| Project/Area Number |
08308020
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 総合 |
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| Research Field |
Statistical science
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| Research Institution | HIROSHIMA UNIVERSITY |
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Principal Investigator |
SATO Manabu Hiroshima University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (90178773)
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| Co-Investigator(Kenkyū-buntansha) |
KANEFUJI Koji The Institute of Statistical Mathematics, Department of Statistical Methodology,, 調査実験解析系, 助手 (40233902)
NISHIDA Nobuo Hiroshima Women's University Faculty of Human Life and Enrironmental Science, Pr, 生活科学部, 教授 (20084155)
SETO Sinya Hiroshima Prefectural Research Center for Health and Enrironmental Science, Atmo, 大気環境部, 主任研究員
NITTA Hiroshi National Institute for Enrironmental Studies, Urban Enrironment and Health Resea, 地域環境研究グループ, 総合研究官 (40156138)
OHTAKI Megu Hiroshima University, Research Institute for Radiation Biology and Medcine, Prof, 原爆放射能医学研究所, 教授 (20110463)
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| Project Period (FY) |
1996
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| Project Status |
Completed (Fiscal Year 1996)
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| Budget Amount *help |
¥3,000,000 (Direct Cost: ¥3,000,000)
Fiscal Year 1996: ¥3,000,000 (Direct Cost: ¥3,000,000)
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| Keywords | source apportionment / indoor air / source profile / least sguares method with constraints |
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| Research Abstract |
We develop a new method of estimating source apportionment of particulate matters based on source profiles with fluctuations. Previous methods for estimating source apportionment are based on the assumption that source profiles are to be constant. This assumption seems not to describe precisely the real world, however. For instance, it is naturally expected that the profiles of tobacco have sharp fluctuations because they depend on various causes such as puffing, kinds of cigarettes, and temperature. In order to analyze such data precisely, we develop a model and a simple estimating method which allows source profiles having fluctuations.
In practice, we analyzed the six data sets applying the proposed method. The estimated apportionments are stable with changing moderately between strata. It should be noticed as for "tobacco smoke" that the estimated source apportionments by smoking status are 22.5%, 31.7%, 45.8% for summer data, and 36.0%, 55.6%, 70.7% for winter data, which coincide with the order of smoking level for both seasons. The estimated c.v.varies widely from 0.53% to 35.88%, the maximum value is for "tobacco smoke" and the minimum is for "steelworks".
Our method can estimate the relative contributions of indoor and outdoor sources based on the less assumptions compared to some of the models previously reported. Nitta et al. (1994) analyzed the data under the assumption that c.v.of the volume concentration of SPM are equal. However, this assumption does not hold, in particular, c.v.of tobacco is much larger than the others.
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