Browsing by Author "Wang, Jue"

Forest carbon offset projects have been growing vigorously in China in the last ten years. It is necessary to form an overall picture of the projects, to analyze the quality of their development processes, and to shed light on the development of upcoming projects. In order to evaluate their development process, a framework of assessment was built up and applied in practical project assessment. In this thesis, firstly, the situation of the global carbon markets and Chinese forest carbon offset projects was introduced. Especially, different international and domestic carbon accounting and other carbon related standards were presented and compared. Secondly, the previous studies about the assessment of sustainable development impacts of the forestry carbon projects were reviewed; the approaches and indicators were compared and summarized. Then, in combination with checklists and multi-criteria approaches, a new assessment framework was established, consisting of a set of indicators and a four-level scoring system. Finally, 16 Chinese forestry projects which have applied different carbon standards were evaluated with this assessment framework. Their performances were compared and analyzed, the characteristics of standards were also compared. According to the results of the assessment, the successfully registered Clean Development Mechanism (CDM) projects gained higher scores, suggesting their development processes were of higher quality. The projects applying Climate, Community, and Biodiversity Standards (CCBS) in pair with another carbon accounting standard also tended to get higher scores, indicating the positive effect of CCBS on the consideration of sustainable co-benefits. The international standards are stricter than domestic standards, which can be seen from the comprehensiveness and meticulousness of the Project Design Documents (PDDs). The result of the assessment corresponds to the previous understanding about the projects and standards, which supports the validity of the assessment framework.