Addressing Peatland Rewetting in Russian Federation Climate Reporting

Rewetting is the most effective way to reduce greenhouse gas (GHG) emissions from drained peatlands and must significantly contribute to the implementation of the Paris Agreement on Climate within the land sector. In 2010–2013, more than 73 thousand hectares of fire-prone peatlands were rewetted in...

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Autores principales: Andrey Sirin, Maria Medvedeva, Vladimir Korotkov, Victor Itkin, Tatiana Minayeva, Danil Ilyasov, Gennady Suvorov, Hans Joosten
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/5cdf22cb06124af696f8f2cbee5d4352
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Sumario:Rewetting is the most effective way to reduce greenhouse gas (GHG) emissions from drained peatlands and must significantly contribute to the implementation of the Paris Agreement on Climate within the land sector. In 2010–2013, more than 73 thousand hectares of fire-prone peatlands were rewetted in the Moscow Region (the hitherto largest rewetting program in the Northern Hemisphere). As the Russian Federation has no national accounting of rewetted areas yet, this paper presents an approach to detect them based on multispectral satellite data verified by ground truthing. We propose that effectively rewetted areas should minimally include areas with wet grasslands and those covered with water (cf. the IPCC categories “rewetted organic soils” and “flooded lands”). In 2020, these lands amounted in Moscow Region to more than 5.3 and 3.6 thousand hectares, respectively. Assuming that most rewetted areas were former peat extraction sites and using IPCC default GHG emission factors, an overall GHG emission reduction of over 36,000 tCO<sub>2</sub>-eq year<sup>−1</sup> was calculated. We furthermore considered the uncertainty of calculations. With the example of a 1535 ha large rewetted peatland, we illustrate the estimation of GHG emission reductions for the period up to 2050. The approach presented can be used to estimate GHG emission reductions by peatland rewetting on the national, regional, and object level.