Biomass burning (BB) in southern Africa is the largest emission source of CO and O3 precursors within Africa during the West African Monsoon (WAM) between June and August. The long range transport and chemical processing of such emissions thus has the potential to exert a dominant influence on the composition of the tropical troposphere over Equatorial Africa (EA) and the Tropical Atlantic Ocean (TAO). We have performed simulations using a three-dimensional global chemistry-transport model (CTM) to quantify the effect that continental transport of such BB plumes has on the EA region. BB emissions from southern Africa were found to exert a significant influence over the TAO and EA between 10° S–20° N. The maximum concentrations in CO and O3 occur between 0–5° S near the position of the African Easterly Jet – South as placed by the European Centre for Medium range Weather Forecasts (ECMWF) meteorological analysis data. By comparing co-located model output with in-situ measurements we show that the CTM fails to capture the tropospheric profile of CO in southern Africa near the main source region of the BB emissions, as well as the "extreme" concentrations of both CO and O3 seen between 600–700 hPa over EA around 6° N. For more northerly locations the model exhibits high background concentrations in both CO and O3 related to BB emissions from southern Africa. By altering both the temporal resolution and the vertical distribution of BB emissions in the model we show that changes in temporal resolution have the largest influence on the transport of trace gases near the source regions, EA, and in the outflow towards the west of Central Africa. Using a set of trajectory calculations we show that the performance of the CTM is heavily constrained by the ECMWF meteorological fields used to drive the CTM, which transport biomass burning plumes from southern Africa into the lower troposphere of the TAO rather than up towards the middle troposphere at 650 hPa. Similar trajectory simulations repeated using an updated meteorological dataset, which assimilates additional measurement data taken around EA, show markedly different origins for pollution events and highlight the current limitations in modelling this tropical region.