Principal component analysis optimization of a PM2.5 land use regression model with small monitoring network.
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Modeling particle number concentrations along Interstate 10 in El Paso, TexasComputation of geographic variables for air pollution prediction models in South KoreaImpact of Land Use on PM2.5 Pollution in a Representative City of Middle ChinaLocal Variability in the Impacts of Residential Particulate Matter and Pest Exposure on Children's Wheezing Severity: A Geographically Weighted Regression Analysis of Environmental Health Justice.A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China.The value of using seasonality and meteorological variables to model intra-urban PM variation
P2860
Principal component analysis optimization of a PM2.5 land use regression model with small monitoring network.
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2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
2012年论文
@zh
2012年论文
@zh-cn
name
Principal component analysis o ...... with small monitoring network.
@ast
Principal component analysis o ...... with small monitoring network.
@en
type
label
Principal component analysis o ...... with small monitoring network.
@ast
Principal component analysis o ...... with small monitoring network.
@en
prefLabel
Principal component analysis o ...... with small monitoring network.
@ast
Principal component analysis o ...... with small monitoring network.
@en
P2093
P2860
P1476
Principal component analysis o ...... with small monitoring network.
@en
P2093
Hector A Olvera
Hongling Yang
Maria A Amaya
Marianne Berwick
Mario Garcia
Nicholas E Pingitore
Orrin Myers
Scott W Burchiel
Wen-Whai Li
P2860
P356
10.1016/J.SCITOTENV.2012.02.068
P577
2012-03-29T00:00:00Z