Weixiang Zhao

On-Road Exposure to Highway Aerosols. 1. Aerosol and Gas Measurements

On-road experiments were conducted to determine the sensitivities of rats to real-world aerosol. This article summarizes the on-road aerosol and gas measurements and provides background information for the companion paper on the rat exposures. Measurements were carried out over 10 days, 6 h/day, driving a route from Rochester to Buffalo. Aerosol instrumentation used in this study included two scanning mobility particle sizers (SMPS) to determine the aerosol size distribution from 10 to 300 nm, 2 stand-alone condensation particle counters to determine the total aerosol number concentration, and an electrical aerosol detector to determine the aerosol length concentration. A thermal denuder (TD) was used with one of the SMPS instruments to determine the size distribution of the non-volatile fraction. Filter samples were collected and analyzed for elemental carbon, and gas analyzers measured ambient levels of CO, CO2, and NO. Average daily total aerosol number concentration ranged from 200,000 to 560,000 particles/cm3. Past studies on urban highways have measured total number concentrations ranging between 104 and 106 particles/cm3. The average daily NO concentration ranged from 0.10 to 0.24 ppm and the corresponding CO2 concentration ranged from 400 to 420 ppm. The average daily geometric number mean particle size determined by the SMPS ranged from 15 to 20 nm. The TD reduced the average SMPS number concentration between 87 and 95% and the SMPS volume between 54 and 83%, suggesting that most of the particles consisted of volatile material. The TD also increased the geometric number mean diameter from 15 to 20 nm to 30 to 40 nm.

On-Road Exposure to Highway Aerosols. 2. Exposures of Aged, Compromised Rats

Ambient particulate pollution is associated with adverse health effects in epidemiological studies of the elderly with cardiopulmonary diseases. We hypothesize that ultrafine particles (UFP) contribute to these effects, especially when they are freshly generated and occur at high number concentrations. Studies to determine adverse effects have been performed using laboratory-generated surrogates, diluted exhaust from stationary engines, or concentrated ambient UFPs. Methodological difficulties exist with such experiments, and questions remain about how well these particles model those found in ambient air. Freshly generated UFPs are present at high concentrations on highways and vehicle passengers are directly exposed to them. We wished to expose rats to these UFPs to test their potential to cause effects. Since such exposures have not been done before, one objective of our study was to demonstrate the feasibility of an on-road exposure study. Secondly, we wished to determine if there are significant exposure-related effects in aged, compromised rats. Old rats (21-mo F-344) were exposed directly on highways to either the aerosol (< 1 μm)/gas phase, gas phase only, or filtered air using an on-road exposure system. Some rats were pretreated with a low dose of inhaled endotoxin or with instilled influenza virus to induce lung inflammation. The exposures in compartmentalized whole-body chambers consisted of 6-h driving periods on I-90 between Rochester and Buffalo once or 3 days in a row. Endpoints related to lung inflammation, inflammatory cell activation, and acute-phase responses were measured after exposure. The on-road exposure system did not affect measured endpoints in filtered air-exposed rats, indicating that it was well tolerated by them. We observed the expected increases in response (inflammation, inflammatory cell activation) to the priming agents. We also found a significant particle-associated increase in plasma endothelin-2, suggesting alterations in vascular endothelial cell activation. In addition, we observed main effects of particles related to the acute-phase response and inflammatory-cell activation. Interactions between on-road particles and the priming agents were also found. These results suggest that exposures to on-road particle mixtures have effects on the pulmonary and cardiovascular system in compromised, old rats. Furthermore, they demonstrate that on-road exposures are feasible and could be performed in future studies with more continuous particle exposures.

Source Apportionment of Airborne Particulate Matter for the Speciation Trends Network Site in Cleveland, OH

Abstract Aerosol composition data from the Speciation Trends Network (STN) site (East 14th Street) in Cleveland, OH, were analyzed by advanced receptor model methods for source apportionment as well as by the standard positive matrix factorization (PMF) using PMF2. These different models are used in combination to test model limitations. These data were 24-hr average mass concentrations and compositions obtained for samples taken every third day from 2001 to 2003. The Multilinear Engine (ME) was used to solve an expanded model to estimate the source profiles and source contributions and also to investigate the wind speed, wind direction, time-of-day, weekend/weekday, and seasonal effects. PMF2 was applied to the same data-set. Potential source contribution function (PSCF) and conditional probability function (CPF) analyses were used to locate the regional and local sources using the resolved source contributions and appropriate meteorological data. Very little difference was observed between the results of the expanded model and the PMF2 values for the profiles and source contribution time series. The identified sources were as ferrous smelter, secondary sulfate, secondary nitrate, soil/combustion mixture, steel mill, traffic, wood smoke, and coal burning. The CPF analysis was useful in helping to identify local sources, whereas the PSCF results were only useful for regional source areas. Both of these analyses were more useful than the wind directional factor derived from the expanded factor analysis. However, the expanded analysis provided direct information on seasonality and day-of-week behavior of the sources.

Source Investigation for Ambient PM 2.5 in Indianapolis, IN

The objectives of this study were to identify the sources of the PM 2.5 in Indianapolis, Indiana and estimate their contributions to the total PM 2.5 mass concentrations by analyzing the data from the samples collected at the EPA Speciation Trends Networks (STN) site in Indianapolis, Indiana. Both positive matrix factorization (PMF2) and an expanded factor analysis model were applied. The two methods obtained essentially identical source profiles and contributions, so the results of the simpler method, PMF, are described in the formal text of this paper in detail while the corresponding results provided by the expanded factor analysis model are presented in the supplemental material for this paper. The seven resolved sources are secondary sulfate (40.2%), secondary nitrate (21.9%), gasoline emission (16.6%), diesel emission (7.9%), airborne soil (5.3%), Fe-related industries (4.4%), and Cu-related industries (2.5%). The comparison between two models suggests that PMF coupled with subsequent data analysis methods (such as CPF, PSCF, seasonal variation analysis, and weekday/weekend variation analysis) yields the results that are comparable to those of the expanded factor analysis. The results suggest that such studies of STN data can be used to assist in the development of State Implementation Plans (SIPs) for PM 2.5 .

A study of health effect estimates using competing methods to model personal exposures to ambient PM2.5.

Various methods have been developed recently to estimate personal exposures to ambient particulate matter less than 2.5 μm in diameter (PM2.5) using fixed outdoor monitors as well as personal exposure monitors. One class of estimators involves extrapolating values using ambient-source components of PM2.5, such as sulfate and iron. A key step in extrapolating these values is to correct for differences in infiltration characteristics of the component used in extrapolation (such as sulfate within PM2.5) and PM2.5. When this is not done, resulting health effect estimates will be biased. Another class of approaches involves factor analysis methods such as positive matrix factorization (PMF). Using either an extrapolation or a factor analysis method in conjunction with regression calibration allows one to estimate the direct effects of ambient PM2.5 on health, eliminating bias caused by using fixed outdoor monitors and estimated personal ambient PM2.5 concentrations. Several forms of the extrapolation method are defined, including some new ones. Health effect estimates that result from the use of these methods are compared with those from an expanded PMF analysis using data collected from a health study of asthmatic children conducted in Denver, Colorado. Examining differences in health effect estimates among the various methods using a measure of lung function (forced expiratory volume in 1 s) as the health indicator demonstrated the importance of the correction factor(s) in the extrapolation methods and that PMF yielded results comparable with the extrapolation methods that incorporated correction factors.