BVOC-aerosol-climate interactions in the global aerosol-climate model ECHAM5.5-HAM2

Abstract

The biosphere emits volatile organic compounds (BVOCs) which, after oxidation in the atmosphere, can partition on the existing aerosol population or even form new particles. The large quantities emitted provide means for a large potential impact on both aerosol direct and indirect effects. Biogenic responses to atmospheric temperature change can establish feedbacks even in rather short timescales. However, due to the complexity of organic aerosol partitioning, even the sign of these feedbacks is of large uncertainty. We use the global aerosol-climate model ECHAM5.5-HAM2 to explore the effect of BVOC emissions on new particle formation, clouds and climate. Two BVOC emission models, MEGAN2 and LPJ-GUESS, are used. MEGAN2 shows a 25% increase while LPJ-GUESS shows a slight decrease in global BVOC emission between years 2000 and 2100. The change of shortwave cloud forcing from year 1750 to 2000 ranges from −1.4 to −1.8 W m<sup>−2</sup> with 5 different nucleation mechanisms. We show that the change in shortwave cloud forcing from the year 2000 to 2100 ranges from 1.0 to 1.5 W m<sup>−2</sup>. Although increasing future BVOC emissions provide 3–5% additional CCN, the effect on the cloud albedo change is modest. Due to simulated decreases in future cloud cover, the increased CCN concentrations from BVOCs can not provide significant additional cooling in the future

Semi-empirical parameterization of size-dependent atmospheric nanoparticle growth in continental environments

“…The volatility assumed for the SOA in atmospheric models significantly affects the way this condensing material modifies the atmospheric aerosol size distribution (see, e.g., Riipinen et al, 2011;Donahue et al, 2011;Zhang et al, 2012b). Current atmospheric large-scale models differ considerably in the ways they treat the condensation of SOA: some assign the SOA a range of volatilities but assume it to be in thermodynamic equilibrium (Yu and Luo, 2009), while others assume the SOA to be completely nonvolatile (Spracklen et al, 2005a, b;Pierce and Adams, 2009;Makkonen et al, 2012). The former approach tends to underestimate the growth of freshly-formed nanoparticles (and thus their contribution to CCN), while the latter is expected to somewhat overpredict it if the total SOA is correctly predicted by the model .…”

Temperature influence on the natural aerosol budget over boreal forests

“…The BSOA affects climate directly by scattering solar radiation and indirectly by aerosolcloud interactions (e.g. Makkonen et al, 2012). The latter effect is tied strongly with atmospheric cloud condensation nuclei (CCN) production, and thereby also with atmospheric new particle formation and growth Yu, 2011;Kerminen et al, 2012;Makkonen et al, 2012).…”

Improving the simulation of global aerosol with size-segregated anthropogenic number emissions

“…MEGAN2 was run offline and its output data were used for the ECHAM-HAM input initialization. More details can be found in Makkonen et al (2012).…”

“…Previous studies have shown that the implementation of an activation-type nucleation improves particle number concentration estimations in modeling (Spracklen et al, 2010;Makkonen et al, 2012). In our experiment, we coupled a binary sulphuric acid-water nucleation scheme (Vehkamäki et al, 2002) with an activationnucleation scheme described by Paasonen et al, (2010, Eq.…”

“…One of the input emission inventories that has been widely used in ECHAM-HAM simulations, as well as in other Earth System Models (Pozzoli et al, 2011;Makkonen et al, 2009Makkonen et al, , 2012Tonttila et al, 2015), is the Aerosol Inter Comparison data set, AeroCom , developed for the purpose of conducting improved simulations of aerosol-climate interactions (Samset et al, 2014). However, the AeroCom emission inventory does not include a specific framework for particle number emissions.…”