Renewable energy, urbanization, and ecological footprint linkage in CIVETS.

Emerging economies are mostly plague by a massive consumption of non-renewable energy amidst an ever inceasing urbanization rate with little or no attention to the quality of the environmental. As such, this paper investigates the relationship between renewable energy, urbanization, economic growth, trade openness, and ecological footprint in CIVETS countries, namely, Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa. The study employs augmented mean group estimator, panel cointegration, and causality tests. The findings reveal that renewable energy improves environmental quality, and trade is not particularly harmful to the environment. However, non-renewable energy consumption and urbanization are the chief contributors to environmental degradation in the CIVETS countries. Economic expansion mitigates environmental deterioration in Colombia, South Africa, and Turkey, but contributes to pollution in Egypt, Indonesia, and Vietnam. Finally, the causality test suggests that urbanization drives environmental degradation. Policy directions are discussed.

Application of gas chromatography/flame ionization detector-based metabolite fingerprinting for authentication of Asian palm civet coffee (Kopi Luwak).

Development of authenticity screening for Asian palm civet coffee, the world-renowned priciest coffee, was previously reported using metabolite profiling through gas chromatography/mass spectrometry (GC/MS). However, a major drawback of this approach is the high cost of the instrument and maintenance. Therefore, an alternative method is needed for quality and authenticity evaluation of civet coffee. A rapid, reliable and cost-effective analysis employing a universal detector, GC coupled with flame ionization detector (FID), and metabolite fingerprinting has been established for discrimination analysis of 37 commercial and non-commercial coffee beans extracts. gas chromatography/flame ionization detector (GC/FID) provided higher sensitivity over a similar range of detected compounds than GC/MS. In combination with multivariate analysis, GC/FID could successfully reproduce quality prediction from GC/MS for differentiation of commercial civet coffee, regular coffee and coffee blend with 50 wt % civet coffee content without prior metabolite details. Our study demonstrated that GC/FID-based metabolite fingerprinting can be effectively actualized as an alternative method for coffee authenticity screening in industries.