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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84096完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳佳堃(Jia-Kun Chen) | |
| dc.contributor.author | Chung-Yin Fang | en |
| dc.contributor.author | 方仲穎 | zh_TW |
| dc.date.accessioned | 2023-03-19T22:04:43Z | - |
| dc.date.copyright | 2022-10-03 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-07-18 | |
| dc.identifier.citation | 1. Taylor, L., Covid-19: Omicron drives weekly record high in global infections. 2022, British Medical Journal Publishing Group. 2. Alexandar, S., et al., A comprehensive review on Covid-19 Delta variant. International Journal of Pharmacology and Clinical Research (IJPCR), 2021. 5(83-85): p. 7. 3. Bazant, M.Z. and J.W. Bush, A guideline to limit indoor airborne transmission of COVID-19. Proceedings of the National Academy of Sciences, 2021. 118(17). 4. 行政院環境保護署. 公告場所室內空氣品質檢驗測定管理辦法. 2021; Available from: https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=O0130006. 5. Somsen, G.A., et al., Small droplet aerosols in poorly ventilated spaces and SARS-CoV-2 transmission. The Lancet Respiratory Medicine, 2020. 8(7): p. 658-659. 6. 行政院環境保護署. 室內空氣品質管理法. 2011; Available from: https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=O0130001. 7. 行政院環境保護署. 室內空氣品質標準. 2012; Available from: https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=O0130005. 8. Wells, W.F., Airborne Contagion and Air Hygiene. An Ecological Study of Droplet Infections. Airborne Contagion and Air Hygiene. An Ecological Study of Droplet Infections., 1955. 9. Riley, R.L., E.C. Riley, and G. Murphy, Airborne Spread of Measles in a Suburban Elementary-School. American Review of Respiratory Disease, 1978. 117(4): p. 255-255. 10. 柳政國, 隔離病房呼氣污染物擴散之數值模擬分析. 臺北科技大學優質電力供電產業研發碩士專班學位論文, 2010: p. 1-81. 11. 林俊杰, 結合多空間氣流模型與感染傳輸模型評估氣懸感染疾病之風險. 宜蘭大學土木工程學系學位論文, 2016: p. 1-124. 12. 王文珊, 圖書館與養老院室內空氣品質之探討. 臺北科技大學優質電力供電產業研發碩士專班學位論文, 2014: p. 1-79. 13. 林政隆, 傳染性疾病居家隔離空間之通風系統對室內氣懸感染機制之影響. 2007. 14. 衛生福利部疾病管制署. 人口密集機構感染管制措施指引. 2021; Available from: https://www.cdc.gov.tw/Category/ListContent/FR9BZ-4u-p4jZvbt_q6IXw?uaid=yqpTfOoGIjZKJ4j5SHxzCA. 15. Organization., W.H. Coronavirus disease (COVID-19): Ventilation and air conditioning. 2021; Available from: https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-covid-19-ventilation-and-air-conditioning. 16. 何志隆, 一般家庭室內空氣污染源擴散排放之模擬. 2010. 17. 許瑾瑜, 室內生物性污染調查與改善策略之研究─ 以圖書館為例. 2018. 18. Kaczmarczyk, J., A. Melikov, and P.O. Fanger, Human response to personalized ventilation and mixing ventilation. Indoor Air, 2004. 14: p. 17-29. 19. Kong, X., et al., Experimental study on the control effect of different ventilation systems on fine particles in a simulated hospital ward. Sustainable Cities and Society, 2021. 73: p. 103102. 20. Qian, H., et al., Dispersion of exhaled droplet nuclei in a two-bed hospital ward with three different ventilation systems. Indoor air, 2006. 16(2): p. 111-128. 21. Ahmed, A.Q., S. Gao, and A.K. Kareem, A numerical study on the effects of exhaust locations on energy consumption and thermal environment in an office room served by displacement ventilation. Energy Conversion and Management, 2016. 117: p. 74-85. 22. Lin, Z., et al., Comparison of annual energy performances with different ventilation methods for cooling. Energy and Buildings, 2011. 43(1): p. 130-136. 23. Sanglier-Contreras, G., E.J. López-Fernández, and R.A. González-Lezcano, Poor ventilation habits in nursing homes have favoured a high number of COVID-19 infections. Sustainability, 2021. 13(21): p. 11898. 24. Mody, L., et al., Environmental contamination with SARS‐CoV‐2 in nursing homes. Journal of the American Geriatrics Society, 2022. 70(1): p. 29-39. 25. Ishigaki, Y., et al., Investigation of air change rate and aerosol behavior during an outbreak of COVID-19 in a geriatric care facility. medRxiv, 2022. 26. Ahlawat, A., et al., Preventing airborne transmission of SARS-CoV-2 in hospitals and nursing homes. 2020, Multidisciplinary Digital Publishing Institute. p. 8553. 27. Stewart, E.J., et al., ASHRAE position document on infectious aerosols. ASHRAE: Atlanta, GA, USA, 2020. 28. Organization, W.H., Roadmap to improve and ensure good indoor ventilation in the context of COVID-19. 2021. 29. Tang, J.W., et al., Covid-19 has redefined airborne transmission. 2021, British Medical Journal Publishing Group. 30. Santarpia, J.L., et al., Aerosol and surface contamination of SARS-CoV-2 observed in quarantine and isolation care. Scientific reports, 2020. 10(1): p. 1-8. 31. Lednicky, J., et al., Viable SARS-CoV-2 in the air of a hospital room with COVID-19 patients. medRxiv. Preprint posted online, 2020. 4. 32. Rudnick, S. and D. Milton, Risk of indoor airborne infection transmission estimated from carbon dioxide concentration. Indoor air, 2003. 13(3): p. 237-245. 33. Harrichandra, A., A.M. Ierardi, and B. Pavilonis, An estimation of airborne SARS-CoV-2 infection transmission risk in New York City nail salons. Toxicology and industrial health, 2020. 36(9): p. 634-643. 34. Pavilonis, B., et al., Estimating aerosol transmission risk of SARS-CoV-2 in New York City public schools during reopening. Environmental Research, 2021. 195: p. 110805. 35. Dai, H. and B. Zhao. Association of the infection probability of COVID-19 with ventilation rates in confined spaces. in Building simulation. 2020. Springer. 36. Zhang, S. and Z. Lin, Dilution-based evaluation of airborne infection risk-Thorough expansion of Wells-Riley model. Building and Environment, 2021. 194: p. 107674. 37. Wei, J. and Y. Li, Airborne spread of infectious agents in the indoor environment. American journal of infection control, 2016. 44(9): p. S102-S108. 38. Gralton, J., et al., The role of particle size in aerosolised pathogen transmission: a review. Journal of Infection, 2011. 62(1): p. 1-13. 39. Cole, E.C. and C.E. Cook, Characterization of infectious aerosols in health care facilities: an aid to effective engineering controls and preventive strategies. American journal of infection control, 1998. 26(4): p. 453-464. 40. Malani, P.N., Mandell, Douglas, and Bennett’s principles and practice of infectious diseases. JAMA, 2010. 304(18): p. 2067-2071. 41. Chao, C.Y.H., et al., Characterization of expiration air jets and droplet size distributions immediately at the mouth opening. Journal of aerosol science, 2009. 40(2): p. 122-133. 42. Hinds, W.C., Aerosol technology: properties, behavior, and measurement of airborne particles. 1999: John Wiley & Sons. 43. 陳雅蓁 and 蕭子健, 人工密閉環境中二氧化碳對人類生理反應之研究. 2011. 44. Issarow, C.M., N. Mulder, and R. Wood, Modelling the risk of airborne infectious disease using exhaled air. Journal of theoretical biology, 2015. 372: p. 100-106. 45. Richardson, E.T., et al., Shared air: a renewed focus on ventilation for the prevention of tuberculosis transmission. PLoS One, 2014. 9(5): p. e96334. 46. Liao, C.M., C.F. Chang, and H.M. Liang, A probabilistic transmission dynamic model to assess indoor airborne infection risks. Risk Analysis: An International Journal, 2005. 25(5): p. 1097-1107. 47. Hyun, S. and C. Kleinstreuer, Numerical simulation of mixed convection heat and mass transfer in a human inhalation test chamber. International journal of heat and mass transfer, 2001. 44(12): p. 2247-2260. 48. Sandberg, M. and M. Sjöberg, The use of moments for assessing air quality in ventilated rooms. Building and environment, 1983. 18(4): p. 181-197. 49. Dutton, S., L. Shao, and S. Riffat, Validation and parametric analysis of EnergyPlus: air flow network model using contam. Proceedings of SimBuild, 2008. 3(1): p. 124-131. 50. ASHRAE. Standard 62.1-2019, Ventilation for Acceptable Indoor Air Quality. 2019; Available from: https://www.ashrae.org/technical-resources/standards-and-guidelines/read-only-versions-of-ashrae-standards. 51. 凃宜彣, 護理之家室內熱舒適與改善對策之研究. 2020. 52. Basarir, M.N., Numerical study of the airflow and temperature distributions in an atrium. Queen’s University (Canada), Canada, 2011. 2009141. 53. Ito, K., et al., CFD benchmark tests for indoor environmental problems: Part 4 air-conditioning airflows, residential kitchen airflows and fire-induced flow. International Journal of Architectural Engineering Technology, 2015. 2(1): p. 76-102. 54. Mak, C.M. and F.W. Yik, A study of natural ventilation in a kitchen using computational fluid dynamics (CFD). Architectural Science Review, 2002. 45(3): p. 183-190. 55. Dassault. Numerical Basis of CAD-Embedded CFD. 2014; Available from: https://www.solidworks.com/sw/docs/flow_basis_of_cad_embedded_cfd_whitepaper.pdf. 56. Persily, A. and L. de Jonge, Carbon dioxide generation rates for building occupants. Indoor air, 2017. 27(5): p. 868-879. 57. Duguid, J., The size and the duration of air-carriage of respiratory droplets and droplet-nuclei. Epidemiology & Infection, 1946. 44(6): p. 471-479. 58. 交通部中央氣象局. 臺灣季節氣候分析. 2022; Available from: https://www.cwb.gov.tw/V8/C/C/Watch/watch_3.html#. 59. 衛生福利部疾病管制署. 第四類法定傳染疾病介紹. 2020; Available from: https://www.cdc.gov.tw/Category/Page/HMC9qDI4FA-gDrbcnFlXgg. 60. 衛生福利部疾病管制署. COVID-19醫療機構感染管制 Q&A. 2022; Available from: https://www.cdc.gov.tw/File/Get/F372M5tH3f25tICkb3WHpw. 61. Cheng, V.C.-C., et al., Outbreak investigation of airborne transmission of Omicron (B. 1.1. 529)-SARS-CoV-2 variant of concern in a restaurant: Implication for enhancement of indoor air dilution. Journal of Hazardous Materials, 2022. 430: p. 128504. 62. Prevention., C.f.D.C.a. Ventilation in Buildings. 2021; Available from: https://www.cdc.gov/coronavirus/2019-ncov/community/ventilation.html. 63. 16798-1:, E., Energy Performance of Buildings—Ventilation for Buildings—Part 1: Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics—Module M1-6. 2019, European Committee for Standardization Brussels, Belgium. 64. Pantelic, J. and K.W. Tham, Adequacy of air change rate as the sole indicator of an air distribution system's effectiveness to mitigate airborne infectious disease transmission caused by a cough release in the room with overhead mixing ventilation: a case study. HVAC&R Research, 2013. 19(8): p. 947-961. 65. Bolashikov, Z.D., et al., Exposure of health care workers and occupants to coughed airborne pathogens in a double-bed hospital patient room with overhead mixing ventilation. Hvac&R Research, 2012. 18(4): p. 602-615. 66. Ghia, U., et al., Assessment of health-care worker exposure to pandemic flu in hospital rooms. ASHRAE transactions, 2012. 118(1): p. 442. 67. Yang, C., X. Yang, and B. Zhao. Person to person droplets transmission characteristics in unidirectional ventilated protective isolation room: The impact of initial droplet size. in Building Simulation. 2016. Springer. 68. Liu, L., et al., Short‐range airborne transmission of expiratory droplets between two people. Indoor air, 2017. 27(2): p. 452-462. 69. Licina, D., et al., Human convection flow in spaces with and without ventilation: personal exposure to floor‐released particles and cough‐released droplets. Indoor air, 2015. 25(6): p. 672-682. 70. Ren, J., et al., Numerical Study of Three Ventilation Strategies in a prefabricated COVID-19 inpatient ward. Building and Environment, 2021. 188: p. 107467. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84096 | - |
| dc.description.abstract | 本研究根據計算流體力學模擬結果發現,自然換氣條件下由窗戶向外抽氣的模型普遍有較低的疾病感染風險,在自然換氣條件下向外抽氣抑制疾病傳播的效果相對較佳,但部分區域有空氣難以交換的死角或迴流區域。自然換氣條件下,即使通風量符合建議規範,仍難以有效均勻置換室內空氣,角落區域易有濃度蓄積情形,有較高的疾病感染風險,長照機構住房使用自然換氣降低空氣傳播疾病感染風險的成效有限。機械換氣條件下的模型能有效提升空氣品質,均勻地混合室內空氣,較少空氣滯留的死角區域,比較不同機械換氣條件發現,當使用中央空調型送風口,並將送迴風口裝設在住房正中央位置時,Wells-Riley計算結果的疾病傳播風險較低,室內空間中有各個方向的速度分布均勻混合空氣,具有低二氧化碳濃度與較佳的空氣品質,並有最少的室內微粒數量,是機械換氣條件下降低疾病傳播風險能力較佳的機械換氣設備。本研究得到結論為,對於尺寸相似的環境建議優先採用機械換氣設備取代自然通風,裝設機械換氣設備時建議選用中央空調型送風口的換氣設備,並將送迴風口裝設在住房正中央位置,以減少健康照護人員與住民的疾病感染風險。 | zh_TW |
| dc.description.abstract | The simulation results found that the model that draws air out of the window under natural ventilation conditions generally has a lower risk of disease infection. The effect of air pumping out under natural ventilation conditions is relatively good in inhibiting the spread of disease. Still, some areas have dead spots or backflow areas where the air is difficult to exchange. Under natural ventilation, it is difficult to effectively and uniformly replace the indoor air, and the corner areas were prone to concentration accumulation, which had a higher risk of disease infection. Using natural ventilation to reduce the risk of contracting airborne diseases was ineffective. Under the conditions of mechanical ventilation, it can effectively improve air quality. When the central air-conditioning type is used, and the return air outlet is installed in the center of the room, the risk of disease transmission is low. This study concluded that it is recommended to use mechanical ventilation equipment for similar environments instead of natural ventilation. When installing mechanical ventilation equipment, it was recommended to use central air-conditioning type ventilation equipment and install the return air outlet in the center of the room to reduce the risk of disease infection. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T22:04:43Z (GMT). No. of bitstreams: 1 U0001-1707202213581400.pdf: 10967231 bytes, checksum: ce47737e980112f274f37de146496536 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 致謝 II 摘要 III Abstract IV 目錄 V 表目錄 VIII 圖目錄 IX 縮寫說明 XIII 符號說明 XIV 第一章 前言 1 1.1 研究動機 1 1.2 文獻探討 3 1.2.1 長照機構與空氣傳播疾病 3 1.2.2 Wells-Riley模型 4 1.2.3 粒徑特性 4 1.2.4 二氧化碳 5 第二章 研究方法與材料 7 2.1 統御方程式 7 2.1.1 質量守恆定律 8 2.1.2 動量守恆定律 8 2.1.3 濃度傳輸方程式 9 2.1.4 粒子軌跡方程式 10 2.1.5 整體通風方程式 10 2.2 模擬分析軟體 10 2.3 現場量測 11 2.4 研究使用儀器 11 2.5 Wells-Riley感染傳輸方程式 12 2.6 空氣局部平均年齡 12 2.7 初始條件與邊界條件 13 2.8 網格獨立性 14 第三章 結果 16 3.1 現場評估長照機構八人住房疾病感染風險 16 3.1.1 長照機構八人住房現場量測二氧化碳濃度 16 3.1.2 長照機構八人住房現場Wells-Riley感染傳輸方程式計算結果 16 3.2 自然換氣條件下八人住房疾病感染風險 18 3.2.1 Wells-Riley感染傳輸方程式計算結果 18 3.2.2 比較二氧化碳濃度 18 3.2.3 比較室內環境LMA 20 3.2.4 比較速度分布情形 21 3.2.5 比較室內環境微粒最終流布情形 23 3.3機械換氣條件下八人住房疾病感染風險 25 3.2.1 Wells-Riley感染傳輸方程式計算結果 25 3.2.2 比較二氧化碳濃度 26 3.2.3 比較室內環境LMA 27 3.2.4 比較速度分布情形 28 3.2.5 比較室內環境微粒最終流布情形 30 第四章 討論 32 4.1 Wells-Riley計算結果 32 4.2 各項指標討論 33 4.3 自然換氣討論 34 4.4 機械換氣討論 35 第五章 結論與建議 36 第六章 研究限制與未來展望 38 第七章 參考文獻 39 附件一 以整體通風方程式模擬計算不同容留人數與停留時間之感染風險 142 附件二 模擬不同通風量對應二氧化碳濃度之感染風險 143 | |
| dc.language.iso | zh-TW | |
| dc.subject | 長照機構 | zh_TW |
| dc.subject | 空氣傳播疾病評估 | zh_TW |
| dc.subject | 計算流體力學 | zh_TW |
| dc.subject | Long-term care facility | en |
| dc.subject | Risk of airborne diseases | en |
| dc.subject | CFD | en |
| dc.title | 長照機構住房換氣型態與空氣傳播疾病風險研究 | zh_TW |
| dc.title | Research on Ventilation Patterns and Risk of Airborne Diseases in the Long-term Care Facility | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蘇大成(Ta-Chen Su),曾子彝(Tzu-I Tseng),邱嘉斌(Chia-Pin Chio),梁佑全(Yu-Chuan Liang) | |
| dc.subject.keyword | 長照機構,空氣傳播疾病評估,計算流體力學, | zh_TW |
| dc.subject.keyword | Long-term care facility,Risk of airborne diseases,CFD, | en |
| dc.relation.page | 147 | |
| dc.identifier.doi | 10.6342/NTU202201507 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-07-19 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 環境與職業健康科學研究所 | zh_TW |
| dc.date.embargo-lift | 2022-10-03 | - |
| 顯示於系所單位: | 環境與職業健康科學研究所 | |
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