Preprints
https://doi.org/10.5194/acp-2022-205
https://doi.org/10.5194/acp-2022-205
21 Mar 2022
 | 21 Mar 2022
Status: this preprint was under review for the journal ACP but the revision was not accepted.

Insights on estimating urban CO2 emissions using eddy-covariance flux measurements

Kyung-Eun Min, Junphil Mun, Begie Perdigones, Soojin Lee, and Kyung-Hwan Kwak

Abstract. Living in an era of government allocated carbon dioxide (CO2) emissions, knowing the accurate amount of human-induced CO2 becomes very critical. To this end, an in-depth understanding of CO2 emissions in urban areas where human activities are concentrated will be of practical help. With this motivation, we quantify CO2 emission strengths of individual urban activities (i.e. vehicle, industry, heat generation, etc.) based on direct observations of vertical CO2 exchanges at urban-atmosphere interface using Eddy-Covariance (EC) method at Gwangju, Korea (2017.11–2018.08). Day of week difference analysis, together with varying wind sector, grounded from carefully designed measurement set-up, enables us to assess CO2 emission factors (EFs) free from seasonal bias (i.e. heating and urban vegetation); evaluated EFs of traffic from day of week difference was 0.017(±0.011) μmol m-2 s-1 car-1 which is more than 10 times larger than that from simple relation (0.0012 ± 0.0011 μmol m-2 s-1 car-1) between CO2 flux and traffic counts. The CO2 emissions due to the car manufacturing industry within the fetch and heating when air temperatures were lower than 18 °C were quantified as 103.25(±42.18) μmol m-2 s-1 and 2.41(±1.71) μmol m-2 s-1 °C-1, respectively. Urban vegetation uptake was estimated as -1.72 kg C m-2 yr-1 only with EFs traffic inferred from day of week difference indicating possible erroneous estimation in simple relation unless it properly reflects representative seasonal changes in a year. Even though our estimations are conservative EFs due to limitations in corrections of horizontal seepage and vertical storage, we found that both EFs for traffic and heat in latest emission inventory were more than 2.5 times lower than our estimations which indicate the urgency in bottom-up inventory validations.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Kyung-Eun Min, Junphil Mun, Begie Perdigones, Soojin Lee, and Kyung-Hwan Kwak

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-205', Anonymous Referee #1, 26 Apr 2022
    • AC1: 'Reply on RC1', Kyung-Eun Min, 10 Jun 2022
  • RC2: 'Comment on acp-2022-205', Anonymous Referee #2, 02 May 2022
    • AC2: 'Reply on RC2', Kyung-Eun Min, 10 Jun 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-205', Anonymous Referee #1, 26 Apr 2022
    • AC1: 'Reply on RC1', Kyung-Eun Min, 10 Jun 2022
  • RC2: 'Comment on acp-2022-205', Anonymous Referee #2, 02 May 2022
    • AC2: 'Reply on RC2', Kyung-Eun Min, 10 Jun 2022
Kyung-Eun Min, Junphil Mun, Begie Perdigones, Soojin Lee, and Kyung-Hwan Kwak
Kyung-Eun Min, Junphil Mun, Begie Perdigones, Soojin Lee, and Kyung-Hwan Kwak

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Short summary
For knowing the accurate amount of human-induced CO2, emission strengths of individual activities were assessed via direct eddy-covariance observations at urban-atmosphere interface. This work extracted emission factors (EFs) with minimized seasonal effects through day of the week difference with varying wind sectors. Our work urges the need for not only emission inventory validation but also seasonal bias free EFs estimations for establishing effective climate mitigation strategies.
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