2014. a
Lerdau M.: A positive feedback with negative consequences, Science, 316, 212–213, https://doi.org/10.1126/science.1141486, 2007. a, b
Li, J., Wang, Y., and Qu, H.: Dependence of summertime surface ozone on NOx and VOC emissions over the United States: Peak time and value, Geophys. Res. Lett., 46, 3540–3550, https://doi.org/10.1029/2018GL081823, 2019. a
Li, N., He, Q., Greenberg, J., Guenther, A., Li, J., Cao, J., Wang, J., Liao, H., Wang, Q., and Zhang, Q.: Impacts of biogenic and anthropogenic emissions on summertime ozone formation in the Guanzhong Basin, China, Atmos. Chem. Phys., 18, 7489–7507, https://doi.org/10.5194/acp-18-7489-2018, 2018. a, b
Liaskoni, M., Huszar, P., Bartík, L., Prieto Perez, A. P., Karlický, J., and Vlček, O.: Modelling the European wind-blown dust emissions and their impact on particulate matter (PM) concentrations, Atmos. Chem. Phys., 23, 3629–3654, https://doi.org/10.5194/acp-23-3629-2023, 2023. a
Liu, S., Xing, J., Zhang, H., Ding, D., Zhang, F., Zhao, B., Sahu, S. K., and Wang, S.: Climate-driven trends of biogenic volatile organic compound emissions and their impacts on summertime ozone and secondary organic aerosol in China in the 2050s, Atmos. Environ., 218, 117020, https://doi.org/10.1016/j.atmosenv.2019.117020, 2019. a
Liu, Y., Li, L., An, J., Huang, L., Yan, R., Huang, Ch., Wang, H., Wang, Q., Wang, M., and Zhang, W.: Estimation of biogenic VOC emissions and its impact on ozone formation over the Yangtze River Delta region, China, Atmos. Environ., 186, 113–128, https://doi.org/10.1016/j.atmosenv.2018.05.027, 2018. a
Liu, Y., Nie, W., Li, Y., Ge, D., Liu, C., Xu, Z., Chen, L., Wang, T., Wang, L., Sun, P., Qi, X., Wang, J., Xu, Z., Yuan, J., Yan, C., Zhang, Y., Huang, D., Wang, Z., Donahue, N. M., Worsnop, D., Chi, X., Ehn, M., and Ding, A.: Formation of condensable organic vapors from anthropogenic and biogenic volatile organic compounds (VOCs) is strongly perturbed by NOx in eastern China, Atmos. Chem. Phys., 21, 14789–14814, https://doi.org/10.5194/acp-21-14789-2021, 2021. a
Luecken, D. J., Hutzell, W. T., Strum, M. L., and Pouliot, G. A.: Regional sources of atmospheric formaldehyde and acetaldehyde, and implications for atmospheric modeling, Atmos. Environ., 47, 477–490, 2012. a
Ma, M., Gao, Y., Wang, Y., Zhang, S., Leung, L. R., Liu, C., Wang, S., Zhao, B., Chang, X., Su, H., Zhang, T., Sheng, L., Yao, X., and Gao, H.: Substantial ozone enhancement over the North China Plain from increased biogenic emissions due to heat waves and land cover in summer 2017, Atmos. Chem. Phys., 19, 12195–12207, https://doi.org/10.5194/acp-19-12195-2019, 2019. a
Ma, M., Gao, Y., Ding, A., Su, H., Liao, H., Wang, S., and Gao, H.: Development and assessment of a high-resolution biogenic emission inventory from urban green spaces in China, Environ. Sci. Technol., 56, 175–184, https://doi.org/10.1021/acs.est.1c06170, 2021. a, b
Maison, A., Lugon, L., Park, S.-J., Baudic, A., Cantrell, C., Couvidat, F., D'Anna, B., Di Biagio, C., Gratien, A., Gros, V., Kalalian, C., Kammer, J., Michoud, V., Petit, J.-E., Shahin, M., Simon, L., Valari, M., Vigneron, J., Tuzet, A., and Sartelet, K.: Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling, Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, 2024. a
Markakis, K., Valari, M., Perrussel, O., Sanchez, O., and Honore, C.: Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology, Atmos. Chem. Phys., 15, 7703–7723, https://doi.org/10.5194/acp-15-7703-2015, 2015. a
Nenes, A., Pilinis, C., and Pandis, S. N.: ISORROPIA: A New Thermodynamic Model for Multiphase Multicomponent Inorganic Aerosols, Aquat. Geochem., 4, 123–152, https://doi.org/10.1023/A:1009604003981, 1998. a
Nenes, A., Pilinis, C., and Pandis, S. N.: Continued Development and Testing of a New Thermodynamic Aerosol Module for Urban and Regional Air Quality Models, Atmos. Environ., 33, 1553–1560, https://doi.org/10.1016/S1352-2310(98)00352-5, 1999. a
Nowak, D. J., Civerolo, K. L., Rao, S. T., Sistla, G., Luley, C. G., and Crane, D. E.: A modeling study of the impact of urban trees on ozone, Atmos. Environ., 34, 1601–1613, https://doi.org/10.1016/S1352-2310(99)00394-5, 2000. a
Otero, N., Sillmann, J., Mar, K. A., Rust, H. W., Solberg, S., Andersson, C., Engardt, M., Bergström, R., Bessagnet, B., Colette, A., Couvidat, F., Cuvelier, C., Tsyro, S., Fagerli, H., Schaap, M., Manders, A., Mircea, M., Briganti, G., Cappelletti, A., Adani, M., D'Isidoro, M., Pay, M.-T., Theobald, M., Vivanco, M. G., Wind, P., Ojha, N., Raffort, V., and Butler, T.: A multi-model comparison of meteorological drivers of surface ozone over Europe, Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, 2018. a
Passant, N.: Speciation of UK Emissions of Non-methane Volatile Organic Compounds, DEFRA, Oxon, UK, https://uk-air.defra.gov.uk/assets/documents/reports/empire/AEAT_ENV_0545_final_v2.pdf (last access: 4 January 2024), 2002. a
Possanzini, M., Di Palo, V., and Cecinato, A.: Sources and photodecomposition of formaldehyde and acetaldehyde in Rome ambient air, Atmos. Environ., 36, 3195–3201, https://doi.org/10.1016/S1352-2310(02)00192-9, 2002. a
Qu, Y., An, J., and Li, J.: Synergistic impacts of anthropogenic and biogenic emissions on summer surface O3 in East Asia, J. Environ. Sci., 25, 520–530, https://doi.org/10.1016/S1001-0742(12)60069-2, 2013. a
Richards, N. A. D., Arnold, S. R., Chipperfield, M. P., Miles, G., Rap, A., Siddans, R., Monks, S. A., and Hollaway, M. J.: The Mediterranean summertime ozone maximum: global emission sensitivities and radiative impacts, Atmos. Chem. Phys., 13, 2331–2345, https://doi.org/10.5194/acp-13-2331-2013, 2013. a, b
Rowlinson, M. J., Rap, A., Hamilton, D. S., Pope, R. J., Hantson, S., Arnold, S. R., Kaplan, J. O., Arneth, A., Chipperfield, M. P., Forster, P. M., and Nieradzik, L.: Tropospheric ozone radiative forcing uncertainty due to pre-industrial fire and biogenic emissions, Atmos. Chem. Phys., 20, 10937–10951, https://doi.org/10.5194/acp-20-10937-2020, 2020. a
Sakulyanontvittaya, T., Cho, S., Aklilu, Y. A., Morris, R., and Nopmongcol, U.: An assessment of enhanced biogenic emissions influence on ozone formation in central Alberta, Canada, Air Qual. Atmos. Hlth., 9, 117–127, https://doi.org/10.1007/s11869-015-0324-9, 2016. a
Sartelet, K. N., Couvidat, F., Seigneur, C., and Roustan, Y.: Impact of biogenic emissions on air quality over Europe and North America, Atmos. Environ., 53, 131–141, https://doi.org/10.1016/j.atmosenv.2011.10.046, 2012. a
Sarwar, G., Luecken, D., Yarwood, G. Whitten, G. Z., and Carter, W. P. L.: Impact of an Updated Carbon Bond Mechanism on Predictions from the CMAQ Modeling System: Preliminary Assessment, J. Appl. Meteorol. Clim., 47, 3–14, https://doi.org/10.1175/2007JAMC1393.1, 2008. a
Schwantes, R. H., Emmons, L. K., Orlando, J. J., Barth, M. C., Tyndall, G. S., Hall, S. R., Ullmann, K., St. Clair, J. M., Blake, D. R., Wisthaler, A., and Bui, T. P. V.: Comprehensive isoprene and terpene gas-phase chemistry improves simulated surface ozone in the southeastern US, Atmos. Chem. Phys., 20, 3739–3776, https://doi.org/10.5194/acp-20-3739-2020, 2020. a, b, c
Simmons, A. J., Willett, K. M., Jones, P. D., Thorne, P. W., and Dee, D. P.: Low-frequency variations in surface atmospheric humidity, temperature and precipitation: inferences from reanalyses and monthly gridded observational datasets, J. Geophys. Res., 115, D01110, https://doi.org/10.1029/2009JD012442, 2010. a
Simon, H., Fallmann, J., Kropp, T., Tost, H., and Bruse, M.: Urban Trees and Their Impact on Local Ozone Concentration – A Microclimate Modeling Study, Atmosphere, 10, 154, https://doi.org/10.3390/atmos10030154, 2019. a
Simpraga, M., Ghimire, R. P., and Van Der Straeten, D.: Unravelling the functions of biogenic volatiles in boreal and temperate forest ecosystems, Eur. J. Forest. Res., 138, 763–787, https://doi.org/10.1007/s10342-019-01213-2, 2019. a
Sindelarova, K., Markova, J., Simpson, D., Huszar, P., Karlicky, J., Darras, S., and Granier, C.: High-resolution biogenic global emission inventory for the time period 2000–2019 for air quality modelling, Earth Syst. Sci. Data, 14, 251–270, https://doi.org/10.5194/essd-14-251-2022, 2022. a, b
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X.-Y.: A Description of the Advanced Research WRF Version 4, NCAR Tech, Note NCAR/TN-556+STR, 145, https://doi.org/10.5065/1dfh-6p97, 2019. a
Strader, R., Lurmann, F., and Pandis, S. N.: Evaluation of secondary organic aerosol formation in winter, Atmos. Environ., 33, 4849–4863, https://doi.org/10.1016/S1352-2310(99)00310-6, 1999. a
Strong, J., Whyatt, J. D., Metcalfe, S. E., Derwent, R. G., and Hewitt, C. N.: Investigating the impacts of anthropogenic and biogenic VOC emissions and elevated temperatures during the 2003 ozone episode in the UK, Atmos. Environ., 74, 393–401, https://doi.org/10.1016/j.atmosenv.2013.04.006, 2013. a
Tagaris, E., Sotiropoulou, R. E. P., Gounaris, N., Andronopoulos, S., and Vlachogiannis, D.: Impact of biogenic emissions on ozone and fine particles over Europe: Comparing effects of temperature increase and a potential anthropogenic NOx emissions abatement strategy, Atmos. Environ., 98, 214–223, https://doi.org/10.1016/j.atmosenv.2014.08.056, 2014. a
Thompson, A. M.: The oxidizing capacity of the earth's atmosphere: probable past and future changes, Science, 256, 1157–1165, https://doi.org/10.1126/science.256.5060.1157, 1992. a
Thunis, P. and Cuvelier, C.: Impact of biogenic emissions on ozone formation in the Mediterranean area – a BEMA modelling study, Atmos. Environ., 34, 467–481, https://doi.org/10.1016/S1352-2310(99)00313-1, 2000. a, b
van der Gon, H. D., Hendriks, C., Kuenen, J., Segers, A., and Visschedijk, A.: Description of current temporal emission patterns and sensitivity of predicted AQ for temporal emission patterns, EU FP7 MACC deliverable report D_D-EMIS_1.3, TNO, Utrecht, the Netherlands, https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf (last access: 10 January 2024), 2011. a
von Schneidemesser, E., Monks, P. S., Gros, V., Gauduin, J., and Sanchez, O.: How important is biogenic isoprene in an urban environment? A study in London and Paris, Geophys. Res. Lett., 38, L19804, https://doi.org/10.1029/2011GL048647, 2011. a
Wang, X., Fu, T. M., Zhang, L., Lu, X., Liu, X., Amnuaylojaroen, T., Latif, M. T., Ma, Y., Zhang, L., Feng, X., and Zhu, L.: Rapidly changing emissions drove substantial surface and tropospheric ozone increases over Southeast Asia, Geophys. Res. Lett., 49, e2022GL100223, https://doi.org/10.1029/2022GL100223, 2022. a
Williams, J. E., Scheele, M. P., van Velthoven, P. F. J., Cammas, J.-P., Thouret, V., Galy-Lacaux, C., and Volz-Thomas, A.: The influence of biogenic emissions from Africa on tropical tropospheric ozone during 2006: a global modeling study, Atmos. Chem. Phys., 9, 5729–5749, https://doi.org/10.5194/acp-9-5729-2009, 2009. a
Wong, K. W., and Stutz, J.: Influence of nocturnal vertical stability on daytime chemistry: a one-dimensional model study, Atmos. Environ., 44, 3753–3760, https://doi.org/10.1016/j.atmosenv.2010.06.057, 2010. a
WRF: Weather Research and Forecast model code, version 4.0 source code [code], https://www2.mmm.ucar.edu/wrf/src/WRFV4.0.TAR.gz (last access 14 May 2024), 2018. a
Wu, K., Yang, X., Chen, D., Gu, S., Lu, Y., Jiang, Q., Wang, K., Ou, Y., Qian, Y., Shao, P., and Lu, S.: Estimation of biogenic VOC emissions and their corresponding impact on ozone and secondary organic aerosol formation in China, Atmos. Res., 231, 104656, https://doi.org/10.1016/j.atmosres.2019.104656, 2020. a
Wu, Y., Huo, J., Yang, G., Wang, Y., Wang, L., Wu, S., Yao, L., Fu, Q., and Wang, L.: Measurement report: Production and loss of atmospheric formaldehyde at a suburban site of Shanghai in summertime, Atmos. Chem. Phys., 23, 2997–3014, https://doi.org/10.5194/acp-23-2997-2023, 2023. a
Yu, H. and Blande, J. D.: Diurnal variation in BVOC emission and CO2 gas exchange from above- and belowground parts of two coniferous species and their responses to elevated O3, Environ. Pollut., 278, 116830, https://doi.org/10.1016/j.envpol.2021.116830, 2021. a
Yu, H., Holopainen, J. K., Kivimäenpää, M., Virtanen, A., and Blande, J. D.: Potential of Climate Change and Herbivory to Affect the Release and Atmospheric Reactions of BVOCs from Boreal and Subarctic Forests, Molecules 2021, 26, 2283, https://doi.org/10.3390/molecules26082283, 2021. a
Yuan, H., Dai, Y., Xiao, Z., Ji, D., and Shangguan, W.: Reprocessing the MODIS Leaf Area Index Products for Land Surface and Climate Modelling, Remote Sens. Environ., 115, 1171–1187, https://doi.org/10.1016/j.rse.2011.01.001, 2011. a, b
Zanis, P., Katragkou, E., Tegoulias, I., Poupkou, A., Melas, D., Huszar, P., and Giorgi, F.: Evaluation of near surface ozone in air quality simulations forced by a regional climate model over Europe for the period 1991–2000, Atmos. Environ., 45, 6489–6500, https://doi.org/10.1016/j.atmosenv.2011.09.001, 2011. a
Zeng, G., Pyle, J. A., and Young, P. J.: Impact of climate change on tropospheric ozone and its global budgets, Atmos. Chem. Phys., 8, 369–387, https://doi.org/10.5194/acp-8-369-2008, 2008. a
Zhang, R., Cohan, A, Biazar, A. P., and Coha, D. S.: Source apportionment of biogenic contributions to ozone formation over the United States, Atmos. Environ, 164, 8–19, https://doi.org/10.1016/j.atmosenv.2017.05.044, 2017. a, b
Zhao, Y., Li, Y., Kumar, A., Ying, Q., Vandenberghe, F., and Kleeman, M. J.: Separately resolving NOx and VOC contributions to ozone formation, Atmos. Environ., 285, 119224, https://doi.org/10.1016/j.atmosenv.2022.119224, 2022. a
Zhu, Q., Schwantes, R. H., Coggon, M., Harkins, C., Schnell, J., He, J., Pye, H. O. T., Li, M., Baker, B., Moon, Z., Ahmadov, R., Pfannerstill, E. Y., Place, B., Wooldridge, P., Schulze, B. C., Arata, C., Bucholtz, A., Seinfeld, J. H., Warneke, C., Stockwell, C. E., Xu, L., Zuraski, K., Robinson, M. A., Neuman, J. A., Veres, P. R., Peischl, J., Brown, S. S., Goldstein, A. H., Cohen, R. C., and McDonald, B. C.: A better representation of volatile organic compound chemistry in WRF-Chem and its impact on ozone over Los Angeles, Atmos. Chem. Phys., 24, 5265–5286, https://doi.org/10.5194/acp-24-5265-2024, 2024. a
Zhu, Z., Zhang, Z., Zhao, X., Zuo, L., and Wang, X.: Characteristics of Land Use Change in China before and after 2000, Sustainability, 14, 14623, https://doi.org/10.3390/su142114623, 2022. a
Short summary
The impact of biogenic emissions of hydrocarbons from vegetation on ozone, as well as on overall oxidative capacity of air, is analyzed for central European cities for a present-day period using a chemistry transport model. Moreover, the analysis evaluates the partial role of urban vegetation in impacting all biogenic emissions. We found substantial increases in ozone due to these emissions, and about 10% of this increase is attributable to vegetation within urban areas.
The impact of biogenic emissions of hydrocarbons from vegetation on ozone, as well as on overall...
Altmetrics
Final-revised paper
Preprint