An innovative land use regression model incorporating meteorology for exposure analysis.
about
Spatial modeling of PM10 and NO2 in the continental United States, 1985-2000.Within-neighborhood patterns and sources of particle pollution: mobile monitoring and geographic information system analysis in four communities in Accra, Ghana.Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study.Development of temporally refined land-use regression models predicting daily household-level air pollution in a panel study of lung function among asthmatic children.The spatial relationship between traffic-generated air pollution and noise in 2 US citiesUrban land-use and respiratory symptoms in infants.An LUR/BME framework to estimate PM2.5 explained by on road mobile and stationary sources.Particles, air quality, policy and health.Can dispersion modeling of air pollution be improved by land-use regression? An example from Stockholm, Sweden.Study of the PM₁₀ concentration variations along two intra-urban roads within a compact city.Transferability and generalizability of regression models of ultrafine particles in urban neighborhoods in the Boston area.Exploring the modeling of spatiotemporal variations in ambient air pollution within the land use regression framework: Estimation of PM10 concentrations on a daily basis.Use of real-time sensors to characterise human exposures to combustion related pollutants.The value of using seasonality and meteorological variables to model intra-urban PM variationEstimating daily surface NO<sub>2</sub> concentrations from satellite data – a case study over Hong Kong using land use regression models
P2860
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P2860
An innovative land use regression model incorporating meteorology for exposure analysis.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年学术文章
@wuu
2007年学术文章
@zh-cn
2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
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2007年學術文章
@zh-hant
name
An innovative land use regression model incorporating meteorology for exposure analysis.
@en
An innovative land use regression model incorporating meteorology for exposure analysis.
@nl
type
label
An innovative land use regression model incorporating meteorology for exposure analysis.
@en
An innovative land use regression model incorporating meteorology for exposure analysis.
@nl
prefLabel
An innovative land use regression model incorporating meteorology for exposure analysis.
@en
An innovative land use regression model incorporating meteorology for exposure analysis.
@nl
P2093
P1476
An innovative land use regression model incorporating meteorology for exposure analysis.
@en
P2093
Bruce Ainslie
Douw Steyn
Jason G Su
Michael Buzzelli
Timothy Larson
P304
P356
10.1016/J.SCITOTENV.2007.10.032
P577
2007-11-28T00:00:00Z