Assessing biogenic emission impact on the ground-level ozone concentration by remote sensing and numerical model

Emission inventory data is one of the major inputs for all air quality simulation models. Emission inventory data for the prediction of ground-level ozone concentration, grouped as point, area, mobile and biogenic sources, are a composite of all reported and estimated pollutant emission information from many organizations. Before applying air quality simulation model, the emission inventory data generally require additional processing for meeting spatial, temporal, and speciation requirements using advanced information technologies. In this study, SMOKE was setup to update the essential emission processing. The emission processing work was performed to prepare emission input for U.S. EPA´s Models-3/CMAQ. The fundamental anthropogenic emission inventory commonly used in Taiwan is the TEDS 4.2 software package. However, without the proper inclusion of accurate estimation of biogenic emission, the estimation of ground-level ozone concentration may not be meaningful. With the aid of SPOT satellite image, biogenic gas emission modeling analysis can be achieved to fit in BEIS-2 in SMOKE. Improved utilization of land use identification data, based on SPOT outputs and emission factors, may be influential in support of the modeling work. During this practice, land use was identified via an integrated assessment based on both geographical information system and remote sensing technologies; and emission factors were adapted from a series of existing database in the literature. The research findings clearly indicate that the majority of biogenic VOCs emissions occurred in the mountains and farmland actually exhibit fewer impacts on ground-level ozone concentration in populated areas than the anthropogenic emissions in South Taiwan. This implies that fast economic growth ends up with sustainability issue due to overwhelming anthropogenic emissions