@Article{FreitasLSSCPAGR:2005:MoTrBi,
author = "Freitas, Saulo Ribeiro de and Longo, Karla Maria and Silva Dias,
Maria Assuncao Faus da and Silva Dias, Pedro L. and Chatfield,
Robert and Prins, Elaine and Artaxo, Paulo and Grell, Georg A. and
Recuero, Fernando S.",
affiliation = "{CPTEC-INPE-Cachoeira Paulista-12630-000-SP-Brasil}",
title = "Monitoring the transport of biomass burning emissions in South
America",
journal = "Environmental Fluid Mechanics",
year = "2005",
volume = "5",
number = "1-2",
pages = "135 - 167",
month = "Apr.",
keywords = "Aerosol transport, air pollution, atmospheric modeling, biomass
burning, climate change, long-distance transpol1, weather
forecast.",
abstract = "The atmospheric transport of biomass buming emissions in the South
American and African continents is being monitored annually using
a numerical simulation of air mass motions; we use a tracer
transport capability developed within RAMS (Regional Atmospheric
Modeling Sys- tem) coupled to an emission modelo Mass conservation
equations are solved for carbon monoxide (CO) and particulate
material (PM2.5). Source emissions of trace gases and particles
associated with biomass buming activities in tropical forest,
savanna and pasture have been parameterized and introduced into
the modelo The sources are distributed spatially and temporally
and assimilated daily using the biomass buming locations detected
by remote sensing. Advection effects (at grid scale) and turbulent
transport (at sub-grid scale) are provided by the RAMS
parameterizations. A sub- grid transport parameterization
associated with moist deep and shallow convection, not explicitly
resolved by lhe modeldue to its low spatial resolution, has also
been introduced. Sinks associated with lhe process of wet and dry
removal of aerosol particles and chemical transformation of gases
are parameterized and introduced in lhe mass conservation
equation. An operational system has been implemented which
produces daily 48-h numerical simulations (including 24-h
forecasts) of CO and PM2.5, in addition to traditional
meteorological fields. The good prediction skills of lhe model are
demonstrated by comparisons with time series of PM2.5 measured at
the surface.",
copyholder = "SID/SCD",
issn = "1567-7419",
language = "en",
targetfile = "Freitas_Monitoring the transport of biomass.pdf",
urlaccessdate = "08 maio 2024"
}