期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 904, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2023.166865
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This study investigates the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric particles. The research reveals that these particles are internally mixed due to long atmospheric aging. By combining different measurement techniques, the study also finds that air masses from different sources have different hygroscopicity parameters.
This study reports results from research conducted at the Observatory of Mount Pico (OMP), 2225 m above mean sea level on Pico Island in the Azores archipelago in June and July 2017. We investigated the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric (FT) particles. FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) simulations reveal that most air masses that arrived at the OMP during the sampling period originated in North America and were highly aged (average plume age > 10 days). We probed size-resolved chemical composition, mixing state, and hygroscopicity parameter (kappa) of individual particles using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX). Based on the estimated individual particle mass from elemental composition, we calculated the mixing state index, chi. During our study, FT particle populations were internally mixed (chi of samples are between 53 % and 87 %), owing to the long atmospheric aging time. We used data from a miniature Cloud Condensation Nucleus Counter (miniCCNC) to derive the hygroscopicity parameter, kappa(CCNC). Combining kappa(CCNC) and FLEXPART, we found that air masses recirculated above the North Atlantic Ocean with lower mean altitude had higher kappa(CCNC) due to the higher contribution of sea salt particles. We used CCSEM-EDX and phase state measurements to predict single-particle kappa (kappa(CCSEM-EDX)) values, which overlap with the lower range of kappa(CCNC) measured below 0.15 % SS. Therefore, CCSEM-EDX measurements can be useful in predicting the lower bound of kappa, which can be used in climate models to predict CCN activities, especially in remote locations where online CCN measurements are unavailable.
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