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    <title>DRUM Collection: Atmospheric &amp; Oceanic Science Research Works</title>
    <link>http://hdl.handle.net/1903/1596</link>
    <description />
    <pubDate>Sat, 25 May 2013 17:32:02 GMT</pubDate>
    <dc:date>2013-05-25T17:32:02Z</dc:date>
    <item>
      <title>Analysis of Summertime PM2.5 and haze in the Mid-Atlantic Region</title>
      <link>http://hdl.handle.net/1903/8950</link>
      <description>Title: Analysis of Summertime PM2.5 and haze in the Mid-Atlantic Region
Authors: Chen, L.-W. Antony; Chow, Judith C.; Doddridge, Bruce G.; Dickerson, Russell R.; Ryan, William F.; Mueller, Peter K.
Abstract: Observations of the mass and chemical composition of&#xD;
particles less than 2.5 �m in aerodynamic diameter&#xD;
(PM2.5), light extinction, and meteorology in the urban&#xD;
Baltimore-Washington corridor during July 1999 and July&#xD;
2000 are presented and analyzed to study summertime&#xD;
haze formation in the mid-Atlantic region. The mass fraction&#xD;
of ammoniated sulfate (SO4&#xD;
2�) and carbonaceous&#xD;
material in PM2.5 were each �50% for cleaner air (PM2.5 �&#xD;
10 �g/m3) but changed to �60% and �20%, respectively,&#xD;
for more polluted air (PM2.5 � 30 �g/m3). This signifies&#xD;
the role of SO4&#xD;
2� in haze formation. Comparisons of data&#xD;
from this study with the Interagency Monitoring of Protected&#xD;
Visual Environments network suggest that SO4&#xD;
2� is&#xD;
more regional than carbonaceous material and originates&#xD;
in part from upwind source regions. The light extinction&#xD;
coefficient is well correlated to PM2.5 mass plus water&#xD;
associated with inorganic salt, leading to a mass extinction&#xD;
efficiency of 7.6 � 1.7 m2/g for hydrated aerosol. The&#xD;
most serious haze episode occurring between July 15 and 19, 1999, was characterized by westerly transport and&#xD;
recirculation slowing removal of pollutants. At the peak&#xD;
of this episode, 1-hr PM2.5 concentration reached �45&#xD;
�g/m3, visual range dropped to �5 km, and aerosol water&#xD;
likely contributed to �40% of the light extinction coefficient.</description>
      <pubDate>Wed, 01 Jan 2003 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/1903/8950</guid>
      <dc:date>2003-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Validation of SO2 retrievals from the Ozone Monitoring Instrument (OMI) over NE China</title>
      <link>http://hdl.handle.net/1903/8948</link>
      <description>Title: Validation of SO2 retrievals from the Ozone Monitoring Instrument (OMI) over NE China
Authors: Krotkov, N. A.; McClure, B.; Dickerson, R. R.; Carn, S.; Li, C.; Bhartia, P. K.; Yang, K.; Krueger, A.; Li, Z.; Levelt, P. F.; Chen, Hongbin; Wang, Pucai; Lu, Daren
Abstract: The Ozone Monitoring Instrument (OMI) launched on the NASA Aura satellite in July 2004 offers unprecedented spatial resolution, coupled with contiguous daily global coverage, for space-based UV measurements of sulfur dioxide (SO2).  We present a first validation of the OMI SO2 data with in-situ aircraft measurements in NE China in April 2005.  The study demonstrates that OMI can distinguish between background SO2 conditions and heavy pollution on a daily basis.  The noise (expressed as the standard deviation, σ) in the PBL SO2 data is ~1.5DU (Dobson Unit, 2.691016 molecules/cm2) for instantaneous field of view (IFOV) data.  By looking at the pristine South Pacific under optimal conditions we have determined that temporal and spatial averaging can improve the resolution of the instrument to σ ~ 0.3 DU; the long term average over this remote location was within 0.1 DU of zero.  Under polluted conditions, however, Collection 2 data are higher than aircraft measurements by a factor of two in most cases.  Parameterization of the airmass factor (AMF) appears to enhance the accuracy of the SO2 data.  Improved calibrations of the radiance and irradiance data (Collection 3) result in better agreement with aircraft measurements on polluted days.  The re-processed and AMF-corrected Collection 3 data still show positive bias and sensitivity to UV absorbing aerosols.  The difference between the in situ data and the OMI daily PBL SO2 measurements within 30 km of the aircraft profiles was about 1 DU, equivalent to ~5 ppb from 0 to 3000 m altitude.  Quantifying the SO2 profile and spectral dependence of aerosol absorption between 310 and 330 nm are critical for accurate estimates of SO2 from satellite UV measurements.</description>
      <pubDate>Tue, 01 Jan 2008 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/1903/8948</guid>
      <dc:date>2008-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Observed Relationship of Ozone air Pollution with Temperature and Emissions</title>
      <link>http://hdl.handle.net/1903/8947</link>
      <description>Title: Observed Relationship of Ozone air Pollution with Temperature and Emissions
Authors: Bloomer, Bryan J. ; Stehr, Jeffrey W. ; Piety, Charles A.; Salawitch, Ross J.; Dickerson, Russell R.
Abstract: Higher temperatures caused by increasing greenhouse gas concentrations are predicted to exacerbate photochemical smog if precursor emissions remain constant. We perform a statistical analysis of 21 years of ozone and temperature observations across the rural eastern U.S. The climate penalty factor is defined as the slope of the ozone/temperature relationship. For two precursor emission regimes, before and after 2002, the climate penalty factor was consistent across the distribution of ozone observations. Prior to 2002, ozone increased by an average of ~3.2 ppbv/°C. After 2002, power plant NOx emissions were reduced by 43%, ozone levels fell ~10%, and the climate penalty factor dropped to ~2.2 ppbv/°C. NOx controls are effective for reducing photochemical smog and might lessen the severity of projected climate change penalties. Air quality models should be evaluated against these observations, and the climate penalty factor metric may be useful for evaluating the response of ozone to climate change.</description>
      <pubDate>Thu, 01 Jan 2009 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/1903/8947</guid>
      <dc:date>2009-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>The Sensitivity of Modeled Ozone to the Temporal Distribution of Point, Area, and Mobile Emissions in the Eastern US</title>
      <link>http://hdl.handle.net/1903/8946</link>
      <description>Title: The Sensitivity of Modeled Ozone to the Temporal Distribution of Point, Area, and Mobile Emissions in the Eastern US
Authors: Castellanos, Patricia; Ehrman, Sheryl H.; Stehr, Jeffrey W.; Dickerson, Russell R.
Abstract: Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields&#xD;
used in air quality models (AQMs) generally show less temporal variability than corresponding&#xD;
measurements. In order to understand how the daily cycle of estimated emissions affects modeled ozone,&#xD;
we analyzed the effects of altering all anthropogenic emissions’ temporal distributions by source group&#xD;
2&#xD;
on 2002 summer-long simulations of ozone using the Community Multi-Scale Air Quality Model&#xD;
(CMAQ) v4.5 and the carbon bond IV (CBIV) chemical mechanism with a 12 km grid. We find that&#xD;
when mobile source emissions were made constant over the course of a day, 8-hour maximum ozone&#xD;
predictions changed by ±7 parts per billion by volume (ppbv) in urban areas on days when ozone&#xD;
concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation&#xD;
of point sources resulted in ozone changes of +6 and –6 ppbv, but only for small areas near sources.&#xD;
Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone,&#xD;
especially in urban areas at night; implications for abatement strategy are discussed.</description>
      <pubDate>Thu, 01 Jan 2009 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/1903/8946</guid>
      <dc:date>2009-01-01T00:00:00Z</dc:date>
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