Carbon Monoxide Levels in Athletes during Exercise in an Urban Environment

ABSTRACT

Gas phase concentrations of individual polycyclic aromatic hydrocarbons (PAHs) were measured in real time in combustion products from a co-flow diffusion flame using laser photoionization (LP) time-of-flight mass spectrometry (TOF/MS). In particular, a naphthalene detection sensitivity of 4 parts per billion (ppb) was demonstrated. The use of calibration mixtures with argon indicated the feasibility of naphthalene detection at about 45 parts per trillion (ppt) at a signal-to-noise (S/N) ratio of 20. This suggests the possibility of low-ppt level detection at a S/N of 1. The novelty of the system is the use of a heated sampling probe and a continuously purged, heated-pulse valve that was positioned close to the ionization zone, thereby allowing the generation of photoions in the high-density region of the sample jet, where concentrations of PAH are high. Because the system developed allows for the real time detection of select species, it represents a useful tool in continuous emissions monitoring (CEM) for environmental compliance as well as direct process control.     

An Urban Diffusion Simulation Model For Carbon Monoxide

A relatively simple Gaussian-type diffusion simulation model for calculating urban carbon monoxide (CO) concentrations as a function of local meteorology and the distribution of traffic is described. The model can be used in two ways: (1) in the synoptic mode, in which hourly concentrations at one or many receptor points are calculated from historical or forecast traffic and meteorological data; and (2) in the climatological mode, in which concentration frequency distributions are calculated on the basis of long-term sequences of input data. For model evaluation purposes, an extensive field study involving meteorological and air-quality measurements was conducted during November-December 1970 in San Jose, Calif., which has an automated network to provide traffic data throughout the central business district. Model refinements made on the basis of the data from this experimental program include the addition of a street-canyon submodel to compensate for the important aerodynamic effects of buildings on CO concentrations at streetside receptors. The magnitude of these effects was underscored by the concentrations measured on opposite sides of the street in San Jose, which frequently differed by a factor of two or more. Evaluation of the revised model has shown that calculated and observed concentration frequency distributions for street-canyon sites are in good agreement. Hour-average predictions are well correlated with observations (correlation coefficient of about 0.6 to 0.7), and about 80 percent of the calculated values are within 3 ppm of the observed hour-average concentrations, which ranged as high as 16 ppm.     

Receptor Oriented Methods of Air Particulate Source Apportionment

Receptor models have evolved rapidly over the past 13 years but have just recently been recognized as a distinct discipline. The general category of receptor models includes both microscopic and chemical methods of apportioning source contributions to ambient air particulates. The number and variations of these methods have grown rapidly over the past few years and include such methods as automated scanning electron microscopy, chemical mass balance and multivariate procedures. These methods as well as hybrid procedures such as target transformation factor analysis, are reviewed and their boundary conditions, strengths, and weaknesses discussed.     

An Urban Airshed Model for Predicting Carbon Monoxide Concentrations in Tucson,Arizona

ABSTRACT

The Electric Power Research Institute (EPRI) is conducting research to investigate mercury removal in utility flue gas using sorbents. Bench-scale and pilot-scale tests have been conducted to determine the abilities of different sor-bents to remove mercury in simulated and actual flue gas streams. Bench-scale tests have investigated the effects of various sorbent and flue gas parameters on sorbent performance. These data are being used to develop a theoretical model for predicting mercury removal by sorbents at different conditions. This paper describes the results of parametric bench-scale tests investigating the removal of mercuric chloride and elemental mercury by activated carbon.

Results obtained to date indicate that the adsorption capacity of a given sorbent is dependent on many factors, including the type of mercury being adsorbed, flue gas composition, and adsorption temperature. These data provide insight into potential mercury adsorption mechanisms and suggest that the removal of mercury involves both physical and chemical mechanisms. Understanding these effects is important since the performance of a given sorbent could vary significantly from site to site depending on the coal- or gas-matrix composition.     

Interpreting Urban Carbon Monoxide Concentrations by Means of a Computerized Blood COHb Model

A practical, inexpensive computer model for estimating the level of blood carboxyhemoglobin (percent COHb) as a function of time for measured carbon monoxide concentrations (ppm CO) was developed from data from published studies on the assimilation of CO into the blood of human subjects. The model was designed to consider more realistically the dynamic characteristics of urban CO concentrations measured continuously at air monitoring stations, and it was applied to a year's CO data measured at the San Jose CA, air monitoring station (8760 hourly values).

The results indicate that the model can be used by local air pollution control agencies to calculate and print out estimated COHb levels alongside continuous CO concentration data. According to the model, the National Ambient Air Quality Standards (NAAQS) for CO sometimes were violated in San Jose without exceeding 2% COHb, as well as the converse: 2% COHb was exceeded without violating the standards. The model's estimated COHb levels also provided an advance warning of impending violation of the 8-hr CO NAAQS, and analysis of the model's response to CO "spikes" suggests that averaging periods as short as 10 or 15 minutes are necessary to preserve completely the dynamic characteristics of ambient CO monitoring data. These findings suggest that the margin of safety included in the current CO NAAQS, would not be the same if the actual time variation of measured CO concentrations is taken into account.     

Carbon Monoxide Exposures Inside an Automobile Traveling on an Urban Arterial Highway

Carbon monoxide (CO) exposures were measured inside a motor vehicle during 88 standardized drives on a major urban arterial highway, El Camino Real (traffic volume of 30,500-45,000 vehicles per day), over a 13-1/2 month period. On each trip (lasting between 31 and 61 minutes), the test vehicle drove the same 5.9-mile segment of roadway in both directions, for a total of 11.8 miles, passing through 20 intersections with traffic lights (10 in each direction) in three California cities (Menlo Park, Palo Alto, and Los Altos). Earlier tests showed that the test vehicle was free of CO intrusion. For the 88 trips, the mean CO concentration was 9.8 ppm, with a standard deviation of 5.8 ppm. Of nine covariates that were examined to explain the variability in the mean CO exposures observed on the 88 trips (ambient CO at two fixed stations, atmospheric stability, seasonal trend function, time of day, average surrounding vehicle count, trip duration, proportion of time stopped at lights, and instrument type), a fairly strong seasonal trend was found. A model consisting of only a single measure of traffic volume and a seasonal trend component had substantial predictive power (R² = 0.68); by contrast, the ambient CO levels, although partially correlated with average exposures, contributed comparatively little predictive power to the model. The CO exposures experienced while drivers waited at the red lights at an intersection ranged from 6.8 to 14.9 ppm and differed considerably from intersection to intersection. A model also was developed to relate the short-term variability of exposures to averaging time for trip times ranging from 1 to 20 minutes using a variogram approach to deal with the serial autocorrelation. This study shows: (1) the mass balance equation can relate exterior CO concentrations as a function of time to interior CO concentrations; (2) CO exposures on urban arterial highways vary seasonally; (3) momentary CO exposures experienced behind red lights vary with the intersection; and (4) an averaging time model can simulate exposures during short trips (20 minutes or less) on urban arterial highways.     

A Mathematical Model for Predicting Trends in Carbon Monoxide Emissions and Exposures on Urban Arterial Highways

Abstract

The roadway is one of the most important microenvironments for human exposure to carbon monoxide (CO). To evaluate long-term changes in pollutant exposure due to in-transit activities, a mathematical model has been developed to predict average daily vehicular emissions on highways. By utilizing measurements that are specific for a given location and year (e.g., traffic counts, fleet composition), this model can predict emissions for a specific roadway during various time periods of interest, allowing examination of long-term trends in human exposure to CO. For an arterial highway in northern California, this model predicts that CO emissions should have declined by 58% between 1980 and 1991, which agrees fairly well with field measurements of human exposure taken along that roadway during those two years. An additional reduction of up to 60% in CO emissions is predicted to occur between 1991 and 2002, due solely to the continued replacement of older cars with newer, cleaner vehicles.     

Persistence Factors for Mobile Source (Roadway) Carbon Monoxide Modeling

A critical step in the modeling of the carbon monoxide (CO) impacts of mobile sources is predicting an 8-hour CO concentration given a modeled "worst-case" 1-hour concentration. Often, this is done by a multiplicative persistence factor. A meteorological persistence factor (MPF) accounts for the variability over 8 hours of wind speed, wind direction, stability class, and temperature. A vehicular persistence factor (VPF) reflects the lower traffic volumes during the off-peak hours.

Hourly meteorological data for ten years for four cities in Florida were obtained from the National Climatic Data Center. The CALINE3 model was used to obtain hourly CO concentrations, which were combined to derive MPFs for each city. Similarly, VPFs were derived from hourly vehicle counts from one busy roadway in each city. The mean VPF multiplied by the second highest MPF was defined as the worst-case total persistence factor (TPF). These worst-case TPFs increased significantly as more hours of nighttime were included in the 8- hour averaging time, but were fairly consistent from city to city. In general, the results suggest worst-case TPFs in the range of 0.4 to 0.5, lower than has been recommended by EPA in the past.     

Improving Source Apportionment of Fine Particles in the Eastern United States Utilizing Temperature-Resolved Carbon Fractions

Abstract

The objectives of this study were to examine the use of carbon fractions to identify particulate matter (PM) sources, especially traffic‐related carbonaceous particle sources, and to estimate their contributions to the particle mass concentrations. In recent studies, positive matrix factorization (PMF) was applied to ambient fine PM (PM_2.5) compositional data sets of 24‐hr integrated samples including eight individual carbon fractions collected at three monitoring sites in the eastern United States: Atlanta, GA, Washington, DC, and Brigantine, NJ. Particulate carbon was analyzed using the Interagency Monitoring of Protected Visual Environments/Thermal Optical Reflectance method that divides carbon into four organic carbons (OC): pyrolized OC and three elemental carbon (EC) fractions. In contrast to earlier PMF studies that included only the total OC and EC concentrations, gasoline emissions could be distinguished from diesel emissions based on the differences in the abundances of the carbon fractions between the two sources. The compositional profiles for these two major source types show similarities among the three sites. Temperature‐resolved carbon fractions also enhanced separations of carbon‐rich secondary sulfate aerosols. Potential source contribution function analyses show the potential source areas and pathways of sulfate‐rich secondary aerosols, especially the regional influences of the biogenic, as well as anthropogenic secondary aerosol. This study indicates that temperature‐resolved carbon fractions can be used to enhance the source apportionment of ambient PM_2.5.     

Sensitivity of Source Apportionment of Urban Particulate Matter to Uncertainty in Motor Vehicle Emissions Profiles

Abstract

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM_2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.     

A Numerical Model of Diffusion of Carbon Monoxide near Highways

A numerical model, which can be used to study the dispersion of carbon monoxide emissions from automobiles traveling on a highway, is described. The model Is based upon the semi-empirical equation of turbulent diffusion. The performance of the model has been tested using carbon monoxide concentration data obtained near highway 401 in the city of Toronto, Canada.     

Estimation of Organic Carbon Blank Values and Error Structures of the Speciation Trends Network Data for Source Apportionment

Abstract

Because the particulate organic carbon (OC) concentrations reported in U.S. Environment Protection Agency Speciation Trends Network (STN) data were not blank corrected, the OC blank concentrations were estimated using the intercept in particulate matter ≤2.5 µm in aerodynamic diameter (PM_2.5) regression against OC concentrations. The estimated OC blank concentrations ranged from 1 to 2.4 μg/m³ showing higher values in urban areas for the 13 monitoring sites in the northeastern United States. In the STN data, several different samplers and analyzers are used, and various instruments show different method detection limit (MDL) values, as well as errors. A comprehensive set of error structures that would be used for numerous source apportionment studies of STN data was estimated by comparing a limited set of measured concentrations and their associated uncertainties. To examine the estimated error structures and investigate the appropriate MDL values, PM_2.5 samples collected at a STN site in Burlington, VT, were analyzed through the application of the positive matrix factorization. A total of 323 samples that were collected between December 2000 and December 2003 and 49 species based on several variable selection criteria were used, and eight sources were successfully identi?ed in this study with the estimated error structures and min values among different MDL values from the ?ve instruments: secondary sulfate aerosol (41%), secondary nitrate aerosol (20%), airborne soil (15%), gasoline vehicle emissions (7%), diesel emissions (7%), aged sea salt (4%), copper smelting (3%), and ferrous smelting (2%). Time series plots of contributions from airborne soil indicate that the highly elevated impacts from this source were likely caused primarily by dust storms.     

Source Resolution of Fine Particulate Polycyclic Aromatic Hydrocarbons Using a Receptor Model Modified for Reactivity

This paper provides source contribution estimates from vehicular and meat-cooking emissions to particulate polycyclic aromatic hydrocarbon (PAH) and elemental carbon (EC) concentrations measured at two Los Angeles sites during a field study in 1989. The source concentration matrix for PAH was based on new data for vehicular emissions and literature data for meat-cooking operations. The chemical mass balance (CMB 7.0) receptor model was used, and source profiles were modified to reflect reactive decay of PAH in the atmosphere. The calculations indicate that the Pico Rivera site was dominated by auto emissions, which account for more than 90 percent of all the PAH (except chrysene), carbon monoxide (CO), and 61 percent of the EC concentrations. In contrast, emissions from meat cooking contributed significantly (20 to 75 percent) to the concentrations of four-ring PAH measured at a residential site at Upland. The five-ring and larger PAH were attributed to auto emissions at Upland as well.     

Source Apportionment of Ambient Total Suspended Particulates and Coarse Particulate Matter in Urban Areas of Jiaozuo,China

Abstract

Approximately 750 total suspended particulates (TSPs) and coarse particulate matter (PM₁₀) filter samples from six urban sites and a background site and >210 source samples were collected in Jiaozuo City during January 2002 to April 2003. They were analyzed for mass and abundances of 25 chemical components. Seven contributive sources were identified, and their contributions to ambient TSP/PM₁₀ levels at the seven sites in three seasons (spring, summer, and winter days) and a “whole” year were estimated by a chemical mass balance (CMB) receptor model. The spatial TSP average was high in spring and winter days at a level of approximately 530 ～g/m³ and low in summer days at 456 ～g/m³; however, the spatial PM₁₀ average exhibited little variation at a level of approximately 325 ～g/m³, and PM_10-to-TSP ratios ranged from 0.58 to 0.81, which suggested heavy particulate matter pollution existing in the urban areas. Apportionment results indicated that geological material was the largest contributor to ambient TSP/PM₁₀ concentrations, followed by dust emissions from construction activities, coal combustion, secondary aerosols, vehicle movement, and other industrial sources. In addition, paved road dust and re-entrained dust were also apportioned to the seven source types and found soil, coal combustion, and construction dust to be the major contributors.     

A Survey Technique for Determining The Representativeness of Urban Air Monitoring Stations With Respect to Carbon Monoxide

An air quality survey technique for measuring the horizontal spatial variation of carbon monoxide concentrations in urban areas is described; it was used to determine how representative an urban air monitoring station is of concentrations throughout the city.

The survey technique was applied in San Jose, Calif., where 1128 samples were collected over a six-month period and were compared with the values recorded simultaneously at the urban air monitoring station. All samples were collected at “breathing height” within a 13-square-mile grid which included the downtown area as well as surrounding residential and industrial locations. Three basic sampling strategies were employed to answer specific questions about the distribution of carbon monoxide concentration: (7) walking sampling, in which samples were obtained while walking along the sidewalks of congested downtown streets, (2) random spatial sampling, in which samples were collected at randomly selected points in the urban grid, and (3) specialized sampling in the immediate vicinity of the air monitoring station.

The results indicate that pedestrians on downtown streets in San Jose can be exposed to concentrations above the federal air quality standards without these values being observed at the air monitoring station. There also is evidence that, at any instant of time, similar values of carbon monoxide exist throughout this city (within a 13-square mile area), provided that measurements are not made in close proximity to streets. Furthermore, the higher concentrations observed in the immediate vicinity of streets decrease quite rapidly with increasing horizontal distance from these streets.

These findings, in the view of the authors, raise serious doubts as to whether it is possible to determine if air quality standards as currently defined are actually being met in urban areas using data from present-day air monitoring stations.     

Source Apportionment of Fine Particulate Matter in the Southeastern United States

Abstract

Particulate matter (PM) less than 2.5 μm in size (PM_2.5)source apportionment by chemical mass balance receptor modeling was performed to enhance regional characterization of source impacts in the southeastern United States. Secondary particles, such as NH₄HSO₄, (NH₄)₂SO₄,NH₄NO₃, and secondary organic carbon (OC) (SOC), formed by atmospheric photochemical reactions, contribute the majority (<50%) of ambient PM_2.5 with strong seasonality. Source apportionment results indicate that motor vehicle and biomass burning are the two main primary sources in the southeast, showing relatively more motor vehicle source impacts rather than biomass burning source impacts in populated urban areas and vice versa in less urbanized areas. Spatial distributions of primary source impacts show that each primary source has distinctively different spatial source impacts. Results also find impacts from shipping activities along the coast. Spatiotemporal correlations indicate that secondary particles are more regionally distributed, as are biomass burning and dust, whereas impacts of other primary sources are more local.     

Source Fingerprints for Receptor Modeling of Volatile Organics

The development of receptor models for the determination of the sources of an ambient air pollutant requires that the composition of the pollutant at the point of emission be known. For this study, composition information for 10 sources of volatile organic compounds (VOC) were evaluated and source fingerprints developed. The source categories include motor vehicles, gasoline vapor, petroleum refineries, architectural coatings, graphic arts, waste-water treatment, vapor degreasing, drycleaning, automobile assembly (including body painting), and polyethylene production. The fingerprints are presented for a group of 23 compounds. These compounds were selected for a variety of reasons including ease of measurement in the ambient environment, compound toxicity, reactivity, and usefulness in previous receptor modeling applications. In general, the data for sources of VOC are remarkably consistent from study to study. Because the profiles for many of the sources of VOC are controlled by physical and chemical processes (e.g. combustion) and not raw material composition, the fingerprints have general applicability.     

Source Apportionment of Particulate Matter (PM10) and Indoor Dust in a University Building

A study on source apportionment of indoor dust and particulate matter (PM₁₀) composition was conducted in a university building by using chemometrics. The objective of this study was to investigate the potential sources of selected heavy metals and ionic species in PM₁₀ and indoor dust. PM₁₀ samples were collected using a low-volume sampler (LVS) and indoor dust was collected using a soft brush. Inductively coupled plasma spectrometry (ICP-MS) was used to determine the concentration of heavy metals, while the concentration of cations and anions was determined by atomic absorption spectrometer (AAS) and ion chromatography (IC), respectively. The concentration of PM₁₀ recorded in the building throughout the sampling period ranged from 20 ± 10 μgm^?3 to 80 ± 33 μgm^?3. The composition of heavy metals in PM₁₀ and indoor dust were dominated by zinc (Zn), followed by lead (Pb), copper (Cu), and cadmium (Cd). Principle component analysis (PCA) and multiple linear regression (MLR) showed that the main sources of pollutants in PM₁₀ came from indoor renovations (73.83%), vehicle emissions (16.38%), earth crust sources (9.68%), and other outdoor sources (0.11%). For indoor dust, the pollutant source was mainly earth crust. This study suggests that chemometrics can be used for forensic investigation to determine the possible sources of indoor contaminants within a public building.