1. Proxy-Based Analysis of Tropospheric Non-Methane
VOC Emissions from U.S. Oil & Gas Fields
Maya Ganesan
under the direction of
Dr. Caroline Nowlan
Dr. Kelly Chance
Harvard-Smithsonian Center for Astrophysics
Research Science Institute
July 30, 2014

2. Abstract
Non-methane volatile organic compounds (NMVOCs) are carcinogenic, neurotoxic substances
often released as byproducts of industrial processes. However, little is understood about the
impact of oil and gas (ONG) drilling activity on NMVOC emissions. To track this impact,
formaldehyde (HCHO) was used as a proxy for NMVOCs, while NO2 was used as a proxy
for ONG activity, to assess the correlation between NMVOC levels and ONG activity. Cor-
relation analysis revealed that ONG activity has no significant impact on NMVOCs, with
inconclusive correlation coefficients ranging from -0.7570 to 0.0027. Stochastic HCHO levels,
as compared to cyclical NO2 levels, suggested that HCHO is neither closely linked to, nor
affected by, NO2.
Summary
The United States is heavily reliant upon oil and gas production for its energy, but the
impacts of this industry on air pollution are not fully understood. While oil and gas drilling
is known to release greenhouse gases, its effects on non-methane volatile organic compounds
(NMVOCs), a class of compounds that cause cancer and brain damage, are less clear. This
study examined the impact of oil and gas activity on NMVOCs in the troposphere by using
tracer molecules to study these two variables. Formaldehyde was used to measure NMVOCs,
while NO2 was used as the known tracer for oil and gas activity. When correlations between
levels of these two variables were assessed over the last decade, it was shown that oil and gas
activity, represented by NO2 levels, does not have a visible impact on NMVOC emissions.

3. 1 Introduction
The United States is heavily reliant on oil and natural gas (ONG): in 2011, 62% of the United
States’ energy was sourced from ONG [1]. However, oil and gas production has detrimen-
tal impacts on the surrounding environment, contributing a variety of polluting emissions
like greenhouse gases, e.g. methane and NO2, and non-methane volatile organic compounds
(NMVOCs), e.g. benzene, toluene, xylene, and formaldehyde. VOCs are a primary compo-
nent of photochemical smog, and most are carcinogenic and neurotoxic [2]. While significant
correlations have been observed between ONG and greenhouse gas levels [3], the impact of
ONG on NMVOCs is not fully understood, with emission estimates remaining inaccurate
and uncertain [4, 5] and leading to a lack of appropriate and necessary regulation of the oil
and gas industry.
This investigation utilizes satellite measurements and computational analysis to char-
acterize and quantify the impact of oil and natural gas production on NMVOC emissions.
Remote sensing data, a common tool for detecting airborne pollutants, was retrieved in this
study from the Ozone Monitoring Instrument (OMI), a sun-synchronous orbiting spectrome-
ter onboard the National Aeronautics and Space Administration (NASA)’s Earth Observing
System (EOS) Aura satellite. OMI is capable of measuring scattered or reflected radiation
from 264-504 nm, encompassing the near-UV, UV, and visible light spectra [6].
However, most VOCs cannot be detected through remote sensing. Some, such as benzene
and toluene, only have measurable absorption features between 200 and 300 nm and are
subject to interference from ozone, which efficiently absorbs UV and thus impedes satellite
measurements. Other VOCs have absorption spectra in the infrared range, but infrared
remote sensing instruments measure in the upper troposphere, so they have low sensitivity to
chemicals near Earth’s surface and cannot gather large amounts of reliable data from ground
sources. Formaldehyde (HCHO) and glyoxal (CHOCHO) are the two primary VOCs with
1

4. absorption spectra conducive to satellite detection and analysis of ground-source emissions
[7]: here, formaldehyde was used as the proxy to track NMVOC emissions due to its higher
signal-to-noise ratio as compared to glyoxal. NO2 was used as a known proxy for ONG drilling
operations as it has previously shown statistically significant correlations with major ONG
drilling regions in the U.S. [8]
Noise for both NO2 and HCHO results from instrument measuring errors, due to factors
like background radiation, unusually high surface reflectivity (albedo) over snowy areas, low
solar zenith angle in winter or in northern latitudes, and disruptive topographical features
like mountains. Studying anthropogenic NO2 and HCHO can also be impeded by biogenic
emissions; NO2 is produced through biomass burning, bacterial denitrification in soil, and
lightning strikes, while HCHO is produced from the oxidation of such natural and anthro-
pogenic precursors as methane, which is produced by living organisms and industry, and
isoprene, which arises from biomass burning [9, 10].
1.1 Deviations from prior research
Little prior research exists that traces formaldehyde trends over oil and gas fields. The only
prior study, by Thompson et al., was unable to establish a significant correlation between
formaldehyde levels and oil and gas activity [11]. However, a number of restrictions were
present in the study: the investigators utilized data over the small sample area of eastern
Texas, which had been collected from 2005 to 2008, just as the process of hydraulic fracturing
(fracking) — which releases hundreds of tons of NMVOCs each day [12] — was becoming
widespread in the United States [3]. Furthermore, the data used in this study, obtained from
OMI, originally contained errors caused by instrument aging and row anomaly, a “partial
external blockage” of the charged coupled device (CCD) array that comprises OMI [13].
As a result of these disturbances, the investigators were unable to establish a noteworthy
correlation between ONG activity and levels of HCHO [11].
2

5. In this investigation, a novel, updated OMI HCHO dataset, revised to remove faulty
data, was used [14]. OMI HCHO levels were then compared with trends in OMI NO2 over
the same time period, as NO2 is a known byproduct of ONG activity [8]. The correlation
between these pollutants was assessed through heat maps, line plots, and linear regression
analysis.
The resulting data may have significant policy implications, as large concentrations of
HCHO in the atmosphere could indicate a significant threat to human health. Furthermore,
HCHO can serve as an indicator of the presence of other VOCs that, due to their chemical
composition, cannot directly be detected from space [6, 14].
2 Materials and Methods
NO2 and HCHO column data were retrieved from OMI onboard Aura, a NASA satellite that
orbits Earth at a constant altitude of 705 km in a sun-synchronous orbit. A sun-synchronous
orbit enables the satellite to pass over any particular spot at the same local time each day,
maintaining the same solar zenith angle on that location on the earth’s surface. This allows
satellite radiance data to be averaged over consecutive days and compared year-to-year
without necessitating adjustment for solar angle or length of the light path [15].
OMI is a CCD spectrometer that measures in the near-UV, UV, and visible light ranges,
from 264 nm to 504 nm. At the time of its launch in late 2004, OMI featured the highest
spatial resolution of any orbiting satellite to date, with a nadir ground pixel size (size of
the pixel directly below the satellite) of 13 × 24 km2
, thus enhancing the quality of its
measurements of air quality standards like NO2, SO2, HCHO, and BrO [6].
At any given time, OMI measures nadir solar backscatter radiation over a 2600 km swath
of Earth’s surface, with a field of view angle of 115◦
. Once radiance data are measured by
OMI, least-squares spectral fitting is used, matching retrieved absorption spectra with lab-
3

6. oratory reference absorption spectra calculated using small-scale models. These simulations
have manipulable light intensities, so the absorption of a certain molecule can be measured
at different intensities and extrapolated to atmospheric conditions. This process, when put
into practice, isolates the absorption spectra of different molecules and produces values for
the slant column of the measured compounds, in molecules/cm2
[15]. Once the slant column
is determined, the vertical column over an area is determined by dividing the slant column by
an air mass factor, an area-specific value that uses a radiative transfer model and a chemical
transport model to accommodate influences like molecule scattering and solar zenith angle
[16]. Data is then averaged over equal-size grids of 0.2◦
× 0.2◦
across the globe, and monthly
means are produced for each pixel.
In this investigation, vertical columns were plotted and mapped over multiple areas of
interest, such as the entire North America, then specifically United States, and finally spe-
cific oil and gas production areas. Out of the four large concentrations of oil and gas activity
— the Bakken Field in North Dakota, production sites in southern Wyoming and northern
Colorado, the Fort Worth basin in Texas, and the Marcellus shale in West Virginia, Pennsyl-
vania, and Ohio (see Figure 1) — the Bakken Field was most conducive to analysis of trends
in NO2 and HCHO, as it was least subject to interference from urban NO2 emissions and had
no salient topographical features, such as mountains, that impeded measurement accuracy.
To maximize accuracy, data points for which the cloud radiance fraction was greater than
30% were also eliminated from the dataset.
Data from 2005 to 2014 were assessed on both a monthly and yearly basis, and three
types of plots were used: heat maps, affording a broad overview of pollutant distributions
across the United States; timeseries, permitting analysis of monthly and yearly trends; and
regression plots, comparing variables to assess the linearity of their correlation. Both HCHO
and NO2 were averaged and plotted on both a monthly and yearly basis.
4

7. Figure 1: Map of oil and gas wells and plays (areas of drilling for exploration or production)
across the United States. Circles demarcate areas with high concentrations of wells, and
the red circle demarcates the Bakken Oil Fields in North Dakota, the primary area for this
pollutant trend assessment. Image obtained from postcarbon.org.
3 Results and Analysis
Out of the four major concentrated areas of oil and gas drilling operations, the most suitable
area was analyzed for pollutant trends. Results from analysis of the Bakken Oil Field are
presented, with the results from analysis of the Ft. Worth Basin serving as a reference to
demonstrate the impracticality of studying the other concentrated oil and gas sites.
3.1 Preliminary data
NO2 and HCHO data were plotted over large areas, such as the North American continent and
the United States subcontinent, to check for broad expected trends in Figures 2 and 3. The
larger the area over which data is plotted, the less noise is present and the more accurate the
observed trends. These included a seasonal cycle for NO2 due to photochemical degradation
5

8. and an overall decrease in NO2 across the U.S. since 2005 due to more stringent power
plant standards and energy-efficient vehicles [17]. Additionally, in Figure 4, high levels of
HCHO were observed over the southeastern United States, which contains one of the world’s
largest coniferous forest ecosystems. Coniferous forests release isoprene when heat-stressed,
and isoprene oxidation forms formaldehyde [10, 16].
Figure 2: Comparison of monthly means of NO2 vertical column over the United States
and North America. Local minima in summer months are explained by peak photochem-
ical degradation of NO2; conversely, local maxima in winter months can be attributed to
accumulation of NO2 in the troposphere.
NO2 over the United States was observed to follow the same seasonal cycle as NO2
over North America, indicating consistency and basic accuracy in the dataset. Levels in the
United States were elevated, suggesting higher emissions from the United States than from
other countries on the continent. However, while NO2 values over North America appeared
relatively stable, the overall trend in United States emissions was, as expected, downward.
6

9. Figure 3: Comparison of yearly means of vertical columns of NO2 over the United States in
2005, at left, and 2013, at right. Hotspots were observed over metropolitan areas, such as
Seattle and Houston, and throughout the northeast. The overall nationwide decrease in NO2
is a result of greater climate regulations and advances in energy-efficient technology.
Figure 4: Comparison of yearly means of vertical columns of HCHO over the United States
in 2005, at left, and 2013, at right. High levels of HCHO in the southeast resulted from
isoprene emissions from heat-stressed coniferous forests; HCHO decreased over time in that
region due to deforestation [18]. Some marine columns were visible, likely due to outflow
from land sources.
7

10. Figure 5: Comparison of monthly means of HCHO and NO2 columns over the Ft. Worth
basin in southeastern Texas. HCHO displayed a strong seasonal cycle, with peaks in the
summer due to isoprene emissions from heat-stressed coniferous forests.
NO2 levels were elevated in the Ft. Worth Basin when compared to North America
or the United States, as demonstrated in Figure 2, likely due to disturbance from nearby
metropolitan areas that produce large quantities of NO2 from burning fossil fuels. The bio-
genic interference in HCHO measurements also made this area unsuitable for analysis of
pollutant trends.
3.2 Bakken Oil Field, North Dakota
As shown in Figure 6, while NO2 levels over North America maintained a relatively stable
cycle, levels over the Bakken Oil Field underwent a visible increase after 2007, as oil produc-
tion doubled between 2006 and 2007 [19]. NO2 levels in the Bakken area appeared to undergo
not only the expected local minimum in summer as a result of photochemical degradation,
but also a consistent local minimum in February, as soil NOx emissions in the central United
States subsequently increase in the spring with rising temperature [20].
8

11. Figure 6: Comparison of monthly means of the vertical column of NO2 over the Bakken Oil
Field and over North America. The data followed the expected seasonal cycle, with local
maxima in the winter and local minima in the summer.
Figure 7: Comparison of yearly means of HCHO vs. NO2 over the Bakken Oil Field in North
Dakota. The two pollutants displayed a strong anticorrelation, with the graphs appearing
as near-mirror images. Data was removed for 2008 due to a faulty monthly mean, which
disrupted the yearly mean.
9

12. NO2 levels were expected to correlate strongly with HCHO, but the yearly means dis-
played a surprising anticorrelation. To analyze this unusual pattern more thoroughly, monthly
means were plotted, shown in Figure 8.
Figure 8: Comparison of monthly means of HCHO vs. NO2 over the Bakken Oil Field. While
NO2 levels followed a regular seasonal cycle, HCHO levels appeared to have little year-to-year
regularity, except a noticeable spike in values in winter.
To investigate the sharp increase in HCHO values in winter, surface albedo was plotted
as high albedo can cause atypically high pollutant measurements.
The exceptionally high albedo from November to March, as displayed in Figure 9, cor-
related directly with high HCHO values at that time of year in Figure 8. To remove this
environmental interference, NO2 and HCHO were plotted exclusively from April to October
of each year.
10

13. Figure 9: Monthly surface albedo over the Bakken Oil Field. High albedo values were observed
in the winter months due to the high surface reflectivity of snow.
Figure 10: Comparison of monthly means of HCHO vs. NO2 over the Bakken Oil Field,
including only data from April to October of each year.
11

14. When plotted from April to October of each year, with distorted data from months
with high albedo removed, HCHO values remained nonpatterned and unpredictable. The
NO2 values maintained their seasonal cycle, but no similar discernible pattern of peaks and
valleys was found in the HCHO dataset, suggesting that the correlation between NO2 and
HCHO was weak.
Figure 11: Comparison of yearly means of HCHO vs. NO2 over the Bakken Oil Field, includ-
ing only data from April to October of each year.
With winter data removed, the yearly means of these two pollutants showed no relation-
ship, as opposed to the inverse one previously observed in Figure 7.
Month Span Dataset R value R2
value
January-December Monthly -0.1378 0.0190
Yearly -0.7570 0.5730
April-October Monthly -0.0486 0.0024
Yearly 0.0027 7.29e-6
Table 1: Correlation coefficients for monthly and yearly plots of the full dataset of HCHO
vs. NO2 as well as the truncated dataset that excluded winter months. The correlations were
inconclusive, not following any identifiable pattern.
12

15. Figure 12: Monthly means of HCHO and NO2, without data from winter months, were
plotted against each other to determine the strength of their correlation. The correlation,
with an R of -0.0486 and an R2
of 0.0024, demonstrated an insignificant anticorrelation.
3.3 Discussion
In this study, formaldehyde and NO2 were used as proxies to determine the impact of oil and
gas activity on levels of non-methane volatile organic compounds in the atmosphere. NO2,
a known tracer for oil and gas activity, served as the proxy for levels of oil and gas drilling;
formaldehyde was used as the proxy for the presence of non-methane VOCs. This study used
a new updated, normalized OMI dataset of both NO2 and HCHO columns with instrument
measuring errors removed. Correlation analysis performed on this dataset revealed that NO2
is poorly correlated with HCHO: therefore, oil and gas operations do not significantly impact
levels of NMVOCs. The R and R2
values for adjusted NO2 and HCHO were -0.0486 and
0.0024 respectively for monthly means and 0.0027 and 7.29e-6 respectively for yearly means,
demonstrating a distinct lack of correlation. However, the exception was the annual full-
year data, which produced high correlation coefficient values. This anomaly likely does not
indicate a substantive correlation, but rather represents an aberration in the process of
averaging data for statistical analysis.
13

16. 3.3.1 Error analysis
Errors were likely present in the data. In theory, higher levels of NO2 should be accompanied
by higher levels of formaldehyde, as the oxidation of methane into formaldehyde also oxidizes
NO into NO2 [21]. This pattern was not observed in practice due to a number of potential
intervening factors. Cloud cover and high levels of haze impede HCHO detection, while
aerosols in the troposphere increase HCHO scattering [10]. These stochastic factors alter
data retrieval and processing and contribute to unexpected results.
While environmental factors likely played a large role in altering data, the potential
for satellite measurement error appears to have been minimal, as retrieved measurements
displayed insignificant precision error in Figures 13 and 14. Error was present but was too
small to noticeably influence trends.
Figure 13: Monthly means of the vertical column of NO2 over the Bakken Field, including
data from only April to October of each year, with error bars present. Error was small
because the high absorptivity of NO2 allows a strong signal to be retrieved.
14

17. Figure 14: Monthly means of the vertical column of HCHO over the Bakken Field, including
data from only April to October of each year, with error bars present. The precision error
for HCHO was larger than that of NO2 but still minimal, so it did not significantly impact
trend analysis.
4 Conclusion
Using the new OMI dataset, oil and gas activity was shown to have no notable impact
on levels of NMVOCs in the troposphere. Correlations between monthly and yearly values,
respectively, of these pollutants were -0.0486 and 0.0027, indicating a negligible relationship.
However, this topic deserves further research in future years as remote sensing technology
becomes more sophisticated.
4.1 Future work
As VOCs and NOx photocatalytically produce tropospheric ozone, ozone levels could be an-
alyzed to determine the amount of these pollutants present. Further, formaldehyde columns
could be plotted on a map of the U.S. to determine if hotspot locations correlate with loca-
tions of high oil and gas activity.
Formaldehyde levels might also be too low at present for accurate detection and quantifi-
15

18. cation of trends. In future years, revisiting a more comprehensive and updated dataset may
reveal the expected upward trend as oil and gas drilling activity continues.
5 Acknowledgements
I would like to thank Dr. Caroline Nowlan of the Harvard-Smithsonian Center for Astro-
physics for her boundless patience, help, and encouragement. I am also grateful to Dr.
Gonzalo Gonzalez Abad, Dr. Andrew Charman, and Ms. Marie Herring for their guidance
and assistance.
I would also like to thank the Center for Excellence in Education, Massachusetts Institute
of Technology, and the Research Science Institute and its staff, as well as Mr. John Yochelson
at Building Engineering and Science Talent (BEST); Mr. Peter Ungaro, President, Director,
and CEO at Cray, Inc.; Dr. Laura Stubbs, Director of Science and Technology Initiatives
at the United States Department of Defense; and Mr. Matthew B. Grice for making this
research possible.
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19. References
[1] U. E. I. Administration. Annual Energy Review, 2012.
[2] A. Songur, O. Ozen, and M. Sarsilmaz. The toxic effects of formaldehyde on the nervous
system. Reviews of Environmental Contamination and Toxicology, 203:105–118, 2010.
[3] R. W. Howarth, R. Santoro, and A. Ingraffea. Methane and the greenhouse-gas footprint
of natural gas from shale formations. Climatic Change, 106:679–690, 2011.
[4] F. Wittrock, A. Richter, H. Oetjen, J. P. Burrows, M. Kanakidou, S. Myriokefalitakis,
R. Volkamer, S. Beirle, U. Platt, and T. Wagner. Simultaneous global observations of
glyoxal and formaldehyde from space. Geophysical Research Letters, 33, 2006.
[5] D. B. Millet, D. J. Jacob, S. Turquety, R. C. Hudman, S. Wu, A. Fried, J. Walega, B. G.
Heikes, D. R. Blake, H. B. Singh, B. E. Anderson, and A. D. Clarke. Formaldehyde
distribution over North America: Implications for satellite retrievals of formaldehyde
columns and isoprene emission. Journal of Geophysical Research, 111, 2006.
[6] N. Aeronautics and S. Administration. OMI frequently asked questions, 2008.
[7] S. Beirle, R. Volkamer, F. Wittrock, A. Richter, J. Burrows, U. Platt, and T. Wag-
ner. DOAS retrieval of glyoxal from space. Proceedings of the Atmospheric Science
Conference, 2006.
[8] B. Pierce. Development of spatially enhanced NO2 column for evaluation of O&G
emissions. 2014.
[9] W. Choi, N. Bouiver-Brown, Z. Chen, J. Gilman, B. Lafranchi, M. McKay, G. Wolfe,
W. Brune, R. Cohen, A. Goldstein, J. de Gouw, J. Thornton, R. Chatfield, and
I. Faloona. Atmospheric observations of abundant formaldehyde above a coniferous
forest provides further evidence of rapid oxidation of arboreal hydrocarbons. American
Geophysical Union, Fall Meeting 2008, 2008.
[10] K. Chance, P. I. Palmer, R. J. Spurr, R. V. Martin, T. P. Kurosu, and D. J. Jacob.
Satellite observations of formaldehyde over North America from GOME. Geophysical
Research Letters, 27:3461–3464, 2000.
[11] A. Thompson, D. Kollonige, B. Pierce, R. Dickerson, D. Jacob, D. Edwards, G. Pfister,
D. Henze, J. Milford, and T. Holloway. Satellite signatures of trace gases associated
with US oil and gas extraction. Presented at the NASA Air Quality Applied Sciences
Team (AQAST) 7th Semiannual Meeting, 2014.
[12] A. Hendler, J. Nunn, J. Lundeen, and R. McKaskle. VOC emissions from oil and con-
densate storage tanks. Technical report, 4800 Research Forest Drive, The Woodlands,
TX, 2009.
17

20. [13] N. L. Boeke, J. D. Marshall, S. Alvarez, K. V. Chance, A. Fried, T. P. Kurosu, B. Rap-
pengl¨uck, D. Richter, J. Walega, P. Weibring, and D. B. Millet. Formaldehyde columns
from the Ozone Monitoring Instrument: Urban versus background levels and evaluation
using aircraft data and a global model. Journal of Geophysical Research, 116, 2011.
[14] G. G. Abad, X. Liu, K. Chance, H. Wang, T. Kurosu, and R. Suleiman. Updated SAO
OMI formaldehyde retrieval. Atmospheric Measurement Techniques, 7:1–31, 2014.
[15] M. R. Dobber, R. J. Dirksen, P. F. Levelt, G. H. J. van der Oord, R. H. M. Voors,
Q. Kleipool, G. Jaross, M. Kowalewski, E. Hilsenrath, G. W. Leppelmeier, J. de Vries,
W. Dierssen, and N. C. Rozemeijer. Ozone Monitoring Instrument calibration. IEEE
Transactions on Geoscience and Remote Sensing, 44, 2006.
[16] L. Zhu, D. J. Jacob, L. J. Mickley, E. A. Marais, D. S. Cohan, Y. Yoshida, B. N.
Duncan, G. G. Abad, and K. V. Chance. Anthropogenic emissions of highly reactive
volatile organic compounds in eastern Texas inferred from oversampling of satellite
(OMI) measurements of HCHO columns, submitted to Environ. Res. Lett. 2014.
[17] A. R. Russell, L. C. Valin, and R. C. Cohen. Trends in OMI NO2 observations over
the United States: effects of emission control technology and the economic recession.
Atmospheric Chemistry and Physics, 12:12197–12209, 2012.
[18] N. R. D. Council. Our forests aren’t fuel. Available at http://www.nrdc.org/energy/
forestsnotfuel/.
[19] N. D. D. of Mineral Resources. Monthly Bakken oil production statistics, 2014.
[20] Y. Choi, Y. Wang, T. Zeng, D. Cunnold, E.-S. Yang, R. Martin, K. Chance, V. Thouret,
and E. Edgerton. Springtime transitions of NO2, CO, and O3 over North America: model
evaluation and analysis. Journal of Geophysical Research, 113, 2008.
[21] R. A. Cox, R. G. Derwent, P. M. Holt, and J. A. Kerr. Photo-oxidation of methane in
the presence of NO and NO2. Journal of the Chemical Society, Faraday Transactions
1: Physical Chemistry in Condensed Phases, 72:2044–2060, 1975.
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