1. 1 23
Air Quality, Atmosphere & Health
An International Journal
ISSN 1873-9318
Air Qual Atmos Health
DOI 10.1007/s11869-015-0363-2
Characterization of pollution transport
into Texas using OMI and TES satellite,
GIS and in situ data, and HYSPLIT back
trajectory analyses: implications for TCEQ
State Implementation Plans
D. Bella, J. Culpepper, J. Khaimova,
N. Ahmed, Adam Belkalai, I. Arroyo,
J. Andrews, S. Gentle, S. Emmanuel,
M. Lahmouh, J. Ealy, et al.

2. 1 23
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3. Characterization of pollution transport into Texas using OMI
and TES satellite, GIS and in situ data, and HYSPLIT back
trajectory analyses: implications for TCEQ State
Implementation Plans
D. Bella1
& J. Culpepper1
& J. Khaimova2
& N. Ahmed3
& Adam Belkalai3
& I. Arroyo4
&
J. Andrews5
& S. Gentle6
& S. Emmanuel7
& M. Lahmouh4
& J. Ealy1
& Zayna King1
&
O. Jenkins4
& D. Fu8
& Y. Choi9
& G. Osterman8
& J. Gruszczynski10
& D. Skeete1
&
C. S. Blaszczak-Boxe1,7,11
Received: 2 April 2015 /Accepted: 8 July 2015
# Springer Science+Business Media Dordrecht 2015
Abstract Transport of pollution from remote sources into the
state of Texas has been shown by modeling techniques, satel-
lite, and in situ data. Attaining a better understanding of the
impact (i.e., temporally) of remote pollution sources will pro-
vide a more robust/quantifiable basis for State Implementation
Plans (SIPs) that govern air quality. Utilizing Tropospheric
Emission Spectrometer (TES) and Ozone Monitoring
Instrument (OMI) and in situ data for ozone (O3) and nitrogen
dioxide (NO2) and Hybrid Single-Particle Lagrangian
Integrated Trajectory Model (HYSPLIT), we assess whether
high-pollution events in Texas are primarily sourced locally
(i.e., within Texas) or remotely. We focus on TES and OMI
dates that exemplify high O3 and NO2, over Texas’s lower
troposphere from August 5, 2006, to June 21, 2009. For all
dates and altitudes, 4-day back trajectory analyses, exempli-
fied by high TES O3, show that remotely sourced from the
Gulf of Mexico, Southeast USA, Midwest USA, Northeast
USA, the Atlantic Ocean, Pacific Ocean, Mexico to Texas.
The only exception is air at 1 km on July 22, 2006, which
shows that air at this altitude is sourced within Texas.
Throughout half of the eastern portion of Texas, TES shows
O3 enhancements in the boundary layer and OMI shows O3
and NO2 enhancements via tropospheric column profiles (O3
between 75 and 90 ppbv; NO2 ≥5.5 molecules cm−2
). These
enhancements complement the HYSPLIT 4-day trajectory
analyses, which gives further indication that they are influ-
enced by transport from remote sources. Dates with co-
located satellite and in situ data (e.g., August 2, 2005) further
Electronic supplementary material The online version of this article
(doi:10.1007/s11869-015-0363-2) contains supplementary material,
which is available to authorized users.
* C. S. Blaszczak-Boxe
cboxe@mec.cuny.edu
1
Department of Physical, Environmental and Computer Science,
Medgar Evers College-City University of New York, 1638 Bedford
Avenue, Brooklyn, NY 11225, USA
2
Brooklyn College of the City University of New York, New
York, NY, USA
3
Brooklyn Technical High School, Brooklyn, NY 11217, USA
4
Khalil Gibran International Academy, Brooklyn, New York 11217,
USA
5
Medgar Evers College Preparatory School, Brooklyn, NY 11225,
USA
6
Brooklyn Academy of Science and Environment (BASE) High
School, Brooklyn, NY 11225, USA
7
Valley Stream South High School, Long Island, NY 11581, USA
8
Earth and Space Science Division, Jet Propulsion Laboratory,
California Institute of Technology, Pasadena, CA 91109, USA
9
Department of Earth and Atmospheric Sciences, University of
Houston, Houston, TX 77004, USA
10
I Liceum Ogólnokształcące im. Stanisława Staszica, Lublinie, Aleje
Racławickie 26, 20-043 Lublin, Poland
11
Chemistry Division, Earth and Environmental Science Division,
CUNY Graduate Center, Manhattan, NY 10016, USA
Air Qual Atmos Health
DOI 10.1007/s11869-015-0363-2
Author's personal copy

4. exemplify the need to consider satellite and in situ data and
modeling data/forecasts when creating SIPs for compliance
with Environmental Protection Agency and the Texas
Commission on Environmental Quality air quality standards.
Despite the fact that quantifying local versus remote sources is
in its early stages, Texas has become increasingly compliant
with Environmental Protection Agency (EPA) regulations.
Environmental Systems Research Institute’s ArcGIS exem-
plifies the noticeable decrease in the number of days that lo-
cales in Texas exceed EPA’s limit for O3. From 2005 to 2009,
population standard deviation and standard error of the mean,
and true sample deviation of the sample mean for O3 and NO2,
at all 16 monitoring sites distributed throughout Texas, are
temporally consistent and small—reinforcing the reliability
of in situ data as they are consistent throughout. This investi-
gation has global implications for regions within countries that
enforce air quality mandates. Such governing bodies should
consider utilizing data assimilation (of in situ data) for air
quality prediction as a part of the governmental process that
produces such laws. This could potentially keep regions more
accountable for emissions both locally and far from high
source points.
Keywords Air quality . TCEQ . SIPs . HYSPLIT . TES .
ArcGIS . OMI . In situ data
Abbreviations
AQ Air quality
AIRS Atmospheric Infrared Sounder
EPA Environmental Protection Agency
GIS Geographical information systems
HGBR Houston-Galveston-Brazoria Region
HYSPLIT Hybrid Single-Particle Lagrangian Integrated
Trajectory Model
HC Hydrocarbon
MODIS Moderate Resolution Imaging
Spectroradiometer
NO2 Nitrogen dioxide
OMI Ozone Monitoring Instrument
O3 Ozone
RAQMS Real-time Air Modeling System
SIPs State Implementation Plans
TES Tropospheric Emission Spectrometer
TCEQ Texas Commission for Environmental Quality
Introduction
Numerous studies have revealed that air quality (AQ), like
climate change, is not just a local, but also a regional and
global issue that recognizes no political boundaries (Wotawa
and Trainer 2000; Colarco et al. 2004), a fact that presents
challenges for international relations and for state agencies
trying to develop effective State Implementation Plans
(SIPs) to come into compliance with Environmental
Protection Agency (EPA) and the Texas Commission on
Environmental Quality (TCEQ) AQ standards. Insights into
the regional and global nature of AQ are greatly assisted by
the current generation of satellite instruments. Current gener-
ation satellites include the following: (1) Disaster Monitoring
Constellation for International Imaging (DMCii), (2) Pleiades
constellation, (3) Earth Resources Observation Satellite A and
B (EROS), (4) Formosat-2, (5) IKONOS, (6) QuickBird, (7)
RapidEye, (8) SPOT, (9) TerraSAR-X/TanDEM-X, (10)
Constellation of small Satellites for the Mediterranean basin
Observation (COSMO)-SkyMed, (11) WorldView-1/
WorldView-2/WorldView-3, (12) GeoEye-1, (13) SROSS-2,
(14) Aqua (EOS PM-1), (15) Aura, (16) Gravity Recovery and
Climate Experiment (GRACE), (17) Jason, (18) Ocean
Surface Topography Mission (OSTM) on Jason-2, (19)
Orbview-2, (20) Orbiting Carbon Observatory 2 (OCO-2),
( 21) Terra (EOS AM-1), (22) Tropical Rainfall Measuring
Mission (TRMM), (23) Geostationary Operational
Environment Satellite (GEOS 13/GEOS 14/GEOS 15), (24)
NOAA-15/NOAA-16/NOAA-18/NOAA-19, (25 METOP-A/
METOP-B, (26) Suomi NPP, (27) MtSAT-1R/Himawari-6,
(28) MYSAT-2/Himawari-7, (29) Landsat 7/Landsat 8, (30:
China-Brazil Earth Resources Satellite 3 (CBERS-3), (31)
CBERS-4, (32) Satellite for Scientific Applications-D (SAC-
D), (33) Satellite Pour l’Observation de la Terre (SPOT 6 and
7), (34) Pleades constellation (1A and 1B), (35) Sentinel-1A,
(36) Megha-Tropiques, (37) Oceansat-2, (38) IMS-1, (39)
Cartosat-2A, (40) IRS P5 (CARTOSAT-1), (41) Greenhouse
Gases Observing Satellite (GOSAT), (42) Advanced Land
Observing Satellite (ALOS), Lapan-TUBsat, (43) Nigerian
Weather and Communication Satellites (Nigeriasat-1, 2,
NigComSat-1, -1R), (44) Pakistan Remote Sensing Satellite,
(45) Elektro-L, (46) Radarsat-2, (47) Gokturk-1 and -2, and
(48) RASAT. Fishman et al. (2008) stress the importance of
AQ issues in the design of future space-based observation
platforms. Furthermore, chronic exposure to poor AQ is asso-
ciated with elevated health risks (McConnell et al. 2002; Bell
et al. 2004) and negative impacts on crop yields (Chameides
et al. 1999; Avnery et al. 2011a, b; Avnery et al. 2011a, b;
Heagle 1989; Feng and Koboyashi 2009; Dingenen et al.
2009; Tubiello et al. 2007; Mauzerall and Xiaoping 2001;
Murphy et al. 1999; Krupa and Manning 1988; Fiscus et al.
2005; Fishman et al. 2008; Fishman et al. 2010).
Over the past several decades, there has been significant
urban growth in various areas of Texas, such as Houston.
Houston has a larger population of car users that leads to
significant vehicular emissions and of the highest and regular-
ly suffers from some of the highest ozone (O3) concentrations
in the USA (Morris et al. 2010). A variety of other factors
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5. contribute to Houston’s exceptional O3 pollution. It is the
fourth largest urban population in the USA, much of which
commutes from remote suburbs, resulting in elevated NOx
(NO + NO2) throughout the Houston-Galveston-Brazoria
Region (HGBR). Houston also contains one of the largest
petrochemical production sectors in the world, which there-
fore frequently produces co-located concentrated hydrocarbon
(HC) and NOx emissions; this is also compounded by the fact
that HC reactivities in the Houston ship channel area are two
to five times higher than those over other US urban locations
(Kleinman et al. 2002; Daum et al. 2003). In addition, the
Parish power plant in Thompsons, TX, is one of the top 5
emitters of CO2 in the USA (Olivier et al. 2013) and produces
more than 5300 t/year of NOx (Kim et al. 2011). Widespread
forests in East Texas are a source of biogenic volatile organic
compounds (VOCs). Also, persistent high pressure and fair
weather during summer and a location near Galveston Bay
and the Gulf of Mexico frequently lead to stagnant air over
the HGBR and/or recirculation of pollution via a land-sea
breeze circulation (Banta et al. 2005) Lastly, long-range trans-
port of O3 and precursors from remote locations can exacer-
bate local pollution levels (Pierce et al. 2009).
The long-range transport of pollutants to different locals,
globally, is a pertinent issue within the climate science com-
munity (Kolb et al. 2010). As a direct atmospheric pollutant,
resulting from biomass burning and incomplete combustion, it
is a precursor to the formation of tropospheric ozone; mea-
surements of carbon monoxide (CO) have, therefore, been
used extensively to forecast and monitor AQ (Kleinman
et al. 2002; Thompson et al. 2008; Morris et al. 2010;
Rappengluck et al. 2008; Crutzen et al. 1979; Logan et al.
1981; Badr and Probert 1994; Forster et al. 2001; Novelli
et al. 2003; Colarco et al. 2004; Yurganov et al. 2008;
Engel-Cox et al. 2005; Morris et al. 2006). With a lifetime
of 2–3 weeks, tropospheric CO can be transported far down-
wind from its emissions source. Past studies have used
Atmospheric Infrared Sounder (AIRS) observations to illus-
trate the impact of long-range transport on local AQ (Stohl
et al. 2007a, b; Thompson et al. 2007; Zhang et al. 2008;
McMillan et al. 2008) and the impact of distant fires on AQ
in the vicinity of Houston, TX (Morris et al. 2006). However,
all of these studies involved monitoring CO transport in the
mid-troposphere, where much of the long-range transport oc-
curring between 400 and 600 mb (McMillan et al. 2008).
The transport of pollution from remote sources into the
state of Texas has been shown in several other studies
(Pierce et al. 2009, McMillan et al. 2010; Kleinman et al.
2002; Thompson et al. 2008; Morris et al. 2010;
Rappengluck et al. 2008; Berkowitz et al. 2004; Daum et al.
2004; Hutchison 2003; Darby 2005; Cowling 2007). Two of
the most recent studies, which were a part of the Second Texas
Air Quality Study (TexAQS II) in 2006, used satellite, in situ
data, and modeling to quantify the contribution of pollution
toward high ozone levels over Houston, TX (Pierce et al.
2009, McMillan et al. 2010). The TexAQS II in 2006 focused
on understanding the meteorological and chemical processes
that lead to high-pollution events within both the HGB and
Dallas-Fort Worth (DFW) ozone nonattainment areas, with a
strong emphasis on regional processes. The TexAQS field
studies supported the Texas Commission on Environmental
Quality (TCEQ) in developing State Implementation Plans
(SIPs) for attaining National Ambient Air Quality Standards
(NAAQS) for ozone in the HGB and DFW ozone
nonattainment areas. One of the primary science questions
that received special emphasis during TexAQS II was as fol-
lows: How do emissions from local and distant sources inter-
act to determine the AQ in Texas? Pierce et al. (2009) and
McMillan et al. (2010) expounded provided a method to better
understand this query. McMillan et al. (2010) illustrated the
transport of carbon monoxide (CO) from fires in the Pacific
Northwest into the Houston area using data from the AIRS
and results from the Real-time Air Modeling System
(RAQMS) chemical transport model. The Pierce et al.
(2009) study also used RAQMS and data from instruments
on the Aura satellite to illustrate effects on ozone production in
Dallas and Houston of pollution generated in the upper
Midwest. This report presents a complementary study by
using both Tropospheric Emission Spectrometer (TES) and
Ozone Monitoring Instrument (OMI) satellite and in situ data
for ozone (O3) and nitrogen dioxide (NO2) and Hybrid Single-
Particle Lagrangian Integrated Trajectory Model (HYSPLIT)
analyses to estimate the source of high-pollution events in
Texas from 2005 through 2009.
Tropospheric emission spectrometer and ozone
monitoring instrument measurements
TES is a Fourier transform spectrometer that was launched on
the Earth Observing System Aura satellite on July 15, 2004
(Beer et al. 2001). Onboard Aura, TES flies in a polar low
Earth orbit and provides profiles of O3 and CO, as well as H2O
vapor, HDO, and temperature among others. Figure 1 shows
an example of the spatial pattern of TES Bglobal survey^ (GS)
measurements for a 16-day repeat cycle in August 2006. TES
GS measurements are made every other day, providing profile
measurements for over 3000 locations over the globe in about
27 h (http://tes.jpl.nasa.gov/instrument/globalsurvey/).
Another observation mode used for tropospheric
composition or validation campaigns (e.g., INTEX-B or
ARCTAS) is the Bstep-and-stare^ mode. In this mode, the
TES instrument takes one nadir observation approximately
every 35 km over a latitude range of about 60° (or about
∼160 observations total). The latitudinal coverage of TES
has been modified over the course of the mission; currently,
GS data are collected from 50° N to 30° S to preserve lifetime.
Since September 2004, the continental USA has been
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6. regularly sampled by TES GS observations. Individual pro-
files from TES GS observations are spaced approximately
180 km apart, but they provide both daytime and nighttime
observations with coverage across North America and coastal
oceans. During science and validation campaign periods, TES
is capable of taking observations with better spatial resolution
made over smaller geographic regions. These special observa-
tions (SO) provide profiles spaced about 45 km apart, primar-
ily during the daytime. In the spring/summer 2006 and the
summers of 2007 and 2008, extensive TES SO campaigns
were carried out over North America. During February–
March 2006, nighttime SOs were taken as well.
TES can typically distinguish two vertical layers in the
troposphere for ozone, and CO measurements are sensitive
to one layer in the troposphere, centered at about 600 mb.
Typical averaging kernels for both daytime and nighttime
ozone observations from TES are shown in Fig. 2. The TES
averaging kernel provides a means of quantifying the sensi-
tivity of the TES measurement to ozone in the atmosphere.
Detailed discussion of TES averaging kernels can be found in
Worden et al. 2007 or in the TES Data User’s Guide
(Osterman et al. 2009). The averaging kernels in Fig. 2 show
TES sensitivity in the lower troposphere for both observa-
tions, with some sensitivity in the free troposphere during
the day. If enough ozone is present or if thermal contrast is
good, TES can resolve upper and lower tropospheric ozones.
The TES ozone observations have been validated against nu-
merous data sources (Boxe et al. 2010; Nassar et al. 2008;
Richards et al. 2008; Osterman et al. 2009). The ozone profiles
show a positive bias of 3–10 ppbv for the TES V002 data (the
second validated data ozone data product) (Nassar et al. 2008).
Ozone from more recent TES data versions has been shown to
be largely consistent with V002. Over the Northern hemi-
sphere, the region of focus for this study, the bias is usually
at a maximum near 200 mb. This bias is persistent over time
and should not impact the spatial analyses. We will have to
account for the bias when making comparisons to model runs
and other remote sensing measurements. An example of TES
ozone as a function of latitude from a TES SO is shown in
Fig. 3. This Bcurtain^ plot shows a broad area of enhanced
ozone in the middle/upper troposphere over Texas and the
Gulf of Mexico and a smaller area over east Texas in the lower
troposphere. TES data can provide information on these broad
(in latitude) ozone features such as that seen in Fig. 3.
Figure 4 shows the TES-sonde ozone percent and absolute
differences relative to sondes (for TES version 4) from 2005 to
2008 for the entire state of Texas. Figure 4a, b shows that the
mean difference or bias is between 5 and 10 % in the tropo-
sphere and stratosphere, and the absolute differences are zero
from the surface to the upper troposphere and less than
0.25 ppbv in the upper troposphere-to-lower stratosphere.
Hence, the TES data are valid to use within the context of this
report.
Similar to TES, OMI is one out of a total of four instru-
ments onboard the Aura spacecraft, which is flown in sun-
synchronous polar orbit at 705-km altitude with a 98.2° incli-
nation. Aura has an equatorial crossing time of 01:45 p.m.
(ascending node) with around 98.8 min per orbit (14.6 orbits
per day on average). OMI has a footprint of 13×24 km at
nadir, while TES has a footprint of 5×8 km at nadir. OMI is
a nadir-scanning instrument that, at visible (350–500 nm) and
UV wavelength channels (UV-1 270–314 nm; UV-2 306–
308 nm), detects backscattered solar radiance to measure col-
umn ozone with near global coverage (aside from polar night
latitudes) over the Earth. Aside from ozone, OMI can also
determine cloud top pressure, aerosols, and aerosol parame-
ters, NO2, SO2, and other trace constituents in the troposphere
and stratosphere (Levelt et al. 2006). Total ozone from OMI is
Fig. 1 TES daytime observations
of ozone over North America
during a 16-day repeat cycle in
August 2006. Nighttime O3 cov-
erage is similar for the TES global
survey
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7. derived from the TOMS version 8 algorithm. OMI tropospher-
ic NO2 columns (Bucsela et al. 2006) are obtained from the
NASA Goddard Earth Sciences Distributed Active Archive
Center.
In situ data
In situ data was taken from TCEQ’s from an online database
(http://www.tceq.state.tx.us/cgi-bin/compliance/monops/
select_summary.pl) that offers continuous ambient monitoring
data of from locations located at multiple sites. These
monitoring stations continuously monitor the atmosphere
and create an average every 5 min for each parameter of
interest. Hourly averages are calculated from the 5-min aver-
age. This data is certified by technical personnel from TCEQ
(or another responsible authority). This database is composed
of data from all TCEQ continuous ambient monitoring sta-
tions since June 1998. This database provides the most current
hourly averaged data available, which is time-tagged begin-
ning of each hour. Data is also presented in local standard time
for each measuring site, which is central time for most of
Texas. A 1-h time lag in data is introduced due to during
daylight savings time. Data that has not been verified by
TCEQ technical personnel may change. Data is collected by
TCEQ ambient monitoring sites and may also include data
collected from other outside agencies, which are updated
hourly. Via EPA guidelines, negative values may be displayed
in hourly data (as of Jan. 1, 2013) due to zero drift in the
electronic instrument output, data logger channel, or calibra-
tion adjustments to the data; prior to this date, negative values
were automatically adjusted to zero.
Hybrid single-particle lagrangian integrated trajectory
model
It is a computer model that is used to compute air parcel
trajectories, dispersion, or deposition of atmospheric trace gas-
es/pollutants. It was developed by Australia’s Bureau of
Meteorology and NOAA. It is used heavily used to establish
whether high levels of air pollution at one location are caused
by transport of air contaminants from another location. Its
back trajectories, combined with satellite data (e.g.,
Moderate Resolution Imaging Spectroradiometer (MODIS)
images, TES data, etc.), can provide insight into whether high
air pollution levels are caused by local air pollution sources or
whether it was sourced (to some large degree) remotely.
HYSPLIT can also be run in client-server mode (i.e.,
HYSPLIT WEB) from NOAA’s website (http://www.arl.
noaa.gov/HYSPLIT.php); this makes it convenient for the
public/community to select gridded historical or forecast
Fig. 2 A plot of TES averaging kernels for daytime (left) and nighttime (right) observations showing instrument sensitivity to ozone over the USA
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8. datasets, configure model runs, and retrieve model results (pdf
or html format) with a web browser.
Environmental systems research institute geographic
information system
Environmental Systems Research Institute (ESRI)’s ArcGIS is
a geographic information system used for working with maps
and geographic information. It is used for the following: cre-
ating and using maps, compiling geographic data, analyzing
mapped information, sharing and discovering geographic in-
formation, using maps and geographic information in a range
of applications, and managing geographic information in a
database. The system provides an infrastructure for making
maps and geographic information available throughout an or-
ganization, across a community, and openly on the Web.
Methodology
We examined the TES data record for evidence of high ozone
in the middle and/or lower troposphere over Texas and the
Southeastern USA. We looked at the TES data during time
periods suggested by TCEQ in addition to additional dates
from 2005 to 2009. The test dates were as follows: August
5–7, 2006; July 22, 2006; July 6–8, 2006; August 23, 2006;
August 23, 2006; July 31–August 2, 4, and 6, 2005; and
June 21, 2009.
Fig. 3 TES curtain plot showing
high ozone in the middle/upper
troposphere and in the lower tro-
posphere over East Texas in Au-
gust 2006. Map shows location of
TES observations and the tropo-
spheric ozone column measured
by TES. Regions of ozone en-
hancements are highlighted by the
bold circle and square
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9. Fig. 6 Curtain plot of ozone and carbon monoxide measured by TES on July 6, 2006. It shows a broad swath of enhanced middle/upper tropospheric
ozone (between 20 and 55 N latitude). It also shows enhanced ozone and carbon monoxide in the lower troposphere over Texas and the Central USA
Fig. 5 a Google Earth image of TES ozone measured on July 6, 2006. The columns show the location of the TES measurements. b TES geolocation
track for July 6, 2006
Fig. 4 TES-sonde ozone percent differences (a) and absolute differences
(b) (for TES version 4) from 2005 to 2009 over Texas. Individual profiles
are shown in gray, and means are overlaid in dark blue. Mean minus one
standard deviation and mean plus one standard deviation ranges are
overlaid in black. The number of coincident comparisons is BN.^ This
figure illustrates comparisons using TES version 4
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10. Using the TES O3 and OMI NO2 data (to find instances
of elevated pollution and locations in space and time for
the basis of a HYSPLIT run), we examined back trajecto-
ries of air observed by TES and OMI. We used the
HYSPLIT online model to perform these trajectories
(Draxler and Rolph 2014). The HYSPLIT model can give
an idea of the history of the air parcel observed by TES.
We focused primarily on cases where TES and OMI sug-
gest enhanced ozone and nitrogen dioxide in the lower tro-
posphere, while also examining cases with high mid-
Fig. 7 a HYSPLIT back trajectories for July 6, 2006, initiated at three
locations in East Texas. Texas, at 33° N latitude (at ~−93.97° longitude). b
Four-day back trajectory, starting at 1, 0.5, and 0.1 km on July 6, 2006,
over NE Texas, at 33° N latitude (at ~−93.97° longitude). c Four-day back
trajectory, starting at 0.01, 0.05, and 0.1 km on July 6, 2006, over NE
Texas, at 33° N latitude (at ~−93.97° longitude). As a reference, 1 hPa=
1 mbar
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11. tropospheric ozone. These analyses were also compared with
TCEQ ground-based O3 and NO2 data.
What we cannot do is provide observations illustrating the
high free tropospheric ozone observed by TES being entrained
into the boundary layer. We attempt to show that there are many
times where reservoirs of enhanced lower/middle tropospheric
ozone sit over or to the east of Texas. Here, we hope that it
provides an idea of the nature and frequency of transport of
ozone from the free troposphere to lower altitudes above Texas.
Many locations, throughout the year, in Texas frequently
exceeded EPA’s 8-h ozone concentration of 75 ppbv. For ex-
ample, in 2005, 2006, 2007, 2008, and 2009, Texas had 1450,
1300, 530, 350, and 370 exceedances, respectively, ground
stations that experienced ozone concentrations ranging from
76 to 126 ppbv. During this time frame, stations in Texas
experienced 80 to 120 days/year where O3 exceeded the
EPA limit for exposure (http://www.tceq.state.tx.us/cgi-bin/
compliance/monops/site_photo.pl).
Fig. 9 TES visualization of
ozone at the border of Texas,
Louisiana, Arkansas, and
Oklahoma. Note: given TES’s ~6-
km vertical resolution, TES O3
surface concentrations represent
concentrations within a broad
tropospheric layer
Fig. 8 OMI NO2 column
measurement for July 6, 2006
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12. TES satellite data are limited by spatial coverage and its
sensitivity to trace gases at low altitudes (e.g., boundary layer)
during cloudy conditions (i.e., high-optical-depth scenarios).
We, therefore, provide results for the following dates: August
5–7, 2006; July 22, 2006; July 6–8, 2006; August 23, 2006;
August 23, 2006; July 31–August 2, 4, and 6, 2005; and
June 21, 2009. We look in depth at July 6, 2006, July 22,
2006, and August 4, 2005, which are also complemented by
OMI NO2 data. TES O3 data and trajectory analyses of other
dates are included in the appendix.
We also calculate (from 2005 to 2009) population
σ ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
n ∑
n
i¼1
xi−xð Þ2
r
, standard deviation s ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
n−1 ∑
n
i¼1
xi−xð Þ2
r
and
standard error of the mean SEx ¼ sffiffi
n
p ; and true sample
deviation of the sample mean SDx ¼ σffiffi
n
p : for O3 and NO2, at
all 16 monitoring sites distributed throughout Texas to assess
the long-term reliability of the in situ data.
Results and discussion
July 6, 2006
On July 6, TES had just begun taking a series of SOs in
support of the TexAQS II. This particular Bstep and stare^
(SS) observation obtained measurements over the Gulf of
Mexico, just to the east of Beaumont (30.0800° N, 94.1267°
Fig. 11 TES geolocation track
for July 22, 2006
Fig. 10 TES Nadir O3 retrieval
for July 22, 2006. Note: high
lower tropospheric O3
concentrations between 80 and
100 ppbv between 33 and 34° N
latitude (at ~−93.97° longitude),
which are located over NE Texas
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13. W), through East Texas (including over Longview) and up
into Oklahoma and Kansas (Fig. 5a, b). The measurements
were made in the afternoon (19:40 UTC). The TES data for
that date shows enhanced levels of ozone and carbon monox-
ide in the lower troposphere for the observations over the
Texas and the Central USA (Fig. 5). It also shows a broad
swath of high ozone in the middle/upper troposphere between
20 and 55 N latitude.
As mentioned earlier, the TES data has enough vertical
resolution to resolve lower troposphere ozone from that in
Fig. 12 a Four-day back trajectory, starting at 2 and 0.05 km on July 22,
2006, over NE Texas, between and 34° N latitude (at ~−93.97° longi-
tude). b Back trajectories for July 22, 2006, at heights of 1, 0.5, and
0.1 km. The 1-km back trajectory shows that O3 values measured at
1 km are sourced just SWof Wichita Falls; although O3 at 1 km is sourced
from Texas, it likely represents only a small fraction of O3 measured over
NE Texas, especially considering that all other height trajectories show
that ozone is sourced from remote sources—i.e., outside of Texas. c Back
trajectories for July 22, 2006, at heights of 12, 10, and 9 km. Air parcels at
these heights are sourced over the Atlantic Ocean. d Back trajectories for
July 22, 2006, at heights of 0.01, 0.05, and 0.1 km. Air parcels at these
heights are sourced at the surface and at higher altitudes over Arkansas
and Indiana
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14. the upper troposphere. The averaging kernels from these TES
retrievals suggest sensitivity peaks in the lower troposphere
(near 700 hPa) with another peak in the middle troposphere.
Images from the NASA MODIS instrument on the Aqua satel-
lite suggest broken clouds in the observing locations though all
internal TES quality flags suggest that most of the profiles are
of good quality. The clouds are heavier over the Gulf of
Mexico, and some of the lack of ozone seen in Fig. 6 over
the Gulf could be due to the influence of clouds (TES would
only measure to the top of the cloud if it is thick and fills the
field of view).
We ran a series of back trajectories for July 6 to examine
the history of the air parcels observed. HYSPLIT back trajec-
tories, starting from Houston, show air coming from the Gulf
and toward the SE USA (see Appendix/Supplementary
Material). The 4-day back trajectories, starting at 0.5 (red),
2.5 (blue), and 4.5 km (green), initiated from the location of
three TES footprints (i.e., Houston, TX) are shown in Fig. 7a.
Fig. 14 OMI O3 for July 22,
2006
Fig. 13 OMI NO2 for July 22,
2006
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15. These trajectories show that the observations over SE Texas
are measuring air that had been over the Gulf 2–4 days earlier.
They do not suggest much vertical movement of the parcels.
The trajectory starting over Longview suggests that the
highest values of lower tropospheric ozone (NE Texas) are
seen in air parcels that originated over the central USA at
higher altitudes and can be traced back to the Midwest/Great
Lakes area for the near surface trajectory. Figure 7b, c shows a
4-day back trajectory analyses, starting at 0.1 (red), 0.5 (blue),
and 1 km (green) for Fig. 7b and 0.01 (red), 0.05 (blue), and
0.1 km (green) for Fig. 7c. It is clearly shown that high ozone
measured over NE Texas is from remote sources. These lower
altitude trajectories show more vertical mixing to transport air
toward the surface. TES data from GSs on July 3–4 and
July 5–6 suggest that there are high levels of middle tropo-
spheric ozone over the Midwestern USA and, to a lesser de-
gree, over the Southeastern USA. The ozone measured over
the Gulf of Mexico is on the order of 50–60 ppbv.
All other TCEQ in situ measurement sites on July 6, 2006,
in Texas measured NO2 at concentrations less than 46 ppbv
(http://www.tceq.state.tx.us/cgi-bin/compliance/monops/site_
photo.pl; please refer to Appendix/Supplementary Material).
Figure 8 displays tropospheric column measurement of NO2
on July 6, 2006, from the Ozone Monitoring Instrument
(OMI), which shows enhancements of NO2 (i.e., ≥5.5×1015
molecules cm−2
) for the mid-to-eastern part of Texas. These
enhancements encompass the latitude and longitude coordi-
nates that also measured high O3 greater than ~80 ppbv via in
Fig. 16 TES Nadir O3 retrieval
for August 2, 2005. Note: high
lower tropospheric O3
concentrations between 80 and
100 ppbv measured between 31
and 33° N latitude (~−97°
longitude), located over mid-
Texas
Fig. 15 TES geolocation track
for August 2, 2005
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16. Fig. 17 a Four-day back trajec-
tory, starting at 1, 0.5, and 0.1 km
on August 2, 2005, over mid-
Texas, starting from Dallas, TX. b
Four-day back trajectory, starting
at 7, 5, and 3 km on August 2,
2005, over mid-Texas, starting
from Dallas, TX. c Four-day back
trajectory, starting at 12, 10, and
9 km on August 2, 2005, over
mid-Texas, starting from Dallas,
TX. d Four-day back trajectory,
starting at 0.01, 0.05, and 0.1 km
on August 2, 2005, over mid-
Texas, starting from Dallas, TX. e
Four-day back trajectory, starting
at 1, 0.5, and 0.1 km on August 2,
2005, over mid-Texas, starting
from Fort Worth, TX. f Four-day
back trajectory, starting at 7, 5,
and 3 km on August 2, 2005, over
mid-Texas, starting from Fort
Worth, TX. g Four-day back tra-
jectory, starting at 12, 10, and
9 km on August 2, 2005, over
mid-Texas, starting from Fort
Worth, TX. h Four-day back tra-
jectory, starting at 0.01, 0.05, and
0.1 km on August 2, 2005, over
mid-Texas, starting from Fort
Worth, TX
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17. situ TCEQ ground stations. On this day, no site TCEQ ground
stations in Texas made measurements exceeding the EPA stan-
dard limit for ozone exposure. Still, no in situ measurement
site exists in the region, which would coincide with where
TES measured high O3 over Texas.
July 22, 2006
The results for the July 22, 2006, TES SS track provide a very
similar picture to that of July 6 (Figs. 9, 10, 11, and 12a, c, d.
The area of high middle tropospheric ozone is not as broad in
latitude as it is on the 6th, but the trajectories suggest similar
sources from outside the state. Figure 12b is the only excep-
tion to this complementary behavior.
The four back trajectory analyses, starting at 2 and 0.5 km,
show clearly that the high O3 concentrations measured by
TES in the lower troposphere (i.e., close to the surface) are
not sourced from Texas but are transported from the Gulf of
Mexico, Southeastern USA, and Northwestern USA.
Figure 12a also indicates that at 2 and 0.5 km, O3 measured
from these altitudes over NE Texas is transported remotely at
higher altitudes.
Except for one Midlothian Tower, which measured an NO2
concentration of 54 ppbv at 8 p.m., all other sites on July, 22,
2006, in Texas measured NO2 at concentrations less than
32 ppbv (http://www.tceq.state.tx.us/cgi-bin/compliance/
monops/site_photo.pl). Figure 13 displays a tropospheric
column measurement of NO2 on July 22, 2006, from the
Ozone Monitoring Instrument (OMI), which shows
enhancements of NO2 (i.e., ≥5.5×1015
molecules cm−2
) for
the mid-to-eastern part of Texas. These OMI NO2
enhancements encompass the latitude and longitude coordi-
nates that also measured high O3 greater than ~80 ppbv. The
Italy High School site was the only site that measured O3
concentrations (76 ppbv) above the EPA limit, which does
coincide with the location of the O3 and NO2 enhancements
measured by TES and OMI. Figure 14 shows a tropospheric
column measurement of O3 for July 22, 2006, from OMI,
which also reveal ozone enhancements (i.e., 45 to 50 ppbv)
in the same region as those shown for NO2 in Fig. 13. The
lifetime of ozone in the troposphere is ~1 month while the
lifetime of NO2 (an ozone precursor) close to the surface is
about a few hours and 1–2 weeks in the upper troposphere.
Given the fact that TES and OMI show O3 and NO2 enhance-
ments in the boundary layer and HYSPLIT trajectory analyses
show transport from remote of air parcels from remote sources
further compounds how to quantitatively separate remote air
parcel influence upon a given local. In other words, observed
O3 enhancements can most certainly (to some degree) be in-
fluence by remote transport—in addition to NO2 as well (on
much shorter timescales—less than few hours for lower tro-
pospheric air and less than 1–2 weeks for air potentially
transported from remote regions in the upper troposphere).
August 2, 2005
Figures 15 and 16 represent TES ozone measurement track
through the middle of Texas, where high O3 concentrations
are measured between 31 and 33° N latitude (~−97° longi-
tude). This latitude-longitude bin is coincident with the loca-
tions of Fort Worth and Dallas, TX. All 4-day back trajectory
analyses show that high ozone values measured over mid-
Fig. 18 OMI tropospheric
column measurement of NO2 on
August 2, 2005
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18. Texas are sourced from the SE region of USA and other re-
mote locations (Fig. 17a–h).
All other sites on August 2, 2005, in Texas measured NO2 at
concentrations less than 29 ppbv (http://www.tceq.state.tx.us/
cgi-bin/compliance/monops/site_photo.pl). Figures 18 and 19
display a tropospheric column measurement of NO2 and O3 on
July 22, 2006, from the Ozone Monitoring Instrument (OMI),
which shows enhancements of NO2 (i.e., ≥5.5×1015
molecules
cm−2
) and O3 (between 45 and 50 ppbv) for the mid-to-eastern
part of Texas. These enhancements encompass the latitude and
longitude coordinates for TES that also measured high O3
greater than ~80 ppbv. On August 2, 2005, 29 sites measured
O3 concentrations (77 to 115 ppbv) above the EPA limit, which
mostly coincide with the location of the O3 and NO2 enhance-
ments measured by TES and OMI. Analogous to Figs. 13 and
14, the difference in lifetimes of O3 and NO2 (and given that
NO2 is a precursor of O3 production) points to the need for the
formulation of implementing not only trajectory analyses but
also modeling and data assimilation to add another layer atop
qualitative analyses to extract quantitative percent contribu-
tions from remote sources (Pierce et al. 2009; Lin et al. 2014).
Although remote sources may compliment formulating ap-
propriate SIPs for locals, Texas has become increasingly com-
pliant with EPA regulations; ESRI’s ArcGIS exemplifies the
noticeable decrease in the number of days that locals in Texas
exceed EPA’s limit for O3 (Fig. 20). Moreover, 2005 to 2009
population σ ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
n ∑
n
i¼1
xi−xð Þ2
r
; standard deviation s ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
n−1 ∑
n
i¼1
xi−xð Þ2
r
and standard error of the mean SEx ¼ sffiffi
n
p ;
and true sample deviation of the sample mean SDx ¼ σffiffi
n
p :
for O3 and NO2, at all 16 monitoring sites distributed through-
out Texas, are temporally consistent—reinforcing the reliabil-
ity of in situ data.
Summary and conclusions
We have examined over 20 days of TES data and run trajec-
tories from the location of the TES and OMI measurements.
Four-day back trajectory analyses of all dates show that up-
per-, mid-, and lower-tropospheric air over Texas (i.e., air at
12, 10, 9, 7, 5, 3, 1, 0.5, and 0.1 km), containing high O3, as
shown by TES, is transported from the Gulf of Mexico,
Southeast USA, Midwest USA, Northeast USA, the Atlantic
Ocean, Pacific Ocean, Mexico, etc., in all cases. The only
exception is air at 1 km on July 22, 2006; 4-day back trajec-
tory analyses show that air at this altitude is sourced within
Texas. TES and OMI show O3 and NO2 enhancements in the
boundary layer, complementing the HYSPLIT 4-day trajecto-
ry analyses, which gives further indication that such enhance-
ments are governed by transport from remote sources. Given
the fact that TES, OMI, and in situ data for O3 and NO2 show
enhancements in the boundary layer, all datasets complement
the HYSPLIT 4-day back trajectory analyses, showing that
such enhancements are governed by transport from remote
sources. Dates with co-located satellite and in situ data (e.g.,
August 2, 2005) further exemplify the need for combining
„Fig. 20 Number of days that O3 levels exceeded EPA
regulations for 2005, 2006, 2007, 2008, and 2009 (see color
caption below)
Fig. 19 OMI O3 tropospheric
column for August 2, 2005
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19. (2005) (2006)
(2007) (2008)
(2009)
(a) (b)
(c) (d)
(e)
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20. satellite and in situ data and modeling tools, as they can pro-
vide more quantifiable and accurate information for develop-
ing effective State Implementation Plans (SIPs) for compli-
ance with Environmental Protection Agency (EPA) and the
Texas Commission on Environmental Quality (TCEQ) AQ
standards. Texas, however, has become more compliant with
EPA regulations. Although we present a regional study fo-
cused on Texas (and locals therein), it has global implications
for regions within countries that have AQ mandates.
Specifically, states/regions around the world that have AQ
controlled by a particular agency should consider utilizing
data assimilation (of in situ data) for AQ prediction as a part
of the political/governmental process to produce such laws. A
prime example is illustrated in a recent study by Lin et al.
(2014); they show that Chinese air pollution related to produc-
tion for exports contributes, at a maximum on a daily basis,
12–24 % of sulfate pollution over the western USA. The US
outsourcing of manufacturing to China might have reduced
AQ in the western USA with an improvement in the east, due
to the combined effects of changes in emissions and atmo-
spheric transport. Therefore, science can provide a basis for
working with policy makers to create more contemporary AQ
laws that address not only local and regional AQ—but also
global AQ as well—to potentially keep locals more account-
able for emissions both locally and remotely without source
pollution biases.
These findings complement Pierce et al. (2009) and
McMillan et al. (2010). Both studies were participants in the
2006 TexAQS II from August 23 to 30, where one of its
primary goals was to assess the impact of distant sources of
AQ over high emission locals in Texas (e.g., Houston, Dallas,
and locations that are deemed ozone nonattainment areas).
Pierce et al. (2009) used ensemble Lagrangian trajectories to
identify and quantify the contribution of remote source re-
gions that impact continental-scale background contributions
of ozone production on Houston and Dallas, TX, AQ. Using
Real-time Air-Quality Modeling System (RAQMS) data and
Aura satellite data, they were able to provide estimates of
background composition along ensemble back trajectories.
Pierce et al. (2009) show that 66 % (6 out of 9) and ~50 %
(7 out of 15) of high ozone time frames were associated with
periods of enhanced background ozone production in Houston
and the Dallas Metropolitan Statistical Area, correspondingly.
Utilizing source apportionment studies, they show that 5-day
Lagrangian averaged O3 production minus loss in excess of
15 ppbv/day can occur during continental-scale transport to
Houston, owing to NOy enhancements from emissions within
the Southern Great Lakes as well as recirculation of the
Houston emissions. In regard to Dallas, its O3 production
minus loss is also associated with NOy enhancements from
emissions but is sourced from both Houston and Chicago.
McMillan et al. (2010) solely focused on remote
source contribution in east Texas. They utilized data
product retrievals of tropospheric CO from NASA’s
Atmospheric Infrared Sounder (AIRS), which revealed
CO transport from fires in the Pacific Northwest of the
USA to Houston. This transport happened behind a cold
front and contributed to the worst ozone exceedance
(~125 ppbv) time frame of the summer 2006 in
Houston. Given that EPA’s NAAQS for ozone (within
an 8-h averaging time) is 75 ppbv, this exceedance is
significant. McMillan et al. (2010) also used NASA A-
Train constellation observational data of the vertical dis-
tribution of aerosol smoke and CO, ground-based in situ
CO measurements in Oklahoma and Texas (to track the
CO plume), ground-based aerosol speciation and lidar
observations (did not indicate smoke aerosol transport),
MODIS aerosol optical depths, and model simulations
(indicated the transport of some smoke aerosols from
the Pacific Northwest through Texas to the Gulf of
Mexico). Chemical transport and forward trajectory anal-
yses exemplified that AIRS envisioned CO transport, the
satellite determined plume height, and the timing of the
observed surface CO increases. The forward trajectory
simulations also revealed that the largest Pacific
Northwest fires likely had the most significant impact
on the ~125-ppbv exceedance.
Pierce et al. (2009), McMillan et al. (2010), and our find-
ings are consistent with aircraft-based estimates of back-
ground ozone contributions during TexAQS II (Kemball-
Cook et al., 2009). They quantified that remote transport to
Houston (during four ozone exceedance days in 2006) con-
tributed to an average of 60 ppbv of ozone. Kemball-Cook
et al. (2009) used upwind aircraft measurements to deduce this
value. Overall, our study complements these previous inves-
tigations—that is, explicitly showing that remote transport
does contribute to background local AQ. The primary differ-
ence is utilizing a regional/local model tool to enable to quan-
tify the percent contribution of remote air transport toward
local AQ, especially during high-pollution exceedance
periods.
Acknowledgments We are thankful for the support, which funded the
investigation described herein, via Con-Edison (Grant # 1054322).
Conflict of interest None (or N/A).
STEM impact (i) Delisha Bella was an NSF-Louis Stokes Alliances
for Minority Participation (LSAMP) research mentee with me during her
junior and senior year at Medgar Evers College of the City University of
New York (MEC-CUNY); she completed two research internships while
at MEC-CUNY: one at University of Maine and another at the Medgar
Evers College Environmental Analysis Center; she received a B.S. in
Environmental Science (and a Chemistry Minor) and is now a Ph.D.
candidate at University at Albany’s School of Public Health. (ii) Jessica
Khaimova is an undergraduate Geology and Planetary Science B.S. major
at Brooklyn College-CUNY. Jessica completed two summer internship:
one during summer 2013 as a CUNY Summer Research Fellow and
another as an NSF-REU research mentee at Pennsylvania State
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21. University’s Meteorology Department and continues do research with my
numerical and planetary modeling. (iii) Johnathan Culpepper received his
B.S. in Environmental Science from MEC-CUNY and is currently a
Ph.D. candidate at University of Iowa’s Civil and Environmental
Engineering Department. (iv) Zayna King is a Biology major at MEC-
CUNYand is scheduled to complete an NSF-REU research internship at
Michigan State University’s Chemistry Department. (v) Shamika Gentle
was a high school researcher with me within ACS’s Project Summer
Research Internship Program for Economically Disadvantaged (SEED)
High School Students. Shamika Gentle is currently a Freshman
Chemistry major at SUNY at Albany, NY. (vi). Nabib Ahmed/Adam
Belkalai (Brooklyn Technical High School), Isabella Arroyo/Maxine
Lahmouh/Oren Jenkins (Khalil Gibran International High School),
Samori Emmanuel (Valley Stream South High School), and Julien
Andrews (Medgar Evers Preparatory High School) are rising juniors
and seniors whom participated in research for the first time. (vii) Jan
Gruszczynski is a freshman in high school in Lublin, Poland; all parties
continue to participate in STEM-related research projects encompassing
earth and planetary science.
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