气候变化领域集成服务门户(CCPortal): Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

CCPortal

DOI	10.1029/2019JD032128
	Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques
	Weise D.R.; Palarea-Albaladejo J.; Johnson T.J.; Jung H.
发表日期	2020
ISSN	2169897X
卷号	125 期号:6
英文摘要	By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char, and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data that violates key assumptions for many of the statistical methods ordinarily used to analyze these data such as linear regression, analysis of variance, and t tests. These data are inherently multivariate, relative, and nonnegative parts of a whole and are then characterized as so-called compositional data. This paper introduces the field of compositional data analysis to the biomass burning emissions community and provides examples of statistical treatment of emissions data. Measures and tests of proportionality, unlike ordinary correlation, allow one to coherently investigate associations between parts of the smoke composition. An alternative method based on compositional linear trends was applied to estimate trace gas composition over a range of combustion efficiency that reduced prediction error by 4% while avoiding use of modified combustion efficiency as if it were an independent variable. Use of log-ratio balances to create meaningful contrasts between compositional parts definitively stressed differences in smoke emissions from fuel types originating in the southeastern and southwestern United States. Application of compositional statistical methods as an appropriate approach to account for the relative nature of data about the composition of smoke emissions and the atmosphere is recommended. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	balance; ilr coordinates; linear trend
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/186092
作者单位	Pacific Southwest Research Station, USDA Forest Service, Riverside, CA, United States; Biomathematics and Statistics Scotland, Edinburgh, United Kingdom; Pacific Northwest National Laboratories, Richland, WA, United States; Department of Mechanical Engineering, University of California, Riverside, CA, United States
推荐引用方式 GB/T 7714	Weise D.R.,Palarea-Albaladejo J.,Johnson T.J.,et al. Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques[J],2020,125(6).
APA	Weise D.R.,Palarea-Albaladejo J.,Johnson T.J.,&Jung H..(2020).Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques.Journal of Geophysical Research: Atmospheres,125(6).
MLA	Weise D.R.,et al."Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques".Journal of Geophysical Research: Atmospheres 125.6(2020).