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@ARTICLE{DeSouzaFernandesDuarte:902391,
author = {De Souza Fernandes Duarte, Ediclê and Franke, Philipp and
Lange, Anne Caroline and Friese, Elmar and Juliano da Silva
Lopes, Fábio and João da Silva, Jonatan and Souza dos
Reis, Jean and Landulfo, Eduardo and Santos e Silva,
Cláudio Moises and Elbern, Hendrik and Hoelzemann, Judith
Johanna},
title = {{E}valuation of atmospheric aerosols in the metropolitan
area of {S}ão {P}aulo simulated by the regional
{EURAD}-{IM} model on high-resolution},
journal = {Atmospheric pollution research},
volume = {12},
number = {2},
issn = {1309-1042},
address = {Blackburn, Vic.},
publisher = {TUNCAP},
reportid = {FZJ-2021-04225},
pages = {451 - 469},
year = {2021},
abstract = {We present a high-resolution air quality study over São
Paulo, Brazil with the EURopean Air Pollution Dispersion -
Inverse Model (EURAD-IM) used for the first time over South
America simulating detailed features of aerosols. Modeled
data are evaluated with observational surface data and a
Lidar. Two case studies in 2016 with distinct meteorological
conditions and pollution plume features show transport (i)
from central South America, associated to biomass burning
activities, (ii) from the rural part of the state of São
Paulo, (iii) between the metropolitan areas of Rio de
Janeiro and São Paulo (MASP) either through the Paraíba
Valley or via the ocean, connecting Brazil's two largest
cities, (iv) from the port-city Santos to MASP and also from
MASP to the city Campinas, and vice versa. A Pearson
coefficient of 0.7 was found for PM10 at MASP CENTER and
EURAD-IM simulations vary within the observational standard
deviation, with a Mean Percentual Error (MPE) of $10\%.$ The
model's vertical distributions of aerosol layers agree with
the Lidar profiles that show either characteristics of
long-range transported biomass burning plumes, or of local
pollution. The distinct transport patterns that agree with
satellite Aerosol Optical Death and fire spot images as well
as with the ground-based observations within the standard
deviations, allows us exploring patterns of air pollution in
a detailed manner and to understand the complex interactions
between local to long-range transport sources.},
cin = {IEK-8},
cid = {I:(DE-Juel1)IEK-8-20101013},
pnm = {2111 - Air Quality (POF4-211)},
pid = {G:(DE-HGF)POF4-2111},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000616932200001},
doi = {10.1016/j.apr.2020.12.006},
url = {https://juser.fz-juelich.de/record/902391},
}