Essays in climate change mitigation strategies
thesisposted on 2022-03-28, 09:39 authored by Yaoyao Ji
Global emissions from agricultural and forestry sectors account for roughly 22 per cent of the total annual greenhouse gas emissions, which is equal to the emissions from fossil fuel consumption in the global transportation sector. Reducing emissions from these two sectors presents an opportunity to effectively mitigate carbon emissions with relatively low mitigation costs. In Asia, countries such as China and Indonesia present significant potential to mitigate carbon emissions within these two sectors. Using conservation tillage (CT) and reducing emissions from deforestation and forest degradation (REDD) programmes as examples of potential options, the objective of this thesis is to enhance our understanding of the challenges associated with mitigating global greenhouse gas emissions in the agricultural and forestry sectors of Asia. In the following paragraphs, I provide a brief outline of my thesis. First, I investigate the socio-economic factors that promote or hinder CT adoption in agriculture using a detailed household level survey of the Huangling County in China. A bivariate probit model with sample selection is applied to analyse farmers’ decision making associated with adopting CT. Results indicate that variables such as government subsidy programmes and household wealth levels play a key role in the continued adoption of CT. Poorer farmers and those whose neighbours have abandoned CT are more likely to give up on CT. Geographical challenges and fragmented land holdings lead to only partial adoption, even under government subsidies. Next, the effects of social and economic factors on the time to CT adoption are analysed using survival analysis. To explore further the influence of training programmes and subsidy schemes provided by the Government, villages covered by the survey are divided into two groups based on the level of support received from the Government. The analysis reveals that families who have a higher farm income and those who have attended the training programmes tend to adopt CT earlier. In addition, those who have already adopted CT help with speeding up the adoption process of their neighbours. In terms of reducing greenhouse gas emissions through REDD programmes in the Indonesian forestry sector, illegal logging is considered as a critical challenge and a threat to the success of REDD projects. A simultaneous-equation econometric model is used to estimate factors causing and promoting illegal logging in Indonesia. The effects from Indonesia’s main timber trading partners, Japan and China, and policies aimed at curbing illegal logging in these countries are also considered as key explanatory factors. The results reveal that corruption and decentralisation in Indonesia have a significant influence on promoting illegal logging supply. Additionally, excess demand in the Japanese construction and furniture industries is a key driver of illegal logging demand. Whereas, in China, an increase in the gross domestic product (GDP) has not necessarily fuelled a proportional increase in demand for illegal logging due to efficiency in wood usage and an increased domestic wood supply resulting from promotion of afforestation in the last two decades. Law enforcement or policies aimed at curbing illegal harvesting in Indonesia are also effective tools. Finally, the potential contributions of the REDD programmes to the global carbon mitigation objective are investigated using an integrated assessment model. It is found that the REDD programmes not only contribute positively towards carbon emissions mitigation through reducing deforestation, they also increase optimal abatement efforts through other conventional abatement. The risk of forest loss, however, makes the REDD option less attractive. The insights derived from the optimisation model suggest that, while investing in REDD, countries with lower risk but higher opportunity costs of REDD programmes should be preferred over countries with higher risk but lower opportunity costs.