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The main aim of this article is to examine empirically the impact of urbanization on carbon dioxide emissions in Singapore from 1970 to 2015. The autoregressive distributed lags (ARDL) approach is applied within the analysis. The main finding reveals a negative and significant impact of urbanization on carbon emissions in Singapore, which means that urban development in Singapore is not a barrier to the improvement of environmental quality. Thus, urbanization enhances environmental quality by reducing carbon emissions in the sample country. The result also highlighted that economic growth has a positive and significant impact on carbon emissions, which suggests that economic growth reduces environmental quality through its direct effect of increasing carbon emissions in the country. Despite the high level of urbanization in Singapore, which shows that 100 % of the populace is living in the urban center, it does not lead to more environmental degradation. Hence, urbanization will not be considered an obstacle when initiating policies that will be used to reduce environmental degradation in the country. Policy makers should consider the country's level of economic growth instead of urbanization when formulating policies to reduce environmental degradation, due to its direct impact on increasing carbon dioxide emissions.

Most previous bioenergy industry research has concentrated on how to implement a certain level of yield. However, few articles have paid attention to rational resource allocation to increase efficiency. To enhance bioenergy production through proper use of available resources, this study identified the effects of internal (country-specific) and external (macroeconomic) determinants of technical efficiency level in the bioenergy industry for the EU28 region. The study was established based on a conceptual framework suggesting a correlation between input use and level of technical efficiency. A panel data analysis method was employed for the analysis and a panel regression analysis framework based on the Fixed Effect (FE) model and Random Effect (RE) model was used to examine the potential determinants of technical efficiency level in the bioenergy industry for the EU28 region for the period between 1990 and 2013. The results indicate that the technical efficiency level of the bioenergy industry in developing countries is higher than in developed countries. The empirical findings also suggest that technical efficiency has greater influence on pure technical efficiency levels. Capital input, labor input, gross domestic product, inflation and interest rate significantly affected the technical efficiency of the bioenergy industry in the developing and developed countries in the EU28 region during the period of this study. The findings clearly call for regulators and decision makers to review the technical efficiency level of the bioenergy industry within the EU28 region. This study also provides better information and guidance to the boards of the bioenergy industry, as they need to have a clear understanding of the influence technical efficiency has on bioenergy production performance. Moreover, the results of this study have implications for investors who focus mainly on profits from their investments.

Theoretically, population growth is believed to increase greenhouse gas emissions, particularly CO 2 emissions through the increase in human activities. Accordingly, this study aimed to investigate this assertion in Nigeria using an autoregressive distributed lag model covering periods from 1971-2000, 1971-2005, and 1971-2010 recursively. The results indicated that population was not a determinant of CO 2 emissions in all the three periods in the long run. However, economic growth was found to be the only long-run CO 2 emissions determining factor within the studied periods. However, in the short run, virtually all the explanatory variables and their lags, that is, population growth, economic growth, and energy consumption, were significant in determining CO 2 emissions. The findings suggested that population growth, which is the focal point of the study, could only determine CO 2 emissions in the short run. Therefore, population checking measures could be a shortrun effective measure to lower the emissions level. Also, further research should be conducted on how to effectively and efficiently manage the population growth-CO 2 emissions relationship.

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Most previous bioenergy industry studies have focused on how to achieve a specific level of production. However, very few studies concentrate on the cost and the allocative and technical efficiency methods to achieve rational resource utilization. In light of the increase in the bioenergy industry's economic competitiveness within the energy market through proper allocation and utilization of available resources, this article analyzed the impact of countryspecific and macroeconomic determinants of cost efficiency rate in the bioenergy industry in the EU28 zone. The fixed effects and random effect models have been used through the unbalanced data panel analysis method to examine the effect of EU28 region countries' development status and external economic determinants on the level of cost efficiency in the bioenergy industry in EU28. The findings show that the cost efficiency rate of the bioenergy industry among developing members are equal to those of developed members. The empirical results appear to suggest that cost efficiency has a different influence on the technical and allocative efficiency levels. It was found that capital cost, labor cost, GDP, inflation and interest rate affect the cost efficiency of the bioenergy industry in EU28 developing and developed members during the period of this study.