The data was collected in the catchment of Lake Cyohoha North to analyze socio-economic impact that the change in Land use/cover and lake degradation have had on smallholder farmers living within this catchment.

Data on water quality for the various boreholes within Naivasha Sub-county

The socio-economic information were collected from Kirua-Kahe village which aimed at understanding the socio-economic activities of the society and assess the needs of Solar water pumping systems. The barriers to adapt of pumping system were analyzed as well as the financial access barrier prior to the design of solar water pumping systems and financial return validation. The technical capacity of technicians on how to handle solar water pumping systems were ranked by TAREA and Frank Prosperous.

Data was obtained for quantitative analysis

These data was collected in the region of south western MAU forest in Riftvalley, Kenya. The aim of the study was to access the status of energy access both for cooking and lighting by the communities living around the forest. Also, social and economic status of the households was captured. The data collection tool was a structured questionnaire which was loaded to an ODK android phone application app. The data was collected between the June 2019 and July 2019 and 215 households were interviewed.

The data collection was done at the district of Ambatolampy, Madagascar, using questionnaire survey about the electrical load of the location for the purpose of the master dissertation in energy engineering.

The data were collected in Musanze district, Rwanda. The purpose of the study is to assess the impact of energy efficiency policies on future energy demand in secondary cities. That was processed by spss. The results showed that four energy sources predominate: electricity, charcoal, firewood and LPG. However, there were urban households with greater diversity of energy sources in urban households, also including electricity (97.89%), candles (44.21%) and liquefied petroleum gas, or LPG (37.89%). Charcoal use is much higher at 82.11%, whereas firewood use is only 29.49%. In order to minimize energy loss in urban households, this research suggests that similar studies in the future may focus more on obtaining previous data, if possible, the study could be conducted over years to use own primary data, or else obtaining as many years’ data as possible to forecast the future energy consumption accurately.

Data was obtained for quantitative analysis

Data was obtained for quantitative analysis