Fairbanks-North Star Borough (FNSB), Alaska perennially experiences some of the worst wintertime air quality in the United States. FNSB was designated as a “serious” nonattainment area by the U.S. Environmental Protection Agency in 2017 for excessive fine particulate matter (PM 2.5 ) concentrations. The ALPACA (Alaskan Layered Pollution And Chemical Analysis) field campaign was established to understand the sources of air pollution, pollutant transformations, and the meteorological conditions contributing to FNSB's air quality problem. We performed on-road mobile sampling during ALPACA to identify and understand the spatial patterns of PM across the study domain, which contained multiple stationary field sites and regulatory measurement sites. Our measurements demonstrate the following: (1) both the between-neighborhood and within-neighborhood variations in PM 2.5 concentrations and composition are large (>10 μg m −3 ). (2) Spatial variations of PM in Fairbanks are tightly connected to meteorological conditions; dramatic between-neighborhood differences exist during strong temperature inversion conditions, but are significantly reduced during weaker temperature inversions, where atmospheric conditions are more well mixed. (3) During strong inversion conditions, total PM 2.5 and black carbon (BC) are tightly spatially correlated and have high absorption Ångstrom exponent values (AAE > 1.4), but are relatively uncorrelated during weak inversion conditions and have lower AAE. (4) PM 2.5 , BC, and total particle number (PN) concentrations decreased with increasing elevation, with the fall-off being more dramatic during strong temperature inversion conditions. (5) Mobile sampling reveals important air pollutant concentration differences between the multiple fixed sites of the ALPACA study, and demonstrates the utility of adding mobile sampling for understanding the spatial context of large urban air quality field campaigns. These results are important for understanding both the PM exposure for residents of FNSB and the spatial context of the ALPACA study.
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Mobile Monitoring of Air Pollution Reveals Spatial and Temporal Variation in an Urban Landscape
Urban air pollution poses a major threat to human health. Understanding where and when urban air pollutant concentrations peak is essential for effective air quality management and sustainable urban development. To this end, we implement a mobile monitoring methodology to determine the spatiotemporal distribution of particulate matter (PM) and black carbon (BC) throughout Philadelphia, Pennsylvania and use hot spot analysis and heatmaps to determine times and locations where pollutant concentrations are highest. Over the course of 12 days between June 27 and July 29, 2019, we measured air pollution concentrations continuously across two 150 mile (241.4 km) long routes. Average daily mean concentrations were 11.55 ± 5.34 μg/m 3 (PM 1 ), 13.48 ± 5.59 μg/m 3 (PM 2.5 ), 16.13 ± 5.80 μg/m 3 (PM 10 ), and 1.56 ± 0.39 μg/m 3 (BC). We find that fine PM size fractions (PM 2.5 ) constitute approximately 84% of PM 10 and that BC comprises 11.6% of observed PM 2.5 . Air pollution hotspots across three size fractions of PM (PM 1 , PM 2.5 , and PM 10 ) and BC had similar distributions throughout Philadelphia, but were most prevalent in the North Delaware, River Wards, and North planning districts. A plurality of detected hotspots found throughout the data collection period (30.19%) occurred between the hours of 8:00 AM–9:00 AM.
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- Award ID(s):
- 1832407
- NSF-PAR ID:
- 10286898
- Date Published:
- Journal Name:
- Frontiers in Built Environment
- Volume:
- 7
- ISSN:
- 2297-3362
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fbuil.2021.648620
