Estimation of Chinese CO2 Emission Based on A Discrete Fractional Accumulation Grey Model

摘要

Global warming, which is primarily caused by CO2 and other greenhouse gases, has seriously threatened the world economy and human security. Accurate estimation of CO2 emission are important for taking effective action to control the amount of emissions. However, rapidly changing conditions, such as China's fast economic growth, make old data of little relevance, and often there is only a limited amount of more recent data from which to construct a forecasting model. The present study uses a grey model to overcome these problems. This study presents a new discrete fractional accumulation GM(1,1) model; we refer to the model as FAGM(1,1,D). A particle swarm optimization algorithm is designed to optimize the value of the fractional accumulation and to minimize the mean absolute percentage error (MAPE) of the model. Other model parameters are obtained via least squares estimation. Using data that span the time period from 1999 until 2012, this study employs the four grey models to estimate future Chinese CO2 emission from 2013 until 2015. The results indicate that the annual amount of Chinese CO2 emission will exceed 12 or possibly even 13 billion tons in 2015.