Gaussian Markov random fields improve ensemble predictions of daily 1 km PM2.5 and PM10 across France

Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification

(2021) Qiang Pu et al.   ENVIRONMENTAL POLLUTION

A Random Forest Approach to Estimate Daily Particulate Matter, Nitrogen Dioxide, and Ozone at Fine Spatial Resolution in Sweden

(2020) Massimo Stafoggia et al.   Atmosphere

A multi-resolution air temperature model for France from MODIS and Landsat thermal data

(2020) Ian Hough et al.   ENVIRONMENTAL RESEARCH

The ERA5 Global Reanalysis

(2020) Hans Hersbach et al.   QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY

Changes in spatial patterns of PM2.5 pollution in China 2000–2018: Impact of clean air policies

(2020) Qingyang Xiao et al.   ENVIRONMENT INTERNATIONAL

Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM2.5) using satellite data over large regions

(2020) Allan C. Just et al.   ATMOSPHERIC ENVIRONMENT

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

(2020) Christopher J L Murray et al.   LANCET

The varying driving forces of PM2.5 concentrations in Chinese cities: Insights from a geographically and temporally weighted regression model

(2020) Qianqian Liu et al.   ENVIRONMENT INTERNATIONAL

A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM2.5 Concentrations across Great Britain

(2020) Rochelle Schneider et al.   Remote Sensing

Spatiotemporal assessment of PM2.5 concentrations and exposure in China from 2013 to 2017 using satellite-derived data

(2020) Qingqing He et al.   JOURNAL OF CLEANER PRODUCTION

Estimating PM2.5 concentrations in Northeastern China with full spatiotemporal coverage, 2005–2016

(2020) Xia Meng et al.   REMOTE SENSING OF ENVIRONMENT

Estimation of daily PM10 and PM2.5 concentrations in Italy, 2013–2015, using a spatiotemporal land-use random-forest model

(2019) Massimo Stafoggia et al.   ENVIRONMENT INTERNATIONAL

Gaussian Markov Random Fields versus Linear Mixed Models for satellite-based PM2.5 assessment: Evidence from the Northeastern USA

(2019) Ron Sarafian et al.   ATMOSPHERIC ENVIRONMENT

Air pollution modeling and exposure assessment during pregnancy in the French Longitudinal Study of Children (ELFE)

(2019) Emmanuel Riviere et al.   ATMOSPHERIC ENVIRONMENT

A Bayesian ensemble approach to combine PM2.5 estimates from statistical models using satellite imagery and numerical model simulation

(2019) Nancy L. Murray et al.   ENVIRONMENTAL RESEARCH

A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

(2019) Jie Chen et al.   ENVIRONMENT INTERNATIONAL

An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution

(2019) Qian Di et al.   ENVIRONMENT INTERNATIONAL

Estimating PM2.5 concentration of the conterminous United States via interpretable convolutional neural networks

(2019) Yongbee Park et al.   ENVIRONMENTAL POLLUTION

Estimating Daily PM2.5 and PM10 over Italy Using an Ensemble Model

(2019) Alexandra Shtein et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Modelling daily PM 2.5 concentrations at high spatio-temporal resolution across Switzerland

(2018) Kees de Hoogh et al.   ENVIRONMENTAL POLLUTION

Constructing Priors that Penalize the Complexity of Gaussian Random Fields

(2018) Geir-Arne Fuglstad et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Satellite-based mapping of daily high-resolution ground PM 2.5 in China via space-time regression modeling

(2018) Qingqing He et al.   REMOTE SENSING OF ENVIRONMENT

MAIAC-based long-term spatiotemporal trends of PM 2.5 in Beijing, China

(2018) Fengchao Liang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Development of a stacked ensemble model for forecasting and analyzing daily average PM 2.5 concentrations in Beijing, China

(2018) Binxu Zhai et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Estimating daily and intra-daily PM10 and PM2.5 in Israel using a spatio-temporal hybrid modeling approach

(2018) Alexandra Shtein et al.   ATMOSPHERIC ENVIRONMENT

National scale spatiotemporal land-use regression model for PM2.5, PM10 and NO2 concentration in China

(2018) Zhenyu Zhang et al.   ATMOSPHERIC ENVIRONMENT

Bayesian geostatistical modelling of PM10 and PM2.5 surface level concentrations in Europe using high-resolution satellite-derived products

(2018) Anton Beloconi et al.   ENVIRONMENT INTERNATIONAL

Estimation of daily PM10 concentrations in Italy (2006–2012) using finely resolved satellite data, land use variables and meteorology

(2017) Massimo Stafoggia et al.   ENVIRONMENT INTERNATIONAL

The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation

(2017) C. A. Randles et al.   JOURNAL OF CLIMATE

ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R

(2017) Marvin N. Wright et al.   Journal of Statistical Software

Estimating ground-level PM 2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model

(2017) Yuanxi Guo et al.   REMOTE SENSING OF ENVIRONMENT

Full-coverage high-resolution daily PM 2.5 estimation using MAIAC AOD in the Yangtze River Delta of China

(2017) Qingyang Xiao et al.   REMOTE SENSING OF ENVIRONMENT

Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors

(2017) Daniel Simpson et al.   STATISTICAL SCIENCE

Estimating ground-level PM 2.5 concentrations over three megalopolises in China using satellite-derived aerosol optical depth measurements

(2016) Yixuan Zheng et al.   ATMOSPHERIC ENVIRONMENT

Assessing PM2.5 Exposures with High Spatiotemporal Resolution across the Continental United States

(2016) Qian Di et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

(2016) Aaron van Donkelaar et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Estimating urban PM 10 and PM 2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data

(2016) Anton Beloconi et al.   REMOTE SENSING OF ENVIRONMENT

Estimating daily PM 2.5 and PM 10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data

(2015) Itai Kloog et al.   ATMOSPHERIC ENVIRONMENT

Daily Estimation of Ground-Level PM2.5 Concentrations over Beijing Using 3 km Resolution MODIS AOD

(2015) Yuanyu Xie et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City

(2015) Allan C. Just et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Spatiotemporal prediction of fine particulate matter using high-resolution satellite images in the Southeastern US 2003–2011

(2015) Mihye Lee et al.   Journal of Exposure Science and Environmental Epidemiology

Fitting Linear Mixed-Effects Models Usinglme4

(2015) Douglas Bates et al.   Journal of Statistical Software

A new hybrid spatio-temporal model for estimating daily multi-year PM2.5 concentrations across northeastern USA using high resolution aerosol optical depth data

(2014) Itai Kloog et al.   ATMOSPHERIC ENVIRONMENT

Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals

(2014) Alexandra A. Chudnovsky et al.   ATMOSPHERIC ENVIRONMENT

Estimating Ground-Level PM2.5 in China Using Satellite Remote Sensing

(2014) Zongwei Ma et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

A satellite-based geographically weighted regression model for regional PM2.5 estimation over the Pearl River Delta region in China

(2014) Weize Song et al.   REMOTE SENSING OF ENVIRONMENT

Estimating spatio-temporal resolved PM10 aerosol mass concentrations using MODIS satellite data and land use regression over Lombardy, Italy

(2013) Francesco Nordio et al.   ATMOSPHERIC ENVIRONMENT

Estimating ground-level PM2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model

(2013) Xuefei Hu et al.   REMOTE SENSING OF ENVIRONMENT

Spatio-temporal modeling of particulate matter concentration through the SPDE approach

(2012) Michela Cameletti et al.   AStA-Advances in Statistical Analysis

Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects

(2012) Yang Zhang et al.   ATMOSPHERIC ENVIRONMENT

Real-time air quality forecasting, part I: History, techniques, and current status

(2012) Yang Zhang et al.   ATMOSPHERIC ENVIRONMENT

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

(2012) Xuefei Hu et al.   ENVIRONMENTAL RESEARCH

Prediction of daily fine particulate matter concentrations using aerosol optical depth retrievals from the Geostationary Operational Environmental Satellite (GOES)

(2012) Alexandra A. Chudnovsky et al.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION

Assessing temporally and spatially resolved PM2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

(2011) Itai Kloog et al.   ATMOSPHERIC ENVIRONMENT

An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach

(2011) Finn Lindgren et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

(2009) Håvard Rue et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY