the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jul 2026
Examining anthropogenic CO2 emission inventories over the Greater Tokyo Area using in situ observations and high-resolution atmospheric simulation
Abstract. Cities are major sources of greenhouse gas emissions, and combining activity-based inventories with atmospheric constraints can support science-based mitigation at subnational levels. We implement high-resolution WRF-Chem simulations over the Greater Tokyo Area (GTA) using five anthropogenic emission inventories (MOSAIC, ODIAC, EDGAR, CAMS-GLOB-ANT, and GCP-GridFED) and examine CO2 concentrations at four sites. Using observations from the summit of Mt. Fuji as a background reference, we derive GTA CO2 enhancements (ΔCO2). The simulations reproduce most observed ΔCO2 variability and the relationship between elevated ΔCO2 and transport from the urban core and the Tokyo Bay, while showing differences in ΔCO2 amplitudes due to five inventories. The four observation sites represent different GTA subregions, providing complementary constraints on inventory spatial patterns and highlighting the importance of site selection in urban assessments. High simulated ΔCO2 at Tsukuba is largely attributable to stronger northern suburban emissions in MOSAIC and ODIAC, whereas high ΔCO2 at Yoyogi in ODIAC and GridFED is attributable to stronger nearby urban-core emissions. CAMS-GLOB-ANT and GridFED overestimate ΔCO2 at Yokosuka because of large emissions along the Tokyo Bay. EDGAR shows the lowest bias, although its spatial distribution is coarse and diffuse compared with MOSAIC and ODIAC. Anthropogenic CO2 is best reproduced by EDGAR and MOSAIC, though this result is strongly influenced by Yoyogi. Corrected total GTA CO2 emissions of inventories range from 60.2 to 81.1 Tg C yr−1. These results show where inventories diverge within a megacity and provide a practical benchmark for improving urban CO2 inventories and future urban emission monitoring.
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Status: open (until 19 Oct 2026)
- RC1: 'Comment on egusphere-2026-2178', Anonymous Referee #1, 18 Sep 2026 reply
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- 1
Thomas Lauvaux
Tomohiro Oda
Charbel Abdallah
Masahide Nishihashi
Makoto Saito
Hirofumi Ohyama
Shigeyuki Ishidoya
Hirofumi Sugawara
Toshinobu Machida
Motoki Sasakawa
Yasunori Tohjima
Cities need accurate emission estimates for climate action. We compared five emission inventories over the Greater Tokyo Area using measurements from four sites and an atmospheric transport model. We found that measurements at the four sites show distinct features of the inventories in emission amount and spatial distribution. Site choice is important for evaluating urban emissions. These findings can help improve emission inventories, future urban observations and simulations.
Cities need accurate emission estimates for climate action. We compared five emission...
This paper looks at CO2 emissions over the Greater Tokyo Area (GTA) from five different inventories, calculates the CO2 enhancement in the atmosphere at four observing sites using an atmospheric transport model, and compares them with observations. The paper provides a modest contribution, building on previous work. The use of four sites is a step beyond previous studies, but I don't believe it fully exploits the benefits of the multiple sites to provide conclusions about emissions from different parts of the GTA. I don't think it would take too much work to provide a bit more insight into the emissions from different parts of the GTA (there is some discussion of this through the paper, but it is not summarised into overall conclusions and nothing is mentioned in the Conclusion section or abstract). I recommend publication after consideration of the comments below.
In the abstract "... the four observation sites represent different GTA subregions providing complementary constraints on inventory spatial patterns". This is true and some conclusions were drawn about the influence of subregions at the observation sites however it was not really exploited for the corrected total because the different inventories were scaled across the whole GTA and not by subregion. Is there anything that can be concluded about the total GTA emissions using the under- or overestimation of different subregions? Or by combining the best parts of the different inventories to give a single better inventory, rather than scaling each one with a fixed spatial pattern? Even qualitatively, if not quantitatively. Or with a conclusion like 'this inventory is the best overall, but is too high in a particular region'? Can the authors give a recommendation on the best inventory (or combination of inventories) to use based on this analysis?
Some more discussion of the difference between MFJ and CAMS as a background should be given. Does the CAMS simulation at the four sites include emissions in the GTA, and could that explain some of the difference between CAMS at the sites and MFJ that is more representative of the regional background? Could mention that the bias is often around 7-8 ppm (or whatever value it is) at the sites, to put it into perspective relative to the enhancements from fossil fuel emissions. There should be some discussion of what the consequence of the bias (mentioned at line 277) is for the results of the study (I imagine it isn't too important, but it would be good to have it quantified).
Figures 5 and 8 are very small for the information contained and I find it hard to see the details.
Specific comments
Line 30 - the corrected range of emissions is given in the abstract, but this could be contrasted with the prior range. There has been a general reduction in the mean of this range. This gives the range of all scaled inventories, but what is the authors' best estimate of the CO2 emissions (and uncertainty range) from the GTA, is it smaller than the range of scaled inventories?
Line 54 - add 'atmospheric' before 'CO2'
Line 57 - maybe some examples of the other components of the error budget could be given. There is no mention elsewhere in the paper about the error budget of inversions.
Line 130 - 'rural area'? Elsewhere TKB is described as being in a suburban area (e.g. line 126). Is it peri-urban? i.e., in the transition between urban and rural?
Line 144 - This sentence jumps from talking about CO2 from northern urban region, to ocean air from the south, then back to winter northerlies - should rearrange the sentence to connect the last part to the first part.
Fig 5 - there is a lot of information in this figure, and it is very hard to see the detail. I am pleased the authors show the biogenic component. However, showing results for all five emission inventories plus observations for a month in part of the figure that is the size of a postage stamp (on an A4 page) means that the reader cannot really distinguish details of the differences between inventories. I would suggest showing two months, maybe one winter and one summer, in separate figures, each month spread the width of the A4 page (keeping all 4 sites). The colors could be more different, particularly the blues. Even zoomed in on the screen, the details discussed from line 367 are too hard to see in Fig 5.
Line 415 - it could be mentioned here that the color scale has changed for the wind-sector-averaged DCO2 in the plot.
Fig 6 - could explain more in the caption: Is this averaged over all 2018? The radius of DCO2 plots indicates wind speed bins.
Fig 7 and line 463 - The text says the mean diurnal cycles are shown for summer and winter, but there is no indication of different seasons, only one set of data is shown. Does this mean summer and winter are averaged together - this would seem unusual. At line 473, the seasonal contrast was discussed, but this is not shown?
Line 469 - do you mean three sites here? As TST has a different pattern.
Line 480 - there is perhaps some evidence of enhancement between 6-9am in the observations at YYG, is that due to peak hour traffic?
Fig 8 - I find it hard to see the details in Fig 8 described in the text because so much data is included in one figure. The colors are hard to distinguish in some cases, and the circles are often overlaid.
Fig 9 - I can't read the text in the colored boxes. Part a is small for the amount of information included - could it be expanded to the full width of the page? Part b is fine the size it is.
Lines 579-587 - check this text, it is a bit repetitive, it mentions the studies have different model domains, time periods etc several times.
Line 609 - "The analysis indicates that the main differences among inventories are related to spatial allocation and emission magnitude." - this is not really a finding of the analysis but a fairly obvious statement, I would have thought.
Line 618 - can an uncertainty estimated be associated with the value 77.4 Tg C/y, it is given quite precisely with three significant figures.
Line 629 - 'more realistic vertical allocation of emissions' - not sure what is meant by allocation, is this referring to vertical transport of the model?
Typos or grammar:
Line 36 - add commas - Human activities, especially fossil fuel combustion, have ...
Line 71 - NASEM 2022 - not in reference list
Line 78 - remove 'the' before 'Paris'
Line 115 - 'hosting' is not quite the right word here, try either 'and home to' or 'and supporting a population of more than 44 million people'
Line 127 - something is wrong with the sentence around the word 'representing'. Should this be something like "Together, these sites capture urban, suburban, and coastal environments and represent the key inflow and outflow pathways relevant to interpreting inventory-driven differences in simulated CO2 concentrations."?
Line 257 - "were discussed (in Sections 3.3-3.5)" - this sounds strange using 'were' (in the past) for a section the reader hasn't read yet. The whole section would sound more natural in the present tense (is/are) than on the past tense (was/were).
Line 275 - Grammar needs correcting - e.g. An enhancement in background CO2 compared with MFJ was observed at the four observation sites.
line 365 - move 'the' in 'Thus, the most of DCO2' to 'Thus, most of the DCO2'
Line 448 - space needed between 'the' and 'DCO2'
Line 569 - change 'arisen from' to 'arising from the'
Line 575 - change 'largely' to substantially' (could also give the percentage change).
Line 590 - add 'out' or 'to' after 'pointed'