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Climate scientists know that organic aerosols—suspensions of microscopic particles or liquids in the air—can shape a region’s climate by scattering sunlight and seeding clouds. But scientists lack complete data on the sources and compositions of these particles, so their models struggle with aerosols’ influence on climate. Now researchers have combined two well-known analytical techniques to capture and analyze the composition of organic aerosols found in the air (Anal. Chem., DOI: 10.1021/ac3020615). The technique can collect samples every few hours, revealing the daily dynamics of the particles composition, which could help scientists understand where the aerosols come from.
For long-term studies of aerosols at research sites, scientists often collect the particles using filters. Unfortunately, with this method, researchers can monitor changes in aerosol composition only every few days, not more often.
To get better time resolution, Markus Kalberer from the University of Cambridge and his colleagues combined a different sampling method with a technique called liquid extraction surface analysis (LESA). On a dairy farm in California’s San Joaquin Valley, the researchers collected aerosols on a 2-cm-wide strip of greased plastic stretched around a rotating drum. The drum sat inside a case directly under a small opening at the case’s top, and turned 1 mm every 2.5 hours for a week, picking up particles as it went.
To analyze compounds adsorbed onto the strips, the team extracted the chemicals using LESA. In the technique, a droplet of solvent 1 mm in diameter dissolves any molecules directly below it on the plastic. To detect the hundreds of small organic molecules in each sample, the researchers then fired each droplet into an electrospray ionization mass spectrometer.
Based on patterns in the swaths of collected data, Kalberer’s team could infer where certain types of aerosols came from. For example, levels of nitrogen-rich molecules spiked when wind speeds increased, suggesting to Kalberer that those aerosols came from local farmland.
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