Our measurements of PM2.5 and PM10 concentrations in and around Braddock, PA, during summer and winter months 2010–2011, highlight the impact of summer morning inversion events on particulate pollution. PM concentrations showed a temporal pattern, but were relatively spatially homogenous for our sampling routes. We observed large temporal variation in short term measured PM2.5 and PM10 across multiple sampling days, including higher PM2.5 and PM10 concentrations in summer vs. winter and morning vs. afternoon. These findings provide a better understanding of the spatial and temporal variability of PM in Braddock, and provided critical information about appropriate sampling windows for future monitoring.
During summer, patterns were observed between morning and afternoon PM concentrations. The PM ratio was above 0.8 for summer sampling, suggesting fresh fine plant-related particle emissions (e.g. furnace and trucks), in contrast to re-suspension at the sampling sites; the PM ratio was above 0.6 for winter sampling, and salt spread on the street may have contributed to re-suspended PM
[29, 30]. Data on this PM ratio are sparse, and the National Resources Defense Council (NRDC) assumes this ratio is typically 60% in US cities.
. Though most influence appeared to be from fine particles, the main influence of PM10 occurred in areas directly adjacent to the plant facilities during the morning. Distance to the mill was a significant covariate in the summer sampling session (Table
2). Further, the decline of PM10 as one moved away from the plant into the community was an important spatial result for the future stationary monitoring campaign throughout Braddock (Figure
8). The spatially-created traffic variables were insignificant in the regression modeling including all stops. However, when comparing a stop that was repeated the same day over a time differential of approximately 3 h, significant differences were seen in PM concentration and traffic may be a contributor to those changes.
The current study demonstrated that spatial and temporal relationships need to be determined in a first step to adequately characterize exposure of individuals living and working in the Braddock area. These findings provide a better understanding of air pollution exposure patterns around Braddock, PA, which may have important public health and policy repercussions
Important factors included topography (i.e. elevation) and local atmospheric inversions. Elevation was a significant covariate for the winter sampling session. Fine PM in this urban area was also influenced by proximity to the steel mill transient emission events,
. During a temperature inversion, the air becomes stagnant, and the valley walls trap air pollution near the surface. Inversion was included for the summer morning PM10 model, but dropped out of significance for the PM2.5 model when the wind interaction term was incorporated (Table
2). For summer sampling, stops 21 to 25 typically recorded PM2.5 and PM10 concentrations lower than those measured at stops 1 to 5. It is likely that the observed variations are due to changes in the influences of sources. Chu et al. (2009) reported that sources to the south and southeast of the Pittsburgh Supersite significantly influenced PM2.5. Sources located in other directions from the monitoring site had less influence despite greater emissions and a high frequency of winds. Building on Chu et al. (2009), we examined the role of wind. In assessing our multiple linear regression models, wind direction appeared to be the strongest covariate for the summer and winter months. Winds have been shown to play important roles in transport of pollutants, such as photochemical transport from New York City into Connecticut
. Wind speed was positively correlated with PM2.5 concentrations during both summer and winter mornings, even though wind speed is generally negatively correlated with air pollutants. However, since the meteorology is measured at an away location in Liberty, PA, local perturbations due to dilution of primary particles from the sources could have been masked by area sources. Chu et al. (2010) demonstrated that high temperatures and relative humidity in the eastern United States may be associated with high PM2.5 concentrations to a greater extent than elevated concentrations of SO2 or O3 or high levels of UV. We did not find association with relative humidity (RH), but an inverse relationship with temperature (higher temperatures resulted in lower PM) was found in models (Table
2). One possibility for higher PM in the summer could be power plant emissions, but more likely in the eastern US it is a higher baseline caused by secondary aerosols formed by photochemical smog. A higher temperature would have broken up an inversion, resulting in lower PM concentrations from local sources; mobile monitoring occurred at specific times of the day (morning versus afternoon hours), so hourly temperature data were used instead of 24 hour average temperatures.
A strength of the mobile monitoring approach is that it allowed us to construct multiple snapshots of spatial and temporal variability in air pollution in areas immediately adjacent to mobile or stationary sources relatively quickly and inexpensively. It also provided a detailed morning versus afternoon pattern in PM concentrations for the summer months 2010, and suggested that fresh combustion and particle re-suspension may be the primary sources for PM pollution in and around Braddock. In contrast to prior mobile monitoring studies, we instituted a practice to account for session temporal variability by re-sampling the same stops at the beginning and end of the route. A criticism of many studies that aim to discover a relationship between air pollution and health is that exposure is typically characterized using measurements from a few sparsely located air quality monitoring stations, and often only one
. Mobile monitoring has been used to characterize spatial variability in black carbon concentrations for land use regression, even though spatial modeling conventionally requires longer-term measurements at multiple locations
. Conversely, our mobile monitoring approach provided preliminary insight towards understanding spatial and temporal exposure variation throughout the Braddock area.
Because the mobile monitoring devices are handheld, cost-effective (e.g. multiple samples with high frequency and mobility), and can provide real-time PM or VOC measurements, there is a possibility that communities could deploy these units after a training program conducted by skilled exposure or air pollution scientists
[37, 38]. Active neighborhood sampling could improve residents’ knowledge about local air pollution concentrations, and enable residents to investigate areas where air pollution is perceived to be elevated. By following a time- and location-specific approach, communities could collect a significant amount of repeated measures data to better understand pollution concentrations where they reside, and to identify high-pollution events. Therefore, mobile monitoring could be investigated for use in community based participatory research (CBPR) to provide neighborhood residents with the opportunity to proactively investigate potential air pollution. However, interpretation of the results will still require skilled professional analysis.
While the mobile monitoring data provided valuable information, one limitation is that a sampling interval of 3 to 5 min is too short to provide an accurate exposure profile for Braddock residents; these data primarily allow us to gain an understanding of patterns of exposure, and future studies can then be designed to better elucidate stable patterns in exposure variation, and examine associations with asthma and other chronic disease outcomes. Although ETSW operates year round, specific plant activity data would have been important in explaining the temporal variation between sampling days, but data was not available for analyses. Future monitoring will include sites with a more complete contrast in source proximity, elevation, and density of traffic, with a specific interest in morning sampling (6 AM to 11 AM), a design that results from this study, to observe potential effects of inversion events on air pollution concentrations across the Pittsburgh region. A technological limitation is that the Hazdust EPAM-5000 is calibrated using “Arizona road dust” (EDC, Plaistow, New Hampshire -personal communication), which is not representative of Pittsburgh-area aerosols. For this reason, comparisons were provided between our data and ACHD federal reference method (FRM) measurements in Pittsburgh. However, it is difficult to calibrate any continuous monitor with the local aerosol because this would require resuspending the material, changing its basic character and size distribution.
Our approach provided the foundation for the design of a longer-term air pollution monitoring strategy for Braddock and the city of Pittsburgh. Based on results from this study, city-wide sampling will be performed Monday through Friday during potential morning inversion hours (6 to 11 AM) using eight stationary monitors (two reference monitors, six distributed monitors), randomized and spatially re-allocated each week, over six weeks each season, to estimate PM2.5 in concentrations capturing the range of elevation, proximity to industry, and traffic density across the Pittsburgh metropolitan area.