Use of AERMOD to Determine a Hydrogen Sulfide Emission Factor for Swine Operations by Inverse Modeling

This study was conducted to determine both optimal settings applied to the plume dispersion model, AERMOD, and a scalable emission factor for accurately determining the spatial distribution of hydrogen sulfide concentrations in the vicinity of swine concentrated animal feeding operations (CAFOs). These operations emit hydrogen sulfide from both housing structures and waste lagoons. With ambient measurements made at 4 stations within 1 km of large swine CAFOs in Iowa, an inverse-modeling approach applied to AERMOD was used to determine hydrogen sulfide emission rates. CAFO buildings were treated as volume sources whereas nearby lagoons were modeled as area sources. The robust highest concentration (RHC), calculated for both measured and modeled concentrations, was used as the metric for adjusting the emission rate until the ratio of the two RHC levels was unity. Utilizing this approach, an average emission flux rate of 0.57 μg/m(2)-s was determined for swine CAFO lagoons. Using the average total animal weight (kg) of each CAFO, an average emission factor of 6.06 × 10(-7) μg/yr-m(2)-kg was calculated. From studies that measured either building or lagoon emission flux rates, building fluxes, on a floor area basis, were considered equal to lagoon flux rates. The emission factor was applied to all CAFOs surrounding the original 4 sites and surrounding an additional 6 sites in Iowa, producing an average modeled-to-measured RHC ratio of 1.24. When the emission factor was applied to AERMOD to simulate the spatial distribution of hydrogen sulfide around a hypothetical large swine CAFO (1M kg), concentrations 0.5 km from the CAFO were 35 ppb and dropped to 2 ppb within 6 km of the CAFO. These values compare to a level of 30 ppb that has been determined by the State of Iowa as a threshold level for ambient hydrogen sulfide levels.     

Surface acoustic wave (SAW) microsensor array for measuring VOCs in drinking water

Exposure to volatile organic chemicals (VOCs) in drinking water has been linked to a number of adverse health effects including cancer, liver, and kidney damage. However, the large number of potential contaminants and the cost and complexity of existing analytical methods limits the extent to which water quality is routinely characterized. This project focused on the laboratory development and evaluation of an instrument for field analysis of VOCs in drinking water. The instrument is based on an array of six polymer-coated surface-acoustic-wave microsensors. A test-set consisting of dichloromethane, chloroform, 1,1,1-trichloroethane, perchloroethylene, and m-xylene was used in a series of experiments designed to optimize the purge-trap preconcentration system, calibrate the instrument over the concentration range of 0.2-2 times the USEPA maximum contaminant levels (MCLs), and compare results to those of a reference laboratory. The primary goal was to develop a cost-effective alternative for on-site evaluation of VOCs in water. Calibration and evaluation test results for spiked water samples demonstrate adequate sensitivity for 19 of the 21 regulated VOCs considered using a ten minute sampling and analysis cycle. Monte Carlo simulations characterized the performance of trained artificial neural networks (ANNs) which had correct classification rates of 99%, 90%, and 80% for the five individual test-set vapors and their binary and ternary mixtures, respectively. These results demonstrate the excellent potential of this technology for addressing the need for improved VOC field-screening methods for water supplies.     

A MATHEMATICAL MODEL FOR EVALUATING THE POTENTIAL OF DESALTING1

ABSTRACT The Office of Saline Water, which has federal responsibility for developing low-cost, saline sources of fresh water, has recognized the need for an improved method of forecasting the future potential of desalting in this country. The magnitude of the role of desalting will influence the plans of federal, state, and local water resource agencies and the research and development programs of manufacturers. A dynamic simulation model has been developed by Arthur D. Little, Inc. under contract by OSW to translate relevant factors of water supply and demand into a forecast of desalting potential. The model projects the needs for desalting in 20 hydrologic regions of the U.S. Model performance has thus far been demonstrated by the development of a forecast and a battery of related sensitivity tests. Current results indicate the following potential desalting capacities: 225 MGD in 1980; 2,250 MGD in 2000; and 7,000 MGD in 2020. Significant improvements in desalting economics promise to increase these potentials by a factor of four or five by 2000-2020. Model inputs and results are continuing to be refined. When completed, OSW will have a dynamic tool with which to guide its R&D program.