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--- sector:other_and_natural_sources:forest_fires [2022/11/09 12:50] – [Methodology] doering
+++ sector:other_and_natural_sources:forest_fires [2023/07/05 12:22] (current) – removed kotzulla
@@ Line 1: / Line 1: @@
-====== 11 - Natural Sources =======
-===== 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//  |
-<hidden>
-----
-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</hidden>
-----
-==== 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) ((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.)).
-{{ :sector:natural_sources:forest_fire.png?nolink&400}}
-//M(C) = 0.45 * A * B * β//
-where:
-.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)((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)) 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
-     * German National Forest Inventories of 1987, 2002, 2012 (Bundeswaldinventuren 1987, 2002, 2012),
-     * [[https://www.thuenen.de/en/institutes/forest-ecosystems/projects/forest-monitoring/greenhouse-gas-inventory-for-forests/inventory-study-2008|the inventory study 2008]]  and,
-     * [[https://www.thuenen.de/en/institutes/forest-ecosystems/projects/forest-monitoring/greenhouse-gas-inventory-for-forests/carbon-inventory-2017|the carbon inventory 2017]].
-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)((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]])) and BZE II Wald (2006)((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]]))).
-Pursuant to König (2007) ((König, H.-C., 2007. Waldbrandschutz - Kompendium für Forst und Feuerwehr. 1. Fachverlag Matthias Grimm, Berlin, 197 S.)), 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)((EMEP/EEA, 2019: https://www.eea.europa.eu/publications/emep-eea-guidebook-2019/part-b-sectoral-guidance-chapters/11-natural-sources/11-b-forest-fires/view)).
-For the calculation of particulate emissions (TSP, PM<sub>10</sub> and PM<sub>2.5</sub>) 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) ((USEPA, 1996: Compilation of Air Pollutant Emission Factors Vol.1. Stationary, Point and Area Sources. Report AP-42, fifth edition)) 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  ^  2000  ^
-| Area of forest burnt  |   1606 |    920 |   4908 |   1493 |   1114 |    592 |   1381 |    599 |    397 |    415 |    581 |
-^                       ^  2001  ^  2002  ^  2003  ^  2004  ^  2005  ^  2006  ^  2007  ^  2008  ^  2009  ^  2010  ^  2011  ^
-| Area of forest burnt  |    122 |    122 |   1315 |    274 |    183 |    482 |    256 |    539 |    757 |    522 |    214 |
-^                       ^  2012  ^  2013  ^  2014  ^  2015  ^  2016  ^  2017  ^  2018  ^  2019  ^ 2020  ^ 2021  ^
-| Area of forest burnt  |    269 |    199 |    120 |    526 |    283 |    395 |   2349 |   2711 |   368 |   148 |
-=== Emission factors ===
-For the year 2021 the estimated emission factors from table 2 were applied.
-__Table 2: Emission factors applied for 2021__
-^ Pollutant         ^ EF<sub>2021</sub>  ^
-| NO<sub>x</sub>    |             155.19 |
-| CO                |           5,535.19 |
-| NMVOC             |             488.86 |
-| SO<sub>x</sub>    |              37.25 |
-| NH<sub>3</sub>    |               41.9 |
-| TSP               |             879.42 |
-| PM<sub>10</sub>   |             569.04 |
-| PM<sub>2.5</sub>  |             465.58 |
-| BC                |              41.90 |
-In addition, a large-scale fire, which occurred in September 2018, is reported under 11.B. A detailed description can be found in the NIR
-in Chapter 6.8.2.5 ((NIR (2020): National Inventory Report 2020 for the German Greenhouse Gas Inventory 1990-2018. Available in April 2020)), because a large amount of CO<sub>2</sub> emissions were released.
-The burned area of the drained moor, which is used as a military facility, covered 1,221 ha. This 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 ((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)).
-The product MB×Cf is set to 336 t dm ha<sup>-1</sup> according to Table 2.6 and formula 2.7, 2013 IPCC Wetlands Supplement ((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)), i.e. it is assumed that the moor was completely drained during the fire.
-For the calculation of CO emissions the EF according to Table 2.7, 2013 IPCC Wetlands Supplement 207 g (kg dm)<sup>-1</sup>, is taken into account. This results in 85 kt CO. For other emissions from land fires on drained organic soils no Tier-1 emission factors exist and are therefore not reported (NO).
-=== Recalculation ===
-^ Pollutant     ^ Submission  | Unit  | 1990   | 1995   | 2000   | 2005   | 2010   | 2015   | 2016   | 2017   | 2018    | 2019    | 2020   |
-| Black Carbon  | Sub 2023    | kt    | 0,061  | 0,022  | 0,022  | 0,007  | 0,020  | 0,021  | 0,011  | 0,016  | 0,096   | 0,112   | 0,015  |
-| Black Carbon  | Sub 2022    | kt    | 0,047  | 0,017  | 0,017  | 0,005  | 0,016  | 0,017  | 0,009  | 0,013  | 0,078   | 0,091   | 0,013  |
-| Black Carbon  | Difference  | kt    | 0,014  | 0,005  | 0,005  | 0,001  | 0,004  | 0,004  | 0,002  | 0,003  | 0,018   | 0,020   | 0,003  |
-| Black Carbon  | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| CO            | Sub 2023    | kt    | 8,043  | 2,949  | 2,879  | 0,911  | 2,641  | 2,771  | 1,506  | 2,114  | 12,684  | 14,762  | 2,019  |
-| CO            | Sub 2022    | kt    | 6,165  | 2,284  | 2,253  | 0,722  | 2,125  | 2,257  | 1,228  | 1,724  | 10,357  | 12,067  | 1,652  |
-| CO            | Difference  | kt    | 1,878  | 0,665  | 0,627  | 0,189  | 0,515  | 0,515  | 0,278  | 0,390  | 2,327   | 2,695   | 0,367  |
-| CO            | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| NH3           | Sub 2023    | kt    | 0,061  | 0,022  | 0,022  | 0,007  | 0,020  | 0,021  | 0,012  | 0,016  | 0,098   | 0,112   | 0,015  |
-| NH3           | Sub 2022    | kt    | 0,047  | 0,017  | 0,017  | 0,005  | 0,016  | 0,017  | 0,009  | 0,013  | 0,078   | 0,091   | 0,013  |
-| NH3           | Difference  | kt    | 0,014  | 0,005  | 0,005  | 0,001  | 0,004  | 0,004  | 0,002  | 0,003  | 0,020   | 0,020   | 0,003  |
-| NH3           | Difference  | %     | 30,0%  | 28,7%  | 27,7%  | 26,8%  | 27,2%  | 25,8%  | 25,5%  | 25,7%  | 25,5%   | 22,3%   | 22,2%  |
-| NMVOC         | Sub 2023    | kt    | 0,710  | 0,260  | 0,254  | 0,080  | 0,233  | 0,245  | 0,133  | 0,187  | 1,120   | 1,304   | 0,178  |
-| NMVOC         | Sub 2022    | kt    | 0,545  | 0,202  | 0,199  | 0,064  | 0,188  | 0,199  | 0,108  | 0,152  | 0,915   | 1,066   | 0,146  |
-| NMVOC         | Difference  | kt    | 0,166  | 0,059  | 0,055  | 0,017  | 0,046  | 0,045  | 0,025  | 0,034  | 0,205   | 0,238   | 0,032  |
-| NMVOC         | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| NOx           | Sub 2023    | kt    | 0,226  | 0,083  | 0,081  | 0,026  | 0,074  | 0,078  | 0,042  | 0,059  | 0,356   | 0,414   | 0,057  |
-| NOx           | Sub 2022    | kt    | 0,173  | 0,064  | 0,063  | 0,020  | 0,060  | 0,063  | 0,034  | 0,048  | 0,290   | 0,338   | 0,046  |
-| NOx           | Difference  | kt    | 0,053  | 0,019  | 0,018  | 0,005  | 0,014  | 0,014  | 0,008  | 0,011  | 0,065   | 0,076   | 0,010  |
-| NOx           | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| PM 10         | Sub 2023    | kt    | 0,827  | 0,303  | 0,296  | 0,094  | 0,271  | 0,285  | 0,155  | 0,217  | 1,304   | 1,518   | 0,208  |
-| PM 10         | Sub 2022    | kt    | 0,634  | 0,235  | 0,232  | 0,074  | 0,218  | 0,232  | 0,126  | 0,177  | 1,065   | 1,241   | 0,170  |
-| PM 10         | Difference  | kt    | 0,193  | 0,068  | 0,064  | 0,019  | 0,053  | 0,053  | 0,029  | 0,040  | 0,239   | 0,277   | 0,038  |
-| PM 10         | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| PM 2.5        | Sub 2023    | kt    | 0,677  | 0,248  | 0,242  | 0,077  | 0,222  | 0,233  | 0,127  | 0,178  | 1,067   | 1,242   | 0,170  |
-| PM 2.5        | Sub 2022    | kt    | 0,519  | 0,192  | 0,189  | 0,061  | 0,179  | 0,190  | 0,103  | 0,145  | 0,871   | 1,015   | 0,139  |
-| PM 2.5        | Difference  | kt    | 0,158  | 0,056  | 0,053  | 0,016  | 0,043  | 0,043  | 0,023  | 0,033  | 0,196   | 0,227   | 0,031  |
-| PM 2.5        | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| SO2           | Sub 2023    | kt    | 0,054  | 0,020  | 0,019  | 0,006  | 0,018  | 0,019  | 0,010  | 0,014  | 0,085   | 0,099   | 0,014  |
-| SO2           | Sub 2022    | kt    | 0,041  | 0,015  | 0,015  | 0,005  | 0,014  | 0,015  | 0,008  | 0,012  | 0,070   | 0,081   | 0,011  |
-| SO2           | Difference  | kt    | 0,013  | 0,004  | 0,004  | 0,001  | 0,003  | 0,003  | 0,002  | 0,003  | 0,016   | 0,018   | 0,002  |
-| SO2           | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |
-| STB           | Sub 2023    | kt    | 1,278  | 0,469  | 0,457  | 0,145  | 0,420  | 0,440  | 0,239  | 0,336  | 2,015   | 2,345   | 0,321  |
-| STB           | Sub 2022    | kt    | 0,980  | 0,363  | 0,358  | 0,115  | 0,338  | 0,359  | 0,195  | 0,274  | 1,646   | 1,917   | 0,262  |
-| STB           | Difference  | kt    | 0,298  | 0,106  | 0,100  | 0,030  | 0,082  | 0,082  | 0,044  | 0,062  | 0,370   | 0,428   | 0,058  |
-| STB           | Difference  | %     | 30,5%  | 29,1%  | 27,8%  | 26,3%  | 24,2%  | 22,8%  | 22,7%  | 22,6%  | 22,5%   | 22,3%   | 22,2%  |

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