Climate Change Integrated Assessment Models And Their Applications

As the largest primary energy consumer and carbon emitter in the world, China is facing great pressure to reduce its carbon dioxide(CO2) emissions. From the international perspective, China‘s pathway of carbon emissions has crucial influence on the achievement of 2℃ target, as its CO2 emissions have grown exponentially with the rapid development of economy. Domestically speaking, China is facing the increasing difficulty of carbon reduction, short supply of domestic fossil energy supply and severe environmental pollutions. China has proposed the strategy of ?One Belt and One Road‘ and established the Asian Infrastructure Investment Bank, which creates new challenges for reducing energy consumption and carbon emissions, as well as opportunities for international cooperation on energy and addressing climate change. It is not wise for China to repeat the development path of developed countries under which greenhouse gases are emitted without restrictions in the period of industrialization. Instead, it needs to explore a win-win road of sustainable development for developing economy and tackling climate change in accordance with China‘s national conditions.China has scientific accumulation in natural science research of climate change, but is still relatively weak in the assessment of impacts on socio-economic system. The academic frontiers of climate change modeling are mainly occupied by developed countries. Most developed countries have their own climate change integrated assessment models(IAMs) which have played an important role in making national climate polices and coping with international climate change negotiations. China needs to develop climate change IAMs from the perspective of national interest to provide theoretical and data support for addressing climate change and improve the discourse power in the field of climate change.Towards the national strategic demands of tackling climate change and international frontiers of climate policy modeling research, this thesis focused on the climate change IAMs and their applications. Applying operational research, econometrics, game theory, input-output analysis, multi-criteria decision making and bibliometrics, this thesis developed climate change IAMs at the global, national and local levels to simulate the relationships between economy, energy, environment and climate change. Some innovative results were acheived as follows,(1) The carbon trading scheme(cap and trade) was introduced into the RICE model to assess and compare the impacts on socio-economic system of four different climate policy equity principles, namely, ability to pay, egalitarian, grandfathering, and historical responsibility. The results showed that global cooperation could promote the process of mitigating climate change. If individual nations undertake policies which are in their national self-interests, the global CO2 emission will be 2.29 times as many as that of cooperative scenarios. From the global perspective, the social damages of climate change under the grandfathering are the smallest, but developing countries get more damages. For China, the preferred principles are ability to pay, historical responsibility, egalitarian, and grandfathering, successively. China‘s advantages of ?historical responsibility‘ and ?egalitarian‘ are decreasing gradually with the rapid growth of carbon emissions.(2) The Integrated Model of Economy and Climate(IMEC) was developed based on the input-output model to assess the economy, energy, environment and climate change. Under the objective of maximizing social welfare, this thesis explored low-carbon pathways for China‘s development, comprehensively considering factors like economic growth, industrial structure, energy structure, and energy efficiency. In order to realize the target of CO2 emissions peaking in 2030, China needs to control the annual gross domestic product(GDP) growth rate under 5% during 2026-2030, and under 4.5% after 2030. China‘s CO2 emissions can peak earliest in 2026 under the constraints that the average annual growth rate of GDP is larger than 6% during 2010–2030. Compared with the scenario of carbon emissions peaking in 2030, peaking in advance can reduce CO2 emissions by 1.18–5.40%, but cause 1.41–12.53% of GDP losses.(3) The Climate Change Mitigation Index(CCMI) was developed with 15 objective indicators, which were divided into four categories, namely, carbon emissions, efficiency, non-fossil energy, and climate policy. The CCMI was used to assess and interpret China‘s provincial efforts on climate change mitigation. The middle Yangtze River area and southern coastal area perform better than other areas in mitigating climate change, while the average performance of the northwest area in China is the worst. Climate change mitigation performance has a negative linear correlation with energy self-sufficiency ratio, so regional resource endowments had better be paid much more attention in terms of mitigating climate change. In addition, climate change mitigation performance does not have a significant linear correlation with social development level, which means that provinces at different stages of development are all capable of performing well in mitigating climate change.(4) An optimization model was developed based on the input-output model to assess the potential impacts of industrial structure adjustment on the energy consumption and CO2 emissions, which was applied to a case study of Beijing, China. This thesis compared the impacts of five decision objectives, namely, maximization of GDP, minimization of energy intensity, minimization of energy consumption, minimization of carbon intensity, and minimization of CO2 emissions, on socio-economic system of five objectives. Industrial structure adjustment has the potential to save energy by 39.42% and reduce CO2 emissions by 46.06% in Beijing from 2010 to 2020. Energy intensity is possible to decrease without negatively affecting economic growth by reasonable industrial structure adjustment. Moreover, compared with ?intensity targets‘, ?total amount targets‘ are more effective on the energy conservation and carbon reduction, but have much greater negative effects on economic growth. Therefore, it needs to be balanced between ?total amount targets‘ and ?intensity targets‘.