Aerosol Research and Inhalation Epidemiological Study (ARIES): Air Quality and Daily Mortality Statistical Modeling— Interim Results

ABSTRACT

The Aerosol Research and Inhalation Epidemiological Study (ARIES) is an EPRI-sponsored project to collect air quality and meteorological data at a single site in northwestern Atlanta, GA. Seventy high-resolution air quality indicators (AQIs) are used to examine statistical relationships between air quality and health outcome end points. Contemporaneous mortality data are collected for Fulton and DeKalb counties in Georgia. Currently, 12 months of air quality and weather data are available for analysis, from August 1998 through July 1999.

The interim mortality analysis used Poisson regression in generalized additive models (GAMs). The estimated log-linear association of mortality with various AQIs was adjusted for smoothed functions of time and meteorological data. The analysis considered daily deaths due to all nonaccidental causes, deaths to persons 65 years or older, and deaths in each of the two constituent counties. The fine particle effect associated with the four mortality subgroups, using only today (lag 0), yesterday (lag 1), 2-day average (average of today and yesterday), and first difference (today minus yesterday) measurements of the air quality relative to today's number of deaths was positive for lag 0, lag 1, and 2-day average and positive only for decedents at least 65 years of age using first difference. The t values ranged from 0.81 to 1.15 for lag 0, 1.04 to 1.53 for lag 1, 1.10 to 1.66 for 2-day average, and -0.32 to 0.33 for first difference with 346 or 347 days of data. No statistically significant estimate of the linear coefficient was found for the other 14 air quality variables in our interim analysis for the four mortality subgroups. We discuss diagnostics to support these models.

These interim analyses did not include an evaluation of sensitivity to a larger set of lag structures, nonlinear model specifications, multipollutant analyses, alternative weather model and smoothing model specifications, air pollution imputation schemes, or cause-specific mortality indicators, nor did they include a full reporting of model selection or goodness-of-fit indicators. No conclusion can be drawn at this time about whether the findings from subsequent studies have sufficiently greater power to detect effects comparable to those found in other U.S. cities including at least 2 or 3 years of data.     

Biological Removal of Gaseous Ammonia in Biofilters: Space Travel and Earth-Based Applications

ABSTRACT

Gaseous NH₃ removal was studied in laboratory-scale biofilters (14-L reactor volume) containing perlite inoculated with a nitrifying enrichment culture. These biofilters received 6 L/min of airflow with inlet NH₃ concentrations of 20 or 50 ppm, and removed more than 99.99% of the NH₃ for the period of operation (101, 102 days). Comparison between an active reactor and an autoclaved control indicated that NH₃ removal resulted from nitrification directly, as well as from enhanced absorption resulting from acidity produced by nitrification. Spatial distribution studies (20 ppm only) after 8 days of operation showed that nearly 95% of the NH₃ could be accounted for in the lower 25% of the biofilter matrix, proximate to the port of entry. Periodic analysis of the biofilter material (20 and 50 ppm) showed accumulation of the nitrification product NO₃ ^- early in the operation, but later both NO₂ ^- and NO₃ ^- accumulated. Additionally, the N-mass balance accountability dropped from near 100% early in the experiments to ~95 and 75% for the 20- and 50-ppm biofilters, respectively. A partial contributing factor to this drop in mass balance accountability was the production of NO and N₂O, which were detected in the biofilter exhaust.     

Seasonal Variability in CH4 Emissions from a Landfill in a Cool,Semiarid Climate

ABSTRACT

Methane exchange with the atmosphere was measured during three seasons at the Rooney Road landfill in Jefferson County, CO. Substantial spatial and temporal variability in exchange rates were observed. Mean fluxes to the atmosphere were 534, 1290, and 538 mg CH₄/m²/day, respectively, in the fall of 1994, winter of 1994–1995, and summer of 1995. Median fluxes were 12.42, 8.62, and 5.65 mg CH₄/m²/day, respectively, during those seasons. Forty-three of 177 measurements had small negative fluxes, suggesting methanotrophic activity in the landfill cover soils. Despite probable methanotrophic activity in cover soils, landfills without gas collection systems may emit substantial CH₄ to the atmosphere, with large spatial and seasonal variability.     

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.     

The 1999 Fresno Particulate Matter Exposure Studies: Comparison of Community,Outdoor, and Residential PM Mass Measurements

ABSTRACT

Two collaborative studies have been conducted by the U.S. Environmental Protection Agency (EPA) National Exposure Research Laboratory (NERL) and National Health and Environmental Effects Research Laboratory to determine personal exposures and physiological responses to par-ticulate matter (PM) of elderly persons living in a retirement facility in Fresno, CA. Measurements of PM and other criteria air pollutants were made inside selected individual residences within the retirement facility and at a central outdoor site on the premises. In addition, personal PM exposure monitoring was conducted for a subset of the participants, and ambient PM monitoring data were available for comparison from the NERL PM research monitoring platform in central Fresno. Both a winter (February 1-28, 1999) and a spring (April 19-May 16, 1999) study were completed so that seasonal effects could be     

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.     

Statistical Considerations in Determining the Health Significance of Constituents of Airborne Particulate Matter

ABSTRACT

Because of the U.S. Environmental Protection Agency’s (EPA) new ambient air quality standard for fine particles, the need is likely to continue for more detailed scientific investigation of various types of particles and their effects on human health. Epidemiology studies have become the method of choice for investigating health responses to such particles and to other air pollutants in community settings. Health effects have been associated with virtually all of the gaseous criteria pollutants and with the major constituents of airborne particulate matter (PM), including all size fractions less than about 20 gm, inorganic ions, carbonaceous particles, metals, crustal material, and biological aerosols. In many of the more recent studies, multiple pollutants or agents (including weather variables) have been significantly associated with health responses, and various methods have been used to suggest which ones might be the most important. In an ideal situation, classical least-squares regression methods are capable of performing this task. However, in the real world, where most of the pollutants are correlated with one another and have varying degrees of measurement precision and accuracy, such regression results can be misleading. This paper presents some guidelines for dealing with such collinearity and model comparison problems in both single- and multiple-pollutant regressions. These techniques rely on mean effect (attributable risk) rather than statistical significance per se as the preferred indicator of importance for the pollution variables.     

Electricity from Fossil Fuels without CO2 Emissions: Assessing the Costs of Carbon Dioxide Capture and Sequestration in U.S. Electricity Markets

ABSTRACT

The decoupling of fossil-fueled electricity production from atmospheric CO₂ emissions via CO₂ capture and sequestration (CCS) is increasingly regarded as an important means of mitigating climate change at a reasonable cost. Engineering analyses of CO₂ mitigation typically compare the cost of electricity for a base generation technology to that for a similar plant with CO₂ capture and then compute the carbon emissions mitigated per unit of cost. It can be hard to interpret mitigation cost estimates from this plant-level approach when a consistent base technology cannot be identified. In addition, neither engineering analyses nor general equilibrium models can capture the economics of plant dispatch. A realistic assessment of the costs of carbon sequestration as an emissions abatement strategy in the electric sector therefore requires a systems-level analysis. We discuss various frameworks for computing mitigation costs and introduce a simplified model of electric sector planning. Results from a “bottom-up” engineering-economic analysis for a representative U.S. North American Electric Reliability Council (NERC) region illustrate how the penetration of CCS technologies and the dispatch of generating units vary with the price of carbon emissions and thereby determine the relationship between mitigation cost and emissions reduction.     

Identification of Selected Hormonally Active Agents and Animal Mammary Carcinogens in Commercial and Residential Air and Dust Samples

ABSTRACT

In order to characterize typical indoor exposures to chemicals of interest for research on breast cancer and other hormonally mediated health outcomes, methods were developed to analyze air and dust for target compounds that have been identified as animal mammary carcinogens or hormonally active agents and that are used in commercial or consumer products or building materials. These methods were applied to a small number of residential and commercial environments to begin to characterize the extent of exposure to these classes of compounds. Phenolic compounds, including nonylphenol, octylphenol, bisphenol A, and the methoxychlor metabolite 2,2-bis (p-hydroxyphenyl)-1,1,1-trichloroethane (HPTE), were extracted, derivatized, and analyzed by gas chromatography/mass spectrometry (GC/MS)–selective ion monitoring (SIM). Selected phthalates, pesticides, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) were extracted and analyzed by GC/MS-SIM. Residential and workplace samples showed detectable levels of twelve pesticides in dust and seven in air samples. Phthalates were abundant in dust (0.3524 μg/g) and air (0.005-2.8 μg/m³). Nonylphenol and its mono- and di-ethoxylates were prevalent in dust (0.82-14 μg/g) along with estrogenic phenols such as bisphenol A and o-phenyl phenol. In this 7-sample pilot study, 33 of 86 target compounds were detected in dust, and 24 of 57 target compounds were detected in air. In a single sample from one home, 27 of the target compounds were detected in dust and 15 in air, providing an indication of chemical mixtures to which humans are typically exposed.     

Investigation of the Potential Antimicrobial Efficacy of Sealants Used in HVAC Systems

ABSTRACT

Recent experiments confirm field experience that duct cleaning alone may not provide adequate protection from regrowth of fungal contamination on fiberglass duct liner (FGDL). Current recommendations for remediation of fungally contaminated fiberglass duct materials specify complete removal of the materials. But removal of contaminated materials can be extremely expensive. Therefore, a common practice in the duct-cleaning industry is the postcleaning use of antimicrobial surface coatings with the implication that they may contain or limit regrowth.

Little information is available on the efficacy of these treatments. This paper describes a study to evaluate whether three commercially available antimicrobial coatings, placed on a cleaned surface that 1 year previously had been actively growing microorganisms, would be able to prevent regrowth. The three coatings contained different active antimicrobial compounds. All three of the coatings were designed for use on heating, ventilation, and air conditioning (HVAC) system components or interior surfaces of lined and unlined duct systems. Coating I was a polyacrylate copolymer containing zinc oxide and borates. Coating II was an acrylic coating containing decabromodiphenyl oxide and antimony trioxide. Coating III was an acrylic primer containing a phosphated quaternary amine complex.

The study included field and laboratory assessments. The three treatments were evaluated in an uncontrolled field setting in an actual duct system. The laboratory study broadened the field study to include a range of humidities under controlled conditions. Both static and dynamic chamber laboratory experiments were performed. The results showed that two of the three antimicrobial coatings limited the regrowth of fungal contamination, at least in the short term (the 3-month time span of the study); the third did not. Before use in the field, testing of the efficacy of antimicrobial coatings under realistic use conditions is recommended because antimicrobials have different baseline activities and interact differently with the substrate that contains them and their local environment.