Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method

Examining the effects of urbanization and industrialization on carbon dioxide emission: Evidence from China's provincial regions

“…Most of them confirm that the main influencing factors are energy intensity, energy mix, gross domestic product structure, and GDP itself [3,4,10,22,30,32,33]. Wang et al [19] decomposed the carbon emissions into population, GDP per capita, energy consumption intensity and energy consumption structure and concluded that the total theoretical decrease of CO 2 emission from 1957 to 2000 can be attributed to fossil fuel mix and renewable energy penetration.…”

“…In this study, LMDI (Logarithmic Mean Divisia index) has been chosen in the energy consumption and carbon dioxide emissions analysis [3,5,10,22,32,33], due to its robust theoretical foundation and the ability to enable the decomposition of plenty of influence factors. In order to explore the mechanisms of urbanization influence on regional CO 2 emissions in depth, this research addresses seven sectors for a decomposition analysis: agriculture, production, construction, transportation, business, urban households, and rural households.…”

“…However, the studies on the urbanization effect on energy-related CO 2 emission in Chinese provinces are incomplete and fragmented. This fragmentation likely stems from the fact that researchers are interested in a broad range of specific questions in particular research contexts and have tackled a variety of sector-specific [6,9,17,18,25,27] and region-specific research [17,18,21,24,32,33], for example, the carbon emission trading in Guangdong Province [20], the energy efficiency in Shandong Province [7], and the industrial restructuring in Jiangsu Province [29]. The fragmented research landscape raises up many fundamental questions for scholars of this field.…”

Energy efficiency in South Africa: A decomposition exercise

“…Decomposition techniques have become a useful tool for energy modelling and analysis over the last two decades with special focus on energy consumption and efficiency [4,11,14,18,19,20,21,22,23,24] as well as carbon emissions [25,26,27,28,29,30] or both energy intensity and emission intensity [31]. For South Africa, Inglesi-Lotz and Blignaut (2011) have used decomposition techniques to examine the factors that affected electricity consumption in the economy-wide and sectoral level.…”

Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China

“…These studies considered a relatively small number (four or fewer) of types of energy, thereby decreasing the accuracy of the accounting. In addition, more detailed information about each sector's carbon emissions and the proportion of total emissions accounted for by each sector that could guide management planning was often not provided [33]; at an urban level, most of the literature focuses on a province/city [36][37][38][39], discussing the mechanism of main factors affecting regional CO 2 emissions, and coming up with alternative policies [40][41][42].…”