Comparison of СO2 Content in the Atmosphere of St. Petersburg According to Numerical Modelling and Observations
- Authors: Nerobelov G.M.1,2, Timofeyev Y.M.1, Smyshlyaev S.P.3, Foka S.C.1, Imhasin H.H.1
-
Affiliations:
- Saint-Petersburg State University
- SPC RAS – Scientific Research Centre for Ecological Safety, Russian Academy of Sciences
- Russian State Hydrometeorological University
- Issue: Vol 59, No 3 (2023)
- Pages: 322-335
- Section: Articles
- URL: https://journals.rcsi.science/0002-3515/article/view/136920
- DOI: https://doi.org/10.31857/S0002351523020050
- EDN: https://elibrary.ru/HPGBSF
- ID: 136920
Cite item
Abstract
Due to the increase in CO2 content in the Earth’s atmosphere, which is highly dependent on anthropogenic emissions of CO2, quality of emission estimation should be improved. Advanced experiment-based methods of the CO2 anthropogenic emission estimation are built on solution of an inverse problem using highly-accurate measurements of CO2 content and numerical models of transport and chemistry in the atmosphere. The accuracy of such models greatly determines errors of the emission estimations. In a current study temporal variations of column-average CO2 content in an atmospheric layer from surface to the height of ~70–75 km (XCO2) in the Russian megapolis of St. Petersburg during Jan 2019–Mar 2020 simulated by WRF-Chem model and measured by IR Fourier-transform spectrometer Bruker EM27/SUN are compared. The research has demonstrated that the WRF-Chem model simulates well the observed temporal variation of XCO2 in the area of St. Petersburg (correlation coefficient of ~0.95). However, using CarbonTracker v2022-1 data as chemical boundary conditions, the model overestimates XCO2 relative to the observations significantly during almost the whole period of investigation – systematic difference and standard deviation of the difference are 4.2 and 1.9 ppm (1 and 0.5%). A correction of the chemical boundary conditions which is based on analysis of a relation between near-surface wind direction and XCO2 variation notably decreases the systematic difference between the modelled and observed data (almost by a factor of 2). The XCO2 variation by the observations and modelling with uncorrected chemical boundary conditions are in a better agreement during vegetation season. Probably this is related to the compensation of the systematic difference by inaccuracies in estimated biogenic contribution. Hence, the reason of the still existing mean difference between the modelled and observed data can be inaccuracies in setting chemical boundary conditions for upper troposphere and in estimating how biosphere influences CO2 content.
About the authors
G. M. Nerobelov
Saint-Petersburg State University; SPC RAS – Scientific Research Centre for Ecological Safety, Russian Academy of Sciences
Author for correspondence.
Email: akulishe95@mail.ru
Russia, 199034, Saint-Petersburg, University Emb., 7/9; Russia, 187110, Saint-Petersburg, Korpusnaya st., 18
Yu. M. Timofeyev
Saint-Petersburg State University
Email: akulishe95@mail.ru
Russia, 199034, Saint-Petersburg, University Emb., 7/9
S. P. Smyshlyaev
Russian State Hydrometeorological University
Email: akulishe95@mail.ru
Russia, 195196, Saint-Petersburg, Malookhtinskiy Prospekt, 98
S. Ch. Foka
Saint-Petersburg State University
Email: akulishe95@mail.ru
Russia, 199034, Saint-Petersburg, University Emb., 7/9
H. H. Imhasin
Saint-Petersburg State University
Email: akulishe95@mail.ru
Russia, 199034, Saint-Petersburg, University Emb., 7/9
References
- Alberti Carlos, Qiansi Tu, Frank Hase, Maria V. Makarova, Konstantin Gribanov, Stefani C. Foka, Vyacheslav Zakharov, Thomas Blumenstock, Michael Buchwitz, Christopher Diekmann, Benjamin Ertl, Matthias M. Frey, Hamud Kh. Imhasin, Dmitry V. Ionov, Farahnaz Khosrawi, Sergey I. Osipov, Maximilian Reuter, Matthias Schneider, Thorsten Warneke. Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations // Atmos. Meas. Tech. 2022. V. 15. P. 2199–2229. https://doi.org/10.5194/amt-15-2199-2022
- Barthlott S., Schneider M., Hase F., Wiegele A., Christner E., González Y., Blumenstock T., Dohe S., García O.E., Sepúlveda E., Strong K., Mendonca J., Weaver D., Palm M., Deutscher N.M., Warneke T., Notholt J., Lejeune B., Mahieu E., Jones N., Griffith D.W.T., Velazco V.A., Smale D., Robinson J., Kivi R., Heikkinen P., Raffalski U. Using XCO2 retrievals for assessing the long-term consistency of NDACC/FTIR data sets // Atmos. Meas. Tech. 2015. V. 8. P. 1555–1573. https://doi.org/10.5194/amt-8-1555-2015
- Beck V., Koch T., Kretschmer R., Marshall J., Ahmadov R., Gerbig C., Pillai D., Heimann M. The WRF Greenhouse Gas Model (WRF-GHG) // Technical Report No. 25. 2011. Max Planck Institute for Biogeochemistry, Jena, Germany.
- Bovensmann H., Buchwitz M., Burrows J.P., Reuter M., Krings T., Gerilowski K., Schneising O., Heymann J., Tretner A., Erzinger J. A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications // Atmos. Meas. Tech. 2010. V. 3. P. 781–811.
- Buchwitz M., de Beek R., Burrows J.P., Bovensmann H., Warneke T., Nothol J., Meirink J.F., Goede A.P.H., Bergamaschi P., Korner S., Heimann M., Schulz A. Atmospheric methane and carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transport models // Atmos. Chem. Phys. 2005. V. 5. P. 941–962. www.atmos-chem-phys.org/acp/5/941.
- Callewaert S., Brioude J., Langerock B., Duflot V., Fonteyn D., Müller J.-F., Metzger J.-M., Hermans C., Kumps N., Mahieu E., Mazière M. Analysis of CO2, CH4 and CO surface and column concentrations observed at Reunion Island by assessing WRF-Chem simulations // Atmos. Chem. Phys. 2022. V. 22. P. 7763–7792. https://doi.org/10.5194/acp-22-7763-2022
- Chevallier F. et al. CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements // J. Geophys. Res. 2010. V. 115. D21307. https://doi.org/10.1029/2010JD013887
- Frey M., Hase F., Blumenstock T., Groß J., Kiel M., Mengistu Tsidu G., Schäfer K., Sha M.K., Orphal J. Calibration and instrumental line shape characterization of a set of portable FTIR spectrometers for detecting greenhouse gas emissions. Atmos. Meas. Tech. 2015. V. 8. P. 3047–3057. https://doi.org/10.5194/amt-8-3047-2015
- Frey M., Sha M.K., Hase F., Kiel M., Blumenstock T., Harig R., Surawicz G., Deutscher N.M., Shiomi K., Franklin J.E., Bösch H., Chen J., Grutter M., Ohyama H., Sun Y., Butz A., Mengistu Tsidu G., Ene D., Wunch D., Cao Z., Garcia O., Ramonet M., Vogel F., Orphal J. Building the COllaborative Carbon Column Observing Network (COCCON): long-term stability and ensemble performance of the EM27/SUN Fourier transform spectrometer // Atmos. Meas. Tech. 2019. V. 12. P. 1513–1530. https://doi.org/10.5194/amt-12-1513-2019
- Gisi M., Hase F., Dohe S., Blumenstock T., Simon A., Keens A. XCO2-measurements with a tabletop FTS using solar absorption spectroscopy // Atmos. Meas. Tech. 2012. V. 5. P. 2969–2980. https://doi.org/10.5194/amt-5-2969-2012
- Grell G.A., Peckham S.E., Schmitz R., McKeen S.A., Frost G., Skamarock W.C., Eder B. Fully coupled 'online' chemistry in the WRF model // Atmos. Environ. 2005. V. 39. P. 6957–6976.
- Hase F., Frey M., Blumenstock T., Groß J., Kiel M., Kohlhepp R., Mengistu Tsidu G., Schäfer K., Sha M.K., Orphal J. Application of portable FTIR spectrometers for detecting greenhouse gas emissions of the major city Berlin // Atmos. Meas. Tech. 2015. V. 8. P. 3059–3068. https://doi.org/10.5194/amt-8-3059-2015
- Hersbach H., Bell B., Berrisford P. et al. The ERA5 global reanalysis // Q J R Meteorol Soc. 2020. V. 146. P. 1999–2049. https://doi.org/10.1002/qj.3803
- Hersbach H., Bell B., Berrisford P., Biavati G., Horányi A., Muñoz Sabater J., Nicolas J., Peubey C., Radu R., Rozum I., Schepers D., Simmons A., Soci C., Dee D., Thépaut J-N. ERA5 hourly data on single levels from 1959 to present // Copernicus Climate Change Service (C3S) Climate Data Store (CDS). 2018. (Accessed on 14-APR-2021). https://doi.org/10.24381/cds.adbb2d47
- Houweling S., Aben I., Breon F.-M., Chevallier F., Deutscher N., Engelen R., Gerbig C., Griffith D., Hungershoefer K., Macatangay R., Marshall J., Notholt J., Peters W., Serrar S. The importance of transport model uncertainties for the estimation of CO2 sources and sinks using satellite measurements // Atmos. Chem. Phys. 2010. V. 10. P. 9981–9992. www.atmos-chem-phys.net/10/9981/2010/https://doi.org/10.5194/acp-10-9981-2010
- Ionov D.V., Makarova M.V., Hase F., Foka S.C., Kostsov V.S., Alberti C., Blumenstock T., Warneke T., Virolainen Ya.A. The CO2 integral emission by the megacity of St Petersburg as quantified from ground-based FTIR measurements combined with dispersion modelling // Atmos. Chem. Physics. 2021. V. 21. № 14. P. 10939–10963. https://doi.org/10.5194/acp-21-10939-2021
- Jacobson A.R., Schuldt K.N., Miller J.B., Tans P., Andrews A., Mund J., Aalto T., Bakwin P., Bergamaschi P., Biraud S.C., Chen H., Colomb A., Conil S., Cristofanelli P., Davis K., Delmotte M., DiGangi J.P., Dlugokencky E., Emmenegger L., Fischer M.L., Hatakka J., Heliasz M., Hermanssen O., Holst J., Jaffe D., Karion A., Keronen P., Kominkova K., Kubistin D., Laurent O., Laurila T., Lee J., Lehner I., Leuenberger M., Lindauer M., Löfvenius M.O., Lopez M., Mammarella I., Manca G., Marek M.V., Marklund P., Martin M.Y., McKain K., Miller C.E., Mölder M., Myhre C.L., Pichon J.M., Plass-Dölmer C., Ramonet M., Scheeren B., Schumacher M., Sloop C.D., Steinbacher M., Sweeney C., Thoning K., Tørseth K., Turnbull J., Viner B., Vitkova G., Wekker S.D., Weyrauch D., Worthy D. CarbonTracker Near-Real Time, CT-NRT.v2020-1 // NOAA Earth System Research Laboratory, Global Monitoring Division. 2020. https://doi.org/10.25925/RCHH-MS75
- Lauvaux T., Miles N.L., Richardson S.J., Deng A., Stauffer D.R., Davis K.J., Jacobson G., Rella C., Calonder G., DeCola P.L. Urban Emissions of CO2 from Davos, Switzerland: The First Real-Time Monitoring System Using an Atmospheric Inversion Technique // J. Applied Meteorology and Climatology. 2013. V. 52(12). P. 2654–2668. https://doi.org/10.1175/JAMC-D-13-038.1
- Li H.D., Claremar B., Wu L.C., Hallgren C., Körnich H., Ivanell S., Sahlée E. A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea // Geosci. Front. 2021. V. 12. P. 101229. https://doi.org/10.1016/j.gsf.2021.101229
- Makarova M.V., Alberti C., Ionov D.V., Hase F., Foka S.C., Blumenstock T., Warneke T., Virolainen Ya.A., Kostsov V.S., Frey M., Poberovskii A.V., Timofeyev Yu.M., Paramonova N.N., Volkova K.A., Zaitsev N.A., Biryukov E.Y., Osipov S.I., Makarov B.K., Polyakov A.V., Ivakhov V.M., Imhasin H.Kh., Mikhailov E.F. Emission Monitoring Mobile Experiment (EMME): an overview and first results of the St. Petersburg megacity campaign-2019 // Atmos. Meas. Tech. 2021. V. 14. P. 1047–1073. https://doi.org/10.5194/amt-14-1047-2021
- Maksyutov S., Oda T., Saito M., Janardanan R., Belikov D., Kaiser J.W., Zhuravlev R., Ganshin A., Valsala V.K., Andrews A., Chmura L., Dlugokencky E., Haszpra L., Langenfelds R.L., Machida T., Nakazawa T., Ramonet M., Sweeney C., Worthy D. Technical note: A high-resolution inverse modelling technique for estimating surface CO2 fluxes based on the NIES-TM–FLEXPART coupled transport model and its adjoint // Atmos. Chem. Phys. 2021. V. 21. P. 1245–1266. https://doi.org/10.5194/acp-21-1245-2021
- Mahadevan P., Wofsy S.C., Matross D.M., Xiao X., Dunn A.L., Lin J.C., Gerbig C., Munger J.W., Chow V.Y., Gottlieb E.W. A satellite-based biosphere parameterization for net ecosystem CO2exchange: Vegetation Photosynthesis and Respiration Model (VPRM) // Global Biogeochem. Cycles. 2008. V. 22. GB2005. https://doi.org/10.1029/2006GB002735
- Martin, Cory R., Ning Zeng, Anna Karion, Kimberly Mueller, Subhomoy Ghosh, Israel Lopez-Coto, Kevin Robert Gurney, Oda T., Kuldeep R. Prasad, Yuqiong Liu, Russell R. Dickerson, James R. Whetstone. Investigating sources of variability and error in simulations of carbon dioxide in an urban region // Atmospheric Environment. 2019. V. 199. P. 55–69.
- 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., Zhou B. (eds.). IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change // Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 2021. 2391 p. https://doi.org/10.1017/9781009157896
- Miller S.T.K., Keim B.D., Talbot R.W., Mao H. Sea breeze: Structure, forecasting, and impacts // Rev. Geophys. 2003. V. 41. P. 1011. https://doi.org/10.1029/2003RG000124
- Mues A., Lauer A., Lupascu A., Rupakheti M., Kuik F., Lawrence M.G. WRF and WRF-Chem v3.5.1 simulations of meteorology and black carbon concentrations in the Kathmandu Valley // Geosci. Model Dev. 2018. V. 11. P. 2067–2091. https://doi.org/10.5194/gmd-11-2067-2018
- Nerobelov G.M., Timofeyev Y.M. Estimates of CO2 Emissions and Uptake by the Water Surface near St. Petersburg Megalopolis // Atmos Ocean Opt. 2021. V. 34. P. 422–427. https://doi.org/10.1134/S1024856021050158
- Nerobelov G., Timofeyev Y., Smyshlyaev S., Foka S., Mammarella I., Virolainen Y. Validation of WRF-Chem Model and CAMS Performance in Estimating Near-Surface Atmospheric CO2 Mixing Ratio in the Area of Saint Petersburg (Russia) // Atmosphere. 2021. V. 12. № 3. P. 387. https://doi.org/10.3390/atmos12030387
- Oda T., Bun R., Kinakh V., Topylko P., Halushchak M., Marland G., Lauvaux T., Jonas M., Maksyutov S., Nahorski Z., Lesiv M., Danylo O., Horabik-Pyzel J. Errors and uncertainties in a gridded carbon dioxide emissions inventory // Mitig Adapt Strateg Glob Change. 2019. V. 24. P. 1007–1050. https://doi.org/10.1007/s11027-019-09877-2
- Peylin P., Law R.M., Gurney K.R., Chevallier F., Jacobson A.R., Maki T., Niwa Y., Patra P.K., Peters W., Rayner P.J., Rödenbeck C., van der Laan-Luijkx I.T., Zhang X. Global atmospheric carbon budget: results from an ensemble of atmospheric CO2 inversions // Biogeosciences. 2013. V. 10. P. 6699–6720. https://doi.org/10.5194/bg-10-6699-2013
- 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., Huang X.-Yu. A Description of the Advanced Research WRF Model Version 4.1 (No. NCAR/TN-556+STR) // https://doi.org/10.5065/1dfh-6p97
- Timofeyev Y.M., Nerobelov G.M. Poberovskii A.V. Experimental Estimates of Integral Anthropogenic CO2 Emissions in the City of St. Petersburg // Izv. Atmos. Ocean. Phys. 2022. V. 58. P. 237245. https://doi.org/10.1134/S0001433822030100
- Timofeyev Y.M., Nerobelov G.M., Virolainen Y.A., Poberovskii A.V., Foka S.C. Estimates of CO2 Anthropogenic Emission from the Megacity St. Petersburg // Dokl. Earth Sc. 2020. V. 494. P. 753756. https://doi.org/10.1134/S1028334X20090184
- Timofeyev Yu., Virolainen Ya., Makarova M., Poberovsky A., Polyakov A., Ionov D., Osipov S., Imhasin H. Ground-based spectroscopic measurements of atmospheric gas composition near Saint Petersburg (Russia) // J. Mol. Spectr. 2016. V. 323. P. 2–14. https://doi.org/10.1016/j.jms.2015.12.007
- Tomohiro O., Maksyutov S. ODIAC Fossil Fuel CO2 Emissions Dataset (Version name: ODIAC2020b) // Center for Global Environmental Research, National Institute for Environmental Studies. 2015. https://doi.org/10.17595/20170411.001
- Vogel F.R., Frey M., Staufer J., Hase F., Broquet G., Xueref-Remy I., Chevallier F., Ciais P., Sha M.K., Chelin P., Jeseck P., Janssen C., Té Y., Groß J., Blumenstock T., Tu Q., Orphal J. XCO2 in an emission hot-spot region: the COCCON Paris campaign 2015 // Atmos. Chem. Phys. 2019. V. 19. P. 3271–3285. https://doi.org/10.5194/acp-19-3271-2019
- Zhao X., Marshall J., Hachinger S., Gerbig C., Frey M., Hase F., Chen J. Analysis of total column CO2 and CH4 measurements in Berlin with WRF-GHG // Atmos. Chem. Phys. 2019. V. 19. P. 11279–11302. https://doi.org/10.5194/acp-19-11279-2019
- Zheng T., Nassar R., Baxter M. Estimating power plant CO2 emission using OCO-2 XCO2 and high resolution WRF-Chem simulations // Environ. Res. Lett. 2019. V. 14. P. 085001.
- Комитет по экономической политике и стратегическому планированию Санкт-Петербурга https:// cedipt.gov.spb.ru/media/uploads/userfiles/2022/11/11/ СПРАВКА_ЧП_январь-сентябрь_2022.pdf, 2022.
- Никитенко А.А., Неробелов Г.М., Тимофеев Ю.М., Поберовский А.В. Анализ наземных спектроскопических измерений содержаний СО2 в Петергофе // Современные проблемы дистанционного зондирования Земли из космоса. 2021. Т. 18. № 6. С. 265–272.
- Тимофеев Ю.М., Березин И.А., Виролайнен Я.А., Макарова М.В., Поляков А.В., Поберовский А.В., Филиппов Н.Н., Фока С.Ч. Пространственно-временные вариации содержания CO2 по данным спутниковых и наземных измерений вблизи Санкт-Петербурга // Изв. РАН, ФАО. 2019. Т. 55. № 1. С. 65–72.