Geography

Permanent URI for this community

http://hdl.handle.net/11660/101

Browse

Browsing Geography by Subject "Agriculture"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Estimation of greenhouse gas emissions from agriculture in the eastern Free State, South Africa
    (University of the Free State, 2017-12) Malaka, Sewela Francinah; Mukwada, G.; Moeletsi, M. E.
    The agriculture sector is responsible for global emissions and the emissions continue to grow rapidly. The food agriculture organization (FAO) reported emissions with 7.1 gigatonnes CO2eq per annum, representing 14.5 % of human-induced GHG emissions; the livestock sector plays an important role in climate change. Beef and cattle milk production account for the majority of emissions, respectively contributing 41 and 20 % of the sector’s emissions. While pig meat and poultry meat and eggs contribute respectively 9 % and 8 % to the sector’s emissions. Feed production and processing, and enteric fermentation from ruminants are the two main sources of emissions, representing 45 and 39 % of sector emissions, respectively. Manure storage and processing represent 10 % in 2013. Contribution of agriculture sector to South Africa’s total CO2eq emissions was 11.6 % in 1990, 9.3 % in 1994 and 4.9 % in 2000. The livestock category was the major contributor to the Agriculture, Forestry and Other Land Use (AFOLU) sector, providing the average of 54.1 % to the total CH4 emissions in 2010. The contribution from livestock has declined by 11.8 % over the 2000 -2010 period. The department of environmental affairs (DEA) reported that, the total enteric CH4 emissions attained for the years (2000, 2004, and 2010) were 903.23 Gg, 1183.56 Gg and 1172.95 Gg. The contributions of dairy cattle to the total cattle emissions in 2004 was 14.3 % and 13.5 % in 2010. The overall objective of this research study was to estimate GHG emissions (CO2, CH4 and N2O) resulting from agricultural farms in Tshiame Ward in the eastern Free State region of South Africa for the years 2010 to 2014. The importance of this research was to assess GHG emissions in agricultural farms for purposes of developing mitigation options. The available data allowed Tier 2 method to calculate all the GHG emission factors (EFs) and emissions from cattle, sheep and cropland farming. However, Tier 1 method was used to estimate EFs and emissions from other livestock categories. Emissions were estimated from the agricultural sources including CH4 emissions from enteric fermentation, CH4 emissions from manure management, N2O emissions from manure management, non-CO2 emissions from biomass burning, Soil N2O emissions from managed soils, and emissions from fuel use. The results have shown relatively high CH4 EFs from enteric fermentation for mature female beef cattle (95- 109 kg/head/year) at all farms. The dairy mature females followed with 71-105 kg/head/animal, dairy mature bulls (63-96 kg/head/animal), beef mature bulls (53-89 kg/head/animal), beef heifers (37-52 kg/head/animal), dairy heifers (33-56 kg/head/animal), dairy calves (10-25 kg/head/animal), and beef calves (10-24 kg/head/year). Ewes recorded an enteric CH4 EF of about 7 kg CH4/head/year, heifers 0.86 kg CH4/head/year, rams with about 9 kg CH4/head/year and lambs were calculated to have an enteric CH4 EF of about 0.22 kg CH4/head/year. The manure CH4 EFs for MMSs varied per animal subcategories. Beef mature females had the highest average CH4 manure EFs ranging from 1.2 to 1.5 kg CH4/animal/year at all farms, followed by the dairy mature females with CH4 manure EFs ranging from 0.8 to 2.2 kg CH4/animal/year. The beef mature bulls had the CH4 manure EFs of 0.9 to 1.2 kg CH4/animal/year which was higher than the dairy mature bulls which ranged from 0.9 to 1 kg CH4/animal/year. The other animal subcategories had the manure CH4 EFs ranging from 0.1 to 1 kg CH4/animal/year by MMSs. In summary, manure CH4 EFs for beef category were higher than the dairy category at all animal subcategories. The livestock EFs in this study were higher than the EFs found in most studies and this might be due to the lower quality of the feeding situation used in the study area. However, the cropland EFs were consistent with those in literature for most of the studies. It was estimated that farm total emissions in the year 2010 ranged from (69220-580877 kg CO2eq), (70977-585732 kg CO2eq) in the 2011, (45338-676245 kg CO2eq) in 2012, (54731-485264 kg CO2eq) in 2013, and (36270-464119 kg CO2eq) in 2014 at all farms. CH4 enteric fermentation was the highest contributor to the total farm emissions at all farms by approximately 50% in all years, followed by CH4 and N2O from manure management respectively. GHG emissions from cropland farming were lower than the emissions produced during livestock farming. In this study, the mitigation options were analysed and evaluated, and as a result, six (6) mitigation options were regarded as the potential mitigation options for Tshiame farms. The six (6) potential mitigation options met the requirements of sustainability, environmental friendly as well as the profitability of farmers. Managing manure as solid storage had reduced the total emitted manure emissions by 21-75% in all years at all farms. Feeding manure to anaerobic digester had resulted in the reduction of manure emissions emitted by 9-24% at all farms. Manure left on pasture had reduced the manure emissions by 20-75%. However, the dry lot reduced the manure emissions by 20-74% in all years. Addition of supplements in feeding situations had reduced the emitted enteric emissions ranging from 81 to 92 percent.
  • Thumbnail Image
    ItemOpen Access
    Vulnerability and adaptation to climate variability: a case study of emerging farmers in the eastern Free State, South Africa
    (University of the Free State, Qwaqwa Campus, 2015-06) Matela, Thabo Elias; Mukwada, G.; Moeletsi, M. E.
    English: A research study on vulnerability and adaptation to climate variability was conducted among emerging farmers in Tshiame Ward of Maluti-A-Phofung Municipality in the Free State Province of South Africa. The research aim was to assess the vulnerability of agricultural systems to climate variability and to identify the adaptation measures that emerging farmers use to cope with the problem. Primary data was collected by means of a semi-structured questionnaire to 19 farmers in the Ward. The data were captured and analysed using SPSS, to obtain the frequency tables. Microsoft Excel 2007 was used for statistical analysis and to plot the regression graphs while the Instat Software was used in the analysis of climate data to determine the dry spells, onset and offset of dates and the calculation of the Crop Performance Indices. The analysis revealed that farmers regard climate variability as a phenomenon taking place in Tshiame Ward. When farmers were asked about the cause of climate variability, some were unsure about their own answers though many of them were able to relate their answers to what is happening in their immediate environment. In order to cope with the impact of climate variability, farmers in Tshiame Ward have adopted a number of practices such as the use of drought and heat tolerant seeds and mixed cropping systems. These practices are based on the already existing knowledge as well as the perceived changes in climatic conditions. The statistical analysis of climate data revealed that some of the views held by some farmers‟ regarding climate variability are in contrast with the results shown by the analysis. The study concludes that the farmers who were able to perceive the change that is taking place in their environment were better able to implement effective adaptation measures and were consequently better-able to sustain their agricultural operations. The fact that farmers were aware or familiar with climate variability, as well as its associated impact can be related to the ongoing project that is being undertaken by Agricultural Research Council, where weather stations have been installed on farms in order to develop the capacity to monitor climate variability in the area.