Correlations between short-term mobile monitoring and long-term passive sampler measurements of traffic-related air pollution.

Mobile monitoring has provided a means for broad spatial measurements of air pollutants that are otherwise impractical to measure with multiple fixed site sampling strategies. However, the larger the mobile monitoring route the less temporally dense measurements become, which may limit the usefulness of short-term mobile monitoring for applications that require long-term averages. To investigate the stationarity of short-term mobile monitoring measurements, we calculated long term medians derived from a mobile monitoring campaign that also employed 2-week integrated passive sampler detectors (PSD) for NOx, Ozone, and nine volatile organic compounds at 43 intersections distributed across the entire city of Baltimore, MD. This is one of the largest mobile monitoring campaigns in terms of spatial extent undertaken at this time. The mobile platform made repeat measurements every third day at each intersection for 6-10 minutes at a resolution of 10 s. In two-week periods in both summer and winter seasons, each site was visited 3-4 times, and a temporal adjustment was applied to each dataset. We present the correlations between eight species measured using mobile monitoring and the 2-week PSD data and observe correlations between mobile NOx measurements and PSD NOx measurements in both summer and winter (Pearson's r = 0.84 and 0.48, respectively). The summer season exhibited the strongest correlations between multiple pollutants, whereas the winter had comparatively few statistically significant correlations. In the summer CO was correlated with PSD pentanes (r = 0.81), and PSD NOx was correlated with mobile measurements of black carbon (r = 0.83), two ultrafine particle count measures (r =0.8), and intermodal (1-3 µm) particle counts (r = 0.73). Principal Component Analysis of the combined PSD and mobile monitoring data revealed multipollutant features consistent with light duty vehicle traffic, diesel exhaust and crankcase blow by. These features were more consistent with published source profiles traffic-related air pollutants than features based on the PSD data alone. Short-term mobile monitoring shows promise for capturing long-term spatial patterns of traffic-related air pollution, and is complementary to PSD sampling strategies.

Protection efficacy of gloves against components of the solvent in a sprayed isocyanate coating utilizing a reciprocating permeation panel.

OBJECTIVES: Determine protection effectiveness of 5-mil natural rubber latex (0.13-mm), 5-mil nitrile rubber (0.13-mm), and 13-mil butyl rubber (0.33-mm) glove materials against solvents present in a commonly used automotive clear coat formulation using a novel permeation panel. The latex and nitrile gloves were the type commonly used by local autobody spray painters. METHODS: Glove materials were tested by spraying an automotive clear coat onto an automated reciprocating permeation panel (permeation panel II). Temperature, relative humidity, and spray conditions were controlled to optimize clear coat loading homogeneity as evaluated by gravimetric analysis. Solvent permeation was measured using charcoal cloth analyzed by the National Institute for Occupational Safety and Health 1501 method. RESULTS: Natural rubber latex allowed 3-5 times the permeation of solvents relative to nitrile rubber for all 10 solvents evaluated: ethyl benzene, 2-heptanone, 1-methoxy-2-propyl acetate, o-xylene, m-xylene, p-xylene, n-butyl acetate, methyl isobutyl ketone, petroleum distillates, and toluene. There is a distinct behavior in solvent permeation before and after the coating dry time. Solvent permeation increased steadily before coating dry time and remained fairly constant after coating dry time. Butyl was not permeated by any of the solvents under the conditions tested. CONCLUSIONS: Commonly used 5-mil thick (0.13-mm) latex and nitrile gloves were ineffective barriers to solvents found in a commonly used clear coat formulation. Conversely, 13-mil (0.33-mm) butyl gloves were found to be protective against all solvents in the clear coat formulation.

Testing of glove efficacy against sprayed isocyanate coatings utilizing a reciprocating permeation panel.

OBJECTIVES: Modify a permeation panel to evaluate dermal protective clothing for resistance to sprayed coatings with minimal variability in spray paint loading across the test panel. Determine isocyanate protection effectiveness of natural rubber latex (5 mil or 0.13mm), nitrile rubber (5 mil or 0.13mm), and butyl rubber (13 mil or 0.33mm) glove materials against a commonly used automotive clear coat formulation. The latex and nitrile gloves were the type used by the local autobody spray painters. METHODS: Glove materials were tested by spraying paint onto an automated reciprocating permeation panel (permeation panel II). Temperature, relative humidity, and spray conditions were controlled to optimize paint loading homogeneity as evaluated by gravimetric analysis. Isocyanate permeation was measured using 1-(2-pyridyl)-piperazine-coated fiber-glass filters analyzed by a modified version of the OSHA 42/PV2034 methods. RESULTS: Latex exhibited a higher permeation rate compared with nitrile for isocyanates (1,6-hexamethylene diisocyanate (HDI) and isophorone diisocyanate monomers) and both materials presented permeation at all of the time points suggesting a fast isocyanate breakthrough. Butyl material exhibited no permeation or breakthrough for isocyanates under the tested conditions. The spray application at 69±8°F was optimally homogeneous at 45±0.5mg weight of dry clear coat per 5cm(2). CONCLUSIONS: The permeation panel II is a reliable method to assess dermal protective clothing performance against polymerizing coatings. Commonly used 5-mil (0.13-mm) latex and nitrile gloves were determined to be ineffective barriers against the isocyanates found in a commonly used clear-coat formulation while butyl gloves were protective.

Use of mobile and passive badge air monitoring data for NOX and ozone air pollution spatial exposure prediction models.

Air pollution exposure prediction models can make use of many types of air monitoring data. Fixed location passive samples typically measure concentrations averaged over several days to weeks. Mobile monitoring data can generate near continuous concentration measurements. It is not known whether mobile monitoring data are suitable for generating well-performing exposure prediction models or how they compare with other types of monitoring data in generating exposure models. Measurements from fixed site passive samplers and mobile monitoring platform were made over a 2-week period in Baltimore in the summer and winter months in 2012. Performance of exposure prediction models for long-term nitrogen oxides (NOX) and ozone (O3) concentrations were compared using a state-of-the-art approach for model development based on land use regression (LUR) and geostatistical smoothing. Model performance was evaluated using leave-one-out cross-validation (LOOCV). Models performed well using the mobile peak traffic monitoring data for both NOX and O3, with LOOCV R2s of 0.70 and 0.71, respectively, in the summer, and 0.90 and 0.58, respectively, in the winter. Models using 2-week passive samples for NOX had LOOCV R2s of 0.60 and 0.65 in the summer and winter months, respectively. The passive badge sampling data were not adequate for developing models for O3. Mobile air monitoring data can be used to successfully build well-performing LUR exposure prediction models for NOX and O3 and are a better source of data for these models than 2-week passive badge data.