In this work, the co-pyrolysis of coal and algae is explored with special emphasis on decomposition kinetics and the possibility of the existence of synergistic effects. Modelling and kinetics analysis based approaches were used for the investigation of the existence of synergistic effects. The co-pyrolysis kinetics was studied using the model-free, Coats–Redfern integral method. The kinetics were evaluated for 1st and 2nd order reaction models. Results reveal that Scenedesmus microalgae is characterised by a two stage decomposition process that occurs at temperature ranges of 200–400 °C and 500–700 °C with activation energy of 145.5 and 127.3 kJ/mol, respectively. Bituminous coal has a two stage, slow decomposition process that occurs at temperature ranges of 400–700 °C and above 750 °C with an activation energy of 81.8 and 649.3 kJ/mol, respectively. Furthermore, co-pyrolysis of coal and microalgae is characterised by three stages whose kinetics are dominated by the pyrolysis of the individual materials. For the studied range of coal/algae ratios, the three pyrolysis stages occur in the approximate temperature ranges of 200–400 °C, 430–650 °C and above 750 °C, with activation energies in the ranges of 131–138, 72–78 and 864.5–1235 kJ/mol, respectively. Modelling and kinetics study showed that there is strong evidence of interactions between coal and microalgae that manifest as synergistic effects especially in the second and third stages of decomposition.

The purpose of the study is to contrast the impact of ‘clean’ and ‘dirty’ electricity production on economic growth for South Africa and determine whether a faster transition from fossil fuels to renewables is beneficial for growth. To this end, we use wavelet coherence analysis to examine the time–frequency relationship between electricity and economic growth for aggregated and disaggregated measures of clean and dirty sources over the period 1985–2021 At an aggregated level, the low frequency (long-run) correlations are eventually substituted with high frequency (short-run) co-movements. At disaggregated level, the results are mixed, with dirty energy components (coal, oil, gas) having a weakening effect on economic growth over time whilst clean energy sources (solar and wind, biomass, hydro) show the greatest potential for growth over both low and high frequency relationships. Moreover, the various structural breaks identified in the frequency bands for different electricity sources allow us to evaluate the impact of energy policies and load shedding on the electricity-growth relationship and offer further insights to which clean sources of electricity production have more potential to be growth enhancing.

This research study contributes to the ever-expanding literature by examining multivariate cointegration and causality relationships between electricity consumption, economic growth and other growth determinants for quarterly South African data collected between 1994/Q1 – 2014/Q4. The motivation behind this current research case study becomes apparent when taking into consideration that no previous studies have gone further than bivariate and trivariate analysis in investigating the electricity-growth nexus in South Africa. In conducting our empirical investigation, our obtained empirical results are two-fold in nature. Firstly, we find significant multivariate long-run cointegration relationships between economic growth, electricity consumption and other growth determinants. Secondly, our empirical analysis offers support in favour of the neutrality hypothesis, that is, the notion of no causal effects existing between electricity consumption and economic growth in the long-run. However, we find that exports directly cause electricity consumption whereas economic growth, domestic investment and employment levels causally flow to exports.