the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Aug 2024
Airborne in-situ quantification of methane emissions from oil and gas production in Romania
Abstract. Production of oil and gas in Romania, one of the largest producers in the EU, is associated with substantial emissions of methane to the atmosphere and may offer high emission mitigation potential to reach the climate objectives of the EU. However, comprehensive quantification of emissions in this area has been lacking. Here we report top-down emission rate estimates derived from aircraft-based in-situ measurements that were carried out with two aircraft during the ROMEO 2019 campaign, supported by simulations with atmospheric models. Estimates from mass balance flights at individual dense production clusters, and around larger regions, show large variations between the clusters, supporting the important role of individual super emitters, and possibly variable operation practices or maintenance state across the production basin. Estimated annual total emissions from the Southern Romanian O&G infrastructure are 227 ± 86 kt CH4 yr-1, consistent with previously published estimates from ground-based site-level measurements during the same period. The comparison of individual plumes between measurements and atmospheric model simulations was complicated by unfavorable low wind conditions. Similar correlations between measured and simulated CH4 enhancements during large-scale raster flights and mass balance flights suggest that the emission factor determined from a limited number of production clusters is representative for the larger regions. We conclude that ground-based and aerial emission rate estimates derived from the ROMEO campaign agree well, and the aircraft observations support the previously suggested large under-reporting of CH4 emissions from the Romanian O&G industry in 2019 to UNFCCC.
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Status: closed
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RC1: 'Comment on egusphere-2024-2135', Anonymous Referee #1, 23 Aug 2024
Airborne in-situ quantification of methane emissions from oil and gas production in Romania presents results from the airborne part of the 2019 ROMEO campaign in Romania. It takes advantages of the numerous flights around more or less large areas to infer methane emissions and emissions factors for these regions and extrapolated to the country. The authors detail the assumptions and limitations of their work clearly and make use of all the data to make them as robust as possible. I recommend publication after minor corrections.
Comments:
Figure1: please add the name of the clusters on the map, also maybe in the SI a table with the number of flights for each cluster and regions, dates, would help understand the results later on.
Section 2.2
Can you elaborate on the quality procedure for the measurements? Though calibration is not necessary for the biases as you deal with differences to background, were there any check for time-drift maybe especially with the AERIS instrument which may not be as stable as PICARRO instrument usually are.
As no met data were measured on the raster flight, how did you check the prevailing wind direction and checked that it didn't change during the flght time?
Section 2.3 l 180-186 this passage is not clear and these tracers are not talked about afterwards. Need to clarify.
Section 27.: can you add an equation or a figure to illustrate the integration of the measurement along the flight path and the way of calculating the emissions from them?
How did you identify the up-stream contaminations?
Section 3.1l314-343: this is not clear, what is weighted and how, why don't you just average for the sites you measured several times? the passage has to be rephrased, streamlined and maybe have a basic equation to show what are you weighting and how.
Minor comments:
l57: substancial instead of substation
l60: emission meaqurements
l88: what of the 2nd phase?
l104: production asset
l106 remove 'total', replace 'where' by 'though'
l119: remove the last sentence or add the black symbol
l144: as above
l 168: remove () around the citation
l173: add space after 2021)
l282: emission quantifications
l 288 remove 'to'
l352: remove 'about'
l357 remove () around citation
l370: replace 'slights' by 'flights'?
l381: replace 'estimated at' by 'reached'
l415: replace Figure 4 by Figure 3
l565: 'EF of'
Citation: https://doi.org/10.5194/egusphere-2024-2135-RC1 - AC1: 'Responses to RC1 - egusphere-2024-2135', Hossein Maazallahi, 28 Oct 2024
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RC2: 'Comment on egusphere-2024-2135', Anonymous Referee #2, 26 Sep 2024
This is a very interesting manuscript that forms one of the outputs from the ROMEO project surveys of 2019. The low-wind conditions at the time were very challenging for flight surveys, but the authors have managed to tease out some important conclusions. The overall finding is that there is good agreement between aircraft and ground surveys, so it would be useful to have a concluding statement about why aircraft should be used in ground-accessible locations for this type of survey going forward, given the relative cost implications and the meteorological challenges. The comparison with the ground surveys already published was quite cursory and could be developed further, as all these surveys should be producing an emission per facility and this is the main output for comparison with the model and inventories.
Detailed Comments:
Line 51 – There is a new version of the Saunois et al paper for 2024.
Line 57 – substation? I think that you mean ‘substantial’
Line 78 – I was not aware of such a significant O&G sector in Poland, so I am just double-checking that this is not a high annual emission for all fossil fuels including coal.
Figure 2 – Can you add wind direction to the figures or include in the captions. It is not easy to locate 2a on figure 1 without the region 7 bounding box. Also there is no explanation of why the lowest concentrations measured during the regional surveys are 2.67 ppm? Is this related to the low wind speeds mentioned during regional surveys, or instrument calibration. If the latter it would be better to display the data as an excess over baseline.
Line 181 – the term CH4 tracers could be confusing, particularly those that associate tracers with the release of a different chemical compound from cylinders at a known rate to calculate CH4 (or other species) emissions from sources.
Line 201 – Unlike for the other inventories you do not specify which data the TNO-CAMS inventory provides.
Line 247 – it would be interesting to know why EDGAR has so few O&G emissions in these ROMEO regions.
Line 258 – ‘lowest value of each circle’ – which instrument data is this referring to? Is the noise of the Aeris instrument baseline small enough that it does not result in a significant overestimate of peak height when dealing with peaks of 50-100 ppb?
Line 349 – why do you need to show the confidence limits twice on the same line?
Line 352 – ‘from about dedicated measurements’?
Line 473 – ‘190 individual plumes evaluated’. Previously you say that 66 plumes were rejected due to upwind sources. At which stage of the evaluation were these rejected?
Line 368 - ‘possible underestimate of non-O&G emissions in the inventories for R7’. If you are comparing with inventory estimates at least give the emissions or refer the reader to S5 and which inventory you are using. As there is such a difference between inventories can you trust them to give a reliable estimate of the non-O&G sources. 3112 kg/hr for TNO is much closer to the flight estimates than 73 kg/hr from EDGAR. It seems that 5104 ± 1600 kg/hr (after upscaling to 100%) is within error of 7038 ± 1769 kg/hr.
Line 381 – ‘estimated emissions estimated at’.
Figure 4 – your dashed lines do not show up as dashes, even at 150% magnification.
Line 502 – Given that your calculated EF is 5.3 kg/hr per site (and the ground surveys we slightly higher), could you not have rerun the simulation with 1.5 g/s (5.4 kg/hr) to improve the comparison?
Supplementary:
Fig S2 – There are farms in R5a and R8 regions. Did ground surveys detect these plumes and attempt to quantify them? Would be an alternative to a quite crude inventory, when attempting to subtract non-O&G emissions.
Table S6 – How can the 4 bottom-right cells (Sum R7 clusters and 100% fossil) be identical to Table 1 in the main paper, when they represent O&G in 2 very different inventories?
Table S7 – It is very concerning that there is such a big discrepancy in O&G emissions for the regions between the two inventories with TNO between 5 and 65 times higher than EDGAR. What is the difference in methodology that causes such difference?
Citation: https://doi.org/10.5194/egusphere-2024-2135-RC2 - AC2: 'Responses to RC2 - egusphere-2024-2135', Hossein Maazallahi, 28 Oct 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-2135', Anonymous Referee #1, 23 Aug 2024
Airborne in-situ quantification of methane emissions from oil and gas production in Romania presents results from the airborne part of the 2019 ROMEO campaign in Romania. It takes advantages of the numerous flights around more or less large areas to infer methane emissions and emissions factors for these regions and extrapolated to the country. The authors detail the assumptions and limitations of their work clearly and make use of all the data to make them as robust as possible. I recommend publication after minor corrections.
Comments:
Figure1: please add the name of the clusters on the map, also maybe in the SI a table with the number of flights for each cluster and regions, dates, would help understand the results later on.
Section 2.2
Can you elaborate on the quality procedure for the measurements? Though calibration is not necessary for the biases as you deal with differences to background, were there any check for time-drift maybe especially with the AERIS instrument which may not be as stable as PICARRO instrument usually are.
As no met data were measured on the raster flight, how did you check the prevailing wind direction and checked that it didn't change during the flght time?
Section 2.3 l 180-186 this passage is not clear and these tracers are not talked about afterwards. Need to clarify.
Section 27.: can you add an equation or a figure to illustrate the integration of the measurement along the flight path and the way of calculating the emissions from them?
How did you identify the up-stream contaminations?
Section 3.1l314-343: this is not clear, what is weighted and how, why don't you just average for the sites you measured several times? the passage has to be rephrased, streamlined and maybe have a basic equation to show what are you weighting and how.
Minor comments:
l57: substancial instead of substation
l60: emission meaqurements
l88: what of the 2nd phase?
l104: production asset
l106 remove 'total', replace 'where' by 'though'
l119: remove the last sentence or add the black symbol
l144: as above
l 168: remove () around the citation
l173: add space after 2021)
l282: emission quantifications
l 288 remove 'to'
l352: remove 'about'
l357 remove () around citation
l370: replace 'slights' by 'flights'?
l381: replace 'estimated at' by 'reached'
l415: replace Figure 4 by Figure 3
l565: 'EF of'
Citation: https://doi.org/10.5194/egusphere-2024-2135-RC1 - AC1: 'Responses to RC1 - egusphere-2024-2135', Hossein Maazallahi, 28 Oct 2024
-
RC2: 'Comment on egusphere-2024-2135', Anonymous Referee #2, 26 Sep 2024
This is a very interesting manuscript that forms one of the outputs from the ROMEO project surveys of 2019. The low-wind conditions at the time were very challenging for flight surveys, but the authors have managed to tease out some important conclusions. The overall finding is that there is good agreement between aircraft and ground surveys, so it would be useful to have a concluding statement about why aircraft should be used in ground-accessible locations for this type of survey going forward, given the relative cost implications and the meteorological challenges. The comparison with the ground surveys already published was quite cursory and could be developed further, as all these surveys should be producing an emission per facility and this is the main output for comparison with the model and inventories.
Detailed Comments:
Line 51 – There is a new version of the Saunois et al paper for 2024.
Line 57 – substation? I think that you mean ‘substantial’
Line 78 – I was not aware of such a significant O&G sector in Poland, so I am just double-checking that this is not a high annual emission for all fossil fuels including coal.
Figure 2 – Can you add wind direction to the figures or include in the captions. It is not easy to locate 2a on figure 1 without the region 7 bounding box. Also there is no explanation of why the lowest concentrations measured during the regional surveys are 2.67 ppm? Is this related to the low wind speeds mentioned during regional surveys, or instrument calibration. If the latter it would be better to display the data as an excess over baseline.
Line 181 – the term CH4 tracers could be confusing, particularly those that associate tracers with the release of a different chemical compound from cylinders at a known rate to calculate CH4 (or other species) emissions from sources.
Line 201 – Unlike for the other inventories you do not specify which data the TNO-CAMS inventory provides.
Line 247 – it would be interesting to know why EDGAR has so few O&G emissions in these ROMEO regions.
Line 258 – ‘lowest value of each circle’ – which instrument data is this referring to? Is the noise of the Aeris instrument baseline small enough that it does not result in a significant overestimate of peak height when dealing with peaks of 50-100 ppb?
Line 349 – why do you need to show the confidence limits twice on the same line?
Line 352 – ‘from about dedicated measurements’?
Line 473 – ‘190 individual plumes evaluated’. Previously you say that 66 plumes were rejected due to upwind sources. At which stage of the evaluation were these rejected?
Line 368 - ‘possible underestimate of non-O&G emissions in the inventories for R7’. If you are comparing with inventory estimates at least give the emissions or refer the reader to S5 and which inventory you are using. As there is such a difference between inventories can you trust them to give a reliable estimate of the non-O&G sources. 3112 kg/hr for TNO is much closer to the flight estimates than 73 kg/hr from EDGAR. It seems that 5104 ± 1600 kg/hr (after upscaling to 100%) is within error of 7038 ± 1769 kg/hr.
Line 381 – ‘estimated emissions estimated at’.
Figure 4 – your dashed lines do not show up as dashes, even at 150% magnification.
Line 502 – Given that your calculated EF is 5.3 kg/hr per site (and the ground surveys we slightly higher), could you not have rerun the simulation with 1.5 g/s (5.4 kg/hr) to improve the comparison?
Supplementary:
Fig S2 – There are farms in R5a and R8 regions. Did ground surveys detect these plumes and attempt to quantify them? Would be an alternative to a quite crude inventory, when attempting to subtract non-O&G emissions.
Table S6 – How can the 4 bottom-right cells (Sum R7 clusters and 100% fossil) be identical to Table 1 in the main paper, when they represent O&G in 2 very different inventories?
Table S7 – It is very concerning that there is such a big discrepancy in O&G emissions for the regions between the two inventories with TNO between 5 and 65 times higher than EDGAR. What is the difference in methodology that causes such difference?
Citation: https://doi.org/10.5194/egusphere-2024-2135-RC2 - AC2: 'Responses to RC2 - egusphere-2024-2135', Hossein Maazallahi, 28 Oct 2024
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