Long-term observation of columnar aerosol optical properties over the remote South China Sea.

The South China Sea (SCS) is a receptor of pollution sources from various parts of Asia and is heavily impacted by strong meteorological systems, which thus dictate aerosol variability over the region. This study analyzes long-term aerosol optical properties observed at Dongsha Island (a representative site in northern SCS) from 2009 to 2021 and Taiping Island (a representative site in southern SCS) from 2012 to 2021 to better apprehend the temporal evolution of columnar aerosols over the SCS. The noticeable difference in loadings, optical properties, and compositions of aerosols between northern and southern SCS was due to the influence of dissimilar emission sources and transport mechanisms. Column-integrated aerosol optical depth (AOD) over northern SCS (range of monthly mean at 500 nm; 0.12-0.51) was significantly greater than southern SCS (0.09-0.21). The maximum AOD in March (0.51 ± 0.28) at Dongsha was attributed to westerlies coupled with biomass-burning (BB) emissions from peninsular Southeast Asia, whereas the maximum AOD at Taiping in September (0.21 ± 0.25) was owing to various pollution from the Philippines, Malaysia, and Indonesia. Fine-mode aerosol dominated over northern SCS (range of monthly mean Angstrom exponent for 440-870 nm: 0.85-1.36) due to substantial influence from continental sources including anthropogenic and BB emissions while coarse-mode particles dominated over southern SCS (0.54-1.28) due to relatively more influence from marine source. More absorbing columnar aerosols prevailed over northern SCS (range of monthly mean single scattering albedo at 675 nm: 0.92-0.99) compared to southern SCS (0.95-0.98) owing to differences in aerosol composition with respect to sources. Special pollution events showcased possible significant impacts on marine ecosystems and regional climate. This study encourages the establishment of more ground-based aerosol monitoring networks and the inclusion of modeling simulations to comprehend the complex nature of aerosol over this vast marginal sea.

Increased aerosols can reverse Twomey effect in water clouds through radiative pathway.

Aerosols play important roles in modulations of cloud properties and hydrological cycle by decreasing the size of cloud droplets with the increase of aerosols under the condition of fixed liquid water path, which is known as the first aerosol indirect effect or Twomey-effect or microphysical effect. Using high-quality aerosol data from surface observations and statistically decoupling the influence of meteorological factors, we show that highly loaded aerosols can counter this microphysical effect through the radiative effect to result both the decrease and increase of cloud droplet size depending on liquid water path in water clouds. The radiative effect due to increased aerosols reduces the moisture content, but increases the atmospheric stability at higher altitudes, generating conditions favorable for cloud top entrainment and cloud droplet coalescence. Such radiatively driven cloud droplet coalescence process is relatively stronger in thicker clouds to counter relatively weaker microphysical effect, resulting the increase of cloud droplet size with the increase of aerosol loading; and vice-versa in thinner clouds. Overall, the study suggests the prevalence of both negative and positive relationships between cloud droplet size and aerosol loading in highly polluted regions.

Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign.

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS-C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground-based observations. The AVIRIS-C instrument acquired data from onboard NASA's high altitude ER-2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal-estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground-based AERONET observations demonstrates that AVIRIS-C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.

Extensive characterization of aerosol optical properties and chemical component concentrations: Application of the GRASP/Component approach to long-term AERONET measurements.

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93-1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives.

Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented.

Large global variations in measured airborne metal concentrations driven by anthropogenic sources.

Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM2.5) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100-3000 compared to crustal concentrations. Levels of metals in PM2.5 and PM10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m-3). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization's risk level for arsenic (6.6 ng m-3). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.

Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model.

Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 µg/m3), mineral dust (1.9-14.7 µg/m3), residual/organic matter (2.1-40.2 µg/m3), and black carbon (1.0-7.3 µg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 µg/m3), industry (6.5 µg/m3), and power generation (5.6 µg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM2.5 provides insight into sources and processes that influence the global spatial variation in PM2.5 composition.

Discerning the pre-monsoon urban atmosphere aerosol characteristic and its potential source type remotely sensed by AERONET over the Bengal Gangetic plain.

In the present study, we evaluated the pre-monsoon urban atmosphere (UA) aerosol characteristics remotely sensed by Aerosol Robotic Network (AERONET) over the Bengal Gangetic plain (BGP) at Kolkata (KOL) and their implication in potential source types and spatiotemporal features. About 70% of the AERONET-sensed aerosol optical depth at 0.50 µ m, AOD0.5 (Angstrom exponent, α at 0.44-0.87 µ m) during the pre-monsoon period (February to June) was greater than 0.50 (≤ 1); the pre-monsoon mean of AOD0.5 (α) was 0.73 (0.83) which was found being slightly higher (lower) than nearby AERONET stations (Dhaka/Bhola) located over the eastern Ganges basin. The volume geometric mean radius for the fine mode (FM) (coarse mode, CM) UA aerosol from AERONET retrievals was estimated to be 0.14-0.17 (2.24-2.75) µ m. The spectral distribution of the monthly mean of UA aerosol single-scattering albedo (SSA) exhibited an increasing trend with an increase in wavelength throughout all wavelengths during April, unlike the rest of the pre-monsoon months. Investigation of aerosol types indicated the pre-dominance of dust during April and a mixture of urban/open burning with mixed desert dust during the rest of the pre-monsoon months. Potential aerosol source fields were identified over the Indo-Gangetic Plain (IGP), east coast, northwestern India, and oceanic regions; these were estimated at elevated layers of atmosphere during April and May but that at surface layers during February and June. Comparison of aerosol characteristics over the BGP (at Kolkata, KOL) with that at six other coincident AERONET sites over India revealed mean AOD at KOL being 11 to 91% higher than the rest of the AERONET stations, with the relative increase at KOL being the highest during March; this was attributed to persistent high values of both FM and CM AOD unlike the rest of the stations. The monthly mean of SSA was the lowest at KOL among AERONET stations, during February and March. Comparison of the AOD from the AERONET aerosol retrievals over the BGP UA with the coincident Moderate Resolution Imaging Spectroradiometer (MODIS) latest retrievals (C005 and C006) indicated a moderate correlation between the two retrievals; discrepancy in MODIS-retrieved relative distribution of FM and CM AOD was inferred compared to AERONET in the UA.

Observation of optical properties and sources of aerosols at Buddha's birthplace, Lumbini, Nepal: environmental implications.

For the first time, aerosol optical properties are measured over Lumbini, Nepal, with CIMEL sunphotometer of the Aerosol Robotic Network (AERONET) program. Lumbini is a sacred place as the birthplace of Lord Buddha, and thus a UNESCO world heritage site, located near the northern edge of the central Indo-Gangetic Plains (IGP) and before the Himalayan foothills (and Himalayas) to its north. Average aerosol optical depth (AOD) is found to be 0.64 ± 0.38 (0.06-3.28) over the sampling period (January 2013-December 2014), with the highest seasonal AOD during the post-monsoon season (0.72 ± 0.44). More than 80% of the daily averaged AOD values, during the monitoring period, are above 0.3, indicating polluted conditions in the region. The levels of aerosol load observed over Lumbini are comparable to those observed at several heavily polluted sites in the IGP. Based on the relationship between AOD and Ångstrom exponent (α), anthropogenic, biomass burning, and mixed aerosols are found to be the most prevalent aerosol types. The aerosol volume-size distribution is bi-modal during all four seasons with modes centered at 0.1-0.3 and 3-4 µm. For both fine and coarse modes, the highest volumetric concentration of ~ 0.08 µm-3 µm-2 is observed during the post-monsoon and pre-monsoon seasons. As revealed by the single-scattering albedo (SSA), asymmetry parameter (AP), and refractive index (RI) analyses, aerosol loading over Lumbini is dominated by absorbing, urban-industrial, and biomass burning aerosols.

Estimation of aerosol optical depth at different wavelengths by multiple regression method.

This study aims to investigate and establish a suitable model that can help to estimate aerosol optical depth (AOD) in order to monitor aerosol variations especially during non-retrieval time. The relationship between actual ground measurements (such as air pollution index, visibility, relative humidity, temperature, and pressure) and AOD obtained with a CIMEL sun photometer was determined through a series of statistical procedures to produce an AOD prediction model with reasonable accuracy. The AOD prediction model calibrated for each wavelength has a set of coefficients. The model was validated using a set of statistical tests. The validated model was then employed to calculate AOD at different wavelengths. The results show that the proposed model successfully predicted AOD at each studied wavelength ranging from 340 nm to 1020 nm. To illustrate the application of the model, the aerosol size determined using measure AOD data for Penang was compared with that determined using the model. This was done by examining the curvature in the ln [AOD]-ln [wavelength] plot. Consistency was obtained when it was concluded that Penang was dominated by fine mode aerosol in 2012 and 2013 using both measured and predicted AOD data. These results indicate that the proposed AOD prediction model using routine measurements as input is a promising tool for the regular monitoring of aerosol variation during non-retrieval time.

RELATIONSHIP BETWEEN AEROSOL OPTICAL DEPTH AND PARTICULATE MATTER OVER SINGAPORE: EFFECTS OF AEROSOL VERTICAL DISTRIBUTIONS.

As part of the Seven Southeast Asian Studies (7SEAS) program, an Aerosol Robotic Network (AERONET) sun photometer and a Micro-Pulse Lidar Network (MPLNET) instrument have been deployed at Singapore to study the regional aerosol environment of the Maritime Continent (MC). In addition, the Navy Aerosol Analysis and Prediction System (NAAPS) is used to model aerosol transport over the region. From 24 September 2009 to 31 March 2011, the relationships between ground-, satellite- and model-based aerosol optical depth (AOD) and particulate matter with aerodynamic equivalent diameters less than 2.5 µm (PM2.5) for air quality applications are investigated. When MPLNET-derived aerosol scale heights are applied to normalize AOD for comparison with surface PM2.5 data, the empirical relationships are shown to improve with an increased 11 %, 10 % and 5 % in explained variances, for AERONET, MODIS and NAAPS respectively. The ratios of root mean square errors to standard deviations for the relationships also show corresponding improvements of 8 %, 6 % and 2 %. Aerosol scale heights are observed to be bimodal with a mode below and another above the strongly-capped/deep near-surface layer (SCD; 0 - 1.35 km). Aerosol extinctions within SCD are well-correlated with surface PM2.5 concentrations, possibly due to strong vertical mixing in the region.

Dust events and their influence on aerosol optical properties over Jaipur in Northwestern India.

In this study, we systematically document the link between dust episodes and local scale regional aerosol optical properties over Jaipur located in the vicinity of Thar Desert in the northwestern state of Rajasthan. The seasonal variation of AOT(500 nm) (aerosol optical thickness) shows high values (0.51 ± 0.18) during pre-monsoon (dust dominant) season while low values (0.36 ± 0.14) are exhibited during winter. The Ångström wavelength exponent has been found to exhibit low value (<0.25) indicating relative dominance of coarse-mode particles during pre-monsoon season. The AOT increased from 0.36 (Aprilmean) to 0.575 (May-June(mean)). Consequently, volume concentration range increases from April through May-June followed by a sharp decline in July during the first active phase of the monsoon. Significantly high dust storms were observed over Jaipur as indicated by high values of single scattering albedo (SSA(440 nm) = 0.89, SSA(675 nm) = 0.95, SSA870 nm = 0.97, SSA(1,020 nm) = 0.976) than the previously reported values over IGP region sites. The larger SSA values (more scattering aerosol), especially at longer wavelengths, is due to the abundant dust loading, and is attributed to the measurement site's proximity to the Thar Desert. The mean and standard deviation in SSA and asymmetry parameter during pre-monsoon season over Jaipur is 0.938 ± 0.023 and 0.712 ± 0.017 at 675 nm wavelength, respectively. Back-trajectory air mass simulations suggest Thar Desert in northwestern India as the primary source of high aerosols dust loading over Jaipur region as well as contribution by long-range transport from the Arabian Peninsula and Middle East gulf regions, during pre-monsoon season.

New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans.

We describe the development of a new suite of aerosol models for the retrieval of atmospheric and oceanic optical properties from the SeaWiFS and MODIS sensors, including aerosol optical thickness (τ), angstrom coefficient (α), and water-leaving radiance (L(w)). The new aerosol models are derived from Aerosol Robotic Network (AERONET) observations and have bimodal lognormal distributions that are narrower than previous models used by the Ocean Biology Processing Group. We analyzed AERONET data over open ocean and coastal regions and found that the seasonal variability in the modal radii, particularly in the coastal region, was related to the relative humidity. These findings were incorporated into the models by making the modal radii, as well as the refractive indices, explicitly dependent on relative humidity. From these findings, we constructed a new suite of aerosol models. We considered eight relative humidity values (30%, 50%, 70%, 75%, 80%, 85%, 90%, and 95%) and, for each relative humidity value, we constructed ten distributions by varying the fine-mode fraction from zero to 1. In all, 80 distributions (8 Rh×10 fine-mode fractions) were created to process the satellite data. We also assumed that the coarse-mode particles were nonabsorbing (sea salt) and that all observed absorptions were entirely due to fine-mode particles. The composition of the fine mode was varied to ensure that the new models exhibited the same spectral dependence of single scattering albedo as observed in the AERONET data. The reprocessing of the SeaWiFS data show that, over deep ocean, the average τ(865) values retrieved from the new aerosol models was 0.100±0.004, which was closer to the average AERONET value of 0.086±0.066 for τ(870) for the eight open-ocean sites used in this study. The average τ(865) value from the old models was 0.131±0.005. The comparison of monthly mean aerosol optical thickness retrieved from the SeaWiFS sensor with AERONET data over Bermuda and Wallops Island show very good agreement with one another. In fact, 81% of the data points over Bermuda and 78% of the data points over Wallops Island fall within an uncertainty of ±0.02 in optical thickness. As a part of the reprocessing effort of the SeaWiFS data, we also revised the vicarious calibration gain factors, which resulted in significant improvement in angstrom coefficient (α) retrievals. The average value of α from the new models over Bermuda is 0.841±0.171, which is in good agreement with the AERONET value of 0.891±0.211. The average value of α retrieved using old models is 0.394±0.087, which is significantly lower than the AERONET value.

Global atmospheric black carbon inferred from AERONET.

AERONET, a network of well calibrated sunphotometers, provides data on aerosol optical depth and absorption optical depth at >250 sites around the world. The spectral range of AERONET allows discrimination between constituents that absorb most strongly in the UV region, such as soil dust and organic carbon, and the more ubiquitously absorbing black carbon (BC). AERONET locations, primarily continental, are not representative of the global mean, but they can be used to calibrate global aerosol climatologies produced by tracer transport models. We find that the amount of BC in current climatologies must be increased by a factor of 2-4 to yield best agreement with AERONET, in the approximation in which BC is externally mixed with other aerosols. The inferred climate forcing by BC, regardless of whether it is internally or externally mixed, is approximately 1 W/m2, most of which is probably anthropogenic. This positive forcing (warming) by BC must substantially counterbalance cooling by anthropogenic reflective aerosols. Thus, especially if reflective aerosols such as sulfates are reduced, it is important to reduce BC to minimize global warming.