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

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.