A major source of airborne pollution in the arid Middle East countries is the fugitive particulate matter (PM), a frequent product of wind erosion. The meteorological conditions and topography of this region makes it highly susceptible to wind-blown particles which raise many air quality concerns. Important tools for estimating the dispersion and deposition of dust particles, which also help in designing dust control procedures, are Air Quality Models (AQM). The cornerstone of every AQM system is an emission inventory, but these are only available currently for the European and North American domains, calling for an immediate need to develop similar knowledge for MEA. The increasing level of urbanization in Middle East countries has thrown the light on the airborne pollution caused by construction and earth work activities. The main scope of the present study is to develop fugitive particulate matter emission factors for construction sites in MEA and to evaluate the accuracy of the existing emission factors to apply for Middle Eastern hot and arid conditions. An experimental campaign along with dispersion modeling using the Fugitive Dust Model (FDM) were implemented in a construction site to examine the relation between the meteorological variables, concentrations and emission rates to understand the behavior of the fugitive dust emissions for MEA. The time period of this work was chosen while the construction site was at rest, where the only particles source was wind erosion of the loose soil. A data analysis was done, using the modeling results, to identify the effect of each meteorological variable (i.e. wind direction, wind speed, stability, .etc.) and its relation to emissions concentrations and rates. Considering the wind-speed dependence of the source emission rate, a power law function was obtained for the calculation of the emission rates. This function was used to re-run the FDM model and the results were evaluated compared to the on-site measured concentrations and to the emission factors reported in USEPA's AP-42 (the related emission rates in this emission inventory have been developed mainly for open coal-mines). Surprisingly, our study showed that a very good agreement between the AP-42 emission factors and our calculations can be obtained if the former are slightly modified. The emission factors developed in this study have been confirmed and can be applied for the impact assessment of similar sources in Middle East and other dry-arid locations. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155039

Dust storms are frequent phenomena in the southwestern United Sates. Dust source areas in the region are often (partly) crusted. A critical prerequisite for dust aerosol modeling is an accurate representation of dust emission. While several dust emission schemes have been developed over the last decades, their applicability for crusted surfaces is not well tested. In this study, we aimed to improve the representation of magnitude, frequency, and PSD of dust emission flux from crusted surfaces. We test the applicability of Shao (2004) size-resolved dust emission scheme (S04), which estimates dust emission based on the soil volume removed by saltation particle impacts, to model PM10 dust emission from a crusted surface in New Mexico, USA, for three dust events in spring 2016. Detailed field data are available for these events which are used as scheme input (surface crust and vegetation fraction, friction velocity, minimally- and fully-dispersed particle-size distributions) and for evaluation (saltation flux and dust emission flux). Results show that the saltation flux modeled with the scheme of White (1979) was overestimated by three orders of magnitude. This is expected as the supply of particles available for saltation is limited at the site, while the model assumes an unlimited supply of saltators. As our focus is on dust emission, a constant scaling factor was applied to match modeled and observed saltation fluxes. Parameters that describe the efficiency of saltator impacts to emit dust and the degree of dispersion during erosion need to be adapted in the S04 scheme to represent the soil surface setting at the study site. Our results show that changing those parameters has little effect on the modeled dust emission and dust emission is generally underestimated when PSDs of the top ~1 cm soil layer are used as is common. The reason for this is that the crust at the site is relatively thin and the soil overall sandy, which results in only a small difference between the minimally- and fully-dispersed PSDs of parent soil. If, however, the minimally- and fully-dispersed PSDs are replaced with the PSDs of, respectively, loose erodible material and crust, then the differences increase and the scheme parameters can be well adapted to give accurate estimates of dust emission. Our tests show that the SO4 scheme is able to more accurately estimate dust emission from a crusted surface provided that sufficient input information is provided. Future research is required to investigate the parameter variability for different crusted surfaces.

Emission factors (EFs) and results from dispersion models are key components in the air pollution regulatory process. The EPA preferred regulatory model changed from ISCST3 to AERMOD in November, 2007. Emission factors are used in conjunction with dispersion models to predict 24-hour concentrations that are compared to National Ambient Air Quality Standards (NAAQS) for determining the required control systems in permitting sources. This change in regulatory models has had an impact on the regulatory process and the industries regulated. In this study, EFs were developed for regulated particulate matter PM10 and PM2.5 from cotton harvesting. Measured concentrations of TSP and PM10 along with meteorological data were used in conjunction with the dispersion models ISCST3 and AERMOD, to determine the emission fluxes from cotton harvesting. The goal of this research was to document differences in emission factors as a consequence of the models used. The PM10 EFs developed for two-row and six-row pickers were 154 + 43 kg/km2 and 425 + 178 kg/km2, respectively. From the comparison between AERMOD and ISCST3, it was observed that AERMOD EFs were 1.8 times higher than ISCST3 EFs for Emission factors (EFs) and results from dispersion models are key components in the air pollution regulatory process. The EPA preferred regulatory model changed from ISCST3 to AERMOD in November, 2007. Emission factors are used in conjunction with dispersion models to predict 24-hour concentrations that are compared to National Ambient Air Quality Standards (NAAQS) for determining the required control systems in permitting sources. This change in regulatory models has had an impact on the regulatory process and the industries regulated. In this study, EFs were developed for regulated particulate matter PM10 and PM2.5 from cotton harvesting. Measured concentrations of TSP and PM10 along with meteorological data were used in conjunction with the dispersion models ISCST3 and AERMOD, to determine the emission fluxes from cotton harvesting. The goal of this research was to document differences in emission factors as a consequence of the models used. The PM10 EFs developed for two-row and six-row pickers were 154 + 43 kg/km2 and 425 + 178 kg/km2, respectively. From the comparison between AERMOD and ISCST3, it was observed that AERMOD EFs were 1.8 times higher than ISCST3 EFs for absence of solar radiation. Using AERMOD predictions of pollutant concentrations off property for regulatory purposes will likely affect a source's ability to comply with limits set forth by State Air Pollution Regulatory Agencies (SAPRAs) and could lead to inappropriate regulation of the source.