Y. ZhangO, R.C. Easter^, S. J. Ghan^, and H. Abdul-Razzak^ · Abdul-Razzak and Ghan\ The number and...

$: Y. ZhangO, R.C. Easter^, S. J. Ghan^, and H. Abdul-Razzak^ · Abdul-Razzak and Ghan\ The number and mass concentrations of aerosols activated for each mode is expressed in terms of$
Impact of aerosol size representations on

aerosol modeling

Y. ZhangO, R.C. Easter , S. J. Ghan , and H. Abdul-Razzak^Atmospheric and Environmental Research, Inc., 2682 Bishop Drive,Suite 120, San Ramon, CA 94583EMail: [email protected], Pacific Northwest National Laboratory, Richland, MSIN K 9-

EMail: [email protected], [email protected]&M University-Kingsville, Campus Box 191, Kingsville, TX

Email: H-Abdul-Razzak@sunlib. tamuk. edu

Abstract

An appropriate representation of aerosol size distribution is a key to the accuratesimulation of aerosol-cloud interactions and aerosol radiative forcing. A 1-Dversion of a global aerosol/cloud/chemistry model using the modal and thesectional approaches is developed to study the impact of different sizerepresentations on aerosol modeling. The relative advantages of the twoapproaches in representing aerosol-cloud-interaction processes such as aerosolactivation and aqueous chemistry are evaluated.

1 Introduction

An appropriate representation of aerosol size distribution is important inmodeling aerosol dynamics, chemistry, and radiative forcing because of thestrong size-dependence of these processes. For example, direct radiative forcingis very sensitive to particle size because the mass scattering efficiency peaks forparticle sizes near the wavelength of light. Indirect forcing is affected by thenumber of particles that act as cloud condensation nuclei (CCN). An enhanced

Transactions on Ecology and the Environment vol 29 © 1999 WIT Press, www.witpress.com, ISSN 1743-3541

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aerosol number concentration may result in an enhanced cloud droplet concentra-tion and an increased cloud shortwave albedo. However, most global modelscurrently use a crude aerosol size treatment (e.g., modal approach with fixed sizedistribution). Such a treatment can not account for the wide variations in theobserved aerosol size distribution, particularly during processing of the aerosolby clouds. The resultant errors in the size distribution can lead to large errors inestimates of both direct and indirect radiative forcing by aerosols.

Three major approaches have been developed to represent the aerosol sizedistribution in atmospheric models: continuous, discrete, and parameterizedrepresentations. Each of these requires a numerical solution to the aerosolgeneral dynamic equation and differs only in their degree of approximation of thesize distribution. The continuous representation is the most accurate approach, inwhich a continuous function is used. However, it is computationally demandingand thus not currently used in 3-D air quality/climate models. In the sectionalapproach, the particle size distribution is approximated by a discrete number ofsize sections based on number, surface area, or volume (or mass). The sectionalapproach has been widely used in urban/regional air quality models. Althoughthere are increasing applications in atmospheric radiative/climate models, itsapplication in 3-D global atmospheric models is limited by the computationalburden and memory constraints. In the parameterized representation, the particlesize distribution is approximated by several analytical functions (generally log-normal distributions) that represent the various modes of the particle population.This modal approach is also used in a number of air quality/climate models.

In this paper, we present a single-column model that simulates variations ofaerosol size distribution and aerosol-cloud interactions through activation andaqueous-phase chemistry. Our objectives are to study the impact of the modaland the sectional approaches on modeling aerosol-cloud interactions and providerecommendations on aerosol size representations in global aerosol modeling.

2 Model Description

The single-column model was constructed based on the 3-D Model for IntegratedResearch on Atmospheric Global Exchanges (MIRAGE) that has been developedby Pacific Northwest National Laboratory and several other external collaborators(Ghan et alJ). In MIRAGE, a detailed tropospheric aerosol-chemistry modelthat predicts concentrations of oxidant, sulfur dioxide, and sulfate aerosols hasbeen coupled in core to a general circulation model that distinguishes betweencloud water mass and droplet number (Ghan et al/). All major clear-air andcloud processes such as emission, 3-D transport, gas- and aqueous-phasechemistry, condensation, coagulation, dry and wet deposition, aerosol activation,Brownian diffusion of particles to droplets, droplet evaporation, and aerosolresuspension are simulated. The aerosol size distribution and aerosol-cloudinteraction processes are treated using the modal approach with a set of log-normally distributed modes. MIRAGE is being used to estimate the direct andindirect radiative impact of aerosols. The single-column model used in this studycan be considered a single column of the global MIRAGE but with vertical


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velocity and lateral boundary conditions prescribed rather than interacting withadjacent columns. It is referred to as single-column MIRAGE (SC-MIRAGE).

As an initial focus on aerosol-cloud interactions, SC-MIRAGE only treatsvertical transport, aerosol activation/cloud droplet nucleation, aqueous-phase SO]oxidation, and droplet evaporation/aerosol resuspension. In this paper SC-MIRAGE only treats sulfate aerosol, as it is the most important speciesinfluencing global radiative forcing. The sulfate aerosol is assumed to beammonium sulfate, which typically comprises the largest fraction of CCN mass.Other aerosols such as methanesulfonic acid, nitrate, carbonaceous aerosol, soildust and sea-salt are normally treated in MIRAGE, but are neglected here.SC-MIRAGE is designed to use either the modal or the sectional approaches

to represent aerosol size distribution. The modal approach assumes that theaerosol population is composed of a single or multiple log-normally distributedmodes characterized by three parameters: number concentration, A ,, geometricmean diameter, D^, and geometric standard deviation, c^. Both aerosol numberand mass are predicted, with a^ prescribed. The sectional approach uses the so-called moving-center size structure developed by Jacobson\ In this structure, thesize section is defined as (Jaconson )

u,= ,,u,._i ^ ; = !,...,# (1)

where u, and u/./ are the volumes of a single particle in size sections i and /-1, V^tis a constant and is defined as the volume ratio of the adjacent sections, and TV isthe total number of sections. The bounds of each section are fixed, whereas themean diameter of particles within each section varies during the aerosol growthprocesses such as aqueous-phase oxidation of SO] and condensation of H SO

Aerosol activation is a fundamental cloud process contributing to clouddroplet concentrations. When an air parcel enters a cloud, a fraction of aerosols(typically the larger ones) are activated to form cloud droplets, splitting theoriginal mode into an interstitial aerosol (i.e., unactivated) fraction and an"aerosol in cloud-droplet" (i.e., activated) fraction. These two fractions evolvefurther due to other cloud processes such as Brownian diffusion scavenging ofinterstitial particles, growth of activated particles via aqueous reactions,coalescence and precipitation scavenging of cloud droplets. Activation ofaerosols as CCN is treated using the parameterization of Abdul-Razzak et al/ andAbdul-Razzak and Ghan\ The number and mass concentrations of aerosolsactivated for each mode is expressed in terms of vertical velocity, aerosol numberconcentration, aerosol composition, and the mode radius and standard deviationof each mode of the aerosol size distribution. This parameterization was for themodal approach. To apply it to the sectional approach, one must assume thateach size section is a log-normal size distribution with a mean diameter and ageometric standard deviation. The geometric standard deviation of each log-normally distributed section, a /, can be either calculated or prescribed. In thiswork, CT£/ is defined as the ratio of the upper and low bounds of the size section:where, D pcr.i and D/ ,, are the upper- and the low-bound diameters of section /,

_ ®upper,i _ , ^G g,i - - Vrat) W


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respectively. When the activation parameterization of Abdul-Razzak and Ghan* isapplied for multi-sections, the sectional representation is actually quasi-sectionalbecause each section is assumed to be log-normal with a geometric standarddeviation prescribed. For simplicity, the quasi-sectional representation isthereafter referred to as the sectional representation.

Aqueous-phase oxidation of SO: in cloud contributes to the growth ofactivated particles and controls the shape of the observed aerosol-in-droplet sizedistribution (Hoppel et al/). The aqueous phase transformation of S(IV) to SO,"in MIRAGE is calculated using bulk cloud-water chemistry and is assumed toproceed through reactions with t C and O,. While the total numberconcentration of activated particles keeps constant, the total mass concentrationincreases because of formation of sulfate. The sulfate produced is thendistributed among the droplet aerosols on a per number basis. For the modalapproach, the size distribution of cloud droplets is assumed to be monodisperse.The growth in diameters of activated particles is calculated using the numberconcentration and the resulting mass concentration. For the sectional approach,the Ziegler non-monodisperse cloud droplet size distribution is used anddiscretized over the multi-sections, assuming the largest particles are in thelargest droplets. If the mean diameter of particles in a given section exceeds theupper-bound diameter of the section, all particles in the section are moved to asingle size section bounding the resulting mean diameter.

3 Simulation Conditions and Procedures

Different clouds may respond quite differently to variation in aerosol concentra-tions. In this work, we focus on stratiform clouds, which account for most of theglobal cloud cover. Three atmospheric conditions are selected for simulations, asshown in Table 1. The aerosol number concentration is 100, 300, and 1000 cmunder marine, remote continental, and continental source conditions, respectively.These values are typical for remote marine and continental boundary layers(Hoppel et al/). The initial size distribution is assumed to be log-normal with Dg= 0.1 jim and cr^ = 1.8, which are characteristic of the remote marine boundarylayer (Hoppel et al/). For each condition, we conducted simulations for a 5-hrperiod during which a cloud event is simulated using 24 model layers fromsurface to 38 km. Cloud formed at 1.67 hr in layers 6 to 8 (corresponding to analtitude of 530-910 m) and dissipated after 4-5 hrs.

Table 1. Initial conditions selected for aerosol-cloud-interaction simulations.

SOz, ppbSulfate number cone., # particle crrf*Sulfate mass cone., (ig cm"*Dyy jimGK

Marine

0.031000.4390.11.8

Remotecontinental0.33001.320.11.8

Continentalsource1.010004.390.11.8


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For each condition, two scenarios are simulated: with and without aqueous-phase chemistry, using both the modal and the sectional approaches. For themodal approach, a single log-normal mode is used. For the sectional approaches,two different size resolutions (40 and 100 size sections) are used for the diameterrange of 0.002 to 5 urn. The absolute errors between the reference and the resultsusing other size representations are quantified,

4 Results

4.1 Comparison of the Activation Parameterization in a Box Model

To evaluate the sectional representation of the activation parameterization used inSC-MIRAGE, we first compare the results of the parameterization in a box modelwith those of a detailed numerical model presented in Abdul-Razzak et al/ Theresults show that the number activation fractions predicted by the modal approachare much greater than those predicted by the sectional approach and the results ofthe modal approach are closer to the numerical model than the sectionalapproach. This is because the activation parameterization was developed forbroad log-normal modes, not for narrow sections. To reduce the differencesbetween the two approaches, we modify the activation parameterization in thesectional approach by using the bulk aerosol properties to determine themaximum supersaturation. Although the total number activated in the sectionaland the modal approaches should be the same for such a treatment if the sizeresolution is sufficiently fine, in practice differences of 10% typically arise.

It is noted that the sectional representation with 100 size sections treats thesize transition between interstitial and activated aerosols much better than themodal approach. Emphasizing the variation in the size distribution, we use thenormalized results with 100-section based on the bulk aerosol properties as thereference results for other size representations in all SC-MIRAGE simulations.The results with 40-section are used to represent the sectional approach andcompared to those of the modal approach and the reference.

4.2 SC-MIRAGE Simulations Without Aqueous-Phase Chemistry

We first focus on vertical mixing and activation processes for simulations of SC-MIRAGE. Aqueous-phase chemistry was turned off in these simulations. Figure1 shows the initial number/mass size distribution of original aerosols and that ofinterstitial aerosols in layer 6 right after cloud formed (i.e., at 1.67 hr) undermarine conditions. Similar plots for activated aerosols are shown in Figure 2.The reference results show that the initial aerosols split into two fractions, 47% asinterstitial aerosols and 53% as activated aerosols. All particles with diametersgreater than 0.057 um were activated. The total mass concentration of activatedaerosols is much greater than that of interstitial aerosols due to a higher massactivation fraction (77%). The results obtained with 40 sections and the modalapproach are similar to reference results, with 49% of aerosols in air and 51% incloud. However, the modal approach fails to predict the abrupt size transition for


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activated aerosols, due to the limitation of the log-normal size distribution. As aresult, the modal approach predicts more activated particles in the small sizerange (i.e., Dg < 0.1 jam) than the sectional approach.

Table 2 summarizes the total number and mass concentrations of activatedparticles right after cloud formed for cases without aqueous-phase chemistry.Under all conditions, the modal approach predicts the aerosol number and massconcentrations similar to the reference values, with differences less than 13%.The results obtained using 40 size sections are within 4% of the reference values.

Table 2. Total number (N) and mass (M) concentrations of activated particles att= 1.67 hr for cases without aqueous-phase chemistry.

Size Representation

1 00 sections (Reference)40 sectionsModal

Marine

TV M52.950.751.8

0.3390.3400.338

RemotecontinentalN M

127.0122.0122.0

0.9840.9890.988

Continentalsource

AT M306.0297.0267.0

3.133.183.05

„-. 1 .52 + 02 -E

en 1.0E + 02 -

"° 5.0E+01 -

1 0 E -04 -

. . . .

— Sectional (40)Modal

^

,•

/\\...

0.001 0.0 1d

0.1 1(urn )

10

(b) Marine conditions, no aqueous chemistry, Layer 6, t= 1.67 hr8.0E-01 -j

m" 6.0E-01 -

2.0E-01 -

1 .OE-04 -

mi la

— —Sectional (40)Modal

Figure 1. Predicted size distribution of interstitial aerosols in layer 6 just aftercloud forms for cases without aqueous-phase chemistry under marineconditions, (a) Number size distribution, (b) Mass size distribution.


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(a) M1 .52+02 -

„-*'E 1.0E + 02 -•oI1 5.0E + 01 -•o

0.0

(b) M,6.0E-01 -

•?"*| 4.0E-01 -

O9°3 2.0E-01 -5•o

0.0

irine conditions, no aqueous chemistry, Layer 6, t=1.67 hr

— — • — S e c t l o n a l (40 ) [J | .

J\01 0.01 0.1 1 10

d (urn )

irlne conditions, no aqueous chemistry, Layer 6, t=1.67 hr

:

A:

:

01 0.01 0.1 1 10d (nm )

Figure 2. Predicted size distribution of activated aerosols in layer 6 just aftercloud forms for cases without aqueous-phase chemistry under marineconditions, (a) Number size distribution, (b) Mass size distribution.

4.3 SC-MIRAGE Simulations With Aqueous-Phase Chemistry

When aqueous-phase chemistry occurs, the activated particles become larger andmove towards to the larger size range. When cloud droplets later evaporate, theresulting residue is larger than the original cloud nucleus on which the dropletformed. Figure 3 shows the number and mass size distributions of activatedaerosols in layer 6 at the end of the cloud event under marine conditions. Thetotal mass concentration predicted by the modal and the sectional approachesincreases by 36-48% due to aqueous-phase production of sulfate, as compared tothat without aqueous-phase chemistry.

For the sectional approach, the resulting size distributions of activated aerosolsdiffer quite significantly from their original one shown in Figure 2, with thenumber and mass concentrations varied significantly from one section to another.This is because particles in different sections have different growth rates andmove into different new sections. At a given time, particles in a particular sectionmay grow into the larger sections due to a large growth rate, while particles in thelower sections may stay in the same sections or jump into a section that is stilllower than that particular section due to a small growth rate. At this particulartime, that particular section contains no particles but it may gain new particles


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later due to continuous growth and jumping of particles in the lower sections. Asa result of being an "empty" section for certain time periods in cloud, the numberand mass concentrations in that particular section can be significantly lower thanthose in adjacent sections. For example, the simulations with 40-section showthat the number and mass concentrations in the section of 0.102-0.13 jim aresignificantly lower than those in adjacent sections, resulting in two distinct peaksin the number and mass size distributions. The results using 40 sections aregenerally consistent with the reference, with the high mass concentration shiftedfrom the range of 0.208 to 0.494 um for the reference to the range of 0.181 to0.421 um in the 40-section simulation.

(a) M2.5E +02 -i

2.0E +02 -

£ 1.5E + 02 -|O9| 1 .OE + 02 -•o

5.0E + 01 -

0.0

(b) M1 .6E + 00 -

•T 1.2E + 00 -E

O 0

Co

o e

oo r

•»G4 P Go| p/wp

0.0

—Sectional (40) n

J#01 0.0 1 0.1 1 10

d (urn )

a rin e c o n d i t i o n s , with a q u e o u s c h e m i s t r y , L a y e r 8, t=4 h r

S action al (40)

/v01 0.0 1 0.1 1 10

d (urn )

Figure 3. Predicted size distribution of activated aerosols in layer 6 just beforecloud dissipates for cases with aqueous-phase chemistry under marineconditions, (a) Number size distribution, (b) Mass size distribution.

4.4 Quantitative Comparisons

A quantitative comparison between results of various size representations and thereference results was conducted for the size range of activated aerosols. Theaverage absolute normalized difference (AAND) is used as a measure of themodel accuracy. It is defined as (Seigneur et al/):

AAND=1

(3)


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where / and k are the section numbers of the smallest and the largest aerosolsactivated, respectively, A , is the total number of sections in the size range of theaerosol activated. Q* is the aerosol number or mass concentrations in section icalculated by the reference simulations with 100 sections, and 0/ is the aerosolnumber or mass concentrations in section i calculated by simulations with themodal or the 40-section representations. A large value of AAND indicates a largedeviation between the reference and the corresponding size representation.

Table 3 shows the AAND for number and mass concentrations of sectionscontaining aerosols activated under three conditions. For the sectional approach,the diameters of the smallest aerosol activated are 0.057, 0.067, and 0.084 jam formarine, remote continental, and continental source conditions, respectively. Theparticle number concentrations in smaller size sections are zero or negligible.For the modal approach, however, the assumption of a log-normal sizedistribution results in a much higher number concentration in these small sizesections, creating significant deviations from the reference values for these smallsections. For consistency, we only compare the sections with mean diametersequal to or greater than these smallest diameters for the modal representation.For most scenarios, the modal approach has a much larger AAND than thesectional approach. The AANDs range from 33% to 622% for the modalapproach and from 22% to 44% for the sectional approach. Although thelimitation of the log-normal size distribution contributes to the large deviationbetween the modal approach and the reference results, it is noted that thereference results using the sectional approach is not conclusive because of theinappropriateness of the activation parameterization for narrow sections.

Table 3. Average absolute normalized difference (%) in total number (N) andmass (M) concentrations of activated particles at t = 4 hr.

SizeRepresentation

40 sectionsModal

Marineaqoff aqon*N M N M22.3 24.532.8 31.9

31.9 30.0104.2 71.0

Remote continentalaqoff aqonN M N M21.6 22.8145.0 153.0

43.9 39.9464.2 254.3

Continental sourceaqoff aqonN M N M27.3 35.5128.5 140.0

41.7 42.3595.4 622.0

* aqon and aqoff indicate results with and without aqueous-phase chemistry, respectively.

5 Summary

We have conducted simulations for aerosol-cloud-interactions using the modaland the sectional size representations in a single-column global model. Resultsusing the sectional approach with 100 sections were used as benchmark toevaluate the appropriateness of the modal approach in representing aerosol-cloudinteraction processes. Under all modeled conditions, the modal and the sectionalapproaches predict similar total number and mass concentrations for interstitialand activated particles. Aqueous-phase chemistry contributes to 36-120%increase in mass concentrations of activated particles and shapes their sizedistribution. The sectional approach well captures the abrupt size transitionbetween the interstitial and activated aerosol fractions, whereas the modal


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approach with log-normal size distributions can not predict this transition due toits inherent limitation. Refinement of the modal representation to treat the twofractions using a more realistic distribution (e.g., truncated log-normal) willsignificantly improve the treatment of aerosol-cloud interactions using the modalapproach.

Recognizing the large uncertainty associated with aerosol-cloud-interaction,our results are preliminary and inconclusive. In particular, the activationparameterization is not designed for narrow section application and will need tobe modified accordingly. A rigorous evaluation of the performance of thereference results with such an activation parameterization against the detailednumerical model is needed. The effect of other processes such as coagulation andcondensation on evolution of aerosol size distribution is not addressed here. Inaddition, a comparison of the predicted/observed activated aerosol sizedistributions should be conducted when such observations become available.

Acknowledgments. This work is supported by the NASA Earth ScienceEnterprise Earth Observing System Program under contract NAS5-98072.

References

1. Ghan, S.J., Easter, R.C., Zhang, Y., Leung, L.R., Saylor, R.D., Peters, L.K.,Zaveri, R. & Lee, P., Radiative forcing of climate by aerosols: A physicallybased modeling approach. Proceedings of the Third AMS Conference onAtmospheric Chemistry, Long Beach CA, pp. 64-69, 1997.

2. Ghan, S.J., Leung, L.R. & Easter, R.C., Prediction of cloud droplet number in ageneral circulation model, J. Geophys. Res., 102, pp. 21777-21794, 1997.

3. Jacobson, M.Z., Development and application of a new air pollution modelingsystem, II, Aerosol module structure and design, Atmos. Environ., 31, pp. 131-144, 1997.

4. Abdul-Razzak, H., Ghan, S.J. & Rivera-Carpio, C., A parameterization ofaerosol activation 1. Single aerosol type, J. Geophys. Res., 103, pp. 6123-6131,1998.

5. Abdul-Razzak, H., & Ghan, S.J., A parameterization of aerosol activation 2.Multiple aerosol types, J. Geophys. Res., submitted, 1999.

6. Hoppel, W.A., Frick, G.M., Fitzgerald, J.W. & Wattle, B.J., A cloud chamberstudy of the effect which nonprecipitating water clouds have on the aerosol sizedistribution, Aerosol Sci. Technol, 20, pp. 1-30, 1994.

7. Hoppel, W.A., Fitzgerald, J.W., Frick, G.M., Larson, R.E. & Mack, E.J.,Aerosol size distributions and optical properties found in the marine boundarylayer over the Atlantic Ocean. J. Geophys. Res. 95D, pp. 3659-3686, 1990.

8. Seigneur, C., Hudischewskyj, A.B., Seinfeld, J.H., Whitby, K.T., Whitby, E.R.,Brock, J.R., & Barnes, H.M., Simulation of aerosol dynamics: A comparativereview of mathematical models, Aerosol Sci. Technol., 5, pp. 205-222, 1986.


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