Assessing the sustainability of bioethanol crops of Taiwan
Date Issued
2014
Date
2014
Author(s)
Su, Mei-Hui
Abstract
An analysis of internationally-proposed biofuel sustainability criteria indicates that certain criteria including energy input, greenhouse gas (GHG) emissions, pesticide and fertilizer usage and waste reduction, can be assessed using life cycle analysis (LCA) tools, while water footprints (WFs) analysis can be used to describe the environmental impact of water, pesticide and fertilizer usage, along with wastewater treatment. Cost-benefit analysis can provide effective comparisons of the economics and productivity of different energy crops and biofuels. Therefore, to investigate the suitability of cultivating bio-ethanol en-ergy crops in Taiwan, this research conducts a broad investigation of first and second generation bioethanol feedstocks, including sugar cane, corn, sweet potato, sorghum and rice straw. Multi-year field survey data were analyzed us-ing LCA, water footprint and cost-benefit analysis methods to explore the po-tential for bioethanol energy crops as a source for sustainable energy, and their impact on the environment, economy and water resources.
LCA analysis results show that, of all energy crops, sugar cane provides the best performance in terms of energy balance, GHG emissions and costs. Given current government subsidies of NT$45,000 per hectare of energy crops per crop period, and a net profit between NT$50,000 to NT$65,000 per crop peri-od, the market price of the resulting bioethanol ranges from NT$27.72~33.00 per liter, making it competitive with imports which are sold for NT$37.2/liter. Given current technology for the production of cellulosic ethanol in Taiwan, the bioethanol conversion rate of rice straw is only 200 liters per ton, thus un-derperforming 1st generation bioethanol in terms of energy balance, GHG emissions and production costs, results which conflict with conclusions in previous studies.
WFs analysis results indicate that sweet potatoes have the smallest WFs, fol-lowed by sugar cane and sweet sorghum, and corn has the largest WFs of en-ergy crops, though the WFs of rice is much larger, which results are consistent with the average global water footprints for these crops. The WFgreen accounts for more than 50% of the overall WF for all energy crops except of corn, indi-cating that the cultivation processes of these energy crops relies more on rain-water, thus, fulfilling low input selection criteria. The WFs of rice is about 13 times larger than that of sweet potatoes and 8.8-10.4 times that of sugar cane, indicating the relative resource inefficiency of cultivating rice as a food crop. WFs for Taiwan-grown sugar cane, corn, and sweet potatoes compare favour-ably to those in the top 3 producing countries (Brazil, United States and Chi-na), as the WFs for Taiwan-cultivated corn is only 52-62% of that for corn planted in the United States. A comparison of energy crop WFs in temperate, subtropical, and tropical climate zones indicates that sugar cane cultivation is relatively more efficient in tropical and subtropical regions, due to its heavy reliance on rainwater, while corn and sweet sorghum perform better in tem-perate and subtropical regions.
An assessment of energy crop sustainability shows that energy balance, GHG reduction benefits and production costs can be used as indicators for the selection of potential energy crops, and that the cultivation of energy crops would not only satisfy environmental sustainability requirements, but would also spur economic development. Overall LCA, WFs and cost-benefit analysis results show that sugar cane is the most suitable energy crop for cultivation in Taiwan. Furthermore, water footprint analysis shows that the water footprint of sugar cane is significantly lower than that of rice, making it suitable for cul-tivation on fallow land and in water-deficient areas.
Subjects
生命週期評估法
水足跡
生質酒精
纖維酒精
能源平衡
二氧化碳排放
成本分析
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-103-D00621101-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):cee30e5b44a2333eb8bda0d4ca48360e
