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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 張斐章(Fi-John Chang) | |
| dc.contributor.author | Angela Huang | en |
| dc.contributor.author | 黃安祺 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:26:56Z | - |
| dc.date.available | 2022-03-07 | |
| dc.date.available | 2022-11-23T09:26:56Z | - |
| dc.date.copyright | 2022-03-07 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-14 | |
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Hydrological Processes. 19, 1431–1444 (2005) Zezza, A.; Tasciotti, L. Urban agriculture, poverty, and food security: Empirical evidence from a sample of developing countries. Food policy 2010, 35(4), 265-273. Zhai……… | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80115 | - |
| dc.description.abstract | "水、糧食和能源是延續生命體和維繫都市運作的三種最重要資源，三者間的供應與使用息息相關。全球人口的快速增長、集中與都市化，大幅增加對水、糧食和能源需求，並對這些資源存量與使用效率形成巨大壓力。台灣雖然預計未來五十年人口將較目前下降，但都市化的趨勢依然明顯，可預期仍將對水、糧食和能源的供應有極大壓力。因此近來國際間針對水，糧食和能源鏈結關係(water-food-energy nexus)的研究越來越多，亦發展出各種分析工具方法來評估三種資源的供應、消耗量，以及彼此間的交互影響與競合關係，期能探索出資源分配利用的最佳化協同效益。然大部分研究的空間規模尺度都很大，例如從國家、河川流域、地理區域等角度來進行後驗的總量分析，而從地方上能事前先經過整體規劃再務實執行的機制，卻尚不多見，特別是從都市農業對水、糧食、能源資源在都會區的影響與貢獻的研究極其有限。2020年起全球新冠肺炎流行病暴發後，各種出行流動的管控措施影響了許多商品貨物及糧食的流通與供應，都市農園遂再度成為在地鮮蔬生產能否有效滿足局部自主供應的議題。 為落實在地資源鏈結之理念，本研究從水-糧食-能源鏈結的資源使用觀點着手，利用市中心的閒置土地空間，結合在地能源、資源收集與市政水電的併用來進行都市農業生產，並以系統動態模型（System Dynamics Modeling, SDM）方法，計算各資源的入出流量，再從水資源與能源的供給與消耗面，分析糧食就近生產所需的單位水電消耗量與收成量之間的關連性（關係）。而作物生長受在地氣候影響很大，故本研究先利用類神經網路方法下之自組織映射（Self-organizing Map，SOM），從北台灣歷史氣象資料中聚類找出北台灣的氣候類型，並特別分析臺北市氣候類型在時間分佈上的特徵，再結合台北市屋頂農園實際成功案例，建構台北市都市農園葉菜作物於氣候-水-糧食-能源資源鏈結之系統動態模型，並進一步以2018年氣象資料為模擬背景，發展全年依氣候條件配置葉菜種植（葉萵苣和地瓜葉）的系統動態基礎模式，探討台北市都市農園（屋頂農場）全季節葉菜作物種植生產在氣候與資源間的關聯性以及資源投入與產出間的利用效率，以提供都市與農業相關部門在規劃發展都市農業時，為未來潛在糧食安全風險提前部署都市地區農園儲備建置時提出策略參考。 本研究模型特色在於能隨時間的演進，透過描述資源的連續性、變化和交互行為特徵，有效捕捉水-糧食-能源鏈結間動態串聯。本研究以台北市大安老人中心屋頂農園實際成功的都市農園生產工作與收穫資料為案例基礎，所建構的氣候-水-能源-糧食鏈結模型評估了台北市屋頂農場葉菜作物生產的有效性和資源利用效率，其結果表明，2018年在120平方公尺的栽植面積裡，全年度在地連續種植葉萵苣和地瓜葉的總年產量可達1.001噸，而該年作物生長期間共需水量為1,170.5噸（包含使用596.8 噸的雨水回收再利用，和213.2 噸的自來水），以及總共645.1千瓦時的能源需求（包括298.4千瓦時太陽能光伏發電和45.8千瓦時的市政電力）。以種植的葉菜類單位面積計算，2018年平均每平方公尺需要9.8噸的澆灌水（5.0 ton/m2 來自雨水回收，以及1.8 ton/m2 的市水供應），以及每平方公尺需要 5.4 kwh的能源需求以啟動澆灌馬達工作（2.5 kwh/m2 來自太陽綠能的收集，以及 0.4 kwh/m2 的市電供應)；再以此單位用量擴展到台北市的建築屋頂的面積，若其中30%的面積（56,602 m2）能施行屋頂農園種植葉萵苣和地瓜葉，其2018年屋頂農園的模擬收穫量得以推估出，除了當年綠水綠能的收集使用外，另僅需消耗4,460噸的市水和575,000kWh市電的能資源成本，供應周邊4,312人（或1,437個三口之家）的全年鮮蔬食用。 本研究分析結果將可提供相關決策單位對都會區鮮蔬葉菜類之糧食供應進行產地的有效調整配置與生產，增加城市居民新鮮農產蔬果的來源，並消除部分糧作因來自外地衍生的”食物里程”與運輸成本，以降低農產品市售價格，且能有效調節天災後的蔬菜供應質量與控制菜價波動，提升都市農業對水、糧食、能源資源的協同效益，期能更符合智慧永續城市的目標。 " | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:26:56Z (GMT). No. of bitstreams: 1 U0001-1102202215053000.pdf: 7303380 bytes, checksum: a3f029d09dcebe323e119f61ac4295e6 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | "Table of Contents 謝誌 i 中文摘要 ii Abstract iv Table of Contents vi List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Overview 1 1.1.1 Trends of population and urbanization 1 1.1.2 Issues of Water, Food Energy Nexus 2 1.1.3 Urban Agriculture 4 1.1.4 Resource-use Sustainability 6 1.1.5 Weather Conditions 7 1.2 Research Formation 8 1.2.1 Problems and Scope 8 1.2.2 Rationale Concepts 10 1.2.3 Research Objectives 11 1.3 Research Flow 12 Chapter 2 Framework and Methodology 14 2.1 From Concepts to Framework 14 2.1.1 Explore Analytical Resource Flows 14 2.1.2 The Real Case as Reference 17 2.2 Materials 19 2.2.1 The Study Area Site 19 2.2.2 The Target Crops 20 2.2.3 The Historical Meteorology Data 21 2.3 Methodology 22 2.3.1 Artificial Neural Network (ANN) 22 2.3.2 Self-Organizing Map (SOM) 23 2.3.3 System Dynamics Modeling (SDM) 23 2.3.4 Integration for UA Evaluation 25 Chapter 3 Literature Review 26 3.1 WFE Nexus 26 3.2 Urban Agriculture 28 3.3 Agriculture Weather Forecasting 31 Chapter 4 Using a SOM to Explore Weather Types and Features 34 4.1 Materials and Methodology 36 4.1.1 Weather Data Collection 37 4.1.2 SOM Approach 39 4.2 SOM Results Analysis 42 4.2.1 Weather Features Types 43 4.2.2 Weather patterns at Five Stations in Northern Taiwan 49 4.2.3. Temporal Pattern of Weather Types 49 4.2.4 Frequency, Duration Distributions of Type Occurrences 52 4.3 Main Weather Features in Taipei City 54 Chapter 5 System Dynamic Modeling for Rooftop Farming 58 5.1 SDM Methodology 58 5.1.1 System dynamics (SD) 59 5.1.2 Construction of the SD Model 59 5.1.3 SD operation Driven by the WEF Nexus 67 5.2 Results of SPL SDM 69 5.2.1 SPL’s CSI, Growth Periods Yields 69 5.2.2 Water, Energy Needs Consumption on a Harvest Basis 71 5.3 Analysis on SPL SDM 75 5.4 SDM Results Analysis on Leafy Lettuce 77 Chapter 6 The All-Year Leafy Vegetables Planting Plan 83 6.1 Weather Features for Leafy Vegetable Planting in Taipei 83 6.2 All-year Planting Plan for Target Crops 85 6.3 The Setting Scheduling for SDM 86 6.4 Results of the All-year Planting SDM on Resource Uses 89 Chapter 7 Discussion and Applications 93 7.1 Weather Types Features 93 7.1.1 SOM Approach Contributions to the Weather Typing 93 7.1.2 Potential Applications with Examples 94 7.2 Resource Use Efficiency on WFE Nexus 97 7.2.1 SDM Contributions to the Resources Continuum in WFE Nexus 97 7.2.2 Potential Applications for Urban Agriculture from WFE Nexus 98 7.3 Prospects for All-year rooftop farming under the WEF Nexus 99 Chapter 8 Conclusions 101 8.1 Weather Features and Applications 101 8.2 Resource-use efficiency Applications on WFE nexus 102 8.3 Suggestions and Future Work 103 Reference List 105 List of Figures Figure 1.1. The interrelationship of water, food, and energy nexus 3 Figure 1.2. Pressures from urbanization and population to the WFE Nexus 4 Figure 1.3. Direction of resource flows among WFE Nexus. 10 Figure 1.4. Research formation flow in this study 13 Figure 2.1. Concept of WFE resource stock and flows 14 Figure 2.2. Conceptual architecture hierarchy of urban WFE Nexus 16 Figure 2.3. Concept of WFE resources as inflows and outflows 16 Figure 2.4. Resource sources to meet demand goal 18 Figure 2.5. Urban rooftop farming mechanism and benefits 18 Figure 2.6. The rooftop farm at the Da-an Senior Service Center. 20 Figure 2.7. Conceptual illustration for basic ANN structure 23 Figure 2.8. Approaches integrated for urban agriculture evaluation 25 Figure 4.1. The locations of five Central Weather Bureau stations in northern Taiwan 38 Figure 4.2. The SOM network for weather features clustering in this research 42 Figure 4.3. The counts of datasets and numbering labels in the SOM topology 43 Figure 4.4. The heatmap of weather factors and their corresponding characteristics 45 Figure 4.5 Weather types #7 and #2 with weather factor significance transformed into radar diagrams 47 Figure 4.6. The weather type distribution on a 10-day basis at Taipei Station 51 Figure 4.7. The annual percentages of nine weather type occurrences at Taipei Station 51 Figure 4.8. The seasonal weather features and the leading types at Taipei Station 52 Figure 4.9. The distribution of main weather types in sections A, B C at Taipei Station from 2014 to 2018 54 Figure 4.10. The major weather types of Sections A, B C in radar diagrams 55 Figure 5.1. The WEF Nexus upon a rooftop farming operation mechanism 59 Figure 5.2. Construction of the Climate Suitability Index (CSI) and four preliminary components 61 Figure 5.3. SD model structure engaging climate, water, energy and food sectors 62 Figure 5.4. The flowchart of urban rooftop farming SD under the WEF Nexus 68 Figure 5.5. Climatic suitability indices and SPL growing results from the SDM 70 Figure 5.6. Climate conditions vs. resource needs and consumption on per harvest basis from the SD model 73 Figure 5.7. Water and energy use obtained from the SD model 74 Figure 5.8. The suitability indices for leafy lettuce in 2014-2016 78 Figure 5.9. Simulated growing periods of leafy lettuce between 2014-2016 79 Figure 5.10. Analysis of the accumulated water and energy resource use for each lettuce harvest 81 Figure 5.11. Water energy resource uses for each lettuce harvest on per unit basis 82 Figure 6.1. The major weather types of 3 weather Sections in Taipei and their statistical characteristics of weather factors 84 Figure 6.2. The percentage of green and city resource uses of each harvest for the all-year leafy vegetable cultivation in Taipei 90 List of Tables Table 3.1. Benefits of Vegetables Yields 30 Table 3.2. Benefits of Food Safety 30 Table 3.3. Benefits of Environment 30 Table 4.1. Basic weather information collected at five weather stations in northern Taiwan during 2014–2018 39 Table 4.2. Weather types and features at 5 weather stations in northern Taiwan 49 Table 4.3. The summarized weather types and features of Sections A, B and C in Taipei 57 Table 5.1. Roles of climate, water, energy and food resources in the SDM 63 Table 5.2. Ratio of SPL resource consumption to annual resource needs obtained from the SDM 76 Table 5.3. SPL yields and resources use simulated by the SDM 76 Table 5.4. Annual yields and resource use for leafy lettuce on per unit basis 80 Table 6.1. The SDM simulation result of all-year leafy vegetable cultivation for rooftop farming in 2018 88 Table 6.2. Resource uses on per unit basis of each harvest for year-round leafy vegetables cultivation 92 " | |
| dc.language.iso | en | |
| dc.subject | 北台灣氣候類型與特徵 | zh_TW |
| dc.subject | 水-糧食-能源鏈結 | zh_TW |
| dc.subject | 都市農業 | zh_TW |
| dc.subject | 資源使用效益 | zh_TW |
| dc.subject | 系統動態模型 | zh_TW |
| dc.subject | 自組織映射網路 | zh_TW |
| dc.subject | 氣候適宜度指數 | zh_TW |
| dc.subject | system dynamics modeling (SDM) | en |
| dc.subject | weather types and features in northern Taiwan | en |
| dc.subject | climate suitability index | en |
| dc.subject | Water-Energy-Food nexus (WEF Nexus) | en |
| dc.subject | urban agriculture (UA) | en |
| dc.subject | sustainable resources-use efficiency | en |
| dc.subject | self-organizing map (SOM) | en |
| dc.title | 都市農業在永續智慧城市水-糧食-能源鏈結下的協同效用 | zh_TW |
| dc.title | SYNERGIES OF URBAN AGRICULTURE TO SUPPORT SUSTAINABLE WATER-FOOD-ENERGY NEXUS IN SMART CITIES | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 盧虎生(Tzong-Lin Jay Shieh),童慶斌(Hsuen-Li Chen),張麗秋(Feng-Yu Tsai),鄭舒婷(Yu-Ching Huang) | |
| dc.subject.keyword | 水-糧食-能源鏈結,都市農業,資源使用效益,系統動態模型,自組織映射網路,氣候適宜度指數,北台灣氣候類型與特徵, | zh_TW |
| dc.subject.keyword | Water-Energy-Food nexus (WEF Nexus),urban agriculture (UA),sustainable resources-use efficiency,system dynamics modeling (SDM),self-organizing map (SOM),climate suitability index,weather types and features in northern Taiwan, | en |
| dc.relation.page | 117 | |
| dc.identifier.doi | 10.6342/NTU202200566 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2022-02-14 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
| 顯示於系所單位： | 生物環境系統工程學系 | |
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| U0001-1102202215053000.pdf | 7.13 MB | Adobe PDF | 檢視/開啟 |
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