Isotopic Signatures of Major Methane Sources in the Coal Seam Gas Fields and Adjacent Agricultural Districts, Queensland, Australia
- 1School of Biological, Earth and Environmental Sciences, UNSW Sydney, NSW, 2052, Australia
- 2Department of Earth Science, Royal Holloway, University of London, Egham, TW20 0EX, UK
- 3British Antarctic Survey, Cambridge, CB3 0ET, UK
- 4Institute for Marine and Atmospheric Research, Faculty of Science, Utrecht University, Utrecht, 3584 CC, the Netherlands
- 5Environmental Defense Fund, Berlin, Germany
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 use of carbon (δ13C) and hydrogen (δD) stable isotopic composition of CH4 can identify, distinguish between and apportion specific emissions 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 discriminate between sources of CH4 in the Surat Basin. We also highlight the benefits of sampling at nighttime in warm to hot climate regions. During two campaigns in 2018 and 2019, a mobile CH4 monitoring system was used to detect CH4 plumes. Seventeen plumes immediately downwind from known CH4 sources were sampled and analysed for their CH4 mole fraction and δ13CCH4 and δDCH4 signatures. The isotopic signatures of the CH4 sources were determined using Miller–Tans plots. 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 −56.0 ‰ and −51.0 ‰ and δDCH4 signatures between −207.0 ‰ and −193.0 ‰. Emissions from an open-cut coal mine have δ13CCH4 and δDCH4 signatures of −60.3 ± 0.2 ‰ and −210.5 ± 0.5 ‰ respectively. Emissions from two ground seeps (abandoned coal exploration wells) have δ13CCH4 signatures of −60.7 ± 0.2 ‰ and −59.9 ± 0.9 ‰ and δDCH4 signatures of −191.2 ± 0.5 ‰ and −185.1 ± 0.9 ‰. A river seep had a δ13CCH4 signature of −61.1 ± 0.9 ‰ and a δDCH4 signature of −225.5± 1.4 ‰. Three dominant agricultural sources were analysed. The δ13CCH4 and δDCH4 signatures of a cattle feedlot are −63.0 ± 1.2 ‰ and −309.0 ± 1.0 ‰ respectively, grazing (pasture) cattle have δ13CCH4 and δDCH4 signatures of −59.9 ± 0.8 ‰ and −291.6 ± 2.4 ‰ respectively, and a piggery sampled had δ13CCH4 and δDCH4 signatures of −47.5 ± 0.2 ‰ and −300.3 ± 1.8 ‰ respectively, which reflects emissions from animal waste. An abattoir had δ13CCH4 and δDCH4 signatures of −44.3 ± 0.3 ‰ and −315.0 ± 1.3 ‰ respectively. A plume from a waste-water treatment plant had δ13CCH4 and δDCH4 signatures of −47.6 ± 0.2 ‰ and −177.5 ± 1.4 ‰ 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.
Xinyi Lu et al.
Xinyi Lu et al.
Xinyi Lu et al.
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