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  • 1.
    Moldanová, Jana
    et al.
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Fridell, Erik
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Matthias, Volker
    Helmholtz Zentrum Geesthacht, Centre for Materials and Coastal Research, Germany.
    Hassellöv, Ida-Maja
    Executive, Universitet, Chalmers.
    Eriksson, Martin
    Executive, Universitet, Chalmers.
    Jalkanen, Jukka-Pekka
    Finnish Meteorological Institute.
    Tröeltzsch, Jeny
    Ecologic Institute, Germany.
    Quante, Markus
    Helmholtz Zentrum Geesthacht, Centre for Materials and Coastal Research, Germany.
    Johansson, Lasse
    Finnish Meteorological Institute.
    Majutenko, Ilja
    Marine Systems Institute, Tallinn University of Technology, Estonia.
    Karl, Matthias
    Helmholtz Zentrum Geesthacht, Centre for Materials and Coastal Research, Germany.
    Sigray, Peter
    Swedish Defence Research Agency, FOI, Sweden.
    Karasalo, Ilkka
    Swedish Defence Research Agency, FOI, Sweden.
    Peltonen, Heikki
    Executive, Forskningsinstitut, The Finnish Environment Institute, SYKE.
    Tang, Lin
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Magnusson, Kerstin
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Jutterström, Sara
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Moldan, Filip
    Executive, Forskningsinstitut, IVL Swedish Environmental Research Institute.
    Ramacher, Martin
    Helmholtz Zentrum Geesthacht, Centre for Materials and Coastal Research, Germany.
    Aulinger, Armin
    Helmholtz Zentrum Geesthacht, Centre for Materials and Coastal Research, Germany.
    Ytreberg, Erik
    Executive, Universitet, Chalmers.
    Granhag, Lena
    Executive, Universitet, Chalmers.
    Uppstu, Andreas
    Finnish Meteorological Institute.
    Hasenheit, Marius
    Ecologic Institute, Germany.
    Raudsepp, Urmas
    Marine Systems Institute, Tallinn University of Technology, Estonia.
    Roth, Eva
    University of Southern Denmark, Department of Environmental and Business Economics, Denmark.
    Demirdjian, Benjamin
    Centre National de la Recherche Scientifique, Marseille Interdisciplinary Centre for Nanoscience, joint research unit UMR 7325, France.
    Piotrowicz, Jakub
    Maritime Institute in Gdansk, Poland.
    Information on completed BONUS SHEBA project2018Report (Other academic)
    Download full text (pdf)
    Information on completed BONUS SHEBA project.pdf
  • 2.
    Ortiz, Carina
    et al.
    Executive, Universitet, Swedish University of Agricultural Sciences, Sveriges lantbruksuniversitet, mark och miljö.
    Lundblad, Mattias
    Executive, Universitet, Swedish University of Agricultural Sciences, Sveriges lantbruksuniversitet, mark och miljö.
    Liski, Jari
    Executive, Forskningsinstitut, The Finnish Environment Institute, SYKE.
    Stendahl, Johan
    Executive, Universitet, Swedish University of Agricultural Sciences, Sveriges lantbruksuniversitet, mark och miljö.
    Karltun, Erik
    Executive, Universitet, Swedish University of Agricultural Sciences, Sveriges lantbruksuniversitet, mark och miljö.
    Lehtonen, Aleksi
    Gärdenäs, Annemieke
    Executive, Universitet, Swedish University of Agricultural Sciences, Sveriges lantbruksuniversitet, mark och miljö.
    Measurements and models –a comparison of quantificationmethods for SOC changes in forestsoils2009Report (Other academic)
    Abstract [en]

    The Swedish UNFCCC

    1-reporting of the LULUCF2-sector is based on methods in

    compliance with the “Good practice” as described by the Intergovernmental Panel

    on Climate Change (IPCC). Biomass and soil inventory data from the Swedish

    Inventory of Forests is the major source of information used to quantify changes in

    the various carbon pools on forest land. Even if the reported uncertainties in soil

    carbon changes are small from a statistical perspective, they are large in relation to

    the total Swedish emissions of green house gases. This is due to the fact that the

    soil carbon pool is so large, that even small and statistically non-significant

    changes may have an impact on the Swedish CO

    2 balance. Sampling based methods

    may also result in considerable inter annual variations that may look conspicuous

    in the reporting. Because of the uncertainty and inter annual variations there

    has been a discussion on the methods used and if there are possibilities to lower the

    uncertainty and to get more stable estimates of soil carbon changes by combining

    measurements and models. In this study results from the two soil carbon models,

    Yasso07 and Q, were compared with repeated measurements of the soil inventory

    during the years 1994 to 2000. Soil carbon fluxes were simulated with the two

    models from 1926 to 2000 with Monte Carlo methodology to estimate uncertainty

    ranges. The results from the models agreed well with measured data. The simulations

    of Yasso07 and Q resulted in a soil organic carbon stock in year 2000 of

    1600 Mton C and 1580 Mton C, respectively while the measured carbon pool was

    1670 Mton C. The annual change in soil organic carbon varies substantially between

    the three methods mainly due to different assumptions regarding annual

    climate variation. However, the five year averaged mean of annual soil organic

    carbon change for the two periods 1994-1998 and 1996-2000 indicate the size and

    direction of the estimated annual changes agree reasonable well. The mean annual

    change for the two periods was for the Q-model 5.5 Mton C yr

    -1 and 5.6 Mton C yr-

    1

    with a confidence interval of 2.1-10.7 Mton C yr-1, and for the Yasso07-model 3.7

    Mton C yr

    -1 and 0.9 Mton C yr-1 respectively with a confidence interval ranging

    between -5 to 12.6 and -7 to 9.8 Mton C yr

    -1 respectively. The mean annual change

    for the two periods estimated using NFI-data was 1.6 M ton C yr

    -1 and 2.5 M ton C

    yr

    -1 with a standard error of 2 The general conclusion drawn from this study is that

    both sampling and the models Yasso07 and Q are possible tools to predict the soil

    organic carbon accumulation and annual changes for Swedish forest soils. The

    estimates based on measurements as well as the modelled results indicate an increase

    in carbon stocks in Swedish forest soils. This study does not support a

    change of method from inventory to model predictions. However, the agreement

    between the methods shows that the models are suitable as a complement to other

    soil carbon estimation methods. They are particularly useful for projections and we

    recommend a further development of the modelling tools.

1 - 2 of 2
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