Impacts of energy consumption, energy structure, and treatment technology on SO2 emissions: A multi-scale LMDI decomposition analysis in China

2016 ◽  
Vol 184 ◽  
pp. 714-726 ◽  
Author(s):  
Xue Yang ◽  
Shaojian Wang ◽  
Wenzhong Zhang ◽  
Jiaming Li ◽  
Yafeng Zou
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Energy Structure ◽  
So2 Emissions ◽  
Treatment Technology ◽  
Multi Scale ◽  
Consumption Energy

scholarly journals Peak of SO2 Emissions Embodied in International Trade: Patterns, Drivers and Implications

2021 ◽  
Vol 13 (23) ◽  
pp. 13351
Author(s):  
Bin Wang ◽  
Dechun Huang ◽  
Chuanhao Fan ◽  
Zhencheng Xing
Keyword(s):  
International Trade ◽  
Financial Crisis ◽  
Global Financial Crisis ◽  
Developing Economies ◽  
Decomposition Analysis ◽  
Energy Structure ◽  
So2 Emissions ◽  
Trade Patterns ◽  
Developed Economies ◽  
Production And Consumption

International trade links countries consuming goods and services to those where products and related SO2 pollution are produced, thereby affecting national mitigation responsibilities. This study combined accounting and decomposition techniques to investigate the patterns and drivers of SO2 emissions embodied in international trade from 1995 to 2015 and quantified the contribution of each country or region on the production and consumption sides. The global embodied emissions increased at an accelerated rate before the global financial crisis and peaked at 51.3 Mt in 2008, followed by a fluctuating decline from 2008 to 2015. Spatially, the transfers of SO2 emissions tended to flow from developed countries to less developed ones, but the trend has weakened after the financial crisis. Our decomposition analysis suggests that the energy and production system transitions and the slowdown in international trade jointly accounted for the peak and decline in emissions. Our contribution analysis indicates that developing economies have contributed to decreased emissions due to their recent efforts in production technology upgrading, energy efficiency improvement and energy structure optimization. The influence of developed economies on emissions decreased due to their reduced dependency on imports. Targeted policy methods are provided from the production and consumption perspectives for developing and developed economies, respectively.

scholarly journals Dynamic Decomposition Analysis and Forecasting of Energy Consumption in Shanxi Province Based on VAR and GM (1, 1) Models

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Herui Cui ◽  
Ruirui Wu ◽  
Tian Zhao
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Coal Industry ◽  
Shanxi Province ◽  
Response Analysis ◽  
Energy Structure ◽  
Low Carbon ◽  
Stirpat Model ◽  
Urbanization Level ◽  
Green Development

Environmental issues caused by energy consumption have attracted increasing attention recently. Shanxi Province, a typical energy-dominated region in China, has long-term dependency on coal industry generating extensive economic growth, which is detrimental to green development. Distinguished from previous studies ignoring driving factors of energy consumption, this paper establishes a vector autoregression (VAR) model to dynamically identify the drivers of energy consumption based on STIRPAT model in Shanxi Province from 1990 to 2015. It can be obtained from the impulse response analysis that a positive shock in population, GDP, and urbanization level, respectively, positively affect energy consumption, and a positive change in technology negatively affects energy consumption in the long run. The variance decomposition results indicate that fluctuation in energy consumption explained by the innovation of the urbanization level accounts for 23.18%, which plays a prevailing role in increasing energy consumption. Meanwhile, the forecasting results of GM (1,1) model manifest that energy consumption in Shanxi Province generally has an increasing trend from 2016 to 2025. Consequently, Shanxi can achieve green development through optimizing energy structure, promoting the transformation of resource-based cities, and promoting low-carbon technological innovation. This paper can be available for other resource-based regions analogous to Shanxi.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3864
Author(s):  
Qiucheng Li ◽  
Jiang Hu ◽  
Bolin Yu
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Decomposition Analysis ◽  
Theil Index ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Index Method ◽  
Inequality Measures ◽  
Influencing Mechanism ◽  
Per Capita

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.

Study on the Relationship between Energy Consumption, Carbon Emission and Economic Growth in China

2013 ◽  
Vol 869-870 ◽  
pp. 746-749
Author(s):  
Tian Tian Jin ◽  
Jin Suo Zhang
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Structure ◽  
Ardl Model ◽  
Relationship Of ◽  
The Relationship ◽  
Reducing Energy

Abstract. Based on ARDL model, this paper discussed the relationship of energy consumption, carbon emission and economic growth.The results indicated that the key to reduce carbon emissions lies in reducing energy consumption, optimizing energy structure.

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