Characterization of PM10 Emission Rates from Roadways in a Metropolitan Area Using the SCAMPER Mobile Monitoring Approach

The SCAMPER mobile system for measuring PM10 emission rates from paved roads was used to characterize emission rates from a wide variety of roads in the Phoenix, AZ metropolitan area. Week-long sampling episodes were conducted in March, June, September, and December. A 180 km-long route was utilized and traveled a total of 18 times. PM10 emission rate measurements were made at 5-second resolution for over 3200 km of roads with a precision of approximately 25%. The PM10 emission rates varied by over two orders of magnitude and were generally low unless the road was impacted with dust deposited by activities such as construction, sand and gravel operations, agriculture, and vehicles traveling on or near unpaved shoulders and roads. The data were tabulated into averages for each of 67 segments that the route was divided into. The segment-averaged PM10 emission rates ranged from zero to 2 mg m−1, with an average of 0.079 mg m−1. There was no significant difference in emission rates between seasons. There was a major drop in emission rates over a weekend, when dust generation activities such as construction are expected to be much reduced. By Monday, the PM10 emission rates had risen to the levels of the previous Friday. This indicates that roads quickly reach an equilibrium PM10 generating potential.

SCAMPER Monitoring Platform to Measure PM10 Emission Rates from Unpaved Roads in Real-Time

The SCAMPER method for measuring PM10 emission rates from roadways was used to evaluate mitigation methods for public unpaved roads and a treated mine haul road. The SCAMPER method uses a small trailer to measure PM10 concentrations behind a vehicle at a point that is representative of the mean PM10 concentration in the vehicle’s wake. This concentration multiplied by the frontal area has been shown to be a reasonable estimate of the emission rate in units of grams per meter traveled. On public roads it was towed by a 2006 Ford Expedition and on a mine haul road it was towed behind both the Expedition and an earth mover weighing over 150 tons fully loaded. Since the SCAMPER is capable of measuring emission rates on both paved and unpaved roadways, a direct comparison of the effectiveness of mitigation methods with respect to a similar paved road was possible.

Case Study of Pollution with Particulate Matter in Selected Locations of Polish Cities

Despite the introduction of increasingly restrictive regulations, the air quality in Poland is still considered one of the worst in Europe. Two cities (Wroclaw and Cracow) were selected for this study, so they represent a pair of Polish cities with poor air quality, and at the same time are academic cities, popular with tourists. The article focuses on the emission of particulate matter, which is one of the most dangerous components of air pollution. The focus was on particles less than 10 µm in diameter which are most often neglected at measuring stations. We have identified the sources of particulate emissions in selected locations in Wroclaw and Cracow, and then measured particles in terms of their mass and number distribution. It was noted that the PM10 emission values obtained as a result of the measurements were different from the value specified by the Inspectorate of the Environmental Protection in Poland.

Inverse AERMOD and SCIPUFF Dispersion Modeling for Farm-Level PM10 Emission Rate Assessment

HighlightsAERMOD and SCIPUFF were employed to back-calculate farm-level PM10 emission rates based on inverse modeling.Both AERMOD and SCIPUFF did not capture the diurnal and seasonal variations of farm-level PM10 emission rates.AERMOD modeling results were affected by wind speed, with higher wind speed leading to higher emission rates.Higher numbers of receptors and PM10 measurements with greater time resolution may be recommended in the future.Abstract. Air pollutant emissions from animal feeding operations (AFOs) have become a serious concern for public health and ambient air quality. Particulate matter with aerodynamic equivalent diameter less than or equal to 10 µm (PM10) is one of the major air pollutants emitted from AFOs. To assess the impacts of PM10 emissions from AFOs, knowledge about farm-level PM10 emission rates is needed but is challenging to obtain through field measurements. The inverse dispersion modeling approach provides an alternative way to estimate farm-level PM10 emission rates. In this study, two dispersion models, AERMOD and SCIPUFF, were employed to back-calculate farm-level PM10 emission rates based on hourly PM10 concentration measurements at four downwind locations in the vicinity of a commercial egg production farm in the southeast U.S. Onsite meteorological data were simultaneously recorded using a 10 m weather tower to facilitate the dispersion modeling. The modeling results were compared with PM10 emission measurements from two layer houses on the farm. Single-area source, double-area source, and double-volume source were used in AERMOD, while only single-point source was used in SCIPUFF. The inverse modeling results indicated that both SCIPUFF and AERMOD did not capture the diurnal and seasonal variations of the farm-level PM10 emission rates. In addition, the AERMOD modeling results were affected by wind speed, and higher emission rates may be predicted at higher wind speeds. The single-point source for SCIPUFF, the plume rise simplification for AERMOD, and insufficient concentration measurement resolution in response to temporal changes in wind direction may have added uncertainties to the modeling results. The results of this study suggest that more receptors covering more representative downwind locations should be considered in future modeling for farm-level emissions assessment. Moreover, ambient data collection with greater time resolution (e.g., less than one hour) is recommended to capture diurnal and seasonal patterns more rigorously. Only in this way can researchers achieve a better understanding of the effectiveness of inverse dispersion modeling for estimation of pollutant emission rates. Keywords: AERMOD, Animal feeding operations, Egg production, Farm-level emission rate, Inverse dispersion modeling, PM10, SCIPUFF.