The Spatial and Seasonal Variability of Coarse Aerosol Mass at Remote Sites across the United States
Abstract
Understanding the spatial and temporal variability in coarse aerosol mass (CM = PM10 - PM2.5, mass of particles with diameters between 2.5 and 10 µm) is important for accurately characterizing and perhaps mitigating its environmental and climate impacts, which include influences on air quality, visibility, radiative forcing, hydrology, heterogeneous chemistry, biogeochemistry, and ecology. The spatial and seasonal variability of ambient CM was characterized at over 160 rural and remote sites in the United States in the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. Monthly, seasonal, and annual means were computed for 2011 through 2015 to investigate the spatial and seasonal variability of CM. Regions with significant CM contributions to PM10 mass included the southwestern United States and southern Great Plains during the spring season and the central United States in spring, summer, and fall (≥70% of PM10 mass). The highest seasonal CM variability occurred in the West, peaking in spring months at sites in the Southwest near local and regional dust sources and in summer and early fall at sites in the Northwest, likely associated with local agricultural activity or biomass burning impacts. Eastern sites experienced relatively low CM seasonal variability. Trend analyses (2000-2015) indicated that CM and its contribution to PM10 have increased during specific seasons and across regions of the United States. Mitigating the environmental and climate impacts of CM will require improving source identification and characterization of its physico-chemical and optical properties.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A22G..02H
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3322 Land/atmosphere interactions;
- ATMOSPHERIC PROCESSES;
- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 1622 Earth system modeling;
- GLOBAL CHANGE