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.
Carbon Dioxide Emission Scenarios for the USA
A model of carbon dioxide emissions of the USA is presented. The model consists of population, income per capita, economic structure, final and primary energy intensity per sector, primary fuel mix, and emission coefficients. The model is simple enough to be calibrated to observations since 1850. The model is used to project emissions until 2100. Best guess carbon dioxide emissions are in the middle of the IPCC SRES scenarios, but incomes and energy intensities are on the high side, while carbon intensities are on the low side. The confidence interval suggests that the SRES scenarios do not span the range of not-implausible futures. Although the model can be calibrated to reflect structural changes in the economy, it cannot anticipate such changes. The data poorly constrain crucial scenario elements, particularly energy prices. This suggests that the range of future emissions is wider still.