Primary Sources of Polycyclic Aromatic Hydrocarbons to Streambed Sediment in Great Lakes Tributaries Using Multiple Lines of Evidence.

Polycyclic aromatic hydrocarbons (PAHs) are among the most widespread and potentially toxic contaminants in Great Lakes (USA/Canada) tributaries. The sources of PAHs are numerous and diverse, and identifying the primary source(s) can be difficult. The present study used multiple lines of evidence to determine the likely sources of PAHs to surficial streambed sediments at 71 locations across 26 Great Lakes Basin watersheds.

Methods for estimating uncertainty in PMF solutions: examples with ambient air and water quality data and guidance on reporting PMF results.

The new version of EPA's positive matrix factorization (EPA PMF) software, 5.0, includes three error estimation (EE) methods for analyzing factor analytic solutions: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement (BS-DISP). These methods capture the uncertainty of PMF analyses due to random errors and rotational ambiguity.

PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ.

As part of an EPA-sponsored workshop to investigate the use of source apportionment in health effects analyses, the associations between the participant's estimated source contributions of PM(2.5) for Phoenix, AZ for the period from 1995-1997 and cardiovascular and total nonaccidental mortality were analyzed using Poisson generalized linear models (GLM). The base model controlled for extreme temperatures, relative humidity, day of week, and time trends using natural spline smoothers.

PM source apportionment and health effects: 1. Intercomparison of source apportionment results.

During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models.

Aerosol particle number concentration measurements in five European cities using TSI-3022 condensation particle counter over a three-year period during health effects of air pollution on susceptible subpopulations.

In this study, long-term aerosol particle total number concentration measurements in five metropolitan areas across Europe are presented. The measurements have been carried out in Augsburg, Barcelona, Helsinki, Rome, and Stockholm using the same instrument, a condensation particle counter (TSI model 3022). The results show that in all of the studied cities, the winter concentrations are higher than the summer concentrations.

A case-crossover analysis of out-of-hospital coronary deaths and air pollution in Rome, Italy.

Rationale: Out-of-hospital coronary heart disease death is a major public health problem, but the association with air pollution is not well understood.

Objectives: We evaluated the association between daily ambient air pollution levels (particle number concentration [PNC]--a proxy for ultrafine particles [diameter < 0.1 microm], mass of particles with diameter less than 10 microm [PM10]; CO, NO2, and O3) and the occurrence of fatal, nonhospitalized coronary events.

Multilinear model for spatial pattern analysis of the Measurement of Haze and Visual Effects project.

A multilinear model was developed for the analysis of the spatial patterns and possible sources affecting haze and its visual effects in the southwestern United States. The data from the project Measurement of Haze and Visual Effects (MOHAVE) collected during the late winter and mid-summer of 1992 at the monitoring sites in four states (i.e.

Advanced factor analysis of spatial distributions of PM2.5 in the eastern United States.

This work analyzes PM2.5 24-h average concentrations measured every third day at over 300 locations in the eastern United States during 2000. The non-negative factor analytic model, Positive Matrix Factorization, has been enhanced by modeling the dependence of PM2.

Extreme Value Estimation Applied to Aerosol Size Distributions and Related Environmental Problems.

This work examines the potential connections between extreme value statistics, problems in aerosol science, and a recent technique of solving ill-posed inversion problems, called EVE (Extreme Value Estimation). EVE estimates functional of the unknown solution by searching the extreme (maximum and minimum) values of that functional within a set of acceptable solutions. The statistics of occurrence of extreme values in real life were not considered when this method was developed.