AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA
Abstract View
Emission Rates of Biological Aerosol Particles in a Montane Pine Forest
STEPHAN NORDMANN, Hang Su, J. Alex Huffman, Ulrich Poeschl, Yafang Cheng, MPIC
Abstract Number: 175 Working Group: Bioaerosols
Abstract The formation and transportation of primary biological aerosol particles (PBAP) are important to understand its climate, ecological and health effects. Although PBAP may significantly contribute to the aerosol burden on a regional scale, they are not considered in atmospheric models. Their explicit description in models is difficult due to the lack of their emission mechanisms. In the Beachon-RoMBAS campaign, which took place in a homogeneous pine forest in Colorado, USA, PBAP were intensively characterized by various techniques. In this study, Huffman et al. (2013) found elevated PBAP concentrations during and after rain and attributed this to particle bursts in the beginning of several rain events and active biota growing on wetted surfaces (e.g. spores from fungis, cryptogamic covers). In the present study we use the Weather Research and Forecast model (WRF) coupled with a chemistry module to derive emission rates of PBAP for the campaign period covering both precipitation and non-precipitation conditions. Two nested model domains were chosen with horizontal resolutions of 3 km and 1 km, respectively. The PBAP in the model were assumed to have the same density and hygroscopicity as bioaerosols described in Bauer et al. (2008). The particle size distribution consists of 8 model bins. We divided the simulation period in July and August 2011 into a non-precipitation and precipitation episode, and examined the emissions from different classes of ecosystems as represented by the Normalized Vegetation Index (0.1-0.4, 0.4-0.7 and 0.7-1). For both episodes, the best correlation between model and observation was found for emissions from NDVI of 0.4- 0.7, which was considered as the major source of observed PBAPs. The emission rates from this class were then retrieved from the regression results between model and observation for the different model bins for precipitation and non-precipitation episodes, respectively. As a result, observed concentration patterns can be simulated by the retrieved emissions and its diurnal variation is mainly due to the diurnal cycle in meteorological variables. Distinct peaks in the time series of observed PBAP were attributed by Huffman et al (2013) to particle bursts when the rain starts. We will simulate this by increasing the emissions at locations and times where and when rain occurred by using a gridded precipitation product from radar and rain gauge observations.