Air Pollution and Mortality: Issues and Uncertainties

Abstract

Results from 31 epidemiology studies linking air pollution with premature mortality are compared and synthesized. Consistent positive associations between mortality and various measures of air pollution have been shown within each of two fundamentally different types of regression studies and in many variations within these basic types; this is extremely unlikely to have occurred by chance. In this paper, the measure of risk used is the elasticity, which is a dimensionless regression coefficient defined as the percentage change in the dependent variable associated with a 1% change in an independent variable, evaluated at the means. This metric has the advantage of independence from measurement units and averaging times, and is thus suitable for comparisons within and between studies involving different pollutants. Two basic types of studies are considered: time-series studies involving daily perturbations, and cross-sectional studies involving longer-term spatial gradients. The latter include prospective studies of differences in individual survival rates in different locations and studies of the differences in annual mortality rates for various communities.

For a given data set, time-series regression results will vary according to the seasonal adjustment method used, the covariates included, and the lag structure assumed. The results from both types of cross-sectional regressions are highly dependent on the methods used to control for socioeconomic and personal lifestyle factors and on data quality. Amajor issue for all of these studies is that of partitioning the response among collinear pollution and weather variables. Previous studies showed that the variable with the least exposure measurement error may be favored in multiple regressions; assigning precise numerical results to a single pollutant is not possible under these circumstances. We found that the mean overall elasticity as obtained from timeseries studies for mortality with respect to various air pollutants entered jointly was about 0.048, with a range from 0.01 to 0.12. This implies that about 5% of daily mortality is associated with air pollution, on average. The corresponding values from population-based cross-sectional studies were similar in magnitude, but the results from the three recent prospective studies varied from zero to about five times as much. Long-term responses in excess of short-term responses might be interpreted as showing the existence of chronic effects, but the uncertainties inherent in both types of studies make such an interpretation problematic.     

Mortality and Air Pollution: Revisited

This paper represents an exploratory effort to estimate a physical nonlinear function between excess mortality rates and the SO₂ concentration with both considerations over econometric problems such as multicollinearity and heteroscedasticity (the residuals of regression analysis), and the threshold levels. Through a recursive and stepwise adjustment procedure, the average physical mortality function was generalized with much more complete specifications. That is, the generalized average mortality model includes not only the demographic, socioeconomic, and climatological determinants but also air pollution variable. The average pollution damage function developed in this study with observations from relevant SMSA’s which have pollution concentrations exceeding the threshold level represents an important departure from the prior studies in which sample observations were selected regardless of the SO₂ concentration level.     

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.     

Measurements of Morbidity and Mortality Related to Air Pollution

Examination of total deaths in New York City by day of occurrence shows periodic peaks in mortality which are associated with periods of high air pollution. These peaks are usually associated with periods of low wind speed and temperature inversion conditions which permit air pollution to build up to high levels. Unlike the experience of London, fog is not a necessary part of this picture, and therefore the presence of these episodes is often not apparent at the time to most inhabitants. A characteristic feature of these episodes is the immediate rise in mortality occurring on the same day as the peaks of pollution. A second characteristic is their frequent influence on death rates in the 45–64 year age group as well as in those over 65. These characteristics suggest that if these excess deaths are related to air pollution (as we believe to be highly likely) the mechanism is probably protean and pervasive affecting the course of a variety of different diseases through a basic physiologic effect. The relationship of morbidity in a normal urban population to air pollution is also demonstrated by time series analysis of correlation coefficients. The relation of two symptoms (cough and eye irritation) in a group of 1090 persons observed for three years is compared with two measures of air pollution (SO₂ and particulate density) to which they were exposed. Time lags of up to 28 days were introduced and a constant relationship between air pollution levels and those symptoms was demonstrated.     

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.     

Modeling Traffic-Related Air Pollution in Street Canyons of Beijing

ABSTRACT

It is important to develop a general model to accurately simulate the air pollution in urban street areas. In this paper, the Operational Street Pollution Model (OSPM) initially developed in Denmark is tested with measured data from a relatively wide and open street in Beijing. Major factors influencing the dispersion, such as emission factors, stationary source emissions, and solar radiation, are analyzed. Results show that the model can reflect the basic dispersion pattern in the street but gives systematically higher concentrations. After modifications to estimate street-level wind speed in the model, performance is obviously improved.     

A Movable Laboratory for Controlled Clinical Studies of Air Pollution Exposure

The cause of the Yokkaichi asthma episode (1960-1969) has been analyzed. It Is concluded that the respiratory diseases were due not to sulfur dioxide but to concentrated sulfuric acid mists emitted from stacks of calciners of a titanium oxide manufacturing plant located windward of the residential area.     

Surface Air Pollutant Concentration Frequency Distributions: Implications for Urban Modeling

With the development of ambient air quality standards (AAQS), the need arises to describe the characteristics of regional surface air-pollutant concentration frequency distributions. In the evaluation of land use plans, numerous agencies will be concerned with evaluating the effectiveness of emission zoning and/or control actions. On a regional basis, one means of performing this assessment lies in determining the changes in the pollutant frequency distributions resulting from control actions.

This study presents new data concerning the surface air-pollutant concentration frequency distributions observed for area sources and continuous point sources, and compares these distributions with those of the pertinent meteorological variables describing the transport and diffusion of the pollutant. The observed surface air pollutant frequency distributions are compared to those corresponding to simple modeling concepts from either an urban area source or a continuous point source. For an urban source and a relatively inert pollutant like CO, we found that the observed frequency distribution for CO surface air concentration parallels the approximately log-normal frequency distribution of the reciprocal of the wind speed. We show that the constant relating these two well-correlated frequency distributions can be determined either experimentally or with a numerical simulation model of air pollution. The usefulness of numerical models in air pollution is discussed.     

Spatial Modeling for Air Pollution Monitoring Network Design: Example of Residential Woodsmoke

Abstract

The purpose of this paper is to demonstrate how to develop an air pollution monitoring network to characterize small-area spatial contrasts in ambient air pollution concentrations. Using residential woodburning emissions as our case study, this paper reports on the first three stages of a four-stage protocol to measure, estimate, and validate ambient residential woodsmoke emissions in Vancouver, British Columbia. The first step is to develop an initial winter nighttime woodsmoke emissions surface using inverse-distance weighting of emissions information from consumer woodburning surveys and property assessment data. Second, fireplace density and a compound topo-graphic index based on hydrological flow regimes are used to enhance the emissions surface. Third, the spatial variation of the surface is used in a location-allocation algorithm to design a network of samplers for the woodsmoke tracer compound levoglucosan and fine particulate matter. Measurements at these network sites are then used in the fourth stage of the protocol (not presented here): a mobile sampling campaign aimed at developing a high-resolution surface of woodsmoke concentrations for exposure assignment in health effects studies. Overall the results show that relatively simple data inputs and spatial analysis can be effective in capturing the spatial variability of ambient air pollution emissions and concentrations.     

Infant Mortality and Air Pollution: A Comprehensive Analysis of U.S. Data for 1990

ABSTRACT

This paper uses U.S. linked birth and death records to explore associations between infant mortality and environmental factors, based on spatial relationships. The analysis considers a range of infant mortality end points, regression models, and environmental and socioeconomic variables. The basic analysis involves logistic regression modeling of individuals; the cohort comprises all infants born in the United States in 1990 for whom the required data are available from the matched birth and death records. These individual data include sex, race, month of birth, and birth weight of the infant, and personal data on the mother, including age, adequacy of prenatal care, and smoking and education in most instances. Ecological variables from Census and other sources are matched on the county of usual residence and include ambient air quality, elevation above sea level, climate, number of physicians per capita, median income, racial and ethnic distribution, unemployment, and population density. The air quality variables considered were 1990 annual averages of PM₁₀, CO, SO₂, SO₄ ^2-, and “non-sulfate PM₁₀” (NSPM₁₀—obtained by subtracting the estimated SO₄ ^2-mass from PM₁₀). Because all variables were not available for all counties (especially maternal smoking), it was necessary to consider various subsets of the total cohort.

We examined all infant deaths and deaths by age (neonatal and postneonatal), by birth weight (normal and low [<2500 g]), and by specific causes within these categories. Special attention was given to sudden infant death syndrome (SIDS). For comparable modeling assumptions, the results for PM₁₀ agreed with previously published estimates; however, the associations with PM₁₀ were not specific to probable exposures or causes of death and were not robust to changes in the model and/or the locations considered. Significant negative mortality associations were found for SO₄ ^2-. There was no indication of a role for outdoor PM_2.5, but possible contributions from indoor air pollution sources cannot be ruled out, given higher SIDS rates in winter, in the north and west, and outside of large cities.     

Measurement of Photochemical Air Pollution with a Sensitive Monitoring Plant

With newly developed monitoring techniques, investigators used the sensitive tobacco variety, Bel-W3, as a monitor for photochemical air pollution at different locations within 75 miles of Cincinnati, Ohio. Observations during the summers of 1966 through 1968 revealed almost daily injury to monitoring plants, fairly uniform total seasonal injury at all locations, and a marked variation in both oxidant and injury from one season to another within the city. The relationship between oxidant level and injury was not found to be consistent.     

Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas.

Implications: In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.     

The United Nations Conference on the Human Environment Its Implications for Air Pollution Prevention Associations

In today's world of misunderstanding, confusion, and conflict man is sadly in need of some force for pulling together and unifying his efforts for peace, progress, safety, and health upon his native Planet. During the latter days of the Conference, when delegates from large nations and small nations and rich nations and poor nations were working tirelessly to reach agreement on a Declaration on the Human Environment, and during the closing hours of the Conference when the Declaration was approved by unanimous vote, it appeared to many persons that the environment might well be such a unifying force for mankind. Throughout the early days of the Stockholm sessions, the conflict of ideologies and political Dr. Barthel is the Director of the Institute of Environmental Sciences, Miami University, Oxford, Ohio 45056. He attended the Stockholm Conference as an accredited representative of the International Union of Air Pollution Associations. principles and severe disagreement on specific issues relating to the environment were all too apparent, but through pertinacity and splendid Conference leadership, differences were resolved and wide-scale agreements reached.     

Estimating the Effect of Being Indoors on Total Personal Exposure to Outdoor Air Pollution

A personal air quality model (PAQM) has been developed to estimate the effect of being indoors on total personal exposure to outdoor-generated air pollution. Designed to improve air toxics risk assessment, PAQM accounts for individual hourly activity patterns, indoor-outdoor differences, physical exercise level, and geographic location for up to 56 different population groups. Unique hourly activity profiles are specified for each population group; group members are assigned each hour to one of up to 10 different indoor and outdoor microenvironments. To illustrate PAQM use, we apply it to two example cases: a long-term example representative of situations where pollutant health impact is related to integrated exposure (as in the case of potentially carcinogenic air toxics) and a short-term example representative of situations where health impact is related to acute exposure to peak concentrations (as with ozone).

Case study results illustrate that personal exposure, and thus health risk, attributable to outdoor-generated air pollution is sensitive to indoor-outdoor differences and population mobility. Where health impact is related to long-term integrated exposure (e.g., air toxics), exposure and subsequent risk are likely to be lower than that estimated by previous modeling techniques which do not account for such effects.     

The Crisis in Air Pollution Manpower Development

There is a crisis in air pollution manpower development within the United States today. This is the conclusion drawn from a series of three studies recently conducted by the National Air Pollution Manpower Development Advisory Committee. These studies, designed to define the essential components of a total manpower development program and to evaluate current efforts on specific segments of such a program, showed that the existing Federal manpower program fails to address many of the problem areas needing attention, that greater effort needs to be directed to meeting the air pollution educational requirements of State highway departments and planning agencies, and that the quality of most graduate level university programs in air pollution control is on the decline because of the withdrawal of Federal financial support.     

A Preliminary Study of Modeling the Air Pollution Effects fromTraffic Engineering Alternatives

Three separate mathematical models were combined to calculate the changes in carbon monoxide (CO) concentrations that might result from traffic engineering changes. The three models used were: (1) The Dynamic Highway Transportation model (DHTM) which relates traffic flow patterns to physical parameters and traffic signal characteristics of a network; (2) an emission model that predicts CO emissions from traffic flow parameters such as number of stops, idling time, etc; and (3) the APRAC-1A urban diffusion model which calculates CO concentrations from source distributions and meteorological factors. The composite model was applied to traffic in downtown Chicago for a specific set of meteorological conditions. Results are compared for two traffic signal control schemes. In those blocks where concentrations were highest, the model indicates a 20% reduction is possible through improved traffic signal controls. The model should be useful for testing other traffic control measures.