|dc.description.abstract||Biosolids applied to agricultural land may upset neighboring communities due to the inherent malodorous smell of biosolids. The problem of the odor becomes a major concern in the wastewater treatment industry when community responses could vary from complaints to legal action to ban or reduce biosolids recycling through land.
Unlike odor at a wastewater treatment facility, which is produced from the characteristics of wastewater itself and from individual unit processes, land-applied biosolids odor depends not only on the quality of biosolids, but also on the biosolids emissions levels, unfavorable weather conditions and topographic characteristics, and variation of human perception. Those factors increase the complexity of nuisance odor at land application sites.
This dissertation aims to assess biosolids emission impacts on surrounding communities by estimating the level of biosolids odor emissions, simulating odor dispersion, and quantifying human perception to biosolids odor.
Odor emission rates at land-applied biosolids fields were estimated using three different approaches: assumed flow rate, statistical inference, and simulated-flux chamber. The estimated emission rates were used as an input to dispersion models. The U.S. Environmental Protection Agency Regulatory Models, both screening and refined models, were used to simulate dispersion of biosolids odor at land application sites. A Geographic Information System (GIS) was employed to support modeling steps and to create maps. Appraisal of odor perception by receptors was assessed by use of Steven's psychophysics power law.
The District of Columbia Water and Sewer Authority (DCWASA) land application fields in Virginia were used as case studies. More specifically, 45 fields in Albemarle and Orange Counties were focused on. Concentration prediction maps along with probability maps were created to support visualization and provide information on potential odor impacts to communities. Possible human perceptions were expressed in Intensity maps. The methods and results described in this dissertation can support decision makers in selecting appropriate land application sites prior distributing biosolids to reduce adverse effects from land-applied biosolids.||en_US