Energy Intensity In China Research Articles

The relationship between energy consumption structure, economic structure and energy intensity in China

This paper investigates the long-run equilibrium relationships, temporal dynamic relationships and causal relationships between energy consumption structure, economic structure and energy intensity in China. Time series variables over the periods from 1980 to 2006 are employed in empirical tests. Cointegration tests suggest that these three variables tend to move together in the long-run. In addition, Granger causality tests indicate that there is a unidirectional causality running from energy intensity to economic structure but not vice versa. Impulse response analysis provides reasonable evidences that one shock of the three variables will cause the periods of destabilized that followed. However, the impact of the energy consumption structure shock on energy intensity and the impact of the economic structure shock on energy consumption structure seem to be rather marginal. The findings have significant implications from the point of view of energy conservation and economic development. In order to decrease energy intensity, Chinese government must continue to reduce the proportion of coal in energy consumption, increase the utilization efficiency of coal and promote the upgrade of economic structure. Furthermore, a full analysis of factors that may relate to energy intensity (e.g. energy consumption structure, economic structure) should be conducted before making energy policies.

Analysis of Influences between the Energy Structure Change and Energy Intensity in China

In this article, based on the data of the energy statistics from 1980 to 2004, we analyze the relationship between the primary energy structures, technique, management, and the energy use per unit of GDP based on the path analysis approach and present the degree of the direct, indirect, and the overall influences of the primary energy structures on the energy use per unit of GDP. The results show that the technical change and management level play a decisive role in the energy use per unit of GDP, and the ratio of oil consumption was the major limiting factor to energy use per unit of GDP. We then found the model of the energy use per unit of GDP and the structures of the primary energy consumption, eliminated the multicollinearity in the model with the path analysis result, and finally, analyzed the influence of the primary energy structure on the energy conservation.

Taking out 1 billion tons of CO 2: The magic of China's 11th Five-Year Plan?

China's 11th Five-Year Plan (FYP) sets an ambitious target for energy-efficiency improvement: energy intensity of the country's gross domestic product (GDP) should be reduced by 20% from 2005 to 2010 [National Development and Reform Commission (NDRC), 2006. Overview of the 11th Five Year Plan for National Economic and Social Development. NDRC, Beijing]. This is the first time that a quantitative and binding target has been set for energy efficiency, and signals a major shift in China's strategic thinking about its long-term economic and energy development. The 20% energy-intensity target also translates into an annual reduction of over 1.5 billion tons of CO 2 by 2010, making the Chinese effort one of the most significant carbon mitigation efforts in the world today. While it is still too early to tell whether China will achieve this target, this paper attempts to understand the trend in energy intensity in China and to explore a variety of options toward meeting the 20% target using a detailed end-use energy model.

What is driving China’s decline in energy intensity?

While energy intensity in China has fallen almost continuously since the onset of economic reform in the late 1970s, beginning in 1996 the data show a striking decline in China’s absolute level of energy use. Most of this decline can be accounted for by falling coal consumption in the industrial sector. In order to investigate this energy puzzle, this paper employs a unique set of panel data for approximately 2500 of China’s most energy intensive large and medium-sized industrial enterprises during 1997–1999. Rising relative energy prices, research and development expenditures, and ownership reform in the enterprise sector, as well as shifts in China’s industrial structure, emerge as the principal drivers of China’s declining energy intensity and use.

Global carbon dioxide emissions scenarios: Sensitivity to social and technological factors in three regions

Carbon dioxide emissions from 1990 to 2100 AD are decomposed into the product of four factors: population size, affluence (measured here as GDP per capita), energy intensity (energy use per unit GDP) and carbon intensity (carbon dioxide emissions per unit energy). These emissions factors are further subdivided into three regions: more developed countries (MDCs), China, and the remaining less developed countries (LDCs). Departures from a baseline scenario (based on IPCC, 1992a — the so-called ‘business-as-usual’ scenario) are calculated for a variety of alternative assumptions concerning the four emissions factors in the three regions. Although the IPCC scenario is called a ‘non-intervention’ scenario, it is shown, for example, that large decreases in energy intensity in China or carbon intensity in MDCs are built into the ‘business as usual’ case — and such large changes vary considerably from region to region. We show what CO2 emissions would look like if each of these four emissions factors projected in the baseline case somehow remained constant at 1990 levels. Certain factors like energy intensity improvements and long-term population growth in LDCs. or GDP growth and carbon intensity improvements in MDCs, are shown to have a big contribution to cumulative global emissions to 2100 AD, and consequently, changes in these projected factors will lead to significant deviations from baseline emissions. None of the scenarios examined in this analysis seems to indicate that any one global factor is clearly dominant, but cultural, economic, and political costs or opportunities of altering each factor may differ greatly from country to country.