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11.B - Forest Fires

Short Description

In Germany’s forests prescribed burning is not applied. Therefore, all forest fires are categorized as wildfires (include emissions from forest fires occurring naturally or caused by humans). - Note that emissions reported here are not accounted for the national totals.

Method AD EF Key Category
CS, T2, T1 CS D not included in key category analysis

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Legend T = key source by Trend / L = key source by Level


Methods D: Default RA: Reference Approach T1: Tier 1 / Simple Methodology * T2: Tier 2* T3: Tier 3 / Detailed Methodology * C: CORINAIR CS: Country Specific M: Model as described in the EMEP/CORINAIR Emission Inventory Guidebook - 2019, in the group specific chapters.


AD:- Data Source for Activity Data NS: National Statistics RS: Regional Statistics IS: International Statistics PS: Plant Specific data AS: Associations, business organisations Q: specific questionnaires, surveys


EF - Emission Factors D: Default (EMEP Guidebook) C: Confidential CS: Country Specific PS: Plant Specific data


Methodology

For calculating the emissions of wildfires a country specific Tier2 approach was used. The mass of carbon emitted M(C) was calculated using the adapted equation follows the methodology of Seiler and Crutzen (1980) 1).

M(C) = 0.45 * A * B * β

where:

0.45 = average fraction of carbon in fuel wood;

A = forest area burnt in [m²];

B = mean above-ground biomass of fuel material per unit area in [kg/m²];

β = burning efficiency (fraction burnt) of the above-ground biomass.

The data on forest areas burnt for the period 1990 to 2021 have been taken from the German forest fire statistic (BLE, 2022)2) managed by the Federal Agency for Agriculture and Food. The mean above-ground biomass of fuel material was determined from the pools above ground biomass, dead wood and litter. The mean above-ground biomass and dead wood biomass was derived for each year by linear extrapolation and interpolation between the

Biomass of Litter was derived for each year by linear interpolation between 1990 and 2006 and extrapolation from 2007 based on the both Forest soil inventories (BZE I Wald (1990)3) and BZE II Wald (2006)4)).

Pursuant to König (2007) 5), 80% of the forest fires in Germany are surface fires and 20% crown fires. In accordance to the IPCC Good Practice Guidance for LULUCF (2003) a burning efficiency of 0.15 was used for surface fires and an efficiency of 0.45 was used for crown fires.

The emissions for the pollutants were calculated by multiplying the mass of carbon with the respective emission factors from table 3-3 (EMEP/EEA, 2019)6).

For the calculation of particulate emissions (TSP, PM10 and PM2.5) the burnt biomass was multiplied with the respective emission factors from table 3-5 (EMEP/EEA, 2019). Those particulate emission factors have been estimated by averaging the emission factors from the US Environmental Protection Agency (USEPA, 1996) 7) methodology, since no better information is available. Those emission factors are assumed to be the same for all types of forest.

The Guidebook does not indicate whether EFs have considered the condensable component (with or without).

Activity data

The data on forest areas burnt for the period 1990 to 2021 are based on the German forest fire statistic (BLE, 2021) managed by the Federal Agency for Agriculture and Food.

Table 1: Area of forest burnt from 1990 until the latest reporting year, in [ha]

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
1,606 920 4,908 1,493 1,114 592 1,381 599 397 415
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
581 122 122 1,315 274 183 482 256 539 757
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
522 214 269 199 120 526 283 395 2,349 2,711
2020 2021
368 148

Emission factors

For the year 2021 the follwing estimated emission factors were applied:

Table 2: Emission factors applied for 2021

EF2021
NOx 155.19
CO 5,535.19
NMVOC 488.86
SOx 37.25
NH3 41.9
TSP 879.42
PM10 569.04
PM2.5 465.58
BC 41.90

In addition, a single but large-scale fire, which occurred in September 2018, is reported under here. A detailed description can be found in the NIR 2020 in Chapter 6.8.2.5 8), because a large amount of CO2 emissions were released.

The burned area of the drained moor used as a military facility covered 1,221 ha. The fire was extensively investigated and documented by the Federal Office for Infrastructure, Environmental Protection and Services of the German Armed Forces. The emissions are calculated according to IPCC GL (2006), chapter 2, form 2.27 9).

The product MB × Cf is set to 336 t d.m. ha-1 according to Table 2.6 and equation 2.7, 2013 IPCC Wetlands Supplement 10), i.e. it is assumed that the moor was completely drained during the fire.

  • MB = mass of fuel available for combustion, tonnes ha-1 (i.e. mass of dry organic soil fuel)
  • Cf = combustion factor, dimensionless

For calculating CO emissions, the EF according to Table 2.7, 2013 IPCC Wetlands Supplement 207 g (kg dm)-1, is taken into account, resulting in 85 kt CO.

Recalculations

Recalculations were made for the complete time series due to the methodology changes (the inclusion of the burning biomass of dead wood and litter, which has not been considered until now). No recalculation was made for the large-scale fire in 2018.

Table 3: Recalculation of air pollutant emisssions from 1990 until the latest reported year, in [kt]

1990 1995 2000 2005 2010 2015 2016 2017 2018 2019 2020
Black Carbon (BC)
current submission 0.061 0.022 0.022 0.007 0.020 0.021 0.011 0.016 0.096 0.112 0.015
previous submission 0.047 0.017 0.017 0.005 0.016 0.017 0.009 0.013 0.078 0.091 0.013
absolute change 0.014 0.005 0.005 0.001 0.004 0.004 0.002 0.003 0.018 0.020 0.003
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Carbon monoxide
current submission 8.043 2.949 2.879 0.911 2.641 2.771 1.506 2.114 12.684 14.762 2.019
previous submission 6.165 2.284 2.253 0.722 2.125 2.257 1.228 1.724 10.357 12.067 1.652
absolute change 1.878 0.665 0.627 0.189 0.515 0.515 0.278 0.390 2.327 2.695 0.367
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Ammonia
current submission 0.061 0.022 0.022 0.007 0.020 0.021 0.012 0.016 0.098 0.112 0.015
previous submission 0.047 0.017 0.017 0.005 0.016 0.017 0.009 0.013 0.078 0.091 0.013
absolute change 0.014 0.005 0.005 0.001 0.004 0.004 0.002 0.003 0.020 0.020 0.003
relative change 30.0% 28.7% 27.7% 26.8% 27.2% 25.8% 25.5% 25.7% 25.5% 22.3% 22.2%
Non-Methane Volatile Organic Compounds (NMVOC)
current submission 0.710 0.260 0.254 0.080 0.233 0.245 0.133 0.187 1.120 1.304 0.178
previous submission 0.545 0.202 0.199 0.064 0.188 0.199 0.108 0.152 0.915 1.066 0.146
absolute change 0.166 0.059 0.055 0.017 0.046 0.045 0.025 0.034 0.205 0.238 0.032
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Nitrogen oxides
current submission 0.226 0.083 0.081 0.026 0.074 0.078 0.042 0.059 0.356 0.414 0.057
previous submission 0.173 0.064 0.063 0.020 0.060 0.063 0.034 0.048 0.290 0.338 0.046
absolute change 0.053 0.019 0.018 0.005 0.014 0.014 0.008 0.011 0.065 0.076 0.010
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Particulate Matter <10µm (PM10)
current submission 0.827 0.303 0.296 0.094 0.271 0.285 0.155 0.217 1.304 1.518 0.208
previous submission 0.634 0.235 0.232 0.074 0.218 0.232 0.126 0.177 1.065 1.241 0.170
absolute change 0.193 0.068 0.064 0.019 0.053 0.053 0.029 0.040 0.239 0.277 0.038
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Particulate Matter <2.5µm (PM2.5)
current submission 0.677 0.248 0.242 0.077 0.222 0.233 0.127 0.178 1.067 1.242 0.170
previous submission 0.519 0.192 0.189 0.061 0.179 0.190 0.103 0.145 0.871 1.015 0.139
absolute change 0.158 0.056 0.053 0.016 0.043 0.043 0.023 0.033 0.196 0.227 0.031
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Sulphur dioxide
current submission 0.054 0.020 0.019 0.006 0.018 0.019 0.010 0.014 0.085 0.099 0.014
previous submission 0.041 0.015 0.015 0.005 0.014 0.015 0.008 0.012 0.070 0.081 0.011
absolute change 0.013 0.004 0.004 0.001 0.003 0.003 0.002 0.003 0.016 0.018 0.002
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
Total suspended particles (TSP)
current submission 1.278 0.469 0.457 0.145 0.420 0.440 0.239 0.336 2.015 2.345 0.321
previous submission 0.980 0.363 0.358 0.115 0.338 0.359 0.195 0.274 1.646 1.917 0.262
absolute change 0.298 0.106 0.100 0.030 0.082 0.082 0.044 0.062 0.370 0.428 0.058
relative change 30.5% 29.1% 27.8% 26.3% 24.2% 22.8% 22.7% 22.6% 22.5% 22.3% 22.2%
1)
Seiler, Wolfgang, and Paul J. Crutzen. “Estimates of gross and net fluxes of carbon between the biosphere and the atmosphere from biomass burning.” Climatic change 2.3 (1980): 207-247.
2)
BLE (Bundesanstalt für Landwirtschaft und Ernährung), (2022, 30. Juni), 2022: Waldbrandstatistik der Bundesrepublik Deutschland für das Jahr 2021, Bonn: 21 p. Retrieved July 2022, https://www.ble.de/DE/BZL/Daten-Berichte/Wald/wald_node.html
3)
WOLFF, B. & RIEK, W. (1997): Deutscher Waldbodenbericht 1996 - Ergebnisse der bundesweiten Bodenzustandserhebung in Wald (BZE) 1987 - 1993. Hrsg.: Bundesministerium für Ernährung, Landwirtschaft und Forsten, Bonn, Bd. 1 u. 2., 144 S.,https://www.bmel-statistik.de/fileadmin/daten/FHB-0320205-1996.pdf
4)
WELLBROCK , N., AYDIN, C.-T., BLOCK, J., BUSSIAN, B., DECKERT, M., DIEKMANN, O., EVERS, J., FETZER, K. D., GAUER, J., GEHRMANN, J., KÖLLING, C., KÖNIG, N., LIESEBACH, M., MARIN, J., MEIWES, K. J., MILBERT, G., RABEN, G., RIEK, W., SCHÄFFER, W., SCHWERHOFF, J., ULLRICH, T., UTERMANN, J., VOLZ, H.-A., WEIGEL, A. & WOLFF, B. (2006): Bodenzustandserhebung im Wald (BZE II) Arbeitsanleitung für die Außenaufnahmen. Bundesministerium für Ernährung, Landwirtschaft und Verbraucherschutz, Berlin, 413 S. https://www.bmel.de/DE/themen/wald/wald-in-deutschland/bodenzustandserhebung.html
5)
König, H.-C., 2007. Waldbrandschutz - Kompendium für Forst und Feuerwehr. 1. Fachverlag Matthias Grimm, Berlin, 197 S.
7)
USEPA, 1996: Compilation of Air Pollutant Emission Factors Vol.1. Stationary, Point and Area Sources. Report AP-42, fifth edition
8)
NIR (2020): National Inventory Report 2020 for the German Greenhouse Gas Inventory 1990-2018. Available in April 2020
9)
IPCC (Intergovernmental Panel on Climate Change) (2006): 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry and Other Land Use. Eds.: Eggleston S., Buendia L., Miwa K., Ngara T., Tanabe K. (Eds). IEA/OECD, IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit, Hayama, Kanagawa, Japan. http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html
10)
IPCC (Intergovernmental Panel on Climate Change) (2014b): 2013 Supplement to the IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands. Hiraishi, T., Krug, T., Tanabe, K., Srivastava, N., Baasansuren, J., Fukuda, M. and Troxler, T.G.(eds). Published: IPCC, Switzerland http://www.ipcc-nggip.iges.or.jp/public/wetlands/index.html