Carbon dioxide (CO₂) and methane (CH₄) are the main greenhouse gases, contributing about 81% of the total human induced radiative forcing. Sufficient observations exist to quantify the global budget of carbon dioxide and methane which is necessary for calculating the resulting radiative forcing. Still, more observations are needed to constrain their time evolution and regional budgets which are needed for climate change mitigation policies. Atmospheric observations are particularly scarce on the African continent, despite Africa’s significant CO2 emissions from agriculture, biomass burning and land use changes, as well as methane emissions from wetlands. there are very few low frequency flask measurements due to limited logistics and there is no land based station at all in equatorial Africa. Satellite observations can only provide an incomplete record due to frequent clouds and aerosol in the equatorial belt.

We have set up a high-frequency in-situ greenhouse gases monitoring station in North West Rwanda at Mount Mugogo. The station is intended to be a long-term station, hence, filling the gap of current lack of measurements in Equatorial Africa. The station is part of the Advanced Global Atmospheric Gases Experiment (AGAGE) and follow its calibration protocols and operational standards, therefore, providing data of internationally recognized quality standards. We have found that massive regional scale biomass burning largely drives the bi-model seasonal cycle of carbon dioxide, carbon monoxide and black carbon with the burning following the shift of the inter-tropical convergence zone. The seasonal cycle of methane is largely driven by the inter-hemispheric gradient, where methane-rich northern hemisphere air masses are advected to the station during the northern winter.

We have used the Reversible Jump Markov Chain Monte Carlo methods to estimated optimized methane and carbon dioxide emissions in the Central and East African region. We have found that the region emitted about 25 Tg of CH₄ and 139 Tg of CO₂ in 2016.