the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Apr 2025
Aerial Estimates of Methane and Carbon Dioxide Emission Rates Using a Mass Balance Approach in New York State
Abstract. Accurate greenhouse gas (GHG) emissions inventories are vital for climate mitigation as they can identify areas of need and ensure effective policy and regulation in reducing GHG emissions. Several studies have shown that self-reporting GHG inventories are undercounting methane emissions across all anthropogenic sectors showcasing an increasing need to validate the inventory with direct measurements. This study carried out aerial observations and emission rates of methane and carbon dioxide across multiple sectors in New York State (NYS). Emission rates were calculated for each of the sources using a mass balance method and were subsequently compared to the 2021 Environmental Protection Agency GHG Reporting Program (EPA GHGRP) Inventory. Landfills were the source of the highest observed methane emission estimates, ranging from 161–3440 kg/hr. There was also significant variation in observed emissions within facilities between seasons indicating a significant influence from meteorology. Observed carbon dioxide emission estimates were dominated by combustion facilities followed by landfills. Comparisons with the inventory show that methane emissions averaged over ten observed landfills are underestimated by a factor of 2. However, out of the ten landfills, five landfills had observed methane emission estimates significantly higher than the inventory value, four landfills had an inventory value within the uncertainty range of the observations, and one landfill observed emission estimate was markedly lower than the reported inventory estimate. Seneca Meadows Landfill was the highest emitter from the measurements and was ~4.3x higher than what was reported to the 2021 EPA GHGRP Inventory. The difference in emissions between landfills could be due to operational differences or waste quantities. NYS can use this information to inform the NYS GHG Inventory and improve emission estimation methodologies to better depict actual emissions.
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RC1: 'Comment on essd-2025-135', Anonymous Referee #1, 23 Apr 2025
The paper by Catena et al. presents aerial measurements of methane (CH4) and carbon dioxide (CO2) emission rates from various sectors in New York State (NYS), including landfills, combustion facilities, wastewater treatment plants (WWTPs), and agricultural sites. Using a mass balance approach based on Gauss’s theorem, the study estimates emission rates and compares them with the 2021 EPA Greenhouse Gas Reporting Program (GHGRP) inventory, revealing that methane emissions from landfills are, on average, underestimated by a factor of 2. The findings provide valuable data to refine the NYS GHG Inventory and support climate mitigation efforts. However, the study suffers from several limitations: the methodology lacks clarity, the uncertainty analysis is inadequate, the scientific merit is limited, and the results may be biased due to insufficient data. Although the paper is well-structured with a logical flow, it lacks in-depth discussion of the findings and their implications. I recommend a major revision to address these shortcomings.
Major concerns:
- Methods:
- The description of the mass balance method using Gauss's theorem is overly brief and lacks critical details. I only understand the method by reading Conley et al. (2017). I recommend the authors expand the methods section to include a detailed explanation of the mass balance approach, explicitly addressing the storage term, data interpolation, and altitude binning, and explain the similarities and differences compared to the study of Conley et al. (2017), clarifying any deviations from their method. Conley assumed that the vertical mixing at the upper boundary is zero, and their schematic in Fig. 1 illustrates that the tracer mixing ratio vertical gradient at the upper boundary is close-to zero, which defends their assumption. However, this paper does not explicitly mention this assumption.
- The authors do not present their flight data (i.e., spatial structure of the data) at all. It is difficult to visualize data and confirm if these data accurately capture the plume. I suggest that the authors present their data in SI. In addition, a schematic in the main text would help to understand the method.
- The city-level emission in Table 5 might be problematic. It is unclear if the measurements adequately sample the downwind region of the entire city. It would be better to show the flight track and wind fields.
- Methods:
- The uncertainty analysis is limited to turbulent flux variability between flight loops, ignoring other sources such as plume extrapolation below the lowest flight altitude, instrument precision, wind measurement errors, or seasonal representativeness. The assumption of a constant methane mixing ratio, from the surface to the lowest flight level, is poorly justified, especially given the potential for strong near-surface gradients in urban or landfill settings. It is unclear how the authors quantify the PBL height and whether lower measurements are all within the PBL. It is unclear how PBL diurnal cycle alters the results. Overall, it is not clear what the sources of uncertainty are. It would be better to provide a high-level summary here rather than only pointing out to other papers.
- The reliance on single-day measurements (or two days for some facilities) introduces potential bias, as emissions may vary significantly due to operational or meteorological changes. The paper acknowledges seasonal differences but does not assess whether one single-day measurement is representative of annual emissions. I can see that the authors mention this potential caveat at the end of the paper, but this should be highlighted very early in the paper. In addition, it is not clear whether the reported 2021 EPA GHGRP emission should be interpreted as annual average or at the time that can be directly compared with airborne measurements. It seems like all the measurements are collected during the daytime. Would the missing of nighttime measurements bias the flux quantification, or in other words, is there a diurnal cycle in the emissions?
- Facilities with non-detectable emissions (e.g., some WWTPs) are inadequately explained, possibly due to sampling limitations in urban areas or insufficient plume capture.
Minor comments:
- Table 3 rows are not lined up.
- L143: For each loop, are you flying at the same height?
- L190-192: This statement might be significantly weakened as you only have one day of data per season. Unless you can somehow show that the emission is consistent over the course of entire season, and your measurement is not sensitive to any sorts of synoptic scale disturbances.
- L193: How does ambient pressure affect CH4 emission?
- L194: Wind speed and direction would change the redistribution of GHG emissions. However, your method accounts for the wind to inversely derive flux from concentration.
- L194: It is unclear what you mean by soil moisture. Soil moisture of the landfill?
- Figure 2: It is unclear what each point represents, and what time of the year is shown. Please print the name of each site on x-axes. Are error bars assumed to be 1-sigma uncertainty?
- Figure 5: This figure does not provide much useful information. Your table is good enough to raise the point.
- L304: Is there a way you can showcase that the extra CO2 emissions you observed comes from biogenic CO2 emissions?
- Although it may be beyond the scope of this study, have you considered using a Lagrangian transport model (i.e., STILT, etc.) to translate concentration to flux, which I believe is much more robust?
- Maybe it is beyond the scope of ESSD, which focuses on presenting the data, but I am curious about the implications of the results, such as why some landfills show larger discrepancies than others. The paper mentions operational differences and waste quantities but lacks specific data or analysis to support these claims.
- The tables (2–5) are comprehensive but you could put in them SI to enhance clarity.
- A lot of the references are not correctly formatted.
Citation: https://doi.org/10.5194/essd-2025-135-RC1 -
RC2: 'Comment on essd-2025-135', Anna Karion, 03 May 2025
Review of Catena et al., "Aerial Estimates of Methane and Carbon Dioxide Emission Rates
Using a Mass Balance Approach in New York State" for ESSD.This manuscript describes the measurements and methods behind reporting of estimates of GHG emissions from
point source facilities and two urban areas in New York State. Emissions rates were calculated using conservation of
mass (mass balance) using aircraft observations of atmospheric enhancements of CH4 and CO2 downwind of emissions sources.
This is useful and valuable information to report in the peer-reviewed literature as such I recommend publication with
a few notes below.First, it seems there is some inconsistency in the language around whether the reports are for methane only or also
CO2. Clearly the authors are reporting emissions of both but in some parts of the paper they refer only to "emissions" when referring
to methane specifically, as if perhaps initially they only calculated methane and then added CO2 in a later revision. I suggest going
through the text with an eye toward consistency once more, and I point out a few places below in the minor comments.Second point is that in the introductory material there are references to the mass balance method and how one may compare to an annual average
emission reported in GHGRP, but the language favors the former. The EPA is more interested in annual emissions, not snapshots, so it
is not a fault or failure of the GHGRP that it only reports annual emissions -- this is the goal. Rather, it is important for the
mass balance measurements to be scaled up to the annual scale. The authors correctly point to this as one possible reason for
discrepancy but somehow the language makes it sound as if there is some blame to be shouldered by the annual inventory.[Note: This review was written before I looked at the other reviewer's notes, so here I will comment on a point of agreement with
that review. As a Data paper, I do not think that this manuscript needs to include much interpretation and is satisfactory
in that regard. However, I agree that the data does not include several sources of uncertainty that should be discussed. The main issue I had already mentioned in my review was with the representativity of the emissions but that uncertainty is obviously difficult to quantify without more information. As I have already noted in my review, this should be mentioned more up front. However, I do agree with the other review that some of the other
sources could and should be estimated and included. ]Specific:
L18: why is meteorology influencing emissions? Are the authors saying that landfill emissions are seasonal or just variable in time in general (other literature points to management practices being the source of temporal variability, i.e. what is going on on the workface -- see Scarpelli et al. recent paper, for example)?
L60-65 This paragraph is a bit awkward between the first sentence and then the second half talking about cities, perhaps just re-read and edit to smooth out the transition?
L75-76 Similar to above, the sentence beginning with "However" is out of place somehow.
L91 again just awkward language, perhaps change to "across these source sectors and from all the sectors in the cities of Buffalo and Rochester"?
L113 "is captured" should be "was captured"
L119 - here only the specs for methane are given when CO2 is also part of this work.
Table 1: What is the surface fraction? It is not mentioned in the caption at all.
L153, 154, I believe there is an assumption of constant air density here, since the equation is focusing on concentration and not mole fraction or mass fraction. Perhaps this should be noted. Esp. in the case of the urban studies this may be a factor where the flights are longer and cover more area.
L268 - methane should be mentioned before "emissions" at least the first time, because I think all these rates are methane, not co2.
L283 - Here this paragraph is overstated, and I would argue the first sentence is not correct. These results do not themselves show the underestimation of an annual inventory -- perhaps they "suggest that the self-reporting... may be underestimated". As the authors discuss, the snapshot results shown here are just snapshots and do not represent an annual mean.
L284 - why does an underestimation in GHGRP mean an underestimation in the NYS inventory? Do they use the same methods or data to determine emissions, or perhaps do they use the GHGRP data directly in the NYS inventory? Also why is there a specific sentence about why the GHGRP may be higher, but that reason is different from the ones where it is lower? Errors are errors so it seems weird to attribute them differently depending on their direction? Looking at Fig. 4(a), it really does not seem to be the case that all landfills are under-reporting, even when just comparing with this snapshot data -- several landfills' reported values are higher than the mass balance estimate. Seneca Meadows is driving the mean bias up as an outlier. I realize this is discussed more in depth in L270+ for each landfill.
L287 - Sentence starting "The difference in emissions..." is confusing. What difference in emissions? If this says what I think (which is not clear), this is saying that the inventory is wrong because of seasonal variations but I would think the inventory calculation does not make actual emissions measurements, do they? They calculate based on annual average data like captured percentage and amount waste etc. So isn't it more likely that the variability is actually causing an error in the upscaling of the flight data rates reported here, when trying to determine annual values?
L290- this is well-stated here, so I think the previous few sentences just need to be clarified - perhaps just reworded because what they are trying to say is confusing and is almost laying the blame on the inventories for the fact that there is variability they don't account for.
Perhaps there should be at least another sentence or two devoted to figure 4(b) and Figure 5. Figure 5 is not discussed at all -- these are not landfills, right? L303-305 could refer to a figure - I think this is referring to Figure 5 results, but these are combustion facilities, not landfills? A little confused, so some clarifying text would be good.
Conclusion seems well-stated.
I also note that I downloaded and checked the accompanying data files.
Citation: https://doi.org/10.5194/essd-2025-135-RC2
Data sets
Raw Aerial Observations of Methane and Carbon Dioxide at Several Sectors in New York State in 2021 Alexandra Catena and Mackenzie Smith https://doi.pangaea.de/10.1594/PANGAEA.979845
Emission Rate Estimates of Methane and Carbon Dioxide at Several Sectors in New York State in 2021 Alexandra Catena and Mackenzie Smith https://doi.pangaea.de/10.1594/PANGAEA.979843
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