UCL Institute for Sustainable Resources


Bernard Tembo

Bernard holds a BEng Mechanical Engineering from University of Zambia (2008) and MSc Eng Energy Studies from University of Cape Town (2012). 

From 2008 to 2011, Bernard worked in Zambia’s energy sector managing the oil supply business to the copper mines and commercial farmers. 

His masters’ research focused on electricity supply options and expansion planning. During his time at University of Cape Town, he was also involved in various energy and development research projects around sub-Sahara Africa.  During his PhD, he will focus on energy efficiency in Africa’s copper industry with a case-study of Zambia’s industry, which is the largest producer in Africa.

Research subject

Energy efficiency in the Zambian copper industry

Primary supervisors: Dr Neil Strachan (UCL Energy Institute) 

Energy efficiency is quickly becoming a priority issue on many national and international agendas for a number of reasons that range from economical benefits, energy security, environmental protection to climate change mitigation. A number of technically and economically feasible measures for the reduction of energy use have been identified in the all sectors – residential, commercial, transport, agricultural and industrial. 

Nonetheless, the implementation of these measures is neglected even when their benefits are obvious. Energy efficiency barriers can broadly be categorised into four: organisational, institutional, behavioural and market barriers. Barriers can be further classifies into six groups namely; “imperfect information, hidden costs, risk and uncertainty, split incentives, access to capital and bounded rationality’. Unfortunately, very little is being done to overcome these challenges in Africa.  

A bottom-up ‘home-grown’ model is needed to aid decision making so that energy efficiency could be achieved by clearly and transparently identifying associated benefits of energy efficiency. However, researchers (Saygin et al., 2011) have acknowledged the challenges of quantifying energy efficiency potential in Africa due to limited accurate information. Therefore, this research will endeavour to bring more understanding on the state of energy use in Africa’s copper industry, and also develop a model that can be used to aid energy-related policy decision making processes.  

Focusing on copper as an important and major non-ferrous metal in sub-Sahara Africa, there has been little economic-energy-environmental research done despite being energy and carbon intensive. In Zambia for instance, copper accounts for more than 70% of its foreign exchange. While at the same time, accounting for 55% and 37% of the total electricity and oil consumed in the country respectively.  This sector offers an opportunity for the country to grow economically but also poses a serious challenge to realising this growth: huge investments have to be made in the energy system sustain growth from this sector.  

After establishing the status of knowledge in the industry, a questionnaire will be developed and a survey carried out in Zambia’s copper industry. This information will then be integrated into a bottom-up model.  Simulation of different policy instruments and institutional mechanisms scenarios will be carried out using an appropriate modelling/simulation approach such as Agent Based Modelling, in order to explicitly represent non-quantitative energy efficiency barriers, uncertainty, technology adoption, organisational limitations (such as capacity and bounded rationality) and market conditions realities in Africa. Traditional modelling tools such has LEAP or MARKAL do not explicitly capture and represent all the energy efficiency barriers (Fleiter et al., 2011).  

This approach will increase the understanding of how firms (and investors) would respond to different scenarios and also provide modelling transparency. This research will add to understanding of the state of energy use in Africa’s Copper sector and above all, it will be an innovative approach of modelling and simulating energy efficiency barriers.