DOI: 10.1016/j.atmosenv.2014.08.023
Scopus记录号: 2-s2.0-84906737333
论文题名: Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China
作者: Situ S ; , Wang X ; , Guenther A ; , Zhang Y ; , Wang X ; , Huang M ; , Fan Q ; , Xiong Z
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 98 起始页码: 105
结束页码: 110
语种: 英语
英文关键词: Biogenic VOCs
; Dinghushan
; Isoprene emission
; MEGAN
; Monte Carlo
; Uncertainty
Scopus关键词: Forestry
; Meteorology
; Monte Carlo methods
; Biogenic VOCs
; Dinghushan
; Isoprene emission
; MEGAN
; Uncertainty
; Uncertainty analysis
; Monte Carlo methods
; isoprene
; ozone
; hydroxyl radical
; biogenic emission
; broad-leaved forest
; coniferous forest
; emission inventory
; isoprene
; mixed forest
; Monte Carlo analysis
; photosynthetically active radiation
; temperature effect
; uncertainty analysis
; volatile organic compound
; aerosol
; confidence interval
; advection
; aerosol
; air sampling
; air temperature
; analytical error
; article
; circadian rhythm
; confidence interval
; controlled study
; environmental parameters
; environmental temperature
; forest
; greenhouse gas
; land use
; leaf area
; megan model
; Monte Carlo method
; nonhuman
; photosynthetically active radiation
; plant leaf
; priority journal
; process model
; relative density
; soil moisture
; steady state
; taiga
; vegetation
; air pollution
; Article
; forest
; meteorology
; oxidation
; temperature
; uncertainty
; Forestry
; Isoprene
; Radiation
; China
; Dinghushan
; Guangdong
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: With local observed emission factor and meteorological data, this study constrained the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 to estimate isoprene emission from the Dinghushan forest during fall 2008 and quantify the uncertainties associated with MEGAN parameters using Monte Carlo approach. Compared with observation-based isoprene emission data originated from a campaign during this period at this site, the local constrained MEGAN tends to reproduce the diurnal variations and magnitude of isoprene emission reasonably well, with correlation coefficient of 0.7 and mean bias of 47.5%. The results also indicate high uncertainties in isoprene emission estimated, with the relative error varied from -89.0-111.0% at the 95% confidence interval. The key uncertainty sources include emission factors, γTLD, photosynthetically active radiation (PAR) and temperature. This implies that accurate input of emission factor, PAR and temperature is a key approach to reduce uncertainties in isoprene emission estimation. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80905
Appears in Collections: 气候变化事实与影响
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作者单位: School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China; Pacific Northwest National Laboratory, Richland, WA 99532, United States; State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou 510640, China; Key Laboratory of Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Recommended Citation:
Situ S,, Wang X,, Guenther A,et al. Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China[J]. Atmospheric Environment,2014-01-01,98