The study of effects on municipal waste recovery in Taiwan

• Main Authors: Su-Chuan Yu, 余素絹
• Other Authors: Hung-Yee Shu
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/24632680485467847270

碩士 === 弘光科技大學 === 環境工程研究所 === 101 === Consumption of energy and resources as well as production of municipal solid waste both are instant threat of human living as world population keeping growth. Therefore, treatment and reduction of municipal solid waste become most important issue for governments around the world. Recycling policy makes the waste reduction and resources reuse efficiencies increase speedily. However, waste recycling rate meets a barrel after years of promotion. Thus, to find the major influence factors of waste recycling rate is the way to fix the problem and keep the waste recycling rate moving swiftly. In this study, municipal solid waste treatment and recycling data base was collected and statistics software was used for correlation and multi-regression analysis. The major influence factors and regression models were obtained to modify the waste recycling policy. Based on the administration of waste management policy, the average Taiwan waste recycling rate increased from 7.0 to 48.9% during years from 1999 to 2010. The waste recycling rate including food waste and furniture reached 60.5 and 61.4% for Taipei and New Taipei city in year 2011 after utilizing pay-as-you-throw policy. From the results, year, population density and location significantly correlate to the waste recycling rate. The regression model developed from these three factors can predict waste recycling rate fairly good with R2=0.702. Using annual growth rate of 5.6% and 4.1% for Taipei and New Taipei city, respectively, can predict that the waste recycling rate of Taichung city will be from 59.33 to 66.86% in year 2016. The major factors influence the electricity recovered from waste incinerator are designed heat value and total shot-down time. Again, regression model developed from these two factors can predict electricity recovered from waste incinerator fairly good with R2=0.719. To conclude this research, recycling policy is a very important measurement for municipal waste management. Through recognizing major factors which influence the waste recycling rate and building regression model can help promoting waste recycling efficiency in right direction. The experiences of pay-as-you-throw policy in Taipei and New Taipei city can be transferred to other cities.