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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 席行正 | |
dc.contributor.author | Kuan-Hsuan Pan | en |
dc.contributor.author | 潘冠璇 | zh_TW |
dc.date.accessioned | 2021-06-17T08:18:33Z | - |
dc.date.available | 2029-08-13 | |
dc.date.copyright | 2019-08-19 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-13 | |
dc.identifier.citation | 國立台灣大學公共衛生學院健康風險及政策評估中心 (2008)。台灣一般民眾暴露參數彙編。DOH96-HP-1801。
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74063 | - |
dc.description.abstract | 評估土壤污染場址之健康風險時,誤食土壤與落塵是重要的污染物暴露途徑, 特別是嬰幼兒,因具有頻繁的手口行為,使其成為高暴露風險族群。計算誤食土壤 與落塵造成之健康風險時,土壤與落塵攝食量是重要的影響參數,因此本研究利用 美國環保署所研發的SHEDS-soil/dust 模式,經由蒐集臺灣相關暴露參數,作為 SHEDS-soil/dust 的輸入參數,模擬臺灣6 至< 12, 12 至< 24 以及24 至< 36 個月的 嬰幼兒之土壤與落塵攝食量,同時,再依據過去研究調查的土壤黏附因子,探討活 動強度(活動前、間接接觸土壤與直接接觸土壤)與土壤質地(砂土和黏土)對於模擬 土壤與落塵攝食量的影響。另外,再利用模擬之土壤與落塵攝食量,估算某一污染 場址周邊家庭嬰幼兒之健康風險。 由SHEDS-soil/dust 結果顯示,在砂土組及黏土組中,6 至< 12, 12 至< 24 以及 24 至< 36 個月的嬰幼兒之土壤與落塵攝食量,在直接接觸土壤的情境下會隨著年 齡組上升而有些微增加。在不同活動強度中,直接接觸土壤的土壤與落塵攝食量明 顯高於間接接觸土壤與活動前之土壤落塵攝食量;另外,砂土組的平均土壤攝入量 高於黏土組的平均土壤攝食量。然而,SHEDS-soil/dust能區分土壤和落塵對於總 攝食量的貢獻,結果顯示,臺灣嬰幼兒之手到口的土壤攝食量明顯高於手到口的落 塵攝食量及物體到口的落塵攝食量。經由SHEDS-soil/dust的敏感度分析結果顯示, 土壤黏附因子、皮膚對表面/土壤表面積接觸比、手放入口比例、手放入口頻率、 手放入口的轉移效率以及洗手頻率皆是影響臺灣嬰幼兒土壤與落塵的攝食量的重 要影響因子。另一方面,將SHEDS-soil/dust 模擬之結果與過去利用追蹤元素法估 算之土壤與落塵攝食量進行比較,追蹤元素法的結果與砂土組在間接接觸情境下 之土壤與落塵攝食量具有相似的趨勢。 由健康風險的結果顯示,食入途徑相較於皮膚接觸,為孩童主要暴露到土壤與 落塵重金屬的暴露途徑。在非致癌風險中,模擬三種情境下,三個年齡組嬰幼兒的 危害指數皆沒有超過1。然而,在致癌風險中,在間接接觸土壤與直接接觸土壤的情境中,三個年齡組的嬰幼兒之第95百分位的風險值皆超過可接受風險值1.00E-06。 本研究提供利用模式估算土壤與落塵攝食量的方法,相較於傳統的追蹤元素 法,能夠有效的考量族群的變異性,也建議未來在污染場址的健康風險評估中,能 夠採用SHEDS-soil/dust 模式進行土壤與落塵攝食量的估算,提供特定族群的更完整的風險描述。 | zh_TW |
dc.description.abstract | Non-dietary ingestion is a crucial pathway for children who may ingest the pollutants in soil and dust due to their frequent mouthing behaviors. Therefore, it is important to determine soil and dust ingestion rate which has been used to underpin human health risk assessment and regulatory decisions pertaining to contaminated sites. In this study, the stochastic human exposure and dose simulation (SHEDS) model was employed to estimate soil and dust ingestion rate for Taiwanese children aged 6 to < 12, 12 to < 24, and 24 to < 36 months. Besides, the activity scenarios (pre-activity, indirect contact with soil, and direct contact with soil) and soil textures (sand and clay) were regarded as simulated inputs based on the soil-to-skin adherence factors that have been investigated in the prior studies. Additionally, the health risk assessment was also conducted to assess the adverse effects of young children exposure to heavy metals in soil and dust who living around the contaminated site.
Results from the SHEDS-soil/dust showed that the soil and dust ingestion rate between age groups slightly increased with the age groups. Comparing the soil and dust ingestion rate in three scenarios, the estimation of soil and dust ingestion in the direct contact with soil was obviously higher than that in other scenarios. In addition, the mean values of soil ingestion rate in the sand group was higher than that in the clay group. The SHEDS-soil/dust model could also distinguish the contribution of soil from that of dust, and then the result showed that hand-to-mouth soil ingestion was the main contribution in the exposure pathway. According to the sensitivity analysis in SHEDS-soil/dust, the parameters which affect the soil and dust ingestion rate with a significant ratio were soil-to-skin adherence factor, skin-soil/surface contact ratio, hand-to-mouth frequency, hand mouth fraction, and hand washing frequency. For health risk assessment, oral pathway, as compared to the dermal pathway, was the main exposure route for children exposure to heavy metals in soil and dust. The 95th percentile of the hazard index was not over the acceptable value of 1 for children of three age groups in three scenarios. However, the 95th percentile of total carcinogenic risks in the scenarios of indirect contact with soil and direct contact with soil exceeded 1.00E-06. This study provides a physical-based method, the SHEDS-soil/dust model, for estimating soil and dust ingestion rate. Compared with the traditional tracer element method, the SHEDS-soil/dust model could provide more information about the variability of the population. It is also recommended that the soil and dust ingestion rate predicted by the SHEDS-soil/dust model will be employed in the health risk assessment of the contaminated site in the future. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T08:18:33Z (GMT). No. of bitstreams: 1 ntu-108-R06541203-1.pdf: 5588315 bytes, checksum: 19f7633a4437dc3ea64ccd5d67adcffb (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | Acknowledgement II
中文摘要 IV Abstract VI Contents VIII List of Figures XII List of Tables XVI Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Research objectives 3 Chapter 2. Literature Review 5 2.1 The background of heavy metals 5 2.2 Children exposure risk 7 2.2.1 Mouthing behavior of age group for children 7 2.2.2 The relationship between the soil particle size and children exposure risk 8 2.3 Estimation of soil and dust ingestion rate 9 2.4 Stochastic human exposure and dose simulation (SHEDS) model 11 Chapter 3. Material and Methods 13 3.1 Research design 13 3.2 Sampling and pretreatment 15 3.2.1 Soil sampling 15 3.2.2 Street dust sampling 16 3.2.3 Household dust sampling 16 3.3 Soil characterization 19 3.3.1 pH 19 3.3.2 Total organic carbon 19 3.3.3 Soil texture analysis 20 3.4 Metal extraction of soil, street dust, and household dust 22 3.5 Stochastic human exposure dose simulation (SHEDS) modeling method for soil/dust ingestion 23 3.5.1 The SHEDS-soil/dust modeling for soil and dust ingestion 24 3.5.2 Definition of exposure scenarios 26 3.5.3 CHAD adjustment for use in Taiwan 27 3.5.4 Input determination 30 3.5.5 Sensitivity analysis in the SHEDS-soil/dust model 36 3.6 Human health risk assessment 37 3.6.1 Hazard identification 37 3.6.2 Dose-response assessment 38 3.6.3 Exposure assessment 39 3.6.4 Risk characterization 45 3.7 Data processing and statistical analysis 48 Chapter 4. Results and Discussion 49 4.1 Soil and dust ingestion rate estimation 49 4.1.1 Age groups 49 4.1.2 Activity scenarios 51 4.1.3 Soil texture 53 4.1.4 Comparison of the contribution between soil and dust 54 4.1.5 Sensitivity analysis in SHEDS-soil/dust 58 4.1.6 Comparison of modeled estimation and tracer element estimation 66 4.2 The properties of samples 69 4.2.1 Soil properties 69 4.2.2 Metal concentration in soil, street dust, and household dust 69 4.3 Health risk assessment 72 4.3.1 Non-carcinogenic health risk assessment 72 4.3.2 Carcinogenic risk assessment 80 4.3.3 Sensitivity analysis 87 Chapter 5. Conclusions and Suggestions 89 5.1 Conclusions 89 5.2 Suggestions 92 Chapter 6. References 94 Appendix 1. Parameters of the SHEDS model 102 Appendix 2. Parameters of health risk assessment 120 | |
dc.language.iso | en | |
dc.title | 以SHEDS模式預測土壤與落塵攝食量評估三歲以下台灣孩童重金屬暴露之健康風險評估 | zh_TW |
dc.title | Probabilistic Health Risk Assessment of Heavy Metal Exposure for Children under Three Years Old in Taiwan by Estimating Soil and Dust Ingestion Rate Using SHEDS Model | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 張立德,闕蓓德,簡伶朱 | |
dc.subject.keyword | SHEDS 模式,土壤與落塵攝食量,健康風險,敏感度分析,蒙地卡羅模擬, | zh_TW |
dc.subject.keyword | SHEDS model,soil and dust ingestion rate,health risk assessment,sensitivity analysis,Monte-Carlo simulation, | en |
dc.relation.page | 125 | |
dc.identifier.doi | 10.6342/NTU201903445 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-08-14 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 環境工程學研究所 | zh_TW |
顯示於系所單位: | 環境工程學研究所 |
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