Anthropogenic CO ₂ emission estimates in the Tokyo metropolitan area from ground-based CO ₂ column observations

Urban areas are responsible for more than 40 % of global energy-related carbon dioxide (COinline-formula₂) emissions. The Tokyo metropolitan area (TMA), Japan, one of the most populated regions in the world, includes various emission sources, such as thermal power plants, automobile traffic, and residential facilities. In order to infer a top–down emission estimate, we conducted an intensive field campaign in the TMA from February to April 2016 to measure column-averaged dry-air mole fractions of COinline-formula₂ (XCOinline-formula₂) with three ground-based Fourier transform spectrometers (one IFS 125HR and two EM27/SUN spectrometers). At two urban sites (Saitama and Sodegaura), measured XCOinline-formula₂ values were generally larger than those at a rural site (Tsukuba) by up to 9.5 ppm, and average diurnal variations increased toward evening. To simulate the XCOinline-formula₂ enhancement (inline-formulaΔXCOinline-formula₂) resulting from emissions at each observation site, we used the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by meteorological fields at a horizontal resolution of inline-formula∼1 km from the Weather Research and Forecasting (WRF) model, which was coupled with anthropogenic (large point source and area source) COinline-formula₂ emissions and biogenic fluxes. Although some of the diurnal variation of inline-formulaΔXCOinline-formula₂ was not reproduced and plumes from nearby large point sources were not captured, primarily because of a transport modeling error, the WRF–STILT simulations using prior fluxes were generally in good agreement with the observations (mean bias, 0.30 ppm; standard deviation, 1.31 ppm). By combining observations with high-resolution modeling, we developed an urban-scale inversion system in which spatially resolved COinline-formula₂ emission fluxes at inline-formula>3 km resolution and a scaling factor of large point source emissions were estimated on a monthly basis by using Bayesian inference. The XCOinline-formula₂ simulation results from the posterior COinline-formula₂ fluxes were improved (mean bias, inline-formula−0.03 ppm; standard deviation, 1.21 ppm). The prior and posterior total COinline-formula₂ emissions in the TMA are 1.026 inline-formula± 0.116 and 1.037 inline-formula± 0.054 Mt-COinline-formula₂ dinline-formula⁻¹ at the 95 % confidence level, respectively. The posterior total COinline-formula₂ emissions agreed with emission inventories within the posterior uncertainty, demonstrating that the EM27/SUN spectrometer data can constrain urban-scale monthly COinline-formula₂ emissions.