Jun Wang

Organization

University of Iowa

Email

Contact person by email

Business Phone

Work

:

(319) 353-4483

Business Address

Chemical and Biochemical Engineering
4126 Seamans Center
Iowa City, IA 52242
United States

Website

ARROMA Group Website

First Author Publications

Wang, J., et al. (2024), published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided , Wang Et Al., 1, 15.
Wang, J., et al. (2022), Resolving and predicting neighborhood vulnerability to urban heat and air pollution: insights from a pilot project of community science, GeoHealth, J. Zeng., 6, e2021GH000575.
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.
Wang, J., et al. (2020), Development of a nighttime shortwave radiative transfer model for remote T sensing of nocturnal aerosols and fires from VIIRS, Remote Sensing of Environment, 241, 111727, doi:10.1016/j.rse.2020.111727.
Wang, J., and J. Wang (2020), Short communication Tropospheric SO2 and NO2 in 2012–2018: Contrasting views of two sensors (OMI and OMPS) from space, Atmos. Environ., 223, 117214, doi:10.1016/j.atmosenv.2019.117214.
Wang, J., et al. (2020), Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts, Atmos. Chem. Phys., 20, 6651-6670, doi:10.5194/acp-20-6651-2020.
Wang, J., et al. (2018), Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model Over the Northern sub-Saharan African Region, J. Geophys. Res., 123, 507-528.
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.
Wang, J., et al. (2016), A multi-sensor view of the 2012 Central Plains drought from space, Front. Environ. Sci., 4, 45, doi:10.3389/fenvs.2016.00045.
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.
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.
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.
Wang, J., et al. (2013), Modeling of 2008 Kasatochi volcanic sulfate direct radiative forcing: assimilation of OMI SO2 plume height data and comparison with MODIS and CALIOP observations, Atmos. Chem. Phys., 13, 1895-1912, doi:10.5194/acp-13-1895-2013.
Wang, J., et al. (2013), Mesoscale modeling of smoke transport over the Southeast Asian Maritime Continent: Interplay of sea breeze, trade wind, typhoon, and topography, Atmos. Res., 122, 486-503, doi:10.1016/j.atmosres.2012.05.009.
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.
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.
Wang, J., et al. (2009), A conceptual model for the link between Central American biomass burning aerosols and severe weather over the south central United States, Environ. Res. Lett., 4, 015003, doi:10.1088/1748-9326/4/1/015003.
Wang, J., et al. (2008), Sensitivity of sulfate direct climate forcing to the hysteresis of particle phase transitions, J. Geophys. Res., 113, D11207, doi:10.1029/2007JD009368.
Wang, J., et al. (2008), Global distribution of solid and aqueous sulfate aerosols: Effect of the hysteresis of particle phase transitions, J. Geophys. Res., 113, D11206, doi:10.1029/2007JD009367.
Wang, J., and S. Martin (2007), Satellite characterization of urban aerosols: Importance of including hygroscopicity and mixing state in the retrieval algorithms, J. Geophys. Res., 112, D17203, doi:10.1029/2006JD008078.
Wang, J., and S. Christopher (2006), Mesoscale modeling of Central American smoke transport to the United States: 2. Smoke radiative impact on regional surface energy budget and boundary layer evolution, J. Geophys. Res., 111, D14S92, doi:10.1029/2005JD006720.
Wang, J., et al. (2004), Diurnal variability of dust aerosol optical thickness and Angström exponent over dust source regions in China, Geophys. Res. Lett., 31, L08107, doi:10.1029/2004GL019580.
Wang, J., et al. (2004), GOES 8 aerosol optical thickness assimilation in a mesoscale model: Online integration of aerosol radiative effects, J. Geophys. Res., 109, D23203, doi:10.1029/2004JD004827.
Wang, J., et al. (2003), Geostationary satellite retrievals of aerosol optical thickness during ACE-Asia, J. Geophys. Res., 108, 8657, doi:10.1029/2003JD003580.
Wang, J., et al. (2003), GOES 8 retrieval of dust aerosol optical thickness over the Atlantic Ocean during PRIDE, J. Geophys. Res., 108, 8595, doi:10.1029/2002JD002494.
Wang, J., and S. Christopher (2003), Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies, Geophys. Res. Lett., 30, 2095, doi:10.1029/2003GL018174.
Wang, J., et al. (2003), The effects of non-sphericity on geostationary satellite retrievals of dust aerosols, Geophys. Res. Lett., 30, 2293, doi:10.1029/2003GL018697.

Note: Only publications that have been uploaded to the ESD Publications database are listed here.

Co-Authored Publications

Wang, Z., et al. (2024), Soil NOx Emission Prediction via Recurrent Neural Networks, Tech Science Press, doi:10.32604/cmc.2023.044366.
Wei, J., et al. (2024), Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study.
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.
Wei, J., et al. (2023), Ground-level gaseous pollutants (NO2 , SO2 , and CO) in China: daily seamless mapping and spatiotemporal variations, Atmos. Chem. Phys., doi:10.5194/acp-23-1511-2023.
Xiao, Q., et al. (2023), Full length article Artificial light at night and social vulnerability: An environmental justice analysis in the U.S. 2012–2019, Environment International, 178, 108096, doi:10.1016/j.envint.2023.108096.
Yorks, J., et al. (2023), A SmallSat concept to resolve diurnal and vertical variations of aerosols, clouds, and boundary layer height, Bull. Amer. Meteor. Soc., 104, E815-E836, doi:10.1175/BAMS-D-21-0179.1.
Zhou, M., et al. (2023), Enhancement of Nighttime Fire Detection and Combustion Efficiency Characterization Using Suomi-NPP and NOAA-20 VIIRS Instruments, IEEE Trans. Geosci. Remote Sens., 61, 4402420, doi:10.1109/TGRS.2023.3261664.
Chen, X., et al. (2022), Analytical Prediction of Scattering Properties of Spheroidal Dust Particles With Machine Learning, Geophys. Res. Lett., 49, e2021GL097548, doi:10.1029/2021GL097548.
Kaaret, P., et al. (2022), remote sensing Communication On the Potential of Flaming Hotspot Detection at Night via Multiband Visible/Near-Infrared Imaging, Remote Sens., 14, 5019, doi:10.3390/rs14195019.
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.
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.
Wei, J., et al. (2022), Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China, Remote Sensing of Environment, 270, 112775, doi:10.1016/j.rse.2021.112775.
Wei, J., et al. (2022), Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence, Environ. Sci. Technol., doi:10.1021/acs.est.2c03834.
Zhang, ., et al. (2022), Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction With Satellite Data for Rural Areas, J. Geophys. Res., 127, e2021JD035563, doi:10.1029/2021JD035563.
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.
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.
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.
Wang, Y., et al. (2021), Improved modelling of soil NOx emissions in a high temperature agricultural region: role of background emissions on NO2 trend over the US, Environmental Research Letter, 16, 084061, doi:10.1088/1748-9326/ac16a3.
Wang, ., et al. (2021), First Retrieval of AOD at Fine Resolution Over Shallow and Turbid Coastal Waters From MODIS, Geophys. Res. Lett., 48, e2021GL094344, doi:https://doi.org/10.1029/2021GL094344.
Wei, J., et al. (2021), Himawari-8-derived diurnal variations in ground-level PM2.5 pollution across China using the fast space-time Light Gradient Boosting Machine (LightGBM), Atmos. Chem. Phys., 21, 7863-7880, doi:10.5194/acp-21-7863-2021.
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.
Bi, L., et al. (2020), Preface, Electromagnetic and light scattering by nonspherical particles XVIII, J. Quant. Specrosc. Radiat. Transfer, 245, 106820, doi:10.1016/j.jqsrt.2019.106820.
Bi, L., et al. (2020), Preface, Electromagnetic and light scattering by nonspherical particles XVIII, J. Quant. Specrosc. Radiat. Transfer, 245, 106820, doi:10.1016/j.jqsrt.2019.106820.
Hou, W., et al. (2020), An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign, J. Quant. Spectrosc. Radiat. Transfer, 253, 107161, doi:10.1016/j.jqsrt.2020.107161.
Usmani, M., et al. (2020), This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modificatio, Usmani Et Al., 1, 9.
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.
Zhang, H., et al. (2020), Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 1. Bias Correction With Surface Observations in Nonrural Areas, J. Geophys. Res., 125, doi:10.1029/2019JD032293.
Christian, K.E., et al. (2019), Radiative Forcing and Stratospheric Warming of Pyrocumulonimbus Smoke Aerosols: First Modeling Results With Multisensor (EPIC, CALIPSO, and CATS) Views from Space, Geophys. Res. Lett., 46, 10,061-10,071, doi:10.1029/2019GL082360.
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.
Zhang, H., et al. (2019), Surface erythemal UV irradiance in the continental United States derived from ground-based and OMI observations: quality assessment, trend analysis and sampling issues, Atmos. Chem. Phys., 19, 2165-2181, doi:10.5194/acp-19-2165-2019.
Zhou, Y., et al. (2019), Compilation and spatio-temporal analysis of publicly available total solar and UV irradiance data in the contiguous United States*, Environmental Pollution, 253, 130-140, doi:10.1016/j.envpol.2019.06.074.
Ge, C., et al. (2018), A molecular perspective for global modeling of upper atmospheric NH3 from freezing clouds, Proc. Natl. Acad. Sci., 115, 6147-6152, doi:10.1073/pnas.1719949115.
Iguchi, T., et al. (2018), NU-WRF Aerosol Transport Simulation over West Africa: Effects of Biomass Burning on Smoke Aerosol Distribution, J. Appl. Meteor. Climat., 57, 1551-1573, doi:10.1175/JAMC-D-17-0278.1.
Jovanovic, D.J.D.V., et al. (2018), Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA, Terms of Use, 12, 042603, doi:10.1117/1.JRS.12.042603.
Lennartson, E.M., et al. (2018), Diurnal variation of aerosol optical depth and PM2.5 in South Korea: a synthesis from AERONET, satellite (GOCI), KORUS-AQ observation, and the WRF-Chem model, Atmos. Chem. Phys., 18, 15125-15144, doi:10.5194/acp-18-15125-2018.
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.
Aegerter, C., et al. (2017), Mesoscale Modeling of the Meteorological Impacts of Irrigation during the 2012 Central Plains Drought, J. Appl. Meteor. Climat., 56, 1259-1283, doi:10.1175/JAMC-D-16-0292.1.
Breider, T.J., et al. (2017), Multidecadal trends in aerosol radiative forcing over the Arctic: Contribution of changes in anthropogenic aerosol to Arctic warming since 1980, J. Geophys. Res., 122, 3573-3594, doi:10.1002/2016JD025321.
Chen, X., et al. (2017), Angular dependence of aerosol information content in CAPI/TanSat observation over land: Effect of polarization and synergy with A-train satellites, Remote Sensing of Environment, 196, 163-177, doi:10.1016/j.rse.2017.05.007.
Ge, C., et al. (2017), Mesoscale modeling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: First comparison of ensemble analysis with in situ observations, J. Geophys. Res., 122, 5380-5398, doi:10.1002/2016JD026241.
Hou, W., et al. (2017), An algorithm for hyperspectral remote sensing of aerosols: 2. Information content analysis for aerosol parameters and principal components of surface spectra, J. Quant. Spectrosc. Radiat. Transfer, 192, 14-29, doi:10.1016/j.jqsrt.2017.01.041.
Polivka, T.N., et al. (2017), Improving Nocturnal Fire Detection with the VIIRS Day-Night Band, Blank 1.
Qu, Z., et al. (2017), Monthly top-down NOx emissions for China (2005–2012): A hybrid inversion method and trend analysis, J. Geophys. Res., 122, 4600-4625, doi:10.1002/2016JD025852.
Sharma, A., et al. (2017), atmosphere Article Intercomparison of MODIS and VIIRS Fire Products in Khanty-Mansiysk Russia: Implications for Characterizing Gas Flaring from Space, www.mdpi.com/journal/atmosphere, 8, 95, doi:10.3390/atmos8060095.
Shiflett, S.A., et al. (2017), Variation in the urban vegetation, surface temperature, air temperature nexus, Science of the Total Environment, 579, 495-505, doi:10.1016/j.scitotenv.2016.11.069.
Zoogman, P., et al. (2017), Tropospheric emissions: Monitoring of pollution (TEMPO), J. Quant. Spectrosc. Radiat. Transfer, 186, 17-39, doi:10.1016/j.jqsrt.2016.05.008.
Calkins, C., et al. (2016), Effects of meteorological conditions on sulfur dioxide air pollution in the North China plain during winters of 2006e2015, Atmos. Environ., 147, 296-309, doi:10.1016/j.atmosenv.2016.10.005.
Campbell, J.R., et al. (2016), Applying Advanced Ground-Based Remote Sensing in the Southeast Asian Maritime Continent to Characterize Regional Proficiencies in Smoke Transport Modeling, J. Appl. Meteor. Climat., 55, 3-22, doi:10.1175/JAMC-D-15-0083.1.
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.
Ge, C., et al. (2016), Satellite-based global volcanic SO2 emissions and sulfate direct radiative forcing during 2005–2012, J. Geophys. Res., 121, 3446-3464, doi:10.1002/2015JD023134.
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.
Ichoku, C., et al. (2016), and the hydrological cycle in Northern sub-Saharan Africa, Environmental Research Letter, 11, 095005, doi:10.1088/1748-9326/11/9/09500.
Ichoku, C., et al. (2016), Biomass burning, land-cover change, and the hydrological cycle in Northern sub-Saharan Africa, Environmental Research Letters, 11, 095005, doi:10.1088/1748-9326/11/9/095005.
Polivka, T.N., et al. (2016), Improving Nocturnal Fire Detection with the VIIRS Day-Night Band, IEEE Transactions on Geoscience &amp, Remote Sensing, 9, 5503-5519.
Polivka, T.N., et al. (2016), Improving Nocturnal Fire Detection with the VIIRS Day-Night Band, IEEE Transactions on Geoscience &amp, Remote Sensing, 9, 5503-5519.
Qu, W., et al. (2016), Opposite seasonality of the aerosol optical depth and the surface particulate matter concentration over the north China Plain, Atmos. Environ., 127, 90-99, doi:10.1016/j.atmosenv.2015.11.061.
Oikawa, ., et al. (2015), Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region, Nature Communications, 6, 8753, doi:10.1038/ncomms9753.
Qu, W.J., et al. (2015), Influence of relative humidity on aerosol composition: Impacts on light extinction and visibility impairment at two sites in coastal area of China, Atmos. Res., 153, 500-511, doi:10.1016/j.atmosres.2014.10.009.
Qu, W., et al. (2015), Effect of cold wave on winter visibility over eastern China, J. Geophys. Res., 120, 2394-2406, doi:10.1002/2014JD021958.
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.
Ge, C., et al. (2014), Mesoscale modeling of smoke transport over the Southeast Asian Maritime Continent: coupling of smoke direct radiative effect below and above the low-level clouds, Atmos. Chem. Phys., 14, 159-174, doi:10.5194/acp-14-159-2014.
Peterson, D.A., et al. (2014), Quantifying the potential for high-altitude smoke injection in the North American boreal forest using the standard MODIS fire products and subpixel-based methods, J. Geophys. Res., 119, 3401-3419, doi:10.1002/2013JD021067.
Peterson, D.A., et al. (2014), Quantifying the potential for high-altitude smoke injection in the North American boreal forest using the standard MODIS fire products and subpixel-based methods, J. Geophys. Res., 119, 3401-3419, doi:10.1002/2013JD021067.
Yang, K., et al. (2014), Advancing measurements of tropospheric NO2 from space: New algorithm and first global results from OMPS, Geophys. Res. Lett., 41, 4777-4786, doi:10.1002/2014GL060136.
Zhang, F., et al. (2014), Sensitivity of mesoscale modeling of smoke direct radiative effect to the emission inventory: A case study in northern sub-Saharan African region, Environmental Research Letter, 9, 075002, doi:10.1088/1748-9326/9/7/075002.
Anderson, J.C., et al. (2013), Long-term statistical assessment of Aqua-MODIS aerosol optical depth over coastal regions: bias characteristics and uncertainty sources, Tellus, 65, 20805.
Kessner, A.L., et al. (2013), Remote sensing of surface visibility from space: A look at the United States East Coast, Atmos. Environ., 81, 136-147, doi:10.1016/j.atmosenv.2013.08.050.
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.
Peterson, D.A., and J. Wang (2013), A Sub-pixel-based calculate of fire radiative power from MODIS observations: 2. Sensitivity analysis and potential fire weather application, Remote Sensing Environment, 129, 231-249, doi:10.1016/j.rse.2012.10.020.
Peterson, D.A., et al. (2013), Short communication A short-term predictor of satellite-observed fire activity in the North American boreal forest: Toward improving the prediction of smoke emissions, Atmos. Environ., 71, 304-310, doi:10.1016/j.atmosenv.2013.01.052.
Peterson, D.A., et al. (2013), A sub-pixel-based calculation of fire radiative power from MODIS observations: 1 Algorithm development and initial assessment, Remote Sensing of Environment, 129, 262-279, doi:10.1016/j.rse.2012.10.036.
Reid, J.S., et al. (2013), Observing and understanding the Southeast Asian aerosol system by remote sensing: An initial review and analysis for the Seven Southeast Asian Studies (7SEAS) program, Atmos. Res., 122, 403-468, doi:10.1016/j.atmosres.2012.06.005.
Shahzad, M.I., et al. (2013), Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products, Journal of the Air & Waste Management Association, 63, 1098-1110, doi:10.1080/10962247.2013.801372.
van Donkelaar, ., et al. (2013), Optimal estimation for global ground-level fine particulate matter concentrations, J. Geophys. Res., 118, 5621-5636, doi:10.1002/jgrd.50479.
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.
Yang, K., et al. (2013), First observations of SO2 from the satellite Suomi NPP OMPS: Widespread air pollution events over China, Geophys. Res. Lett., 40, 1-6, doi:10.1002/grl.50952.
Yang, Z., et al. (2013), Mesoscale modeling and satellite observation of transport and mixing of smoke and dust particles over northern sub-Saharan African region, J. Geophys. Res., 118, 12139-12157, doi:10.1002/2013JD020644.
Holt, E., and J. Wang (2012), Trends in Wind Speed at Wind Turbine Height of 80 m over the Contiguous United States Using the North American Regional Reanalysis (NARR), J. Appl. Meteor. Climat., 51, 2188-2202, doi:10.1175/JAMC-D-11-0205.1.
Hyer, E.J., et al. (2012), Biomass Burning Observations, Modeling, and Data Assimilation, Bull. Am. Meteorol. Soc., ES10, doi:10.1175/BAMS-D-11-00064.1.
Spurr, R., et al. (2012), Linearized T-matrix and Mie scattering computations, J. Quant. Spectrosc. Radiat. Transfer, 113, 425-439, doi:10.1016/j.jqsrt.2011.11.014.
Gatebe, C.K., et al. (2011), Effects of ship wakes on ocean brightness and radiative forcing over ocean, Geophys. Res. Lett., 38, L17702, doi:10.1029/2011GL048819.
Kopacz, ., et al. (2011), Origin and radiative forcing of black carbon transported to the Himalayas and Tibetan Plateau, Atmos. Chem. Phys., 11, 2837-2852, doi:10.5194/acp-11-2837-2011.
Veefkind, P., et al. (2011), Global satellite analysis of the relation between aerosols and short-lived trace gases, Atmos. Chem. Phys., 11, 1255-1267, doi:10.5194/acp-11-1255-2011.
Bhattacharjee, ., et al. (2010), Importance of including ammonium sulfate ((NH4)2SO4) aerosols for ice cloud parameterization in GCMs, Ann. Geophys., 28, 621-631.
Drury, E., et al. (2010), Synthesis of satellite (MODIS), aircraft (ICARTT), and surface (IMPROVE, EPA‐AQS, AERONET) aerosol observations over eastern North America to improve MODIS aerosol retrievals and constrain surface aerosol concentrations and sources, J. Geophys. Res., 115, D14204, doi:10.1029/2009JD012629.
Peterson, D., et al. (2010), Effects of lightning and other meteorological factors on fire activity in the North American boreal forest: implications for fire weather forecasting, Atmos. Chem. Phys., 10, 6873-6888, doi:10.5194/acp-10-6873-2010.
Reid, J.S., et al. (2009), Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program, Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 2, 144-162, doi:10.1109/JSTARS.2009.2027443.
Boersma, K.F., et al. (2008), Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space, J. Geophys. Res., 113, D16S26, doi:10.1029/2007JD008816.
Drury, E., et al. (2008), Improved algorithm for MODIS satellite retrievals of aerosol optical depths over western North America, J. Geophys. Res., 113, D16204, doi:10.1029/2007JD009573.
Zeng, J., et al. (2008), High-spectral resolution simulation of polarization of skylight: Sensitivity to aerosol vertical profile, Geophys. Res. Lett., 35, L20801, doi:10.1029/2008GL035645.
Christopher, S., and J. Wang (2004), Intercomparison between multi-angle imaging spectroradiometer (MISR) and sunphotometer aerosol optical thickness in dust source regions over China: implications for satellite aerosol retrievals and radiative forcing calculations, Tellus, 56B, 451-456.
Christopher, S., et al. (2003), Estimation of diurnal shortwave dust aerosol radiative forcing during PRIDE, J. Geophys. Res., 108, 8596, doi:10.1029/2002JD002787.

Note: Only publications that have been uploaded to the ESD Publications database are listed here.