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Journal ArticleDOI

Estimating ground-level PM2.5 concentrations in the southeastern U.S. using geographically weighted regression

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.

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Citations
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Journal ArticleDOI

Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria.

TL;DR: In this paper, the authors investigated whether significant changes in air quality in Nigeria occurred primarily due to statewide COVID-19 lockdown, and they applied a neural network approach to derive monthly average ground-level fine aerosol optical depth (AODf) across Nigeria from year 2001-2020, using the Multi-angle Implementation of Atmospheric Correction (MAIAC) AODs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellites, AERONET aerosol optic properties, meteorological and spatial parameters.
Proceedings ArticleDOI

Extending Urban Air Quality Maps Beyond the Coverage of a Mobile Sensor Network: Data Sources, Methods, and Performance Evaluation

TL;DR: This work proposes two novel approaches for estimating the targeted pollutant level at desired time-location pairs, extending also to areas of the city that are beyond the coverage of the mobile sensor network.
Posted Content

Combining Satellite Imagery and Numerical Model Simulation to Estimate Ambient Air Pollution: An Ensemble Averaging Approach

TL;DR: In this paper, the authors developed a method to combine estimates for PM$2.5$ using satellite-retrieved aerosol optical depth (AOD) and simulations from the Community Multiscale Air Quality (CMAQ) modeling system.
Journal ArticleDOI

The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing-Tianjin-Hebei Region and Surrounding Areas.

TL;DR: The study investigated the spatiotemporal evolution of PM2.5 concentration in the Beijing–Tianjin–Hebei region and surrounding areas during 2015–2017, and then analyzed its socioeconomic determinants to improve the robustness of the model estimation.
Journal ArticleDOI

Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

TL;DR: In this paper, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site.
References
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Journal ArticleDOI

Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution

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)

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?

Pierre Legendre
- 01 Sep 1993 - 
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

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.
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