Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships
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[1] Zhongmin Zhu,et al. A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth , 2016 .
[2] Alexei Lyapustin,et al. Spatial scales of pollution from variable resolution satellite imaging. , 2013, Environmental pollution.
[3] Zev Ross,et al. A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States. , 2013, Environmental science & technology.
[4] R. Koelemeijer,et al. Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe , 2006 .
[5] Xianfeng Zhang,et al. Evaluation of Different Machine Learning Approaches to Forecasting PM2.5 Mass Concentrations , 2019, Aerosol and Air Quality Research.
[6] P. Gupta,et al. Satellite Remote Sensing of Particulate Matter Air Quality: The Cloud-Cover Problem , 2010, Journal of the Air & Waste Management Association.
[7] Lorraine A. Remer,et al. Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions , 2018, Atmospheric Measurement Techniques.
[8] Chris C. Lim,et al. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter , 2018, Proceedings of the National Academy of Sciences.
[9] Jingfeng Huang,et al. A satellite-based geographically weighted regression model for regional PM2.5 estimation over the Pearl River Delta region in China , 2014 .
[10] Yiran Peng,et al. MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison , 2019, Atmospheric Environment.
[11] Lorraine A. Remer,et al. MODIS 3 km aerosol product: algorithm and global perspective , 2013 .
[12] J. Schwartz,et al. Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states. , 2012, Environmental science & technology.
[13] D. Jacob,et al. Mapping annual mean ground‐level PM2.5 concentrations using Multiangle Imaging Spectroradiometer aerosol optical thickness over the contiguous United States , 2004 .
[14] P. Gupta,et al. Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: Multiple regression approach , 2009 .
[15] M. G. Estes,et al. Estimating ground-level PM(2.5) concentrations in the southeastern U.S. using geographically weighted regression. , 2013, Environmental research.
[16] Armistead G Russell,et al. "What We Breathe Impacts Our Health: Improving Understanding of the Link between Air Pollution and Health". , 2016, Environmental science & technology.
[17] S. Christopher,et al. Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land? , 2009, Journal of the Air & Waste Management Association.
[18] Brandon Feenstra,et al. Performance evaluation of twelve low-cost PM2.5 sensors at an ambient air monitoring site , 2019, Atmospheric Environment.
[19] F. Lurmann,et al. Evaluation of the TEOM method for measurement of ambient particulate mass in urban areas. , 1997, Journal of the Air & Waste Management Association.
[20] Matthew L. Thomas,et al. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015 , 2017, The Lancet.
[21] Lina Balluz,et al. Ischemic Heart Disease and Ambient Air Pollution of Particulate Matter 2.5 in 51 Counties in the U.S. , 2007, Public health reports.
[22] P. Gupta,et al. Particulate Matter Air Quality Assessment using Integrated Surface, Satellite, and Meteorological Products , 2009 .
[23] M. Agrawal,et al. The effects of air pollution on urban ecosystems and agriculture , 2011 .
[24] J. Burrows,et al. A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations , 2019, International Journal of Remote Sensing.
[25] J. H. Belle,et al. Estimating PM2.5 Concentrations in the Conterminous United States Using the Random Forest Approach. , 2017, Environmental science & technology.
[26] Jun Wang,et al. Intercomparison between satellite‐derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies , 2003 .
[27] L. Remer,et al. The Collection 6 MODIS aerosol products over land and ocean , 2013 .
[28] Jun Ma,et al. Deep learning-based PM2.5 prediction considering the spatiotemporal correlations: A case study of Beijing, China. , 2020, The Science of the total environment.
[29] Yang Liu,et al. Estimating Regional Spatial and Temporal Variability of PM2.5 Concentrations Using Satellite Data, Meteorology, and Land Use Information , 2009, Environmental health perspectives.
[30] W. Collins,et al. Radiative Forcing of Climate: The Historical Evolution of the Radiative Forcing Concept, the Forcing Agents and their Quantification, and Applications , 2019, Meteorological Monographs.
[31] Richard T Burnett,et al. Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors. , 2019, Environmental science & technology.
[32] J. Schwartz,et al. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations , 2011 .
[33] Yang Liu,et al. Multi-Angle Imager for Aerosols , 2017, Public health reports.