RESUMEN
Coastal southeast Florida experiences a wide range of aerosol conditions, including African dust, biomass burning (BB) aerosols, as well as sea salt and other locally-emitted aerosols. These aerosols are important sources of cloud condensation nuclei (CCN), which play an essential role in governing cloud radiative properties. As marine environments dominate the surface of Earth, CCN characteristics in coastal southeast Florida have broad implications for other regions with the added feature that this site is perturbed by both natural and anthropogenic emissions. This study investigates the influence of different air mass types on CCN concentrations at 0.2% (CCN0.2%) and 1.0% (CCN1.0%) supersaturation (SS) based on ground site measurements during selected months in 2013, 2017, and 2018. Average CCN0.2% and CCN1.0% concentrations were 373 ± 200 cm-3 and 584 ± 323 cm-3, respectively, for four selected days with minimal presence of African dust and BB (i.e., background days). CCN concentrations were not elevated on the four days with highest influence of African dust (289 ± 104 cm-3 [0.2% SS] and 591 ± 302 cm-3 [1.0% SS]), consistent with high dust mass concentrations comprised of coarse particles that are few in number. In contrast, CCN concentrations were substantially enhanced on the five days with the greatest impact from BB (1408 ± 976 cm-3 [0.2% SS] and 3337 ± 1252 cm-3 [1.0% SS]). Ratios of CCN0.2%:CCN1.0% were used to compare the hygroscopicity of the aerosols associated with African dust, BB, and background days. Average ratios were similar for days impacted by African dust and BB (0.54 ± 0.17 and 0.55 ± 0.17, respectively). A 29% higher average ratio was observed on background days (0.71 ± 0.14), owing in part to a strong presence of sea salt and reduced presence of more hydrophobic species such as those of a carbonaceous or mineral-dust nature. Finally, periods of heavy rainfall were shown to effectively decrease both CCN0.2% and CCN1.0% concentrations. However, the rate varied at which such concentrations increased after the rain. This work contributes knowledge on the nucleating ability of African dust and BB in a marine environment after varying periods of atmospheric transport (days to weeks). The results can be used to understand the hygroscopicity of these air mass types, predict how they may influence cloud properties, and provide a valuable model constraint when predicting CCN concentrations in comparable situations.
RESUMEN
This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO4 2-. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl-, NO3 -, SO4 2-, and Na+ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol-cloud-precipitation interactions.
RESUMEN
The MONterey Aerosol Research Campaign (MONARC) in May-June 2019 featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. The objective of this study is to use MONARC data along with machine learning analysis to evaluate relationships between both supermicrometer sea salt aerosol number (N>1) and volume (V>1) concentrations and wind speed, wind direction, sea surface temperature (SST), ambient temperature (Tamb), turbulent kinetic energy (TKE), relative humidity (RH), marine boundary layer (MBL) depth, and drizzle rate. Selected findings from this study include the following: (i) Near surface (<60 m) N>1 and V>1 concentration ranges were 0.1-4.6 cm-3 and 0.3-28.2 µm3 cm-3, respectively; (ii) four meteorological regimes were identified during MONARC with each resulting in different N>1 and V>1 concentrations and also varying horizontal and vertical profiles; (iii) the relative predictive strength of the MBL properties varies depending on predicting N>1 or V>1, with MBL depth being more highly ranked for predicting N>1 and with TKE being higher for predicting V>1; (iv) MBL depths >400 m (<200 m) often correspond to lower (higher) N>1 and V>1 concentrations; (v) enhanced drizzle rates coincide with reduced N>1 and V>1 concentrations; (vi) N>1 and V>1 concentrations exhibit an overall negative relationship with SST and RH and an overall positive relationship with Tamb; and (vii) wind speed and direction were relatively weak predictors of N>1 and V>1.