Economic growth with coal, oil and renewable energy consumption in China: prospects for fuel substitution

We examine the relationship between Chinese aggregate production and consumption of three main energy commodities: coal, oil and renewable energy. Both autoregressive distributed lag (ARDL) and vector error correction modeling (VECM) show that Chinese growth is led by all three energy sources. Economic growth also causes coal, oil and renewables consumption, but with negative own-price effects for coal and oil and a strong possibility of fuel substitution through positive cross-price effects. The results further show coal consumption causing pollution, while renewable energy consumption reduces emissions. No significant causation on emissions is found for oil. Hence, making coal both absolutely and relatively expensive compared to oil and renewable energy encourages shifting from coal to oil and renewable energy, thereby improving economic and environmental sustainability.

Stable superhydrophobic surface based on silicone combustion product

Discarded silicone products can be recycled to prepare superhydrophobic powder by simply burning and smashing. The powder can be used to fabricate a superhydrophobic surface with mechanical durability such that the superhydrophobicity was kept after 50 abrasion cycles. A robust electroconductive superhydrophobic surface can also be obtained by this simple method.

The role of technology on the dynamics of coal consumption-economic growth: new evidence from China

Coal comprises 70% of primary energy sources and 80% of electricity generation in China. This paper investigates the coal consumption-economic growth nexus in an integrated demand-supply framework over the period from 1978 to 2010. We incorporate the role of coal technology to explain the growth process. Using the Autoregressive Distributed Lag bounds testing approach, we find improvement in the coal-to-electricity efficiency indicator, a proxy for coal technology, causing almost a 35% increase in real GDP in the long run. The Toda-Yamamoto causality test indicates unidirectional causality from coal consumption to economic growth, feedback effects both for coal-to-electricity efficiency indicator to economic growth and coal demand and openness to coal consumption. For a robustness check, we forecast the validity of the causal relationships beyond the sample horizon using the generalised forecast error variance decomposition method. Our analysis suggests that improving overall efficiency in coal sector will continue to play a significant role in maintaining sustainable growth in China in the long run.