Development of probabilistic concentration analysis method for environmental pollutants by Bayesian statistics
| Project/Area Number |
17H04945
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
Architectural environment/Equipment
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥23,920,000 (Direct Cost: ¥18,400,000、Indirect Cost: ¥5,520,000)
Fiscal Year 2019: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2018: ¥7,280,000 (Direct Cost: ¥5,600,000、Indirect Cost: ¥1,680,000)
Fiscal Year 2017: ¥10,270,000 (Direct Cost: ¥7,900,000、Indirect Cost: ¥2,370,000)
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| Keywords | 建築環境・設備 / 確率論 / 流体工学 / シミュレーション工学 |
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| Outline of Final Research Achievements |
We have developed a method to estimate the concentration distribution in the environment with higher accuracy and spatial resolution for air pollution caused by unknown pollutant sources in urban and architectural spaces. For this purpose, we used a probabilistic methodology called Bayesian statistics to integrate sensor measurements of concentration with computer predictions of airflow and concentration. To build this method, we extended each elemental technology required for the method, and made it more accurate and efficient. In addition, the effectiveness of each proposed method was clarified by empirical analysis based on experimental data.
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| Academic Significance and Societal Importance of the Research Achievements |
都市や建築といった環境中の空気汚染の解析においては、計測またはコンピュータによる解析のどちらかを選択するというのが従来の基本的な考え方であった。しかし、両者にはそれぞれに長所および短所が存在する。本研究の成果は、両者を有機的に接合することで、互いの短所を補いつつ長所を強め、従来の方法論ではなし得なかった高い精度および高い空間解像度での空気汚染物質濃度の評価を実現するものである。本研究では、このような考え方に基づく濃度解析において、学術的にも新たな知見を多く提供するとともに、最終的には人々の居住空間の空気の質を高め、その健康や快適性の向上に資することを目指した。
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Report
(4 results)
Research Products
(27 results)
