Characteristics of elevated aerosol layer over the Indian east coast, Kattankulathur (12.82oN, 80.04°E): A northeast monsoon region

The elevated aerosol layer (EAL) plays a vital role in weather and climate by modifying the Earth's radiation budget. In the present study, the EAL occurrence and its characteristics in the pre-monsoon season using micropulse lidar (MPL) observations during 2016-2018 and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during 2007-2018 over Kattankulathur is being reported. We have collected 147 days (101 cases) of MPL (CALIPSO) observations during clear sky conditions in the pre-monsoon 2016-2018 (2007-2018), out of which EAL is observed for 56 days (61 cases). The EAL width is generally found to be ~2.0 km and occurs between ~1.0 km and 5.0 km. Three different types of EALs are categorized based on their altitudinal occurrence using the zero-crossing method. The EALs with their base at ~1.0-1.5 km, ~1.5-2.0 km, and ~ 2.0-3.0 km are taken as types I, II, and III, which occur for 9, 20, and 27 days, respectively. The EAL significantly modifies the total columnar aerosol optical depth (AOD). It is found that AOD, in total, within ABL and EAL, are ~0.72 (0.61), 0.28 (0.25), and 0.45 (0.36) using MPL (CALIPSO), respectively. The aerosols within ABL contribute ~38 % (41 %) while EAL ~ 62 % (59 %) to the total AOD obtained using MPL (CALIPSO). We observed that the ABL and EAL are characterized by different aerosol subtypes, such as dust marine (31 %) and smoke (~ 27 %) aerosols. Other aerosol subtypes, such as dust and polluted dust, commonly occur within the ABL (54 %) and EAL (52 %).

Ensemble averaging using remote sensing data to model spatiotemporal PM10 concentrations in sparsely monitored South Africa

There is a paucity of air quality data in sub-Saharan African countries to inform science driven air quality management and epidemiological studies. We investigated the use of available remote-sensing aerosol optical depth (AOD) data to develop spatially and temporally resolved models to predict daily particulate matter (PM₁₀) concentrations across four provinces of South Africa (Gauteng, Mpumalanga, KwaZulu-Natal and Western Cape) for the year 2016 in a two-staged approach. In stage 1, a Random Forest (RF) model was used to impute Multiangle Implementation of Atmospheric Correction AOD data for days where it was missing. In stage 2, the machine learner algorithms RF, Gradient Boosting and Support Vector Regression were used to model the relationship between ground-monitored PM₁₀ data, AOD and other spatial and temporal predictors. These were subsequently combined in an ensemble model to predict daily PM₁₀ concentrations at 1 km × 1 km spatial resolution across the four provinces. An out-of-bag R² of 0.96 was achieved for the first stage model. The stage 2 cross-validated (CV) ensemble model captured 0.84 variability in ground-monitored PM₁₀ with a spatial CV R² of 0.48 and temporal CV R² of 0.80. The stage 2 model indicated an optimal performance of the daily predictions when aggregated to monthly and annual means. Our results suggest that a combination of remote sensing data, chemical transport model estimates and other spatiotemporal predictors has the potential to improve air quality exposure data in South Africa's major industrial provinces. In particular, the use of a combined ensemble approach was found to be useful for this area with limited availability of air pollution ground monitoring data.

Particulate Matter (PM2.5) Characterization, Air Quality Level and Origin of Air Masses in an Urban Background in Pretoria

Several sources have been identified as contributing to the concentration of ambient fine particulate matter, which has been associated to a variety of health issues. The chemical characteristics and sources of trace elements in PM_2.5, as well as the air quality index, were investigated in this study. Twenty four-hour fine aerosol particles were collected in an urban area in Pretoria, South Africa, from April 2017 to April 2018. Eighteen trace elements were determined using an XEPOS 5 energy-dispersive X-ray fluorescence (EDXRF) spectrometer, while black and organic carbon were estimated using an optical transmissometer from the samples collected. The HYPLIT model (version 4.9) was used to estimate air mass trajectories. Health risk was calculated by comparing it to the World Health Organization's air quality index (AQI). The overall mean PM_2.5 concentration of the collected sample equals 21 µg/m³. Majority of PM_2.5 exceedances were reported during mid-autumn and winter seasons, as compared to daily WHO guidelines and South African standards. S had the highest concentrations, greater than 1 µg/m³. Ni, Se, Br and Sb showed they were extremely enriched, (EF > 10) and suggestive of anthropogenic or non crustal origin The 24-h PM, soot, BC and OC were significantly different by the geographical origin of air masses (p < 0.05). The AQI showed that 70% of the samples showed levels above the AQI range of good and healthy air. The findings include details on the concentration, composition, and potential sources of fine PM_2.5, which is essential for policy formulation and mitigation strategies in South Africa's fight against air pollution.

New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements

Above-low-level-cloud aerosols (ACAs) have gradually gained more interest in recent years; however, the combined aerosol–cloud radiation effects are not well understood. The uncertainty about the radiative effects of aerosols above cloud mainly stems from the lack of comprehensive and accurate retrieval of aerosols and clouds for ACA scenes. In this study, an improved ACA identification and retrieval methodology was developed to provide a new global view of the ACA distribution by combining three-channel CALIOP (The Cloud–Aerosol Lidar with Orthogonal Polarization) observations. The new method can reliably identify and retrieve both thin and dense ACA layers, providing consistent results between the day- and night-time retrieval of ACAs. Then, new four-year (2007 to 2010) global ACA datasets were built, and new seasonal mean views of global ACA occurrence, optical depth, and geometrical thickness were presented and analyzed. Further discussion on the relative position of ACAs to low clouds showed that the mean distance between the ACA layer and the low cloud deck over the tropical Atlantic region is less than 0.2 km. This indicates that the ACAs over this region are more likely to be mixed with low-level clouds, thereby possibly influencing the cloud microphysics over this region, contrary to findings reported from previous studies. The results not only help us better understand global aerosol transportation and aerosol–cloud interactions but also provide useful information for model evaluation and improvements.

Aerosol and boundary-layer interactions and impact on air quality

Air quality is concerned with pollutants in both the gas phase and solid or liquid phases. The latter are referred to as aerosols, which are multifaceted agents affecting air quality, weather and climate through many mechanisms. Unlike gas pollutants, aerosols interact strongly with meteorological variables with the strongest interactions taking place in the planetary boundary layer (PBL). The PBL hosting the bulk of aerosols in the lower atmosphere is affected by aerosol radiative effects. Both aerosol scattering and absorption reduce the amount of solar radiation reaching the ground and thus reduce the sensible heat fluxes that drive the diurnal evolution of the PBL. Moreover, aerosols can increase atmospheric stability by inducing a temperature inversion as a result of both scattering and absorption of solar radiation, which suppresses dispersion of pollutants and leads to further increases in aerosol concentration in the lower PBL. Such positive feedback is especially strong during severe pollution events. Knowledge of the PBL is thus crucial for understanding the interactions between air pollution and meteorology. A key question is how the diurnal evolution of the PBL interacts with aerosols, especially in vertical directions, and affects air quality. We review the major advances in aerosol measurements, PBL processes and their interactions with each other through complex feedback mechanisms, and highlight the priorities for future studies.

An overview of regional and local characteristics of aerosols in South Africa using satellite, ground, and modeling data

We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during austral spring (September-October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM₁₀ concentrations as much as 136 % higher in townships that in industrial areas. We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.

North-south cross sections of the vertical aerosol distribution over the Atlantic Ocean from multiwavelength Raman/polarization lidar during Polarstern cruises

Shipborne aerosol lidar observations were performed aboard the research vessel Polarstern in 2009 and 2010 during three north-south cruises from about 50°N to 50°S. The aerosol data set provides an excellent opportunity to characterize and contrast the vertical aerosol distribution over the Atlantic Ocean in the polluted northern and relatively clean southern hemisphere. Three case studies, an observed pure Saharan dust plume, a Patagonian dust plume east of South America, and a case of a mixed dust/smoke plume west of Central Africa are exemplarily shown and discussed by means of their optical properties. The meridional transatlantic cruises were used to determine the latitudinal cross section of the aerosol optical thickness (AOT). Profiles of particle backscatter and extinction coefficients are presented as mean profiles for latitudinal belts to contrast northern- and southern-hemispheric aerosol loads and optical effects. Results of lidar observations at Punta Arenas (53°S), Chile, and Stellenbosch (34°S), South Africa, are shown and confirm the lower frequency of occurrence of free-tropospheric aerosol in the southern hemisphere than in the northern hemisphere. The maximum latitudinal mean AOT of 0.27 was found in the northern tropics (0- 15°N) in the Saharan outflow region. Marine AOT is typically 0.05 ± 0.03. Particle optical properties are presented separately for the marine boundary layer and the free troposphere. Concerning the contrast between the anthropogenically influenced midlatitudinal aerosol conditions in the 30- 60°N belt and the respective belt in the southern hemisphere over the remote Atlantic, it is found that the AOT and extinction coefficients for the vertical column from 0-5km (total aerosol column) and 1-5km height (lofted aerosol above the marine boundary layer) are a factor of 1.6 and 2 higher at northern midlatitudes than at respective southern midlatitudes, and a factor of 2.5 higher than at the clean marine southern-hemispheric site of Punta Arenas. The strong contrast is confined to the lowermost 3km of the atmosphere.