Mineral dust aerosols
On this page we provide information about the treatment of mineral dust aerosols in GEOS-Chem.
Overview
From Fairlie et al [2007]:
We implemented two dust mobilization schemes in GEOS-Chem: (1) the scheme of Ginoux et al. (2004, hereafter G04), developed for the GOCART CTM and (2) the dust entrainment and deposition (DEAD) scheme of Zender et al. (2003a, b hereafter Z03a,b). Both schemes treat the vertical dust flux as proportional to the horizontal saltation flux. The DEAD scheme (Z03) follows MB95 in computing a total horizontal saltation flux, Qs, based on the theory of White (1979):
RHOair ( U*,t ) ( U*,t )^2
Qs = Cz * --------- * Ustar^3 * ( 1 - ------ ) * ( 1 + ------- ) (1)
g ( U* ) ( U* )
where U* is the friction velocity, U*,t(D) is the threshold friction velocity, RHOair is the air density, g is the acceleration of gravity, and Cz is a global tuning parameter. Qs is computed at D = 75μm, where U*,t is a minimum, and the total vertical flux is given by:
F = Am * Sz * ALPHA * Qs (2)
where the sandblasting mass efficiency, ALPHA, depends on the fraction Mclay of clay in the soil, Am is the fractional area of land suitable for mobilization, and Sz is the ‘‘erodibility,’’ an efficiency factor that favors emissions from specified geographic features. We followed Z03b in using ‘‘geomorphic erodibility,’’ which depends on upstream runoff area, and set Mclay = 0.2 globally. We computed U from the 10-m wind speed assuming neutral stability below and used a roughness length Z0 = 100 mm, recommended by Z03a for dust mobilization candidate cells. F is distributed by particle size as a globally uniform tri-modal lognormal probability density function, which we project on to the selected size bins specified above.
The GOCART scheme (G04) follows Gillette and Passi (1988) in computing a size segregated vertical dust flux, Fp, for each size class, p:
Fp = Cg * S * sp * U10^2 * ( U10 - U*,t ) (3)
where the ‘‘source function,’’ S, serves the same role as the product Am * Sz in DEAD (Eq. (2)), sp is the mass fraction applied to each size class, U10 is the 10-m wind speed, and Cg is a global constant. S confines dust emissions to topographic depressions in desert and semi-desert areas of the world (Ginoux et al., 2001, hereafter G01) and is time invariant....
Although the DEAD and GOCART schemes differ in detail, they differ most fundamentally in representing the role of vegetation. GOCART restricts emissions to persistent arid regions, whereas DEAD permits regions that become seasonally devegetated to mobilize....
--Bob Y. (talk) 16:32, 26 October 2015 (UTC)
Recent updates
The following updates were made to Fairlie et al [2007]:
Sub-micron dust mass partitioning change
This update was tested in the 1-month benchmark simulation v9-01-03d and approved on 12 Jan 2012.
David Ridley wrote:
- Originally, dust mass in the smallest (0.1-1.0 micron) transport tracer was partitioned equally between four bins used for the optical calculations. Using data from aircraft PCASP measurements of Saharan dust (Highwood et al., 2003, Fig 4b) we have inferred a more realistic partitioning for the dust mass into the sub-micron size bins. The mass fraction in each bin is now 6%, 12%, 24%, 58% from smallest to largest, rather than 25% in each.
- There is a change to the code in aerosol_mod.f file. At line 450, this:
! Lump 1st dust tracer for het chem
DO N = 1, 4
SOILDUST(I,J,L,N) =
& 0.25d0 * STT(I,J,L,IDTDST1) / AIRVOL(I,J,L)
ENDDO
- has become this:
! Lump 1st dust tracer for het chem
SOILDUST(I,J,L,1) =
& 0.06d0 * STT(I,J,L,IDTDST1) / AIRVOL(I,J,L)
SOILDUST(I,J,L,2) =
& 0.12d0 * STT(I,J,L,IDTDST1) / AIRVOL(I,J,L)
SOILDUST(I,J,L,3) =
& 0.24d0 * STT(I,J,L,IDTDST1) / AIRVOL(I,J,L)
SOILDUST(I,J,L,4) =
& 0.58d0 * STT(I,J,L,IDTDST1) / AIRVOL(I,J,L)
- The result of this change in dust particle size is a reduction in the AOD of up to 25% close to source and up to 40% downwind where sub-micron aerosol dominate (Ridley et al., 2011).
--Melissa Payer 14:20, 3 January 2012 (EST)
Surface chemistry on dust
This update was validated with 1-month benchmark simulation v11-01b and 1-year benchmark simulation v11-01b-Run0. This version was approved on 19 Aug 2015.
T. Duncan Fairlie wrote:
- I have developed GEOS-Chem modules to include additional sources of sulfate and nitrate, associated with the uptake of SO2, and HNO3, on dust, limited by dust alkalinity, and uptake of H2SO4, limited by competition with other surfaces.
- The modules I am working on entail the addition of 12 new tracers, represent nitrate on dust, sulfate on dust, and dust alkalinity. Each of these 3 constituents is represented in 4 size bins, corresponding to the 4 dust size bins in the current version of the model. Each of these new tracers is transported, and subject to wet and dry deposition. Dust alkalinity is introduced at the point of emission and corresponds Ca2+ and Mg2+ cation equivalents of 3.0% and 0.6% respectively of the dust by mass. Uptake of acid components consumes dust alkalinity. Uptake of H2SO4 may continue after dust alkalinity titration. Uptake of acid components is represented by a standard first order uptake parameterization. Details are given by Fairlie et al. (ACP, 2010)
- I am using the routines that Becky Alexander and Rokjin Park developed for acidic uptake on sea salt as a template. Those routines are associated with the coarse mode SO4s and NITs constituents.
- Uptake of acid components is represented by a standard first order uptake parameterization. A thermodynamic equilibrium condition may be appropriate for the fine mode sulfate and nitrate, as is done in the case of sea salt, but results of our study indicate that this is not appropriate for supermicron components. Here, we use RH-dependent functions for γ(HNO3) and γ(SO2), as shown in Fig. 1 of Fairlie et al. (2010). The RH-dependences are based on laboratory results for uptake on calcite particles (Liu et al., 2008, for HNO3; Preszler-Prince et al., 2007, for SO2),
- Notes:
- Hygroscopic growth affects the dry deposition of aerosols. Dust is typically not subject to hygroscopic growth. However, when submicron dust is coated with sulfate or nitrate hygroscopic growth might be expected, and hence to affect deposition frequencies. This is not done in the model. We compute deposition frequencies for dust-sulfate, dust-nitrate, in addition to those for dust and dust alkalinity, and store in DEPSAV.
- Updates are based on v8.01.01 of the code. I ran at 2x2.5 resolution on my SGI machine "crunch". I had some issues running tpcore_fvdas with v8.01.01, associated with the memory capacity of my I’ve circumvented some of the issues by eliminating the static declaration of 4-d flux arrays in tpcore associated with ND24->26. However, transition to crunch was necessary to run at 2x2.5.
--Bob Y. 11:55, 6 September 2011 (EDT)
Improved dust size distribution scheme
This update was validated with 1-month benchmark simulation v11-01b and 1-year benchmark simulation v11-01b-Run0. This version was approved on 19 Aug 2015.
Li Zhang wrote:
- This is Li Zhang from University of Colorado Boulder. We implemented a new dust size distribution scheme into GEOS-Chem, which significantly improves the PM2.5 surface dust concentration over western U.S.. Corresponding results have been published in GRL:
- Zhang, L., J. F. Kok, D. K. Henze, Q. Li, and C. Zhao (2013), Improving simulations of fine dust surface concentrations over the western United States by optimizing the particle size distribution, Geophys. Res. Lett., 40, 3270–3275, doi:10.1002/grl.50591.
Colette Heald wrote:
- We have discussed this update with Daven Henze and Li Zhang. The Aerosols Working Group recommends that this update be implemented in the standard code, but there is one small caveat. This code has been evaluated for US/Asian dust, but not for Africa. So we'd like to keep an eye on Africa in the benchmarks and if there is any substantial change in AOD over the region, we may consider reverting to the "old" code for this region (since it's such an important dust region). I have asked Li and Daven to ensure that the code provided to you is easily revert-able. The Aerosols Working Group will review this change in the benchmark and we'll make a recommendation on Africa at that time.
--Bob Y. 10:12, 23 January 2014 (EST)
Validation
See Fairlie et al, 2007 and Fairlie et al, 2010.
--Bob Y. (talk) 16:32, 26 October 2015 (UTC)
Source code and data
In GEOS-Chem v10-01 and higher versions
In GEOS-Chem v10-01 and newer versions, the DEAD data files are read with the HEMCO emissions component. We have created new DEAD data files (in COARDS-compliant netCDF format) for use with HEMCO. These new data files are contained in the HEMCO data directory tree. For detailed instructions on how to download these data files to your disk server, please see our Downloading the HEMCO data directories wiki post.
--Bob Y. 13:20, 3 March 2015 (EST)
In GEOS-Chem versions prior to v10-01
The GEOS-Chem dust chemistry modules are contained in files dust_mod.f and dust_dead_mod.f.
In GEOS-Chem v9-02 and older versions, the DEAD and GINOUX data files are stored in binary punch format. They are available on the following grids:
For more information about the data, please see the README files in the following GEOS-Chem data directories:
- 0.5° x 0.666° China nested grid
- 0.5° x 0.666° North America nested grid
- 2° x 2.5° global grid
- 4° x 5° global grid
--Bob Y. 16:28, 13 February 2015 (EST)
Anthropogenic PM2.5 dust source in GEOS-Chem
NOTE: This update will be implemented in v11-02.
Sajeev Philip wrote:
We have added a new PM2.5 dust emission inventory (in addition to the default mineral dust simulation) into GEOS-Chem, termed as Anthropogenic Fugitive, Combustion and Industrial Dust (AFCID). Inclusion of AFCID improved the comparison of simulated dust and total PM2.5 mass in comparison with in situ observations (Philip et al., ERL, 2017). Users have the option to turn on/off this new inventory within the module: GeosCore/HEMCO/Extensions/hcox_dustdead_mod.F.
Reference:
Philip, S., R. V. Martin, G. Snider, C. Weagle, A. van Donkelaar, M. Brauer, D. Henze, Z. Klimont, C. Venkataraman, S. Guttikunda and Q. Zhang, Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models, Environ. Res. Lett., in press, 2017.
--Melissa Sulprizio (talk) 13:48, 20 March 2017 (UTC)
Computing PM2.5 concentrations from GEOS-Chem output
For information on how to compute particulate matter (PM2.5) from GEOS-Chem diagnostic outputs, please see our Particulate matter in GEOS-Chem wiki page.
--Bob Yantosca (talk) 21:13, 10 February 2016 (UTC)
Previous issues that are now resolved
The following bugs and/or technical issues with the GEOS-Chem mineral dust simulation have now been resolved.
Bug in ND21 diagnostic indexing for size-resolved dust species
Chris Holmes wrote:
I’ve found a bug in the ND21 aerosol diagnostics in v11-01. [I tried to plot...] the surface area density of sea-salt aerosols (tracers 14017, 14020). The data in the bpch file must be some dust property, however, since it is concentrated over Africa, not the ocean. I’ve found this problem in v11-01 4x5 GEOS5 using both SOA chemistry and UCX chemistry.
Bob Yantosca replied:
Basically the counter for ND21 in GeosCore/dust_mod.F was off by 5 slots. The code in RED was removed, code in GREEN added.
! There are always 5 + (NRHAER*23) preceding size-res dust ! Each subsequent set is separated by a further distance of ! (NRHAER + NDUST) !----------------------------------------------------------------------------- ! Prior to 3/27/17: ! This formula for NOUT caused the size-resolved dust AOD's to be written ! to slots 16-22 of AD21, thus overwriting other diagnostics. They should ! be written to slots 21-27. Change the NRHAER*2 to NRHAER*3 to make the ! counting come out right. This is just an empirical fix. Maybe the issue ! was caused by a modification in aerosol_mod.F. (cdh, bmy, 3/27/17) ! NOUT = 5 + (NRHAER*2) + ((NRHAER+NDUST)*(W-1)) + N !----------------------------------------------------------------------------- NOUT = 5 + (NRHAER*3) + ((NRHAER+NDUST)*(W-1)) + N
Bug fixes for hydrophobic aerosol properties
This update was validated with 1-month benchmark simulation v11-01f and 1-year benchmark simulation v11-01f-geosfp-Run0. This version was approved on 16 Apr 2016.
Seb Eastham identified several bugs setting hydrophobic aerosol properties in aerosol_mod.F, as described below.
Hydrophobic aerosol properties fix (1 of 2):
The order of operations in calculating the "average" radius for
mixed hydrophilic and hydrophobic aerosol was resulting in the
following calculation:
r = ((r_dry * A_dry) + (r_wet * (A_dry + A_wet)))/(A_dry + A_dry + A_wet)
This has now been changed to:
r = ((r_dry * A_dry) + (r_wet * A_wet))/(A_dry + A_wet)
This will slightly decrease the mean radius of BC and OC. This is the
first of two connected corrections.
Old code:
TAREA(JLOOP,N+NDUST) = TAREA(JLOOP,N+NDUST) + DRYAREA
ERADIUS(JLOOP,NDUST+N) = ( ERADIUS(JLOOP,NDUST+N) *
& TAREA(JLOOP,N+NDUST) +
& RW(1) * DRYAREA ) /
& ( TAREA(JLOOP,N+NDUST) +
New code:
TAREA(JLOOP,N+NDUST) = WTAREA(JLOOP,N+NDUST) + DRYAREA
ERADIUS(JLOOP,NDUST+N) = ( WERADIUS(JLOOP,NDUST+N) *
& WTAREA(JLOOP,N+NDUST) +
& RW(1) * DRYAREA ) /
& ( WTAREA(JLOOP,N+NDUST) +
Hydrophobic aerosol properties (fix 2 of 2):
When calculating total SAD and radius of BC and OC, the properties
of the hydrophobic component were calculated using a radius which
was given in um but expected to be in cm. As a result, the additional
SAD due to hydrophobic aerosol was underestimated by x10,000, and the
average aerosol radius was overestimated in a similar fashion. This
has been corrected by applying a 1.0D-4 factor wherever RW(1) is
referenced. This is the second of two connected corrections.
Old code:
DRYAREA = 3.D0 * DAERSL(I,J,L,N-1) / ( RW(1) *
& MSDENS(N) )
ERADIUS(JLOOP,NDUST+N) = ( WERADIUS(JLOOP,NDUST+N) *
& WTAREA(JLOOP,N+NDUST) +
& RW(1) * DRYAREA ) /
& ( WTAREA(JLOOP,N+NDUST) +
& DRYAREA )
New code:
DRYAREA = 3.D0 * DAERSL(I,J,L,N-1) / ( RW(1) *
& 1.0D-4 * MSDENS(N)
ERADIUS(JLOOP,NDUST+N) = ( WERADIUS(JLOOP,NDUST+N) *
& WTAREA(JLOOP,N+NDUST) + /
& RW(1) * 1.0D-4 * DRYAREA )/
& ( WTAREA(JLOOP,N+NDUST) +
& DRYAREA )
Fixed indexing bug for WTAREA in aerosol_mod:
WTAREA was incorrectly indexed in aerosol mod, resulting in
zero SAD for non-dust aerosols and overwriting of dust SAD
by other aerosol data. This only affects carbonaceous aerosol
calculations in carbon_mod.
Old code:
WTAREA(JLOOP, N) = TAREA(JLOOP, N+NDUST)
WERADIUS(JLOOP, N) = ERADIUS(JLOOP, N+NDUST)
New code:
WTAREA(JLOOP, N+NDUST) = TAREA(JLOOP, N+NDUST)
WERADIUS(JLOOP, N+NDUST) = ERADIUS(JLOOP, N+NDUST)
--Lizzie Lundgren (talk) 19:16, 5 January 2016 (UTC)
--Bob Yantosca (talk) 15:24, 30 March 2016 (UTC)
Bug fix for offline dust aerosols when UCX is on
This update was validated with 1-month benchmark simulation v11-01d and 1-year benchmark simulation v11-01d-Run1. This version was approved on 12 Dec 2015.
Seb Eastham wrote:
- On or around line 1450 of dust_mod.F [in v10-01], the dry radius and extinction of dust are retrieved from QQAA and RDAA. If RRTMG is active, the single scattering albedo and asymmetry factors are also retrieved, from SSAA and ASYMAA. However, they are always read from entry [X,Y,Z,6] of the corresponding array.
- Unfortunately, this index is only correct if the UCX is off; if the UCX is on, the entry should be 8, not 6 (based on fast_jx_mod, where these arrays are populated). It looks like an index variable was prepared for this purpose but it's not used. As it is, when the UCX is on, dust radius, surface area and scattering will actually be calculated based on stratospheric sulfate aerosol properties.
--Lizzie Lundgren (talk) 15:51, 23 October 2015 (UTC)
Now treat DST2-DST4 as coarse mode in wet scavenging
This fix was validated with 1-month benchmark simulation v11-01b and 1-year benchmark simulation v11-01b-Run0. This version was approved on 19 Aug 2015.
While resolving some of the conflicts in the acid uptake on dust aerosol code (based on v8-01-01), it was brought to Duncan Fairlie's attention that we now use different scavenging coefficients for fine and coarse aerosols. In GEOS-Chem v9-01-03, we implemented Qiaoqiao Wang's updates for aerosol scavenging efficiency. With this update, we now calculate WASHFRAC for accumulation mode and coarse mode aerosol using washout efficiency from Feng (2007). This paper has efficiency for aerosol sizes 0.001-0.04 μm, 0.04-2.5 μm (accumulation mode), 2.5-16 μm (coarse mode) and 16-100 μm. Based on those numbers, Qiaoqiao used accumulation mode for DST1-DST3 and coarse mode for DST4. Duncan has suggested that we revisit what we consider fine and coarse mode for dust in the wet deposition code. He suggests we treat DST1 as accumulation mode and DST2-DST4 as coarse mode.
The dust size bins are currently defined as:
- DST1: 0.1–1.0 μm
- DST2: 1.0–1.8 μm
- DST3: 1.8–3.0 μm
- DST4: 3.0–6.0 μm
Jeff Pierce wrote:
- The dust bin sizes you provide are radius, whereas the efficiencies diameter (weird that accumulation mode could go up to D=5 μm... even 2.5 μm is big for accumulation mode). Thus, we need to multiply the dust-bin sizes by 2. In which case DST3 and DST4 are both coarse and DST2 sits in between (with a larger fraction in coarse). I support Duncan's suggestion.
- We should stop the use of radius for aerosol size measurements. It's a minority, and causes errors and confusion in cases such as this.
--Melissa Sulprizio (talk) 19:01, 20 July 2015 (UTC)
Known issues
The following issues have not yet been resolved. These are active problems of research.
Low bias at 4x5 resolution
The following comments are in the documentation header to source code file dust_dead_mod.f, which is the implementation of Zender's DEAD scheme in GEOS-Chem:
T. Duncan Fairlie wrote:
- NOTE: The current [dust] code was validated at 2 x 2.5 resolution. We have found that running at 4x5 we get much lower (~50%) dust emissions than at 2x2.5. Recommend we either find a way to scale the U* computed in the dust module, or run a 1x1 and store the the dust emissions, with which to drive lower resolution runs.
- -- Duncan Fairlie, 1/25/07
Daniel Jacob wrote:
- NOTE: [We'll] implement the [dust] code in the standard [GEOS-Chem] model and put a warning about expected low bias when the simulation is run at 4x5. Whoever is interested in running dust at 4x5 in the future can deal with making the fix.
- -- Daniel Jacob, 1/25/07
--Bob Y. 10:34, 22 February 2010 (EST)
References
- Chin, M., P. Ginoux, S. Kinne, B. Holben, B. Duncan, R. Martin, J. Logan, A. Higurashi, and T. Nakajima, Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sunphotometers measurements, J. Atmos Sci., 2001.
- Chin, M., et al., Aerosol distribution in the Northern Hemisphere during ACE-Asia: results from global model, satellite observations, and Sun photometer measurements, J. Geophys. Res., 109, D23S90, 2004.
- Fairlie, T.D., D.J. Jacob, J.E. Dibb, B. Alexander, M.A. Avery, A. van Donkelaar, and L. Zhang, Impact of mineral dust on nitrate, sulfate, and ozone in transpacific Asian pollution plumes, Atmos. Chem. Phys., submitted, 2010. PDF
- Fairlie, T. D., D.J. Jacob, and R.J. Park, The impact of transpacific transport of mineral dust in the United States, Atmos. Environ., 41, 1251-1266, 2007. PDF
- Gillette, D.A., Passi, R., Modeling dust emission caused by wind erosion, J. Geophys. Res., 93, 14,233–14,242, 1988.
- Ginoux, P., et al., Sources and distributions of dust aerosols simulated with the GOCART model, J. Geophys. Res, 106 (D17), 20255–20274, 2001.
- Ginoux, P., et al., Long-term simulation of global dust distribution with the GOCART model: correlation with North Atlantic oscillation, Environmental Modeling and Software, 19, 113–128, 2004.
- Ridley, D. A., C. L. Heald, and B. J. Ford, North African dust export and deposition: A satellite and model perspective, J. Geophys. Res., doi:10.1029/2011JD016794, in press, 2011.
- White, B.R., Soil transport by winds on Mars, J. Geophys. Res., 84, 4643–4651, 1979.
- Zender, C.S., Bian, H., Newman, D., The mineral dust entrainment and deposition (DEAD) model: description and 1990s dust climatology, J. Geophys. Res, 108 (D14), 4416, 2003a.
- Zender, C.S., Newman, D., Torres, O., Spatial heterogeneity in aeolian erodibility: uniform, topographic, geomorphic and hydrologic erodibility, J. Geophys. Res., 108 (D17), 4543, 2003b.
- Zhang, L., Gong, S., Padro, J., Barrie, L., A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atm. Environ., 35, 549–560, 2001.
--Melissa Payer 14:35, 3 January 2012 (EST)