气候变化领域集成服务门户(CCPortal): Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion

CCPortal

DOI	10.5194/acp-20-15487-2020
	Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion
	Luhar A.K.; Etheridge D.M.; Loh Z.M.; Noonan J.; Spencer D.; Smith L.; Ong C.
发表日期	2020
ISSN	1680-7316
起始页码	15487
结束页码	15511
卷号	20 期号:23
英文摘要	Methane (CH4) is a potent greenhouse gas and a key precursor of tropospheric ozone, itself a powerful greenhouse gas and air pollutant. Methane emissions across Queensland's Surat Basin, Australia, result from a mix of activities, including the production and processing of coal seam gas (CSG). We measured methane concentrations over 1.5 years from two monitoring stations established 80 km apart on either side of the main CSG belt located within a study area of 350 km × 350 km. Using an inverse modelling approach coupled with a bottom-up inventory, we quantify methane emissions from this area. The inventory suggests that the total emission is 173.2 × 106 kgCH4 yr-1, with grazing cattle contributing about half of that, cattle feedlots ∼25 %, and CSG processing ∼8 %. Using the inventory emissions in a forward regional transport model indicates that the above sources are significant contributors to methane at both monitors. However, the model underestimates approximately the highest 15% of the observed methane concentrations, suggesting underestimated or missing emissions. An efficient regional Bayesian inverse model is developed, incorporating an hourly source-receptor relationship based on a backward-in-time configuration of the forward regional transport model, a posterior sampling scheme, and the hourly methane observations and a derived methane background. The inferred emissions obtained from one of the inverse model setups that uses a Gaussian prior whose averages are identical to the gridded bottom-up inventory emissions across the domain with an uncertainty of 3% of the averages best describes the observed methane. Having only two stations is not adequate at sampling distant source areas of the study domain, and this necessitates a small prior uncertainty. This inverse setup yields a total emission of (165.8±8.5) × 106 kgCH4 yr-1, slightly smaller than the inventory total. However, in a subdomain covering the CSG development areas, the inferred emissions are (63.6±4.7) × 106 kgCH4 yr-1, 33% larger than those from the inventory. We also infer seasonal variation of methane emissions and examine its correlation with climatological rainfall in the area. © Author(s) 2020.
语种	英语
scopus关键词	atmospheric pollution; Bayesian analysis; cattle; coal seam; data inversion; emission; gas production; greenhouse gas; methane; troposphere; Australia; Queensland; Surat Basin; Varanidae
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/247283
作者单位	CSIRO Oceans and Atmosphere, Aspendale, VIC 3195, Australia; Katestone Environmental Pty. Ltd., Milton, QLD 4064, Australia; CSIRO Energy, Kensington, WA 6152, Australia
推荐引用方式 GB/T 7714	Luhar A.K.,Etheridge D.M.,Loh Z.M.,et al. Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion[J],2020,20(23).
APA	Luhar A.K..,Etheridge D.M..,Loh Z.M..,Noonan J..,Spencer D..,...&Ong C..(2020).Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(23).
MLA	Luhar A.K.,et al."Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.23(2020).