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

Xinyi Lu,David Lowry,Bryce F J Kelly,Stephen J Harris,Carina Van Der Veen,Rebecca E Fisher,James L France,Malika Menoud,Thomas Röckmann,Stefan Schwietzke,Euan G Nisbet

doi:10.5194/acp-21-10527-2021

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.

Highlights

If we are to achieve the goals of limiting the rise in global temperature to 2 ◦C as outlined in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC), we need to locate and mitigate sources of greenhouse gases due to anthropogenic industrial and agricultural activities (e.g. Ganesan et al, 2019; Pachauri et al, 2014; Nisbet et al, 2020)
In 2018, we did not detect plumes from coal mines, river seeps, abattoirs, piggeries, or wastewater treatment plants (WWTPs), and we shifted our focus from daytime surveying in 2018 to nighttime surveying in 2019
We present the δ13CCH4 isotopic signatures for 16 plumes and the δDCH4 isotopic signatures for 13 plumes, from the analyses of over 160 air samples

Summary

Introduction

If we are to achieve the goals of limiting the rise in global temperature to 2 ◦C as outlined in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC), we need to locate and mitigate sources of greenhouse gases due to anthropogenic industrial and agricultural activities (e.g. Ganesan et al, 2019; Pachauri et al, 2014; Nisbet et al, 2020). Many sources of greenhouse gases have a characteristic isotopic signature, which can be used for source attribution when used in conjunction with other data. The gas fields are surrounded by grazing cattle, piggeries, coal mines, urban centres, and some natural sources of CH4. In such regions it is a necessary but difficult task to determine how much CH4 each sector contributes (Kille et al, 2019; Luhar et al, 2020; Mielke-Maday et al, 2019; Smith et al, 2015; TownsendSmall et al, 2015, 2016)

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