Estimation of CO2 Fluxes from Tokyo Using a Global Model and Tower Observation
Quantifying emissions from megacities is important for reduction of greenhouse gases. We used atmospheric carbon dioxide (CO2) concentration data obtained at an altitude of around 250 m above the ground on TOKYO SKYTREE (TST; a 634-m-high freestanding broadcasting tower; 35.71°N, 139.81°E), which is...
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Veröffentlicht in: | Journal of the Meteorological Society of Japan 2025, pp.2025-004 |
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Sprache: | jpn |
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Zusammenfassung: | Quantifying emissions from megacities is important for reduction of greenhouse gases. We used atmospheric carbon dioxide (CO2) concentration data obtained at an altitude of around 250 m above the ground on TOKYO SKYTREE (TST; a 634-m-high freestanding broadcasting tower; 35.71°N, 139.81°E), which is located north of central Tokyo, Japan. To use the TST observations for estimating net CO2 fluxes from Tokyo, a global, high-resolution simulation of atmospheric CO2 transport with CO2 flux data from a global inverse analysis was performed. In the simulation, atmospheric CO2 variations were well reproduced at remote sites around Japan. The application of tagged tracers in the simulation revealed that variations of CO2 concentrations at TST were largely driven by fluxes in the southwest region of Tokyo, including the western Tokyo Bay area where huge power plants are located. Then, we performed a regression analysis of modeled and observed Tokyo-originated CO2 concentrations, both of which were derived from the simulated background concentrations, while changing the minimum wind speed used in the analysis. The removal of low wind speeds altered the slope of the regression line, and excluding wind speeds below 7 m s−1 resulted in a stabilized slope of 0.93 ± 0.08. This stabilized regression indicated that the annual net CO2 emission from Tokyo is 79.5 ± 6.6 Tg-C year−1. Our findings demonstrate that analysis using a global high-resolution model with tagged tracers has the potential to monitor emissions changes in a megacity. |
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ISSN: | 0026-1165 2186-9057 |
DOI: | 10.2151/jmsj.2025-004 |