Organization
University of Maryland, Baltimore County
First Author Publications
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Xu, X., et al. (2019), Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space, Atmos. Meas. Tech., 12, 3269-3288, doi:10.5194/amt-12-3269-2019.
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Xu, X., et al. (2018), A pilot study of shortwave spectral fingerprints of smoke aerosols above liquid clouds, J. Quant. Spectrosc. Radiat. Transfer, 221, 38-50, doi:10.1016/j.jqsrt.2018.09.024.
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Xu, X., and J. Wang (2015), Retrieval of aerosol microphysical properties from AERONET photopolarimetric measurements: 1. Information content analysis, J. Geophys. Res., 120, 7059-7078, doi:10.1002/2015JD023108.
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Xu, X., et al. (2013), Constraints on aerosol sources using GEOS-Chem adjoint and MODIS radiances, and evaluation with multisensor (OMI, MISR) data, J. Geophys. Res., 118, 6396-6413, doi:10.1002/jgrd.50515.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
Co-Authored Publications
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Lu, Z., et al. (2023), First Mapping of Monthly and Diurnal Climatology of Saharan Dust Layer Height Over the Atlantic Ocean From EPIC/DSCOVR in Deep Space, Geophys. Res. Lett., 50, e2022GL102552, doi:10.1029/2022GL102552.
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Li, C., et al. (2022), AAAS Journal of Remote Sensing Volume 2022, Article ID 9817134, 17 pages, Journal of Remote Sensing, 9817134, doi:10.34133/2022/9817134.
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Li, ., et al. (2022), Direct retrieval of NO2 vertical columns from UV-Vis (390-495 nm) spectral radiance using a neural network, Journal of Remote Sensing, ID, article, doi:10.34133/2022/9817134.
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Chen, X., et al. (2021), First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates, Remote Sensing of Environment, 265, 112674, doi:10.1016/j.rse.2021.112674.
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Chen, X., et al. (2021), Can multi-angular polarimetric measurements in the oxygen-A and B bands improve the retrieval of aerosol vertical distribution?, J. Quant. Spectrosc. Radiat. Transfer, 270, 107679, doi:10.1016/j.jqsrt.2021.107679.
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Lu, Z., et al. (2021), Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season, Front. Remote Sens., 2, 766628, doi:10.3389/frsen.2021.766628.
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Meng Zhou, M.Z.M.Z., et al. (2021), Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations, Remote Sensing of Environment, 267, 112717, doi:10.1016/j.rse.2021.112717.
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Wang, J., et al. (2020), Detecting nighttime fire combustion phase by hybrid application of visible T and infrared radiation from Suomi NPP VIIRS, Remote Sensing of Environment, 237, 111466, doi:10.1016/j.rse.2019.111466.
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Wang, Y., et al. (2020), Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data - Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631-6650, doi:10.5194/acp-20-6631-2020.
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Remer, L.A., et al. (2019), Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument, Ocean Color Instrument. Front. Earth Sci., 7, 152, doi:10.3389/feart.2019.00152.
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Wang, J., et al. (2017), Article MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water, www.mdpi.com/journal/remotesensing, 9, 595, doi:10.3390/rs9060595.
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Ding, S., et al. (2016), Polarimetric remote sensing in oxygen A and B bands: sensitivity study and information content analysis for vertical profile of aerosols, Atmos. Meas. Tech., 9, 2077-2092, doi:10.5194/amt-9-2077-2016.
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Hou, W., et al. (2016), An algorithm for hyperspectral remote sensing of aerosols: 1. Development of theoretical framework, J. Quant. Spectrosc. Radiat. Transfer, 178, 400-415, doi:10.1016/j.jqsrt.2016.01.019.
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Wang, J., et al. (2016), Potential application of VIIRS Day/Night Band for monitoring nighttime surface PM2.5 air quality from space, Atmos. Environ., 124, 55-63, doi:10.1016/j.atmosenv.2015.11.013.
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Wang, J., et al. (2016), A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts, Geophys. Res. Lett., 43, 9931-9938, doi:10.1002/2016GL070204.
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Wang, J., et al. (2014), A numerical testbed for remote sensing of aerosols, and its demonstration for evaluating retrieval synergy from a geostationary satellite constellation of GEO-CAPE and GOES-R, J. Quant. Spectrosc. Radiat. Transfer, 146, 510-528, doi:10.1016/j.jqsrt.2014.03.020.
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Meland, B.S., et al. (2013), Assessing remote polarimetric measurement sensitivities to aerosol emissions using the geos-chem adjoint model, Atmos. Meas. Tech., 6, 3441-3457, doi:10.5194/amt-6-3441-2013.
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Wang, J., et al. (2012), Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model, Geophys. Res. Lett., 39, L08802, doi:10.1029/2012GL051136.
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Wang, J., et al. (2010), Improved algorithm for MODIS satellite retrievals of aerosol optical thickness over land in dusty atmosphere: Implications for air quality monitoring in China, Remote Sensing of Environment, 114, 2575-2583, doi:10.1016/j.rse.2010.05.034.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
