Estimating Maximum Concentrations for Open Path Monitoring Along a Fixed Beam Path

ABSTRACT

Researchers have applied open path optical sensing techniques to a variety of workplace and environmental monitoring problems. Usually these data are reported in terms of a path-average (or path-integrated) concentration. When assessing potential human exposures along a beam path, this path-average value is not always informative, since concentrations along the path can vary substantially from the beam average. The focus of this research is to arrive at a method for estimating the upper-bound in contaminant concentrations over a fixed open beam path. The approach taken here uses a statistical model to estimate an upper-bound concentration based on a combination of the path-average and a measure of the spatial variability computed from point samples along the beam path. Results of computer simulations and experimental testing in a controlled ventilation chamber indicate that the model produced conservative estimates for the maximum concentration along the beam path. This approach may have many applications for open path monitoring in workplaces or wherever maximum concentrations are a concern.     

Daily Mortality in the Philadelphia Metropolitan Area and Size-Classified Particulate Matter

ABSTRACT

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO₄ ^2-, and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM_2.5 and coarse particles, SO₄ ^2- and non-SO₄ ^2- portions of total suspended particulate [TSP] and PM₁₀), measured on the day of death and the previous day.

We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O₃. Using joint regressions on peak O₃ with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O₃ seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

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.     

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.     

Pilot-Scale Demonstration of an Innovative Treatment for Vapor Emissions

ABSTRACT

Researchers from the National Renewable Energy Laboratory recently conducted a pilot-scale study at McClellan Air Force Base (AFB) in Sacramento, CA. The objective of the test was to determine the effectiveness of an ambient-temperature, solar-powered photocatalytic oxidation treatment unit for destroying emissions of chlorinated organic compounds from an air stripper. This paper reports test results and discusses applications and limitations of the technology.

A 10-standard-cubic-foot-per-minute (SCFM) (28.3 L/min) slip stream of air from an air stripper at Operative Unit 29-31 at McClellan AFB was passed through a reactor that contained a lightweight, perforated, inert support coated with photoactive titanium dioxide. The reactor faced south and was tilted at a 45° angle from vertical so that the light-activated catalyst received most of the available sunlight. An online portable gas chro-matograph with two identical columns simultaneously analyzed the volatile organic compounds contained in the reactor inlet and outlet air streams. Summa canister grab samples of the inlet and outlet were also collected and sent to a certified laboratory for U.S. Environmental

Protection Agency Method TO-14 analysis and verification of our field analyses. Three weeks of testing demonstrated that the treatment system's destruction and removal efficiencies (DREs) are greater than 95% at 10 SCFM with UV intensities at or greater than 1.5 milliwatts/square centimeter (mW/cm²). DREs greater than 95% at 20 SCFM were obtained under conditions where UV irradiation measured at or greater than 2 mW/cm². In Sacramento, this provided 6 hours of operation per clear or nearly clear day in April. A solar tracking system could extend operating time. The air stream also contained trace amounts of benzene. We observed no loss of system performance during testing.     

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.     

Estimates of Particle Hygroscopicity during the Southeastern Aerosol and Visibility Study

ABSTRACT

Aerosol water content was determined from relative humidity controlled optical particle counter (ASASP-X) size distribution measurements made during the Southeastern Aerosol and Visibility Study (SEAVS) in the Great Smoky Mountains National Park during summer 1995. Since the scattering response function of the ASASP-X is sensitive to particle refractive index, a technique for calibrating the ASASP-X for any real refractive index was developed. A new iterative process was employed to calculate water mass concentration and wet refractive index as functions of relative humidity. Experimental water mass concentrations were compared to theoretically predicted values assuming only ammonium sulfate compounds were hygroscopic. These comparisons agreed within experimental uncertainty. Estimates of particle hygroscopicity using a rural aerosol model of refractive index as a function of relative humidity demonstrated no significant differences from those made with daily varying refractive index estimates. Although aerosol size parameters were affected by the assumed chemical composition, forming ratios of these parameters nearly canceled these effects.     

Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale

Abstract

Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area’s ability to sequester carbon in terrestrial ecosystems. As the ecosystems within a landscape change due to natural or anthropogenic processes, they may go from being a carbon sink to a carbon source or vice versa. Satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of terrestrial carbon. The coupling of Landsat Thematic Mapper (TM) data with a physiologically based forest productivity model (PnET-II) and historic climatic data provides an opportunity to enhance field plot-based forest inventory and monitoring methodologies. We use periodic forest inventory data from the U.S. Department of Agriculture (USDA) Forest Service’s Forest Inventory and Analysis (FIA) Program to obtain estimates of forest area and type and to generate estimates of carbon storage for evergreen, deciduous, and mixed-forest classes. The area information is used in an accuracy assessment of remotely sensed forest cover at the regional scale. The map display of modeled net primary production (NPP) shows a range of forest carbon storage potentials and their spatial relationship to other landscape features across the southern United States. This methodology addresses the potential for measuring and projecting forest carbon sequestration in the terrestrial biosphere of the southern United States.