Understanding intra-neighborhood patterns in PM2.5 and PM10 using mobile monitoring in Braddock, PA

Abstract

BackgroundBraddock, Pennsylvania is home to the Edgar Thomson Steel Works (ETSW), one of the few remaining active steel mills in the Pittsburgh region. An economically distressed area, Braddock exceeds average annual (>15 μg/m3) and daily (>35 μg/m3) National Ambient Air Quality Standards (NAAQS) for particulate matter (PM2.5).MethodsA mobile air monitoring study was designed and implemented in morning and afternoon hours in the summer and winter (2010–2011) to explore the within-neighborhood spatial and temporal (within-day and between-day) variability in PM2.5 and PM10.ResultsBoth pollutants displayed spatial variation between stops, and substantial temporal variation within and across study days. For summer morning sampling runs, site-specific mean PM2.5 ranged from 30.0 (SD = 3.3) to 55.1 (SD = 13.0) μg/m3. Mean PM10 ranged from 30.4 (SD = 2.5) to 69.7 (SD = 51.2) μg/m3, respectively. During summer months, afternoon concentrations were significantly lower than morning for both PM2.5 and PM10, potentially owing to morning subsidence inversions. Winter concentrations were lower than summer, on average, and showed lesser diurnal variation. Temperature, wind speed, and wind direction predicted significant variability in PM2.5 and PM10 in multiple linear regression models.ConclusionsData reveals significant morning versus afternoon variability and spatial variability in both PM2.5 and PM10 concentrations within Braddock. Information obtained on peak concentration periods, and the combined effects of industry, traffic, and elevation in this region informed the design of a larger stationary monitoring network.

Indoor air sampling for fine particulate matter and black carbon in industrial communities in Pittsburgh

“…Following on our prior studies on spatial variance in multiple ambient air pollutants across this area (Tunno et al, 2015;Shmool et al, 2014;Tunno et al, 2012), here we examined indoor PM 2.5 and black carbon (BC) concentrations in Braddock and Clairton households, during summer 2011 and winter 2012, to quantify the contribution of high outdoor concentrations in industrial communities to indoor concentrations, and to compare the contribution of outdoor concentrations vs. indoor sources. We hypothesize that the high outdoor air pollution concentrations in these communities should contribute significantly to indoor concentrations, and further hypothesize that pollutant concentrations would: (1) be higher indoors vs. outdoors, (2) vary by season, and (3) vary by indoor source activity, including cooking and smoking.…”

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

“…It offers the flexibility in monitoring pathways where the route can be customized so as to include the particular areas of concern, such as high-traffic roads or the specific sources of interest. The applicability of mobile data can be improved by the repeated measures, integrating meteorology and land use characteristics and improving the spatial and temporal characteristics of a fixedsite monitoring network (Tunno et al 2012). Many studies have used different mobile platforms (van, car, bicycle) for the personal exposure studies (Elen et al 2013;Hagler, Thoma, and Baldauf 2010;Kaur, Nieuwenhuijsen, and Colvile 2007;Krecl et al 2014;Wallace et al 2009).…”

Reduction of atmospheric fine particle level by restricting the idling vehicles around a sensitive area

“…Very local PM emissions, such as from idling operation during vehicle shortparking, might directly affect the health of the people with heart or lung disease, older adults, and children (EPA 2014). Recently, mobile monitoring has become well known in measuring the properties of PM 2.5 and has recently been used to assess exposure with high spatial variability in various geographical settings, using instrumented vehicles (Hagler, Thoma, and Baldauf 2010;Riley et al 2014;Tunno et al 2012), bicycles (Pattinson, Longley, and Kingham 2014;Peters et al 2013;Thai, McKendry, and Brauer 2008), or pedestrians with monitoring instruments (Kaur, Nieuwenhuijsen, and Colvile 2005;Zwack et al 2011aZwack et al , 2011bRakowska et al 2014). These studies introduced the advantages of mobile monitoring for investigating the spatial-temporal variations of atmospheric pollutant concentrations.…”