Global spatially explicit CO2 emission metrics at 0.25° horizontal resolution for forest bioenergy

Abstract:

Bioenergy is the most important renewable energy option in studies designed to align with future RCP projections, reaching approximately 250 EJ/yr in RCP2.6, 145 EJ/yr in RCP4.5 and 180 EJ/yr in RCP8.5 by the end of the 21^st century. However, many questions enveloping the direct carbon cycle and climate response to bioenergy remain partially unexplored. Bioenergy systems are largely assessed under the default climate neutrality assumption and the time lag between CO₂ emissions from biomass combustion and CO₂ uptake by vegetation is usually ignored. Emission metrics of CO₂ from forest bioenergy are only available on a case-specific basis and their quantification requires processing of a wide spectrum of modelled or observed local climate and forest conditions. On the other hand, emission metrics are widely used to aggregate climate impacts of greenhouse gases to common units such as CO₂-equivalents (CO₂-eq.), but a spatially explicit analysis of emission metrics with global forest coverage is today lacking. Examples of emission metrics include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Here, we couple a global forest model, a heterotrophic respiration model, and a global climate model to produce global spatially explicit emission metrics for CO₂ emissions from forest bioenergy. We show their applications to global emissions in 2015 and until 2100 under the different RCP scenarios. We obtain global average values of 0.49 ± 0.03 kgCO₂-eq. kgCO₂^-1 (mean ± standard deviation), 0.05 ± 0.05 kgCO₂-eq. kgCO₂^-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr^-1)^-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr^-1)^-1 for GWP, GTP and aSET, respectively. We also present results aggregated at a grid, national and continental level. The metrics are found to correlate with the site-specific turnover times and local climate variables like annual mean temperature and precipitation. Simplified equations are derived to infer metric values from the turnover time of the biomass feedstock and the fraction of forest residues left on site after harvest. Our results provide a basis for assessing CO₂ emissions from forest bioenergy under different indicators and across various spatial and temporal scales.