Download Article
Total Page：16
File Type：pdf, Size：1020Kb
OPEN ACCESS Related content - Modelling the impact of fungal spore ice How important is biological ice nucleation in clouds nuclei on clouds and precipitation Ana Sesartic, Ulrike Lohmann and Trude on a global scale? Storelvmo - Modeling of the Wegener–Bergeron–Findeisen To cite this article: C Hoose et al 2010 Environ. Res. Lett. 5 024009 process—implications for aerosol indirecteffects T Storelvmo, J E Kristjánsson, U Lohmann et al. - The global influence of dust mineralogical View the article online for updates and enhancements. composition on heterogeneous ice nucleation inmixed-phase clouds C Hoose, U Lohmann, R Erdin et al. Recent citations - Concentration and Physical Characteristics of Black Carbon in Winter Snow of Beijing in 2015 Delong Zhao et al - An overview of optical and thermal methods for the characterization of carbonaceous aerosol D. Massabò and and P. Prati - Water uptake of subpollen aerosol particles: hygroscopic growth, cloud condensation nuclei activation, and liquid–liquid phase separation Eugene F. Mikhailov et al This content was downloaded from IP address 170.106.35.93 on 25/09/2021 at 14:33 IOP PUBLISHING ENVIRONMENTAL RESEARCH LETTERS Environ. Res. Lett. 5 (2010) 024009 (7pp) doi:10.1088/1748-9326/5/2/024009 How important is biological ice nucleation in clouds on a global scale? C Hoose1,2,JEKristjansson´ 1 andSMBurrows3 1 Department of Geosciences, University of Oslo, Oslo, Norway 2 Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Karlsruhe, Germany 3 Max Planck Institute for Chemistry, Mainz, Germany E-mail: [email protected] Received 22 April 2010 Accepted for publication 8 June 2010 Published 22 June 2010 Online at stacks.iop.org/ERL/5/024009 Abstract The high ice nucleating ability of some biological particles has led to speculations about living and dead organisms being involved in cloud ice and precipitation formation, exerting a possibly significant influence on weather and climate. In the present study, the role of primary biological aerosol particles (PBAPs) as heterogeneous ice nuclei is investigated with a global model. Emission parametrizations for bacteria, fungal spores and pollen based on recent literature are introduced, as well as an immersion freezing parametrization based on classical nucleation theory and laboratory measurements. The simulated contribution of PBAPs to the global average ice nucleation rate is only 10−5%, with an uppermost estimate of 0.6%. At the same time, observed PBAP concentrations in air and biological ice nucleus concentrations in snow are reasonably well captured by the model. This implies that ‘bioprecipitation’ processes (snow and rain initiated by PBAPs) are of minor importance on the global scale. Keywords: ice nucleation, biological aerosol, aerosol–cloud interactions 1. Introduction measurements seem to provide new indications of the possible atmospheric relevance of biogenic particles for ice formation: Ice formation in mixed-phase clouds (at temperatures between Christner et al (2008) observed that ice nucleation active ◦ 0and−38 C) is initiated by so-called ice nuclei (INs), bacteria are ubiquitous in precipitation on different continents; which are a small subset of the aerosol population. Without Pratt et al (2009) identified 33% of the ice crystal residual INs, the droplets would remain liquid (in a metastable particles sampled in a wave cloud over Wyoming as biogenic; state) throughout this temperature range. Once the first and Prenni et al (2009) found that chamber-measured INs in ice crystals have formed in a mixed-phase cloud, they the Amazon basin were composed to a significant fraction can rapidly grow (Wegener–Bergeron–Findeisen process), of biological carbonaceous particles. However, it is unclear stimulating precipitation formation. Various insoluble particles how representative these results are for global climatological like mineral dust, metallic particles, soot, and primary conditions. biological particles can act as INs. Some bacteria (especially Pseudomonas syringae) and fungal spores have been found Sensitivity studies with small-scale models have demon- to be among the most efficient INs, initiating freezing at strated the potential impact of bioaerosols on cloud micro- temperatures as high as −2 ◦C (Yankofsky et al 1981). physics (e.g. Levin et al 1987,Diehlet al 2006,Gr¨utzun et al After the discovery of ice nucleating biological particles in 2008,Ariyaet al 2009, Phillips et al 2009), but extrapolation the 1970s, it was suggested that the biosphere plays an active to their broader atmospheric relevance is hampered by the fact role in cloud glaciation and precipitation initiation (Sands et al that the prescribed bioaerosol concentrations were often not 1982, Morris et al 2004). For a long time, observational realistic or not clearly specified. evidence in support of the ‘bioprecipitation hypothesis’ was The purpose of the present study is to simulate realistic limited and only indirect (M¨ohler et al 2007). Recent biological particle concentrations and to constrain their 1748-9326/10/024009+07$30.00 1 © 2010 IOP Publishing Ltd Printed in the UK Environ. Res. Lett. 5 (2010) 024009 C Hoose et al Table 1. Simulation description. Table 2. Bacterial emission fluxes (best-fit and 95th percentiles of emission estimates by Burrows et al (2009a)), and ecosystem area in Simulation Ice nucleation properties of bacteria and the CLM land model (Bonan et al 2002). Emissions from coastal fungal spores areas are not considered with a separate emission flux in the present PBAP 1% Pseudomonas syringae-like, with a study, because they cannot be unambiguously attributed to a plant maximum allowed IN fraction of 0.1%, and functional type. 99% inactive. −2 −1 −2 −1 Fi (m s )in Fi (m s ) PBAP-intermediate 1% Pseudomonas syringae-like, with a Area simulations PBAP and in simulation maximum allowed IN fraction of 0.1%, and Ecosystem (106 km2) PBAP-intermediate PBAP-MAX 99% intermediate INA (same nucleation parameters as for mineral dust). Coastal 0 900 4 996 PBAP-MAX 100% Pseudomonas syringae-like, no Crops 22.7 704 1 578 upper limit on IN fraction. Higher bacterial Deserts 19.1 0 52 emission fluxes (see table 2). Forests 30.3 0 187 Grasslands 32.9 648 1 811 Land-ice 15.5 7.7 16 contribution to atmospheric ice nucleation for the first time in Seas 362.6 0 226 a global model. Recently published emission parametrizations Shrubs 20.3 502 619 Tundra 7.0 0 579 for bacteria, fungal spores and pollen are implemented in Wetlands 4.2 196 14 543 the CAM-Oslo model, and the simulated concentrations are compared to observations. Heterogeneous ice nucleation via immersion freezing in mixed-phase clouds is parametrized 2.2. PBAP emissions following classical nucleation theory, with aerosol-specific parameters derived from laboratory experiments. The relative Burrows et al (2009a) have derived bacterial emission fluxes importance of biological INs compared to mineral dust and in different ecosystems from observation-based best estimates soot INs is assessed. of near-surface number concentrations. The best-fit number fluxes Fi (see table 2) are used here, weighted by the area fraction of the respective ecosystems in the gridbox ( f ). 2. Model description i 10 2.1. CAM-Oslo Fbacteria = fi Fi . (1) i=1 The aerosol–climate model CAM-Oslo with a detailed aerosol module (Seland et al 2008) and a prognostic double-moment Here the index i runs over the up to ten ecosystems cloud microphysics scheme (Storelvmo et al 2008, Hoose with nonzero bacterial emissions. The fractions of the et al 2009) has been modified by a new treatment of ice different ecosystems are obtained from the corresponding plant nucleation by mineral dust, soot, bacteria, fungal spores and functional type area fractions of the land model CLM (Bonan pollen (Hoose et al 2010). These primary biological aerosol et al 2002) used in CAM-Oslo, and are not necessarily equal to particles (PBAPs) are included with emission parametrizations the ones used in the Burrows et al (2009a) study. In simulation listed below. PBAP dry and wet deposition are treated as PBAP-MAX, the 95th percentiles of the emission estimates by described for other aerosol species in Seland et al (2008). For Burrows et al (2009a) are used. The bacterial diameter is set to wet deposition, the same in-cloud and below-cloud scavenging 1 µm, assuming single cells. Bacteria can also be aggregated coefficients are assumed as for coarse mode sea salt particles, in clumps or rafted on plant/soil debris (Tong and Lighthart implying that the bioaerosols are easily wettable (supported 2000). The size assumption influences the particle deposition by measurements reviewed in Ariya et al (2009)). In the rate. A sensitivity study by Burrows et al (2009a) showed that absence of sufficient size-resolved measurements, the PBAPs an increase of the bacterial diameter from 1 to 3 µm results are assumed to be monodisperse (diameters given below), in a decrease of the atmospheric residence time by up to about spherical, and with a density of 1 g cm−3. 20%. Three simulations (see table 1) are presented, each of For fungal spores (including spores of lichen fungi), we them integrated for five years after a four-month spin-up follow the approach by Heald and Spracklen (2009), which is period: one with our best estimates on PBAP emissions based on observations compiled by Elbert et al (2007). Heald and ice nucleation properties (simulation ‘PBAP’), and two and Spracklen (2009) assume that the fungal spore emissions sensitivity studies (‘PBAP-intermediate’ and ‘PBAP-MAX’). are linear functions of the LAI (leaf area index) and of the ‘PBAP-intermediate’ attempts to include bacteria and fungal specific humidity q at the surface. As in Elbert et al (2007), we spores with intermediate ice nucleation activity. In ‘PBAP- assume a spore diameter of 5 µm. To approximately match the MAX’, extreme assumptions on bacterial emissions as well Heald and Spracklen (2009) emissions, we apply the following as on bacteria and fungal spore ice nucleation efficiencies are formulation for the number emission flux: made in order to calculate an upper estimate.