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This paper endeavors to analyze and provide fresh global insights from the asymmetric nexus between the recent outbreak of COVID-19, crude oil prices, and atmospheric CO 2 emissions. The analysis employs a unique Morlet's wavelet method. More precisely, this paper implements comprehensive wavelet coherence analysis tools, including continuous wavelet coherence, partial wavelet coherence, and multiple wavelet coherence to the daily dataset spanning from December 31, 2019 to May 31, 2020. From the frequency perspective, this paper finds significant wavelet coherence and vigorous lead and lag connections. This analysis ascertains significant movement in variables over frequency and time domain. These results demonstrate strong but varying connotations between studied variables. The results also indicate that COVID-19 impacts crude oil prices and the most contributor to the reduction in CO 2 emissions during the pandemic period. This study offers practical and policy implications and endorsements for individuals, environmental experts, and investors.

The issue of urbanization has gained much importance over the last few decades due to its significant influence on economic growth and environmental quality, especially in developing countries. The non-linearity puzzle has been a long-debated issue, and prior studies provide mixed evidence. This study addresses the issue of urbanization using the measure of urban agglomeration and investigates the non-linear relation between urbanization and CO2 emissions at the regional level. The South Asian region represents approximately one-fourth of the world population and its urbanization needs to be addressed properly. This paper uses the annual data over the period of 1974–2014 for four South Asian countries, namely, Pakistan, India, Bangladesh, and Nepal. The panel cointegration tests establish the long-run relation between urbanization, urban agglomeration, economic growth, trade openness, energy consumption, financial development, and CO2 emissions. The fully modified ordinary least squares (FMOLS) model further confirms the existence of Environmental Kuznets Curve (EKC) in South Asia. Moreover, urbanization has an inverted U-shaped relation with CO2 emissions, while urban agglomeration has a U-shaped nexus with CO2 emissions for overall sample. The bidirectional causal relationship has also been confirmed between urbanization and CO2 emissions, between urban agglomeration and CO2 emissions, between financial development and CO2 emissions both in the long-run and short-run. On the other hand, unidirectional causality runs from economic growth, trade openness, and energy consumption to CO2 emissions in the long-run. The rising trend of urban agglomeration in metropolitan cities in South Asia is adversely affecting the environment. The current study has implications for policymakers and respective governments to adhere to more stringent urban planning.

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