Classification of MODIS fire emission data based on aerosol absorption Angstrom exponent retrieved from AERONET data.

Biomass burning emits a large quantity of gaseous pollutants and aerosols into the atmosphere, which perturbs the regional and global climate and has significant impacts on air quality and human health. In order to understand the temporal and spatial distributions of biomass burning and its contribution to aerosol optical and radiative impacts, we examined fire emission data and its contribution to aerosol optical and radiative impacts over six major hot-spot continents/sub-continents across the globe, namely North-Central (NC) Africa, South America, US-Hawaii, South Asia, South East Asia, and Australia-New Zealand, using long-term satellites, ground-based and re-analysis data during 2000-2021. The selected six sites contributed ∼70% of total global fire data. The classification of biomass burning, such as pre, active, and post burning phases, was performed based on the Absorption Angstrom Exponent (AAE) estimated from 55 AERONET (AErosol RObotic NETwork) stations. The study found the highest contribution of fire count (55 %) during the active burning phase followed by post (36 %) and pre (8 %) burning phases. Such high fire counts were associated with high absorption aerosol optical depth (AAOD) during the active fire event. Strong dominance of fine and coarse mode mixed aerosols were also observed during active and post fire regimes. High AAOD and low Extinction Angstrom Exponent (EAE) over NC Africa during the fire events suggested presence of mineral dust mixed with biomass burning aerosols. Brightness temperature, fire radiative power and fire count were also dominated by the active burning followed by post and pre burning phases. The maximum heating rate of 3.15 K day-1 was observed during the active fire events. The heating rate profile shows clear variations for three different fire regimes with the highest value of 1.80 K day-1 at ∼750 hPa altitude during the active fire event.

Anthropogenic aerosol drives uncertainty in future climate mitigation efforts.

The 2016 Paris agreement set a global mean surface temperature (GMST) goal of not more than 2 degrees Celsius above preindustrial. This is an ambitious goal that will require substantial decreases in emission rates of long-lived greenhouse gasses (GHG). This work provides a mathematical framework, based on current state of the art climate models, to calculate the GHG emissions consistent with prescribed GMST pathways that meet the Paris agreement goal. The unique capability of this framework, to start from a GMST timeseries and efficiently calculate the emissions required to meet that temperature pathway, makes it a powerful resource for policymakers. Our results indicate that aerosol emissions play a large role in determining the near-term allowable greenhouse gas emissions that will limit future warming to 2 °C, however in the long term, drastic GHG emissions reductions are required under any reasonable aerosol scenario. With large future aerosol emissions, similar to present day amounts, GHG emissions need to be reduced 8% by 2040 and 74% by 2100 to limit warming to 2 °C. Under a more likely low aerosol scenario, GHG emissions need to be reduced 36% and 80% by 2040 and 2100, respectively. The Paris agreement Intended Nationally Determined Contributions are insufficient to meet this goal.