Refined Sea Salt Markers for Coastal Cities Facilitating Quantification of Aerosol Aging and PM2.5 Apportionment

Sea salt (ss) aerosols in PM2.5 are often quantified through source apportionment by applying sodium (Na+) and chloride (Cl-) as the markers, but both markers can be substantially emitted from anthropogenic sources. In this study, we differentiate ss from nonss (nss) portions of Na+ and Cl- to better apportion PM2.5 in a coastal tropical urban environment. Size-resolved ionic profiles accounting for Cl- depletion of aged ss were applied to 162-day measurements during 2012 and 2018-2019. Results show that the nss (likely anthropogenic) portions, on average, account for 50-80% of total Na+ and Cl- in submicron aerosols (PM1). This corresponds to up to 2.5 μg/m3 of ss in submicron aerosols that can be ∼10 times overestimated if one attributes all Na+ and Cl- in PM1 to ss. Employing the newly speciated ss- and nss-portions of Na+ and Cl- to source apportionment of urban PM2.5 via positive matrix factorization uncovers a new source of transported anthropogenic emissions during the southwest monsoon, contributing to 12-15% of PM2.5. This increases anthropogenic PM2.5 by ≥19% and reduces ss-related PM2.5 by >30%. In addition to demonstrating Cl- depletion (aging) in submicron aerosols and quantifying ssNa+, nssNa+, ssCl-, as well as nssCl- therein, the refined PM2.5 apportionment resolves new insights on PM2.5 of anthropogenic origins in urban environments, useful to facilitate policy making.

Spatial distribution, sources, and direct radiative effect of carbonaceous aerosol along a transect from the Arctic Ocean to Antarctica

Carbonaceous aerosols (CA) have a high impact on air quality and climate. However, the composition and spatial variability of CA in the marine boundary layer (MBL) remain understudied, especially in the remote regions. Here, atmospheric organic carbon (OC) and elemental carbon (EC) measurements using DRI Model 2001 Thermal/Optical Carbon Analyzer in the MBL were performed during the Chinese Antarctic (2019-2020) and Arctic (2021) research expedition, spanning about 160 latitudes. Due to varying intensities of atmospheric transport from the continents, a significant latitudinal gradient in OC and EC was observed. OC exhibited the highest concentration over the coastal East Asia (CEA), with a mean of 4324 ng m-3 (358-18027 ng m-3), followed by the Arctic Ocean (AO). Similar OC levels were detected over the Southern Ocean (SO) and the Antarctic Ice Sheet (AIS). Similarly, the highest EC was also observed over CEA, with a mean of 867 ng m-3 (71-3410 ng m-3), followed by AO and SO, while the lowest EC appeared over the AIS, with a mean of 30 ng m-3 (2-70 ng m-3). The lower Char-EC/Soot-EC ratios over AO and CEA compared to SO and AIS indicated that fossil fuel combustion contributed more to EC over AO and CEA, while biomass burning played a more significant role in EC levels over SO and AIS. The high OC/EC ratio over AIS was associated with an extremely low EC level and the formation of secondary OC over AIS. SBDART model results suggested that EC had a net warming effect on the atmospheric column, with the highest direct radiative effects (DRE) over AO (5.50 ± 0.15 W m-2, corresponding a heating rate of 0.15 K day-1) and the lowest DRE over SO (1.35 ± 0.04 W m-2, corresponding a heating rate of 0.04 K day-1).

A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely even larger than what was diagnosed here. We conclude with a discussion on how MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research.

Relationships Between Supermicrometer Sea Salt Aerosol and Marine Boundary Layer Conditions: Insights From Repeated Identical Flight Patterns

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.

Atmospheric Research Over the Western North Atlantic Ocean Region and North American East Coast: A Review of Past Work and Challenges Ahead

Decades of atmospheric research have focused on the Western North Atlantic Ocean (WNAO) region because of its unique location that offers accessibility for airborne and ship measurements, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews these scientific investigations for the WNAO region, including the East Coast of North America and the island of Bermuda. Over 50 field campaigns and long-term monitoring programs, in addition to 715 peer-reviewed publications between 1946 and 2019 have provided a firm foundation of knowledge for these areas. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO atmospheric research into eight major categories, with some studies fitting into multiple categories (relative %): Aerosols (25%), Gases (24%), Development/Validation of Techniques, Models, and Retrievals (18%), Meteorology and Transport (9%), Air-Sea Interactions (8%), Clouds/Storms (8%), Atmospheric Deposition (7%), and Aerosol-Cloud Interactions (2%). Recommendations for future research are provided in the categories highlighted above.

Observations of the Interaction and Transport of Fine Mode Aerosols with Cloud and/or Fog in Northeast Asia from Aerosol Robotic Network (AERONET) and Satellite Remote Sensing

Analysis of sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in mid-visible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological co-variation with atmospheric stability and convergence. The new development of Aerosol Robotic network (AERONET) Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the Spectral Deconvolution Algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of AERONET L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.