A new methodology for organic soils in national greenhouse gas inventories: Data synthesis, derivation and application

被引:118
作者
Tiemeyer, Baerbel [1 ]
Freibauer, Annette [1 ,8 ]
Borraz, Elisa Albiac [2 ]
Augustin, Juergen [2 ]
Bechtold, Michel [1 ,9 ,10 ]
Beetz, Sascha [3 ]
Beyer, Colja [4 ,11 ]
Ebli, Martin [5 ]
Eickenscheidt, Tim [6 ]
Fiedler, Sabine [5 ,7 ]
Foerster, Christoph [6 ]
Gensior, Andreas [1 ]
Giebels, Michael [2 ]
Glatzel, Stephan [3 ,12 ]
Heinichen, Jan [6 ]
Hoffmann, Mathias [2 ]
Hoeper, Heinrich [4 ]
Jurasinski, Gerald [3 ]
Laggner, Andreas [1 ]
Leiber-Sauheitl, Katharina [1 ,13 ]
Peichl-Brak, Mandy [7 ]
Droesler, Matthias [6 ]
机构
[1] Thunen Inst Climate Smart Agr, D-38116 Braunschweig, Germany
[2] Leibniz Ctr Agr Landscape Res, Inst Landscape Biogeochem, D-15374 Muncheberg, Germany
[3] Rostock Univ, Fac Agr & Environm Sci, D-18059 Rostock, Germany
[4] State Author Min Energy & Geol Lower Saxony, D-30655 Hannover, Germany
[5] Johannes Gutenberg Univ Mainz, Inst Geog, D-55099 Mainz, Germany
[6] Univ Appl Sci Weihenstephan Triesdorf, Chair Vegetat Ecol, D-85354 Freising Weihenstephan, Germany
[7] Univ Hohenheim, Inst Soil Sci & Land Evaluat, D-70593 Stuttgart, Germany
[8] Bavarian State Res Ctr Agr, Inst Organ Farming Soil & Resource Management, D-85354 Freising Weihenstephan, Germany
[9] Katholieke Univ Leuven, Dept Earth & Environm Sci, B-3001 Heverlee, Belgium
[10] Katholieke Univ Leuven, Dept Comp Sci, B-3001 Heverlee, Belgium
[11] 3N Lower Saxony Network Renewable Resourc, Werlte, Germany
[12] Univ Vienna, Fac Geosci Geog & Astron, A-1090 Vienna, Austria
[13] Leibniz Univ Hannover, Inst Soil Sci, D-30419 Hannover, Germany
关键词
Peatland; MRV; Drainage; Rewetting; mitigation measures; Greenhouse gases; LAND-USE; CO2; FLUXES; METHANE EMISSIONS; CARBON; PEATLANDS; FEN; N2O; DYNAMICS; DRAINAGE; BALANCE;
D O I
10.1016/j.ecolind.2019.105838
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Drained organic soils are large sources of anthropogenic greenhouse gases (GHG) in many European and Asian countries. Therefore, these soils urgently need to be considered and adequately accounted for when attempting to decrease emissions from the Agriculture and Land Use, Land Use Change and Forestry (LULUCF) sectors. Here, we describe the methodology, data and results of the German approach for measurement, reporting and verification (MRV) of anthropogenic GHG emissions from drained organic soils and outline ways forward towards tracking drainage and rewetting. The methodology was developed for and is currently applied in the German GHG inventory under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. Spatial activity data comprise high resolution maps of land-use, type of organic soil and mean annual water table (WT). The WT map was derived by a boosted regression trees model from data of more than 1000 dipwells. Emissions of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) were synthesized from a unique national data set comprising more than 250 annual GHG balances from 118 sites in most land-use categories and types of organic soils. Measurements were performed with harmonized protocols using manual chambers. Nonlinear response functions describe the dependency of CO2 and CH4 fluxes on mean annual WT, stratified by land-use where appropriate. Modelling results were aggregated into "implied emission factors" for each land-use category, taking into account the uncertainty of the response functions, the frequency distribution of the WT within each land-use category and further GHG sources such as dissolved organic carbon or CH4 emissions from ditches. IPCC default emission factors were used for these minor GHG sources. In future, response functions could be applied directly when appropriate WT data is available. As no functional relationship was found for N2O emissions, emission factors were calculated as the mean observed flux per land-use category. In Germany, drained organic soils emit more than 55 million tons of GHGs per year, of which 91% are CO2. This is equivalent to around 6.6% of the national GHG emissions in 2014. Thus, they are the largest GHG source from agriculture and LULUCF. The described methodology is applicable on the project scale as well as in other countries where similar data are collected.
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