Energy use and CO2 emissions of the Moroccan transport sector

In this paper, optimized models based on two different machine learning (ML) methods were developed to forecast the transport energy consumption (TEC) and carbon dioxide (CO2) emissions in Morocco by 2030. More precisely, artificial neural networks (ANN) and support vector regression (SVR) were used for modelling non-linear TEC and CO2 emissions data. This study uses data from 1990 to 2020 and employs various independent parameters, including population, gross domestic product, urbanization rate, evolution of the number of vehicles, and the number of electric vehicle introductions. Four statistical metrics are derived to assess the effectiveness of the ML algorithms used. The forecasts for 2030 were based on six scenarios, including three scenarios for the growth of gross domestic product (GDP) and two scenarios for the evolution of electric cars’ introduction into Moroccan vehicle fleet. The ANN model outputs showed that a decrease in TEC and CO2 emissions is expected until 2030. However, the SVR model predicts outputs values close to those in 2020. The study's results also indicate that: i) TEC and transport CO2 emissions are positively impacted by economic growth in Morocco and ii) electric vehicles will be essential components enabling substantial reductions in overall CO2 emissions in future transport systems

Energy prices and energy intensity in China : a structural decomposition analysis and econometric study

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2005.Includes bibliographical references (p. 113-115).Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., physical energy consumption per unit of Gross Domestic Product (GDP), has declined dramatically, by about 70%, in spite of increases in energy consumption. Is this just a coincidence? Or does a systematic relationship exist between energy prices and energy intensity? In this study, I examine whether and how China's energy price changes affect its energy intensity trend during 1980-2002 at a macro level. I conduct the research using two complementary economic models (the input-output-based structural decomposition analysis and econometric regression models) and a decomposition method of own-price elasticity of energy intensity. Findings include a negative own-price elasticity of energy intensity, a price-inducement effect on energy-efficiency improvement, and a greater sensitivity, in terms of the reaction of energy intensity towards changes in energy prices, of the industry sector, compared to the overall economy. Analysts can use these results as a starting point for China's energy use and carbon emission forecasts, which they traditionally conduct in China without accounting for energy intensity and energy prices.(cont.) In addition, policy implications may initiate new thinking about energy policies that are needed to conserve China's energy resources and reduce carbon emissions.by Xiaoyu Shi.M.C.P