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Microalgae biodiesel production in China: A preliminary economic analysis

handle: 2440/121757
Abstract Despite strong governmental support, microalgae biodiesel has failed to report rapid growth in China. Thus, it is imperative to conduct an economic analysis on microalgae biodiesel so that useful inputs could be provided for policy making. The analysis is based on a model with a 100-ha production facility. In addition, a sensitivity analysis is performed in this study to determine critical factors contributing to the economic feasibility of microalgae biodiesel. Furthermore, a learning curve is employed to predict the production cost from 2019 to 2022. The production cost is estimated as USD 2.29/kg, which is significantly higher than that of commercial diesel. The findings highlight that biodiesel projects lack economic feasibility and the main barriers are microalgae productivity, annual operating days and product benefits. According to the learning curve prediction, these issues cannot be alleviated within a short period, particularly considering the limitations associated with the current policies. The study concludes with policy implications e.g. a policy system to facilitate the development of microalgae biodiesel.
- University of Adelaide Australia
- Huazhong University of Science and Technology China (People's Republic of)
- Hubei University of Technology China (People's Republic of)
- Hubei University of Technology China (People's Republic of)
- University of Adelaide Australia
Biodiesel policy, microalgae productivity, microalgae biodiesel, learning curve, economic feasibility, 339
Biodiesel policy, microalgae productivity, microalgae biodiesel, learning curve, economic feasibility, 339
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).113 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
