Analysing Nigeria’s Energy system in light of the UN’s Sustainable Development Goals : A CLEWs assessment

Detta är en Kandidat-uppsats från KTH/Industriell ekologi

Författare: Obiora Okolo; Haoran Teng; [2017]

Nyckelord: ;

Sammanfattning: Today 57.7 % of Nigerians has access to electricity with less than 1 % using electric stoves for cooking. Fuelwood is used for cooking in 63.7 % of the households and is one of the main contributors to Nigeria having the third highest deforestation rate in the world with 410 000 hectares of forest cut down per year. The country is also listed as one of the ten most vulnerable countries to climate change in the world. The main objective of this thesis is therefore to evaluatea key section of the integrated Climate, Land, Energy and Water system (CLEWs) nexus for Nigeria between 2015–2030 with the main CLEWs interlinkages focused on being the ones between energy (electricity & cooking), land (deforestation) and climate (CO2 emissions). The further aim of this thesis is to contribute in the UNDP’s work towards the SDG 7 (affordable andclean energy) and 15 (life on land). Through the modelling of 10 different scenarios in the long-term energy planning tool OSeMOSYS (Open Source Energy Modelling System) the outcomes of all scenarios are analysed and compared regarding costs and their implications on the deforestation rate and CO2 emissions. The results show that the scenarios with NREEEP leads to a 30 % reduction in CO2 emissions in Nigeria compared to those in the cost-optimized scenarios. The results on deforestation show that the forests in the country will be gone or almost gone by 2030 both in the cost-optimal scenarios as well as in the business as usual and high growth scenarios. The No fuelwood and charcoal scenario saved the most of the forests, but had the highest CO2 emissions which indicates that there is a conflict between SDG 7 and 15. For futurework it is recommended to expand the modelling work done in this study through, among other things, enforcing OSeMOSYS to create an optimal cooking sector based on environmental factors through the use of parameters such as emission penalty and implementing other types of innovative stoves in the model to analyse the outcomes.

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