Guidance for the Field Demonstration of Remediation Technologies

This paper will focus on the demonstration of hazardous waste cleanup technologies in the field. The technologies will be at the pilot- or full-scale, and further referred to as field-scale. The main objectives of demonstration at the field-scale are development of reliable performance and cost data. Technology demonstrations provide performance, cost effectiveness, and reliability data so that potential technology users have sufficient information to make effective decisions as to the applicability of the technology to a specific situation. The demonstration and evaluation of a technology should be conducted with the purpose of characterizing performance, need for pre- and post-processing of the waste feed, identification of waste type and constituents applicable to the technology, system throughput, problems and limitations of the technology, and operating and maintenance costs. Table I provides a summary of remediation activities for demonstration projects.     

The Potential of Pulse-Jet Baghouses for Utility Boilers. Part 2: Performance of Pulse-Jet Fabric Filter Pilot Plants

Pulse-jet fabric filters (PJFFs) are widely used in U.S. industrial boiler applications and in utility and industrial boilers abroad. Their small size and reduced cost relative to more conventional reverse-gas baghouses makes the use of PJFFs appear to be an attractive particulate control option for utility boilers. This paper (Part 2 of a three-part series) summarizes the results of pilot PJFF studies sponsored by the Electric Power Research Institute at different utility sites in the United States. The purpose of these tests is to evaluate PJFF performance for U.S. fossil-fuel-fired applications. These data are also used to corroborate the results of a recent worldwide survey of PJFF user experience, as described in Part 1 of this series. Part 3 will provide a cost comparison of PJFFs to other particulate control options such as electrostatic precipitators and reverse-gas baghouses.     

Seasonal Variations in Aerosol Composition and Acidity at Shenandoah and Great Smoky Mountains National Parks

The concentration of elements Na through Pb, select ions, and organic carbon from fine (<2.5 µm) particles has been monitored at Shenandoah and Great Smoky Mountains National Parks from 1988 through 1995. The data obtained from 1988 through 1994 show that significant changes in the concentrations of many aerosol constituents occur on a seasonal basis. Particulate sulfate and organic carbon are shown to exhibit substantially higher concentrations during the summer, while sulfur dioxide and nitrate concentrations are highest during the winter.

A method for estimating the degree of neutralization of particulate sulfate is given. This method uses routinely measured aerosol elemental compositions because ammonium ion, the primary neutralizing species for sulfate, is not measured on a routine basis. Application of this method to the selected data set shows that sulfate aerosol is most acidic during summer with an average molar H_s (moles of hydrogen associated with sulfur) to S (moles of sulfur) ratio of approximately 4. This suggests the average sulfate particle during the summer has a molar coon slightly more acidic than ammonium bisulfate (NH₄HSO₄) which has a molar hydrogen to sulfur ratio of 5. Winter H_s to S ratios, however, are approximately 8, suggesting the aerosol is on average fully neutralized ammonium sulfate [(NH₄)₂SO₄].     

Receptor Modeling Applied to Patterns in Space (RMAPS)Part III–Apportionment of Airborne Particulate Sulfur in Western Washington State

Abstract

Data obtained from 24 of the 31 sites of the Pacific Northwest Regional Visibility Experiment Using Natural Tracers (PREVENT) study were analyzed by the Receptor Model Applied to Patterns in Space (RMAPS) multivariate receptor model. Four spatial patterns were found and interpreted as showing the effect of the coal-fired power plant in Centralia, WA; transport from the northwest; the Se-attle-Tacoma urban area; and transport from the southeast. In Mt. Rainier National Park, up to one-third of the sulfate can be attributed to the Centralia power plant. In the North Cascades National Park, 65-82% of the sulfur is accounted for by transport from Canada. The model was applied separately to sites in the northern and southern sections of the study area. The southern sites were affected only by the Centralia, urban, and southeast transport sources; the northern sites were affected only by the northwest transport, urban, and southeast transport sources. This gave two independent estimates of the normalized source contributions of the urban and southeast transport factors, which had a correlation coefficient of more than 0.90.     

Comparison of Computer Simulations of Total Lung Deposition to Human Subject Data in Healthy Test Subjects

ABSTRACT

A mathematical model was used to predict the deposition fractions (DF) of PM within human lungs. Simulations using this computer model were previously validated with human subject data and were used as a control case. Human intersubject variation was accounted for by scaling the base lung morphology dimensions based on measured functional residual capacity (FRC) values. Simulations were performed for both controlled breathing (tidal volumes [V_T] of 500 and 1000 mL, respiratory times [T] from 2 to 8 sec) and spontaneous breathing conditions. Particle sizes ranged from 1 to 5 um. The deposition predicted from the computer model compared favorably with the experimental data. For example, when V_T = 1000 mL and T = 2 sec, the error was 1.5%. The errors were slightly higher for smaller tidal volumes. Because the computer model is deterministic (i.e., derived from first principles of physics), the model can be used to predict deposition fractions for a range of situations (i.e., for different ventilatory parameters and particle sizes) for which data are not available. Now that the model has been validated, it may be applied to risk assessment efforts to estimate the inhalation hazards of airborne pollutants.     

Characterization of Fine Particulate Matter Produced by Combustion of Residual Fuel Oil

ABSTRACT

Combustion experiments were carried out on four different residual fuel oils in a 732-kW boiler. PM emission samples were separated aerodynamically by a cyclone into fractions that were nominally less than and greater than 2.5 |j.m in diameter. However, examination of several of the samples by computer-controlled scanning electron microscopy (CCSEM) revealed that part of the PM_2.5 fraction consists of carbonaceous cenospheres and vesicular particles that range up to 10 |j.m in diameter. X-ray absorption fine structure (XAFS) spectroscopy data were obtained at the S, V, Ni, Fe, Cu, Zn, and As K-edges and at the Pb L-edge. Deconvolution of the X-ray absorption near edge structure (XANES) region of the S spectra established that the dominant molecular forms of S present were sulfate (26-84% of total S) and thiophene (13-39% of total S). Sulfate was greater in the PM_2.5 samples than in the PM₂₅₊ samples. Inorganic sulfides and elemental sulfur were present in lower percentages. The Ni XANES spectra from all of the samples agreed fairly well with that of NiSO₄, while most of the V spectra closely resembled that of vanadyl sulfate (VO?SO₄?xH₂O). The other metals investigated (i.e., Fe, Cu, Zn, and Pb) also were present predominantly as sulfates. Arsenic was present as an arsen-ate (As⁺⁵). X-ray diffraction patterns of the PM_2.5 fraction exhibit sharp lines due to sulfate compounds (Zn, V, Ni, Ca, etc.) superimposed on broad peaks due to amorphous carbons. All of the samples contain a significant organic component, with the loss on ignition (LOI) ranging from 64 to 87% for the PM_2.5 fraction and from 88 to 97% for the PM_2.5+ fraction. Based on ¹³C nuclear magnetic resonance (NMR) analysis, the carbon is predominantly condensed in graphitic structures. Aliphatic structure was detected in only one of seven samples examined.     

Polyfunctional Plants for Industrial Waste Disposal—Part II: Economics and Model Evaluation

ABSTRACT

This is the second part of a two-part paper dealing with the preliminary design and costing of polyfunctional waste treatment plants. In this article, we present some criteria for estimating capital investment and annual operating costs of polyfunctional plants for industrial waste treatment. The process and equipment design methods presented in Part I of this article, together with the economic approach proposed here, allow for complete technical/economic analyses. The overall mathematical model appears to be a useful tool in economic feasibility studies. The accuracy of the developed computer mathematical model has been demonstrated, referring to actual cost data from the literature.     

Cost-Effectiveness Analysis of Waste Gas Treatment Plants for the Glass Industry

ABSTRACT

Cost-effectiveness of different plant solutions for glass furnace waste gas cleaning is compared in the present paper. Plant arrangements based on electrostatic precipi-tator or fabric filter dust collectors and wet, semi-dry, or dry processes for acid gas removal have been considered. A critical survey of each solution's advantages and disadvantages has been presented, taking into account both effectiveness and costs resulting from each available system. Finally, a quantitative assessment has been provided with reference to a case study involving actual float glass production lines at SIV plants located in northern and central Italy.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.