Carbon emissions and electricity generation modeling in Saudi Arabia

被引：0
作者：
Reema Ghazi Alajmi
机构：
[1] King Saud University,Economics Department, College of Applied Studies and Community Service
来源：
Environmental Science and Pollution Research | 2022年 / 29卷
关键词：
Carbon emissions; Structural time series model (STSM); Underlying energy demand trend (UEDT); Logarithmic mean Divisia index (LMDI) approach; Electricity generation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Fossil fuel electricity generation in Saudi Arabia increased greatly from 1980 to 2017. This paper aims to quantify the electricity generation effect on the environmental quality of Saudi Arabia and explore the role of energy-efficient technological innovation. A structural time series model (STSM) to estimate long-run elasticities and logarithmic mean Divisia index (LMDI) is employed. The results showed that variables (GDP, electricity generation, and population) have a significant effect on carbon dioxide (CO2) emissions. Also, the underlying energy demand trend (UEDT) showed an upward slope for the entire period, which suggests that over the study time there is no improvement in energy efficiency. In decomposing the factors for carbon emissions growth in Saudi Arabia, the findings of applying additive LMDI analysis showed a 1377.56 million tonne (MT) increase in CO2 emissions from the three factors between 1980 and 2017 in the country. The results of additive decomposition showed that the primary factor that drives the carbon emissions growth in Saudi Arabia was the structure effect. Saudi Arabian policymakers could make more informed decisions regarding electricity generation by focusing on increasing energy efficiency and demanding strict environmental regulations to contribute to sustainable economic growth.
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页码：23169 / 23179
页数：10
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