of 15
Atmos. Meas. Tech., 12, 6667–6681, 2019
https://doi.org/10.5194/amt-12-6667-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Towards accurate methane point-source quantification from
high-resolution 2-D plume imagery
Siraput Jongaramrungruang
1
, Christian Frankenberg
1,2
, Georgios Matheou
3
, Andrew K. Thorpe
2
, David
R. Thompson
2
, Le Kuai
4
, and Riley M. Duren
2
1
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
2
NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
3
Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA
4
Joint Institute for Regional Earth System Science and University of California, Los Angeles, CA 90095, USA
Correspondence:
Siraput Jongaramrungruang (siraput@caltech.edu) and Christian Frankenberg (cfranken@caltech.edu)
Received: 25 April 2019 – Discussion started: 6 May 2019
Revised: 18 October 2019 – Accepted: 22 October 2019 – Published: 17 December 2019
Abstract.
Methane is the second most important anthro-
pogenic greenhouse gas in the Earth climate system but emis-
sion quantification of localized point sources has been proven
challenging, resulting in ambiguous regional budgets and
source category distributions. Although recent advancements
in airborne remote sensing instruments enable retrievals of
methane enhancements at an unprecedented resolution of 1–
5 m at regional scales, emission quantification of individual
sources can be limited by the lack of knowledge of local
wind speed. Here, we developed an algorithm that can esti-
mate flux rates solely from mapped methane plumes, avoid-
ing the need for ancillary information on wind speed. The al-
gorithm was trained on synthetic measurements using large
eddy simulations under a range of background wind speeds
of 1–10 m s
1
and source emission rates ranging from 10
to 1000 kg h
1
. The surrogate measurements mimic plume
mapping performed by the next-generation Airborne Visi-
ble/Infrared Imaging Spectrometer (AVIRIS-NG) and pro-
vide an ensemble of 2-D snapshots of column methane en-
hancements at 5 m spatial resolution. We make use of the
integrated total methane enhancement in each plume, de-
noted as integrated methane enhancement (IME), and in-
vestigate how this IME relates to the actual methane flux
rate. Our analysis shows that the IME corresponds to the
flux rate nonlinearly and is strongly dependent on the back-
ground wind speed over the plume. We demonstrate that the
plume width, defined based on the plume angular distribu-
tion around its main axis, provides information on the associ-
ated background wind speed. This allows us to invert source
flux rate based solely on the IME and the plume shape itself.
On average, the error estimate based on randomly generated
plumes is approximately 30 % for an individual estimate and
less than 10 % for an aggregation of 30 plumes. A validation
against a natural gas controlled-release experiment agrees to
within 32 %, supporting the basis for the applicability of this
technique to quantifying point sources over large geographi-
cal areas in airborne field campaigns and future space-based
observations.
1 Introduction
Methane is the second most important anthropogenic green-
house gas in Earth’s atmosphere, with additional indirect im-
pacts as it affects both tropospheric ozone and stratospheric
water vapor. Despite its significance, our understanding of
global and regional CH
4
budgets has remained inadequate
due to the fact that the strength and distribution of CH
4
emissions from various source types are not well-constrained
(Houweling et al., 2017; Turner et al., 2017). Estimates of
CH
4
emissions from point sources (e.g., at facility scale) are
particularly uncertain, since space-based observations lack
sufficiently fine spatial resolutions while in situ measure-
ments are too sparse and mostly representative of large-scale
background concentrations. Improved estimates of the CH
4
emissions at this point-source scale are critical in guiding
emission mitigation efforts.
Published by Copernicus Publications on behalf of the European Geosciences Union.
6668
S. Jongaramrungruang et al.: CH
4
quantification from 2-D plume imagery
Recent developments in airborne imaging spectroscopy
techniques to quantify CH
4
plumes have opened the way
for CH
4
measurements at a sufficiently high spatial resolu-
tion needed to differentiate various local sources within re-
gional scales (Frankenberg et al., 2016; Hulley et al., 2016;
Thompson et al., 2015; Thorpe et al., 2016a, 2017; Tratt et
al., 2014). A recent airborne campaign in the Four Corners
region retrieved column methane enhancements at a resolu-
tion of 3 m (Frankenberg et al., 2016), enabling the obser-
vation of the plume shape in the direct vicinity of the point
source. During the campaign, many plumes of various sizes
ranging from a few tens of meters to hundreds of meters were
detected across the region, with the majority of their source
emission rates between 10 and 1000 kg (CH
4
) h
1
(Franken-
berg et al., 2016). This allows for an effective way to re-
motely identify and locate CH
4
emissions from point sources
such as pipeline leaks or oil and gas facilities. The retrievals
provide the quantification of a column enhancement (e.g., in
molecule cm
2
above background), which can be integrated
across the entire methane plume to derive the total amount of
methane within the plume, denoted as integrated methane en-
hancement (IME, either in molecule or mass units, Franken-
berg et al., 2016). In addition, the instrument observes the
fine structure of the plume at an unprecedented spatial reso-
lution. However, the flux inversion from the observed plumes
to the actual emission rate at the source remains complicated
due to the dependence on tropospheric boundary layer con-
ditions such as wind speed and atmospheric stability during
the overpass. To interpret the relationship between the ob-
served plumes and flux rates, previous studies have relied
on Gaussian plume inversion models (Krings et al., 2011,
2013; Rayner et al., 2014; Nassar et al., 2017; Schwandner
et al., 2017) or an airborne in situ approach using a mass
balance calculation based on the enhancement downwind of
the source (Cambaliza et al., 2015; Conley et al., 2016; Gor-
don et al., 2015; Jacob et al., 2016; Lavoie et al., 2015).
Frankenberg et al. (2016) used a simple linear scaling be-
tween the IME and flux rate, which allowed for a straight-
forward derivation of fluxes from the observed IME given
an averaged wind speed across a large region for the cam-
paign over several days. Varon et al. (2018) estimated the
flux rate as the IME divided by the residence time of methane
in the plume calculated based on the effective length of the
plume from its area and the effective wind speed inferred
from 10 m wind speed by in situ measurement or meteoro-
logical reanalysis data. All of these methods rely on knowl-
edge of local wind speed, which is acquired through either
in situ wind measurements or the estimation from meteoro-
logical forecast or reanalysis data. The former can be costly
and time consuming without prior knowledge of source lo-
cations, while the latter can be inaccurate due to the rapid
changes of a local plume over a much shorter temporal and
spatial scale (minutes, hundreds of meters) than the typical
atmospheric reanalysis products (a-few-hourly average, tens
of kilometers).
In this work, we aim to improve our understanding of
how the inferred emission rates change under different atmo-
spheric conditions, e.g., the errors due to a lack of accurate
wind measurements. To investigate this relationship and as-
sociated errors, we used large eddy simulations (LESs, Math-
eou and Bowman, 2016) to simulate the plume dynamics
at high spatial resolution (5 m) with prescribed source rates
under various background wind speeds and typical surface
latent and sensible heat fluxes. Using 3-D LES model out-
put for each snapshot, we simulated synthetic 2-D airborne
measurements by applying the respective averaging kernels.
Based on these synthetic measurements, we developed an al-
gorithm to deduce the wind speed from the plume’s spatial
distribution and investigate the degree to which the flux rate
can be inverted from only the remotely sensed CH
4
retrievals.
This allowed us to perform an end-to-end test of errors in in-
verted methane fluxes in both the absence and presence of
ancillary information on the actual wind speed (Sect. 6.3).
This work was inspired by the use of IME to quantify
methane single-point sources from field campaigns using air-
borne instruments. These plumes generally are of small-to-
medium sizes (
<
2 km). The concept, nevertheless, can be
applicable to larger sources as well as toward measurement
of localized sources from space in the coming decade for
satellite retrievals at a much finer spatial resolution (Thorpe
et al., 2016b).
Section 2 illustrates the plume observations and the instru-
ment specifications. Section 3 will give a brief overview of
Gaussian plume modeling. The setup of the LES and appli-
cation of instrument operators to simulate airborne measure-
ments are described in Sects. 4 and 5 respectively. Section 6
shows simulated plumes under different atmospheric scenar-
ios and the relationship between observed IME and actual
emission rates. The error analysis of flux inversion based on
the IME method is also provided. The final section provides
a discussion and conclusion.
2 Plume observations and instrument specifications
Figure 1 shows examples of observed methane plumes us-
ing the next-generation Airborne Visible/Infrared Imaging
Spectrometer (AVIRIS-NG) and the Hyperspectral Thermal
Emission Spectrometer (HyTES) during the Four Corners
flight campaign (Frankenberg et al., 2016). The iterative
maximum a posteriori differential optical absorption spec-
troscopy (IMAP-DOAS) method (Thompson et al., 2015)
and clutter matched filter (CMF) were used to retrieve the
scenes from AVIRIS-NG and HyTES respectively. In this
case, the aircraft repeatedly flew over a coal mine venting
shaft, with approximately 10 min revisit time. Evidently, the
plume is changing in time and exhibits fine-scaled features
due to atmospheric turbulence. Quantifying the source rate
from detected plumes using atmospheric simulations to un-
derstand their behavior and variations in space and time is
Atmos. Meas. Tech., 12, 6667–6681, 2019
www.atmos-meas-tech.net/12/6667/2019/
S. Jongaramrungruang et al.: CH
4
quantification from 2-D plume imagery
6669
Figure 1.
Methane plume over a venting shaft in the Four Corners region, observed from four individual AVIRIS-NG airborne instrument
overpasses (2.8 m spatial resolution) 7–9 min apart on 22 April 2015 between 16:19:02 and 16:45:06 UTC
(a–d)
compared with observations
from HyTES overpasses (2.3 m spatial resolution) in the similar interval between 16:17:16 and 16:47:17 UTC
(e–h)
. The background is from
©Google Earth imagery.
www.atmos-meas-tech.net/12/6667/2019/
Atmos. Meas. Tech., 12, 6667–6681, 2019