Monitoring the Transport of Biomass Burning and Anthropogenic Pollution in South America
Abstract
The atmospheric transport of biomass burning and anthropogenic emissions over the South American and African continents and the South Atlantic Ocean is monitored by CPTEC/INPE on an operational basis<meioambiente.cptec.inpe.br>. A real time operational transport monitoring system was implemented in 2003 using the on-line 3-D transport model CATT-BRAMS (Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modelling System) coupled to an emission model. In this model, the mass conservation equation is solved for carbon monoxide (CO) and particulate material PM2.5. Source emissions of gases and particles associated with biomass burning activities in tropical forest, savanna and pasture are parameterized and introduced in the model. The sources are spatially and temporally distributed and assimilated daily according to the biomass burning locations obtained by remote sensing (AVHRR, MODIS and GOES-12). Anthropogenic sources of CO are also included, according to the EDGAR/RETRO/CETESB databases. Grid-scale advection is solved using a forward upstream scheme of second-order, the horizontal diffusion is based on the Smagorinsky formulation, and the vertical diffusion is parameterized according to the Mellor and Yamada 2.5 scheme, which employs a prognostic of the turbulent kinetic energy. A parameterization is also introduced for sub-grid transport associated with wet, deep and shallow convection not explicitly resolved by the model due to its low spatial resolution. The plume rise sub-grid scale transport associated with vegetation fires is simulated by embedding a 1D cloud resolving model, with appropriate lower boundary conditions, in each column of the CATT-BRAMS host model. Sinks, associated with generic processes of removal/transformation of gases and particles, are parameterized and introduced in the mass conservation equation.coupled to an emission model. In this model, the mass conservation equation is solved for carbon monoxide (CO) and particulate material PM2.5. Source emissions of gases and particles associated with biomass burning activities in tropical forest, savanna and pasture are parameterized and introduced in the model. The sources are spatially and temporally distributed and assimilated daily according to the biomass burning locations obtained by remote sensing (AVHRR, MODIS and GOES-12). Anthropogenic sources of CO are also included, according to the EDGAR/RETRO/CETESB databases. Grid-scale advection is solved using a forward upstream scheme of second-order, the horizontal diffusion is based on the Smagorinsky formulation, and the vertical diffusion is parameterized according to the Mellor and Yamada 2.5 scheme, which employs a prognostic of the turbulent kinetic energy. A parameterization is also introduced for sub-grid transport associated with wet, deep and shallow convection not explicitly resolved by the model due to its low spatial resolution. The plume rise sub-grid scale transport associated with vegetation fires is simulated by embedding a 1D cloud resolving model, with appropriate lower boundary conditions, in each column of the CATT-BRAMS host model. Sinks, associated with generic processes of removal/transformation of gases and particles, are parameterized and introduced in the mass conservation equation.
History of model development
The development of the current model system was initiated during the Ph. D. programs of Saulo R. Freitas and Karla M. Longo at the Physics Institute of the University of São Paulo under the supervision of Professor Maria Assunção Silva Dias and Professor Paulo Artaxo. Further improvements were carried out at the NASA Ames Research Center in collaboration with Dr. Robert Chatfield. Currently, the model development under progress at CPTEC-INPE is carried out in collaboration with the University of Orleans and the University of São Paulo.
Model Description
BRAMS - Brazilian developments on the Regional Atmospheric Modeling System
BRAMS (www.cptec.inpe.br/brams) is based on the Regional Atmospheric Modeling System (RAMS, Walko et al., 2000) version 6 with several new functionalities and parameterizations specialized for the tropics and sub-tropics. RAMS is a multipurpose, numerical prediction model designed to simulate atmospheric circulations spanning from hemispheric scales down to large eddy simulations (LES) of the planetary boundary layer (Walko et al., 2000, www.atmet.com). The equation set used is comprised of the quasi-Boussinesq non-hydrostatic equations described by Tripoli and Cotton (1982). The model is equipped with a multiple grid nesting scheme which allows the model equations to be solved simultaneously on any number of interacting computational meshes of differing spatial resolution. It has a complex set of packages to simulate processes such as radiative transfer, surface-air water, heat and momentum exchanges, turbulent planetary boundary layer transport, and cloud microphysics. The initial conditions can be defined from various observational data sets that can be combined and processed with a mesoscale isentropic data analysis package (Tremback, 1990). For the boundary conditions, the 4DDA schemes allow the atmospheric fields to be nudged towards the large-scale data. BRAMS features used in this system include an ensemble version of a deep and shallow cumulus scheme based on the mass flux approach (Grell and Devenyi, 2002) and soil moisture initialization data (Gevaerd and Freitas, 2006).
Some of the following parameterizations are used in the model:
  • The horizontal diffusion coefficients are based on the Smagorinsky (1963) formulation.
  • The vertical diffusion is parameterized according to the Mellor and Yamada (1974) scheme, which employs a prognostic of the turbulent kinetic energy.
  • The surface-atmosphere water, momentum and energy exchanges are simulated by the Land Ecosystem Atmosphere Feedback model (LEAF-3), which represents the storage and vertical exchange of water and energy in multiple soil layers, including the effects of freezing and thawing soil, temporary surface water or snowcover, vegetation, and canopy air (Walko et al., 2000).
  • The advection scheme is forward upstream of second-order (Tremback et al, (1987)).
  • Bulk microphysics (Walko et al., 2000)
  • Convective cumulus scheme for deep and shallow convection based on Grell and Devenyi (2002).
  • The 4D Data Assimilation (4DDA), a nudging type scheme in which the model fields can be nudged toward assimilated observational data.
Coupled Aerosol and Tracer Transport model coupled to BRAMS (CATT-BRAMS)
CATT-BRAMS utilizes the BRAMS tracer transport capability of using slots for scalars. The in-line transport model follows the Eulerian approach, solving the mass conservation equation for carbon monoxide (CO) and particulate material (PM2.5), where the tracer mixture ratio s (=ρ/ρair), is calculated using the mass conservation equation (using tendencies notation)

where adv, PBL turb and deep(shallow) conv stand for grid-scale advection, sub-grid transport in the planetary boundary layer (PBL) and sub-grid transport associated with moist and deep (shallow, non-precipitating) convection, respectively. W accounts for the convective wet removal of PM2.5, R is a sink term associated with generic processes of removal/transformation of tracers (dry deposition and sedimentation for PM2.5 and chemical transformation for CO), and Qplume-rise is the source emission associated with the biomass burning process including the plume rise mechanism.
The grid-scale advection is a forward upstream scheme of second-order, the horizontal diffusion is based on the Smagorinsky formulation and the vertical diffusion is parameterized according to the Mellor and Yamada scheme. The sub-grid transport associated with deep and shallow convective transport is coupled to the Grell cumulus scheme. For PM2.5, the tracer convective transport scheme also accounts for the wet (in and below cloud) removal based on the work of Berge (1993). The plume rise associated with the vegetation fires is included following the super-parameterization concept (Freitas et al., 2006, 2007). Dry deposition and sedimentation follows the resistance approach. Figure 1 illustrates several sub-grid atmospheric processes simulated by CATT-BRAMS. Also, an additional radiation parameterization was implemented, which includes the interaction between aerosol particles and short and long wave radiation using the rapid two-stream approximation (Toon, et al., 1989), and calculates the aerosol scattering and absorption with the Mie code for stratified spheres (Toon and Ackerman, 1981). For smoke aerosols, a dynamic model is used, derived from three years of optical properties retrievals from some of the Amazonian AERONET sites measurements (Procópio et al., 2003).
Figure 1. Some sub-grid process involved in gas/aerosol transport and simulated by the CATT-BRAMS model.
Source emission parameterization
A biomass burning tracer emission parameterization based on the work of Freitas (1999) was implemented. The biomass burning source emission parameterization (for CO, CO2, CH4, NOx and PM2.5) is based on the GOES-12 WF_ABBA fire product (Prins et al., (1998), http://cimss.ssec.wisc.edu/goes/burn/abba.html) GOES-12, AVHRR and MODIS fire observation from CPTEC-INPE (http://www.cptec.inpe.br/queimadas/), and field observations. For each fire detected by remote sensing, the mass of emitted tracers is calculated (details: source emission ) and its emission in the model follows the diurnal burning cycle (emission rate). The type of burning vegetation is obtained from the IGBP-INPE 1km vegetation map (http://edcdaac.usgs.gov/glcc/glcc.html) and (http://www.cptec.inpe.br/proveg/). The sources are spatially and temporally distributed and assimilated daily according to the biomass burning locations defined by the satellite observations (Figure 2). The biomass burning emissions are added to the EDGAR agricultural waste burning and fuelwood burning emissions with 1x1 degree horizontal resolution and 1 year time resolution (see pictures
). On the African continent, the biomass burning emissions are always defined following the GFEDv2 prescription.
The carbon monoxide emissions associated with anthropogenic processes (industrial, power generation, transportation, etc.) are provided by the EDGAR/RETRO databases with a CETESB correction for the São Paulo Metropolitan Area (CETESB/2002).

Figure 2. Biomass burning emissions inventory used by CATT-BRAMS model.

Product description
Model configuration, initial and boundary conditions
The model is set up with 3 grids at horizontal resolutions of 150, 30 and 15 km (Figure 3). The vertical resolution starts at 150 m near the surface, stretching at a rate of 1.15 to a final resolution of 850 m, with the model top at about 20 km. The coarse grid, covering the South American and African continents, is intended to generate the tracer inflow from Africa to South America. The atmospheric model is initialized and nudged with the CPTEC global model (6 hours 1.875 degrees) analysis/forecast data. The 3D tracer concentration fields of the previous run are used as the tracer initial condition for the next, and the constant inflow condition is used as the tracer boundary condition in the coarse grid. The simulation is performed for 48 hours, beginning at 00 UTC the previous day. The soil moisture is initialized based on the antecedent precipitation index method (Gevaerd and Freitas, 2006). Analysis and forecast of carbon monoxide and aerosol particles mass concentration, aerosol optical thickness, and aerosol particle deposited wet mass fields are provided daily at meioambiente.cptec.inpe.br. Comparison of model results with remote sensing aerosol and trace gas products and direct measurements have demonstrated the good prediction skills of the model.

Figure 3. Operational model grids

Model comparison and evaluation with observational and remote sensing data for 2002 dry season
Model evaluation with SMOCC/RaCCI 2002 surface and airborne measurements Figure 4 shows two time series with a comparison of surface CO and PM2.5 from the model and observations. An intercomparison of PM2.5 and CO model results at 1200 UTC with daily averages of the measurements centered at 1200 Z reveals good agreement in terms of the values and general pattern of temporal evolution.

Figure 4. Time series with comparison between near surface CO (ppb, top) and PM2.5 (g m-3, bottom) observed (black) and model results (red). The measurements were daily averaged, centered at 1200 Z. The error bars are the standard deviations of the mean values. The model results are presented as instantaneous values at 1200 UTC.

Comparisons of simulated CO profiles in the PBL and lower troposphere with observed data were performed using SMOCC/RaCCI campaign airborne measurements. Figure 5 shows comparisons for sixteen flights. The mean and STD of the observed CO profiles are shown; note that STD represents the actual variability of the concentrations, not the measurement error.

Figure 5. Comparison between CO (ppb) observed during sixteen flights of the LBA-SMOCC/RaCCI field campaign (black solid line represents the mean while the grey zone shows the standard deviation range) and model results (blue).

The overall model performance can be evaluated in Figure 6, where the mean observed CO profile and its STD are presented together with the mean model CO. The model result is very consistent with the observed mean, being always inside the STD range. Figure 6 also indicates that the model is able to accurately capture the vertical distribution of the observed concentrations.

Figure 6. Comparison between the mean CO (ppb) observed during sixteen flights of the LBA-SMOCC/RaCCI field campaign (black solid line represents the mean while the grey zone shows the standard deviation range) and the mean of model results (blue).

5.2 Model comparisons with MOPITT data
Model performance on larger scales and including upper tropospheric levels is evaluated in this section, using data retrieved by the Measurements of Pollution in the Troposphere (MOPITT) instrument, onboard the Earth Observing System Terra satellite. MOPITT retrievals of tropospheric CO mixing ratio (ppb) are reported for 7 pressure levels, from the surface to 150 hPa (Deeter et al., 2003). Because MOPITT data have large horizontal areas without valid data due to swath width and cloud cover, the model results and MOPITT data were monthly averaged, after applying the averaging kernel and a priori profile, and using retrievals with < 50% a priori contribution. Figure 7 shows the comparisons for the months of August, September and October on five vertical levels (850, 700, 500, 350 and 250 hPa) on the large scale grid. The quantity depicted in the above-mentioned figure is the relative model error (ME) defined as
,
where COmodel is the monthly mean of model CO mixing ratio after applying the averaging kernel and a priori fraction < 50%.

Figure 7. CO model relative error (%) relative to the MOPITT CO retrieval for the months of August, September and October, 2002 at five vertical levels (850, 700, 500, 350 and 250 hPa). Positive values mean that model results are underestimated in reference to the MOPITT retrieved data and vice-versa.

An upper troposphere study (September 7 to 9, 2002 cold front convective case)

Figure 8. Model CO mixing ratio (ppb, on the left) and the model error relative to the MOPITT CO retrievals (%, on the right) at 250, 350 and 500 hPa. Model and MOPITT data were time averaged over the days September 6, 7, 8 and 9, 2002. White areas, on the right, denote places without valid data for MOPITT during the time averaged period.

5.2 Model comparisons with MODIS/TERRA data
Comparison of the aerosol optical thickness (550 nm channel) derived from MODIS-TERRA observations and calculated from the model (combination of the regional grid and coarse grid) for August 27, 2002. A smoke corridor is evident that was associated with an anticyclone circulation centered over the Atlantic Ocean. The long-range transport of smoke results in transboundary air pollution with smoke-laden air crossing into South American countries, such as Paraguay, Argentina and Uruguay.

Figure 9. Model and MODIS AOT (550 nm) comparison.

Winds and columnar particulate material for August 25, 2002. The detail shows the true color image from MODIS-TERRA observations at 14:05 Z on the same day.
Contacts: karla.longo@cptec.inpe.br and/or saulo.freitas@cptec.inpe.br
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