JSRESA_SP2014_BRUNTON (1)

34 Journal of Student Research in Environmental Science at Appalachian
Distributions of Volatile Organic
Compounds in the Great Houston Area:
Influences of VOCs on Air Quality
Carley Brunton1, Yong Zhou2, Barkley Sive1,2
1Environmental Science Program, Appalachian State University, Boone, NC
2A.R. Smith Department of Chemistry, Appalachian State University, Boone, NC
estridgeke@appstate.edu
Abstract
Daily can samples were collected atop Moody Tower on the University of Houston’s
campus (Houston, TX) from January 28 to May 20, 2013. These samples were analyzed
for hydrocarbons, halocarbons, alkyl nitrates, several OVOCs, and select sulfur com-
pounds using a multichannel GC/FID/ECD and GC/MS analytical system. Temporal
distributions of selected VOCs were investigated. The average mixing ratios of total al-
kanes, alkenes, and aromatic hydrocarbons were determined to be 966 pptv,185 pptv
and 164 pptv respectively. Possible sources of the measured alkanes were identified
by comparing the slopes of the correlations of different trace gases with previously
reported emission ratios of these gases. The major sources of these analyzed gases
were associated with vehicular emissions. Ozone production potentials of the mea-
sured VOCs were calculated for the Houston, Texas area. Alkanes, alkenes, and aro-
matic hydrocarbons accounted for 30%, 48%, and 27% respectively of anthropogenic
OH reactivity. This study provides baseline information for future policies designed to
control emissions.
1.0 Introduction
Volatile Organic Compounds (VOCs), including
nonmethane hydrocarbons (NMHCs), are trace
gases in the atmosphere (e.g. [1]), and are of
concern for air quality regulators [2]. VOCs react
with oxidants such as the hydroxyl radical (OH)
in the atmosphere to create secondary air pol-
lutants, including ozone and secondary organic
aerosols (SOA) (e.g. [1,2]). Ground level ozone is
a major component of photochemical smog and
has adverse effects on human health, including
ear and lung complications, eye irritation, respi-
ratory problems [www.epa.gov], vegetation and
materials [1,3]. Aerosols can also have adverse
health effects, such as cardiovascular, respiratory
and allergic diseases [4]. VOCs such as benzene,
toluene, and xylene are classified as toxic air pol-
lutants [www.epa.gov].
In 2006, Houston was one of the regions in
the U.S that was failing to meet the National Am-
bient Air Quality Standards (NAAQS) of 120 parts
per billion (ppb) (1 hour average) for ozone [2].
Characterizing the atmospheric distributions,
identifying sources of VOCs, and understanding
their contributions to ozone production may in-
form policies to reduce emission sources, reduce
toxic air pollutants, and help control ozone and
aerosol concentrations in the Houston area.
In this study, measurements of VOCs were
conducted in Houston, TX. Canister samples
were collected at approximately noon each day
atop Moody Tower from January 28 to May 20,
2013. The temporal distributions of VOCs were
presented in a time series. Sources were studied
using correlations between different gases and
their reactivity with the OH radical were calcu-
lated to help determine the potential for ozone
production from these gases.
2.0 Methods
The University of Houston is located in the city
of Houston, TX. Houston is surrounded by In-
terstate 45, residential areas along with heavy
industrial and commercial areas, and is located
in the southeastern part of the state, about 60
miles from the Gulf of Mexico. Moody Tower

Volume 4, 1st Edition • Spring 2014 35
(29.717605°, -95.342307°) is an 18-story dormi-
tory on campus, where the air samples were col-
lected. The tower is surrounded by the Houston
campus, on all sides and is 5 miles from central
downtown. A canister sample was collected
around noon (local time) each day at the top of
the Tower from January, 28 to May 20, 2013. Be-
fore sampling, the 2-liter electropolished stain-
less steel canisters were flushed with ultra-high
purity (UPH) helium that was passed through
an activated charcoal/molecular sieve (13X) trap
immersed in liquid nitrogen and were evacuated
to 10-2 torr (e.g. [1]). When sampling, the valve of
the canister was opened until the canister was
filled with ambient pressure, and then closed.
The 113 electro-polished canisters were sent
to Appalachian State University in Boone, NC and
analyzed within 2 weeks after they were filled.
The air samples were analyzed for hydrocarbons,
halocarbons, alkyl nitrates, several OVOCs and
selected sulfur compounds.
Details of the analytical system and proce-
dures are given in [1, 5, 6]. Briefly, a three gas
chromatographic (GC) system equipped with
two flame ionization detectors (FID), two elec-
tron capture detectors (ECD), and a mass spec-
trometer (MS) were used for analysis of each
sample. For each sample, a 1275 cm3 (STP) ali-
quot of air was trapped on a glass bead-filled
loop immersed in liquid nitrogen. After the sam-
ple was trapped, the loop was isolated, warmed
to 80 C and injected.The carrier gas (UHP helium)
flushed the contents of the loop and the stream
was split into five, with each sub-stream feeding
a separate GC column/detector pair as follows:
(1) a CP-Al2O3/Na2SO4 PLOT connected to an FID
was used to measure C2-C7 NMHCs; (2) a VF-1ms
column connected to an FID measured C4-C10
NMHCs; (3) A CP-PoraBond Q column coupled
with a Restek XTI-5 column connected to a FID
was used to measure selected OVOCs; (4) an OV-
1701 column connected to an ECD was used to
measure C1-C5 alkyl nitrates and C1-C2 halocar-
bons; (5) an OV-624 column connected to an
MS measured C6-C10 NMHCs, C1-C2 halocarbons,
selected OVOCs and reduced sulfur compounds.
Two whole air standards were analyzed alter-
nately every 12 runs using the same analysis pro-
tocol as that used for analyzing the air samples.
Response factors for each gas were calculated by
dividing detector response values (peak areas)
by mixing ratios of the compounds in the stan-
dards (e.g., 1, 5, 6]). The mixing ratios of gases in
the samples were then calculated from the re-
sponse factors and the peak areas. The measure-
ment precision represented by the relative stan-
dard deviation (RSD) of the peak areas for each
compound in the whole air standards were 15%
for halocarbons, 1-8% for the NMHCs, 3-8% for
the alkyl nitrates, 3-5% for the sulfur compounds
,and 8-10% for the OVOCs [7].
3.0 Data
Figures 1 a-f show the time series of ethane,
propane, isobutene, n-butane, isopentane, n-
pentane, n-hexane, ethene, propene, 1-butene,
ethyne, benezene, toluene, ethylbenzene, m+p
xylene, and o-xylene measured daily at about
noon local time at Moody Tower in Houston,
TX from January 28 to May 20, 2013. The statis-
tics for more gases measured in this study are
listed in Table 1. For all gases, except isoprene
and α-pinene and β-pinene, the average mixing
ratios were higher in February and March than
April and May. Figures 2 a-c show the correla-
tions between n-butane and i-butane, n-pentane
and i-pentane, benzene and ethyne, toluene and
benzene, which help determine the source of
these gases. OH reactivities were calculated for
all the trace gases to evaluate their potentials for
ozone production in the Houston area (Table 2).
4.0 Results and Discussion
4.1 Temporal Distributions
Ethane and propane track each other very close-
ly (Figure 1a). The correlation of these two gases
was strong (R2 = 0.93), suggesting that they are
from common sources. The average mixing ra-
tios were measured to be 4651 pptv for ethane
and 2599 pptv for propane (Table 1). These val-
ues were about 2-3 factors higher than the mea-
sured values at Thompson Farm (TF), in Durham,
NH (rural site), during February to May (2004-
2008) (ethane: 1953 pptv and propane: 868 pptv)
[1], indicating urban influences in Houston.
For ethane and propane as well as the other
gases reported here, except for the biogenic iso-
prene, and α-pinene and β-pinene (Table 1), the
average mixing ratios were higher in February
and March than April and May, which is associat-
ed with photochemical processing. Photochemi-
cal removal of most VOCs increases in warm sea-
sons with increased OH concentrations [1].
Isobutane and n-butane also track each other
very well throughout the timeframe of the study

Figure 1-b. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.
Figure 1-a. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.
Figure 1-c. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.

Figure 1-d. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.
Figure 1-e. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.
Figure 1-f. Time series of VOCs (pptv) in Houston, TX between January 28 – May 20, 2013.

(Figure 1b), suggesting they are from the same
or similar sources.The correlation between these
two gases was strong (R2= 0.76) but weaker than
that of ethane and propane. During the study,
the average mixing ratios were analyzed to be
657 pptv and 1348 pptv for isobutane and n-
butane respectively (Table 1). These values were
significantly higher than those observed in TF,
where the average mixing ratios for i-butane and
n-butane were measured to be 150 pptv and 256
pptv respectively [1].
Isopentane and n-pentane as well as n-
hexane also track each other very well (Figure
1c). The correlation between i-pentane and n-
pentane is robust (R2 = 0.91). The correlations
between i-pentane and n-pentane vs n-hexane
were weaker with R2 value ~0.72. This could be
because of their slightly different photochemical
lifetimes; the lifetimes of the pentanes and n-
hexane are ~3 and 2 days respectively [8].The av-
erage mixing ratios for these gases are 624 pptv,
393 pptv, and 156 pptv for i-pentane, n-pentane,
and n-hexane (Table 1). These values were 5
magnitudes higher than those measured previ-
ously at TF. The average mixing rations of i-pen-
tane, n-pentane, and n-hexane were measured
to be 107 pptv, 62 pptv and 26 pptv respectively
during Feburary to May (2004-2008) at TF [1].
Ethene, ethyne, and benzene also track each
other throughout the period of the study (Figure
1d). However, the correlation between ethene
and ethyne (R2 = 0.25) and between ethyne and
benzene (R2 = 0.36) were weak. The regression
lines might be affected by some outlier data
points that could be associated with fresh emis-
sions. Also, the relatively weaker correlations
may reflect the different photochemical lifetimes
of ethene (~1 day), ethyne (15-30 days), and ben-
zene (~12 days) [8]. The average mixing ratios
for these gases are 836 pptv, 731 pptv, and 171
pptv for ethene, ethyne, and benzene respec-
tively (Table 1), which were higher than those at
TF (ethene: 333 pptv, ethyne: 480 pptv, and ben-
zene: 110 pptv).
Although toluene (lifetime: ~2.4 days) and
ethylbenzene (~7 hour lifetime) track each other
over the sampling months, the correlation was
weak (R2 = 0.36) (Figure 1e). The average mixing
ratios were 233 pptv and 40 pptv for toluene and
ethylbenzene respectively. The correlation of
m+p xylene with o-xylene is R2 = 0.64, meaning
they are most likely from the same source (Fig-
ure 1f). The average mixing ratios are 225 pptv
for m+p xylene and 113 pptv for o-xylene. To
put these gases in perspective, the average mix-
ing ratios of toluene, ethylbenzene, m+p xylene
and oxylene were 99 pptv, 13 pptv, 14 pptv, and
8 pptv, respectively, at TF. The elevated mixing
ratios observed at this study clearly reflect abun-
dant urban influences on the air mass composi-
tion.
4.2 Source relationship of VOCs
Atmospheric VOCs have a variety of sources.
The sources of i-butane, n-butane, i-pentane,
and n-pentane include vehicular exhaust, fuel
evaporation, LGP, and natural gas while the ma-
jor sources of ethane, ethyne, benzene, toluene,
and xylenes are incomplete combustion of fos-
sil fuels, biomass burning, and vehicular exhaust
emissions (e.g. [1]).
The sources of measured VOCs can be ob-
tained by comparing the ambient ratios of the
different compounds with emission ratios of
these compounds (Table 3). In this study, the
slope of the correlation between n-butane and
i-butane was 0.43 (Figure 2a) and was within the
range of many reported emission ratios from
several different sources, including: vehicular
exhaust (~0.2-0.3), LPG (0.46) and natural gases
(~0.6 to >1) (B. Sive, unpublished data; [1] and
references therein). Iso-pentane is a component
of gasoline and is elevated relative to n-pentane
[9]. The slope of the correlation between n-pen-
tane and i-pentane (1.54, Figure 2b) was within
the range of reported emission ratios for liquid
gasoline (1.5-3) and fuel evaporation (1.8-4.6),
but lies outside the ratios observed for vehicular
exhaust (~2.2-3.8) ([1] and references therein).
Ethyne, benzene, and toluene have similar
sources, principally vehicular exhaust. The ben-
zene and ethyne correlation had a slope of 0.31
(Figure 2c) which falls into the emission ratio of
vehicular exhaust. Toluene reacts more rapidly
with OH than benzene [8]. The ratio of toluene to
benzene is an indicator of automotive and urban
emissions. The slope of the correlation of tolu-
ene and benzene is 1.5 (Figure 2d), higher than
reported values (~0.6 – 1.1) at Boulder Atmo-
spheric Observatory, Wield, CO [7], a semirural
site, suggesting more fresh influence on vehicu-
lar emissions.
These results suggest that a mix of emissions
from alkanes and aromatic VOC sources is ob-
served in the Houston area, but they are mostly
involving vehicular emissions.

Table 1. Field data collected at each sampling period. NDC=No Data Recorded.
ethane ethene propane propene i-butane n-butane ethyne t-2-butene 1-butene c-2-butene
January Mean 3330.8 335.5 2407.7 124.1 578.8 1615.1 355.2 11.4 19.3 8.9
Median 3453.3 327.7 2786.7 102.1 580.4 1353.1 353.9 8.6 14.3 5.6
Max 4904.3 458.5 3601.3 231.4 1018.9 3199.9 494.6 20.3 35.3 16.8
Min 1512.5 227.9 456.2 60.9 135.4 554.2 218.3 5.5 13.3 4.3
RSD 43.0 28.6 57.7 61.5 65.2 70.6 39.4 68.3 55.3 77.1
February Mean 5656.5 1066.3 3538.8 465.2 959.9 2046.8 1064.7 20.8 69.6 17.6
Median 5205.1 549.6 3158.1 159.8 807.2 1625.3 604.2 11.4 28.9 8.6
Max 11670.0 7437.8 7036.9 3436.1 2990.8 6760.4 15467.7 91.2 452.8 77.1
Min 43.0 28.6 57.7 28.7 65.2 70.6 39.4 0.0 0.0 0.0
RSD 49.5 144.8 51.8 167.3 72.8 62.0 244.7 117.1 147.2 126.3
March Mean 4901.0 677.0 2764.6 236.7 617.1 1549.0 685.9 9.7 28.4 8.9
Median 5011.9 505.5 2571.1 106.6 512.9 1276.1 543.9 7.1 19.7 6.6
Max 10043.6 2508.7 7630.2 1332.3 2175.5 5578.8 2680.8 56.9 113.4 36.7
Min 1860.2 162.7 531.8 32.9 89.9 271.8 292.5 0.0 6.6 0.0
RSD 47.6 83.7 68.2 147.9 82.6 82.0 76.4 128.1 89.5 93.4
April Mean 3579.9 730.3 1754.3 218.3 430.6 741.0 505.6 7.8 39.1 7.8
Median 3463.1 696.8 1552.6 193.1 394.9 657.6 434.3 5.7 25.9 7.0
Max 7281.3 1310.5 3975.0 964.3 1326.7 1596.1 1294.4 31.7 253.5 20.2
Min 1165.4 290.3 329.2 61.7 107.2 253.8 189.9 0.0 10.0 0.0
RSD 46.1 38.6 61.0 86.7 66.4 56.7 50.3 95.3 123.3 64.2
May Mean 3417.0 648.2 1674.8 178.6 408.5 618.0 422.0 6.8 45.3 6.5
Median 3159.3 605.2 1333.7 154.8 320.4 491.1 387.2 3.1 23.0 4.4
Max 6523.3 1548.6 3663.2 492.0 1365.3 1408.6 1064.6 28.8 379.2 32.2
Min 750.1 280.0 230.6 34.0 52.9 110.5 105.0 0.0 0.0 0.0
RSD 47.6 57.0 69.0 64.6 84.6 71.2 54.9 127.4 188.2 116.7
cyclopen-
tane
i-pentane n-pentane n-hexane isoprene n-heptane benzene toluene benzene n-hep-
tane
January Mean 31.0 495.6 446.3 165.6 18.2 56.8 115.5 75.3 116.3 58.2
Median 28.4 400.5 302.7 100.3 18.8 37.3 118.2 90.7 114.9 47.2
Max 48.5 973.3 1098.1 425.6 28.8 116.9 133.3 108.2 156.9 97.3
Min 18.5 208.3 81.6 36.4 6.4 35.7 94.9 11.7 78.3 41.1
RSD 43.1 67.6 100.2 106.2 51.2 70.6 16.7 58.4 27.8 45.0
February Mean 40.7 760.4 542.4 245.3 30.1 83.4 218.9 257.8 208.0 84.6
Median 33.7 567.1 423.3 165.6 17.2 56.8 175.7 178.8 164.2 61.4
Max 134.1 3090.9 1647.0 817.6 238.1 370.9 812.6 1165.4 604.4 373.5
Min 12.1 67.6 81.6 36.4 3.2 4.6 16.7 11.7 27.8 8.6
RSD 66.2 79.3 68.3 87.5 158.2 88.1 72.3 107.3 66.5 88.2
March Mean 31.2 708.0 492.0 147.6 24.3 71.6 171.3 204.8 182.6 65.3
Median 21.2 424.1 324.0 101.7 10.3 39.9 141.4 151.8 153.1 45.0
Max 160.0 4829.0 3038.1 584.3 277.3 508.2 581.1 940.8 595.1 213.9
Min 8.0 123.3 56.0 23.2 0.0 0.0 73.5 34.1 59.5 8.8
RSD 102.6 130.9 118.4 104.3 212.2 144.9 73.3 98.0 74.4 83.6
April Mean 21.0 450.6 242.5 98.9 78.0 45.3 138.4 191.8 131.9 46.7
Median 18.5 378.3 190.1 77.8 50.3 40.5 124.8 156.8 117.9 43.1
Max 81.6 2496.6 1335.5 249.9 226.5 148.0 318.2 512.4 302.6 174.2
Min 10.5 147.3 61.9 23.7 12.6 0.0 63.0 58.0 64.8 5.5
RSD 67.4 99.0 99.8 66.1 77.3 77.6 38.1 66.6 40.4 78.2
May Mean 19.4 459.9 203.0 98.3 169.1 36.2 110.3 267.6 111.8 49.6
Median 17.0 279.0 168.5 84.5 113.4 30.0 115.3 161.0 106.1 32.3
Max 40.8 2207.8 498.5 303.4 750.1 142.8 243.5 1580.7 294.8 144.3
Min 8.4 104.3 41.3 19.7 3.6 0.0 33.1 16.5 27.5 4.0
RSD 51.5 115.0 70.7 76.8 109.1 92.2 49.0 138.6 59.0 78.4
4.3 Potential Ozone Production
Volatile organic compounds have many air qual-
ity concerns, including having the potential to in-
crease ozone production (e.g., [7]. Ozone is a pol-
lutant that can cause respiratory and inflammation
issues such as asthma [www.epa.gov].The hydroxyl
radical (OH), in the presence of nitrogen oxides, ini-
tiates ozone production by the oxidation of VOCs.
By determining the OH reactivity (OHR) of each
VOC, a measure of potential ozone production can
be associated with them [7].
OHR= ∑ [VOC]i × kVOCi+OH (1)
[VOC]i is the concentration of each VOC, kVOCi+OH is
the reaction rate constant for eachVOC with OH [8].
The mean OHR of VOCs was determined to be
1.56 ± 1.22 s-1 (Table 2) with a range of 0.27 – 6.69
s-1. The OHR was dominated by anthropogenic
VOCs (72%). Excluding biogenic VOCs, the mean

Table 1, continued. Field data collected at each sampling period. NDC=No Data Recorded.
toluene n-octane ethylbenzene m+p-xylene styrene o-xylene a-pinene b-pinene MeONO2
January Mean 116.2 36.0 12.8 97.2 116.6 28.4 57.2 56.7 3.8
Median 104.0 38.6 12.8 80.7 116.6 30.0 57.2 43.5 4.3
Max 175.8 49.3 16.0 189.0 141.0 41.4 95.7 93.7 4.4
Min 80.9 17.8 9.6 38.3 92.2 12.4 18.7 32.8 2.3
RSD 35.9 40.6 35.4 66.8 29.6 51.6 95.1 57.4 26.6
February Mean 285.5 49.4 39.2 165.3 103.1 75.1 83.4 38.9 4.2
Median 229.6 42.9 31.8 97.2 64.1 47.2 57.2 29.3 3.7
Max 1243.3 126.6 249.2 958.7 550.1 373.6 446.9 134.3 26.6
Min 35.9 13.8 5.5 21.7 0.0 10.7 3.2 0.4 1.7
RSD 88.7 61.5 112.9 110.2 117.6 101.8 122.0 88.0 100.5
March Mean 236.8 41.1 47.9 190.1 57.0 90.0 105.1 25.9 2.9
Median 153.2 35.1 23.8 80.1 29.5 62.4 43.6 15.7 2.7
Max 1212.7 209.7 378.8 2350.2 495.1 536.3 1180.8 164.1 5.3
Min 18.5 5.3 3.0 18.6 1.2 12.9 9.0 0.0 1.0
RSD 104.3 98.3 162.8 227.6 176.4 113.5 223.3 134.9 38.1
April Mean 314.4 42.9 32.4 281.9 84.8 148.6 233.4 46.1 2.2
Median 266.4 38.2 29.2 226.9 65.4 83.8 104.2 33.7 2.0
Max 780.0 81.3 64.0 1025.8 353.0 514.5 1064.4 142.5 3.3
Min 104.8 15.6 12.0 44.7 7.1 24.2 23.8 8.1 0.8
RSD 51.0 51.0 52.1 79.3 99.4 93.9 128.0 83.3 28.3
May Mean 265.9 40.7 34.3 289.4 88.1 154.7 315.7 72.8 2.2
Median 199.9 32.0 28.9 173.4 58.7 97.9 171.6 47.9 2.2
Max 1054.6 129.0 102.6 1016.5 319.7 576.6 1174.8 238.9 3.2
Min 59.6 7.8 8.1 45.1 5.3 8.6 7.2 5.5 0.9
RSD 92.2 75.3 66.3 97.7 92.5 101.5 111.8 101.5 26.0
EtONO2 C2HCl3 2-PrONO2 1-PrONO2 C2Cl4 2-BuONO2 3-PenONO2 2-PenONO2
January Mean 4.0 4.1 14.6 2.1 20.8 24.8 5.3 8.8
Median 3.9 4.2 14.4 1.9 16.7 23.4 5.6 9.3
Max 5.5 5.3 21.2 3.1 38.7 39.8 8.5 14.1
Min 2.7 2.5 8.5 1.6 11.1 12.4 1.5 2.4
RSD 29.5 30.6 36.1 30.3 60.1 45.8 54.9 55.5
February Mean 5.8 8.5 19.8 3.4 26.1 34.7 10.1 16.1
Median 4.7 4.8 19.5 2.4 19.1 30.0 8.0 14.1
Max 29.5 43.3 41.7 30.3 79.0 69.5 54.9 55.5
Min 2.7 1.4 1.0 1.0 5.1 12.4 1.5 2.4
RSD 80.1 110.7 48.2 145.6 69.5 43.4 91.7 66.6
March Mean 4.9 4.3 19.3 2.3 17.4 30.4 7.2 12.2
Median 4.7 2.4 19.4 2.2 13.0 31.0 7.4 12.9
Max 7.9 29.2 37.1 3.9 69.6 58.5 16.6 30.5
Min 1.6 0.3 1.1 0.8 5.2 14.8 0.9 2.1
RSD 28.3 135.5 40.6 32.2 90.7 37.4 53.1 55.5
April Mean 4.6 3.4 17.0 1.8 20.4 23.5 6.1 10.4
Median 4.1 1.7 16.1 1.9 13.2 22.3 6.0 9.5
Max 7.1 15.0 33.7 3.8 65.8 49.1 14.3 27.0
Min 2.8 0.4 5.7 0.0 5.7 6.0 1.2 1.8
RSD 24.0 106.8 38.8 45.5 84.6 45.7 56.7 56.1
May Mean 4.3 3.1 14.3 1.5 29.6 18.2 4.9 8.5
Median 4.2 2.7 15.4 1.4 25.2 15.9 4.8 6.7
Max 7.1 9.2 28.2 3.2 64.5 40.5 11.6 19.6
Min 2.1 0.8 1.2 0.0 7.5 2.7 0.5 0.7
RSD 33.8 80.2 52.4 67.1 67.7 60.6 64.2 66.2
OHR of VOCs was 1.14 ± 1.00 s-1. The alkanes,
alkenes, and aromatics accounted for 30%, 48%
and 27% respectively, of the anthropogenic OHR.
Although, alkanes (∑ average = 10553 pptv) had
a higher mixing ratio than alkanes (∑ average =
1200 pptv), alkenes contributed more ozone pro-
duction than alkanes. This is because the alkenes
react faster with the hydroxyl radical compared
to the alkanes. Because the major source of al-
kenes is automotive exhaust, the highest contri-
bution of alkenes to potential ozone production
is likely attributed to vehicular exhaust in the
Houston area. Although refineries may also be a
source, vehicular exhaust remains dominant.The
reduction of vehicular VOC emissions, especially
alkenes, could be important for air quality in the
greater Houston area.
5.0 Conclusions
A variety of VOCs were measured at Moody Tow-
er in Houston,TX area from January 28 to May 20,
2013. The mixing ratios of VOCs were generally
higher than those measured at rural areas, be-
cause of the widespread urban influences. These

Figure 2. Correlations between selected VOCs (pptv).
trace gas measurements exhibited higher aver-
age mixing ratios in February and March than
April and May; this is likely a result of seasonal
trends of emissions and photochemical process-
ing, i.e, the seasonality of OH radical. By using
correlation plots, sources were determined to be
mostly vehicular emissions in the Houston area.
The potential ozone production as reflected
by the OHR value was determined to be 1.56 ±
1.22 s-1, with 72% of the OHR contributing to an
thropogenic VOCs. Alkenes accounted for 48%
of these anthropogenic OHR, suggesting that
reduction of vehicular VOC emissions could be
important for air quality in the Greater Houston
area.
Acknowledgements
Financial support for this work was provided by
the College of Arts and Sciences at Appalachian
State University, NC Space Grant New Investiga-
tor Program and the A.R. Smith Department of
Chemistry.
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Table 2. OH Reactivity (s-1) for VOCs.
Can # Date/Time Anthropogenic
OHR
Biogenic
OHR
Total
OHR
Can # Date/Time Anthropogenic
OHR
Biogenic
OHR
Total
OHR
1823 1/28/13 12:02 1.1 0.3 1.3 1426 3/27/13 12:12 0.4 0.1 0.5
0516 1/29/13 11:58 0.7 0.2 0.9 0701 3/28/13 10:57 0.4 0.1 0.6
1327 1/30/13 12:09 0.5 0.0 0.5 9999 3/29/13 12:00 0.4 0.2 0.5
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1620 2/1/13 12:00 0.8 0.2 1.0 1130 3/31/13 12:12 0.4 0.1 0.5
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1318 2/3/13 12:18 1.0 0.0 1.1 1921 4/2/13 12:00 2.3 0.4 2.8
0922 2/4/13 12:00 0.6 0.1 0.7 1429 4/3/13 12:00 1.1 0.4 1.5
1323 2/4/13 12:06 1.8 0.2 2.0 0124 4/4/13 11:18 1.0 0.5 1.5
0422 2/5/13 12:00 - - - 1114 4/5/13 12:00 1.2 0.1 1.4
0910 2/6/13 12:00 3.6 0.4 4.0 1722 4/6/13 12:30 0.6 0.3 0.8
1403 2/7/13 11:55 6.2 0.4 6.6 2430 4/7/13 12:20 0.8 0.4 1.3
1109 2/8/13 12:00 1.1 0.1 1.2 0920 4/8/13 12:01 0.7 0.6 1.3
1320 2/9/13 12:32 1.0 0.1 1.1 1107 4/9/13 11:57 0.5 0.6 1.2
2324 2/10/13 12:14 1.1 0.6 1.7 0420 4/10/13 12:32 1.0 1.5 2.6
1209 2/11/13 12:05 3.5 0.2 3.7 1811 4/11/13 11:22 1.0 0.3 1.3
1627 2/12/13 12:00 5.9 0.8 6.7 0923 4/12/13 11:00 - - -
2323 2/13/13 12:08 0.9 0.0 0.9 1607 4/13/13 11:45 1.3 0.3 1.6
0607 2/14/13 12:15 2.6 0.2 2.8 0821 4/14/13 11:30 1.0 0.8 1.8
1417 2/15/13 12:00 2.0 0.1 2.0 1804 4/15/13 12:02 0.4 0.6 0.9
0820 2/16/13 12:20 0.7 0.0 0.7 1728 4/16/13 12:36 1.3 2.0 3.3
1112 2/17/13 12:00 0.3 0.0 0.3 1612 4/17/13 12:41 1.3 0.7 2.0
0214 2/18/13 12:34 0.8 0.2 0.9 1011 4/18/13 11:45 1.7 1.9 3.6
0203 2/19/13 12:03 0.9 0.3 1.2 2412 4/19/13 11:00 0.9 0.1 1.0
0509 2/20/13 12:02 1.8 0.2 2.1 0120A 4/20/13 11:00 1.0 0.3 1.3
1115 2/21/13 12:15 0.4 0.2 0.7 0225 4/21/13 11:25 0.7 0.2 0.8
0426 2/22/13 12:00 2.3 0.3 2.5 2121 4/22/13 11:20 0.7 0.3 1.0
0204 2/23/13 12:03 1.6 0.9 2.5 1110 4/24/13 11:35 - - -
1013 2/24/13 12:20 1.0 0.2 1.2 0413 4/25/13 11:05 0.9 0.2 1.0
2308 2/25/13 12:09 0.5 0.1 0.6 1330 4/26/13 11:00 0.8 1.3 2.1
1111 2/26/13 12:00 0.7 0.0 0.7 0228 4/27/13 12:20 1.0 0.8 1.7
2208 2/27/13 12:02 0.8 0.1 0.9 1717 4/28/13 11:45 1.5 0.4 1.9
1828 2/28/13 12:12 0.8 0.4 1.3 1317 4/29/13 14:06 0.6 0.4 1.0
2229 3/1/13 12:00 0.7 0.1 0.8 1302 4/30/13 10:20 0.5 0.2 0.7
1304 3/2/13 12:30 0.6 0.0 0.6 2407 5/1/13 11:18 1.7 1.6 3.3
0113 3/3/13 12:00 1.1 0.1 1.3 0525 5/2/13 11:24 1.1 1.1 2.2
2309 3/4/13 12:00 0.5 0.2 0.7 2528 5/3/13 11:46 0.6 0.3 0.9
9060 3/5/13 12:03 - - - 1621 5/4/13 12:05 0.4 0.2 0.5
1106 3/6/13 12:03 1.0 0.1 1.1 2523 5/5/13 11:45 0.6 0.2 0.8
0120 3/7/13 12:15 1.3 0.7 2.0 2313 5/6/13 11:25 0.7 1.9 2.6
1805 3/8/13 12:00 1.0 0.9 1.9 1219 5/7/13 11:40 1.3 0.5 1.8
0522 3/9/13 12:00 1.4 0.1 1.4 1006 5/8/13 12:30 0.5 1.0 1.5
2132 3/10/13 12:00 0.9 0.1 1.1 1724 5/9/13 11:13 1.3 2.4 3.7
1128 3/11/13 12:35 0.4 0.0 0.4 2508 5/10/13 12:05 2.2 0.6 2.7
1124 3/12/13 11:04 2.5 0.1 2.6 2106 5/11/13 11:43 - - -
1127 3/13/13 11:22 2.9 0.1 3.0 0222 5/12/13 11:00 1.8 0.6 2.4
0105 3/14/13 12:15 0.6 0.2 0.8 1015 5/13/13 11:00 0.8 0.5 1.3
0210 3/15/13 12:10 0.6 0.1 0.7 1618 5/14/13 12:15 0.4 0.4 0.8
1820 3/16/13 11:44 0.2 0.0 0.3 2111 5/15/13 12:40 - - -
1314 3/17/13 12:03 0.5 0.2 0.8 0416 5/16/13 11:08 0.5 1.1 1.6
1911 3/18/13 11:37 0.4 0.1 0.5 2011 5/17/13 12:15 - - -
2507 3/19/13 12:30 1.1 0.4 1.5 1605 5/18/13 10:30 1.2 2.5 3.7
1512 3/20/13 12:20 - - - 1101 5/19/13 12:04 0.6 1.1 1.7
0514 3/21/13 11:54 - - - 1408 5/20/13 11:44 0.3 1.4 1.7
0806 3/22/13 12:00 0.6 0.3 0.9 0906 0.6 0.1 0.6
1720 3/23/13 11:35 4.5 2.0 6.6 Mean 1.1 0.5 1.6
1718 3/24/13 12:10 1.4 0.1 1.5 Max 6.2 2.5 6.7
1309 3/25/13 12:01 1.1 0.1 1.2 Min 0.2 0.0 0.3
0425 3/26/13 12:02 0.9 0.1 1.0 stdev 1.0 0.5 1.2
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