| Biogenic emissions make a significant contribution to the levels of aeroallergens and secondary air pollutants such as ozone. Understanding major factors contributing to allergic airway diseases requires accurate characterization of emissions and transport/transformation of biogenic emissions. However, biogenic emission estimates are laden with large uncertainties. Furthermore, the current biogenic emission estimation models use low-resolution data for estimating land use, vegetation biomass and VOC emissions. Furthermore, there are currently no established methods for estimating bioaerosol emissions over continental or regional scale, which can impact the ambient levels of pollent that have synergestic effects with other gaseous pollutants.;In the first part of the thesis, an detailed review of different approaches and available databases for estimating biogenic emissions was conducted, and multiple geodatabases and satellite imagery were used in a consistent manner to improve the estimates of biogenic emissions over the continental United States. These emissions represent more realistic, higher resolution estimates of biogenic emissions (including those of highly reactive species such as isoprene). The impact of these emissions on tropospheric ozone levels was studied at a regional scale through the application of the USEPA's Community Multiscale Air Quality (CMAQ) model. Minor, but significant differences in the levels of ambient ozone were observed.;In the second part of the thesis, an algorithm for estimating emissions of pollen particles from major allergenic tree and plant families in the United States was developed, extending the approach for modeling biogenic gas emissions in the Biogenic Emission Inventory System (BEIS). A spatio-temporal vegetation map was constructed from different remote sensing sources and local surveys, and was coupled with a meteorological model to develop pollen emissions rates. This model overcomes limitations posed by the lack of temporally resolved dynamic vegetation mapping in traditional pollen emission estimation methods. The pollen emissions model was applied to study the pollen emissions for North East US at 12 km resolution for comparison with ground level tree pollen data. A pollen transport model that simulates complex dispersion and deposition was developed through modifications to the USEPA's Community Multiscale Air Quality (CMAQ) model. The peak pollen emission predictions were within a day of peak pollen counts measured, thus corroborating independent model verification. Furthermore, the peak predicted pollen concentration estimates were within two days of the peak measured pollen counts, thus providing independent corroboration. The models for emissions and dispersion allow data-independent estimation of pollen levels, and provide an important component in assessing exposures of populations to pollen, especially under different climate change scenarios. |
