the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Nov 2025
Fugitive emissions of natural gas in York, United Kingdom: Adapting existing algorithms parameters to be based on instrument specifications
Abstract. Reducing methane emissions has become increasingly important in recent years due to its importance for radiative forcing. Of the many sources of methane, fugitive emissions from a country's domestic natural gas network are one that can have a direct impact on the citizens of a country. Previous studies have shown the ability to detect these emissions by use of mobile surveys measuring methane, some of these use secondary co-emitted compounds as a means of confirming the nature of the emission. This study aims to adapt existing algorithms parameters by investigating the limitations of equipment used within the platform used for mobile surveys. This has led to reduced enhancement parameters as well as reduced time clustering parameters. These changes suggest that previous methods may underpredict the number of Leak Indications (LIs) by 53.5 % with number of LIs detected in the old method being 27 and the new method detecting 58. When source appointment was included as a core step within the algorithm itself, the total fugitive natural gas emissions within a city was reduced from 185.10 L min-1 to 60.23 L min-1, nearly three times lower.
- Preprint
(1185 KB) - Metadata XML
-
Supplement
(522 KB) - BibTeX
- EndNote
Status: open (until 17 Jan 2026)
-
RC1: 'Comment on egusphere-2025-5348', Anonymous Referee #1, 12 Dec 2025
reply
-
RC2: 'Reply on RC1', Anonymous Referee #1, 12 Dec 2025
reply
Addendum to review above:
I would like to offer the team a way to prove me wrong if they are confident that I may have misunderstood the empirical emissions estimation method. I offer this as this paper could also be a really interesting investigation of the pros and cons and accuracy of empirical emissions methods from mobile sampling - a discussion that has been all too lacking in many other studies that have attempted to apply it, but which has gone mostly unchallenged in the literature thus far. I am concerned there is a group think going on with this method, as the first of its kind slipped the net. I could be wrong though. This paper could be a great contribution to that debate if it refocuses to be a narrative about how (and how not) such methods could be used.
My assertion that an emissions relationship derived under a specific set of environmental conditions is not transferrable to any other (significantly different) set of conditions is based on how any emission plume would be conceived to advect and disperse due to wind, turbulence, convection and diffusion. Any change in any one of these parameters would affect the downwind concentrations from a point source sampled downwind and mapped by a mobile vehicle (whether near to a source, or further afield). As the empirical emissions method solely relies on measured concentration enhancements and wind at an unknown distance from source downwind, the emissions would therefore be calculated to be different if any of these environmental parameters varied, compared to the conditions under which the empirical relationship was derived. Is this correct so far? If not, I apologise completely as I've misunderstood the method and I should be corrected.
Assuming the above assumptions I have made are correct(?), the team could attempt to calculate the emissions error that would result if any of the operational (i.e. a later survey using the relationship) environmental conditions varied in some defined parameter space, by using a physical advection-dispersion relationship (such as a Gaussian Plume) as a control. For example, a simple simulation/test could be set up using a 2D Gaussian plume equation (or convection/diffusion equation if very local scales are preferred). For plumes with the same simulated emission rate in all cases, but with different environmental conditions (wind and surface roughness etc), how would the emissions from the same derived empirical relationship change as a function of those conditions if you pseudo-sampled the simulated plume at ground level using the instrumentation described in the paper? If you were able to test this in such a simulation, you could get a handle on the potential errors that you might get in the York environment versus the validation survey by making some informed assumptions/observations about the wind and roughness conditions in York versus the validation environment. I appreciate that the whole idea of an empirical relationship is to sidestep the impossible complexity that comes with such varying conditions, but for it to be useful, a conceptual validation must be shown at the very least. If you were able to do this in this paper, it would not only place meaningful uncertainties on the emissions derived in Section 3, but it would also provide an important commentary and resource on the utility of this method for others to follow. If you did it, it would turn this into a very impactful paper I believe and a very useful course correction to the method.
I wanted to offer this idea as I feel awful about recommending the paper is rejected. I recognise the effort of the fieldwork. If the team would prefer to take this idea offline and revise the paper with my help along the above lines, I'd be happy to drop anonymity if you would like to withdraw the paper and work on it together. Alternatively, if I've totally misunderstood the method and you can defend it conceptually and convincingly in review here, I'd be very open to being shown why I am wrong. If that were the case, the other aspects of the paper raised in my review could be corrected via major corrections. Well done again with the fieldwork and I look forward to seeing what you think about these ideas.
Citation: https://doi.org/10.5194/egusphere-2025-5348-RC2
-
RC2: 'Reply on RC1', Anonymous Referee #1, 12 Dec 2025
reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 122 | 25 | 10 | 157 | 14 | 8 | 9 |
- HTML: 122
- PDF: 25
- XML: 10
- Total: 157
- Supplement: 14
- BibTeX: 8
- EndNote: 9
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Summary:
This paper describes the adaptation of algorithms for mobile methane emission rate calculation using instruments operated on the WACL survey vehicle, specifically with a LGR MGGA, and complementary measurements of ethane/NOx etc for source apportionment. An empirical emissions rate relationship is calculated for vehicle surveys of a controlled release conducted in Bedford. This relationship is then applied to measurements sampled in a driving survey of York, UK.
The paper has some merit and strengths. It demonstrates how complementary measurements of ethane can be used for source apportionment. It described how surveys can be used to detect fugitive emissions and defines this for the specific instrumentation used. However, there are a great many major and results-critical weaknesses in the paper at present and I have significant concerns about the validity of the emissions results included in the paper as the methodology appears conceptually flawed: an empirical emissions relationship derived in an idealised environment such as Bedford cannot be applicable to the highly heterogeneous conditions of an urban environment – at least in the way in which they have been here. As there is no discussion of this conceptual difference, nor any attempt to quantify any emissions error that might result, I cannot have confidence in the quantitative results. There are other important weaknesses, which include the fact that none of the figures/plots included in the paper are referred to or discussed in the narrative. There are also many typos and grammar errors. The paper needs a thorough refresh, with input from co-authors, especially on proof-reading of a final version.
Very sadly, I have to recommend rejection and resubmission of the paper as the scope of the changes needed are substantial and would represent a completely different paper. I believe the work has some great merit, and it represents some great effort in field work and measurement science, but the potential results are not those presented in the paper (i.e. emissions quantification). Some specific comments and technical correction examples are listed below.
Specific comments:
Title: The title is grammatically incorrect – please correct.
Abstract, line 16: I don’t understand why fugitive emissions can have a direct impact on citizens, as stated here. Please rephrase, or otherwise better explain what this sentence is trying to convey.
Line 20: The sentence “This has led to reduced enhancement parameters as well as reduced time clustering parameters” makes no sense to the reader at the abstract stage. Either explain better what this is here, and why its relevant, or delete from the abstract. It would be confusing to any reader of the abstract alone.
Line 30: The growth rate of methane has not slowed recently as stated. This is a worrying and misleading oversight/inaccuracy. The Kirschke paper cited is 12 years old, and was published after the end of a rare methane plateau, which ended around 2007. Methane’s rise has been accelerating in the past 15 years and every contemporary paper confirms this. Please correct this statement and cite a more recent paper which discusses the global average concentration trends.
Line 39, Nisbet et al., 2025 published a guide to achieving agricultural methane reductions – it would be useful to cite and discuss that paper in this paragraph. https://doi.org/10.1098/rspa.2024.0390
Line 82: The units in the equation need to be defined in the text (i.e. what are the specific units of concentration and emission rate), as specific units will only be valid for the numerical constants in the equation. Importantly, the reader needs to know if concentration units are not columns (i.e ppm.metres as defined in the earlier equation on line 75) to avoid confusion.
Section 2.1.2: The discussion of the lab-based baseline is useful. However, it is unclear how the survey baseline was derived – i.e. why was a value of 1.05 times the baseline selected? And how? And can you be confident that a value of 1.05 times a baseline would be appropriate in all survey conditions? Can you be sure that a singular value is appropriate for all types of survey? If not, what should surveyors look at in the data to check that a value of 1.05 is appropriate for their survey?
Section 2.3 Line 158 – By this point, I have no idea which of the published detection algorithms described in Section 1.1 have been adopted for use in the study. Which one have you used/adapted? It will be useful to remind readers of the algorithm you are referring to, i.e. cross-reference to the earlier section where this is introduced.
None of the figures are referred to, or discussed in the narrative at all. This is not acceptable. Every figure must be referred to and discussed in the text.
Line 207 – Presumably this relationship was calculated from Figure 5, though figure 5 is not mentioned at all in the text. What is the uncertainty in the emission rate resulting from the quality of the fit to the data in Figure 5 etc? What is the goodness of the linear fit in general? This is perhaps the most significant comment I would make about the paper in terms of the novel science it offers. Why would a relationship such as this (calculated for a controlled release at Bedford) be applicable to releases in York? As stated earlier, previous studies have quantified their own relationships for other cities/environments, under very different conditions, so how is the relationship for Bedford relevant elsewhere? And what is the potential uncertainty that results in applying it elsewhere? The fact that some other studies cited seem to have been published with similarly worrying oversights does not validate the approach here. A quick look at Figures 2 to 5 show just how flaky any empirical relationship is. I do believe that mobile methods such as this can be a great way to detect fugitive emissions in urban environments in general. But I am not convinced here that they can be used to derive emissions rates with any traceable error, especially using empirical relationships derived in one location/conditions, and then applied to very different environments (e.g. with buildings/obstacles perturbing flow). It makes no conceptual dynamical sense. The relationship between enhancement and emission rate would be different for different windspeeds, surface roughness etc. With that in mind, I have no confidence in the accuracy of the leak rates presented in Figure 12 and section 3. The methods described in the paper could be very useful for leak detection, but not leak quantification. I would recommend the paper is resubmitted to describe mobile use in leak detection and source attribution (i.e. source type using ethane and NOX as discriminators for example). Alternatively, a robust emissions error quantification, accounting for differences between Bedford and York conditions, could make the results in Section 3 more meaningful.
Technical corrections:
Line 49: Change to “UK’s”.
Line 51. Full stop in wrong place? Sentence does not make sense.
Line 84. Full stop needed after …”emissions”.
Line 86 Change “has” to “have”.
Line 135- sentence does not make sense.
Line 142_ Change “drives,…” to “mobile surveys” to avoid confusion. Check other instances.
Figure 2 is not referred to explicitly in the text. Please add to Section 2.2.
Line 160 – space needed between number and unit “5 s”, as has been done correctly on line 158 – please check and correct throughout. “44.5m” on line 161 is another example correction. There are many more.
At this point, I will have to stop listing typos, grammar mistakes and other technical corrections. It is not a reviewer’s job to correct a paper in detail. The paper needs a thorough proof-read. Some of the mistakes do affect the potential meaning of the narrative. There are several senior co-authors on this paper – it is disappointing that they did not help the lead author a little more with this, or insist it was checked well prior to submission.
Line 283 – equation has a black square – something went wrong in the version online?