Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment

An observing system simulation experiment to assess the impact of multiple uncertainties

Kai Wu, Thomas Lauvaux, Kenneth J. Davis, Aijun Deng, Israel Lopez Coto, Kevin Gurney, Risa Patarasuk

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 μmol m-2 s-1 compared to the spatially averaged anthropogenic CO2 emissions of 5 μmol m-2 s-1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

Original languageEnglish (US)
Article number17
JournalElementa
Volume6
DOIs
StatePublished - Jan 1 2018

Fingerprint

Fossil fuels
fossil fuel
Fluxes
atmospheric transport
simulation
experiment
Experiments
biogenic structure
point source
Uncertainty
greenhouse gas
temporal variation
spatial variation
road
Random errors
Systematic errors
Measurement errors
Gas emissions
Greenhouse gases

Keywords

  • Atmospheric inversion
  • Atmospheric transport error
  • Biogenic CO fluxes
  • Flux error structure
  • Observation strategy
  • OSSE
  • Urban CO emissions

ASJC Scopus subject areas

  • Oceanography
  • Environmental Engineering
  • Ecology
  • Geotechnical Engineering and Engineering Geology
  • Geology
  • Atmospheric Science

Cite this

Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment : An observing system simulation experiment to assess the impact of multiple uncertainties. / Wu, Kai; Lauvaux, Thomas; Davis, Kenneth J.; Deng, Aijun; Coto, Israel Lopez; Gurney, Kevin; Patarasuk, Risa.

In: Elementa, Vol. 6, 17, 01.01.2018.

Research output: Contribution to journalArticle

Wu, Kai ; Lauvaux, Thomas ; Davis, Kenneth J. ; Deng, Aijun ; Coto, Israel Lopez ; Gurney, Kevin ; Patarasuk, Risa. / Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment : An observing system simulation experiment to assess the impact of multiple uncertainties. In: Elementa. 2018 ; Vol. 6.
@article{6d4eb62ff98445048a268bd8659cc024,
title = "Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties",
abstract = "The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 μmol m-2 s-1 compared to the spatially averaged anthropogenic CO2 emissions of 5 μmol m-2 s-1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.",
keywords = "Atmospheric inversion, Atmospheric transport error, Biogenic CO fluxes, Flux error structure, Observation strategy, OSSE, Urban CO emissions",
author = "Kai Wu and Thomas Lauvaux and Davis, {Kenneth J.} and Aijun Deng and Coto, {Israel Lopez} and Kevin Gurney and Risa Patarasuk",
year = "2018",
month = "1",
day = "1",
doi = "10.1525/elementa.138",
language = "English (US)",
volume = "6",
journal = "Elementa",
issn = "2325-1026",
publisher = "BioOne",

}

TY - JOUR

T1 - Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment

T2 - An observing system simulation experiment to assess the impact of multiple uncertainties

AU - Wu, Kai

AU - Lauvaux, Thomas

AU - Davis, Kenneth J.

AU - Deng, Aijun

AU - Coto, Israel Lopez

AU - Gurney, Kevin

AU - Patarasuk, Risa

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 μmol m-2 s-1 compared to the spatially averaged anthropogenic CO2 emissions of 5 μmol m-2 s-1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

AB - The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 μmol m-2 s-1 compared to the spatially averaged anthropogenic CO2 emissions of 5 μmol m-2 s-1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

KW - Atmospheric inversion

KW - Atmospheric transport error

KW - Biogenic CO fluxes

KW - Flux error structure

KW - Observation strategy

KW - OSSE

KW - Urban CO emissions

UR - http://www.scopus.com/inward/record.url?scp=85054294902&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054294902&partnerID=8YFLogxK

U2 - 10.1525/elementa.138

DO - 10.1525/elementa.138

M3 - Article

VL - 6

JO - Elementa

JF - Elementa

SN - 2325-1026

M1 - 17

ER -