Optimal estimation for global ground-level fine particulate matter concentrations
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Spatiotemporal Pattern of PM2.5 Concentrations in Mainland China and Analysis of Its Influencing Factors using Geographically Weighted Regression.A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution.Cohort Profile: The ONtario Population Health and Environment Cohort (ONPHEC).
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Optimal estimation for global ground-level fine particulate matter concentrations
description
article
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wetenschappelijk artikel
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наукова стаття, опублікована в червні 2013
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name
Optimal estimation for global ground-level fine particulate matter concentrations
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Optimal estimation for global ground-level fine particulate matter concentrations
@nl
type
label
Optimal estimation for global ground-level fine particulate matter concentrations
@en
Optimal estimation for global ground-level fine particulate matter concentrations
@nl
prefLabel
Optimal estimation for global ground-level fine particulate matter concentrations
@en
Optimal estimation for global ground-level fine particulate matter concentrations
@nl
P2093
P2860
P356
P1476
Optimal estimation for global ground-level fine particulate matter concentrations
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P2093
Aaron van Donkelaar
Easan Drury
Lorraine A. Remer
Randall V. Martin
Robert C. Levy
Robert J. D. Spurr
P2860
P304
P356
10.1002/JGRD.50479
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P577
2013-06-10T00:00:00Z