In part one of this series of papers on a new integrated modelling system (IMS), the interactive three-dimensional chemical transport model (CTM), we present a detailed description of the interactive emission scheme for biogenic species and outline the datasets used for anthropogenic species. In addition, we describe the transport scheme employed in this model. The biogenic emission schemes incorporate the high-resolution Olson World Ecosystem data (Olson, 1992), the satellite-sensed terrestrial vegetation data from AVHRR (A Very High Resolution Radiometer) (Brown et al., 1985), and the CZCS (Coastal Zone Color Scanner) data (Erickson and Eaton, 1993). These datasets provide seasonal variations in surface biogenic emissions. The emission schemes are tested against other estimates (e.g., GEIA) and equilibrium emissions. A comparison of terrestrial biogenic fluxes, both the spatial and temporal (seasonal) variation of modelled surface net primary production, is consistent with the geographical variations of the global vegetation index (GVI) distribution derived from AVHRR. The annual net primary production is 76000 Tg C yr-1, which compares well with the 40500-78000 Tg C yr-1 estimated by Melillo et al. (1993). This indicates that the model works well in capturing spatial and seasonal variations in the terrestrial vegetation. The modelled surface vegetation fluxes are verified against data from Guenther et al. (1995). While the comparison shows a generally good agreement in terms of the temporal and spatial distributions of isoprene (530 Tg yr-1), large discrepancies are seen over the tropical locations which often exhibit strong seasonality in rainfall and very small variation in temperature. These differences indicate that a large difference in the estimation between an empirical relation and an LSM calculation occurs if an area in which seasonal distribution of rainfall is the main factor which determines the type of vegetation. In this paper, we assess (results are discussed in following papers) the role of changing surface biogenic distributions in surface-to-atmosphere biogenic fluxes (both ocean-to-atmosphere and land-to-atmosphere).