TY - JOUR
T1 - A comparison of CO2 emissions from the national greenhouse gases inventory report with CO2 emissions from the global inverse models and the regional WRF-Chem in the Korean Peninsula
AU - Cho, Yunjae
AU - Kim, Hyun Mee
AU - Seo, Min Gyung
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature B.V. 2025.
PY - 2025/2
Y1 - 2025/2
N2 - Under the Paris Agreement, each party is obliged to reduce greenhouse gas emissions based on its nationally determined contribution target. The status of greenhouse gas emissions is summarized by the National Greenhouse Gases Inventory Report (NIR). This report has some uncertainties. Inverse model and online coupled regional chemistry-meteorology model can be used to supplement NIR. In this study, the annual CO2 emissions of South Korea estimated using surface CO2 flux data from CarbonTracker, Copernicus Atmosphere Monitoring Service (CAMS), and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) were compared with the annual CO2 emissions of the NIR over 10-year period (2009–2018). To compare CO2 fluxes from models with CO2 emissions of the NIR, a method to convert CO2 fluxes from the models to CO2 emissions was devised. In South Korea, net CO2 emissions of the NIR were greater than those estimated from the model results. CarbonTracker, CAMS, and WRF-Chem provided net CO2 emission estimates and spatiotemporal CO2 emission information suitable for comparing with the NIR CO2 emissions. Meanwhile, land use, land use change, and forestry (LULUCF) sector CO2 emissions were more comparable to the biospheric CO2 emissions of the regional WRF-Chem than those of global inverse models (i.e., CarbonTracker and CAMS). This implies that the high-resolution regional model may provide more detailed spatiotemporal CO2 emission information and its tendency due to the application of the more detailed land use and vegetation information to the model. The CO2 emission information from the models is expected to be used for evaluating CO2 emissions of the NIR and supporting CO2 emission reduction policymaking.
AB - Under the Paris Agreement, each party is obliged to reduce greenhouse gas emissions based on its nationally determined contribution target. The status of greenhouse gas emissions is summarized by the National Greenhouse Gases Inventory Report (NIR). This report has some uncertainties. Inverse model and online coupled regional chemistry-meteorology model can be used to supplement NIR. In this study, the annual CO2 emissions of South Korea estimated using surface CO2 flux data from CarbonTracker, Copernicus Atmosphere Monitoring Service (CAMS), and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) were compared with the annual CO2 emissions of the NIR over 10-year period (2009–2018). To compare CO2 fluxes from models with CO2 emissions of the NIR, a method to convert CO2 fluxes from the models to CO2 emissions was devised. In South Korea, net CO2 emissions of the NIR were greater than those estimated from the model results. CarbonTracker, CAMS, and WRF-Chem provided net CO2 emission estimates and spatiotemporal CO2 emission information suitable for comparing with the NIR CO2 emissions. Meanwhile, land use, land use change, and forestry (LULUCF) sector CO2 emissions were more comparable to the biospheric CO2 emissions of the regional WRF-Chem than those of global inverse models (i.e., CarbonTracker and CAMS). This implies that the high-resolution regional model may provide more detailed spatiotemporal CO2 emission information and its tendency due to the application of the more detailed land use and vegetation information to the model. The CO2 emission information from the models is expected to be used for evaluating CO2 emissions of the NIR and supporting CO2 emission reduction policymaking.
KW - CO emissions
KW - Global inverse model
KW - National greenhouse gases inventory report
KW - WRF-Chem
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U2 - 10.1007/s11027-024-10195-5
DO - 10.1007/s11027-024-10195-5
M3 - Article
AN - SCOPUS:85217803262
SN - 1381-2386
VL - 30
JO - Mitigation and Adaptation Strategies for Global Change
JF - Mitigation and Adaptation Strategies for Global Change
IS - 2
M1 - 9
ER -