DOCUMENTATION AND EVALUATION OF THE GEOS-CHEM SIMULATION
FOR 2002 PROVIDED TO THE VISTAS GROUP

Final Report

Principal Investigator: Daniel J. Jacob, Harvard University (djacob@fas.harvard.edu) Co-Investigators: Rokjin Park and J ennifer A. Logan, Harvard University

June 24, 2005TABLE OF CONTENTS

1. PROJECT OBJECTIVE AND PRODUCTS DELIVERED 3

2. DESCRIPTION OF GEOS-CHEM SIMU LATIONS FOR VISTAS 3

2.1 The GEOS-Chem Model 3

2.2 Model configuration used for VISTAS 4

2.3 PM sources used in VISTAS simulations 5

2.3.1 Sulfate-nitrate ammonium 5

2.3.3 Carbonaceous aerosols 6

2.3.4 Soil dust 6

2.3.5 Sea salt 6

2.4 Biomass burning emission inventory for 2002 7

2.4.1 The United States and Canada 7

2.4.2 Russia and Kazakhstan 8

2.4.3 Summary 9

3. MODEL PERFORMANCE EVALUATION 9

4. REFERENCES 11

FIGURES 13

Appendix A: Rokjin J. Park, Daniel J. Jac ob, Mian Chin, and Randall V. Martin (2003),
Sources of carbonaceous aerosols over the Unit ed States and implications for natural visibility, J. Geophys. Res. , 108(D12), 4355, doi:10.1029/2002JD003190. 22

Appendix B: Rokjin J. Park, Daniel J. Jac ob, Brendan D. Field, Robert M. Yantosca, and
Mian Chin (2004), Natural and transboundary pollu tion influences on sulfate-nitrateammonium aerosols in the United States: implications for policy, J. Geophys. Res. , 109, D15204, doi:10.1029/2003JD004473. 48

21. PROJECT OBJECTIVE AN D PRODUCTS DELIVERED

The objective of this project was to pr ovide chemical boundary conditions with synoptic-scale resolution fr om the GEOS-Chem global chem ical transport model (CTM) to serve as continental-scale CMAQ re gional simulations for 2002 conducted by the VISTAS group. The GEOS-Chem simulations we re to include a de tailed representation
of ozone-NO

x -VOC-PM chemistry as described by Park et al. [2003, 2004] (appended to this report). They were to replicate the Pa rk et al. [2003, 2004] simulations but with coarser resolution (4 o x5 o horizontal resolution vs. 2 o x2.5 o ), updated anthropogenic emissions from the EPA NEI 1999, and 2002-specific biomass burning emissions. They were also to include prelimin ary simulations of soil dust and sea salt. We conducted three full-year simulations for 2002:

1. A baseline simulation with best estimates of 2002 emissions;

2. A background simulation modified from the baseline by shutting off U.S. anthropogenic 1 emissions;

3. A natural simulation modified from the base line by shutting off anthropogenic
emissions worldwide.

3-D concentration fields with 3-hour tem poral resolution were archived from each simulation to serve as boundary conditions for CMAQ. A model performance evaluation (MPE) was conducted through comparisons of the baseline simulation to IMPROVE and
CASTNET observations in the Un ited States, using the same metrics as in Park et al. [2003, 2004].

2. DESCRIPTION OF GEOS-CHEM SIMULATIONS FOR VISTAS

2.1. The GEOS-Chem model

The GEOS-Chem model (http://www-as.harv ard.edu/chemistry/trop/geos) is a cooperative global CTM used by 21 institutions in North America and Europe, and centrally managed by Daniel Jacob’s group at Harvard. It is driven by assimilated meteorological observations from the Global Earth Observation System (GEOS) of the NASA Global Modeling and Assim ilation Office (GMAO). It is presently being applied to a wide range of atmospheric compos ition problems including greenhouse gases, oxidants, PM, mercury, and othe r species. The coupled ozone-NO

x -VOC-PM version of
GEOS-Chem is described in Park et al. [2004] (appendix B). The GEOS-Chem model is documented in over 100 papers in the refer eed literature (see above web site for the

1 “Anthropogenic” here includes all fuel, industrial, and agricultural sources; it does not include biomass burning. See Park et al. [2004] for detail on source specifications.

3publication list). Evaluations of the global PM simulation ar e presented in Park et al. [2003, 2004, 2005ab], Li et al. [2005], Alexander et al. [2005], and Heald et al. [2005].

2.2. Model configuration used for VISTAS

The GEOS-Chem simulations for VI STAS used GEOS meteorological observations for the year 2002. These were obtained from GMAO as a 6-hourly archive (3-hour for surface quantities such as mixing depths). The data through August 2002 are from the GEOS-3 assimilation, w ith horizontal resolution of 1 o x1 o and 55 vertical layers. The data after August 2002 are from the upda ted GEOS-4 assimilation, with horizontal
resolution of 1 o x1.25 o and 48 vertical layers.

GEOS-Chem simulations can be conducted e ither with the nativ e resolution of the GEOS meteorological data, or with degr aded horizontal resolution to reduce computational expense. The Park et al. [2003, 2004] simulations used a 2 o x2.5 o

horizontal resolution. Continen tal-scale simulations for North America have been
conducted with the native 1 o x1 o resolution of the GEOS-3 data [Li et al., 2005; Park et al., 2005b]. The VISTAS simulations used a coarser horizontal resolution of 4 o latitude x

5 o longitude, as this was considered sufficien t to provide boundary conditions outside of
North America for use in continental-scale CMAQ simulations. In Fiore et al. [2003], we previously compared ozone simulations for North America using GEOS-Chem with

4 o x5 o and 2 o x2.5 o resolution, and the MAQSIP regional model with 36x36 km 2 resolution. We found that using the 4 o x5 o resolution of GEOS-Chem significantly degraded the ability of the model to reproduc e the observed variability of concentrations over North America, but still maintained the synoptic-scale structur e and did not incur a significant continental-scale mean bias.

Significant modifications to the representa tion of PM sources were made in the
VISTAS simulations relative to the work of Park et al. [ 2003, 2004] and are described in more detail below. They include (1) use of U.S. anthropogenic emissions from the EPA NEI 1999 inventory; (2) use of forest fire in formation specific to 2002; (3) inclusion of the secondary organic aeroso l (SOA) formation mechanis m from Chung and Seinfeld [2002]; (4) inclusion of prototype soil dust and sea salt simulations. An additional modification was the application of surface emissions and dry deposition to the GEOSdiagnosed mixed layer column rather than to the surface layer of the model. This was introduced to correct for the effect of 1-hour operator splitting between transport and chemistry (including emissions and dry deposit ion) in the model, when dealing with avery shallow surface layer (only 10-m deep in GEOS-3). The effect is significant for fastdepositing gases such as HNO 3 and NH 3 ; correcting it is an objective model improvement that has since been implemented in the standard version of GEOS-Chem.

Other aspects of the simulation (transport, chemistry, deposition) are as described in Park et al. [2004]. Briefly, transport us es the advection scheme of Lin and Rood [1998], with instantaneous vertical mixing through the local mixing depth, and convective transport computed from GEOS-3 archived convective mass fluxes by replicating the convection al gorithm of the parent GEOS general circulation model

4(GCM). Natural sources are calculated with in the GEOS-Chem simu lation as a function
of local values of meteor ological variables (temperature, insolation, soil moisture, precipitation, wind speed, c onvective cloud tops). The description of ozone-NO

x -VOCPM chemistry includes ~100 chemical spec ies and ~400 chemical reactions. A full documentation of this mechanism is poste d as a pdf document on the GEOS-Chem web site (http://www.env.leeds.ac.uk/%7Emat/GEO S-CHEM/geoschem_mech.pdf). Coupling
of PM with ozone-NO

x -VOC oxidant chemistry takes pla ce through sulfate, nitrate, and SOA formation and thermodynamics, aeros ol effects on UV actinic fluxes, and heterogeneous radical chemistry. Wet deposi tion of soluble gases and PM follows the scheme of Liu et al. [2001] and includes contributions from scavenging in convective updrafts, rainout and washout in convective and large-scale precipita tion, and partial or total release during re-evaporat ion below cloud base. Dry deposition is computed with a
standard resistance-in-series scheme [Wang et al., 1998].

All simulations were conducted from September 1, 2001 to December 31, 2002.
The first four months were used to achiev e proper initialization. Results delivered to
VISTAS are from the 12-month 2002 simulation.

2.3. PM sources used in VISTAS simulations

We describe here briefly the PM sour ces used in the VISTAS simulations. Description of the biomass burning emission i nventory for 2002 is presented in section

2.4.

2.3.1. Sulfate-nitrate-ammonium

Global GEOS-Chem budgets of sulfate, nitrate, and ammonium aerosols, including breakdown by source types of emissions for sulfur, NO

x , and ammonia, are given by Park et al. [2004]. Anthropogeni c emissions are from the Global Emission Inventory Activity (GEIA) with 1 o x1 o spatial resolution and s easonal temporal resolution,
and are scaled for individual countries to the year 1998 on the basi s of national emission
inventories and fuel use statis tics. Park et al. [2004] give global totals for non-U.S. anthropogenic emissions computed in this manner. They used the same procedure also
for U.S. emissions. For the VISTAS base line simulation, we used monthly mean anthropogenic U.S. emissions from the NEI 1999 inventory produced by EPA. An archive of monthly mean NEI 1999 emissi ons from that inventory with 0.25 o x0.25 o horizontal resolution was generated for us by Alice Gilliland of EPA/ORD, and was regridded to 4 o x5 o for application to VISTAS. The U.S. emission of ammonia in the NEI99 inventory (3.6 Tg N yr -1 ) is known to be too high [Gillila nd et al., 2004]. Therefore we retained for that species the U.S. emission inventory of Park et al. [2004] (2.2 Tg N yr -1 )

Natural emissions except for biomass burni ng are as given by Park et al. [2004].
Volcanic sulfur emissions are from the GE IA climatology. Emission of dimethylsulfide (DMS) by phytoplankton uses a global distribut ion of DMS seawater concentrations from Kettle et al. [1999] and a sta ndard sea-air exchange parame terization driven by the local
wind. Soil emissions of NO

x are from GEIA and are function of local temperature and precipitation history. Lightning emissions of NO

x are computed globally with a standard

5algorithm based on convective cloud tops [Wang et al., 1998] and are scaled to yield a global source of 6 Tg N yr -1 [Martin et al., 2002]. Emissions of ammonia from soils and
oceans are from GEIA.

2.3.2. Carbonaceous aerosols

Detailed discussion of the EC and OC em ission source processe s in the model is given in Park et al. [2003] (appendix A). An thropogenic emissions of EC and OC outside the U.S. are from the Cooke et al. [1999] inventory. For the VISTAS baseline simulation we used U.S. anthropogenic emissions from Park et al. [2003], who optimized EC and OC sources using monthly IMPROVE obser vations for 1998. Both EC and OC have major sources from biomass burning; emi ssion factors are from Andreae and Merlet [2001] and are applied to the 2002 biomass burning inventory described in section 2.4. Secondary organic aerosol (SOA) formati on from biogenic hydrocarbons follows the scheme of Chung and Seinfeld [2002] develope d for application in global models (the Park et al. [2003] simulations simply scal ed the SOA source to 10% of monoterpene emission). The Chung and Seinfeld [2002] de scribes SOA formation from oxidation of several classes of biogenic hydrocarbons th rough gas-aerosol partitioning of the semivolatile products as a function of loca l temperature and pre-existing OC mass
concentration.

2.3.3. Soil dust

We included in the VISTAS simulations a preliminary representation of soil dust using the global dust mobilization scheme of Ze nder et al. [2003]. Dust particles in four different size classes were transported as separate tracers with different source and settling properties, thus allowing in particular some segregation of PM 2.5 and PM 10-2.5 . A global evaluation of this preliminary dust simulation in GEOS-Chem was presented by Fairlie [2004]. Asian and African dust source s are simulated without obvious bias. There is a large overestimate at many IMPROVE sites in fall due to spurious local dust generation from seasonally dry and vege tation-deprived prai rie ecosystems.

2.3.4. Sea salt

The sea salt concentrations in the VI STAS simulations are from a new GEOSChem capability developed by Alexander et al . [2005]. The simulation uses the standard source scheme of Monahan [1986] which is function of surface wind speed over the oceans, and transports sea salt PM in two size classes (0.1-1 and 1-10 μ m). The resulting global source of sea salt in GEOS-Chem is 5400 Tg yr -1 , consistent with earlier literature (3500-7600 Tg yr -1 ). Alexander et al. [2005] present further discussion of the global sea salt budget and distributions in GEOS-Chem, including comparisons to observations and previous global models.

62.4. Biomass burning emissi on inventory for 2002

2.4.1. The United States and Canada

We developed an inventory for emissions from fires in the United States using data for areas burned that are reported by several federal agencies, by regional interagency coordination centers such as th e Pacific Northwest, Western Great Basin, Eastern Great Basin, and Southwest (www.or.blm.gov/nwcc/, www.nv.blm.gov/wgbcc/, www.blm.gov/utah/egbcc/, www.fs.fed.us/r3/fire /) and by various states. We also
obtained a data base of fires in the southeastern United States from G. Stella of Alpine Geophysics. In the western half of the U.S. and Alaska, most of the land is federally owned, so the fire information is thought to be comprehensive. Reports from the Bureau of Indian Affairs, Bureau of Land Manageme nt (BLM), National Park Service, Fish and Wildlife Service, and U.S. Fore st Service are available on-line (http://famweb.nwcg.gov/weat herfirecd). These reports give the fire name, start and end date, their location (latitude a nd longitude), and area burned. We analyzed these data to spatially and temporally allocate the fires. A simple concatenation of data was not possible as different agencies sometimes repor ted the same fires, so we ensured that duplicate reports for the same fire were e liminated. The Daily Incident Management Reports (www.cidi.org/wildfire) of the Nationa l Interagency Coordina tion Center (NICC) were consulted to corroborate incidence, location and sizes of major fires, and to
determine whether these fires were surface or crown fires.

Our database of all fires with areas la rger than 100 acres gives a total of 1626 fires, of which 338 are located in the south eastern states. These fires consumed 2.65 x

10 6 ha in the United States in 2002. The da ta provided by Alpine Geophysics for the southeast gave a total area of 0.044 x 10 6 ha. Six states accounted for over 80% of the national area burned, namely Alaska, Ore gon, Colorado, California, New Mexico, and
Arizona. Alaska accounted for one third of the area burned in the United States, and the seven largest fires in Alaska contributed 55% of the area burned for the state. For the entire United States, the largest 20 fires acc ounted for half the ar ea burned nationally.

The area burned in the United States in 2002 was the second highest for the previous ten years. To put the area burned in a larger context, th e area burned in Canada was similar to that in the United States, 2.76 x 10 6 ha, while 2.8 x 10 6 ha burned in Kazakhstan, and 11 x 10 6 ha in Asiatic Russia. It was also a very high fire year in Russia.

For our initial estimate of the amount ofdry matter burned (used in the GEOSCHEM simulations) we adopted a loading 2.6 kg DM/m 2 for Alaskan fires, and 1.8 kg
DM/m 2 for the lower states. We f ound that 47 Tg of dry matte r was consumed by fires in the United States, producing CO emissions of 5 Tg in about 3 months. We developed preliminary maps of dry matter burned on a 1ox1o grid by month by assuming that each fire burned at the same rate during each day of the burn period.

For Canada, we relied on a product provided by David Lavoue (Environment Canada). He is developing an inventory fo r Canada using a detailed data-base on the location of the size and position of the fires; that data-base is not yet publicly available. He gave us an interim product that consists of monthly totals of fuel consumed on a map

7with resolution of 1ox1o latit ude by longitude. Lavoue estimates that 58 Tg of dry matter was consumed by fires in 2002, which gives rise to CO emissions of 7 Tg..

2.4.2. Russia and Kazakhstan

The most detailed fire information was available for eastern Russia. The IFFN report (http://www.fire.uni-freib urg.de/iffn/iffn_28/Russia-1.pdf ) gives estimates by province of the total areas burned in Asian Russia for the fire season of 2002. The total
area burned was 11 x 10 6 ha. The Fire Laboratory of the Sukachev Institute of Forest, Krasnoyarsk, provides maps showing the loca tions of large fires for 10-day periods
derived from NOAA AVHRR data (http://www.fir e.uni-freiburg.de/current/ archive/archive.htm). We used these maps to spatially and temporally apportion the area burned in each province among all of the fires lo gged for the province; burn scars at the end of the fire season were approximated as rectangles. The areas burned were put on a grid of 1ox1o (lat. x long.) for each 10 da y period. The Kamchatka Peninsula was not included on the burning maps for eastern Russia. Areas burned there were confined to June and July (IFFN report). Maps of ATSR fire counts were used to locate the fires.

Most of the burning in Russia was in Ju ly-August in the northern province of Yakutia. There was a smaller peak in the bu rning in May, primarily in the provinces of
southern Siberia. We relied on a detailed vegetation map of Russia to determine the dominant vegetation type in each gridbox, and applied appropriate fuel loads to
determine the amount of biomass burned.

Table 1. Loadings used for fires in Russia, in kg dry matter (DM) m -2

Vegetation Type kg DM m -2

Tundra 1.8
Wooded Tundra 2.0 Taiga 2.5
Boreal Forest 3.0
Grasslands 0.3 Steppe 0.3

Desert 0.3
Farmlands 0.3

Recent work indicates the importance of including the burning of peat as a component of boreal fires. We track peat bur ning separately from burning of other forest fuels as it has a higher moisture content, hence less efficient combustion, and higher emission factors for CO. The construction of peatland map is in progress for Russia (L. Pozdnyakova, personal communication), there is not one currently available. As a surrogate, we used maps of wetlands and so il drainage to give the distribution of boggy or poorly drained soils, as advised by S. Conard and M. Turetsky. The locations of individual fires given by the remote sensi ng data were superimposed on this map; burning of peat was confined to the area de fined by the perimeter of the fires. Few

8experiments have been reported which descri be measurements of fuel consumed and emissions from peat fires in boreal forests. We assumed that 2.2 kg C m -2 was burned.

For western Russia, wildfi res other than peat bog fi res were not reported in
sufficient detail to ascertain their whereabou ts. Qualitative descriptions of major peat bog fires in July to September around Mo scow, St. Petersburg, Nizhny Novgorod, and other cities were abundant, but few estimates of areas burne d and depth of peat burned
were found. From the IFFN news and CNN re ports, we used quant itative and qualitative information to approximate the areas burned in the peat bogs around four of the major
cities

. We distributed the burning homogeneously in the oblast (province) that contained each city and applied a fuel consumption estimate for peat burning as above.

Maps of fires for each month and the annual amount burned (2.8 x 10 6 ha) were available for Kazakhstan. Here also, ATSR fi re counts were used to locate the fires on a monthly basis. We used a vegetation map for Kazakhstan [http://www.fire.unifreiburg.de/iffn/country/ kz/kz_2_1b.gif] and an agricultural map of the CIS (Major World Crop Areas and Climatic Profiles) to determine the fuel loads to use. Based on these maps, we postulated that the fires in the s outhern regions were burning of agricultural residues, for whic h we adopted a loading of 1.2 kg DM m -2 ; for the pine forests in the north, we adopted a loading recommended for Kazakhstan’s pine forests, 2 kg DM m -2

.

2.4.3. Summary

We find that 409 Tg dry matter was consumed in Russia, 52 Tg in Kazakhstan, and 47 Tg in the United States. For Canada, Lavoue’s es timate of 58 Tg of dry matter consumed in 2002 is low in comparison to our estimate for Russia, given the ratio of areas. Lavoue did not include burning of peat in Canada as he believes it in not an im portant component of the Canadian fires (personal communication). These estimates were used in the GEOSCHEM simulations to provide monthly em issions from biomass burning. In other regions we replied on the work of Van der Werf et al. (Science, 2003), based on VIRS
satellite data.

3. MODEL PERFORMANCE EVALUATION

Model performance evaluation (MPE) of the baseline VISTAS simulation focused
on the annual and seasonal PM concentration st atistics previously reported by Park et al. [2003, 2004] using observations from IMPROVE and CASTNET sites. The Park et al. simulations were conducted for 1998 and 2001, whereas the VISTAS simulation was for
2002. We use here observations from 145 IMPROVE sites and 84 CASTNET sites
available for 2002.

The limitations of using U.S. concentr ation data to evaluate a global PM
simulation with 4 o x5 o horizontal resolution should be stressed. Any variability on scales
less than ~500 km cannot be resolved. This compromises the evaluation for individual sites, particularly in urba n, industrial, and coastal regions. We focus therefore our evaluation on the large-scale sp atial distribution and on seasonal statistics for the national

9ensemble of sites. The eval uation figures shown here repr oduce similar figures presented by Park et al. [2003, 2004] for their 1998 and 2001 simulations with 2 o x2.5 o resolution. Direct comparison to these figures can therefor e be made to assess the relative quality of the simulations. We use the slopes of the re gression lines in the simulated vs. observed scatterplots to diagnose mean biases in the m odel. Regression lines are computed with the reduced major axis method [Hirsch and Gilroy, 1984].

Figure 1 compares simulated and observed annual mean sulfate concentrations at the ensemble of IMPROVE and CASTNET sites for the year 2002, plotted on the 4 o x5 o model grid. Values are highest in the industr ial midwest, in both model and observations, reflecting the distribution of anthropogenic emissions. Fi gure 2 shows sca tterplots of
simulated vs. observed annual and seasonal sulf ate concentrations for the ensemble of (left) IMPROVE and (middle) CASTNET sites. The right column in Figure 2 compares simulated and observed sulfate precipitation data for 2002 at NADP sites. The correlation between model and observations is high for the annual mean values (R 2 = 0.82 for the concentration data and 0.71 for the deposition data) and also for the seasonal means (R 2 = 0.63–0.87 for the concentration data). An exception is the deposition data in summer, for
which correlation between mode l and observations is low (R 2 = 0.18). Overall, the correlations presented here are consistent wi th those presented by Park et al. [2004] for 2001 (see Figures 3 and 4 of appendix B) alt hough that simulation was more successful in capturing the variance in summer deposition.

Figure 3 compares simulated and observ ed annual mean concentrations of
ammonium at CASTNET sites. Observed concen trations are higher in the east than in the west and are highest in the midwest, re flecting agricultural op erations. The model reproduces this spatial distri bution. Scatterplots of simulated vs. observed annual and
seasonal ammonium concentrations are shown in Figure 4 for the ensemble of sites. The model reproduces the variab ility of observed ammonium concentrations, both in an annual mean sense (R 2 = 0.81) and in different seasons (R 2 = 0.72-0.81). The R 2 values are slightly lower than the values from th e Park et al. [2004] simulation (Figure 6 of appendix B). That simulation showed a fact or of 2 high bias in fall due to too high seasonal ammonia emission. Despite the same ammonia emission, the VISTAS simulation shows much reduced bias (50% fo r ammonium concentration in fall). This reflects in part the increase in the effectiv e ammonia deposition velo city resulting from application of the dry depositi on sink throughout the mixed layer column, as described in
section 2.2.

Figure 5 compares simulated and observed annual mean nitrate concentrations at
the IMPROVE and CASTNET sites. Maximum concentrations are in the Midwest, reflecting the limitation of amm onium nitrate formation by the availability of ammonia. The model captures the observed spatial distri bution of nitrate concentrations but tends to be high on an annual mean basis (slope = 1.41-1. 80 in Figure 4). This is however also an improvement over Park et al. [2004], which f ound a factor of 2 high bias (slope = 1.87 – 2.43 in Figure 6 of appendix B), and reflects the improved treatment of HNO 3 dry deposition. The high bias in the VISTAS simu lation is mainly driven by the fall months, when the model appears to produce too mu ch ammonium nitrate due to too high ammonia emission [Park et al., 2004].

10Figure 6 compares simulated and observed annual mean concentrations of EC at IMPROVE sites, and the scatterplots of Figure 7 compare seasonal mean concentrations. The model reproduces about half of the observe d spatial variability in different seasons (R 2 = 0.42-0.58) except in summer (R 2 = 0.18). Simulated concentrations tend to be higher than observed (slope = 1.58-1.74) excep t in summer (slope = 0.76). The high bias is mostly driven by IMPROVE site s in the northeastern corridor.

Figure 8 compares simulated and observed annual mean concentrations of organic carbon mass (OMC) at IMPROVE sites, and Figu re 9 shows the seas onal scatterplots. Although the ability of the model to reproduce variability in the obs ervations is poor, particularly in summer, the simulated seasona l mean concentrations are generally within
a factor of two of observations. The simulatio n is significantly worse than that described by Park et al. [2003]; this reflects the use of the Chung and Seinfeld [2002] SOA parameterization, which appears to undere stimate the source from vegetation.

Overall, the MPE conducted for the VIST AS simulation for the U.S. shows the level of agreement that can be expected consid ering the state of the science in large-scale aerosol modeling and the intrinsic limitations of a simulation with 4 o x5 o horizontal resolution. Simulated concentrations are mainly within a factor of 2 of observations on regional and seasonal scales, a nd can generally account (excep t for OC) for most of the observed variability on those scales.

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- NO -hydrocarbon chemistry, 1. Model formulation

, 3

x J. Geophys. Res., 103 (D9), 10,713-10,726. Zender, C. S., H. Bian, and D. Newman (2003), Mineral Dust Entrainment and Deposition (DEAD) model: Descripti on and 1990s dust climatology, J. Geophys.

Res. , 108(D14), 4416, doi:10.1029/2002JD002775.

12Figure 1. Annual mean concentrations of sulf ate in surface air over the United States in 2002. The top panel shows results from the GEOS-CHEM model. The middle and bottom panels show the observations from the IMPROVE and CASTNET networks, respectively, averaged over the model 4 o × 5 o grid.

13Figure 2. Scatterplot of simulated versus observed sulfate concentrations at the IMPROVE and CASTNET sites, and sulfate depo sition fluxes at NADP sites. Values are annual means (top panels) and seasonal mean s for 2002. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses a nd open circles, respectively. Thick solid lines are reduced major axis re gressions for the ensemble of the data; regression equations and R 2 are shown inset. Thin solid li nes show the y=x relationship.

14Figure 3. Annual mean concentrations of ammonium in surface air over the United States in 2002. The top panel shows results from the GEOS-CHEM model. The bottom panel
shows the observations from the CASTNET network.

15Figure 4. Scatterplot of simulated versus observed ammonium concentrations at the CASTNET sites (left column), and nitrat e concentrations at the CASTNET and IMPROVE sites (right two columns). Values are annual means (top panels) and seasonal
means for 2002. Sites in the western and eas tern United States (separated at 95 o W) are shown as pluses and open circ les, respectively. Thick solid lines are reduced major axis regressions for the ensemble of th e data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

16Figure 5. Same as Figure 3 but for nitrate.

17Figure 6. Annual mean concentrations of el emental carbon (EC) aerosol in surface air over the United States in 2002. The top pa nel shows results from the GEOS-CHEM model. The bottom panel shows the obs ervations from the IMPROVE network.

18Figure 7. Scatterplot of simulated versus obs erved EC aerosol concentrations at the
IMPROVE sites. Values are seasonal means for 2002. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses a nd open circles, respectively. Thick solid lines are reduced major axis re gressions for the ensemble of the data; regression equations and R 2 are shown inset. Thin solid li nes show the y=x relationship. Dotted lines show the y=2x and y=0.5x relationships.

19Figure 8. Same as Figure 6 but for organic carbon mass (OMC)

20Figure 9. Same as Figure 7 but for organic carbon mass (OMC)

21Appendix A: Rokjin J. Park, Daniel J. Jac ob, Mian Chin, and Randall V. Martin (2003), Sources of carbonaceous aerosols ov er the United States and implications for natural visibility, J. Geophys. Res. , 108(D12), 4355, doi:10.1029/2002JD003190.

Abstract. We use a global 3-D model (GEOS-CH EM) to better quantify the sources of elemental carbon (EC) and organic carbon (O C) aerosols in the United States through simulation of year-round observations for 1998 at a network of 45 sites (IMPROVE).
Simulation with our best a priori understanding of sources, in cluding global satellite data to constrain fire emissions, captures mostof the variance in the observations (R 2 = 0.84 for EC, 0.67 for OC) with a low bias of 15% for EC and 26% for OC. Multiple linear regression to fit the IMPROVE data yields be st estimates of 1998 U.S. sources of 0.60 Tg

yr -1 EC and 0.52 Tg yr -1 OC from fossil fuel; 0.07 Tg yr -1 EC and 0.89 Tg yr -1 OC from biofuel; 0.08 Tg yr -1 EC and 0.60 Tg yr -1 OC from wildfires; and 1.10 Tg yr -1 OC from vegetation. We find that fires in Mexico a nd Canada contributed 40-70% of annual mean
natural EC in the United States for 1 998, and 20-30% of annual mean natural OC. Transpacific transport from Asian pollution sources amounted to less than 10% of the
natural EC and less than 2% of the natural OC; in contrast to ozone, we find that intercontinental transport of anthropogeni c carbonaceous aeroso ls does not enhance significantly the natu ral background. IMPROVE observations and model simulations for
the summer of 1995 show that Canadian fi re emissions can produce large events of
elevated EC and OC in the southeastern Unite d States. Our best estimates of mean natural
concentrations of EC and OC in the Un ited States, using a model simulation with climatological monthly mean fire emissions, ar e 2-3 times higher than the default values recommended by the U.S. Environmental Protection Agency (EPA) for visibility calculations, except for OC in the ea stern United States (16% lower).

1. Introduction
Carbonaceous aerosol is one of the least understood components of fine particulate matter (PM). It is usually divided in tw o fractions, elemental carbon (EC) and organic carbon (OC). OC is the second most abundant component of the aerosol in the United States after sulfate, and the dominant com ponent of the natural continental aerosol [ Malm
et al. , 2000]. EC is the dominant component of the light-absorbing aerosol. Carbonaceous aerosol is presently the subject of intense scrutiny because of its impact on human health, visibility, and climate. We present here an assessment of the sources of EC and OC in the United States by using a global 3-D model (GEOS-CHEM) simulation of observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. Our focus is on quantifying the anthropogenic and na tural sources of these aerosols, the role of transboundary transport, and the implicati ons for visibility. The U.S. Environmental Protection Agency Regional Haze Rule [ U.S. EPA , 2001] mandates a schedule of increasing emission controls to achieve “natural visibility conditions” in national parks and other wilderness areas by 2064. The ambi guity in defining “natural visibility conditions” requires better information on natu ral PM concentrations and the perturbing
effects from fires and from sources outside the United States. Elemental carbon is emitted to the atmosphere by combustion. Major sources in the United States include coal burning and diesel engines. Organic carbon is emitted directly

22to the atmosphere (primary OC) and formed in situ by condensation of low-volatility products of the photooxidation of hydrocarbons (secondary OC). Primary sources of OC
in the United States are wood fu el, coal burning, and wild fires [ Seinfeld and Pandis

, 1998; Cabada et al. , 2002]. Secondary OC includes an anthropogenic component from oxidation of aromatic hydrocarbons, and a biogenic component from oxidation of terpenes [ Griffin et al. , 1999]. Our approach is to conduct a 3-D model si mulation of EC and OC concentrations in the United States for 1998, with best a priori sources, compare results with observations from the IMPROVE network, and use the constraints from the comparison to optimize our treatment of sources by multiple linear regression. Our treatment of fire emissions accounts for year-to-year variability th rough satellite observations; 1998 was a particularly active fire year, thus offering good constraints on emissions from that source. We also present a case study for the summe r of 1995 to demonstrate the large-scale
enhancements of EC and OC concentrations in the United States that can arise from Canadian fires. We go on to quantify mean natural EC and OC concentrations in the United States for different seasons and regi ons, using climatologica l fire emissions and sources from vegetation, and to assess th e enhancement of EC and OC background concentrations resulting from transp acific transport of Asian pollution.

2. Model Description

2.1 General We use the GEOS-CHEM global 3-D model of tropospheric chemistry [ Bey et al.

, 2001] to simulate EC and OC aerosols for 1998 (1 year) and 1995 (summer). The model (version 4.23, http://www-as.harvard.edu/ch emistry/trop/geos /index.html) uses assimilated meteorological data from th e NASA Goddard Earth Observing System (GEOS) including winds, convective mass fluxe s, mixed layer depths, temperature, precipitation, and surface properties. Meteorological data for 1995 and 1998 are available with 6-hour temporal resolution (3-hour for surface variables and mixing depths), 2 o latitude by 2.5 o longitude horizontal resoluti on, and 20 (GEOS1 for 1995) or 48 (GEOS3 for 1998) sigma vertic al layers. We retain this spatial resolution in the
GEOS-CHEM simulation. The lowest model levels are centered at approximately 50, 250, 600, 1100, and 1750 m above the local surface in GEOS1 and 10, 50, 100, 200, 400, 600, 900, 1200, and 1700 m in GEOS3.
The simulation of carbonaceous aerosols in GEOS-CHEM follows that of the Georgia Tech/Goddard Global Ozone Chemistry Aero sol Radiation and Transport (GOCART) model [ Chin et al. , 2002], with a number of modificati ons described below. The model resolves EC and OC, with a hydrophobic and a hydrophilic fraction for each (i.e., four aerosol types). Combustion sources em it hydrophobic aerosols that then become hydrophilic with an e-folding time of 1.2 days following Cooke et al. [1999] and Chin et
al. [2002]. We assume that 80% of EC and 50% of OC emitted from all primary sources are hydrophobic [ Cooke et al. , 1999; Chin et al. , 2002; Chung and Seinfeld , 2002]. All secondary OC is assumed to be hydrophilic. The four aerosol types in the model are
further resolved into contributions from foss il fuel, biofuel, and bi omass burning, plus an OC component of biogenic origin, resulting in a total of 13 trace rs transported by the
model.

23Simulation of aerosol wet and dry deposition follows the schemes used by Liu et al. [2001] in previous GEOS-CHEM simulations of 210 Pb and 7 Be aerosol tracers. Wet deposition includes contributions from scave nging in convective updrafts, rainout from convective anvils, and rainout and washout from large-scale precipitation. Wet deposition is applied only to the hydrophilic component of th e aerosol. Dry deposition of
aerosols uses a resistan ce-in-series model [ Walcek et al. , 1986] dependent on local surface type and meteorological conditions; it is small compared to wet deposition. Liu
et al. [2001] found no systematic bias es in their simulations of 210 Pb and 7 Be with GEOSCHEM.

2.2 A priori sources of EC and OC We use global anthropogenic emissions of EC (6.4 Tg yr -1 ) and OC (10.5 Tg yr -1 ) from the gridded Cooke et al. [1999] inventory for 1984. This inventory includes contributions from domestic, vehicular, and i ndustrial combustion of various fuel types.
In the GOCART simulation of Chin et al. [2002], the Cooke et al. [1999] inventory was
used with no seasonal variati on. However, the source from h eating fuel should vary with season [ Cabada et al. , 2002]. Cooke et al. [1999] do not resolve th e contributions to EC and OC emissions from heating fuel. We a ssume these contributions to represent 8% (EC) and 35% (OC) of total anthropogenic emissions, based on data for the Pittsburgh
area from Cabada et al. [2002] and apply local seasonal va riations of emissions using the heating degree days approach [ EIA , 1997; Cabada et al. , 2002]. In this manner we find that anthropogenic EC emission in the United States in winter is 15% higher than in summer. For OC the anthropogenic winter emission is twice that in summer.
The Cooke et al. [1999] inventory does not includ e biofuels, which provide however an important source of heating in rural househ olds and are also used in agroindustrial factories. We use a global biofuel use inventory with 1 o x1 o spatial resolution from Yevich and Logan [2002] with emission factors of 1.0 g EC and 5 g OC per dry mass burned [ Street et al. , 2001; Dickerson et al. , 2002]. For the United States and Canada, we supersede that inventory w ith data on wood fuel consumption for residential and
industrial sectors available for individual st ates and provinces [ EIA , 2001] and which we distribute on a rural population map. Emission factors for this North American wood fuel source are 0.2 g EC and 3.0 g OC per kg dry wood burned [ Cabada et al. , 2002].
Seasonal variation in biofuel emissions is included for the United States only and is estimated according to the h eating degree-days approach. Biomass burning emissions of EC and OC are calculated using the global biomass burning inventory of Duncan et al. [2002]. This inventory uses a fire climatology compiled on a 1 o x1 o grid by Lobert et al. [1999], and applies monthly and interannual variability to that climatology from satell ite observations. Emission factors are 2g EC and 14 g OC per kg dry mass burned [ Chin et al. , 2002], higher than for biofuels because
combustion is less efficient. For boreal forest fires, which are of particular interest here, emission factors reported in the literature range from 0.38 to 2.55 g EC per kg dry mass burned [ Lavoué et al. , 2000, and references therein], c onsistent with the value assumed
here. The OC/EC emission ratio of 7 is within the range of 6.9 to 8.2 used by Liousse et
al. [1996]. Figure 1 shows the resulting annual OC emissions from biomass burning in North and Central America for 1997-2000 as well as the climatological mean. An ENSO-related drought resulted in catastrophic wildfires in the tropical forests of southern

24Mexico and Central America in 1998 [ Peppler et al. , 2000]. Canadian fire emissions were also unusually large in 1998. Fire emi ssions in the United States were 38% higher than the climatological mean. Figure 2 shows the spatial and seasonal di stribution of biomass burning OC emission
from our model in 1998. Fires in Mexico and Central America were most intense in May [ Peppler et al. , 2000, Cheng and Lin , 2001]. Canadian fires peaked in July-September. In the United States, most fires occurred in the northwest (Idaho, Montana) in summer; additional fires occurred in spring in Fl orida, due to the ENSO-induced drought. Secondary formation of OC from oxidati on of large hydrocarbons is an important source but uncertainties are large [ Griffin et al. , 1999; Kanakidou et al. , 2000; Chung and Seinfeld , 2002]. Chung and Seinfeld [2002] find that biogenic terpenes are the main source of secondary OC aerosols. We assume a 10% carbon yield of OC from terpenes [ Chin et al. , 2002], and apply this yield to a globa l terpene emission inventory dependent on vegetation type, monthly adjusted leaf area index, and temperature [ Guenther et al.

, 1995]. Table 1 shows a summary of a priori EC and OC emissions used in the GEOSCHEM simulation for 1998. The most importa nt global source for both is biomass burning. In the United States, EC is mostly emitted from the combustion of fossil fuel and OC originates mostly from vegetation (but with large seasonal variation, as discussed below).

3. Model evaluation A global evaluation of the EC and OC aerosol simulation was done by Chin et al. [2002] as part of a more general evaluati on of aerosol optical depth using ground and
satellite observations. Our simu lation of aerosol sources and meteorological processes is
similar to that of Chin et al. [2002] and our global dist ributions of EC and OC concentrations are comparable. We focus here our model evaluation on the United States, using observations at the IMPROVE sampling sites. The IMPROVE monitoring program was initiated in 1987 in national pa rks and other protected environments to identify the contribution of different aeros ol components to visibility degradation [ Malm
et al. , 1994]. The data for 1995 and 1998 c onsist of 24-h speciated aerosol
concentrations measured twice a week. The EC and OC concentra tions are determined using the Thermal Optical Reflectance (TOR) me thod, which is state of the science but is subject to uncertainties that are difficult to quantify [ Chow et al. , 1993; Malm et al.

, 1994]. In the present paper we take the data at face value. There are 45 IMPROVE sites with continuous measurements for 1998 (Figure 3). Figure 4 compares simulated and observed a nnual mean EC and OC concentrations at the 45 IMPROVE sites for the year 1998. The IMPROVE measurements are plotted on
the 2 o x 2.5 o model grid. The bottom panels show the differences (model bias). A general objection to evaluating model results with 24-hr averaged concentrations in
continental surface air is the inability of models to reso lve nighttime stratification [ Jacob
et al. , 1993]. This is not an issue in our case because of high verti cal resolution of the
model near the surface and because the IMPROV E sites are not in the vicinity of large sources. We verified that the 24-h averag e concentrations simulated by the model in layers 1 (0-10m), 2 (10-50m), and 3 ( 50-100m) are not significantly different.

25Observed concentrations of EC and OC are generally highe r in the eastern than the western United States, reflecting higher anth ropogenic and vegetative (OC) emissions in
the east. The OC maximum is shifted south relative to the EC maximum, and shows a secondary maximum along the west coast, re flecting the vegetative source. The model captures well this large-scale spatial distribut ion of EC and OC. Fires in the model also lead to high concentrations over Cent ral America and western Canada. Site-to-site comparisons re veal however some major discrepancies between model and observations, as shown in the bottom pane l of Figure 4 and in the scatterplot of Figure 5. Some of these discrepancies appear to reflect inadequate spatial resolution in
the model. Model overestimates at coastal si tes with large local urban or fire sources (BRIG in New Jersey; OKEF in Georgia; REDW, PORE, and PINN in California) are due to the inability of the model to simulate steep subgrid land-to-sea gradients in mixing depth [ Fiore et al. , 2002]. Model overestimates at SEQU (California) and GLAC (Montana) are due to local fire emissions (F igure 1) for which averaging over the grid scale may induce large errors in the simulation of local obse rvations. We exclude these
seven sites in further stat istical data analysis. The model overestimates OC concentrations at THSI (Oregon) and MORA (Washington) sites due to a particularly large vegetative source in the model in summer that is apparently not seen in the observations . The discrepancy is lo cal in nature (it is not found at nearby sites). As discussed further below, our specification of the vegetative OC source appears inadequate to describe OC concentrations at these two sites, and
therefore we exclude them from further statistical analysis. Figure 5 shows that the model generally reproduces the annual mean EC and OC
concentrations to within a factor of two and capture s the spatial pattern well ( R 2 =0.84 for
EC and R 2 =0.67 for OC). However, the slope of the reduced major axis line [ Hirsch and Gilroy , 1984] is 0.85±0.06 for EC and 0.74±0.08 for OC, reflecting a low bias in the
model. We will correct for this model bias by adjusting the sources, as discussed below. Figure 6 and Figure 7 compare seasonal vari ations of simulated and observed EC and
OC concentrations at selected IMPROVE sites. Contributions from individual sources to
the model concentrations are shown. Seasona l variations for EC di ffer considerably from site to site, and the model has significant success in capturing these differences. Fossil
fuel is the dominant source for EC at most sites, but seasonal maxi ma in May-September
over the western United States are due to fo rest fires. The OC concentrations are generally highest in summer and lowest in winter, both in the model and in the observations; this seasonal variation is mostly due to the biogenic source. Peaks in OC in May-September in the western United States are seen both in the model and in the observations and are due to wildfires, as for EC. Wintertime OC is higher in the eastern than the western United States, and include s contributions of comparable importance
from biofuels and fossil fuels. Rogers and Bowman [2001] used satellite measurem ents and air parcel trajectory
calculations to illustrate the transport of the 1998 fire plumes from Central America to the
central and southern United States. Our m odel successfully captures the corresponding peaks of EC and OC observed in May at th e IMPROVE sites (e.g., BIBE in Texas, CHIR in Arizona, CANY in Utah, MOZI in Colorado, UPBU in Arkansas, GRSM in Tennessee). The enhancement in concentratio ns is much stronger for OC than for EC,

26both in the model and in the observations, re flecting high OC/EC fire emission ratios and the relatively large fossil fuel source of EC in the United States. The model has also some success in reproduc ing the influences from fire emissions within the United States. For example, the hi gh OC in April-June at CHAS in Florida is well captured in the model. Fires in the west ern United States result in peak EC and OC concentrations in September at several sites (MORA, Washi ngton; THSI, Oregon; LAVO, California; JARB, Nevada). Figure 8 compares simulated and observed monthly mean concentrations for the ensemble of IMPROVE sites and for separa te seasons. The model simulation with a priori sources has success in reproducing the variability of observed EC and OC for winter and spring, as measured by the high R 2 (0.67-0.79) correlation between model and observations. The slope of th e regression line (0.84-0.98) is close to one for both EC and
OC. The R 2 is lower in summer and fall, particul arly for OC (0.37-0.40) and the slope of the regression line is off from one (0.72-0.74 for EC and 0.74-1.06 for OC). The slope of the OC regression line in fall is close to one only because high model bias from wildfire
sources at western sites offsets the lo w model bias at eastern sites.

4. Top-down emission estimates The statistical model biases apparent in Figure 8 could reflect errors in the a priori sources. We examine what adjustments in the sources would be needed for least-squares
minimization of the bias between simulate d and observed monthly mean EC and OC concentrations. We identify for this purpose four source components: fossil fuel, biofuel, biomass burning, and vegetation (the latter for OC only). We use a multiple linear regression to fit the annual mean U.S. s ource for each component to the monthly mean
IMPROVE observations. In order to give equal weight to EC and OC concentrations in the least-squares minimization, we normalize them by their respective annual mean concentrations for the ensemble of IMPROVE sites (0.29 μ g m -3 for EC, 1.23 μ g m -3 for OC).
We find in this manner that fossil fuel a nd biofuel emissions should be increased by 15% and 65% respectively from a priori levels, while biomass burning emissions should be decreased by 17% and the biogenic source for OC should be increased by 11%. We consider these adjustments to be we ll within the uncertainties on the a priori estimates.
The a posteriori values of our adjusted sources are gi ven in Table 1. The increase in the biofuel source is largely determined by the model underestimate of observed OC for the
cold season. Figure 9 presents annual mean surface air concentrations of EC and OC in the model using a posteriori sources. Relative to the simulation with a priori sources (Figure 4),
there are 15-20% increases in EC and OC c oncentrations in the eastern United States. Changes in the western United States are sm aller because the decrease in the biomass burning source offsets the increase in the biogenic OC source. The effect of source adjustment on the ability of the model to fit observed EC and OC concentrations is shown by the scatterplots in Figure 8. Compared to the simulation with a priori sources, the R 2 correlation coefficients are slig htly higher and the slopes of the regression lines are closer to unity. Fi gures 6 and 7 show the effect of the a posteriori
sources on the simulation at individual sites. The adjustments are generally too small to

27correct site-specific discrepancies, which would require modifying the geographic
distributions of the sources. Figures 10 and 11 show the contributions of individual a posteriori sources to EC and OC for winter and summer. Fossil fuel is the most important source of EC everywhere in the United States, except in some areas in the west in summer where wildfires make a more important contribution. For OC, the an thropogenic sources (f ossil and biofuel) dominate in winter, while the natural sources (fires and vege tation) are more important in summer. The fossil fuel OC is mostly concentrated in the northeastern corridor, the industrial Midwest and Southern California, whereas the biofuel OC is more widely distributed. Biogenic OC in summer is highest in the southeast and along the west coast. We previously discussed in the context of Figure 7 the large OC enhancements in the
southern United States due to fires in Cent ral America, but these enhancements are in spring (cf. Figure 2) and t hus not apparent in Figure 11. Figure 11 shows a large
enhancement in OC concentrations over the north-central United Stat es due to Canadian fires, but the IMPROVE sites are not well situated to obser ve this enhancement (Figure 3). We present below a case study for summer 1995 demonstrating Canadian fire
influence over the eastern United States.

5. Canadian fire influence: a case study for the summer of 1995 Previous studies [ Wotawa and Trainer , 2000; Fiore et al. , 2002; McKeen et al. , 2002] have shown that major Canadian wildfires in June-July 1995 caused large enhancements
of CO and smaller enhancements of ozone in the southeastern United States. The Canadian fire plumes were carried by north erly flows associated with high pressure systems on the back side of cold fronts. We use here a GEOS-CHEM simulation for the summer 1995 to demonstrate large aerosol EC and OC enhancements from these fires at IMPROVE sites in Arkansas (UPBU), Tennessee (GRSM) and Kentucky (MACA).
Our simulation of the 1995 Canadian wildfi res uses daily, geographically resolved
emission data estimated from the area burned in each province. Those data are given by
Wotawa and Trainer [2000] for CO, and are scaled he re to our climatological biomass burning emission inventory for CO [ Lobert et al. , 1999] to derive corresponding EC and OC emissions. The resulting EC and OC em issions from the fires are 0.34 and 2.41 Tg, respectively, and are distributed in five areas (Northwest Territories, Alberta, Saskatchewan, Manitoba, and Ontario) for four burning periods from 17 June to 13 July. Figure 12 shows the time series of simulated and observed EC and OC concentrations
at three sites in the southeas tern United States: UPBU in Arkansas, MACA in Kentucky, and GRSM in Tennessee. There are two large peaks in the observations, for July 1 and July 8, which are captured by the model and are due to the Canadian fires (compare solid and dashed lines in Figure 12). The timing of those peaks is consistent with those concurrently observed for CO at nearby sites [ McKeen et al. , 2002]. Our simulation of the magnitude of the July 7-9 event is im proved in a sensitivity simulation where we assume initial lifting of the fire emissions up to 4 km altitude (Figure 12, dotted line). Such lifting can be expected from buoyanc y, particularly for large crown fires [ Liousse et
al. , 1996; 1997; Lavoué et al. , 2000].
Our model simulation allows us to assess th e influence of Canadi an fire emissions on
seasonal aerosol concentrations in the United States for th e summer of 1995. We find
that the events associated with Canadian fire plumes persisted typically for 3-5 days. On

28a seasonal basis, they caused the mean J une-August 1995 natural EC to increase by 80% (east) and 36% (west) and the mean OC to increase by 23% (east) and 16% (west), relative to a sensitivity simula tion with no Canadian fires.

6. Implications for natural visibility in the United States
We use results from our model to estimate the role of natural carbonaceous aerosols in visibility reduction and compare to the default values recommended by EPA [2001] for application of the Regional Haze Rule. Our 1998 simulation with a posteriori sources yields annual average concentra tions of natural EC and OC from fires and vegetation of

0.09 μ g/m 3 and 1.09 μ g/m 3 , respectively, for the western United States (west of 95 o W)
and 0.06 μ g/m 3 and 0.95 μ g/m 3 , respectively, for the eastern United States. In order to compute the light extinction by OC we need to multiply the OC ma ss by 1.4 to obtain an Organic Carbon Mass (OMC) that accounts fo r the non-carbon additional mass attached to OC aerosols [ Malm et al. , 1994]. The resulting annual average for natural OMC is

1.52 μ g/m 3 and 1.33 μ g/m 3 for the west and east, respec tively. Except for OMC in the eastern United States, our best estimates of natural concentrations for EC and OMC are significantly higher than the de fault values recommended by EPA [2001] which are 0.02

μ g/m 3 for EC, and 0.47 μ g/m 3 (west) and 1.40 μ g/m 3 (east) for OMC.
Several issues need to be addressed in th is comparison to the EPA default values. First, 1998 had unusually high fi re emissions, principally fr om Mexico and Canada, as shown in Figure 1. Second, it is important to quantify the contribu tion of transboundary transport to natural EC and OC concentrati ons in the United States. Third, there is ambiguity from a U.S. policy standpoint as to whether intercontinental transport of anthropogenic pollution (as from Asia) should be considered part of the “natural” background. To address these issues we c onducted three sensitivity simulations, with
sources modified from those in our standa rd 1998 simulation. The first includes no EC and OC sources in the United States to qua ntify the contributions from transboundary transport, mostly from Canada and Mexic o. The second includes EC and OC sources from Asia only, to quantify the transpacific transport. The third uses climatological biomass burning emissions as shown in Figure 1 in order to derive mean default values of
natural EC and OC concentrati ons in the United States. Th e results are summarized in
Table 2. We find that the transboundary transport of anthropogenic sources makes only a small contribution (less than 10%) to the total anth ropogenic concentrations of EC and OC in the United States. However, the transboundary transport of natural sources, mostly from fires in Canada and Mexico, makes a larg e contribution to annual mean natural concentrations in the United States for 1998 (44% in the west and 67% in the east for EC;
28% in the west and 37% in the east for OC). Transpacific transport from Asian sources is found to make little contribution to EC
and OC concentrations in the United Stat es, even in the context of the natural background. The concentrations generated in the simulation with anthropogenic and natural Asian sources only (Table 2) am ount to less than 2% of the natural OC concentrations from the standard simulation, and less than 10% of the natural EC. The
small role of intercontinen tal transport in contributi ng to background EC and OC
concentrations over the United States reflects the short lifetime of these species against wet deposition, particularly considering that the lifting of air from the continental

29boundary layer to the free troposph ere involves wet processes [ Stohl , 2001]. This can be contrasted to ozone, for which transport from outside North America makes a large contribution to the U.S. background [ Fiore et al. , 2002].
Our best estimates of mean natural EC a nd OC concentrations for comparison to the
EPA default values are obtained from the simulation using mean climatological fire emissions. We find annual average concen trations of natural EC and OMC of 0.06 μ g/m 3

and 1.25 μ g/m 3 , respectively, for the western United States and 0.04 μ g/m 3 and 1.17

μ g/m 3 , respectively, for the eastern United States (Table 2). These are higher by a factor of 2-3 than the EPA default values except for OMC in the eastern United States which is lower by 16%. The implications of our results for natural visibility estimates are substantial, particularly in the western United States. Ou r higher natural OMC component relative to
EPA’s default estimates results in lo wer natural visibil ity. For example, EPA [2001] uses
its default natural PM concentrations to derive mean light extinctions of 15.60×10 -6 m -1

and 15.78×10 -6 m -1 at Bandelier National Monument (BAND, New Mexico) and at Yellowstone National Park (YELL, Wyoming). Applying the EPA [2001] visibility formula with our best estimates of natural EC and OMC (from the simulation with climatological mean fires), and using EPA default values for the other PM components, we find natural light extinctions of 19.13×10 -6 m -1 and 19.31×10 -6 m -1 at BAND and YELL, respectively, about 22% higher than EPA values.

7. Conclusions We used the GEOS-CHEM global 3-D model to simulate observed concentrations of elemental carbon (EC) and organic carbon (OC) from a network of 45 sites in relatively remote regions of the United States (IMP ROVE network). Our focus was to better quantify the anthropogenic and natural sources of EC and OC in the United States, and the role of transboundary and in tercontinental transport, in the context of assessing the effect of these aerosols on visibility. We conducted a 1-year simulation for 1998 using best a priori estimates of EC and OC sources, including global satellite observations of fires, and comp ared the results to
observed concentrations at the IMPROVE sites. Wildfire emissions were from a gridded climatological inventory, scal ed to monthly fire emissions for 1998 using satellite fire count data. The model reproduces well th e spatial pattern in the observations (R 2 = 0.84 for EC, R 2 = 0.67 for OC) but is biased low by 15% for EC and 26% for OC. From a multiple linear regression fit we concluded that fossil fuel and biofuel emissions for EC
and OC in the United States should be increased by 15%, and 65% respectively from a priori levels, while biomass burning emissions for both EC and OC should be decreased by 17% and the biogenic source for OC s hould be increased by 11%. Our best a posteriori estimates are given in Table 1.
Canadian fire influence on the United Stat es in 1998 was largel y confined to the upper Midwest, where no IMPROVE data are available. We conducted an additional simulation for the summer of 1995, for which larg e CO enhancements in the southeastern
United States from Canadian fires had previously been reported [ Wotawa and Trainer

, 2000]. We find correspondingl y large EC and OC enhancements in the IMPROVE observations for this region, which the mode l captures and diagnoses as being due to
Canadian fire emissions. Model results indica te that Canadian fires in 1995 enhanced the

30mean June-August natural EC a nd OC concentrations in the eastern United States by 80% and 23%, respectively.
Our 1998 and 1995 simulations lead confidence in the representation of fire emissions
of EC and OC in the model. We used a simu lation with climatological monthly mean fire emissions, together with our best estimate of the biogenic OC source, to estimate natural
concentrations of carbonaceous aerosols in the United States for purpose of natural visibility assessments and applica tion of the EPA Regional Haze Rule [ EPA , 2001]. Our
best estimates of natural annual mean concentrations for EC are 0.06 μ g/m 3 in the western United States (west of 95 o W) and 0.04 μ g/m 3 in the east; for organic carbon mass (OMC = 1.4 OC, to account for the non-carbon contribution to OC aerosols), they are

1.25 μ g/m 3 in the west and 1.17 μ g/m 3 in the east. These values are 2-3 times higher than the default values recommended by EPA [2001] for application of the Regional Haze Rule, except for OMC in the east (16% lower). Our higher estimates of the natural OMC
concentrations relative to EPA’s default estimat es result in higher na tural light extinction (and hence lower natural visibility) by 22% in the western United Stat es. We also find a large seasonal variability in na tural light extinction from EC and OC, with highest values in summer due to sources from wildfires and vegetation. We further investigated the contribution from transboundary transport to EC and OC
concentrations in the United States. A sens itivity simulation with no EC and OC sources
in the United States shows that fires in Me xico and Canada made a large contribution to
annual mean natural concentrations of EC (40-70%) and OC (30-40%) in the United States in 1998. A sensitivity simulation with Asian sources only shows that transpacific transport contributes less th an 10% of the natural backgr ound EC over the United States,
and less than 2% of the natural background OC.

Acknowledgments. This research was supported by the Electric Power Research Institute (EPRI) and the U.S. Environmental Protection Agency (EPA). The authors are grateful to R. Yevich for providi ng her annual biofuel emission data.

References

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Figures Captions

Figure 1. Yearly biomass burning OC em ission in 1997-2000 for North and Central America, and climatological mean value (see text).

Figure 2. Annual biomass burning OC emissi on over North and Central America in 1998 (top) and seasonal variations for different regions (bottom).

Figure 3. IMPROVE sampling sites w ith continuous records for 1998.

Figure 4. Annual mean concentrations of EC (l eft) and OC (right) in surface air over the United States in 1998. The top panel shows results from the GEOS-CHEM model using a priori sources. The middle panel shows th e IMPROVE observations plotted on the
model 2 o × 2.5 o grid. The bottom panel shows the difference between the two.

Figure 5. Scatterplot of simulated (GEO S-CHEM) vs. observed (IMPROVE) annual
mean EC and OC concentrations for the da ta shown in Figure 4. The pluses and the
circles indicate data in the western and eastern United States (separated at 95 o W), respectively. The asterisks with letter labels indicate sites discarded in the statistical analysis (see text): REDW(A), PORE(B), PINN(C), SEQU(D), GLAC(E), OKEF(F), and BRIG(G). The squares indicate OC data at MORA(H) and THSI(I) sites which were

33discarded in statistical analysis for OC. The thin solid and dotted li nes represent the y = x
relation and a factor of 2 deviation. The thic k solid line represents the reduced major-axis linear regression [ Hirsch and Gilroy , 1984], excluding sites A-I. The Pearson correlation
coefficients R 2 and regression equations are indicated.

Figure 6. Seasonal variation of monthly mean EC concentrations in 1998 at selected
IMPROVE sites. Site locations are shown in Figure 1. Values are monthly means. Closed
circles indicate the observations. Dashed and solid lines represent the model simulations
with a priori and a posteriori sources, respectively. The a priori model components by source types are indicated as thin solid lines with symbols: asterisks (fossil fuel combustion), diamonds (biomass burning), and squares (biofuel use).

Figure 7. Same as in Figure 6 but for OC. The a priori model results by source types are represented as thin solid lin e with asterisks (fossil fuel ), diamonds (biomass burning), squares (biofuel), and triangles (biogenic terpenes).

Figure 8. Scatterplots of monthly mean EC (left two columns) and OC (right two columns) simulated vs. observed concentrations with a priori (left) and a posteriori (right) sources, for the ensemble of IMPROVE sites and for indivi dual seasons in 1998.
Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circles, respectively. Thin solid li nes indicate a perfect match of the model results with observations, and do tted lines denote a factor of 2 departure. Thick solid lines represent the reduced major axis regressi on. The Pearson correlation coefficients R 2 are indicated.

Figure 9. Annual mean concentrations of EC (l eft) and OC (right) in surface air over the United States in 1998 from the GEOS-CHEM model using a posteriori sources.

Figure 10. Contribution from different so urces types to EC concentrations ( μ g m -3 ) in
surface air for DJF and JJA. Values are model results for 1998 using a posteriori sources (Table 1).

Figure 11. Same as Figure 10 but for OC.

Figure 12. Concentrations of EC and OC at th ree southeastern U.S. sites (UPBU, MACA, and GRSM) in June-July 1995. Observations (2 4-h averages, twice a week) are shown as
asterisks. The solid line shows results from the standard model simulation. Results from sensitivity simulations without Canadian fi re emissions (dashed line) and with fire emissions initially mixed to 600 hP a (dotted line) are also shown.

34Tables

Table 1. Carbonaceous aerosol source s in the GEOS-CHE M model (1998). Aerosol Source type Global (Tg yr -1 ) a United States (Tg yr -1 ) A priori A posteriori

EC 22.0 0.66 0.75
Fossil fuel 6.6 0.52 0.60
Biofuel 1.4 0.04 0.07 Biomass burning 14.0 0.10 0.08

OC 129.8 2.70 3.11
Fossil fuel 10.6 0.45 0.52
Biofuel 7.6 0.54 0.89 Biomass burning 97.9 0.72 0.60 Biogenic 13.7 0.99 1.10

a Including a posteriori emissions for the United States.

Table 2. Natural and anthropogeni c EC and OC concentrations ( μ g m -3 ) in the United

States a

. Natural concentrations Anthropogenic concentrations

West East West East

EC 1998 emissions (base) 0.09 0.06 0.21 0.62

No U.S. sources 0.04 0.04 0.02 0.02 Asian sources only 0.003 0.001 0.005 0.003 Climatological fire emissions 0.06 0.04 0.21 0.62

OMC b
1998 emissions (base) 1.52 1.33 0.52 1.90

No U.S. sources 0.43 0.49 0.05 0.05 Asian sources only 0.022 0.013 0.013 0.007 Climatological fire emissions 1.25 1.17 0.52 1.90

a Values are annual means from the standard 1998 simulation (base) and from the sensitivity simulations described in section 5. Partition between West and East is at

95 o W. The natural concentrations from the si mulation with climatological fire emissions can be compared to the de fault estimates suggested by EPA [2001] for application of the Regional Haze Rule: 0.47 μ g m -3 (West) and 1.40 μ g m -3 (East) for OMC, and 0.02 μ g m 3 for EC.

b Organic carbon mass (OMC), defined as 1.4 times the OC mass to account for noncarbon contributions to the organic aerosol.

35Figures

Figure 1. Yearly biomass burning OC em ission in 1997-2000 for North and Central America, and climatological mean value (see text).

36Figure 2. Annual biomass burning OC emissi on over North and Central America in 1998 (top) and seasonal variations for different regions (bottom).

37Figure 3. IMPROVE sampling sites with continuous records for 1998.

38Figure 4. Annual mean concentrations of EC (l eft) and OC (right) in surface air over the United States in 1998. The top panel shows results from the GEOS-CHEM model using a priori sources. The middle panel shows th e IMPROVE observations plotted on the
model 2 o × 2.5 o grid. The bottom panel shows the difference between the two.

39Figure 5. Scatterplot of simulated (GEO S-CHEM) vs. observed (IMPROVE) annual
mean EC and OC concentrations for the da ta shown in Figure 4. The pluses and the
circles indicate data in the western and eastern United States (separated at 95 o W), respectively. The asterisks with letter labels indicate sites discarded in the statistical analysis (see text): REDW(A), PORE(B), PINN(C), SEQU(D), GLAC(E), OKEF(F), and BRIG(G). The squares indicate OC data at MORA(H) and THSI(I) sites which were discarded in statistical analysis for OC. The thin solid and dotted li nes represent the y = x
relation and a factor of 2 deviation. The thic k solid line represents the reduced major-axis linear regression [ Hirsch and Gilroy , 1984], excluding sites A-I. The Pearson correlation
coefficients R 2 and regression equations are indicated.

40Figure 6. Seasonal variation of monthly mean EC concentrations in 1998 at selected
IMPROVE sites. Site locations are shown in Figure 1. Values are monthly means. Closed
circles indicate the observations. Dashed and solid lines represent the model simulations
with a priori and a posteriori sources, respectively. The a priori model components by source types are indicated as thin solid lines with symbols: asterisks (fossil fuel combustion), diamonds (biomass burning), and squares (biofuel use).

41Figure 7. Same as in Figure 6 but for OC. The a priori model results by source types are represented as thin solid lin e with asterisks (fossil fuel ), diamonds (biomass burning), squares (biofuel), and triangles (biogenic terpenes).

42Figure 8. Scatterplots of monthly mean EC (left two columns) and OC (right two columns) simulated vs. observed concentrations with a priori (left) and a posteriori (right) sources, for the ensemble of IMPROVE sites and for indivi dual seasons in 1998.
Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circles, respectively. Thin solid li nes indicate a perfect match of the model results with observations, and do tted lines denote a factor of 2 departure. Thick solid lines represent the reduced major axis regressi on. The Pearson correlation coefficients R 2 are indicated.

43Figure 9. Annual mean concentrations ( μ g m -3 ) of EC (left) and OC (right) in surface air over the United States in 1998 from the GEOS-CHEM model using a posteriori sources.

44Figure 10. Contribution from different so urces types to EC concentrations ( μ g m -3 ) in
surface air for DJF and JJA. Values are model results for 1998 using a posteriori sources (Table 1).

45Figure 11. Same as Figure 10 but for OC.

46Figure 12. Concentrations of EC and OC at th ree southeastern U.S. sites (UPBU, MACA, and GRSM) in June-July 1995. Observations (2 4-h averages, twice a week) are shown as
asterisks. The solid line shows results from the standard model simulation. Results from sensitivity simulations without Canadian fi re emissions (dashed line) and with fire emissions initially mixed to 600 hP a (dotted line) are also shown.

47Appendix B: Rokjin J. Park, Daniel J. Jacob, Brendan D. Field, Robert M. Yantosca, and Mian Chin (2004), Natural and transboundary pollution influences
on sulfate-nitrate-ammonium aerosols in the United States: implications for policy, J. Geophys. Res. , 109, D15204, doi:10.1029/2003JD004473.

Abstract.

We use a global 3-D coupled oxidant-aer osol model (GEOS-CHEM) to estimate natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosol
concentrations in the United States. This wo rk is motivated in part by the Regional Haze
Rule of the U.S. Environmental Protecti on Agency (EPA), which requires immediate action to improve visibility in U.S. wilderne ss areas along a linear trajectory towards an endpoint of “natural visibility conditions” by 2064. We present full-year simulations for
1998 and 2001 and evaluate them with nationwid e networks of observations in the United States and Europe (IMPROVE, CASTNET, NADP, EMEP) and with Asian outflow
observations from the NASA TRACE-P aircra ft mission. Shutting off U.S. anthropogenic emissions in the model defines “background” aerosol concentrations representing contributions from both natural and transboundary pollution sources. We find that transboundary transport of po llution from Canada, Mexico, and Asia dominates over
natural influences for both sulfate and nitrat e. Transpacific transport of Asian pollution accounts for 30% of background sulfate in both the western and eastern United States.
Our best estimates of natural concentrat ions for ammonium sulfate and ammonium
nitrate in the United States are either consis tent with or lower than the default values recommended by EPA for natural visibil ity calculations. However, the large transboundary pollution influence in our calcu lation suggests that a natural visibility objective cannot be approached without international emission controls.

1. Introduction Visibility degradation in the United Stat es is mostly due to fine aerosols [ Malm et al., 2000] including carbonaceous (elemental and organic), sulfate, nitrate, and soil dust components. These aerosols originate from both anthropogenic and natural sources. The U.S. Environmental Protection Agency Regional Haze Rule [ U.S. EPA , 2003a] mandates a schedule of increasing emission controls to achieve “natural visibility conditions” in national parks and other wilderness areas of the United States by 2064. Defining this natural visibility endpoint re quires better information on na tural aerosol co ncentrations and on the perturbing effects from trans boundary transport of anthropogenic pollution. We previously examined this issue in a global 3-D mode l simulation of carbonaceous aerosols [ Park et al. , 2003] and found that quantification of wildfire emissions was of critical importance. Transboundary transpor t of anthropogenic po llution was relatively unimportant for carbonaceous aerosols becau se of the large natural sources from wildfires and vegetation. We a pply here the same analysis to sulfate and nitrate aerosols, which are other important components of visi bility degradation and hence prime targets for regulation. As we will see, transb oundary transport of pollution including intercontinental transport from Asia emerge s in this case as a critical concern.
The main sources of sulfate and nitrate aerosols are atmospheric oxidation of SO 2 and nitrogen oxides (NO

x ≡ NO + NO 2 ) to H 2 SO 4 and HNO 3 , respectively [ NARSTO

,

482003]. Fossil fuel combustion is the dominant source of SO 2 and NO

x in the United States. Important natural sour ces include volcanoes and atmos pheric oxidation of oceanic dimethylsulfide (DMS) for SO 2 ; and lightning, soils, and wildfires for NO

x [ NARSTO

, 2003]. The low vapor pressure of H 2 SO 4 over H 2 SO 4 -H 2 O solutions implies that all of sulfate is in the aerosol phase. The sulfate aerosols can be partly or totall y neutralized by ammonia (NH 3 ) emitted from livestock, fertilizer use, and other less important sources. If excess ammonia is available beyond that require d for sulfate neutralization to ammonium sulfate (NH 4 ) 2 SO 4 , then ammonium nitrate (NH 4 NO 3 ) aerosol can form; otherwise, and except for cloudy conditions, nitric acid rema ins in the gas phase. This simple H 2 SO 4 - HNO 3 -NH 3 thermodynamic framework provides a remarkably successful general description of sulfate and nitrate aerosols in the United States [ Seinfeld and Pandis , 1998;

NARSTO , 2003]. Sulfate and nitrate can also be incorporated in so il dust or sea salt particles, but these contributions appear to be significant only in desert and coastal areas. Transboundary transport of pollution could compromise the objective of “natural visibility” in the Regional Haze Rule. We de fine here an aerosol “background” following

U.S. EPA [2003b] as the aerosol co ncentration that would be present over the United
States in the absence of dome stic anthropogenic emissions. It includes contributions from natural sources but also from transboundary transport of pollution. If the latter are significant, then a “natural visibility” objective can be approached only through
international emission controls. Alternativ ely, one should replace this objective by a “background visibility” objectiv e that allows for uncontrollable emissions outside U.S.
borders. Intercontinental transport of Asian pollution is of particular interest for our study.
Previous studies have shown that Asia n pollution makes a significant (2-6 ppbv) contribution to background ozone concentrations in surface air in the United States [ Berntsen et al. , 1999; Jacob et al. , 1999; Fiore et al. , 2002], principally by enhancing the northern hemispheric ozone background [ Fiore et al. , 2003b]. Export a nd transpacific transport of Asian aerosol pollution is expect ed to be far less efficient than for ozone because the lifting of Asia n air to the free troposphere involves wet processes (convection, warm conveyor belts) [ Liu et al. , 2003] that scavenge aerosols with high efficiency [ Koike et al. , 2003]. Most previous studies of transpacific transport of aerosols have focused on dust events, where the Asian source is very large and the lifting to the free troposphere takes place by dry processes [ Husar et al. , 2001; McKendry et al. , 2001; Vaughan et al. , 2001]. However, Jaffe et al. [1999, 2003] and Bertschi et al. [2003] also showed significant aerosol enhancements in Asian pollution plumes sampled over the west coast of the United States in spring. As we will see, our model results suggest that transpacific Asian pollution is a major cont ributor to the sulfate background over the United States on an annual average basis.

2. Model description 2.1 General description We use the GEOS-CHEM chemical transport model (CTM) [ Bey et al. , 2001a] to conduct full-year simulations for 1998 a nd 2001 of the sulfate-nitrate-ammonium inorganic aerosol system coupled to oxidant chemistry. Most of our analysis focuses on the 2001 simulation. The 1998 simulation is used for evaluation with European observations, as 2001 observations were not available in a timely manner. The GEOS49CHEM model (version 5.03, http://www-as .harvard.edu/chemistry/trop/geos) uses assimilated meteorological data from th e NASA Goddard Earth Observing System (GEOS) including winds, convective mass fluxe s, mixed layer depths, temperature, clouds, precipitation, and surface properties. Meteorological data for 1998 and 2001 are available with 6-hour temporal resolution (3-hour for surface variables and mixing depths), 1 o latitude by 1 o longitude (1 o × 1 o ) horizontal resolution, and 48 sigma vertical layers. We degrade the horizontal resolution to 2 o × 2.5 o for computational expediency.
The lowest model levels are centere d at approximately 10, 50, 100, 200, 400, 600, 900, 1200, and 1700 m above the local surface. The GEOS-CHEM simulation of tropos pheric oxidant chemistry includes a
detailed ozone-NO

x -hydrocarbon chemical mechanism (~80 species, ~300 reactions).
Results from this simulation have been reported in a number of papers [ Bey et al., 2001ab; Li et al., 2001, 2002ab; Liu et al. , 2002; Martin et al., 2002] including focused
studies of surface ozone in North Am erica and North American outflow [ Fiore et al., 2002, 2003ab; Li et al. , 2004]. GEOS-CHEM simulations of aerosols have been reported previously for radionuclides [ Liu et al., 2001] and carbonaceous species [ Park et al., 2003]. The H 2 SO 4 -HNO 3 -NH 3 aerosol simulation is a new capability for GEOS-CHEM and is described in more detail below. The aerosol and oxidant simulations are coupled through formation of sulfate and nitrate, HNO 3 (g)/NO 3 - partitioning of total inorganic nitrate, heterogeneous chemistry [ Jacob , 2000], and aerosol eff ects on photolysis rates [ Martin et al., 2003]. Partitioning of total ammonia and nitric acid between the gas and aerosol phases is calculated using th e MARS-A thermodynamic equilibrium model [ Binkowski and Roselle, 2003]. The wet deposition scheme for aerosols is described by Liu et al. [2001]. It includes contributions from scavenging in conve ctive updrafts, rainout and washout from convective anvils and large-scale precipitation, and it allows for return to the atmosphere following evaporation. We extend it here to so luble gases on the basi s of their effective Henry’s law partitioning in warm clouds, re tention efficiency upon droplet freezing in mixed clouds, and surface coating or co-condens ation of ice crystals in cold clouds [ Mari
et al. , 2000]. Scavenging of SO 2 is limited by the local availability of H 2 O 2 as a fast aqueous-phase oxidant converting SO 2 to sulfate [ Chin et al. , 1996, 2000a]. Dry deposition of aerosols and gases uses a standa rd resistance-in-series model dependent on local surface type and me teorological conditions [ Wesely , 1989], and implemented as described by Wang et al. [1998].
We conducted five different simulati ons for 2001 including one standard simulation as described above, and four sens itivity simulations ex cluding anthropogenic emissions (1) globally, (2) in the United Stat es, (3) in North America, and (4) in Asia. From these we quantify the influences of natural, transboundary, and intercontinental pollution sources on sulfate-ni trate-ammonium aerosol concentrations in the United

States.
Each simulation was carried out as follo ws. We first conducted a fully coupled
oxidant-aerosol simulation at 4 o × 5 o horizontal resolution for computational expediency. Oxidant concentration fields (OH, O 3 , NO 3 ), H 2 O 2 production rates and photolysis frequencies, and total inorganic nitrate concen trations (gas-phase nitric acid plus aerosol nitrate) were archived from this simu lation and used to conduct an aerosol-only
simulation at finer 2 o × 2.5 o horizontal resolution. The aeros ol-only simulation includes 9

50prognostic chemical species: dimethylsulfide (DMS), SO 2 , sulfate, methane sulfonic acid (MSA), HNO 3 (g), NO 3 - , NH 3 (g), NH 4 + , and H 2 O 2 . The 2001 and 1998 simulations were initialized on October 1, 2000 and October 1, 1997, respectively, and conducted for 15
months. The first three months were used to achieve proper initialization, and we focus our attention on the following 12 months.

2.2 Sulfur simulation
The sulfur simulation in GEOS-CHEM is based on the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiat ion and Transport (GOCART) model [ Chin et al., 2000a], with a number of modifications described below. Our fossil fuel and industrial emission inventory is for 1999-2000 and is obtained by scaling the gridded, seasonally resolved inventory from the Globa l Emission Inventory Activity (GEIA) for 1985 [ Benkovitz et al. , 1996] with updated national emission inventories and fuel use data [ Bey et al. , 2001a]. The emissions for the Un ited States and Canada are from U.S. EPA [2001], and the emissions for Eu ropean countries are from EMEP [2003]. Asian sulfur emission in the model is 20 Tg S yr -1 , which can be compared to year 2000 estimates of 17 Tg S yr -1 by Streets et al. [2003] and 25 Tg S yr -1 by IPCC [2001]. Anthropogenic
sulfur is emitted as SO 2 except for a small fraction as sulfate, 5% in Europe and 3% elsewhere [ Chin et al. , 2000a]. Other anthropogenic sources of SO 2 in the model include gridded monthly aircraft emissions (0.07 Tg S yr -1 ) taken from Chin et al. [2000a] and biofuel use. We use a global biofuel CO emission inventory with 1 o × 1 o spatial resolution from Yevich and Logan [2003] and apply an emi ssion factor of 0.0015 moles SO 2 per mole CO [ Andreae
and Merlet , 2001]. Seasonal variations in biofuel em issions are specified from the heating degree-days approach [ Park et al., 2003]. Natural sources of sulfur in the model include DMS from oceanic phytoplankton
and SO 2 from volcanoes and biomass burning. The oceanic emission of DMS is calculated as the product of local seawater DMS concentration and sea-to-air transfer velocity. The seawater DMS concentrati ons are gridded monthly averages from Kettle et
al. [1999], and the transfer velocity of DMS is computed using an empirical formula from
Liss and Merlivat [1986] as a function of the surface (10m) wind speed. The GEOS
surface winds used here assimilate remote sensing data from the Special Sensor Microwave Imager (SSM/I) instru ment. Volcanic emissions of SO 2 from continuously
active volcanoes are included from the database of Andres and Kasgnoc [1998]. Emissions from sporadically erupting volcanoe s show large year-to- year variability and are not included in the model. No major volcanic eruptions occu rred in 2001. Biomass burning emissions of SO 2 are calculated using a gr idded monthly biomass burning inventory of CO constrained from satellite observations in 2001 by Duncan et al. [2003]
with an emission factor of 0.0026 moles SO 2 per mole CO [ Andreae and Merlet , 2001]. Table 1a summarizes global and contiguous U.S. (excluding Alaska and Hawaii)
sulfur emissions for 2001. The United States c ontribute 10% of the global source (15% of the global anthropogenic source). Natural sources contribute 27% globally and are negligible within the contiguous United States. The gas-phase sulfur oxidation chemistr y in the model includes DMS oxidation by OH to form SO 2 and MSA, by nitrate radicals (NO 3 ) to form SO 2 , and SO 2 oxidation by OH to form sulfate. Reaction rates are from DeMore et al. [1997] and the yields of

51SO 2 and MSA from DMS oxidation are from Chatfield and Crutzen [1990]. Aqueousphase oxidation of SO 2 by O 3 and H 2 O 2 in clouds to form sulfate is included using kinetic
data from Jacob [1986] and assuming a pH of 4.5 for the oxidation by O 3 . Cloud liquid
water content is not available in the GEOS data and we specify it instead in each cloudy grid box by using a temperature- dependent parameterization [ Somerville and Remer

, 1984]. The cloud volume fraction in a given grid box is specified as an empirical function of the relative humidity following Sundqvist et al. [1989].

2.3 Ammonia simulation
Ammonia emissions in the model are based on annual data for 1990 from the 1 o × 1 o GEIA inventory of Bouwman et al. [1997]. Source categories in that inventory include domesticated animals, fertilizers, human bodies, industry, fossil fuels, oceans, crops, soils, and wild animals. We view the first five as anthropogenic and the last four as natural. Additional emissions from biomass burning and biofuel use are computed using the global inventories of Duncan et al. [2003] and Yevich and Logan [2003], with an emission factor of 1.3 g NH 3 per kg dry mass burned [ Andreae and Merlet , 2001]. The resulting total annual source of ammonia for the United St ates is reduced by 10% to match that derived by Gilliland et al. [2003] from an inverse m odel analysis of monthly precipitation chemistry (NH 4 + ) data. Table 1b shows a summary of global and c ontiguous U.S. ammonia emissions for
2001. The United States account for 5% of the global source (6% of the global anthropogenic source). Natural sources amount to 37% of global ammonia emissions and 21% of contiguous U.S. emissions.
Several ammonia sources in Table 1b ha ve strong seasonal variations. For the
emissions from domesticated animals a nd soils we use exponential dependences on temperature reported by Aneja et al. [2000] and Roelle and Aneja [2002], respectively. Ammonia emissions from crops and fertilizers are assumed to vary seasonally with the number of daylight hours [ Adams et al. , 1999]. Seasonal variations in biomass burning and biofuel emissions are specified from satellite observations [ Duncan et al. , 2003] and the heating degree-days approach [ Park et al., 2003], respectively. Figure 1 shows the resulting seasonal variation of ammonia emi ssion in the United States. The summer maximum is driven mainly by domesticated an imals. Compared to the results of the
Gilliland et al. [2003] inverse model analysis, also shown in Figure 1, our seasonal cycle lags in phase by 1-2 months and emission in October is a factor of 2 higher.

2.4 Nitrate simulation Production of total inorganic nitrate (gas-pha se nitric acid and aerosol nitrate) in the model is computed from the ozone-NO

x -hydrocarbon chemical mechanism (see section 2.1). Table 1c gives a summary of global and contiguous U.S. NO

x emissions;
details on these sources are in Bey et al. [2001a] and Martin et al. [2002]. The United States account for 17% of global emissions (25% of global anthropogenic emissions). Natural sources from lightning, soils, and biomass burning account for 38% of global
emissions and 9% in the contiguous United States.

2.5 Global budgets

52Tabulated summaries of the global sulf ate, nitrate, and ammonium aerosol budgets in GEOS-CHEM are given by Martin et al. [2004], who applied the model to an investigation of phase transi tion effects on aerosol radiativ e forcing. The global sulfate,
nitrate and ammonium burd ens for 2001 are 0.40 Tg S, 0.07 Tg N, and 0.32 Tg N, respectively. The lifetimes against deposition are 3.9, 3.2, a nd 3.8 days, respectively. Wet deposition accounts for 80 - 90% of total deposition. Our global sulfate burden is lower than t hose (0.54-1.03 Tg S) from models that participated in the COmparison of large-scale atmospheric Sulfate Aerosol Models (COSAM) [ Barrie et al., 2001]. Our anthropogenic emission (57 Tg S yr -1 ) is lower than that used in COSAM (67 Tg S yr -1 ) because our emission inventory is for 1999-2000 (vs. 1985 in COSAM) and accounts for emission redu ctions in Europe (by 61% since 1985) and the United States (by 22% since 1985). The major natural sulfur sources in our model from oceans (15 Tg S yr -1 ) and volcanoes (5 Tg S yr -1 ) are also lower than those used in COSAM (29 and 10 Tg S yr -1 , respectively). These natural sources contribute disproportionately to the global atmospheric sulfate burden because their sulfur can be delivered efficiently to the free troposphe re where precipitation is infrequent [ Chin and
Jacob , 1996]. The lifetime of sulfate in our simula tion (3.9 days) is at the low end of the 3.6 – 7.5 days found in COSAM. Our annual average tropospheric ammonium burden (0.32 Tg N) is consistent with values from previous m odel studies (0.30 – 0.33 Tg N) [ Dentener and Crutzen

, 1994; Adams et al. , 1999] and the lifetime of ammonium is also similar (4.2 – 4.5 days). Our annual average tropospheric nitrate burden (0.07 Tg N) is within the range of 0.03 to 0.09 Tg N found in the previous model study by Adams et al. [1999, 2001].

3. Model evaluation
We focus our model evaluation on surface networks of sulfat e-nitrate-ammonium
aerosol observations in the United States a nd Europe. We also use sulfate wet deposition
data in the United States as a test of the su lfur budget, and aircraft observations off the Asian Pacific Rim as a test of Asian export. Previous evaluation with sulfate observations at remote sites has been presented by Chin et al. [2000b] using the GOCART model
which is similar to ours. Previous ev aluations of GEOS-CHEM with aerosol radionuclides globally, and with carbonaceous ae rosols in the United States, have been presented by Liu et al. [2001] and Park et al. [2003], respectively. Other GEOS-CHEM
studies have evaluated the simulation of ozone and nitrogen oxides in the United States [ Fiore et al ., 2002, 2003ab; Li et al. , 2004] and the transpacific transport of Asian ozone and CO pollution [ Jaeglé et al. , 2003; Heald et al. , 2003].

3.1 United States
We use aerosol observations for the year 2001 at 141 IMPROVE and 79 CASTNET sites, and wet deposition data at 226 NADP sampling sites (Figure 2). The IMPROVE monitoring program was initiate d in 1987 in national parks and other protected environments to identify the cont ributions of different aerosol components to visibility degradation [ Malm et al. , 1994]. The data for 2001 c onsist of 24-h sulfate and nitrate concentrations measured every thir d day by Particle Induced X-ray Emission (PIXE) and ion chromatography (IC), respec tively. There are no ammonium data. The
CASTNET network of rural site s was initiated in 1990 to mo nitor regional air pollution

53[ Lavery et al. , 2002]. It provides weekly average concen trations of sulfate, nitrate, and ammonium measured by IC. The NADP networ k provides weekly chemical precipitation data [ NADP , 2002]. Sites are predominantly located in rural areas and away from point sources of pollution. Weekly precipitation sa mples are analyzed for sulfate using IC. Figure 3 compares simulated and observed annual mean sulfate concentrations at
the 141 IMPROVE and 79 CASTNET sites fo r the year 2001, plotted on the 2 o × 2.5 o model grid. Values are higher in the eastern than the western United States and are highest in the industrial midw est, reflecting the distributi on of anthropogenic emissions. Figure 4 shows scatterplots of simulated vs. observed annual and seasonal sulfate concentrations for the ensemble of IMPROVE (left) and CASTNET sites (center). The right column in Figure 4 compares simulate d and observed sulfate precipitation data at
NADP sites. The correlation between model a nd observations is high for the annual mean values (R 2 = 0.91-0.94 for the concentration data, 0.75 for the deposition data) and also for the seasonal means (R 2 = 0.79-0.90 for the concentr ation data, 0.58-0.74 for the deposition data). Western sites in the scatte rplots are represented with “+” symbols and should be in general most represen tative of background conditions. The R 2 coefficients
between model and observations for the subs et of western sites alone are 0.35-0.39 for
the annual mean concentrations at the IMPR OVE and CASTNET sites, lower than for the ensemble of U.S. sites, although this coul d largely reflect the weaker dynamic range. There is no significant bias in the simulation of concentrations at the cleanest western
sites. Regression lines are computed here and elsewhere with the reduced major axis method, which minimizes the area of the right triangle formed by vert ical and horizontal lines running from the observed point to the regression line. It is the most appropriate linear regression to characterize a relationship between two data sets with uncertainties [ Hirsch and Gilroy , 1984]. Results in Figure 4 show no significant model bias in the
simulation of annual mean concentrations (slope = 0.91-0.95) but a 30% low bias in summer (slope = 0.71-0.74). Loss of SO 2 in convective updrafts accounts for about 50% of sulfate wet deposition in summer in the model, and much less in other seasons. Our algorithm scavenges SO 2 in convective updrafts as a titr ation reaction limited solely by the supply of H 2 O 2 entrained in the updraft. However, kinetic limitations in the aqueousphase reaction of SO 2 with H 2 O 2 , as well as scavenging of H 2 O 2 , can greatly reduce the

SO 2 scavenging efficiency [ Mari et al., 2000; Kreidenweis et al , 2003]. Accounting for these limitations might correct the model bias but was not attempted here. Figure 5 compares simulated and observ ed annual mean concentrations of
ammonium at CASTNET sites. Observed concen trations are higher in the east than in the west and are highest in the midwest, re flecting agricultural op erations. The model reproduces this spatial distri bution but is too high in the midwest. Scatterplots of
simulated vs. observed annual and seasonal ammonium concentrations are shown in Figure 6 (left column) for the ensemble of sites. The model reproduces the variability of observed ammonium concentrations, both in an annual mean sense (R 2 = 0.90) and in different seasons (R 2 = 0.82-0.85). It shows a 30% high bias in annual mean concentrations which is mainly driven by th e fall (slope = 2.0). Co mparison with results
from the Gilliland et al. [2003] inverse model analysis suggests that our ammonia emissions are excessive in the fall (Figure 1). It appears that a simple exponential temperature dependence of emissions from livestock, as assumed here, does not

54adequately describe the seasonal variation of this dominant source. For the subset of
western sites alone th e model has a lower R 2 coefficient (0.53) between the simulated and
observed annual mean concentration than that for the ensemble of U.S. sites but no apparent high bias (slope = 1.02). Figure 7 compares simulated and observed annual mean nitrate concentrations at
the 141 IMPROVE and 79 CASTNET sites for 2001. The spatial distribution is similar to
that of ammonium concentrations in both th e observations and the model, reflecting the limitation of ammonium nitrate formation by th e availability of ammonia as discussed
further below. The model tend s to be too high, by a factor of 2 on an annual basis as shown by the scatterplots of Figure 6. Most of the bias is driven by summer and fall.
Nitrate formation is determin ed by the availability of ammonia beyond that required for sulfate neutralization; we find in a sensitivity analysis that the summer high bias for nitrate can be explained in large part by the low bias of sulfate. High nitrate in fall is likely caused by excessive ammonia emissions. However, the factor of 2 high bias for the simulated annual mean nitrate concentration relative to the observation is not apparent for the subset of western sites alone (slope = 1.09 - 1.34). Figure 8 shows the simulated Gas Ratio (GR) defined as

][ ][2][

3 2

4 3

T T

HNO SO NH GR −

−

= , (1)

where concentrations are in molar units, [NH 3 T ] is the sum of gas-phase ammonia and aerosol-phase ammonium concentrations, [HNO 3 T ] is the total inorganic nitrate concentration (sum of gas-phase nitr ic acid and aerosol nitrate), and [SO 4 2- ] is the sulfate concentration. The value of GR diagnoses th e limiting reactant (ammonia or nitric acid) for the formation of ammonium nitrate [ Ansari and Pandis , 1998]. We find that
ammonium nitrate formation in most of North America is generally limited by the supply of ammonia (GR < 1). Exceptions are the upper Midwest and Mexico, where GR > 1
indicates that nitrate formation is limite d by the supply of nitric acid. Negative GR values, indicating an acidic sulfate aerosol, are mainly confined to the oceans. This neutralization of the aerosol is further illustrated in Figure 9, which compares the simulated (top) vs. observed (bottom) acidity of aerosols at CASTNET sites for different seasons as the regression slopes of the [NH 4 + ] vs. (2[SO 4 2- ] + [NO 3 - ]) scatterplots. The observations show an annual mean slope of 0.84, i.e., within 16% of neutralization, and varying from 0.79 in summer to 0.93 in winter. The higher acidity in summer reflects the faster sulfate formation. The model is slig htly less acidic than the observations on an annual mean basis (slope 0.90) but has the same seasonal trend (0.84 in summer, 0.98 in winter). The weaker apparent model acidity re flects at least in part the association of
sulfate and nitrate in the observations with other alkaline cations (e.g., Ca 2+ ) not included
in the model.

3.2 Europe Figure 10 compares model results to a nnual and seasonal mean observations of sulfate, nitrate, and ammonium at 93 Europ ean EMEP sites in 1998. Sulfate in the model reproduces the variability in the observations (R 2 = 0.60 - 0.78) with no systematic bias (the regression slope for the annual mean data is 0.98). There is a slight underestimate in winter (slope = 0.84), possibly caused by seasalt sulfate included in the EMEP observations but not in the model [ Chin et al. , 2000b; Gong et al. , 2002]. Simulated

55nitrate and ammonium compare less well with observations, with 40-60% overestimates of ammonium in summer and fall, like ly due to excessive ammonia emission.

3.3 Asia
We evaluate our simulation of Asian out flow by using sulfate observations from
the TRACE-P aircraft mission conducted off the Asian Pacific Rim from bases in Hong Kong and Japan during February-April 2001 [ Jacob et al. , 2003]. Previous applications
of GEOS-CHEM to simulation of TRAC E-P observations for ozone, CO, CO 2 , CH 4 , and nitriles indicate a good simulation of Asian outflow pathways [ Liu et al. , 2004; Heald et
al. , 2003; Palmer et al. , 2003; Kiley et al. , 2003; Suntharalingam et al. , 2003; Xiao et al.

, 2003; Li et al. , 2003]. Bulk aerosol measurements from the DC-8 aircraft indicate that 40% of non–seasalt sulfate (nss-SO 4 2- ) on average was incorporated in dust particles [ Jordan et al. , 2003]. Figure 11 compares mean vertical profiles of simulated and
observed nss-SO 4 2- concentrations for the ensemble of DC-8 flights over the NW Pacific
west of 177 o E and at 30 o -45 o N latitude [ Liu et al. , 2003]. Monthly mean concentrations in the model were sampled along the flight track s. The observations shows strong outflow in
the 0-5 km column. The model also shows an enhancement in that column but is lower than observations, by up to a factor of two. Targeted sampling of Asian outflow in the observations [ Jacob et al. , 2003] could account for part of this discrepancy. In any case, the comparison argues that the model does not overestimate the outflow of sulfate from Asia. This is an important point for our later discussion of transpacific pollution
influence.

4. Background aerosol in the United Stat es: transboundary pollution influence We now apply our model simulations to quantify backgr ound sulfate-nitrateammonium aerosol concentrations in the United States, and to separate the contributions to this background from natural sources a nd from transboundary pollution. We use for this purpose a sequence of four sensitiv ity simulations excl uding anthropogenic emissions of both oxidant and aerosol precursor s (1) globally, (2) in the United States, (3) in North America, and (4) in Asia. The re sults are summarized in Table 2 as annual averages for the western (west of 95 o W) and eastern United States. The EPA Regional Haze Rule document [ EPA , 2003a] recommends “default aver age natural concentrations
of ammonium sulfate and a mmonium nitrate” in these tw o regions to serve as 2064 endpoints for application of the Rule. For purpose of comparison we present our model
results for sulfate and nitrate in Table 2 as those of the corresponding ammonium salts; in the model, almost all of the sulfate and n itrate are indeed associated with ammonium (Figure 9). Model results for the sum of natu ral and transboundary pollution contributions do not exactly add up to the independently ca lculated background concentrations because
of chemical nonlinearities [ Chin and Jacob , 1996; West et al. , 1999]. Our 2001 base simulation yields annual average concentrations of ammonium
sulfate and ammonium nitrate of 1.52 and 1.53 μ g m -3 , respectively, for the western
United States and 4.11 and 3.26 μ g m -3 , respectively, for the eastern United States. We use the sensitivity simulation with anthropoge nic emissions shut off globally to estimate natural concentrations. They are 0.11 μ g m -3 ammonium sulfate and 0.03 μ g m -3

ammonium nitrate for both the western and ea stern United States. Our estimate of natural
concentrations for ammonium sulfate is c onsistent with the EPA default value (0.12 μ g

56m -3 ) in the west but is factor of 2 lower than that (0.23 μ g m -3 ) in the east. Oxidation of DMS is the major natural source of sulfate in the United States in the model. Our
estimate of natural ammonium nitrate is th ree times lower than the EPA default value (0.1 μ g m -3 ); it is not clear how that default value was obtained. Let us now examine the background con centrations from the sensitivity simulation including anthropogenic emissions only outside of the United States. The mean annual concentrations of background am monium sulfate and nitrate in surface air
over the United States are 0.43 and 0.27 μ g m -3 for the west and 0.38 and 0.37 μ g m -3 for the east. These values are several-fold higher than the natural concen trations because of the influence from transboundary pollution. Ba ckground sulfate is slightly higher in the west than the east, because of Asian pollution influence as discussed further below, while background nitrate is higher in the east because of Canadian pollution influence. We thus find that transboundary pollu tion influence dominates over natural sources in contributing to sulfate and nitr ate background concentra tions in the United States. Transboundary transport of anthropogeni c emissions from Canada and Mexico is most important for nitrate, but for sulfate tr anspacific transport of Asian pollution is of comparable importance (Table 2). Remarkably, we find that this transpacific pollution
source accounts for 30% of the sulfate aeros ol background in the United States. Figure 12a shows the global distribution of Asian pollution influence on sulfatenitrate-ammonium aerosol concentrations in surface air, as determined by difference
between the standard simulation and the sens itivity simulation with anthropogenic Asian emissions shut off. Transpacific transport from Asia to the United States mostly involves lifting of Asian air to the free troposphere by wet processes (convection, warm conveyor belts), followed by rapid adv ection in the westerlies a nd subsidence over the United States, generally behind cold fronts. Ammonium aerosol as well as gas-phase ammonia are scavenged in this wet lifting and we s ee therefore that transpacific transport of ammonium is negligible. In contrast, signi ficant transpacific transport of sulfate can

occur as SO 2 partly escapes scavenging during lifting [ Mari et al. , 2000; Koike et al.

, 2003; Tu et al. , 2003]. Subsidence over the United States takes place mainly in the downwelling regions of the west and east, less in the upwelling region in the center of the country. Ammonium nitrate as we have seen is largely determined by difference between the total ammonium [NH 3 T ] and the sulfate concentration, and the preferen tial export of
sulfate relative to ammonium from Asia l eads to a slight negative effect of Asian pollution on nitrate concentrati ons in the United States. It is of interest to compare the transp acific influence of Asian pollution on North
America to the transatlantic influence of North American pollution on Europe. Figure
12b shows the latter as the difference between the standard simulation and the sensitivity simulation with anthropogenic emissions in North America s hut off. We find a sulfate
enhancement > 0.1 μ g m -3 in surface air in Western Europe and northern Africa, comparable in magnitude to Asian pollution in fluence over North America. As in the case of Asian pollution, we find that export of ammonium from North American pollution is far less efficient than for sulfate, resulting in small negative influences on nitrate aerosol concentrations over Europe and Asia.
We show also in Table 2 the natural a nd background concentrations of elemental carbon (EC) and organic carbon mass (OMC) from our previous work [ Park et al. , 2003]. In that work we derived optimized estim ates of individual EC and OMC sources by

57fitting model results to observations from the IMPROVE sites. We concluded that the
EPA default natural estimates were a factor of 3 too low in the west due to underestimate
of wildfire influences. Our values for the east were more consistent with EPA. In contrast to sulfate and nitrate, transboundary transp ort of anthropogenic carbonaceous aerosols is insignificant relative to the la rge natural influences from wildfires and vegetation. We further find that transpacific transport of carbonaceous aerosols from Asian pollution is
less efficient than for sulfate because of s cavenging in the wet lifting processes involved
in Asian outflow. The excess of SO 2 over H 2 O 2 in the Asian outflow allows part of the sulfur to escape scavenging [ Koike et al. , 2003; Tu et al. , 2003]. This result is consistent
with Jaffe et al. [2003] who found a larger increase in sulfate concentrations relative to
carbonaceous aerosol at three IMPROVE site s in the western United States during a transpacific transport event of Asian pollution.

5. Policy implications: the Regional Haze Rule The U.S. EPA Regional Haze Rule [ U.S. EPA , 2003a] requires st ates to develop plans for achieving natural vi sibility conditions in nationa l parks and other wilderness areas by 2064. Visibility degradation is measured by the deciview index
dv = 10 ln ( b ext /10) , (2)
where b ext is atmospheric light extinction in units of inverse megameters (Mm -1 =10 -6 m -1 ). In the phase 1 implementation of the Regional Haze Rule, states have to show how they will decrease anthropogenic emissions over the 2004-2018 period in order to achieve a linear trajectory of decreasing deciviews to wards the natural visi bility endpoint of 2064. A linear decrease in deciviews implies an expon ential decrease in aero sol extinction; as a result, and as we will see, the definition of the 2064 endpoint has important implications for determining the level of emission cont rols required during the 2004-2018 phase 1 implementation. The EPA Regional Haze Rule document [ U.S. EPA , 2003a] recommends a simple formula to estimate aerosol extinction by us ing dry mass concentrations of individual aerosol components (ammonium sulfate, amm onium nitrate, OMC, EC, soil dust, and coarse mass (CM)), as follows:

, (3) 10][6.0][][10][4 ])[(3]))[((3 34 424

+++++ + =

CM soilEC OMC NONHRHfSONHRHf ext b

where b ext is in units of Mm -1 , aerosol concentrati ons are in units of μ g m -3 , and f(RH) is a correction factor for hygros copic growth as a function of relative humidity (RH). The
constant of 10 Mm -1 describes the scattering by air molecu les and is such that an aerosolfree atmosphere would have a de ciview index of zero. “Soil” in equation (3) is the fine component of soil dust (diameter < 2.5 μ m) and “coarse mass” is the total mass of particles with diameter > 2.5 μ m, mostly contributed by dus t and sea salt. Recommended
values of f(RH) for individual wilderness areas ar e given in the Regional Haze Rule document [ U.S. EPA , 2003a]. In what follows we use typical f(RH) values of 2 and 3 for the west and east, respectively. Applying equation (3) to aeros ol concentrations given in Table 2, and assuming EPA natural default values for fine soil dust (0.5 μ g m -3 ) and coarse mass (3.0 μ g m -3 ), we compute deciview index values for baseli ne (present-day) conditi ons and for different definitions of the 2064 natural or background visibility endpoint. We use the results (Table 3) to estimate the implications of our results for phase 1 (2004-2018)

58implementation of the Regional Haze Rule. Under the EPA Regional Haze Rule, the linear improvement in visibility is to be appl ied to the 20% most impaired visibility days and at specific locations. Here we use visi bility calculated from annual mean aerosol extinctions averaged over the western and easte rn United States. Nevertheless, the results
serve to illustrate the se nsitivity of the required 2004-2018 emission controls to the choice of 2064 endpoint. Table 3 gives a baseline (c urrent) visibility degrada tion of 14 and 23 deciviews
for the western and the eastern United Stat es, respectively. The natural visibility degradation is 6.3 and 6.2 d eciviews, respectively. Organic aerosols are the dominant
contributors to natural visibi lity degradation. Our estimate for natural visibility degradation as expressed in deciviews is 37% higher in the west and 17% lower in the east than the values computed using the natural default aerosol concentrations recommended by EPA (4.6 and 7.5 deciview s). We have previously argued in Park et al. [2003] that the EPA natural default concen trations underestimate the influence of
wildfires in the west. Figure 13 shows the trajectories of linear visibility improvement towards a 2064 endpoint of natural visibility defined either from our results (dashed line) or from the EPA defaults (dotted line). Following these trajectories, we find that visibility degradation during the 2004-2018 phase 1 im plementation of the Regional Haze Rule should be reduced by 1.8 deciviews (west) and 3.9 deciviews (east) if our estimate of the 2064 natural visibility endpoint is used, and by 2.2 deciviews (west) and 3.6 deciviews (east) if the EPA default endpoint is used. The corres ponding reductions in light
extinction are 6.7 Mm -1 (west) and 32.2 Mm -1 (east) if our estima te of the 2064 natural visibility endpoint is used, and 8.1 Mm -1 (west) and 30.1 Mm -1 (east) if the EPA default endpoint is used. Let us now estimate the required percenta ge reductions in U.S. anthropogenic emissions needed to achieve such improvements in light extinction. We assume a linear correspondence between aerosol extinction, ae rosol concentrations, and emissions. The
current aerosol extinction from U.S. anthr opogenic emissions can be calculated from the data in Table 2 by subtracting the background from the baseline aerosol concentrations, and applying equation (3). We obtain values of 18.1 Mm -1 in the west and 73 Mm -1 in the east. The resulting percentage decreases of U.S. anthropogenic emissions over 2004-2018 are shown in Figure 13. They are 37% and 44% for the western and eastern United States, respectively, using our natural visibility e ndpoint, and 44% and 41% , respectively, using the EPA natural visibility endpoint. These differences are significant, bu t looking beyond the 201 8 horizon exposes a more fundamental problem with the Regi onal Haze Rule. Continued linear decrease
towards a 2064 natural visibi lity endpoint would require total shutdown of U.S. anthropogenic emissions by 2041-2049 (west) or 2053-2058 (east), as shown in Figure 13. Because of transboundary pollution (assumed here to be unchanged in the future), natural visibility canno t be achieved even with total s uppression of U.S. anthropogenic emissions. It will be therefore necessary to either impose emission controls on an
international level or to amend the 2064 endpoint to allow for uncontrollable transboundary pollution influences. Such an amendment should define the 2064 endpoint as a background rather than natural visibility . One would then have to make estimates of future trends in foreign emissions.

59However, amendment of the Regional Haze Rule to target a background visibility endpoint has major implications for phase 1 (2004-2018) emission controls in the west. Using the background deciview values in Table 3 as 2064 endpoi nt, the required 2004- 2018 decrease in visibility degradation is 1. 4 deciviews (west) and 3.3 deciviews (east). The corresponding percentage decrease of U.S. anthropogenic emissions in the west is 29%, much lower than 37% if a natural visib ility endpoint from our results is used or 44% if the natural visibility endpoin t from the EPA defaults is used.

6. Conclusions We used a global 3-D coupled oxidant-a erosol model (GEOS-CHEM) to quantify natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosol
concentrations in the United States. Th e U.S. EPA Regional Haze Rule requires immediate action to improve visibility in U. S. national parks and other wilderness areas along a linear trajectory towards an endpoint of “natural visibility conditions” by 2064. We need to better quantify the natural aeros ol concentrations defining this natural visibility, and to determine if transboundary transport of pollution not amenable to
domestic emission controls elevates bac kground aerosol concentrations in the United States significantly above the natural values . If they do, then the Regional Haze Rule
must either involve international emission c ontrols or be amended to an endpoint of “background” as opposed to “natural” visibil ity. “Background” is defined here following

EPA [2003b] as the aerosol concentr ations that would be presen t in the absence of U.S. anthropogenic emissions, but allowing for c ontributions from transboundary pollution. We conducted full-year si mulations for 1998 and 2001. Results were evaluated with observations from surface networks in the United States and Europe (IMPROVE, CASTNET, NADP, EMEP) and with Asia n outflow observations from the NASA
TRACE-P aircraft mission over the northwest Pacific. The model reproduces well the spatial pattern and variability of sulfate obs ervations in the United States and Europe across all seasons, with no systematic biases. Comparison with the TRACE-P
observations indicates that Asia n outflow of sulfate is if anything underestimated. Nitrate
and ammonium aerosol concentrations in the model are highly correlated with observations but are too high in summer and fall, a problem that we attribute to seasonal overestimate of ammonia emissions [ Gilliland et al. , 2003]. We find that the availability
of ammonia limits the formation of ammonium nitrate in most of North America. The aerosol is typically 80-100% ne utralized, both in the model a nd in the observations, with maximum acidity in summer. We used a sequence of sensitivity si mulations to quantify background sulfatenitrate-ammonium aerosol concentrations in the United States, and to separate the contributions to this background from natural sources and from transboundary pollution. Our 2001 base simulation yields annual averag e concentrations of ammonium sulfate and
ammonium nitrate of 1.52 and 1.53 μ g m -3 , respectively, for the western United States
and 4.11 and 3.26 μ g m -3 , respectively, for the eastern United States. Our best estimates
of mean annual natural concentrations are 0.11 μ g m -3 ammonium sulfate and 0.03 μ g m -3

ammonium nitrate for both the western a nd eastern United States. Our values are
consistent with or lower than the defa ult values recommended by EPA for natural visibility calculations in the context of the Regional Haze Rule.

60Our best estimates of background concentrations for ammonium sulfate and
ammonium nitrate are 0.43 and 0.27 μ g m -3 for the west and 0.38 and 0.37 μ g m -3 for the east. These values are considerably higher than the natural concentrations, pointing to the dominance of transboundary pollution in defi ning the background. Transpacific transport of Asian pollution is of comparable importan ce to transport from Canada and Mexico in contributing to the background sulfate enhanc ement over the United St ates. A significant
enhancement of sulfate relative to other ae rosols in the Asian outflow can occur as SO 2 partly escapes scavenging during wet lifting pr ocesses. In the case of ammonium nitrate, the transboundary pollution enhancement is mo stly from Canada, and transpacific Asian pollution actually causes a slig ht depression (less than 0.1 μ g m -3 ) due to the added
sulfate. We assessed the implications of our results for implementation of the Regional Haze Rule. For this purpose we used our mode l to define the linear trend of visibility from present (2004) to natural or bac kground (2064) conditions . We found that transboundary pollution prevents natural visib ility from being achieved even with total suppression of U.S. anthropogeni c emissions, implying the need for either international
emission controls or for amendment of the 2064 endpoint to allow for uncontrollable transboundary pollution influences. The latter would require some estimates of future trends in transboundary pollution influen ces but these have large uncertainties. Projections by IPCC [2001] for 2060 anthropogenic sulf ur emissions from Asia range from 30% to 160% of present-day levels depending on the socioeconomic scenario. Consideration of a background ra ther than natural visibili ty 2064 endpoint would have immediate implications for phase 1 implem entation (2004-2018) of the Regional Haze Rule. It would imply, at least in the we st, a significantly slower schedule of U.S. anthropogenic emission reductions. Our results are only a first attempt to quantify natural and transboundary pollution influences in the United States using a global 3-D model analysis. In future work we plan
to examine in more detail the observa tional constraints on aerosol background concentrations in the United States, incl uding site-by-site anal ysis and frequency distributions of aerosol concentrations. Specification of natural and background aerosol concentrations for regulatory purposes will require formal uncertainty bounds to be placed on model estimates, and again this will require more extensive evaluation with observations as well as higher-resolution simu lations with a nested regional model.

Acknowledgments. This work was supported by the Electric Power Research Institute (EPRI) and by the EPA Intercontinenta l transport and Climatic effects of Air Pollutants (ICAP) program. Development of the GEOS-CHEM model is supported by the Atmospheric Chemistry Modeling and Anal ysis Program (ACMAP) of the National Aeronautics and Space Ad ministration (NASA).

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Figures Captions

Figure 1. Monthly ammonia emissions in the contiguous United States. The values used in this work, broken down by source type (left bars), are compared to the values reported by Gilliland et al. [2003] (right bars) fr om inverse modeling of eight months of precipitation NH 4 + data.

66Figure 2. Sampling sites from the I[M]PROV E, [C]ASTNET, and NA[D]P networks in

2001.

Figure 3. Annual mean concentrations of sulf ate in surface air over the United States in 2001. The top panel shows results from th e GEOS-CHEM model. The middle and bottom panels show the observations from the IMPROVE and CASTNET networks, respectively, averaged over the model 2 o × 2.5 o grid.

Figure 4. Scatterplot of simulated versus observed sulfate concentrations at the IMPROVE and CASTNET sites, and sulfate de position fluxes at NADP sites (Figure 2). Values are annual means (top panels) and s easonal means for 2001. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circles, respectively. Thick solid lines are reduced majo r axis regressions for the ensemble of the data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

Figure 5. Annual mean concentrations of ammonium in surface air over the United States in 2001. The top panel shows results from the GEOS-CHEM model. The bottom panel
shows the observations from the CASTN ET networks averaged over the model 2 o × 2.5 o grid (ammonium is not measured at the IMPROVE sites).

Figure 6. Scatterplot of simulated versus observed ammonium concentrations at the CASTNET sites (left column), and nitrat e concentrations at the CASTNET and IMPROVE sites (right two columns). Values are annual means (top panels) and seasonal
means for 2001. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circle s, respectively. Thick solid lines are reduced major axis regressions for the ensemble of th e data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

Figure 7. Same as in Figure 3 but for nitrate.

Figure 8. Simulated gas ratio (GR; equati on (1)) defined as th e available ammonia concentration beyond that requ ired for sulfate neutraliza tion, divided by the total inorganic nitrate concentration (gas + aerosol) [ Ansari and Pandis , 1998]. Values are computed from annual mean concentrations in surface air. Form ation of ammonium nitrate aerosol is limited by the availability of nitric acid if GR > 1, by the availability of ammonia if 0 < GR < 1, and is totally suppressed if GR < 0.

Figure 9. Scatterplot of seasonal mean [NH 4 + ] vs. (2[SO 4 2- ]+[NO 3 - ]) at CASTNET sites in 2001, in the GEOS-CHEM model (top) a nd in observations ( bottom). The reducedmajor–axis regression slopes (given on the Figure) indicate the degree of acid
neutralization.

Figure 10. Scatterplot of simulated versus obs erved sulfate (left), nitrate (middle) and ammonium (right) conc entrations at 93 European EMEP sites. Values are annual means (top panels) and seasonal means for 1998. Th ick solid lines are reduced major axis

67regressions for the ensemble of th e data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

Figure 11. Simulated vs. observed mean vertic al profiles of non-sea- salt sulfate (nssSO 4 2- ) concentrations over the NW Pacific from the TRACE-P aircraft mission in February-April 2001. The observations are binned vertically in 1-km intervals. The solid
line shows mean observed values from Jordan et al. [2003] for the ensemble of DC-8 flights north of 30 o N (30-45 o N, 124-177 o E), with standard deviations represented by
horizontal bars. The dashed line shows th e corresponding monthly mean model values along the flight tracks.

Figure 12a. Enhancements of sulfate-nitrate- ammonium aerosol concentrations in surface air due to anthropogenic emissions from As ia. Values are annual means for 2001 and were obtained by difference between the sta ndard model simulation and a sensitivity
simulation with Asian anthr opogenic sources shut off.

Figure 12b. Same as in Figure 12a but for an thropogenic emissions from North America.

Figure 13. Illustrative example of required visibility improvements (top) and domestic emission reductions (bottom) over the 2004- 2064 period for the west ern and the eastern United States (separated at 95 o W) under the EPA Regional Haze Rule [ U.S. EPA , 2003a]. The visibility endpoints are as given in Table 3. The required percentage decrease in U.S. anthropogenic emissions corresponding to a give n visibility improvement is computed by assuming a linear correspondence between aerosol extinction and emissions. Results are
shown for different choices for the 2064 e ndpoint: (1) EPA natural default visibility (dotted lines), (2) our estimate of natural visi bility (dashed lines), and (3) our estimate of background visibility (solid lines). Backgr ound includes contributions from both natural and transbounary pollution sources. Year 2018 (t hin vertical line) is the target date for phase 1 implementation of the Regional Haze Rule.

68Tables

Table 1a. Sulfur emissions for 2001 (Tg S yr -1 ). Source type Globe Contiguous
United States
Total 78 8.3 Anthropogenic source total 57 8.3 Industrial activity 56 8.3
Biofuel use 0.27 < 0.01
Aircraft 0.07 0.02

Natural source total 21 0.01 Ocean (DMS) 15 0
Volcanoes 4.8 0 Biomass burning 1.3 0.01

Table 1b. Ammonia emissions for 2001 (Tg N yr -1 ). Source type Globe Contiguous
United States
Total 55 2.8 Anthropogenic source total 35 2.2
Domesticated animals 21 1.3
Fertilizers 9.0 0.49
Human bodies 2.6 0.13
Biofuel use 1.6 0.18 Industry 0.2 0.03
Fossil fuel use 0.1 0.06

Natural source total 20 0.59
Ocean 8.2 0 Biomass burning 5.9 0.04 Crop 3.5 0.44
Soil 2.4 0.1
Wild animals 0.1 0.01

69Table 1c. NO

x emissions for 2001 (Tg N yr -1 ). Source type Globe Contiguous
United States
Total 43 7.4 Anthropogenic source total 27 6.8
Fossil fuel use 24 6.7
Biofuel use 2.2 0.02
Fertilizer 0.47 0.07

Natural source total 17 0.66 Biomass burning 6.5 0.05
Natural soil 5.3 0.36 Lightning 4.7 0.25

Table 2. Background aerosol concentrations (μg m -3 ) in the United States a

. Ammonium
sulfate Ammonium
nitrate Elemental
carbon Organic
carbon mass

West East West East West East West East Baseline (2001) 1.52 4.11 1.53 3.26 0.27 0.66 1.77 3.07 Background 0.43 0.38 0.27 0.37 0.08 0.06 1.30 1.22
Natural 0.11 0.11 0.03 0.03 0.06 0.04 1.25 1.17 Transboundary pollution 0.28 0.26 0.18 0.23 0.02 0.02 0.05 0.05

Canada and
Mexico 0.15 0.14 0.2 0.25 0.02 0.02 0.04 0.04

Asia 0.13 0.12 -0.02 -0.02 <0.01 <0.01 0.01 <0.01
EPA natural
defaults b 0.12 0.23 0.1 0.1 0.02 0.02 0.47 1.40

a Values are annual and spatial means from th e standard 2001 simulation (baseline) and from the sensitivity simulations described in section 2.1. Partitioning between west and
east is at 95 o W. Background and natural concentrations are obtained from the sensitivity simulations without U.S. and global anthropogenic emissions, respectively. Transboundary pollution influences from Canada and Mexico are determined by difference between two sensitivity simulations with anthropogenic emissions shut off in the United States versus in all of North America. Transpacific pollution influences from Asia are determined by difference between th e standard simulation and the sensitivity simulation with anthropogenic sources shut off in Asia. Results for elemental carbon (EC) and organic carbon mass (OMC ) are from our previous work [ Park et al. , 2003] in a simulation using climatological emissions from wildfires.

b ”Default average natural concentrations” recommended by U.S. EPA [2003a] for estimating natural visibility conditions as 2064 endpoint in the application of the EPA Regional Haze Rule.

70Table 3. Visibility degradation (deciviews) in the United States a

. West East Baseline (2001) 14 23 Background b

Natural
This work
EPA default 8.1

6.3
4.6 9.0

6.2

7.5

a Visibility degradation in deciviews (e quation (2)) calculated from mean annual aerosol extinction as given by e quation (3). Aerosol concentra tions for use in equation (3) are from Table 2, with in addition EPA de fault natural values for soil (0.5 μg m -3 ) and coarse mass (CM) (3.0 μg m -3 ). Values of f(RH) in equation (3) are 2 in the west and 3 in
the east.

b Including contributions to visibility degradation from both natural and transboundary pollution sources.

71Figures

Figure 1. Monthly ammonia emissions in the contiguous United States. The values used in this work, broken down by source type (left bars), are compared to the values reported by Gilliland et al. [2003] (right bars) fr om inverse modeling of eight months of precipitation NH 4 + data.

72Figure 2. Sampling sites from the I[M]PROV E, [C]ASTNET, and NA[D]P networks in

2001.

73Figure 3. Annual mean concentrations of sulf ate in surface air over the United States in 2001. The top panel shows results from th e GEOS-CHEM model. The middle and bottom panels show the observations from the IMPROVE and CASTNET networks, respectively, averaged over the model 2 o × 2.5 o grid.

74Figure 4. Scatterplot of simulated versus observed sulfate concentrations at the IMPROVE and CASTNET sites, and sulfate de position fluxes at NADP sites (Figure 2). Values are annual means (top panels) and s easonal means for 2001. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circles, respectively. Thick solid lines are reduced majo r axis regressions for the ensemble of the

75data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

Figure 5. Annual mean concentrations of ammonium in surface air over the United States in 2001. The top panel shows results from the GEOS-CHEM model. The bottom panel
shows the observations from the CASTN ET networks averaged over the model 2 o × 2.5 o grid (ammonium is not measured at the IMPROVE sites).

76Figure 6. Scatterplot of simulated versus observed ammonium concentrations at the CASTNET sites (left column), and nitrat e concentrations at the CASTNET and IMPROVE sites (right two columns). Values are annual means (top panels) and seasonal
means for 2001. Sites in the western and eastern United States (separated at 95 o W) are shown as pluses and open circle s, respectively. Thick solid lines are reduced major axis

77regressions for the ensemble of th e data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

Figure 7. Same as in Figure 3 but for nitrate.

78Figure 8. Simulated gas ratio (GR; equati on (1)) defined as th e available ammonia concentration beyond that requ ired for sulfate neutraliza tion, divided by the total inorganic nitrate concentration (gas + aerosol) [ Ansari and Pandis , 1998]. Values are computed from annual mean concentrations in surface air. Form ation of ammonium nitrate aerosol is limited by the availability of nitric acid if GR > 1, by the availability of ammonia if 0 < GR < 1, and is totally suppressed if GR < 0.

79Figure 9. Scatterplot of seasonal mean [NH 4 + ] vs. (2[SO 4 2- ]+[NO 3 - ]) at CASTNET sites in 2001, in the GEOS-CHEM model (top) a nd in observations ( bottom). The reducedmajor–axis regression slopes (given on the Figure) indicate the degree of acid
neutralization.

80Figure 10. Scatterplot of simulated versus obs erved sulfate (left), nitrate (middle) and ammonium (right) conc entrations at 93 European EMEP sites. Values are annual means (top panels) and seasonal means for 1998. Th ick solid lines are reduced major axis regressions for the ensemble of th e data; regression equations and R 2 are shown inset. Thin solid lines show the y=x relationship.

81Figure 11. Simulated vs. observed mean vertic al profiles of non-sea- salt sulfate (nssSO 4 2- ) concentrations over the NW Pacific from the TRACE-P aircraft mission in February-April 2001. The observations are binned vertically in 1-km intervals. The solid
line shows mean observed values from Jordan et al. [2003] for the ensemble of DC-8 flights north of 30 o N (30-45 o N, 124-177 o E), with standard deviations represented by
horizontal bars. The dashed line shows th e corresponding monthly mean model values along the flight tracks.

82Figure 12a. Enhancements of sulfate-nitrate- ammonium aerosol concentrations in surface air due to anthropogenic emissions from As ia. Values are annual means for 2001 and were obtained by difference between the sta ndard model simulation and a sensitivity
simulation with Asian anthr opogenic sources shut off.

83Figure 12b. Same as in Figure 12a but for an thropogenic emissions from North America.

84Figure 13. Illustrative example of required visibility improvements (top) and domestic emission reductions (bottom) over the 2004- 2064 period for the west ern and the eastern United States (separated at 95 o W) under the EPA Regional Haze Rule [ U.S. EPA , 2003a]. The visibility endpoints are as given in Table 3. The required percentage decrease in U.S. anthropogenic emissions corresponding to a give n visibility improvement is computed by assuming a linear correspondence between aerosol extinction and emissions. Results are
shown for different choices for the 2064 e ndpoint: (1) EPA natural default visibility (dotted lines), (2) our estimate of natural visi bility (dashed lines), and (3) our estimate of background visibility (solid lines). Backgr ound includes contributions from both natural and transbounary pollution sources. Year 2018 (t hin vertical line) is the target date for phase 1 implementation of the Regional Haze Rule.

85