10 million tonnes for 2020. This study shows that a number of non-grain feedstocks such as cassava, sweet sorghum and sweet potato grown in low productive arable lands or marginal lands have enough potential to meet ethanol targets in 2020. The costs of ethanol production from these feedstocks vary from 4,887 Yuan/tonne to 6,802 Yuan/tonne. Which are comparable to existing wholesale prices of ethanol in China. However, should these lands be used for biofuels is not an easy question to answer as these lands could be utilized to produce grains to meet china’s self-sufficiency target on grain supply. On other hand, cellulosic feedstocks, such as agricultural and forest residues have a much higher technical potential of supplying ethanol, but their costs are much higher as compared to those non-grain crops mentioned above. In the case of biodiesel, the target set for 2020 is 2 million tonnes. Alternative feedstocks, such as waste oil and oil fruit bearing non-edible shrubs (e.g., jatropha), each would have more technical capacity to meet the targets. Again, production costs are the major barriers as costs of biodiesel produced from these feedstocks would be higher compared to diesel price in China. Various policy measures, particularly, financial incentives, such as direct subsidies to non-grain sugar and starch based ethanol and cellulosic ethanol, building up recycling system to reduce the feedstock cost of waste oil-based biodiesel, and increasing subsidies to oil-bearing shrubs would be needed to overcome the costs barriers to biofuels in China.

This study also reviews several studies that projects production of biofuels for China. Due to differences on underlying assumptions and structures of models used, the projections vary widely across the studies. Nevertheless, most studies predict that China could not meet its biofuel targets in the business as usual scenarios. However, with the introduction of additional policy interventions, the country would meet those targets.

# **Acknowledgements**

The authors acknowledge the financial support of the Knowledge for Change (KCP) Trust Fund of the World Bank. The authors would like to thank Scott Paap, Carter Brandon, Ximing Peng and two anonymous reviewers for their constructive comments. The views expressed are of authors and do not represent funding organizations.

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