Journal ArticleDOI
Estimating ground-level PM2.5 concentrations in the southeastern U.S. using geographically weighted regression
Xuefei Hu,Lance A. Waller,Mohammad Z. Al-Hamdan,William L. Crosson,Maurice G. Estes,Sue Estes,Dale A. Quattrochi,Jeremy A. Sarnat,Yang Liu +8 more
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TLDR
A geographically weighted regression model was developed to examine the relationship among PM(2.5), aerosol optical depth, meteorological parameters, and land use information, and suggested that North American Land Data Assimilation System could be used as an alternative of North American Regional Reanalysis to provide some of the meteorological fields.About:
This article is published in Environmental Research.The article was published on 2013-02-01. It has received 288 citations till now. The article focuses on the topics: Data assimilation & Cross-validation.read more
Citations
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Addressing the source contribution of PM2.5 on mortality: an evaluation study of its impacts on excess mortality in China
TL;DR: In this paper, the authors estimated PM2.5 concentrations using satellite data and population mortality values for cause-specific diseases and employed the integrated exposure-response model to obtain the associations between exposure and response.
Journal ArticleDOI
OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning
Florian Lautenschlager,Martin Becker,Konstantin Kobs,Michael Steininger,Padraig Davidson,Anna Krause,Andreas Hotho +6 more
TL;DR: This work introduces OpenLUR, an off-the-shelf approach for modeling air pollution that works on a set of novel features solely extracted from the globally and openly available data source OpenStreetMap and is based on state-of- the-art machine learning featuring automated hyper-parameter tuning in order to minimize manual effort.
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Simplicity versus accuracy for estimation of the PM2.5 concentration: a comparison between LUR and GWR methods across time scales
TL;DR: In this article, the authors compared land use regression (LUR) and geographically weighted regression (GWR) models in PM2.5 concentration mapping over California (USA) and found that LUR model is more accurate than GWR model.
Journal ArticleDOI
Monitoring, Mapping, and Modeling Spatial-Temporal Patterns of PM2.5 for Improved Understanding of Air Pollution Dynamics Using Portable Sensing Technologies.
TL;DR: Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height).
Journal ArticleDOI
Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing
Wei Chen,Aiping Fan,Lei Yan +2 more
TL;DR: The results demonstrate that the MODIS 3 km DT AOD product may not be the appropriate proxy to be used in the satellite retrieval of surface PM2.5, especially for those areas with frequent haze-fog events like Beijing.
References
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Journal ArticleDOI
Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution
C. Arden Pope,Richard T. Burnett,Michael J. Thun,Eugenia E. Calle,Daniel Krewski,Kazuhiko Ito,George D. Thurston +6 more
TL;DR: Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality and long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopULmonary and lung cancer mortality.
Journal ArticleDOI
NCEP–DOE AMIP-II Reanalysis (R-2)
Masao Kanamitsu,Wesley Ebisuzaki,John S. Woollen,Shi-Keng Yang,J. J. Hnilo,M. Fiorino,Gerald L. Potter +6 more
TL;DR: The NCEP-DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the "50-year" (1948-present) N CEP-NCAR Reanalysis Project.
Journal ArticleDOI
Spatial Autocorrelation: Trouble or New Paradigm?
TL;DR: The paper discusses first how autocorrelation in ecological variables can be described and measured, and ways are presented of explicitly introducing spatial structures into ecological models, and two approaches are proposed.
Journal ArticleDOI
North american regional reanalysis
Fedor Mesinger,Geoff DiMego,Eugenia Kalnay,Kenneth E. Mitchell,Perry Shafran,Wesley Ebisuzaki,Dusan Jovic,John S. Woollen,Eric Rogers,Ernesto Hugo Berbery,Michael Ek,Yun Fan,Robert Grumbine,Wayne Higgins,Hong Li,Ying Lin,Geoff Manikin,David F. Parrish,Wei Shi +18 more
TL;DR: The North American Regional Reanalysis (NARR) project as mentioned in this paper uses the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output) to capture regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.
Book
Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
TL;DR: In this paper, the basic GWR model is extended to include local statistics and local models for spatial data, and a software for Geographically Weighting Regression is described. But this software is not suitable for the analysis of large scale data.