DOI: 10.1016/j.atmosenv.2017.07.001
Scopus记录号: 2-s2.0-85022089001
论文题名: Methane emissions from global wetlands: An assessment of the uncertainty associated with various wetland extent data sets
作者: Zhang B ; , Tian H ; , Lu C ; , Chen G ; , Pan S ; , Anderson C ; , Poulter B
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 165 起始页码: 310
结束页码: 321
语种: 英语
英文关键词: Methane
; Tropics
; Uncertainty
; Wetland
; Wetland data set
Scopus关键词: Methane
; Tropical engineering
; Tropics
; Wetlands
; Data set
; Dynamic land ecosystem models (DLEM)
; Integrating multiple sources
; Quantitative assessments
; Scientific community
; Spatial and temporal distribution
; Spatiotemporal distributions
; Uncertainty
; Uncertainty analysis
; methane
; assessment method
; bottom-up approach
; data set
; ecosystem modeling
; emission
; flux measurement
; global change
; methane
; satellite data
; spatial resolution
; tropical region
; uncertainty analysis
; wetland
; Article
; community
; ecosystem
; priority journal
; South America
; uncertainty
; wetland
; South America
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: A wide range of estimates on global wetland methane (CH4) fluxes has been reported during the recent two decades. This gives rise to urgent needs to clarify and identify the uncertainty sources, and conclude a reconciled estimate for global CH4 fluxes from wetlands. Most estimates by using bottom-up approach rely on wetland data sets, but these data sets show largely inconsistent in terms of both wetland extent and spatiotemporal distribution. A quantitative assessment of uncertainties associated with these discrepancies among wetland data sets has not been well investigated yet. By comparing the five widely used global wetland data sets (GISS, GLWD, Kaplan, GIEMS and SWAMPS-GLWD), it this study, we found large differences in the wetland extent, ranging from 5.3 to 10.2 million km2, as well as their spatial and temporal distributions among the five data sets. These discrepancies in wetland data sets resulted in large bias in model-estimated global wetland CH4 emissions as simulated by using the Dynamic Land Ecosystem Model (DLEM). The model simulations indicated that the mean global wetland CH4 emissions during 2000–2007 were 177.2 ± 49.7 Tg CH4 yr−1, based on the five different data sets. The tropical regions contributed the largest portion of estimated CH4 emissions from global wetlands, but also had the largest discrepancy. Among six continents, the largest uncertainty was found in South America. Thus, the improved estimates of wetland extent and CH4 emissions in the tropical regions and South America would be a critical step toward an accurate estimate of global CH4 emissions. This uncertainty analysis also reveals an important need for our scientific community to generate a global scale wetland data set with higher spatial resolution and shorter time interval, by integrating multiple sources of field and satellite data with modeling approaches, for cross-scale extrapolation. © 2017 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82331
Appears in Collections: 气候变化事实与影响
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作者单位: International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, United States; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China; Department of Ecology, Evolution, and Organismal Biology, Iowa State UniversityIA, United States; NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, United States; Institute on Ecosystems and Department of Ecology, Montana State University, Bozeman, MT, United States
Recommended Citation:
Zhang B,, Tian H,, Lu C,et al. Methane emissions from global wetlands: An assessment of the uncertainty associated with various wetland extent data sets[J]. Atmospheric Environment,2017-01-01,165