Analysis of Biomass Use as Energy Sources among Rural Households in Khaukhwe, North West Province South Africa

Abstract

The main objective of the study was to analyse the use of biomass energy in Khaukhwe village of the Greater Taung municipality of the North-West Province. The study was conducted among 180 respondents. Data were collected using structured questionnaires which included open and closed ended questions. Questionnaires were coded, captured and analysis was done using statistical package for Social Sciences (SPPS). The findings show that 23.9% of the respondents were married and were mostly females (62.2%); 56.67% had 1-3 children with 11.67% having 4-6 children; 66.7% of the respondents have high school qualifications. The respondents have large families, 68.2% had between 4-6 members in the household. The findings revealed that 89.91% respondents walks 1-3 km to collect biomass fuel. The most predominant type of energy used is biomass at 99.4% and the respondents preferred biomass at 99.4% and 91.1% indicated that it is important to them. Of all types of biomass listed, wood was the most predominant type used (98.3%) and was also important to them (97.2%). The findings show that respondents were favourably disposed to the use of biomass through the following statements and indicated that biomass is cheap (77.8%), biomass collection is gender biased (68.3%), biomass collection is time consuming (53.9%) and biomass is easily accessible (46.7%). It was strongly agreed that biomass is cheap, hence, the high dependency rate. The study revealed that biomass was mainly used for cooking and space warming (100%), the constraints in biomass collection were impacted on the harvesters (100%), distance travelled for harvesting was 100%, labour involved in harvesting was 100%, harvesting biomass is time consuming (100%) and is done, frequently (100%), there were health hazards (100%) and reduces agricultural activities (99.4%). The analysis of the results shows that the autonomous level of use of biomass by rural dwellers is -10.26. The model has a good fit and it is significant at 1% (?2 = 84263.00, df = 162, p < 0.01). Fourteen explanatory variables were significant while four variables were insignificant. The significant variables include attitude ( t =-4.112 , p < 0.05), constraints ( t = 3.815, p < 0.05), age ( t = 4.944, p < 0.05), race( t = 2.234, p < 0.05), gender( t = 3.406, p < 0.05), language( t = -13.544, p < 0.05), educational level( t =-8.189 , p < 0.05), employment type( t = -10.115, p < 0.05), dwelling type( t = 2.364, p < 0.05), distance for biomass collection ( t = 5.142, p < 0.05), cooking times per day ( t = -12.385, p < 0.05), cooking duration per meal ( t = 14.882, p < 0.05), cooking years ( t = -9.846, p < 0.05) and homes with separate kitchen ( t = -7.908, p < 0.05).

DOI: 10.5901/mjss.2014.v5n27p948