Hydrogen sulfide, sulphide, odor, odour, buffering distance, aermod, construction and demolition landfills, c and d, c & d, dispersion modeling
Emissions of hydrogen sulfide (H2S) from construction and demolition (C & D) landfills can result in odors that are a significant nuisance to nearby neighborhoods and businesses. As Florida’s population continues to grow and create development pressures, housing is built closer to existing landfills. Additionally, new landfills will be created in the future. This research project was undertaken to develop a detailed modeling methodology for use by counties and other landfill owners to provide them with an objective and scientifically defensible means to establish odor buffer zones around C & D landfills. A technique for estimating methane (and odorous gas) emissions from municipal solid waste (MSW) landfills was recently developed by researchers at the University of Central Florida. This technique was based on measuring hundreds of ambient methane concentrations near the surface of the landfill, and combining that data with matrix inversion mathematics to back-solve the dispersion equations. The technique was fully documented in two peer-reviewed journal articles. This project extends that methodology. In this work the author measured ambient H2S concentrations at various locations in a C & D landfill, and applied those same matrix inversion techniques to determine the H2S emission rates from the landfill. The emission rates were then input into the AERMOD dispersion model to determine H2S odor buffer distances around the landfill. Three sampling trips to one C & D landfill were undertaken, data were taken, and the modeling techniques were applied. One problem encountered was that H2S emissions from C & D landfills are typically about 1000 times smaller than methane emissions (from MSW landfills). Thus, H2S iv ambient concentrations often are near the detection limits of the instruments, and the data may not be as reliable. However, this approach could be used for any particular C & D landfill if the appropriate amount of data were available to characterize its emissions with some certainty. The graphical tool developed in this work shows isopleths of "H2S" concentrations at various distances, and color codes the isopleths into a "green-yellow-red" scheme (analogous to a traffic signal) that depicts zones where private landowners likely will not detect odors, where they may experience some odors, or where they likely will experience odors. The "likelihood" can be quantified by selecting the Nth highest hourly concentrations in one year to form the plot. In this study, N was conservatively selected as 8. Requiring that concentrations be at or below the 8 th highest concentration in a year corresponds to a 99.9% probability of not exceeding that concentration at that distance in any future year. The graphical tool can be applied to any C & D landfill but each landfill is different. So this technique depends on having a fairly good estimate of the rate of emissions of H2S from the landfill in question, and at least one year’s worth of hourly meteorological data (wind speed, direction, and stability class) that is representative of the landfill location. The meteorological data can be obtained with relative ease for most locations in Florida; however, the emission data must be obtained from on-site measurements for any given landfill.
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Cooper, C. David
Master of Science in Environmental Engineering (M.S.Env.E.)
College of Engineering and Computer Science
Civil, Environmental, and Construction Engineering
Length of Campus-only Access
Masters Thesis (Open Access)
Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic
Bolyard, Steven Jeffrey, "Monitoring And Modeling To Estimate Hydrogen Sulfide Emissions And Dispersion From Florida Construction And Demolition Landfills To Construct Odor Buffering Distances" (2012). Electronic Theses and Dissertations, 2004-2019. 2099.