An Overview of EPA’s Quality Assurance Program

Quality Assurance has been defined in many different ways to express concern for the “quality” of the output of some operation or function. For the purpose of this presentation, quality assurance is defined as the sum of those activities within an environmental monitoring or measurement program which are primarily for the purpose of documenting the precision, accuracy, representativeness, and completeness of the data that are produced. Further, we view quality assurance as a management tool which encompasses both administrative and technical functions which generally fall into three categories: (1) Prevention which includes those activities carried out prior to the proper placement and operation of the measurement system; (2) Evaluation which includes the continuous overview and checks on the performance of the systems and operators; and (3) Correction which includes changes made to improve or stabilize the capability and performance of the system.     

Heavy Duty Diesel Particulate Emission Factors

For the past several years, EPA has been measuring particulate emissions from a variety of heavy-duty diesel engines through contracts with Southwest Research Institute. Particulate emissions samples have been collected using an exhaust splitter to divert a fraction of the engine exhaust into a standard dilution tunnel. A small fraction of the diluted exhaust from the tunnel is pulled through a filter from which particulate mass and, in some cases, organic content of the particulate is determined. This paper discusses the sampling system and gives particulate emission factors that have been computed from truck and bus fuel consumption data as well as average truck and bus speed data from New York and Los Angeles (freeway and nonfreeway usage). Average particulate emission test results (steady state tests) for 2-stroke engines were 4.74 g/kg fuel and for 4-stroke engines were 2.64 g/kg fuel. Using average particulate emissions results, a particulate emission factor range of 0.8 to 1.3 g/km was computed. Nationwide diesel particulate emissions were calculated to be 88,000 metric tons per year.     

R&D Activities,Operating Experience Discussed at Fabric Alternatives Forum

ABSTRACT

Previously reported volatile organic compounds (VOC) radiocarbon (¹⁴C) measurements for 1992 summertime Atlanta, GA, have been compared with chromatographic data and emissions inventory predictions. The chromatographic approach that was used provided a more comprehensive VOC characterization than typically achieved, and the emissions inventory was research-grade level (date-, site-, and time-specific). The comparisons are in general agreement that biogenic emissions contribute only modestly (<10%) to the VOC content of the particular ambient samples that were collected and measured. The choices of sampling site (near city-center) and times (early morning and late evening) are major influences on the results, which consequently should not be regarded as representing the average VOC biogenic impact for the Atlanta area.     

Blast Furnace Casthouse Control Technology and Recent Emissions Test Data

By the fall of 1980, three new and seven retrofit casthouse emission control systems had been installed in North America. A number of prototype systems are being evaluated by steel companies and regulatory agencies. By 1981, the U.S. steel industry had made commitments to install controls on at least 58 additional casthouses in the U.S.

This paper describes the current status of casthouse control technology in the U.S. and Canada as of the spring of 1981, addresses future trends, and presents emissions test data collected in 1980 and 1981. Mass emissions and inhalable particulate test results from sampling at DOFASCO’s No. 3 blast furnace casthouse are presented. Roof monitor visible emissions data are also provided to describe performance of installed and demonstration systems including three J&L plants, Wheeling-Pittsburgh and Bethlehem Steel, and Inland’s new furnace.     

A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

Rotary Kiln Incineration III. An Indepth Study—Kiln Exit/Afterburner/Stack Train and Kiln Exit Pattern Factor Measurements During Liquid CCl4 Processing

Temperature and stable species concentration data are presented from various locations within a full-scale rotary kiln incinerator firing natural gas/carbon tetrachloride/air. The data are being collected as part of a cooperative program involving university, industry and government participation. The overall goal of the program is to develop a more sophisticated understanding of and a predictive capability for rotary kiln and afterburner performance as influenced by basic design and operational parameters. Non-uniformities in stable species and temperature exist for this particular kiln, at the kiln exit, under certain operating conditions. Flow perturbations from within the kiln were found to persist into the afterburner, but not into the stack. High destruction and removal efficiencies (DRE’s) were achieved under the operating conditions of these tests through adequate secondary combustion processing.     

Rotary Kiln Incineration IV. An Indepth Study— Kiln Exit,Transition and Afterburner Sampling During Liquid CCl4 Processing

Detailed temperature and stable species concentration data are presented from the kiln exit, transition section and afterburner of a full-scale incinerator facility firing natural gas/carbon tetrachloride/air. The data are collected as part of a cooperative program involving university, industry and government participation. The overall goal of the program is to develop an understanding and predictive capability for rotary kiln and afterburner performance as influenced by basic design and operational parameters. The data demonstrate that nonuniformities in stable species and temperature exist, under certain operating conditions, at the kiln exit in the vertical direction only. Measurements from the transition section indicate that non-uniformities may exist within this region under certain operating conditions. Flow perturbations from within the kiln can persist into the afterburner, although the degree of nonuniformity is substantially reduced compared to either the kiln or transition sections. High destruction and removal efficiencies were achieved under all operating conditions of these tests through a combination of kiln and secondary combustion processing.     

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.     

Second generation anticoagulant rodenticides in predatory birds: Probabilistic characterisation of toxic liver concentrations and implications for predatory bird populations in Canada

Second-generation anticoagulant rodenticides (SGARs) are widely used to control rodent pests but exposure and poisonings occur in non-target species, such as birds of prey. Liver residues are often analysed to detect exposure in birds found dead but their use to assess toxicity of SGARs is problematic. We analysed published data on hepatic rodenticide residues and associated symptoms of anticoagulant poisoning from 270 birds of prey using logistic regression to estimate the probability of toxicosis associated with different liver SGAR residues. We also evaluated exposure to SGARs on a national level in Canada by analysing 196 livers from great horned owls (Bubo virginianus) and red-tailed hawks (Buteo jamaicensis) found dead at locations across the country. Analysis of a broader sample of raptor species from Quebec also helped define the taxonomic breadth of contamination. Calculated probability curves suggest significant species differences in sensitivity to SGARs and significant likelihood of toxicosis below previously suggested concentrations of concern (<0.1mg/kg). Analysis of birds from Quebec showed that a broad range of raptor species are exposed to SGARs, indicating that generalised terrestrial food chains could be contaminated in the vicinity of the sampled areas. Of the two species for which we had samples from across Canada, great horned owls are exposed to SGARs to a greater extent than red-tailed hawks and the liver residue levels were also higher. Using our probability estimates of effect, we estimate that a minimum of 11% of the sampled great horned owl population is at risk of being directly killed by SGARs. This is the first time the potential mortality impact of SGARs on a raptor population has been estimated.     

Quantifying summed fullerene nC60 and related transformation products in water using LC LTQ Orbitrap MS and application to environmental samples

The application of engineered nanomaterials increases strongly. Development of analytical techniques and their application to environmental samples is essential for human and environmental risk assessment of the nanoparticles. The objective of this study was to develop a sensitive analytical method to quantify nC(60) in water, using accurate mass screening liquid chromatography-hybrid linear ion trap Orbitrap mass spectrometry. nC(60) can be transformed by oxidation, reduction and photochemical reaction. Therefore, the formation of some transformation products of nC(60) was studied as well. Finally, the developed analytical method was applied to surface water samples from several locations in the Netherlands. The developed method enabled to detect and quantify aqueous concentrations of the summed nC(60) and its transformation products as low as 5 ng/L. It was observed that nC(60) transformation products exceed quantities of the parent C(60). Despite the high sensitivity of the developed method, no nC(60) or transformation products were detected in an array of Dutch surface waters. This might be due to low emissions, losses in the aqueous phase by sedimentation, sorption or further transformation processes.