RESUMEN
The project portfolio of carbon capture system and power to gas (CP project) is considered to be a key technology combination for achieving carbon emission reduction and recycling in the future. However, due to a dearth of associated engineering practices and business activities, there is no widely used business model for the large-scale deployment of the CP technology portfolio. The design and evaluation of the business model is crucial for projects with a long industrial chain and complex relationships between stakeholders, such as CP projects. Based on carbon chain and energy flow, this paper analyzes the cooperation mode and profitability among stakeholders in the CP industry chain, selects three suitable business models, and establishes nonlinear optimization models under the three business models. By analyzing the key factors (e.g. carbon price) that can promote investment and have policy influence, the tipping points of the key factors and the cost of support policies are given. Results show that the vertical integration model has the greatest demonstration deployment potential since it has the best performance in terms of cooperation and profitability realization. However, required crucial factors in the CP projects vary from business models, policy makers need to take appropriate supporting measures prudently.
RESUMEN
International trade has important impacts on a country's energy consumption. This paper first uses the time-series (2005-2015) extended input-output database to study China's embodied energy and intensity in both normal and processing exports. Structural decomposition analysis (SDA) is then applied to analyze the driving forces behind the embodiment changes. The empirical results show that China's energy embodied in both normal and processing exports first increased in 2005-2008, dropped in 2009 due to the global financial crisis, and then rose again after 2009, and finally dropped in 2014-2015. The embodied energy in trade as a percentage of total energy consumption in China was relatively stable before and after the global financial crisis, at around 28% over the 2005-2008 period, and 22% over the 2009-2015 period. The contribution of the aggregate embodied intensity (AEI) of exports to China's aggregate energy intensity dropped from 30% in 2005 to 21% in 2015. Among China's trading partners, the United States, Japan and Korea together accounted for around half of China's embodied energy and AEI in exports in 2005, but their shares dropped to only one third in 2015. Energy efficiency improvement played the key role in reducing the embodied energy and intensity in China's exports. Similar analysis can be applied to other regions and indicators.
RESUMEN
This study develops an input-output linear programming (IO-LP) model to identify a cost-effective strategy to reduce the economy-wide carbon dioxide (CO2) emissions in China from 2020 to 2050 through a shift in the electricity generation mix. In particular, the fixed capital formation of electricity technologies (FCFE) is endogenized so that the capital-related CO2 emissions of various generation technologies can be captured in the model. The modeling results show that low-carbon electricity, e.g., hydro, nuclear, wind, and solar, is associated with lower operation-related CO2 emissions but higher capital-related CO2 emissions compared to coal-fired electricity. A scenario analysis further reveals that a shift in the electricity generation mix could reduce the accumulated economy-wide CO2 emissions in China by 20% compared to the business-as-usual (BAU) level and could help peak China's CO2 emissions by 2030. The emission reduction is mainly due to a drop in operation-related CO2 emissions of electricity, contributing to a decrease in accumulated economy-wide emissions by 21.4%. The infrastructure expansion of electricity, on the other hand, causes a rise in the accumulated emissions by 1.4%. The proposed model serves as an effective tool to identify the optimal technology choice in the electricity system with the consideration of both direct and indirect CO2 emissions in the economy.