臺灣博碩士論文加值系統

本研究針對台灣自2001年至2015年共15年間之24項進口食品商品進行食物里程之分析，由於在過去許多學者研究中，針對二氧化碳排放量之研究，自工業革命後多以工業污染為主要之研究對象，鮮少有關於進口食品其背後在運輸過程中所製造之二氧化碳排放量加以研究調查。尤其台灣因先天土地及良田又因國土面積狹小，使得雖然看似物產豐沛的我們仍然對於糧食存在不足之疑慮。除此之外又因後天農村人口老化、農地荒廢及多項政府政策迫使轉型下，使得耕地面積更為限縮，引進外國食品來補足已是一項不爭的事實。因此本研究將以食物里程之三個構面進口量、運輸距離及運輸模式統計，進行後續二氧化碳排放量之計算，找出相互影響關聯性。
根據本研究之調查結果可以發現，台灣在24項進口食品當中最主要仰賴進口之食品為HS10穀類。除此之外，為了要瞭解三個構面相互影響之關聯性，本研究選定台灣2015年之進口食品統計結果來做後續探討。發現在海運、鐵路及公路運輸模式下，二氧化碳排放量最高之運輸模式為公路運輸，佔總碳排放量之64％，而海運則佔總碳排放量之35%，顯示公路運輸為台灣進口食品主要的二氧化碳排放來源。
除此之外，為了探討運輸距離對於二氧化碳排放量之影響程度，本研究選擇2015年之水產品進口量作為研究對象，由於水產品在過去的統計中，進口量呈現上升之趨勢，顯示國人對於水產品之需求程度增加，因此本研究採用此商品作為研究對象，想瞭解運輸距離是否會對碳排放量存在影響。
根據實證結果顯示台灣在水產品之進口量統計中HS0303冷凍全魚為最主要仰賴進口之商品，總進口量為77,065公噸，其食物里程及碳排放量也因進口量之統計結果可以看出亦為最高值，分別為865,771,418公噸-公里及25,904公噸。此外，透過食物里程之分析計算，本研究亦瞭解到水產品在不同運輸模式下其所產生之食物里程及碳排放量。透過食物里程之計算，本研究根據統計結果可以看出，水產品高達86%仰賴海運運輸，14%為公路運輸，僅接近1%為鐵路運輸。除了整體進口商品之運輸模式外，本研究也統計了單一進口水產品之食物里程。根據統計可以得知各項商品在不同運輸模式下之食物里程。
在各項運輸模式之二氧化碳排放量計算上，本研究根據統計結果可以看出水產品在公路運輸上之碳排放量為最高，佔總碳排放量之67％。其次為海運運輸，佔總碳排放量之32%。然而在鐵路運輸模式中僅佔1%之碳排放量，顯示如何有效管理並提升公路運輸之效率為當務之急。
除此之外，本研究亦統計各項進口水產品之主要進口地區可以發現，台灣的水產品來源供應地主要來自亞洲地區。本研究亦將進口距離加以分段區隔，根據統計結果可以看出台灣水產品主要進口距離落在6000到8000公里處，其進口量佔總進口量之40.2%。根據統計結果可以看出台灣隨著進口距離越遠，進口量越為攀升，其所造成的食物里程亦隨之增加，顯示運輸距離對於食物里程存在正向之效果影響。
本研究在最後統計了台灣在各項水產品之總運輸距離及平均進口量之二氧化碳排放量，根據統計結果可以得知HS0302冰鮮魚片/全魚為最遠運輸距離之商品，由於進口國家之遠近不同，使得運輸距離較遠的國家確實會對碳排放量產生顯著之影響，此結果符合食物里程之概念。

The purpose of this study is to analyze the food miles of 24 types of import food products in Taiwan between 2001-2015 of the total 15 years time span. However, researchers often aimed at industrial pollution after the industrial revolution as major research subjects in previous studies on carbon emission, and there is limited studies on carbon emission on transportation of imported food products. Taiwan is consisted of particularly fertile lands but a limited land area, thus Taiwan is still faced with food security issues even with its seemingly abundant resources. In addition, with increasing numbers of aging farmers, abandoned farmland and land use transformation under government policies, land use in agriculture are even more limited and food product imports has become an essential action. This paper will investigate the three dimensions of food miles, including the amount of import, the distance of transportation, and the transportation methods to calculate carbon emission and find the relationships between factors.
Based on the survey results of this study, grain (HS 10) is the item most dependent on import among the 24 import food product types in Taiwan. In addition, this paper aim to conduct further research on the statistical results of the import food products in 2015 of Taiwan to investigate the relationship between the three dimensions. This study found among ocean freight transportation, railway transportation, and road transportation, road transportation has the highest carbon emission among these transportation methods, which accounts for 64% of the total carbon emission, whereas ocean freight transportation accounts for 35%. This indicated that road transportation is the major source of carbon emission of import foods transportation method in Taiwan.
In addition, this study aimed at the imports of fishery products of 2015 as the research subject to investigate the effect of distance of transportation on carbon emission. Previous studies has shown a growing tendency of the imports of fishery products, and this indicated the growing demand of fishery products in Taiwan. In order to investigate the effect of distance of transportation on carbon emission, the researcher has made the study of the the fishery industry as its research subject.
Based on the findings of the fishery products imports in Taiwan, Frozen fish (HS 0303) is the item most dependent of imported fishery products, with the number of total import 77,065T, and its food miles and carbon emission are also considered the highest from the amount of imports, 865,771,418T-Km and 25,904 T respectively.
In addition, this paper has also investigated different food miles and carbon emission of fishery products under different transportation method through the calculation of food miles. Through the calculation of food miles, this paper found that 86% of fishery products were imported through ocean freight transportation, 14%through road transportation, and merely approximate 1% through railway transportation. In addition to the entire transportation methods of import goods, this study also calculated the single food miles of each fishery product, thus food miles of different products through different transportation methods can be calculated.
The calculation of different transportation methods in this study found that according to statistical results to deliver fishery products through road transportation has the highest carbon emission, which accounts for 67% of the total carbon emission. However, railway transportation method only accounts for 1% of carbon emission. This calls for immediate measures on the effective management and improvement of road transportation.
In addition, this study also found the major export regions of all type of fishery products supply in Taiwan are located in Asia. This study also divide the import regions by distance. Based on the results, the major locations of import fishery products in Taiwan is located at the distance between 6000-8000KM, which accounts for 40.2% of the total fishery imports. The result indicated that the import amount increases with greater distance to Taiwan, and this also creates increased food miles. This finding shows transportation distance has positive impact on food miles.
The researcher calculated the total transportation distance and the average carbon emission of import goods of all types of fishery products in the last section of the paper. The results show frozen fish fillet/ fish meat (HS 0302) is the fishery product with the greatest transportation distance. Due to difference of distance to each country, countries with greater distance clearly has significant effect on carbon emission. This result corresponds with the concept of food miles.

摘 要 I
Abstract III
目 錄 V
圖 次 VI
表 次 IX
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機 4
第三節 研究方法 16
第四節 研究目的 16
第五節 研究流程 17
第二章 文獻回顧 18
第三章 資料來源說明與研究方法 20
第一節 名詞定義說明 20
第二節 研究架構 23
第三節 資料來源說明 24
第四節 研究方法 26
第四章 實證結果 32
第一節 實證結果 32
第二節 食物里程剖析 130
第五章 結論與建議 155
第一節 結論 155
第二節 建議 158
第三節 研究限制 159
參考文獻 160
附錄一、HS 2 Code商品之國際商品統一分類 163
附錄二、HS 4 Code食品商品之國際商品統一分類 169

中文文獻
曾彥蓉. (2015). 臺灣肉類進口食物里程分析. (碩士), 國立臺灣海洋大學, 基隆市.
台灣加入WTO十周年
<http://taiwan10years.wtocenter.org.tw/gains.asp>.
台灣食品安全事件列表, 維基百科
<https://zh.wikipedia.org/wiki/%E5%8F%B0%E7%81%A3%E9%A3%9F%E5%93%81%E5%AE%89%E5%85%A8%E4%BA%8B%E4%BB%B6%E5%88%97%E8%A1%A8>.
主婦聯盟環境保護基金會第185期會訊
<http://forum.yam.org.tw/women/digest/backinfo/recreation/pu/pu18502.htm>.

英文文獻
Andersson, K., Ohlsson, T., & Olsson, P. (1998). Screening life cycle assessment (LCA) of tomato ketchup: a case study. Journal of cleaner production, 6(3), 277-288.
Campbell, C. J., & Laherrère, J. H. (1998). The end of cheap oil. Scientific American, 278(3), 60-65.
Carlsson-Kanyama, A. (1998). Climate change and dietary choices—how can emissions of greenhouse gases from food consumption be reduced? <http://seminar.mannlib.cornell.edu/topics/food_security/resources/FS01.pdf>. Food Policy, 23(3/4), 277-293.
Coley, D., Howard, M., & Winter, M. (2009). Local food, food miles and carbon emissions: A comparison of farm shop and mass distribution approaches. Food Policy, 34, 150-155.
Corbett, J. J., & Koehler, H. W. (2003). Updated emissions from ocean shipping. Journal of Geophysical Research: Atmospheres, 108(D20).
Dauvergne, P. (2008). The shadows of consumption. Consequences for the Global Environment.
Davis, S., & Diegel, S. (2007). Transportation Energy Data Book, Edition 26; Oak Ridge National Laboratory ORNL-6978: Oak Ridge, TN, 2007.
FAOSTAT. (2010). <http://faostat.fao.org/default.aspx>.
Garnett, T. (2011). Where are the best opportunities for reducing greenhouse gas emissions in the food system (including the food chain)? Food Policy, 36, S23-S32.
Huang, H., von Lampe, M., & van Tongeren, F. (2011). Climate change and trade in agriculture. Food Policy, 36, S9-S13.
Jackson, T. (2004). Negotiating Sustainable Consumption: A review of the consumption debate and its policy implications. Energy & Environment, 15(6), 1027-1051.
Kissinger, M. (2012). International trade related food miles–The case of Canada. Food Policy, 37(2), 171-178.
Kissinger, M., & Rees, W. E. (2009). Footprints on the prairies: Degradation and sustainability of Canadian agricultural land in a globalizing world. Ecological Economics, 68(8), 2309-2315.
MEA. (2005). Millennium Ecosystem Assessment Synthesis Report. .
Nashawi, I. S., Malallah, A., & Al-Bisharah, M. (2010). Forecasting world crude oil production using multicyclic Hubbert model. Energy & Fuels, 24(3), 1788-1800.
Peters, G. P. (2008). From production-based to consumption-based national emission inventories. Ecological Economics, 65(1), 13-23.
Pretty, J. N., Ball, A. S., Lang, T., & Morison, J. I. L. (2005). Farm costs and food miles: An assessment of the full cost of the UK weekly food basket. Food Policy, 30, 1-19.
Princen, T. (1999). Consumption and environment: some conceptual issues. Ecological Economics, 31(3), 347-363.
Roy, P., Nei, D., Okadome, H., Nakamura, N., Orikasa, T., & Shiina, T. (2008). Life cycle inventory analysis of fresh tomato distribution systems in Japan considering the quality aspect. Journal of Food Engineering, 86(2), 225-233.
Saunders, C., Barber, A., & Taylor, G. (2006). Food Miles–Comparative Energy/Emissions Performance of New Zealand’s Agriculture Industry. . .
Sim, S., Barry, M., Clift, R., & Cowell, S. J. (2007). The relative importance of transport in determining an appropriate sustainability strategy for food sourcing. The International Journal of Life Cycle Assessment, 12(6), 422.
WEBER, C. L., & MATTHEWS, H. S. (2008). Food-Miles and the Relative Climate Impacts of Food Choices in the United States. Environ. Sci. Technol, 42, 3508-3513.
The World Bank, Trade（% of GDP）
<http://data.worldbank.org/indicator/NE.TRD.GNFS.ZS>.
The World Bank, Food imports（% of merchandise imports）
<http://data.worldbank.org/indicator/TM.VAL.FOOD.ZS.UN>.