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1.
Sci Total Environ ; 846: 157322, 2022 Nov 10.
Article in English | MEDLINE | ID: mdl-35872207

ABSTRACT

Russia has the largest forest area on earth. Its boreal forests officially store about 97 Pg C, which significantly affect the global carbon cycle. In recent years, forest fires have been intensifying on the planet, leading to increased carbon emissions. Here we review how differences in fire control management of Russian forests affect fire related emissions. Carbon emissions due to fire were estimated using satellite data and compared to official reports for 2001-2021. We found that the relative areas affected by fire did differ between different fire protection zones, and 89 % of the area burnt was in forests controlled by fire-fighting aircraft or areas without protection. As a result, 417.7 Mha of poor or unprotected Russian forests (42 % of total) account about a half of total carbon emissions. According to our estimates, the average area of burnt forests in Russia was about 8.3 Mha per year between 2016 and 2021, resulting in annual carbon emission of 193 million metric tons (Mt) C emissions, and 53 % of them were from unprotected forest. These estimated carbon emissions are significantly higher than official national reports (79 Mt C yr-1). We estimated that net carbon uptake for Russia for 2015-2021 was about 333 ± 37 Mt C, which is roughly double the official estimates. Our results highlight large spatial differences in fire protection and prevention strategies in fire related emissions. The so-called control zone which stretches across large parts of Eastern Russia has no fire control and is the region of major recent fires. Our study shows that to estimate the Russian forest carbon balance it is critical to include this area. Implementation of some forest management in the remote areas (i.e., control zone) would help to decrease forest loss and resulting carbon emissions.


Subject(s)
Fires , Wildfires , Carbon , Forests , Taiga
2.
Environ Pollut ; 306: 119324, 2022 Aug 01.
Article in English | MEDLINE | ID: mdl-35513193

ABSTRACT

With increased forest fires due to climate change, PM2.5 emissions also intensified. Record PM2.5 emissions according to Copernicus Atmosphere Monitoring Service in Russia amounted to 8 megatons (Mt) in 2021, which is 78% higher than the average level of 2004-2021 (4.5 Mt). Seven federal subjects (the constituent entities) with vast forest areas without fire protection produced 86% of emissions (6.8 Mt) in 2021, the major losses (6.1 Mt) in Yakutia (Sakha Republic). The ambient temperature in Eastern Siberia is increasing, especially in months of winter and spring seasons (up to +3.6 °C) in 1990-2020 compared to 1901-2020 (CEDA Archive); climate change has affected meteorological conditions leading to increased forest fires. The results of the SARIMAX model study for PM2.5 emissions considering meteorological factors using ERA5 and burnt forest area using MODIS (MCD64A1), establishing a significant dependence of PM2.5 emissions on the lack of precipitation and the associated parameters of complete and potential evaporation. This influence long before the fire season (up to 9 months), as it affects the snow cover and the dryness of the fuel by the beginning of forest fires. In turn, high PM2.5 emission values are accompanied by a drop in 2 m air temperature and surface solar radiation downwards due to the aerosol saturation with suspended particles. The average COR for seven federal subjects was 0.79, with the highest forecast result in Yakutia (0.95), indicating the maximum propensity for record emissions due to weather conditions. In combination with forest management without fire protection, meteorological parameters have caused an increase in PM2.5 emissions in recent years in Siberia. The forest needs other ways to manage under the pressures of climate change to reduce environmental pollution associated with PM2.5 emissions from vast Siberian fires.


Subject(s)
Air Pollutants , Wildfires , Aerosols/analysis , Air Pollutants/analysis , Environmental Monitoring , Humans , Particulate Matter/analysis
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