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Identification and analysis of driving factors of CO2 emissions from economic growth in Pakistan

pmid: 31077046
This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO2 emissions over the period 1990-2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved.
- Beijing Institute of Technology China (People's Republic of)
- Peking University China (People's Republic of)
- Beijing Institute of Technology China (People's Republic of)
- Zagreb School of Economics and Management Croatia
- Zagreb School of Economics and Management Croatia
Conservation of Energy Resources, Agriculture, Carbon Dioxide, Models, Theoretical, Coal, Industry, Pakistan, Economic Development
Conservation of Energy Resources, Agriculture, Carbon Dioxide, Models, Theoretical, Coal, Industry, Pakistan, Economic Development
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).20 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
