Abstract
Due to urbanization’s substantial impact on economic development and environmental quality, particularly in emerging nations, the subject has attracted major attention in recent years. Urbanization increases infrastructure, transportation, and high energy consumption demand, leading to increased environmental degradation. Therefore, this study examines how urbanization has affected environmental degradation in Pakistan using yearly data from 1970 to 2020. A non-linear autoregressive distributed lag (NARDL) model is applied to study the asymmetric impact of urbanization on ecological footprint per capita. The results show that urbanization is asymmetrically associated with environmental degradation. Positive changes in urbanization led to increased environmental degradation, while negative changes in urbanization led to a decline in environmental degradation in Pakistan. Foreign direct investment and industrial production are positive and significant factors of environmental degradation, while trade openness and money supply are negatively linked with environmental degradation in Pakistan. Economic growth shows a positive link, while economic growth square shows a negative link with environmental degradation. These findings also confirm the environmental Kuznets curve (EKC) hypothesis in Pakistan. It is suggested that the urbanization threshold should be analyzed to determine where environmental degradation tends to decline, and less polluting technology and renewable energy resources should be encouraged to reduce environmental degradation in Pakistan.
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Data availability
The Global Footprint Network and World Development Indicators databases have data used in the study’s analysis.
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Muhammad Arif: writing the original manuscript, conceptualization, data collection, and formal analysis.
Abid Rashid Gill: supervised and reviewed the paper.
Minhaj Ali: formal analysis, methodology, and writing review and editing.
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Arif, M., Gill, A.R. & Ali, M. Analyzing the non-linear association between urbanization and ecological footprint: an empirical analysis. Environ Sci Pollut Res 30, 109063–109076 (2023). https://doi.org/10.1007/s11356-023-30012-x
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DOI: https://doi.org/10.1007/s11356-023-30012-x