An Aerosol Climatology and Implications for Clouds at a Remote Marine Site: Case Study Over Bermuda

Aerosol responses to precipitation along North American air trajectories arriving at Bermuda

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location a suitable natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 μm normalized by the enhancement of carbon monoxide above background (PM2.5/ΔCO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December-February (DJF) show that most trajectories come from North America and have the highest APTs, resulting in a significant reduction (by 53 %) in PM2.5/ΔCO under high-APT conditions (> 13.5 mm) relative to low-APT conditions (< 0.9 mm). Moreover, PM2.5/ΔCO was most sensitive to increases in APT up to 5 mm (-0.044 μg m-3 ppbv-1 mm-1) and less sensitive to increases in APT over 5 mm. While anthropogenic PM2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt, in contrast, was comparable between high- and low-APT conditions owing to enhanced local wind and sea salt emissions in high-APT conditions. The greater sensitivity of the fine-mode volume concentrations (versus coarse mode) to wet scavenging is evident from AErosol RObotic NETwork (AERONET) volume size distribution data. A combination of GEOS-Chem model simulations of the 210Pb submicron aerosol tracer and its gaseous precursor 222Rn reveals that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter and spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222Rn tracer emissions contribute most to surface 210Pb concentrations at Bermuda in winter (~75 %-80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the US East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the US East Coast.

Biomass Burning Over the United States East Coast and Western North Atlantic Ocean: Implications for Clouds and Air Quality

Biomass burning (BB) aerosol events were characterized over the U.S. East Coast and Bermuda over the western North Atlantic Ocean (WNAO) between 2005 and 2018 using a combination of ground-based observations, satellite data, and model outputs. Days with BB influence in an atmospheric column (BB days) were identified using criteria biased toward larger fire events based on anomalously high AERONET aerosol optical depth (AOD) and MERRA-2 black carbon (BC) column density. BB days are present year-round with more in June-August (JJA) over the northern part of the East Coast, in contrast to more frequent events in March-May (MAM) over the southeast U.S. and Bermuda. BB source regions in MAM are southern Mexico and by the Yucatan, Central America, and the southeast U.S. JJA source regions are western parts of North America. Less than half of the BB days coincide with anomalously high PM2.5 levels in the surface layer, according to data from 14 IMPROVE sites over the East Coast. Profiles of aerosol extinction suggest that BB particles can be found in the boundary layer and into the upper troposphere with the potential to interact with clouds. Higher cloud drop number concentration and lower drop effective radius are observed during BB days. In addition, lower liquid water path is found during these days, especially when BB particles are present in the boundary layer. While patterns are suggestive of cloud-BB aerosol interactions over the East Coast and the WNAO, additional studies are needed for confirmation.

Extreme Aerosol Events at Mesa Verde, Colorado: Implications for Air Quality Management

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM2.5). The purpose of this study was to examine PM2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and “other”. Our results show that extreme PM2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from “other” sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to “other” events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors

Cloud drop number concentrations (N _d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N _d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N _d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N _d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N _d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N _d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N _d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N _d.