Spatiotemporally resolved ambient particulate matter concentration by fusing observational data and ensemble chemical transport model simulations

Autore
E. Chianese
A. Galletti
G. Giunta
T.C. Landi
L. Marcellino
R. Montella
A. Riccio
Parole chiave
Air quality
Environmental Protection Agency
Forecasting
Landforms
Mean square error
Monte Carlo methods
Particles (particulate matter)
Ambient particulate Matter
Annual average concentration
Chemical transport models
data assimilation
Matter flows
Particulate Matter
Population exposure
World Health Organization
Population statistics
Air quality
ambient air
atmospheric dynamics
Atmospheric modeling
atmospheric pollution
atmospheric transport
chemical analysis
concentration (composition)
data assimilation
Particulate Matter
pollution exposure
spatiotemporal analysis
World Health Organization
Italy
PO Valley
Year of Publication
2018
Journal
Ecological Modelling
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050980380&doi=10.1016%2fj.ecolmodel.2018.07.019&partnerID=40&md5=990bb6ad2a993fc7b486ea288c234aa5
DOI
10.1016/j.ecolmodel.2018.07.019