Introduction
Oil and natural gas (O&NG) production in the US has grown significantly
over the past decade and is expected to continue to grow through 2020 (US EIA
(Energy Information Administration), 2014). Improved production methods such
as hydraulic fracturing and horizontal drilling technologies have enabled
O&NG producers to access reservoirs that previously were economically
infeasible (US Department of Energy, 2009). The US EIA (2012) estimates an
increase in shale gas production from 5.0 trillion cubic feet (tcf) per year
in 2010 to 13.6 tcf per year by 2035, when shale gas is expected to account
for half of total US gas production. Some of this new development is
scheduled to take place in Wyoming, an energy rich state, ranked second in
the US in total energy production for the 2012 data. In terms of proven
natural gas reserves in the US for 2009, the Pinedale Anticline Project Area
(Pinedale Anticline) and the Jonah Field, both in the Upper Green River basin
(UGRB) of Sublette County, Wyoming, rank 3rd and 7th, respectively. These
fields are both in the top 100 of proven US reserves for oil, with the
Pinedale Anticline ranked 49th and Jonah ranked 65th (US EIA, 2010).
Adverse atmospheric impacts of the development and operation of O&NG
fields include emissions of methane, a potent greenhouse gas (Allen et al.,
2013; Karion et al., 2013; Brandt et al., 2014; Caulton et al., 2014). A
further concern is degraded local air quality, which can impact human health
and well-being (Adgate et al., 2014; Colburn et al., 2014; McKenzie et al.,
2012, 2014) through the emission of a range of air toxics and other
pollutants (Pétron et al., 2012; Field et al., 2014; Helmig et al.,
2014; Moore et al., 2014; Warneke et al., 2014) that can lead to the
subsequent photochemical production of ozone (O3) (Edwards et al.,
2013; Gilman et al., 2013; Oltmans et al., 2014).
Until recently, the formation of high levels of O3 in surface air was
considered to be a summertime phenomenon in polluted urban areas. The
discovery of O3 mixing ratios exceeding 100 ppbv in 2005 in the rural
UGRB in winter (Schnell et al., 2009), well above the pre-2008 National
Ambient Air Quality Standard (NAAQS) of 85 ppbv for the fourth highest 8 h
average, was therefore unexpected. Similar wintertime high O3 episodes
have subsequently reoccurred in the UGRB and, more recently, have also been
observed in the nearby Uintah Basin of Utah. At both locations, O3
formation has been directly linked to emissions from O&NG sources (Schnell
et al., 2009; Martin et al., 2011; Oltmans et al., 2014), although specific
details of the role played by non-methane hydrocarbons (NMHC) were initially
not fully appreciated. Studies show that development of elevated O3
mixing ratios requires significant snow cover to facilitate both a high
actinic flux and the formation of strong persistent shallow inversions.
Inversions lead to the build up of adequate amounts of volatile organic
compounds (VOCs) and oxides of nitrogen (NOx), the gaseous
precursors of O3. Episodes are most frequent later in winter
(January–March) when insolation is increasing, but before snow cover
decreases.
Since 2005, additional air quality network and meteorological monitoring
stations have been deployed throughout the UGRB to determine the extent of
O3 episodes and their characteristics. Modeling studies have also been
carried out (Carter and Seinfeld, 2012; Rappenglück et al., 2014). They
point to the need for more definitive information on both the distribution
and specific identity of O3 precursor VOC compounds. These monitoring
and modeling studies have led to significant progress in understanding the
mechanisms and critical reaction pathways for wintertime O3 formation,
but questions remain. Notwithstanding the apparent importance of HONO for
O3 production (Rappenglück et al., 2014), the exact roles played by
nitrogen-containing compounds and many individual VOCs, and, in consequence,
the behavior of their radical derivatives, remain to be clarified. Many of
these questions have recently been answered for the Uintah Basin (Edwards et
al., 2013, 2014), but the similarities and differences of wintertime O3
formation chemistry in the different basins remains to be determined.
When wintertime ozone, measured at Wyoming Department of Environmental (WDEQ)
monitoring stations in 2005 and 2008 in the UGRB, was first reported by
Schnell et al. (2009), the subtleties of photochemical production mechanisms
were not clear. Modeling studies of 2011 wintertime ozone in the UGRB by
Carter and Seinfeld (2012) and Rappenglück et al. (2014) have
demonstrated that ozone production is critically dependent upon NMHC. These
studies used some data from the University of Wyoming Boulder South Road
(BSR) site as model input together with other available data in the UGRB.
Here we present the entire speciated NMHC data set from BSR and explore
intra-species correlations to investigate sources. Rather than photochemical
modeling of ozone, we attempt to reconcile contributing emission sources with
observed speciated NMHC. We also show the relationship of species sub-groups
to O3 during days with active wintertime photochemistry. Specifically,
in this study we identify the most important speciated NMHC for O3
formation, and by using positive matrix factorization (PMF) source
apportionment (Brown et al., 2007; Buzcu and Fraser, 2008; McCarthy et al.,
2013) determine the relative contributions of various emission sources to
observed hydrocarbon levels.
Methodology
Figure 1 shows well locations and monitoring locations in the Pinedale
Anticline and Jonah Field developments. Table S2 in the Supplement gives more
details of these locations and other sampling sites employed in the study.
Summary statistics for the BSR site are given in Table S4. The UGRB, at an
elevation of approximately 2150 m m.s.l., is enclosed by the Wyoming
mountain range to the west, the Gros Ventre range to the north, and the Wind
River mountains to the northeast. To the south it broadens and opens onto
lower elevation plains and the Interstate 80 corridor. It is located in
Sublette County, Wyoming, where the population density, as reported by the US
Census Bureau (2010), is a sparse 2.1 people per square mile (0.8 per
km2). As the Pinedale Anticline and Jonah Field developments are both
ranked within the top 10 of wet gas fields for proven reserves in the US (US
EIA, 2010), the area has a high density of O&NG wells. Pollutant emissions
in the UGRB are almost entirely from O&NG activities (WDEQ, 2014a) with
minimal contributions from other sources (Schnell et al., 2009).
Map of study area including principal monitoring sites and locations
of oil and natural gas wells within the Jonah Field and the Pinedale
Anticline.
Measurements characterizing air quality in the UGRB were carried out in and
around the Pinedale Anticline. The principal monitoring site was at BSR, a
location that experiences surface air containing relatively well-mixed trace
gases representative of emissions from a variety of nearby O&NG
development sources. This site was first used in 2009 as a comparative site
(Soltis and Field, 2009) to the WDEQ Boulder site (BLDR). As shown in Fig. 1
BSR (2142 m m.s.l.) is located about 5 km to the southeast of BLDR
(2162 m m.s.l.) at a slightly lower elevation. Measurements of O3,
reactive nitrogen compounds (NO / NO2 / NOx), total
NMHC, methane (CH4), and carbon monoxide (CO) mixing ratios, and
standard meteorological parameters, were carried out continuously at BSR
during the winters of 2010/2011 and 2011/2012. Table S1 in the Supplement
lists the measurement uncertainties of these parameters and details of
instrumentation employed.
Total NMHC measurements employed a Thermo Scientific 55i back-flush gas
chromatographic system that provides direct measurements of CH4 and
total NMHC. The back-flush method provides a direct measurement of total
NMHC concentrations and this allows accurate and precise measurement of low
levels of total NMHC even if methane is at a much higher concentration.
The total NMHC peak consists of C2 to C11 compounds, with the
possibility of some C12 compound being captured. This upper range is due
to sample losses on the walls of transport tubing with the analyzer designed
for ambient sampling without a heated inlet (Francis, 2014). While the Thermo
Scientific model 55i analyzer measurement of total NMHC includes VOC
containing halogens, nitrogen and oxygen, the sensitivity is anticipated to
be lower for these classes compared to hydrocarbons. All compounds with
C-bonds are detected, with a generally greater relative sensitivity for
compounds with a higher number of C-H bonds. While sensitivity is
proportional to carbon number, the replacement of C-H bonds with other
functional groups typically results in a decrease in sensitivity.
Speciated NMHC analyses
Hourly online measurements of speciated NMHC were performed at BSR during
2010/2011. Discontinuous speciated NMHC measurements at BSR in 2011/2012 and
2012/2013 were carried out using canister sampling (Entech silonite 6 L
canisters). Similar discontinuous measurements were made at other locations
in all three winter periods (Fig. 1). Individual NMHC selected for this study
are listed in Table 1. They include 15 alkanes, 10 alkenes, two alkynes and
10 aromatics. In 2010/2011 and 2011/2012, canister samples from locations
other than BSR were collected for 24 h periods, except when co-located
diffusive samplers were concurrently deployed, when sample times were
extended to 72 h. The results of diffusive sampling are the subject of a
separate analysis to be reported elsewhere. Canister sampling duration was
controlled using an Entech CS1200E flow regulation system. Sites close to
emission sources were included in 2011/2012 and in 2012/2013. Table S2
provides geographic coordinates of the monitoring sites and lists the number
of samples at each site. Additional details are given elsewhere (Soltis and
Field, 2011a, b, 2012a, b).
Speciated NMHC measured with the Perkin Elmer Ozone Precursor
Analyzer.
Alkane
Alkene (&Alkyne)
Aromatic
Ethane
ethene (ethylene)
benzene
Propane
propene (propylene)
toluene
Butane (n-butane)
trans-but-2-ene (t-2-butene)
ethylbenzene
2-Methylpropane (i-butane)
but-1-ene (1-butene)
m+p-xylene
Pentane (n-pentane)
cis-but-2-ene (c-2-butene)
o-xylene
2-Methylbutane (i-pentane)
1,3-butadiene
styrene
Cyclopentane
pent-1-ene (1-pentene)
1,2,3-trimethylbenzene*
Hexane (n-hexane)
trans-pent-2-ene (t-2-pentene)
1,2,4-trimethylbenzene*
2-Methylpentane (i-hexane)
cis-pent-2-ene (c-2-butene)
1,3,5-trimethylbenzene*
3-Methylpentane
2-methyl-1,3-butadiene (isoprene)
Heptane (n-heptane)
Octane (n-octane)
ethyne (acetylene)
Cyclohexane
prop-1-yne (propyne)
Nonane
Decane*
* not reported during 2011–2012 or 2012–2013; during
2010–2011 indicative only.
Speciated NMHC analyses were carried out using a Perkin Elmer (PE) O3
Precursor Analyzer (OPA) system that incorporates a Peltier cooled inlet
adsorption sample concentrator within a TurboMatrix 300 Thermal Desorption
system, a Nafion® dryer to remove water
vapor, and a PE Clarus 500 Gas Chromatograph (GC) equipped with flame
ionization detectors (FIDs). The chromatograph utilizes two parallel columns
for the separate analysis of lower (C6 to C12) and more (C2 to
C6) volatile fractions in the sample. It was operated using ultrapure
helium as the carrier gas. Further details of the OPA system are given
elsewhere (Broadway and Tipler, 2012). During 2010/2011 canister samples were
analyzed at the BSR field site. Consistent quality of the two sampling
methods was ensured through recovery testing using span and zero gases. In
2011/2012 and 2012/2013, only canisters were used for sample collection,
which were subsequently analyzed with minimal delay by the OPA at the
University of Wyoming, using the same analytical protocol and data processing
methods as those employed at BSR, thereby achieving equivalent analytical
quality. Instrument calibrations were conducted with a custom trace gas
standard mixture supplied by Apel-Riemer Environmental, Inc. The mole
fraction of reported compounds ranged from 3.6 to 44.6 ppbv. Calibration
curves that encompassed the entire measurement range encountered in the field
were achieved through varying the trapping time for analysis. Table S1 in the
supplementary material lists the measurement uncertainties calculated for
this study. Further details of monitoring sites, experimental sampling
protocols, analytical instrumentation, and analysis techniques are given in
the supplementary material, and by Soltis and Field (2011a, b, 2012a, b).
Data processing
The output data from the OPA were processed and validated with a data
management system provided by Ricardo-AEA, Ltd., UK. This system, used by the
UK Automatic Hydrocarbon Network for more than 20 years (Dollard et al.,
1995), analyzes batches of multiple chromatograms to yield an output file
containing compiled time-stamped validated data that include peak areas,
widths, and retention times, for identified chromatogram eluents in each
analyzed sample (Dernie and Dumitrean, 2013). Initialization of the
processing software requires template calibration information that provides
comparator data for the input chromatograms, which in this study were grouped
into 1-month-long periods. Proprietary artificial intelligence (neural
network) pattern recognition MatchFinder®
software was employed to identify specific hydrocarbon peaks in the monthly
batch analysis output files. Quality assurance and control procedures
developed for the UK Automatic Hydrocarbon Network are then applied to ensure
that peaks are correctly identified and without co-elution or peak merging
issues (Derwent et al., 2014).
Conversion of chromatogram raw peak areas to mixing ratios was carried out
using response factors derived from calibration gas mixtures. Calibration
responses were proportional to carbon number (from C2 to C10) with
calculated accuracies given in Table S1. Response factor differences were
observed, however, for ethyne, isoprene, and 1,3-butadiene, due to slow
wall-induced heterogeneous loss of these compounds within the calibration gas
mixture cylinder. Consequently, relative response factors were used to
calculate mixing ratios of these gases. In addition, chromatographic problems
resulting from measurable “carry over” effects for decane, and the
trimethylbenzenes in successive analyses, resulted in the derived mixing
ratios for these compounds being removed from validated data sets used for
subsequent interpretive analyses of ambient atmospheric behavior. The quality
of validated data was demonstrated through a blind test of an unknown mixture
with the support of the National Center for Atmospheric Research (NCAR) shown
in Table S3.
Positive matrix factorization analysis of speciated NMHC
Positive matrix factorization (PMF) analyses of the BSR speciated NMHC data
have been carried out to determine emission source characteristics and
contributions. This analysis technique, developed by Paatero and
Tapper (1994) and Paatero (1997), solves a bilinear receptor model that
assumes that the data set being analyzed is composed of contributions from a
small number of factors, each with an unknown but constant source profile,
that vary in magnitude with time. PMF analysis aims to evaluate the optimum
value of the chemical profile of each factor, and the mass contributions from
each factor. It provides results as factors, or groups of compounds, each of
which effectively constitutes a pattern or signature of an emission source or
group of sources. The final output is analyzed to determine how well modeled
results reproduce the input data by examining the residuals for each
compound, scatter plots for predicted and observed compound correlations, and
mass recovery. The multivariate factor analysis EPA PMF tool, widely applied
to ambient air quality data (Poirot et al., 2001; Song et al., 2001), was
used for analysis of the BSR speciated NMHC data for the period October 2010
through March 2011. Uncertainties in the solution are estimated using a
bootstrapping technique (Efron, 1982; Efron and Tibshirani, 1993; Norris et
al., 2008). Each resampled data set is decomposed into profile and
contribution matrices using PMF, and the results of each bootstrap run are
then compared with the base run. If the original, base-run factors are
consistently found or mapped with the resampled bootstrap runs, the factors
are considered to be robust and the data are not over-fit.
PMF receptor modeling relies on data with known quality and accuracy, as
measured by uncertainty. Uncertainties were calculated on both an absolute
and relative basis to account for method detection limits and peak fitting
imprecision. All speciated NMHC were assigned a conservative base uncertainty
of 0.1 ppbv, plus 3 % of the measured value of a given sample. For
example, a measured value of 1 ppbv would have an uncertainty of 0.13 ppbv,
while a measured value of 10 ppbv would have an uncertainty of 0.4 ppbv.
Compounds were removed from the analysis if their signal-to-noise
(S / N) ratios were below 1.3. Application of this criterion removed
1-butene, 1,3-butadiene, t-2-butene, c-2-butene, 1-pentene, isoprene,
propyne, styrene, and propene from the analyses. Four consecutive samples on
26 November 2010 were also excluded from analysis because they contained high
outlier values for toluene with values ranging from 28.5 pppv to
274.4 ppbv. Three outlier values for CO were removed on 23 November 2010.
These unrepresentative samples would not be effectively modeled using the PMF
statistical technique. In addition to speciated NMHC, hourly data for total
NMHC, background corrected CO, and background corrected CH4, were
included in the analyses. NOx is not included in the PMF analysis
presented here as the focus of this study is source apportionment of
speciated NMHC, and preliminary analyses revealed that NOx was
the only parameter in a separate factor.
Results and discussion
Temporal variation of O3, total NMHC and
NOx
WDEQ ozone measurements at the BLDR site commenced in 2005 and have been
performed continuously since then. They reveal numerous occasions when hourly
averaged O3 levels were at or above 75 ppbv, and several occurrences
during 2005, 2008, and 2011 when fourth highest 8 h average values also
exceeded 75 ppbv. In 2012, the UGRB was designated a non-attainment zone for
the National Ambient Air Quality Standard for O3. In 2011, daily 8 h
ozone averages exceeded 75 ppbv at BLDR on 8 days. Similar exceedances
occurred in 2011 at other UGRB WDEQ sites, albeit less frequently and at
slightly lower O3 levels. During 2011, measurements at BSR, also close
to the Pinedale Anticline O&NG development (see Fig. 1), corroborated
elevated ozone measurements at BLDR. At BSR, seven exceedances were observed
in 2011. Of note however, is that in contrast to the significant number of
ozone episodes in 2011, there were only 3 days in 2012 during the January
to March “ozone season” when the hourly average ozone mixing ratio exceeded
75 ppbv, and a complete absence of days with non-compliant 8 h ozone
averages. Figure 2 shows plots of hourly averaged mixing ratios of O3,
NOx, and total NMHC at BSR during the months January to March in
2011 and 2012. It is evident that both O3 episodes (hourly
O3 ≥ 85 ppbv) and high total NMHC values are significantly more
frequent in 2011 than in 2012, while NOx levels in these years
are similar.
Time series of O3, NOx, and NMHC at Boulder South
Road (BSR) for the period January through March during 2011 and 2012.
Species mixing ratios are influenced by their emission and/or formation
rate(s), their removal rate, and by meteorological factors affecting dilution
and dispersion. If meteorology were the only factor resulting in the
year-to-year NMHC and O3 differences shown in Fig. 2, then
NOx behavior should exhibit a similar pattern as NMHC.
Observations at BLDR show similar behavior as those at BSR (MSI, 2012), with
16 hourly values of total NMHC greater than 2 ppmC in 2011 compared to none
in 2012. In addition, a reduction in the average NMHC mixing ratio for the
January to March period was found at both sites, from 0.34 ppmC in 2011 to
0.19 ppmC in 2012 at BLDR, and from 0.23 to 0.07 ppmC at BSR. For
NOx, similar reductions in the analogous mixing ratios were also
observed, from 5 to 2 ppbv at BLDR and from 6 to 4 ppbv at BSR. These
mixing ratio reductions may be linked to estimated emissions reductions of
∼ 20 and ∼ 50 % for VOCs and NOx respectively,
reported in the winter emission inventory for Sublette County, from 2011 to
2012 (WDEQ, 2014a).
Snow cover and meteorological conditions, including temperature and wind
speeds, at both BLDR and BSR in 2011 and 2012 were broadly similar, with no
significant differences, suggesting that neither factor can solely account
for the observed mixing ratio differences (MSI, 2012). Moreover, 8 h average
mixing ratio O3 episodes were not only absent in 2012, but also in 2013
and 2014, at all UGRB sites, even though apparently favorable conditions
(snow cover extent, 700 mb pressure, temperature, and wind speed) for
O3 formation prevailed (MSI, 2012, 2013, 2014).
The weight of evidence suggests that the observed decreases in NMHC and
NOx mixing ratios and the concomitant lack of O3 episode
occurrence since 2011, likely result primarily from reduced O3 precursor
emission rates. However, factors associated with snow cover and
meteorological conditions cannot be entirely discounted, because they can
strongly affect ozone production rates. The influence of meteorology is
recognized to affect year-to-year variability of O3 levels. A lack of
O3 episodes in 2009 was for example linked with the absence of snow
cover.
O3 variations at BSR and BLDR
Similar O3 mixing ratios were observed at BSR and BLDR in 2009, 2010,
2011 and 2012 during spring, summer, and fall. In November and December 2011,
the average difference of hourly O3 measurements at the two sites is
3 ppbv, and when values at BLDR exceed 40 ppbv, only three measurements differ
from those at BSR by more than 10 ppbv, none of which occur during afternoon
hours. Similar behavior is found in November and December 2010. Afternoon
maximum O3 mixing ratios at the two sites are invariably similar. By
contrast, the behavior observed in months associated with wintertime O3
is different. For example, in February and March 2012, when O3 values
exceeded 40 ppbv at BLDR, 11 of the 12 measurements with a difference of
greater than 10 ppbv are in the afternoon, 4 of which occur when O3 is
higher than 70 ppbv at BLDR. Wintertime differences were even more apparent
in February and March 2011, when 91 afternoon hours differed by more than
10 ppbv, with 73 occurring when O3 was higher than 70 ppbv at BLDR.
In the winter of 2011, O3 episodes (average hourly O3 ≥ 85 ppbv) were observed on 13 days in the UGRB. Diurnal variations in
O3 mixing ratio observed at BSR and at BLDR (WDEQ, 2014b), located some
5 km to the northwest, are illustrated by the 24 h time-series plots on
four days in 2011 in Fig. 3. These plots indicate the effect of variability
in background levels, local production, and transport of O3 to the
different measurement sites. On 26 February 2011, when BSR O3 mixing
ratios increase by ∼ 60 ppbv, peak O3 at BSR exceeds that at BLDR
by ∼ 20 ppbv. However, on 1 March 2011, O3 increased by
∼ 120 ppbv at BLDR, but only by ∼ 70 ppbv at BSR. Similar
behavior is evident on 2 March 2011. Both of these days are associated with
light southwesterly winds. By contrast on 15 March 2011, O3 mixing
ratios behave similarly at both BLDR and BSR, except for a short
∼ 20 ppbv increase at BSR around 14:00. O3 behavior for all 13
episode days are given in Fig. S5.
O3 mixing ratios during four episodes at Boulder sites February to
March 2011.
Figure 2 plots suggest that high O3 levels in 2011 are promoted by
relatively high levels of total NMHC at relatively moderate NOx
levels. Understanding the observed differences in O3 episode variability
is perhaps best achieved by examining the detailed composition and mixing
ratios of the constituent NMHC, together with the concomitant levels of
NOx, at the two sites.
Relationship of O3 to NMHC and
NOx
Surface NMHC measurements from October 2010 to March 2011 show diurnal and
seasonal variations, with the highest values during the coldest months and at
night. Low surface temperatures in winter are associated with nocturnal
radiation inversions that lead to pollutant trapping and accumulation, and
consequential elevated mixing ratios (Schnell et al., 2009; Oltmans et al.,
2014).
An assessment of the fractional contribution of OPA detected hydrocarbons to
the total NMHC measured by the Thermo 55i instrument (Table S1) was
undertaken to understand the utility of total NMHC measurements, and to
determine the contributions of speciated NMHC selected for this study. To
achieve these aims, a mass balance comparison of the total NMHC to the sum of
the OPA identified speciated NMHC (C2 to C8) was performed. Total
integrated NMHC measured by the Thermo 55i includes both hydrocarbons and
their halogenated, oxygenated, and nitrogen-containing derivatives, up to
C11 compounds. The mass balance comparison between total NMHC and the
sum of the OPA identified speciated NMHC is shown in Fig. S6, for the period
October 2010 to March 2011. A simple linear regression fit to the 2320 data
points yields a best fit line of slope 0.57 and a coefficient of
determination (R2) of 0.90. While there is a strong correlation between
the two NMHC data sets, using only identified OPA NMHC omits ∼ 43 %
of the carbonaceous material included in the total NMHC measurement. Diurnal
analyses reveal no significant differences by time of day. A second analogous
comparison was carried out in which all of the unreported and unidentified
carbonaceous material detected by the OPA was included in the NMHC summation.
This additional material increased the mass from identified C2–C6
aliphatic hydrocarbons by a factor of 1.1, and that from identified
C7–C8 aliphatic and C6–C9 aromatic compounds by a
factor of 2.0. The augmented summation of speciated NMHC mass resulted in
both the slope and R2 values of the regression line increasing, to 0.88
and 0.92 respectively. Measurement uncertainties, as outlined in Table S1,
could account for the mass deficit implied by a regression fit slope less
than unity.
Wintertime measurements at BLDR from 2007 to 2014 reveal contributions of
∼ 70 % for alkanes, ∼ 15 % for aromatics, and
> 5 % each for naphthalenes, alkenes and oxygenates to the observed
VOCs (MSI, 2014). These measurements suggest that hydrocarbon classes
dominate the total mass of VOC in the UGRB. Contributions of oxygenated VOCs
not detected by the OPA are likely to be small, even though it is likely that
they play an important role in wintertime photochemistry (Edwards et al.,
2014), a contention supported by measurements of carbonyl compounds at BLDR
that suggests formaldehyde and acetaldehyde contribute significantly to VOC
reactivity (MSI, 2014).
Identified C2 to C9 compounds contributing most to the total carbon
NMHC mass measured by the OPA at BSR, namely ethane (26 %), propane
(15 %), toluene (11 %), m+p-xylene and p-xylene (7 %),
i-butane (5 %), and n-butane (5 %), make up 69 % of the
identified carbonaceous mass. Similarly, analyses of 16 canister samples
collected at BLDR in the winters of 2011/2012 and 2012/2013, during the Upper
Green winter O3 studies (UGWOSs) (MSI, 2012, 2013) show that the three
most important contributors are ethane (21 %), propane (19 %), and
toluene (8 %). The same dominant hydrocarbons are found at both
measurement sites indicating that the hydrocarbon composition at BSR and BLDR
is similar, as expected given their close proximity. This examination of the
relative contributions of identified hydrocarbons showed that while missing
mass is related to heavier NMHC, the most abundant NMHC in the C2 to
C8 range are reported.
Variations in the measured O3 mixing ratio together with changes in
total NMHC and NOx at BSR are shown in Fig. 4, constructed from
hourly averaged observations obtained between 11:00 and 20:00 during the
three-month winter period from January to March 2011. Highest O3 mixing
ratios are associated with total NMHC mixing ratios above 0.2 ppmC, when
NOx mixing ratios are 6–20 ppbv, and decrease significantly as
the mixing ratios of these precursors decline. As noted previously, O3
production only occurs when actinic flux levels are high, and when this
requirement is not met, O3 mixing ratios remain low, irrespective of
precursor concentrations. The data shown in Fig. 4 are undoubtedly influenced
by a number of environmental parameters including meteorology, actinic flux
intensity, and NMHC composition. An analogous plot constructed using BLDR
measurements is shown in the supplementary information (Fig. S7). It exhibits
the same trends evident in Fig. 4, but shows greater variability of
NOx for high ozone values (80–120 ppbv). Thus, unlike at BSR,
high O3 mixing ratios are occasionally observed at BLDR when
NOx is low. Reported NOx mixing ratios at BLDR
frequently display erratic hour-to-hour variability throughout the period
January to March 2011, during periods of both high and low O3 mixing
ratio. This suggests that the measurement uncertainties at BLDR may be larger
than at BSR, and allows for the possibility that the greater scatter evident
in Fig. S7 compared to Fig. 4 results from these uncertainty differences. The
figures reinforce the notion that high NMHC precursor mixing ratios are a
necessary but insufficient condition for O3 formation. Other factors, as
outlined above, must also be favorable. Thus for many daytime hours, there are
elevated precursor levels without high O3, suggesting that assuming
constant emissions rates, favorable meteorological conditions required for
O3 formation are absent. Conducive conditions for high rates of ozone
production were identified by WDEQ for ∼ 15 % of days in January
through March 2011 (MSI, 2011). While the thresholds of required precursor
mixing ratios, and consequently emissions, are as yet not determined
definitively, the ambient data presented here show the importance of elevated
levels of total NMHC to O3 formation.
O3, NMHC and NOx during daytime (11:00 to 20:00)
for the period January to March 2011 at Boulder South Road (BSR).
Source identification using PMF analysis
Hourly measurements at BSR, collected from October 2010 to March 2011, of
speciated NMHC, and other selected parameters, allowed PMF analyses that
explored the sensitivity of possible solutions for factor signatures of
emission sources to be carried out. Other parameters included CO (with
background subtracted), CH4 (with background subtracted), total NMHC
(measured by the Thermo Scientific model 55i analyzer) and NOx.
Preliminary PMF analyses showed that NOx generated its own
factor, unrelated to those for other species. As the analyses were primarily
designed to identify the sources of speciated NMHC, NOx was
excluded from subsequent analyses.
Possible solutions to the PMF analyses were obtained for contributions from
two, three, and four factors. Of these solutions, that for three factors was
selected, because it yielded factors that are associated with likely
emissions sources, was numerically stable using bootstrapping, and produced a
solution for which the coefficients of determination (R2) for all
predicted compounds are greater than 0.8, with 21 out of 24 compounds
predicted with R2 > 0.88. All solutions converged and were stable
over multiple runs, and bootstrapping in each of 400 runs reproduced the same
factor characteristics. The three-factor solution is also favored because
while factors 1 and 2 show a positive correlation, contributions from
factor 1, unlike those from factor 2, show no relationship to wind direction.
By contrast, the four-factor solution is not stable with respect to
bootstrapping, and the two-factor solution has significantly worse
coefficients of determination for reproducing individual compound mixing
ratios, with 15 of the 24 compounds predicted with R2 of < 0.88. The
percentage contributions of each of the three derived factors to the mixing
ratio of each constituent compounds are shown in Fig. 5.
The three PMF factor signatures each contain many common component compounds,
but at different abundance levels. As previously noted, factors are not
necessarily derived from specific emission sources, but can represent groups
of sources. Oil and gas developments have numerous continuous and
intermittent emission source types, many of which may well have their own
unique compositional emissions pattern. Some sources are known to be
difficult to quantitatively characterize and/or report, in particular
flow-back from well completions and evaporative losses from produced water.
Speciated NMHC emissions can, however, be broadly classified as emanating
from combustion, fugitive, or product handling sources, e.g., gas dehydration
and condensate evaporation. Emission inventory data for the Pinedale
Anticline development (February and March 2011 winter inventory) reveals that
∼ 90 % of total VOC emissions (∼ 400 t) are from “natural
gas leakage”, from source categories coded as tanks, dehydration units,
pneumatic pumps, and fugitives (WDEQ, 2014a). Of the estimated ∼ 70 t
of BTEX (benzene, toluene, ethylbenzene, m+p-xylene, and o-xylene)
emissions for the winter 2011 inventory, ∼ 50 t are assigned to
dehydration units, and ∼ 10 t are assigned as fugitive emissions.
Thus, based on the emission inventory, while VOC emissions are from many
leakage sources, BTEX emissions are dominated by natural gas dehydration.
Percentage contribution of PMF factors to the average mixing ratio
of each analyzed pollutant (-b signifies minus background) from the whole
sampling period at Boulder South Road (BSR).
Figure 5 illustrates the average contribution of each PMF factor to the total
derived mixing ratio for each compound across the entire monitoring period.
For CO, factor 1 provides the dominant contribution. For speciated C1 to
C6 non-aromatic hydrocarbons, factor 2 dominates; whereas in the heavier
hydrocarbon range (C≥7), up to o-xylene, factor 3 becomes dominant.
Benzene and ethyne are the only two hydrocarbons that have roughly equivalent
contributions from all 3 factors. The average percentage contribution of each
factor to the measured mass of total NMHC are ∼ 10, ∼ 50, and
∼ 40 %, for factors 1, 2, and 3, respectively. However, for the 14
speciated NMHC used for Fig. 6, this weighting is 25, 60, and 15 %,
respectively. Eight speciated NMHC are excluded from Fig. 6 as they are
reported as grouped rather than individual compounds within emission
profiles. The contribution of factor 3 weighting declines relative to the
other factors due to the absence of these individual reported NMHC species
(e.g., nonane). Furthermore, factor 3 is also associated with heavier
unidentified NMHC. Figure 6 compares factor profiles with selected emission
source profiles.
(a) Comparison of factor 1 with emission source profiles as
percentage contribution by mass for selected NMHC. (b) Comparison of
factor 2 with emission source profiles as percentage contribution by mass for
selected NMHC. (c) Comparison of factor 3 with emission source
profiles as percentage contribution by mass for selected NMHC.
Designation of factor 1 as combustion (traffic) is supported by the
significant contributions of background corrected CO, ethyne, benzene,
i-octane, toluene, and o-xylene, all characteristic of vehicle emissions.
Contributions from other engines are possible. However, the diurnal profile
for factor 1 shows a morning peak associated with peak traffic flow. Other
combustion sources, e.g., drill rigs and compressor stations, in the Pinedale
Anticline are reported to have relatively low CO emission rates while being
important sources of NOx (Litovitz et al., 2013). Of the three
factors, factor 1 displays the least variability, with maximum contributions
that are less than five times the average mass values, and also has the
lowest overall impact on O3 production, as discussed below. The profile
for factor 1 resembles a combination of background, measured at the boundary
of the UGRB, and traffic dominated profiles. The traffic profile in Fig. 6a
is derived from a combination of profiles of gasoline and diesel vehicle
exhaust (Schauer et al., 1999, 2002) with a weighting of 75 % diesel
derived from traffic surveys performed within the Pinedale Anticline and
Jonah Field developments during 2009/2010. While emissions from traffic are
likely to contribute to this factor, the roadside profile at the town of
Pinedale also differs somewhat from the distribution derived for factor 1.
This difference of factor 1 from profiles dominated by traffic is due to the
additional contributions related to factor 2. Such smearing is anticipated to
some extent from PMF analysis.
The “fugitive natural gas” designation for factor 2 is largely suggested by
the high contributions to its signature from background corrected methane,
ethane and propane. The distribution of its component compounds, which
closely resembles that for natural gas, includes significant contributions
from butanes, pentanes, and several of the compounds also found in factor 1
(e.g., ethene, ethyne, and benzene). For some emission plumes, factor 2 ranges
up to ∼ 14 times the average mass value. Compositional profiles for
natural gas are from the Wyoming Oil and Gas Conservation Commission (WOGCC)
for samples collected from 2001 to 2012 (WOGCC, 2014). The WOGCC averaged
profiles for 20 natural gas samples from both the Riverside and Mesa lease
areas of the Pinedale Anticline shown in Fig. 6b, are in good agreement with
each other and with factor 2, and clearly demonstrate that natural gas NMHC
composition is dominated by light (≤ C5) hydrocarbons.
Measurements carried out at 190 natural gas production sites in Appalachia,
the Gulf Coast, and the Midcontinent and Rocky Mountain regions of the USA,
indicate that at many sites pneumatic controllers and pumps are an important
source of fugitive gas (Allen et al., 2013). Measurements of fugitive gas in
the Pinedale Anticline, from 14 grab samples obtained in this study near
operating pneumatic pumps, were used to derive a fugitive emissions profile.
This profile, shown in Fig. 6b, matches WOGCC profiles of natural gas. The
gas profiles are very similar to factor 2. However, factor 2 has slightly
elevated contributions from BTEX, and this is likely due to emissions from
dehydration activities being coincident with those of fugitive natural gas.
Sources cannot be distinguished by PMF analysis when they are co-produced at
each well site; however, the compositional analysis shown in Fig. 6 clearly
identifies fugitive natural gas as the dominant emission source. While it is
impossible to differentiate emissions from specific well-pad components,
their identity is well known, e.g., pneumatic controllers and dehydration
units. Observations show that fugitive natural gas emissions have the
greatest impact on NMHC composition at BSR, with strong correlations between
many of the light hydrocarbons, as shown in Fig. 7 for methane, ethane,
propane, and n-butane.
The designation of factor 3 as “fugitive condensate” is supported by high
contributions from C7 to C9 compounds, in particular benzene,
toluene, ethylbenzene, and xylene isomers (BTEX). Factor 3 also includes
significant contributions from nonane, octanes, n-heptane, and cyclohexane.
The compound distribution closely resembles that for condensate, with the
largest contribution from toluene and m+p-xylene. The impact of this factor
on air samples measured at BSR were most evident during air flow from the
southwest. For some emission plumes, factor 3 reaches ∼ 42 times
average mass values. Also shown in Fig. 6c are WOGCC average profiles for
condensate, derived from 20 samples, all with very similar compositions, from
both the Riverside and Mesa lease areas. These condensate profiles are
dominated by heavier (> C5) NMHC constituents. This is also evident
for factor 3, but there are differences in relative contributions. These
differences suggest the presence of a significant condensate source, proposed
here to be a water treatment and recycling facility (Anticline Disposal
facility), located 6 km west–southwest of the BSR monitoring site, as shown
in Fig. 1. Figure 6c shows a strong similarity of the profile for factor 3
and that for fence line samples next to the water treatment facility.
Identification of emission source associated with PMF factor 3 at
BSR
The Anticline Disposal facility was constructed to purify and recycle
contaminated produced water and hydraulic fracturing flow back water,
together with other drilling wastes from the Pinedale Anticline. Water
treatment processes at this facility are described in detail by
Schafer (2011) and Cox and Schafer (2010). Recycled water for use in
hydraulic fracturing is the result of API separator, anaerobic basin,
aeration basin, clarifier, and sand filter treatment steps. Aeration of
contaminated water within large heated ponds that are open to the environment
is expected to enhance evaporative losses from the treated water. Further
treatment steps, including a membrane bioreactor, reverse osmosis and
electro-coagulation, produce water of sufficient quality for re-injection.
Discharge quality water is produced with an additional treatment step of
boron ion exchange. Schafer (2011) reports that the contaminated water feed
to the facility contains BTEX between 28 000 and
80 000 µg L-1, gasoline organics in the range of 88 000 to
420 000 µg L-1, and diesel organics that range from 77 to
1100 µg L-1. One of the three main Pinedale Anticline
operators reports between three and four million barrels of their produced
water, including flow back water, are treated annually at this facility (US
BLM, 2014).
Correlation of methane, propane and n-butane with ethane at
Boulder South Road (BSR) from 2010 to 2011.
An “in versus out” calculation of emissions is not possible due to a lack
of process information. The WDEQ inventory estimates emissions for the 2011
calendar year from the facility as ∼ 49 t of VOC and ∼ 21 t of
BTEX, of which ∼ 18 t is reported as benzene. Canister samples taken
at the facility fence line indicate a speciated NMHC profile dominated by
toluene and xylenes (70 % of total hydrocarbon mass), as shown in
Fig. 6c. The average composition distribution of the fence line water
treatment facility samples are very similar to that of factor 3 suggesting
this facility is the contributing source for factor 3. However, the
possibility of some influence from other condensate emission sources to
factor 3, e.g., flow back from completions, cannot be excluded. While
quantification of the emission rate is not possible with this data, fence
line measurements indicate a BTEX:benzene ratio of ∼ 15 : 1, rather
than ∼ 1 : 1 as implied by inventory data. Additionally, fence line
mixing ratios up to 992 ppbv of toluene and 911 ppbv of xylene isomers were
measured suggesting significant emissions. An inventory derived emission rate
of 20 t year-1 of BTEX for the water treatment facility (footprint of
0.08 miles2; 0.21 km2) corresponds to an emission intensity of
∼ 250 t mile-2 (∼ 95 t km-2). This value compares
to a general intensity for the Pinedale Anticline (footprint of
312 miles2; 808 km2) of ∼ 1 t mile-2
(∼ 0.39 t km-2) when emissions from dehydration
(258 t year-1), pneumatics (30 t year-1) and fugitives
(73 t year-1) from the 2045 operating wells in 2011 are combined.
Emission inventory estimates therefore show that the facility has a far
higher emission rate than the average value for the development. Factor 3
could equally well be labeled “water treatment facility fugitive
condensate”. While the facility is an important point source of VOC and
BTEX, the magnitude of emissions is uncertain. Overall, these data suggest
that water treatment operations may have a significant influence on ambient
VOC composition and on O3 formation.
Spatial variability of speciated NMHC in the UGRB
Speciated NMHC distributions throughout the UGRB, and in particular in the
Pinedale Anticline, were evaluated by carrying out canister sampling surveys.
A total of 28 sampling sites were identified, each of which was chosen to be
representative of either background, boundary, downwind, upwind, or O&NG
development conditions (Table S2). The surveys in 2010 and 2011 focused on
determining differences between mixing ratios at background sites with those
observed downwind and close to development activities. Mixing ratios varied
significantly, both between sites in each survey and between surveys. Ethane
and other speciated NMHC mixing ratios at sites near BLDR and BSR were
generally more than twice those found at boundary sites upwind of the
development area. At sites closer to development activities, reported ethane
mixing ratios were higher, often between 3 × and 10 × those
at BLDR and BSR.
Strong correlations of methane, propane and n-butane (Fig. 8) with ethane
were observed in the data obtained from 255 canister samples collected at 27
sites throughout the UGRB during the period 2010 to 2013. (Samples close to
the water treatment facility and production locations with pneumatic pump
related fugitive natural gas emissions were excluded from this analysis.)
These correlations suggest a commonality of contributing sources and are
consistent with the dominance of fugitive natural gas emissions throughout
the UGRB. The ratios between these light hydrocarbons are a close match to
both those measured at BSR (Fig. 7) and those derived from natural gas
composition profiles reported by the WOGCC (Fig. 6b) for samples collected at
locations ranging from background sites to those downwind of drilling
operations. While the ratios of light hydrocarbons are relatively constant,
ambient mixing ratios showed considerable variability, reflecting the local
influence of meteorology and various O&NG operations. For example, in 2013
at Middle Crest (Table S2), a site within ∼ 100 m of active drill
rigs, fugitive natural gas signatures with ethane and toluene values of 485
and 11.3 ppbv, respectively, were observed. Similarly, measurements
∼ 300 m downwind of flow back operations at Mesa South Loop (Table S2)
showed fugitive natural gas and condensate signatures with ethane and toluene
up to 179 and 202 ppbv, respectively.
Correlation of methane, propane and n-butane with ethane for
locations within and around the Pinedale Anticline during 2010–2013
surveys.
During 2011/2012, 12 surveys of 24 h or 3-day duration were performed at the
same 10 sites within and around the Pinedale Anticline boundary. Both Boulder
sites are considered as well-mixed downwind sites, often with the lowest
speciated NMHC values. While the dominance of alkanes to the total speciated
NMHC mass (C2 to C8) is consistent, there are enhanced aromatic
contributions at three sites, namely Boulder Crest Road, Mesa North, and Mesa
South, as shown in Fig. 9. Boulder Crest Road is located ∼ 1.5 km to
the northwest of the water treatment facility, which likely explains enhanced
aromatics at this site. The two Mesa sites were in an area of intensive
drilling, completion, and production activities. Inventory data identifies
dehydration as the most significant source of BTEX emissions, with
enhancement relative to aliphatic hydrocarbons, leading, for example, to a
much higher BTEX / n-hexane ratio than that for the condensate
signature shown in Fig. 6c (WDEQ, 2014a). Over 80 % of Pinedale Anticline
BTEX production emissions are from dehydration units according to the 2011
winter inventory. Since dehydration emission sources are widely dispersed
throughout the Pinedale Anticline, a somewhat uniform distribution of BTEX is
anticipated. However, given the high level of activity on the Pinedale Mesa,
the influence of emissions from other activities is also possible. For
example, completion and flow back operations, neither of which is represented
adequately in current emission inventories, are likely to have contributed to
elevated BTEX emissions. The Wyoming DEQ (Department of Environment Quality)
inventory reports emissions from the completion category in 2011 as zero for
BTEX (WDEQ, 2014a). While the underlying causes of elevated BTEX on the
Pinedale Mesa are uncertain, measurements at Boulder Crest and BSR suggest
that a nearby water treatment facility causes a significant increase in
contributions of higher molecular weight species to NMHC mixing ratios at
these sites. Omission of water treatment and completions in inventories could
therefore be a significant oversight.
NMHC class distributions for 2011–2012 surveys at 10 sites within
and around the Pinedale Anticline (Average mass are scaled as shown relative
to the key value of 100 µg m-3).
Emission inventory source categories labeled as tanks, pneumatic pumps, and
fugitives can be considered as contributing to “fugitive natural gas”;
while dehydration unit emissions can equate to “fugitive condensate”.
Combining estimates of these emissions rates according to this source
categorization from the WDEQ emissions inventory for 2011 (WDEQ, 2014a) shows
that ∼ 75 % of the inventory is assigned to “fugitive natural
gas” and ∼ 25 % to “fugitive condensate”. Together, these
categories comprise 93 % of the 407 t of VOC and 99 % of the 68 t
of BTEX for February and March 2011 in the WDEQ inventory. The predominance
of fugitive gas emissions is consistent with the measurements reported here.
The importance of each PMF factor to episodic
O3 formation
O3 episodes at both Boulder sites are associated with high total NMHC
mixing ratios. Despite being located only 5 km apart, peak O3
differences of > 50 ppbv were evident on both 1 and 2 March 2011
(Fig. 3). These episode days are the least impacted by factor 3 at BSR. The
BLDR site is located 7.5 km north of the water treatment facility (Fig. 1).
It is possible that, unlike at BSR, BLDR was impacted by emissions from this
facility on these 2 days. The large differences in maximum O3 mixing
ratio at the two sites together with the observed hour by hour variations,
indicates the localized nature of O3 production and transport and the
difficulties of modeling O3 variability and its spatial distribution in
the UGRB, particularly as flow patterns in the shallow surface layer below
the inversion are as yet only partially characterized (Emery, 2013).
Figure 10 shows time series plots of the total OH (hydroxyl radical)
reactivity of each PMF factor with the NOx and O3 mixing
ratios, for four representative O3 episode days. Reactivities for
measured compounds with OH were calculated at standard temperature and
pressure (298.15 K and 1013.25 hPa) using the recommended kOH
rate coefficients also employed by Gilman et al. (2009), derived from a
variety of previous studies (Atkinson, 1986, 1990; Atkinson and Arey, 2003;
Atkinson and Aschmann, 1988; DeMore et al., 1997). While the ozone mixing
ratio is consistently scaled to 120 (ppbv), OH reactivity is scaled from
0–10 (s-1) for 2 March 2011, 0–20 (s-1) for 5 and
15 March 2011, and 0–40 (s-1) for 18 February 2011. Spiking of OH
reactivity in Fig. 10 is most prevalent for factor 3. Individual rate
coefficient (kOH) values are listed in Table S9. Figure S8 shows
similar plots for all episode days. For factor 1, OH reactivity is dominated
by contributions from CO. The contribution of local methane (total methane
minus background methane in the unpolluted troposphere) for factors 1 and 2
accounted for ∼ 2 %, and ∼ 5 % of the factor 1 OH
reactivity, respectively. Contributions from individual hydrocarbons in
factor 2 to total OH reactivity are relatively uniform because with
increasing carbon number, decreases in mixing ratio are offset by higher
kOH values. Factor 3 reactivity contributions are dominated by
those from the xylenes and toluene, both of which react relatively rapidly
with OH. The plotted reactivities do not account for variations in actinic
flux, so would perhaps be best described as potential reactivities that
reflect the atmospheric composition.
The plots vary significantly from day to day, but common themes emerge, such
as correlated increases in O3 and factor 3 reactivity contributions,
often resulting from increases in m+p-xylene mixing ratio (and other
compounds within the factor 3 profile). However, it is also clear that
O3 formation cannot be directly correlated with OH reactivity, and that
NMHC species are mixed into the air parcels after O3 has been formed.
Relationship of PMF factor OH reactivity, NOx and
O3 during selected episodes at Boulder South Road (BSR).
On 18 February, NOx levels are somewhat higher than usual so that
accumulated O3 is reduced before and after sunrise. A secondary spike in
O3 in early evening correlates with a rapid increase in reactivity due
to factor 3. Of the measured factor 3 hydrocarbons, m+p-xylene is the most
important contributor to OH reactivity. The measured mixing ratio of
m+p-xylene in this plume peaks at 37.9 ppbv. Factor 2 contributes most of
the OH reactivity for much of the day on 2 March 2011, when O3 peaks
some 50 ppbv higher at BLDR than at BSR, as noted in Fig. 3. Again, as on
18 February 2011, an increase in m+p-xylene late in the day, from 0.5 to
5.1 ppbv, coincides with an observed O3 increase in early evening. The
influence of two-peak reactivity contributions from factor 3 on 5 March 2011
occur when m+p-xylene mixing ratios increase from 1.0 to 7.8 ppbv at 12:00
and then, after declining, increase from 3.0 to 16.0 ppbv at 15:00. On
15 March 2011, factor 3 spikes, and there is an associated increase of
m+p-xylene from 0.4 to 12.3 ppbv at 13:00. Each of these elevated factor 3
contributions coincides with a measured spike in O3. Changes in wind
direction could obviously advect factor 3 species to other locations, e.g.,
BLDR, and thereby affect O3 production rates. Such an event may have
occurred on 1 and 2 March 2011, when southwesterlies (∼ 210∘)
from the direction of the water treatment facility were reported at BLDR, and
higher O3 mixing ratios were observed.
In summary, the time series plots in Fig. 10 (and Fig. S8) suggest that
factor 3 emission sources, associated with high NMHC values, have a
significant role in O3 formation in surface air impacting the Boulder
area downwind of the Pinedale Anticline. Toluene and the xylenes are the
principal compounds that lead to increases in factor 3 total reactivity and
hence in O3 production potential. These compounds alone frequently
contribute more than 50 % of OH reactivity for factor 3. It should be
noted that other unreported compounds are likely to be present within this
emission source. Trimethylbenzenes are also expected to add significantly to
factor 3 reactivity, but unfortunately, though known to be present in the air
samples that contain xylenes, their mixing ratios could not be accurately
assessed. Table S9 contrasts reactivity, derived from the sum of pseudo-first
order rate coefficients of speciated NMHC, CH4, and CO with OH, for 2
different days at 18:00. Total reactivity at 18:00 on 20 February
(1.89 s-1), with relatively low O3 and factor 3 contributions, is
considerably lower than at 18:00 on 18 February (49.42 s-1), with
relatively high O3 and factor 3 contributions (Fig. 10). The listed values
also lead to the conclusion that neither CO nor CH4 are important
contributors to OH reactivity during O3 episodes.
Wintertime O3 episodes in the UGRB and the Uintah Basin share many
important common characteristics (Oltmans et al., 2014). Episodic O3
production in both basins is associated with high NMHC levels and moderate
NOx. A key difference is that unlike the Uintah basin, O3 in
the UGRB can be spatially highly variable with large gradients over small
distances. In the UGRB, our results show that fugitive condensate material,
and in particular its methylated aromatic constituents, frequently plays an
important role in determining NMHC reactivity towards OH. A similar
conclusion, derived from a numerical modeling study, has recently been
reported for the Uintah Basin (Ahmadov et al., 2015).