The Association between Ambient Carbon Monoxide Levels and Daily Mortality in Toronto,Canada

ABSTRACT

The role of ambient levels of carbon monoxide (CO) in the exacerbation of heart problems in individuals with both cardiac and other diseases was examined by comparing daily variations in CO levels and daily fluctuations in nonaccidental mortality in metropolitan Toronto for the 15-year period 1980–1994. After adjusting the mortality time series for day-of-the-week effects, nonparametic smoothed functions of day of study and weather variables, statistically significant positive associations were observed between daily fluctuations in mortality and ambient levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, coefficient of haze, total suspended particulate matter, sulfates, and estimated PM_2.5 and PM₁₀. However, the effects of this complex mixture of air pollutants could be almost completely explained by the levels of CO and total suspended particulates (TSP). Of the 40 daily nonaccidental deaths in metropolitan Toronto, 4.7% (95% confidence interval of 3.4%–6.1%) could be attributable to CO while TSP contributed an additional 1.0% (95% confidence interval of 0.2–1.9%), based on changes in CO and TSP equivalent to their average concentrations. Statistically significant positive associations were observed between CO and mortality in all seasons, age, and disease groupings examined. Carbon monoxide should be considered as a potential public health risk to urban populations at current ambient exposure levels.     

Daily Mortality and Air Pollution in the Netherlands

ABSTRACT

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models.

Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM₁₀ concentration by 100 u.g/m³ was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM₁₀, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO₂ and NO₂. Aerosol SO₄ ^-2, NO₃ ^-, and BS were more consistently associated with total mortality than was PM₁₀. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM₁₀ was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Statistical Study of Air Pollutant Concentrations via Generalized Gamma Distributions

This paper deals with modeling observed frequency distributions of air quality data measured in the area of Venice, Italy. The paper discusses the application of the generalized gamma distribution (ggd) which has not been commonly applied to air quality data notwithstanding the fact that it embodies most distribution models used for air quality analyses. The approach yields important simplifications for statistical analyses. A comparison among the ggd and other relevant models (standard gamma, Weibull, lognormal), carried out on daily sulphur dioxide concentrations in the area of Venice underlines the efficiency of ggd models in portraying experimental data.     

A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania

We have studied the possible association of daily mortality with ambient pollutant concentrations (PM10, CO, O3, SO2, NO2, and fine [PM2.5] and coarse PM) and weather variables (temperature and dew point) in the Pittsburgh, PA, area for two age groups--less than 75, and 75 and over--for the 3-year period of 1989-1991. Correlation functions among pollutant concentrations show important seasonal dependence, and this fact necessitates the use of seasonal models to better identify the link between ambient pollutant concentrations and daily mortality. An analysis of the seasonal model results for the younger-age group reveals significant multicollinearity problems among the highly correlated concentrations of PM10, CO, and NO2 (and O3 in spring and summer), and calls into question the rather consistent results of the single- and multi-pollutant non-seasonal models that show a significant positive association between PM10 and daily mortality. For the older-age group, dew point consistently shows a significant association with daily mortality in all models. Collinearity problems appear in the multi-pollutant seasonal and non-seasonal models such that a significant, positive PM10 coefficient is accompanied by a significant, negative coefficient of another ambient pollutant, and the identity of this other pollutant changes with season. The PM2.5 data set is half that of PM10. Identical-model runs for both data sets reveal instability in the pollutant coefficients, especially for the younger age group. The concern for the instability of the pollutant coefficients due to a small signal-to-noise ratio makes it impossible to ascertain credibly the relative associations of the fine- and coarse-particle modes with daily mortality. In this connection, we call for caution in the interpretation of model results for causal inference when the models use fully or partially estimated PM values to fill large data gaps.     

A Method of Predicting Point and Path- Averaged Ambient Air VOC Concentrations,Using Meteorological Data

A method of predicting point and path-averaged ambient air VOC concentrations is described. This method was developed for the case of a plume generated from a single point source, and is based on the relationship between wind directional frequency and concentration. One-minute means of wind direction and wind speed were used as inputs to a Gaussian dispersion model to develop this relationship.

Both FTIR spectrometry and a whole-air sampling method were used to monitor VOC plumes during simulated field tests. One test set was also conducted using only whole-air samplers deployed in a closely-spaced network, thus providing an evaluation of the prediction technique free of any bias that might exist between the two analytical methods.

Correlations between observed point concentrations and wind directional frequencies were significant at the 0.05 level in most cases. Predicted path-integrated concentrations, based on observed point concentrations and meteorological data, were strongly correlated with observed values. Predicted point concentrations, based on observed path-integrated concentrations and meteorological data, accurately reflected the location and magnitude of the highest concentrations from each test, as well as the shape of the concentration-versus-crosswind distance curve.     

Sources of atmospheric carbonaceous particulate matter in Pittsburgh,Pennsylvania

The organic carbon (OC)/elemental carbon (EC) tracer method is applied to the Pittsburgh, PA, area to estimate the contribution of secondary organic aerosol (SOA) to the monthly average concentration of organic particulate matter (PM) during 1995. An emissions inventory is constructed for the primary emissions of OC and EC in the area of interest. The ratio of primary emissions of OC to those of EC ranges between 2.4 in the winter months and 1.0 in the summer months. A mass balance model and ambient measurements were used to assess the accuracy of the emissions inventory. It is estimated to be accurate to within 50%. The results from this analysis show a strong monthly dependence of the SOA contribution to the total organic PM concentration, varying from near zero during winter months to as much as 50% of the total OC concentration in the summer.     

Measurement of Ozone Concentrations in Ambient Air Using a Badge-Type Passive Monitor

Abstract

A badge-type passive monitor was used to evaluate the effectiveness of four ozone trapping reagents for measuring O₃ concentrations in the air. These were sodium nitrite (NaNO₂), 3-methyl-2-benzothiazolinone acetone azine (MBTH), p-acetamidophenol (p-ATP), and indigo carmine. Experiments in an exposure chamber showed that only NaNO₂ and MBTH monitors gave sensitive and linear responses over realistic ranges of O₃ concentrations. When tested in ambient air, NaNO₂ and MBTH monitors with a single-layer diffusion barrier overestimated O₃ concentrations by a significant amount. This was largely canceled out in the NaNO₂ monitor by using a multi-layered diffusion barrier to combat wind turbulence effects. However it had almost no effect on the MBTH monitor, and it was found that NO₂ was a source of serious interference. We concluded that using the NaNO₂ monitor with an effective diffusion barrier can measure O₃ in ambient air with an accuracy of ±16%.     

A Physical Explanation of the Lognormality of Pollutant Concentrations

Investigators In different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, Indoor air quality, trace metals In streams, metals in biological tissue, calcium In human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that Is simulated on the computer.     

Exposure of Chronic Obstructive Pulmonary Disease Patients to Particulate Matter: Relationships between Personal and Ambient Air Concentrations

ABSTRACT

Most time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects.

Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM_{2 5} monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM₁₀ and PM_2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO₄ ^2-, which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM_{2 5} samples as an indicator of accumulation mode particu-late matter of ambient origin.     

State-Space Modeling of the Relationship between Air Quality and Mortality

ABSTRACT

A portion of a population is assumed to be at risk, with the mortality hazard varying with atmospheric conditions including total suspended particulates (TSP). This at-risk population is not observed and the hazard function is unknown; we wish to estimate these from mortality count and atmospheric variables. Consideration of population dynamics leads to a state-space representation, allowing the Kalman Filter (KF) to be used for estimation. A harvesting effect is thus implied; high mortality is followed by lower mortality until the population is replenished by new arrivals.

The model is applied to daily data for Philadelphia, PA, 1973-1990. The estimated hazard function rises with the level of TSP and at extremes of temperature and also reflects a positive interaction between TSP and temperature. The estimated at-risk population averages about 480 and varies seasonally. We find that lags of TSP are statistically significant, but the presence of negative coefficients suggests their role may be partially statistical rather than biological. In the population dynamics framework, the natural metric for health damage from air pollution is its impact on life expectancy. The range of hazard rates over the sample period is 0.07 to 0.085, corresponding to life expectancies of 14.3 and 11.8 days, respectively.     

Differences between Weekday and Weekend Air Pollutant Levels in Southern California

Abstract

Ambient air quality data were analyzed to empirically evaluate the effects of reductions of volatile organic compounds (VOCs) and oxides of nitrogen (NO_x) emissions on weekday and weekend levels of ozone (O₃; 1991–1998) and particulate NO₃ ^- (1980–1999) in southern California. Despite significantly lower O₃ precursor levels on weekends, 20 of 28 South Coast Air Basin (SoCAB) sites (28 of all 78 southern California sites) showed statistically significant higher mean O₃ levels on Sundays than on weekdays (p < 0.01); 49 of the remaining 50 sites showed no significant differences between mean weekday and Sunday peak O₃ levels. We also observed no statistically significant differences between mean weekday and weekend concentrations of particulate NO₃ ^- or nitric acid (HNO₃, the precursor of particulate NO₃ ^-). Averaged over sites, the mean Sunday NO_x and nonmethane hydrocarbon concentrations were 25–41% and 16–30% lower, respectively, than on weekdays. Site-to-site differences between weekend and weekday mean peak hourly O₃ levels were related to whether O₃ formation was limited by the availability of NO_x. A thermodynamic equilibrium model predicts that particulate NO₃ ^- levels would decrease in response to a reduction of HNO₃, and that particulate ammonium NO₃ ^- formation was not limited by the availability of ammonia. The similarity of mean weekday and weekend levels of NO₃ ^- therefore did not result from limitations on the formation of particulate NO₃ ^- from its precursor, HNO₃.     

Ambient Air Benzene Concentrations in Canada (1989-1993): Seasonal and Day of Week Variations,Trends, and Source Influences

Abstract

Since 1987, the Pollution Measurement Division of the Environmental Protection Service, Environment Canada, has operated a field program for measuring benzene in ambient air. With the cooperation of provincial and municipal environmental agencies, samples have been collected at over 30 urban and rural monitoring sites across the country. Samples are collected in evacuated canisters and analyzed by gas chromatography with a mass-selective detector. Using data from all sites, the composite average benzene concentration for Canada over the years 1989 to 1993 was 3.6 μg/m³ and the composite median was found to be 2.6 μ/m³. Benzene concentrations are highest at urban sites near major streets and at sites influenced by industrial sources. For eighteen urban and suburban trend sites (those with no nearby industrial sources), composite annual median benzene concentrations decreased by 20% between 1989 and 1993. For the same period, median benzene concentrations decreased by 33% at four trend sites with nearby industries. At most monitoring sites the parameters for benzene and CO are highly correlated; supporting the inventory estimate that most emissions of benzene are due to vehicle exhaust. For sites with nearby industrial sources of benzene, the industries are estimated to account for 35 to 70% of the benzene dose experienced at the sites. These site specific contributions are much more significant than the estimated national emissions assigned to industrial sources.     

A High-Volume Sampler for the Determination of Particle Size Distributions in Ambient Air

A size selective particle sampler has been developed for continuous sampling of the urban aerosol over periods ranging from hours to weeks, providing relatively large sample weights. The system, which is now operating in New York City, uses a parallel array of two-stage samplers. The cyclones used as the first stage collectors have 50% particle retention at 3.5,2.5,1.5 and 0.5 µm aerodynamic diameter, respectively. Undersize particles which pass through the cyclones are captured on glass fiber filters. Equal intake velocities are assured by using flow equalizers on the inlets to the cyclones. Accurate control of the flow through the cyclones is obtained by the use of an integrated circuit pressure transducer in conjunction with a specially designed feedback control circuit. The collection efficiencies of the cyclone were calibrated using monodisperse ferric oxide test aerosols tagged with Tc-99m. Mass balances of the par-ticulates collected on the cyclones and filters are obtained for the five sampling stages. Preliminary results show the distributions of the total suspended particulates in New York City to be bimodal. The distributions of lead, copper, and manganese with particle size are also discussed.     

Regional Monitoring of Ambient Air Carbon Monoxide in Fairbanks,Alaska

A method employing the timed fill of Mylar bags was used to obtain average carbon monoxide concentration values for ten locations in the Fairbanks, Alaska, area. The method is shown to be accurate, reliable, and inexpensive. The correlation coefficient between the bag sampling method and a continuous carbon monoxide analyzer was 0.945; correlation of carbon monoxide data from several locations to a reference in downtown Fairbanks showed a general decrease with distance from the reference analyzer. Analysis of data from Fairbanks shows that carbon monoxide concentrations during the winter months may have to be reduced 50-75% to achieve the State and National Ambient Air Quality Standards; the high levels of carbon monoxide are the result of emissions from automobile traffic during periods of severe inversion in the Fairbanks basin.     

Lead Concentrations in Detroit,New York,and Los Angeles Air

Lead concentrations in air were measured at 12 sites in Detroit, New York and Los Angeles as part of a program to relate automobile emissions and polynuclear aromatic hydrocarbons in air. The information on lead is reported separately because of the current interest in lead as an air pollutant. Sampling was conducted by means of a large “absolute” filter and equipment contained in a step-van truck. A portion of the filter was macerated in nitric acid and the lead determined spectrographically. The combined annual average lead concentration for four sites in metropolitan Los Angeles was approximately 40% higher than the combined averages of either the five sites in metropolitan New York or the three sites in metropolitan Detroit. Concentrations ranged from 0.4 ug/M³ at Santa Monica, to 18.4 ug/M³ at a Los Angeles Freeway Interchange. Concentrations were generally highest in freeway areas, intermediate in commercial areas, and lowest in residential areas. They were about 40% higher in daytime than at night. Average lead concentrations were highest during autumn in New York and winter in Los Angeles reflecting an inverse relationship with wind speed. Correlation coefficients between lead and carbon monoxide, at all sites, were statistically non-zero with 99% confidence and varied from 0.75 to 0.96. Lead concentrations in this study were higher than concentrations reported by others for Detroit, New York, and Los Angeles, presumably because sampling in this study was closer to traffic. However, concentrations in this study were lower than in-traffic concentrations given in the literature.     

The Impact of Particulate Matter on Daily Mortality in Bangkok,Thailand

ABSTRACT

Several studies conducted in U.S. cities report an association between acute exposures to particulate matter (PM), usually measured as PM_10, and mortality. Evidence of high concentrations of PM₁₀ in Eastern Europe and in large metropolitan areas outside of the United States, such as Mexico City and Bangkok, underscores the need to determine whether these same associations occur outside of the United States. In addition, conducting studies of mortality and air pollution in regions that have distinctly different seasonal patterns than those of the United States provides an effective opportunity to assess the potentially confounding aspects of seasonality. Over the last few years, daily measures of ambient PM₁₀ have been collected in Bangkok, a tropical city of over 6 million people. In this metropolitan area, PM₁₀ consists largely of fine particles generated from diesel- and gasoline-powered automobiles, and from two-stroke motorcycle engines. Our analysis involved the examination of the relationship between PM₁₀ and daily mortality for 1992 through 1995. In addition to counts of daily natural mortality (total mortality net of accidents, homicides, and suicides), the data were compiled to assess both cardiovascular and respiratory mortality, and natural mortality by age group. A multivariate Poisson regression model was used to explain daily mortality while controlling for several covariates including temperature, humidity, day of the week, season, and time. The analysis indicated a statistically significant association between PM10 and all of the alternative measures of mortality. The results suggest a 10-µg/m³ change in daily PM₁₀ is associated with a 1–2% increase in natural mortality, a 1–2% increase in cardiovascular mortality, and a 3–6% increase in respiratory mortality. These relative risks are generally consistent with or greater than those reported in most studies undertaken in the United States.     

The Influence of Annual Meteorological Variations On Regional Air Pollution Modeling: A Case Study of Allegheny County,Pennsylvania

The influence of year-to-year meteorological variations on the prediction of annual average ground-level pollutant concentrations has been examined via case studies of Allegheny County, Pa. Twenty-two stability wind roses representing different averaging intervals of from one to seven years were employed in the Air Quality Display Model to predict annual average SO₂ concentrations in two multiple source sub-basins, and from two single point sources representing industrial and utility boiler stacks. Effects of annual meteorological variations were manifested by changes in the magnitude of peak concentrations, the location of peak concentrations, and the geographic distribution of pollutants. For fixed rates of emission, the peak annual average SO₂ ground-level concentration varied by an average of up to 33% of highest values for point sources and 17% for sub-basin complexes. In both cases, there was relatively little change in the location of peak concentration, though occasional directional shifts were noted. In contrast, marked variations were noted in the geographic area exposed to annual average concentrations in excess of several selected values. To aid in regional planning, several methods were formulated which considerably reduced the uncertainty in predicting peak annual concentration for varying degrees of historical data on regional stability wind rose. These methods are-especially applicable to analysis of control strategies directed at attaining annual ambient air quality standards which nominally must never be exceeded.