The Sub-Saharan Africa (SSA) is far lag behind the sustainable targets that set out in the United Nation's Sustainable Development Goals (SDGs), which is highly needed to embark the priorities by their member countries to devise sustainable policies for accessing clean technologies, energy demand, finance, and food production to mitigate high-mass carbon emissions and conserve environmental agenda in the national policy agenda. The study evaluated United Nation's SDGs for environmental conservation and emission reduction in the panel of 35 selected SSA countries, during a period of 1995-2016. The study further analyzed the variable's relationship in inter-temporal forecasting framework for the next 10 years' time period, i.e., 2017-2026. The parameter estimates for the two models, i.e., CO2 model and PM2.5 models are analyzed by Generalized Method of Moment (GMM) estimator that handle possible endogeneity issue from the given models. The results rejected the inverted U-shaped Environmental Kuznets Curve (EKC) for CO2 emissions, while it supported for PM2.5 emissions with a turning point of US$5540 GDP per capita in constant 2010 US$. The results supported the "pollution haven hypothesis" for CO2 emissions, while this hypothesis is not verified for PM2.5 emissions. The major detrimental factors are technologies, FDI inflows, and food deficit that largely increase carbon emissions in a panel of SSA countries. The IPAT hypothesis is not verified in both the emissions; however, population density will largely influenced CO2 emissions in the next 10 years' time period. The PM2.5 emissions will largely be influenced by high per capita income, followed by trade openness, and technologies, over a time horizon. Thus, the United Nation's sustainable development agenda is highly influenced by socio-economic and environmental factors that need sound action plans by their member countries to coordinate and collaborate with each other and work for Africa's green growth agenda.
Matched MeSH terms: Energy-Generating Resources/statistics & numerical data
In this study, fatty acid methyl esters (FAME) have been successfully produced from transesterification reaction between triglycerides and methyl acetate, instead of alcohol. In this non-catalytic supercritical methyl acetate (SCMA) technology, triacetin which is a valuable biodiesel additive is produced as side product rather than glycerol, which has lower commercial value. Besides, the properties of the biodiesel (FAME and triacetin) were found to be superior compared to those produced from conventional catalytic reactions (FAME only). In this study, the effects of various important parameters on the yield of biodiesel were optimized by utilizing Response Surface Methodology (RSM) analysis. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum yield of biodiesel. The optimum conditions were found to be 399 degrees C for reaction temperature, 30 mol/mol of methyl acetate to oil molar ratio and reaction time of 59 min to achieve 97.6% biodiesel yield.
With the increasing scarcity of traditional energy sources, global warming and environmental degradation, the increased use of renewable energy (RE) has become an effective path for sustainable development. Therefore, countries are paying more and more attention to the development of the RE industry, and the world trade in renewable energy products (REPs) is developing rapidly. First of all, this paper defines REPs, refines the scope of REPs, and proposes the "Equalization Technology Classification" method for the technology classification of REPs. Second, based on the United Nations Comtrade (COMTRADE) data, the export technology structure of China's REPs from 2007 to 2016 was empirically measured. Finally, a comparative study was conducted on the renewable energy product (REP) export technologies of major REP exporting countries (or regions) in the world. We found that (1) China's exports of REPs are mainly medium-high and medium technical complexity products, and that there are few high technical complexity products; (2) the export technology structure of China's REPs is deteriorating, and its overall technical level is in the middle of the global industrial value chain. The export technology of China's REPs has a gap compared with that of Denmark, Hong Kong China, and Singapore; (3) the technological competition of the world's REPs is becoming increasingly fierce. The growth rates of REP technologies in South Korea, Japan, and Malaysia's REPs are significantly higher than that of China.
Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
The objective of the study is to establish the link between air pollution, fossil fuel energy consumption, industrialization, alternative and nuclear energy, combustible renewable and wastes, urbanization, and resulting impact on health services in Malaysia. The study employed two-stage least square regression technique on the time series data from 1975 to 2012 to possibly minimize the problem of endogeniety in the health services model. The results in general show that air pollution and environmental indicators act as a strong contributor to influence Malaysian health services. Urbanization and nuclear energy consumption both significantly increases the life expectancy in Malaysia, while fertility rate decreases along with the increasing urbanization in a country. Fossil fuel energy consumption and industrialization both have an indirect relationship with the infant mortality rate, whereas, carbon dioxide emissions have a direct relationship with the sanitation facility in a country. The results conclude that balancing the air pollution, environment, and health services needs strong policy vistas on the end of the government officials.
Matched MeSH terms: Energy-Generating Resources/statistics & numerical data