Spatial and temporal variations in traffic-related particulate matter at New York City high schools

Relatively little is known about exposures to traffic-related particulate matter at schools located in dense urban areas. The purpose of this study was to examine the influences of diesel traffic proximity and intensity on ambient concentrations of fine particulate matter (PM_2.5) and black carbon (BC), an indicator of diesel exhaust particles, at New York City (NYC) high schools. Outdoor PM_2.5 and BC were monitored continuously for 4–6 weeks at each of 3 NYC schools and 1 suburban school located 40 km upwind of the city. Traffic count data were obtained using an automated traffic counter or video camera. BC concentrations were 2–3 fold higher at urban schools compared with the suburban school, and among the 3 urban schools, BC concentrations were higher at schools located adjacent to highways. PM_2.5 concentrations were significantly higher at urban schools than at the suburban school, but concentrations did not vary significantly among urban schools. Both hourly average counts of trucks and buses and meteorological factors such as wind direction, wind speed, and humidity were significantly associated with hourly average ambient BC and PM_2.5 concentrations in multivariate regression models. An increase of 443 trucks/buses per hour was associated with a 0.62 μg/m³ increase in hourly average BC at an NYC school located adjacent to a major interstate highway. Car traffic counts were not associated with BC. The results suggest that local diesel vehicle traffic may be important sources of airborne fine particles in dense urban areas and consequently may contribute to local variations in PM_2.5 concentrations. In urban areas with higher levels of diesel traffic, local, neighborhood-scale monitoring of pollutants such as BC, which compared to PM_2.5, is a more specific indicator of diesel exhaust particles, may more accurately represent population exposures.     

STREAM CHEMISTRY IN THE SOUTHERN BLUE RIDGE: FEASIBILITY OF A REGIONAL SYNOPTIC SAMPLING APPROACH1

ABSTRACT: A pilot study, which was conducted in the Southern Blue Ridge geographical province of the Southeastern U.S., demonstrated the feasibility of a probability-based regional synoptic design for the National Stream Survey, which is a project aimed at estimating the number and percentage of streams in various regions of the U.S. that are acidic or at risk from acid deposition. Estimated population distributions for key chemical variables were not appreciably affected by week-to-week variability in stream chemistry during the spring index period chosen for the study. Differences were observed in estimated acid neutralizing capacity (ANC), nitrate, and pH frequency distributions between spring and summer. Observations made at the downstream node did not represent the chemistry of the entire reach for some variables (ANC and nitrate) as indicated by differences in chemical concentrations between upstream and downstream sampling locations. Coefficients of variation in chemical species were low enough to provide a reasonably stable classification of streams based on ANC. Although median ANC, sulfate, and nitrate concentrations were quite low in the region, the probability of finding streams with ph < 6.3 is less than 1.3 percent at the α= 0.05 confidence level.     

On the use of expert judgment to characterize uncertainties in the health benefits of regulatory controls of particulate matter

Health benefits assessment is an analytic tool used extensively by the U.S. Environmental Protection Agency (EPA) in characterizing the costs and benefits of air quality regulations. In a 2002 review of EPA methods, the U.S. National Research Council (NRC) called on EPA to more fully account for and communicate uncertainties in estimates of the health benefits of air pollution regulations. In particular, the NRC recommended that EPA use expert judgment to quantify uncertainties in cases where empirical estimates are lacking. In response, EPA developed and carried out an expert elicitation (EE) study to quantify uncertainties in the effects of fine particulate matter (PM_2.5) on mortality in the U.S. This work has yielded new estimates of the uncertainty distribution of a key relationship – the concentration–response (C–R) function – used around the world in benefits analyses for air quality regulations. This paper discusses the ways in which the EE results have informed and influenced recent regulatory impact analyses (RIAs) carried out by EPA to characterize and communicate the health benefits of regulations affecting ambient PM_2.5 concentrations. Given the growing importance of PM benefits analysis across the globe, recent developments pioneered by EPA could have widespread relevance.     

Correspondence between spatial patterns in fish assemblages in ohio streams and aquatic ecoregions

Land classification systems can be useful for assessing aquatic ecosystems if relationships among them exist. Because the character of an aquatic ecosystem depends to a large extent upon the character of the landscape it drains, spatial patterns in aquatic ecosystems should correspond to patterns in the landscape. To test this hypothesis, the US state of Ohio was divided into four aquatic ecoregions based on an analysis of spatial patterns in the combination of land-surface form, land use, potential natural vegetation, and soil parent material. During the period July–October 1983, fish assemblages were sampled in 46 streams that were representative of the ecoregions, and that had watersheds relatively undisturbed by human activities. Spatial patterns of the fish assemblages were examined relative to the ecoregions; distinct regional differences were identified. The assemblages differed most between the Huron/Erie Lake Plain region and the Western Allegheny Plateau region; assemblages in the Eastern Corn Belt Plains and the Erie/Ontario Lake Plain-Interior Plateau regions were intermediate. This pattern also reflects the gradient in landscape character as one moves from the northwest to the southeast of Ohio.     

Environmental Modeling and Methods for Estimation of the Global Health Impacts of Air Pollution

Air pollution is increasingly recognized as a significant contributor to global health outcomes. A methodological framework for evaluating the global health-related outcomes of outdoor and indoor (household) air pollution is presented and validated for the year 2005. Ambient concentrations of PM2.5 are estimated with a combination of energy and atmospheric models, with detailed representation of urban and rural spatial exposures. Populations dependent on solid fuels are established with household survey data. Health impacts for outdoor and household air pollution are independently calculated using the fractions of disease that can be attributed to ambient air pollution exposure and solid fuel use. Estimated ambient pollution concentrations indicate that more than 80% of the population exceeds the WHO Air Quality Guidelines in 2005. In addition, 3.26?billion people were found to use solid fuel for cooking in three regions of Sub Saharan Africa, South Asia and Pacific Asia in 2005. Outdoor air pollution results in 2.7?million deaths or 23?million disability adjusted life years (DALYs) while household air pollution from solid fuel use and related indoor smoke results in 2.1?million deaths or 41.6?million DALYs. The higher morbidity from household air pollution can be attributed to children below the age of 5 in Sub Saharan Africa and South Asia. The burden of disease from air pollution is found to be significant, thus indicating the importance of policy interventions.     

On the propagation of error in air pollution measurements

Four methods for estimating the uncertainties in air pollution measurements are outlined. The approaches are: analytical solution-approximation; application of distribution theory; experimentation; and simulation. The advantages and disadvantages of each method are illustrated using data from High-Volume air samplers, the instrument most commonly used for monitoring ambient concentrations of airborne particles.Dr Evans is Assistant Professor of Environmental Science and Mr Kinney is a doctoral candidate in the Department of Environmental Science and Physiology, Harvard School of Public Health. Dr Cooper is at the Manufacturing Research Laboratory, Thomas J. Watson Research Center, IBM, Yorktown Heights, NY.     

SUITABILITY ANALYSIS FOR SELECTION OF PIPELINE ROUTES1

ABSTRACT: A brief review of environmental assessment methods is presented as an introduction to a study of environmental management problems in a coastal area of southern Louisiana. The assessment method used in the study is called suitability analysis and involves the use of matrices. The matrix approach is simply a convenient method for organizing all factors representing environmental concerns in a region. The matrices proved to be very useful in defining the present state of an environmental regime and in maintaining an inventory of regional features and potential impacts. The method is described in detail and illustrated by evaluating the potential impacts of a major pipeline construction job in the area. Of major concern is the potential impact on the water resources of the region. Disruption to the natural drainage could be detremental, and affect the suitability of available water for a given use. Limitations of the method are discussed and potential areas for improvement and research are noted. Coupled with an economic assessment, the suitability analysis method should prove beneficial for selecting development sites for industries, residential areas, and other construction activities.