Abstract. The island of Hateruma is the southernmost inhabited island of Japan. Here we interpret observations of carbon monoxide (CO), ethane (C2H6), propane (C3H8), nitrogen oxides (NOx and NOy) and ozone (O3) made from the island in 2018 with the GEOS-Chem atmospheric chemistry transport model. We simulated the concentrations of these species within a nested grid centered over the site, with a model resolution of 0.5°×0.625°. We use the Community Emissions Data System (CEDS) emissions dataset for anthropogenic emissions and add a geological source of C2H6 and C3H8. The model captured the seasonality of primary pollutants (CO, C2H6, C3H8) at the site - high concentrations in the winter months when oxidation rates are low and flow is from the north, and low concentrations in the summer months when oxidation rates are higher and flow is from the south. It also simulates many of the synoptic scale events with Pearson’s correlation coefficients (r) of 0.74, 0.88 and 0.89 for CO, C2H6 and C3H8, respectively. Concentrations of CO are well simulated by the model (with a gradient of best fit between model and measurements of 0.91) but simulated concentrations of C2H6 and C3H8 are significantly lower than the observations (gradients of best fit between model and measurement of 0.57 and 0.41, respectively), most noticeably in the winter months. Simulated NOx concentrations were underestimated but NOy appear to be overestimated. The concentration of O3 is moderately well simulated (gradient of best fit line of 0.76, with an r of 0.87) but there is a tendency to underestimate concentrations in the winter months. By switching off the model’s biomass burning emissions we show that during winter biomass burning has limited influence on the concentration of compounds in the winter but can represent a sizeable fraction in the summer. We also show that increasing the anthropogenic emissions of C2H6 and C3H8 in Asia by factors of 2.22 and 3.17, respectively, significantly increases the model’s ability to simulate these species in the winter months, consistent with previous studies.