Future projections of Siberian wildfire and aerosol emissions

Abstract. Wildfires are among the most influential disturbances affecting ecosystem structure and biogeochemical cycles in Siberia. Therefore, accurate fire modeling via dynamic global vegetation models is important for predicting greenhouse gas emissions and other biomass-burning emissions to understand changes in biogeochemical cycles. We integrated the widely used SPread and InTensity of FIRE (SPITFIRE) fire module into the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM) to improve the accuracy of fire predictions and then simulated future fire regimes to better understand their impacts. The model can reproduce the spatiotemporal variation in biomass, fire intensity, and fire-related emissions well compared to the recent satellite-based estimations: aboveground biomass (R2=0.847, RMSE =18.3 Mg ha−1), burned fraction (R2=0.75, RMSE=0.01), burned area (R2=0.609, RMSE =690 ha), dry-matter emissions (R2=0.624, RMSE =0.01 kg DM m−2; dry matter), and CO2 emissions (R2=0.705, RMSE =6.79 Tg). We then predicted that all of the 33 fire-related gas and aerosol emissions would increase in the future due to the enhanced amount of litter as fuel load from increasing forest biomass production under climate forcing of four Representative Concentration Pathways: RCP8.5, RCP6.0, RCP4.5, and RCP2.6. The simulation under RCP8.5 showed that the CO2, CO, PM2.5, total particulate matter (TPM), and total particulate carbon (TPC) emissions in Siberia in the present period (2000–2020) will increase relatively by 189.66±6.55, 15.18±0.52, 2.47±0.09, 1.87±0.06, and 1.30±0.04 Tg species yr−1, respectively, in the future period (2081–2100) and the number of burned trees will increase by 100 %, resulting in a 385.19±40.4 g C m−2 yr−1 loss of net primary production (NPP). Another key finding is that the higher litter moisture by higher precipitation would relatively suppress the increment of fire-related emissions; thus the simulation under RCP8.5 showed the lowest emissions among RCPs. Our study offers insights into future fire regimes and development strategies for enhancing regional resilience and for mitigating the broader environmental consequences of fire activity in Siberia.

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Publication Details

Journal
Biogeosciences
Published
2024-09-26
DOI
https://doi.org/10.5194/bg-21-4195-2024
Citations
5
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
1.41

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article

Future projections of Siberian wildfire and aerosol emissions

Tomomichi Kato, Nicolas Delbart, Lea Végh, Hisashi Sato et al.
5 citations
Biogeosciences
Fire effects on ecosystems
1.41
article

Future projections of Siberian wildfire and aerosol emissions

Tomomichi Kato, Nicolas Delbart, Lea Végh, Hisashi Sato, Hideki Ninomiya, Tatsuya Miyauchi, Reza Kusuma Nurrohman, Tomohiro Shiraishi, Ryuichi Hirata
article en
5 citations

Abstract

Abstract. Wildfires are among the most influential disturbances affecting ecosystem structure and biogeochemical cycles in Siberia. Therefore, accurate fire modeling via dynamic global vegetation models is important for predicting greenhouse gas emissions and other biomass-burning emissions to understand changes in biogeochemical cycles. We integrated the widely used SPread and InTensity of FIRE (SPITFIRE) fire module into the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM) to improve the accuracy of fire predictions and then simulated future fire regimes to better understand their impacts. The model can reproduce the spatiotemporal variation in biomass, fire intensity, and fire-related emissions well compared to the recent satellite-based estimations: aboveground biomass (R2=0.847, RMSE =18.3 Mg ha−1), burned fraction (R2=0.75, RMSE=0.01), burned area (R2=0.609, RMSE =690 ha), dry-matter emissions (R2=0.624, RMSE =0.01 kg DM m−2; dry matter), and CO2 emissions (R2=0.705, RMSE =6.79 Tg). We then predicted that all of the 33 fire-related gas and aerosol emissions would increase in the future due to the enhanced amount of litter as fuel load from increasing forest biomass production under climate forcing of four Representative Concentration Pathways: RCP8.5, RCP6.0, RCP4.5, and RCP2.6. The simulation under RCP8.5 showed that the CO2, CO, PM2.5, total particulate matter (TPM), and total particulate carbon (TPC) emissions in Siberia in the present period (2000–2020) will increase relatively by 189.66±6.55, 15.18±0.52, 2.47±0.09, 1.87±0.06, and 1.30±0.04 Tg species yr−1, respectively, in the future period (2081–2100) and the number of burned trees will increase by 100 %, resulting in a 385.19±40.4 g C m−2 yr−1 loss of net primary production (NPP). Another key finding is that the higher litter moisture by higher precipitation would relatively suppress the increment of fire-related emissions; thus the simulation under RCP8.5 showed the lowest emissions among RCPs. Our study offers insights into future fire regimes and development strategies for enhancing regional resilience and for mitigating the broader environmental consequences of fire activity in Siberia.

BiogeosciencesVol. 21(18)
Centre National de la Recherche Scientifique (FR), Japan Agency for Marine-Earth Science and Technology (JP), University of Mataram (ID), National Institute for Environmental Studies (JP), Hokkaido University (JP), Nippon Bunri University (JP), Laboratoire Interdisciplinaire des Énergies de Demain (FR), Universitas Nusa Tenggara Barat (ID)
Japan Society for the Promotion of Science, Japan Agency for Marine-Earth Science and Technology
Climate action
Openalex Percentile: Top 19%
Fire effects on ecosystems
1.41
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