A medium and long-term carbon emission forecasting method for provincial power grid
The development of low-carbon electric power industry is a key way to deal with the greenhouse effect and lower the PM2.5. When integrated into power grid, renewable energy can efficiently cut down the output of the thermal power and reduce the carbon emission of the grid significantly. However, it lacks a more comprehensive and systematic approach to forecast a medium and long-term carbon emission for provincial power grid. Thus, in this paper, life cycle assessment (LCA) method and gray prediction model are used to forecast the medium and long-term carbon emission. In addition, the carbon intensity of provincial power grid is evaluated based on historical data such as electricity consumption, gross domestic product (GDP), carbon emission coefficient. Taking Jiangxi power grid as the example, the results indicate that the proposed method is of good accuracy and the integration of renewable energy can effectively reduce the carbon emission and the carbon intensity.
Analysis on the paths to China's goal of carbon intensity by 2020
Based on the IPAT identity and using the economic, social and statistical data, this article selects STIRPAT model to create China's driving factors model of carbon emission. With the method of scenario analysis through the model, we predict under the base scenario, the energy saving scenario, the economic structure optimization scenario, the economic structure optimization scenario and the multiple policies scenario and obtain the predicted values of carbon emission and carbon intensity by 2020 under the five scenarios. The values show that, compared with the base scenario, the policies under the four other scenarios can all extend the decline of the carbon intensity by 2020. But no matter which policy is implemented alone cannot achieve the goal of cutting carbon intensity by 40% to 45% by 2020, only the simultaneous implementation of three policies combined can achieve this goal. To this end, China must develop and implement new energy conservation policy, economic and energy structure optimization policy, new energy and renewable energy policy.
Decomposing international polarization of per capita CO2 emissions
The aim of this paper is to analyze the international polarization of per capita CO2 emissions with exogenous groups based on the Z-K measure (Zhang and Kanbur, 2001), whose main differential advantage lies on its factor-decomposability. In particular, we propose to use the factor decomposition based on Kaya (1989) by applying the methodology suggested by Duro and Padilla (2006). The main empirical results derived can be summarized as follows. First, the international polarization of emissions has significantly decreased over time during the period 1971-2006, when regional sets of nations based on the IEA structure are used; secondly, this decrease can be almost exclusively based on the reduction of the average dissimilarities among sets of countries and not due to a within-group cohesion process. Lastly, this reduction can be mainly attributed to the role of the affluence factor, and to a lesser extent, to the energy intensities. Thus, and given the values achieved for the different components, it seems that further reductions in the international polarization will continue be based on the economic convergence among groups.