Sustainable Bioenergy Use and Climate Change in China : a Spatial Agent Model for the Case of Jiangsu Province

In the context of climate change and energy crisis, bioenergy, which accounts for the largest share of renewable energy in the global energy mix, has drawn considerable attention from an increasing number of countries. While its potential to curb greenhouse gas emissions and to provide energy has been widely acknowledged, concerns over the side effects of bioenergy are still being voiced. In particular, its perceived threats on food security and local ecosystems have largely impeded its development, which is best exemplified by the role that bioenergy takes in the EU's growth strategy of "Europe 2020". This fact provided the motivation for the reflections presented in this thesis on how to realize a sustainable development of the bioenergy industry. To answer this question, we have selected a coastal province in eastern China as the region in which to conduct our study. China is simultaneously the most populated country and the largest GHGs emitter in the world. It can, therefore, be expected that the entire international community can learn some valuable lessons from the practical experience that China has gathered in the field of bioenergy. Following a brief outline of the background information on our research in the initial two chapters, Chapter 3 frames the structure of the bioenergy industry and clarifies the role of each actor. Depending on their relative importance in the industry, these actors can be assigned to one of the two categories of stakeholders: central or peripheral. Based on the local practice, we present the construction process of the bioenergy industry in China from both the supply side and the demand side. This descriptive analysis is intended to help the reader form a general understanding of the bioenergy industry in China, on which our subsequent quantitative analysis is based. Chapter 4 focuses on farmers as one of the central stakeholders that are located at the upstream of the bioenergy supply chain. We develop a biomass feedstock provision model compiled with GAMS to simulate the responsive behaviors of farmers – the agents in our spatial-agent dynamic model – to the challenges arising from emerging energy crops. Using this model, we delineate land use changes after the insertion of the bioenergy industry. We further fix the sources of the promising biomass feedstock, with the straws of conventional crops accounting for 85% of feedstock and energy crops for the remaining 15%. In view of the geographical characteristics of the