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Dive into the research topics where Charles Smeltzer is active.

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Featured researches published by Charles Smeltzer.


Environmental Science & Technology | 2013

Reduction in NO x Emission Trends over China: Regional and Seasonal Variations

Dasa Gu; Yuhang Wang; Charles Smeltzer; Zhen Liu

We analyzed satellite observations of nitrogen dioxide (NO2) columns by the Ozone Monitoring Instrument (OMI) over China from 2005 to 2010 in order to estimate the top-down anthropogenic nitrogen oxides (NOx) emission trends. Since NOx emissions were affected by the economic slowdown in 2009, we removed one year of abnormal data in the analysis. The estimated average emission trend is 4.01 ± 1.39% yr(-1), which is slower than the trend of 5.8-10.8% yr(-1) reported for previous years. We find large regional, seasonal, and urban-rural variations in emission trends. The average NOx emission trend of 3.47 ± 1.07% yr(-1) in warm season (June-September) is less than the trend of 5.03 ± 1.92% yr(-1) in cool season (October-May). The regional annual emission trends decrease from 4.76 ± 1.61% yr(-1) in North China Plain to 3.11 ± 0.98% yr(-1) in Yangtze River Delta and further down to -4.39 ± 1.81% yr(-1) in Pearl River Delta. The annual emission trends of the four largest megacities, Shanghai, Beijing, Guangzhou, and Shenzhen are -0.76 ± 0.29%, 0.69 ± 0.27%, -4.46 ± 1.22%, and -7.18 ± 2.88% yr(-1), considerably lower than the regional averages or surrounding rural regions. These results appear to suggest that a number of factors, including emission control measures of thermal power plants, increased hydro-power usage, vehicle emission regulations, and closure or migration of high-emission industries, have significantly reduced or even reversed the increasing trend of NOx emissions in more economically developed megacities and southern coastal regions, but their effects are not as significant in other major cities or less economically developed regions.


Science of The Total Environment | 2012

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Mark A. Engle; Lawrence F. Radke; Edward L. Heffern; Jennifer M.K. O'Keefe; James C. Hower; Charles Smeltzer; Judith M. Hower; Ricardo A. Olea; Robert J. Eatwell; D. R. Blake; Stephen D. Emsbo-Mattingly; Scott A. Stout; Gerald Queen; Kerry L. Aggen; Allan Kolker; Anupma Prakash; Kevin R. Henke; Glenn B. Stracher; Paul A. Schroeder; Yomayra Román-Colón; Arnout ter Schure

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires.


Journal of Geophysical Research | 2014

Anthropogenic emissions of NOx over China: Reconciling the difference of inverse modeling results using GOME-2 and OMI measurements

Dasa Gu; Yuhang Wang; Charles Smeltzer; K. Folkert Boersma

Inverse modeling using satellite observations of nitrogen dioxide (NO2) columns has been extensively used to estimate nitrogen oxides (NOx) emissions in China. Recently, the Global Ozone Monitoring Experiment-2 (GOME-2) and Ozone Monitoring Instrument (OMI) provide independent global NO2 column measurements on a nearly daily basis at around 9:30 and 13:30 local time across the equator, respectively. Anthropogenic NOx emission estimates by applying previously developed monthly inversion (MI) or daily inversion (DI) methods to these two sets of measurements show substantial differences. We improve the DI method by conducting model simulation, satellite retrieval, and inverse modeling sequentially on a daily basis. After each inversion, we update anthropogenic NOx emissions in the model simulation with the newly obtained a posteriori results. Consequently, the inversion-optimized emissions are used to compute the a priori NO2 profiles for satellite retrievals. As such, the a priori profiles used in satellite retrievals are now coupled to inverse modeling results. The improved procedure was applied to GOME-2 and OMI NO2 measurements in 2011. The new daily retrieval-inversion (DRI) method estimates an average NOx emission of 6.9 Tg N/yr over China, and the difference between using GOME-2 and OMI measurements is 0.4 Tg N/yr, which is significantly smaller than the difference of 1.3 Tg N/yr using the previous DI method. Using the more consistent DRI inversion results, we find that anthropogenic NOx emissions tend to be higher in winter and summer than spring (and possibly fall) and the weekday-to-weekend emission ratio tends to increase with NOx emission in China.


Journal of Geophysical Research | 2016

Large vertical gradient of reactive nitrogen oxides in the boundary layer: Modeling analysis of DISCOVER-AQ 2011 observations

Yuzhong Zhang; Yuhang Wang; G. Chen; Charles Smeltzer; J. H. Crawford; J. R. Olson; James J. Szykman; Andrew J. Weinheimer; D. J. Knapp; D. D. Montzka; Armin Wisthaler; Tomas Mikoviny; Alan Fried; Glenn S. Diskin

An often used assumption in air pollution studies is a well-mixed boundary layer (BL), where pollutants are evenly distributed. Because of the difficulty in obtaining vertically resolved measurements, the validity of the assumption has not been thoroughly evaluated. In this study, we usemore than 200 vertical profiles observed in the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) aircraft campaign in July 2011 to examine the vertical distributions of pollutants over the Washington-Baltimore area. While many long-lived species are well mixed in daytime, the observed average vertical profile of NOx shows a large negative gradient with increasing altitude in the BL. Our analysis suggests that the magnitude of the NOx gradient is highly sensitive to atmospheric stability. We investigate how parameterizations of the BL and land-surface processes impact vertical profiles in a 1-D chemical transport model, using three BL schemes (Asymmetric Convective Model version 2 (ACM2), Yonsei University (YSU), and Mellor-Yamada-Janjic (MYJ)) and two land-surface schemes (Noah and Rapid Update Cycle (RUC)). The model reasonably reproduces the median vertical profiles of NOx under different BL stability conditions within 30% of observations, classified based on potential temperature gradient and BL height. Comparisons with NOx observations for individual vertical profiles reveal that while YSU performs better in the turbulent and deep BL case, in general, ACM2 (RMSE=2.0ppbv) outperforms YSU (RMSE=2.5ppbv) and MYJ (RMSE=2.2ppbv). Results also indicate that the land-surface schemes in the Weather Research and Forecasting (WRF) model have a small impact on the NOx gradient. Usingmodel simulations, we analyze the impact of BL NOx gradient on the calculation of the ozone production rate and satellite NO2 retrieval. We show that using surface measurements and the well-mixed BL assumption causes a~45%highbias in the estimated BL ozoneproduction rate and that the variability of NO2 vertical profiles is responsible for 5–10% variability in the retrieved NO2 tropospheric vertical columns.


International Journal of Coal Geology | 2011

Quantifying greenhouse gas emissions from coal fires using airborne and ground-based methods

Mark A. Engle; Lawrence F. Radke; Edward L. Heffern; Jennifer M.K. O'Keefe; Charles Smeltzer; James C. Hower; Judith M. Hower; Anupma Prakash; Allan Kolker; Robert J. Eatwell; Arnout ter Schure; Gerald Queen; Kerry L. Aggen; Glenn B. Stracher; Kevin R. Henke; Ricardo A. Olea; Yomayra Román-Colón


Atmospheric Measurement Techniques | 2016

Inverse modelling of NO x emissions over eastern China: uncertainties dueto chemical non-linearity

Dasa Gu; Yuhang Wang; Ran Yin; Yuzhong Zhang; Charles Smeltzer


Atmospheric Chemistry and Physics | 2016

Enhanced trans-Himalaya pollution transport to the Tibetan Plateau by cut-off low systems

Ruixiong Zhang; Yuhang Wang; Qiusheng He; Laiguo Chen; Yuzhong Zhang; Hang Qu; Charles Smeltzer; Jianfeng Li; Leonardo M. A. Alvarado; M. Vrekoussis; Andreas Richter; F. Wittrock; J. P. Burrows


International Journal of Coal Geology | 2018

Gas emissions, tars, and secondary minerals at the Ruth Mullins and Tiptop coal mine fires

Jennifer M.K. O'Keefe; Erika R. Neace; Max L. Hammond; James C. Hower; Mark A. Engle; Joseph East; Nicholas J. Geboy; Ricardo A. Olea; Kevin R. Henke; Gregory C. Copley; Edward W. Lemley; Rachel S. Nally; Antonia E. Hansen; Allison R. Richardson; Anne B. Satterwhite; Glenn B. Stracher; Larry Radke; Charles Smeltzer; Christopher S. Romanek; D. R. Blake; Paul A. Schroeder; Stephen D. Emsbo-Mattingly; Scott A. Stout


Atmospheric Measurement Techniques Discussions | 2018

Reconciling the differences between OMI-based and EPA AQS in situ NO 2 trends

Ruixiong Zhang; Yuhang Wang; Charles Smeltzer; Hang Qu; William J. Koshak; K. Folkert Boersma


Atmospheric Measurement Techniques | 2018

Comparing OMI-based and EPA AQS in situ NO 2 trends: towards understanding surface NO x emission changes

Ruixiong Zhang; Yuhang Wang; Charles Smeltzer; Hang Qu; William J. Koshak; K. Folkert Boersma

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Yuhang Wang

Georgia Institute of Technology

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Dasa Gu

University of California

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Yuzhong Zhang

Georgia Institute of Technology

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K. Folkert Boersma

Wageningen University and Research Centre

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Hang Qu

Georgia Institute of Technology

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Mark A. Engle

United States Geological Survey

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Ricardo A. Olea

United States Geological Survey

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