Blog by Akala Haron & Mike Olendo
The Agriculture sector is the backbone of Kenya’s economy which contributes to 45% of the country’s source of revenue, 75% industrial raw materials and more than 50% of the export earnings (IFPRI) and provides employment to 40% of the total population (FAO). Increasing population demands more agricultural products which results to increased emissions of CH4, N2O and CO2 due to intensive use of fertilizers and manure management for improved yields. Aggregated sources and non-CO2 emissions sources on land (C3 components) include: Emissions from biomass burning; liming; Urea application; Direct and indirect emissions from managed soils; Indirect N2O emissions from manure management; and Rice cultivation.
CI’s Capacity Building Initiative and Transparency (CBIT) project supported a one-week training workshop for the Agriculture sector at the Climate Change Directorate (CCD) Resource Center, the workshop was facilitated by Greenhouse Gas Management Institute (GHGMI).
Objectives of the training included:
- To understand how to conduct Key Category Analysis in Agriculture sector;
- To understand and identify the activity data for emissions estimation;
- To model the data using spreadsheet;
- To transfer modeled data into the IPCC software;
The training covered the following areas
- Building Sustainable National GHG Inventory Management Systems.
- Modelling of direct and indirect emissions of CH4, N2O and CO2 from managed soils (liming, urea application, rice cultivation), from livestock (manure left on pasture-including linkages with livestock sector) and biomass burning-including linkages with the energy sector.
Modelling of the agriculture sector for Greenhouse gas (GHG) emissions reporting is among the most complex sectors, advanced formulae and emission factors are involved in calculating emissions as well as large volumes data - hence the need to build necessary capacity building to understand the dynamics and diversity of the sector through collaborative engagements from relevant institutions and partners to ensure the key deliverables are met.
The training was interactive with group participation in various stages and impromptu quizzes at to gauge understanding of the subject. The team displayed understanding of modelling the agriculture sector at the end of the training by the ability to conduct practical assignments and an average score of 80% of a structured quiz. These skills will be translated to modelling of emissions especially from N2O which has the highest GWP of 280 in 20 years as compared to CH4- 56 and CO2- 1 (UNFCCC), these will further fast track the development of the GHG inventory for NIR.
For more information, please contact Mike Olendo at email@example.com