• Arrouays, D. , and Coauthors, 2018: Soil sampling and preparation for monitoring soil carbon. Int. Agrophys., 32, 633643, https://doi.org/10.1515/intag-2017-0047.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baldocchi, D. , 2014: Measuring fluxes of trace gases and energy between ecosystems and the atmosphere – The state and future of the eddy covariance method. Global Change Biol., 20, 36003609, https://doi.org/10.1111/gcb.12649.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baldocchi, D. , and Coauthors, 2001: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bull. Amer. Meteor. Soc., 82, 24152434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Basu, S. , and Coauthors, 2020: Estimating US fossil fuel CO2 emissions from measurements of 14C in atmospheric CO2. Proc. Natl. Acad. Sci. USA, 117, 13 30013 307, https://doi.org/10.1073/pnas.1919032117.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Breon, F. M. , and Coauthors, 2015: An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements. Atmos. Chem. Phys., 15, 17071724, https://doi.org/10.5194/acp-15-1707-2015.

    • Search Google Scholar
    • Export Citation
  • Calfapietra, C. , Ü. Niinemets, and J. Peñuelas, 2015: Urban plant physiology: Adaptation-mitigation strategies under permanent stress. Trends Plant Sci., 20, 7275, https://doi.org/10.1016/j.tplants.2014.11.001.

    • Search Google Scholar
    • Export Citation
  • Copernicus, 2015: Towards a European operational observing system to monitor fossil CO2 emissions. European Commission, 65 pp., https://op.europa.eu/s/uz3d.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Copernicus, 2019: An operational anthropogenic CO2 emissions monitoring & verification support capacity: Needs and high level requirements for in situ measurements. European Commission, 72 pp., https://doi.org/10.2760/182790.

    • Search Google Scholar
    • Export Citation
  • Dickson, A. G. , C. L. Sabine, and J. R. Christian, Eds., 2007: Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publ. 3, IOCCP Rep. 8, 191 pp., https://cdiac.ess-dive.lbl.gov/ftp/oceans/Handbook_2007/Guide_all_in_one.pdf.

  • El Yazidi, A. , and Coauthors, 2018: Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4. Atmos. Meas. Tech., 11, 15991614, https://doi.org/10.5194/amt-11-1599-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ESFRI, 2006: European roadmap for research infrastructures: Report 2006. European Strategy Forum on Research Infrastructures, 84 pp., www.esfri.eu/sites/default/files/esfri_roadmap_2006_en.pdf.

    • Crossref
    • Export Citation
  • ESFRI, 2016: Strategy report on research infrastructures. European Strategy Forum on Research Infrastructures, 208 pp., www.esfri.eu/sites/default/files/20160309_ROADMAP_browsable.pdf.

    • Search Google Scholar
    • Export Citation
  • Franz, D. , and Coauthors, 2018: Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: A review. Int. Agrophys., 32, 439455, https://doi.org/10.1515/intag-2017-0039.

    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P. , and Coauthors, 2020: Global carbon budget 2020. Earth Syst. Sci. Data, 12, 32693340, https://doi.org/10.5194/essd-12-3269-2020.

    • Search Google Scholar
    • Export Citation
  • GCOS, 1994: Report of the GCOS/GTOS Terrestrial Observation Panel. WMO/TD-642; GCOS-08, 53 pp., https://library.wmo.int/doc_num.php?explnum_id=3804.

    • Crossref
    • Export Citation
  • GCOS, 2016: The Global Observing System for Climate: Implementation Needs. GCOS-200, GOOS-214, 315 pp., https://library.wmo.int/doc_num.php?explnum_id=3417.

    • Search Google Scholar
    • Export Citation
  • Gielen, B. , M. Op de Beeck, D. Loustau, R. Ceulemans, A. Jordan, and D. Papale, 2017: Integrated Carbon Observation System (ICOS): An infrastructure to monitor the European greenhouse gas balance. Terrestrial Ecosystem Research Infrastructures: Challenges and Opportunities, 1st ed. A. Chabbi and H. W. Loescher, Eds., CRC Press, 505–520.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gielen, B. , and Coauthors, 2018: Ancillary data measurements at ICOS sites. Int. Agrophys., 32, 645664, https://doi.org/10.1515/intag-2017-0048.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graf, A. , and Coauthors, 2020: Altered energy partitioning across terrestrial ecosystems in the European drought year 2018. Philos. Trans. Roy. Soc. London, 375B, 20190524, https://doi.org/10.1098/rstb.2019.0524.

    • Search Google Scholar
    • Export Citation
  • Hazan, L. , J. Tarniewicz, M. Ramonet, O. Laurent, and A. Abbaris, 2016: Automatic processing of atmospheric CO2 and CH4 mole fractions at the ICOS Atmosphere Thematic Centre. Atmos. Meas. Tech., 9, 47194736, https://doi.org/10.5194/amt-9-4719-2016.

    • Search Google Scholar
    • Export Citation
  • Hufkens, K. , and Coauthors, 2018: Assimilating phenology datasets automatically across ICOS ecosystem stations. Int. Agrophys., 32, 677687, https://doi.org/10.1515/intag-2017-0050.

    • Search Google Scholar
    • Export Citation
  • ICOS, 2015: ICOS RI data policy. ICOS ERIC, 11 pp., www.icos-cp.eu/sites/default/files/cmis/ICOS%20RI%20Data%20Policy.pdf.

  • ICOS, 2017a: ICOS Atmospheric Station specifications, version 1.3. ICOS ATC, 55 pp., https://doi.org/10.18160/SDW6-BX90.

  • ICOS, 2017b: ICOS Marine Station Labelling Step 2. ICOS OTC, 23 pp., https://otc.icos-cp.eu/sites/default/files/2018-05/ICOS%20Marine%20Station%20Labelling%20Step%202%20v4_crb.docx_.pdf.

    • Search Google Scholar
    • Export Citation
  • ICOS, 2019: ICOS Strategy. ICOS ERIC, 40 pp., www.icos-cp.eu/sites/default/files/cmis/ICOS%20Strategy.pdf.

  • ICOS, 2020a: ICOS Handbook 2020. ICOS ERIC, 152 pp., www.icos-cp.eu/sites/default/files/2020-12/ICOS%20Handbook%202020.pdf.

  • ICOS, 2020b: ICOS Ocean Station Labelling Step 2. ICOS OTC, 20 pp., https://doi.org/10.18160/8SDC-K4FR.

  • ICOS, 2020c: Jupyter Notebook for ICOS Flask Sampling Strategy (Version 1.0). ICOS ERIC, https://doi.org/10.18160/FSS2-SH26.

  • ICOS, 2021: ICOS Five-Year Evaluation 2020. ICOS ERIC, 127 pp., www.icos-cp.eu/sites/default/files/2021-05/ICOS%20Evaluation%202020%20Report%20_online%20low.pdf.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 1992: Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment. J. T. Houghton, B. A. Callander, and S. K. Varney, Eds., Cambridge University Press, 200 pp.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2019: Global Warming of 1.5°C. V. Masson-Delmotte et al., Eds., IPCC, 630 pp.

  • Janssens, I. , and Coauthors, 2003: Europe’s terrestrial biosphere anthropogenic CO2 emissions. Science, 300, 15381542, https://doi.org/10.1126/science.1083592.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joosten, H. , and D. Clark, 2002: Wise Use of Mires and Peatlands: Background and Principles Including a Framework for Decision-making. International Mire Conservation Group and International Peat Society, 304 pp.

    • Search Google Scholar
    • Export Citation
  • Jung, M. , and Coauthors, 2020: Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach. Biogeosciences, 17, 13431365, https://doi.org/10.5194/bg-17-1343-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Karion, A. , C. Sweeney, P. Tans, and T. Newberger, 2010: AirCore: An innovative atmospheric sampling system. J. Atmos. Oceanic Technol., 27, 18391853, https://doi.org/10.1175/2010JTECHA1448.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeling, C. D. , 1978: The influence of Mauna Loa Observatory on the development of atmospheric CO2 research. Mauna Loa Observatory. A 20th Anniversary Report, J. Miller, Ed., U.S. Department of Commerce, 3654.

    • Search Google Scholar
    • Export Citation
  • Lauvaux, T. , and Coauthors, 2020: Policy-relevant assessment of urban CO2 emissions. Environ. Sci. Technol., 54, 10 23710 245, https://doi.org/10.1021/acs.est.0c00343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levin, I. , B. Kromer, M. Schmidt, and H. Sartorius, 2003: A novel approach for independent budgeting of fossil fuel CO2 over Europe by 14CO2 observations. Geophys. Res. Lett., 30, 2194, https://doi.org/10.1029/2003GL018477.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levin, I. , S. Hammer, E. Eichelmann, and F. R. Vogel, 2011: Verification of greenhouse gas emission reductions: The prospect of atmospheric monitoring in polluted areas. Philos. Trans. Roy. Soc. London, A369, 19061924, https://doi.org/10.1098/rsta.2010.0249.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levin, I. , and Coauthors, 2020: A dedicated flask sampling strategy developed for ICOS stations based on CO2 and CO measurements and STILT footprint modelling. Atmos. Chem. Phys., 20, 11 16111 180, https://doi.org/10.5194/acp-20-11161-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • López-Ballesteros, A. , and Coauthors, 2018: Towards a feasible and representative pan-African research infrastructure network for GHG observations. Environ. Res. Lett., 13, https://doi.org/10.1088/1748-9326/aad66c.

    • Crossref
    • Export Citation
  • Loustau, D. , and Coauthors, 2018: Sampling and collecting foliage elements for the determination of the foliar nutrients in ICOS ecosystem stations. Int. Agrophys., 32, 665676, https://doi.org/10.1515/intag-2017-0038.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luyssaert, S. , and Coauthors, 2010: The European carbon balance. Part 3: Forests. Global Change Biol., 16, 14291450, https://doi.org/10.1111/j.1365-2486.2009.02056.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, X. , W. Liu, R. J. Allen, G. Huang, and X. Li, 2020: Dependence of regional ocean heat uptake on anthropogenic warming scenarios. Sci. Adv., 6, eabc0303, https://doi.org/10.1126/sciadv.abc0303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nemitz, E. , and Coauthors, 2018: Standardisation of eddy-covariance flux measurements of methane and nitrous oxide. Int. Agrophys., 32, 517549, https://doi.org/10.1515/intag-2017-0042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nordbo, A. , L. Järvi, S. Haapanala, C. R. Wood, and T. Vesala, 2012: Fraction of natural area as main predictor of net CO2 emissions from cities. Geophys. Res. Lett., 39, L20802, https://doi.org/10.1029/2012GL053087.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Op de Beeck, M. , and Coauthors, 2018: Soil-meteorological measurements at ICOS monitoring stations in terrestrial ecosystems. Int. Agrophys., 32, 619631, https://doi.org/10.1515/intag-2017-0041.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Papale, D. , 2020: Ideas and perspectives: Enhancing the impact of the FLUXNET network of eddy covariance sites. Biogeosciences, 17, 55875598, https://doi.org/10.5194/bg-17-5587-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Papale, D. , and R. Valentini, 2003: A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization. Global Change Biol., 9, 525535, https://doi.org/10.1046/j.1365-2486.2003.00609.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pavelka, M. , and Coauthors, 2018: Standardisation of chamber technique for CO2, N2O and CH4 fluxes measurements from terrestrial ecosystems. Int. Agrophys., 32, 569587, https://doi.org/10.1515/intag-2017-0045.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, W. , and Coauthors, 2010: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations. Global Change Biol., 16, 13171337, https://doi.org/10.1111/j.1365-2486.2009.02078.x.

    • Search Google Scholar
    • Export Citation
  • Petrescu, A. M. R. , and Coauthors, 2021: The consolidated European synthesis of CH4 and N2O emissions for European Union and United Kingdom: 1990–2017. Earth Syst. Sci. Data, 13, 23072362, https://doi.org/10.5194/essd-13-2307-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pfeil, B. , and Coauthors, 2013: A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT). Earth Syst. Sci. Data, 5, 125143, https://doi.org/10.5194/essd-5-125-2013.

    • Search Google Scholar
    • Export Citation
  • Rebmann, C. , and Coauthors, 2018: ICOS eddy covariance flux-station site setup: A review. Int. Agrophys., 32, 471494, https://doi.org/10.1515/intag-2017-0044.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rhein, M. , and Coauthors, 2013: Observations: Ocean. Climate Change 2013: The Physical Science Basis. T. F. Stocker et al., Eds., Cambridge University Press, 255315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rinne, J. , and Coauthors, 2020: Effect of the 2018 European drought on methane and carbon dioxide exchange of northern mire ecosystems. Philos. Trans. Roy. Soc. London, B375, 20190517, https://doi.org/10.1098/rstb.2019.0517.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rogelj, J. , and Coauthors, 2019: Mitigation pathways compatible with 1.5°C in the context of sustainable development. Global Warming of 1.5°C, V. Masson-Delmotte et al., Eds., IPCC, 93174.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, M. , and Coauthors, 2018: Importance of reporting ancillary site characteristics, and management and disturbance information at ICOS stations. Int. Agrophys., 32, 457469, https://doi.org/10.1515/intag-2017-0040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schulze, E. D. , and Coauthors, 2009: Importance of methane and nitrous oxide for Europe’s terrestrial greenhouse-gas balance. Nat. Geosci., 2, 842850, https://doi.org/10.1038/ngeo686.

    • Search Google Scholar
    • Export Citation
  • Schulze, 2010: The European carbon balance. Part 4: Integration of carbon and other trace-gas fluxes. Global Change Biol., 16, 14511469, https://doi.org/10.1111/j.1365-2486.2010.02215.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, N. E. , and Coauthors, 2020: Spring enhancement and summer reduction in carbon uptake during the 2018 drought in northwestern Europe. Philos. Trans. Roy. Soc. London, B375, 20190509, https://doi.org/10.1098/rstb.2019.0509.

    • Search Google Scholar
    • Export Citation
  • Steinhoff, T. , and Coauthors, 2019: Constraining the oceanic uptake and fluxes of greenhouse gases by building an ocean network of certified stations: The ocean component of the integrated carbon observation system, ICOS-oceans. Front. Mar. Sci., 6, 544, https://doi.org/10.3389/fmars.2019.00544.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. , G. Broquet, C. Gerbig, G. Monteil, M. Lang, and F.-T. Koch, 2019: Drought-2018 ensemble of inversion results for 2009–2018. ICOS-ERIC, https://doi.org/10.18160/YQ8P-P7CF.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. , and Coauthors, 2020: Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations. Philos. Trans. Roy. Soc. London, B375, 20190512, https://doi.org/10.1098/rstb.2019.0512.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • United Nations, 2015a: Paris Agreement. 16 pp., https://unfccc.int/files/meetings/paris_nov_2015/application/pdf/paris_agreement_english_.pdf.

    • Crossref
    • Export Citation
  • United Nations, 2015b: Transforming our world: The 2030 Agenda for Sustainable Development. 35 pp., www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_70_1_E.pdf.

    • Search Google Scholar
    • Export Citation
  • Vetter, M. , and Coauthors, 2008: Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models. Biogeosciences, 5, 561583, https://doi.org/10.5194/bg-5-561-2008.

    • Search Google Scholar
    • Export Citation
  • Vitale, D. , G. Fratini, M. Bilancia, G. Nicolini, S. Sabbatini, and D. Papale, 2020: A robust data cleaning procedure for eddy covariance flux measurements. Biogeosciences, 17, 13671391, https://doi.org/10.5194/bg-17-1367-2020.

    • Search Google Scholar
    • Export Citation
  • Wilkinson, M. D. , and Coauthors, 2016: The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18.

    • Search Google Scholar
    • Export Citation
  • WMO, 2009: A history of climate activities. WMO Bull., 58, 141.

  • WMO, 2014: The Global Atmosphere Watch Programme: 25 years of global coordinated atmospheric composition observations and analyses. WMO-1143, 45 pp., https://library.wmo.int/doc_num.php?explnum_id=7886.

    • Crossref
    • Export Citation
  • WMO, 2019: An Integrated Global Greenhouse Gas Information System (IG3IS) science implementation plan. GAW Rep. 245, 62 pp., https://library.wmo.int/doc_num.php?explnum_id=10034.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • WMO, 2020a: WMO WDCGG data summary. WDCGG-44, 95 pp., https://gaw.kishou.go.jp/static/publications/summary/sum44/sum44.pdf.

  • WMO, 2020b: 20th WMO/IAEA meeting on carbon dioxide, other Greenhouse Gases and Related Measurement Techniques (GGMT-2019). GAW Rep. 255, 140 pp., https://library.wmo.int/doc_num.php?explnum_id=10353.

    • Search Google Scholar
    • Export Citation
  • Yver Kwok, C. , and Coauthors, 2015: Comprehensive laboratory and field testing of cavity ring-down spectroscopy analyzers measuring H2O, CO2, CH4 and CO. Atmos. Meas. Tech., 8, 38673892, https://doi.org/10.5194/amt-8-3867-2015.

    • Search Google Scholar
    • Export Citation
  • Yver Kwok, C. , and Coauthors, 2021: Evaluation and optimization of ICOS atmosphere station data as part of the labeling process. Atmos. Meas. Tech., 14, 89116, https://doi.org/10.5194/amt-14-89-2021.

    • Search Google Scholar
    • Export Citation
  • View in gallery
    Fig. 1.

    Map of ICOS stations. The dots represent fixed stations in different domains (ocean, ecosystem, atmosphere) and lines represent the Ships of Opportunities. Up-to-date details (e.g., station class, contact info, data) from each station can be found at www.icos-cp.eu/observations/station-network.

  • View in gallery
    Fig. 2.

    Schematic figure of the carbon cycle and related data collection process and user access to all the data via the Carbon Portal. The color-coding links the areas of the biogeochemical carbon cycle to the respective stations and Thematic Centres. The green color indicates the exchange of carbon, GHGs, and energy between the atmosphere and ecosystems (vertical arrows); the red color indicates the atmospheric gas concentrations, chemistry, and transport processes (horizontal arrows); and the blue color indicates the ocean–atmosphere gas exchange (vertical arrows), observed within the ICOS stations of respective domains (dots in the lower part and also in Fig. 1). The observations are centrally processed within the Thematic Centres and the data stored to ICOS repository, with Carbon Portal serving as a one-stop shop for all ICOS data products.

  • View in gallery
    Fig. 3.

    An example of ICOS tool to analyze the potential impact of natural and anthropogenic emissions to the CO2 concentrations in the atmosphere, based on model simulation of Lagrangian transport model Stochastic Time Inverted Lagrangian Transport (STILT) together with emission-sector and fuel-type-specific emissions from a prerelease of the EDGARv4.3 inventory provided by the European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL). Figure shows results for the ICOS class 1 Jungfraujoch station in Switzerland, including biospheric and anthropogenic carbon emissions. (a) Modeled footprint and wind directions influencing the measurement tower signal. (b) Selected towers, location of atmospheric tower in Europe, and variables that are available for interactive visualization. (c) Time series of a selected variable, including measured and modeled concentrations.

  • View in gallery
    Fig. 4.

    Example of a regional-scale atmospheric inversion result, estimating the net ecosystem exchange (NEE) based on atmospheric observations from ICOS and other stations. The presented example is part of a multimodel ensemble of atmospheric inversions, available at Carbon Portal (Thompson et al. 2019), that was used to estimate the effect of the 2018 drought on net ecosystem exchange over Europe (Thompson et al. 2020).

  • View in gallery
    Fig. A1.

    The governance structure of ICOS.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2375 2334 199
PDF Downloads 1160 1146 127

The Integrated Carbon Observation System in Europe

Jouni HeiskanenHead Office, Integrated Carbon Observation System European Research Infrastructure Consortium, and Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland;

Search for other papers by Jouni Heiskanen in
Current site
Google Scholar
PubMed
Close
,
Christian BrümmerThünen Institute of Climate-Smart Agriculture, Braunschweig, Germany;

Search for other papers by Christian Brümmer in
Current site
Google Scholar
PubMed
Close
,
Nina BuchmannDepartment of Environmental Systems Science, ETH Zurich, Zurich, Switzerland;

Search for other papers by Nina Buchmann in
Current site
Google Scholar
PubMed
Close
,
Carlo CalfapietraInstitute of Research on Terrestrial Ecosystems, National Research Council, Porano, Italy;

Search for other papers by Carlo Calfapietra in
Current site
Google Scholar
PubMed
Close
,
Huilin ChenCentre for Isotope Research, University of Groningen, Groningen, Netherlands;

Search for other papers by Huilin Chen in
Current site
Google Scholar
PubMed
Close
,
Bert GielenDepartment of Biology, University of Antwerp, Wilrijk, Belgium;

Search for other papers by Bert Gielen in
Current site
Google Scholar
PubMed
Close
,
Thanos GkritzalisFlanders Marine Institute, Ostend, Belgium;

Search for other papers by Thanos Gkritzalis in
Current site
Google Scholar
PubMed
Close
,
Samuel HammerInstitut für Umweltphysik, Heidelberg University, Heidelberg, Germany;

Search for other papers by Samuel Hammer in
Current site
Google Scholar
PubMed
Close
,
Susan HartmanNational Oceanography Centre, Southampton, United Kingdom;

Search for other papers by Susan Hartman in
Current site
Google Scholar
PubMed
Close
,
Mathias HerbstCentre for Agrometeorological Research, German Meteorological Service, Braunschweig, Germany;

Search for other papers by Mathias Herbst in
Current site
Google Scholar
PubMed
Close
,
Ivan A. JanssensDepartment of Biology, University of Antwerp, Wilrijk, Belgium;

Search for other papers by Ivan A. Janssens in
Current site
Google Scholar
PubMed
Close
,
Armin JordanMax-Planck-Institute for Biogeochemistry, Jena, Germany;

Search for other papers by Armin Jordan in
Current site
Google Scholar
PubMed
Close
,
Eija JuurolaInstitute for Atmospheric and Earth System Research, University of Helsinki, Helsinki, Finland;

Search for other papers by Eija Juurola in
Current site
Google Scholar
PubMed
Close
,
Ute KarstensICOS ERIC, Carbon Portal, Lund, Sweden;

Search for other papers by Ute Karstens in
Current site
Google Scholar
PubMed
Close
,
Ville KasurinenHead Office, Integrated Carbon Observation System European Research Infrastructure Consortium, Helsinki, Finland;

Search for other papers by Ville Kasurinen in
Current site
Google Scholar
PubMed
Close
,
Bart KruijtDepartment of Environmental Sciences, Wageningen University and Research, Wageningen, Netherlands;

Search for other papers by Bart Kruijt in
Current site
Google Scholar
PubMed
Close
,
Harry LankreijerICOS ERIC, Carbon Portal, Lund, Sweden;

Search for other papers by Harry Lankreijer in
Current site
Google Scholar
PubMed
Close
,
Ingeborg LevinInstitut für Umweltphysik, Heidelberg University, Heidelberg, Germany;

Search for other papers by Ingeborg Levin in
Current site
Google Scholar
PubMed
Close
,
Maj-Lena LindersonDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden;

Search for other papers by Maj-Lena Linderson in
Current site
Google Scholar
PubMed
Close
,
Denis LoustauINRAE, ISPA, Villenave d’Ornon, France;

Search for other papers by Denis Loustau in
Current site
Google Scholar
PubMed
Close
,
Lutz MerboldAgroscope, Research Division Agroecology and Environment, Zurich, Switzerland;

Search for other papers by Lutz Merbold in
Current site
Google Scholar
PubMed
Close
,
Cathrine Lund MyhreAtmosphere and Climate Department, Norwegian Institute for Air Research, Kjeller, Norway;

Search for other papers by Cathrine Lund Myhre in
Current site
Google Scholar
PubMed
Close
,
Dario PapaleDepartment for Innovation in Biological Agro-Food and Forest Systems, University of Tuscia, Viterbo, and Euro-Mediterranean Center on Climate Change, Lecce, Italy;

Search for other papers by Dario Papale in
Current site
Google Scholar
PubMed
Close
,
Marian PavelkaDepartment of Matter and Energy Fluxes, Global Change Research Institute, CAS, Brno, Czech Republic;

Search for other papers by Marian Pavelka in
Current site
Google Scholar
PubMed
Close
,
Kim PilegaardDepartment of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark;

Search for other papers by Kim Pilegaard in
Current site
Google Scholar
PubMed
Close
,
Michel RamonetUniversité Paris-Saclay, CEA, CNRS, UVSQ, Laboratoire des Sciences du Climat et de l'Environnement (LSCE/IPSL), Gif-sur-Yvette, France;

Search for other papers by Michel Ramonet in
Current site
Google Scholar
PubMed
Close
,
Corinna RebmannHelmholtz Centre for Environmental Research, GmbH, Leipzig, Germany;

Search for other papers by Corinna Rebmann in
Current site
Google Scholar
PubMed
Close
,
Janne RinneDepartment of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden;

Search for other papers by Janne Rinne in
Current site
Google Scholar
PubMed
Close
,
Léonard RivierATC ICOS, Université Paris-Saclay, CEA, CNRS, UVSQ, Laboratoire des Sciences du Climat et de l'Environnement (LSCE/IPSL), Gif-sur-Yvette, France;

Search for other papers by Léonard Rivier in
Current site
Google Scholar
PubMed
Close
,
Elena SaltikoffHead Office, Integrated Carbon Observation System European Research Infrastructure Consortium, Helsinki, Finland;

Search for other papers by Elena Saltikoff in
Current site
Google Scholar
PubMed
Close
,
Richard SandersClimate Department, Norwegian Research Centre, Bergen, Norway;

Search for other papers by Richard Sanders in
Current site
Google Scholar
PubMed
Close
,
Martin SteinbacherLaboratory for Air Pollution/Environmental Technology, Empa, Duebendorf, Switzerland;

Search for other papers by Martin Steinbacher in
Current site
Google Scholar
PubMed
Close
,
Tobias SteinhoffChemical Oceanography, GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany, and NORCE Norwegian Research Centre AS, Bergen, Norway;

Search for other papers by Tobias Steinhoff in
Current site
Google Scholar
PubMed
Close
,
Andrew WatsonCollege of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom;

Search for other papers by Andrew Watson in
Current site
Google Scholar
PubMed
Close
,
Alex T. VermeulenICOS ERIC, Carbon Portal, Lund, Sweden;

Search for other papers by Alex T. Vermeulen in
Current site
Google Scholar
PubMed
Close
,
Timo VesalaInstitute for Atmosphere and Earth System Research/Physics, Faculty of Science, and Institute for Atmosphere and Earth System Research/Forest Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Helsinki, Finland, and Yugra State University, Khanty-Mansiysk, Russia;

Search for other papers by Timo Vesala in
Current site
Google Scholar
PubMed
Close
,
Gabriela VítkováGlobal Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

Search for other papers by Gabriela Vítková in
Current site
Google Scholar
PubMed
Close
, and
Werner KutschHead Office, Integrated Carbon Observation System European Research Infrastructure Consortium, Helsinki, Finland;

Search for other papers by Werner Kutsch in
Current site
Google Scholar
PubMed
Close
Open access

Abstract

Since 1750, land-use change and fossil fuel combustion has led to a 46% increase in the atmospheric carbon dioxide (CO2) concentrations, causing global warming with substantial societal consequences. The Paris Agreement aims to limit global temperature increases to well below 2°C above preindustrial levels. Increasing levels of CO2 and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the atmosphere are the primary cause of climate change. Approximately half of the carbon emissions to the atmosphere are sequestered by ocean and land sinks, leading to ocean acidification but also slowing the rate of global warming. However, there are significant uncertainties in the future global warming scenarios due to uncertainties in the size, nature, and stability of these sinks. Quantifying and monitoring the size and timing of natural sinks and the impact of climate change on ecosystems are important information to guide policy-makers’ decisions and strategies on reductions in emissions. Continuous, long-term observations are required to quantify GHG emissions, sinks, and their impacts on Earth systems. The Integrated Carbon Observation System (ICOS) was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. It provides standardized and open data currently from over 140 measurement stations across 12 European countries. The stations observe GHG concentrations in the atmosphere and carbon and GHG fluxes between the atmosphere, land surface, and the oceans. This article describes how ICOS fulfills its mission to harmonize these observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and deliver information and GHG-related products to stakeholders in society and policy.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

Corresponding author: Jouni Heiskanen, jouni.heiskanen@helsinki.fi

Abstract

Since 1750, land-use change and fossil fuel combustion has led to a 46% increase in the atmospheric carbon dioxide (CO2) concentrations, causing global warming with substantial societal consequences. The Paris Agreement aims to limit global temperature increases to well below 2°C above preindustrial levels. Increasing levels of CO2 and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the atmosphere are the primary cause of climate change. Approximately half of the carbon emissions to the atmosphere are sequestered by ocean and land sinks, leading to ocean acidification but also slowing the rate of global warming. However, there are significant uncertainties in the future global warming scenarios due to uncertainties in the size, nature, and stability of these sinks. Quantifying and monitoring the size and timing of natural sinks and the impact of climate change on ecosystems are important information to guide policy-makers’ decisions and strategies on reductions in emissions. Continuous, long-term observations are required to quantify GHG emissions, sinks, and their impacts on Earth systems. The Integrated Carbon Observation System (ICOS) was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. It provides standardized and open data currently from over 140 measurement stations across 12 European countries. The stations observe GHG concentrations in the atmosphere and carbon and GHG fluxes between the atmosphere, land surface, and the oceans. This article describes how ICOS fulfills its mission to harmonize these observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and deliver information and GHG-related products to stakeholders in society and policy.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

Corresponding author: Jouni Heiskanen, jouni.heiskanen@helsinki.fi

Since the industrial revolution, the combination of land-use change and fossil fuel combustion has led to a 46% increase in the atmospheric CO2 concentrations, totaling to a buildup of 2200 ± 320 GtCO2 in the atmosphere (Friedlingstein et al. 2020; Rogelj et al. 2019). Consensus is that this has led to a significant warming of the atmosphere and increased heat storage of the upper ocean with subsequent effects of considerable societal importance. Human-induced increases in atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), are the primary cause of the ongoing climate warming (IPCC 2019). The atmospheric buildup of CO2 would have been about twice as large had approximately half of the carbon emitted to the atmosphere not been sequestered by ocean and land sinks, leading to the rate of warming being reduced (Friedlingstein et al. 2020). However, the size, nature, and stability of these sinks are uncertain, which, together with the uncertainty of the speed of release of the heat stored in the ocean surfaces, leads to large uncertainties in the projected global climate warming with different GHG mitigation scenarios (Ma et al. 2020; Rhein et al. 2013). Improving the quantification and reducing the uncertainty of these projections is important to support policy-making and the size and timing of reductions in global emissions. There are uncertainties in the emission sources, but the largest cause for uncertainty in the global carbon budget estimates are likely due to the lack of understanding of land and ocean sinks (Friedlingstein et al. 2020). Understanding of these sinks, sources, and the related processes can only be achieved with research based on spatially and temporally comprehensive and precise data. This is ever more important now that a specific goal has been set at limiting average global surface temperature increases to well below 2°C above preindustrial levels: the Paris Agreement (United Nations 2015a) was ratified by 189 countries to guide the actions to combat climate change.

Anthropogenic emissions of GHGs to the atmosphere are superimposed on with the much larger natural GHG exchange fluxes between the atmosphere and the terrestrial ecosystems and ocean, which are further affected by ongoing climate warming. Quantifying the anthropogenic perturbation therefore depends on quantifying both natural and anthropogenic emissions and sinks and understanding the drivers of feedback mechanisms over both.

The Integrated Carbon Observation System (ICOS), which currently includes over 140 stations, was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. ICOS is motivated by understanding the sources, sinks, and cycling of greenhouse gases in the atmosphere–biosphere–hydrosphere continuum. The European Commission, Belgium, Finland, France, Germany, Italy, the Netherlands, Norway, Sweden, and Switzerland committed to this mission when the ICOS European Research Infrastructure Consortium (ERIC) was established in 2015.

Key aspects of climate science addressed by ICOS have been elaborated on in earlier articles, with Schulze et al. (2009) emphasizing the importance of N2O and CH4 in the European greenhouse gas budget, Peters et al. (2010) quantifying European net terrestrial CO2 exchange, Gielen et al. (2017) briefly summarizing the different components of the network, Franz et al. (2018) giving an overview on ICOS ecosystem observations, Steinhoff et al. (2019) describing the ocean network, and Levin et al. (2020) addressing the atmospheric network. This article provides a comprehensive overview of the ICOS Research Infrastructure (RI), including a historical overview, describing the structure, operations, and financial sustainability of the ICOS RI, elaborating present and future scientific questions, and discussing lessons learned and challenges addressed by ICOS.

The rationale and path into Integrated Carbon Observation System

Even though the connection between human actions and climate change had been made by the end of the twentieth century (IPCC 1992), many important questions were still open, such as how much CO2 from fossil fuel burning remains in the atmosphere and how much was taken up by oceans and terrestrial ecosystems (Keeling 1978). A major obstacle in answering these questions was limited data availability and the use of different observational methods, units, and scales by different countries and sites. This required global harmonization of observations, first started in the atmosphere by the World Meteorological Organization Global Atmosphere Watch (WMO GAW) program in 1989 (WMO 2014) and with the FLUXNET ecosystem global network in 1996 (Baldocchi et al. 2001).

Another obstacle was how to draw conclusions from various pieces of data and information. This called for a framework how to systematically provide scientific knowledge in global scale, giving birth to the Intergovernmental Panel on Climate Change (IPCC), established in the end of 1980s. Eyes turned next to land, where various methods had been developed to understand highly diverse and complex terrestrial ecosystems. This posed challenges to compare the results, and the Global Climate Observing System (GCOS) was established to harmonize terrestrial observations and to define a set of Essential Climate Variables (GCOS 1994, 2016; WMO 2009). Quantifying relatively small long-term trends in CO2 and other GHG concentration and fluxes against a background of much larger short-term variations caused by the “natural” carbon cycle requires highly precise and accurate observations. To decrease uncertainties by improving the quality of observations, and to draw general conclusions, research- and investigator-based European ecosystem networks, with foci on CO2, energy, and water exchange, emerged in the 1990s with the support of the European Commission funding programs (EuroFlux, CarboEurope IP, and GHG Europe). During 1998–2002, the EuroFlux network covered 30 stations mainly in forest ecosystems across Europe (Janssens et al. 2003), which later developed into the network of ecosystem stations within ICOS.

At the beginning of the 1990s, the Global Ocean Observing System (GOOS) was established to coordinate and harmonize ocean observations together with GCOS. The scientific community undertook the task to provide open access to global ocean surface CO2 data via the Surface Ocean CO2 Atlas (SOCAT; Pfeil et al. 2013). These data are essential to estimate ocean carbon budget and acidification. As a community effort, SOCAT depends heavily on voluntary data submission and secondary quality control, and the Ocean Carbon Data System of the National Oceanic and Atmospheric Administration and ICOS support SOCAT and contribute significantly to its data operations and development.

The development of observation networks had been fragmented into various projects in Europe (see Fig. 1 in Franz et al. 2018). By the beginning of the 2000s, it was possible to estimate the European terrestrial carbon budget by either using the few ecosystem network data available (e.g., Papale and Valentini 2003) or by methods using atmospheric network data, but these provided dissimilar and highly uncertain results (Janssens et al. 2003). The results suggested that increase in ecosystem representation and data would reduce the uncertainty in the bottom-up approach and that including more atmospheric stations would improve the accuracy of top-down estimates. The EU-funded CarboEurope Integrative Project (2004–08), was a major step toward integrated studies, harmonized observations, and data flows, covering atmosphere and ecosystem sciences (Schulze et al. 2009). In parallel, the CarboOcean IP conducted over 2005–09 developed systematic ocean carbon observations and analysis across Europe. The observations collected in the context of these projects were an important example to demonstrate how a large and coordinated network could provide a unique dataset valuable for the modeling activities to estimate continental-scale GHG fluxes (e.g., Luyssaert et al. 2010; Schulze et al. 2009; Vetter et al. 2008).

Fig. 1.
Fig. 1.

Map of ICOS stations. The dots represent fixed stations in different domains (ocean, ecosystem, atmosphere) and lines represent the Ships of Opportunities. Up-to-date details (e.g., station class, contact info, data) from each station can be found at www.icos-cp.eu/observations/station-network.

Citation: Bulletin of the American Meteorological Society 103, 3; 10.1175/BAMS-D-19-0364.1

European countries have been at the forefront of setting up the Paris Agreement to reduce emissions. Implementation of climate change mitigation is done by individual nations, but to effectively curb the increase of GHG concentrations in the future, a comprehensive strategy of emission reductions and natural sink conservation must be designed collectively. The success of the scientific projects showing capability of the scientific community to provide quantitative information at a European scale paved way for the political will to develop ICOS—an observation system that will narrow down future uncertainties and provide observational evidence of the current state of the carbon cycle perturbation. Throughout the development of ICOS, the policy-makers, funders, and scientists have been in constant dialogue to improve the scientific foundation of decision-making and obtain the political and financial commitments across European countries.

The ICOS foundation required negotiating the concept for such as system, with clear purpose and governance as well as financial structure and responsibilities of each participants, in which the countries could then commit. This was the purpose of ICOS preparatory phase project in 2008–13 (FP7 project 211574, see also appendix A).

A user-centric approach drove the development of a centralized data provision hub for all ICOS data, the Carbon Portal. The problem of different types of observations in atmosphere, ecosystem, and ocean stations was addressed by centralizing the quality control and data processing in three respective Thematic Centres with specific experience and knowledge. To allow measurements of required precision, the Central Analytical Laboratories was designed to provide calibration gases to atmospheric and ocean monitoring stations. The process for scientific development was planned on the interactions between these components and the monitoring station assemblies (MSAs), which include all station principal investigators (PIs).

The financial challenges were tackled by acquiring commitments from various countries interested to build a national network of ICOS stations or propose a central facility. The host countries provide the majority of the financial support by direct governmental grants (ICOS Ecosystem Thematic Centre is hosted by Italy, France, and Belgium; Atmosphere Thematic Centre by France and Finland; Ocean Thematic Centre by Norway and the United Kingdom; the Central Analytical Laboratories by Germany; and the Carbon Portal by Sweden and the Netherlands). The stations are maintained by individual countries, and each country also contributes to the general costs for the upkeep of the RI. The principles for sharing the financial responsibilities were written in the ICOS financial rules.

With scientific, technical, and financial concepts in place, the last challenge was how to coordinate such an infrastructure across many countries. The solution was to establish a legal entity designed to manage Research Infrastructures and recognized in all European countries, called ICOS European Research Infrastructure Consortium (ERIC; https://ec.europa.eu/info/research-and-innovation/strategy/european-research-infrastructures/eric_en), hosted by Finland and France with participation from all member countries), to coordinate the whole research infrastructure and to report to and consult with the ministerial stakeholders.

The mission of ICOS is to harmonize European carbon and GHG observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and to deliver GHG-related products to stakeholders in society and policy. The first five years of ICOS from 2015 to 2019 focused on establishing an operational infrastructure, and as an acknowledgment of successful implementation, ICOS ERIC was included in the European Strategy Forum on Research Infrastructures’ strategy as a landmark infrastructure (ESFRI 2016). Since becoming operational in 2015, the Czech Republic, Denmark, the United Kingdom, and Spain have joined ICOS, and Poland has announced to join ICOS, considerably expanding the network; in addition, negotiations are currently under way with Estonia, Greece, Hungary, Ireland, Portugal, and Romania. The second phase of ICOS, described in the ICOS strategy published in 2019 (ICOS 2019), and its associated implementation plan, will place emphasis on the use of data and on enhancing the network’s capability to analyze anthropogenic impacts on the carbon cycle. We foresee the new European Green Deal launched by the EU Commission at the end of 2019 (https://ec.europa.eu/info/strategy/priorities-2019-2024/european-green-deal_en), designed to make Europe the first net-zero continent, will further strengthen ICOS’ role in the forthcoming years.

Description of ICOS observations and data

ICOS provides the core network of highly accurate, long-term European in situ observations of carbon and GHGs (see appendix B for full list of observed variables). The terrestrial network of over 100 stations ranges from Sweden (latitude 68°N in WGS84 coordinates) to the Mediterranean Sea (latitude 36°N), from the United Kingdom (longitude 3°W) to Finland (longitude 30°E), from the lowlands near sea level to alpine regions (2168 m MSL, Italy), with stations also outside of Europe (e.g., in French Guyana, Greenland, and the Democratic Republic of the Congo). The marine network of over 20 stations and vessels extends from polar areas to the equator and from coasts to open ocean (Fig. 1).

The atmospheric network of tall towers, mountain, and coastal stations covers large parts of Europe with continuous measurements of CO2 and CH4 mole fractions. When coupled with an atmospheric model, these data provide an integrated view of all natural and anthropogenic fluxes. In fully equipped ICOS stations, meteorological variables, N2O and 222Rn are observed to link concentration variations to atmospheric mixing. In addition, N2O, SF6, H2, and for CO2 source apportionment CO, 13C-CO2, 14C-CO2, 18O-CO2, and the O2:N2 ratio, are analyzed in air sampled by automated flask samplers at the most extensively equipped stations, called class 1 stations (ICOS 2017a; Levin et al. 2020; appendix B).

GHG fluxes in different terrestrial ecosystems (forests, croplands, grasslands, mires, wetlands, shrublands, lakes, Mediterranean savannas, urban sites) are observed at comprehensively equipped stations to quantify the exchange of carbon, GHGs, and energy between the atmosphere and the ecosystems (Franz et al. 2018), by using the eddy covariance technique (Rebmann et al. 2018). Biosphere–atmosphere exchange measurements at flux towers represent the only direct method to provide detailed data at ecosystem scale, and they are valuable also for different user communities: e.g., sensible and latent heat fluxes are important to understand the water cycle and to improve weather forecasts, and turbulence data are used in studying boundary layer physics. In a subset of stations, fluxes of CH4 and N2O are observed (Nemitz et al. 2018). Complementary data comprise, e.g., soil organic carbon content, green area index, litterfall, aboveground biomass, records of disturbances, and vegetation properties such as leaf nutrients and phenological status, as well as management activities (Arrouays et al. 2018; Gielen et al. 2018; Hufkens et al. 2018; Loustau et al. 2018; Op de Beeck et al. 2018; Pavelka et al. 2018; Saunders et al. 2018). These various observations are used to estimate the contributions of different components of the ecosystem, such as soil or vegetation, to the seasonal and interannual variability of the carbon and GHG budget of the whole ecosystem, as well as when upscaling carbon fluxes to regional and global scales (Jung et al. 2020).

The ocean observations are conducted either on fixed platforms (e.g., moorings and surface buoys) or on ships operating predominantly in the North Atlantic, Nordic, Baltic, and Mediterranean Seas, but occasionally also in polar regions and the equatorial Atlantic. Partial pressure of sea surface CO2 is used in conjunction with other parameters (temperature, salinity, mixed layer depth) and satellite remote sensing products including wind fields and chlorophyll to calculate oceanic uptake of CO2 (ICOS 2017b, 2020b; Steinhoff et al. 2019). Other carbon cycle parameters (pH, alkalinity, dissolved inorganic carbon) and related properties such as nutrients and oxygen are used to investigate ocean transports and controls over carbon uptake. This latter work involves collaboration across various elements of the European RI landscape and components of the Global Ocean Observing System (GOOS) including Euro-Argo (European Consortium for Operating Argo Floats), EMSO (the European Multidisciplinary Seafloor and Water Column Observatory), and GO-SHIP (the Global Ocean Ship-Based Hydrographic Investigations Program). While the main policy framework that ICOS contributes to is the Paris Agreement, Agenda 2030 (United Nations 2015b) and its Sustainable Development Goal 14.3 are also supported with monitoring of ocean acidification.

The variables and related costs for all ICOS observations are detailed in the ICOS Handbook, released every 2 years (ICOS 2020a). For example, to build one fully equipped atmosphere or ecosystem station (class 1) costs between 0.5 and 1 million euros (not including personnel costs), whereas costs for stations having only a subset of observations (class 2) can be between 0.1 and 0.3 million euros. Maintenance requirements and collection of ancillary data are also provided, with the most significant component being person-power, ranging from 0.3 to 4 full-time equivalents per annum depending on the type of the station.

Quality assurance and quality control (QA/QC)

Within the CarboEurope IP project (Schulze et al. 2010) the challenges to achieve highly compatible atmospheric data became obvious. Large efforts were undertaken to assess the compatibility of atmospheric measurements done by different laboratories at different observational sites. Yet, results from these exercises repeatedly yielded evidence that the WMO compatibility goals were not met by all participants and for all tracers. Biases between laboratories could sometimes be of the same order of magnitude as the atmospheric signals that should be captured, and it was not possible to define a network data compatibility. This was motivating the ICOS concept with highly standardized measurement approaches at the observatories (including aspects such as instrumentation, procedures to account for atmospheric humidity, and calibration procedures) and the establishment of central facilities that assess the adequate performance of all installed analyzers and assure transparent data processing [Atmosphere Thematic Centre (ATC)], as well as the consistency of sample measurement results and reference gas assignments that are used within the monitoring network [Central Analytical Laboratories (CAL)]. To have the ability to make a defendable uncertainty assessment that is required for observational data (WMO 2020b), the following QA/QC approaches are applied that cover all levels of the observational system (stations as well as central facilities). To minimize uncertainties in both observations provided by single stations and studies using data from multiple stations, several steps are taken. The instruments themselves have strict requirements, they are systematically calibrated, their setup is based on stringent protocols, and the data are processed by the Thematic Centres with proven and standardized methodologies (Hazan et al. 2016; El Yazidi et al. 2018; Vitale et al. 2020).

Scientists in the ICOS atmosphere community, coordinated via the Atmospheric MSA, have defined and approved protocols for instrumentation setup and sampling strategies (ICOS 2017a; Levin et al. 2020) to ensure that atmospheric measurements comply with the compatibility goals set by the WMO for measurements of major GHGs and associated tracers (WMO 2020b). Stringent network compatibility within ICOS and with other networks is key when using the observations in concert with atmospheric transport models to quantify GHG sources and sinks. Calibration gases are prepared and calibrated centrally for the network by the Flask and Calibration Laboratory (FCL) of the CAL, which maintains tight links to the WMO Central Calibration Laboratory to ensure the traceability of ICOS data to internationally accepted WMO calibration scales by one unique path. To assess the accuracy of the implementation of these scales, the FCL maintains several ongoing round robin exercises with the NOAA laboratories as quality control. The FCL is also responsible for flask analyses except for 14C-CO2, which is analyzed by the Central Radiocarbon Laboratory of the CAL. The precision and stability of all GHG analyzers are tested at the Atmosphere Thematic Centre prior to deployment (Yver Kwok et al. 2015). A comprehensive overview of the optimization of the quality management as part of the labeling process of atmosphere stations is given in Yver-Kwok et al. (2021). For quality control of the continuous in situ measurements, automated QC figures are generated on a daily level by the ATC that summarize the statistics of the measurement precision (repeatability and target gas bias), which provide a basis to quantify the measurement uncertainty. Additional auditing is made with traveling instrumentation (ICOS Mobile Laboratory) operated at selected stations for a couple of weeks, and by ongoing comparison of flask results with in situ observations at class 1 stations (Levin et al. 2020).

To ensure high quality of observations in diverse ecosystems, with various drivers influencing the carbon and GHG fluxes, the observation methods need careful attention. Since diverse observation methods were established for different climate regions and ecosystem types in the past decades, a community-driven effort was necessary to define key and ancillary components to be observed in each ecosystem type to analyze carbon and GHG fluxes. Also, much effort has been put into defining the specifications and methodology of observations by the community, together with the Ecosystem MSA and the Ecosystem Thematic Centre. Both optimal sets of variables and practical feasibility were considered when harmonizing the observations, which resulted in a compromise suitable for high-quality and long-term continental-scale observation system (Franz et al. 2018). Over 100 scientists’ efforts were acknowledged in a set of publications describing the ecosystem measurement protocols in 2018 (see special issue of International Agrophysics, 2018, Vol. 32, No. 4). Starting from the protocols, more practical and detailed instruction documents were prepared and published by the ETC (http://www.icos-etc.eu/documents/instructions) that are revised and updated regularly, following the newest developments and knowledge.

For the ocean observations, the major challenges are the complexity of the carbonate system, the often remote location of stations, and suitability of different observing methods for different types of stations. Tailored solutions are needed in order for each station to deliver the best possible data, and the ICOS ocean community, supported by the Ocean Thematic Centre, has adopted and adapted existing and proven best-practice guidelines and protocols (Dickson et al. 2007) for observations made by different types of stations (Steinhoff et al. 2019). ICOS is the first multinational entity within the marine community that has standardized CO2 observations (Steinhoff et al. 2019). The Fixed Ocean Stations’ maintenance and calibration are done during the visit by research vessels, ideally several times per year, whereas observations on Ships of Opportunity (SOOP) are calibrated even more frequently. Inclusion of marine towers with direct flux observations is currently under development (Steinhoff et al. 2019). CO2 observations are calibrated with standards traceable to the WMO calibration scales (ICOS 2020b). Data quality, control, and uniformity is also supported by a customized QuinCe tool developed by the OTC.

To guarantee the quality of observations in all three network components (atmosphere, ecosystem, and ocean), it is necessary for a station to pass an ICOS station certification process. Here, the station characteristics are evaluated, its compliance with measurement protocols and standards is analyzed, and data transfer and quality are evaluated by the respective Thematic Centres during a test measurement period of a few months. After successfully completing this process, which typically takes 2–3 years, the station receives the ICOS certificate. This means the station meets the high standards of the ICOS network and continuously provides ICOS data. Of the over 140 stations in the ICOS network, over 60 stations have been certified by the end of 2020.

Open data access

ICOS has addressed the major challenge of data access and simplification of data use (Fig. 2) thanks to the PI and Central Facilities’ work that agreed on a continuous data submission and adoption of an open data license (Creative Commons Attribution 4.0 International, which also allows commercial use). Additionally, the services provided to make data distribution easier and assignment of digital object identifier (DOI) to datasets are major advances to improve and promote open data.

Fig. 2.
Fig. 2.

Schematic figure of the carbon cycle and related data collection process and user access to all the data via the Carbon Portal. The color-coding links the areas of the biogeochemical carbon cycle to the respective stations and Thematic Centres. The green color indicates the exchange of carbon, GHGs, and energy between the atmosphere and ecosystems (vertical arrows); the red color indicates the atmospheric gas concentrations, chemistry, and transport processes (horizontal arrows); and the blue color indicates the ocean–atmosphere gas exchange (vertical arrows), observed within the ICOS stations of respective domains (dots in the lower part and also in Fig. 1). The observations are centrally processed within the Thematic Centres and the data stored to ICOS repository, with Carbon Portal serving as a one-stop shop for all ICOS data products.

Citation: Bulletin of the American Meteorological Society 103, 3; 10.1175/BAMS-D-19-0364.1

To serve various user needs, different levels of the data are openly accessible with different levels of processing and quality check. Much attention has been paid to the metadata that follow the specifications defined by the Carbon Portal in collaboration with the Thematic Centres, also considering existing international standards. All steps of data flows were designed based on the Findable, Accessible, Interoperable, Reusable (FAIR) principles (Wilkinson et al. 2016), giving the user sufficient tools to interpret the data (ICOS 2015).

Different levels of data are stored throughout the process, from raw sensor data (level 0), to the automatically calibrated near-real-time data (level 1; available within 24 h of the measurement) to the final, quality-checked data (level 2). All the data are passed on to the Carbon Portal, which provides free and open access to ICOS data. The data are minted with Persistent Identifiers to provide unique identification and citation of the datasets and their contributors (ICOS 2019). The Carbon Portal offers tailor-made tools and services (Fig. 3) and distributes products (level 3) that are created by the scientific community based on ICOS data and possibly from other data sources (Fig. 4). The Carbon Portal has started to develop and provide tools for online analysis of data and model results (see, e.g., ICOS 2020c). These enable transparent analyses of data by station PIs, interactive collaboration with the data users, and utilization of cloud services as virtual working environments.

Fig. 3.
Fig. 3.

An example of ICOS tool to analyze the potential impact of natural and anthropogenic emissions to the CO2 concentrations in the atmosphere, based on model simulation of Lagrangian transport model Stochastic Time Inverted Lagrangian Transport (STILT) together with emission-sector and fuel-type-specific emissions from a prerelease of the EDGARv4.3 inventory provided by the European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL). Figure shows results for the ICOS class 1 Jungfraujoch station in Switzerland, including biospheric and anthropogenic carbon emissions. (a) Modeled footprint and wind directions influencing the measurement tower signal. (b) Selected towers, location of atmospheric tower in Europe, and variables that are available for interactive visualization. (c) Time series of a selected variable, including measured and modeled concentrations.

Citation: Bulletin of the American Meteorological Society 103, 3; 10.1175/BAMS-D-19-0364.1

Fig. 4.
Fig. 4.

Example of a regional-scale atmospheric inversion result, estimating the net ecosystem exchange (NEE) based on atmospheric observations from ICOS and other stations. The presented example is part of a multimodel ensemble of atmospheric inversions, available at Carbon Portal (Thompson et al. 2019), that was used to estimate the effect of the 2018 drought on net ecosystem exchange over Europe (Thompson et al. 2020).

Citation: Bulletin of the American Meteorological Society 103, 3; 10.1175/BAMS-D-19-0364.1

Major scientific questions and glimpse to the future

Many major scientific questions have guided the development of systematic, continental observations of carbon and GHG budgets. Scientists have been able to answer how much of emitted CO2 from fossil fuels have accumulated in the atmosphere, oceans, and terrestrial ecosystems (Friedlingstein et al. 2020). Many advancements have been made in defining how terrestrial ecosystems are affected by and how they feed back to climate change, e.g., by changes in evapotranspiration or albedo.

With the ICOS network reaching maturity via station certification, the compilation of the European carbon and GHG budget, which was previously possible as one-time effort (Schulze et al. 2009), can soon be produced annually at high spatial resolution and with reduced uncertainty. This is a significant step forward in assessing changes and trends on the continental scale. Advancements have been made in providing detailed information on the dominantly studied ecosystems, e.g., forests, grasslands, and croplands, while we still have only rudimentary understanding of some other ecosystem types, e.g., lakes, rivers, peatlands, Mediterranean savannas, and Arctic tundra (Baldocchi 2014; Schulze et al. 2010), or on urban systems. Mitigation capacity of urban areas as well as their adaptation capacity will need much deeper attention as the urban population is continuously growing and urban areas represent the major sources of GHGs in Europe and in most of the continents (Calfapietra et al. 2015).

ICOS data are widely used in publications from various scientific fields. The number of ICOS-related publications per year have increased from 30 in 2012 to roughly 200 in 2020, and the citations from 600 to 11,000, respectively (https://www.icos-cp.eu/science-and-impact/society-impact/references). The publications are associated to almost 60 categories, with the two largest being meteorology and atmospheric sciences (37% of all publications) and environmental sciences (34%) (ICOS 2021). The cross-domain integration in ICOS allows us to comprehensively address the biogeochemical fluxes of carbon and GHGs and to identify and study existing gaps in knowledge. A recent example are the 17 publications, based on data from more than 100 stations, following the drought in Europe in 2018. The drought was analyzed from how it was detectable in the atmospheric station network and how it affected ecosystem processes and GHG budgets, to regional assessments of its influences on ecosystem carbon exchange, and relations to major crops (see special issue of Philosophical Transactions of the Royal Society, 2020, Vol. B375, No. 1810). ICOS made this rapid scientific response possible by building the foundation for fast action, by harmonizing observations and centralized data processing, by analyzing the data in near–real time to detect anomalies in drivers and ecosystem responses, by facilitating networking of scientists, and by providing virtual solutions for joint work. The results show that the drought affected more the productivity of crops and grasslands than forests, which protected themselves by reducing their evaporation and growth, leading to decreased uptake of carbon dioxide (see special issue of Philosophical Transactions of the Royal Society, 2020, Vol. B375, No. 1810). In general, carbon sinks decreased by 18% in a study covering 56 ecosystem sites (Graf et al. 2020). The dry conditions even turned some mires from sinks into sources (Rinne et al. 2020). In some parts of Europe, the winter of 2018 was wet, leaving a lot of soil moisture in the ground, while spring was sunny and came early—this caused the vegetation to grow in spring more than average. In some places, this early spring growth was enough to offset the reduction of carbon uptake later in summer (e.g., Smith et al. 2020). Currently, there is a joint effort of similar magnitude under preparation analyzing the warm winter of 2019/20. The above mentioned topics are also reflected in the biennial ICOS Science Conference that brings scientists from different disciplines together to discuss science as well as, e.g., methodological improvements and societal relevance of long-term observations of climate-related variables.

Now, with the Paris Agreement having clear processes to guide the nations with climate change mitigation, the pressure is increasing to provide robust information to support the review of the impact of these actions (Article 14.1 in the Paris Agreement). ICOS is actively engaged with GCOS to provide observations of Essential Climate Variables and to draft a suitable indicator representing terrestrial ecosystems. ICOS provides data and participates to the development of Global Carbon Budget to reduce the uncertainty of the global estimates and to build a solid foundation for some of the global data sources, such as SOCAT and FLUXNET, the global network of gas flux observations between ecosystems and the atmosphere (Papale 2020). ICOS is in active dialogue with the United Nations Framework Convention on Climate Change (UNFCCC) Subsidiary Body for Scientific and Technological Advice to facilitate discussion between science and policy. ICOS is currently focusing on providing the needed information at national and regional levels with the separation of natural and anthropogenic fluxes. For example, VERIFY (H2020 project 776810) aims to improve national GHG inventories with top-down (atmospheric inversions) and bottom-up (inventories made with complementary methods and data than used by governmental authorities) scientific approaches (Petrescu et al. 2021).

The capability to disentangle the natural cycle and the anthropogenic disturbance has made progress, and consensus exists that the required next step is to link tightly in situ and remote sensing observations and modeling to more accurately quantify anthropogenic CO2 emissions (Copernicus 2015, 2019). The calibration and verification of satellite products and models within this system aim to rely on the in situ ICOS network, including potential atmospheric vertical profiling of GHGs using AirCore (Karion et al. 2010) and collaboration with the Total Carbon Column Observing Network (TCCON). This system is currently developed by scientists involved in ICOS and peers in the CoCO2 project (H2020 project 958927). Further developments could include the provision of more accurate observations of hot spots of human activities, mainly in urban areas (WMO 2019). The 14C methodology is used for quantifying the CO2 emissions from fossil fuel burning, as the fossil energy sources are void of 14C. Their contribution can be derived from measurements of the 14C:12C ratio in atmospheric CO2 (Basu et al. 2020; Levin et al. 2003, 2011). These observations are systematically made in ICOS but mostly in sparsely populated locations. The concept of an urban observatory has been tested in some European and U.S. cities (Breon et al. 2015; Lauvaux et al. 2020), but more development, probably combining atmospheric observations and modeling with flux observations, is needed before the methodology is mature enough to be incorporated into a research infrastructure such as ICOS. This system for greenhouse gas measurements in urban areas is developed by ICOS in the H2020 project PAUL (Pilot Application in Urban Landscapes—Towards integrated city observatories for greenhouse gases). Additionally, the flux towers are invaluable to provide data on carbon sinks over vegetated urban surfaces at neighborhood scale (e.g., Nordbo et al. 2012).

Lack of sufficient geographical coverage of observations is a source of major uncertainty in most regions of the world (WMO 2020a). Even in Europe, where the in situ observations of CO2 and other GHGs were brought together by ICOS, large parts of eastern Europe are still to join this network. The benefits are understood at the scientific level, but as membership in a research infrastructure obliges sustained funding and commitments, the discussions must enter the political level. Currently, the discussions are ongoing with seven countries to join ICOS.

ICOS is collaborating with complementary networks in Europe and in other continents toward more harmonized standardization of observations and data processing, common data policies, and common data citation system. Examples are the Long-Term Ecosystem Research (eLTER), the European Research Infrastructure for the Observation of Aerosol, Clouds and Trace Gases (ACTRIS), the AmeriFlux Management Project and the National Ecological Observatory Network (NEON) in the United States and the U.S. Carbon Cycle Science Program, the Chinese Ecosystem Research Network, the Terrestrial Ecosystem Research Network (TERN) in Australia, and the National Institute for Environmental Studies in Japan. ICOS also supports and develops the global data networks, such as WMO Global Atmosphere Watch and the World Data Centre of Greenhouse Gases for atmospheric observations, FLUXNET for ecosystem GHG fluxes, SOCAT, and Global Ocean Data Analysis Project (GLODAP). ICOS contributes to the development of harmonized observations in Africa via design study and capacity building (Lopéz-Ballesteros et al. 2018).

Many global coordination frameworks are in place to address the global environmental challenges. However, there is a huge distance between global frameworks and local actions. Developments are needed on different scales to improve the observational capacity and to transform the data into information useful for local and national decision-makers, nongovernmental organizations, and the private sector. Examples of the urgently needed developments are defining how changing climate affects the ability of natural terrestrial and ocean sink to sequester carbon, supporting the verification of national GHG inventories, and understanding and validating the efficacy of mitigation actions. ICOS provides the European in situ observations of CO2 and other GHGs, and is well positioned to coordinate the in situ component of a comprehensive system that caters to different information needs at different spatial and temporal scales (Copernicus 2019). Combatting climate change needs reliable information, and ICOS is here to deliver.

Acknowledgments.

Academy of Finland (Grants 281255, 319871, 320124, 329221); the Danish Agency for Science and Higher Education; Danish Ministry of Energy, Utilities and Climate; EU (Grants 211574, 730944); Finnish Ministry of Transport and Communication; Flemish Fund for Scientific Research (FWO Grant G0H3317); French Ministry of Research (MESRI); German Ministry of Education and Research (BMBF); German Ministry of Transport and Digital Infrastructure (BMVI); the Italian Ministry of Universities and Research; the Netherlands Ministry of Education, Culture and Science; the Netherlands Organisation for Scientific Research; the Ministry of Education, Youth and Sports of the Czech Republic; the Natural Environment Research Council of the United Kingdom; Norwegian Environmental Agency, Norwegian Ministry of Climate and Environment, Research Council of Norway; Swedish Research Council (Grant 2019-00205); Swiss National Science Foundation (ICOS-CH Phase 1 and Phase 2, 20FI21_148992 and 20FI20_173691); and the ETH domain.

Appendix A: ICOS governance and funding

Governance.

The European Strategy Forum for Research Infrastructures (ESFRI) produced a roadmap of RIs in 2006, including the preparation of ICOS to cover European carbon dioxide and other GHG observations (ESFRI 2006). The ICOS Preparatory Phase Project (2008–13) focused on integrating the already existing stations into a single network and establishing a model for sustained funding since the ICOS observations at the stations was usually limited to the lifetime of regular research projects. Besides harmonized observations, data management and archiving, this unprecedented effort covered also administrative, financial and legal aspects. ICOS ERIC was established in 2015 with the member (Belgium, Finland, France, Germany, Italy, the Netherlands, Norway, Sweden) and observer (Switzerland) countries committing to the long-term funding of the RI.

The governance and operational structure of Integrated Carbon Observation System European Research Infrastructure Consortium (ICOS ERIC) and ICOS RI is shown in Fig. A1. The data are provided by the ICOS National Networks, which are networks of stations operated at national level and form the backbone of ICOS RI. The Central Facilities receive, quality control, and process the data measured at the ICOS stations. The Central Facilities are operated by one or several Host Institutions either at national or at multinational level, and they include the Atmosphere Thematic Centre (ATC), Ecosystem Thematic Centre (ETC), Ocean Thematic Centre (OTC), and Central Analytical Laboratories (CAL). Monitoring Station Assemblies (MSAs) in atmosphere, ecosystem, and ocean domains gather together the ICOS station principal investigators (PIs) to discuss technical and scientific topics. All data from raw, near-real-time to final quality-controlled data are stored and published through the ICOS Carbon Portal, part of ICOS ERIC.

Fig. A1.
Fig. A1.

The governance structure of ICOS.

Citation: Bulletin of the American Meteorological Society 103, 3; 10.1175/BAMS-D-19-0364.1

The task sharing between ICOS ERIC and Central Facilities is clearly defined and agreed upon in ICOS ERIC–Central Facilities agreements. Furthermore, the basic management and internal distribution of the work is organized by the Central Facilities host institutions, and employment practices are carried out according to the respective institutional practices. Financial governance follows the similar approach: the host institutions have their own responsibility but have to comply with common rules and are monitored by ICOS ERIC.

The decision-making body in ICOS ERIC is the General Assembly consisting of delegates from all member and observer countries. The Research Infrastructure Committee, with representatives from the ICOS ERIC and Central Facilities and MSAs, advises the Director General and the General Assembly on scientific and organizational topics. Scientific Advisory Board and Ethical Advisory Boards are external bodies for giving strategic guidance for ICOS RI.

Funding.

The national networks are funded mainly by the national funding agencies and respective ministries, with additional support by the host institutions of the measuring stations. A substantial part of the total costs of the Central Facilities and ICOS ERIC is covered by contributions of the hosting country/countries (host premium contribution) of the Central Facilities, Head Office, and Carbon Portal.

Member and observer countries of ICOS ERIC pay annual membership contributions. Total membership contributions are formed by the following elements: common basic contribution, common GNI based contribution, and number and type of stations. The latter part of the membership contribution is redistributed to the activities in the ICOS Central Facilities. The Central Facilities are also supported by the host organizations. ICOS ERIC seeks funding opportunities from European Commission and other sources.

Appendix B: Observed variables at ICOS stations

All the observed variables at ICOS stations are presented in Tables B1B4.

Table B1.

List of variables observed at ICOS atmosphere stations.

Table B1.
Table B2.

List of variables observed at ICOS Ecosystem Stations, with numbers indicating class 1 and 2 stations. Wetland includes all different water-inundated or saturated ecosystems according to Joosten and Clark (2002). The list of variables for lake, marine, and urban sites is under discussion. Fac = facultative variable; N.R. = not relevant for the ecosystem; SW = shortwave; LW = longwave; PPFD = photosynthetic photon flux density; TA = air temperature; RH = relative humidity; GAI = green area index; DOC = dissolved organic carbon.

Table B2.
Table B3.

List of variables measured at ICOS Ships of Opportunity.

Table B3.
Table B4.

List of variables measured at ICOS Fixed Ocean Stations.

Table B4.

References

  • Arrouays, D. , and Coauthors, 2018: Soil sampling and preparation for monitoring soil carbon. Int. Agrophys., 32, 633643, https://doi.org/10.1515/intag-2017-0047.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baldocchi, D. , 2014: Measuring fluxes of trace gases and energy between ecosystems and the atmosphere – The state and future of the eddy covariance method. Global Change Biol., 20, 36003609, https://doi.org/10.1111/gcb.12649.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baldocchi, D. , and Coauthors, 2001: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bull. Amer. Meteor. Soc., 82, 24152434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Basu, S. , and Coauthors, 2020: Estimating US fossil fuel CO2 emissions from measurements of 14C in atmospheric CO2. Proc. Natl. Acad. Sci. USA, 117, 13 30013 307, https://doi.org/10.1073/pnas.1919032117.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Breon, F. M. , and Coauthors, 2015: An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements. Atmos. Chem. Phys., 15, 17071724, https://doi.org/10.5194/acp-15-1707-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Calfapietra, C. , Ü. Niinemets, and J. Peñuelas, 2015: Urban plant physiology: Adaptation-mitigation strategies under permanent stress. Trends Plant Sci., 20, 7275, https://doi.org/10.1016/j.tplants.2014.11.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Copernicus, 2015: Towards a European operational observing system to monitor fossil CO2 emissions. European Commission, 65 pp., https://op.europa.eu/s/uz3d.

    • Search Google Scholar
    • Export Citation
  • Copernicus, 2019: An operational anthropogenic CO2 emissions monitoring & verification support capacity: Needs and high level requirements for in situ measurements. European Commission, 72 pp., https://doi.org/10.2760/182790.

    • Search Google Scholar
    • Export Citation
  • Dickson, A. G. , C. L. Sabine, and J. R. Christian, Eds., 2007: Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publ. 3, IOCCP Rep. 8, 191 pp., https://cdiac.ess-dive.lbl.gov/ftp/oceans/Handbook_2007/Guide_all_in_one.pdf.

    • Crossref
    • Export Citation
  • El Yazidi, A. , and Coauthors, 2018: Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4. Atmos. Meas. Tech., 11, 15991614, https://doi.org/10.5194/amt-11-1599-2018.

    • Search Google Scholar
    • Export Citation
  • ESFRI, 2006: European roadmap for research infrastructures: Report 2006. European Strategy Forum on Research Infrastructures, 84 pp., www.esfri.eu/sites/default/files/esfri_roadmap_2006_en.pdf.

  • ESFRI, 2016: Strategy report on research infrastructures. European Strategy Forum on Research Infrastructures, 208 pp., www.esfri.eu/sites/default/files/20160309_ROADMAP_browsable.pdf.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Franz, D. , and Coauthors, 2018: Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: A review. Int. Agrophys., 32, 439455, https://doi.org/10.1515/intag-2017-0039.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P. , and Coauthors, 2020: Global carbon budget 2020. Earth Syst. Sci. Data, 12, 32693340, https://doi.org/10.5194/essd-12-3269-2020.

    • Search Google Scholar
    • Export Citation
  • GCOS, 1994: Report of the GCOS/GTOS Terrestrial Observation Panel. WMO/TD-642; GCOS-08, 53 pp., https://library.wmo.int/doc_num.php?explnum_id=3804.

  • GCOS, 2016: The Global Observing System for Climate: Implementation Needs. GCOS-200, GOOS-214, 315 pp., https://library.wmo.int/doc_num.php?explnum_id=3417.

    • Search Google Scholar
    • Export Citation
  • Gielen, B. , M. Op de Beeck, D. Loustau, R. Ceulemans, A. Jordan, and D. Papale, 2017: Integrated Carbon Observation System (ICOS): An infrastructure to monitor the European greenhouse gas balance. Terrestrial Ecosystem Research Infrastructures: Challenges and Opportunities, 1st ed. A. Chabbi and H. W. Loescher, Eds., CRC Press, 505–520.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gielen, B. , and Coauthors, 2018: Ancillary data measurements at ICOS sites. Int. Agrophys., 32, 645664, https://doi.org/10.1515/intag-2017-0048.

    • Search Google Scholar
    • Export Citation
  • Graf, A. , and Coauthors, 2020: Altered energy partitioning across terrestrial ecosystems in the European drought year 2018. Philos. Trans. Roy. Soc. London, 375B, 20190524, https://doi.org/10.1098/rstb.2019.0524.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hazan, L. , J. Tarniewicz, M. Ramonet, O. Laurent, and A. Abbaris, 2016: Automatic processing of atmospheric CO2 and CH4 mole fractions at the ICOS Atmosphere Thematic Centre. Atmos. Meas. Tech., 9, 47194736, https://doi.org/10.5194/amt-9-4719-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hufkens, K. , and Coauthors, 2018: Assimilating phenology datasets automatically across ICOS ecosystem stations. Int. Agrophys., 32, 677687, https://doi.org/10.1515/intag-2017-0050.

    • Search Google Scholar
    • Export Citation
  • ICOS, 2015: ICOS RI data policy. ICOS ERIC, 11 pp., www.icos-cp.eu/sites/default/files/cmis/ICOS%20RI%20Data%20Policy.pdf.

  • ICOS, 2017a: ICOS Atmospheric Station specifications, version 1.3. ICOS ATC, 55 pp., https://doi.org/10.18160/SDW6-BX90.

  • ICOS, 2017b: ICOS Marine Station Labelling Step 2. ICOS OTC, 23 pp., https://otc.icos-cp.eu/sites/default/files/2018-05/ICOS%20Marine%20Station%20Labelling%20Step%202%20v4_crb.docx_.pdf.

    • Search Google Scholar
    • Export Citation
  • ICOS, 2019: ICOS Strategy. ICOS ERIC, 40 pp., www.icos-cp.eu/sites/default/files/cmis/ICOS%20Strategy.pdf.

  • ICOS, 2020a: ICOS Handbook 2020. ICOS ERIC, 152 pp., www.icos-cp.eu/sites/default/files/2020-12/ICOS%20Handbook%202020.pdf.

  • ICOS, 2020b: ICOS Ocean Station Labelling Step 2. ICOS OTC, 20 pp., https://doi.org/10.18160/8SDC-K4FR.

  • ICOS, 2020c: Jupyter Notebook for ICOS Flask Sampling Strategy (Version 1.0). ICOS ERIC, https://doi.org/10.18160/FSS2-SH26.

  • ICOS, 2021: ICOS Five-Year Evaluation 2020. ICOS ERIC, 127 pp., www.icos-cp.eu/sites/default/files/2021-05/ICOS%20Evaluation%202020%20Report%20_online%20low.pdf.

    • Search Google Scholar
    • Export Citation
  • IPCC, 1992: Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment. J. T. Houghton, B. A. Callander, and S. K. Varney, Eds., Cambridge University Press, 200 pp.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2019: Global Warming of 1.5°C. V. Masson-Delmotte et al., Eds., IPCC, 630 pp.

  • Janssens, I. , and Coauthors, 2003: Europe’s terrestrial biosphere anthropogenic CO2 emissions. Science, 300, 15381542, https://doi.org/10.1126/science.1083592.

    • Search Google Scholar
    • Export Citation
  • Joosten, H. , and D. Clark, 2002: Wise Use of Mires and Peatlands: Background and Principles Including a Framework for Decision-making. International Mire Conservation Group and International Peat Society, 304 pp.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jung, M. , and Coauthors, 2020: Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach. Biogeosciences, 17, 13431365, https://doi.org/10.5194/bg-17-1343-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Karion, A. , C. Sweeney, P. Tans, and T. Newberger, 2010: AirCore: An innovative atmospheric sampling system. J. Atmos. Oceanic Technol., 27, 18391853, https://doi.org/10.1175/2010JTECHA1448.1.

    • Search Google Scholar
    • Export Citation
  • Keeling, C. D. , 1978: The influence of Mauna Loa Observatory on the development of atmospheric CO2 research. Mauna Loa Observatory. A 20th Anniversary Report, J. Miller, Ed., U.S. Department of Commerce, 3654.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lauvaux, T. , and Coauthors, 2020: Policy-relevant assessment of urban CO2 emissions. Environ. Sci. Technol., 54, 10 23710 245, https://doi.org/10.1021/acs.est.0c00343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levin, I. , B. Kromer, M. Schmidt, and H. Sartorius, 2003: A novel approach for independent budgeting of fossil fuel CO2 over Europe by 14CO2 observations. Geophys. Res. Lett., 30, 2194, https://doi.org/10.1029/2003GL018477.

    • Search Google Scholar
    • Export Citation
  • Levin, I. , S. Hammer, E. Eichelmann, and F. R. Vogel, 2011: Verification of greenhouse gas emission reductions: The prospect of atmospheric monitoring in polluted areas. Philos. Trans. Roy. Soc. London, A369, 19061924, https://doi.org/10.1098/rsta.2010.0249.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Levin, I. , and Coauthors, 2020: A dedicated flask sampling strategy developed for ICOS stations based on CO2 and CO measurements and STILT footprint modelling. Atmos. Chem. Phys., 20, 11 16111 180, https://doi.org/10.5194/acp-20-11161-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • López-Ballesteros, A. , and Coauthors, 2018: Towards a feasible and representative pan-African research infrastructure network for GHG observations. Environ. Res. Lett., 13, https://doi.org/10.1088/1748-9326/aad66c.

    • Crossref
    • Export Citation
  • Loustau, D. , and Coauthors, 2018: Sampling and collecting foliage elements for the determination of the foliar nutrients in ICOS ecosystem stations. Int. Agrophys., 32, 665676, https://doi.org/10.1515/intag-2017-0038.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luyssaert, S. , and Coauthors, 2010: The European carbon balance. Part 3: Forests. Global Change Biol., 16, 14291450, https://doi.org/10.1111/j.1365-2486.2009.02056.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ma, X. , W. Liu, R. J. Allen, G. Huang, and X. Li, 2020: Dependence of regional ocean heat uptake on anthropogenic warming scenarios. Sci. Adv., 6, eabc0303, https://doi.org/10.1126/sciadv.abc0303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nemitz, E. , and Coauthors, 2018: Standardisation of eddy-covariance flux measurements of methane and nitrous oxide. Int. Agrophys., 32, 517549, https://doi.org/10.1515/intag-2017-0042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nordbo, A. , L. Järvi, S. Haapanala, C. R. Wood, and T. Vesala, 2012: Fraction of natural area as main predictor of net CO2 emissions from cities. Geophys. Res. Lett., 39, L20802, https://doi.org/10.1029/2012GL053087.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Op de Beeck, M. , and Coauthors, 2018: Soil-meteorological measurements at ICOS monitoring stations in terrestrial ecosystems. Int. Agrophys., 32, 619631, https://doi.org/10.1515/intag-2017-0041.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Papale, D. , 2020: Ideas and perspectives: Enhancing the impact of the FLUXNET network of eddy covariance sites. Biogeosciences, 17, 55875598, https://doi.org/10.5194/bg-17-5587-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Papale, D. , and R. Valentini, 2003: A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization. Global Change Biol., 9, 525535, https://doi.org/10.1046/j.1365-2486.2003.00609.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pavelka, M. , and Coauthors, 2018: Standardisation of chamber technique for CO2, N2O and CH4 fluxes measurements from terrestrial ecosystems. Int. Agrophys., 32, 569587, https://doi.org/10.1515/intag-2017-0045.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, W. , and Coauthors, 2010: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations. Global Change Biol., 16, 13171337, https://doi.org/10.1111/j.1365-2486.2009.02078.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Petrescu, A. M. R. , and Coauthors, 2021: The consolidated European synthesis of CH4 and N2O emissions for European Union and United Kingdom: 1990–2017. Earth Syst. Sci. Data, 13, 23072362, https://doi.org/10.5194/essd-13-2307-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pfeil, B. , and Coauthors, 2013: A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT). Earth Syst. Sci. Data, 5, 125143, https://doi.org/10.5194/essd-5-125-2013.

    • Search Google Scholar
    • Export Citation
  • Rebmann, C. , and Coauthors, 2018: ICOS eddy covariance flux-station site setup: A review. Int. Agrophys., 32, 471494, https://doi.org/10.1515/intag-2017-0044.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rhein, M. , and Coauthors, 2013: Observations: Ocean. Climate Change 2013: The Physical Science Basis. T. F. Stocker et al., Eds., Cambridge University Press, 255315.

    • Search Google Scholar
    • Export Citation
  • Rinne, J. , and Coauthors, 2020: Effect of the 2018 European drought on methane and carbon dioxide exchange of northern mire ecosystems. Philos. Trans. Roy. Soc. London, B375, 20190517, https://doi.org/10.1098/rstb.2019.0517.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rogelj, J. , and Coauthors, 2019: Mitigation pathways compatible with 1.5°C in the context of sustainable development. Global Warming of 1.5°C, V. Masson-Delmotte et al., Eds., IPCC, 93174.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, M. , and Coauthors, 2018: Importance of reporting ancillary site characteristics, and management and disturbance information at ICOS stations. Int. Agrophys., 32, 457469, https://doi.org/10.1515/intag-2017-0040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schulze, E. D. , and Coauthors, 2009: Importance of methane and nitrous oxide for Europe’s terrestrial greenhouse-gas balance. Nat. Geosci., 2, 842850, https://doi.org/10.1038/ngeo686.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schulze, 2010: The European carbon balance. Part 4: Integration of carbon and other trace-gas fluxes. Global Change Biol., 16, 14511469, https://doi.org/10.1111/j.1365-2486.2010.02215.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, N. E. , and Coauthors, 2020: Spring enhancement and summer reduction in carbon uptake during the 2018 drought in northwestern Europe. Philos. Trans. Roy. Soc. London, B375, 20190509, https://doi.org/10.1098/rstb.2019.0509.

    • Search Google Scholar
    • Export Citation
  • Steinhoff, T. , and Coauthors, 2019: Constraining the oceanic uptake and fluxes of greenhouse gases by building an ocean network of certified stations: The ocean component of the integrated carbon observation system, ICOS-oceans. Front. Mar. Sci., 6, 544, https://doi.org/10.3389/fmars.2019.00544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. , G. Broquet, C. Gerbig, G. Monteil, M. Lang, and F.-T. Koch, 2019: Drought-2018 ensemble of inversion results for 2009–2018. ICOS-ERIC, https://doi.org/10.18160/YQ8P-P7CF.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. , and Coauthors, 2020: Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations. Philos. Trans. Roy. Soc. London, B375, 20190512, https://doi.org/10.1098/rstb.2019.0512.

    • Search Google Scholar
    • Export Citation
  • United Nations, 2015a: Paris Agreement. 16 pp., https://unfccc.int/files/meetings/paris_nov_2015/application/pdf/paris_agreement_english_.pdf.

    • Crossref
    • Export Citation
  • United Nations, 2015b: Transforming our world: The 2030 Agenda for Sustainable Development. 35 pp., www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_70_1_E.pdf.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vetter, M. , and Coauthors, 2008: Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models. Biogeosciences, 5, 561583, https://doi.org/10.5194/bg-5-561-2008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vitale, D. , G. Fratini, M. Bilancia, G. Nicolini, S. Sabbatini, and D. Papale, 2020: A robust data cleaning procedure for eddy covariance flux measurements. Biogeosciences, 17, 13671391, https://doi.org/10.5194/bg-17-1367-2020.

    • Search Google Scholar
    • Export Citation
  • Wilkinson, M. D. , and Coauthors, 2016: The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data, 3, 160018, https://doi.org/10.1038/sdata.2016.18.

    • Search Google Scholar
    • Export Citation
  • WMO, 2009: A history of climate activities. WMO Bull., 58, 141.

  • WMO, 2014: The Global Atmosphere Watch Programme: 25 years of global coordinated atmospheric composition observations and analyses. WMO-1143, 45 pp., https://library.wmo.int/doc_num.php?explnum_id=7886.

  • WMO, 2019: An Integrated Global Greenhouse Gas Information System (IG3IS) science implementation plan. GAW Rep. 245, 62 pp., https://library.wmo.int/doc_num.php?explnum_id=10034.

    • Search Google Scholar
    • Export Citation
  • WMO, 2020a: WMO WDCGG data summary. WDCGG-44, 95 pp., https://gaw.kishou.go.jp/static/publications/summary/sum44/sum44.pdf.

  • WMO, 2020b: 20th WMO/IAEA meeting on carbon dioxide, other Greenhouse Gases and Related Measurement Techniques (GGMT-2019). GAW Rep. 255, 140 pp., https://library.wmo.int/doc_num.php?explnum_id=10353.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yver Kwok, C. , and Coauthors, 2015: Comprehensive laboratory and field testing of cavity ring-down spectroscopy analyzers measuring H2O, CO2, CH4 and CO. Atmos. Meas. Tech., 8, 38673892, https://doi.org/10.5194/amt-8-3867-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yver Kwok, C. , and Coauthors, 2021: Evaluation and optimization of ICOS atmosphere station data as part of the labeling process. Atmos. Meas. Tech., 14, 89116, https://doi.org/10.5194/amt-14-89-2021.

    • Crossref
    • Search Google Scholar
    • Export Citation
Save