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Preliminary Measurement of the K-Shell Ionization Cross Sections of Ti by Positron Impact in the Low Energy Region

Plasma Science and Technology 2012年第5期14卷 434-437页

作者：田丽霞刘慢天朱敬军安竹王宝义秦秀波 Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and TechnologySichuan University East China Institute of Technology Key Laboratory of Nuclear Analysis Techniques Institute of High Energy PhysicsCAS

Measurements were performed of K-shell ionization cross sections of Ti element by 10～30 keV positron impact using the thick-target method. The effects of multiple scattering of incident positron and from bremsstrahlung photons and annihilation photons with the thick-target method are discussed with the monte Carlo code PENELOPE. Meanwhile, the monte Carlo method is also applied to determine the detection efficiencies of X- and γ-ray detectors. Our experimental K-shell ionization cross sections for Ti element are compared with the distorted-wave Born approximation （DWBA） theoretical predictions, and it is found that the agreement of the experimental data and theoretical values is good and this indicates that the experimental method adopted in this study is applicable.

关键词： positron impact ionization cross sections thick-target method monte carlosimulation

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Bayesian meta-analysis of regional biomass factors for Quercus mongolica forests in South Korea

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Journal of Forestry Research 2015年第4期26卷 875-885页

作者： Tzeng Yih Lam Xiaodong Li Rae Hyun Kim Kyeong Hak Lee Yeong Mo Son Division of Forest Management Department of Forest and Climate Change Korea Forest Research Institute57 Hoegiro Dongdaemun-gu Seoul 130-712 South Korea School of Forestry and Resource Conservation National Taiwan University

Indirect approaches to estimation of biomass factors are often applied to measure carbon flux in the forestry sector. An assumption underlying a country-level carbon stock estimate is the representativeness of these factors. Although intensive studies have been conducted to quantify biomass factors, each study typically covers a limited geographic area. The goal of this study was to employ a meta-analysis approach to develop regional bio- mass factors for Quercus mongolica forests in South Korea. The biomass factors of interest were biomass conversion and expansion factor （BCEF）, biomass expansion factor （BEF） and root-to-shoot ratio （RSR）. Our objectives were to select probability density functions （PDFs） that best fitted the three biomass factors and to quantify their means and uncertainties. A total of 12 scientific publications were selected as data sources based on a set of criteria. Fromthese publications we chose 52 study sites spread out across South Korea. The statistical model for the meta- analysis was a multilevel model with publication （data source） as the nesting factor specified under the Bayesian framework. Gamma, Log-normal and Weibull PDFs were evaluated. The Log-normal PDF yielded the best quanti- tative and qualitative fit for the three biomass factors. However, a poor fit of the PDF to the long right tail of observed BEF and RSR distributions was apparent. The median posterior estimates for means and 95 % credible intervals for BCEF, BEF and RSR across all 12 publica- tions were 1.016 （0.800-1.299）, 1.414 （1.304-1.560） and 0.260 （0.200-0.335）, respectively. The Log-normal PDF proved useful for estimating carbon stock of Q. mongolica forests on a regional scale and for uncertainty analysis based on monte Carlo simulation.

关键词： Uncertainty analysis monte carlosimulation Bayesian hierarchical model Nestingstructure Biomass estimation

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