Aerosol Research and Inhalation Epidemiological Study (ARIES): air quality and daily mortality statistical modeling--interim results

The Aerosol Research and Inhalation Epidemiological Study (ARIES) is an EPRI-sponsored project to collect air quality and meteorological data at a single site in northwestern Atlanta, GA. Seventy high-resolution air quality indicators (AQIs) are used to examine statistical relationships between air quality and health outcome end points. Contemporaneous mortality data are collected for Fulton and DeKalb counties in Georgia. Currently, 12 months of air quality and weather data are available for analysis, from August 1998 through July 1999. The interim mortality analysis used Poisson regression in generalized additive models (GAMs). The estimated log-linear association of mortality with various AQIs was adjusted for smoothed functions of time and meteorological data. The analysis considered daily deaths due to all nonaccidental causes, deaths to persons 65 years or older, and deaths in each of the two constituent counties. The fine particle effect associated with the four mortality subgroups, using only today (lag 0), yesterday (lag 1), 2-day average (average of today and yesterday), and first difference (today minus yesterday) measurements of the air quality relative to today's number of deaths was positive for lag 0, lag 1, and 2-day average and positive only for decedents at least 65 years of age using first difference. The t values ranged from 0.81 to 1.15 for lag 0, 1.04 to 1.53 for lag 1, 1.10 to 1.66 for 2-day average, and -0.32 to 0.33 for first difference with 346 or 347 days of data. No statistically significant estimate of the linear coefficient was found for the other 14 air quality variables in our interim analysis for the four mortality subgroups. We discuss diagnostics to support these models. These interim analyses did not include an evaluation of sensitivity to a larger set of lag structures, nonlinear model specifications, multipollutant analyses, alternative weather model and smoothing model specifications, air pollution imputation schemes, or cause-specific mortality indicators, nor did they include a full reporting of model selection or goodness-of-fit indicators. No conclusion can be drawn at this time about whether the findings from subsequent studies have sufficiently greater power to detect effects comparable to those found in other U.S. cities including at least 2 or 3 years of data.     

Is daily mortality associated specifically with fine particles? Data reconstruction and replication of analyses

In 1996, Schwartz, Dockery, and Neas reported that daily mortality was more strongly associated with concentrations of PM2.5 than with concentrations of larger particles (coarse mass [CM]) in six U.S. cities ("original paper"/"original analyses"). Because of the public policy implications of the findings and the uniqueness of the concentration data, we undertook a reanalysis of these results. This paper presents results of the reconstruction of these data and replication of the original analyses using the reconstructed data. The original investigators provided particulate air pollution data for this paper. Daily weather and daily counts of total and cause-specific deaths were reconstructed from original public records. The reconstructed particulate air pollution and weather data were consistent with the summaries presented in the original paper. Daily counts of deaths in the reconstructed data set were lower than in the original paper because of restrictions on residence and place of death. The reconstruction process identified an administrative change in county codes that led to higher numbers of deaths in St. Louis. Despite these differences in daily counts of deaths, the estimated effects of particulate air pollution from the reconstructed dataset, using analytic methods as described in the original paper, produced combined effect estimates essentially equivalent to the originally published results. For example, the estimated association of a 10 micrograms/m3 increase in 2-day mean particulate air pollution on total mortality was 1.3% (95% confidence interval [CI] 0.9-1.7%, t = 6.53) for PM2.5 based on the reconstructed dataset, compared to the originally reported association of 1.5% (95% CI 1.1-1.9%, t = 7.41). For coarse particles, the estimated association from the reconstructed dataset was 0.4% (95% CI -0.2-0.9%, t = 1.43) compared to the originally reported association of 0.4% (95% CI -0.1-1.0%, t = 1.48). These results from the reconstructed data suggest that the original results reported by Schwartz, Dockery, and Neas were essentially replicated.     

Development and evaluation of the Lake Macroinvertebrate Integrity Index (LMII) for New Jersey lakes and reservoirs

In response to the recent focus by the U.S. EnvironmentalProtection Agency on bioassessment of lakes, a multimetric index was developed for New Jersey lakes and reservoirs using benthicmacroinvertebrates. Benthic samples were collected fromreference and impaired lakes with muck and intermediate sedimentsin central and northern New Jersey during summer 1997. We used astepwise process to evaluate properties of candidate metrics andselected five for the Lake Macroinvertebrate Integrity Index(LMII): Hilsenhoff Biotic Index (HBI), percent chironomidindividuals, percent collector-gatherer taxa, percentoligochaetes/leeches, and number of Diptera taxa. We scoredmetrics as the fraction of the best expected value (based on allsites) achieved at a site and summed them into the LMII. Evaluation of the LMII showed that it discriminated well betweenreference and impaired lakes and was strongly related to severalpotential stressors. Chemical and physical gradients distinguished between reference and impaired lakes, and the LMIIsummarized these gradients well. The LMII corresponded stronglywith land use, but some lakes with more urban land use stillachieved high scores. Based on a power analysis, the ability ofthe LMII to detect differences in condition was sensitive to thenumber of samples from each lake.     

Urban emissions measured with aircraft

Detailed knowledge of the quantity and composition of urban emissions is a prerequisite for successful application of atmospheric models to predict transport and distribution of primary and secondary air pollutants in the troposphere. We investigate the prospects and limitations of aircraft measurements in the determination of emission fluxes from urban areas. Our analysis focuses on data collected in September 1994 in and around Athens, Greece. Generally, emission fluxes from cities can be quantified with aircraft and with the minimum acceptable precision (uncertainty better than a factor of 2) only under very favorable meteorological conditions, namely in a homogeneous flow field in a well-mixed boundary layer. Better accuracy can be achieved only through ensemble averaging of repeated measurements. From our measurements in the Athens area, we deduced relative emission ratios of pollutant gases. With the support of ground-based measurements in a street canyon, the emission ratios NOx/CO, SO2/CO, and volatile organic compounds/CO (34 individual VOCs) could be determined with high precision. These results are very useful in analyzing differences between various existing emission inventories. Our data for VOCs reveal that the non-traffic emissions are of the same magnitude as the emissions originating from traffic.     

Remote monitoring of air pollutant emissions from point sources by a mobile lidar/sodar system

This paper describes remote monitoring of air pollutant emissions by a mobile lidar (light detection and ranging)/ sodar (sound detection and ranging) system. First, measurements are carried out in the flue gas plume of a public power plant. The investigations focus mainly on quantifying SO2 emissions, but the uncertainties of such measurements are also emphasized. Furthermore, an example providing valuable data sets for the development and validation of plume dispersion models is outlined with measurements of the dilution of SO2 along the plume axis. Series of repeated determinations of SO2 emissions show a large variation in the obtained flux values, with moderate margins of error. Incomplete recording of the plume within the individual lidar scans, induced by strong looping movements of the flue gas plume, predominantly causes the variations of flux values. Therefore, the highest flux values determined are considered to be the most exact. This is verified by a comparison of measured fluxes with in situ measurements made by the plant operators. The results further indicate that lidar measurements illustrate the location and dimension of aerosol plumes better than the location and dimension of the plumes of gaseous compounds. The wind direction affecting the plume at any moment can be determined faster by lidar than by sodar because the latter requires much longer time intervals of signal averaging. Measurements show higher concentrations of SO2 compared with results from a Gaussian plume model for periods of less than 5 min after dispersion. The findings emphasize the suitability of remote sensing for detecting emissions and for investigating the propagation and dilution of air pollutant plumes.     

Application of ground-based Lidar for studies of the dynamics of ozone in a mountainous basin

A ground-based Differential Absorption Lidar was employed to study the dynamics of atmospheric O3 within the planetary boundary layer of a basin in the 'Fichtelgebirge' mountains, NE Bavaria. In particular, the night-time dynamics of O3 linked to the ground were investigated. The Lidar system measured vertical profiles of O3 up to 1 km above ground. For detailed analysis of the night-time dynamics of ozone, supplementary data from three ground-based stations (measuring mixing ratios of O3 and NO(x), as well as meteorological parameters) are essential. The Lidar results could be evaluated with these data from various altitudes above the basin floor. For the station with the largest (vertical) distance to the ground-based Lidar, the agreement was very good at all times. The Lidar method proved to be useful for examining the spatial distribution of O3. The observed night-time decrease of O3 at the bottom of the basin was due to deposition and to advection of air masses containing less O3 from the mountain slopes.