AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus PublicationsGöttingen, Germany10.5194/amt-10-3833-2017Airborne DOAS retrievals of methane, carbon dioxide, and water vapor concentrations at high spatial resolution: application to AVIRIS-NGThorpeAndrew K.andrew.k.thorpe@jpl.nasa.govhttps://orcid.org/0000-0001-7968-5433FrankenbergChristianhttps://orcid.org/0000-0002-0546-5857ThompsonDavid R.https://orcid.org/0000-0003-1100-7550DurenRiley M.https://orcid.org/0000-0003-4723-5280AubreyAndrew D.BueBrian D.https://orcid.org/0000-0002-7856-3570GreenRobert O.GerilowskiKonstantinKringsThomasBorchardtJakobhttps://orcid.org/0000-0002-2380-0823KortEric A.SweeneyColmhttps://orcid.org/0000-0002-4517-0797ConleyStephenRobertsDar A.DennisonPhilip E.Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USADivision of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USAInstitute of Environmental Physics (IUP), University of Bremen, Bremen, GermanyDepartment of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan, USACooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USAGlobal Monitoring Division, NOAA Earth System Research Laboratory, Boulder, Colorado, USAScientific Aviation, 3335 Airport Road, Boulder, Colorado, USADepartment of Geography, University of California, Santa Barbara, Santa Barbara, California, USADepartment of Geography, University of Utah, Salt Lake City, Utah, USAAndrew K. Thorpe (andrew.k.thorpe@jpl.nasa.gov)19October201710103833385018February20175September201729August20179May2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/articles/10/3833/2017/amt-10-3833-2017.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/articles/10/3833/2017/amt-10-3833-2017.pdf
At local scales, emissions of methane and carbon dioxide
are highly uncertain. Localized sources of both trace gases can create
strong local gradients in its columnar abundance, which can be discerned using absorption spectroscopy at high spatial resolution. In
a previous study, more than 250 methane plumes were observed in the San Juan Basin near Four Corners during April 2015 using the next-generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and a linearized matched filter. For the first time, we apply
the iterative maximum a posteriori differential optical absorption spectroscopy (IMAP-DOAS) method to AVIRIS-NG data and generate gas
concentration maps for methane, carbon dioxide, and water vapor plumes. This demonstrates a comprehensive greenhouse gas monitoring
capability that targets methane and carbon dioxide, the two dominant anthropogenic climate-forcing agents. Water vapor results
indicate the ability of these retrievals to distinguish between methane and water vapor despite spectral interference in the shortwave infrared. We focus on selected cases from anthropogenic and natural sources, including emissions from mine ventilation shafts,
a gas processing plant, tank, pipeline leak, and natural seep. In addition, carbon dioxide emissions were mapped from the flue-gas
stacks of two coal-fired power plants and a water vapor plume was observed from the combined sources of cooling towers and cooling
ponds. Observed plumes were consistent with known and suspected emission sources verified by the true color AVIRIS-NG scenes and
higher-resolution Google Earth imagery. Real-time detection and geolocation of methane plumes by AVIRIS-NG provided unambiguous
identification of individual emission source locations and communication to a ground team for rapid follow-up. This permitted
verification of a number of methane emission sources using a thermal camera, including a tank and buried natural gas pipeline.
Introduction
It is important to better understand the processes controlling changes in atmospheric methane (CH4) and carbon dioxide
(CO2), the two dominant anthropogenic climate-forcing agents. CH4 and CO2 contribute approximately 17
and 64 % of the total radiative forcing attributed to anthropogenic greenhouse gases and halocarbons . The
atmospheric growth rates are strongly influenced by anthropogenic emissions of CH4 and dominated by fossil fuel CO2
emissions. Anthropogenic CH4 sources were estimated to contribute 10.6 % of the total 2014 anthropogenic emissions of the
United States, with major sources including natural gas systems (2.6 %), enteric fermentation (2.4 %), landfills
(2.2 %), petroleum systems (1.0 %), and coal mining (1.0 %) . CH4 is a precursor for tropospheric
ozone and is strongly linked with co-emitted reactive trace gases that are the focus of air quality mitigation policies. US
anthropogenic CO2 sources make up 81 % of the total anthropogenic emissions and are dominated by fossil fuel combustion,
including electricity generation (30 %), transportation (25 %), and industrial emissions (12 %) . US
emissions of both gases are projected to increase and a number of studies have suggested that EPA bottom-up emission
inventories are underestimated for CH4. US fossil fuel CO2 emissions are better
constrained through existing inventories of fossil fuel sales and combustion, but global uncertainties are growing with the rise
of a number of large developing countries where emissions information is not readily available .
There remains uncertainty regarding the sources and sinks of atmospheric CH4, as reflected by the ongoing scientific discussion
on both the hiatus in the atmospheric growth rate in the early 21st century and the unexpected rise starting in 2007
. Further, regional top-down emissions estimates cannot discriminate source categories and thereby attribute fluxes to
specific processes or sources. Uncertainty in anthropogenic CH4 emissions is large at multiple scales and process attribution
remains challenging because emissions originate from biological processes, venting, and leaks .
Recent studies suggest that the majority of CH4 emissions from oil and gas supply chains are caused by a number of
super-emitters, which could explain underestimates in bottom-up inventories . The
ability to identify emission sources offers the potential to constrain regional greenhouse gas budgets and improve partitioning between
anthropogenic and natural emission sources. Although CH4 has a short atmospheric lifetime (about 9 years), it has
a very high global warming potential (GWP) that is 86 times greater than CO2 on a 20 year timescale
. This means that even small amounts of emissions reduction will result in large reductions in the overall atmospheric
radiative forcing.
Driving surveys using in situ instruments have been used to identify CH4 emission sources in major US metropolitan areas like
the Los Angeles basin , Boston , and Washington, D.C. , as well as to measure fluxes
. Recently, ground-based thermal imaging systems have also been used to identify CH4 emissions .
However, these methods require comprehensive sampling techniques, are time consuming, and can be limited to regions with sufficient road access.
In situ airborne measurements offer the potential for increased coverage and have been used for US regional CH4 flux estimates using mass
balance approaches for the Uintah Basin in northeastern Utah , the Marcellus formation in southwestern Pennsylvania ,
and the Barnett Shale formation in Texas . These measurements reflect gas concentrations at the flight altitude and
these studies are designed to estimate aggregate emissions for large regions rather than identifying individual emissions sources.
More recently, in situ airborne measurements using a chemically instrumented Mooney aircraft have been used to estimate fluxes from known
sources like the Aliso Canyon leak and for a number of sources identified by imaging spectrometers in the Four Corners
region . This method samples the atmosphere directly at the flight path altitude and can measure multiple gas species.
The Methane Airborne MAPper (MAMAP) spectrometer has also been used to measure elevated CH4 and CO2
column abundances to quantify emissions from a coal mine ventilation shaft , power plants , and a landfill
. MAMAP is a non-imaging spectrometer with a small field of view limited to flying transects across gas plumes rather
than quickly mapping their morphology and extent on small scales. Both instruments are better suited for either investigating known emission
sources or identifying larger regional emissions as opposed to individual sources.
High-resolution gas Jacobians plotted in lighter colors and for AVIRIS-NG (5 nm spectral resolution and sampling) for
(a)CH4 (red), (b)CO2 (green), and (c)H2O (blue). These examples were calculated
for a 5 % change in CH4 (red), (b)CO2 (green), and (c)H2O over the total
column. AVIRIS-NG retrieval windows are indicated by the black outlines.
Locations of gas plumes presented in this study.
(a) AVIRIS-NG true color image subset. (b) A number of CH4 plumes are clearly visible with maximum
enhancements in excess of 5000 ppm⋅ m. (c) Close-up of AVIRIS-NG true color image shown by
black outline in (a). (d) Higher-resolution Google Earth imagery for same area reveals drilling rigs at an active
underground coal mine, suggesting that the origin of these plumes is mine workings ventilation shafts. (e)H2O retrieval
does not indicate enhancements. For all images, north is up.
Airborne imaging spectrometers
Airborne imaging spectrometers like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the next-generation
instrument AVIRIS-NG can map large regions while providing the spatial resolution required to identify individual
emissions within scenes. While not originally designed for mapping emissions, these instruments measure the 0.38 to 2.5 µm
range, which includes many gas absorption features (Fig. ). This has permitted quantitative retrievals of CH4 using
AVIRIS (approximately 10 nm spectral resolution and sampling) for marine seeps . Water vapor
retrievals have been demonstrated with AVIRIS mainly for atmospheric correction and reflectance
retrievals. However, AVIRIS water vapor retrievals have also been used to measure plant transpiration, demonstrating potential
application to the fields of ecology and meteorology .
AVIRIS has been used for high-resolution mapping of CO2 plumes from industrial sources and wildfires .
More recently, AVIRIS-NG (approximately 5 nm spectral resolution and sampling) has surveyed large regions to identify CH4 emissions associated
with oil production , gas extraction , hydraulic fracturing , and a landfill .
This is possible due to a 34∘ field of view, which results in an image swath of 1.8 km when flying at
3 kma.g.l. (above ground level).
Airborne imaging spectrometers that operate in the thermal infrared, such as the Mako and HyTES instruments , have also been
used for mapping CH4 plumes. However, the altitude of maximum sensitivity varies with environmental conditions like thermal contrast ,
which can make plumes difficult to detect and quantify, and sensitivity to near-surface emissions decreases with flight altitude, which can limit ground coverage.
Because AVIRIS and AVIRIS-NG measure reflected solar radiation in the shortwave infrared, CH4 retrieval sensitivity is impacted only slightly by
flight altitude due to additional gas attenuation along the optical path. However, at higher flight altitude and coarser spatial resolution a gas enhancement
is diluted over a larger image pixel, thereby decreasing instrument sensitivity. The ability to fly high results in more efficient flight campaigns due to
improved ground coverage. For example, AVIRIS-NG consistently observed plumes for a CH4 controlled release experiment for all altitudes flown
(up to 3.8 kma.g.l.) and AVIRIS has observed CH4 plumes flying at 8.9 kma.g.l.. AVIRIS has also mapped CH4
plumes over multiple days from the Aliso Canyon leak by flying 6.6 kma.g.l., resulting in an image swath approximately 4.0 km wide
. This also offers the potential for space-based detection of emission sources, like the observed CH4 plume from Aliso Canyon
using the orbital Hyperion imaging spectrometer .
In a previous study , the iterative maximum a posteriori differential optical absorption spectroscopy (IMAP-DOAS) retrieval was applied
to AVIRIS for quantitative mapping of CH4 from natural and anthropogenic sources. In this study, the application of IMAP-DOAS has been expanded
for use with AVIRIS-NG for multiple gas species, including CH4, CO2, and H2O. We present results from AVIRIS-NG data acquired in
New Mexico and Colorado, including from a flight campaign in the San Juan Basin near Four Corners. We will present results for a number of sources,
including CH4 from mine ventilation shafts, a gas processing plant, tank, pipeline leak, and natural seep, as well as CO2 and H2O
plumes associated with power plants (Fig. ).
(a) AVIRIS-NG measured and modeled radiance for one image pixel within the CH4 plume used for the CH4 retrieval
(see Fig. b). (b) The residual is plotted with 1σ SD boundary calculated from residuals for the entire scene.
(a) AVIRIS-NG measured and modeled radiance for one image pixel within the CH4 plume used for the H2O retrieval
(see Fig. e). (b) The residual is plotted with 1σ SD boundary calculated from residuals for the entire scene.
Study sites and AVIRIS-NG data
Space-based observations collected by the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument
showed CH4 enhancements in the Four Corners region . This made for an ideal location for follow-up
surveys using AVIRIS-NG to identify individual emission sources. During the flight campaign, the AVIRIS-NG instrument was equipped with a real-time
CH4 mapping capability using a waterfall display monitored by the instrument operator. Observed CH4 plumes were overlaid on a true
color image displaying location information and the maximum CH4 enhancement . This permitted adaptive survey
strategies to investigate observed plumes and the ability to send images of the plume with accurate locations to a ground crew for subsequent
follow-up. A Xenics Onca-VLWIR-MCT-384 thermal imaging camera with a Spectrogon optical filter centered at 7.746 µm was used by the
ground crew to verify a number of plumes observed in real time by AVIRIS-NG.
Located in New Mexico and Colorado, the San Juan Basin produces natural gas from sandstone, coal bed CH4, and shale formations and is the
fourth largest US gas field when it comes to total production . During a 5-day campaign in April 2015, AVIRIS-NG targeted an area
corresponding to the highest CH4 enhancements observed with SCIAMACHY . A 2500 km2 area was covered in
approximately 2 days (9.2 flight hours) flying at 3 kma.g.l., resulting in scenes with an image swath of around 1.8 km and
a ground resolution of 3 m. The remaining flight days were used for additional follow-up flights and some repeat observations, sometimes
at lower flight altitudes. During the campaign, a number of potential CH4 emission sources were targeted, including infrastructure
associated with natural gas production like well pads, tanks, gas processing plants, a coal mine, and natural coal bed CH4 seeps.
While the flight campaign focused on CH4 sources, the coal-fired San Juan power-generating station was also flown as a potential CO2 emission source.
IMAP-DOAS retrievals
A detailed description of the IMAP-DOAS retrieval for AVIRIS can be found in . Gas retrievals were performed on
orthocorrected radiance data. Atmospheric profiles were generated by updating prior gas profiles from the US standard atmosphere
obtained from the radiative transfer models LOWTRAN/MODTRAN using volume mixing ratios (VMRs) from the NOAA Mauna
Loa station, United States . Temperature, pressure, and water vapor VMR profiles representative of the time period
of the flight campaign were acquired from the National Centers for Environmental Prediction/National Center for Atmospheric Research
(NCEP/NCAR) reanalysis project . Spectral parameters for CH4, CO2, H2O, and N2O
were used from the HITRAN 2008 database and a classical Voigt spectral line shape was used to calculate vertical
optical densities for 14 atmospheric layers that spanned sea level to the top of the atmosphere.
Above the aircraft, vertical optical densities were combined and an air mass factor (AMF) was calculated to account for one-way
transmission. Vertical optical densities below the aircraft were also combined with an AMF reflecting two-way transmission. This
resulted in a two-layer atmospheric model that speeds up the retrieval and incorporates the ground elevation and flight altitude for each
AVIRIS-NG scene. The two-layer model was used to model reflected solar radiation perturbed by the absorbing species CH4,
CO2, H2O, and N2O. Three retrieval windows were used, each targeting the primary gas of interest. CH4
retrievals were performed between 2215 and 2410 nm (Fig. ) and included fits for H2O and N2O. Gas
Jacobians that reflect changes in absorption due to the absorbing species CH4, CO2, and H2O are shown in Fig. .
Because N2O has weak absorption features, these Jacobians are not shown. Between 1904 and 2099 nm, CO2
retrievals included H2O and N2O as additional unknown variables of the retrieval, while H2O retrievals between
1103 and 1178 nm also included CO2 and N2O. Therefore, the state vector (xn) for each retrieval
window has six entries (three gases for two atmospheric layers). Modeled radiance at high spectral resolution was calculated for each
wavelength with a forward radiative transfer model using the following
equation:
Fhrxi=I0hr⋅exp-∑n=16An⋅τnref⋅xn,i⋅∑i=0kakλk,
where Fhrxi is the forward modeled
radiance at the ith iteration of the state vector; I0hr is
the incident intensity, a solar transmission spectrum (G. Toon, personal communication, 2013); An is the AMF
for each n number of atmospheric state vector elements; τnref is the reference vertical optical density
for each n number of atmospheric state vector elements (including optical densities of the three absorbing species); xn,i is
the trace-gas-related state vector at the ith iteration, which scales the prior optical densities of each of the absorbing species in
each n layer (six rows, three gases for two atmospheric layers); and ak are polynomial coefficients to account for low-frequency spectral variations.
The state vector contains the spectral shift (not shown here) and a low-order polynomial function (ak) to account for the
broadband variability in surface albedo see. The high-resolution modeled radiance is convolved using the
instrument line shape function and sampled to the center wavelengths for each AVIRIS-NG spectral band, resulting in a lower-resolution
modeled radiance at the ith iteration of the state vector Flrxi, calculated using a known
τnref scaled by xn,i.
A Jacobian matrix is calculated for each iteration i, where each column represents the derivate vector of the sensor radiance with
respect to each element of the state vector (xi).
Ki=∂Flr(x)∂xxi
The state vector at the ith iteration can be optimized as follows
:
xi+1=xa+KiTSε-1Ki+Sa-1-1KiTSε-1⋅y-Flrxi+Ki(xi-xa),
where xa is the a priori state vector (six rows),
xi is the state vector at the ith iteration (six rows),
Sε is the error covariance matrix,
Sa is the a priori covariance matrix, y is the measured AVIRIS-NG radiance, Flrxi
is the forward model evaluated at xi, and Ki is the Jacobian of the forward model at xi.
(a) AVIRIS-NG true color image subset. (b) A small CH4 plume is visible from a confirmed geological
source at Moving Mountain near Durango, Colorado. (c) Close-up of AVIRIS-NG true color image. (d) Higher-resolution Google Earth
imagery provides additional spatial context. For all images, north is up.
The retrieval optimizes a scaling factor relative to the a priori profile. The a priori scaling factor is set to one as an initial
guess for each gas in the two layers, while the a priori covariance matrix was set to constrain the fit to the atmospheric layer
beneath the aircraft where high variance is expected. To do so, very small prior covariances were set for the uppermost layer (above
the aircraft). Because the observed plumes are not expected to extend above the AVIRIS-NG flight altitude, this assumption is
reasonable. Gas concentrations were calculated in ppm⋅ m by multiplying the gas state vector at the last iteration (gas scaling
factor) by the VMR for the lowest layer of the reference atmosphere and the distance between the aircraft and the ground. In subsequent
figures, color bars will indicate the scaling factors and gas enhancements relative to background, which were calculated by
subtracting the retrieved gas concentration from the background concentration for the lowest layer of the reference atmosphere.
The covariance S^ was calculated to estimate expected IMAP-DOAS retrieval errors as follows:
S^=KTSε-1K+Sa-1-1,
where the diagonal of S^ corresponds to the covariance at each atmospheric layer associated with the gases used for each fitting
window. Sε, the error covariance matrix, is a diagonal matrix representing expected errors for the retrieval
algorithm. For each gas retrieval, the square root of the corresponding diagonal entry of S^ is multiplied by the VMR in the
lowest layer of the atmospheric model for each retrieved gas (CH4: 1.86 ppm; CO2: 399 ppm; H2O:
7745 ppm). Using scene parameters for a 1 km flight altitude a.g.l. with 25.6∘ solar zenith and variable signal-to-noise
ratio, this corresponds to an error of between 0.14 and 0.55 ppm CH4 beneath the aircraft. For CO2, the error ranges
between 6.6 and 26.4 ppm and for H2O between 9.4 and 37.5 ppm.
ResultsCH4 emissions from natural gas sector
AVIRIS-NG identified over 250 CH4 plumes during the Four Corners flight campaign using a linearized
matched filter . The linearized matched filter models the background of radiance spectra as a multivariate Gaussian
and provides a scalar value that represents the fraction of the gas target signature that perturbs the background. Because the target
signature is defined as the change in radiance of the background caused by adding a unit mixing ratio length of CH4, detected
quantities are reported in mixing ratio lengths (ppm⋅ m). This method is computationally efficient and accounts for the full covariance of
background (atmosphere and surface) and instrument noise using in-scene data, providing high sensitivity to local enhancements.
The current speed of the IMAP-DOAS retrieval algorithm precludes it from being applied to all 250 examples presented in the previous
study . Instead, IMAP-DOAS retrievals for only a few examples will be presented here, reflecting CH4,
CO2, and H2O plumes from a variety of emission sources. The first example from a 20 April 2015 flight at
1.1 kma.g.l. (Fig. b) is made up of at least 10 plumes with maximum enhancements in excess of 5000 ppmm,
which is equivalent to a concentration of 0.5 % in a 1 m thick layer or roughly an XCH4 (dry air column-averaged mole
fraction) enhancement of around 500 ppb that is almost 25 % of a total background column. Results from the H2O
retrieval (Fig. e) do not indicate enhancements collocated with CH4 plumes. The true color image subset in
Fig. a reveals a few dirt roads, but the close-up of the AVIRIS-NG scene indicated by the black boxes in
Fig. a and b indicates some visible infrastructure that is difficult to interpret at the 1 m AVIRIS-NG pixel resolution
(Fig. c).
In Fig. d, Google Earth imagery for the same area provides improved spatial resolution and reveals what appears to be
drilling rigs at an active underground coal mine on 15 March 2015, suggesting the origin of these plumes are mine workings ventilation
shafts. estimated an aggregate flux of 2236 kgh-1 for these plumes. Measured and modeled radiance is
shown for one image pixel within the CH4 plume for the CH4 retrieval fitting window (Fig. a) and for the
H2O retrieval (Fig. a). For both examples, the residuals are also plotted (Fig. b, Fig. b) in
addition to the 1σ SD boundary calculated from residuals for the entire scene.
Additional examples are presented in Appendix , including from another 20 April 2015 flight at 1.4 kma.g.l.
that results in a 1.2 m resolution (Fig. b). Multiple CH4 plumes are visible from this gas processing
facility, one emanating from a source beyond the east edge of the AVIRIS-NG scene. This example was associated with a planned
maintenance operation, which resulted in a large temporary CH4 plume that was recorded and reported through the normal
Greenhouse Gas Reporting Program . A second plume is visible at a location shown by the black box in
Fig. a, indicating white pipes associated with an interstate pipeline as the likely emission source (Fig. c and
d).
(a) AVIRIS-NG true color image subset. (b)CO2 plume is visible. (c) Close-up of AVIRIS-NG
true color image. (d) Higher-resolution Google Earth imagery provides additional spatial context. For all images, north is up.
(a) AVIRIS-NG measured and modeled radiance for one image pixel within the CO2 plume for the CO2 retrieval
(see Fig. b). (b) The residual is plotted with 1σ SD boundary calculated from residuals for the entire scene.
An H2O retrieval was also performed for this scene and did not reveal enhancements collocated with the CH4 plumes. For
all subsequent examples, H2O retrievals were performed but will be shown only in cases where H2O plumes were observed
(see Sect. ). As shown in Fig. a, the CH4 plumes cross over many land cover types with variable
brightness and very dark surfaces resulted in anomalously high retrievals. CH4 results from radiances less than
0.01 µWcm-2sr-1nm-1 for any band of the CH4 fitting window, corresponding to shadows and water, were
removed from the results shown in Fig. b.
In Fig. b and e, CH4 emissions from a tank were observed on 19 and 21 April 2015 at 2.8 and 3.2 kma.g.l.
(pixel resolutions of 2.6 and 3.0 m respectively). The Google Earth close-up shown in Fig. d indicates a tank as
the likely emission source, which was confirmed by the ground crew using a thermal imaging camera on multiple days. Video A1 (see
Supplement) was acquired on 21 April 2015 at around 18:00 UTC and clearly shows a CH4 plume originating at the top of the tank
that is consistent with the AVIRIS-NG CH4 plume observed the same day.
In , CH4 emissions from a pipeline leak were presented see Fig. 4 and Movie S2;
and subsequent to publication another suspected pipeline leak Fig. S6; was confirmed (K. Spray, Department
of Energy, personal communication, 2016). That leak was independently identified and repaired by the operator as a part of their normal
operations prior to publication. In Fig. b, the CH4 plume from the 19 April 2015 flight at 3.0 kma.g.l.
(2.7 m pixel resolution) does not appear associated with visible infrastructure and subsequent investigation by the ground
crews identified the plume origin on 24 April 2015 using the thermal camera (Video A2, see Supplement). This location was along
a marked, buried natural gas pipeline and was subsequently confirmed as a pipeline leak and ultimately shut down for repairs by the
local pipeline operators. The estimated flux for this example is 28 kgh-1, which would result in an
estimated annual loss of 13.2 million cubic feet, equivalent to USD 100 000 (assuming constant annual flux and average cost of USD 7.40
per thousand cubic feet).
Geological CH4 emissions
AVIRIS has been used for quantitative retrievals of CH4 for marine seeps and more recently a plume
observed with AVIRIS-NG was verified as a geological source see Fig. S6 in. Subsequent analysis of the Four
Corners data set revealed another CH4 plume from a confirmed geological source at Moving Mountain near Durango, Colorado
. This AVIRIS-NG scene was acquired at 1.3 kma.g.l. (1 m pixel resolution) and shows a 10 m long
plume (Fig. b).
CO2 and H2O emissions from power plants
While demonstrated the ability of AVIRIS for high-resolution mapping of CO2 plumes, in this study we present
two examples using quantitative retrievals. The first example is from the coal-fired San Juan Generating Station near Farmington, New
Mexico, that was flown on 20 April 2015 at 1.2 kma.g.l. Two CO2 plumes are clearly visible in Fig. b and
correspond to two flue-gas stacks that appear active given visible emissions in the true color image (Fig. a, c). A third
flue-gas stack appears inactive (Fig. a) with no visible CO2 plume (Fig. b). The San Juan Generating
Station reported 2015 emissions of 9843 kt of CO2, equivalent to a flux of 1 123 666 kgCO2h-1. An example of a CO2 retrieval fit and the residual is shown in (Fig. ).
The second example is from a 12 September 2014 flight that included the coal-fired Craig Station near Craig, Colorado. CO2
plumes are visible from flue-gas stacks (Fig. b) and extend more than 1 km downwind. This power plant reported 2014
emissions of 9300 kt of CO2, equivalent to a flux of 1 061 644 kgCO2h-1. Within the
same scene, an H2O plume is also visible (Fig. d) emanating from a region that contains a number of cooling towers
adjacent to two large cooling ponds (Fig. a). CH4 retrieval results are also shown in Fig. c,
indicating that
CH4 plumes are not visible in the scene and emphasizing the ability of these retrievals to distinguish between CH4 and
H2O despite spectral interference (see Fig. ). Results for dark surfaces like the cooling ponds were removed from
Fig. b by excluding radiances less than 0.10 µWcm-2sr-1nm-1 for any band of the CO2
fitting window, for radiances less than 0.002 µWcm-2sr-1nm-1 for any band of the H2O fitting window
(Fig. d), and for radiances less than 0.01 µWcm-2sr-1nm-1 for any band of the CH4
fitting window (Fig. c).
In Fig. a, the AVIRIS-NG true color image is shown for the close-up indicated by the black box in Fig. . The
flue-gas stacks are visible in the lower left as CO2 sources and cooling towers in the upper right as possible H2O
sources. Ellipses delineate the shapes of plumes visible in the true color images for the flue-gas stacks (red) and cooling towers
(blue). The arrows indicate winds to the southeast for the flue-gas stacks (consistent with CO2 plumes in Fig. b)
and to the east for the cooling towers (consistent with H2O plumes in Fig. d). In b, the higher-resolution Google Earth imagery clearly indicates the flue-gas stacks are much taller (182 m) than the cooling tower
based on assessment of shadows, which could explain variable wind directions at the flue-gas stacks and in the vicinity
of the cooling towers. Given the presence of the cooling ponds immediately adjacent to the cooling towers, it is unclear whether the
observed H2O plume shown in Fig. d is caused solely by the cooling towers or reflects the combined influence of the
towers and evaporation from the cooling ponds.
Conclusions
In this study, we use the airborne imaging spectrometer AVIRIS-NG and the IMAP-DOAS retrieval to generate gas concentration maps for
observed CH4, CO2, and H2O
plumes. While more than 250 CH4 plumes were observed in the San Juan Basin near Four Corners , this study
focused on a few results from anthropogenic and natural sources, including emissions from mine ventilation shafts, a gas processing
plant, tank, pipeline leak, and natural seep. In addition, CO2 emissions were observed from the flue stacks of two coal-fired
power plants and an H2O plume was mapped for the cooling towers for one power plant. Observed plumes were consistent with known
and suspected emission sources verified by true color AVIRIS-NG imagery and higher-resolution Google Earth imagery.
AVIRIS-NG has the high spatial resolution necessary to resolve small-scale emissions and can map large regions quickly, covering
the 2500 km2 Four Corners study in approximately 2 days (9.2 flight hours). This capability is aided by real-time
detection and geolocation of gas plumes, permitting unambiguous identification of individual emission source locations and
communication to ground teams for rapid follow-up. This permitted verification of a number of emission sources presented in this study
using a thermal camera, including a tank and buried natural gas pipeline. The AVIRIS and AVIRIS-NG instruments have demonstrated
CH4 plume mapping capabilities at multiple flight altitudes, ranging from as low as 0.4 to 3.8 kma.g.l.
(0.4 to 3.8 m pixels) for a controlled release experiment to 9 kma.g.l. for the Coal Oil Point
marine seeps (Thorpe et al., 2014). AVIRIS observed the Aliso Canyon leak on multiple flight days at 6.6 kma.g.l.
(6.6 m pixels) while the Hyperion imaging spectrometer, also 10 nm spectral resolution but 30 m pixels, mapped
the plume and demonstrated the potential for a space-based application .
This study demonstrates a comprehensive greenhouse gas monitoring capability that targets CH4 and CO2, the two dominant
anthropogenic climate-forcing agents. The ability to identify individual point source locations of CH4 and CO2
emissions has relevance to the research community and the private sector. Understanding the spatial and temporal distribution and the magnitude of these emissions is of interest given the large uncertainties associated with anthropogenic emissions. This
includes industrial point source emissions of CH4 and CO2, CH4 from oil and gas operations as well as natural
gas distribution and storage, CH4 from agricultural sources, and CH4 and CO2 from landfills. Site operators
could identify and mitigate CH4 emissions, which reflect both a potential safety hazard and lost revenue. Water vapor results
demonstrate the ability of these retrievals to distinguish between CH4 and H2O despite spectral interference in the
shortwave infrared while offering the potential to improve atmospheric correction and reflectance retrievals with application to the
fields of ecology and meteorology.
Despite these promising results, an imaging spectrometer built exclusively for quantitative mapping of gas plumes would have improved
sensitivity compared to AVIRIS-NG . For example, an instrument providing a 1 nm spectral resolution and
sampling (2000–2400 nm) would permit mapping CH4, CO2, H2O, CO, and N2O from more diffuse
sources using both airborne and orbital platforms . The ability to identify emission sources offers the potential to
constrain regional greenhouse gas budgets and improve partitioning between anthropogenic and natural emission sources. Because the
CH4 lifetime is only about 9 years and CH4 has a high GWP, targeting reductions in anthropogenic
CH4 emissions offers an effective approach to decrease overall atmospheric radiative forcing.
The AVIRIS-NG data used in this study are available upon request at http://avirisng.jpl.nasa.gov/ or
http://aviris.jpl.nasa.gov/. Videos showing methane plumes observed using a thermal
imaging camera are available at 10.5446/30884 and 10.5446/30883 (Thorpe and Krohn, 2017a, b).
This appendix contains additional figures referenced in Sect. .
CH4 emissions from gas processing facility
(a) AVIRIS-NG true color image subset. (b) Multiple CH4 plumes are visible
from this gas processing facility, one emanating from a source beyond the east edge of the AVIRIS-NG scene. A second plume is
visible at a location shown by the black box. (c) Close-up of AVIRIS-NG true color image indicates white pipes
associated with an interstate pipeline as the likely emission source. (d) Higher-resolution Google Earth imagery
provides additional spatial context. For all images, north is up.
CH4 emissions from tank
(a) AVIRIS-NG true color image subset from 19 April 2015. (b) Prominent CH4 plume visible
from location indicated by the black box. (c) Close-up of 19 April 2015 AVIRIS-NG true color image. (d)
Higher-resolution Google Earth imagery indicates the emission source is a tank. (e) Scene from 21 April 2015 indicates
a CH4 plume from the same source with an different orientation due to changes in wind direction. For all images,
north is up. A thermal camera video for this source is shown in Video A1.
CH4 emissions from pipeline leak
(a) AVIRIS-NG true color image subset. (b) A CH4 plume is visible for a confirmed
leak from a buried natural gas pipeline. (c) Close-up of AVIRIS-NG true color image. (d) Higher-resolution
Google Earth imagery does not indicate visible infrastructure. For all images, north is up. A thermal camera video for this source is shown in Video A2.
CO2 and H2O emissions from power plant
(a) AVIRIS-NG true color image subset. (b)CO2 plumes are visible emanating from
flue-gas stacks. (c)CH4 retrieval results. (d)H2O plume visible from cooling towers
(see Fig. ). For all images, north is up.
(a) AVIRIS-NG true color image for close-up indicated by black box in Fig. . Flue-gas
stacks visible in lower left as CO2 sources and cooling towers in upper right as H2O sources. Ellipses
delineate shapes of plumes visible in true color images for the flue-gas stacks (red) and cooling towers (blue). The
arrows indicate winds to the southeast for the flue-gas stacks (consistent with CO2 plumes in Fig. b)
and to the east for the cooling towers (consistent with H2O plumes in Fig. d). (b) Higher-resolution
Google Earth imagery clearly indicates the flue-gas stacks are much taller than the cooling towers based on assessment of shadows.
For both images, north is up.
The Supplement related to this article is available online at https://doi.org/10.5194/amt-10-3833-2017-supplement.
CF and AKT designed research; CF, ADA, AKT, DRT, BDB, ROG, EAK, CS and SC provided flight campaign support; AKT, CF, DRT, KG, TK and
JB performed research; RMD, ROG, KG, TK, JB, DAR and PED advised the research; AKT and CF analyzed data and wrote the paper.
The authors declare that they have no conflict of interest.
Acknowledgements
The authors thank NASA HQ and Jack Kaye for funding the flight campaign. We would like to acknowledge the contributions of the
AVIRIS-NG flight and instrument teams, including Michael Eastwood, Sarah Lundeen, Ian Mccubin, Mark Helmlinger, Scott Nolte, and
Betina Pavri. We would also like to thank Simon Hook and Bill Johnson for their support and for the use of the thermal camera. This
work was undertaken in part at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA.
Edited by: Andreas Hofzumahaus
Reviewed by: two anonymous referees
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