Articles | Volume 20, issue 20
https://doi.org/10.5194/acp-20-11655-2020
© Author(s) 2020. 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-20-11655-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The impact of urban land-surface on extreme air pollution over central Europe
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Jan Karlický
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Institute of Meteorology and Climatology, Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendel-Straße 33, 1180 Vienna, Austria
Jana Ďoubalová
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Czech Hydrometeorological Institute (CHMI), Na Šabatce 17, 14306, Prague 4, Czech Republic
Tereza Nováková
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Kateřina Šindelářová
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Filip Švábik
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Michal Belda
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Tomáš Halenka
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
Michal Žák
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, V Holešovičkách 2, 18000, Prague 8, Czech Republic
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Ranjeet S. Sokhi, Nicolas Moussiopoulos, Alexander Baklanov, John Bartzis, Isabelle Coll, Sandro Finardi, Rainer Friedrich, Camilla Geels, Tiia Grönholm, Tomas Halenka, Matthias Ketzel, Androniki Maragkidou, Volker Matthias, Jana Moldanova, Leonidas Ntziachristos, Klaus Schäfer, Peter Suppan, George Tsegas, Greg Carmichael, Vicente Franco, Steve Hanna, Jukka-Pekka Jalkanen, Guus J. M. Velders, and Jaakko Kukkonen
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Publication in GMD not foreseen
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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.
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
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The analysis summarizes how sensitive the modelling of urban environment is to changes in physical parameters describing the city (e.g. reflectivity of surfaces) and to several heat island mitigation scenarios in a city quarter in Prague, Czech Republic. We used the large-eddy simulation modelling system PALM 6.0. Surface parameters connected to radiation show the highest sensitivity in this configuration. For heat island mitigation, urban vegetation is shown to be the most effective measure.
Beata Opacka, Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Katerina Sindelarova, Jana Markova, and Alex B. Guenther
Atmos. Chem. Phys., 21, 8413–8436, https://doi.org/10.5194/acp-21-8413-2021, https://doi.org/10.5194/acp-21-8413-2021, 2021
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Isoprene is mainly emitted from plants, and about 80 % of its global emissions occur in the tropics. Current isoprene inventories are usually based on modelled vegetation maps, but high pressure on land use over the last decades has led to severe losses, especially in tropical forests, that are not considered by models. We provide a study on the present-day impact of spaceborne land cover changes on isoprene emissions and the first inventory based on high-resolution Landsat tree cover dataset.
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.
Cited articles
Aleksankina, K., Reis, S., Vieno, M., and Heal, M. R.: Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model, Atmos. Chem. Phys., 19, 2881–2898, https://doi.org/10.5194/acp-19-2881-2019, 2019. a
Barnes, M. J., Brade, T. K., MacKenzie, A. R., Whyatt, J. D., Carruthers, D. J., Stocker, J., Cai, X., and Hewitt, C. N.: Spatially-varying surface roughness and ground-level air quality in an operational dispersion model, Environ. Pollut., 185, 44–51, https://doi.org/10.1016/j.envpol.2013.09.039, 2014. a
Berg, P., Wagner, S., Kunstmann, H., and Schädler, G.: High resolution regional climate model simulations for Germany: part I–validation, Clim. Dynam., 40, 401–14, https://doi.org/10.1007/s00382-012-1508-8, 2013. a, b
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.,
published by University of Hertfordshire, Paper presented at Air
Quality 2018 conference, Barcelona, 12–16 March 2018, Vol. 27, https://doi.org/10.18745/PB.19829, 2018. a
Bougeault, P. and Lacarrère, P.: Parameterization of orography-induced turbulence in a meso-beta-scale model, Mon. Weather Rev., 117, 1872–1890, 1989. 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, US EPA, North Carolina, 1999. 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
Chapman, S., Watson, J. E. M., Salazar, A., Thatcher, M., and McAlpine, C. A.: The impact of urbanization and climate change on urban temperatures: a systematic review, Landscape Ecol., 32, 1921–1935, https://doi.org/10.1007/s10980-017-0561-4, 2017. a
Civerolo, K., Hogrefe, C., Lynn, B., Rosenthal, J., Ku, J.-Y., Solecki, W., Cox, J., Small, C., Rosenzweig, C., Goldberg, R., Knowlton, K., and Kinney, P.: Estimating the effects of increased urbanization on surface meteorology and ozone concentrations in the New York City metropolitan region, Atmos. Environ., 41, 1803–1818, 2007. a
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, 2001. a
Chen, S. and Sun, W.: A one-dimensional time dependent cloud model, J. Meteorol. Soc. Jpn., 80, 99–118, 2002. a
Chen, B., Yang, S., Xu, X. D., and Zhang, W.: The impacts of urbanization on air quality over the Pearl River Delta in winter: roles of urban land use and emission distribution, Theor. Appl. Climatol., 117, 29–39, 2014. a
Cornes, R., van der Schrier, G., van den Besselaar, E. J. M., and
Jones, P. D.: An Ensemble Version of the E-OBS Temperature and Precipitation
Datasets, J. Geophys. Res.-Atmos., 123, 9391–9409, https://doi.org/10.1029/2017JD028200,
2018. a
Ďoubalová, J., Huszár, P., Eben, K., Benešová, N.,
Belda, M., Vlček, O., Karlický, J., Geletič, J., and
Halenka, T.: High Resolution Air Quality Forecasting Over Prague within the
URBI PRAGENSI Project: Model Performance During the Winter Period and the
Effect of Urban Parameterization on PM, Atmosphere, 11, 625, https://doi.org/10.3390/atmos11060625,
2020. a
Emery, Ch.: The WRFCAMx preprocessor, Ramboll Environ, Novato, California, available at: http://www.camx.com/getmedia/a751f2f5-fb0f-461d-a978-44b69c8130bd/wrfcamx-31May20_1.tgz, last access: 14 October 2020. 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
Fallmann, J., Forkel, R., and Emeis, S.: Secondary effects of urban heat island mitigation measures on air quality, Atmos. Environ., 25, 199–211, 2016. a
Fallmann, J., Wagner, S., and Emeis, S.: High resolution climate projections to assess the future vulnerability of European urban areas to climatological extreme events, Theor. Appl. Climatol., 127, 667–683, https://doi.org/10.1007/s00704-015-1658-9, 2017. a
Fan, Y., Hunt, J. C. R., and Li, Y.: Buoyancy and turbulence-driven
atmospheric circulation over urban areas, J. Environ. Sci., 59, 63–71, https://doi.org/10.1016/j.jes.2017.01.009, 2017. a
Flagg, D. D. and Taylor, P. A.: Sensitivity of mesoscale model urban boundary layer meteorology to the scale of urban representation, Atmos. Chem. Phys., 11, 2951–2972, https://doi.org/10.5194/acp-11-2951-2011, 2011. a
Flandorfer, C., Hirtl, M., and Scherllin-Pirscher, B.: Evaluation of O3 forecasts of ALARO-CAMx and WRF-Chem, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13535, https://doi.org/10.5194/egusphere-egu2020-13535, 2020. a
Folberth, G. A., Butler, T. M., Collins, W. J., and Rumbold, S. T.: Megacities and climate change – A brief overview, Environ. Pollut., 203, 235–242, https://doi.org/10.1016/j.envpol.2014.09.004, 2015. a
Freney, E. J., Sellegri, K., Canonaco, F., Colomb, A., Borbon, A., Michoud, V., Doussin, J.-F., Crumeyrolle, S., Amarouche, N., Pichon, J.-M., Bourianne, T., Gomes, L., Prevot, A. S. H., Beekmann, M., and Schwarzenböeck, A.: Characterizing the impact of urban emissions on regional aerosol particles: airborne measurements during the MEGAPOLI experiment, Atmos. Chem. Phys., 14, 1397–1412, https://doi.org/10.5194/acp-14-1397-2014, 2014. a
Gallus Jr., W. A. and Pfeifer, M.: Intercomparison of simulations using 5 WRF microphysical schemes with dual-Polarization data for a German squall line, Adv. Geosci., 16, 109–116, https://doi.org/10.5194/adgeo-16-109-2008, 2008. a
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M., Bi, X.,
Elguindi, N., Diro, G. T., Nair, V., Giuliani, G., Cozzini, S., Guettler, I.,
O'Brien, T. A., Tawfi, A. B., Shalaby, A., Zakey, A., Steiner, A.,
Stordal, F., Sloan, L., and Brankovic, C.: RegCM4: model description and
preliminary tests over multiple CORDEX domains, Clim. Res., 52, 7–29, 2012. a, b, c, d
Giuliani, G. (Ed.): ICTP: The Regional Climate Model version 4.6.1 source
code, available at: https://gforge.ictp.it/gf/project/regcm/frs/?action=FrsReleaseView&release_id=257 (last access:
31 March 2020), 2019. a
Granier, C. S., Darras, H., Denier van der Gon, J., Doubalova, N., Elguindi, B., Galle, M., Gauss, M., Guevara, J.-P., Jalkanen, J., and Kuenen, C.: The Copernicus Atmosphere Monitoring Service Global and Regional Emissions, Report April 2019 version (Research Report), ECMWF, Reading, UK, https://doi.org/10.24380/d0bn-kx16, 2019. a
Grell, G.: Prognostic evaluation of assumptions used by cumulus parameterizations, Mon. Weather Rev., 121, 764–787, 1993. a
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 6957–6975, 2005. a
Güttler, I., Brankovic, Č., O'Brien, T. A., Coppola, E., Grisogono, B., and Giorgi, F.: Sensitivity of the regional climate model RegCM4.2 to planetary boundary layer parameterization, Clim. Dynam., 43, 1753–1772, https://doi.org/10.1007/s00382-013-2003-6, 2014. a
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006. 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
Halenka, T., Belda, M. Huszar, P., Karlicky, J., Novakova, T., and Zak, M.: On the comparison of urban canopy effects parameterisation, Int. J. Environ. Pollut., 65, 1–3, https://doi.org/10.1504/IJEP.2019.101840, 2019. a
Han, B.-S., Baik, J.-J., Kwak, K.-H., and Park, S.-B.: Effects of cool roofs on turbulent coherent structures and ozone air quality in Seoul, Atmos. Environ., 229, 117476, https://doi.org/10.1016/j.atmosenv.2020.117476, 2020. a
Han, W., Li, Z., Wu, F., Zhang, Y., Guo, J., Su, T., Cribb, M., Fan, J., Chen, T., Wei, J., and Lee, S.-S.: The mechanisms and seasonal differences of the impact of aerosols on daytime surface urban heat island effect, Atmos. Chem. Phys., 20, 6479–6493, https://doi.org/10.5194/acp-20-6479-2020, 2020. a
Hao, L., Huang, X., Qin, M., Liu, Y., Li, W., and Sun, G.: Ecohydrological processes explain urban dry island effects in a wet region, southern China, Water Resour. Res., 54, 6757–6771, https://doi.org/10.1029/2018WR023002, 2018. a
Holtslag, A. A. M., de Bruijn, E. I. F., and Pan, H.-L.: A high resolution air mass transformation model for shortrange weather forecasting, Mon. Weather Rev., 118, 1561–1575, 1990. a
Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation, Mon. Weather Rev., 132, 103–120, https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2, 2004. a
Hong, S., Noh, Y., and Dudhia, J.: A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/MWR3199.1, 2006.
Hong, S., Sunny Lim, K., Kim, J., Lim, J. J., and Dudhia, J.: Sensitivity Study of Cloud-Resolving Convective Simulations with WRF Using Two Bulk Microphysical Parameterizations: Ice-Phase Microphysics versus Sedimentation Effects, J. Appl. Meteorol. Clim., 48, 61–76, https://doi.org/10.1175/2008JAMC1960.1, 2009. a
Huszar, P., Juda-Rezler, K., Halenka, T., Chervenkov, H., Syrakov, D., Krüger, B. C., Zanis,
P., Melas, D., Katragkou, E., Reizer, M., Trapp, W., and Belda, M.: Effects of climate change on ozone and particulate matter over Central and Eastern Europe, Clim. Res., 50, 51–68, https://doi.org/10.3354/cr01036, 2011. a
Huszar, P., Miksovsky, J., Pisoft, P., Belda, M., and Halenka, T.: Interactive coupling of a regional climate model and a chemistry transport model: evaluation and preliminary results on ozone and aerosol feedback, Clim. Res., 51, 59–88, https://doi.org/10.3354/cr01054, 2012. a, b
Huszar, P., Halenka, T., Belda, M., Zak, M., Sindelarova, K., and Miksovsky, J.: Regional climate model assessment of the urban land-surface forcing over central Europe, Atmos. Chem. Phys., 14, 12393–12413, https://doi.org/10.5194/acp-14-12393-2014, 2014. a, b, c
Huszár, P., Belda, M., Karlický, J., Pišoft, P., and Halenka, T.: The regional impact of urban emissions on climate over central Europe: present and future emission perspectives, Atmos. Chem. Phys., 16, 12993–13013, https://doi.org/10.5194/acp-16-12993-2016, 2016b. 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, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A.,
and Collins, W. D.: Radiative forcing by longlived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys. Res., 113, 2–9,
https://doi.org/10.1029/2008JD009944, 2008. a
Im, U. and Kanakidou, M.: Impacts of East Mediterranean megacity emissions on air quality, Atmos. Chem. Phys., 12, 6335–6355, https://doi.org/10.5194/acp-12-6335-2012, 2012. a
Im, U., Markakis, K., Poupkou, A., Melas, D., Unal, A., Gerasopoulos, E., Daskalakis, N., Kindap, T., and Kanakidou, M.: The impact of temperature changes on summer time ozone and its precursors in the Eastern Mediterranean, Atmos. Chem. Phys., 11, 3847–3864, https://doi.org/10.5194/acp-11-3847-2011, 2011.
Jacobson, M. Z., Nghiem, S. V., Sorichetta, A., and Whitney, N.: Ring of
impact from the mega-urbanization of Beijing between 2000 and 2009, J. Geophys. Res., 120, 5740–5756, https://doi.org/10.1002/2014JD023008, 2015. a, b
Janjic, Z. I.: The step-mountain Eta coordinate model: Further developments of the convection, viscous layer, and turbulence closure schemes, Mon. Weather Rev., 122, 927–945, 1994. a
Janssen, R. H. H., Tsimpidi, A. P., Karydis, V. A., Pozzer, A., Lelieveld, J., Crippa, M., Prévôt, A. S. H., Ait-Helal, W., Borbon, A., Sauvage, S., and Locoge, N.: Influence of local production and vertical transport on the organic aerosol budget over Paris, J. Geophys. Res., 122, 8276–8296, https://doi.org/10.1002/2016JD026402, 2017. a
Jiang, X., Wiedinmyer, C., Chen, F., Yang, Z.-L., and Lo, J. C.-F.: Predicted impacts of climate and land use change on surface ozone in the Houston, Texas, area, J. Geophys. Res., 113, D20312, https://doi.org/10.1029/2008JD009820, 2008. a, b
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, b
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. Discuss., https://doi.org/10.5194/acp-2020-433, in review, 2020. a
Kiehl, J., Hack, J., Bonan, G., Boville, B., Breigleb, B., Williamson, D.,
and Rasch, P.: Description of the NCAR Community Climate Model (CCM3),
National Center for Atmospheric Research Tech Note NCAR/TN-420 + STR, NCAR,
Boulder, CO, 1996. a
Kim, Y., Sartelet, K., Raut, J.-Ch., and Chazette, P.: Influence of an urban canopy model and PBL schemes on vertical mixing for air quality modeling over Greater Paris, Atmos. Environ., 107, 289–306, https://doi.org/10.1016/j.atmosenv.2015.02.011, 2015. a, b, c, d
Kyselý, J. and Plavcová, E.: A critical remark on the applicability of EOBS European gridded temperature data set for validating control climate simulations, J. Geophys. Res., 115, D23118, https://doi.org/10.1029/2010JD014123, 2010. 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, 2001. a
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton,P. E.,
Swenson, S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S.,
Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements
and functional and structural advances in version 4 of the Community Land
Model, J. Adv. Model. Earth Sy., 3, M03001, https://doi.org/10.1029/2011MS00045,
2011. a
Lawrence, M. G., Butler, T. M., Steinkamp, J., Gurjar, B. R., and Lelieveld, J.: Regional pollution potentials of megacities and other major population centers, Atmos. Chem. Phys., 7, 3969–3987, https://doi.org/10.5194/acp-7-3969-2007, 2007. a
Lee, J., Hong, J., Lee, K., Hong, J., Velasco, E., Lim, Y. J., Lee, J. B., Nam, K., and Park, J.: Ceilometer Monitoring of Boundary-Layer Height and Its Application in Evaluating the Dilution Effect on Air Pollution, Bound.-Lay. Meteorol., 172, 435–455, https://doi.org/10.1007/s10546-019-00452-5, 2019. a
Lee, S.-H., Kim, S.-W., Angevine, W. M., Bianco, L., McKeen, S. A., Senff, C. J., Trainer, M., Tucker, S. C., and Zamora, R. J.: Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign, Atmos. Chem. Phys., 11, 2127–2143, https://doi.org/10.5194/acp-11-2127-2011, 2011. a
Li, M., Wang, T., Xie, M., Zhuang, B., Li, S., Han, Y., and Cheng, N.: Modeling of urban heat island and its impacts on thermal circulations in the Beijing-Tianjin-Hebei region, China, Theor. Appl. Climatol., 128, 999–1013, 2017.
Li, Y., Barth, M. C., and Steiner, A. L.: Comparing turbulent mixing of atmospheric oxidants across model scales, Atmos. Environ., 199, 88–101, https://doi.org/10.1016/j.atmosenv.2018.11.004, 2019a. a
Li, Y., Zhang, J., Sailor, D. J., and Ban-Weiss, G. A.: Effects of urbanization on regional meteorology and air quality in Southern California, Atmos. Chem. Phys., 19, 4439–4457, https://doi.org/10.5194/acp-19-4439-2019, 2019b. a, b, c, d
Liao, J., Wang, T., Wang, X., Xie, M., Jiang, Z., Huang, X., and Zhu, J.: Impacts of different urban canopy schemes in WRF/Chem on regional climate and air quality in Yangtze River Delta, China, Atmos. Res., 145–146, 226–243, https://doi.org/10.1016/j.atmosres.2014.04.005, 2014. a
Madronich, S.: Photodissociation in the atmosphere: 1. Actinic flux and the effect of ground reflections and clouds, J. Geophys. Res., 92, 9740–9752, 1987. 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, b
Marke, T., Löhnert, U., Schemann, V., Schween, J. H., and Crewell, S.: Detection of land-surface-induced atmospheric water vapor patterns, Atmos. Chem. Phys., 20, 1723–1736, https://doi.org/10.5194/acp-20-1723-2020, 2020. a
Marlier, M. E., Jina, A. S., Kinney, P. L.: Extreme Air Pollution in Global Megacities, Curr. Clim. Change Rep., 2, 15, https://doi.org/10.1007/s40641-016-0032-z, 2016. a
Masson, V., Gomes, L., Pigeon, G., Liousse, C., Pont, V.,
Lagouarde, J.-P., Voogt, J., Salmond, J., Oke, T. R., Hidalgo, J., Legain, D., Garrouste, O., Lac, C., Connan, O.,
Briottet, X., Lachérade, S., and Tulet, P.: The Canopy
and Aerosol Particles Interactions in TOulouse Urban Layer
(CAPITOUL) experiment, Meteorol. Atmos. Phys., 102, 135,
https://doi.org/10.1007/s00703-008-0289-4, 2008. a
Martilli, A., Roulet, Y.-A., Junier, M., Kirchner, F., Rotach, M. W., and Clappier, A.: On the impact of urban surface exchange parameterisations on air quality simulations: the Athens case, Atmos. Environ., 37, 4217–4231, https://doi.org/10.1016/S1352-2310(03)00564-8, 2003. a, b
Myhre, G., Grini, A., and Metzger, S.: Modelling of nitrate and ammonium-containing aerosols in presence of sea salt, Atmos. Chem. Phys., 6, 4809–4821, https://doi.org/10.5194/acp-6-4809-2006, 2006. a
Nenes, A., Pandis, S. N., and Pilinis, C.: ISORROPIA: a new thermodynamic
equilibrium model for multiphase multicomponent inorganic aerosols, Aquat.
Geochem., 4, 123–152, 1998. a
Oke, T., Mills, G., Christen, A., and Voogt, J.: Urban Climates, Cambridge
University Press, Cambridge, https://doi.org/10.1017/9781139016476, 2017. a
Oke, T. R.: The energetic basis of the urban heat island, Q. J. Roy. Meteor. Soc., 108, 1–24,
https://doi.org/10.1002/qj.49710845502, 1982. a
Oleson, K., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M.,
Swenson, S. C., Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J.-F., Lawrence, P. J., Leung, L. R.,
Lipscomb, W., Muszala, S., Ricciuto, D. M., Sacks, W., Sun, Y.,
Tang, J., and Yang, Z.-L.: Technical Description of version 4.5
of the Community Land Model (CLM), NCAR Technical Note
NCAR/TN-503+STR, Boulder, Colorado, 420 pp., 2013. a
Passant, N.: Speciation of UK Emissions of Non-methane Volatile Organic Compounds, DEFRA, Oxon, UK, 2002. a
Pleim, J. E.: A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part I: Model Description and Testing, J. Appl. Meteorol. Clim., 46, 1383–1395, https://doi.org/10.1175/JAM2539.1, 2007.
Price, C. and Rind, D.: A simple lightning parameterization for calculating global lightning distributions, J. Geophys. Res.-Atmos., 97, 9919–9933, https://doi.org/10.1029/92JD00719, 1992. a
Ren, Y., Zhang, H., Wei, W., Wu, B., Cai, X., and Song, Y.: Effects of
turbulence structure and urbanization on the heavy haze pollution process,
Atmos. Chem. Phys., 19, 1041–1057, https://doi.org/10.5194/acp-19-1041-2019, 2019. a
Rotach, M. W., Vogt, R., Bernhofer, C., Batchvarova, E., Christen, A., Clappier, A., Feddersen, B., Gryning, S.-E., Martucci, G., Mayer, H., Mitev, V., Oke, T. R., Parlow, E., Richner, H., Roth, M., Roulet, Y.-A., Ruffieux, D., Salmond, J. A., Schatzmann, M., and
Voogt, J. A.: BUBBLE – an urban boundary layer meteorology project, Theor. Appl. Climatol., 81, 231–261, 2005.
Ryu, Y.-H., Baik, J.-J., Kwak, K.-H., Kim, S., and Moon, N.: Impacts of urban land-surface forcing on ozone air quality in the Seoul metropolitan area, Atmos. Chem. Phys., 13, 2177–2194, https://doi.org/10.5194/acp-13-2177-2013, 2013a. a, b
Ryu, Y.-H., Baik, J.-J., and
Lee, S.-H.: Effects of anthropogenic heat on ozone air quality in
a megacity, Atmos. Environ., 80, 20–30,
https://doi.org/10.1016/j.atmosenv.2013.07.053, 2013b. a, b
Schaap, M., van Loon, M., ten Brink, H. M., Dentener, F. J., and Builtjes, P. J. H.: Secondary inorganic aerosol simulations for Europe with special attention to nitrate, Atmos. Chem. Phys., 4, 857–874, https://doi.org/10.5194/acp-4-857-2004, 2004. a
Schell, B., Ackermann, I. J., Hass, H., Binkowski, F. S., and Ebel, A.: Modeling the formation of secondary organic aerosol within a comprehensive air quality model system, J. Geophys. Res., 106, 28275–28293, https://doi.org/10.1029/2001JD000384, 2001. a
Seinfeld, J. H.: Urban Air Pollution: State of the Science, Science, 243, 745–752, https://doi.org/10.1126/science.243.4892.745, 1989. a
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air
Pollution to Climate Change, J. Wiley, New York, 1998. a
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
Sindelarova, K., Granier, C., Bouarar, I., Guenther, A., Tilmes, S., Stavrakou, T., Müller, J.-F., Kuhn, U., Stefani, P., and Knorr, W.: Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years, Atmos. Chem. Phys., 14, 9317–9341, https://doi.org/10.5194/acp-14-9317-2014, 2014. a
Stock, Z. S., Russo, M. R., Butler, T. M., Archibald, A. T., Lawrence, M. G., Telford, P. J., Abraham, N. L., and Pyle, J. A.: Modelling the impact of megacities on local, regional and global tropospheric ozone and the deposition of nitrogen species, Atmos. Chem. Phys., 13, 12215–12231, https://doi.org/10.5194/acp-13-12215-2013, 2013. a
Stockwell, W. R., Middleton, P., Chang, J. S., and Tang, X.: The second generation regional acid deposition model chemical mechanism for regional air quality modeling, J. Geophys. Res., 95, 16343, https://doi.org/10.1029/JD095iD10p16343, 1990. a
Strader, R., Lurmann, F., and Pandis, S. N.: Evaluation of secondary organic aerosol formation in winter, Atmos. Environ., 33, 4849–4863, 1999. a
Sun, L., Xue, L., Wang, Y., Li, L., Lin, J., Ni, R., Yan, Y., Chen, L., Li, J., Zhang, Q., and Wang, W.: Impacts of meteorology and emissions on summertime surface ozone increases over central eastern China between 2003 and 2015, Atmos. Chem. Phys., 19, 1455–1469, https://doi.org/10.5194/acp-19-1455-2019, 2019. a
Tyagi, B., Magliulo, V., Finardi, S., Gasbarra, D., Carlucci, P., Toscano, P.,
Zaldei, A., Riccio, A., Calori, G., D'Allura, A., and Gioli, B.: Performance
Analysis of Planetary Boundary Layer Parameterization Schemes in WRF Modeling
Set Up over Southern Italy, Atmosphere, 9, 272, https://doi.org/10.3390/atmos9070272, 2018. a
Tie, X., Brasseur, G., and Ying, Z.: Impact of model resolution on chemical ozone formation in Mexico City: application of the WRF-Chem model, Atmos. Chem. Phys., 10, 8983–8995, https://doi.org/10.5194/acp-10-8983-2010, 2010. a
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization in
Large-Scale Models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Trusilova, K., Jung, M., Churkina, G., Karstens, U., Heimann, M., and Claussen, M.: Urbanization Impacts on the Climate in Europe: Numerical Experiments by the PSU–NCAR Mesoscale Model (MM5), J. Appl. Meteorol. Clim., 47, 1442–1455, https://doi.org/10.1175/2007JAMC1624.1, 2008. a
Tuccella, P., Curci, G., Visconti, G., Bessagnet, B., Menut, L., and Park, R. J.: Modeling of gas and aerosol with WRF/Chem over Europe: Evaluation and sensitivity study, J. Geophys. Res., 117, D03303, https://doi.org/10.1029/2011JD016302, 2012. a, b
UN: The 2018 Revision of the World Urbanization Prospects, Population Division
of the United Nations Department of Economic and Social Affairs (UN DESA), New
York, available at:
https://www.un.org/development/desa/publications/2018-revision-of-world-urbanization-prospects.html
(last access: 14 October 2020), 2018. a
Vaisala: USER'S GUIDE – Vaisala Ceilometer CL31, Vaisala Oyj, P.O. Box 26, 00421 Helsinki, Finland, 2015. a
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, available at:
https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf
(last access: 14 October 2020), 2011. a
Varentsov, M., Konstantinov, P., Baklanov, A., Esau, I., Miles, V., and Davy, R.: Anthropogenic and natural drivers of a strong winter urban heat island in a typical Arctic city, Atmos. Chem. Phys., 18, 17573–17587, https://doi.org/10.5194/acp-18-17573-2018, 2018. a
Wang, Z. Q., Duan, A. M., and Wu, G. X.: Impacts of boundary layer parameterization schemes and air-sea coupling on WRF simulation of the East Asian summer monsoon, Sci. China Earth Sci., 57, 1480–1493, https://doi.org/10.1007/s11430-013-4801-4, 2014. a
Wei, W., Zhang, H., Wu, B., Huang, Y., Cai, X., Song, Y., and Li, J.: Intermittent turbulence contributes to vertical dispersion of PM2.5 in the North China Plain: cases from Tianjin, Atmos. Chem. Phys., 18, 12953–12967, https://doi.org/10.5194/acp-18-12953-2018, 2018. a
WRF: WRF-Chem version 4.1, available at:
https://www.acom.ucar.edu/wrf-chem/download.shtml, last access: 14 October 2020. a
Xie, M., Zhu, K., Wang, T., Feng, W., Gao, D., Li, M., Li, S., Zhuang, B.,
Han, Y., Chen, P., and Liao, J.: Changes in regional meteorology induced by
anthropogenic heat and their impacts on air quality in South China,
Atmos. Chem. Phys., 16, 15011–15031, https://doi.org/10.5194/acp-16-15011-2016, 2016a. a, b, c, d
Xie, M., Liao, J., Wang, T., Zhu, K., Zhuang, B., Han, Y., Li, M., and Li, S.:
Modeling of the anthropogenic heat flux and its effect on regional meteorology
and air quality over the Yangtze River Delta region, China,
Atmos. Chem. Phys., 16, 6071–6089, https://doi.org/10.5194/acp-16-6071-2016,
2016b. a, b
Yan, S., Zhu, B., Huang, Y., Zhu, J., Kang, H., Lu, C., and Zhu, T.: To what extents do urbanization and air pollution affect fog?, Atmos. Chem. Phys., 20, 5559–5572, https://doi.org/10.5194/acp-20-5559-2020, 2020. a
Yarwood, G., Rao, S., Yocke, M., and Whitten, G. Z.: Updates to the Carbon
Bond chemical mechanism: CB05, Final Report prepared for US EPA, Novato, NC,
USA, available at:
http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf (last access:
14 October 2020), 2005. a
Yu, M., Tang, G., Yang, Y., Li, Q., Wang, Y., Miao, S., Zhang, Y., and Wang, Y.: The interaction between urbanization and aerosols during a typical winter haze event in Beijing, Atmos. Chem. Phys., 20, 9855–9870, https://doi.org/10.5194/acp-20-9855-2020, 2020. a
Žák, M., Nita, A., Dumitrescu, A., and Sorin, Ch.: Influence of
synoptic scale atmospheric circulation on the development of urban heat island
in Prague and Bucharest, Urban Climate, 34, 100681,
https://doi.org/10.1016/j.uclim.2020.100681, 2020. a
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, b
Zha, J., Zhao, D., Wu, J., and Zhang, P.: Numerical simulation of the effects
of land use and cover change on the near-surface wind speed over Eastern
China, Clim. Dynam., 53, 1783–1803, https://doi.org/10.1007/s00382-019-04737-w, 2019. a
Zhang, L., Brook, J. R., and Vet, R.: A revised parameterization for gaseous dry deposition in air-quality models, Atmos. Chem. Phys., 3, 2067–2082, https://doi.org/10.5194/acp-3-2067-2003, 2003. a
Zhao, L., Lee, X., Smith, R. B., and Oleson, K.: Strong contributions of local background climate to urban heat islands, Nature, 511, 214–219, 2014. a
Zhao, L., Lee, X., and Schultz, N. M.: A wedge strategy for mitigation of urban warming in future climate scenarios, Atmos. Chem. Phys., 17, 9067–9080, https://doi.org/10.5194/acp-17-9067-2017, 2017. a
Zhao, N., Jiao, Y., Ma, T., Zhao, M., Fan, Z., Yin, X., Liu, Y., and Yue, T.: Estimating the effect of urbanization on extreme climate events in the Beijing-Tianjin-Hebei region, China, Sci. Total Environ., 688, 1005–1015, https://doi.org/10.1016/j.scitotenv.2019.06.374, 2019. a
Zhong, S., Qian, Y., Zhao, C., Leung, R., Wang, H., Yang, B., Fan, J., Yan, H., Yang, X.-Q., and Liu, D.: Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China, Atmos. Chem. Phys., 17, 5439–5457, https://doi.org/10.5194/acp-17-5439-2017, 2017.
a
Zhong, S., Qian, Y., Sarangi, C., Zhao, C., Leung, R., Wang, H.,
Yan, H.,
Yang, T., and
Yang, B.:
Urbanization effect on winter haze in the Yangtze River Delta region of China,
Geophys. Res. Lett., 45, 6710–6718, https://doi.org/10.1029/2018GL077239, 2018. a
Zhu, K., Xie, M., Wang, T., Cai, J., Li, S., and Feng, W.: A modeling study on the effect of urban land surface forcing to regional meteorology and air quality over South China, Atmos. Environ., 152, 389–404, https://doi.org/10.1016/j.atmosenv.2016.12.053, 2017. a, b, c, d
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.
The paper shows how extreme meteorological conditions change due to the urban land-cover forcing...
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