Statistical model for aerosol size distribution parameters according to weather parameters

1995 ◽  
Author(s):  
Itai Dror ◽  
Norman S. Kopeika
Keyword(s):  
Statistical Model ◽  
Size Distribution ◽  
Aerosol Size Distribution ◽  
Distribution Parameters ◽  
Weather Parameters

scholarly journals An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

2017 ◽  
Vol 10 (4) ◽  
pp. 1817-1833 ◽  
Author(s):  
Daniel Rothenberg ◽  
Chien Wang
Keyword(s):  
Size Distribution ◽  
Relative Error ◽  
Climate Model ◽  
Cloud Condensation Nuclei ◽  
Full Range ◽  
Model Development ◽  
Cloud Droplet ◽  
Aerosol Size Distribution ◽  
Mean Relative Error ◽  
Distribution Parameters

Abstract. We describe an emulator of a detailed cloud parcel model which has been trained to assess droplet nucleation from a complex, multimodal aerosol size distribution simulated by a global aerosol–climate model. The emulator is constructed using a sensitivity analysis approach (polynomial chaos expansion) which reproduces the behavior of the targeted parcel model across the full range of aerosol properties and meteorology simulated by the parent climate model. An iterative technique using aerosol fields sampled from a global model is used to identify the critical aerosol size distribution parameters necessary for accurately predicting activation. Across the large parameter space used to train them, the emulators estimate cloud droplet number concentration (CDNC) with a mean relative error of 9.2 % for aerosol populations without giant cloud condensation nuclei (CCN) and 6.9 % when including them. Versus a parcel model driven by those same aerosol fields, the best-performing emulator has a mean relative error of 4.6 %, which is comparable with two commonly used activation schemes also evaluated here (which have mean relative errors of 2.9 and 6.7 %, respectively). We identify the potential for regional biases in modeled CDNC, particularly in oceanic regimes, where our best-performing emulator tends to overpredict by 7 %, whereas the reference activation schemes range in mean relative error from −3 to 7 %. The emulators which include the effects of giant CCN are more accurate in continental regimes (mean relative error of 0.3 %) but strongly overestimate CDNC in oceanic regimes by up to 22 %, particularly in the Southern Ocean. The biases in CDNC resulting from the subjective choice of activation scheme could potentially influence the magnitude of the indirect effect diagnosed from the model incorporating it.

scholarly journals Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions

2002 ◽  
Vol 2 (6) ◽  
pp. 2095-2131 ◽  
Author(s):  
C. Andronache
Keyword(s):  
Size Distribution ◽  
Field Experiments ◽  
Aerosol Particles ◽  
Rainfall Rate ◽  
Aerosol Size Distribution ◽  
Size Distributions ◽  
Coarse Particles ◽  
Distribution Parameters ◽  
Cloud Scavenging ◽  
Scavenging Rates

Abstract. Below-cloud scavenging (BCS) coefficients of aerosols by rainfall are estimated for reported aerosol size distributions measured during field experiments in various environments. The method employed is based on explicit calculations of the efficiency of collision between a raindrop and aerosol particles. Results show that BCS coefficient increases with rainfall rate and has a significant dependence on aerosol size distribution parameters. Thus, BCS is important for very small particles (with diameters less than 0.01 µm) and for coarse particles (with diameters larger than 2 µm). For rainfall rate R ~ 1 mm hr -1, the 0.5-folding time of these particles is of the order of one hour. It is shown that BCS is negligible for aerosol particles in the range [0.1-1] µm if compared with in-cloud scavenging rates for low and moderate rainfall rates (R ~ 0.1-10 mm hr -1). The results indicate that a boundary layer aerosol size distribution with coarse mode is drastically affected very shortly after rain starts (in a fraction of one hour) and consequently, the below-cloud aerosol size distribution becomes dominated by particles in the accumulation mode.

Maximization of pulmonary hygroscopic aerosol deposition

1987 ◽  
Vol 63 (3) ◽  
pp. 1205-1209 ◽  
Author(s):  
D. D. Persons ◽  
G. D. Hess ◽  
P. W. Scherer
Keyword(s):  
Size Distribution ◽  
Isotonic Saline ◽  
Droplet Size Distribution ◽  
Aerosol Deposition ◽  
Solution Concentration ◽  
Aqueous Salt Solution ◽  
Inhalation Therapy ◽  
Aerosol Size Distribution ◽  
Pulmonary Deposition ◽  
Distribution Parameters

A newly developed computer model is used to predict the aqueous salt solution concentration, breathing pattern, and inhaled droplet size distribution parameters that will maximize pulmonary deposition of hygroscopic medicinal aerosols. The parameter values providing maximum pulmonary deposition include 1) a NaCl concentration in the aerosolized solution of 0.035 g/ml or higher if the subject can tolerate it, 2) as nearly a monodispersed inhaled aerosol size distribution as possible, 3) an aerosol mass median diameter of 2–3 micron, and 4) slow (7 breaths/min) uninterrupted breathing of 1.5–2 liters of aerosol/breath. With these values, the model predicts that pulmonary deposition can be increased by greater than 100% relative to the deposition achieved in conventional inhalation therapy with isotonic saline-based medications.

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