Assessing the impact of differential measurement error on estimates of fine particle mortality

In air pollution epidemiology, error in measurements of correlated pollutants has been advanced as a reason to distrust regressions that find statistically significant weak associations. Much of the related debate in the literature and elsewhere has been qualitative. To promote quantitative evaluation of such errors, this paper develops an air pollution time-series model based on correlations among unit-normal variables. Assuming there are no other sources of bias present, the model shows the expected amount of relative bias in the regression coefficients of a bivariate regression of coarse and fine particulate matter measurements on daily mortality. The model only requires information on instrumental error and spatial variability, along with the observed regression coefficients and information on the true fine-course correlation. Analytical results show that if one pollutant is truly more harmful than the other, then it must be measured more precisely than the other in order not to bias the ratio of the fine and course regression coefficients. Utilizing published data, a case study of the Harvard Six-Cities study illustrates use of the model and emphasizes the need for data on spatial variability across the study area. Current epidemiology time-series regressions can use this model to address the general concern of correlated pollutants with differing measurement errors.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

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 (PM2.5 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.     

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.     

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.     

A New Multipollutant,No-Threshold Air Quality Health Index Based on Short-Term Associations Observed in Daily Time-Series Analyses

Abstract

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0–10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multi-pollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 µm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.     

A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0-10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multipollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 microm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.     

Air pollution and mortality: A history

Mortality is the most important health effect of ambient air pollution and has been studied the longest. The earliest evidence relates to fog episodes but with the development of more precise methods of investigation it is still possible to discern short-term temporal associations with daily mortality at the historically low levels of air pollution that now exist in most developed countries. Another early observation was that mortality was higher in more polluted areas. This has been confirmed by modern cohort studies that account for other potential explanations for such associations. There does not appear to be a threshold of effect within the ambient range of concentrations. Advances in the understanding of air pollution and mortality have been driven by the combined development of methods and biomedical concepts. The most influential methodological developments have been in time-series techniques and the establishment of large cohort studies, both of which are underpinned by advances in data processing and statistical analysis. On the biomedical side two important developments can be identified. One has been the application of the concept of multifactorial disease causation to explaining how air pollution may affect mortality at low levels and why thresholds are not obvious at the population level. The other has been an increasing understanding of how air pollution may plausibly have pathophysiological effects that are remote from the lung interface with ambient air. Together, these advances have had a profound influence on policies to protect public health. Throughout the history of air pollution epidemiology, mortality studies have been central and this will continue because of the widespread availability of mortality data on a large population scale and the weight that mortality carries in estimating impacts for policy development.     

Meta-analysis of time-series studies of air pollution and mortality: effects of gases and particles and the influence of cause of death,age, and season

A comprehensive, systematic synthesis was conducted of daily time-series studies of air pollution and mortality from around the world. Estimates of effect sizes were extracted from 109 studies, from single- and multipollutant models, and by cause of death, age, and season. Random effects pooled estimates of excess all-cause mortality (single-pollutant models) associated with a change in pollutant concentration equal to the mean value among a representative group of cities were 2.0% (95% CI 1.5-2.4%) per 31.3 microg/m3 particulate matter (PM) of median diameter < or = 10 microm (PM10); 1.7% (1.2-2.2%) per 1.1 ppm CO; 2.8% (2.1-3.5%) per 24.0 ppb NO2; 1.6% (1.1-2.0%) per 31.2 ppb O3; and 0.9% (0.7-1.2%) per 9.4 ppb SO2 (daily maximum concentration for O3, daily average for others). Effect sizes were generally reduced in multipollutant models, but remained significantly different from zero for PM10 and SO2. Larger effect sizes were observed for respiratory mortality for all pollutants except O3. Heterogeneity among studies was partially accounted for by differences in variability of pollutant concentrations, and results were robust to alternative approaches to selecting estimates from the pool of available candidates. This synthesis leaves little doubt that acute air pollution exposure is a significant contributor to mortality.     

Significant Relationships Concerning Exponential Transmission or Penetration

This paper reviews the statistical evidence linking human mortality with air pollution due to sulfur oxides and particulates. Three types of analyses are discussed: episodic increases in mortality coincident with high pollution, perturbations in mortality in a given city as a time-series in relation to perturbations in air quality, and comparisons of geographic differentials in both pollution and mortality rates. The paper concludes that there are no reliable statistical associations between SO _x and mortality, but that particulates are in some cases associated with excess mortality. Establishing whether the association is in fact causal would require elimination of potential confounding effects such as occupational exposures.     

Meta-Analysis of Time-Series Studies of Air Pollution and Mortality: Effects of Gases and Particles and the Influence of Cause of Death,Age, and Season

Abstract

A comprehensive, systematic synthesis was conducted of daily time-series studies of air pollution and mortality from around the world. Estimates of effect sizes were extracted from 109 studies, from single- and multipollutant models, and by cause of death, age, and season. Random effects pooled estimates of excess all-cause mortality (single-pollutant models) associated with a change in pollutant concentration equal to the mean value among a representative group of cities were 2.0% (95% CI 1.5-2.4%) per 31.3 μg/m³ particulate matter (PM) of median diameter <10 μm (PM₁₀); 1.7% (1.2-2.2%) per 1.1 ppm CO; 2.8% (2.1-3.5%) per 24.0 ppb NO₂; 1.6% (1.1-2.0%) per 31.2 ppb O₃; and 0.9% (0.7-1.2%) per 9.4 ppb SO₂ (daily maximum concentration for O₃, daily average for others). Effect sizes were generally reduced in multipollutant models, but remained significantly different from zero for PM₁₀ and SO₂. Larger effect sizes were observed for respiratory mortality for all pollutants except O₃. Heterogeneity among studies was partially accounted for by differences in variability of pollutant concentrations, and results were robust to alternative approaches to selecting estimates from the pool of available candidates. This synthesis leaves little doubt that acute air pollution exposure is a significant contributor to mortality.     

A critical assessment of shrinkage-based regression approaches for estimating the adverse health effects of multiple air pollutants

Most investigations of the adverse health effects of multiple air pollutants analyse the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. Concerns have been raised about this type of analysis, and it has been stated that new methodology or models should be developed for investigating the adverse health effects of multiple air pollutants. In this paper, we introduce the use of the lasso for this purpose and compare its statistical properties to those of ridge regression and the Poisson log-linear model. Ridge regression has been used in time series analyses on the adverse health effects of multiple air pollutants but its properties for this purpose have not been investigated. A series of simulation studies was used to compare the performance of the lasso, ridge regression, and the Poisson log-linear model. In these simulations, realistic mortality time series were generated with known air pollution mortality effects permitting the performance of the three models to be compared. Both the lasso and ridge regression produced more accurate estimates of the adverse health effects of the multiple air pollutants than those produced using the Poisson log-linear model. This increase in accuracy came at the expense of increased bias. Ridge regression produced more accurate estimates than the lasso, but the lasso produced more interpretable models. The lasso and ridge regression offer a flexible way of obtaining more accurate estimation of pollutant effects than that provided by the standard Poisson log-linear model.     

Air pollution and health studies in China--policy implications

During the rapid economic development in China, ambient air pollutants in major cities, including PM10 (particulate matter with aerodynamic diameter < or =10 microm) and SO2 have been reduced due to various measures taken to reduce or control sources of emissions, whereas NO2 is stable or slightly increased. However, air pollution levels in China are still at the higher end of the world level. Less information is available regarding changes in national levels of other pollutants such as PM2.5 and ozone. The Chinese Ministry of Environmental Protection (MOEP) set an index for "controlling/reducing total SO2 emissions" to evaluate the efficacy of air pollution control strategy in the country. Total SO2 emissions declined for the first time in 2007. Chinese epidemiologic studies evidenced adverse health effects of ambient air pollution similar to those reported from developed countries, though risk estimates on mortality/morbidity per unit increase of air pollutant are somewhat smaller than those reported in developed countries. Disease burden on health attributable to air pollution is relatively greater in China because of higher pollution levels. Improving ambient air quality has substantial and measurable public health benefits in China. It is recommended that the current Chinese air quality standards be updated/revised and the target for "controlling/reducing total SO2 emissions" be maintained and another target for "reducing total NO2 emissions" be added in view of rapid increase in motor vehicles. Continuous and persistent efforts should be taken to improve ambient air quality.     

Daily mortality and air pollution in The Netherlands

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 micrograms/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.     

Ambient Air Pollution and Daily Pediatric Hospitalizations for Asthma (5 pp)

Background, Aim and Scope A series of severe air pollution episodes in Europe and North America prior to 1960 have focused scientific and regulatory attention on the adverse effects of air pollution on human health. As a consequence of significant reductions in ambient air pollution levels in the intervening years, scientists and public health officials have become more concerned with the potential health effects of exposure to routine concentrations of air pollution. Several recent time series studies conducted world-wide have found relatively low levels of air pollutants that are below national standards were associated with adverse effects on mortality and morbidity. This study examined the effects of ambient air pollution indicators on the daily rate of pediatric hospital admissions for asthma in the Oklahoma City Metropolitan area from 2001-2003. Results: Negative binomial regression analysis revealed significant relationships between the total number of hospitalizations per day and the one-hour maximum NO2 level, the proportion of susceptible children < 5 years old, and the ratio of temperature to humidity. Discussion: This study of the total number of children aged ≤ 14 years old experiencing hospitalizations on a daily basis in the Oklahoma City area from 2001-2003 underscores factors other than ambient air pollution, especially when concentrations are low, affect hospitalizations for pediatric asthma. For example, information related to indoor air quality, health care, family history, and exposure to environmental tobacco smoke and other irritants are not obtainable. Yet, those factors are risk drivers for asthma. Similarly, health privacy requirements prevented obtaining data on physiological factors specific to each child such as differentials in airways functional capacity or other impairments influenced asthma exacerbation. This makes calculating relative risk inappropriate. Conclusions: Although ambient air pollution concentrations and meteorological conditions influence pediatric asthma hospitalizations, they are not the major predictors in the Oklahoma City metropolitan area. This is consistent with other research that finds limited effects associated with low levels for concentrations of the criteria pollutants.     

Long-term associations of morbidity with air pollution: A catalog and synthesis

I searched the National Institutes of Health MEDLINE database through January 2017 for long-term studies of morbidity and air pollution and cataloged them with respect to cardiovascular, respiratory, cancer, diabetes, hospitalization, neurological, and pregnancy-birth endpoints. The catalog is presented as an online appendix. Associations with PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), PM₁₀ (PM with an aerodynamic diameter <10 μm), and nitrogen dioxide (NO₂) were evaluated most frequently among the 417 ambient air quality studies identified. Associations with total suspended particles (TSP), carbon, ozone, sulfur, vehicular traffic, radon, and indoor air quality were also reported. I evaluated each study in terms of pollutant significance (yes, no), duration of exposure, and publication date. I found statistically significant pollutant relationships (P < 0.05) in 224 studies; 220 studies indicated adverse effects. Among 795 individual pollutant effect estimates, 396 are statistically significant. Pollutant associations with cardiovascular indicators, lung function, respiratory symptoms, and low birth weight are more likely to be significant than with disease incidence, heart attacks, diabetes, or neurological endpoints. Elemental carbon (EC), traffic, and PM_2.5 are most likely to be significant for cardiovascular outcomes; TSP, EC, and ozone (O₃) for respiratory outcomes; NO₂ for neurological outcomes; and PM₁₀ for birth/pregnancy outcomes. Durations of exposure range from 60 days to 35 yr, but I found no consistent relationships with the likelihood of statistical significance. Respiratory studies began ca. 1975; studies of diabetes, cardiovascular, and neurological effects increased after about 2005. I found 72 studies of occupational air pollution exposures; 40 reported statistically significant adverse health effects, especially for respiratory conditions. I conclude that the aggregate of these studies supports the existence of nonlethal physiological effects of various pollutants, more so for non–life-threatening endpoints and for noncriteria pollutants (TSP, EC, PM_2.5 metals). However, most studies were cross-sectional analyses over limited time spans with no consideration of lag or disease latency. Further longitudinal studies are thus needed to investigate the progress of disease incidence in association with air pollution exposure.

Implications: Relationships of air pollution with excess mortality are better known than with long-term antecedent morbidity. I cataloged 489 studies of cardiovascular, respiratory, cancer, and neurological effects, diabetes, and birth outcomes with respect to 12 air pollutants. About half of the studies reported statistically significant relationships, more frequently with noncriteria than with criteria pollutants. Indoor and cumulative exposures, coarse or ultrafine particles, and organic carbon were seldom considered. Significant relationships were more likely with less-severe endpoints such as blood pressure, lung function, or respiratory symptoms than with incidence of cancer, chronic obstructive pulmonary disease (COPD), heart failure, or diabetes. Most long-term studies are based on spatial relationships; longitudinal studies are needed to link the progression of pollution-related morbidity to mortality, especially for the cardiovascular system.     

Air Pollution Patterns In New York City

Some preliminary analyses of data selected from three years of smoke shade and sulfur dioxide measurements from the forty air monitoring stations in New York City are presented. The purpose of these analyses is to investigate the spatial-temporal variation in concentration of these pollutants throughout the five boroughs of the city. Air pollution health effects studies in New York City have often used city-wide daily morbidity or mortality statistics and related them to air pollution levels obtained from a single monitoring station. The question of whether readings at one station in New York City can adequately represent the air pollution exposure for the population in the five boroughs is examined in this paper. Some samples of correlation matrices of daily pollution averages obtained from the forty air monitoring stations are presented to illustrate the day-to-day variation in pollution in various sections of New York City. It was found that interstation correlations are not high enough to justify the use of one central pollution measuring station as representative of a large metropolitan area. Sulfur dioxide correlates better between stations than smoke shade; this may reflect the different nature and spatial distribution of sources of the two pollutants. Close proximity of stations, or the fact that they were at similar heights above street or sea level did not necessarily lead to higher correlation coefficients.     

Air Pollution Research Needs: Herbaceous and Ornamental Plants and Agriculturally Generated Pollutants

Effects of various air pollutants on economically important crops and ornamentals have been studied since before the turn of the century.

Summaries of this research on the effects of air pollutants, that have appeared in criteria documents developed by the Environmental Protection Agency, should be reviewed with respect to differences in plant susceptibility found in various regions of the country. These susceptibility differences are associated with variations in both environmental conditions and distribution of pollutants. Research efforts on air pollution injury to vegetation have often been poorly coordinated leaving many gaps in our knowledge. A better assessment of the impact of air pollution on vegetation is required to attain realistic controls for pollutants affecting agriculture. Research areas of major concern include: baseline information on effects of pollutants on agricultural productivity; dose-response information to support predictive mathematical models for acute and chronic studies of growth, yield, and quality effects; effects of pollutants interacting with other pollutants and with insects and plant diseases; mechanisms of pollutant action; genetic changes related to pollutant effects; effects of environmental stresses on plant response to pollutants; evaluation of plants including soil microbes as pollutant sinks; development of techniques to minimize pollutant effects; and, the effects of agricultural chemicals as air pollutants. There is a need for studies that consider the whole plant in its natural environment. Conceptual models interrelating pollutant effects and their interactions and ultimately mathematical models will be needed to develop an intelligent approach to land management. The effects of agriculturally produced pollutants on plants and other receptors must be identified and quantified.     

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.     

Air Pollution and Mortality: The Implications of Uncertainties in Regression Modeling and Exposure Measurement

In a previous paper,¹ we showed that the mean effects on daily mortality associated with air pollution are essentially the same for gases and particulate matter (PM) and are invariant with respect to particle size and composition, based on 27 statistical studies that had been published at that time. Since then, a new analysis² reported stronger mortality associations for the fine fractions of PM obtained from dichotomous samplers, relative to the coarse fractions. In this paper, we show that differential measurement errors known to be present in dichotomous sampler data preclude reliable determination of such statistical relationships by particle size. Further, it is necessary to consider gaseous pollutants simultaneously with particles to provide robust estimates of the responsibilities for the implied daily mortality gradients. Finally, certain regression model specifications may be sensitive to differences in frequency distribution characteristics according to particle size.     

Fiber Glass Fabric Filters for High Temperature Dust and Fume Control

Foliar markings on vegetation have proven a highly sensitive criterion for the presence of many air pollutants; proper evaluation of such effects can serve as a valuable and inexpensive tool for delineating an air pollution condition. Injury symptoms from fluoridt, sulfur dioxide, photochemical oxidants and other pollutants have been described and can be recognized by experienced observers. Field studies provide a valuable technique for appraising an air pollution problem when diagnosis is not confused by other factors. Careful inspection can avert difficulties arising in diagnosis where similar symptoms are produced by agents other than air pollutants. Several factors must be considered in appraising injury. These include a knowledge of the relative sensitivity of plant species to various pollutants, the syndrome of injury on a number of plants and species, and distribution and geographic relation of affected plants to the suspected source. Background information on cultural, environmental, disease and insect conditions which might be responsible for, or modify, foliar markings or chronic effects in question must also be understood. For some pollutants a chemical analysis of foliage and air may prove helpful. When these factors are studied, the presence, distribution and magnitude of an air pollution situation can be evaluated, thus providing a sensitive criterion of air quality.