DOI: 10.1016/j.atmosenv.2014.08.044
Scopus记录号: 2-s2.0-84906347916
论文题名: Estimation of CO2 effluxes from suburban forest floor and grass using a process-based model
作者: Chun J ; A ; , Szlavecz K ; , Bernard M ; , Ferrer D ; , Hom J ; , Saliendra N
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 97 起始页码: 346
结束页码: 352
语种: 英语
英文关键词: Pulse effect
; SOILCO2
Scopus关键词: Forestry
; Greenhouse gases
; Mean square error
; Soil moisture
; Urban growth
; Atmospheric concentration
; Monitoring stations
; Process-based modeling
; Pulse effects
; Root mean square errors
; SOILCO2
; US Forest Service
; Volumetric soil moistures
; Forest floors
; Carbon dioxide
; carbon dioxide
; polyvinylchloride
; carbon dioxide
; carbon flux
; concentration (composition)
; deciduous forest
; diurnal variation
; estimation method
; forest floor
; greenhouse gas
; numerical model
; soil emission
; soil surface
; suburban area
; carbon cycle
; grass
; article
; capnometry
; carbon cycle
; carbon dioxide transport
; circadian rhythm
; environmental factor
; environmental monitoring
; environmental parameters
; forest
; grass
; land use
; priority journal
; sensor
; soil carbon dioxide efflux
; soil moisture
; soil respiration
; soil temperature
; soil water content
; soilco2 model
; suburban area
; temperature
; thermal conductivity
; thermistor
; Article
; ecosystem
; forest
; grass
; greenhouse gas
; measurement
; model
; soil
; Carbon Dioxide
; Forestry
; Greenhouse Gases
; Moisture
; Soil
; Maryland
; United States
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: Carbon dioxide is an important greenhouse gas, and its atmospheric concentration has been predicted to increase in the future. The objective of this study was to quantify the soil CO2 efflux in a suburban area including mixed deciduous forest and grass by numerically modeling the CO2 transport through the soil profile. Three stations per land-cover (forest and grass) were selected at the Cub Hill site (MD, USA), where the US Forest Service operates an urban flux tower. Six VAISALA CO2 sensors (Vaisala Inc., Finland) per monitoring station were horizontally installed at 6 different depths (soil surface, 0.02, 0.05, 0.10, 0.20, and 0.30m from the soil surface) in the mid of May, 2011. Temperature and volumetric soil moisture measurements were taken using thermistors and EC-5 sensors (Decagon devices, Pullman, WA, USA) that were installed at the same depths as the CO2 sensors except for the soil surface. These data were recorded every 10min. To evaluate the numerical model (SOILCO2), CO2 efflux using the standard chamber method was measured once a week. The CO2 effluxes from the standard chamber method ranged from 3.32×10-9 to 7.28×10-8m3m-2s-1 and 6.79×10-9 to 1.45×10-7m3m-2s-1 for forest and grass, respectively. The CO2 effluxes from "bare" soil at the grass site varied with the range of 3.63×10-8 to 9.37×10-8m3m-2s-1. The "pulse effect" (a rapid increase of CO2 concentrations right after rainfall events) in grass, where changes in soil moisture were larger than in the forest, was more apparent than in the forest. Diurnal patterns similar to those of temperature were observed from CO2 profiles in soils. The SOILCO2 model estimated the soil CO2 effluxes with coefficients of correlation of 0.64 and 0.76 at forest and grass, respectively, and root mean square error (RMSE) of 1.58×10-8 and 2.06×10-8m3m-2s-1 for forest and grass, respectively. This study suggests that the SOILCO2 model can provide a better understanding of the contribution of the soil ecosystem to the carbon cycle in suburban environments including mixed deciduous forest and grass. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81022
Appears in Collections: 气候变化事实与影响
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作者单位: APEC Climate Center, 12 Centum 7-ro, Haeundae-gu, Busan 612-020, South Korea; Johns Hopkins University, Baltimore, MD 21218, United States; USDA Forest Service, Newtown Square, PA 19073, United States; USDA-ARS NGPRL, Mandan, ND 58554, United States
Recommended Citation:
Chun J,A,, Szlavecz K,et al. Estimation of CO2 effluxes from suburban forest floor and grass using a process-based model[J]. Atmospheric Environment,2014-01-01,97