Abstract: As earth climate warms rapidly, the problem of carbon emissions has become a universal concern, the study of the factors involving carbon emissions will be the basis in finding the way to the reduction. LMDI established a framework to study the change in emission intensity and its mechanism. Using the extend Kaya Identity to decompose the driving factors into energy structure, energy ...

China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China,...

In a comprehensive LMDI-STIRPAT-ARDL framework, this research investigates the residential electricity consumption (REC)-income nexus in Morocco for period 1990 to 2018. The logarithmic mean Divisia index (LMDI) results show that economic activity and intensity are leading drivers of Morocco’s REC, followed by population structure. And then, LMDI analysis was combined with stochastic impacts re...

6 7 Decomposition analyses are helpful to policymakers and analysts who aim to reduce carbon 8 dioxide (CO2) emissions from car travel. A large number of decomposition methods have been 9 proposed till date. However, there is still no consensus regarding the best decomposition 10 method because each method has certain advantages and disadvantages. Which method is 11 valid for the decomposition ...

Analysis of the change overall energy efficiency performance an system is a fundamental work for energy-saving policymaking. However, previous studies seldom focus on stages from useful to final service, while most attention are paid source energy. In this paper, we develop high-resolution Societal Exergy and Logarithmic Mean Divisia Index (SEA-LMDI) method analysis changes driving factors aggr...