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Measuring CO2 emission linkages with the hypothetical extraction method (HEM).

Authors :
Ali, Yousaf
Source :
Ecological Indicators. Jul2015, Vol. 54, p171-183. 13p.
Publication Year :
2015

Abstract

The issue of CO 2 emission has become a major issue causing greater concern to the global economies due to its potential environmental effects and impact on climate change. In order to address this issue and mitigate its harmful effects on the environment, it is imperative to reduce CO 2 emission drastically and fairly quickly. In this paper we have been focusing on alternative linkage methodologies for measuring CO 2 emission, which entails linkages among the productive sectors in an economy. Methods, dealing with inter-sectoral carbon linkage measures can be summarized into two main categories, i.e. (a) the concept of traditional backward and forward linkages and (b) hypothetical extraction method (HEM). The (HEM) method is used to hypothetically extract a sector from an economic system and examine the influence of this extraction on other sectors in an economy. In this study we will evolve the environmentally extended input–output model to measure the CO 2 emission linkages among the productive sectors in Italy using data obtained in 2011. Using the HEM method, the backward linkage emission and forward linkage emission are calculated to characterize the behavior of these sectors. The results obtained from these measures will enable us to formulate hypothesis about the direction and strength of the relationship between various linkages and will also indicate which key CO 2 emitter sector measures are most similar and which are most dissimilar. According to the size of the various linkage measures, all sectors of the economy can be grouped into four categories. These measures allow us to examine and identify those sectors, which deserve more consideration in formulating mitigation policies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1470160X
Volume :
54
Database :
Academic Search Index
Journal :
Ecological Indicators
Publication Type :
Academic Journal
Accession number :
102852611
Full Text :
https://doi.org/10.1016/j.ecolind.2015.02.021