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1.
J Environ Manage ; 356: 120690, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38547827

RESUMO

In the aftermath of the 28th Conference of the Parties (CoP) climate summit in the UAE, the majority of developing countries encounter challenges in attaining their objectives of carbon neutrality for a sustainable economy. The association of economic factors such as economic growth, governance structures, forest area, renewable energy consumption, technological innovation, and urbanization with environmental elements (carbon footprint) is vital for sustainable economic development and environmental management strategies. Therefore, this research reveals this association in five selected high-emitting countries spanning from 1990 to 2022. This research utilizes the Environmental Kuznets Curve (EKC) framework to investigate the interrelationship between these variables. To do so, this study employs the cross-sectional autoregressive distributed lags (CS-ARDL) statistical technique to determine the short- and long-term impacts of the variables under investigation on carbon footprint. In contrast, the mean group (MG) and common correlated effect mean group (CCEMG) have been applied for robustness. The findings revealed that GDP, urbanization, and forest area have positive associations with carbon footprints, whereas GDP square, renewable energy consumption, technological innovation, and governance effectiveness have inverse relationships with carbon footprints. These findings provide all stakeholders with valuable policy recommendations and management advice for accelerating the transition of renewable energy to low-carbon and green growth.


Assuntos
Dióxido de Carbono , Carbono , Estudos Transversais , Energia Renovável , Desenvolvimento Sustentável , Desenvolvimento Econômico
2.
Environ Sci Pollut Res Int ; 28(22): 28624-28639, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-33547610

RESUMO

This paper examines the nexus between the Covid-19 confirmed cases, deaths, meteorological factors, including an air pollutant among the world's top 10 infected countries, from 1 February 2020 through 30 June 2020, using advanced econometric techniques to address heterogeneity across the nations. The findings of the study suggest that there exists a strong cross-sectional dependence between Covid-19 cases, deaths, and all the meteorological factors for the countries under study. The findings also reveal that a long-term relationship exists between all the meteorological factors. There exists a bi-directional causality running between the Covid-19 cases and all the meteorological factors. With Covid-19 death cases as the dependent variable, there exists bi-directional causality running between the Covid-19 death cases and Covid-19 confirmed cases, air pressure, humidity, and temperature. Temperature and air pressure exhibit a statistically significant and negative impact on the Covid-19 confirmed cases. Air pollutant PM2.5 also exhibits a significant but positive impact on the Covid-19 confirmed cases. Temperature indicates a statistically significant and negative impact on the Covid-19 death cases. At the same time, Covid-19 confirmed cases and air pollutant PM2.5 exhibit a statistically significant and positive impact on the Covid-19 death cases across the ten countries under study. Hence, it is possible to postulate that cool and dry weather conditions with lower temperatures may promote indoor activities and human gatherings (assembling), leading to virus transmission. This study contributes both practically and theoretically to the concerned field of pandemic management. Our results assist in taking appropriate measures in implementing intersectoral policies and actions as necessary in a timely and efficient manner. Causal relations of Meteorological factors and Covid-19 (2 models used in the study).


Assuntos
Poluentes Atmosféricos , COVID-19 , Poluentes Atmosféricos/análise , Estudos Transversais , Humanos , Conceitos Meteorológicos , Pandemias , SARS-CoV-2
3.
Heliyon ; 7(1): e05965, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33490698

RESUMO

This study investigates the impact of various economic, social and environmental indicators on economic growth in South Asian countries. Using the data throughout 1990-2017, a panel data estimation method is adopted with sophisticated econometric approaches. The obtained results indicate a long-term positive effect of biological capacity, financial development, human development index, income inequality on economic growth while the effect of energy use is the opposite. The findings of the study suggest that governments and associated bodies must promote financial development, human development, and biocapacity to not only attain economic growth in the long-run and but dissuade ecological footprint, and income inequality at the same time while matching the energy consumption with the bio-capacity of each economy.

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