Heterogeneous impact of dust on tropospheric ozone Sensitivity to season, species, and upta

Submitted to J.Geophys.Res.Atm.November21,st Change:April23,2004. Heterogeneous impact of dust on tropospheric ozone:Sensitivity to season,species,and uptake ratesHuisheng BianGoddard Earth Sciences and Technology Center,University of Maryland-Baltimore County,NASA Goddard Space Flight Center,Greenbelt,Maryland,USACharles S.ZenderDepartment of Earth System Science,University of California at IrvineAbstract.Heterogeneous chemistry on mineral dust particles causes significant reductions in important tropospheric trace gases such as O3,OH,and HNO3in dust-dominated regions such as the North African Tropical Atlantic region.We analyze the spatial and temporal modes of dust-induced heterogeneous ozone removal(∆H O3)using empirical orthogonal functions(EOFs)and principal components analysis.We use the results to attribute ozone removal to specific pathways,and to assess the sensitivity of ozone removal to uncertainties in key heterogeneous uptake rates.Thefirst EOF mode dominates∆H O3variance(93%) and shows that dust reduces O3through heterogeneous reactions globally and year-around with the maximum in July.The second mode explains only4%of ∆H O3spatial variance yet accounts for most∆H O3seasonality.With base-value uptake coefficients,indirect ozone reduction due to HNO3uptake exceeds direct heterogeneous uptake of O3.However,uncertainties in uptake rates allow the possibility that direct O3uptake exceeds HNO3-induced O3uptake,especially in Northern Spring.Recently published HNO3uptake coefficients on authenticdust range from10−5<γHNO3<0.2,and imply that dust destroys0.5–5.2%oftropospheric O3,respectively.ImprovedγHNO3measurements and correct modelrepresentation of global dust composition,deliquesence,and aging are required to further reduce these order-of-magnitude uncertainties.1.IntroductionHeterogeneous chemistry on mineral dust aerosol is an important factor in determining tropospheric composition because mineral dust accounts for up to half of all aerosol surface area[Penner et al.,2001]and heterogeneous uptake of many key oxidants(e.g.,HNO3and HO2)occurs quickly on dust[e.g.,Dentener et al.,1996].Yet many gaps remain in our understanding of the role of dust heterogeneous chem-istry in the tropospheric O3cycle.In particular,uptake co-efficients for heterogeneous reactions are poorly constrained [e.g.,Michel et al.,2002],the specific pathways that domi-nate dust-induced O3changes are poorly understood[Bian and Zender,2003],and the role of heterogeneous mineralcomposition(and multi-component aerosols in general)on chemical processing is difficult to assess at global scales [Martin et al.,2002;Rodriguez and Dabdub,2004].This paper quantifies our understanding of thefirst two of these problems,important reaction pathways and uptake uncer-tainty.The impact of dust heterogeneous chemistry on tropo-spheric O3has been investigated on regional[Zhang and Carmichael,1999;Galy-Lacaus et al.,2002;Underwood et al.,2001b;Martin et al.,2002]and global scales[Den-tener et al.,1996;Liao et al.,2003;Bian and Zender, 2003;Bauer et al.,2004].Dust reduces O3by10–40% in dust storm conditions[Dentener et al.,1996;Zhang and Carmichael,1999].Dust appears to play a minor role in 1the distribution of tropical tropospheric ozone[Martin et al., 2002;Bian and Zender,2003].Dust reduces global tro-pospheric ozone by1–5%[Bian and Zender,2003;Bauer et al.,2004]depending on the uptake coefficients employed. Partitioning this ozone reduction between direct uptake of O3on mineral surfaces[Michel et al.,2002;Hanisch and Crowley,2003b]and precursor removal is the focus of this study.Characterizing the spatial and temporal patterns of O3variation due to heterogeneous reactions on mineral dust helps us understand the chemical pathways governing dust-induced O3heterogeneous changes,and is potentially use-ful in siting future dust-chemistryfield campaigns.This pa-per augments previous discussions of spatial and temporal changes[Dentener et al.,1996;Bian et al.,2003;Bian and Zender,2003]with a different approach.Mineral dust affects the photochemical oxidant cycle by providing additional reaction pathways for species such as NO y and H x O y[Underwood et al.,2001b;Galy-Lacaus et al.,2002;Hanisch and Crowley,2003a].These species, in turn,influence ozone production/destruction rates[Den-tener et al.,1996;Zhang and Carmichael,1999].Zhang and Carmichael[1999]studied the regional decrease in O3 concentration by dust influence resulting from three paths: reduction in photolytic rates;direct O3uptake;and destruc-tion of important precursors.They conclude that direct up-take of O3by dust is the dominant pathway in the change in O3by heterogeneous chemistry.However,dust-induced tro-pospheric O3reduction is highly sensitive to the assumed uptake coefficient[Dentener et al.,1996;Bian and Zen-der,2003;Bauer et al.,2004].As we will show,indirect heterogeneous chemistry mechanisms(especially uptake of HNO3)dominate O3reduction by dust with our base-value uptake coefficients.Our primary objectives are to:1.Quantify the relative importance of O3change reac-tion paths assuming base-value uptake rates2.Quantify the sensitivity of tropospheric O3change tothe measured uncertainty in uptake ratesTo accomplish these objectives,we perform EOF analyses of a suite of model simulations of tropospheric O3varia-tions caused by prescribed heterogeneous reactions on min-eral dust.This analysis technique meets two secondary ob-jectives,to characterize3.The spatial modes of tropospheric O3variation due toheterogeneous reactions on mineral dust4.The seasonality of dust heterogeneous impacts on tro-pospheric O3changeThe effect of each irreversible uptake reaction on the vari-ance structures is evaluated with a particular emphasis on re-Figure1.Monthly mean dust optical thickness at340nm in January and July.duced or elevated individual uptake coefficients.The dom-inant variance structures help us associate the spatial and temporal modes with the atmospheric chemistry phenomena related to dust heterogeneous reactions.Understanding the variance patterns of these species and their causes is impor-tant for prioritizing future laboratory andfield research to constrain on uptake rates.The paper is organized as follows.Section2describes the simulated impact of mineral dust on tropospheric chemistry, and introduces the EOF analysis methodology.Section3 presents the results of the EOF and sensitivity analyses.We discuss the uncertainties and implications of ourfindings in Section4.2.Models and Methods2.1.Mineral Dust DistributionThe monthly-varying global3-D dust concentrations used in this study are taken from the predictions of the mineral Dust Entrainment And Deposition(DEAD)model simula-tion of the1990s[Zender et al.,2003].Figure1shows the predicted geographic distribution of mean dust optical thickness at340nm in January and July.Maxima occur in the subtropical belts which contain Earth’s major deserts in-cluding North Africa,and the Saudi Arabian peninsula.Sec-ondary maxima occur in Australia,and central and east Asia. In July,strong summertime convection lifts northern hemi-sphere dust higher than in January.This helps dust spread to remote regions.Dust centers around10◦N in Januaryand shifts north to20◦N in ing monthly mean dust concentration effectively suppresses the dust concentration during dust events and increases dust concentration between events.The limitations and advantages of using monthly meanfields are discussed in Bian and Zender[2003].2.2.Heterogeneous Dust Chemistry and OzoneThe UCI Chemical Transport Model(UCICTM)[Wild and Akimoto,2001]is a global3D chemical transport model including emission,transport,deposition,and gas-phase O3-NO x-NMHC chemistry.UCICTM has been described and evaluated in previous tropospheric and stratospheric chem-istry studies[Avallone and Prather,1997;Olsen et al.,2000; McLinden et al.,2000;Wild and Prather,2000;Wild and Akimoto,2001;Prather and Ehhalt,2001;Bian,2001;Bian et al.,2003].Bian and Zender[2003]used UCICTM to study the relative roles of photolysis and heterogeneous chemistry in dust forcing tropospheric chemistry.We rep-resented irreversible uptake of reactions of eight species on dust:O3,OH,HO2,H2O2,HNO3,NO2,NO3,and N2O5. Here we use additional UCICTM simulations to determine the relative roles and spatial patterns of all eight mineral dust heterogeneous reaction represented.The consequences of the large uncertainty in the uptake rate coefficients on the pathways of ozone reduction are de-termined by four distinct types of UCICTM simulation,us-ing base-value and end-member uptake coefficient values for each species of interest.The uptake coefficients in Bian and Zender[2003]are the base-value coefficients.Type P sim-ulations allow dust to influence chemistry only by altering photolysis(i.e.,UV actinicfluxes)through its scattering and absorbing properties.We also call this photolysis forcing. Type PH simulations are Type P with the addition of het-erogeneous chemistry from the eight important irreversible uptake reactions using the base-value uptake rate coeffici-ents[Bian and Zender,2003].Type PH0X simulations are Type PH except that the heterogeneous uptake of one partic-ular species X is omitted.Type PHSX are Type PH except we reduce or increase the uptake coefficient of a particular species X by either multiplying the base-value by an uncer-tainty factor S of0.5,1.0,or2.0,or by assigning its mini-mum and maximum values measured in the literature.We accomplish Objectives3and4(Section1)by EOF analysis of heterogeneous O3variation(∆H O3)derived by subtracting Type P from Type PH simulations.Similar EOF analyses are conducted for the heterogeneous O3variation due to irreversible uptake of each species X,∆X H O3.The species-specific contribution to ozone reduction,∆X H O3,is obtained by subtracting Type PH0X from Type PH(for Ob-jective1),and Type PH0X from Type PHSX(for Objec-tive2).As before,dust distribution is from DEAD simulations of1994–1998[Zender et al.,2003]with NCEP meteorology [Kalnay,1996]in the NCAR MATCH model[Rasch et al., 1997](T62×L28resolution)re-gridded to the UCICTM res-olution(4◦×5◦,9vertical layers).Each simulation spins up for six months before the one year period analyzed here. 2.3.EOF AnalysisEmpirical orthogonal function(EOF)analysis is a use-ful tool for uncovering dominant variance structures within a gridded dataset evolving through time[e.g.,Olsen,2000]. The EOF structure and the principal components(PCs)help determine which processes control the data variance v(r,t) (e.g.,perturbation of O3by dust).Here r is the spatial co-ordinate,and t is time.We expand v(r,t)on an EOF ba-sis.This is a diminishing series of time-evolving,spatially uniform PCs,PC i(t),and time-constant,spatially variable EOFs,EOF i(r)[Olsen,2000]:v(r,t)=Ni=1PC i(t)EOF i(r)+Ni=N +1PC i(t)EOF i(r)(1) The eigenvalues and EOFs are ordered from largest to small-est.We retain i≤N terms and discard the rest.Thefirst two EOFs(N =2)suffice for our purposes.These EOFs highlight the dominant modes of variability while greatly re-ducing dataset size.The eigenvalue magnitudeλi is the variance along EOF i: Percent Variance Along EOF i=100×λiNi=1λi(2)The denominator is the total variance in all modes.The Lin-ear Algebra PACKage(LAPACK)[Anderson et al.,1999] routine dgesvd computes the singular value decomposi-tions.3.ResultsAll chemical and meteorological boundary conditions for UCICTM are based on monthly varying climatologi-cal means.The gas emission inventory averages the late 1980s and early1990s and the meteorology is consistent with1980s climatological sea surface temperatures.3.1.Modes and Seasonality of Heterogeneous O3 ReductionFigure2shows thefirst and second EOFs and PCs of ∆H O3.The primary EOF,EOF1,contributes93%of the−0.1−0.0590N04−0.25−0.2−0.15−0.1−0.0500.0590NFigure 2.Variance of ∆H O 3shown by EOF 1(upper-left)and EOF 2(bottom-left)for spatial patterns,and PC 1(upper-right)and PC 2(bottom-right)for seasonality.EOFs are labeled with percent variance explained by each.O 3variance.This first mode shows that heterogeneous reac-tions on mineral dust suppress tropospheric O 3globally,and that Northern Hemisphere (NH)summer dust causes most O 3variance.The spatial distribution of EOF 1is similar to the July zonal mean dust distribution (Figure 1)convolved with the ambient O 3distribution (e.g.,Figure 3of Bian and Zender [2003]).The greatest O 3reduction coincides with the July zonal dust maxima above 20◦N caused by dust from North Africa and the Saudi Arabian peninsula.Tropospheric O 3formation and transport modulate the meridional extent and altitude of the ozone reduction signal.Tropospheric O 3concentrations increase in northern polar regions and elevated altitudes,with minimal O 3column near the equator.Thus O 3concentration moves the ∆H O 3signal north of the dust maxima,elongates the signal toward higher altitudes,and reduces the impact of southern hemispheric dust.The continuously positive value of PC 1indicates that EOF 1continually reduces (rather than enhances)ozone year-round.The shape of PC 1demonstrates that the O 3re-duction gradually intensifies from NH winter to NH summer to form an annual cycle with maximum in July.Strong NH summer dust emission and convection [e.g.,Zender et al.,2003]and photochemistry [Bian and Zender ,2003]explain the ∆H O 3seasonality.EOF 2contains a dipole feature in ∆H O 3.The negative pole occupies the Equator low to middle troposphere.NHwinter African dust carried in tropical north-easterlies heav-ily influences this region.The positive pole is in the north-ern tropical mid-to upper-troposphere.We attribute this to NH summer dust from North Africa and the Saudi Arabian peninsula.Though it accounts for only 4%of the global to-tal O 3variance,this second mode of ∆H O 3reinforces the seasonality of ∆H O 3seen in the first mode.The negative pole reduces O 3in NH winter and increases O 3in NH sum-mer,as shown by PC 2.The positive pole has the opposite seasonality.3.2.Heterogeneous O 3Reduction by SpeciesFigure 3shows EOF 1and PC 1of ∆X H O 3for the seven species X whose irreversible uptake on dust is represented:O 3,OH ,HO 2,HNO 3,NO 2,NO 3,and N 2O 5.H 2O 2is omitted from the presentation due to its negligible impact.EOF 1accounts for the greatest total variance of ∆H O 3(Fig-ure 2)and is extremely similar (spatial correlation r =0.97)to EOF 1of ∆HNO 3HO 3(Figure 3).EOF 1explains about 90%of each ∆XH O 3dataset,dominating the variance.PC 1of ∆H O 3and ∆HNO 3HO 3are virtually identical with correla-tion r =0.82.Both display strong seasonal cycles that peak in July.EOF 1of ∆H O 3is also highly correlated with EOF 1ofboth ∆NO 3H O 3and ∆NO 2HO 3(r =0.98and 0.97,respec-tively).However,the temporal correlation is high between∆H O 3and ∆NO 3HO 3(r =93%),and low between ∆H O 3and ∆NO 2H O 3(r =53%).Furthermore,PC 1of ∆NO 2HO 3is one order of magnitude smaller than PC 1of ∆NO 3H O 3.Thus NO 2uptake by mineral dust is a relatively minor contribu-tion to ∆H O 3.The impact of direct O 3uptake on ozone levels,∆O 3H O 3,is weaker than ∆HNO 3H O 3except in April.∆O 3H O 3is compa-rable to ∆NO 3HO 3in NH summer.Direct O 3uptake produces lower correlations of EOF 1and PC 1with ∆H O 3(r =0.79and 0.47,respectively)than do ∆HNO 3H O 3and ∆NO 3HO 3.Direct O 3uptake exerts maximal influence on O 3in April,three months earlier than the July peak in ∆H O 3(Figure 2).These results show that direct O 3uptake is a significant,but not dominant,pathway for O 3reduction with the base-value uptake coefficients.Figure 3also shows that direct uptake of N 2O 5,HO 2,and OH on mineral dust cause only negligible reductions in tropospheric O 3.Dentener et al.[1996]investigated O 3impact of N 2O 5,O 3,and HO 2-radical uptake on dust using γO 3=5×10−5.They found tropospheric ozone decreases up to 10%in and nearby dust source areas.Most of their O 3reduction (2–6%)was due to direct uptake of O 3destruction on mineral aerosol.Our EOF analysis supports their conclusion when we consider only N 2O 5,O 3,and HO 2-radicals.−0.1−0.05O3 , EOF1 92%, r=0.79−0.08−0.02OH , EOF1 85%, r=0.60−0.005−0.10 HO2 , EOF1 88%, r=0.70−0.14−0.07HNO3, EOF1 91%, r=0.97−0.12−0.08−0.04NO2 , EOF1 92%, r=0.97−0.15−0.1−0.050NO3 , EOF1 93%, r=0.98−0.06−0.04−0.0290NN2O5, EOF1 93%, r=0.20Figure 3.Zonal mean EOF 1of ∆X H O 3variances due to irreversible uptake of seven reactive species on mineral dust (left)and the corresponding seasonal variation of PC 1(right).Percent variances along EOF 1(2)are indicated.Correlation r between EOF 1of ∆H O 3and ∆X H O 3is shown for each species,as is the correlation between PC 1of ∆H O 3and ∆X H O 3.Zhang and Carmichael [1999]show that direct uptake of O 3on dust significantly decreases O 3concentrations ifγO 3∼>1×10−4.They find that ∆O 3H O 3dominates ∆H O 3if γO 3=1×10−4.The significant difference in the impor-tance of direct ozone uptake between Zhang and Carmichael [1999]and ours study clearly demonstrates that the rela-tive importance of ∆O 3H O 3depends on γO 3.We discuss the uncertainty in uptake coefficients and its influence on dust-induced O 3reductions in Section 3.3.The main nitrogen oxide reservoir species,NO x and HNO 3,strongly affect tropospheric O 3through complex photochemical cycles [e.g.,Seinfeld and Pandis ,1997].Ac-cording to Underwood et al.[2001b ],initial uptake coeffi-cients for NO 2and HNO 3,adjusted for roughness effects,must exceed 10−4to significantly impact NO x ,HNO 3,and O 3concentrations.Box-model calculations show that γNO 2=1×10−5is sufficient to reduce HNO 3concentra-tions [Underwood et al.,2001b ].Thus our base-value uptake coefficient for NO 2on dry surfaces,γNO 2=4.4×10−5,is slightly too low to significantly impact the photochemical oxidant cycle,With our base-value uptake coefficient of γHNO 3=1.1×10−3,irreversible uptake of HNO 3has the most significant effect on O 3.Yet,this choice may still be conservative [e.g.,Hanisch and Crowley ,2001a ,b ]and will be discussed fur-ther below.In any case,the mechanism by which HNO 3affects O 3is important.In dusty regions,coarse particles adsorb HNO 3and sediment to the planetary surface at a rate that exceeds gas phase HNO 3removal.Consequently,heterogeneous uptake of HNO 3on mineral dust substan-tially reduces the O 3precursor NO x ,and makes HNO 3the most important species for dust-induced heterogeneous O 3variation.Field and laboratory studies confirm that a large fraction of gas-phase nitric acid is neutralized and removed by alkaline mineral aerosol [Tabazadeh et al.,1998;Zhang and Carmichael ,1999;Goodman et al.,2000;Song and Carmichael ,2001;Bey et al.,2001].3.3.Sensitivity to Assumed Uptake Coefficients Given the uncertainty in the uptake coefficients,it is nat-ural to ask how sensitive our results are to the uptake coef-ficients assumed.We focus on uncertainty in γHNO 3,γO 3and γNO 3since they dominate O 3reduction (Figure 3).We determined the uncertainty in γHNO 3,γO 3and γNO 3by re-viewing the literature.Ideally,direct measurements of species uptake on authen-tic atmospheric dust would be available for our model stud-ies.Such experiments for O 3and HNO 3became available only in recent years.To our knowledge,no direct measure-ment of NO 3on mineral dust has been conducted so far.In some cases we were forced to estimate uptake rates from in-direct evidence.Dentener et al.[1996]use O 3uptake mea-surements over different soil types to estimate thatγO3fordust aerosol ranges from3×10−4to1×10−5.This corre-sponds to O3dry deposition velocities from0.1–3.0cm s−1.Another indirect way to estimate O3uptake on dust aerosolis to assume O3reacts with trace metals,such as iron andmanganese,and oxidation of organic material.ThenγO3 may be estimated from knowledge of O3uptake on con-densed phases constrained by the atmospheric dust mineral-ogy.Zhang and Carmichael[1999]review O3uptake coef-ficients on various surfaces and translate this to mineral dustaerosol.These uptake coefficients strongly depend on themolecular properties of the impinging gas,and the surfaceproperties and abundance of particles.Some studies showedthat sub-micron carbon and iron particles destroy ozone ef-ficiently[DeMore et al.,1997],with10−4<γO3<10−3.Asian dust usually contains2–10%iron by mass[Nishikawa et al.,1991;Zhang et al.,1993;Meskhidze et al.,2003]and some organic carbon[Ohta,1991].Zhang and Carmichael[1999]chooseγO3to be similar to that for carbon and ironparticles measured by Fendel et al.[1995].Their base-valueofγO3is1×10−4with the range of1×10−5to2×10−4.Dentener et al.[1996]estimated thatγO3is about2×10−5if O3destruction is mostly determined by its reaction withiron.They chose a base-valueγO3of5×10−5with a rangeof1×10−5to2×10−4.Many direct measurements of O3uptake on mineral dust were recently performed with conflicting results[Michel et al.,2002,2003;Hanisch and Crowley,2003b].Michel et al.[2002]investigated O3uptake on mineral oxides and dusts using a Knudsen cell apparatus at296K.Their exper-iments showed thatγO3is2.7±0.9×10−5for China loess,6±3×10−5for ground Saharan sand,and4±2×10−6 for sieved Saharan sand.Hanisch and Crowley[2003b]alsomeasuredγO3on authentic Saharan dust with a Knudsen re-actor at296K.TheirγO3for authentic Saharan dust surfacesdepended on O3concentration.They foundγO3varied be-tween1.5×10−4and5.5×10−6for the initial uptake coe fficient with an approximation of3×10−5at30ppbv O3 STP and between4.8×10−5and2.2×10−6for the steady-state uptake coefficient with an approximation of7×10−6at30ppbv O3STP.Our base-valueγO3is5×10−5.Thisis between the initial and steady-stateγO3from recent labexperiments.From direct and indirect evidence,we assume aγO3range of2.2×10−6–1.0×10−4.Dentener et al.[1996]estimatedγHNO3>10−3basedon indirect evidence from HNO3resistance to various soils. HNO3uptake on dust particles is followed by a simple neutralization reaction when alkaline material such as cal-cium is present in the aerosol.DeMore et al.[1997]esti-mateγHNO3=0.038±0.008for amorphous carbon and(2.8±0.3)×10−2for solid powdered seasalt.For water dropletsγHNO3∼0.1[Doren et al.,1990;Worsnop et al., 1989].In the previous model studies,Dentener et al.[1996]choseγHNO3=0.1and Zhang and Carmichael[1999] chose0.01as the base-value with a range of0.001–0.1.Direct observations ofγHNO3on various oxide particlesand authentic dust samples using a Knudsen cell reactorhave recently been reported[Goodman et al.,2000;Hanischand Crowley,2001a;Underwood et al.,2001a,b;Grassian,2002].In laboratory measurements of HNO3uptake onCaCO3as a function of relative humidity(RH),Goodmanet al.[2000]foundγHNO3∼(2.5±0.1)×10−4in dry con-ditions.γHNO3increased in the presence of water vapor,to2.5×10−3at20%RH.The upper limit wasγHNO3∼0.05. Underwood et al.[2001a]observed a large irreversible initialγHNO3on dry Gobi dust of2.7×10−2–1.04×10−1.Aftertaking into account gas diffusion into the underlying layersof a porous sample,this group found the true initial uptakecoefficients of5.2×10−5for Gobi dust and2.0×10−5forSaharan dust[Underwood et al.,2001a;Grassian,2002].Water vapor enhances the dryγHNO3about by factorsof50and160for20and80%RH,respectively[Grassian,2002].Applying these factors leads to true initialγHNO3 on mineral dust of1.0×10−3and8.32×10−3for20and80%RH,respectively.These are maximum estimates sinceinitial uptake decreases to steady-state.Underwood et al.[2001b]adjustedγHNO3for multiple collision caused by theroughness of the individual particles and foundγHNO3∼1.1×10−3for China Loess.Unfortunately,γHNO3for Sa-haran sand was impossible to correct for this effect due to itslarge size distribution.Hanisch and Crowley[2001a]observed a largeγHNO3 on various authentic and synthetic mineral dust and mineraloxide surfaces.They foundγHNO3=(11±3)×10−2forSahara dust,and(6±1.5)×10−2for Arizona dust.Contraryto Underwood et al.[2001a],Hanisch and Crowley[2001a]find that porosity plays no significant role inγHNO3for Chi-nese dust.Our base-value ofγHNO3=1.1×10−3from ameasurement of China Loess[Underwood et al.,2001b]ismuch lower than the large irreversible uptakes ranging from4.5×10−2–1.4×10−1measured by Hanisch and Crow-ley[2001a].We examine this uncertainty choosing aγHNO3 range of2.5×10−4–1.5×10−1.No direct measurement ofγNO3on mineral dust has beenreported and the reaction mechanism is not clear[Denteneret al.,1996].Measurements ofγNO3on other condensedmaterial are also sparse.Thomas et al.[1993]reportedγNO3=2×10−4for NO3uptake by liquid water.Zhangand Carmichael[1999]chose a base-valueγNO3=0.1with a range of0.01–0.2.We choose a base-valueγNO3=0.1 with range2.0×10−4–0.2.We multiply the base-values forγHNO3,γO3,andγNO3−0.1−0.08−0.06−0.04−0.02−0.1−0.08−0.06−0.04−0.02−0.1−0.08−0.06−0.04−0.02−0.1−0.08−0.06−0.04−0.0290NFigure 4.As in Figure 3but for spatial distribution (EOF 1)and temporal behavior (PC 1)of ∆O 3H O 3simulated using up-take coefficients of the minimum,the 0.5,1.0,and 2.0times the base-value γO 3,and the maximum γO 3.The maximum γO 3is twice the base-value.by the same uncertainty factors (0.5,1.0,and 2.0)to char-acterize the correlation of O 3responses to uptake coeffi-cients.We also examine the potential heterogeneous O 3variation range by using the lower and upper uptake coef-ficient bounds.Figures 4,5,and 6show the resulting pri-mary modes of ∆O 3H O 3∆HNO 3H O 3,and ∆NO 3H O 3respec-tively.The O 3reduction is approximately linear with γO 3.However,O 3reduction due to γHNO 3and γNO 3is non-linear.The sensitivity of ∆X H O 3to γX decreases as species X changes from O 3,HNO 3,to NO 3.Thus the im-portance of HNO 3in ∆H O 3decreases while the importance of O 3increases for the same relative increase in γ.If our assumed γHNO 3(1.1×10−3)is too high and our assumed γO 3(5.0×10−5)is too low,then O 3uptake might be more important for O 3reduction than HNO 3uptake.On the other hand,direct O 3uptake is not the dominant pathway in het-erogeneous O 3variation unless our base-value coefficients are in significant error globally.For our base-value coeffici-ents,∆O 3H O 3exceeds ∆HNO 3HO 3only in Spring.−0.15−0.1 −0.05−0.15−0.1−0.05−0.15 −0.1−0.05 −0.15 −0.1−0.05 −0.15−0.1−0.0590N1Figure 5.As in Figure 4but for HNO 3.Figure 7shows the model and observations of the Jan-uary O 3vertical profile over Abidjan (5◦N,4◦W)from the 1994–1999MOZAIC experiment [Martin et al.,2002].We compared three modeled dust perturbations of O 3to the ob-servations:no mineral dust influences at all;dust photolysis effects;and dust photolysis and heterogeneous uptake with two sets of uptake coefficients.For the latter,one simula-tion (thick dashed line)uses our base-value uptake rates for heterogeneous mineral dust reactions.As discussed in Sec-tion 3.3,Hanisch and Crowley [2001a ]found smaller γO 3and larger γHNO 3than our base-values and our base-value γNO 3is three orders of magnitude larger than γNO 3mea-sured for liquid water.Our final model experiment (thick dash-dot line)tests these alternative findngs by adopting γO 3=7.0×10−6,γHNO 3=0.1,and γNO 3=0.01.The modeled mineral dust influence occurs below 500mb.Both photolysis and heterogeneous perturbations reduce O 3。