為減少溫室氣體排放，台灣與其他國家相同開始制定減量目標以期減緩氣候變遷惡化。在調查台灣溫室氣體排放源中發現，台灣住商部門的溫室氣體排放呈現不斷上升的趨勢。探究其排放源，主要是來自於電器用品所消耗大量電力所致;台灣位處北半球之熱帶地區，每年的四至八月氣溫居高不下，人們為了降低氣溫以及獲得舒適的濕度，空調之使用於此期間便顯得十分頻繁。因此，若能著手於空調系統之節能，便可有效控制住商部門之溫室氣體排放。
本研究匯集不同資料來源所需之數據，建立一個模型用以評估台灣空調之生命週期(包括製造、使用以及廢棄三階段)所排放之溫室氣體。利用Logistic function、 Weibull distribution、population balance model (PBM)與每年所銷售之空調的壽命分布，來模擬未來四十年，每年空調販售的數量、使用中之總量以及廢棄量。計算空調之數量再結合製造新空調、使用中空調之能源消耗與冷媒洩漏(使用階段以及廢棄空調時回收冷媒的階段)進一步做計算以了解空調所造成的溫室氣體排放。
空調之能源可藉由以下三項策略來達到節約效果，包括空調之(1)使用管理(溫度設定與使用行為)，(2)效率技術之改善以及(3)汰舊換新。研究之結果顯示，管理使用者行為較能有效減少溫室氣體之排放。若單獨探討此策略，發現此策略顯著減少溫室氣體排放量，經由模式模擬發現2030年可回到2005年之排放量。而其他兩個策略，對於更進一步減少溫室氣體亦有潛在的影響。以提升空調技術之情境來看，由於主要之溫室氣體排放來源來自於老舊之空調，若依照現階段替換之模式與速率來評估，其減少之貢獻量效果有限。而若是與促進汰舊換新的政策結合，科技進步可更有效減少溫室氣體排放。
本研究證明，此模型之建立所提供之不同情境可用以分析科技與政策。此外，本模型除了可提供政府作為施行政策之參考之外，亦可幫助空調使用者了解，其所使用行為對於溫室氣體排放減量是如何重要。

Taiwan has been paying efforts synchronized with the rest of the global society to reduce greenhouse gases (GHGs) emission to mitigate climate change. Despite its efforts, the GHGs emission from services and residential sector maintains its increasing trend. Most of its GHGs emission induced by activities in these sectors occur in the form of Scope 2 emissions, namely energy consumption of electrical appliances. In Taiwan, located in tropical region in the northern hemisphere, air conditioner (AC) is particularly important during April to October for lowering temperature and humidity. Therefore, energy saving of AC systems is considered one of the most direct and effective strategy to reduce GHGs emission in the services and residential sector.
In this study, compiling the necessary information form scattered data sources, a model was tailored for Taiwan to estimate the GHGs emission associated with AC product life cycle, including manufacturing, use and disposal stages. Logistic function, Weibull distribution and Population balances model (PBM) are used to simulate for future 40 years, the number of AC in use, discarded, and sold by assuming a lifetime distribution of ACs sold in a year. Using these information, the GHGs emission from manufacturing a new AC, energy consumption of AC in use and refrigerant leakage (at use, at recycling when ACs are discarded) are calculated.
Using the model, three energy saving strategies related to ACs, including 1) managing the user behavior (i.e., temperature setting, use intensity), 2) improving the efficiency of heat pump technology and 3) replacing the old machine with newer ones, are investigated. It was found that management of user behaviors is the most effective in GHG emission reduction. This strategy alone can bring the emission level back to the 2005 level by 2030. To further reduce the emission, the other two strategies are potentially effective. Contribution of technology improvement scenarios are limited under current rate and patterns of replacement, because most of GHG emission are from old ACs. Combined with replacement acceleration policy, technology improvement can reduce GHG emission effectively.
As demonstrated in this study, the constructed model allows technology and policy analyses using scenario approach. Using this model, policies can be designed based on quantitative insights. It can also make the information more transparent, and assist AC users to understand how their use behavior is important in reducing GHG emissions.

1. Chen Chung-Hsien, Hou Wain-Sun, Taiwan's Sustainable Energy Policy Framework Energy Saving and Carbon Reduction Action Plans, Bureau of Energy, Ministy of Economic Affairs, R.O.C. (Taiwan), 2009.
2. Bureau of Energy, Ministy of Economic Affairs, R.O.C. (Taiwan), 我國燃料燃燒CO2排放統計與分析, 2011.
3. 台灣綠色生產力基金會, 家庭節約能源手冊, 經濟部能源局, 2009.
4. 台灣綠色生產力基金會, 空調技術手冊案例, 經濟部能源局, 2008.
5. 余培煜, 替代冷媒的技術發展介紹, Industrial Tecnolody Research Institute, 2012.
6. Kim Man-Hoe, Pettersen Jostein, and Bullard C.W., Fundamental process and system design issues in CO2 vapor compression system. Progress in Energy and Combustion Science, 2004. 30: p. 119-174.
7. 馬利艷, 全球空調產品市場趨勢, Industrial Tecnolody Research Institute, 2008.
8. Bureau of Energy, Ministy of Economic Affairs, R.O.C. (Taiwan); Available from: http://www.moeaboe.gov.tw/.
9. 黃達海、傅孟臺、蘇捐儀、廖文華、高淑芳、陳永棟, 老舊冷氣機能源效率衰退試驗研究, Industrial Tecnolody Research Institute.
10. 蕭慧娟, 台灣溫室氣體減量政策與行動, 2010.
11. 台灣綜合研究院, 永續能源政策綱領下我國長期能源政策, 2009.
12. Environment Protect Administration Executive Yuan, R.O.C. (Taiwan). Available from: http://www.epa.gov.tw/.
13. Key World Energy Statistics, International Energy Agency, 2012.
14. 高紹惠、高淑芳、葉旭輝, 我國「容許耗用能源耗用基準」及「能源效率分級標示制度能源報導」, 經濟部能源局, 2011. p. 8.
15. Yokota Kazuhiko, Matsuno Yasunari, Yamashita Masaru, Adachi Yoshihiro, Integration of Life Cycle Assessment and Population Balance Model fro Assessing Environmental Impacts of Product Population in a Social Scale. Int J LCA, 2003. 8(3): p. 129-136.
16. 洪怡芳、陳志恆、張添晉, 廢電子電器暨廢資訊物品衍生特殊廢棄物管理與處理技術, 桃園縣大學校院產業環保技術服務團.
17. 彭佳玲, 2010 Household Appliances Availability Survey,台灣電力股份有限公司, 2010.
18. 薛佑佳, 未來50 年廢棄家用電器之鐵資源回收再製流程情境模擬, 行政院國家科學委員會補助大專學生參與專題研究計畫研究成果報告, 2008.
19. 許菁君, 台灣冷氣機產業技術創新與能源政策, 中央大學產業經濟研究所, 2004.
20. 中央氣象局. Available from: http://www.cwb.gov.tw/V7/.
21. 經濟部能源局, 101年度電力排放係數, 經濟部能源局.
22. 劉家宏、劉中哲、高國棟、林振源, The study on estimating at the consumption and the emissions of refrigerant in Taiwan, 冷凍與空調, 2005. p. 76-85.
23. Hamby, D.M., A review of techniques for parameter sensitivity of environmental models. Environmental Monitoring and Assessment, 1994. 32: p. 135-154.
24. Chen Jhen-Wei, Exploring greenhouse gas emission reduction potential of microalgae-derived bio-fuel production process, in Department of environmental engineering, National Cheng Kung Unerversity, 2009.
25. Iman Ronald L., Helton Jon C., An investigation of uncertainty and sensitivity analysis techniques for computer models. Risk analysis, 1988. 8(1): p. 71-90.
26. Bureau of Energy, Ministy of Economic Affairs, R.O.C. (Taiwan), Industrial Production Statistics, Available from: https://2k3dmz2.moea.gov.tw/gwWeb/Industry/gwIndProd.aspx.
27. 田崎智宏、小口正宏、龜屋隆志、浦野紘平, 使用済み耐久消費財の発生台数の予測方法. 廃棄物学会論文誌, 2001. 12: p. 49-58.