Dynamic Impacts of Economic Growth, Energy Use, Urbanization, and Trade Openness on Carbon Emissions in the United Arab Emirates

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO2 emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO2 emissions, as a 1% increase in each raises CO2 by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-06-24
DOI
https://doi.org/10.3390/su17135823
Citations
1
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
3.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic Impacts of Economic Growth, Energy Use, Urbanization, and Trade Openness on Carbon Emissions in the United Arab Emirates

Hatem Ali, Hatem Ahmed Adela, Wadeema BinHamoodah Aldhaheri
1 citations
Sustainability
Energy, Environment, Economic Growth
3.13
article

Dynamic Impacts of Economic Growth, Energy Use, Urbanization, and Trade Openness on Carbon Emissions in the United Arab Emirates

Hatem Ali, Hatem Ahmed Adela, Wadeema BinHamoodah Aldhaheri
article en
1 citations

Abstract

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO2 emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO2 emissions, as a 1% increase in each raises CO2 by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions.

SustainabilityVol. 17(13)
Abu Dhabi Health Services (AE), Sadat Academy for Management Sciences (EG), Zayed University (AE)
Openalex Percentile: Top 8%
Energy, Environment, Economic Growth
3.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.