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Daniel Q. Tong  - - - 
Top co-authors See all
Li Pan

515 shared publications

Menghua Wang

99 shared publications

NOAA National Environmental Satellite, Data, and Information Services

Joshua S. Fu

66 shared publications

Youhua Tang

43 shared publications

Xinyi Dong

39 shared publications

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Distribution of Articles published per year 
(1997 - 2018)
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9
 
Publications See all
Article 1 Read 0 Citations Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Devel... Chao Gao, Xuelei Zhang, Wenyong Wang, Aijun Xiu, Daniel Tong... Published: 22 February 2018
Atmosphere, doi: 10.3390/atmos9020078
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Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100~670 m, but exponentially decreased between the heights of 670~1800 m. Both the correlation and the variation tendency of simulated PBLH from the Weather Research and Forecasting (WRF) model & Shin-Hong (SHIN)/California Meteorological (CALMET) model (WRF_SHIN/CALMET) were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated the Planetary Boundary Layer Height (PBLH) could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively.
Article 1 Read 0 Citations 3D-Var versus Optimal Interpolation for Aerosol Assimilation: a Case Study over the Contiguous United States Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius L... Published: 11 July 2017
Geoscientific Model Development Discussions, doi: 10.5194/gmd-2017-147
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2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. GSI results are compared with those obtained using the optimal interpolation (OI) method (Tang et al., 2015) for July, 2011 over CONUS. Both GSI and OI assimilate surface PM2.5 observations at 00, 06, 12, and 18 UTC, and MODIS AOD at 18 UTC. In the GSI experiments, assimilation of surface PM2.5 leads to stronger increments in surface PM2.5 compared to the MODIS AOD assimilation. In contrast, we find a stronger impact of MODIS AOD on surface aerosols at 18 UTC compared to the surface PM2.5 OI assimilation. The increments resulting from the OI assimilation are spread in 11×11 horizontal grid cells (12 km horizontal resolution) while the spatial distribution of GSI increments is controlled by its background error covariances, and the horizontal/vertical length scales. The assimilations of observations using both GSI and OI generally help reduce the prediction biases, and improve correlation between model predictions and observations. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). In this study, OI uses the relatively big model uncertainties, which helps yield better mean biases, but sometimes causes the RMSE increase. We also examine and discuss the sensitivity of the assimilation experiments results to the AOD forward operators]]>
Article 1 Read 0 Citations Impact of the 2008 Global Recession on air quality over the United States: Implications for surface ozone levels from ch... Daniel Tong, Li Pan, Weiwei Chen, Lok Lamsal, Pius Lee, Youh... Published: 05 September 2016
Geophysical Research Letters, doi: 10.1002/2016gl069885
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Satellite and ground observations detected large variability in nitrogen oxides (NOx) during the 2008 economic recession, but the impact of the recession on air quality has not been quantified. This study combines observed NOx trends and a regional chemical transport model to quantify the impact of the recession on surface ozone (O3) levels over the continental United States. The impact is quantified by simulating O3 concentrations under two emission scenarios: business-as-usual (BAU) and recession. In the BAU case, the emission projection from the Cross-State Air Pollution Rule (CSAPR) is used to estimate the “would-be” NOx emission level in 2011. In the recession case, the actual NO2 trends observed from Air Quality System (AQS) ground monitors and the Ozone Monitoring Instrument (OMI) on the Aura satellite are used to obtain “realistic” changes in NOx emissions. The model prediction with the recession effect agrees better with ground O3 observations over time and space than the prediction with the BAU emission. The results show that the recession caused a 1-2 ppbv decrease in surface O3 concentration over the eastern United States, a slight increase (0.5-1 ppbv) over the Rocky Mountain region, and mixed changes in the Pacific West. The gain in air quality benefits during the recession, however, could be quickly offset by the much slower emission reduction rate during the post-recession period.
Conference 1 Read 0 Citations Impact of Wildfires on Atmospheric Ammonia Concentrations in the US: Coupling Satellite and Ground Based Measurements Casey Bray, William Battye, Viney Aneja, Daniel Tong, Pius L... Published: 15 July 2016
The 1st International Electronic Conference on Atmospheric Sciences, doi: 10.3390/ecas2016-b001
DOI See at publisher website
Article 2 Reads 7 Citations Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling syst... Xinyi Dong, Joshua S. Fu, Kan Huang, Daniel Tong, Guoshun Zh... Published: 06 July 2016
Atmospheric Chemistry and Physics, doi: 10.5194/acp-16-8157-2016
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The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from −55.42 and −31.97% by the original CMAQ to −16.05 and −22.1% by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42−), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3−). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50%. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.
Article 0 Reads 1 Citation Reconstructing Fire Records from Ground-Based Routine Aerosol Monitoring Hongmei Zhao, Daniel Q. Tong, Pius Lee, Hyuncheol Kim, Hang ... Published: 14 March 2016
Atmosphere, doi: 10.3390/atmos7030043
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Long-term fire records are important to understanding the trend of biomass burning and its interactions with air quality and climate at regional and global scales. Traditionally, such data have been compiled from ground surveys or satellite remote sensing. To obtain aerosol information during a fire event to use in analyzing air quality, we propose a new method of developing a long-term fire record for the contiguous United States using an unconventional data source: ground-based aerosol monitoring. Assisted by satellite fire detection, the mass concentration, size distribution, and chemical composition data of surface aerosols collected from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are examined to identify distinct aerosol characteristics during satellite-detected fire and non-fire periods. During a fire episode, elevated aerosol concentrations and heavy smoke are usually recorded by ground monitors and satellite sensors. Based on the unique physical and chemical characteristics of fire-dominated aerosols reported in the literature, we analyzed the surface aerosol observations from the IMPROVE network during satellite-detected fire events to establish a set of indicators to identify fire events from routine aerosol monitoring data. Five fire identification criteria were chosen: (1) high concentrations of PM2.5 and PM10 (particles smaller than 2.5 and 10 in diameters, respectively); (2) a high PM2.5/PM10 ratio; (3) high organic carbon (OC/PM2.5) and elemental carbon (EC/PM2.5) ratios; (4) a high potassium (K/PM2.5) ratio; and (5) a low soil/PM2.5 ratio. Using these criteria, we are able to identify a number of fire episodes close to 15 IMPROVE monitors from 2001 to 2011. Most of these monitors are located in the Western and Central United States. In any given year within the study period fire events often occurred between April and September, especially in the two months of April and September. This ground-based fire climatology is also consistent with that derived from satellite retrievals. This study demonstrates that it is feasible to reconstruct historic records of fire events based on continuous ground aerosol monitoring. This dataset can provide not only fire activity information but also fire-induced aerosol surface concentrations and chemical composition that can be used to verify satellite-based products and evaluate air quality and climate modeling results. However, caution needs to be exercised because these indicators are based on a limited number of fire events, and the proposed methodology should be further tested and confirmed in future research.