Updated Oct 5, 2023 (version 14.2.0)
Citing GEOS-Chem | Name | Original references | Configurations | Met fields & grids | Nesting | Transport & deposition
Radiation | Emissions | Chemistry | Aerosols | Carbon gases | Mercury | POPs | Transport tracers | Diagnostics
Model adjoint | References
We give here a narrative description of the current standard version of the GEOS-Chem model, with two purposes:
- To provide you with a quick overview of GEOS-Chem components and capabilities;
- To assist you in correctly citing relevant model components in your publications.
We strongly encourage you to be generous in citations—this not only recognizes the developer's work but also increases the traceability of your paper. Offering co-authorship to developers is encouraged for new developments flagged in this narrative if they are important for your work. It may also be appropriate to offer co-authorship for older model developments if they were new when you started your work. See the New GEOS-Chem Developments page for more specific information on the developer(s) to be credited, and contact the Model Scientist or appropriate Working Group chair if you need guidance.
The narrative below is reviewed and updated by the GEOS-Chem Steering Committee at every new X.Y model version release.
GEOS-Chem should be referenced by its version number X.Y.Z and corresponding DOI. See the history of model versions and their DOIs. The website http://www.geos-chem.org is also a useful reference. In addition, we strongly encourage you to cite GEOS-Chem journal publications, both for your general use of GEOS-Chem and for your specific applications. We also encourage you to name GEOS-Chem in your Abstract (or in your title, if appropriate) so that your paper gets picked up by GEOS-Chem searches and gets listed in the GEOS-Chem publications page. Consult the narrative below for referencing specific components of the model. For questions on citations please contact the relevant Working Group Chair or Model Scientist.
The name "GEOS-Chem" was coined in 2001 and is first referred to in Bey et al. . It is not an acronym - there is nothing to spell out. GEOS stands for Goddard Earth Observing System and Chem stands for Chemistry but calling it the "Goddard Earth Observing System - Chemistry" model would be inappropriate because the GEOS Earth System Model can use other chemical modules besides GEOS-Chem, and GEOS-Chem can use other meteorological drivers besides GEOS.
If an abbreviated name for GEOS-Chem needs to be used, such as in a Figure or other context where space is limited, then 'GC' is acceptable and is frequently used for informal communication within the GEOS-Chem community. No other abbreviation is acceptable. In particular, 'GEOS' should not be used because of confusion with the GEOS Earth System Model.
Bey et al.  is the first reference to GEOS-Chem that includes a detailed model description. It is suitable as an original reference for the model. It only describes a model for gas-phase tropospheric oxidant chemistry. Subsequent original references for major additional model features are:
- Park et al.  for aerosol chemistry;
- Y.X. Wang et al.  for the nested model;
- Henze et al.  for the model adjoint;
- Selin et al.  for the mercury simulation;
- Trivitiyanurak et al.  for TOMAS aerosol microphysics;
- Yu and Luo  for APM aerosol microphysics;
- Eastham et al.  for stratospheric chemistry;
- Keller et al.  for HEMCO;
- Long et al.  for the grid-independent GEOS-Chem;
- Eastham et al.  for the high-performance GEOS-Chem (GCHP);
- Hu et al.  for GEOS-Chem within the GEOS ESM (GEOS-GC);
- Lin et al.  for GEOS-Chem within WRF (WRF-GC);
- Zhuang et al. [2019, 2020] for implementations of GEOS-Chem Classic and GCHP on the cloud.
- Bindle et al.  for the stretched-grid capability in GCHP.
- Murray et al.  for GEOS-Chem driven by GISS GCM fields (GCAP 2.0)
GEOS-Chem is a grid-independent model. It operates on 1-D columns with default or user-specified horizontal gridpoints, vertical gridpoints, and timesteps. The GEOS-Chem chemical module updates column concentrations for the effects of emissions, chemistry, aerosol microphysics, and deposition at each time step. This chemical module can be implemented in three different configurations:
- GEOS-Chem Classic (sometimes abbreviated GCC). This uses archived GEOS meteorological data on a rectilinear latitude-longitude grid to compute horizontal and vertical transport. Parallelization is through an Open-MP shared-memory architecture and scales efficiently up to about 30 CPUs.
- GEOS-Chem High Performance (GCHP). This uses archived GEOS meteorological data on their original cubed-sphere grid to compute horizontal and vertical transport. Parallelization is through an MPI distributed memory architecture and scales efficiently on thousands of CPUs. GCHP is described by Eastham et al. . Improved advection, resolution, performance, and community access are described by Martin et al. .
- GEOS-Chem in on-line applications. This uses the GEOS-Chem chemical module coupled with an independent simulation of atmospheric dynamics from a meteorological model, where the meteorological model handles the transport of chemicals together with that of the dynamical variables. The off-line transport component of GEOS-Chem is either totally disabled or limited to fast vertical transport (convective and boundary layer mixing). In this way GEOS-Chem can serve as an on-line atmospheric chemistry module for meteorological models.
GEOS-Chem Classic and GCHP can be run on the cloud as originally described by Zhuang et al. [2019, 2020]. The functionality for GCHP required further maintenance, development, and documentation. This update is a new development in version 14.2.0.
GEOS-Chem in off-line mode (Classic or GCHP) is driven by assimilated meteorological data from the Goddard Earth Observation System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). The two GEOS latitude-longitude data archives used by GEOS-Chem are:
- the operational data stream starting in 2012 from the GEOS Forward Processing (GEOS-FP) (native resolution 0.25° x 0.3125°, 72 levels)
- the consistent MERRA-2 reanalysis for 1979-present (native resolution 0.5° x 0.625°, 72 levels)
These archives have 3-hour temporal resolution for 3-D fields and 1-hour resolution for 2-D fields. A C720 GEOS-FP archive at hourly resolution for advection variables is also available for March 2021 to present and this is a new development in version 13.4.0.
The GEOS data are pre-processed for use in GEOS-Chem, in particular to generate coarser-resolution archives. The GEOS data can also be used directly without pre-processing and this is a new development in version 13.4.0.
GEOS-Chem simulations can be conducted at the native spatial resolution of the GEOS fields or at coarser resolutions. Simulations focused on the troposphere can reduce the number of vertical levels from 72 to 47 by coarsening the vertical resolution in the stratosphere and mesosphere. GEOS-Chem Classic simulations can also be conducted in nested mode (see Nesting below). The default timesteps are optimized to balance accuracy and speed as described by Philip et al. .
GEOS-Chem can also use off-line meteorological fields from the GISS GCM for future climates and paleoclimates. These implementations are referred to as the GCAP and ICECAP models. GCAP 2.0 is described by Murray et al.  and is a new development in version 13.1.0.
The GEOS-Chem chemical module can be used in on-line applications on any grid of the parent meteorological model:
- On-line coupling with the GEOS ESM is described by Hu et al.  and is called GEOS-GC
- On-line coupling with the Beijing Climate Center (BCC) climate model is described by Lu et al.  and is called BCC-GC
- On-line coupling with the Weather Research Forecast (WRF) model is described by Lin et al.  and Feng et al.  and is called WRF-GC.
The nested capability for GEOS-Chem was first implemented and described by Y. X. Wang et al. . It allows simulations at the native-grid horizontal resolution of the GEOS data over a user-selected regional domain with dynamic boundary conditions from a coarser global simulation. The nesting can either be 1-way, with no influence from the nested domain on the global domain, or 2-way where the two domains interact with each other. The 2-way nesting capability with multiple nests is described by Yan et al.  and on this wiki page.
The current nested version of GEOS-Chem Classic uses GEOS-FP data with 0.25° x 0.3125° resolution or MERRA-2 data with 0.5° x 0.625° resolution within the nested domain. The capability to operate at 0.25° x 0.3125°resolution with full aerosol-oxidant chemistry was originally developed by Zhang et al.  for East Asia and Kim et al.  for North America. FlexGrid allows users to define any nested domain at runtime, with no pre-processing of meteorological or other data files, requiring only the generation of boundary condition files at the global model resolution.
GCHP cannot use nested grids but can instead use the stretched-grid configuration of Bindle et al.  to provide high resolution over regions of interest. The refinement region characteristics can be specified at runtime without any preprocessing or generation of boundary condition files. Resolution varies smoothly away from refinement region. This is a new development in version 13.0.0.
GEOS-Chem Classic uses the TPCORE advection algorithm of Lin and Rood  on the latitude-longitude grid of the archived GEOS meteorological data. GCHP uses the FV3 advection algorithm of Putnam and Lin  on a cubed sphere grid after remapping the archived GEOS meteorological data on that grid. Convective transport in GEOS-Chem is computed from the convective mass fluxes in the meteorological archive as described by Wu et al. . Boundary layer mixing in GEOS-Chem uses the non-local scheme implemented by Lin and McElroy ; an option allows instead for full instantaneous mixing up to the GEOS-diagnosed mixing depth.
The wet deposition scheme in GEOS-Chem is described by Liu et al.  for water-soluble aerosols and by Amos et al.  for gases. Henry's law constants are from the compilation by Sander  including for water-soluble organics [Safieddine and Heald, 2017]. Scavenging of aerosol by snow and cold/mixed precipitation is described by Q. Wang et al. [2011, 2014]. Faster scavenging as described by Luo et al.  is an option in the model (new development in version 13.2.0.).
Dry deposition is based on the resistance-in-series scheme of Wesely  as implemented by Y. Wang et al. [1998a]. Size-dependent aerosol dry deposition is from Emerson et al.  and this is a new development in version 13.3.0.; older versions used aerosol dry deposition from Zhang et al. . Aerosol deposition to snow/ice is described by Fisher et al. . Gravitational settling is from Fairlie et al.  for dust and Alexander et al.  for coarse sea salt. Sea-salt deposition is from Jaegle et al. . Cold-temperature HNO3 deposition is from Jaegle et al. . There is an option for dependence of stomatal conductance on CO2 levels [Franks et al., 2013]. Ozone deposition to the ocean is from Pound et al. . Ozone deposition to snow and ice is from Barten et al.  and this is a new development in version 13.4.0.
See the mercury section for description of air-sea-land exchange of mercury.
GEOS-Chem can calculate the radiative forcing from changes in atmospheric composition using the optional RRTMG module. Implementation of RRTMG in GEOS-Chem is described in Heald et al. .
Photolysis frequencies for stratospheric and tropospheric chemistry are calculated with the Fast-JX code of Bian and Prather  as implemented in GEOS-Chem by Mao et al.  for the troposphere and Eastham et al.  for the stratosphere. Fractional cloud optical depths are represented with the approximate random overlap method [Liu et al., 2006, 2009]. The effect of aerosol extinction is as described by Latimer and Martin . There is an option to add absorption of UV by brown carbon [Hammer et al., 2016].
All GEOS-Chem emissions are configured at run-time using the HEMCO 3.0 facility described by Lin et al. ; this is a new development in version 13.1.0. HEMCO allows users to mix and match inventories from the GEOS-Chem library or add their own, apply scaling factors, overlay and mask inventories, etc. without having to edit or compile the code. HEMCO also has extensions to compute emissions with meteorological dependencies and to process other input/output data in GEOS-Chem. HEMCO 3.0 has a number of new features including greater modularity for adaptation to other models and an intermediate grid for more accurate regional masking of emissions.
Emissions of dust aerosol, lightning NOx, biogenic VOCs, soil NOx, and sea salt aerosol are dependent on the local meteorological conditions. These emissions are computed off-line at the native resolution of the GEOS meteorological data and then archived along with the GEOS data as input to GEOS-Chem. In that way, emissions in GEOS-Chem remain the same at any model resolution. Users can also choose to compute emissions on-line rather than using the off-line emission files. Off-line biogenic VOCs, soil NOx and sea salt aerosol emissions are described in Weng et al. . Off-line dust emissions are described in Meng et al. . Updated biogenic VOC and soil NOx emissions are a new development in version 14.0.0.
Anthropogenic. Global anthropogenic emissions up to 2019 are from the CEDS v2 inventory (CEDS v_2021_04_21 gridded emissions data | Datahub (pnnl.gov) as of version 13.2.0. An older CEDS version from McDuffie et al.  was a new development in version 13.0.0. The option to use HTAPv3 emissions [Crippa et al. 2023] at 0.1 degree resolution is a new development in version 14.1.0. EDGAR v4.3.2 [Crippa et al., 2018] with trash emissions from Wiedinmyer et al.  is available as an alternative option to CEDS (trash emissions are already included in CEDS). Ethane emissions from Tzompa-Sosa et al.  and propane emissions from Xiao et al.  overwrite the corrsponding CEDS and EDGAR v4.3.2 emissions in the default model. Diurnal variation of Chinese power plant emissions is from X. Liu et al.  and this is a new development in version 13.1.0. Vertical allocation of emissions by sector follows Hemispheric CMAQ [US EPA, 2019] and this is a new development in version 13.1.0.
Future projections of anthropogenic emissions following the RCP scenarios have been implemented into GEOS-Chem by Holmes et al. .
Aircraft. Aircraft emissions are from the AEIC 2019 inventory with reference to Simone et al.  and this is a new development in version 13.4.0. Older versions used the AEIC 2009 inventory [Stettler et al., 2011].
Ships. Global shipping emissions are from CEDS. Shipping emissions of NOx are processed by the PARANOX module of Vinken et al.  to account for ozone and HNO3 production in the plume. The PARANOX module was updated by Holmes et al. .
Open Fires. Emissions from open fires for individual years are from the GFED4.1s inventory with options to use instead the FINNv1.5 inventory [Wiedinmyer et al., 2011], the QFED inventory, or the GFAS inventory. The GFED4 biomass burning data have been extended through October 2022; this is a new development in version 14.2.0. The option to use a climatology of GFED4 biomass burning data is a new development in version 14.2.0. BB4CMIP historical fire emissions for 1750-2014 are from van Merle et al. . VOC fire emissions [Carter et al., 2022] are a new development in version 14.2.0.
Lightning. Lightning NOx emissions are as described by Murray et al.  to match OTD/LIS climatological observations of lightning flashes. The option to use climatology has added as a new development in version 14.2.0.
Biogenic VOCs. Biogenic VOC emissions in GEOS-Chem are from the MEGAN v2.1 inventory of Guenther et al.  as implemented by Hu et al. [2015b]. Leaf area indices (LAIs) used in MEGAN v2.1 are from the Yuan et al.  MODIS product for 2005-2020. Dependence on CO2 was added by Tai et al. . Acetaldehyde emissions are from Millet et al. (2010). Biogenic non-agricultural ammonia sources are from GEIA.
Soils. Biogenic soil NOx emissions are from Hudman et al. .
Ocean. Marine emissions of DMS are from the Lana et al.  dataset as implemented in GEOS-Chem by Breider et al. . Air-sea exchange of acetone assumes fixed ocean concentrations as described by Fischer et al. . Ocean acetaldehyde emissions are from Millet et al. (2010). Ammonia emissions from Arctic seabirds are from Croft et al. . Ocean ammonia emissions are from GEIA [Bouwman et al., 1997].
Volcanoes. Eruptive and non-eruptive volcanic SO2 emissions for individual years from 1978 to present are from the AEROCOM data base. Extension of the data to May 2020 is a new development in version 13.3.0. Older versions did not extend beyond 2018. For simulations of more recent periods when data are not available the non-eruptive volcanic emissions are set to a climatology and the eruptive emissions are set to zero.
Other. See the carbon gases section for GEOS-Chem references on emissions of CO2 and methane. See the aerosols section for GEOS-Chem references on primary aerosol emissions. See the mercury section for GEOS-Chem references on emissions of mercury. See the POPs section for GEOS-Chem references on emissions of persistent organic pollutants (POPs).
GEOS-Chem simulates detailed oxidant-aerosol chemistry in the troposphere and stratosphere. The chemical solver is KPP 3.0 [Lin et al., 2023] as implemented in GEOS-Chem with the FlexChem interface, and includes the option to use an adaptive chemical solver. KPP 3.0 is a new development in version 14.1.0.
Chemical mechanism kinetics generally follow JPL/IUPAC recommendations but go beyond the recommendations for specific aspects of the mechanism including for:
- Isoprene [Bates and Jacob, 2019].
- Aromatics [Bates et al., 2021]; this is a new development in version 13.3.0. Older versions used parameterized aromatic chemistry from Fischer et al. , mainly for PAN formation.
- Ethylene and acetylene chemistry [Kwon et al., 2021]; this is a new development in version 13.3.0.
- Methanol [Chen et al., 2019]. The CH3O2 + OH reaction was subsequently added as a source of methanol following Bates et al.  and this is a new development in version 13.3.0.
- Methyl, ethyl, and propyl nitrates [Fisher et al., 2018].
- Hydroxymethanesulfonate (HMS) chemistry [Moch et al., 2020]; this is a new development in version 13.3.0.
- Tropospheric halogen chemistry [Wang et al., 2021]; this is a new development in version 12.9.0. Older versions used a scheme based on Sherwen et al.  and Chen et al. . Sea salt debromination was restored in the standard model in version 14.2.0; it was an option in versions 13.4.0-14.1.0.
- Criegees [Millet et al., 2015].
- Mercury redox chemistry [Shah et al., 2022]; this is a new development in version 13.4.0. Older versions used Horowitz et al. 
- Aerosol nitrate photolysis [Shah et al., 2023]; this is a new development in version 14.2.0. Older versions had an option to add aerosol nitrate photolysis following Kasibhatla et al. .
- Lumped furans [Carter et al., 2022]; this is a new development in version 14.2.0.
See the radiation section for the calculation of photolysis frequencies. Methane is prescribed as a surface boundary condition from monthly mean maps of spatially-interpolated NOAA flask data, and subsequently allowed to advect and react [Murray, 2016]. Water is specified from the driving meteorological fields in the troposphere but is transported as a reactive tracer in the stratosphere.
Reactive uptake of NO2, NO3, and N2O5 by aerosols is as described by Holmes et al. , with reactive uptake coefficients for N2O5 on sulfate-nitrate-ammonium-organic aerosol from McDuffie et al. [2018ab]. HO2 uptake is from Mao et al.  with a reactive uptake coefficient of 0.2 for conversion to H2O. Acid uptake by dust particles from Fairlie et al.  is an option in the model. Aerosol hygroscopicity for calculating surface areas is from Latimer and Martin . Cloudwater pH is calculated following Shah et al. .
Reactive uptake of nitrogen oxides by clouds accounts for entrainment in the subgrid cloudy fraction of gridboxes. The same treatment is also applied for halogen reactive uptake by clouds starting with version 12.9.0. However, a bug caused the limitation by entrainment not to be implemented properly until version 13.3.0 and this is a new development in version 13.3.0.
GEOS-Chem simulations prior to version 13.2.0 could be configured to have full chemistry only in the troposphere (“troposphere-only simulation”) with simple linear representation of stratospheric chemistry following the Linoz algorithm of McLinden et al.  for ozone and monthly mean sources and loss rate constants for other gases [Murray et al., 2012]. This capability was disabled in version 13.2.0.
Sulfate-nitrate-ammonium aerosol. SNA thermodynamics are computed with the ISORROPIA thermodynamic module [Fontoukis and Nenes, 2007], most recently updated to version 2.2. Sulfur oxidation in clouds and aerosols is coupled with gas-phase chemistry through KPP and this is a new development in version 13.4.0.
Carbonaceous aerosol. Q. Wang et al.  describes the BC simulation in GEOS-Chem. Organic aerosol in the default model follows the 'simple SOA' scheme of Pai et al. . The model has an option for 'complex SOA' following the Volatility Basis Set (VBS) scheme of Pye et al.  and also including the aqueous-phase isoprene SOA scheme of Marais et al.  coupled to the isoprene gas-phase chemistry mechanism.
Dust aerosol. The dust simulation in GEOS-Chem is described by Fairlie et al. . Dust size distributions are from Li Zhang et al. . Fine anthropogenic dust from combustion and industrial sources is from the AFCID inventory of Philip et al. .
Sea salt. The sea salt aerosol simulation in GEOS-Chem is described by Jaegle et al. . An update to include emissions from blowing snow [Huang and Jaegle, 2017] is a new development in version 13.2.0.
Marine POA. There is an option to emit marine POA following Gantt et al. .
Trace metals. Simulation of 12 aerosol-borne trace metals is from Xu et al.  and is a new development in version 13.2.0.
Aerosol microphysics. Two alternate simulations of aerosol microphysics are implemented in GEOS-Chem: the TOMAS simulation [Kodros and Pierce, 2017] and the APM simulation [Yu and Luo, 2009].
Aerosol optical depth. Aerosol optical depth affecting photolysis rates is calculated in GEOS-Chem using RH-dependent aerosol optical properties from Latimer and Martin . Dust optics are from Ridley et al. .
Aerosol-only simulation. In addition to the fully coupled gas-aerosol simulation described in the Tropospheric Chemistry section, there is an option to conduct aerosol-only simulations using fixed 3-D monthly oxidant concentrations (from a GEOS-Chem simulation of old vintage) and simple SOA. This is described by Leibensperger et al. .
CO2. The current form of the simulation is described by Nassar et al. . Anthropogenic emissions are from ODIAC2019 [Oda and Maksyutov, 2011; Oda et al., 2018] and this is a new development in version 13.0.0.
Methane. The current form of the simulation is described by Maasakkers et al. . Updated soil uptake is from the MeMo model v1.0 [Murguia-Flores et al., 2018]. Default global anthropogenic emissions are from EDGAR version 7; this update from EDGAR version 6 is a new development in version 14.2.0. Updated emission from fuel exploitation is from Scarpelli et al. [2022a] and is a new development in version 13.4.0. older versions used Scarpelli et al.  which was a new development in version 13.0.0. Anthropogenic emissions from Mexico are from Scarpelli et al. [2020b] and this is a new development in version 13.1.0. Anthropogenic emissions from Canada are from Scarpelli et al. [2022b] and this is a new development in version 13.4.0. Methane emissions from hydropower reservoirs is from Delwiche et al. ; this is a new development in version 14.2.0.
CO. Simulation of CO in GEOS-Chem can be conducted either as part of the standard full-chemistry simulation or as a separate tagged-tracer simulation that resolves CO sources from individual regions or processes, and uses archived OH fields from a full-chemistry simulation to compute the CO sink. The most recent version is described by Fisher et al. .
Carbon simulation. A carbon simulation (CO2-CO-CH4-OCS) via KPP is a new development in version 14.1.0.
The original GEOS-Chem coupled atmosphere-ocean simulation of mercury was described by Selin et al.  for the atmosphere and by Strode et al.  for the ocean. Extension to a coupled atmosphere-ocean-land model was described by Selin et al. . The current version of the atmospheric simulation is described by Shah et al.  and this is a new development in version 13.4.0. Older versions used Horowitz et al. . Improvements in modeled Hg0 dry deposition to land is a new development in version 14.1.0 [Feinberg et al. 2022]. The current version of the ocean simulation is described by Soerensen et al. , with updated ocean rate coefficients from Song et al. . Treatment of Arctic sea ice and rivers is as described by Fisher et al. [2012, 2013]. Gas-aerosol partitioning of Hg(II) is from Amos et al. .There is an option to couple GEOS-Chem with the terrestrial mercury module developed by Smith-Downey et al. . The option to use AMAP 2015 emissions [Steenhuisen and Wilson, 2022] is a new development in version 14.1.0.
Anthropogenic emissions are from Y. Zhang et al. . Future SRES emission scenarios have been implemented by Corbitt et al. . Options are available to use anthropogenic emissions from Streets et al.  or from EDGAR v4.2 [Muntean et al., 2018], and these are new developments in version 13.0.
The model includes a simulation of PAHs as described by Friedman et al. .
Radon-222 emissions are from B. Zhang et al.  and this is a new development in version 13.4.0.
The model offers detailed output diagnostics in NetCDF format including species concentrations, production and loss rates, family production and loss rates, emissions, deposition fluxes and velocities, budgets and fluxes, time series at fixed locations or along selected aircraft flight tracks and satellite orbits, etc. See the GEOS-Chem wiki diagnostics page for more information. The NOAA Obspack diagnostic is available for comparison of model output to compiled global suborbital observations of greenhouse gases.
Surface ozone and HNO3 concentrations can be diagnosed below the lowest model gridpoint to take into account aerodynamic resistance to deposition [Travis and Jacob, 2019].
The model PM2.5 diagnostic is calculated as described by Latimer and Martin . The PM10 diagnostic is calculated as described by Zhai et al.  and this is a new development in version 13.4.0.
See the GEOS-Chem adjoint wiki page for description and references.
- Alexander, B., R.J. Park, D.J. Jacob, Q.B. Li, R.M. Yantosca, J. Savarino, C.C.W. Lee, and M.H. Thiemens, Sulfate formation in sea-salt aerosols: Constraints from oxygen isotopes, J. Geophys. Res., 110, D10307, 2005.
- Amos, H. M., D. J. Jacob, C. D. Holmes, J. A. Fisher, Q. Wang, R. M. Yantosca, E. S. Corbitt, E. Galarneau, A. P. Rutter, M. S. Gustin, A. Steffen, J. J. Schauer, J. A. Graydon, V. L. St. Louis, R. W. Talbot, E. S. Edgerton, Y. Zhang, and E. M. Sunderland, Gas-Particle Partitioning of Atmopsheric Hg(II) and Its Effect on Global Mercury Deposition, Atmos. Chem. Phys., 12, 591-603, 2012.
- Barten, J.M.G., L.N. Ganzeveld, J.-G. Steeneveld, and M.C. Krol, Role of oceanic ozone deposition in explaining temporal variability in surface ozone at High Arctic sites, Atmos. Chem. Phys., 21, 10229–10248, 2021.
- Bates, K.H., and D.J. Jacob, A new model mechanism for atmospheric oxidation of isoprene: global effects on oxidants, nitrogen oxides, organic products, and secondary organic aerosol, Atmos. Chem. Phys., 19, 9613-9640, 2019.
- Bates, K.H., Jacob, D.J., Wang, S., Hornbrook, R.S., Apel, E.C., Kim, M.J., Millet, D.B., Wells, K.C., Chen, X., Brewer, J.F., Ray, E.A., Diskin, G.S., Commane, R., Daube, B.C. and Wofsy, S.C., The global budget of atmospheric methanol: new constraints on secondary, oceanic, and terrestrial source, J. Geophys. Res., 126, e2020JD033439, 2021.
- Bates, K. H., Jacob, D. J., Li, K., Ivatt, P. D., Evans, M. J., Yan, Y., and Lin, J.: Development and evaluation of a new compact mechanism for aromatic oxidation in atmospheric models, Atmos. Chem. Phys., 21, 18351–18374, https://acp.copernicus.org/articles/21/18351/2021/, 2021.
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- Bian, H. S., and M. J. Prather, Fast-J2: Accurate simulation of stratospheric photolysis in global chemical models, J. Atmos. Chem., 41, 281-296, 2002.
- Bindle, L., Martin, R. V., Cooper, M. J., Lundgren, E. W., Eastham, S. D., Auer, B. M., Clune, T. L., Weng, H., Lin, J., Murray, L. T., Meng, J., Keller, C. A., Putman, W. M., Pawson, S., and Jacob, D. J.: Grid-stretching capability for the GEOS-Chem 13.0.0 atmospheric chemistry model, Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, 2021.
- Bouwman, A. F., D. S. Lee, W. A. H. Asman, F. J. Dentener, K. W. Van Der Hoek, and J. G. J. Olivier (1997), A global high-resolution emission inventory for ammonia, Global Biogeochem. Cycles, 11(4), 561-587.
- Breider, T.J., L.J. Mickley, D.J. Jacob, C. Ge, J. Wang, M.P. Sulprizio, B. Croft, D.A. Ridley, J.R. McConnell, S. Sharma, L. Husain, V.A. Dutkiewicz, K. Eleftheriadis, H. Skov, and P.K. Hopke, Multi-decadal trends in aerosol radiative forcing over the Arctic: contribution of changes in anthropogenic aerosol to Arctic warming since 1980, J. Geophys. Res., 122(6), 3573-3594, doi:10.1002/2016JD025321, 2017.
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