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Atmos. Meas. Tech., 17, 5861–5885, 2024
https://doi.org/10.5194/amt-17-5861-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Local and regional enhancements of CH
4
, CO, and CO
2
inferred
from TCCON column measurements
Kavitha Mottungan
1,a
, Chayan Roychoudhury
1
, Vanessa Brocchi
1,b
, Benjamin Gaubert
3
, Wenfu Tang
3
,
Mohammad Amin Mirrezaei
1
, John McKinnon
1
, Yafang Guo
1
, David W. T. Griffith
4
, Dietrich G. Feist
5,6,7
,
Isamu Morino
8
, Mahesh K. Sha
9
, Manvendra K. Dubey
10
, Martine De Mazière
9
, Nicholas M. Deutscher
4
,
Paul O. Wennberg
11
, Ralf Sussmann
12
, Rigel Kivi
13
, Tae-Young Goo
14
, Voltaire A. Velazco
15
, Wei Wang
16
, and
Avelino F. Arellano Jr.
1,2
1
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ 85721, USA
2
Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ 85721, USA
3
NSF National Center for Atmospheric Research, Boulder, CO 80307, USA
4
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences,
University of Wollongong, Wollongong, Australia
5
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany
6
Physik der Atmosphäre, Ludwig-Maximilians-Universität München, Munich, Germany
7
Max Planck Institute for Biogeochemistry, Jena, Germany
8
National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
9
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
10
Los Alamos National Laboratory, Earth Systems Observations (EES-14), Los Alamos, NM 87545, USA
11
Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA
12
Institute of Meteorology and Climate Research Atmospheric Environmental Research (IMK-IFU),
Karlsruhe Institute of Technology, Karlsruhe, Germany
13
Space and Earth Observation Centre, Finnish Meteorological Institute, Sodankylä, Finland
14
Convergence Meteorological Research Department, National Institute of Meteorological Sciences (NIMS),
Seogwipo city 63568, Korea
15
Deutscher Wetterdienst (DWD), Meteorological Observatory Hohenpeissenberg, 82383 Hohenpeissenberg, Germany
16
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei, China
a
now at: National Physical Laboratory (NPL), Teddington, UK
b
now at: Atmo Auvergne-Rhône-Alpes, association agréé de surveillance de la qualité de l’air, 69500 Bron, France
Correspondence:
Avelino F. Arellano Jr. (afarellano@arizona.edu)
Received: 8 March 2024 – Discussion started: 3 April 2024
Revised: 25 June 2024 – Accepted: 31 July 2024 – Published: 7 October 2024
Abstract.
In this study, we demonstrate the utility of avail-
able correlative measurements of carbon species to identify
regional and local air mass characteristics as well as their
associated source types. In particular, we combine different
regression techniques and enhancement ratio algorithms with
carbon monoxide (CO), carbon dioxide (CO
2
), and methane
(CH
4
) total column abundance from 11 sites of the Total
Carbon Column Observing Network (TCCON) to infer rel-
ative contributions of regional and local sources to each of
these sites. The enhancement ratios provide a viable alter-
native to univariate measures of relationships between the
trace gases that are insufficient in capturing source-type and
transport signatures. Regional enhancements are estimated
from the difference between bivariate regressions across a
specific time window of observed total abundance of these
species (BERr for bulk enhancement regression ratio) and
inferred anomalies (AERr for anomaly enhancement regres-
sion ratio) associated with a site-specific background. Since
Published by Copernicus Publications on behalf of the European Geosciences Union.
5862
K. Mottungan et al.: Local and regional enhancements of CH
4
, CO, and CO
2
BERr and AERr represent the bulk and local species en-
hancement ratio, respectively, its difference simply repre-
sents the site-specific regional component of these ratios. We
can then compare these enhancements for CO
2
and CH
4
with
CO to differentiate between combustion and non-combustion
air masses. Our results show that while the regional and lo-
cal influences in enhancements vary across sites, dominant
characteristics are found to be consistent with previous stud-
ies over these sites and with bottom-up anthropogenic and
fire emission inventories. The site in Pasadena shows a domi-
nant local influence (
>
60 %) across all species enhancement
ratios, which appear to come from a mixture of biospheric
and combustion activities. In contrast, Anmyeondo shows
more regionally influenced (
>
60 %) air masses associated
with high-temperature and/or biofuel combustion activities.
Ascension Island appears to only show a large regional in-
fluence (
>
80 %) on CO
/
CO
2
and CO
/
CH
4
, which is in-
dicative of transported and combustion-related CO from the
nearby African region, consistent with a sharp rise in column
CO (3.51
±
0.43 % ppb yr
1
) at this site. These methods have
important applications to source analysis using spaceborne
column retrievals of these species.
1 Introduction
The rise in the abundance of greenhouse gases (e.g., CO
2
(carbon dioxide), CH
4
(methane)) in recent decades, because
of anthropogenic activities and natural emissions associated
with climate change, such as wetland and biomass burning
emissions associated with El Niño (Zhang et al., 2018; Ku-
mar et al., 2023; van Vuuren and Riahi, 2008; Arneth et al.,
2017), has large implications for quantifying atmospheric
chemistry–climate relationships. This rising trend increases
the complexity of understanding the feedback mechanism
between CH
4
, OH (hydroxyl), and CO (carbon monoxide);
retrieval bias in less validated regions or unresolved uncer-
tainty in tropical emissions (e.g., based on TROPOspheric
Monitoring Instrument (TROPOMI) and Greenhouse Gases
Observing Satellite (GOSAT)) (Lunt et al., 2019; Palmer et
al., 2019); and emission estimates from fossil fuel use over
growing megacities (Tang et al., 2020; Maasakkers et al.,
2019). Understanding today’s regional CO
2
and CH
4
sources
and sinks is a key area in carbon cycle and atmospheric com-
position science, given the necessity for reliable projections
of future atmospheric CO
2
and CH
4
concentrations. This is
especially problematic in megacities with the fastest pace
of urbanization and where the anthropogenic activities are
most intense, accompanied by immense energy consump-
tion mainly in the form of fossil fuel combustion (Kennedy
et al., 2015; Grimm et al., 2008; Agudelo-Vera et al., 2012;
Banerjee et al., 1999; Lamb et al., 2021). Emission estimates
from fossil fuels remain uncertain due to the poor character-
ization of combustion activity, efficiency, fuel-use mixtures
emerging from the lack of details on pollution control strate-
gies, energy use, and combustion practices (Zhu et al., 2012;
Creutzig et al., 2015; Kennedy et al., 2009; Baiocchi et al.,
2015; Weisz and Steinberger, 2010; Bettencourt et al., 2007;
Dodman, 2009; Bai et al., 2018). The high-efficiency com-
bustion of fossil fuels leads to large CO
2
emissions com-
pared to CO, whereas low-efficiency combustion of residen-
tial combustion and biomass burning, among others, pro-
duces more CO (Andreae and Merlet, 2001; Silva and Arel-
lano, 2017; Halliday et al., 2019; Tang et al., 2019; Wei et
al., 2012; Andreae, 2019; Park et al., 2021). This uncertainty
is further complicated by limited observations at the spa-
tiotemporal scales necessary to resolve variations in combus-
tion and fuel-use patterns (Streets et al., 2013; Nassar et al.,
2013; Hutyra et al., 2014; Gately and Hutyra, 2017; Creutzig
et al., 2019; Arioli et al., 2020). This leads to difficulties in
teasing small anthropogenic signatures from the large natu-
ral sources and sinks dominating the carbon cycle and the
uncertainties in modeling atmospheric transport (Peylin et
al., 2013; Thompson et al., 2016; Erickson and Morgenstern,
2016; Oda et al., 2019; Duncan et al., 2020; Gaubert et al.,
2019). This is especially true for flux estimations of CO
2
and
CH
4
using top-down approaches, despite the increase in air-
craft and satellite measurements of CO
2
and CH
4
abundance
in recent years (Hutyra et al., 2014; Houweling et al., 2015,
2017; Chevallier et al., 2019; Crowell et al., 2019; Lu et al.,
2021; Chandra et al., 2021). Studies have also highlighted the
importance of fossil fuel emission uncertainties for their es-
timates, suggesting the need for temporally defined emission
inventories (Gurney et al., 2005; Peylin et al., 2011; Thomp-
son et al., 2016; Saeki and Patra, 2017; Gurney et al., 2020).
The abundance of a species at a particular location is
mainly dependent on the variations of sources and sinks. Fur-
thermore, both regional transport and local transport (long-
range, vertical transport and dilution in the boundary layer)
influence the abundance of the species (especially in the col-
umn) and confound measurement interpretations. The ma-
jor sources of CO
2
include anthropogenic emissions, espe-
cially fossil fuel combustion, cement production, and land-
use change, while sinks include uptakes by ocean and land
from the atmosphere (Friedlingstein et al., 2022). While
CO is primarily produced through incomplete combustion of
carbon-containing fuels, oxidation of CH
4
and other volatile
organic compounds by OH contributes to secondary produc-
tion of CO (Bakwin et al., 1995; Gaubert et al., 2016; Hoesly
et al., 2018). The main chemical sink of CO in the atmo-
sphere is OH, followed by dry deposition through soil up-
take (Levy, 1971; Bartholomew and Alexander, 1981; Khalil
and Rasmussen, 1990; Cordero et al., 2019). This coupling
of CH
4
–OH–CO has significant impacts on the growth rate
and source–sink characterization of CH
4
(Gaubert et al.,
2017; Zhao et al., 2019, 2020; Guthrie, 1989; Prather, 1994;
Lelieveld et al., 2002). Anthropogenic sources of CH
4
in-
clude agricultural activities (rice and livestock), solid waste,
fossil fuels, and biomass burning in addition to natural
Atmos. Meas. Tech., 17, 5861–5885, 2024
https://doi.org/10.5194/amt-17-5861-2024