Estimation of ambient BVOC emissions using remote sensing techniques

Abstract

Abstract The contribution of Biogenic Volatile Organic Compounds (BVOCs) to local air quality modelling is often ignored due to the difficulty of obtaining accurate spatial estimates of emissions. Yet their role in the formation of secondary aerosols and photochemical smog is thought to be significant, especially in hot tropical cities such as Hong Kong, which are situated downwind from dense forests. This paper evaluates Guenther et al.’s [Guenther, A., Hewitt, C.N., Erickson, D., Fall, R., Geron, C., Graedel, T.E., Harley, P., Klinger, L., Lerdau, M., McKay, W.A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmerman, P., 1995. A global model of natural volatile organic compound emissions. Journal of Geophysical Research 100, 8873–8892] global model of BVOC emissions, for application at a spatially detailed level to Hong Kong’s tropical forested landscape using high resolution remote sensing and ground data. The emission estimates are based on a landscape approach which assigns emission rates directly to ecosystem types not to individual species, since unlike in temperate regions where one or two single species may dominate over large regions, Hong Kong’s vegetation is extremely diverse with up to 300 different species in one hectare. The resulting BVOC emission maps are suitable for direct input to regional and local air quality models giving 10 m raster output on an hourly basis over the whole of the Hong Kong territory, an area of 1100 km2. Due to the spatially detailed mapping of isoprene emissions over the study area, it was possible to validate the model output using field data collected at a precise time and place by replicating those conditions in the model. The field measurement of emissions used for validating the model was based on a canister sampling technique, undertaken under different climatic conditions for Hong Kong’s main ecosystem types in both urban and rural areas. The model-derived BVOC flux distributions appeared to be consistent with the field observations, indicating the robustness of the landscape modelling approach when applied to tropical forests at detailed level, as well as the promising role of remote sensing in BVOC mapping.