Isotopic signatures of major methane sources in the coal seam gas fields and adjacent agricultural districts, Queensland, Australia

Abstract

Abstract. In regions where there are multiple sources of methane (CH4) in close proximity, it can be difficult to apportion the CH4 measured in the atmosphere to the appropriate sources. In the Surat Basin, Queensland, Australia, coal seam gas (CSG) developments are surrounded by cattle feedlots, grazing cattle, piggeries, coal mines, urban centres and natural sources of CH4. The characterization of carbon (δ13C) and hydrogen (δD) stable isotopic composition of CH4 can help distinguish between specific emitters of CH4. However, in Australia there is a paucity of data on the various isotopic signatures of the different source types. This research examines whether dual isotopic signatures of CH4 can be used to distinguish between sources of CH4 in the Surat Basin. We also highlight the benefits of sampling at nighttime. During two campaigns in 2018 and 2019, a mobile CH4 monitoring system was used to detect CH4 plumes. Sixteen plumes immediately downwind from known CH4 sources (or individual facilities) were sampled and analysed for their CH4 mole fraction and δ13CCH4 and δDCH4 signatures. The isotopic signatures of the CH4 sources were determined using the Keeling plot method. These new source signatures were then compared to values documented in reports and peer-reviewed journal articles. In the Surat Basin, CSG sources have δ13CCH4 signatures between −55.6 ‰ and −50.9 ‰ and δDCH4 signatures between −207.1 ‰ and −193.8 ‰. Emissions from an open-cut coal mine have δ13CCH4 and δDCH4 signatures of -60.0±0.6 ‰ and -209.7±1.8 ‰ respectively. Emissions from two ground seeps (abandoned coal exploration wells) have δ13CCH4 signatures of -59.9±0.3 ‰ and -60.5±0.2 ‰ and δDCH4 signatures of -185.0±3.1 ‰ and -190.2±1.4 ‰. A river seep had a δ13CCH4 signature of -61.2±1.4 ‰ and a δDCH4 signature of -225.1±2.9 ‰. Three dominant agricultural sources were analysed. The δ13CCH4 and δDCH4 signatures of a cattle feedlot are -62.9±1.3 ‰ and -310.5±4.6 ‰ respectively, grazing (pasture) cattle have δ13CCH4 and δDCH4 signatures of -59.7±1.0 ‰ and -290.5±3.1 ‰ respectively, and a piggery sampled had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -300.1±2.6 ‰ respectively, which reflects emissions from animal waste. An export abattoir (meat works and processing) had δ13CCH4 and δDCH4 signatures of -44.5±0.2 ‰ and -314.6±1.8 ‰ respectively. A plume from a wastewater treatment plant had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -177.3±2.3 ‰ respectively. In the Surat Basin, source attribution is possible when both δ13CCH4 and δDCH4 are measured for the key categories of CSG, cattle, waste from feedlots and piggeries, and water treatment plants. Under most field situations using δ13CCH4 alone will not enable clear source attribution. It is common in the Surat Basin for CSG and feedlot facilities to be co-located. Measurement of both δ13CCH4 and δDCH4 will assist in source apportionment where the plumes from two such sources are mixed.

Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights

“…Our sampling from East African cattle, to be detailed elsewhere [ 47 ], found δ 13 C CH 4 around −57‰, a range comparable to −57 to −52‰ values we previously found in Zimbabwean cattle [ 7 ] and broadly similar to Australian results of −59.7 ± 0.7‰ from grazing cattle, and −62 : 9 ± 1 : 3‰ from feedlot cattle [ 48 ]. However, we note our results are significantly more 13 C rich than the values around −65‰ found for sub-Saharan Africa by Chang et al .…”

“…However, like our results over Lake Wamala, Tyler et al [20] also found a range of values in other Kenyan wetlands, from −54‰ to −31‰, although with very high CO 2 measurements in many samples, suggesting complex perturbation. Our sampling from East African cattle, to be detailed elsewhere [47], found δ 13 C CH 4 around −57‰, a range comparable to −57 to −52‰ values we previously found in Zimbabwean cattle [7] and broadly similar to Australian results of −59.7 ± 0.7‰ from grazing cattle, and −62 : 9 ± 1 : 3‰ from feedlot cattle [48]. However, we note our results are significantly more 13 C rich than the values around −65‰ found for sub-Saharan Africa by Chang et al [49] (their fig.…”

Blasting Law of Liquid CO2 Phase Change in Coal Mine Based on Numerical Simulation

“…Therefore, accelerating the extraction and utilization of gas and transforming harmful gas into useable energy is a major trend in the energy field [ 11 ]. Lu et al and others said that in order to protect the living environment of mankind, the development and utilization of coalbed methane is regarded as an energy plan in the new century all over the world, which will inevitably promote the rapid development of China's coalbed methane mining industry [ 12 ]. Xie et al and others believe that the main problem at present is the low permeability of coal seam, and the adsorbed gas is difficult to be fully decomposed and absorbed, which brings great difficulties to the development of coalbed methane.…”

Methane (CH<sub>4</sub>) sources in Krakow, Poland: insights from isotope analysis

“…The Upper Silesian Coal Basin (USCB), where most mining activity occurs in Poland, is certainly a CH 4 emission hotspot in Europe. Atmospheric measurements at the USCB have mostly been performed in recent years (Swolkień, 2020;Luther et al, 2019;Gałkowski et al, 2020;Fiehn et al, 2020) and focused on the coal extraction activities. The CH 4 emission rates were estimated at the regional scale (Luther et al, 2019;Fiehn et al, 2020), with a relatively good agreement with the inventories (Luther et al, 2019;Fiehn et al, 2020;Gałkowski et al, 2020).…”

“…Atmospheric measurements at the USCB have mostly been performed in recent years (Swolkień, 2020;Luther et al, 2019;Gałkowski et al, 2020;Fiehn et al, 2020) and focused on the coal extraction activities. The CH 4 emission rates were estimated at the regional scale (Luther et al, 2019;Fiehn et al, 2020), with a relatively good agreement with the inventories (Luther et al, 2019;Fiehn et al, 2020;Gałkowski et al, 2020). Swolkień (2020) performed direct measurements of CH 4 fluxes at individual shafts and emphasised the large variability of emission patterns between different sites.…”