## Review of the IMPROVE Equation for Estimating Ambient Light Extinction Coefficients
J. L. Hand and W

. C. M a lmTABLE OF CONTENTS Abstract

....................................................................................................................... .................... 1 1. Introduction

................................................................................................................ ............... 1 2. Sa m p ling Biases

............................................................................................................. ........... 5 2.1. Nitrate Sampling Issues

.................................................................................................. 7 2.2. Ammonium Sa m p ling Issues

.......................................................................................... 9 2.3. Carbonaceo us Aerosol S a m p ling Issues

....................................................................... 10 2.4. Issues Related to Elem enta l Species and Coarse Mass

................................................. 12 3. Che m ical and Physical F o rm s of Spe c ies in the IMPROVE Equation

................................... 13 3.1. Particulate Organic Material (POM)

............................................................................. 13 3.2. Nitrate

................................................................................................................... ........ 26 3.3. Sulfate

................................................................................................................... ........ 31 3.4. Soil Com p osition

.......................................................................................................... 33 3.5. Coarse Mass

............................................................................................................... ... 35 3.6. Sea Salt..................................................................................................................

........ 37 3.7. Size Distributions

........................................................................................................ .. 38 Urban Observations

.......................................................................................................... 41 Rural Observations............................................................................................................ 4 2 Recent Obs e rvations of Size Distributions Using DMA an d OPC Data at Nation a l Park Service Special S t udies

..................................................................................................... 43 Southeastern Aerosol and Visibility Study (SEAVS)

................................................... 43 Grand Canyon Visibility Study (GRAVS)

................................................................... 43 Big Bend Regional Aerosol and Visibil ity Observational Study (BRAVO)

................ 43 Yose m ite Aerosol Characterization S t udy (YACS)

..................................................... 44 4. Hygroscopic Growth

.......................................................................................................... ..... 44 5. Mass Scattering Efficiencies

................................................................................................ ... 52 5.1. Theoretical Discussion

.................................................................................................. 52 5.2. Methods for Deriving Mass Scattering Efficiencies

..................................................... 59 5.3. Survey of Mass Scattering Efficiencies

........................................................................ 62 5.3.1. Theoretical Method

............................................................................................... 64 5.3.2. Measurem ent Method

........................................................................................... 67 5.3.3. MLR Method

........................................................................................................ 69 5.3.4. Partial Scattering Method

..................................................................................... 71 5.3.5. Apportionment Method

......................................................................................... 72 5.3.6. Mass Absorption Efficiencies

............................................................................... 75 5.4. Estim ates of Dry Mass S cattering E fficiencies from IMPROVE Data

........................ 78 6. Evaluation of the Com b ined Data Set

................................................................................... 110 7. Biases between Reconstructe d and Measured S cattering

..................................................... 114 8. Summ ary of Suggested Refine m e nts to the IMPROVE Equation........................................ 121 References

..................................................................................................................... .............. 126

iLIST OF FI GURE S Figure 1. Mean values of R oc m u ltip lie r de rived f r om an ordina ry least squ a re multi- linea r regression analysis (equation 6).

....................................................................................... 21 Figure 2. Mean seaso n al valu es o f R oc for all sites. S t andard deviations are also shown as upper and lower error bars.

......................................................................................................... 2 2 Figure 3. (a) Fine m o de (D p < 1 μm ) nitrate speciation of NH 4 NO 3 , NaNO 3 and Ca(NO 3 ) 2 at several IM PROVE sites. The size of the pie chart reflects th e magnitude of the concentration of total nitrate in this size m ode, which is lis ted under each chart. (b) Sam e as (a) bu t for D p < 3.2 μm. (c) Sam e as (a) but for coarse m o de (D p > 1 μ m ).

................. 27 Figure 4. Mean value s of the soil coef f i cien t f r om an ordinary lea s t square multi- linea r regression analysis (equation 6).

....................................................................................... 35 Figure 5. (a) f (RH) curves using the “ no solids” m e thod for amm o ni um sulfate, ammonium bisulfate, an d sulfuric acid (a ssum i ng a size distribution with D g = 0.4 μm and σ g = 1.9). (b) Sulfate m a ss scattering efficien cies for a mmonium sulfate, amm onium bisulfate, and sulf uric acid using the c u rves in pa r t (a ). (c) Ratios of ammonium bisulfate and sulfuric acid m a ss s cattering efficien cies to the a mmonium sulfate m a ss scattering efficiency shown in (b).

.................................................................................................................. ... 50 Figure 6. (a) Diagram contrasting m a ss scattering efficien cies for internally versu s externally m i xed particles. (b ) Pa rtial sc attering efficienc i es for internally and e x terna lly m i xed particles.

..................................................................................................................... ....... 56 Figure 7. Method 1 measured to tal am bient scattering and reco nstructed total scattering using equation 25 for Acadia National Park.

.............................................................................. 87 Figure 8. Method 2 recons tructed m i xed scattering ( b mix,est , Mm -1 ) com p ared to m easured m i xed scattering ( b mix , Mm -1 ) using equation 20 (fine mode contributions) for Acadia National Park.

.......................................................................................................................... ........ 88 Figure 9. The com p arison of fi ne mode m i xed inorganic and organic mass concentrations ( M mix , μg m -3 ) and the SCF for Acadia National Park. T h e Th iel regression line is shown.

...... 90 Figure 10. Com p arisons of m e thod 3 reconstructed m i xed scattering ( b m i x,est , Mm -1 ) to m e asured m i xed scattering ( b mix , Mm -1 ) for Acadia National Park.

.................................................. 91 Figure 11. Method 4 estim ates of reconstructed scattering compared to measured scattering ( b sp , Mm -1 ) for Acadia National Park.

....................................................................................... 93 Figure 12. Map of the m ean a mmonium sulfate m a ss scattering efficiencies (m 2 g -1 ) for the United States derived using m e thod 1. The size of the circle reflects the magnitude of the efficiency, which is printe d next to the circle.

.................................................................. 95 Figure 13. Map of the m ean POM m a ss scattering efficiencies (m 2 g -1 ) f o r the United Sta t es derived using m e thod 1. The size of the circle reflects the m a gnitude of the efficiency, which is printed next to the circle.

.................................................................................... 96 Figure 14. Map of inorganic specific m a ss scattering efficiencies ( α i nor g

, m 2 g -1 ) f o r the United States using m e thod 2. The size of the circle reflects the m a gnitude of the efficiency, which is printed next to the circle.

.................................................................................... 99 Figure 15. Map of organic (POM) m a ss scattering efficiencies ( α or

g

, m 2 g -1 ) f o r the United State s using m e thod 2. The size of the circle reflects the m a gnitude of the efficiency, which is printed next to the circle.

................................................................................................ 100

iiFigure 16. Map of percent change in specifi c mass scattering efficiency (for either α inorg or α org ) due to a doubling of m i xture m a ss ( M mix ) using m e thod 3. The size of the circle reflects the m a gnitude of the change, which is printed next to the circle.

................................... 102 Figure 17. Map of the intercept fr om the Theil regression in m e thod 3. The size of the circle reflects the m a gnitude of the intercept, wh ich is printed next to the circle.

................... 103 Figure 18. Map of m e an inorganic sp ecific m a ss scattering efficiencies ( α inorg , m 2 g -1 ) from m e thod 3. The size of the circle reflects the m a gnitude of the efficiency, which is printed next to the circle.

............................................................................................................ . 105 Figure 19. Map of organic m a ss scattering efficiencies ( α org , m 2 g -1 ) from m e thod 3. The size of the circle ref l ects the m a gnitude of the effici ency, which is printed next to the circle.. 106 Figure 20. Map of the m ean a mmonium sulfate m a ss scattering efficiencies ( α AS

, m 2 g -1 ) fro m m e thod 4. The size of the circle reflects the m a gnitude of the efficiency, which is printed near the circle.

............................................................................................................... .. 109 Figure 21. Map of m e a n POM ma s s scattering efficiencies ( α POM , m 2 g -1 ) from method 4. The size of the c i rc le ref l e c ts the m a gnitude of th e efficien cy, which is printed near the circle.

............................................................................................................................... .......... 110 Figure 22. The average biases fo r each site corresponding to tim e periods with low m easured scattering values (10–20%) (see Table 26).

.................................................................... 116 Figure 23. The average biases fo r each site corresponding to tim e periods with m e dian m e asured scattering values (45–55%) (see Table 27).

.................................................................... 117 Figure 24. The average biases for each site co rresponding to tim e periods with high m e asured scattering values (80–90%) (see Table 28).

.................................................................... 118 Figure 25. Average biases for the com b ined data set (all sites and tim e) for tim e pe riods with low (10–20%), m e dian (45–55%), and high (8 0–90%) scattering ranges , as calculated using m e thods 3 and 4, and the current IMPROVE algorithm. Also shown is the average of the per-site biases from Tables 26–28. T h e f (RH) curves were calcu lated for continuous growth from 1 < RH < 90%.

........................................................................ 118 Figure 26. Average biases for the com b ined data set (all sites and tim e) for tim e pe riods with low (10–20%), m e dian (45–55%), and high (8 0–90%) scattering ranges , as calculated using m e thods 3, 4, and the current IMPROVE algorithm. The f (RH) curves were calculated from 1 < RH < 95% assum i ng crystallization growth curves.

....................... 119

iiiLIST OF TABLES Table 1. Statis tic ally signif i cant (95%) regression coefficients us ing the ordinary least square multiple -lin ear reg r ess i on analysis (equation 6) . Site code is in th e f i r s t colum n. The rem a ining colum n s correspond to coefficients associated with amm onium sulfate (AS), ammonium nitrate (A N), particulate orga nic m a tter (P OM), light-absorbing carbon (LAC), soil, and sea salt, resp ectively. Insignifican t coefficients are replaced with “.”.

. 16 Table 6. Summary of mass scattering efficienci es reported in Tables 2 through 5 (Appendix 2). The “Apportionm ent” colum n refers to re sults from White (1991). The “IMPROVE” colum n lists values used in the current IMPROVE for m ula tion. Entries correspond to the f i ne m ode unless o t her w ise sta t ed in the ro w header. Sulf ate efficien cies co rrespo nd to dry amm oni um sulfate, and POM efficien cies h a ve been no rm alized to an R oc value of 1.8............................................................................................................................

.......... 74 Table 8. V a lues used for the dry m a ss scattering efficiencies for th e large and small m a ss size distributions for each species.

........................................................................................... 83 Table 9. A statistical summ ary of m a ss concentrations (μ g m -3 ) at A cadia Na tio nal Park. CM and FM refe r to gravim etri c coarse m a ss and fine (PM 2. 5 ) mass, respectively. AS and AN refer to am monium sulfate and ammonium nitrate, resp ectiv ely. P O M is p a rticula t e organic m a tter using an R oc factor of 1.8. Mass units are ( μ g m -3 ). RH refers to am bient rela tive hum idity. The n u m b er of nephelelom e te r data points in a 24-hr average is given by N(b sp ) . The values of the revised f

(RH) curves for the ambient RH ( f

(RH) amb, new ) and the nephelom e ter chamber RH ( f

(R H) chamb, new ) are also listed. Sim ilar values are reported for the current f (RH) curves ( f

(RH) amb, old and f (R H) chamb, old ).

........................................... 84 Table 10. A summ ary of b sp (Mm -1 ) for Acadia National P a rk. Va lues correspond to m e asured tota l am bient sca tte ring ( b sp ), recons truc ted to tal am bient sc atte ring ( b sp_recon ), m e asured scattering as sociated with inorganics and organics ( b mix ), estim a ted scattering asso ciated with inorganics and organics ( b mix_est ), scattering due to ammonium s u lfate ( b sp ( AS ) ), ammonium nitrate ( b sp ( AN ) ), particulate organic m a terial ( b sp ( POM ) ), soil and co arse m a ss ( b sp ( soil+CM ) ), sea salt ( b sp ( SS ) ), and water ( b sp ( H 2 0 ) )

. Light absorption ( b ap ) was com puted assum i ng a m a ss absorption efficien cy of 10 m 2 g -1 . New f (RH) curves were used to estim ate wet sc attering. POM was computed assuming an R oc factor of 1.8 and m a ss scattering efficiency of 3.8 m 2 g -1

. ........................................................................... 85 Table 11. Fractional contribution to total ambient scattering at Acadia National Park using equation 25. AS corresponds to ammonium su lfate and AN corresponds to ammonium nitrate. Particulate organ i c m a tter (P OM) fractio n was com p uted assum i ng an R oc factor of 1.8. The coarse m ode fraction is given by CM.

............................................................ 86 Table 12. T h e results from m e t hod 1 for Acadia National Park (s ee equation 17). The regression coefficients ( a i ) are listed, along with the standa rd error. Derived m a ss scatterin g efficiencies are also list ed for ammonium sulfate (A S ) , amm onium nitrate (AN), particulate organic m a tter (POM = 1.8·OC), coar se m a ss combined with soil (soil+CM). and sea salt. The num b e r of valid cases wa s 267 and there were 370 m i ssing data points. The r 2 coefficient was 0.95.

.............................................................................................. 86 Table 13. Results for method 2 for estim ating speci fic m a ss scattering effici encies for inorganics ( α inorg ) and organics ( α

or

g ) for Acadia National Park. See text for full description.

........ 88 Table 14. Results of the m e thod 3 Thiel regression of SCF versus m a ss ( M mix = inorganics + organics ) for Acadia National Park.

................................................................................. 89
ivTable 15. Method 3 estim ates of the overall m ean and upper and lower specific scattering efficiencies associated with the 15% uppe r and lower m a ss concentrations of mixed inorganic and organic m a ss fo r Acadia National Park...................................................... 90 Table 16. S u mm ary of the m e thod 3 SCF and sp ecific m a ss scattering ef ficiencies fo r ino r ganics ( α inorg ) and organics ( α or

g ) for Acadia National Park.

...................................................... 91 Table 17. Method 4 estim ates of the m ean, and th e upper and lower m a ss scattering efficiencies (m 2 g -1 ) associated with the 15% upper and lo wer m a ss concentrations for Acadia National Park.

................................................................................................................. .. 92 Table 18. S u mm ary of m a ss scattering efficiencies (m 2 g -1 ) and standa rd erro rs for all sites us ing m e thod 1. Mass scattering efficiencies are lis ted for ammonium sulfate (AS), ammonium nitrate (AN), particulate or ganic m a tter (POM = 1.8·OC), soil and coarse m a ss (soil + CM), and sea salt..............................................................................................................

. 94 Table 19. S u mm ary of specific m a ss scattering efficiencies (m 2 g -1 ) for inorganics ( α inorg ) and organics ( α or

g ) for all sites using m e thod 2.

...................................................................... 98 Table 20. Summ ary of the results from m e thod 3 using the Thiel regression of SCF and m a ss ( M mix ) for each site. Th e fourth colum n corresponds to th e percen t change in sp ecific m a ss scattering efficiency (either for inorga nic or organics) from a doubling of the m i xed inorganic and organic m a ss concentration ( M mix ).

.......................................................... 101 Table 21. The m ean, upper, and low e r specific scattering efficienci es for inorganics ( α inorg ) a nd organics ( α or

g ) com puted with m e thod 3. The upper and lower estim ates are calculated by averaging the specific scatteri ng efficiencies associated with the upper and lower 15% m i xed mass concentrations ( M mix ). The percent change between the upper and lower m a s s scattering efficiencies (final colum n ) corresponds to both ( α inor g ) and ( α org ).

............... 104 Table 22. The m ean, upper, and lower specific scattering efficiencies (m 2 g -1 ) for ammonium sulfate (AS), amm onium nitr ate (AN), and particulate or ganic m a tter (POM) computed with m e thod 4. The upper and lower estim a te s are calculated by averaging the m a ss scattering efficiencies associated with th e upper and lower 15% m a ss concentrations. The percent changes between the upp er and lower m a ss scattering efficien cies are sho w n in the final three colum n s.
................................................................................................... 108 Table 23. A statistical summ ary of m a ss conc entrations (μg m -3 ) f o r the com b ined data set (a ll optica l m onitor i ng s ite s excep t Pho e nix and th e Virgin Islands). CM and FM refer to gravim etric coarse m a ss and fine (PM 2. 5 ) mass, respe c tively. AS and AN refer to ammonium sulfate and amm oni um nitrate, res p ectiv ely. P O M is particulate organic m a tter using an R oc factor of 1.8. RH refers to ambi ent relative hum idity. The number of nephelom e ter data points in a 24-hr average is given by N(b sp ) . The values of the f (RH) corresponding to the nephelom e ter cham ber fo r the ammonium sulfate sm all m ode, l a rge mode, current IMPROVE estim ate, and NaCl curves are also listed. The contribution to fine m a ss is provided in parentheses.

.............................................................................. 111 Table 24. A summ ary of the low, m ean, and high m a ss s cattering efficiencies (m 2 g -1 ) for th e com b ined data set with m e thod 4 (M4-C), two statistical corrections to m e thod 4 results (M4-C1 and M4-C2, see text), and results fr om m e thod 3 applied to the com b ined data (M3-C). Results correspond to ammonium sulfate (AS), a mmonium nitrate (AN), and particulate organic m a terial (POM).

............................................................................... 112 Table 25. A summ ary of b sp (M m -1 ) f o r the com b ined data s e t (all m onitoring site s exc e p t Phoenix and the Virgin Islands). Values corre spo nd to m easured tota l ambient sca t ter i ng ( b sp ), recons truc ted to tal am bient scatter i ng ( b sp _re c on ), m easured scattering associated with

vfine m ode inorgani cs and organics ( b mix ), es tim ated scattering asso ciated with inorganics and organics ( b mix_est ), scattering du e to amm o nium sulfate ( b sp ( AS ) ), a mmonium nitrate ( b sp ( AN ) ), particulate organic m a terial ( b sp ( POM )), sea salt ( b sp ( SS ) ), and water ( b sp ( H 2 0 ) ). Light absorption ( b ap ) was com puted assum i ng a mass absorption efficiency of 10 m 2 g -1 . New f (RH) curves were used to estim ate wet scattering.

............................... 113 Table 26. Average biases for tim e periods with low (10–20%) m easured scattering values for m e thods 1–4 and the curre nt IMPROVE equation.

........................................................ 115 Table 27. A v erage biases for tim e periods with the m e dian (45–55%) m eas ured scattering values for m e thods 1–4 and the current IMP R OVE equa tion.................................................... 116 Table 28. Average biases for tim e periods with high (80–90%) m easured scattering values for m e thods 1–4 and the curre nt IMPROVE equation.

........................................................ 117 Table 29. Values used for the dr y m a ss scattering efficiencies (m 2 g -1 ) for the large and sm all m a ss size distributions for each sp ecies (amm onium sulfate, amm oni um nitrate, and particulate organic m a terial, POM)................................................................................. 124 Disclaimer The assum p tions, findings, conclusions, judgm e n ts, and views presented herein are those of the authors and should not be interpreted as nece ssarily representing the National P a rk Service polic ies.

viABST RACT The Interagency Monitoring of Protected Vi sual Environm ents (IMPROVE) protocols for reconstructing a m bient light extinction from m easured aerosol species are th e basis for evaluating com p liance under the Regional Haze Ru le. W e review the assum p tions involved in

com puting reconstructed light extinction using the IMPROVE pr otocol. This review includes

exam ining the biases in the m easurem ents of aerosol com p osition, th e assum e d chem ical forms of aerosol species, particle hygroscopicity, and assum e d mass scattering e fficiencies. W e present a thorough survey of estim ates of m a ss sc atte ring efficiencies from recent peer-reviewed literature. F u rtherm ore, we use IMP R OVE nephel om etry and com position data to estim ate m a s s scattering efficiencies using a variety of m e thods. The current m a ss scattering efficiencies applied in the IMPROVE equation are then interpre ted in the context o f this survey and results derived from the IMPROVE data analyses. F i na lly, a summ ary of provis ional recomm endations for refine ments to the IMPROVE equation and a discussion of i m portant uncertainties to consider in the assum p t i ons are presented. Al though tentative recomm endations of refinem e nts to the IMP R OVE equa tion are presented, final refinem e nts to the IMPROVE equation await future discussions of the results presented here.
1. Introductio n The role of aerosols in visibili ty degradation has been the s ubject of res earch for several decades, bu t recen tly interest has intensified with attem p ts to quantify the optical p r operties of aerosols, especially because of the uncertaintie s surrounding the role of aerosols in clim ate change and because of the need for com p liance unde r the Regional Haze Rule. In most instances, visibility re duction is p r im arily due to scatte rin g and absorption by particles. Particle scattering and absorption properties can, w ith a num b er of lim iting assum p tions, be calculated using Mie theory (Mie, 1908; van de Hulst, 1981).

1Com p liance under the Regional Haze Rule is based on protoco l s for reconstructing aerosol m a s s and light extinction ( b ext ) from speciated m a ss con centrations. Reconstruction equation s are used to estim ate P M 2. 5 m a ss concentrations (for particles with aerodynam i c diam eters less than 2.5 μm ) as we ll as light extinction coefficients. Dry PM 2. 5 fine m a ss is

com puted using equations 1 and 2
PM 2. 5 = (NH 4 ) 2 SO 4 + NH 4 NO 3 + POM + LAC + Soil ( 1 ) Soil = 2.2 Al + 2.49 Si + 1.94 Ti + 1.63 Ca + 2.42 Fe ( 2 ) where su lfate is assumed to be fu lly neutralized amm oni um sulfate ( (NH 4 ) 2 SO 4 ) , nitrate is

assum e d to be in the form of a m monium nitrate ( NH 4 NO 3 ), and organic carbon is included as particulate organic m a terial (POM), co m puted by m u ltip lying organic carbon (OC) concentratio ns by a m o l ecular weig ht per ca rbo n weight ra tio (POM = R oc · OC). Light-absorbing carbon is referred to as LAC. W e use the term LAC bec a use it is m o re representative of the optical properties of light-absorbing carbon rath er than elem ental (EC) or black carbon (BC), although th ese term s are often used interch a n g eably in th e literature. Fine soil co ncentration s include the contributions from assum e d for m s of elem ental species (eq u ation 2) (Malm et al., 1994b). Mass concentrations are given in units of μg m -3

. The ligh t ex tinction co efficient ( b ext ) includes the contributions from light scattering by particle s ( b sp ) and gases ( b sg ), and light absorp tion by particles ( b ap ) and g a ses ( b ag ). b ext = b sp + b ap + b sg +b ag (3) The only gas in the atm o sphere that absorb s visible light is n itrogen dioxide, NO 2 . Absorption by
NO 2 at a wa velength of 550 nm is com puted as b ag = 330[NO 2 ] , where the units of b ag are Mm -1 (Mm -1 = 10 -6 me t e r s -1 ) and the units of [N O 2 ] are ppm (Dixon, 1940; H odkinson, 1966). Light scattering by gases ( b sg ) is described by Ra yleigh scattering theory (van de Hulst, 1981).

2Rayleigh scattering is isotropic a nd is near ly co mpletely po lar i zed f o r light sca tte ring at 90° to incom i ng radiation. Rayleigh scattering is propor tional to molecular number density and has a strong spectral dependence ( λ -4
, wh ere λ is the wavelength of light). Correspondingly, b sg = 12
Mm -1 at sea level and λ = 550 nm

. Reconstructed scattering and absorption by particles as form ulated in the IMPROVE (Interagency Monitoring of Protected Visual En vironm ents) protocol ar e given by equations 4 and 5, respectively, assum i ng an externally m i xed aerosol. b sp = 3.0 f(RH) AS [AS ] +3.0 f ( RH ) AN [AN ] + 4.0 R OC [OC ] + 1.0 [Soil ] + 0.6 [CM ] (4) b ap = 10.0 [LAC ] (5) Estim ates of total am bient b sp in this f o rm ulation are in un its of Mm -1 and correspond to visible wavelengths ( λ ~ 550 nm ). This form ulation assum e s that contributions to total am bient light scattering are from ammoni um sulfate (AS), a m m onium nitr ate (AN), organic carbon (OC), soil, and co arse m a ss (CM). Each species has a corresponding dry m a ss sca ttering or absorption efficiency ( α ) in m 2 g -1 . The term s in the brackets correspon d to m a ss concentr ation s in μg m -3

. Organic carbon m a ss is multiplied b y an or ganic aerosol m a ss to organ i c carbon ratio, R oc = 1.4, to estim ate particulate o r ganic m a tter. The effects of the uptake of water as a function of relative hum i dity (R H) by hygroscopic species are estimated by the f (RH) factor. The form ula tion of the equations used in the IMPROVE reconstruc tions (equations 1–5) requires a num b er of as sum p tions. Each assumpti on has associated uncertainties that obviously will have co nsequences for reconstructed extinc tion, albeit to varying degrees. The purpose of this report is to evaluate or com m e nt on e ach assum p tion, and when possible, suggest refinem e nts. Refine m e nts of m a ny of the assum p ti ons are not suggested at this tim e because data do not currently exist to support m o difications, or they woul d require further m easurem ents to

3characterize. Suggested refine m e nts do include increasing the R oc factor used to com pute particulate organic m a tter and m odifying the f (R H) factor to reflect some water asso ciated with particles below a relative hum idity of 40%. Mass scattering efficiencies for amm o nium sulfate and POM m a y also be adjus t ed to reflect cu rrent data. The assum p tions and som e related questions are listed below, al ong with the section in which they are discu ssed. Although estim ating u n certainties and their co mbined eff ects on extinction from the assum p tions described in the follow i ng sections is im portant, it is beyond the scope of this report.

• Section 2. S a m p ling biases: definitions and descrip tions of their eff ects on nitrate (2.1), ammonium (2.2), carbo n aceous aerosols (2.3 ), and elem ental and coarse m a ss (2.4).

• Section 3. Che m ical and physical for m s of species : m u ltip lier used to com pute particulate organic m a tter from organic carbon (3 .1), nitrate as a m m onium nitrate (3.2), sulfate as ammonium sulfate (3.3), soil com position (3.4 ), coarse m a ss speciation (3. 5 ), sea salt (3.6), and size distributions (3.7).

• Section 4. Hygroscopic growth curves and scattering enhancem ent curves ( f

(RH)): hygroscopicity of species, assum e d growth curves, and relative hum idity ranges.

• Section 5. Mass scattering efficiencies : theore tical discu ssion of mass scattering efficiencies (5.1), review of m e thods used for deriving e fficiencies (5.2), survey of reported efficiencies (5.3), and derive d values using IMPROVE data (5.4).

• Section 6. Evaluation of m e thods for com puting m a ss scattering efficiencies using the

com b ined IMPROVE data se t.

• Section 7. Discussion of com puted biases be tween m e asured and reconstruc ted scattering for various m e thods of cal culating m a ss scattering efficiencies.

• Section 8. Suggested refinem e nts of IMPROVE equation.

42. Sampling Biases Before investig ating the assum p t i ons involv e d for each species included in the IMPROVE equation, it is of interest to review an y sam p ling issues or uncertainties related to the

m easure m ents of these species. The IMPROVE ne twork utilizes four separate sam p ling m odules to characterize the PM 2. 5 aerosol composition and total m a ss. Module A is equipped w ith Teflon ®
f ilter s used f o r analys is of PM 2. 5 m a ss by gravim etry and elem ental com position by X-ray fluorescence (XRF). In module B, nylon filters are us ed to collect particles for ion analysis us ing ion ch rom a tography (IC). The m odule is p r eceded by a denu der designed to captu re acidic gases. Module C incorporates quar tz filters for use in qu antifying organic and light -absorbing carbon by therm a l optical reflectance (Chow et al., 1993), and m odule D uses Teflon ® f ilter s to colle ct particle s f o r gravim etric PM 10 total m a ss m easurem ents. Sa m p ling artifacts, or biases, are not unco mmon with filter sam p ling. An artifact is def i ned as a ny increa se or decre a se in the m a te r i al be ing sa mpled that r e sults in a positiv e or negativ e bia s in the am bient conc e n tra tion m e as ured. Artifacts can occur due to contam ination issues (con tam i nation of the f ilter m e dium or of the cassettes during tr ansport) or adsorption of gases on the filter m e dium during sa m p ling or transpo r tation and h a ndling. Th ese types o f artif acts are consid ered positiv e. Ne gative sam p li ng artif acts ar ise f r om vola tiliza t ion of gases f r om disassociated par t icle s on the f ilter o r du ring handlin g af ter collection (Mc D ade et al., 2004). Sampling biases affect aerosol species differently, depending on the volatility of the particles being m easured and the sampling techni que being used; theref or e applying corrections for sam p ling biases is not always straightforward. Corrections of IMPROVE data due to sam p ling ar tifacts have been applied as part of the routin e IMP R OVE m e thodology sin ce the begin n ing of the network. We will briefly review the

m e thodology IMPROVE applies for ar tifact correction and then di scuss recent research about

5artifacts that are associated with sp e c if ic spe c ies , such as ni trate, amm o nium , and carbonaceous aerosols. Dyna m i c field blanks for both Teflon ® and nylo n f ilte rs ar e colle cted at all of th e sites. These filters are trea ted like network filters in th a t they are placed in the s a m p ler, but no sam p le air is drawn through them. Concentrations on Teflon ® field blanks are sta tistica lly ins i gnif i can t, so no corrections are m a de for m easurem ents on Teflon ® filters. The con centration s m easured on the nylon filter field blanks are su btracted fro m the m easured fi lters. Monthly me di an ar ti fact corrections have been applied to th e data s i nce the change in IMPROVE data processing from seasonal to monthly in June 2002. Th ese corrections are applied sepa rately for each ion. Analysis of artifacts o n the nylon filter sugge s t s that su lfate ion artifacts ar e typically less than 10% of the

am bient concentration, and n itrate artifacts range between 10 and 20% (McDade et al., 2004). Further discussion of nitrate ar tifacts, including discussions on denuder efficiency will be presented in the next section. Quartz field blanks are also collected at al l of the sites, but quartz af ter-f ilter s are colle cted at six s ites only. The after-filte rs a r e placed b e hind the p r im ary qua rtz filter and a r e designed to capture organic gases (p ositiv e artifa ct). Negativ e artifacts for carbonaceous aerosols

are assum e d to be insig n ificant co mpared to p o sitiv e artif acts, althou gh other s t u d ies sugges t negative artifacts (volatilization) can be im portant (Turpin et al ., 2000). Concentrations from the af

ter-f ilter s f r om the subset of site s a r e used to co rrec t f o r pos itiv e ar tif acts f r om data at all of the sites. Month l y m e dian values are als o used for q u artz filters, and each fr action of organic carbo n has a separate artifact correcti on. Typical artifacts for organic carbon can correspond to half of the reported a m bient concentr ation (McDade et al., 2004). A m o re in-depth discussion of carbonaceou s aeroso l artifacts will b e presented in section 2.3.

62.1. Nitrate Sa mpling Issues The nylon filters in m odule B are used for an alysis of particulate nitrate because the nitrate ion is retained by the filter when ammonium nitrate disso ciates under conditions of high
tem p erature and low relative hum idity. P r eced ing th e filter is an annu lar denuder coated with
Na 2 CO 3 and glycerin to rem ove gaseous nitric acid that would othe rwise be re tain ed by the nylon filter. The denuders are serviced once per year during annu al m a intenance. A positive artifact could occur due to degradation of efficiency of the denuder w ith tim e , allowing nitric acid to be collected on the nylon filter. Ther efore characterizing the efficien cy of the denuders has been a topic of recent study (Ashbaugh et al., 2004; Yu et al., 2005a). Daily samples were collected for four consecutive weeks during diffe rent tim es o f the yea r a t IMPROVE sites, rep r es enting are a s with sign if ic ant se asonal nitrate contributions to fine m a ss (Bri gantine National W i ldlife Refuge NJ, Grand Canyon National Park AZ, San Gorgonio W ildern e ss CA, and Bondville IL). At each site a com b ination of IMPROVE ion m odules w ith different denuder configurations were operated. T h e denuder configurations were desi gned to com p are freshly coated denuders to denuders that had been previously exposed to high levels of nitr ic acid. The com b ination also represented different coating options, from the typical IMPR OVE coating to no coating. One module was operated with no denude r at all. For all the sites, no differences in nitrate concentrations due to the different denude r configurations were observed. The denuder configuration used regularly as a part of the IMPROVE networ k was found to be efficientl y

rem oving HNO 3 (Ashbaugh et al., 2004). As part of the sam e study, the extraction effi ciency of nitrate from the nylon filter was investigated (Yu et al., 2005a). Typically, basic solutions (e.g., s odium bicarbonate) are used to
extra c t nitra t e on nylon f ilters; ho wever, this leads to interf erence f r o m Na + ions during ion chrom a tography (IC). In stead, th e us e of deionize d water for extraction o f nylon filters has been

7investigated. Data from t h is study suggest that deionized water extraction with ultrasonification efficiently extracts nitrate and sulfate ions fr om nylon filters (Yu et al., 2005a) and successfully avoids issues of Na + and NH 4 + interference du rin g IC analys is. While the previous discussions suggest that n itrate m e asurem ents and artifacts from denuder-ny l on filter co nfiguration s are fairly well unders tood, the ef fects of nitrate lo ss on Teflon ® filters rem a in a sam p ling issue and have im portant im plications for m e a s urem ents of fine m a ss concentrations by gravim etry. Hering and Cass (1999) investigated the effects of nitrate loss from the Federal Refere nce Method (FRM) m easurem ents of PM 2. 5 m a ss on Teflon ® filters. They found that nitrate conc entrations w e re 28% lo wer on Teflon ® f ilters c o m p ared to nylon f ilte rs . Ammonium nitrate p a rticles a r e v o latile and d i sassoc i a t e to f o rm nitric acid gas an d ammonia gas, and th is reaction is v e ry sens itiv e to tem p eratu r e, pre ssure, and re lative hum idity. Changes in these param e ters during sam p ling can caus e significan t loss es of nitrate an d ammonium from the sampling m e dia, as Teflon ® f ilters do not retain nitric acid a s nylon f ilte rs do. Correcting m a ss concentrations for lost nitrate is difficult because kn owledge of the history of the equilibrium of ammonium nitrate/nitric acid and ammonia gases at the temperature,
pressur e , an d relative hu m i dity that the f ilter sub s tra t e exper i enced durin g the sam p ling period is required. Recent work by Frank (2005) suggests th at applying a therm o d ynam i c m o del can assist in reducing the uncerta inties in f i ne m a ss due to nitra t e volatilizatio n. Diurnal and seasonal trends in n i trate loss were observed by Hering and Cass (1999), as well as Ashbaugh and Eldred (2004) who perform e d a sim ilar study. The implicat ions for the negative artifact of sa m p ling volatile particles on Teflon ® filters are obvious. Underreporting ni trate concentratio ns results in

an overem p hasis of nonvolatile species such as dust and sulfate when com p uting m a ss concentrations. Com p arisons of reconstructed fine m a ss us ing the IMPROVE equation and

8gravim etric fine m a ss could be highly affected by significant underestim ati ons of nitrate due to the volatilization of ammonium nitrate from the Teflon ® f ilte r used f o r gr avim etric an alysis.
2.2. Ammonium Sampling I ssues Although ammonium is not routin ely analyzed as part of th e IMPROVE procedures, it is
im portant to review the sam p li ng issues related to ammonium to understand m easurem ents m a de during special s t udie s an d by oth e r r e sear chers. The ef f ects of ammonium loss f r om f ilte r m e dia were studied as part of the ni trate loss study described in the pr evious section (Yu et al., 2005b). Losses of ammonium are affect ed by sam p le location (urban versus rural), m e teorological

sam p ling conditions (e.g ., relative hu m i dity, temperatu r e), ch em ical composition of the sam p led aerosol, and gas-to-particle pa rtitioning. Volatilization of amm onium nitrate can lead to ammonium loss from filter m e dia, as can reactio n of a mmonium nitrate with strong acids. Also, when a m monium nitrate is captu red by the nylon filter, nitrate is bound by the filter bu t ammonium can volatilize. Two filter pack confi gurations were designed to study amm onium loss: denuded nylon-nylon (N-N) and denuded Teflon ® -nylon (T-N). Ammonium loss from nylon filters was observed at the fou r sites where m easurem ents were perfor m ed (ranging from ~ 10 to 52%), suggesting a single nyl on filter is not sufficient for captu r ing amm o nium nitrate. Results fro m the N-N and T-N filter pack system s suggest that the T-N configuratio n is as good as, or better than, the N-N configuration for ammonium retention (Yu et al., 2005b). Applying a correction f actor for the negative bias in amm o nium would require es tim a tes of ammonium loss
at ea ch site, which is a dif f i cult tas k. Understa nding the sampling biases for ammonium is very
im portant, especially during special studies when NH 4 + is measured, because its con centration s are required in pred ictin g the chem ical form of aerosol species, which reduces th e u n certainty i n reconstructed fine m a ss and light extinction.

92.3. Carbonaceous Aerosol Sampling Issues Understanding sam p ling biases for carbonaceo us aerosols is im portant for accurately quantifying the concentrations of organic and light-absorbing ca rbon and has been the focus of several studies. Before we discuss the sam p ling i ssues related to quantifying the concentrations of carbonaceous aerosols, we provide a brief revi ew of the analytical technique used by the IMPROVE network. The Desert Research In stitu te (DRI ) therm a l/o ptica l ref l e c t ance (TOR) technique used for IMP R OVE (Chow et al., 1993) is one of the therm a l m e thods available to analyze carb onaceous aerosols (also referred to as evolved gas analysis). Typically, for therm a l

m e thods the sam p le filter is heated in a step -wis e m a nner in different atmospheres (e.g., oxygen or helium ) a nd the vola t ilized ca rbo n f r om the filt er is detected. For each tem p erature reg i m e a carbon concentration is de term ined, with the lower tem p erat ure concentrations summ ed for organic carbon (O1, O2, O3, O4, and OP) and th e highest tem p erature regim e corresponding to what is typ i cally ref e r

r e d to a s e l e m ental or light-absorbing carbon (E 1, E2, and E3). A m o r e representative nom enclature would refer to this high tem p erature carbon as refractory carbon; because of its low vola tility it does not evolv e withou t o x idants at lower tem p eratures. The pyrolysis of organic carbon on th e filter as the tem p erature is increas e d can contribute to th e concentratio ns of refractory carbon. To account for this effect, the filter is m onitored by the reflectance (or transm ittance, as is u s ed in therm a l optical transm ittance m e thods) of laser light, which decreases when the filte r darkens due to pyrolys is. On ce oxygen is introdu ced in to the cham ber, the pyrolized carbon com busts, the filter lightens, and the laser light returns to its original intensity. After this point, the am ount of carbon m easured is associated with refractory (ligh t -ab s orbing) carbo n. The split between org a nic and lig h t-abso rbing carbon is b a sed on the conditions for which this process occurs and is dependent on refractory properties of both pyrolyzed and light-absorbing carbon. Huebert and Charlson (2000) disc uss several of the

10uncertainties associated with m easurem ents of therm a lly defined carbonaceous aerosols, especially pointing out that these m e thods differ from one laboratory to another (e.g.,
tem p eratures regim e s, rate of tem p erature chang e s, carrier g a ses in th e cham ber), m a king it very difficult to com p are resu lts. In sectio n 5.3 we will di scuss in more detail the issues related to the definition s o f OC and LAC by this m e thod. Turpin et al. (2000) review the difficulties in herent in m easuring particulate o r g a nic carbon. Interference from gaseous and condensable or ganics can result in sam p ling errors due to inte ractions with the f i lter m e dia. Positiv e ar tif a c ts ar ise f r o m adsorptio n of organic gases onto the f ilter, an d negativ e a r tif ac ts occu r due to vol atiliza tion o f particu l at e organics. T h ey repor t artifact contributions to organi c carbon m a ss ranging from -80 to +50%. Positive and negative artifacts occur sim u ltaneously, which m a kes corre c ting f o r th em dif f i cult. Subra m anian et a l

. (2004) utilized several sam p ling approaches in an attem p t to estim ate these artifacts. Depending on the types of denude rs and filter configurati ons, they found that positiv e artifacts could be elim inated, or that artif acts m a y depend on sam p ling duration and probably also depend on

sam p ling location. Huebert and Charlson (2000) state that system atic errors on the order of ±80% are possible using therm a l m e t hods. The IMPROVE network assum e s negative artifacts are insig n ificant and only corrects for positiv e a r tif acts tha t a r e estim ated f r o m quartz af te r-f ilte rs co llec t ed at si x sites (Chir i cahua AZ, Grand Canyon AZ, Yosem ite CA, Okefenokee GA, Shenandoah VA, and Mount Rainier W A ) (McDade et al., 2004 ). The after- filters are placed directly behi nd th e prim ary q u artz filter. Quartz filter field blan ks are co llected at ev ery site and are only used for identification of problem s. Field blank filters and th e af ter-f ilter s have sim ilar c oncentrations; however, the afterfilters are us ed because they are exp o sed to the sam e air sample as the prim ary filte r. Artifacts

11are d e term ined separately for each fraction of organ i c an d ligh t -ab s o r bing carbo n from TO R analyses. McDade et al. (2004) evaluate the artifacts for O3 and E2, the m o re prom inent fractions of OC and LAC. The O3 artifact repr esen ts n early half o f the repo rted am bient concentratio n (higher for cleaner conditions ), an d the E2 artifact decreas e d to less th an 10% of

am bient concentrations after the IMPROVE sa mpler switched to version 2 in 2000. Although

som e spatial and seasonal differences are observed in the artifact estim a tes (the Okefenokee site has highe r a r tif ac ts than the oth e r sites, and summ er appears to ha ve highe r O3 a n d E2 a r ti fa c t s than winter), the sam e monthly m e dian artifact va lue is ap plied to the entire netwo r k. Based on studies perf orm e d at the University of California, Davis, it appears tha t the pos itiv e artif a ct is due to saturation of the quartz filter from expos ure to am bient organic acids in the atm o sphere and would probably affect all filter s sent to the f i eld sim ilar l y . These resu lts a r e subs tantia ted by Subram anian et al. (2004), who found that quar tz after-filters provide d a robust estim ate of positiv e artifacts for sam p ling du rations of 24 ho ur s, long en ough for eq uilib rium to be ach i eved. However, if som e volatile organic co mpounds are be ing los t from the prim ary filter to the afterf ilter, this co rrec tion cou l d be too la rg e. 2.4. Issues Related to Elemental Species and Coarse Mass An X-ray fluorescen ce (XRF) tech nique is us ed to dete r m ine concentra tions of trace elem ents with atom ic mass num ber (Z) from 11 to 82 (Na-P b ). W h ite et al. (2004) report on the uncertainties and de tec tio n lim its for trace elem ents. Lower Z elem ents (e.g ., Na, Mg) h a ve m u ch higher m i nimum detection lim its ( W hite, personal communication, 2004), and therefore detectable amounts of those elem en ts can be m u ch m o re difficult to obtain. Other unc ertainties in trace elem ents, especially those correspondi ng to coarse m ode aerosols, arise due to uncertainties in the f l ow r a tes of th e s a m p lers

. The size cut of the cy clone us ed to collect and separate PM 2. 5 aerosols is v e ry sens itiv e to the flow rate of the s a m p ler. Variations in the flow rate (e.g., due to

12clogged inlets) can have significant im pacts on th e size range of aerosols being collected and
term ed “fine”. This iss u e can be important w h en interpreting fine m a ss versus coarse m a ss because the soil contribution in th e IMPROVE equation typically co rresponds to the tail o f

coarse m o de m i neral aerosols. Th e size dis t ribu tion of the coarse mode aerosols can vary significantly, as shown by Hand et al. (2002). Over a four-m onth study in Big Bend National Park, th e vo lum e m ean diam eter of the coarse mode ranged f r om ~ 2 μm to 5 μm . The ta il of th is mode that is m easured as part of the PM 2. 5 m a s s is obviously sensitive to the size distribution statistics of the coarse mode aeros ols, which co m p licates a ny correctio n th at m a y be applied to data with f l ow rate is sues. The interpr e ta tion of coarse soil as f i ne soil has im portant consequences for reconstructed m a ss as well as re constructed light ex tinction because the applied optica l prop erties a r e sig n ificantly different for each m ode (as will be s e e n in sec tion 5).
3. Chemical and Physical Forms of S p ecies in the IMPROVE Equation Aerosol sp ecies inclu d ed in the recons tructed m a ss and IMPROVE reconstructed extinction equation are assum e d to be in specific chem ical form s and si ze ranges. In this sectio n we investig ate wheth e r these assu mptions are a ppropriate. In particular we inve stiga t e the speciation of POM, sulfate, soil, ni trate, coarse m a ss, and sea salt.
3.1. Particula t e Organic Materia l (POM ) Accurate es tim ates of particulate organic m a teria l (POM) are requ ired in order to

com pute PM 2. 5 m a ss closure and to estim a te optical properties such as light scattering. Estim ating the contributions of organic carbon aero sol to m a ss or scattering requires an estim ate of the to tal m a ss associated with organi c carbo n. The organic carbon multiplier ( R oc ) used to estim ate particu l ate o r ganic m a terial (POM) is an estim ate of the averag e m o lecular weight per carbon weight for org a nic carbon aeroso l an d takes into account contribu tions from other elem ents associated with the organic m a tter, su ch as N, O, and H. It is highly spatially and

13tem porally variable. It is im possible to determ ine which and how m a ny elem ents are associated with POM without knowing the ch em ical formula of the orga nic com p ound, and it is comm on for ~ 20–40 % of organic aerosol m a ss to re m a in unidentified (Turpin and Lim , 2001). Because the organic co mpounds that com pose POM are largely unkno wn, the approach
f o r taking in to accoun t o t her elem ents in POM ma ss has been to app l y an average m u ltiplier. As Turpin and Lim (2001) review, the often-used va lue of 1.4 dates back to sa m p les collected in Pasadena C A in the early 1970s and 1980s (Grosjean and Friedlander, 1975; W h ite and Roberts, 1977; Van Vaeck and Van Cauwenbe rghe, 19 78; Countess et al., 198 0; Japar et al., 1984). More

recen tly, Tu rpin and Lim (2001) have rev i ewed several estim ates of R oc in term s of the typ e s of

com pounds known to com pose POM, and that review will not be repeated here. However, to summarize their findings, they recommend a factor of 1.6 ± 0.2 fo r urban organic aerosols, a factor of 2.1 ± 0.2 for nonurban organic aerosols, and values ra nging from 2.2 to 2.6 for sam p le s with im pacts from biom ass burning. Russell (2003) used Fourier Transfor m Infrared (FTIR) spectroscopy to estim a te POM from the num ber of carbon bonds present and the m o lecular m a ss of each functional group associated with the carbon bonds. Over 90% o f R oc from estim ates from

sam p les in northeastern Asia and the Caribbean were between 1.2 and 1.6, with m ean values below 1.4. Values of R oc like those reported by Turpin an d Lim (2001) and Russell (2003) are derived using techniques that depend on the functional groups and molecular compounds of organic carbon aerosols. El-Zanan et al. (20 05) used solvent extractions from archived IMPROVE f ilter s at f i ve sites to dir ectly m easure POM m a ss and ca rbo n conten t an d derive an
average R oc of 1.92 (range of 1.58–2.58). They also used a mass balance approach to estim ate the
R oc ratio using the IMPROVE data that result ed in an average va lue of 2.07 across the IMPROVE network. Other types of m e thods result in sim i lar fi ndings. Reconstruction of fine

14m a ss and light scattering coefficients allow estimates of R oc to be derived, as was done in a twomonth study in Yose m ite National P a rk by Malm et al. (2005a) where POM dom i nated the fine

m a ss. They found that an R oc factor of approximately 1.8 allo wed for closure in fine m a ss and light scattering coefficients for perio d s that en compassed both pristine conditions as well as the
im pacts of biom ass burning and regional haze. Poirot and Husar (2004) found better agreem ent between m easured and reconstr ucted fine m a ss by applying an R oc factor of 1.8 during a biom ass burning event in the New England and m i d-Atlantic state regions. Previous in vestig ator s have attem p ted to estimate R oc from com p arison s of gravi m etric and reconstructed m a ss; however, a num b er of issu es a r is e with this type of analysis. These issues originate from t h e uncertainties in th e assum p tions involved in the formulation of reconstructed m a ss and have been discussed in the literature (Andrews et al., 2000; Rees et al., 2004; Tanner et al., 200 4; El-Zanan et al., 2005); therefore they will be m e ntioned only briefly here. Som e of the uncertain ties inh e rent in re co nstruc ted mass equation s include th e assum e d for m of aerosol species . For exam ple, sulf ate is typic a lly assum e d to be in the f o rm of f

u lly neutralized ammonium sulfate, a lthough in reality the fo rm of sulfate could be different (m ore acidic). Nitr ate is as sumed to be in the f o rm of a mmonium nitr ate, and as we will show later, th is

assum p tion m a y be inappropriate under certain conditions. W a ter m a y be retained by hygroscopic species on the filters us ed to determ ine gravim etric PM 2. 5 m a ss. Soil m a ss requires

an assum p tion of soil com position as defined by equation 2, and OC concentrations m a y be affected by sam p ling artifacts and analytical is s u es regardin g the m e thod-dependen t definition s of organic and light-absorbing carbon. El-Zanan et al. (2005) perform e d sensitivity studies related to these issues and found th at values of R oc varied between 1.7 4 and 2.2, although they

15believe the lower values are not realis tic. They also found higher values of R oc determ ined f r om

m a ss balance m e thods in the summ er ( 2.33) compared to the winter (1.87). The approach im ple m ented here for estim a ting R oc from IMPROVE data applies an ordinary lea s t squar e (O LS) m u ltiple -lin ear regre ssion (MLR ) analys is us ing
PM 2. 5, i = a 1 [(NH 4 ) 2 SO 4 ] i + a 2 [NH 4 NO 3 ] i

+ a 3 [OC ] i

+ a 4 [LAC ] i

+ a 5 [soi l] i + a 6 [se a sal t ] i (6) The resu lts of the reg r es sion analysis for each site are p r esen ted in Appendix 1, in clu d in g a statistical summary of gravim etric m a ss and a e rosol species m a ss concentration s (m ini m um,

m a xi m u m, m ean, and standard deviation). Also presen ted for each site is th e fractional contribution of each species to grav im etric m a ss and a comparison between recons tructed and gravim etric m a ss. The statistically s i gnifican t (9 5% level) regress i on co efficients fo r ea ch s ite
are repor ted in Tab l e 1, with the mean and sta nda rd dev i ation of th e coefficients listed in the final two ro ws. If the m a ss for each species (other than P O M) is accurately es tim a ted and the regression is unbiased, then the regression coef ficient for a gi ven species should equal 1. The regression coefficient for POM corresponds to the R oc factor. Scatter plots of gravim etric and reconstructed m a ss are presented in Appendix 1. Reconstructed m a ss ha s been computed using equation 1 and using the regression co efficients derived from equation 6.
T a bl e 1. St ati s ti cal l y si gni f i c an t ( 9 5 % ) regression c o efficients using the o r dina ry lea s t squa re multiple-linea r regression analysis (equati o n 6). Site c o de is in the first colum n . The remaining columns c o rrespond to coefficients as sociated with ammo nium sulfate (AS), amm o nium n i trat e (AN), par t iculate or ganic matter (PO M ), light-abs orbin g car b on (L AC), s o il, and se a s a lt , respectiv ely . Insignifican t coe fficients are replaced w i th “. ”. S i t e A S A N P O M L A C S o i l S e a Sal t AC A D 1

. 2 3

. 1. 8 5

. 1. 4 0 1. 0 2 AD P I 1

. 2 3 0. 4 9 1. 6 7

. 1. 6 8

. AGT I 1

. 0 5 0. 6 7 1. 6 3

. 1. 0 9

. AR E N 1

. 0 8 0. 8 0 1. 7 0 2. 3 6 0. 5 0

. B A D L 1

. 1 4 0. 6 5 1. 9 8

. 1. 0 6

. B A L D 1

. 2 9 0. 7 5 1. 7 6

. 1. 1 8

. B A N D 1

. 2 1 0. 5 4 1. 5 2

. 1. 1 2

. B I B E 1

. 0 8 0. 7 4 1. 8 4

. 1. 0 2

. B L I S 1

. 2 5 0. 5 4 1. 7 4

. 1. 0 6

.

16B L M O 1

. 0 0 1. 0 9 1. 2 7

. 1. 0 9

. B O A P 1

. 1 8 0. 6 8 1. 7 1 0. 6 5 1. 3 0

. B O N D 0

. 9 8 1. 0 1 1. 2 8

. 1. 1 7

. B O W A 1

. 1 8 0. 8 4 1. 8 8

. 1. 3 2

. B R C A 1

. 2 5 0

. 5 0 1

. 4 0 1

. 1 6 1

. 4 1

. B R E T 1

. 1 6 0. 7 0 1. 5 3

. 1. 5 1

. B R I D 1

. 3 1

. 1. 7 3

. 1. 2 2

. B R I G 1

. 0 8 0. 5 4 1. 9 9

. 1. 1 8 0. 9 5 B R L A 0

. 9 7

. 1. 9 1

. 1. 5 2

. B R M A 1

. 0 4

. 1. 4 2

. 1. 1 0

. C A B A 1

. 1 7 0. 5 6 1. 1 6 2. 5 2 1. 1 0 1. 1 9 C A B I 1

. 4 6

. 2. 0 5

. 1. 1 9

. C A C O 1

. 2 5 0. 5 1 1. 6 2

. 1. 3 1 0. 8 2 C A C R 1

. 1 1 0. 5 0 1. 6 7

. 1. 0 6

. C A D I 1

. 2 2 0. 6 3 1. 4 0 2. 7 7 1. 0 5

. C A N Y 1

. 1 0 0. 5 5 1. 7 4

. 1. 2 1

. C A P I 1

. 0 4 0. 5 0 2. 0 7

. 1. 2 1

. C E B L 1

. 1 1 1. 1 4 2. 0 7

. 1. 1 1

. C H A S 1

. 1 7

. 1. 4 4 0. 9 0 0. 9 9 0. 5 9 C H ER 1

. 1 1 0. 9 8 1. 4 3

. 1. 5 7

. C H IR 1

. 2 8 0. 7 9 1. 3 6 1. 5 9 1. 1 5 0. 8 8 C L P E 1

. 2 5

. 1. 7 1

. 1. 3 8

. C O G O 1

. 1 0 0. 5 7 1. 6 3

. 1. 1 0

. C O H I 1

. 2 1 0. 6 3 1. 9 2

. 1. 6 8

. C O H U 1

. 0 1 0. 3 3 1. 7 1

. 1. 1 6

. C O R I 1

. 3 3 0. 6 0 1. 5 9

. 1. 1 4 0. 9 5 C R E S 1

. 0 0 0. 9 8 2. 1 6

. 1. 1 4

. C R L A 1

. 6 8

. 1. 6 8 0. 4 8 1. 1 0 1. 1 0 C R M O 1

. 4 0 0. 7 1 1. 9 6

. 1. 2 5

. DEN A 1

. 3 9

. 1. 8 9

. 0. 8 5 1. 1 3 DEV A 1

. 0 5 0. 7 0 1. 6 5

. 1. 2 5

. DOM E 0

. 9 5 0. 8 1 1. 7 7

. 1. 3 6

. DO S O 1

. 1 6

. 1. 5 8

. 1. 0 0

. ELD O 1

. 1 3 0. 8 2 1. 4 4

. 1. 0 5

. E L L I 1

. 0 7 0

. 9 7 2

. 0 7

. 1

. 1 0

. EVER 1

. 0 0

. 1. 4 4 4. 4 0 1. 2 0

. F L A T 1

. 3 3

. 1. 7 4

. 1. 2 3

. F O P E 1

. 1 0 0. 4 9 2. 0 6

. 1. 2 7

. GAM O 1

. 2 0

. 1. 6 6

. 1. 2 9

. GIC L 1

. 2 2 1. 7 9 1. 5 4

. 1. 0 9

. GLAC 1

. 1 6 0. 9 3 1. 5 8 1. 4 3 1. 1 7

. GR B A 1

. 4 5 0. 5 8 1. 7 0

. 1. 3 5

. GR C A 1

. 2 9

. 1. 3 6 4. 6 6 1. 2 7

. GR G U 1

. 1 0

. 1. 6 5 3. 9 0 0. 9 9

. GR R I 1

. 0 4 0. 9 6 1. 7 3

. 1. 3 4

. GR S A 1

. 3 4

. 1. 9 8

. 1. 1 6

. GR SM 1

. 2 3

. 1. 7 1

. 1. 0 2

.

17GUM O 1

. 1 4

. 1. 6 6

. 1. 0 2 1. 9 6 HAL E 1

. 0 1 2. 0 5 1. 4 5

. 0. 9 7

. HA V O 1

. 6 1

. 1. 4 5

. 1. 1 5

. HEC A 1

. 0 1 0. 6 9 1. 5 2

. 1. 2 9

. HEG L 1

. 0 9 0. 6 9 1. 7 5

. 1. 1 9

. HIL L 1

. 3 6

. 2. 0 4

. 1. 4 2

. HO O V 1

. 3 7

. 2. 0 8

. 1. 5 9

. IKB A 1

. 1 2 0. 3 3 1. 8 6

. 1. 6 1

. IN G A 1

. 1 2

. 1. 3 6

. 1. 2 7

. I S L E 1

. 0 0 0. 8 2 1. 6 7

. 0. 7 2 0. 5 1 JAR B 1

. 2 3 0. 9 9 1. 4 9

. 1. 2 9

. JAR I 1

. 2 2 0. 5 2 1. 6 6 1. 3 9 0. 7 3

. JOS H 1

. 2 5 0. 7 4 2. 0 0

. 1. 0 3

. KA I S 1

. 1 1 1. 0 3 1. 8 1

. 1. 2 7

. KALM 2

. 2 5

. 2. 1 6

. 1. 6 4

. LAB E 0

. 8 6 1. 4 8 1. 7 2

. 1. 4 1 0. 8 5 LAS U 1

. 1 0 1. 0 1 1. 5 4

. 1. 0 3

. LAV O 1

. 5 2 0. 4 3 1. 4 1 1. 4 2 1. 1 7

. LIG O 1

. 2 4

. 1. 7 5

. 1. 0 7

. LIV O 1

. 2 6 0. 7 3 1. 7 9

. 1. 1 7

. L O S T 1

. 1 6 0. 9 3 1. 8 0

. 1. 3 7

. LYB R 1

. 1 0 0. 3 7 1. 6 3

. 1. 0 2

. M A C A 1

. 0 1 0. 2 2 1. 8 1

. 1. 0 8

. M E L A 1

. 0 8 0. 8 0 1. 8 4

. 1. 1 6

. M E V E 1

. 3 2 1. 2 7 1. 4 5

. 1. 0 0

. M I N G 1

. 2 7 0. 8 5 1. 4 5

. 1. 1 4

. M K G O 1

. 3 9 0. 6 6 1. 3 8

. 0. 4 0

. M O H O 1

. 3 6

. 1. 7 7

. 1. 1 1 1. 2 3 M O M O 1

. 0 8

. 2. 0 4

. 1. 3 5

. M O N T 1

. 4 8

. 1. 7 4 11 .0 8 2. 2 1

. M O O S 1

. 1 3 0. 6 2 1. 6 6 0. 6 8 1. 5 0 1. 0 4 M O R A 1

. 3 0 0. 7 6 1. 5 9 1. 5 5 0. 9 0 1. 1 4 M O Z I 1

. 2 5

. 1. 7 0

. 1. 1 1

. NEB R 1

. 2 1 0. 6 6 2. 0 6

. 1. 2 0

. NO AB 0

. 8 2

. 1. 2 6 4. 9 8 1. 3 0

. NOC A 1

. 6 2

. 1. 4 8

. 1. 0 9 1. 6 0 NOC H

. . 1. 7 1

. 2. 6 4

. OKE F 1

. 1 2

. 1. 4 4 2. 5 1 1. 0 1 0. 6 2 OLT O 1

. 1 5 0. 9 7 1. 2 9 0. 9 7 1. 0 1 0. 6 6 OLYM 1

. 1 5 0. 9 6 1. 7 3

. 1. 3 6 0. 8 0 PAS A 1

. 5 4

. 1. 5 3

. 1. 2 1 2. 8 5 P E F O 1

. 3 5 0. 7 7 1. 7 6 2. 1 3 1. 1 8

. PH O E 1

. 2 8 0. 6 8 1. 2 9 0. 7 8 1. 1 3

. PIN N 1

. 3 2 0. 6 4 1. 6 6 0. 8 9 1. 2 8 1. 1 5 PM R F 1

. 2 2 0. 5 4 1. 3 6

. 1. 0 2

. POR E 1

. 2 8 0. 7 4 1. 9 3

. 1. 2 6 1. 0 4 PR I S 0

. 9 3 1. 0 0 1. 3 0

. 1. 1 9 0. 6 2

18PUS O 1

. 2 3 0. 7 6 1. 3 5 0. 8 2 1. 0 7 1. 2 1 QUC I 1

. 3 0 0. 6 4 1. 9 5

. 0. 4 0

. QUR E 1

. 0 5 0. 2 8 1. 6 3 2. 1 2 0. 8 7

. QU V A 1

. 1 7 0. 7 9 2. 0 0

. 1. 3 7

. R

A F A 1

. 3 9 0. 9 5 1. 5 7

. 0. 9 6 1. 2 0 R E D W 1

. 2 3 1. 5 9 2. 1 6

. 1. 2 5 0. 9 2 R O M A 1

. 1 9

. 1. 6 0

. 1. 2 0 0. 9 1 R O M O 1

. 2 7

. 1. 7 1

. 1. 3 4

. SAC R 1

. 3 0 0. 9 7 1. 4 5

. 1. 5 5 2. 8 0 SAF O 1

. 0 8 0. 9 9 1. 6 3

. 0. 8 0

. SA G A 1

. 1 2 0. 6 0 1. 5 7

. 0. 9 1

. SA G O 1

. 0 0 0. 9 1 1. 2 7

. 1. 0 7 1. 4 6 SA G U 1

. 2 5 0. 2 6 1. 5 0 1. 2 9 1. 2 6

. SAM A 1

. 1 7

. 1. 5 8

. 1. 4 2

. S A P E 1

. 0 8

. 1. 5 7

. 1. 2 3

. SA W E 1

. 3 0

. 1. 5 0

. 1. 2 9

. SA W T 1

. 8 4

. 1. 7 4

. 1. 2 0

. S E N E 1

. 1 6 0. 7 0 1. 8 1

. 0. 7 2

. SEQ U 1

. 2 9 0. 9 1 1. 3 5 2. 9 3 0. 9 8

. SHE N 1

. 1 1

. 1. 9 7

. 0. 8 7

. SHR O 1

. 2 2

. 1. 7 4

. 1. 1 0

. SIA N 1

. 1 0 0. 3 8 1. 3 7 2. 2 5 1. 3 7

. SIK E 1

. 1 8

. 1. 5 3

. 1. 1 5

. SIM E 1

. 4 3

. 1. 2 8

. 1. 3 2 1. 1 6 S I P S 1

. 0 4

. 1. 6 9

. 1. 0 4

. SNP A 1

. 3 3 0. 6 4 1. 7 1

. 1. 2 3 1. 2 3 SPO K 1

. 2 4 0. 7 1 1. 6 6

. 1. 2 8

. STAR 1

. 6 1

. 1. 1 1

. 1. 7 0

. SUL A 1

. 5 8

. 1. 6 3

. 1. 1 5

. S W A N 1

. 1 3

. 1. 7 5

. 1. 3 3

. SYC A 1

. 4 3 0. 4 4 1. 5 9

. 1. 1 0

. T A L L 1

. 0 5 0. 8 4 1. 1 2 3. 3 4 1. 5 1

. THB A 1

. 0 0 0. 7 7 1. 8 4

. 1. 0 4

. THR O 1

. 1 3 0. 8 1 1. 8 5

. 1. 0 1

. THS I 1

. 7 5

. 1. 2 8

. 1. 5 2

. TON T 1

. 1 7 0. 6 7 1. 9 2

. 1. 0 9

. T R C R 1

. 5 9

. 1

. 9 1

. 0

. 6 2

. TR I N 2

. 0 8

. 1. 1 6

. 1. 1 5 1. 0 3 TUX E 2

. 2 0

. 1. 9 1 3. 0 9 0. 6 2 1. 0 5 ULB E 0

. 9 8 0. 9 1 1. 9 9

. 1. 1 7

. UPB U 1

. 1 0 0. 6 7 1. 9 4

. 0. 8 8

. VI I S 0

. 7 5 2. 3 4 1. 4 4

. 1. 3 1

. VIL A 1

. 0 7 1. 0 2 1. 2 7

. 0. 8 0

. VO Y A 1

. 2 2 1. 0 1 1. 8 3

. 1. 3 2 0. 8 9 WA S H 1

. 1 6 0. 8 2 1. 7 0 0. 8 7 1. 0 4 0. 8 2 WEM I 1

. 4 1

. 1. 6 8

. 1. 2 1

. WH I T 1

. 2 3 1. 0 4 2. 1 9

. 1. 2 3

.

19WH P A 1

. 1 3 0. 9 6 1. 5 7

. 1. 0 9

. WH P E 1

. 0 5

. 1. 6 6 0. 8 7 1. 3 1

. WHR I 1

. 3 2

. 1. 7 4

. 1. 2 7

. WIC A 1

. 0 6 0. 5 5 1. 9 3

. 1. 1 7

. WIM O 1

. 2 3 0. 8 0 1. 5 5

. 1. 1 8

. Y E L L 1

. 1 2 0

. 6 2 1. 5 4 2

. 5 7 1

. 3 0

. YO S E 1

. 1 5 0. 7 4 1. 6 8

. 1. 2 6 0. 9 9 ZIO N 1

. 3 4 0. 6 4 1. 6 3

. 1. 2 8

. Av g 1. 2 2 0

. 7 8 1. 6 6 2. 2 8 1. 1 8 1. 1 2 Std De v 0. 2 2 0

. 3 2 0. 2 4 2. 0 0 0. 2 6 0. 5 1

The m ean values of R oc derived from equation 6 (see Tabl e 1) are shown as a summary in Figure 1. Th ere are clear spatial tren ds in th e R oc factor. The highest co efficients of 1.8–2.0+ are just east of the Rocky Mountain range and m a y be reflective of wild and pr escribed fire activity to the west of this region. Both Malm et al. (2005a) and Poirot and H u sar (2004) derived R oc factors near 1.8 at sites with air m a sses in fluenced by aged biom ass s m oke, and higher R oc values corresponding to biom ass burning were reported by Turpin and Lim ( 2001). Three of the four sites in Alaska (not shown) also have coeffi cients near 1. 9, with the exception of Si m e onof National W i ldlife Refuge on the Alaskan pe ninsula. Other remo te loca tio ns have R oc values near 1.8. Coefficients ranging from 1.6 to 1.8 are f ound around m o st of the United States, with distinct regions having coefficien ts less th an 1. 6. Regions in the North w est, inte rio r Midwest, and Northeast are in th is catego r y.

20Fi gure 1 . M e an v a l u es of R oc multiplie r deriv e d from a n o r dina ry lea s t squa re multi-linea r reg ression an al ysi s (equ a t i o n 6 ) .

The average coefficient over all sites is R oc = 1.66 ± 0.24, with all 158 sites having significan tly valid coefficients. On a seasonal basi s the coefficients do not vary significantly, as seen by the m ean and st andard deviation values presented in Figure 2. The m e an summ er value ( R oc ~ 1.7) is near the average value of 1.66, while the lowest values were derived during winter ( R oc ~ 1.5). Som e seas onality in R oc is expected, with higher values in summ er due to photochem i cal reactions from warm er te m p er atur es and higher solar insolation. Results from these analyses suggest that the existing R oc value of 1.4 in the IMPROVE equation is probably too low. Based on estim a tes reported from other s t udies and the an alysis perform e d here, we

recomm end an R oc value in the range of 1.7–1.8.

21Fi gure 2. Me an se as on al v a l u es of R oc for all sites . S t andar d de viati o ns are als o s h own as uppe r an d lower error bars .

As will be discussed in s ection 5, th e particle den s ity is of ten needed to c o m pute optical properties. Inorganic particle densities for speci es such as ammoniated sulfate are well known; however, the density of organic aero sols can range from 1 to 2 g cm -3 or higher, depending on the organ i c com position. Because the com position of organic aerosol is largely u nknown, the value of organic density has large uncertainties. Turpin and Lim (2001) review densities of particle-phase organic com pounds and summ ar i ze them by com pound class. The values they report range from 0.77 to 1.64 g cm -3 . Values near 1.2 g cm -3 were found for the urban areas of the Los Angeles Basin, W e st Los Angeles, downtown Los Angeles, Pasadena, and Roubidoux CA (Rogge et al., 1993). However, higher values of organic aerosol density would be expected with increased concentrations of carboxylic acids and/or polycyclic arom atic hydrocarbons, or in the presence of significant c oncentrations of am ines and am ino acids (T urpin and L i m , 2001). Investigating m a ss closure studies can assist in understanding if a particular organic density is appropriate, particularly when orga nic m a ss fractions are s i gnificant.

22During the Aerosols99 cam paign, Quinn et al. (2001) perf orm e d closure studies of m a ss and light extinction from cruise -based m easurem ents from Virgin ia to South Africa. Organ i c carbon was collected using a thr ee-stage im pactor and analyzed with therm ographic m e thods. Particulate o r ganic m a terial (POM) w a s com puted by assum i ng an R oc factor for North Am erican air m a sses and a value of 2.1 for all other air m a sses (Turpin and Li m , 2001). POM was assum e d to be nonhygroscopic and distributed as non-sea- salt sulfate and the organic density was 1.4 g

cm -3 . The highest subm i c ron POM m a ss fractions were m e asured off the coas t of North Am erica (~ 15%) and for biom ass burning air m a sses off th e coast of Africa (15– 20 %). For both of these regions the subm icron m a ss closure was within e xperim e ntal uncertainty, as was the m easured and com put ed ligh t scattering co efficient. During INDOEX (Indian Ocean Experim e nt), Qu inn et al. (2002b) used a sim ilar m e thod to the Aerosols99 cam paign, but collected three sa m p les with a seven-stage im pactor to obtain OC size distributions. An R oc value of 1.6 was a pplied to all sam p les. Or ganics were assum e d to be nonhygroscopic and an organic aerosol density of 1.4 g c m -3 wa s applied. The highest subm icron POM m a ss fr actions were obtained for Arabian a i r m a sses (~ 15%). Both calcu lated

m a ss and l i ght scattering coefficients agreed with m easured value s within e xperim e ntal uncertainty. During the ACE-Asia (Aerosol Characterizatio n Experim e nt in Asia) study, Quinn et al. (2004) used a seven-stage im pact or to collect organic carbon and com puted POM assum i ng an R oc of 2.1 in m a rine regions and 1.6 elsewher e. POM was a ssum e d to be nonhygroscopic and a density of 1.4 g cm -3 was applied. At m o s t , the POM subm icron m a ss fractions were approxim a tely 20% and calculated and m easured m a ss and light s cattering co efficients agre ed within experim e ntal uncertainty.

23Hand and Kreidenweis (2002) used differential mobility an alyzer (DMA ), optical particle counter (OP C ), and aerodynam i c particle sizer (APS) volum e di stributions to compute m a ss concentratio n during th e Big Bend Regional Ae rosol and Visibility Observation a l (BRAVO) study. Closure between m easured and reconstructed total m a ss was found between these data,

assum i ng an R oc of 1.4 and an organic density of 1.4 g cm -3 . On average, POM was 22% of the
PM 2. 5 m a ss. Good agreem ent between m i cro-orif ice uniform deposit impactor (MOUDI) size distributions and DMA volum e dist ributions converted to m a ss di stributions (as a function of aerodynam i c diam eter) was also found.
Am es et al. (2000) computed m a ss concentrat ions from OPC volum e distributions during the Southeastern Aerosol and Visibility Study (SEAVS) in the Great Sm oky Mountains National Park and found good agreem ent with m easur ed m a ss concentrations when assum i ng R oc = 1.4 and an organic density of 1.4 g cm -3 . Dick et al. (2000) also appl ied an organic density of 1.4 g

cm -3 during SEAVS. Although the above studies did ach ieve closure w ith the assu mptions m a de about organic aerosols, it is difficult to glean too much info rm ation about organics fro m closure studies when they are not the dom inant aerosol typ e , becaus e the integrated m a ss or optica l prop erties will be less sensitive to what is assum e d for organic properties. Very few gr ound-based closure studies exist with a carbon-dom inated aerosol, except during extrem e sm oke events. During a field study in Yose m ite National Park, the submicron orga n i c m a ss fraction was 69% on average (Malm et al., 2005a). McMeeking et al. (2005 ) used DMA and OPC size distributions in successful closure studies of m a ss concentrations and light s cattering coefficien ts as su m i ng an R oc of 1.8 and organic density of 1.4 g cm -3 . Si m ilar agreem ent was found by Malm et al. (2005a) during the

24sam e study, suggesting these estim ates were reas onable for organic aerosol properties at this location. Organic aerosol densities typically applied by research ers tend to va ry f r om 1 to 2 g cm -3 , depending on the application and type of organi cs (e.g., urban, rural, smoke). Since there are large uncertainties on organic com p ounds them s e lv es (20–40% of organic m a ss is unidentified, Turpin and Lim , 2001), there is also high uncertainty in its density. Furtherm ore, direct

m easure m ents of aerosol density do not ex ist, s o these valu es ha ve to be inferred from other

m easure m ents. Because this num ber is not well known, investig ators often apply a reasonab l e

num b er. A value of ρ = 1 g c m -3 previously has been used (e.g., Sloane et al., 1991; Zhang et al., 1993; Neusüß et al., 2002; Ad am et al., 2004), as well as ρ = 1.4 g cm -3 (e.g., Am es et al., 2000; Dick et al., 2000; Hand, 2001; Quinn et al., 2001, 2002b, 2004; Ha nd et al., 2002; 2004; Gao et al., 2004; McMeeking et al., 2005). Currently a value of ρ = 1.2 g c m -3 of ten is being applied that corresponds to a value recomm ended by Turpin and Lim (2001) for urban organic aerosol

m easure m ents in Los Angeles (e.g., Lowenthal et al., 2000; McMurry et al., 2002; Wang et al., 2002; Fridlind and Jacobson, 2003; Ga sparini et al., 2004; Stanier et al., 2004; Z h ang et al., 2005). Reid et al. (2005) report higher densities for specific organic aerosol types, such as

sm oke, from various investigators in a review of biom ass burning propert ies. Va lues be tween 0.79 and 1.35 g c m -3 were reported by Stith et al. (1981) for two te m p erate fires. Densities of 1 g

cm -3 and 1.53 g c m -3 were reported by Radke et al. (19 88, 1991) and Martins et al. (1996), respectively, for te m p erate forest fires, and Reid and Hobbs ( 1998) report a value of 1.35 g c m -3
for fires in the Am azon. From th ese estim a tes, Reid et al. (2005) suggest the average density of dry sm oke particles range from 1.2 to 1.4 g cm -3

.

253.2. Nitrate Nitra t e is an im portant seasonal con t ributo r to pa rticula t e m a tter at m a ny locations in the United State s . Nitrate is assum e d to be present in the fine mode as ammonium nitrate; however, it can be p r esent in the coarse m ode also. Fi eld studies at several IMP R OVE monitor i ng sites investigated the sp eciation and size of aerosol n itrate u s ing a size-resolved im pactor (MOUDI) and have shown that nitrate is of ten present as coarse m ode nitrat e. Lee et al. (2004a) com puted the spec ia tion of nitra t e by f i rst cal culating leftover ammonium from (NH 4 ) 2 SO 4 . Excess ammonium is then associated with nitrate as NH 4 NO 3 , and an y excess nitrate no t as so ciated with ammonium is determ ined. Sodium i s first com b ined with Cl - as sea salt, and any excess sodium is com b ined with excess nitrate (NaNO 3 ). If addition a l n i tr ate is lef t o v er, it is ass o ciated with crustal com pounds such as Ca +2 or Mg +2 (Ca(N O 3 ) 2 or Mg(NO 3 ) 2 ).
NH 4 NO 3 form s from the reaction of gas phase a m m onia and nitric acid and is more favorable in regions with high ammonia and n itr ic a c id concen trations and low sulf ate concentrations. The equilibrium reaction producing aerosol-phase NH 4 NO 3 is sensitive to smal l changes in tem p erature and rela tive hum i dity that can shif t the equilib rium to the gas phase. However, the reaction of gas phase nitric acid with sea salt or calci um carbonate is not an equilibrium reac tion and resu lts in n itr ate being transferred to the aero s o l phas e and associated with coarse mode particles. Two estim a t es of fine mode nitrate for th e three form s discussed above have been

com puted by summ ing t h e nitrate in th e MOUDI size bins corresponding to D p < 1 and D p < 3.2
μm (although the MO UDI does not have a 2.5 μm size bin, we assum e that the fine m ode corresponding to D p < 3 .2 μm m o st closely rep r esents the IMPROVE PM 2. 5 m easurem ent). Fine mode nitrate estim a tes are presen ted in Figures 3a and 3b for D p < 1 and D p < 3.2 μm , respectively. Coarse m o de nitrate is com puted in a sim ilar m a nner for D p > 1 μm and is

26presented in Figure 3c. The size of the pie char ts in Figure 3 rep r esents the total n itr ate concentration in that size range (in these figures, a doubling of the pie size corresponds to 8 tim es the concentr ation ) , and the tota l nitra t e con centr ation in that size mode is listed beside its chart. Figure 3. (a ) Fine m o de (D p < 1 μm) ni tra t e speci ati o n of NH 4 NO 3 , Na NO 3 and Ca(NO 3 ) 2 at several IMP R OVE sites. The siz e of the pie char t reflects the ma gnitu d e o f the c o ncen tra t ion of to t a l n i trate in this siz e mode, w h ich is listed u n d er eac h ch ar t. (b) S a me as (a ) b u t fo r D p < 3. 2 μm . ( c ) Same as ( a ) b u t for co arse mode (D p > 1 μm).

NH 4 NO 3 NaNO 3 Ca(NO 3 ) 2 76% 23% 1%

100% 4%

1% 96%

100%

43% 56% 33% 67% 67% 13% 20%

500 ng/m 3 Great Smoky Moutains (summer) 27 ng/m 3 B o n d v ille (winter) 3646 ng/m 3

San Gorgonio (April) 2389 ng/m 3 Brigantine (fall) 630 ng/m 3 Yosemite (summer-fall)

450 ng/m 3

Big Bend (summer) 408 ng/m 3 Grand Canyon (spring) 233 ng/m 3

27NH 4 NO 3 NaNO 3 Ca(NO 3 ) 2 71% 26%

3%

87% 7% 2%

1% 63%

63% 2%

61% 38% 14%
86% 35%

35%

6%

500 ng/m 3 26% 43% 31% Great Smoky Moutains (summer) 102 ng/m B o n d v ille (winter) 3930 ng/m 3

San Gorgonio (April) 2993 ng/m 3 Brigantine (fall) 953 ng/m 3 Yosemite (summer-fall)

711 ng/m 3

Big Bend (summer) 640 ng/m 3 Grand Canyon (spring) 606 ng/m 3

28NH 4 NO 3 NaNO 3 Ca(NO 3 ) 2 64% 6%

69% 2% 30%

32% 24% 6% 17%

44% 12%

91% 9% 29% 77%

64% 24% 36% 64%

6%



### 500 ng/m 3 Great Smoky Moutains (summer) 389 ng/m 3 B ondv i l l e (winter) 453 ng/m 3

San Gorgonio (April) 941 ng/m 3 Brigantine (fall) 651 ng/m 3 Yosemite (summer-fall)

586 ng/m 3)

Big Bend (summer) 256 ng/m 3 Grand Canyon (spring) 631 ng/m 3

The data presented in F i gure 3a demonstrate that fine m ode (D p < 1 μ m ) nitrate is not always speciated as ammonium nitrate. For ex ample, during summer in Big Bend National Park TX, only 1% of fine mode nitrate was in the fo rm of a m monium nitrate, and during winter in Bondville IL, a m m onium nitrate accounted for 76% of the nitrate sp ecies in the fin e m ode while Ca(NO 3 ) 2 accounted for 24%, even though the fine m ode tot a l nitrate concen trations in Bondville are considerably higher than th e other sites. During spring in Grand Ca nyon National Park AZ,
NH 4 NO 3 wa s 67% of fine m ode nitrate, and durin g summ er at Great Sm oky Mountains National Park TN, it was only 33%. However, in both Sa n Gorgonio National Park CA (spring) and
Yosem ite Nationa l Park CA (summ e r), the f i ne m ode nitra t e was com p letely s p ecia t ed as ammonium nitrate, and in Brigantine NJ (autum n), it was nearly all ammonium nitrate (96%).

29For the sites where ammonium nitrate was not th e dom inant f o rm of nitrate in the fine mode, the contribution of nitrate ion to PM 2. 5 mass concen tration wa s less than ~ 20 %.
Coarse m o de speciation of nitrate at thes e sites (see Figure 3c) reflects the reaction pathways of nitr ic acid with m i neral ae rosols di scussed earlier. For example, at several of the sites (Brigan tine NJ, Yosem ite National Park CA , and Big Be nd National Park TX), coarse m ode nitrate was associated with sea s a lt as NaNO 3 . At Big Bend National Park TX, nitrate had replaced Cl - in sea salt (NaNO 3 ) (Lee et al., 2004a), and MOUDI data showed that nitrate and sodium had sim ilar size distributi ons. However, at other sites nitr ate was associated with crus tal

m a terial (C a(NO 3 ) 2 ) (B ondville IL, Great Sm oky Mountai ns National Park TN, and Grand Canyon National Park A Z ).
At m a ny of the sites, the nitr at e concentrations in the coars e mode were higher than in the fine m ode. For example, data from Grand Canyon National Park (spring) indicate that concentratio ns of nitrate in the coarse m ode we re alm o st th ree tim e s higher than n i tra t e in the fine m ode, and roughly 14 tim e s higher in Gr eat Sm oky Mountains Na tional Park. Nitrate concentratio ns at Yose m ite National Park we re com p arable for both m odes, s i m ilarly for Brigantine NJ. The only sites where fine m ode n itrate m a ss was consid erably higher than coa r s e mode nitrate m a ss were Bondv ille IL and San Gorgonio CA. The two estim ates of fine m ode nitrate for D p < 1 μm and D p < 3.2 μm in Figures 3a and 3b, respectively, were com puted to dem onstrate the im portance of the size cut of the im pactor on the in te rpre tation of nitr ate sp eciatio n. For exam ple, sh ifting the fine m o de cutpoint from 1 to 3.2
μm f o r data f r om the Brigantine NJ site res u lts in the specia tion o f nitrate ch anging f r o m predom inantly NH 4 NO 3 (96%) to 63 % NH 4 NO 3 and 35% NaNO 3 bec a use m o re of the coarse mode tail is being included (see Figures 3a–c). Sim ilar behaviors are observed at Grand Canyon

30National Park AZ, Big Bend National Park TX, a nd Great Smoky Mountains National Park TN, where the sp eciation of fine m ode nitrate changes significantly because of the inclus io n of coarse mode nitrate m a ss. Determ ining or pr edic ting the f o r

m

of nitrat e is not straightforward; it depends on

m e teorological param e ters such as temperature a nd relative hum i dity, as well as the presence and acidity of other species such as sulfate. Also, the am ount of coarse m ode nitrate be ing attributed to the fine mode also d e pends on th e cutpo i nt of the im pactor, which dep e nds on th e accura cy of the flow rate. However, for data gathered at th e sites show n in Figures 3a–c, when fine m o de total nitrate concentrations were roughly greater than 0.5 μg m -3 , a m m o nium nitrate contributed over 70% of the observed total nitr ate in the fine m ode. Obviously, the for m of ni trate is very
im portant in accurately accountin g for contributions of nitrate to fine m a ss and to ligh t extinction—optical properties of fine m ode ammonium nitrate (as well as hygroscopic properties ) are qu ite dif f erent from coarse m o de sodium nitra t e or ca lc ium nitrate. Accurately estim ating the specia tio n of nitr ate would require m easurem ents of fine m ode a mmonium and speciation o f coarse m a ss. Because these m easurem ents are not currently available at all s ites, and based on the previous discussion that suggest s higher levels of nitrat e in the fine m ode are probably associated with NH 4 NO 3 , we recomm end that n itrate rem a ins in the for m of ammoniu m nitr ate in the IMPROVE f o rm ulation.
3.3. Sulfate Elem ental sulfur and the sulfate ion are m eas ured as part of the IMPROVE network. To assess the contributions of sulfate to fine m a ss or light extin ction, the molecular f o rm of sulfate must be kn own. The I M PROVE algor ithm assum e s that sulf ate is in the f o rm of f u lly ammoniated sulfate ((N H 4 ) 2 SO 4 ). The m o lecular form of su lfate depends on its degree of neutralization, for whic h routine m easure m ents of the ammonium ion are required. The

31IMPROVE network does not m easure the NH 4 + ion, and as discussed in section 2.2, there are inheren t sa mpling issu es with r e s p ect to ammonium measurem ents . The m o lar ra tio of ammonium to sulfate ranges from 2 for fully neut ralized ammonium sulfate to 0 for sulfuric acid. Many authors have shown that aerosol sulfate aci dity can vary tem porally and spatially. More acidic aerosols have been m easured at m a ny loca tions around the United St ates (e.g., Gebhart et al., 1994; L i u et al., 1996; Day et al., 1997; L o wenthal et al., 2000; Lefer and T a lbot, 2001; Quinn et al., 2002a; Chu, 2004; Hogrefe et al., 2 004; Schwab et al., 2004; Tanner et al., 2004; Zhang et al., 2005). Special studies at IMPROVE sites have also dem o nstrated variability. At
Great Sm oky Mountains Nationa l Park during the summ e r of 1995 (SEAVS), a mmonium t o sulfate m o lar ratios of 1.1 were observed (H and et al., 2000). During the BRAVO study at Big Bend National Park, L ee et al . (2004a) found ammonium to su lfate molar ratios of 1.54 on
average. Also, on average, fully n e utralized ammonium sulfate was observed at Yosem ite National P a rk during the summer of 2002 (Malm et al., 2005a). Seasonal and spatial variations in aerosol acid ity com p licate recomm endations of a si ngle form of a mmoniated sulfate, and regular

m easurem ents of the NH 4 + ion at IMPROVE sites do not exist. The coefficient ( a 1 ) m u ltiply ing am monium sulf ate in the r e gress i on model des c rib e d in section 3.1 provides som e indication of the role of sulfate in recons tructed fine m a ss. A coefficient greater than 1 suggests that water m a s s retained on the gravimetric filter is associated with sulfate, because ammonium sulfate is ass u m e d in the regress i on and it has the highest molecular weight of any ammoniated sulfate sp ecies. Gravim etric fine m a ss is m e asured from Teflon ® f ilte rs tha t ar e weighed at a relativ e hu m i d ity of ~ 40%; th eref ore an ac idic sulf ate (or other) species could be responsib le for retain ed water on the filter. The amount of residual water on the filter is a function of th e re lative hum idity a t whic h the f ilter is weighed and the RH

32history to w h ich the aerosol is exposed. Issues related to wate r on the filter cannot be avoided because acidic sulfate s p ecies retain water to very low relative hum i dity . On average, the MLR coefficient associated with su lfate w a s greater th an 1 at almost all of th e IMPROVE sites (see Table 1). Others have found sim ila r results; for exam ple, Andrews et al. (2000) suggested that up to half of the discrepancy betw een m easured and reconstructed fi ne m a ss could be accounted for by water uptake on the T e flon ® f ilter by sulf ate s p ecies during the SEAVS study in Gr eat Sm oky Mountains National Park. As previously stated, it is im poss i ble to know the for m of sulfate to

assum e in the IMPROVE equatio n becaus e a mmonium is not m e asured ; th erefore we

recomm end that amm onium sulfate rem a in as the for m of sulfate in the IMPROVE e quation.
3.4. Soil Compo s ition The com pos ition of soil varies as a function of soil taxonomy at a given location. Soil
taxonom y c h arts show variability ac ross the United States with soil type, with the southwestern United States differing from the eastern United States, and m a ny finer differentiations beyond that. Soil com position can also vary due to long-range interc on tinen tal and tran scontin enta l transport. S e veral studies have shown that c ontributions of Asian dust to U.S. fine soil concentrations can be significan t episodically, affecting aerosol concentrations and m i neralogy across the U n ited States (e.g., VanCuren and Ca hill, 2002; J a ffe et al., 2003; VanCuren, 2003). Transport o f North African dus t to the United States o ccurs regularly, affecting aeroso l concentratio ns in the Virgin Is land s, the easte r n

and southeastern United States (P erry et al., 1997), and even as far w e st as Big Bend National Pa rk (Hand et al., 2002). Due to the spatial and
tem poral var i ability in d u st sourc e s, it is very d i f f i cult to cha r acterize an appropriate aerosol soil

com position for each m easurem ent site. Soil mass concentrations are therefore estim ated by a general m e thod that sum s the oxides of elem e n ts that are typically as sociated with soil (Al 2 O 3 ,

33SiO 2 , CaO, K 2 O, FeO, F e 2 O 3 , TiO 2 ), with a correction for other com pounds such as MgO, Na 2 O,
H 2 O and carbonates (Malm et al., 1994b). Elem ental c oncentr ation s are m u ltiplied by f acto r s tha t rep r e s ent th e m a ss concentrations of the oxide for m s. Seve ral corre ctions are also m a de. Molar concentrations of iron are assum e d to be equally abundant in the for m s of FeO and Fe 2 O 3 . Potassium has a nonsoil contribution from biom ass s m oke, so the soil potassium is estim ated by using Fe as a surrogate, or [K] = 0.6[Fe ]

. The form ula for com puting soil con centration is given in equation 2 an d has been divided by 0.86 to tak e into acco unt m i ssing com pounds. Results from the multip le linear reg r ess i on technique described in section 3.1 (see Table 1 a nd Figure 4) suggest that, on average for all the IMPROVE sites, the soil com p osition is be ing underestim ated by roughly 20%. Spatial variability is observed in the so il coefficient from the MLR m e t hod, with soil conc entrations in the western United States being underestim ated more than in the Midwest and eastern United States. An area of the country from Michigan south through the Ohio River valley appears to have overestim ated soil concentrations by 10–30 %. Although the results from the MLR m e thod suggest an underestimation of soil m a ss on average, the lack of m e asurements of soil

com position around the United States and th e ad d ition a l com p lication of contribution s of longrange (Mexico, Asia, and Africa) soil at m a ny U.S. sites do not allow for suggestions for ref i nem e nts to the so il f o rm ula at this tim e.

34Fi gure 4. M e an v a l u es of t h e soi l c o ef fi c i ent fr om an o r dina ry lea s t squa re multi- linear re gres sion analysis (equ ati o n 6).

S o i l m u lt ipl i er

3.5. Coarse Mass Coarse m a ss is the difference between PM 10 and PM 2. 5 mass concentrations m e asured gravim etrically and is n o t routinely analyzed f o r spec iatio n ; the r ef ore the IMPR OVE equation treats all of coarse m a terial as nonhygroscopic dus t. A few short-term special studies at national parks during which coarse m a ss speciation and aer osol m a ss size distributions were m easured have shown that co arse m a ss consists of a sub s tantial am ount (~ 40–5 0%) of carbonaceous

m a terial and inorganic salts such as calcium and sodium nitrate (Malm and Day, 2000; Hand, 2001; Lee et al., 2004a,b). To inve stigate the speciation of coar se m a ss, a coa r se particle speciation network was initiated at nine IMPR OVE sites in 2003. Sites were selected to be
repres entative of the continen tal United St ates and were operated accord ing to IMPROVE

35protoco l an alytic procedures for a period of one year, with addition a l A, B, and C m odules operating with PM 10 inlets. Prelim inary results from one year of data from the sites suggest that over 50% of coarse m a ss is soil (as define d by the I M PROVE soil equ a tion ) , with so il contributions higher in the western than eastern ha lf of the country. Particulate organic m a terial is the next highest contributor (15–35%) with fairly hom ogeneous spa tia l dis t r i butio n. Nitra t e is next highest contributor (5–15%), probably associat ed with sea salt on th e coast and dust in the inner and w e stern areas of the c ountry. Sulfate is a m i nor contribu tor to coarse m a ss, although at coastal reg i ons in the Northeas t it averaged up to 10%, probably related to sea salt. The optical, physical, chem ical, and hygroscopic properties of coarse mode aer osols can vary significantly, depending o n the com p osition and size d i s t ribu tion of co ar se m a ss, and could h a v e im portan t im plications to total scattering, because in som e rem o te areas c ontributions to total scattering from the coarse m ode scattering co uld be com p ar able to fine m ode cont ributions. F o r exam ple , there were several periods dur ing the BRAVO s t udy in Big Bend National Park when up to 80% of total scattering was attributable to th e coarse mode (Hand, 2001; Hand et al., 2002). Several special studies at IM PROVE sites have suggested th at the coarse m ode aerosol

com position can affect the fine m o de m a ss because often the tail of the coarse m ode is m e asured as part of the fine m ode. For exam ple, durin g the BRAVO study at Big B e nd National Park, sizesegregated MOUDI i m pactor m easurem ents (Lee et al., 2004a), as well as particle size distribution m easure m ents (Ha nd et al., 2002), suggested that a 1 μm aerodynam i c diam eter was

a m u ch m o r e realistic separation between the fine and coarse m ode . Si m i lar results w e re found in
Yose m ite National Park, San Gorgonio CA, Gr and Canyon AZ, Brigantine NJ, and Great Sm oky Mountains National Park (Lee et al., 2004b). The use of a P M 2. 5 size cut for IMPROVE sam p lers results in a substantia l f r action of the tail of th e coarse m ode distribution in fine m o de sam p les ,

36and this can vary significantly with a variab le s a m p ler f l ow rate th at af f ects the siz e cut of the cyclone. The im plications can be im portant for understanding the hygroscopicity, optical properties, m i xing, and trends of fine m ode aerosols.
3.6. Sea Salt Although contributions from sea salt to coarse mass (and indirectly to fine m a ss) are not included in the IMPROVE reconstruction equation, sea salt can be a signifi cant fraction of th e fine m a ss at m a ny coastal locations, (e.g., the Virgin Islands), as well as c ontribute significantly to light scattering (e.g., Quinn et al., 2001, 200 2b, 2004). Sea salt concentr ations are typically

com puted fr om sea salt m a rkers like the sodium i on, chloride ion, or combination of ions (Quinn et al., 2001). Difficulties in com put ing sea salt from data from the IMPROVE network arise because pos itiv e ions are not analyz ed; therefore s odium ion (the stron g est indicator of sea salt) data are no t available. Elem ental sodium da ta are available from XRF analyses; however sensitivity issues regarding poor detection of Na result in large uncertainties corresponding to Na from XRF (White et al., 2004). Issues also arise when using th e chloride ion or chlorine to estim ate sea salt becaus e reaction o f gaseous n i tr ic acid with sea salt p r oduces sod i um nitrate particles and the release of gaseous HCl. The depletion of chlo ride during this reaction results in an underestim ation of se a salt when using chloride to com p ute it. For noncoastal sites, the inclusion of sea sa lt is not expected to have a considerable
im pact on reconstructed light scattering, so underes tim ating the contribution at those sites is not significant. However, Lowenthal and Kum a r ( 2003) found that includi ng sea salt (com pute d using Na and Cl) in reconstructed fine m a ss at Po int Reyes CA increased reconstructed fine m a ss by 30% on average. Because sea sa lt is hygroscopic, the added e ffects of water mass to light scattering in coastal higher RH environm ents could be im portant also. Recent work by Lowenthal and Kum a r ( 2005) suggests the possibility of using strontium as a surrogate for sea

37salt. Investigations into this possibility are ongoing. The elemental abundan ce of strontium varies depending on the type of soil (Siefert et al., 1999 ) and estim ates of Sr-derived sea salt depend on accurate estim a tes of its crus tal abundance in relation to other elem ents. Bec a use m a ny IMPROVE sites have been shown to be influen ced by long-range transport of Asian and North African dust (e.g., Perry et al., 1997; VanCur en and Cahill, 2002; J a ffe et al., 2003, 2005; VanCuren, 2003; Hand et al., 2004) as well as local dust sources, it is very im por tant that the contribution s to Sr from dust sources versus s e a salt be accu rately charac terized, as both can be very im portant contributors to ligh t sca tte ring. For exam ple, in Barb ados (ne a r the Virg in Islands), Li et al. (1996) found th at f o r a 10-year m ean, dust cont ributed 56% to light scattering,

com p ared to 33% by sea salt. The MLR a n alysis in se ction 3.1 an d summ arized in Tab l e 1 includ ed s ea salt as 1. 6·Cl - (NaCl). This analysis suggests that east and we st coastal sites underestim ate sea salt m a ss by about 10% on average, even with som e chloride depletion. W e recommend that sea salt be included in the reconstructed fine m a ss equati on as 1.8·C l (sea salt is 55% Cl by weight as defined by the com p osition of sea water by Se infeld and Pandis, 1998) because of th e uncertainties related to sodium measurem ents. In terestingly, the ratio of the 1.8 and 1.6 factors is 1.12, sim ilar to the average regression coeffici ent for sea salt, so perhaps som e of the underestim ate was related to the sea salt m u ltiplicati on facto r . The contributions of sea salt to the light extinction equation (incl uding its hygroscopic properties) should also be included.
3.7. Size Distrib u tions At m o spheric aerosols are typically describe d by a trim odal size distribution. The three modes are comm only referred to as the nucleation m ode (0.01 < D p < 0.1 μm ), accum ulation mode (0.1 < D p < 1 μm ), and the coarse m ode (D p > 1 μm ), and each m ode is typically

38associated w ith d i fferent for m ation mechanism s
. However, several observa tions have shown that bim odal stru cture can exist in the accum ulation mode. The existence of a bi modal size distribu tion was docum ented by Hering and Friedlander (1982) in the urban Los Angeles area. Their m eas urem ents of sulfur size distributions using a low pressure im pactor dem onstrated two types of distributions. Type I distributions had m a ss

m ean aerodynam i c diam eters (D ae ) ranging from 0.42 to 0.65 μm and were observed over a wide range of sulfur concen trations (5–52 μg m -3 ), but typically on days wi th heavy sulfate loadings. Type II distributions were associated with sm aller m a ss m e dia n diam eters (D ae ranging from 0.17 to 0.22 μm ) and occurred on days w ith low sulfat e loadings and lower relative hum idity. Their calculations suggested that Type I sulfate distributions form ed from a e rosol phase reactions, while Type II distributions for m ed from gas ph ase reaction s . Later m easurem ents by Hering et al. (1997 ) in southern California d u ring th e S outhern California Air Quality Stu dy (SCAQS)

cam paign in 1987 suggested that that the total size distribution (in contrast to a single species) was bi m odal in the accum ulation mode with peaks around 0.25 and 0.65 μm in the summ er, while size distribu tion s m easured in the fall were m o re m onomodal. Other m a ss size distribution m easurem ents perfor m ed during SCAQS by John et al. (1990) suggested that typical su lfate size distributions were bim odal with aerodynam i c m a ss

m ean dia m eters around 0.2 and 0.7 μm . The averag e m ode concentration increased with m o de diam eter, with the larg er s i ze m ode correspon di ng to the highest sulfat e concen trations on average. The transition observed between the modes suggested thatthe larger size mode was a continuation of the sm aller m ode.

39The for m ation of the two m odes observed by He ring and Friedlander (1 982), Hering et al. (1997), and John et al. (1990) was investigated by Meng and Seinfeld (1994) using m odeling. The first mode is referred to as the condensation m ode (D ae ~ -0.2 μm ) and is believed to be for m ed from nucleation and/or c ondensation processes. The larger s i ze mode is ref e rred to as th e droplet m o de (D ae ~ 0.7 μm ). Hering and Friedlander (1982) dem ons trated that for am bient concentrations, coagulation of su bmicrom e ter pa rticles to f o rm th e droplet m ode is too slow to account for the droplet mode within norm a l re side nce times, as is growth of the c ondensation mode by accretion of water vapor or by gas- phase or aerosol-ph ase production. Meng and Seinfeld (1994) dem onstrated that activation of condensation m ode partic les into fog or cloud drops, followed by aqueous phase sulfate form a tion and then evaporation, is a realistic

m echanism f

o r f o rm atio n of the d r o p let m ode. This m echanism dem o nstra t es the importance of heterogeneous aerosol processing in the for m ation of the droplet m ode. The early evidence for the bim o dality of the accum u lation m ode and several of the following exam ples that will be discussed are f r om i m pactor m easurem ents that typically have fairly coarse size resolutions. Inversions of i m p actor m easurem ents using techniqu es such as the
Twom ey inversion m a y provide further size-resolv ed information, but inte rpretation of Twom eyinverted size distributions should also be cautio ned, as artifacts can re sult using this m e thod, possibly producing spurious m odes. Ideally, si ze distributions m e asur ed w ith finer size resolu tion techniques (e.g., differential m obility an alyzer, DMA, and optical particle coun ter, OPC) can be quite us ef ul in obse r v i ng m u lti-modes; howe v er, thes e instrum e nts m easure the
tota l ae rosol and canno t be eas ily assigned to a single species. Bo th ty p e s of m e asurem ents are included in the following discussion of exam ples of bim odal accum u lation m ode size

40distributions. It should be pointed out that the type of di am eter reported m a y be different depending on the type of m easurem e n t, e.g., aerodynam i c (D ae ) versus ge om etric s i ze (D g ). Although the early observations of bim odality in the accumulation m o de were m a de in urban regio n s, John et al. (1990) state that th e presence of bim odality in the accum u lation m ode is a general feature of atm o spheric aerosols a nd not just a feature of urban aerosols. The following exam ples are by no m eans exhaustive, but are prov ided to dem onstrate that these types of size dis t ributions are not necess a rily as s i gned to one type of location o r aeroso l

. Urban Observations Zhuang et al. (1999) perform e d M O UDI m easur em ents for 22 days in Hong Kong in the winter of 1996 and early 1997. These im pactor data were analyzed for sulfate, am monium , and nitr ate, and f it with log norm a ls. Sulf ate and ammonium s i ze distributi ons were bim odal with aerodynam i c m ode diam eters around 0.2 ± 0.15 μm and 0.58 ± 0.11 μm . The droplet m ode dom i nated and was associated with high rela tive hum idity and low clouds. During the 2002 Baltim ore field cam paign (4–12 July 2002), Adam et al. (2 004) observ e d a haze event that was due to sm oke originating from Canadian forest fi res. Size distributions were m easured with an SMPS (scan ning m obility particle sizer) and an APS (aerodynam i c particle sizer), and volume size d i stribu tions showe d m u ltiple m odes in th e a ccum u lation m ode range

. MOUDI aerosol size distributions were m easur ed during the Pittsbur gh A i r Quality Study (PAQS) for one year during summer of 2001 thr ough summ er 2002. Caba da et al. (2004) showed that in sum m e r sulfate size distributions peak ed around 0.7 μm, with another peak around 0.2 μ m revealed by the Twom ey inverted data. W i nter sulfate size distributions w e re m o re bimodal (D ae around 0.2 and 0.7 μm ), corresponding to lowe r sulfate concentrations overall.

41Rural Observations Aircraft m easurem ents perform e d by Hegg et al. (1993) in remote regions over the North Atlantic Ocean suggested that m e asurem ents in clouds show different types of sulfur size distribution com p ared to those in clear air, probably due to hete rogeneous aerosol processing by clouds. In Point Reyes National Seashore, Rive ra-Carpio et al. (1996) m easured MOUDI an d DMPS (differential m obility pa rticle sizer) si ze distributions in Oc tober 1993 and summer 1994.
Low m a ss sulfate concentrations corresponded to bim odal peaks in the accum u lation m ode (D g ~ 0.1, 0.4 μm ) , m e dium mass concentrations corresponded to a m onomodal peak (D g ~ 0.25 μm ), and high sulfate concentrat ions corresponded to a m o stly m o nom odal peak around D g ~ 35 μm

. In October, bim odal sulfate distributions were observed for both low and high m a ss days, with peak diam eters around 0.15 and 0.35 μm . Si m ilar m eas urem e n ts were perfor m ed at El Yunque in Puerto Rico in spring 1992 that indicated two type s of sulfate size distributions. Most of the

sam p les we re bim odal with peaks around 0.1 a nd 0.3 μm, and m onomodal size distributions peaked around 0.3 μm

. Several size distribution m eas ure m ents have been perform e d i n the Grand Canyon region. Zhang et al. (1994) report sulfate size distributi ons m easured with a low-pressure im pactor corresponding to D ae around 0.1–0.3 μm and 0.5-1.0 μm , and in som e cases bimodal size distribution. Malm and Pitchf ord (1997) report DRUM (Davis rotating universal size-cut monitor) size distributions m easured at th e Grand Canyon in winter 1988 and in summer in Shenandoah. Larger geom etric m a s s m ean diam eters were observed at Shenandoah (0.32 μm ) than at the Grand Canyon (0.21 μm ). Relati onships between size param e ters and m a s s concentrations suggest larger sulfate m a sses correspond to larger m a ss m ean diam eters, especially at Shenando ah. At both locations sulfate higher m a ss concentration s were also associated w ith narrower size distributions.

42Recent Observations of Size Distr i b u tions Usin g DMA and OPC Data at National P a rk Service Special Studies Southeastern Aerosol and Visibility Study (SEAVS) During the SEAVS study at Great Smoky Moun tains National Park TN in 1995, ASASPX size distributions were m easured in the size ra nge from 0.1 to 3 μm (Am e s et al., 2000; Hand et al., 2000 ). Because o f the m u lti-valued resp onse of the instrum e nt in the 0.4–0. 6 μm range, determ ining bi m odality of these distribu tion s is difficult, although th ere were several period s where the p r esence of multi-m odes was indicated. Grand Canyon Visibility Study (GRAVS) Size dis t rib u tion m easurem ents were m a de using a DMA and OPC (active scattering aerosol spectrom e ter probe, ASASP-X) durin g the GRAVS study in Grand Canyon National Park AZ in summer 1998 (Hand, unpublished data). These size distributi ons are not ideal for investigatin g bim odality of the accumulation m o de because a n im pactor was used with the DMA
to rem ove large pa rticle s that contribute to m u ltiple -charg ed particles. T h e ASASP- X data are aligned with the DM A data for sizes greater than 0.5 μm , but the ASASP- X data have consider able uncerta inty due to calibr a tion issues. However, there are some size distrib u tions th at do appear to be bim odal in the accumulation m o de. Big Bend Regional Aerosol and Visibi lity Observationa l Study (BRAVO) Size distribution data were obtained using a DMA, OPC (L ASAIR), and APS during the BRAVO study at Big B e nd National Park in 1999 (Hand and Kreidenweis, 2002; Hand et al. 2002). Bimodal accumulation m o de volum e size di stributions were of ten observed. Out of 117 days of hourly size distributi ons, bimodal structure in the accum u lation m ode was observed for

som e part or all of the day for 62 days.

43Yosemite A erosol Char acter i z a tion Study (YACS) During the Yose m ite Aerosol Characteriz ation Study (YACS) of 2002, DMA, and OPC size distribution m easurem ents were perform e d during sum m e r and early fall (McMeeking et al., 2005). Although less frequently than at BRAVO, bim odal accum u lation m ode size distributions were observed for som e portion of eight days during the study.
4. Hygroscopic Grow th The hygroscopicity of atmospheric aerosols is an im portant characteri stic that determ ines how a particle will behave in a changing relative hum idity (RH) environ m ent. Soluble par t icle s will up take water, resulting in incr e a sed m a ss a nd particle size, bo th o f which determ ine how ef

f i ciently p a rticle s sca t ter light, as well as the i r atm o spheric lifetim es. A pure salt particle (e.g., ammonium sulfate) exp o sed to increasing RH will undergo an abrupt change from a solid particle to a droplet at a particular relative hum idity (referred to as deliquescence) th at is specific to its chem ical com position. Above this point th e particle continues to grow exponentially. As the RH decr eases, th e so lution d r oplet will lose wa ter by ev aporation an d rem a in in a m e tastable supersaturated state until it efflor esc e s and r e tur n s to a so lid partic le at a lower RH than th at at which it deliquesced. The m e tastab le state can ex ist for indefinite periods of ti m e . This behavior is also referred to as h y steresis because th e particle follows a different path of growth and evaporation. Although extensive laborato ry studies have been perform e d to charac terize the hysteresis behavior of hygroscopic aeroso l s of know n c o m position (e.g., Tang and Munkelwitz, 1994; Tang, 1996), m a ny field studies have also been perform e d to unders tand the relationship between the hygroscopic, optical, and chem ical propert ies of ambient aerosols. These types of

m easure m ents are typ i cally perform e d by a fe w different m e thods. Tandem differential m obility analyze r s (T DMA) arran g ed in serie s allow f o r the selec tion of a single particle s i ze in the f i rst

44DMA (typically a dry size). The pa rticle size is m easured in th e second DMA after it has been exposed to increased (or decreas ed) relative hum i dity in a condi tioner that separates the two DMAs. Growth factors ( D/D o ) are derived fro m these m easurem ents as a ratio of a hum idified particle diam eter ( D ) to the initia l d r y par tic le d i am eter ( D o ) as a f unctio n of rela tive hum idity. This technique has been e m ployed in m a ny fi el d studies, several of which are reviewed by Cocker et al. (2001). The results of most of thes e studies suggest the presence of particle m odes with varying degrees of solubil ity and hygroscopic characteristics (“m o re” or “less” hygroscopic modes), reflecting the varying chem ical com p osition and m i xing properties of the aerosols.
Bi m odal growth of urban aerosols has been shown to have a less hygroscopic m ode with D/D o ranging from 1.0 to 1.4 (for RH ~ 80–90 %) and a m o re hygroscopic mode with D/D o = 1.1–1.8 (e.g., Zhang et al., 1993; Busch et al., 1999; Ferron et al., 1999). Carrico et al. (2005) observed

monom odal, bim odal, and trim odal growth prof iles at Yosem ite National Park. They found an inverse relationship between th e mass fraction of POM and hygros copicity and found that the growth factors were significantly lower than expected for ionic com ponents of the aerosol

com position, especially during periods dom inated by biom as s sm oke. Another technique for characterizing particle gr owth utiliz e s optical par tic le coun ter s tha t

m easure aerosol size d i s t ribu tions at changing relative hum idities . During SEAVS, Kr eisberg et al. (2001) used a relative-hum idity-m oderated differential m obility optical particle s i ze spectrom e ter to m easure dry and hu m i dified particle size distribu tions. Hand et al. (2000) used a rela tive

- humidity -controlled op tica l particle co unter to obtain both dry and hum idified size distributions. Size distributions statistics (su c h as geom etric m ean diam eter and integrated volum e concentrations) for both the wet and dry di stributions are used to construct diam eter growth curves ( D/D o ). This m e thod differs from the TDMA m e thod in that D/D o curves are

45determ ined for an integrated aerosol size distri bution, rather than for individual sizes, s o inform ation regarding mixing and “more” and “l ess” hygroscopic m odes is not available. Both of the above m e ntioned techniques to m easure growth curves rely on m easurem ent s of particle size in a changi ng relative hum idity environm ent. Another m e thod for estim a ting particle gro w th is to co ndition the aerosol sam p le in a nep h elom etry s y stem . Day et al. (2000 ) describ e an experim e ntal techn i qu e used to m easure dry and humidified light scattering coefficients from which ligh t scattering g r owth curves ( f(

RH) = b sp (R H ) /

b sp (dry ) ) have been derived for several special stud ies in national parks (e.g., Day and Malm , 2001; Malm et al., 2003; Malm et al., 2005b). Several investigators have used a variation on this technique of

m easuring a dry and hum i dified b sp to com pute f (RH) (e.g., Sheridan et al., 2001; E l dering et al., 2002; Carrico et al., 2003). Growth curves derived from nephelom etry system s ( f

(RH)) and from TDMA system s ( D/D o ) are no t d i rectly com p arable because, besides being a function of aerosol

com position and m i xing characteristics (sim ilar to D/D o ), f (RH) curves are also a function of aerosol size distributions that could be changing independen tly of RH effects during a

m easure m ent cycle and correspond to an average of scattering due to aerosol types growing at different rates. Laboratory studies suggest that m i xed salt particles have a com p licated growth behavior with m u ltiple deliquescence points (Tang, 1997), but the behavior is fairly well und erstood an d can be predicted by several equi librium m odels (Ki m et al., 1993; Clegg et al., 1998a,b; Nenes et al., 1998). Less is understood about the hygros copic properties of organic aerosols or inorganic/organic aerosol m i xtures . Laboratory and som e fi eld studies h a ve investig ated the ro le that o r gan i c species hav e in th e hygroscopic growth of inorganic salts or m i nerals and indicate that organics can change the deliquescence poin t of the pure inorgani c species (e.g., Andrews

46and Larson, 1993; Lightstone et al., 2000) and, depe nding on the properties and m a ss fractions of the organic com pounds, can enhance, reduce, or not effect the rate of growth of the inorganic species (Andrews and L a rson, 1993; Saxena et al., 1995; Hansson, et al., 1998; Lightstone et al., 2000; Chan and Chan, 2003; Prenni et al., 2003; Brooks et al., 2004; Gysel et al., 2004; Mikhilov et al., 2004; Carrico et al., 2005; Malm et al., 2005b). Many organic com pounds have been shown to have no deliquescent or efflorescent be havior at all (e.g., Peng et al., 2001). Virkkula et al. (1999) f ound during a field study in Spain th at internally m i xed pa rticles of a m m oniu m sulfate and organic com p ounds take up water independently of one another. In the atm o sphere, the aerosols are a com p licated m i xture of inorganic and organic species with com p lex gr owth behaviors that m a y not be well represented by laboratory studies. It is like ly th a t a larg e f r action of h ygroscopic pa rticle s ex ist in supe rs atura t ed eq uilib rium as aqueous droplets below their deliquescence RH, based on the num e rous studies that report a

sm ooth func tion of particle growth with rela tiv e hum i dity ra ther than step-wise growth behavior. This behavior has been observed for D/D o g r o w th curves in sou t heas t Texas (San tarp ia e t al., 2004, 2005), Great Sm oky Mountains National Park (Hand et al., 2000), a nd Yosemite National Park (Carrico et al., 2005). Sm ooth f (RH) curves have also b een obs erved in the Netherlands (te n Brink et al., 1996), Great Sm oky Mountains, Grand Canyon, Big Be nd, and Yose m ite national parks (e.g., Malm and Day, 2001; Malm et al ., 2003, 2005b), Portugal (Carrico et al., 2000), China (Xu et al., 2002), North Carolina (Im et al., 2001), the Maldives (Eldering et al., 2002), and during ACE-Asia (Carrico et al., 2003). Although a variety of aerosol types likely exist at these lo catio ns, their sm ooth growth curves sug g est thes e particle s exis t eithe r in a equilibrium state, lacking growth characteristics like deliq uescence points due to their nonsoluble/soluble

47m i xture, or in a supersaturated equilibrium stat e with a very low efflorescence RH (i.e., ac idic aerosols). In either cas e, water a ppears to be associated with thes e aerosols at low values of RH. The difference between f (RH) for amm oniated sulfate states between fully neutralized ammonium sulfate and more acid i c sulfate is su mmarized in Figur es 5a–c. Figure 5a shows the f

(RH) “no solids” curves (Clegg et al., 1998b) for am m onium sulfate, bisulfate, and sulfuric acid for a m a ss size distribution with D g = 0.4 μm and σ g = 1.9. Notice there is little difference between the ammonium sulfate and bisulfate f (R H) curves u p to ~ 70% RH, while for RH > 70% the bisu lf ate f (RH) curv e is abou t 1 .2 tim es the ammoni um sulfate cu rve. The su lfuric a c id f

(RH) curve is about twice the ammonium sulfate curve for most RH va lues. However, the dry

m a ss scattering efficiencies for a mmonium sulfat e, bisulfate, and sulf uric acid are 3.72, 3.35, and
2.66 m 2 g -1 , respec tive l y, of f

s etting the dif f e ren ces in f (RH) curves at high hum i dity. The m a s s scattering efficiencies for ammonium sulfate, bisulf ate, and sulfuric acid are plotted as a function of RH in Fi gure 5b to assess the effective scattering of a fixed am ount of sulfate ion interpreted as any of these three form s of sulfat e. Notice th at at low R H the m a ss scattering efficiency for bisulfate is lower than the a mmonium sulfate m a ss scattering efficiency and about equal at higher RH. Sulfuric acid m a ss scattering efficien cy is abou t the sam e as ammonium sulfate m a ss scattering efficiency at low RH but greater at high RH. Figure 5c summ arizes thes e differences. The ratio of the sulfate ion m a ss scattering efficiency inte rpreted as ammonium bisulfate and as sulfuric acid to th e ammonium sulfate efficiency curve is sho w n as a func tion of RH. Notice that at low RH (10–70%) the bisulfate efficiency is about 20% lowe r than the ammonium sulfate

m a ss scattering efficiency, and at high RH they ar e about equal. Sulfur ic acid m a ss scattering efficiencies are 10–20% greater than a m m onium su lfate efficiencies over m o st of the RH range and 40% greater at very high RH values (95–98%).

48In the IMP R OVE for m ulation, the for m of sulf ate is assum e d to be ammonium sulfate

. From Figure 5c it is evident tha t this choice o f a mmonium sulfate can either be an over- or underestim ate of true sulf ate scattering, depending on the ratio of the ammonium t o sulfate ion. However, the current f (RH) growth curve u s ed in th e IMPROVE e quation is based on an inte rpola t ed D/D o cu rv e between the asce nding and descending branches of growth for ammonium sulfate and reaches a va lue of 1 at 40 % RH (no water is associated with th e particles below 40% RH) (Sisler and Malm , 1994). This curve was derived to approxim a te smooth growth curves observed in field st udies. W e propose applying an f (RH) growth curv e corresponding to equilibrium calcu lations for amm o nium sulfate be low the deliquescence point to 0% RH using the Aerosol Inorganics Model (AIM) with the “no solids” option (Clegg et al., 1998b). This

sm ooth curve also approxim a tes the behavior obs erved for m i xtures of aerosols as those observed in the studies cited above ; however, it differs from the cu rrent curve in that it allows
water to be associated with the aerosol for RH values below 40%. Organics are assum e d to be nonhygroscopic because of the lack of conclusive evidence; however , laboratory and field results suggest they are weakly to nonhygroscopic, (Malm et al., 2003; Carrico et al., 2005; Malm et al. 2005b). Sea salt f (RH) curves are com puted using NaCl growth factors derived from the AIM model (Clegg et al., 1998b). No wat e r is associated with sea salt below its crystallization point (RH = 47%).

49Fi gure 5. ( a ) f (R

H) c u rves usi n g the “n o s o l i d s” me t h od f o r a m m o ni um s u l f ate , amm o ni u m bi sul f a t e, an d sulfuric acid (ass umin g a siz e distribution with D g = 0. 4 μm a n d σ g = 1 . 9 ) . (b ) Sul fa te m a s s sca tterin g efficiencies for amm o nium sulfate, am m o nium bisulfate, and s u lfuri c acid using the cur v es in par t (a). (c ) Ratios of am monium bisul f ate and s u lfu r ic acid m a ss sc attering efficiencies to th e amm o nium sulfate m a ss scattering effi ciency s h own in (b).

5a

505b

5c

515. Mass Scattering Efficiencies In order to review mass sca ttering efficiencies, it is important to understand the
term inology used and the im pact of assum e d a e rosol m odels upon the resulting estim a tes. W e motivate this section b y a theo retical d i scus s i on of m a ss scattering efficiencies, includ ing derivations and effects of th e assum e d model on derived estim ates. Later we review other

em pirical methods used for estim ating m a ss scatte ring efficiencies from m easure m ents and how the assum p tions applied in these methods m a y re sult in estim ates that, although they m a y be referred to as m a ss scattering effi ciencies, in fact m a y actually differ in their physical m eaning. The final subsections provide a survey of repor ted m easured m a ss scattering efficiencies u s in g different m e thods and estim ates derived from IMPROVE data.
5.1. Theoretica l Discussion The role of aerosols in visibi lity degradation or clim ate forcing has m o tivated efforts to quantify the optical properties of specific aeroso l species. The term inology used and the im pact of assum e d m odels on the am ount of change in extinction apportioned to individual aerosol species h a v e been subjects of deb a te. For ex am ple, ranges in estimates of m a s s scattering efficiency of sulfate aerosol applied in clim ate forcing m ode ls (Penner et al., 1993) arose due to the assum p tions regarding the presence of other chem ical species (e.g., ammonium and/or water)

or assum p tions concerning shifts in the size di stribu tion with ch anges in ae rosol m a ss in the calculation of m a ss scattering efficiency (Zhang et al., 1993; Anderson et al., 1994; McMurry et al., 1996). White (1986) presents a thorough discussion of the definiti ons of extinction efficiency and the consequences of various assum p tions of the assumed aerosol m i crostructure upon the apportionm e n t of extinction to its chem ical com p onents. Mass extinction (or s cattering) efficiencies ar e d e f i ned as th e tota l aeros o l extin ction (or scattering) divided by the total aerosol m a ss a nd can be calculated th eoretically for spherical

52particles of known composition and size using Mie theo ry (van de Hulst, 1981). Aerosol m odels typically as sum e that aerosol species are m i xed externally ; th e s i m p lest ex am ple is a particle

com posed of a single chem ical species such as ammonium sulfate, and for this case th e extinction efficiency is referred to as a “m ass extinction effi ciency”. However, realistically, particles in the atm o sphere com p rise a variety of inorganic and organic sp ecies. These types of particles are referred to as internal m i xtures, and their extin c tion efficiencies are term ed “specific

m a ss extinction efficiencies”. In tern ally m i xed part icles can also be externally m i xed from other particle populations; th e m o st obvious case would be inte rnally m i xed fine mode aerosols externally m i xed from coarse m ode aerosols. For the following discussion, the aerosol size distribution refe rs to an exte rnally m i xe d aerosol of a single chem ical com p onent, j . For a corresponding aero sol num ber distribution f

N,j (D p ) and com p lex refractive index n j = m + ik , the light extinction coefficient ( b ext , j ) is

com puted with equation 7 and has units of inverse length. 

## ∫ ∞

= 0 , 2

, ) ( ) , , ( 4 p p j N p j ext p j ext dD D f D n Q D b λ π ( 7 )

The Mie ex tinction efficiency is g i ven by Q ext (n j ,D p , λ ) and is a function of refractive index, particle d i a m eter ( D

p ), and wavelength ( λ ). Equation 7 can be reform ulated in term s of aerosol

m a ss size distribu tion f M,j (D p ) by ma king the following substituti on for the num b er distribution (equation 8), with species particle density given by ρ j : ) ( 6 ) (
, 3 , p j M p j p j N D f D D f π ρ = ( 8 )

Substitu ting equation 8 into equation 7 gives

53

## ∫ ∞

= 0 , , , ) ( ) , , ( p p j M p j j ext j ext dD D f D n b λ α ( 9 )

where the s i ngle particle m a ss extinction efficien cy ( α ext,j ) has units of m 2 g -1 and is given by

p j p j ext j ext D D n Q ρ λ α ) , , ( 2 3

, = (10)

Nor m alizing equation 9 by the total m a ss concentration of species j ( M

j ) allows th e extinc tion efficiency to be written as 

## ∫ ∞ ′ = 0 p p j M j ext M D d D f j ) ( ) ( , , α α (11)

where f' M,j (D p ) is the norm a lized m a ss distrib u tion

. If f' M,

j (D p ) does not vary with total m a ss concentratio n, then the average m a ss scatterin g efficiency for species j can be considered a constant and the light extinction coefficient corresponding to species j can be written as
b ext,j = j M α M j (12)
The tota l extinction is th en a lin ear c o m b ination of the specie s m a ss concentra tions.
b ext = Σ j M α M j (13) Equation 13 also holds for an in tern ally m i xed aerosol where the chem ical sp ecies are m i xed in fixed proportions to each other, th e index of refraction is not a function of com position or size, and the aerosol density is independent of volum e
. W h en com p uting tota l extinc tion u s ing M i e theory, the m i croscopic structure of the aerosol (that is, the extent of inte rnal or external m i xing) is found to be relatively unimportant, so that the assu mption of in terna lly vers us externa l ly m i xed particles does not have m u ch im pact on the predicte d results. This insens itivity of total sc atte ring or e x tinc tion to the aeroso l m i xture has

54been dem o nstrated by a num b er of authors, including Hasan and Dzuba y (1983), S l oane (1983),
Pilin is et al. (1995), and McMurry et al. (1996). The m a ss extinction (or scatteri ng) efficiency is a stronger function of density and size than optica l proper tie s such as ref r activ e inde x (see equation 10). Severa l investigators have reported on the size dependence of m a ss scattering efficiencies (M alm and Pitchford, 1997; L i et al., 2000; Hand, 2001; Malm et al., 2003). Other authors report the dependence of m a s s scattering on m a ss concentrations (Malm et al ., 2003) or on light sca ttering coefficients (Lowenthal and Kum a r, 2004); how ever, these re lationships arise due to the dependence of b sp and m a ss on particle size. Estim ating the change in extin ction due to th e r e m oval or addition of a single spec ies is different from assigning a fraction of extinction to a chem ical speci es or m i xture of species, and
is referred to as a “partial m a ss extinction efficien cy” ( α ext,part ).
⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ∂

∂ j ext part ext M b
= α , ( 14)
The par tia l extinc tion e f f i ciency is dependent o n change in com positio n as we ll as change in aerosol s i ze as species are added o r rem oved. For exam pl e, McMurry et al. (199 6) exam ined

α

ext,part as a function of for m ation mechanism s for sulfate. If sulfate was form ed by gas phase

reac tions, lo wer hum i dity condition s led to sm aller pa rticles sizes; whe r eas when sulf ate was for m ed in aqueous processes, the higher relative hum i dity co nditions led to la rger pa r tic le sizes. A sim p le exam ple illustrating som e of these concepts is sh own in Figure 6 (Malm and Kreidenweis, 1997). The insensitivity of the tota l com puted scattering to the m i xing assum p tion is presented in Figure 6a. Two aerosol species w ith the sam e total volum e, size distribution, and index of refraction, but with dens ities differing by a factor of 2, ar e externally m i xed. They have

55m a ss scattering efficiencies of 3 m 2 g -1 and 6 m 2 g -1 , respectively. The externally m i xed aerosol contains 10 μg m -3 of species 1 an d 5 μg m -3 of species 2, with each species contributing 30
Mm -1 to the tota l aero s ol scatter i ng o f 60 Mm -1

. Fi gure 6. ( a ) Di agr am c o nt ras t i n g m a ss sc a tteri n g e fficiencies for inter n all y versus exter n ally mi xed par t icles. (b) Parti a l sc atter i ng e fficiencie s for internally an d external ly mixe d parti c les.

If species 1 and species 2 are now assum e d to be internally m i xed (see lower part of Figure 6a), the specific m a ss scattering efficien cy for the m i xed particle is now required for calcu lation of the to tal aeroso l s c attering. Th e specific m a ss scattering efficiency can be

com puted as the m a ss-weighted average of the efficiencies o f the individual species (4 m 2 g -1 ),

assum i ng several conditions are m e t. The optical properties of the m i xtur e m u st be sim ilar to those for th e indiv i dual species (wh i ch m u st als o be sim ilar ; th is cond ition is m e t, f o r exam ple,

56by a m i xture of a m m o nium sulfate and organics, with real refractive in dices of 1.53 and 1.5, respectively). Volum e conservati on must be invoked, and the size d i str i bution of the in terna l

m i xture m u st be sim ilar to the size distributio ns of the external m i xtures. By applying the specific m a ss scattering efficiency, a total aeros o l b sp for the sam p le is again com p uted as 60
Mm -1 (see Figure 6a). However, the apportionm e nt of scattering to species 1 and 2 is di fferent under these two models. Using the externally m i xed m odel, sp ecies 1 and 2 each contri bute 50% of the to tal scattering. In the internally m i xed case, species 1 contributes 66% of the scattering budget (since it m a kes up 66% of the tota l m a ss), while species 2 con t r i b u tes 33 %. T h is discrep a ncy ar ises because when the species are in ternally m i xed, the sam e scattering efficiency is ass i g n ed to both species, although independently they have different efficiencies . This discrepancy can only be resolved if the specific mass scatter i ng efficiency of the mixed aerosol is prorated to its chemical constituents, based on their relati ve densities. The apportionment of scattering to specific species is therefore independent of whether an exter nally or internally mixed model is assumed. This sim p le exam ple demonstrates that the c ontr i bution of ea ch species to tota l extin c tion is sensitive to the assumed m i croscopic structure of the aerosol. W h ite (1986) refers to this as the apportionm e n t problem , distinct fr om the problem of com p uting total extinction from estim ates of size-dep e ndent chem ical com posit ion tha t we just dem onstrated to be s i m ilar f o r th e two cas e s in Figure 6a. For the externally m i xed case, the to tal ex tinc t ion f o r the m i xture is c a lculated by

com puting the contribu tion of each species sep a rately, and th e species co ntribu tion to the total is well defined if we know the size dis t ribu tion of each species

. For the internally m i xed case, it

m a y be m i sleading to a ssign a p e rc entage of th e tota l ex tin ction to ea c h specie s o n a m a ssweighted basis, as dem onstrated in F i gure 6a.

57The previous discussion concer ns itself with ap portion i ng e x tinc tion to a spe c ie s a s it resides in the am bient atmosphere. F r om a regulator y standpoint, the change in total scattering as a function of the rem o val of a species m a y be of interest. T o tal scattering can be com puted for the m i xture, and for th e case when one species has been rem oved from the m i xture; the difference between these values pr ovides the contribution of the sp ecies to total scattering. As an

exam ple, we com pute the partial s cattering effi cien cy for species 2 u nder the ass u m p tions of
extern ally m i xed particles. The pa rtial s catter i ng ef f i cienc y is ob taine d by com p uting the to ta l aerosol scattering assuming only sp e c ies 1 is p r e s ent (30 M m -1 , see Figure 6b). Subtracting this value f r om the total s cattering obtained for the mixture (60 Mm -1 , see Figure 6a), we deduce that species 2 contributed 30 M m -1 ( h alf) to the m i xed aerosol scattering. The de rived partial scattering efficiency of 6 m 2 g -1 for species 2 [ ∆ b sp /

∆ mass = (60-30 Mm -1 )/(5 μg m -3 )] is the

sam e as its m a ss scattering efficiency from Figure 6a. Investigatin g the sam e scenario but for the internally m i xed case (see the lower part Figure 6b), we assum e that the rem oval of one s p ecies from the internal m i xture would conserve particle nu mber concentra tions bu t reduce par tic le size. T h is size red u ction alter s the specif i c scattering efficiency of the m i xture, which is now assum e d to be 2 m 2 g -1 . The total a e roso l scattering is thus 20 Mm -1 , which leads to the c onclusion th at the partial scattering efficiency of species 2 is 8 m 2 g -1 [ ∆ b sp /

∆ mass = (60-20 Mm -1 )/(5 μg m -3 )]. W h ite (1986) presents a thorough discussion of the definitions of spe c ific extin ction and m a ss extinction efficiency and of the consequences of various assum p tions of aeros ol m i crostructure upon the apportionm ent of extinction to its ch em ical com ponents. Issues also arise when apporti oning scattering to species th at have different hygroscopic properties. Consider an extern al m i xture of hygroscopic a nd nonhygroscopic aerosols species

58with sim ilar m a sses. The m a ss scattering effici encies of the dry nonhygroscopic and hygroscopic species are each 3 m 2 g -1 , while that of the wet hygroscopic species is, because of associated water, 8 m 2 g -1 . W h en internally m i xed, the wet specifi c m a ss scattering efficiency will be 3–8

m 2 g -1 , depending on the hygroscopic pr operties of the m i xed aerosol . Several authors discuss aerosol gro w th characteristics as a function of RH and have succe ssf ully predicted th e sca tte rin g characteristics of the mixed particles (Ande rson et al., 1994; Sl oane, 1983, 1986; Malm and Pitchford, 1997; Malm et al., 2000, 2003, 2005b). Howe ver, the apportionm ent of scattering to a particular species is still probl em atic. Typically, one growth curve is developed for the m i xed species, and scattering due to water is apporti oned proportionally am ong all aerosol com ponents, even though only one of the species m a y be hygr oscopic. An exa m ple would be a m i xture of ammonium sulfate and a weakly hygroscopic organic species.
5.2. Methods for Deriving Mass Scattering Efficiencies The m e thods typically used to estimate m a ss scattering efficiencies depend on the type of

m easure m ents and data available. In this se ction we will discuss th e most common m e thods used. W e use the term “m ass scattering efficien cy” to refer to estim at es that correspond to a single aerosol com pone nt such as dry ammonium sulfate, and although one could argue that species su ch as POM and soil corres pond to a combination o f che m ical com ponents, we will use this term to correspond to thos e ef ficiencies also. W e use th e term “specific m a ss scattering efficiency” to refer to aerosols com posed of m o r e than one species, for exam ple, a “fine m ode specif i c m a ss scatte ring ef f i ciency”. W e will also us e this te rm to ref e r to aerosols that includ e
water m a ss. For ex am ple, if an efficiency for an inorg a nic salt par tic le with assoc i ated wa ter

m a ss is reported, we refer to it as a “s pecific m a ss scattering efficiency”. The sim p lest m e thod for com puting efficiencies is with m easured m a ss concentrations
f r om f

ilter s a m p les and m easured light scatter i n g coef f i cients f r om nephelom etry. For an aeroso l

59population, a specific m a ss scattering efficiency α sp_s pec can be defined as the ratio of a light scattering coefficient corresponding to the m a ss concentration ( M ) of that population.

M b sp spec sp =

_ α (15)
The averag e specific m a ss sca ttering efficiency can be esti m a ted by dividing the average scattering coefficient b y the averag e m a ss concen tration for a given set of m easurem ents, or a linear regression can be pe rform e d on the data and the slope of the linea r f it can be interpr e ted a s the specific m a ss scattering efficiency. Specific m a ss scattering efficiencies deriv e d in this

m a nner represent an average aero s ol th at co ul d be changing due to va riations in relativ e hum i dity, s i ze dis t ribution, and co mposition d u ring the sampling period. Mass concentration s used in this m e thod could be either gravim etric m a ss or the sum of chem i cally analyzed m a sses, or be com p uted from integrated volum e distributions using an assum e d de nsity.
A num b er of investigators have taken advantage of the form of equation 13 ( b ext = Σ

α

Mj

M

j ) to construct a m u lti-line ar r e gres sio n (MLR) model with b ext as the independent
variab le, an d the m easured aeroso l m a ss concentrations for each species j ( M

j ) as the dependent variab les. T h e regres sio n coefficients are then interpreted as m a ss extinction (or scattering or absorption) efficiencies. The assu m p tions required in this formula tion are that all the com ponents contributing to extinction are included, equati on 13 is a reasonable approxim a tion to the relationship between extinction and the various aer osol species, the number of sa m p les is large enough to give stable results, and the concentrations of the species are uncorrelated. However, as stated by White (1991), “Model sim u lations show the procedure to yield usefully accurate results under favor able conditions. An i m portant lia bility is that the availability of standard software m a kes it easy to perf orm regression under unfa vorable conditions.” Regression -derived efficiencies are vulnerab l e to a variety of system atic and random errors. At

60the m o st basic leve l, th ere is the is sue that m e te orologically driven fluctuations of the existing aerosol con centration s m a y cause aerosol mass concentrations of different species to be collinear. The high degree of collinearity com m only found am ong aerosol species can m a ke regression results very se nsitive to the choice of species to be included in the analysis. A m o re practical difficulty is that re gression results can be biased by random uncertainties in the

m easure m ents. Standard regression models tend to ov erpred ict the coefficien ts of sp ecies that have lower uncertainties (e.g., sulfates) and underpre dict the coefficients of species with larger

m easure m ent uncertainties (e.g., organics), sim ilar to the discussion in section 3.1. The theoretical approach described at the begi nning of this section (see equations 7–10) is often used to com put e m a ss scattering effici encies from m a ss (or number) distributions of aerosol spec ies f r om impactor m easurem ents or mobility o r optica l m easurem ents. However, th is

m e thod requires assumptions of the m easured sp ecies chem ical for m a nd m i xing properties of the aerosols, as well as their optical propertie s. Estim ates from this m e thod often assum e a n
extern ally m i xed aerosol, but if the size distri bution m easurem ent is obtained by m obility or optical m easurem ents (num ber size distribution) , an in tern ally m i xed aerosol is assum e d, but perhaps for separate size m odes. This m e thod has been shown to accur ately reconstruct light scattering. For exam pl e, m easurem ents of si ze distributions have been incorporated with estim ates of aeroso l optical prop erties to rec onstruct m easured scattering (and es tim ate specific

m a ss scattering efficiencies) on fine tim e sc ales (Hand et al., 2002 ; Malm et al., 2005a; McMeeking et al., 2005). These estim ates have the added advantage of allowing for the investigation of the functional dependence of efficiencies on particle size, com p osition, and hum i dity. T h e theo retical m e thod pr ovides the most accurate estim a te of efficiencies out of those discussed in this section. A disadvantage to th is m e thod is that size distribution m e asurem ents

61are m o re analytically intensive and not often available fo r routine m o nitoring, so com puting

m a ss scattering efficiencies by this method is not rou tinely possible. Estim ating m a ss scattering efficiencies as the change in b ext resulting from the removal (or addition ) of a single species is d i fferent from assigning a fraction of m easured extinction to a chem ical species o r a m i xture of species. The ch ange in extinction resulting from a change in aerosol species concentration was described previ ously (equation 14). As species are added o r

rem oved from an aerosol, the efficiency is de pendent on change in co mposition as well as on change in aerosol size. Com puting partial m a ss scat tering efficiencies in this context requ ires a model to account for the effects of rem oval of m a ss on lig ht scattering coeffi cients, such as the ELSIE (Elastic Light S cattering Interactive Efficienci es) m odel (S loane, 1983; S l oane et al., 1991; Lowenthal et al., 1995; Om ar et al., 1999). Am ong the assum p tions in the EL SIE m odel are those as sociated with rem oving aerosol m a ss. Mass can be rem ove d or added by assum i ng that the particle s i ze changes but not the particle num b er, or that the particle num ber changes but not the particle size (L owenthal et al., 1995). Unless the option is chos en to keep the size constant, the efficiencies derived from this m e thod cannot be com p ar ed to efficiencies from other

m e thods. Al so, assum p tions m u st be m a de regard ing how to treat water m a ss associated with a

rem oved species. Although this techni que is useful in a regulatory context, in practice it is no t possible to m easure the change in light scattering due to a change in m a ss concentration, so m o re

em pirical approaches were adopted to estim ate mass scattering efficiencies.

5.3. Survey of M a ss Scattering Efficiencies A review of ground-based m easured m a ss sca ttering efficiencies from peer-reviewed literature since 1990 includes values derived from the four different methods described above (theoretical, m easure m ent, m u lti-lin ear regres sion, and partial scattering approach) and are summarized by several tables (Tables 2–5 in Appe ndix 2). The tables can be understood in the

62following way: the m a s s scattering efficiencies are listed by speci es (e.g., sulfate, POM) or as specific m a ss scattering efficiencies for m i xtures of aerosols by size m o de (i.e., fine, coarse, or total). The tables also list th e study location, study na m e , aerosol characteristics (e.g., s m oke) if noted, and the study tim e period. Each m e thod ta ble has a correspondi ng notes table that provides details of the m easure m ents, s i ze rang es, th e relative hum idity of the m e asurem ents,

assum p tions, and the wavelength at which the measur em ents were m a de if it was oth e r than 550

nm ; these can found in Appendix 2. Occasion a lly th is inf o rm ation may also be found in a footnote in the m a ss scattering efficiency met hod table for quick refe rence. Citations are

num b ered consecutively in alphab etical order (a full citation lis t can also be found in Appendix 2). The “note” colum n in the tab l e refers to the citation num ber as well as the en try in the notes table. W h en appropriate, we com put e the averag e (and one standard deviation) for values in the cited literature and note it in the footnotes. Except for averages, values are listed as found in the literature, and furthermore, sulfate m a ss scatte ring efficiencies have been norm a lized to dry ammonium sulfate when possib l e. This norm a lizat ion is perform e d because su lfate efficiencies
are repo rted under a variety of conditions. Fo r exam ple, they m a y be reported in term s such as sulfate ion, ammonium sulfate m a ss, or amm oniated sulfate m a ss (depending on the acidity), and they m a y be reported for a range of relative hum i dity values corresponding to associated water

m a ss. Sulfa t e m a ss scattering efficiencies repo rted for R H > 45% were converted to dry ammonium sulfate m a ss scattering efficiencies based on reported ammonium to sulfate m o lar ratios and f (RH) curves corresponding to amm onium sulfate. For all the entries, the original sulfate m a ss scattering efficienci es are reported, al ong with corrected dr y amm onium sulfate

m a ss scattering efficien cies in italicized font (i f already reported in th e cited m a nuscript), or noted with a (†) sym bol if we perform e d the correction to a dry amm onium s u lfate basis.

63Occasionally there was not enough infor m ation avai lable to do this correction. Other correction s in the tab l e include no rm alizing the POM effi ciencies to a m u ltiplier of 1.8. Most of the estim ates were repo rted correspond ing to POM com puted with m u ltipliers of 1.2, 1.4, 1.6, or 2.1 (see notes table for each m e thod). We norm a lized the efficiencies to R oc = 1.8 so that estim ates derived in the next section can be directly com p ared. Both efficien cies are lis ted in th e tables bu t the norm a liz ed values ar e ita lic ized. We begin our review with the theoretical m e t hod efficiencies so that later discussions of efficiencies derived by more si m p le m e thods can be understood in the context of theoretical predictions. Theoretical m a ss scattering efficien cies are rep o rted in T a b l e 2. These efficiencies are th e m o st repres enta tive estim a tes because the effects of particle siz e a nd com position can be included in the calculation fo r a single tim e period, and as pr eviously m e ntioned, derived efficiencies accurately reconstru c t s cattering ov er very fine tim e resolutions. The theore tic al

m e thod relies on com puted scat tering that is dependent on Mie theory and corresponding

assum p tions of spherical particles and optical properties.
5.3.1. Theoretica l Method The averag e fine m o de dry ammonium sulf ate m a ss scattering efficiency from the theoretical m e thod is 2.5 ± 1.1 m 2 g -1 (see Table 6). Most of the values reported correspond to the fine m o de, although coarse and total sulfate are repo rted and noted in Table 2 (see Appendix 2). The h i gh est va lue in this tab l e (6. 0 m 2 g -1 ) was repo rted for China by Li et al. (2000) and we have corrected it from a mmonium bisulfate to ammonium s u lfate but perform e d no hum idity correction. It is unclear at what relative hum idity this value is reported, although Li et al. (2000) state that particle growth based on Tang ( 1997) has been assum e d. Having som e water m a ss associa t ed with this es tim a te would be consis te nt with its higher va lue com p ared to the oth e r estim ates. For exam ple, wet specific m a ss scatteri ng efficiencies reported for Hopi Point AZ,

64Meadview AZ, Shenandoah National Park, and Great Sm oky M ountains National Park correspond to different RH values (see notes tabl e) and demonstrate the large effect water m a ss has on efficiencies, especially at Shenandoah wh ere the ambient humidity is high in summ er. Re m oving the highest value (6.0 m 2 g -1 , reported by Li et al., 2000) from the calculated average results in a m ean dry ammonium s u lfat e m a ss scattering efficiency of 2.2 ± 0.6 m 2 g -1 . The lowest value in the table (1.12 m 2 g -1 ) was observed in the Southern Ocean region south of Australia during the ACE-1 (Southern Hem i sphere Aer o sol Char act er i za tion Experim e nt) study (Quinn et al., 1998), corresponding to a sm all aver age surface m ean diam eter of 0.20 ± 0.04 μm. It is in ter e sting that give n the global distribution in the m easurem en ts, a f a irly low variab ility in dry amm oni um sulfate efficiencies is observed, perhaps a reflect ion of the robus tness of this

m e thod for com puting e fficiencies, especially w h en the optical and hygroscopic properties are well understood. The average POM m a ss scattering ef fi ciency without corrections for R oc differences was
5.9 ± 1.0 m 2 g -1 and was m o st likely affected by the assum p tions in com puting POM from

m easured organic carbon and the range of types of organics m easured. To correct for the dif f e rent m u ltip lie rs use d to com pute PO M, we norm a lized these values to an R oc of 1.8, and the resulting norm alized average POM m a ss scattering efficiency was 5.5 ± 1.6 m 2 g -1 (see Table 6). The norm a lization did n o t s i gnif i can tly change most of the estim ates (s ee italicized values in the table) becau se m o st of the studies u s e R oc values ranging from 1.4 to 2.1. This norm a lization did change the estim ate by Li et al. (200 0) in China because no R oc was reported in that study, so we

assum e d they used a value of 1. Most of the au th ors in these studies applied R oc values consistent with Turpin and Lim ’ s (2001) sugge sted values that vary accordi ng to aerosol type. F o r exam ple, during the Aerosols99 study, Quinn et al. (2001) reported values for locations ranging from the

65Atlantic Oc ean of f the coas t of Virgin ia to C a pe Town, South Africa , with aerosol origins ranging from re m o te m a rine to African dus t and biomass burning. They applied a POM multiplier of 1.6 for North Am erican air m a sses (m ore urban aero s ols ) and 2.1 for all o t her air

m a sses. W ith the exception of Li et al. (2001) , these studies did not assum e organics were hygroscopic; however, the RH corresponding to the va lue by Li et al. (2001) is unspecified. Average fin e , coarse, an d total (fine + coarse) du st m a ss scattering efficiencies were 3 .4 ± 0.5, 0.7 ± 0.2, and 1.2 ± 0.3 m 2 g -1 , respectively. It is probable th at fine dust corresponds to the tail of the coarse m ode dust di stribution; however, the higher fine m ode efficiencies are a resu lt of

these siz e s interac tin g m o re ef f i ciently with light, com p ared to the coarse m ode. Mid-range values corresponding to the total aerosol mode reflect the integrat ion over all sizes. The variab ility f o r each of these es tim ates is fairly low, conside r ing d i fferences in dust com position and size distributions, the study locations, and dust origins, wh ich include Asia, the Indian Ocean, and off the coast of North Africa (Chiapello et al., 1999; Li et al., 2000; Quinn et al., 2001, 2002b, 2004). The average fine and coarse m ode specific m a ss scattering efficiencies were 4.3 ± 0.7 m 2

g -1 and 1.6 ± 1.0 m 2 g -1 , respectively. The fine m ode values could include amm o niated salts, carbonaceous aerosols, and m i neral aerosols. These efficiencies were reported for a range of hum i ditie s, and no co rrections to a dry ae roso l were perform e d because of the lack of inform ation on the fine mode com p osition. The cut- off diam eter for these m odes m a y also vary from study to study, ranging from 1 to 2.5 μm. Given these differe nces, there is still a fairly narrow range of values reported for fine m ode sp ecific efficiencies. A much larger variation in the coarse mode efficiencies was observed. T h e com position, si ze distribution, and optical properties of the coarse m ode m a y vary consid erably given the studies reported here. For

66exam ple, the lowest value of 0.6 m 2 g -1 at Big B e nd National Park (Hand, 2001) reflects the fact that so il do m i nated the coarse com position (~ 4 0 % on average). In con t ras t , the v a lues deriv e d from the m a ny cruise-based m easurem ents (Q uinn et al., 2001, 2002b, 2004) m a y be influenced by sea salt or other species. Average fine, coarse, and total sea salt spec ific m a ss scattering efficiencies were 5.3 ± 0.8, 1.2 ± 0.3, and 2.3 ± 0.9 m 2 g -1 , respectively. Sea sa lt spe c if ic m a ss s cattering efficien cies are
not cor r ec te d f o r re lativ e hum idity and include the effects of aeroso l water m a ss. Sim ilar to what was observed with dust m a ss scattering efficien cies, th e fine m ode sea s a lt s p ecific m a ss scattering efficiencies are larger than the coarse m ode, with the total a e r osol (f ine + coarse ) in the m i ddle of the range.
5.3.2. Measurement Method Estim ates of m a ss scattering efficiencies fo r the m easure m ent m e t hod are reported in Table 3 (see Appendix 2 and Ta ble 6). Most of these values correspond to specific m a ss scattering efficiencies for the fine o r coarse m ode because the m easurem ents were perfor m ed for fine (or coarse) m a ss and m easured ligh t s catte ring. Thes e valu es are not averag ed together because the relativ e hu m i dity at which th e m e asurem ents are m a de, the types of m a ss data (gravim e tric or sum of c h em ically analyzed), and the com p osition and size ranges corresponding
to ea ch m o de vary ; the r ef ore norm a liz ing thes e data to a common RH or com p osition is not possible. S o m e studies have several values r e ported (su c h as in th e Mald ives during the INDOEX study) because they are re ported for ranges of light scat tering coefficients and for different m e asurem ent m e thods (land- and cruise-b ased) by different inve stigators a nd averaging them together would be inappropriate. Even wi th th ese d i f f e rence s , so m e spatial patte rns are noticeable. The highest fine m ode s p eci fic m a ss scattering efficiencies (> 5 m 2 g -1 ) are repo rted in urban locations such as Me xico City, Mexico (Chow et al ., 2002), F o rt Meade MD (Chen et

67al., 2003), and the New England–mid-Atlantic re gion (Poirot and Husar, 2004). These values could be high due to relative hum idity effects (esp ecia lly in the easte rn United Sta t es ) , or due to the aerosol com position. For exam ple, the efficiency of 6 m 2 g -1 reported by Poirot and Husar (2004) corresponds to sm oke aerosol that m a y have higher effi ciencies (Malm et al., 2005a; McMeeking et al., 2005). W ith the exception of s ites in Phoenix AZ and sites near Denver CO, the urban (e.g., Beijing , China, Atlanta GA, Da llas TX) fi ne m ode specific m a ss scattering efficiencies are greater than 3 m 2 g -1 . Most of the rural sites in the southwestern U n ited States correspond to lower specific e fficiencies (less than ~ 2.5 m 2 g -1 ) in Meadview AZ , Mount Zirkel in Colorado, and Spirit Mountain NV, which are close to the theoretical m a ss scattering efficiencies com puted for dry am m o nium sulfate. The exceptions to thes e low value s are thos e reported for the northwestern Unite d State s (Mo unt Rainier W A a nd North Cascades W A ) and in Bondville IL with efficiencies greater than 4 m 2 g -1 . Higher specific m a ss scattering efficiencies (usually gr e a ter than 3 m 2 g -1 ) were observed during the INDOEX expe rim e nt in the Maldives. Specific m a ss scattering efficiencies for this s t udy are ordered as a func tion of light scattering coefficients and no s i g n ificant d i ffere nce was observed for low scattering ( b sp < 25 Mm -1 )

com p ared to high sc attering periods ( b sp > 55 M m -1 ), in con t ras t to the r e lationship Lowenthal and Kum a r (2004) observed for data from the IMPROVE network. The sp ecific efficiencies reported for the Maldiv es are for an RH of 33 %, so the effects of aerosol water m a ss are probably not significant for thes e data. Specific efficiencies corresponding to the total aerosol mode were reported for Yulin, China (Alfaro et al., 2003), during the ACE-Asia study. Values were higher during polluted peri ods com p ared to periods dom i nated by dust aerosols, probably because of the change in aerosol size distribution s
.

685.3.3. MLR Method Estim ates of m a ss scattering ef ficiencies obtained using the MLR m e thod are summarized in Table 4 (see Appendix 2). These va lues are subject to v a riability based on how the regressions were p e rform e d (with or wit hout in tercepts, or acco unting for m easure m ent uncertainties) and the types of data used. Averag e fine m ode specific m a ss scattering efficiencies
were 3.1 ± 1.5 m 2 g -1 , which were som e what lower than th e average estim ate derived from the theoretical m e thod, although with much larger variability. The highest values (> 5 m 2 g -1 ) were reported in Israel, and the lowest values (2–3 m 2 g -1 ) were reported in the southwestern United States (Neva d a, Arizona, and Colorado), which is sim ilar to the spatia l distribu tion se en with the results from the m easurem ent method. Average coar se m ode specific m a ss scattering efficiencies
are 0.7 ± 0.6 m 2 g -1 , ranging from values greater than 1 m 2 g -1 in Nevada and Arizona to values less than 0.5 m 2 g -1 in Colorado, Arizona, and Israel. The variability of coarse m ode com position and size d i stributions co uld resu lt in larg e v a riability in der i ve d ef f i ciencie s
. The averag e fine m o de dry ammonium sulf ate m a ss scattering efficiency was
4 ± 3 m 2 g -1 , higher than theoretically predicted for fi ne m o de dry ammonium sulfate and with a large v a riability due to o u tliers. Rem oving the o u tliers (i.e., 10.9 and 8 ± 3 m 2 g -1 ) results in an average dry ammonium sulfate efficiency of 3.2 ± 1.2 m 2 g -1 , m u ch closer to what has been theore tic ally derived. It is poss i ble that these high values are due to wa ter a ssociate d with the nephelom e ter data, or due to uncertainties in the nephelometer data. Many of the s u lfate m a ss scattering ef ficiencies reported in th e MLR tab l e were corrected to a dry amm oni um sulfate basis, which could also contribute to uncertainties in these values. Variatio ns in rela tiv e hum i dity or aerosol acidity could result in u n certainties in the corr e c tions as th ese were ap plied in an average sense. The lowest value reported in the table (0.83 m 2 g -1 ) corresponds to the total ( D

p < 10 μm ) size distribution, dem ons trating the effects of averagi ng over larger pa rtic les (highe r

69m a ss) that h a ve less efficient light scattering properties. Also, it is pro b able that the chem ical for m of sulfate in the co arse m ode was different from a mmonium sulfate. The unnormalized average value of POM m a ss scattering efficiency was 3 ± 4 m 2 g -1 , with the la r g e var i ability ref l ec ting the range in valu es reported. The average POM m a ss scattering efficiency norm a lized to an R oc of 1.8 is 2 ± 3 m 2 g -1 . Outliers in the s e values a r e reported for Uniontown PA (12 ± 8 m 2 g -1 , Lowenthal et al., 1995), an d rem oving that outlier from the norm alized efficiencies resu lts in an average value of 1.6 ± 0.6 m 2 g -1 , which is considerably lower than th e average value of 5.5 ± 1.6 m 2 g -1 derived with th e theore tica l

m e thod. If we rem ove the cases that were computed assum i ng or ganics are som e what soluble during higher RH periods, th e average value is 2.3 ± 1.0 m 2 g -1 . Besides the outlier, the highest value reported is fo r Bondville IL (4.11 m 2 g -1 ) (Koloutsou-Vakakis et al., 2001) and has not been norm a lized becau se it correspon ds to a carb onaceous aerosol that in cludes both organic and light-absorbing carbon. The low va lues of POM m a ss scattering efficiency derived by this

m e thod provide a good exa m ple of how uncertainties associated with organics m a y result in an underprediction of derived m a ss scattering efficiencies. The average amm onium nitrate m a ss sc attering efficiency w a s 4 ± 2 m 2 g -1 . The highest values are reported for Meadview AZ and Mount Zirkel CO. However , no spatial dependence is seen, as the lowest values reported are also in the southwestern United States (Grand Canyon AZ, Canyonlands UT, and Phoenix AZ). The averag e fine, coarse, and total dust m a ss scattering efficiencies are 3 ± 2, 0.40 ± 0.08, and 0.7 ± 0.2 m 2 g -1 , respectively. Fine m o de dust m a ss scattering efficiencies are quite sim ilar to t hose derived using the theoretical m e thod (3.4 ± 0.5

m 2 g -1 ); however, coarse m ode and total dust effi ciencies are som e what lower for the MLR

70m e thod. Given the range of assum p tions and differ ent m easurem ents that are incorporated into these es tim ates, th e conv ergence of fine dust efficiencies towards 3 m 2 g -1 is notable. The average sea salt sp ecific m a ss s cattering efficien cies for the fin e , co arse, and total modes are 4.0 ± 1.6, 1.6 ± 1.2, and 2.2 (one number reported) m 2 g -1 , r e spectively. These value s are also quite sim ilar to those re ported in the theoretical table. Sea salt is hygrosc opic; therefore any water associated with m easured scattering co uld be attributed to s ea salt in the regression.
5.3.4. Partial Sca t tering Meth od Values of m a ss scattering efficien cy derive d from the partial scattering approach are reported in Table 5 (see Appendi x 2). Most of these studies em ployed the ELSIE m odel, as described previously. Species included in the m odel are su lfate, POM, nitrate, dust, elem ental carbon, and fine m ode aerosols. The two entries lis ted in the table per site for the first eight entries correspond to model results using two scenarios: (1) assum i ng a hom ogeneous

com position with constant particle size, and ( 2 ) a core /s hell sc enar io with cons tant pa rticle

num b er. All estim ates re ported in th e table using th e constant size assum p tion are in bold font. It is not appropriate to average efficiencies co m puted with both scen arios because the second scenario corresponds to changing size distributions that would al so change the efficiency. The
entr ies lis te d f o r Hopi Point towa r d the end o f the tab l e all correspo nd to es tim ates m a de at different relative hum idities. The averag e dry ammonium sulfate partial sc attering efficiency for the first scenario (including those we corrected ) in T a ble 5 is 2.7 ± 0.4 m 2 g -1 , sim ilar to the resu lts f r om the theoretical m e thod, as would be ex pected because the th eoretical basis is th e sam e . Most of the studies inc l uded in this table oc cur r ed in the western or southwestern United S t ates with th e exception of the rural sites of Bondville IL and Uniontown PA. The sites in the Southwest are mostly rural with the exception of Phoenix AZ. No strong spatial variation is noticeable. Values

71derived in Meadview AZ are som e what high er than those derived in Hopi Point. Both loc a tion s are near the Grand Canyon, with Hopi Point on th e southern rim of the canyon and Meadview on the western edge of the canyon. Ob servations from Meadview have been used to characterize subregional aerosol and visibili ty in the Southwe s t (M easu r e m en t of Haze and Vis u al Effects, MOHAVE, study) (Turpin et al., 1 997; Lowenthal et al., 2000). It is possible that the aerosols

m easured in Meadv i ew were influenced by lon g -range tran sport and th erefore p r ob ably ag ed, resulting in som e what higher efficien cies

. The average norm a lized POM m a ss scattering efficiency is 3.0 ± 1.4 m 2 g -1 . High values were m easured in Uniontown PA, Denver CO, and the Grand Canyon (Hopi Point), a m i x of rural and urban locations. The ELSIE m odel treats POM

m a ss as partly soluble (values for these studies ra nge from 25 to 60% solu bility, and th at f r ac tio n is as so luble as amm oni um sulfate), so a direct com p arison of POM partia l sca tte rin g ef f i ciency from this method to the other m e thods is not a ppropriate. T h e average a mmonium nitrate partial scattering ef ficiency is 3 .8 ± 1.5 m 2 g -1 , with an outlier v a lu e in Denver CO. The average fine dust m a ss scattering efficiency is 2.8 ± 1.0 m 2 g -1 . Especially high dust effi cien cies were repo rted for Uniontown PA.
5.3.5. Apportionment Method As part of the 1991 National Acid Precip itation Assessm ent Program (NAPAP) Report 24 on visibility, m a ss scattering effi ciencies were com puted fr om light scatte ring coefficien ts and

m a ss data based on several studies around the Unite d States. Scattering was apportioned to m a jor species such as ammonium sulfate and orga nics (W hite, 1991). Th e intention of the apportionm e n t schem e was to provide the range of efficiencies based on extrem e assum p tions

. Low estim ates of sulfate m a ss sca ttering effici encies were derived assum i ng that sulfates, nitrates, and POM scatter twice as efficiently as the rem a ining ae rosol. The high e s tim ates f o r sulfates were derived as sum i ng that sulfates alo n e scatter twice as efficiently as all other fine

72aerosols. Low estim ates of POM mass scatterin g efficiency were deriv e d assum i ng that POM and nonsulfate species scatter half as effici ently as sulfates. High POM m a ss scattering efficiencies were derived assum i ng that POM is th ree tim es as efficient, and sulfate is twice as efficient, as the rem a ining aerosol in the fine mode. The range of these values is reported in Table 6, along with a summ ary of efficiencies for all the m e thods. Values for POM mas s scattering ef ficiencies are norm a lized to an R oc multiplier of 1.8. The valu es reported in Tab l e 6 for the apportionm ent m e thod are from studies that occurred around urban and rural U.S. locations. T h e average specific m a ss scattering efficiency for the fine m o de was 2.6 ± 0.8 m 2 g -1 , with higher values in the ru ral and urban eastern United States (4.5 ± 0.8 and 3.5 ± 0.4 m 2 g -1 , respectively ) . The lowest values were com puted for the rural and urban western United States, especially San Jose CA (1.83 m 2 g -1 ). The apportionm ent m e thod fine m ode specific m a ss scattering efficiency was the lowest of all the m e thods; however, it was closest to the MLR

m e thod. Alt hough these values are reported as dry, it is possible that the RH environm ent where the m easurem ents were m a de has an effect on th e values derived, perh aps through associated water on th e f ilter o r ae r o sol proce s s i ng ef f ects.

73Table 6. Summar y of m a ss sc atteri ng efficiencies repor ted in Tabl es 2 thr o u g h 5 (App endix 2). Th e “A pp orti onm e nt ” col u mn r e fers t o res ults from Whi t e (1991). The “I MP ROVE” c o lumn lists values used in the current I M P R OVE for m ulati o n. Entries correspond to the fine mode unless otherwise stated in the row header . Sulfate efficiencies c o rrespond to dry amm o nium sulfate, and POM e fficiencies have been norm aliz ed to an R oc va lue of 1 . 8 . Summ a ry o f Ma ss Sc at teri ng E fficiencie s fr om All Me tho d s * Species/

Mo de Theoretic al (m 2 g -1 ) MLR (m 2 g -1 ) Parti a l (m 2 g -1 ) App o rti o nme n t ** (m 2 g -1 ) IMP R O V E
Fi ne 4. 3 ± 0. 7 ( 26 ) 3. 1 ± 1. 5 ( 17 ) 2. 6 ± 0. 8 ( 30 ) C o arse 1. 6 ± 1. 0 ( 21 ) 0. 7 ± 0. 6 ( 13 ) 0. 6
Tot a l 2. 2 ± 1. 0 ( 9 ) Sul f at e 2. 5 ± 1. 1 ( 16 ) 3. 2 ± 1. 2 ( 24 ) 2. 7 ± 0. 4 ( 6

) 3. 0 ± 0. 9 – 3. 9 ± 0. 9 ( 30 ) 3. 0
Nitrate 4 ± 2 ( 16 ) 3. 8 ± 1. 5 ( 6

) 3

. 0
POM 5. 5 ± 1. 6 ( 20 ) 2. 3 ± 1. 0 ( 23 ) 3. 0 ± 1. 4 ( 6

) 1. 5 ± 0. 3 – 3. 2 ± 0. 9 ( 30 ) 4. 0

Fi ne Dust 3. 4 ± 0. 5 ( 19 ) 3 ± 2 ( 19 ) 2. 8 ± 1. 0 ( 4 ) C o arse D u st 0. 7 ± 0. 2 ( 21 ) 0. 40 ± 0

. 0 8 ( 2 ) 1. 0
Tot a l D u st 1. 2 ± 0. 3 ( 9 ) 0. 7 ±0 .2 ( 3 ) Fine Sea Salt 5. 3 ± 0. 8 ( 22 ) 4. 0 ± 1. 6 ( 3 ) Coarse Sea Salt 1. 2 ± 0. 3 ( 20 ) 1. 6 ± 1. 2 ( 3 ) To tal Sea Salt 2. 3 ± 0. 9 ( 9 ) 2. 2 ± 0 ( 1 )

* Num b er o f o b ser v at i o ns i n pare nt hese s ** Ap po rt i onm ent val u es fr o m Tabl e H-1 i n A ppe n d i x H i n Whi t e (1 9 9 1 ) an d refe rences t h erei n. Dry a m m o nium sulfate m a ss scattering effici encies derived from the apportionm e nt

m e thod ranged from 3.0 ± 0.9 to 3.9 ± 0.9 m 2 g -1 for the low and high apportionm ent strategies, respectively. These estim ates are sim ilar to the values derived from th e other m e thods but are still larger than what is derived from th e theoretical method. Th e POM m a ss scattering efficiencies are lower than other estim ates reported in Table 6, although the MLR m e thod estim ates fall within the range of low and high values from the apportionm ent schem e s. It is inte resting that deriv e d sulf ate m a ss scatte ring e f f i ciencies a r e f a irly ins e nsitive to the low and high apportionm e nt schem e , while the POM effici encies are approxim a tely double, based on the

74apportionm e n t schem e , probably due to uncerta inties associated with organic carbon

m easure m ents. The spatial variability in both su lfate and P O M m a ss scattering efficien cies are sim ilar to th e fine m ode specific efficiency. The highest values are derive d in the eas tern Unite d States (both rural and urban) and th e lowest values in the urban W e st. 5.3.6. Mass Absorption Efficiencies Reported estim a tes of mass scattering and abso rption efficiencies of LAC, as well as for other species, are reported in Table 7 (see Appendix 2). E fficiencies listed in this table h a ve been derived using all the m e thods described above , which is noted in the first colum n of the table. Typically, m a ss absorption efficiencies are com puted by the m easurem ent m e thod, by dividing a ligh t abs o rption coe f f i cient m e asured by transm itta nce (m easured with a n aethalom e ter or particle soot absorption photom e t er) by the m a ss of LAC from therm a l analyses. Light absorption coefficients m eas ured with a phot oacoustic technique also are used to derive

m a ss absorption efficiencies (e.g., Arnott et al., 2003) . The theoretical method can be used if the size distribution of LAC is m easured, or by appl ying a complex refractive index to num b er or volum e size distribu tion s in th e Mie calcu lation. In Table 7 the values reported for a wavelength
other than 550 nm have been co rrected to 550 nm assum i ng a λ -1 relationship (Bohren and
Huffm an, 1983). It is w e ll known th at large uncertainties surround the values of m a ss absorption efficiencies by LAC, as is evidenced by the rang e of values reported in the table. Much of the uncertainty stem s from the fact that estim ates of LAC mass concentrations are m e thod-dependent (as described in section 2.3), as are light absorp tion efficiencies, on the wavelength at which the

m easure m ents are perform e d, due to the spectral dependence of light absorption. Uncertainties also ar ise d u e to the w i de range in optica l pro p erties (i.e., com p lex refractive ind e x) of LAC applied in theoretical m e thods.

75Reconstructed extinction equations typically treat LAC as externally m i xed (see equations 4 and 5), as well as assum e that it is the only com ponent of the aerosol that is absorbing so lar radiation in the v i sib l e waveleng ths. This formulation is based on the assum p tion that LAC refers only to “soot” particles; however, ther e is s ubstantial e v idence th at som e of the carbonaceous aerosol, especially biom ass s m ok e, being characterized as LAC by therm a l

m e thods is not soot and in fact is probably re fractory organic carbon. Others have reported that light-absorbing carbon and a signi ficant fraction of organic carbon from biom ass sm oke have sim ilar vola tility and co mbustion te mperature s , causing th e split b e twee n LAC and OC to be poorly defined (and method-dependent) and lead ing to an overestim ation of LAC and an underestim ation of OC for biom ass sm oke (e.g., Novakov a nd Corrigan, 1995; Gelencsér et al., 2000; Mayol-Bracero et al., 2002; F o rm enti et al., 2003; Guyon et al., 2003). A previous study by Malm e t al. (1994a) in the northwestern United States s howed that light absorption coefficients (as m easured independently) correlated well with higher tem p erature fractions of OC as well as LAC. Analyses of single particle d a ta from Yosem ite National Park (Hand et al., 2005) showed that both the m easured LAC and OC from TOR analysis corresponded to a type of nongraphitic refractory carbonaceous particle called tar balls, wh ich are efficient at both scattering and absorbing light. Ca ution should be taken in alwa ys interpreting data from TOR analyses only as externally m i xed OC and LAC particles, because TOR an alyses are based on the refracto r y properties of carbon particles and not necessarily on their light-abso r bin g characteristics. Theoretical calculations perfor m e d by Fuller et al. (1999) su ggest a reasonable LAC m a s s absorption efficiency of 6.5 m 2 g -1 ; however, th e average v a lue of the empirical values lis ted in Table 7 is 13 ± 6 m 2 g -1 . The IMPROVE equation applies a value of 10 m 2 g -1 . The scattering due

76to LAC is not considered in the IMPROVE equa tion. Estimates reported in Table 7 suggest an average fine m ode LAC m a ss scat tering efficiency of 3.6 ± 1.3 m 2 g -1 . Clearly, m o re work is needed to understand the absorption char acteristics of carbona ceous aerosols. The summ ar y of the survey results for all m e thods, including values currently used in the IMPROVE for m ulation, is report ed in Table 6. The results suggest that POM m a ss scattering efficiencies are higher than what is applie d in the IMPROVE recons truction equation, even though the current IMPROVE for m ul ation assum e s an R oc m u ltip lier of 1.4. However, in general, the IMPROVE efficiencies fall with in the range of the va riab ility s een in the su rvey results. Fine soil in the I M PROVE form ulation is assum e d to correspond to the tail of the coarse dust size distribution; therefore the m a ss sc attering effici ency as so ciated with dust in a reconstructed
PM 2. 5 b ext calculation corresponds to a coarse dust m a ss s cattering efficiency. If the fine dust concentration actually correspond s to a size distribution that peaks in the fine m ode, the corresponding m a ss scattering efficiency would actually be quite higher (~ 3 m 2 g -1 ). Size distribution m easure m ents at IMPR OVE sites sug g est th is is n o t typically the case ( e .g. , Hand et al., 2002; Lee et al., 2004a, 2004b). Lowenthal and Kum a r ( 2004) suggest that the ma ss scattering efficiencies applied in the IMPROVE for m ulation should be reevaluate d based on a com p a r ison of measured and reconstructed scattering that im p lies that sc atter i ng is overes tim ated 66% of the time on averag e at 20 IMPROVE sites. Dry ammonium sulfate m a ss scattering efficiencies from the survey are

som e what lower and ammonium nitrate efficien cies are so m e what higher than the IMPROVE values, bu t the IMPROVE m a ss scattering efficienci es f a ll within the variab ility s een in th e survey results. Coarse m a ss (CM) efficiency is assum e d to be 0.6 m 2 g -1 , and the absorption efficiency for light-absorbing carbon (LAC) is 10 m 2 g -1 , both falling within the range of

77variab ility r e ported in th e survey. In genera l th e values of d r y m a ss scat tering efficiency applied in the IMP R OVE equation are reasonable, given the range of ground-based values reported in the literature since 1990.
5.4. Estima tes of Dry Mass Scatte ring Ef fic i encie s fr om IMPROVE Data The for m of the IMPROVE equation for r econstructing particle extinction is
b ex t = (3

. 0 )f

(R H ) {

[

(N

H

4 ) 2 SO 4 ] + [ N

H

4 NO 3 ]

} + ( 4 .0) [ POM ] + 1. 0[ Soil ] + ( 0 .6) [ CM ] + ( 10.0) [LAC] (16) where b ext is the extin ction coefficient (Mm -1 ) and enclosed in the brack e ts is th e aerosol species

m a ss concentration (μg m -3 ). The p a renth e tically enclos ed num e rals in front of POM, soil, and

coarse m a ss (CM) are the optim al dry m a ss scatte ring efficiencies as reviewed by White (1990) and Malm et al. (1994b). A nom inal m a ss scattering efficien cy value of 3.0 m 2 g -1 is applied for dry amm oni um sulfate and dry am monium nitrate. The ratio of wet and dry scattering as a function of RH is the relative hum id ity scattering enhancem ent factor f (R H)

. In the IMP R OVE m o nitoring program , nephelo m e ters collocated with particle m a ss

sam p lers have been operated at 22 sites, in so m e cases f o r m o re than 10 years. Therefore th e valid ity of the assum p tions assoc i ated with equ a tion 16 can be explored and possibly refined by

com p aring m easured and recons tructed scattering. Four m e thods will be used as part of th is strategy to estim ate m a ss scattering efficiencies

. W e describ e each m e thod below, followed by a

com p arison of results from each method for one site (Acadia National Park) and later for all sites. In ad dition to th e uncerta inties descr i be d in previo us sections, the results f r om these

m e thods are subject to uncertainties in the b sp values m easured by Optec NGN nephelom eters at a wavelength of 550 nm

. Method 1 uses a sim p le linear regression tech nique that assumes the relationship betw een scattering and species m a ss con centrations can be represented by equation 17. P O M is assume d to be 1.8·OC, sea salt is estim ated as 1.6·Cl - , and soil and CM are grouped together.

78b sp = a o + a 1 f(R H ) [

(N H

4 ) 2 SO 4 ] + a 2 f(RH)[NH 4 NO 3 ] + a 3 [P O M

] + a 4 [so il + C M

] + a 5 [ sea salt ] (17) The regress i on coefficients are in terpreted as the m a ss scattering efficiencies an d the f (RH) curves are those associated with ammonium sulfate assum i ng a m a ss m e an diam eter of D g = 0.4
μm and geom etric standard deviatio n of 2, and an ammonium sulfate D/D o curve estim a ted using the AIM “n o solids” m o del (assum e s equilibr ium below the crystallization point). The f (RH) was calculated on one-hour intervals and averaged to 24 hours to be commensurate with the one-day

sam p ling duration of the aerosol samples. Method 2 assum e s an aerosol m odel of a fi ne m ode internal m i xture of inorganic ammonium salts (sulfate and nitr ate ) and POM that is exte rn ally m i xed f r om soil, coarse m a ss, and sea salt. The m easured fi ne m o de m i xture scattering ( b mix ) is approxim a ted by b mix = b open – b CM – b soil – b SS (18) where b open is m easured with the P M 10 open air nephelom e ter, and b CM , b soil , and b SS (sca tte rin g due to sea salt) are estim ated u s ing co arse m a ss, fine soil, and sea salt m a ss (1.6 ·Cl - ),
respec tive l y
. Sea salt sc a tte ring is es tim a ted by multip ly ing th e sea s a lt m a ss by a m a ss scatter i ng efficiency of 1.37 m 2 g -1 and the f (R H) value defined above. If the assumptions are met that allow scattering as sociated with an internal and exte rnal m i xture to be approxim a tely equal, then

α

mix M mix = [(NH 4 ) 2 SO 4 + NH 4 NO 3 ] α inorg + 1.27[POM ] α inorg (19)
where the s p ecific m a ss scattering efficiency α mix of the m i xed aerosol m a ss ( M mix = (NH 4 ) 2 SO 4 + NH 4 NO 3 + POM) is p r orated to its chem ical co ns titu ents based on their re lative dens ities (1.27 = 1.78/1.4). The specific m a ss scatte ring efficiency of a m m o nium sulfate and ammonium nitrate
is α inorg , and α POM corresponds to the m a ss scattering efficiency of POM

. Im plicit assum p tions in equation 19 are that the refractiv e i ndi ces of al l t h e speci es ar e si m ilar, the m i xing ratios of the

79species are independent of the si ze distribution of the m i xed aeros ols, and the organic density is known. Therefore the estim a ted scattering of the m i xture ( b mix_est ) is written as b mix_est = (3. 0 )f

(RH ) [(N H

4 ) 2 SO 4 + NH 4 NO 3 ] + 3.81 [POM ] (20) where 3 m 2 g -1 is the nom i nal m a ss scatter i ng ef f i ci ency assigned to ammonium sulfate and ammonium nitrate, and 3.81 m 2 g -1 is the den s ity-weighted m a ss scattering efficien cy of POM (3.81 = 1.27·3). A regression is perform e d for b mi x and b mix_est with a reg r ession coefficient of a 1 . The inorgan i c and org a n i c specific ef fi ciencies can therefore b e written as α inorg = a 1 ·3.0 and α org

= a 1 ·3.81 , respectively. Both m e thods 1 and 2 assum e that the discrepancy between m easured and estim ated scattering can be accounted for by a single m u ltiplica tive co nstant, eith er for each sp ecies o r for the m i xed aerosol. These approaches do not acc ount for the possibility that m a ss scattering efficiencies vary as a function of m a ss conc e n tration (due to its functional dependence on particle size, as described in the section 5.1). Th erefore m e thod 3 is used to investigate how m a ss scattering ef ficiencies m a y vary with m a ss c oncentrations. A scatteri ng correction factor ( SCF ) is defined as the ratio of m easur ed scattering of the m i xture ( b mix ) from equation 18 to the estim a ted scattering for the m i xture ( b mix_est ).

] [ 81

. 3 ] ) )[( ( 0

. 3 3 4 4 2 4

_ POM NO NH SO NH RH f b b b b b b SCF SS soil CM open est mix mix + + −

− − = = (21)

The SCF should equal 1 for all m a ss values if the assum p tions used in com puting b mix and b mix_est are app r opriate and if th ere is no functional dependence between m a ss scattering ef ficiency and
M mix . The functional relationship of SCF with the m i xtur e m a ss ( M mix ) was explored using equation 22
SCF = a o + a 1 [M mix ] (22)

80where a o an d a 1 are the regres sion coefficients d e term in ed using a Theil regr ession analysis, and
SCF is the scattering correction fact or com puted from equation 21. In this ca se, a linea r relationship is hypothesized; however, any func tional relationship coul d be assum e d. A ne w estim ate of b' mix can be calcu lated u s ing b'

mix_est = SCF'[3f(RH)[(NH 4 ) 2 SO 4 + N H

4 NO 3 ] + 3.81[POM ]

] (23) where SCF ′ is the estim a ted scaling factor derived fr om equation 22. Ne w inorganic and organic specific m a ss scatterin g efficiencies are then calculated as α ' inorg = 3.0·SCF' and α ' org = 3.81·SCF'

. Methods 1–3 rely on statistical regressions be tw een m easured scattering coefficients and observed aerosol m a ss concentrations. For m o st si tes, the m a ss scattering efficienc i es in creas e

as am bient aerosol m a ss concen trations increas e , presum ably because of heterogeneous aerosol processes th at are related to the agin g of the aero s ol. The increase in m a ss scattering efficiency is prim arily due to the aerosol size distribution growi ng into a size range that is m o re efficient at scattering light as m a ss concentrations increase . Method 4 takes into account changes in m a ss scattering efficiency as a function of m a ss due to shifts in particle size through a sim p le physical model of a linear combination of bim odal fi ne m ode ae rosol m a ss size distributions. One distr i bution is asso cia t ed with th e s m all size mode, lower m a ss concentr ations, and lower m a ss scattering efficiencies, while the second size dist ribution corresponds to a larger size mode often observed under higher m a ss con centrations and higher mass scat terin g efficiencies. As was discussed in section 3.7, bim odal si ze distributions in the fine m ode reflect different atm o spheri c processes. However, th ese pro ce sses include not only changes in pa rticle size, but also chang e s in com position as the particles age and undergo processing. The im plications for the om ission of

81com positional chang e s in m e thod 4 will be d i sc ussed later for results correspon ding to the Phoenix site. The review of aerosol s i ze distr i bution data rep o rted in the peer- r evie wed lite ratu re in section 3.7 indicates that low aerosol m a ss concentrations are t ypically associated with m a ss size distributions with m a ss m ean diam e t ers ( D

g ) around 0.2 μm and with la rger geom etric standard deviations ( σ g ), while higher m a ss loadings correspond to size distributions with D g

near 0.5 μm and sm aller values of σ g . Therefore th e two m a ss size dist ributions were assum e d to be lognorm a ls with a D g

of 0.2 μm and σ g

of 2.2, and D g

of 0.5 μm and σ g

of 1.2 for the sm all and large size m odes, respectively. Thes e size d i stribu tions were applied for all fine mode species (e.g., Hering et al., 1997) and used to com pute dry m a ss scattering efficiencies. Hum i dification factors were com puted for each size dis t ributi on and species also. The am bient scattering coefficient for a linear com b ination of the bim o dal size distributi on is computed using

) ( ) ( ) ( ) ( ) ( ) (
, s l l j l j l s l j l s j s j sp M M M M RH f M M M M M RH f M b

− − +

− − = α

α (24)

where α s , α l , M s , M l , f s (RH), an d f l (RH) are the dry m a ss scattering efficiencies, m a ss concentrations, and hum i difica tion factors as sociated with the sm all and large m a ss size distributions, respectively. The spec ies m a ss concentration is given by M j . The m a ss scattering efficiencies associated with th e sm all and larg e m a ss size dis t ribu tion s for each species are presented in Table 8. Unless otherwise stated , M s = 0.0 μg m -3 and M l = 20.0 μg m -3 f o r all species ; wh en the sp ecies m a ss c oncentration s exceeded 20 μg m -3 , the dry m a ss scattering efficiency was set equ a l to the large values show n in Table 8.

82Table 8. Val u es use d for the dr y ma ss s c attering effic i encies for the la r g e and sm all mass siz e distribu tions for eac h speci es. (m 2 g -1 ) Amm o nium Sulfa te Amm o nium Nitr ate POM

α

s (sm a ll) 2. 2 2

. 4 2. 8
α

l (larg e ) 4. 8 5

. 1 6. 1

To dem onst r ate the differences in these four methods and their e ffects on reconstructed scattering, data from Acadia National Park (ACAD) wi ll be presented for each m e thod. Reconstructed total scattering ( b sp_t ot ) was com put ed using
b sp _to t = (3

. 0 )f

( R H ) [

( N

H

4 ) 2 SO 4 + NH 4 NO 3 ] + 3.8 1 [ P O M

] + ( 1 .0) [ Soil ] + ( 0 .3)[ CM ] + ( 1 .0)[ Sea sa lt ] (25) We applied ammonium sulfate and ammonium nitrate m a ss scat tering efficiencies o f 3.0 m 2 g -1 , a POM m a ss scattering efficiency o f 3.81 m 2 g -1 (a ssum i ng a POM m u ltiplier of 1.8 ) , and a CM specific efficiency of 0.3 m 2 g -1 to account for coarse particle truncation issues in the nephelom e ter. A statistical summ ary of the m a ss concentrations, RH, average num ber of hours in each 24-hou r period of useable nep h elom eter data, average f (RH) using am bient RH and RH inside the nephelom e ter cham ber, and new and presently used f (RH) curves for ACAD are provided in Table 9. A summary of measured and reconstruc ted total am bient scatter i ng, absorption, and contribu tions to scattering from each species is f ound in Table 10. Also listed in Table 10 is estim ated scattering due to absorbed water on th e a mmoniated salts. Reconstructed total am bient scattering associated w ith dry m a ss is overestim ated by about 15% on average, and scattering due to absorbed water is about ha lf of the scattering due to inorganic m a ss,

em phasizing the im portance of selecting an appropriate f (RH) curve (see Appendix 3 for sim ilar
t a bl es for al l si tes) . The fi nal row of Table 10 shows the bias in the calcu lation of reconstructed b sp .

83T a bl e 9. A st ati s ti cal sum m ar y o f mas s concen tr ati o n s (μg m -3 ) at Aca d ia Na t i onal Pa rk. CM and FM re fer to gravimetric c oar se m a ss and fine (PM 2. 5 ) m a ss, respectively. AS and AN refer to am monium sulfate and amm o nium ni trate, respec t ively. PO M is par t iculate or ganic m a tter using an R oc f a ct or of 1. 8. Ma ss u n i t s ar e ( μ g m -3 ). RH refers to am bient relati v e humidity. The num ber of nephelelome ter data points in a 24-hr aver a ge i s gi v e n b y N( b sp ) . The values of the re vised f (R H) cur v es for the am bient RH ( f

(R H) am b, n e w ) and t h e nephelometer chamber RH ( f

(RH) cha m b,ne w ) are also listed. Similar values are repor ted for the current f (R H) curves ( f

(R H) a m b,old and f (RH) cha m b,old ). Vari a b l e M e a n S t d De v M i n i m u m M a x i m u m Valid CM ( μ g m -3 ) 3. 7 7 3

. 8 9 -0 .4 5 76 .1 9 10 9 3 FM ( μ g m -3 ) 6. 1 5 5

. 1 8 0. 4 6 45 .5 8 11 2 0 AS ( μ g m -3 ) 2. 9 6 3

. 1 2 0. 1 8 28 .3 7 11 3 8 AN ( μ g m -3 ) 0. 3 6 0

. 3 9 0. 0 1 3. 3 0 11 2 5 POM ( μ g m -3 ) 1. 8 7 1

. 7 2 0. 0 5 28 .4 3 11 3 2 LAC ( μ g m -3 ) 0. 2 4 0

. 1 8 -0 .0 1 1. 3 3 11 3 2 So il ( μ g m -3 ) 0. 2 4 0

. 2 7 0. 0 0 4. 3 4 11 3 9 Sea Salt ( μ g m -3 ) 0. 0 8 0

. 3 7 0. 0 0 5. 4 4 11 5 8 RH (% ) 68 .7 0 1 2 .3 1 30 .4 1 89 .7 8 10 5 2 b sp (M m -1 ) 21 .7 9 2 5 .4 6 1. 9 6 24 0. 9 2 40 6

N (b sp ) 16 .2 9 8

. 2 1 1. 0 0 24 .0 0 11 5 8 f

(RH) chamb,new 2. 2 8 0

. 5 1 1. 3 3 4. 2 6 10 3 8 f

(RH) chamb,old 2. 0 8 0

. 5 4 1. 0 1 3. 6 5 10 3 8 f

(RH) chamb,smal l 2

. 2 9 0. 5 6 1. 0 7 4. 3 5 10 3 8 f

(RH) chamb,large 1. 9 4 0

. 3 8 1. 0 6 3. 2 2 10 3 8 f

(RH) chamb,NaCl 2. 8 9 0

. 6 9 1. 0 0 4. 7 8 10 3 8

84Table 10. A s u mmar y of b sp (M m -1 ) for Acadia Nati onal P a rk. Val u es c o rrespond to me as u red total ambient scattering ( b sp ), rec ons t ruc t ed total am bient sc atteri ng ( b sp_recon ), meas u red s c attering as s o ciated with i n org a ni cs an d org a ni cs ( b mi x ), esti m a t e d scat teri n g associ ate d w i th i n org a ni cs and org a n i c s ( b m i x_est ), scattering due to amm o ni um sulfate ( b sp ( AS ) ), amm o nium ni trate ( b sp ( AN ) ), particulate or ganic materi al ( b sp ( PO M ) ), s o il and coarse mass ( b sp ( so il+CM ) ), sea salt ( b sp ( SS ) ), an d w a ter ( b sp ( H 2 0 ) ). Ligh t abs o rp tion ( b ap ) was compute d assuming a mass ab s o rpti on efficiency of 10 m 2 g -1 . New f (RH) curves were used to estim a te wet scatterin g . PO M w a s c o mpute d assu ming an R oc f a ctor o f 1. 8 an d ma ss sc at ter i ng e ffi ci enc y of 3 . 8 m 2 g -1

. Vari a b l e M e a n S t d De v M i n i m u m M a x i m u m V a l i d b sp 22 .2 2 2 6 .0 6 2. 3 8 24 0. 9 2 37 7 b sp_recon 25 .1 6 2 3 .9 9 3. 7 8 21 9. 3 5 37 7

b mix 20 .6 9 2 5 .7 5 0. 8 2 24 0. 1 6 37 7 b mix_est 23 .6 4 2 3 .5 6 3. 3 4 21 8. 5 9 37 7 b sp ( AS ) 14 .1 4 1 8 .2 5 1. 2 8 18 4. 8 5 37 7 b sp ( AN ) 2. 4 5 3

. 1 5 0. 1 8 27 .7 6 37 7 b sp ( POM ) 7. 0 5 5

. 9 4 0. 8 3 67 .2 4 37 7 b sp ( Soil ) 0. 2 8 0

. 2 2 0. 0 1 2. 2 7 37 7 b sp ( CM ) 2. 2 4 3

. 0 0 -0 .2 1 45 .7 1 37 7 b sp ( SS

) 0. 1 3 0

. 8 0 0. 0 0 12 .2 7 37 7 b sp ( so il+CM ) 2. 5 2 3

. 0 6 -0 .0 7 46 .2 0 37 7 b ap 2. 4 4 1

. 7 9 0. 4 2 13 .2 5 37 7 b sp ( H 2 O ) 8. 4 8 1 1 .2 6 0. 7 5 11 2. 6 3 37 7 

## ( )

mix est

mix mix b b b

_ − -0 .1 4

The fractional contribution of each species to total scattering using equation 25 is presented in Table 11. The results from m e thod 1 are rep o rted in Table 12. A com p arison of

m easured total am bient scattering and recons tructed total scattering using equation 25 and

m e thod 1 is shown in Figure 7 (sim ilar tables corresponding to m e thod 1 for all sites can be found in Appendix 3 and figures can be found in Appendix 4). N o tice that reconstructed scattering from equation 25 is underestim ated for low values of b sp and overestim ated at high values of b sp , suggesting that m a ss scattering effici encies vary with m a ss concentration. Reconstructed b sp derived from m e thod 1 rem oves the biases observed at low and high b sp , bu t at the expense of having what appear s to be un rea l istic m a ss scatte ri ng efficiencies. Th e soil + CM specific scattering efficiency is negative, which is unphysical, and the sea salt efficiency is 1.23

m 2 g -1 (see Table 12), sim ilar to values reported by Quinn et al. (2001, 2002b, 2004) for higher RH values. The average ammonium sulfate a nd POM m a ss scattering efficiencies of 3.29 m 2 g -1

85and 3.43 m 2 g -1 , respectively, are physically reasonabl e. However, sulfate m a ss scattering efficiencies m a y be overestim ated an d POM m a ss scattering efficiencies m a y be underestim a ted due to the relative uncertainties in each of those m easurem ents.
Table 11. Fr action al contri bution to to t a l ambi en t sc at teri ng a t Ac a d i a N a ti on al Park usi n g eq uati on 2 5 . AS corresponds to amm o nium sulfate an d AN c o rresponds to am monium nitr ate. Particul ate organic matter (PO M ) fr acti o n w a s c o m put ed as sumin g a n R oc f a ct or of 1. 8. T h e c o ar se mo de frac ti on i s gi ven by CM . S p e c i e s F r a c t i o n of

b sp AS 0. 64 AN 0. 11 POM 0. 32 So il 0. 01 CM 0. 10 Sea salt 0. 01

Table 12. The results fr om method 1 for Ac adia Nati on al P a rk (see equation 17). The regres sion coe fficients ( a i ) are liste d, al ong with the standard error . De rive d m a ss s c attering efficien cies are also liste d for amm o nium s u lfate (AS), ammoniu m ni trate (AN), particulate organic ma tt er (P OM = 1. 8· OC ), coarse mass co mbined with so il (so il+CM). a n d sea s a lt. The n u m b er of valid c a ses w a s 267 and the re wer e 370 missin g data poin ts. T h e r 2 c o efficient was 0.95. Aca d i a N a ti on al P a rk Vari a b l e C o e f f i c i e n t ( a i ) Stand a rd Error Derived Mass Scattering Efficiency (m 2 g -1 ) A S 1

. 1 0 0. 0 3 3. 2 9 A N 0

. 6 2 0. 1 3 1. 8 7 POM 0

. 9 0 0. 0 7 3. 4 3 Soi l + C M

- 0 .2 3 0. 1 3 -0 .1 4 Sea sal t 1. 23 0. 50 1. 68

86Figure 7. Me thod 1 me asured total ambient scattering and reconstructed total s c at tering using equati on 25 for Ac adi a Na ti on al P a rk.

Method 1



### IMPR O VE and Method 1 Scatt ering (Mm -1 

### )Measured Scattering (Mm-1) 

### AC A D

Estim ates of specific scattering efficiencies for amm oniated salts (s ulf a tes and nitrates) and POM mass scattering efficiency derived from m e thod 2 are report ed in the last two rows of Table 13. The derived sulfate and ni trate sp ecific efficiency was 2.88 m 2 g -1 and the POM m a ss scattering efficiency was 3.65 m 2 g -1 . Com p arisons of m e asured m i xed b mix to re construc te d

m i xed b mix,e s t using method 2 and equation 20 are shown in Figure 8 (sim ilar tables corresponding to all sites for m e thod 2 are found in Appendix 3 and figures are found in Appendix 4). The sing le m u ltiplica tion f acto r derived f r o m the regre ssion be tween b mix and b mix_est that was used to correct the inorgan i c an d organic m a ss scattering efficiencies does not

87rem ove the biases observed at low and high scatte ring values. It only serves to m a ke the average

m e thod 2 reconstructed scattering equal that which is m easured. Figure 8. Me thod 2 recons tructe d mixe d scattering ( b m i x,est , Mm -1 ) c o mpared to measure d mixed scattering ( b mi x , Mm -1 ) u s ing eq uation 20 (fine mode c o nt ributi o ns ) for Ac adi a Na tion al P a rk.

Method 2



### IMPR O VE and Method 2 Scatt ering (Mm -1 

### )Measured Scattering (Mm-1) 

### AC A D

Table 13. Re sults for method 2 for estim a ting specific mass sc attering efficiencies for inor ganics ( α inorg ) and org a ni cs ( α org ) fo r A c adia Na t i o n a l Pa rk. S ee te xt for full description. Resul t s f o r M e th od 2 Re gre ssi on (Ac a di a N a tio n al P a rk ) a1 coe fficient 0. 96 Standard e rror in a1 0. 01 α

inorg (m 2 g -1 ) 2. 88 α

or

g (m 2 g -1 ) 3. 65

Statistical summaries of m e thod 3 for Acadia National Park ar e reported in Tables 14–16. The inte rce p t and slop e f r om the Thiel regre ssion of SCF versus m a ss ( M mix ) are presented in

88Table 14. A slope of 0 corresponds to a constant m a ss scattering efficien cy over the entire m a ss range, while the intercept is pr oportional to the over- or underestim ation of the assum e d m a ss scattering efficiencies for su lfates and POM (3 and 3.81 m 2 g -1 , respectively). An intercept of 1 and slope of 0 would im ply that the assum e d values provid ed good agreem ent between m easured and reconstructed m i xed (inorganic and POM) scattering. The co mpar ison of fine m o de inorganic and organic m a ss concentrations and SCF is shown in Figure 9 (sim ilar tables for all sites corresponding to method 3 can be found in Appendix 3 and si m ilar figures can be found in Appendix 4). The Thiel regression line is also shown, dem onstrating a fairly flat slope as reported in Table 14. Mass scat t e ri ng effi cienci es for ammoni ated salts and P O M that are associated with the 15% upper and lower m a s s concentrations are reported in Table 15. Finally, the com p arison of recon s tructed and estim ated m i xed scattering using efficiencies derived from

m e thod 3 is shown in Figure 10. T h e summ ary of derived efficiencies from m e thod 3 and the
SCF factor are reported in Table 16. Accounting for the dependence of mass scatterin g efficiency

on m a ss with m e thod 3 rem oves these biases obse rved at low and high s cattering by increasing the value o f the efficiencies for low m a ss con centration s , and decreasing efficiencies that correspond to high m a ss concentrations (see Fi gure 10). A s shown in Table 16, the average inorganic specific m a ss scattering efficiency using m e thod 3 at A cadia National Park is 2.51 m 2

g -1 (ranging from 2.36 to 3.45 m 2 g -1 )

. The m ean POM m a ss scat tering efficiency was 3.18 m 2 g 1 (ranging from 3.00 to 4.39 m 2 g -1 ).
T a bl e 14 . Resul t s of t h e m e th od 3 T h i e l regressi on o f SCF versus mass ( M mi

x = inorganics + organics ) f o r Aca d i a N a ti on al P a rk. Method 3 Theil Regre ssion re sults (Ac a di a N a tio n al P a rk )

Intercept 0. 78

Slope 0. 01 1 Sig n ifica n ce 0. 04

89Fi gure 9. T h e comp ari s o n o f fi ne m o de m i xed i n or g a ni c and or gani c mass c o ncen tr ati o ns ( M mi

x , μg m -3 ) and the SCF for Acadia National Park. The T h iel reg ressi on line is sho w n.



### Inorganics + Organics ( 

### : g/m 3 

### )SCF 

### AC A D

Table 15. Meth od 3 estim a tes of the overall me an a nd upper and lower spe c ific scatterin g efficiencie s ass o ciated with the 15% u pper and low er mass c o nc en tr ati o ns o f mi xed i n or g a n i c and or ga ni c mass f o r Aca d i a N a ti on al P a rk. Aca d i a N a ti on al P a rk Specific Sc attering Efficiency (m 2 g -1 ) L o w e r M e a n U p p e r Inor ga ni cs ( α i n org ) 2. 3 9 2

. 5 1 2. 7 7 Organics ( α org ) 3. 0 4 3

. 1 8 3. 5 1

90Figure 10. Com p aris ons of me thod 3 recons tructe d mixed sc attering ( b m i x,est , Mm -1 ) to me asured mixe d scattering ( b mi x , Mm -1 ) for A c adia N a tion a l Park .



### IMPR O VE and Method 3 Scatt ering (Mm -1 

### ) Method 3Measured Scattering (Mm-1) 

### AC A D

Table 16. Summar y of the method 3 SC F and s p ecific mas s sc atteri ng e fficiencies for inor ganics ( α inorg ) and org a ni cs ( α org ) fo r A c adia Na t i o n a l Pa rk. Aca d i a N a ti on al P a rk Vari able Mean Std De v Minimum Maximum Valid data

SC F 0. 8 4 0

. 2 8 0. 0 9 3. 0 6 37 7 α

inorg (m 2 g -1 ) 2. 5 1 0

. 1 4 2. 3 6 3. 4 5 11 1 9

α

org (m 2 g -1 ) 3. 1 8 0

. 1 8 3. 0 0 4. 3 9 11 1 9

From the discussion of these m e thods for data f r om Acadia National Par k , it is clear that incorporatin g the dep e nd ence of m a ss scattering efficiencies on m a ss concentrations rem oved the biases ob served between m easured and reconstructed extinction, and improved the com p arison of reconstructed and m e asured scattering. For most sites, a linear relati onship between m a ss and

91SCF appears to be a reasonable assum p tion, except at Great Sm oky National Park (GRSM) where the r e seem s to be a distinc t nonlinea rity. At GRSM the SCF is about 0.5 at lower m a s s concentrations (< 5.0 μg m -3 ) and rapidly approaches one for higher m a ss concentrations. The m a ss scattering efficiencies computed w ith m e thod 4, based on a physical m odel , are quite sim ilar to those derived using m e thod 3, a statistical fitting approach. The m e thod 3 specific m a ss scattering efficiencies associated with low m a ss concen tra tions a r e 2.3 9 m 2 g -1 and
3.04 m 2 g -1 for inorganics and organics , respectively. Mass scatteri ng ef ficiencies derived using

m e thod 4 a r e 2.28, 2.21, and 2.89 m 2 g -1 for low con centr ation s of a m m oni um sulfate, ammonium nitrate, and POM, respectiv ely (s ee Table 17). The difference between the tw o

m e thods is on the order of 5%. The differences in sulfate m a ss scattering efficiencies corresponding to high m a ss conce n trations between m e thod 3 and m e t hod 4 were larger, with a difference o f 10%. POM m a ss scattering efficiencies for h i gh m a ss concentration s POM were very sim ilar for both m e thods. A comparison of measured b sp and reconstructed b sp using m e thod 4 is shown in Figure 11. The good a g reem ent between the two estim ates is dem onst r ated through an OLS regression forced through a zero intercept with a slope of 1.01 ± 0.013 and an R 2 = 0.91.
Table 17. Method 4 es timates of the m e an, and the upper and lower mass sc attering efficiencies (m 2 g -1 ) ass o ciated with the 15% up per and l o wer mass concentrati o ns for Ac adi a N a ti on al Park . Aca d i a N a ti on al P a rk Mass Sc atteri ng Efficiency (m 2 g -1 ) L o w e r M e a n U p p e r Amm o nium S u lfate 2. 2 8 2

. 5 8 3. 2 9 Amm o nium Nitrate 2. 2 1 2

. 2 5 2. 3 4 POM 2. 8 9 3

. 1 0 3. 5 6

92Figure 11. Method 4 estim a tes of rec ons t ructe d sc atte ring c o mpare d to me asure d scattering ( b sp , Mm -1 ) f o r Aca d i a N a ti on al P a rk.

Method 4



### IMPR O VE and Method 4 Scatt ering (Mm -1 

### )Measured Scattering (Mm-1) 

### AC A D

We now summarize and discuss these m e thods for all of the sites where the analyses were perform e d. The m a ss scattering efficienci es derived from m e t hod 1 are summarized in Table 18, along with the standard error associated with each estim ate. Fo r ammonium sulfate th e regression coefficients are a ll statistically significant at 5%, except for Snoqualam i e WA (SNPA), which is near the Cascade m ountain range in the northwestern United States. The values are summ arized for all s ites in Figure 12, where the size of the circle corresponds to the

m a gnitude of the m a ss scattering efficien cy. Th e site in the Colum b ia River Gorge W A (CORI) is influenced by air masses from Portland, is in a high RH environm ent, and has a dry ammonium sulfate m a ss scattering effici ency that is g r eater than 3.0 m 2 g -1 . However, typically

93the highest ammonium s u lfate m a ss scattering efficiencies ar e found in the eastern U n ited S t ates, as well as B i g Bend National Park T X (BIBE) where they are typically g r eater than 3.0 m 2 g -1

. In the south w estern United States, the valu es are near 2.0 m 2 g -1 with the site in Sycam ore Canyon AZ (SYCA) having the lowest value at 1.40 m 2 g -1 . The average dry amm o nium sulfate

m a ss scattering efficiency for the s i tes that ar e s t atistically s i gnifican t at 5% is 2.65 m 2 g -1 . This value is sim ilar to the average va lues reported in the l iterature review of th e theoretical m e thod.
Table 18. Summar y of m a ss scattering e fficiencies (m 2 g -1 ) and s t an dard err ors for all sites using method 1. Mass sc attering e fficiencie s are liste d for amm o nium sul f ate ( A S), amm o ni u m nitr ate (AN), particul ate org a nic ma tte r (PO M = 1 . 8· OC ), s o il a nd coar se m a ss (s oil + C M ), an d sea s a lt. S i t e A S A S Std Err A N A N Std Err P O M P O M Std Err CM + So il CM+So il Std Err Sea Salt Sea Sal t Std Err
ACA D 3. 2 9 0

. 0 8 1. 8 7 0. 4 0 3. 4 3 0. 2 8 -0 .1 4 0. 0 8 1. 6 8 0. 6 8 B I B E 3. 2 0 0. 0 8 1. 3 8 0. 7 6 3. 5 8 0. 2 1 0. 2 9 0

. 0 2 5 6 .0 3 58 .1 7 BOWA 3. 0 1 0

. 4 7 6. 1 4 0. 3 6 3. 4 5 1. 3 7 -0 .5 6 0. 3 3 2. 2 6 5. 9 8 CORI 3. 5 9 0

. 2 4 5. 1 5 0. 2 0 2. 5 4 0. 2 2 0. 0 6 0. 0 5 0. 8 4 0. 5 5 DO SO 3. 4 7 0

. 2 7 3. 9 0 1. 3 8 4. 5 1 1. 0 6 -1 .1 9 0. 4 4 0. 0 0 0. 0 0 GICL 1. 6 6 0

. 1 5 2. 3 8 1. 1 8 5. 7 3 0. 0 8 0. 1 1 0. 0 4 1. 5 5 24 .8 8 HA NC 2. 4 4 0

. 2 1 6. 6 8 0. 7 3 3. 8 1 0. 2 0 0. 2 0 0. 0 4 0. 0 0 83 .5 7 GRSM 3. 6 4 0

. 0 8 4. 5 8 0. 6 9 3. 0 4 0. 3 7 -0 .8 5 0. 1 9 0. 0 0 53 2. 7 4 IKB A 1. 7 6 0

. 2 6 2. 1 3 0. 5 4 3. 2 2 0. 2 7 0. 5 5 0. 0 2 0. 0 0 16 .7 6 JARB 1. 4 8 0. 5 1 3. 3 4 0. 3 9 5. 1 1 0. 2 4 0. 2 5 0

. 0 5 2 1 .7 5 15 .2 6 LOPE 2. 7 7 0

. 2 8 4. 7 7 0. 1 3 3. 3 0 0. 2 3 0. 1 3 0. 0 6 4. 4 8 37 .5 1 MA CA 3. 3 6 0

. 1 5 4. 5 2 0. 2 3 2. 6 6 0. 5 2 -0 .1 9 0. 2 6 0. 0 0 60 1. 1 8 MO RA 3. 2 3 0

. 5 3 4. 9 9 2. 9 0 3. 9 7 0. 4 3 -0 .3 6 0. 2 7 3. 4 5 5. 5 6 OKE F 4. 1 2 0

. 3 0 0. 7 7 2. 3 6 3. 5 0 0. 8 4 -0 .1 7 0. 2 9 0. 0 0 0. 0 0 PHOE 1. 8 5 0

. 1 8 2. 6 8 0. 1 5 2. 5 6 0. 0 9 0. 3 1 0. 0 2 1. 0 1 3. 0 2 SENY 2. 3 5 0

. 1 7 4. 2 3 0. 1 9 4. 4 1 0. 5 6 0. 0 6 0. 3 9 16 1. 4 8 25 4. 8 9 SHE N 3. 4 4 0

. 1 0 2. 6 4 0. 3 5 2. 3 3 0. 5 1 -0 .5 9 0. 2 5 0. 0 0 48 9 5

. 5 1 SNP A 0. 4 0 0

. 7 9 7. 2 3 1. 0 6 4. 5 1 0. 4 8 0. 2 4 0. 1 7 0. 0 0 38 6. 1 2 SYCA 1. 4 0 0

. 3 0 5. 0 6 0. 8 5 4. 5 6 0. 1 6 0. 2 4 0. 0 2 -0 .9 4 12 .0 5 THIS 1. 4 4 0

. 4 8 2. 8 6 1. 0 5 5. 4 1 0. 2 5 -0 .0 2 0. 1 0 0. 5 9 7. 7 4 UPBU 3. 6 2 0

. 0 9 4. 8 6 0. 3 4 1. 4 4 0. 4 3 0. 2 7 0. 1 0 0. 0 0 53 7. 7 6 VI IS 3. 1 5 0

. 2 9 9. 4 7 1. 5 1 -3 .4 6 0. 8 5 0. 8 8 0. 0 5 2. 0 6 0. 2 1 Av g 2. 6 5 3

. 9 1 3. 6 7 -0 .0 6 12 .1 0

94Figure 12. Map of the mean ammonium sulfate m a ss scattering efficiencies (m 2 g -1 ) for the Uni t ed States derived using method 1. The siz e of th e circle reflects the m a gnitude of the ef ficiency, which is printed next to the circle.

The derived m a ss scattering efficien cies for POM are statistically sign ificant at 5 % at all sites excep t at Dolly So ds W V (DOSO). The va lues are su mmarized in Figure 13. A negative value was derived at the Virgin Islands (VIIS) (not shown), which is unphysical. In the East, as with sulf ate s , the im plie d m a ss scat tering efficiencies are near 3.0 m 2 g -1 or greater. In the W e st, the coefficients are higher and variable but all w ithin ranges that would be considered physically reasonable. Those sites typicall y influenced by wild fires tend to have higher P O M m a ss scattering efficiencies, consistent with recent analyses by Malm et al . (2005a) and Poirot and Husar (2004). The average POM m a ss scattering effi ciency f o r statistically significant sites is
3.67 m 2 g -1 and is within range of the values reporte d in Table 6, although closest to the MLR

95average valu e. The ratio of amm onium sulfate to POM m a ss s catteri ng efficien cies on average is 1.38, which is sim ilar to the ra tio of PO M to ammonium sulfate density of 1.21. Figure 13. Map of the me an POM m a ss scattering efficiencies (m 2 g -1 ) for the United States der i ved using method 1. The siz e of the cir c le reflects the magnitude of the e fficienc y , which is printed ne xt to the circle.

Many of the ammonium nitrate mass scattering efficiencies are h i gh er than cou l d be reasonably expected, possibly because fine nitrate m a y be a surrogate for coarse particle n i trate (see section 3.2). Coarse m a ss sp ecific m a ss sca t t e r i ng effi ci enci es t h at ar e st ati s ti cal l y significant vary from a low of 0.06 m 2 g -1 at CORI and Seney MI (SENY) to a high of 0.88 m 2 g 1 at VIIS. S ea salt specific m a ss scattering effici encies are o n ly statis tic ally significant at two locations, A C AD and VI IS. The specific m a ss scattering efficien cies for am moniated salts (sulfa te and nitrate) and
POM m a ss scattering efficiencies derived from m e thod 2 are summ arized for all of the sites in
Table 19. The values of α inorg range from 2.02 t o 5.41 m 2 g -1 , with an average of 2.87 m 2 g -1 . A

96summary of the values is shown in Figure 14. The high value is in the Virg in Islands (not shown) where there is known to be large contributions to aero sol m a ss from s ea salt and dust, so the inorganic salts could be influenced by those c ontributions. The low value occurred at Phoenix AZ (PHOE)

. The low and high values of efficien cies for POM also occu rred at PHOE and VIIS, with 2.56 and 6.87 m 2 g -1 , res p ectiv ely. These estim ates are summarized in Figure 15. Throughout most of the United States, POM m a s s sc attering efficiencies vary between about 3.5 and 4.0 m 2 g -1 , with the Arizona site s having th e lowest va lu es (F igure 1 5 ). POM m a ss sca t tering efficiencies are higher th an those for inorgan i cs; however, th ere is less sp atia l var i ability in POM

m a ss scattering efficiencies com p ared to m e thod 1 because of the internal m i xing assum p tions inheren t in m e thod 2. Because only one m u ltiplicativ e factor is us ed to scale bo th the inorgan i cs and the org a nics, the b i as between measured and reconstructed scattering for low and high m a ss concentratio ns rem a ins.

97Table 19. Summar y of spe c ific mass sc attering efficiencies (m 2 g -1 ) for i n or gani c s ( α inorg ) and organics ( α org ) for all sites usi n g m e th od 2 . Site α inorg (m 2 g -1 ) α org (m 2 g -1 ) ACA D 2. 8 7 3

. 6 5 BIBE 2. 9 1 3

. 6 9 BOWA 3. 7 2 4

. 7 2 CORI 2. 9 7 3

. 7 8 DO SO 3. 0 6 3

. 8 8 GICL 3. 3 5 4

. 2 5 HA NC 2. 8 1 3

. 5 7 GRSM 3. 1 3 3

. 9 7 IKB A 2. 5 8 3

. 2 7 JARB 3. 1 3 3

. 9 7 LOPE 3. 2 1 4

. 0 8 MA CA 3. 1 1 3

. 9 5 MO RA 2. 8 5 3

. 6 2 OKE F 3. 2 9 4

. 1 7 PHOE 2. 0 2 2

. 5 6 SENY 2. 9 8 3

. 7 9 SHE N 2. 8 2 3

. 5 8 SNP A 2. 9 9 3

. 8 0 SYCA 2. 4 4 3

. 1 0 THIS 3. 0 7 3

. 9 0 UPBU 3. 1 4 3

. 9 9 VI IS 5. 4 1 6

. 8 7 Av g 2. 8 7 3

. 6 5

98Figure 14. Map of inor ganic specifi c mass scattering efficiencies ( α inorg , m 2 g -1 ) for the Unite d Sta t es usin g method 2. The siz e of the cir c le reflects the magnitude of the e fficienc y , which is printed ne xt to the circle.

99Fi gure 1 5 . Ma p o f or ga ni c (POM ) m a ss scatte ring efficiencies ( α org

, m 2 g -1 ) for the United States using method 2. The siz e of the cir c le reflects the magnitude of the e fficienc y , which is printed ne xt to the circle.

The results from m e thod 3 us ing the Thiel regression of SCF and M mi

x (intercept, slope, and t-values) from m e thod 3 are li sted in Table 20 for each site . As previously m e ntioned, a slope of 0 corresponds to a constant m a ss scatte ring efficiency over the entire m a ss range, whil e the intercept is proportiona l to the underestim ati on of the assum e d m a ss scattering efficiencies for sulfates and POM (3 and 3.81 m 2 g -1 , respectively). An intercept of 1 and slope of 0 would
im ply that the assum e d values provided good ag reem ent between m easured and reconstructed

m i xed (inorganic and POM) scattering. The averag e and one standard deviation intercept for all 22 sites is 0.76 ± 0.16, while the average slope is 0.02 ± 0.03.

100Table 20. Summar y of the results from method 3 using the Thiel re gression of SC F an d m a ss ( M

mi

x ) for eac h site. The four th c o lumn c o rresponds to the percent c h ange in spec ific mas s sc attering efficiency (either for i n org a ni c or o r ga ni cs) fr om a d o u b l i n g of the mi xed i n o r ga ni c a nd or ga ni c m a ss c o ncentr ati o n ( M

mi

x ). S i t e I n t e r c e p t s l o p e t - v a l u e % c h a n g e ACA D 0. 7 8 0

. 0 1 0. 0 4 2. 6 2 BIBE 0. 6 6 0

. 0 3 0. 0 0 9. 5 4 BOWA 1. 0 1 0

. 0 0 0. 9 6 -0 .2 9 CORI 0. 5 7 0

. 0 4 0. 0 0 12 .1 5 DO SO 0. 7 8 0

. 0 1 0. 1 0 2. 7 5 GICL 0. 6 5 0

. 0 5 0. 0 0 13 .7 3 HA NC 0. 9 5

- 0 .0 1 0. 4 6 -2 .5 2 GRSM 0. 6 4 0

. 0 2 0. 0 0 6. 0 5 IKB A 0. 4 7 0

. 1 0 0. 0 0 28 .9 6 JARB 0. 9 2 0

. 0 1 0. 7 2 3. 0 0 LOPE 0. 6 7 0

. 0 4 0. 0 0 11 .6 2 MA CA 0. 9 8 0

. 0 0 0. 5 5 0. 4 3 MO RA 0. 8 2 0

. 0 1 0. 4 3 2. 6 6 OKE F 0. 6 5 0

. 0 4 0. 0 0 10 .5 5 PHOE 0. 6 3 0

. 0 0 0. 4 9 0. 6 6 SENY 1. 1 3

- 0 .0 1 0. 1 6 -2 .4 8 SHE N 0. 7 2 0

. 0 1 0. 0 0 3. 9 4 SNP A 0. 7 4 0

. 0 3 0. 0 9 8. 5 0 SYCA 0. 7 2 0

. 0 1 0. 3 7 2. 5 4 THIS 0. 6 9 0

. 0 5 0. 0 2 12 .0 5 UPBU 0. 8 0 0

. 0 2 0. 0 0 3. 7 6 VI IS 2. 5 2

- 0 .2 1 0. 0 1 -2 0. 2 2 Av g 0. 7 6 0

. 0 2 0. 2 1 6. 2 0 Std De v 0. 1 6 0

. 0 3 0. 2 9 7. 2 1

The fourth colum n in Table 20 corresponds to the percent change in m a ss scattering efficiency (either for inorganic or organics) resulting from a doub ling of the m i xed inorganic and organic m a ss concentration ( M mix ). T h e resu lts in the final co lum n are sho w n in graph i cal form in Figure 16. Notice that the percen t change in m a ss sca ttering efficiency resulting from a doubling of

m a ss concentr ation is lowest in the eas tern United Sta t es, with on ly a f e w per cent ch ange along the O h io River valley. Great Sm oky Mount ains National Park T N (GRSM) has a 6% change in mass scattering efficiency for a doubling of mass, while OKE F (Okefenokee GA) has an 11% change. Sites in the western United States exhibit th e largest ch ange in m a ss scattering efficiency as a function of m a ss. Sites in th e Northwest and Great Basin region all have percent

101changes between about 10 and 15%, while sites in Arizona vary from a bout a 1% change to as high as 29% at IKBA (Ikes Back bone AZ). The intercept data ar e shown in Figure 18. Sites along the O h io River valley have intercepts betw een 0.9 and 1.0, im plying 3.0 m 2 g -1 and 3.81 m 2

g -1 are reaso n able cho i ces for dry m a ss scattering efficiencies . In th e western United States, th e intercepts range between 0.5 and 0.7, with a low value of 0.47 at IKBA, implying a lower m a ss scattering ef ficiency would be m o re appropriate th e r e. Th is resu lt is c onsisten t with what is observed at other site s in that region. Figure 16. Map of pe rce nt change in speci fic mass scattering efficiency (for either α inorg or α org ) d u e t o a dou b l i n g of m i xture m a ss ( M

mi

x ) using m e thod 3. The siz e of the circl e reflects the magnitude of the change, which is printed ne xt to the circle.

102Figure 17. Map of the i n tercept fr om the Theil regression in me thod 3. The s i z e of the circle reflects the magnitude of the intercept, which is printed ne xt to the circle.

The m ean, upper, and lower specific m a ss sc attering efficienci es for the m i xed ammonium salts and P O M m a ss scattering efficien cies are reported in Table 21. The upper and lower m a ss scattering efficiencies are calcu late d by averaging the m a ss scattering efficiencies associated w ith the upper and lowe r 15% m i xed m a ss concentrations ( M mi

x ). The percent chang e between the upper and lower m a ss scattering effici encies (either inorganics or organics) is reported in the last co lu mn. The highest averag e inorganic s p ecific m a ss scattering efficiencies are found in the southeast United St ates, where they are near 3 m 2 g -1 or less (see Figure 18 for spatial distribution). The inorgani c s p ecific scattering efficiencies decrease towards the western United States. The lowest inorg a nic specifi c mass scatterin g efficiencies (near 2.0 m 2 g -1 ) are found in Arizona. (IKBA, PHOE, a nd SYCA). Th e average inorganic sp ecific m a ss scattering efficiency is 2.35 ± 0.34 m 2 g -1

.

103Table 21. The mean, upper, an d lower s p ecific scatteri ng e fficiencies for inorganic s ( α inorg ) and organics ( α org ) compu t ed with method 3. The upper an d lower es tim a tes ar e calcu l ated by aver agin g the spe c ific scatterin g efficiencies as sociated with the upper an d lower 15 % mixed mas s concentr ations ( M

mi

x ). The percent change between the upper and lowe r mass sc atter i ng e fficiencie s (final c o lum n ) c o rresponds to both ( α inor g ) and ( α org ).

α

inorg (m 2 g -1 ) α inorg (m 2 g -1 ) α inorg (m 2 g -1 ) α org (m 2 g -1 ) α org (m 2 g -1 ) α org (m 2 g -1 ) Percent Ch an ge α

Inorg & α Org S i t e L o w e r M e a n U p p e r L o w e r M e a n U p p e r AC A D 2

. 3 9 2. 5 1 2. 7 7 3. 0 4 3. 1 8 3. 5 1 15 .6 5 B I B E 2

. 1 3 2. 4 8 3. 0 6 2. 7 1 3. 1 5 3. 8 9 43 .4 7 B O W A 2

. 9 8 3. 0 1 3. 0 2 3. 7 8 3. 8 2 3. 8 4 1. 4 0 C O R I 1

. 8 9 2. 3 3 3. 1 6 2. 4 0 2. 9 6 4. 0 1 66 .8 4 DO S O 2

. 4 6 2. 7 1 3. 1 7 3. 1 2 3. 4 4 4. 0 2 29 .0 2 GIC L 2

. 1 0 2. 5 1 3. 6 0 2. 6 7 3. 1 9 4. 5 7 71 .5 1 HA NC 2

. 6 8 2. 7 7 2. 8 3 3. 4 0 3. 5 2 3. 5 9 5. 7 5 GR SM 2

. 1 3 2. 5 8 3. 3 9 2. 7 0 3. 2 7 4. 3 0 59 .2 7 IKB A 1

. 7 5 2. 2 5 2. 9 0 2. 2 3 2. 8 5 3. 6 8 65 .3 9 JAR B 2

. 7 8 2. 8 4 2. 9 7 3. 5 3 3. 6 1 3. 7 7 6. 7 5 L O P E 2

. 2 0 2. 5 1 3. 0 8 2. 7 9 3. 1 9 3. 9 1 40 .0 8 M A C A 2

. 9 8 3. 0 3 3. 1 0 3. 7 9 3. 8 5 3. 9 4 3. 9 5 M O R A 2

. 4 7 2. 5 8 2. 7 4 3. 1 4 3. 2 7 3. 4 8 10 .7 4 OKE F 2

. 4 1 3. 0 0 3. 9 2 3. 0 6 3. 8 1 4. 9 7 62 .5 3 PH O E 1

. 9 1 1. 9 4 2. 0 1 2. 4 3 2. 4 7 2. 5 5 5. 1 5 SEN Y 2

. 7 6 3. 1 4 3. 3 2 3. 5 0 3. 9 9 4. 2 1 20 .3 4 SHE N 2

. 2 7 2. 5 5 3. 0 4 2. 8 8 3. 2 3 3. 8 6 33 .9 4 SNP A 2

. 2 9 2. 5 4 2. 9 7 2. 9 0 3. 2 2 3. 7 7 29 .8 9 SYC A 2

. 2 0 2. 2 5 2. 3 6 2. 7 9 2. 8 6 2. 9 9 7. 3 3 THI S 2

. 1 1 2. 4 4 3. 1 1 2. 6 8 3. 1 0 3. 9 5 47 .1 5 UPB U 2

. 5 4 2. 8 3 3. 2 9 3. 2 2 3. 5 9 4. 1 8 29 .8 7 VI I S 4

. 9 0 6. 2 2 6. 9 7 6. 2 2 7. 9 0 8. 8 6 42 .3 4 Av g 2. 3 5 2

. 6 1 3. 0 4 2. 9 9 3. 3 1 4. 0 8 31 .2 4 Std De v 0. 3 4 0

. 3 0 0. 4 0 0. 4 4 0. 3 8 0. 5 0 23 .7 0

104Figure 18. Map of mean inorganic s p eci fic mass sc atte ring efficiencies ( α inorg , m 2 g -1 ) fr om me th od 3. T h e siz e of the circle re flects the magnitude of the e ffi ciency, whic h is printed ne xt to the circle .

The spatial distribution of POM mass scattering efficiencies from m e thod 3 is shown in Figure 19. Inorganic and organic ae rosols wer e assum e d to be inte rna lly m i xed; theref ore the POM scattering efficien cies are sc a l ed to ino r g a nic ef f i cie n cies by th e ra tio of the i r d e nsities (1.31) and the spatial variab ility across the United States is the sam e for both. Notice, however, that in the c e ntra l e a ste r n United S t a t es th e POM scattering efficiencies approach 4.0 m 2 g -1 , the value curren tly assum e d in the Regional Haze Rule guidance. Also note that at GRSM there is less than a 6% change in m a ss scattering efficiency for a doubling of m a ss concentration, but that the ac tual v a riab ility in observed m a ss results in a 60% change in m a ss scattering efficien cy between the upper and lower estim a tes when the functional depende nce on m a ss is accounted for by this m e th od. The average POM mass scatterin g efficiency is 3.31 ± 0.3 8 m 2 g -1 , sim ilar to tha t derived for inorganics.

105Figure 19. Map of or ganic ma ss scatte ring efficienci es ( α org

, m 2 g -1 ) from me thod 3. The size of the circle reflects the m a gnitude of the efficienc y , which is prin te d ne xt to the c i rcle..

In the eastern United S t ates the P O M m a ss scattering efficiencies for m e thod 3 are sim ilar to method 1. However, m e thod 3 results are quite different from m e thod 1 in the western part of the country, where the efficiencies were near 2.0 m 2 g -1 or lower. One interes t ing f eature showing up in both analyses is lower m a ss s cat tering efficien cies in Arizona com p ared to adjacen t m o nitoring sites. Table 22, like Table 20 for m e thod 3, provides the m e an, lower, and upper m a ss scattering efficiencies for each species as derive d using m e thod 4. The upper and lo wer estim ates

are com puted by averaging the m a ss scattering effi ciencies associated with the upper and lower 15% m a ss c oncentrations. Although results for VIIS are reported, calculations of the average and standard deviation in m a ss scattering efficien cies do no t in clude data from VIIS. The results derived with m e thod 4 are quite sim ilar to thos e from method 3, with sim ilar values of the

106average m ean, lower, and upper m a s s scattering effici encies for all the sites. However, there is much greater variability in the results from m e thod 3 com p ar ed to those f r om method 4. Method 3 also yields a significantly lower P O M m a ss scatte ring efficiency for the urban area of Phoenix

com p ared to m e thod 4 (m ean values of 2.47 versus 3.71 m 2 g -1 ). In fact, m e thod 4 yields the highest POM m a ss scatteri ng efficiencies (3.71 m 2 g -1 ) compared to other s ites because it has

som e of the highest POM m a ss concentrations; however, results from m e thod 3 indicate that PHOE has t h e lowest POM m a ss scattering efficienci es of all the s ites. A possible reason for this discrepancy is the calculation of POM. An R oc factor of 1.8 is used on all sites in m e thods 3 and 4; however, the MLR regression in section 3.1 suggests that P hoenix has a m u ch lower average
R oc f a c t o r ( 1

. 3 )

. I f P O M m a s s i s o v e restimated in Phoenix due to a high R oc factor, the efficiencies derived with m e thod 4 will b e more strongly affected th at tho s e derived us ing

m e thod 3 because of how m a sses are weighted in the respectiv e algo rithm s . If we correct th e

m e thod 4 Phoenix POM m a ss scattering efficiency for an R oc factor of 1.3, the valu e d ecreases to 2.68 m 2 g -1 and we obtain a closer agreem ent with m e thod 3 (2.47 m 2 g -1 ). These d i fferences in

m a ss scattering efficiencies between m e thod 3 and 4 generally occur for all m onitoring sites in the Southwest, suggestin g that the difference in com position of the two size m odes, not just th e change in size, is potentially im portant and is not included in the m e thod 4 form ulation. These differences are highlighted by co m p aring Figures 18 and 19 to Figures 20 and 21 where the m a ss scattering efficiencies f o r each m onitoring s ite and species are shown. The effects of th e different m a ss scattering efficiencies on es tim ated sca tte ring will be inv e stig ated in section 7, where we present the biases between m easured and estim ated scattering for all the m e thods.

107Table 22. The mean, uppe r, and low er specific scatte ring efficiencies (m 2 g -1 ) fo r a m mo n i u m su lf at e (A S) , amm o nium nitrate (AN), and p a rtic ul ate or ganic matter (P OM) c o mpute d with method 4. T h e upper and lower estim a tes are c a lculated by aver aging the mas s scatterin g e ffi ciencies ass o c i ated with the upper and lower 15 % mass c o nce n trati o ns. The percent change s be tween the upper and lower m a ss scatterin g efficiencies ar e shown in the final three col u mns.

m 2 g -1 α AS α AS α AS α AN α AN α AN α POM α POM α POM A S A N P O M
S i t e l o w e r m e a n u p p e r l o w e r m e a n u p p e r lower mean upper % diff % diff % diff ACA D 2. 2 8 2

. 5 8 3. 2 9 2. 2 1 2

. 2 5 2. 3 4 2. 8 9 3

. 1 0 3. 5 6 43 .9 5 6. 0 3 23 .4 8 BIBE 2. 2 9 2

. 5 8 3. 0 6 2. 2 1 2

. 2 4 2. 3 0 2. 8 7 3

. 0 7 3. 5 0 33 .2 5 4. 0 0 22 .0 5 BOWA 2. 2 6 2

. 4 4 2. 7 9 2. 2 0 2

. 2 7 2. 5 6 2. 8 6 3

. 0 9 3. 6 0 23 .4 9 15 .9 9 25 .6 8 CORI 2. 2 5 2

. 3 9 2. 6 2 2. 2 2 2

. 3 3 2. 7 2 2. 9 2 3

. 2 7 3. 9 5 16 .6 4 22 .8 7 35 .4 9 DO SO 2. 4 0 3

. 0 5 4. 2 7 2. 2 1 2

. 2 8 2. 4 5 2. 9 8 3

. 3 3 3. 8 2 78 .2 8 10 .5 1 28 .2 2 GICL 2. 2 5 2

. 3 6 2. 5 3 2. 2 0 2

. 2 2 2. 2 5 2. 7 6 3

. 0 9 3. 8 5 12 .3 9 1. 9 6 39 .5 9 HA NC 2. 2 3 2

. 3 1 2. 4 4 2. 2 0 2

. 2 3 2. 2 8 2. 8 2 2

. 9 9 3. 3 3 9. 3 1 3. 3 2 17 .9 3 GRSM 2. 4 0 3

. 0 5 4. 2 2 2. 2 1 2

. 2 6 2. 4 1 2. 9 7 3

. 3 9 4. 0 2 75 .4 7 8. 6 8 35 .2 9 IKB A 2. 2 5 2

. 3 5 2. 4 9 2. 2 1 2

. 2 5 2. 3 2 2. 8 8 3

. 0 2 3. 2 7 10 .7 7 4. 9 3 13 .7 5 JARB 2. 2 2 2

. 2 7 2. 3 4 2. 2 0 2

. 2 2 2. 2 6 2. 8 5 3

. 0 3 3. 4 5 5. 3 9 2. 4 7 21 .2 5 LOPE 2. 2 5 2

. 3 4 2. 4 8 2. 2 2 2

. 3 0 2. 6 1 2. 8 9 3

. 1 1 3. 4 9 10 .0 8 17 .8 2 20 .7 4 MA CA 2. 4 8 3

. 1 1 4. 2 0 2. 2 3 2

. 3 4 2. 6 5 3. 0 3 3

. 4 1 4. 0 2 69 .2 0 19 .0 1 32 .9 0 MO RA 2. 2 2 2

. 3 5 2. 6 1 2. 2 0 2

. 2 3 2. 2 8 2. 8 6 3

. 2 0 3. 8 1 17 .5 7 3. 3 3 33 .0 2 OKE F 2. 4 3 2

. 8 7 3. 6 2 2. 2 2 2

. 2 6 2. 3 3 3. 0 1 3

. 3 4 3. 8 7 49 .0 4 5. 1 1 28 .7 8 PHOE 2. 2 9 2

. 4 2 2. 6 0 2. 2 4 2

. 3 7 2. 8 3 3. 1 4 3

. 7 1 4. 9 8 13 .2 4 26 .6 4 58 .2 1 SENY 2. 2 8 2

. 5 4 3. 2 4 2. 2 1 2

. 3 2 2. 7 6 2. 8 5 3

. 1 4 3. 6 9 42 .3 1 25 .0 5 29 .2 5 SHE N 2. 3 7 2

. 9 7 4. 0 9 2. 2 2 2

. 3 0 2. 4 9 2. 9 2 3

. 2 3 3. 8 4 72 .7 7 12 .3 0 31 .7 2 SNP A 2. 2 3 2

. 3 5 2. 5 6 2. 2 1 2

. 2 5 2. 3 4 2. 8 4 3

. 1 0 3. 6 2 15 .0 8 5. 8 5 27 .2 0 SYCA 2. 2 4 2

. 3 2 2. 4 3 2. 2 1 2

. 2 4 2. 3 0 2. 9 0 3

. 1 3 3. 5 7 8. 8 8 4. 2 8 23 .0 3 THIS 2. 2 1 2

. 2 9 2. 4 5 2. 2 0 2

. 2 2 2. 2 6 2. 8 2 3

. 1 1 3. 7 6 10 .7 5 2. 4 5 33 .3 7 UPBU 2. 3 4 2

. 8 1 3. 6 7 2. 2 2 2

. 3 4 2. 6 6 2. 9 7 3

. 3 3 3. 9 3 57 .3 0 19 .9 7 32 .1 9 VI IS 2. 2 6 2

. 3 3 2. 4 6 2. 2 1 2

. 2 3 2. 2 6 2. 8 2. 9 3. 1 8. 8 5 2. 2 6 10 .7 1 Av g 2. 2 7 2

. 4 9 2. 9 1 2. 2 1 2

. 2 6 2. 3 9 2. 9 1 3

. 1 8 3. 7 4 32 .1 5 10 .6 0 29 .2 0 Std De v 0

. 0 7 8 0

. 2 8 9 0

. 6 8 9 0

. 0 0 9 0

. 0 4 6 0

. 1 9 0 0

. 0 8 6 0

. 1 7 2 0

. 3 5 3 2 5

. 4 3 3 8

. 2 6 1 9

. 2 9 3

108Figure 20. Map of the mean amm o nium su lfate mass s c attering e ffic i encies ( α AS

, m 2 g -1 ) fr om meth o d 4 . The siz e of the circ le reflects the magnitude of th e e fficienc y , which is printed ne ar the ci rcle.

109Figure 21. Map of me an P O M ma s s sc attering efficiencies ( α POM , m 2 g -1 ) fr om method 4. The siz e of the circle reflects the m a gnitude of the efficienc y , which is prin te d ne ar the cir c le.

6. Evaluation of the Combined Data Set Section 5 focused on the various m e thods for estim ating mass scattering efficiencies for each site ind i vidually. We now apply m e thods 3 and 4 to a com b ined data set from all th e sites. Data from PHOE and VIIS were no t includ ed in this com b ined data set b ecause the results from these s i tes w e re con s is tent outliers. W h en analy s es are perform e d on a per-site basis, site specifi c coefficients are app l ied to data from each s ite; ho wever, in this section we apply on ly one set of

assum p tions to the com b ined data se t. W e will ref e r to resu lts f r om m e thods 3 and 4 as applied to the com b ined data set as “M3-C” and “M4-C”, re spectively. Method 3 yi elds an intercept and slope for the com b ined data set of 0.8 and 0.015, respectively, and can be com p ared to the values

110derived for individual sites from Table 20. The average intercept and slope of all the individual sites was 0.69 and 0.04, respectively. Table 23 presents a s t atistical summ ary of aerosol m a ss concentration s for each s p ecies, rela tive hum idity, tota l a e rosol sc atte ring, and th e average f (RH) estim ates correspon ding to the ammonium sulfate sm all size m ode, large size mode, current IMPROVE estim ate, and sodium chlor i de f o r the com b ined data f r om all the si tes and tim e periods (except PHOE and VIIS). Ammonium sulfate composes 43% of the fi ne m a ss while POM contributes 34%. Soil contributes 10% of the fine m a ss, ammonium n itrate is 7%, and light-absorbing carbon is 4%. Sea salt contributes less than 1%.
Ta b l e 23 . A s t a t is t i ca l s u m m a ry o f ma s s co n c en t r at io n s ( μ g m -3 ) f o r the co mbined da ta set (a ll opt i ca l monitoring sites exce pt Phoenix and the Virgin I s lan d s ). C M and F M re f er to gr avime tric coarse mas s and fine (P M 2.5 ) m a ss, res pecti v e l y. AS and AN refer to am monium s u lfate and amm o nium nitr ate, respectivel y. POM is par t iculate or ganic matter usin g an R oc fact or of 1. 8. R H refers to ambi ent relati v e humidity. The number o f n e phel o me ter dat a p o i n ts i n a 24 -hr av erage i s gi ve n by N( b sp ) . The values of the f (R H) corresponding to the nephe lometer chamber for the amm o nium sulf ate sm all mode , lar g e mode , current IMP R O V E e s tima te, and Na Cl cur v e s are also li sted. T h e contribu tion t o fine m a ss i s pro v ided i n parenthese s . Vari able Mean Std De v Minimum Maximum Valid CM (μg / m 3 ) 4. 71 5. 09 -1 7. 7 4 11 6. 5 6 13 2 17 FM (μ g/m 3 ) 7. 15 6. 35 -0 .7 1 68 .0 4 13 6 30 AS (μg/m 3 ) 3. 05 ( 4 3%) 3. 90 0. 00 46 .6 9 13 9 82 AN (μ g/m 3 ) 0. 51 ( 7 % ) 0. 92 -0 .0 6 16 .9 2 13 6 95 POM (μg/m 3 ) 2. 45 ( 3 4%) 2. 68 -0 .1 9 10 4. 4 1 13 7 94 LAC (μg/m 3 ) 0. 30 ( 4 % ) 0. 30 -0 .0 2 13 .3 9 13 7 68 So il (μg / m 3 ) 0. 68 ( 1 0%) 1. 34 0. 00 29 .2 6 13 8 81 Sea Salt (μ g/m 3 ) 0. 02 (< 1% ) 0. 14 0. 00 5. 44 15 0 51 RH (%) 61 .4 8 1 8 .0 2 5. 8 5 90 .0 0 13 3 0 0 b sp (M m -1 ) 25 .9 2 3 1 .2 8 0. 0 4 32 5. 9 6 58 9 9

N(b sp ) 1 5 .8 6 8. 8 3 1. 0 0 24 .0 0 15 0 5 1 f

(RH) c,small 2

. 0 9 0. 5 9 1. 0 4 4. 3 5 12 7 2 7 f

(RH) c,large 1

. 8 0 0. 4 0 1. 0 4 3. 2 2 12 7 2 7 f

(RH) c,IMPROVE 1

. 8 7 0. 5 9 1. 0 0 3. 6 5 12 7 2 7 f

(RH) c,NaCl 2

. 5 4 0. 8 6 1. 0 0 4. 7 8 12 7 2 7

111Table 24. A s u mmar y of the low, me an, a nd high mas s scatteri ng e f ficiencies (m 2 g -1 ) for the c o mbined data set with method 4 (M4-C), two statis tic a l corrections to method 4 re sults (M4-C1 and M4-C2, s ee text), and results fr om method 3 applied to the c o mbined data (M3-C). Results corre sp ond to ammonium sulfate (AS ) , amm o nium ni trate (AN), an d p a rtic ul ate organic mater i al (POM).

Using the combined data, we now investigat e the perfor m a nce of method 4 by evaluating different statistical regressions between the method 4 estim ated and m easured scattering. The results of the regressions are summarized in Table 24. The m ean and lower and upper m a s s scattering efficiencies for the com b ined data se t as derived by m e thod 4 are referred to as “M4- C”. The first statistical approach (M4-C1) corresponds to a regres sion of the scattering estim ates from m e thod 4 for each species ag ainst the m easured s cattering, b mix , with adjus t m e nts to the

m e thod 4 dry m a ss scattering efficiencies by the regression coefficients correspond ing to each species. The regression coefficients were near 1, indicating that m e thod 4 results in average m a ss scattering efficiencies that ar e representative o f the actu a l m a ss scattering efficiencies. The statistical approached referred to as “M4-C2” is sim ilar to M4-C1 e x cept the r e gress i on is between fine m ode (summed inorganics and organics, b mix_est ) scattering from m e thod 4 and

m easured b mix (sim ilar to m e thod 2), resu lting in a single regression coefficient instead of coefficients correspond ing to each species. The regr ession coefficient is not statistically different from 1, implying again that dry m a ss scatte ring efficiencies deri ved with method 4 are representative of actual values. Finally, results from m e t hod 3 applied to the combined data (M3-C) are very sim ilar to the re sults from m e thod 4 (see last row in Table 24). The values in Table 24 should be contrasted to those used in the cur r ent IMPROVE equation f o r

estim ating α (m 2 g -1 ) A S A N P O M

C a s e l o w m e a n h i g h l o w mea n h i g h l o w m e a n h i g h M 4 -C 2

. 2 3 2. 5 2 3. 2 8 2. 2 1 2. 2 5 2. 4 1 2. 8 7 3. 1 8 3. 8 0 M 4 -C 1 2

. 1 9 2. 4 7 3. 2 2 4. 1 2 4. 2 1 4. 4 9 2. 5 9 2. 8 7 3. 4 3 M 4 -C 2 2

. 2 8 2. 5 7 3. 3 6 2. 2 6 2. 3 1 2. 4 6 2. 9 4 3. 2 5 3. 8 9 M 3 -C 2

. 4 5 2. 6 7 3. 1 4 2. 4 5 2. 6 7 3. 1 4 3. 1 0 3. 3 8 3. 9 7

112scattering. The curren t IMPROVE ammonium sulfate, ammonium n itrate, and POM m a ss scattering ef ficiencies are 3.0, 3.0, and 4.0 m 2 g -1 , respectively, rough ly 20–25% higher than estim ates obtained from m e thod 4 (2. 52, 2.25, and 3.18 m 2 g -1 for ammon i um sul f at e, ammoni u m nitr ate, and POM, respe c tive l y).
A summ ary of m easured and recon s tructed to tal b sp and accum u lation mode b mix using

m e thod 4 is presented in Table 25. Also presen ted are estim a tes of sca ttering associated with each sp ecies, fine particle abso rptio n , and scatte ring du e to water. Th ere is on ly about a 3% difference on average between estim ated and m easured scattering for both fine and total scattering. Ammonium sulfate a nd POM contribute 41 a nd 27%, re spec tive l y, to to tal ex tinc tion , while CM contribu tes 1 2 %. Nitrate and soil ea ch contribute less than 10% of total scatter i ng, and sea salt contributes less than 0.2 of one percent.
Table 25. A summar y of b sp (Mm -1 ) f o r the c o mbined da ta se t (all moni toring sites except Phoenix and the Virgin Isl ands). Value s cor respond to mea s ured to ta l a m bient sca ttering ( b sp ), re cons truc ted total ambient scattering ( b sp _recon ), measur e d scattering ass o ciated with fi ne mode i n or ga ni cs and org a ni cs ( b mi x ), estim a te d scat teri n g ass o ci a t ed w i th i n or ga ni cs an d or g a ni cs ( b m i x_est ), sc atter i ng due to ammonium sul f ate ( b sp ( AS ) ), amm o nium nitrate ( b sp ( AN ) ), par t iculate organic mater i al ( b sp ( PO M )), sea s a lt ( b sp ( SS ) ), and water ( b sp ( H 2 0 ) ). L i ght abs o rp t i on ( b ap ) was computed ass u ming a m a ss abs o rption e f ficiency of 10 m 2 g -1 . New f (RH) curves were used to e s timate wet sc attering. Vari able (Mm -1 ) Mea n Std De v Minimum Ma ximum Valid b sp 25 .5 6 3 0 .0 0 0. 0 4 27 3. 5 0 50 9 0 b sp_recon 24 .8 0 2 7 .8 3 0. 2 7 30 1. 0 0 50 9 0

b mix 22 .7 4 2 9 .9 2 -1 1. 0 1 27 1. 9 9 50 9 0 b mix_est 21 .9 8 2 7 .6 1 0. 1 0 29 8. 7 0 50 9 0 b sp (A S ) 1 1 .9 2 21 .8 4 0. 3 9 29 2. 3 9 50 9 0 b sp (A N ) 2

. 2 7 4. 9 0 -0 .1 9 74 .1 6 50 9 0 b sp (P OM ) 7

. 7 9 9. 0 1 -0 .3 6 19 4. 1 3 50 9 0 b sp (S oi l ) 1

. 0 2 1. 6 6 0. 0 1 29 .2 6 50 9 0 b sp (C M ) 3

. 5 2 3. 6 8 -3 .1 2 69 .9 4 50 9 0 b sp (SS ) 0

. 0 4 0. 4 1 0. 0 0 15 .1 2 50 9 0

b ap 2. 7 4 2

. 1 5 -0 .1 1 30 .2 5 50 9 0 b sp (H 2 O ) 6

. 3 1 11 .5 5 0. 0 6 15 8. 1 5 50 9 0

1137. Biases betw een Reconstructed and Measured Scattering In th is s ection we present a brief summ ary of the skill with which each m e thod
reconstruc ts tota l sc atte ring as m e asured by th e Optec am bient op en air neph elo m eter. W e

com pute the averag e bias as (b sp _recon - b s p_meas )/

b sp_meas for tim e periods with low (10–20%),

m e dian (45–55%), and high (80–90 %) m easured sca ttering values. The resu lts for each of th e five m e thods (current IMPROVE a nd m e thods 1–4) are presente d in Tables 26–28 and Figures
22–26. The poorest perform a nce for all the m e thods corresponds to tim e pe riods with the 10– 20% lowest m easured scattering coef ficients. Th e statistical models (m ethods 1–3) dem onstrate the weakest perform a nce, with average biases across all sites for m e t hod 1 and m e thod 2 of 63 and 82%, respectively. Methods 3 and 4 perform the best, with average biases of 46 and 44%, respectively. The biases for all the methods tend to increase and decrease for each sites sim ilarly (see Figure 22). The bias was near 150% at Ikes Backbone AZ (IKBA) and Jarbridge
W ilderness NV (JARB) and near zero at Shena ndoah National Park VA (SHEN), Three Sisters
W ilderness OR (THIS), and Upper Buffalo W ild erness AR (UPBU). Th e biases corresponding to the eastern m onitoring sites were the lo west, ranging from 25–30 % for m e thods 3 and 4. The lowest average biases corresponding to tim e periods with the median (45–55%)

m easured scattering coefficients w e re 4. 3 and 1.2%, corresponding to m e thods 3 and 4, respectively. The highest average biases fo r this case were 13 a nd 22%, corresponding to

m e thods 1 a nd 2, respectively. Note that the bi as at Phoenix is sm allest (<10%) for the m e thods that were applied on a site-by-si te basis (m ethods 1–3), com p ared to the highest bias (~ 30%) for

m e thod 4, which was applied similarly to the en tire data set. Phoenix has relatively high concentrations of POM with quite low m a ss scattering efficiencies, as co mpared to more rem o te

114nonurban lo cation s ; th ese unique conditions are acc ounted for in the site -by-s ite evaluations (m ethods 1–3), but not in the site-indep endent algorithm applied in m e thod 4. Methods 1 and 2 have the lowest biases (1–2%) corresponding to the highest (80–90%) scattering values; however, all m odels perform e d well under these c onditions, with biases of less than 10%. Method 4 has an average bias across al l sites of -9%. Methods 1–3 perfor m the best for the Phoenix site for the reasons discussed above.
Table 26. Average biases for time peri ods with lo w (10–20% ) measured sc atteri ng values for meth o ds 1–4 and the curre nt I M P R OVE equati on. Site Met h o d 1 Met h o d 2 Met h o d 3 Met h o d 4 IMP R O V E AC A D 0

. 43 3 0. 51 0 0. 27 0 0. 21 3 0. 32 0 B I B E 0

. 77 9 0. 86 6 0. 40 2 0. 51 8 0. 57 7 B O W A 0

. 44 0 1. 34 1 0. 79 0 0. 48 5 0. 57 1 C O R I 1

. 10 5 1. 41 9 0. 64 0 0. 96 5 1. 10 9 DO S O 0

. 63 7 0. 73 2 0. 48 5 0. 30 8 0. 26 5 GIC L 0

. 87 5 1. 45 0 0. 47 8 0. 67 6 0. 85 8 HA NC 0

. 55 6 0. 56 8 0. 51 5 0. 18 8 0. 35 9 GR SM 0

. 42 3 0. 56 5 0. 09 7 0. 23 5 0. 24 2 IKB A 1

. 45 5 1. 42 1 0. 81 9 1. 19 9 1. 38 3 JAR B 1

. 35 8 1. 80 0 1. 32 8 1. 06 6 1. 27 7 L O P E 0

. 52 1 0. 84 1 0. 38 0 0. 34 5 0. 42 8 M A C A 0

. 30 8 0. 37 6 0. 31 8 0. 08 7 0. 12 5 M O R A 1

. 53 6 1. 53 0 0. 95 6 1. 02 5 1. 15 7 OKE F 0

. 56 3 0. 75 4 0. 37 4 0. 28 8 0. 33 6 PH O E 0

. 10 9 0. 20 1 0. 09 6 0. 42 1 0. 46 8 SEN Y

- 0 .0 2 7 0. 03 1 0. 14 0

- 0 .211
- 0 .093 SHE N 0

. 42 9 0. 58 4 0. 31 7 0. 33 6 0. 40 4 SNP A 0

. 40 5 0. 55 4 0. 24 3 0. 22 5 0. 33 6 SYC A 0

. 81 0 0. 83 7 0. 67 7 0. 77 4 0. 85 7 THI S 0

. 32 7 0. 45 6 0. 11 6 0. 09 9 0. 18 2 UPB U 0

. 21 0 0. 39 8 0. 13 0 0. 05 0 0. 09 9

Av g 0. 63 1 0

. 82 1 0. 45 6 0. 44 2 0. 53 6

115Figure 22. The aver a ge biases for each site correspo nding to time periods with low measured scattering v a l ues (10 –20% ) ( s ee Ta ble 2 6 ) . B i as cor r e s p on di n g t o L o w S cat t e r i n g

R a n g e

-0

. 5 0. 0 0. 5 1. 0 1. 5 2. 0

AC AD BI

BE

BO WA CO RI

DO S

O

GI

C

L HA NC GR S M

I K

BA J AR B

LO

P

E MA C

A M

O

R

A

OK E

F

P

HO E

SE

N

Y

SH

E

N

S N

P A

SY

C

A

T

HI

S UP

B

U

Si

t eAverage Bias

Me t h o d 1 Me t h o d 2 Me t h o d 3 IM P R O V E Me t h o d 4

Table 27. Average bi ases for time periods with the median (45–55% ) measu re d sc attering value s for methods 1–4 and the c u rrent IMPROVE e q uation.
Site Met h o d 1 Met h o d 2 Met h o d 3 Met h o d 4 IMP R O V E AC A D 0

. 14 0 0. 18 6 0. 01 6

- 0 .028 0. 05 4 B I B E 0

. 20 4 0. 23 2 0. 00 2 0. 02 7 0. 03 8 B O W A

- 0 .0 4 3 0. 24 8 -0 .0 4 1

- 0 .208
- 0 .117 C O R I 0

. 25 0 0. 43 2 0. 05 2 0. 20 1 0. 24 6 DO S O 0

. 36 2 0. 23 9 0. 09 0

- 0 .023
- 0 .057 GIC L 0

. 09 7 0. 48 9 0. 00 0 0. 04 3 0. 12 3 HA NC 0

. 23 2 0. 23 5 0. 20 2 0. 01 4 0. 07 2 GR SM 0

. 19 0 0. 25 8 0. 01 0 0. 07 7 0. 04 5 IKB A 0

. 16 9 0. 19 4 0. 02 0 0. 09 7 0. 16 3 JAR B 0

. 15 2 0. 29 9 0. 13 3

- 0 .011 0. 04 9 L O P E 0

. 16 0 0. 39 2 0. 10 0 0. 04 3 0. 08 0 M A C A 0

. 11 0 0. 11 4 0. 07 6

- 0 .062
- 0 .072 M O R A 0

. 22 4 0. 21 8 0. 04 5 0. 07 5 0. 09 3 OKE F 0

. 09 7 0. 17 0 0. 02 7

- 0 .081
- 0 .069 PH O E

- 0 .0 2 0 0. 06 2 -0 .0 1 8 0. 33 1 0. 29 9 SENY

- 0 .118

- 0 .057 0

. 0 2 8

- 0 .256
- 0 .151 SHE N 0

. 08 5 0. 18 4 0. 03 7 0. 05 4 0. 07 3 SNP A 0

. 18 7 0. 25 7 0. 10 7 0. 04 2 0. 07 2 SYC A

- 0 .0 0 7 0. 03 5 -0 .0 5 0 0. 00 3 0. 05 5 THI S 0

. 04 2 0. 15 7 -0 .0 1 0

- 0 .087
- 0 .043 UPB U 0

. 13 4 0. 23 1 0. 06 9

- 0 .010
- 0 .014

Av g 0. 12 6 0

. 21 8 0. 04 3 0. 01 2 0. 04 5

116Figure 23. The average bi ases for e a ch site corres pond ing to time periods with m e dian me asur ed scattering v a l ues (45 –55% ) ( s ee Ta ble 2 7 ) .
B i as co r r e s p o n d i n g

t o M e d i an S cat t e r i n g

R a n g e

-0

. 3 -0

. 2 -0

. 1 0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6

AC AD B

I BE

B

O

WA CO R

I DO S

O

G

IC

L H

AN C GR S M

IK

B

A

JA

R

B

LO

P

E MA C

A MO RA

OK E

F

PH

O

E

S

E

N

Y

SH

E

N

SN

P

A

S YC A

TH

I S U

PB

U

Si

t eAverage Bias

M e t h od 1 M e t h od 2 M e t h od 3 I MPR O V E M e t h od 4

Table 28. Average biases for time periods with high (80–90% ) measured sc atteri ng value s for meth o ds 1–4 and the curre nt I M P R OVE equati on.

Site Met h o d 1 Met h o d 2 Met h o d 3 Met h o d 4 IMP R O V E AC A D 0. 09 3 0. 11 9 0. 02 0

- 0 .0 1 6 0

. 02 4 BI B E

- 0 .022

- 0 .020

- 0 .073

- 0 .121

- 0 .152 BOW A

- 0 .006 0

. 2 2 4

- 0 .027

- 0 .191

- 0 .115 CO RI

- 0 .054 0

. 1 0 6

- 0 .057

- 0 .006

- 0 .031 DO S O 0

. 14 0 0. 05 6 -0 .0 1 1 -0 .0 9 8 -0 .1 3 9 GIC L 0

. 04 9 0. 18 2 -0 .0 4 7 -0 .1 1 7 -0 .1 1 3 H A N C

- 0 .152

- 0 .149

- 0 .166

- 0 .270

- 0 .254 G R S M 0

. 0 0 2

- 0 .008

- 0 .029

- 0 .016

- 0 .131 I K B A

- 0 .068

- 0 .071

- 0 .007

- 0 .110

- 0 .088 JA R B

- 0 .144

- 0 .080

- 0 .147

- 0 .275

- 0 .250 LO P E

- 0 .042 0

. 0 2 5

- 0 .132

- 0 .208

- 0 .181 MA CA

- 0 .016

- 0 .039

- 0 .063

- 0 .140

- 0 .169 MO RA

- 0 .012

- 0 .020

- 0 .095

- 0 .093

- 0 .109 O K E F

- 0 .002

- 0 .004 0

. 0 1 5

- 0 .155

- 0 .194 PH O E

- 0 .0 5 7 -0 .0 2 5 -0 .0 6 7 0. 45 6 0. 19 3 SEN Y 0

. 00 5 -0 .0 0 3 0. 01 1 -0 .1 5 4 -0 .1 0 8 SHE N

- 0 .0 0 6 0. 04 6 0. 00 0 0. 02 8 -0 .0 2 1 SN PA

- 0 .010

- 0 .049

- 0 .096

- 0 .178

- 0 .183 SY CA

- 0 .068

- 0 .072

- 0 .128

- 0 .039

- 0 .056 THI S 0

. 00 9 0. 04 5 0. 06 1 -0 .0 8 8 -0 .1 5 2 U P BU

- 0 .053

- 0 .024

- 0 .069

- 0 .135

- 0 .161

Av g - 0 .020 0

. 0 1 1

- 0 .053

- 0 .092

- 0 .114

117Figure 24. The aver a ge biases for each site correspo nding to time periods with high measure d scattering v a l ues (80 –90% ) ( s ee Ta ble 2 8 ) .
B i a s c o r r e s p o n d i ng

t o H i gh S c a t t e r i ng R a nge

-0

. 4 -0

. 3 -0

. 2 -0

. 1 0. 0 0. 1 0. 2 0. 3 0. 4 0. 5

A

C

AD BI

B

E BO W

A

CO RI

DO S

O

GI

CL

HA NC GR S M

IK

B

A

JA

R

B

LO

P

E MA C

A MO R

A

OK E

F

PH

OE SH

E

N

S EN

Y

S NP

A

SY

C

A

TH

I S U

P BU

Si

t eAverage Bias

M e t h od 1 M e t h od 2 M e t h od 3 IM P R O V E MW S
Figure 25. Average bi ases for the c o mbi n ed data se t (all sites and ti me) for time periods with l o w (10–20% ), median (45–55 % ) , and high (80–90 % ) sc attering ranges, as ca lcul ated using methods 3 and 4, and the current IMP R O V E al gori t hm. Al so sh ow n i s the a v era ge of t h e per-si te bi a s es fr om T a bl e s 2 6

– 2 8 . T h e f (RH) c u rves were calculate d for c o ntinuous gr owth fr om 1 < RH < 90 % . 

### Bi a s f o r C o m b i

n e d D a t a ( R H < 9 0 % c u t o f f - C o nt i nuo us C u r v e )

-0

. 2 -0

. 1

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6

L o w M e d ia n H ig hAverage Bias 

### M e t h od 4 ( M 4- C ) M e t h od 3 ( M 3- C ) IM P R O V E M e t h o d 4 ( p er - s i t e av g ) M e t h o d 3 ( p er - s i t e av g ) I M P R O V E ( p er - s i t e av g )

118Figure 26. Average bi ases for the c o mbi n ed data se t (all sites and ti me) for time periods with l o w (10–20% ), median (45–55 % ) , and high (80–90% ) scat tering ranges, as calcul ated us ing methods 3, 4, and the current IMP R O V E al gori t hm. T h e f (RH) cur v es were calculated from 1 < RH < 95 % assuming cr ystalliz ation grow th curves . B i as f o r

C o m b i

n ed D a t a ( R H < 9 5 % c u t o f f - C r y s t a ll iz a t io n C u r v e )

-0

. 2 -0

. 1

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5

L o w M e d ia n H ig hAverageBias M e t h od 4 ( M 4- C ) M e t h od 3 ( M 3- C ) IM P R O V E

The biases were also co mputed for the com b ined data set of all sites and tim e periods. In this analy s is the bias is calcu lated for each 24 -hour sam p ling pe riod and then averaged, thus biasing the results toward those m o nitoring sites that have been operating over longer periods of tim e. This approach should be c ontrasted again s t th e bias com put ed as the grand av erage of all the s ite average b i ases, thus weigh ting each m onitoring site or geogra phic location equally. Figures 25 and 26 show the average bias corresponding to tim e periods with low, m e dian, and high scattering periods for m e thod 4 (MC-4), m e thod 3 (MC-3), and the current IMPROVE algor ithm f

o r the com b ined data set. Two f (RH) curves were used in thes e calculation s. Because the Regional Haze Rule suggests using an R H cutoff of 95%, the bias calcu l ations were

com puted using RH cutoff values of both 90 and 95%. Figu re 25 p r esen ts th e biases com puted

assum i ng a 90% RH cutoff and continuous (1 < RH < 90%) f (RH) curve s for both th e com b ined data set and the site-by

- site average, while Figure 26 presents the sam e biases com p uted with a

11995% RH cutoff and f (RH) curves corresponding to the crys tallization branch for the com b ine d data set only. For the f (R H) curve corresponding to a 90% cutoff RH, the biases corresponding to the low scattering values are the largest for all the m e thods, ranging from 45 to alm o st 60%. The biases corresponding to the m e dian scattering values range from 0–10%, and the biases corresponding to the highest scattering values are negative (-10–0%) (see Figure 25). The biases

com puted for an average of all th e s i tes are lowe r th an biases com puted for the combined data set, by about 10% for the low s cattering range, 5% at the m e dian scattering range, and within a few percent at the high scattering range. The lo wer bias corresponding to the averaged per-site estim ates is consistent w ith the earlier exam pl e of better perfor m ance at the Phoen i x site when analyses are perfor m e d on a per-site basis. The bi ases com p uted from method 3 as applied to the

com b ined data s e t (M3

- C) were h i g h est f o r the low and m e dian scatterin g range, and the m e thod 4 average of the p e r-site analyses had the lowest biases for th e low and median s cattering rang es. For the time periods w ith the highest scatteri ng range, M3-C had the lowest bias, while the
current IMP R OVE for m ulation had the largest (most negative) bias. Overall, M4 for the per-site analyses had the lowest bias. Com p uting the b i ases with f (RH) curves corres ponding to a higher RH cutoff ( 95%) resulted in lowering the biases for all the m e thods com p ared to an R H cutoff of 90%. This d ecrease in b i as does not imply that th e bias was n ecessarily improved, because a b i as could decrease from -10 to -20% , reflecting a larger difference between m easured and predicted scattering. The biases corresponding to the lo w scattering range droppe d by about 10%, and the

m e dian and high bias dropped by about 6–8%. Met hod 4 (M4-C) results are biased negatively by about 14% for the high s cattering values, negativ e ly by 6% for the m e dian values, an d positiv ely by 31% for low scattering values.

1208. Summary o f Suggested Refineme nts to the IM PROVE Equation The current equation used to estim a te extin ction associated with measured aerosol species is
b ext = α AS

f(RH) AS [A S] + α AN

f(RH) AN [A N] + α PO

M

[P O M

] + α so il [

Soil ] + α CM [CM ] + α LAC [L

A C ] (25)
where it is a ssum e d that the dry m a ss scattering and absorptio n efficiencies α AS , α AN , α POM , α soil ,

α

CM , and α LA C are 3.0, 3.0, 4.0, 1.0, 0.6, and 10.0 m 2 g -1 , respectively, and the f (RH) curve is calculated on an hourly basis and averaged to 24 hours to be comm e n su rate with the 24-hour average aerosol m a ss measurem ents . The f (RH) curve is a “s moothed” ammonium sulfate curv e that reflects continuous particle gro w th starting at 40 % RH. The form s assum e d for each of the aerosol species are ammonium sulfate and amm onium nitrate, 1.4· OC, soil, and gravim etric

coarse m a ss (PM 10 –PM 2. 5 ).
Uncerta inty in estim ated extinc tion is depe ndent on not only the assum e d for m s of e ach of the aeros ol species and their res p ectiv e m a ss scattering efficiencies a nd growth factors, but also on m e asurem ent and analytic accuracy and pr ecis i on. One uncertainty of special concern is the variatio n in flow rate associated wi th the IMPR OVE monitoring sys t em, because uncertainties in the f l ow rate af f ect th e cutpo i nt of the inlet. Th e I M PROVE 2.5 μm inle t intersects the size rang e corresponding to th e coarse m ode; therefore any changes in the cutpoint of the inlet (due to variations in the flow ra te) cause significant and varying am ounts of coarse

m a terial to be characterized as fine m a ss. The fine m ode m a ss scattering efficiency associated with the f i ne tail of the coarse m ode can vary sig n if icantly. This issue is especia lly im portan t f o r sites where soil m a ss contribu tes significantly to estim ated extinc tion (e.g., m o st sites in the West during spring m onths) and for sites where coar se particle nitrate con centration s are h i gh.
Som e of the issues associated with measurem ent un certainty have been disc ussed, but this report

121does not make any recomm endations on change s in m e a s urem ent methodology or analytic procedures. Another significant uncert ainty in reconstructed b ext is th e chem ical form of each of the aerosol sp ecies. Again, this issu e is discussed in som e detail in th is report, but b ecause the ammonium ion is not measured, th e current assum p tion of i n terpreting sulfate and nitrate in the fine m ode as amm oni um sulfate and ammoni um nitrate is not changed. However, the

m u ltiplica tio n f actor ( R oc = 1.4) used to estim ate particulat e organic m a terial from m easured organic carbon m a ss in the current equation is undoubtedly low. B a sed on recent literature review and an analysis of IMPROVE data, we recomm end a value of 1

. 8. W e also recomm end the inclusion of fine sea salt in the IMPROVE equation as 1.8· Cl per the above discussion. Recognizing that fine sea salt is probably th e fine tail of coarse m ode sea salt, a new f (RH) function and dry m a ss scattering efficiency for s ea salt was developed. No new recommendation of fine m a ss absorpti on efficiency is m a de.
Because co arse m a ss is not speciated, we canno t recomm end a ch ange in coarse mass scattering efficiency. Co arse m a ss is not com posed only of crustal m a terial but also contains significant fractions of organic and inorganic species, som e of which ar e hygroscopic and light absorbing and therefore have m a s s scattering efficiencies that differ significan tly from the currently assum e d value of 0.6 m 2 g -1 . Thus it sho u ld be recog n ized tha t co arse m a ss extinc tion is only a very rough estimate. Coarse m a ss concentr ations are also only a pproxim a te because the
PM 2. 5 cutpoint intersects the size rang e that corresponds to the peak of the coarse m ode m a ss size distribution, and flow rate variability can cause th e cut point to vary substantially.
At m o st m o nitoring sites, dry m a ss scatteri ng efficien cies increase with in creas ing m a ss concentration. This relationship was observed at most of the rural s ites an d at the one urban site

122(Phoenix) in the optical mon itoring network. The trend to ward increas ing m a ss scattering efficiency with m a ss concentration s was treate d with two separate approaches. A variety of statistical regressions of m a ss c oncentration and scattering coeffi cients w e re applied (m ethods 1– 3); however, results from statistical regression s are only as ro bust as th e d a ta th em selves. Therefore the second approach (m ethod 4) was ba sed on a physical m o del of a bim o dal fine mode size distribution. T h e sm all size m ode corresponds to lower m a ss c oncentrations and particle s tha t are less ef ficien t at sca t ter i ng ligh t , while the large size m ode is asso ciated with higher m a ss concentrations and pa rticles th at are more efficient at s cattering light. Th e m a ss scattering efficiencies were com puted for a sim p le linear m i xing of these s i ze m odes as a function of m a ss. This model was applied to those species typically found in the fine ( D

p < 2.5
μm ) m ode, nam e ly sulfates, n itrates , and POM. The fine mode bi m o dal m a ss s i ze distri butions were assum e d to be lognorm a l distributions with m a ss m ean dia m eters ( D

g ) of 0.2 μm and 0.5 μm fo r the sm all an d larg e s i z e modes, respectively, and with geom etric standard deviations ( σ g ) of 2.2 and 1.2, respectively, consistent with what is reported in the lite ratu re. The am bient scattering coef f i cient f o r ea ch species is calculated u s ing the same size distribution param e ters. An ammonium sulfate f (RH) curve is calculated for each size d i stribu tion and the am bient s cattering for each species is calcu lated u s ing

) ( ) ( ) ( ) ( ) ( ) (
, s l l j l j l s l j l s j s j sp M M M M RH f M M M M M RH f M b

− − +

− − = α

α (26)

where α s , α l , M s , M l , f s (RH), an d f l (RH) are the dry m a ss scattering efficiencies, m a ss concentrations, and humidification f actors associ ated with the sm all and large m o de m a ss size distributions, respectively. The spec ies m a ss concentration is given by M j . The m a ss scattering efficiencies associated with th e sm all and larg e m a ss size dis t ribu tion s for each species are

123presented in Table 29. Unless otherwise stated, M s = 0.0 μg m -3 and M l = 20.0 μg m -3 ; when the species m a ss concentrations exceeded 20 μg m -3 , the dry m a ss scattering e fficiency was set equal to the large values show n in Table 2 9

. Table 29. Values use d for the dr y m a ss scattering efficiencies (m 2 g -1 ) for the large and s m all mass size distributions for e a ch spec ies (amm onium sulfate, a mmoniu m nitrate , an d par t iculate organic material , POM).

m 2 g -1 A m m o n i u m sulfate Amm o nium nitrate POM

α s (sm a l l ) 2. 2 2. 4 2. 8
α l

(l ar ge ) 4. 8 5. 1 6. 1

The bias between m ode led and m easured scat tering is sim ilar for m e thod 3 (statistical approach) and m e thod 4 (physically based m odel ) as applied to the com b ined data set; however

m e thod 4 ha s an advantage of being less depe ndent on the data set in its form ulation. A substantial num ber of m easurem e n ts of D/D o and f (RH) curves ind i c a te tha t ae r o sol growth occu rs a t low RH values well below th e crys ta lliza tion po ints. New f (RH) curves are

recomm ended that are based on an amm onium sulfate D/D o “no solids” growth curve with a

m a ss size distribution correspondin g to those m a ss size distributio ns discussed above. The “ n o solids” curv e extends th e D/D o curv e to re lative hum i dity v a lues be low the am m o nium sulf ate crysta lliza t ion point. However, there is littl e difference in the b i as between estim ated an d

m easured scattering for the case wh en f (RH) is assum e d to be 1 below the crys ta llization po int

com p ared to when continuous growth between 1 < RH < 90% is assum e d. Currently, organic

m a ss is not assum e d to be hygroscopic and no change is recomm ended in this assum p tion, although there is som e evidence that am bient orga nics m a y be very weakly hygroscopic at high RH values (RH > 85%). The for m of the extinction equation using m e thod 4, and including site-specific Rayleigh scattering and absorption by gaseous NO 2 , is

124

## [ ] [ ] [ ] [ [ ] [ ] [ ] [ ] [ ] [ ] [ ] 2 2 3 4 3 4 4 2 4 4 2 4

) ( 6

. 0 ) ( 4

. 1 1 10 arg 1

. 6 8

. 2 arg ) ( 1

. 5 ) ( 4

. 2 ) ( arg ) ( 8

. 4 ) ( ) ( 2

. 2

NO EE Specific Site Scattering Rayleigh Mass Coarse Salt Sea RH f Soil Fine Carbon

Elemental POM e L POM Small NO NH e L RH f NO NH Small RH f SO NH e L RH f SO NH Small RH f b

NO SS L S L S ext

× + + × + × × + × + × + × + × + × × + × × + 

## ] × × + × × ≈

(27)

The apportionm e nt of the total concen trations of a mmonium sulfate ((NH 4 ) 2 SO 4 ) into the concentratio ns of the s m all and large size fr actions is accom plishe d using the following equation s : 

## [ ] [ ] [ ] 4 2 4 4 2 4 4 2 4 ) ( 20 ) ( ) ( arg SO NH Total SO NH Total SO NH e L × = (28) 

## [ ] [ ] [ ] 4 2 4 4 2 4 4 2 4 ) ( arg ) ( ) ( SO NH e L SO NH Total SO NH Small

− = (29)
Sim ilar equ a tions are u s ed to appo r tion to ta l a m m onium nitr ate (NH 4 NO 3 ) and to tal p a rticulate organic m a terial (POM = 1.8· OC) concentratio n s into th e sm all and larg e size f r ac tio ns.

125REFE RE NCES Ada m , M., M. Pahlow, V. A. Kovalev, J. M. O ndov, M. B. Parlange, and N. Nair, T h e Baltim ore Supersite experim e nt during the C a nadi an forest fi re smoke i n trusi o n, J. Geophys. Res., 109(D16), doi:10.1029/2003JD004047, 2004. A l f a r o , S

. C

. , L

. G o m e s , J

. L

. R a j o t , S

. L a f on, A. Gaudichet, B. Chatenet, M. Maille, G. Cautenet, F. Lasserre, H

. Cachier, and X. Y. Zhang, Chem ical and op tical characterization of aerosols m e asured in spring 2002 at the AC E-Asia supersite, Zhenbeitai, China, J. Geophys. Res., 108(D23) , 8641, doi:10.1029/2002JD003214, 2003. A m e s , R

. B

. , J

. L

. H a n d , S

. M

. K r e i d e n w e i s , D

. E

. D a y , a n d W

. C

. M a l m , O p t i c a l m e a s u r e m e n t s of aerosol size distributi ons in Great Smoky Mountains National Park: dry aerosol characterization, J. Air Waste Manage., 50 , 665-676, May 2000. Anderson, T. L., R. J. Charlson, W. H. Wh ite, and P. H. McMurry, Comm ent on: Light scattering and cloud condensation nucleus activ ity of sulfate aerosol m easured over the northeas t Atlantic Ocean , J. Geophys. Res., 99, 25947-25949, 1994. Andrews, E., and S. M. Larson, Effect of su r f actant lay e rs on the size changes of aerosol particle s as a f unction of rela tive hu m i dity, Environ. Sci. Technol., 27, 857-865, 1993. Andrews, E., P. Saxena, S. Musarra, L. M. Hildem ann, P. Koutrak i s, P. H. McMurry, I. Olm e z, and W

. H. White, Concentration and com pos ition of atmospheric aerosols from the 1995 SEAVS experim e nt and a review of the cl osure between chemical and g r avim etric m easurem ents, J. Air Waste Manage., 50, 648-664, May 2000. A r n o t t , W

. P

. , H

. M o o s m u l l e r , P

. J

. S h e r i d a n , J

. A

. O g r e n , R

. R a s p e t , W

. V

. S l a t o n , J

. L

. H a n d , S. M. Kreid e nweis, and J. L. Colle tt, Jr., Photoacoustic and filter-bas ed ambient aero sol light absorption m easurem ents: Instrum e nt com p ar isons and the role of relative hum idity, J. Geophys. Res ., 108(D1) , 4034, doi:10.1029/2002JD002165, 2003. Ashbaugh, L. L., and R. A. Eldred, Loss of partic le nitrate from Teflon sam p ling filters : Effects on m easured gravim etric m a ss in Calif ornia and in the IMPROVE network, J. Air Was t e Manage., 54, 93-104, January 2004. Ashbaugh, L. L., C. E. McDade, W. H. W h ite, P. W a kabayashi, J. L. C o llett, Jr., and X.-Y. Yu, Efficiency of IMPROVE network denuders fo r rem oving nitric acid, Paper # 32, A& W M A Specialty co nference: R e gional and Global Pers pectiv es on Haze: Causes, Consequences and Controversies, Asheville, NC, October 25-29, 2004. Bohren, C. F., and D. R. Huffman, Absorption and Scattering of Light by Sma ll Particles , W iley Interscience, New York, 1983. Brooks, S. D., P. J. DeMott, and S. M. Kreide nweis, W a ter uptake by particles containing hum ic m a terials and m i xtures of hum i c m a teria l s with a m m onium sulf ate, A t mos. Environ., 38, 1859- 1868, 2004.

126Busch, B., C. Sprengard-Eichel, K. Kandler, an d L. Schültz, Hygroscopic properties and water soluble fraction of atm o spheric particles in the d i am eter rang efrom 50 nm to 3.8 μ m during the Aerosol Characterization Expe rim e nt in Lindenberg 1998, J. Aerosol Sci., 30(S1), S513- S514, 1999. Cabada, J. C., S. Rees , S. Takaham a , A. Khl y stov, S. Pandis, C. I. Davidson, and A. L. Robinson, Mass size distributions and size resolv ed chem ical com position of fine particulate m a tter at th e Pittsbu rgh s upersite, Atmos. Environ., 38, 3127-3141, 2004. Carrico, C. M., M. J. Rood, J. A. Ogren, C. Neusüß, A. W i edensohler, and J. Heintzenberg, Aerosol optical prop erties at Sagres, Portugal, during ACE-2, Tellus, 52B, 694-715, 2000. Carrico, C. M., M. H. Bergin, J. Xu, K. Baum ann, and H. Maring, Ur ban aerosol radiative properties: Measurem ents during th e 1999 Atlanta Supersite Experim e nt, J. Geophys. Res., 108(D7) , 8422, doi:10.1029/2001JD001222, 2003. C a r r i c o , C

. M

. , S

. M

. K r e i d e n w e i s , W

. C

. M a l m , D

. E

. D a y , T

. L e e , J

. C a r r i l l o , G

. R

. McMeeking, and J. L. Collett, Jr., Hygros copic growth behavior of a carbon-dom i nated aerosol in Yosem ite National Park, A t mos. Enviro n., 39 , 1393-1404, 2005. Chan, M.-N., and C. K. Chan, Hygroscopic proper ties of two m odel hum ic-lik e substances an d their m i xtures with inorganics of atmospheric importance, Environ. Sci. Technol., 37, 5109- 5115, 2003. Chen, L.- W

. A., J. C. Chow, B. G. Doddridge, R. R. Dickerson, W

. F. Ryan, and P. K. Mueller, Analysis of a summ ertim e PM 2. 5 and haze ep isode in th e Mid-Atlantic region, J. Air Was t e Manage., 53 , 946-956, Aug 2003. Chiapello, I., G. Bergam etti, B. Chatenet, F. Du lac, I. Jankowiak, C. Liousse, and E. Santos Soares, Contribution of the differe nt aerosol species to the aeros ol m a ss load and optical depth over the no rtheastern tro p ical Atlantic, J. Geophys. Res, 104(D4) , 4025-4035, 1999. Chow, J. C., J. G. W a tson, L. C. Pritchett, W

. R. Pierson, C. A. Frazier, and R. G. Purcell, The DRI thermal/optical reflectance carbon analys is system : Description, evaluation and applic ation s in U.S. air q u ality stud ie s, Atmos. Env., 27A(8 ) , 1185-1201, 1993. Chow, J. C., J. G. W a tson, D. H. Lowenthal, an d L. W

. Richards, Comparability between PM 2. 5 and particle light scattering m easurem ents, Environ. Mon. Assess. 79, 29-45, 2002. Chu, S.-H., PM 2. 5 episodes as observed in th e speciation trends network, Atmos. Environ., 38, 5237-5246, 2004. Clegg S.L., P. Brim ble c om be, and A.S. W e xl er, A therm odynam i c model of the system H+- NH4+-SO4 2 --NO3--H2O at tropospheric tem p eratures, J. of Phys. Chem., 102A , 2137-2154, 1998a.

127Clegg S.L., P. Brim ble c om be, and A.S. W e xl er, A therm odynam i c model of the system H+- NH4+-Na+-SO42—NO3—Cl—H2O at 298.15 K, J. of Phys. Chem., 102A , 2155-2171, 1998b. Cocker, D. R., N. E. W h itlock, R. C. Flagan, and J. H. Seinf e ld, Hygroscopic properties o f Pasadena, California aerosol, Aeroso l Sci. Techn o l., 35, 637-647, 2001. Countess, R. J., G. T. Wolff, and S. H. Ca dle, The Denver winter aerosol: A comprehensive chem ical characterizatio n, J. Air Pollution Control Assoc., 30, 1194-1200, 1980. Day, D. E., W. C. Mal m , and S. M. Kreidenweis, Seasonal variations in aerosol com position and acidity at Shenandoah and Great Smoky Mountains national parks, J. Air Waste Manage., 47, 411-418, March 1997. Day, D. E., W

. C. Malm, and S. M. Kreidenwei s, Aeros o l light scattering m easurem ents as a function of relative hum idity, J. Air Waste Manage., 50, 710-716, May 2000. Day, D. E. and W

. C. Malm , Aerosol ligh t sc attering m easurem ents as a function of relative hum i dity: a com p arison between m easurem en ts m a de at thre e dif f e rent s ites, Atmos. Environ., 35, 5169-5176, 2001. Dick, W

. D. , P. Saxena, and P. H. McMurry, Estim a tion of water upta ke by organic com pounds in subm icron aerosols m easured during the S outheastern Aerosol and Visibility Study, J. Geophys. Res., 105(D1) , 1471-1479, 2000. Dixon, J. K, The absorption coefficient of nitrogen dioxide in the visible spectrum, J. Chem. Phys., 8(2) , 157-160, 1940. Eldering, A., J. A. Ogren, Z. Chowdhury, L. S. Hughes, and G. R. Cass, Aerosol optical properties d u ring INDOEX based on m easured aeroso l particle size and com p osition, J. Geophys. Res.,107(D22) , 8001, doi:10.1029/2001JD001572, 2002. El-Zanan, H. S., D. H. L o wenthal, B. Zielinska, J. C. Chow, and N. Kuma r, Determ ination of the organic aerosol m a ss to organic ca rbon ratio in IMPROVE s a m p les, Chemosphere, 60(4) , 485- 496, July 2005. Ferron, G. A., E. Karg, B. Busch, and J. He yder, Hygroscopicity of am bient p a r tic les, J. Aeros o l Sci. 30(S1) , S19-S20, 1999 Form enti P., W

. Elbert, W. Maenhaut, J. Haywood, S. Osborne, and M. O. Andreae, Inorgan i c and carbonaceous aerosols during the South Af rican Regional Scienc e Initiative (SAFARI 2000) experim e nt: Che m ical characteristics, phys ical properties, and em ission data for s m oke from Afr i can biom ass burning, J. Geophys. Res. , 108(D13) , 8488, doi:10.1029/2002JD002408, 2003. Frank, N. H., Retained nitrate, hydrated su lfate and carbon aceous m a ss in Federal Reference Method PM2.5 for six eastern U.S. cities, Submitted to J. A i r Waste Manage., 2005.

128Fridlind, A. M., and M. Z. Jacobson, Point and colum n aerosol radiative closure during ACE 1: Effects of article shape and size, J. Geophys. Res., 108(D3) , 4094, doi:10.1029/2001JD001553, 2003. Fuller, K. A., W

. C. Malm , and S. M. Kr eidenweis, E ffects of mixing on extinction by carbonaceous particles, J. Geophys. Res., 104, 15941-15954, 1999. Gao, S., M. Keywood, N. L. Ng, J. Surratt, V. Varu tbangkul, R. Bahreini, R. C. F l agan, and J. H. Seinfeld, L o w- m o lecular-weight and oligom eric com ponents in secondary organic aerosol from the ozonolysis of cycloalkenes and α -p in ene, J. Phys. Chem. A., 108, 10147-10164, 2004. Gasparini, R., R. Li, and D. R. Collins, Integr ation of size dis t r i butions and size -re solv ed hygroscopicity m easured during the Houston Su pe rsite for com positional categorization of the aerosol, A t mos. Environ., 38, 3285-3303, 2004. Gebhart, K. A., W. C. Malm , and D. E. Day, Exam ination of the effects of sulfate acidity and relative hum i dity on light scattering at Shenandoah National Park, Atmos. Environ., 28(5), 841-849, 1994. Gelencsér, A., A. Ho ffe r, A. Molnár, Z. Krivács y, Gy. Kiss, E. Mészáros, Therm a l behaviour of carbonaceous aerosol from a continental background site, A t mos. Env., 34, 823-831, 2000. Grosjean, D ., and S. K. Friedlander, Gas-partic le distribution factors f o r organics and other pollutants in the Los Angeles atmosphere, J. Air Pollution Control Assoc., 25, 1038-1044, 1975. Guyon, P., B. Graham , G. C. Roberts, O. L. Ma yol-Bracero, W

. Maenhaut, P. Artaxo, and M. O. Andreae, In -canopy grad ients, com p osition, sources , and op tical p r operties of aeroso l over th e Am azon for e st, J. Geophys. Res. , 108(D18) , 4591, doi:10.1029/2003JD003465, 2003. Gysel, M., E. W e ingartner, S. Nyeki, D. Paulse n, U. Baltensperger, I. Galam bos, a nd G. Kiss, Hygroscopic properties of wate r-soluble m a tter and hum ic-like or ganics in atm o spheric fine aerosol, A t mos. Chem. Phys., 4, 35-50, 2004. Hand, J. L. , A new technique for obtaining aerosol s i ze distr i butio ns with applica tions to estim ates of aerosol properties, Ph.D. Di ssertation, Colorado State University, 2001. Hand, J. L., and S. M. Kreidenweis, A new m e thod for retrieving particle refractive index and effective density from aeros ol size distribution data, Aerosol Sci. Technol., 36, 1012-1026, 2002. Hand, J. L., R. B. Am e s , S. M. Kreidenweis, D. E. Day and W

. C. Malm , Estim ates of partic le hygroscopicity during the Southeaste rn Aerosol and Visibility Study, J. Air Waste Manage., 50, 677-685, May 2000.

129H a n d , J

. L

. , S

. M

. K r e i d e n w e i s , D

. E

. S h e r m a n , J

. L

. C o l l e t t , J r
. , S

. V

. H e r i n g , D

. E

. D a y , W

. C

. Malm , Aerosol size distributions and visibi lity estim a tes during the Big Bend Regional Aerosol Visibility and O b servational Study (BRAVO), Atmo s. Environ., 36 , 5043-5055, 2002. Hand, J. L., N. M. Mahowald, Y. Chen, R. L. Si efert, C. Luo, A. Subram ania m , and I. Fung, Estim ates o f atm o spheric-pro cess e d solub l e iron from obs ervations and a global m i neral aerosol m odel: Bio g eochem ical im plications, J. Geophys. Res., 109(D17205) , doi:10.1029/2004JD004574, 2004. H a n d J

. L

. , W

. C

. M a l m , D

. E

. D a y , T

. L e e , C

. C a rrico, J. Ca rrillo, J. L. Co llett, Jr., A. Laskin, C. Wang, J. P. Cowin, M. J. Iedem a , Optical, physi cal and chem ical properties of tar balls during the Yosem ite Aerosol Characterization Study, J. Geophys. Res

. , 110(D21), doi:10.1029/2004JD005728, 2005. Hansson, H.-C., M. J. Rood, S. Koloutsou-Vakaki s, K. Hä m e ri, D. Orsini, and A. W i edensholer, NaCl aerosol particle hygr oscopicity dependence on m i xing with organic com p ounds, J. Atmos. Chem., 31, 321-346, 1998. Hasan, H. a nd T. G. Dz ubay, Apportioning light ex tinction coefficients to chem ical species in the atm o spheric aeroso l , Atmos. Environ., 17, 1573-1581, 1983. Hegg, D. A., R. J. Ferek, and P. V. Hobbs, Ae rosol size distributions in the cloudy atmospheric boundary layer of the North Atlantic Ocean, J. Geophys. Res., 98(D5), 8841-8846, 1993. Hering, S., and G. Cass, The m a gnitude of bias in the m easurem ent of PM 2. 5 arising from volatilizatio n of particu l ate nitra t e f r om Tef l on f ilte rs, J. A i r Waste Manage., 49, 725-733, June 1999. Hering, S. V. and S. K. Friedlander, Origins of aerosol sulfur size distributions in the Los Angeles Basin, Atmos. Environ., 16(11) , 2647-2656, 1982. Hering, S., A. Eldering, and J. H. Seinfeld, Bimodal character of accu mulation m ode aero s ol m a ss distrib u tions in sou t hern California, Atmos. Environ., 31(1 ) , 1-11, 1997. Hodkinson, J. R., Calculations of color and visi bility in urban atm o s pheres polluted by gaseous NO2, Air Water Pollut., 10(2) , 137-144, 1966. Hogrefe O., J. J. Schwab , F. Drewnick, G. G. Lala , S. Peters, K. J. Dem e rjian, K. Rhoads, H. D. Felton, O. V. Rattigan, L. Husain, a nd V. A. Dutkiewicz, Sem i continuous PM 2. 5 sulfate and nitrate m easurem ents at an urban and rura l loc a tion in Ne w York: PMTACS-NY sum m er 2001 and 2002 cam paigns, J. Air Waste Manage., 54, 1040-1060, September 2004. Huebert, B. J., and R. J. Charlson, Un certain ties in data on organic a e rosols, Tellus, 52B(5 ), 1249-1255, 2000. Im , J.-S., V. K. Saxena , and B. N. W e nny, An assessm ent of hygroscopic growth factors for aerosols in the surface b oundary lay e r for com p uting direct radiative forcing, J. Geo phys. Res., 106(D17) , 20213-20224, 2001

130Jaffe, D., J. Snow, and O. Cooper, The April 2 001 Asian dust events: Tr ansport and substantial im pact on surface particulate m a tter con centration s across th e United States, Eos, Transactions , Nove m b er 18, 2003. Jaffe, D., S. Tam u ra, and J. Harris, S easonal cy cle and com position of ba ckground fine particles long the west coast of the U.S., Atmos. Environ., 39, 297-306, 2005. J a p a r , S

. M

. , A

. C

. S z k a r l a t , R

. A

. G o r s e , J r
. , E

. K

. Heyerdahl, R. L. Johnson, J. A. Rau, and J. J. Huntzicker, Com p arison of solvent extraction and therm a l optical carbon analysis m e thods: Application to diesel vehicle exhaust aerosol, Environ. Sci. Techonol., 18, 231-234, 1984. John, W ., S. M. W a ll, J. L. Ondo, and W

. Winklm a yr, Modes in the size distributions of atm o spheric inorganic aerosol, A t mos. Environ., 24A(9) , 2349-2359, 1990. Ki m , Y, P., J. H. Seinfeld, P. Saxena, Atm o s pheric gas-aerosol equili brium 2. Analysis of common approxim a tions and activity -coefficient calculation m e thods, Ae rosol Sci. Technol., 19(2) , 182-198, 1993. Koloutsou-Vakakis, S., C. M. Carrico, P. Kus, M. J. Rood, Z. Li, R. Shrestha, J. A. Ogren, J. C. Chow, and J. G. W a tson, Aerosol properties at a m i dlatitude Northern Hem i sphere continental site, J. Geophys. Res., 106(D3) , 3019-3032, 2001. Kreisberg, N. M., M. R. Stolzenb u rg, S. V. Hering, W

. D. Dick, and P. H. Mc Murry, A new m e thod for m easuring the dependence of particle size distributions on relative hum idity, with the application to the Southeaste rn Aerosol and Visibility S t udy, J. Geophys. Res., 106(D14), 14935-14949, 2001. Lee, T., S. M. Kreid e n w eis, and J. L. Collett, Jr., Aerosol io n characteris tics during the Big Bend Regional A e rosol and Visibi lity O b servational Study, J. Air Waste Manage., 54, 585-592, May 2004a. Lee, T., X-Y. Yu, B. Ayres, J. Carr illo, C. Carrico, P. Herckes, G. R. McMeeking, G. Engling, S. M. Kreiden w eis, J. L. Collett, Jr., D. E. Da y, and W

. C. Malm , Characteris tics o f aerosol nitr ate a t se veral IMPROVE m onitoring sites, Paper # 38, A& W M A Specialty co nference: Regional and Global Perspectives on Haze: Ca uses, Consequences and Controversies , Asheville, NC, October 25-29, 2004b. Lefer, B. L., and R. W

. Talbot, Summ erti m e m e as urem ents of aerosol n i trate and am monium at a northeas te rn U.S. site, J. Geophys. Res., 106(D17), 20365-20378, 2001. Li, S-M., J. Tang, H. Xue, and D. Toom -Sa untry, Size distribution and estim a ted optical properties of carbonate, water solubl e organic carbon, and sulfate in aerosols at a remote high altitude s ite in western C h ina, Geophys. Res. Letts., 27(8) , 1107-1110, 2000. Li, X., H. Maring, D. Savoie, K. Vos s , and J. M. Prospero, Dom i nance of m i neral dust in aerosol light-scattering in the North Atlantic trade winds, Nature, 380, 416-419, 1996.

131Lightstone, J. M., T. B. Onasch, D. Im re, and S. Oatis, Deliquescence, efflorescence, and water activ ity in a m m onium nitr ate and m i xed am m o nium nitrate / succ inic ac id m i croparticle s, J. Phys. Chem. A., 104, 9337-9346, 2000. Liu L.-J. S., R. Burton, W. E. W ilson, and P. Ko utrakis, Comparison of aerosol acidity in urban and sem i -rural environments, Atmos. Environ., 30(8 ) , 1237-1245, 1996. Lowenthal, D. H., C. F. Rogers, P. Saxena, J. G. W a ts on, and J. C. Chow, Sensitivity of estim ated light extinctio n coefficients to m odel assum p tions and m easurem ent errors, Atmos. Environ., 29, 751-766, 1995. Lowenthal, D. H., J. G. W a tson, P. Saxena, Contributions to light extinction during project MOHAVE, Atmos. Environ., 34, 2351-2359, 2000. Lowenthal, D. H., and N. Ku m a r, PM 2. 5 and light extinction r econstruction in IMP R OVE, J. Air Waste Manage., 53, 1109-1120, Septem ber 2003. Lowenthal, D. H., and N. Ku mar, Variation of m a ss scatte ring efficien cies in IMP R OVE, J. Air Waste Manage., 54, 926-934, August 2004. Lowenthal, D. H., and N. Ku m a r, Light s cattering from sea salt aerosols in IMPROVE, Prepared for submission to J. Air Waste Manage., 2005. Malm , W

. C. and D. E. Day, Optical propert ies of aerosols at Grand Canyon National Park, Atmos. Environ., 34, 3373-3391, 2000. Malm W.C. and D. E. Day, Estim ates of aerosol species s cattering characteristics as a function of rela tive hum idity, A t mos. Environ., 3 5 , 2845-2860, 2001. Malm , W. C. and S. M. Kreide nweis, The effects of m o dels of aerosol hygroscopicity on the apportionm e n t of extinction, Atmos. Environ., 31(13) , 1965-1976, 1997. Malm W

. C. and M. Pitchford, Com p arison of calculated sulfate s cattering efficiencies as estim ated from size-resolved particle m easurem ents at three nation al locations , Atmos. Environ., 31(9) , 1315-1325, 1997 Malm , W

. C., K. A. Gebhart, J. Molenar, T. C a hill, R. Eldred, and D. Huffm an, Exam ining the relationship between atmospheric aerosols and light extin ction at Mou n t Rainie r a nd North Cascades National Park s, Atmos. Environ., 28(2), 347-360, 1994a. Malm , W. C., J. F. Sisler, D. Huffm a n, R. A. Eldred, and T. A. Cahi ll, Spatial and seasonal trends in pa rticle con c e n tra tion and optica l extinction in th e United States, J. Geo phys. Res., 99(D1), 1347-1370, 1994b. Malm , W

. C., D. E. Day, and S. M. Kreidenweis, Light scattering characteri stics of aerosols as a function of relative hum i dity: Part 1: A comp arison of m easured scattering an d aeroso l concentrations using th e theore tic al m odels, J. Air Waste Manage., 50, 686-700, 2000

132M a l m W

. C

. , D

. E

. D a y , S

. M

. Kreidenweis, J. L. Collett, Jr., and T. L ee, Hum i dity dependent optical properties of fine particles during the Big Bend Re gional A e rosol and Visibility Observational study (BRAVO), J. Geophys. Res. 108(D9), 4279, doi:10.1029/2002JD002998, 2003. Malm W

. C., D. E. Day, C. Carrico, S. M. Kreidenw eis, J. L. Collett, Jr., G. McMeek ing, T. Lee, and J. Carr illo, Inte r-c om parison and closur e calculation s using m e asurem ents of aerosol species and optical propertie s during the Y o sem ite Aero sol Characterization Study, J. Geophys. Res., 110(D14), Art. No. D14302, July 19, 2005a. M a l m , W

. C

. , D

. E

. D a y , S

. M

. K r e i d e n w e i s , J

. L

. C o l l e t t , J r
. , C

. C a r r i c o , G

. M c M e e k i n g , a n d T

. Lee, Hygroscopic properties of an organic-laden aerosol , A t mos. Environ. , 39(27) , 4969-4982, Septem ber 2005b. Martins, J. V., P. Artaxo, P. V. Hobbs, C. Liou sse, H. Ca chier, Y. J. Kaufm a n, a nd A. PlanaFattori, Particle size distributions, elem enta l compositions, carbon m easurem ents, and optical properties of s m oke from biom ass burning in th e Pacific Northwest o f the United States, in : Global Biomass Burning and Global Change, edited by Levine, J. S., pp. 716-732, MIT Press, Ca m b ridge, 1996. Mayol-Bracero, O. L., P. Guyon, B. Graham , G. Roberts, M. O. Andreae, S. Desesari, M. C. Facchini, S. Fuzzi, and P. Artaxo, W a ter-solu b le o r ganic com pounds in b i om ass burning aerosols over Am azonia 2. Apportio nm ent of the chem ical composition and im portance of the polyacid i c fraction, J. Geophys. Res., 107(D20), 8091, doi:10.1029/2001JD000522, 2002. McDade, C. E., R. A. Eldred, and L

. L. Ashba u gh, Artif ac t corre ction s in IMPROVE, Paper # 15, A& W M A Specialty conference: Regional and Global Perspectiv es on Haze: Causes, Consequences and Controversies, Asheville, NC, October 25-29, 2004. M c M e e k i n g G

. R

. , S

. M

. K r e i d e n w e i s , C

. C a r r i c o , T

. L e e , J

. L

. C o l l e t t , J r
. , a n d W

. C

. M a l m , Observations of s m oke -influenced aerosol du ring the Yosem ite Aerosol Charac teriz a tio n Study: Size distributions and chem ical composition, J. Geophys. Res., 110(D09), doi:10.1029/2004JD005389, 2005. McMurry, P

. H., X. Zhang, and C.-T. Lee, Issues in aerosol m easurem ents for optics assessm ent, J. Geophys. Res., 101, 19189-19197, 1996. McMurry, P

. H., X. W a ng, K. Park, and K. Ehara, The re lationship be tween m a ss and m obility for atm o spheric p a rtic le s: A new tec hni que for m easuring particle density, Aerosol Sci. Technol., 36, 227-238, 2002. Meng Z., and J. H. Seinfeld, On the source of the subm icr o m e ter d r op let m ode of urban and regional aerosols, Aerosol Sci. Technol., 20, 253-265, 1994. Mie, G., Beitraege zur optic trueber m e di en, spe z iell kolloidaler m e talosungen, Ann. Physik, 25 , 377-445, 1908.

133Mikhilov, E ., S. Vlasenko, R. Niesner, and U. Pö schl, Interaction of aeros ol particles com pose d of protein and salts with water vapor: hygrosco pic growth and m i crostructural rearrangem e nt, Atmos. Chem. Phys., 4, 323-350, 2004. Nenes A., S. N. Pandis, C. Pilinis, ISORROPI A: A new therm odyna m i c equilib rium m odel for m u ltiphase m u lticom ponent ino r gan i c ae rosols, Aqua. Geochem., 4, 123-152, 1998. Neusüß, C., H. W e x, W

. Bir m ili, A. W i edensohl er, C. Kozier, B. Busch, E. Brüggem a nn, T. Gnauk, M. Ebert, and D. S. Cover t , Charact erization and param e teri zation of atmospheric particle nu mber-, m a ss-, and chem ical-size dis t ribu tions in centr al Eu rope during LACE 98 and MINT, J. Geophys. Res., 107(D21) , 8127, doi:10.1029/2001JD000514, 2002. Novakov, T., and C. E. Corrigan, Therm a l characterization of biom ass s m oke particles, Mikroch i m. Acta., 119, 157-166, 1995. Om ar, A. H., S. Biegalski, S. M. Larson, S. Landsberger, Particulate contributions to light extinction and local forcing at a rura l Illinois s i te, Atmos. Environ., 33, 2637-2646, 1999. Peng, C., M.-N. Chan, and C. K. Chan, Th e hygroscopic properties of dicarboxylic and m u ltif unctio nal a c ids : Measurem ents and UNIFAC predictions, Environ. Sci. Technol., 35, 4495-4501, 2001. Penner, J. E ., R. J. Charlson, J. M. Hales, N. La ulainen, R. Leifer, T. Novakov, J. Ogren, L. F. Radke, S. E. Schwarz, and L. Travis, Quanti fying and m i nim i zing uncertainty of clim ate forcing by anthropogenic aerosols, B u ll. Am. Met. Soc., 75, 375-400, 1993. Perry, K. D., T. A. Ca hill, R. A. Eldred, and D. D. Dutcher, Long-range transp ort of North Af rican dust to the e a ste r n United Sta t es, J. Geophys. Res., 102(D10), 11225-11238, 1997. Pilin is, C., S. N. Pandis, and J. H. Seinf e ld, Sen s itiv ity of direct c lim ate f o rcing by atm o spheric aerosols to aerosol size and com position, J. Geophys. Res.,100, 18739-18754, 1995. Poirot, R. L., and R. B.Husar, Chem ical and physical characteristics of wood sm oke in the northeastern U.S. during July 2002: Im pacts fr om Quebec forest fires, Paper # 94, A& W M A Specialty co nference: R e gional and Global Pers pectiv es on Haze: Causes, Consequences and Controversies, Asheville, NC, October 25-29, 2004. Prenni, A. J., P. J. DeM o tt, and S. M. Kreidenw eis, W a ter uptake of interna lly m i xed particle s containing ammonium s u lfate and dicarboxylic acids, Atmos. Environ., 37, 4243-4251, 2003. Quinn, P. K., D. J. Coffm an, V. N. Kapustin, T. S. Bates, and D. S. Covert, Aerosol optical properties in the m a rine boundary layer during th e First Aerosol Characterization Experim e nt (ACE 1) and the underlying chem i cal and physical aero sol properties, J. Geophys. Res., 103(D13), 16547-16563, 1998. Quinn, P. K. , D. J. Coffm an, T. S. Bates, T. L. Miller, J. E. Johnson, K. Voss, E. J. Welton, and C. Neususs, Dom i nant aerosol chem ical co m p onents and their contribution to extinction

134during the Aerosols99 cruise across the Atlantic, J. Geophys. Res., 106(D18) , 20783-20809, 2001. Quinn, P.K., T. L. Miller , T. S. Bates, J. A. Og ren, E. Andrews, and G. E. Shaw, A 3-year recor d of sim u ltaneously m easured aeroso l chem ical and optical properties at Barrow, Alaska, J. Geophys. Res., 107(D11), 4130, 10:1029/2001JD001248, 2002a. Quinn, P. K., D. J. Coffm a n, T. S. Bates, T. L. Miller, J. E

. Johnson, E. J. W e lton, C. Neususs , M. Miller, and P. J. S h eridan, Aerosol opt ical properties during INDOEX 199 9: Means, variability, and cont rolling f actors, J. Geophys. R e s., 107(D19) , 8020, doi:10.1029/2000JD000037, 2002b. Quinn, P. K., D. J. Coffm an, T. S. Bates, E. J. W e lton, D. S. Covert, T. L. Miller, J

. E. Johnson, S. Maria, L. Russell, R. Arim oto, C. M. Carrico , M. J. Rood, and J. Anderson, Aerosol optical properties measured on board the R onald H. Brown during ACE-Asia as a function of aerosol chem ical com position and source region, J. Geophys. Res., 109(D19) , doi:10.1029/2003JD004010, 2004. Radke, L., D. A. Hegg, J. H. Lyons, C. A. Brock, P. V. Hobbs, R. Weiss, R. Rassm ussen, Airborne measurem ents on s m okes from biom a ss burning, in Aerosols and Climate , edited by P. V. Hobbs and M. P. McCorm ick, pp. 411-422, Deepak Publishing, Hampton VA, 1988. Radke, L. F. , D. A. Hegg, P. V. Hobbs, J. D. Na n ce, J. H. Lyons, K. K. Laursen, R. E. W e iss, P. J. Riggan, and D. E. Ward, Part iculate and trace e m issions from large biom ass fires in North Am erica, in : Global Biomass Burning: Atmospheric, Climatic and Biosphe ric Implications, edited by J. S. Levine, pp. 209-224, MIT Press, Ca m b ridge MA, 1991. Reid, J. S., and P. V.Hobbs, Physical and opti cal properties of sm oke from individual biom ass f i res in Bra z il, J. Geophys. Res., 103, 32013-32031, 1998. Reid, J. S., R. Koppmann, T. F. Eck, and D

. P. Eleuterio, A revi ew of biom a ss burning em issions, Part II: Intensive physical properties of biom ass burning particles, At mo s
. Ch e m
. Phys. , 5, 799-825, 2005. Rees, S. L., A. L. Robinson, A. Khlystov, C. O. Stanier, and S. N. Pandis, Mass balance closu r e and the Federal Reference Method for PM 2. 5 in Pittsbu rgh, Pennsylvania, Atmos. Environ., 38, 3305-3318, 2004. Rivera-Carpio C. A., C. E. Corriga n, T. Novakov, J. E. Penner, C. F. Rogers, and J. C. Chow, Derivation of contributions of sulfate and carbonaceous aerosols to cloud condensation nuclei from m a ss size distributions, J. Geophys. Res., 101(D14), 19483-19493, 1996. Rogge, W

. F., M. Mazurek, L. M. Hildem ann, a nd G. R. Cass, Quantification of urban organic aerosols at a m o lecular leve l: Indentification, abundan ce and seasonal variation, Atmos. Environ., 27, 1309-1330, 1993. Russell, L. M., Aerosol organic

- m a ss-to-org anic- carbon ratio m easurem ents, Environ. Sci

. Technol., 37, 2982-2987, 2003.

135Santarp i a, J. L., R. Li, a nd D. R. Collins, Dire ct m easurem ent of the hyd ration state of am bient aerosol populations, J. Geophys. Res., 109(D18), Art. No. D18209, Septem ber 29, 2004. Santarp i a, J. L., R. Gasparin i, R. Li, and D. R. Collins, Diurnal v a riations in the h ygroscopic growth cycles of am bient aerosol populations, J. Geophys. Res., 110, doi:10.1029/2004JD005279, 2005. Saxena, P., L. M. Hildem ann, P. H. McMurry, a nd J. H. Seinfeld, Organics alter hygroscopic behavior of atm o spheric particles, J. Geophys. Res., 100(D9) , 18755-18770, 1995. Schwab, J. J., H. D. Felton, and K. L. De m e r jian, Aerosol chem ical composition in New York state from integrated filter sam p les: Urban/ru ral and seaso n al con t rasts, J. Geoph ys. Res., 109(D16), doi:10.1029/2003JD004078, 2004. Seinfeld, J. H., and S. N. Pandis, Atmospheric Chemistry and Phys ics: From Air Pollution to Climate Change, John Wiley, New York, pp 444, 1998. Sheridan, P

. J., D. J. Delene, and J. A. Og ren, Four years of c ontinuous surface aerosol m easure m ents from the Departm e nt of En ergy’s Atm o s pheric Radiation Measurem ent Program Southern Great Plains Cl oud and Radiation Testbed site, J. Geophys. Res., 106(D18), 20735-20747, 2001. Siefert, R. L., A. M. Johansen, and M. R. Hoff m a n, Chem i cal characteri zation of ambient aero s ol collected during the so uthwest m o nsoon and interm onsoon seasons over the Arabian Sea: Labile-Fe(II) and other trace m e tals, J. Geophys. Res., 104(D3) , 3511-3526, 1999. Sisler, J. F. and W

. C. Malm , The relative im por tance of soluble aerosols to spatial a nd seasonal trends of im pared vis i bility in the Un ited States, Atmos. Environ., 28(5) , 851-862, 1994. Sloane, C. S., Optical properties of aerosols- com p arisons of m e asurem ents with m odel calcu lations, Atmos. Environ., 17, 409-416, 1983. Sloane, C. S., Effect of com position on aeros o l light scattering efficiencies, Atm o s. Environ., 20(5) , 1025- 1037, 1986. Sloane, C. S., J. W a tson, J. Chow, L. Pritchett, L. W

. Ric h ards, Size se gregated fine particle m easurem ents by ch em i cal sp ecies and their imp act on the visibility im pairm e nt in Denver, Atmos. Environ., 25A(5/6) , 1013-1024, 1991. Stanier, C. O., A. Y. Khlystov, and S. N. Pa ndis, Am bient aerosol size distributions and num ber concentratio ns during th e Pittsbu rgh Air Quality Study (PAQS), Atmos. Environ., 38, 3275- 3284, 2004. Stith, J. L., L. F. Radke, and P. V. Hobbs, Pa rticulate em ission and th e production of ozone an d nitrogen oxides from the burning of forest slash, Atmos. Environ., 15, 73-82, 1981. Subram anian, R., A. Y. Khlystov, J. C. Cabda, and A. L. Robinson, Evaluation of measurem ent m e thods, Ae rosol Sci. and Technol., 38(S1) , 27-48, 2004.

136Tang, I. N., Che m ical and size effects of hygros copic aerosols on light scattering coefficients, J. Geophys. Res.,101(D14) , 19245-19250, 1996. Tang, I. N. , Therm odynam i c and optical proper ties of mixed-salt aer osols of atmospheric im portance, J. Geophys. Res.,102(D2), 1883-1893, 1997. Tang, I. N., and H. R. Munkelwit z, W a ter activities, de nsities, and refractiv e indices of aqueous sulfates and sodium nitrate d r opl ets of atm o spheric im portance, J. Geophys. Res., 99(D9), 18801-18808, 1994. Tanner, R. L., W

. J. Parkhurst, M. L. Valent e, and W

. D. Phillips, Regional com positio n of PM 2. 5 aerosols m e asured at urban, rural, and “background” sites in the Tennessee valley, Atmos. Environ., 38, 3143-3153, 2004. ten Brink, H. M., J. P. Veefki nd, A. W a ijers

- I jpe l aan, an d J. C. Van der Hag e , Aerosol ligh t scatter i ng in the Nethe r lands, Atmos. Environ., 30(24 ) , 4251- 4261, 1996. Turpin, B. J., and H.-J. Li m , Spec ies contributions to PM 2. 5 m a ss concentr ation s : Revisiting common assum p tions for estim a ting organic m a ss, Aerosol Sci. Technol., 35, 602-610, 2001. Turpin, B. J., P. Sa xena, G. Allen, P. Koutrakis, P. McMurry, and L. Hildem ann, Characterization of the southweste rn desert aerosol, Meadv i ew, AZ, J. Air Waste Manage., 47(3) , 344-356, March 1997. Turpin, B. J., P. Saxena, and E. Andrews, Meas uring and simulating partic ulate organics in the atm o sphere: Problem s and prospects, Atmos. Environ., 34, 2983-3013, 2000. VanCuren, R. A., Asian aeroso l s in North Am er ic a: Extra c ting the ch em ical com position and m a ss concentration of the Asian continental aero sol plum e from long-term aerosol records in the weste r n United Sta t es, J. Geophys. Res.,108(D20) , 4623, doi:10.1029/2003JD003459, 2003. VanCuren, R. A., and T. A. Cahill, Asian aeroso l s in North A m erica: Fre quency and concentration of fine dust, J. Geophys. Res., 107(D24) , 4804, doi:10.1029/2002JD002204, 2002. van de Hulst, H. C., Light Scattering by Small Pa rtic les , New York, Dover, 1981. Van Vaeck, L., and K

. Van Cau w enberghe, Cas cade impactor m easurem ents of the s i ze distribution of the m a jor classes of organic pollutants in atm o spheric particulate m a tter, Atmos. Environ., 12, 2239, 1978. Virkkula A., R. Van Dingenen, F. Raes, J. Hjorth, Hygroscopic pr operties of aerosol for m ed by oxidation of lim onene, alpha-p inen e, and b e ta-pinene, J. Geophys. R e s., 104, 3569-3579, 1999. W a ng, J., R. C. Flagan, J

. H. Seinf e ld, H. H. Jonsson, D. R. Collins, P. B. Russell, B. Schm id, J. Redem a nn, J. M. Livingston, S. Gao, D. A. He gg, E. J. W e lton, and D. Bates, Clear-colum n

137radia tive c l o s ure du ring ACE-Asia: Com p aris on of m u ltiwavelength extinction de rived f r om particle size and com p osition wi th results from Sun photometry, J. Geophys. Res., 107(D23) , 4688, doi:10.1029/2002JD002465, 2002. W h ite, W

. H., On the theoretical and em pirical basis for apportioning extin ction by aerosols: A cr it i c al r e vi ew, Atmos. Environ., 20, 1659-1672, 1986. White, W

. H., The components of atm o spheric light extinction: A survey of ground-level budgets, Atmos. Environ., 24A(10) , 2673-2679, 1990. White, W

. H., Contributions to light ex tinc t ion, In National Acid Precipitation Assessment Program (NAPAP) Repo rt 24 on Visibility , pp 24-85–24-102, 1991. White, W

. H., and P. T. Roberts, On the nature a nd origins of visibility-reducing aerosols in the Los Angels Air Basin, A t mos. Enviro n., 11, 803-812, 1977. White, W

. H., R. A. Eldred, P. J. F eeney, C. E. McDade, B

. P. Perley, D. J. Shadoan, and P. H. Wakabayashi, Behavior of fine -particle elem ental da ta n ear the dete ction lim it, Pa per # 24, A& W M A Specialty conference: Regional a nd Global Perspectives on Haze: Causes, Consequences and Controversies, Asheville, NC, October 25-29, 2004. Xu, J., M. H. Bergin, X. Yu, G. Liu, J. Zhao, C. M. Carrico, and K. Baum ann, Measurem ent of aerosol chem ical, physical and radiative prope rties in the Yangtze delta region of China, Atmos. Environ., 36, 161-173, 2002. Y u , X

. - Y

. , T

. L e e , B

. A y r e s , S

. M

. K r e i d e n w e i s , W

. C

. M a l m , a n d J

. L

. C o l l e t t , J r
. , P a r t i c u l a r nitrate m easurem ent using nylon filters, Submitted to Atmos. Environ., 2005a. Yu X.-Y., T. Lee, B. Ayres, S. M. Kreidenweis, W

. C. Malm , and J. L. C o lle tt, Jr., N e gativ e bias of a m m onium nitrate determ ination using nylon filters, Submitted to Atmos. Environ., 2005b. Zhang, X. Q., P. H. M c Murry, S. V. Hering, and G. S. Casuccio, Mixing characteristics and water content of subm i c ron aerosols m easured in Los Angeles and at the Grand Canyon, Atmos. Environ., 27A, 1593-1607, 1993. Zhang X., B. J. Turpin, P. H. McMurry, S. V. Hering, and M. R. Stolzenburg, Mie theory evaluation of species contributions to 1990 wi ntertim e visibility reduction in the Grand Canyon, J. Air Waste Manage., 44, 153-162, February 1994. Zhang, Q., M. R. Canagaratna, J. T

. Jayne, D. R. W o rsnop, and J.-L. Jim e nez, Tim e - and sizeresolved che m ical com p osition of subm icron pa rticles in Pittsburgh: Im plica tions f o r aero s ol sources and processes, J. Geophys. Res., 110(D07) , doi:10.1029/2004JD004649, 2005. Zhuang, H., C. K. Cha n , M. Fang, and A. S. Wexler, Si ze distributions of particulate su lfate, nitrate, and ammonium at a coastal site in Hong Kong, Atmos. Environ., 33, 843-853, 1999.

138