Rebound Effect of Energy Intensity Changes on Energy Consumption

Author(s):  
Taoyuan Wei
2019 ◽  
Vol 144 ◽  
pp. 233-239 ◽  
Author(s):  
Taoyuan Wei ◽  
Jinjin Zhou ◽  
Hongxia Zhang

2001 ◽  
Vol 40 (2) ◽  
pp. 135-147 ◽  
Author(s):  
Shaista Alam ◽  
Mohammad Sabihuddin Butt

Complete decomposition model has been employed in the present study to decompose the changes in energy consumption and energy intensity in Pakistan during 1960 to 1998. A general decomposition model raises a problem due to residual term. In some models the residual term is omitted, which causes a large estimation error, while in some models the residual term is regarded as an interaction that might create a puzzle for the analysis. A complete decomposition model is used here to solve this problem.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4199
Author(s):  
Jinjin Zhou ◽  
Zenglin Ma ◽  
Taoyuan Wei ◽  
Chang Li

Based on threshold regression models, this paper analyzes the effect of economic growth on energy intensity by using panel data from 21 developed countries from 1996 to 2015. Results show that a 1% increase in GDP per capita can lead to a 0.62–0.78% reduction in energy intensity, implying economic growth can significantly reduce energy intensity. The extent of the reduction in energy intensity varies depending on the economic development stages represented by key influencing factors including energy mix in consumption, urbanization, industrial structure, and technological progress. Specifically, the reduction in energy intensity due to economic growth can be enhanced with relatively more renewable energy consumption and more urban population until a threshold point, where the enhancement disappears. On the other hand, the extent of the energy intensity reduction due to economic growth can be weakened with relatively more tertiary industry activities and more research and development (R&D) investment in an economy until a threshold point, where the weakening cannot continue. However, compared to the early stages represented by the low ends of renewable energy consumption, urban population, tertiary industry activities, and R&D investment, the later stages represented by the high ends of these key factors after a threshold show the weakened effect of economic growth on the decline of energy intensity. Hence, when an economy is well-developed, policy makers are advised to put fewer expectations on the role of economic growth to reduce energy intensity, while pursuing relatively cleaner energy, greater urbanization, more tertiary industry activities, and advanced technologies.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3775 ◽  
Author(s):  
Khaled Bawaneh ◽  
Farnaz Ghazi Nezami ◽  
Md. Rasheduzzaman ◽  
Brad Deken

Healthcare facilities in the United States account for 4.8% of the total area in the commercial sector and are responsible for 10.3% of total energy consumption in this sector. The number of healthcare facilities increased by 22% since 2003, leading to a 21% rise in energy consumption and an 8% reduction in energy intensity per unit of area (544.8 kWh/m2). This study provides an analytical overview of the end-use energy consumption data in healthcare systems for hospitals in the United States. The energy intensity of the U.S. hospitals ranges from 640.7 kWh/m2 in Zone 5 (very hot) to 781.1 kWh/m2 in Zone 1 (very cold), with an average of 738.5 kWh/m2. This is approximately 2.6 times higher than that of other commercial buildings. High energy intensity in the healthcare facilities, particularly in hospitals, along with energy costs and associated environmental concerns make energy analysis crucial for this type of facility. The proposed analysis shows that U.S. healthcare facilities have higher energy intensity than those of most other countries, especially the European ones. This necessitates the adoption of more energy-efficient approaches to the infrastructure and the management of healthcare facilities in the United States.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stuti Haldar ◽  
Gautam Sharma

Purpose The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India. Design/methodology/approach The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use. Findings Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India. Research limitations/implications The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces. Originality/value There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).


Author(s):  
Chibueze, E. Nnaji ◽  
Nnaji Moses ◽  
Jonathan N. Chimah ◽  
Monica C. Maduekwe

<div><p><em>This paper analysed the status of energy intensity of economic sectors (agriculture, industry, commercial, residential) in MINT (Mexico, Indonesia, Nigeria, Turkey) countries and its implications for sustainable development. We utilised descriptive statistics as well as the Logarithmic Mean Divisia Index (LMDI) decomposition analysis to examine energy and efficiency trends, from 1980-2013, in MINT countries. Empirical results indicate inefficient energy use in the residential and industrial sectors of Nigeria and Indonesia. The analysis  also indicates that income/output growth (activity effect) contributed to an increase in sectoral energy consumption of MINT countries. It also revealed that while structural effects contributed to a reduction in energy consumption in virtually all the sectors in Turkey and Mexico, it contributed to an increase in energy consumption of the residential, industrial and commercial sectors of Indonesia and Nigeria in virtually all the periods. These results suggest that a policy framework that emphasizes the utilization of energy efficient technologies especially electricity infrastructural development aimed at energy service availability, accessibility and affordability will help to trigger desirable economic development and ensure rapid sustainable development of MINT economies.</em></p></div>


2020 ◽  
pp. 0958305X2092159
Author(s):  
Xiongfeng Pan ◽  
Mengna Li ◽  
Chenxi Pu ◽  
Haitao Xu

This study establishes a multi-sector dynamic computable general equilibrium framework that integrates energy intensity module to explore the reverse feedback effect of energy intensity control on industry structure. The results indicate that (1) the tightening effect of energy intensity constrains on the Industrial sector is most significant, followed by the Tertiary Industry, with the least impact on Agriculture; (2) when there is no technological progress in the departments, the change of industrial structure is mainly reflected in the sharp decline in the proportion of Industry and the significant increase in the proportion of Tertiary Industry. When technological progress exists in high energy-consumption departments, the tightening effect of energy intensity constraints on the industrial sector will be reduced; when there is technological progress in all departments, the industrial structure will have a smaller change, and the technology progress can alleviate the tightening effect of the energy intensity target on various sectors; (3) under the constraint of energy intensity, the high energy-consuming industry shifts to the Equipment Manufacturing with low energy-consumption and high-added value. The increasing proportion of Tertiary Industry mainly comes from two industries including Wholesale, Retail, Hoteling and Catering, and Transportation, Storage, and Post.


Sign in / Sign up

Export Citation Format

Share Document