This paper presents and discusses the results obtained from the gravimetric and chemical analyses of the 24-hr average dichotomous samples collected from five sites in the El Paso-Cd. Juarez air quality basin between August 1999 and March 2000. Gravimetric analysis was performed to determine the temporal and spatial variations of PM 2.5 (particulate matter less than 2.5 µm in diameter) and PM 2.5-10 (particulate matter less than 10 µm but greater than 2.5 µm in diameter) mass concentrations. The results indicate that ~25% of the PM 10 (i.e., PM 2.5 + PM 2.5-10
Lordsburg Playa, a dry lakebed in the Chihuahuan Desert of southwestern New Mexico (USA), is crossed by Interstate Highway 10 (I-10). Dust from the playa threatens highway safety and has caused dozens of fatal accidents. Two numerical models—the U.S. Department of Agriculture’s Single-Event Wind Erosion Evaluation Program (SWEEP) and the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD)—were used to simulate and predict the generation and dispersion of windblown soil, dust, and PM10 from playa hotspots and estimate PM10 concentrations downwind. SWEEP simulates soil loss and particulate matter emissions from the playa surface, and AERMOD predicts the concentration of transported dust. The modeling was informed by field and laboratory data on Lordsburg Playa’s properties, soil and land use/land cover databases, and weather data from meteorological stations. The integrated models predicted that dust plumes originating on the playa—including a large, highly emissive area away from the highway and a smaller, less emissive site directly upwind of the interstate—can lead to hourly average PM10 concentrations of tens, to hundreds of thousands, of micrograms per cubic meter. Modeling results were consistent with observations from webcam photos and visibility records from the meteorological sites. Lordsburg Playa sediment contains metals, as will its dust, but human exposures will be short-term and infrequent. This study was the first to successfully combine the SWEEP wind erosion model and the AERMOD air dispersion model to evaluate PM10 dispersion by wind erosion in a playa environment. With this information, land managers will be able to understand the potential levels of dust and PM10 exposure along the highway, and better manage human health and safety during conditions of blowing dust and sand at Lordsburg Playa.
Residents living in near-road communities are exposed to traffic-related air pollutants, which can adversely affect their health. Near-road communities are expected to observe significant spatial and temporal variations in pollutant concentrations. Determining these variations in the surrounding areas can help raise awareness among government agencies of these underserved communities living near highways. This study conducted traffic and air quality measurements along with emission and dispersion modeling of the exposure to transportation emissions of a near-road urban community adjacent to the US 54 highway (US 54), with annual average daily traffic (AADT) of 107,237. The objectives of this study were (i) to develop spatial and temporal patterns of pollutant concentration variation and (ii) to apportion the differences in exposure concentrations to background concentrations and those that are contributed from major highways. It was observed that: (a) particulate matter (PM2.5) in near-road communities is dominated by the regional background concentrations which account for more than 85% of the pollution; and (b) only near-road receptors are affected by the traffic-related air pollutant emissions from major highways while spatial and temporal variations of PM2.5 concentrations in near-road communities are less influenced by local traffic, subsiding rapidly to negligible concentrations at 300 m from the road. Modeled PM2.5 concentrations were compared with monitored data. For better air quality impact assessments, higher quality data such as time-specific traffic volume and fleet information as well as site-specific meteorological data could help yield more accurate concentration predictions. Modeled-to-monitored comparison shows that air quality in near-road communities is dominated by regional background concentrations.
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