Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model

Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin Gurney, Debra Wunch, Paul O. Wennberg

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr-1 for the study period of July 2013-August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr-1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr-1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342-440 Gg CH4 yr-1). CO emissions are estimated at 487 ± 122 Gg CO yr-1, much lower than previous top-down estimates (1440 Gg CO yr-1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 %, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

Original languageEnglish (US)
Pages (from-to)16271-16291
Number of pages21
JournalAtmospheric Chemistry and Physics
Volume18
Issue number22
DOIs
StatePublished - Nov 16 2018
Externally publishedYes

Fingerprint

megacity
remote sensing
carbon
satellite data
urban area
trajectory
coast
air
basin
inversion
OCO

ASJC Scopus subject areas

  • Atmospheric Science

Cite this

Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model. / Hedelius, Jacob K.; Liu, Junjie; Oda, Tomohiro; Maksyutov, Shamil; Roehl, Coleen M.; Iraci, Laura T.; Podolske, James R.; Hillyard, Patrick W.; Liang, Jianming; Gurney, Kevin; Wunch, Debra; Wennberg, Paul O.

In: Atmospheric Chemistry and Physics, Vol. 18, No. 22, 16.11.2018, p. 16271-16291.

Research output: Contribution to journalArticle

Hedelius, JK, Liu, J, Oda, T, Maksyutov, S, Roehl, CM, Iraci, LT, Podolske, JR, Hillyard, PW, Liang, J, Gurney, K, Wunch, D & Wennberg, PO 2018, 'Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model', Atmospheric Chemistry and Physics, vol. 18, no. 22, pp. 16271-16291. https://doi.org/10.5194/acp-18-16271-2018
Hedelius, Jacob K. ; Liu, Junjie ; Oda, Tomohiro ; Maksyutov, Shamil ; Roehl, Coleen M. ; Iraci, Laura T. ; Podolske, James R. ; Hillyard, Patrick W. ; Liang, Jianming ; Gurney, Kevin ; Wunch, Debra ; Wennberg, Paul O. / Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model. In: Atmospheric Chemistry and Physics. 2018 ; Vol. 18, No. 22. pp. 16271-16291.
@article{cfa8883c5e9e4b08bce8754199400ae5,
title = "Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model",
abstract = "We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr-1 for the study period of July 2013-August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr-1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr-1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342-440 Gg CH4 yr-1). CO emissions are estimated at 487 ± 122 Gg CO yr-1, much lower than previous top-down estimates (1440 Gg CO yr-1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 {\%}, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.",
author = "Hedelius, {Jacob K.} and Junjie Liu and Tomohiro Oda and Shamil Maksyutov and Roehl, {Coleen M.} and Iraci, {Laura T.} and Podolske, {James R.} and Hillyard, {Patrick W.} and Jianming Liang and Kevin Gurney and Debra Wunch and Wennberg, {Paul O.}",
year = "2018",
month = "11",
day = "16",
doi = "10.5194/acp-18-16271-2018",
language = "English (US)",
volume = "18",
pages = "16271--16291",
journal = "Atmospheric Chemistry and Physics",
issn = "1680-7316",
publisher = "European Geosciences Union",
number = "22",

}

TY - JOUR

T1 - Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model

AU - Hedelius, Jacob K.

AU - Liu, Junjie

AU - Oda, Tomohiro

AU - Maksyutov, Shamil

AU - Roehl, Coleen M.

AU - Iraci, Laura T.

AU - Podolske, James R.

AU - Hillyard, Patrick W.

AU - Liang, Jianming

AU - Gurney, Kevin

AU - Wunch, Debra

AU - Wennberg, Paul O.

PY - 2018/11/16

Y1 - 2018/11/16

N2 - We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr-1 for the study period of July 2013-August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr-1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr-1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342-440 Gg CH4 yr-1). CO emissions are estimated at 487 ± 122 Gg CO yr-1, much lower than previous top-down estimates (1440 Gg CO yr-1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 %, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

AB - We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the SoCAB to be 104 ± 26 Tg CO2 yr-1 for the study period of July 2013-August 2016. We obtain a slightly higher estimate of 120 ± 30 Tg CO2 yr-1 using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360 ± 90 Gg CH4 yr-1) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342-440 Gg CH4 yr-1). CO emissions are estimated at 487 ± 122 Gg CO yr-1, much lower than previous top-down estimates (1440 Gg CO yr-1). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25 %, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

UR - http://www.scopus.com/inward/record.url?scp=85056898562&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056898562&partnerID=8YFLogxK

U2 - 10.5194/acp-18-16271-2018

DO - 10.5194/acp-18-16271-2018

M3 - Article

AN - SCOPUS:85056898562

VL - 18

SP - 16271

EP - 16291

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 22

ER -