Articles | Volume 13, issue 5
https://doi.org/10.5194/amt-13-2697-2020
https://doi.org/10.5194/amt-13-2697-2020
Research article
 | 
27 May 2020
Research article |  | 27 May 2020

Net CO2 fossil fuel emissions of Tokyo estimated directly from measurements of the Tsukuba TCCON site and radiosondes

Arne Babenhauserheide, Frank Hase, and Isamu Morino

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Cited articles

Andres, R. J., Gregg, J. S., Losey, L., Marland, G., and Boden, T. A.: Monthly, global emissions of carbon dioxide from fossil fuel consumption, Tellus B, 63, 309–327, https://doi.org/10.1111/j.1600-0889.2011.00530.x, 2011. a
Babenhauserheide, A., Basu, S., Houweling, S., Peters, W., and Butz, A.: Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions, Atmos. Chem. Phys., 15, 9747–9763, https://doi.org/10.5194/acp-15-9747-2015, 2015. a
Babenhauserheide, A., Hase, F., and Morino, I.: Code and Data for amt-2018-224, https://doi.org/10.5281/zenodo.3845548, 2020. a, b, c, d, e
Bagan, H. and Yamagata, Y.: Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells, Environ. Res. Lett., 9, 064015, https://doi.org/10.1088/1748-9326/9/6/064015, 2014. a, b
Bannon, P. R., Bishop, C. H., and Kerr, J. B.: Does the Surface Pressure Equal the Weight per Unit Area of a Hydrostatic Atmosphere?, B. Am. Meteorol. Soc., 78, 2637–2642, https://doi.org/10.1175/1520-0477(1997)078<2637:dtspet>2.0.co;2, 1997. a
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This paper demonstrates that the carbon dioxide emissions of Tokyo can be estimated from long-term ground-based measurements of column-averaged atmospheric carbon dioxide abundances recorded at the TCCON site Tsukuba.
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