气候变化领域集成服务门户(CCPortal): Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion

CCPortal

DOI	10.5194/acp-22-12945-2022
	Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion
	Stell, Angharad C.; Bertolacci, Michael; Zammit-Mangion, Andrew; Rigby, Matthew; Fraser, Paul J.; Harth, Christina M.; Krummel, Paul B.; Lan, Xin; Manizza, Manfredi; Muhle, Jens; O'Doherty, Simon; Prinn, Ronald G.; Weiss, Ray F.; Young, Dickon; Ganesan, Anita L.
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	12945
结束页码	12960
卷号	22 期号:19 页码:16
英文摘要	Nitrous oxide is a potent greenhouse gas (GHG) and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions, which includes prior emissions with truncated Gaussian distributions and Gaussian model errors, in order to examine the drivers of the atmospheric surface growth rate. We show that both emissions and climatic variability are key drivers of variations in the surface nitrous oxide growth rate between 2011 and 2020. We derive increasing global nitrous oxide emissions, which are mainly driven by emissions between 0 and 30 degrees N, with the highest emissions recorded in 2020. Our mean global total emissions for 2011-2020 of 17.2 (16.7-17.7 at the 95 % credible intervals) Tg N yr(-1), comprising of 12.0 (11.2-12.8) Tg N yr(-1) from land and 5.2 (4.5-5.9) Tg N yr(-1) from ocean, agrees well with previous studies, but we find that emissions are poorly constrained for some regions of the world, particularly for the oceans. The prior emissions used in this and other previous work exhibit a seasonal cycle in the extra-tropical Northern Hemisphere that is out of phase with the posterior solution, and there is a substantial zonal redistribution of emissions from the prior to the posterior. Correctly characterizing the uncertainties in the system, for example in the prior emission fields, is crucial for deriving posterior fluxes that are consistent with observations. In this hierarchical inversion, the model-measurement discrepancy and the prior flux uncertainty are informed by the data, rather than solely through expert judgement. We show cases where this framework provides different plausible adjustments to the prior fluxes compared to inversions using widely adopted, fixed uncertainty constraints.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000865444100001
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/273917
作者单位	University of Bristol; University of Wollongong; University of Bristol; Commonwealth Scientific & Industrial Research Organisation (CSIRO); University of California System; University of California San Diego; Scripps Institution of Oceanography; National Oceanic Atmospheric Admin (NOAA) - USA; University of Colorado System; University of Colorado Boulder; Massachusetts Institute of Technology (MIT)
推荐引用方式 GB/T 7714	Stell, Angharad C.,Bertolacci, Michael,Zammit-Mangion, Andrew,et al. Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion[J],2022,22(19):16.
APA	Stell, Angharad C..,Bertolacci, Michael.,Zammit-Mangion, Andrew.,Rigby, Matthew.,Fraser, Paul J..,...&Ganesan, Anita L..(2022).Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(19),16.
MLA	Stell, Angharad C.,et al."Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.19(2022):16.