Articles | Volume 22, issue 16
https://doi.org/10.5194/acp-22-10443-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-22-10443-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Columnar and surface urban aerosol in the Moscow megacity according to measurements and simulations with the COSMO-ART model
Natalia E. Chubarova
Faculty of Geography, Lomonosov Moscow State University, Moscow,
119991, Russian Federation
Heike Vogel
CORRESPONDING AUTHOR
Karlsruhe Institute of Technology, Karlsruhe, Germany
Elizaveta E. Androsova
Faculty of Geography, Lomonosov Moscow State University, Moscow,
119991, Russian Federation
Alexander A. Kirsanov
Hydrometeorological Research Center of Russian Federation, Moscow,
123242, Russian Federation
Olga B. Popovicheva
Faculty of Physics, Lomonosov Moscow State University, Moscow, 119991,
Russian Federation
Bernhard Vogel
Karlsruhe Institute of Technology, Karlsruhe, Germany
Gdaliy S. Rivin
Faculty of Geography, Lomonosov Moscow State University, Moscow,
119991, Russian Federation
Hydrometeorological Research Center of Russian Federation, Moscow,
123242, Russian Federation
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Lukas O. Muser, Gholam Ali Hoshyaripour, Julia Bruckert, Ákos Horváth, Elizaveta Malinina, Sandra Wallis, Fred J. Prata, Alexei Rozanov, Christian von Savigny, Heike Vogel, and Bernhard Vogel
Atmos. Chem. Phys., 20, 15015–15036, https://doi.org/10.5194/acp-20-15015-2020, https://doi.org/10.5194/acp-20-15015-2020, 2020
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Volcanic aerosols endanger aircraft and thus disrupt air travel globally. For aviation safety, it is vital to know the location and lifetime of such aerosols in the atmosphere. Here we show that the interaction of volcanic particles with each other eventually reduces their atmospheric lifetime. Moreover, we demonstrate that sunlight heats these particles, which lifts them several kilometers in the atmosphere. These findings support a more reliable forecast of volcanic aerosol dispersion.
Cited articles
AERONET: https://aeronet.gsfc.nasa.gov/, last access:
28 January 2022.
ACTRIS: https://actris.nilu.no, last access: 28 January 2022.
AEROCOM: https://aerocom.met.no/, last access: 28 January 2022.
Air quality in Europe: 2020 report, EEA Report No 09/2020, Luxembourg,
Publications Office of the European Union, 164 pp., ISSN 1977-8449, 2020.
Amato, F., Pandolfi, M., Escrig, A., Querol, X., Alastuey, A., Pey, J.,
Perez, N., and Hopke, P. K.: Quantifying road dust resuspension in urban
environment by Multilinear Engine: A comparison with PMF2, Atmos.
Environ., 43, 2770–2780, https://doi.org/10.1016/j.atmosenv.2009.02.039,
2009.
Baklanov, A., Smith Korsholm, U., Nuterman, R., Mahura, A., Nielsen, K. P., Sass, B. H., Rasmussen, A., Zakey, A., Kaas, E., Kurganskiy, A., Sørensen, B., and González-Aparicio, I.: Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2), Geosci. Model Dev., 10, 2971–2999, https://doi.org/10.5194/gmd-10-2971-2017, 2017.
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer,
M., and Reinhardt, T.: Operational
Convective-Scale Numerical Weather Prediction with the COSMO Model:
Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905,
https://doi.org/10.1175/MWR-D-10-05013.1, 2011.
Bellouin, N., Quaas, J., Morcrette, J.-J., and Boucher, O.: Estimates of aerosol radiative forcing from the MACC re-analysis, Atmos. Chem. Phys., 13, 2045–2062, https://doi.org/10.5194/acp-13-2045-2013, 2013.
Bhugwant, C. and Brémaud, P.: Simultaneous Measurements of Black Carbon,
PM10, Ozone and NOx Variability at a Locally Polluted Island in the Southern
Tropics, J. Atmos. Chem., 39, 261–280,
https://doi.org/10.1023/A:1010692201459, 2001.
Binkowski, F. S. and Shankar, U.: The regional particulate matter model, 1.
Model description and preliminary results, J. Geophys. Res., 100,
26191–26209, 1995.
Bohren, C. F. and Huffman, D. R.: Absorption and Scattering of Light by
Small Particles, Wiley, New York, 1983.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T.,
DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne,
S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M.,
Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K.,
Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U.,
Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C.
S.: Bounding the role of black carbon in the climate system: A scientific
assessment, J. Geophys. Res.-Atmos., 118, 5380–5552,
https://doi.org/10.1002/jgrd.50171, 2013.
Chen, X., Zhang, Z., Engling, G., Zhang, R., Tao, J., Lin, M., Sang, X.,
Chan, C., Li, S., and Li, Y.: Characterization of fine particulate black
carbon in Guangzhou, a megacity of South China, Atmos. Pollut. R., 5,
361–370, https://doi.org/10.5094/APR.2014.042, 2014.
Chou, M.-D., Lin, P.-H., Ma, P.-L., and Lin, H.-J.: Effects of aerosols on the
surface solar radiation in a tropical urban area, J. Geophys. Res., 111,
D15207, https://doi.org/10.1029/2005JD006910, 2006.
Chubarova, N. Y.: Seasonal distribution of aerosol properties over Europe and their impact on UV irradiance, Atmos. Meas. Tech., 2, 593–608, https://doi.org/10.5194/amt-2-593-2009, 2009.
Chubarova, N. Y. (Ed.): Aerosol urban pollution and its effects on weather,
regional climate and geochemical processes, MAKS Press, Moscow, Russian
Federation, https://doi.org/10.29003/m1475.978-5-317-06464-8, 2020.
Chubarova, N., Smirnov, A., and Holben, B.: Aerosol properties in Moscow
according to 10 years of AERONET measurements at the Meteorological
Observatory of Moscow State University, Geography, Environment,
Sustainability, 4, 19–32,
https://doi.org/10.24057/2071-9388-2011-4-1-19-32, 2011a.
Chubarova, N. Y., Sviridenkov, M. A., Smirnov, A., and Holben, B. N.: Assessments of urban aerosol pollution in Moscow and its radiative effects, Atmos. Meas. Tech., 4, 367–378, https://doi.org/10.5194/amt-4-367-2011, 2011b.
Chubarova, N., Sviridenkov, M., Kopeikin, V., Emilenko, K., Verichev, A.
and Skorokhod, S. E.: Aerosol pollution over Moscow area, 3rd Meeting
on Pan-Eurasian Experiment (PEEX), 26–28 August 2013, Hyytiala, Finland,
2013.
Chubarova, N. E., Nezval', E. I., Belikov, I. B., Gorbarenko, E. V.,
Eremina, I. D., Zhdanova, E. Yu., Korneva, I. A., Konstantinov, P. I.,
Lokoshchenko, M. A., Skorokhod, A. I., and Shilovtseva, O. A.: Climatic and
environmental characteristics of Moscow megalopolis according to the data of
the Moscow State University Meteorological Observatory over 60 years, Russ.
Meteorol. Hydrol., 39, 602–613, https://doi.org/10.3103/S1068373914090052,
2014.
Chubarova, N. Y., Poliukhov, A. A., and Gorlova, I. D.: Long-term variability of aerosol optical thickness in Eastern Europe over 2001–2014 according to the measurements at the Moscow MSU MO AERONET site with additional cloud and NO2 correction, Atmos. Meas. Tech., 9, 313–334, https://doi.org/10.5194/amt-9-313-2016, 2016.
Chubarova, N. Y., Androsova, Y. Y., and Lezina, Y. A.: The dynamics of
the atmospheric pollutants during the COVID-19 pandemic 2020 and their
relationship with meteorological conditions in Moscow, Geography,
Environment, Sustainability, 14,
168–182, https://doi.org/10.24057/2071-9388-2021-012, 2021.
COSMO: http://www.cosmo-model.org/, last access: 28 January 2022.
Diapouli, E., Kalogridis, A.-C., Markantonaki, C., Vratolis, S., Fetfatzis,
P., Colombi, C., and Eleftheriadis, K.: Annual Variability of Black Carbon
Concentrations Originating from Biomass and Fossil Fuel Combustion for the
Suburban Aerosol in Athens, Greece, Atmosphere, 8, 234,
https://doi.org/10.3390/atmos8120234, 2017.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of
aerosol optical properties from Sun and sky radiance measurements, J.
Geophys. Res., 105, 20673–20696, https://doi.org/10.1029/2000JD900282,
2000.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M.
D., Tanre, D., and Slutsker, I.: Variability of absorption and optical
properties of key aerosol types observed in worldwide locations, J. Atmos.
Sci., 59, 590–608, 2002.
Elansky, N. F.: Air quality and CO emissions in the Moscow megacity, Urban
Clim., 8, 42–56, https://doi.org/10.1016/j.uclim.2014.01.007, 2014.
Elansky, N. F., Ponomarev, N. A., and Verevkin, Y. M.: Air quality and
pollutant emissions in the Moscow megacity in 2005–2014, Atmos. Environ.,
175, 54–64, https://doi.org/10.1016/j.atmosenv.2017.11.057, 2018.
Evans, M. J., Fiore, A., and Jacob, D. J.: The GEOS-CHEM chemical mechanism:
Version 5-07-8, Tech. rep., University of Leeds, Leeds, UK, 2003.
Filonchuk, M., Hurynovich, V., Yan, H., Zhou, L., and Gusev, A.: Climatology
of aerosol optical depth over Eastern Europe based on 19 years (2000–2018)
MODIS TERRA data, Int. J. Climatol., 40, 3531–3549,
https://doi.org/10.1002/joc.6412, 2019.
FIRMS: https://firms.modaps.eosdis.nasa.gov/map/, last access: 15 September 2021.
Gamma-ET Instruments: Gamma-ET, http://www.etek-ltd.ru/, last
access: 28 January 2022.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Gilardoni, S., Vignati, E., and Wilson, J.: Using measurements for evaluation of black carbon modeling, Atmos. Chem. Phys., 11, 439–455, https://doi.org/10.5194/acp-11-439-2011, 2011.
Gliß, J., Mortier, A., Schulz, M., Andrews, E., Balkanski, Y., Bauer, S. E., Benedictow, A. M. K., Bian, H., Checa-Garcia, R., Chin, M., Ginoux, P., Griesfeller, J. J., Heckel, A., Kipling, Z., Kirkevåg, A., Kokkola, H., Laj, P., Le Sager, P., Lund, M. T., Lund Myhre, C., Matsui, H., Myhre, G., Neubauer, D., van Noije, T., North, P., Olivié, D. J. L., Rémy, S., Sogacheva, L., Takemura, T., Tsigaridis, K., and Tsyro, S. G.: AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations, Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, 2021.
Golitsyn, G. S., Grechko, E. I., Wang, G., Wang, P., Dzhola, A. V.,
Emilenko, A. S., Kopeikin, V. M., Rakitin, V. S., Safronov, A. N., and
Fokeeva, E. V.: Studying the pollution of Moscow and Beijing atmospheres
with carbon monoxide and aerosol, Izv. Atmos. Ocean. Phys., 51, 1–11,
https://doi.org/10.1134/S0001433815010041, 2015.
Gubanova, D. P., Belikov, I. B., Elansky, N. F., Skorokhod, A. I., and
Chubarova, N. E.: Variations in PM2.5 Surface Concentration in Moscow
according to Observations at MSU Meteorological Observatory, Atmos. Ocean.
Opt., 31, 290–299, https://doi.org/10.1134/S1024856018030065, 2018.
Herich, H., Hueglin, C., and Buchmann, B.: A 2.5 year's source apportionment study of black carbon from wood burning and fossil fuel combustion at urban and rural sites in Switzerland, Atmos. Meas. Tech., 4, 1409–1420, https://doi.org/10.5194/amt-4-1409-2011, 2011.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer,
A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F.,
Jankowiak, I., and Smirnov, A.: AERONET – A Federated Instrument Network and
Data Archive for Aerosol Characterization, Remote Sens. Environ., 66, 1–16,
https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Hosiokangas, J., Vallius, M., Ruuskanen, J., Mirme, A., and Pekkanen, J.:
Resuspended dust episodes as an urban air-quality problem in subarctic
regions, Scand. J. Work Environ. Health, 30, 28–35, 2004.
Huang, R. J., Zhang, Y., Bozzetti, C., Ho, K. F., Cao, J. J., Han, Y., Daellenbach, K. R., Slowik, J. G., Platt, S. M., Canonaco, F., Zotter, P., Wolf, R., Pieber, S. M., Bruns, E. A., Crippa, M., Ciarelli, G., Piazzalunga, A., Schwikowski, M., Abbaszade, G., Schnelle-Kreis, J., Zimmermann, R., An, Z., Szidat, S., Baltensperger, U., El Haddad, I., Prévôt, A. S.: High secondary aerosol
contribution to particulate pollution during haze events in China, Nature,
514, 218–222, https://doi.org/10.1038/nature13774, 2014.
Huang, X. and Ding, A.: Aerosol as a critical factor causing forecast biases
of air temperature in global numerical weather prediction models, Sci.
Bull., 66, 1917–1924, https://doi.org/10.1016/j.scib.2021.05.009, 2021.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, 1535, https://doi.org/10.1017/cbo9781107415324.004, 2013.
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working
Group I to the Sixth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L.,
Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell,
K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T.,
Yelekçi, O., Yu, R., and Zhou, B., in press, 2022.
Jacobson, M. Z.: Climate response of fossil fuel and biofuel soot,
accounting for soot's feedback to snow and sea ice albedo and emissivity, J.
Geophys. Res., 109, D21201, https://doi.org/10.1029/2004JD004945, 2004.
Jacobson, M. Z.: Effects of absorption by soot inclusions within clouds and
precipitation on global climate, J. Phys. Chem. A, 110, 6860–6873,
https://doi.org/10.1021/jp056391r, 2006.
Jin, X., Zhu, Q., and Cohen, R. C.: Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMI, Atmos. Chem. Phys., 21, 15569–15587, https://doi.org/10.5194/acp-21-15569-2021, 2021.
Kerminen, V.-M. and Wexler, A. S.: Post-fog nucleation of H2SO4 –
H2O particles in smog, Atmos. Environ., 28, 2399–2406, 1994.
Kinne, S., O'Donnel, D., Stier, P., Kloster, S., Zhang, K., Schmidt, H.,
Rast, S., Giorgetta, M., Eck, T. F., and Stevens, B.: MAC-v1: A new global
aerosol climatology for climate studies: MAC-v1 for Climate Studies, J. Adv.
Model. Earth Syst., 5, 704–740, https://doi.org/10.1002/jame.20035, 2013.
Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the
spectral dependence of light absorption by aerosols is affected by organic
carbon, J. Geophys. Res., 109, D21, https://doi.org/10.1029/2004JD004999,
2004.
Kislov, A. V. (Ed.): Climate of Moscow in global warming conditions, Moscow
University Press, Moscow, Russian Federation, ISBN 978-5-19-011227-6, 2017.
Koepke, P., Hess, M., Schult, I., and Shettle, E. P.: Global Aerosol Data
Set, Rep. No. 243, Max-Planck-Institut für Meteorologie, Hamburg,
Germany, 1997.
Kozlov, V., Panchenko, M., and Yausheva, E.: Mass fraction of black carbon
in submicron aerosol as an indicator of influence of smoke from remote
forest fires in Siberia, Atmos. Environ., 42, 2611–2620,
https://doi.org/10.1016/j.atmosenv.2007.07.036, 2008.
Kozlov, V. S., Panchenko, M. V., Pol'kin, V. V., and Terpugova, S. A.: Technique for determination of the single scattering albedo of submicron aerosol in the
approximation of lognormal size distribution of black carbon, Proc. SPIE
10035, 22nd International Symposium on Atmospheric and Ocean Optics:
Atmospheric Physics, 100352Z, 29 November 2016, https://doi.org/10.1117/12.2247992,
2016.
Kozlov, V., Panchenko, M., and Yausheva, E.: Diurnal variations of the submicron aerosol and black carbon in the near-ground layer, Atmos. Ocean. Opt., 24, 30–38, 2011.
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.
Kulbachevsky,
A. O. (Ed.): Report on the state of the environment in Moscow in 2018, http://www.ecology.moscow/eco/ru/report_result/o_452195 (last access: 16 September 2021), 2019.
Kulbachevsky,
A. O. (Ed.): Report on the state of the environment in Moscow in 2019, https://www.mos.ru/upload/documents/files/7452/Gosdoklad_last_edit_ll_.pdf (last access:
16 September 2021), 2020.
Kumar, S., Srivastava, A. K., and Pathak, V.: Surface solar radiation and its association with aerosol characteristics at an urban station in the
Indo-Gangetic Basin: Implication to radiative effect, J. Atmos.
Sol.-Terr. Phy., 193, 105061,
https://doi.org/10.1016/j.jastp.2019.105061, 2019.
Kuznetsova, I. N., Shalygina, I. Yu., Nakhaev, M. I., Glazkova, A. A.,
Zakharova, P. V., Lezina, E. A., and Zvyagintsev, A. M.: Unfavorable
meteorological factors for air quality, Proceedings of Russian
Hydrometeorological Center, 351, 154–172, 2014.
Li, H., Meier, F., Lee, X., Chakraborty, T., Liu, J., Schaap, M., and
Sodoudi, S.: Interaction between urban heat island and urban pollution
island during summer in Berlin, Sci. Total Environ., 636, 818–828,
https://doi.org/10.1016/j.scitotenv.2018.04.254, 2018.
Liu, C., Chung, C. E., Yin, Y., and Schnaiter, M.: The absorption Ångström exponent of black carbon: from numerical aspects, Atmos. Chem. Phys., 18, 6259–6273, https://doi.org/10.5194/acp-18-6259-2018, 2018.
Loeb, N. G. and Su, W.: Direct Aerosol Radiative Forcing Uncertainty Based
on a Radiative Perturbation Analysis, J. Climate, 23, 5288–5293,
https://doi.org/10.1175/2010JCLI3543.1, 2010.
Logothetis, S.-A., Salamalikis, V., and Kazantzidis, A.: Aerosol classification in
Europe, Middle East, North Africa and Arabian Peninsula based on AERONET
Version 3, Atmos. Res., 239, 104893, https://doi.org/10.1016/j.atmosres.2020.104893, 2020.
Lu, F., Xu, D., Cheng, Y., Dong, S., Guo, C., Jiang, X., and Zheng, X.:
Systematic review and meta-analysis of the adverse health effects of ambient
PM2.5 and PM10 pollution in the Chinese population, Environ. Res., 136,
196–204, https://doi.org/10.1016/j.envres.2014.06.029, 2015.
Lugon, L., Vigneron, J., Debert, C., Chrétien, O., and Sartelet, K.: Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert), Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, 2021.
Lyapustin, A., Wang, Y., Korkin, S., and Huang, D.: MODIS Collection 6 MAIAC algorithm, Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, 2018.
Manisalidis, I., Stavropoulou, E., Stavropoulos, A., and Bezirtzoglou, E.:
Environmental and Health Impacts of Air Pollution: A Review, Front. Public
Health, 8, 14, https://doi.org/10.3389/fpubh.2020.00014, 2020.
Markowicz, K. M., Ritter, C., Lisok, J., Makuch, P., Stachlewska, I. S., Cappelletti, D., Mazzola,
M., and Chilinski, M. T.: Vertical variability of aerosol
single-scattering albedo and equivalent black carbon concentration based on
in-situ and remote sensing techniques during the iAREA campaigns in
Ny-Ålesund, Atmos. Environ., 431–447, https://doi.org/10.1016/j.atmosenv.2017.06.014, 2017.
Mosecomonitoring State Environmental Protection Agency: http://mosecom.mos.ru/, last access: 28 January 2022.
Myachkova, N. A.: Climates of the USSR, Moscow University Press, Moscow,
1983.
Myhre, G.: Consistency Between Satellite-Derived and Modeled Estimates of
the Direct Aerosol Effect, Science, 325, 187–190,
https://doi.org/10.1126/science.1174461, 2009.
Myhre, G., Berglen, T. F., Johnsrud, M., Hoyle, C. R., Berntsen, T. K., Christopher, S. A., Fahey, D. W., Isaksen, I. S. A., Jones, T. A., Kahn, R. A., Loeb, N., Quinn, P., Remer, L., Schwarz, J. P., and Yttri, K. E.: Modelled radiative forcing of the direct aerosol effect with multi-observation evaluation, Atmos. Chem. Phys., 9, 1365–1392, https://doi.org/10.5194/acp-9-1365-2009, 2009.
Myhre, G., Samset, B. H., Schulz, M., Balkanski, Y., Bauer, S., Berntsen, T. K., Bian, H., Bellouin, N., Chin, M., Diehl, T., Easter, R. C., Feichter, J., Ghan, S. J., Hauglustaine, D., Iversen, T., Kinne, S., Kirkevåg, A., Lamarque, J.-F., Lin, G., Liu, X., Lund, M. T., Luo, G., Ma, X., van Noije, T., Penner, J. E., Rasch, P. J., Ruiz, A., Seland, Ø., Skeie, R. B., Stier, P., Takemura, T., Tsigaridis, K., Wang, P., Wang, Z., Xu, L., Yu, H., Yu, F., Yoon, J.-H., Zhang, K., Zhang, H., and Zhou, C.: Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations, Atmos. Chem. Phys., 13, 1853–1877, https://doi.org/10.5194/acp-13-1853-2013, 2013.
Odum, J. R., Hoffmann, T., Bowman, F., Collins, D., Flagan, R. C., and
Seinfeld, J. H.: Gas/Particle partitioning and secondary organic aerosol
yields, Environ. Sci. Technol., 30, 2580–2585, 1996.
O'Neill, N. T., Dubovik, O., and Eck, T. F.: Modified Ångström
exponent for the characterization of submicrometer aerosols, Appl. Optics, 40,
2368, https://doi.org/10.1364/AO.40.002368, 2001.
OPTEC: https://www.optec.ru/, last access: 28 January 2022.
Poliukhov, A. A. and Blinov, D. V.: Aerosol Effects on Temperature Forecast
in the COSMO-Ru Model, Russ. Meteorol. Hydrol., 46, 19–27,
https://doi.org/10.3103/S1068373921010039, 2021.
Popovicheva, O. B., Evangeliou, N., Eleftheriadis, K., Kalogridis, A. C.,
Sitnikov, N., Eckhard, S., and Stohl, A.: Black Carbon Sources Constrained by
Observations in the Russian High Arctic. Environmental Science and
Technology, American Chemical Society (United States), 51,
3871–3879, 2017.
Popovicheva, O. B., Volpert, E., Sitnikov, N. M., Chichaeva, M. A., and
Padoan, S.: Black carbon in spring aerosols of Moscow urban background,
Geography, Environment, Sustainability, 13, 233–243,
https://doi.org/10.24057/2071-9388-2019-90, 2020.
Popovicheva, O., Chichaeva, M., Kovach, R., Zhdanova, E., and Kasimov, N.:
Seasonal, Weekly, and Diurnal Black Carbon in Moscow Megacity Background
under Impact of Urban and Regional Sources, Atmosphere, 2022, 563,
https://doi.org/10.3390/atmos13040563, 2022.
Rajesh, T. A. and Ramachandran, S.: Black carbon aerosol mass concentration,
absorption and single scattering albedo from single and dual spot
aethalometers: Radiative implications, J. Aerosol Sci.,
119, 77–90,
https://doi.org/10.1016/j.jaerosci.2018.02.001, 2018.
Ramanathan, V. and Carmichael, G.: Global and regional climate changes due
to black carbon, Nat. Geosci., 1, 221–227, https://doi.org/10.1038/ngeo156,
2008.
Ramachandran, S. and Rajesh, T. A.: Black carbon aerosol mass concentrations
over Ahmedabad, an urban location in western India: Comparison with urban
sites in Asia, Europe, Canada, and the United States, J. Geophys. Res., 112,
D06211, https://doi.org/10.1029/2006JD007488, 2007.
Reddy, M. S. and Venkataraman, C.: Inventory of aerosol and sulphur dioxide
emissions from India: I – Fossil fuel combustion, Atmos. Environ., 36,
677–697, https://doi.org/10.1016/S1352-2310(01)00463-0, 2002.
Riemer, N., Vogel, H., Vogel, B., and Fiedler, F.: Modeling aerosols on the
mesoscale-γ: Treatment of soot aerosol and its radiative effects,
J. Geophys. Res., 109, 4601, https://doi.org/10.1029/2003JD003448, 2003.
Rivin, G. S., Rozinkina, I. A., Astakhova, E. D., Blinov, D. V., Bundel'A,
Y., Kirsanov, A. A., and Churiulin, E. V.: COSMO-Ru high-resolution
short-range numerical weather prediction system: its development and
applications, Hydrometeorol. Res. Forecast., 374, 37–53,
2019.
Rolph, G., Stein, A., and Stunder, B.: Real-time Environmental Applications
and Display sYstem: READY, Environ. Modell. Softw., 95, 210–228,
https://doi.org/10.1016/j.envsoft.2017.06.025, 2017.
Schell, B., Ackermann, I. J., 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, 2001.
Segura, S., Estellés, V., Utrillas, M.,
and Martínez-Lozano, J.: Long term analysis of the columnar and surface
aerosol relationship at an urban European coastal site, Atmos.
Environ., 167, 309–322, https://doi.org/10.1016/j.atmosenv.2017.08.012, 2017.
Seinfeld, J. H. and Pandis, S. N. (Eds.): Atmospheric chemistry and
physics: from air pollution to climate change, 3rd Edn., A Wiley-
Interscience publication, Hoboken, New Jersey, USA, 2016.
Singh, S., Tiwari, S., Gond, D. P., Dumka, U. C., Bisht, D. S., Tiwari, S.,
Pandithurai, G., and Sinha, A.: Intra-seasonal variability of black carbon
aerosols over a coal field area at Dhanbad, India, Atmos. Res., 161–162,
25–35, https://doi.org/10.1016/j.atmosres.2015.03.015, 2015.
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D.,
and Ngan, F.: NOAA's HYSPLIT atmospheric transport and dispersion modeling
system, B. Am. Meteorol. Soc., 96, 2059–2077,
https://doi.org/10.1175/BAMS-D-14-00110.1, 2015.
Stockwell, W. R., Middleton, P., and Chang, J. S.: The second generation
regional acid deposition model chemical mechanism for regional air quality
modelling, J. Geophys. Res., 95, 16343–16367, 1990.
Su, W., Loeb, N. G., Schuster, G. L., Chin, M., and Rose, F. G.: Global
all-sky shortwave direct radiative forcing of anthropogenic aerosols from
combined satellite observations and GOCART simulations, J. Geophys. Res.-Atmos., 118, 655–669, https://doi.org/10.1029/2012JD018294, 2013.
Sun, J., Zhi, G., Hitzenberger, R., Chen, Y., Tian, C., Zhang, Y., Feng, Y., Cheng, M., Zhang, Y., Cai, J., Chen, F., Qiu, Y., Jiang, Z., Li, J., Zhang, G., and Mo, Y.: Emission factors and light absorption properties of brown carbon from household coal combustion in China, Atmos. Chem. Phys., 17, 4769–4780, https://doi.org/10.5194/acp-17-4769-2017, 2017.
Szkop, A., Pietruczuk, A., and Posyniak, M.: Classification of Aerosol over
Central Europe by Cluster Analysis of Aerosol Columnar Optical Properties
and Backward Trajectory Statistics, Acta Geophys., 64, 2650–2676, 2016.
Tang, T., Shindell, D., Zhang, Y., Voulgarakis, A., Lamarque, J.-F., Myhre, G., Faluvegi, G., Samset, B. H., Andrews, T., Olivié, D., Takemura, T., and Lee, X.: Distinct surface response to black carbon aerosols, Atmos. Chem. Phys., 21, 13797–13809, https://doi.org/10.5194/acp-21-13797-2021, 2021.
TNO: https://www.tno.nl/en/, last access: 15 September 2021.
Toll, V., Gleeson, E., Nielsen, K. P., Männik, A., Mašek, J., Rontu, L.,
and Post, P.: Impacts of the direct radiative effect of aerosols in numerical
weather prediction over Europe using the ALADIN-HIRLAM NWP system, Atmos.
Res., 172, 163–173, 2016.
Ukhov, A., Mostamandi, S., da Silva, A., Flemming, J., Alshehri, Y., Shevchenko, I., and Stenchikov, G.: Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations, Atmos. Chem. Phys., 20, 9281–9310, https://doi.org/10.5194/acp-20-9281-2020, 2020.
Vil'fand, R. M., Kirsanov, A. A., Revokatova, A. P., Rivin, G. S., and
Surkova, G. V.: Forecasting the transport and transformation of atmospheric
pollutants with the COSMO-ART model, Russ. Meteorol. Hydrol., 42, 292–298,
https://doi.org/10.3103/S106837391705003X, 2017.
Vogel, B., Hoose, C., Vogel, H., and Kottmeier, C.: A model of dust
transport applied to the Dead Sea area, Meteorol. Z., 14, 611–624, 2006.
Vogel, B., Vogel, H., Bäumer, D., Bangert, M., Lundgren, K., Rinke, R., and Stanelle, T.: The comprehensive model system COSMO-ART – Radiative impact of aerosol on the state of the atmosphere on the regional scale, Atmos. Chem. Phys., 9, 8661–8680, https://doi.org/10.5194/acp-9-8661-2009, 2009.
Vogel, H., Bäumer, D., Bangert, M., Lundgren, K., Rinke, R., and
Stanelle, T.: COSMO-ART: Aerosols and Reactive Trace Gases Within the COSMO
Model, in: Integrated Systems of Meso-Meteorological and Chemical Transport
Models, edited by: Baklanov, A., Alexander, M., and Sokhi, R., Springer,
Berlin, Heidelberg, Germany, 75–80,
https://doi.org/10.1007/978-3-642-13980-2_6, 2010.
Wang, D., Szczepanik, D., and Stachlewska, I. S.: Interrelations between surface, boundary layer, and columnar aerosol properties derived in summer and early autumn over a continental urban site in Warsaw, Poland, Atmos. Chem. Phys., 19, 13097–13128, https://doi.org/10.5194/acp-19-13097-2019, 2019.
Wang, X., Dickinson, R. E., Su, L., Zhou, C., and Wang, K.: PM2.5 Pollution
in China and how it has been exacerbated by terrain and meteorological
conditions, B. Am. Meteorol. Soc., 99, 105–119,
https://doi.org/10.1175/BAMS-D-16-0301.1, 2018.
Wang, Y., Le, T., Chen, G., Yung, Y. L., Su, H., Seinfeld, J. H., and Jiang,
J. H.: Reduced European aerosol emissions suppress winter extremes over
northern Eurasia, Nat. Clim. Chang., 10, 225–230,
https://doi.org/10.1038/s41558-020-0693-4, 2020.
Weingartner, E., Keller, C., Stahel, W. A., Burtscher, H., and
Baltensperger, U.: Aerosol emission in a road tunnel, Atmos. Environ., 31,
451–462, https://doi.org/10.1016/S1352-2310(96)00193-8, 1997.
Whitby, E. R., McMurray, P. H., Shankar, U., and Binkowski, F. S.: Modal
Aerosol Dynamics Modeling, Technical Report 600/3- 91/020, (NTIS
PB91-161729/AS Natl. Tech. Inf. Serv. Springfield, Va.), Atmos. Res. and
Exposure Assess. Lab. U.S. Environ. Prot. Agency, Research Triangle Park,
N.C., 1991.
WMO-COST: Joint Report of COST Action 728 and GURME – Overview of Existing
Integrated (off-line and on-line) Mesoscale Meteorological and Chemical
Transport Modelling Systems in Europe (WMO TD No. 1427), GAW report 177,
https://library.wmo.int/doc_num.php?explnum_id=9379 (last access: 16 September 2021),
2008.
World Data Centre for Aerosols: https://www.gaw-wdca.org, last
access: 28 January 2022.
Wu, D., Wu, C., Liao, B., Chen, H., Wu, M., Li, F., Tan, H., Deng, T., Li, H., Jiang, D., and Yu, J. Z.: Black carbon over the South China Sea and in various continental locations in South China, Atmos. Chem. Phys., 13, 12257–12270, https://doi.org/10.5194/acp-13-12257-2013, 2013.
Wu, T. and Boor, B. E.: Urban aerosol size distributions: a global perspective, Atmos. Chem. Phys., 21, 8883–8914, https://doi.org/10.5194/acp-21-8883-2021, 2021.
Zawadzka, O., Markowicz, K. M., Pietruczuk, A., Zielinski, T., and
Jaroslawski, J.: Impact of urban pollution emitted in Warsaw on aerosol
properties, Atmos. Environ., 69, 15–28,
https://doi.org/10.1016/j.atmosenv.2012.11.065, 2013.
Zhdanova, E. Y., Chubarova, N. Y., and Lyapustin, A. I.: Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product, Atmos. Meas. Tech., 13, 877–891, https://doi.org/10.5194/amt-13-877-2020, 2020.
Zhuang, B., Wang, T., Liu, J., Che, H., Han, Y., Fu, Y., Li, S., Xie, M., Li, M., Chen, P., Chen, H., Yang, X.-Q., and Sun, J.: The optical properties, physical properties and direct radiative forcing of urban columnar aerosols in the Yangtze River Delta, China, Atmos. Chem. Phys., 18, 1419–1436, https://doi.org/10.5194/acp-18-1419-2018, 2018.
Short summary
Effects of urban aerosol pollution in Moscow were analyzed using the COSMO-ART chemical transport model and intensive measurement campaigns. We show that urban aerosol comprises about 15–20% of columnar aerosol content, consisting mainly of fine aerosol mode. The black carbon (BC) fraction is about 5 %, depending on particle dispersion intensity (IPD). The BC fraction low value explains weak absorbing properties of the Moscow atmosphere. IPD also defines the daily cycle of urban aerosol species.
Effects of urban aerosol pollution in Moscow were analyzed using the COSMO-ART chemical...
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