Characterization of fresh PM deposits on calcareous stone surfaces: Seasonality, source apportionment and soiling potential

Particulate matter (PM) pollution is one of the major threats to cultural heritage outdoors. It has been recently implied that organic aerosols will prevail over inorganic carbon particulates in the future, changing the main mechanisms of damage caused by poor air quality to calcareous heritage in particular. We studied fresh particulate deposits on marble and limestone surfaces exposed to urban air in sheltered and unsheltered configurations. Due to different air pollution sources in different seasons, the amount and composition of surface deposits varied throughout the year. The main and most constant contributor to PM_2.5 (particles smaller than 2.5 μm) were primary traffic emissions (30 %), followed by secondary formation of acidic inorganic aerosols, such as sulphate in summer and nitrate in winter (33 % altogether), and seasonal biomass-burning emissions (14 %). Although biomass burning is the major source of primary organic aerosols including the light-absorbing fraction that prevailed over black carbon (BC) in colder months (up to 60 % carbonaceous aerosol mass), we show that surface darkening causing the soiling effect is still governed by the minor BC fraction of atmospheric aerosols, which remained below 20 % of the carbonaceous aerosol mass throughout the year. This, however, can change in remote environments affected by biomass-burning emissions, such as winter resorts, or by rigorous BC mitigation measures in the future. In the short run, sheltered positions were less affected by different removal processes, but we show that surface deposits are not simply additive when considering longer periods of time. This must be taken into account when extrapolating surface accumulation to longer time scales.

Accuracy assessment and climatology of MODIS aerosol optical properties over North Africa

In this study, the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) product was compared with ground-based measurements at five sites of the Aerosol Robotic Network (AERONET) in North Africa. The MODIS AOD showed a good correlation coefficient of ~0.78, a very small mean bias error of 0.009, and a root mean square error of 0.126 with AERONET. The Dark Target/Deep Blue (DT/DB) algorithm showed better performance at low aerosol loading while underestimating AOD at higher aerosol loading, mainly for coarse-dominated aerosol types. This work also showed the benefits of using MODIS retrievals as a reliable data source for aerosols and providing a long-term aerosol type classification. The primary aerosol type is dust emitted from the Sahara Desert, and the dusty atmosphere becomes gradually mixed with pollution aerosols approaching the coastal region. The annual mean MODIS AOD at 550 nm and Ångström exponent at 412-650 nm (AE) ranged from 0.17 to 0.45 and from 0.13 to 1.25, respectively, in Algeria between 2001 and 2019. Lower AOD (< 0.22) and higher AE (> 1) were found in the northern region, while the highest AOD (0.35 to 0.45) and the lowest AE (< 0.25) were observed over the Tanezrouft desert in southern Algeria. The seasonal mean AOD was highest in summer, while the lowest was in winter due to very high easterly and northeasterly Harmattan surface wind over Zone of Chotts and the Tidikelt Depression, respectively. The negative AOD trends observed over Algeria could be partially connected to the decline (increase) in surface (850 hPa) winds over potential dust source areas in southern Algeria.

The Role of Meteorological Variables and Aerosols in the Transmission of COVID-19 During Harmattan Season

The role of atmospheric parameters and aerosols in the transmission of COVID-19 within tropical Africa, especially during the harmattan season, has been under-investigated in published papers. The harmattan season within the West African region is associated with significant dust incursion from the Bodele depression and biomass burning. In this study, the correlation between atmospheric parameters (temperature and humidity) and aerosols with COVID-19 cases and fatalities within seven locations in tropical Nigeria during the harmattan period was investigated. COVID-19 infection cases were found to be significantly positively correlated with atmospheric parameters (temperature and humidity) in the southern part of the country while the number of fatalities showed weaker significant correlation with particulate matters only in three locations. The significant correlation values were found to be between 0.22 and 0.48 for particulate matter and -0.19 to -0.32 for atmospheric parameters. Although, temperature and humidity showed negative correlations in some locations, the impact is smaller compared to particulate matter. In December, COVID-19 cases in all locations showed strong correlation with particulate matter except in Kano State. It is suggested that a reduction in atmospheric particulate matter can be used as a control measure for the spread of COVID-19.

Combining Optical and Radar Satellite Imagery to Investigate the Surface Properties and Evolution of the Lordsburg Playa, New Mexico, USA

Driven by erodible soil, hydrological stresses, land use/land cover (LULC) changes, and meteorological parameters, windblown dust events initiated from Lordsburg Playa, New Mexico, United States, threaten public safety and health through low visibility and exposure to dust emissions. Combining optical and radar satellite imagery products can provide invaluable benefits in characterizing surface properties of desert playas—a potent landform for wind erosion. The optical images provide a long-term data record, while radar images can observe land surface irrespective of clouds, darkness, and precipitation. As a home for optical and radar imagery, powerful algorithms, cloud computing infrastructure, and application programming interface applications, Google Earth Engine (GEE) is an invaluable resource facilitating acquisition, processing, and analysis. In this study, the fractional abundance of soil, vegetation, and water endmembers were determined from pixel mixtures using the linear spectral unmixing model in GEE for Lordsburg Playa. For this approach, Landsat 5 and 8 images at 30 m spatial resolution and Sentinel-2 images at 10–20 m spatial resolution were used. Employing the Interferometric Synthetic Aperture Radar (InSAR) techniques, the playa’s land surface changes and possible sinks for sediment loading from the surrounding catchment area were identified. In this data recipe, a pair of Sentinel-1 images bracketing a monsoon day with high rainfall and a pair of images representing spring (dry, windy) and monsoon seasons were used. The combination of optical and radar images significantly improved the effort to identify long-term changes in the playa and locations within the playa susceptible to hydrological stresses and LULC changes. The linear spectral unmixing algorithm addressed the limitation of Landsat and Sentinel-2 images related to their moderate spatial resolutions. The application of GEE facilitated the study by minimizing the time required for acquisition, processing, and analysis of images, and storage required for the big satellite data.

Aerosol Direct Radiative Effects under Cloud-Free Conditions over Highly-Polluted Areas in Europe and Mediterranean: A Ten-Years Analysis (2007–2016)

This study investigates changes in aerosol radiative effects on two highly urbanized regions across the Euro-Mediterranean basin with respect to a natural desert region as Sahara over a decade through space-based lidar observations. The research is based on the monthly-averaged vertically-resolved aerosol optical depth (AOD) atmospheric profiles along a 1∘×1∘ horizontal grid, obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument measurements aboard the Cloud-Aerosol lidar and Infrared Pathfinder Satellite Observation (CALIPSO). To assess the variability of the anthropogenic aerosols on climate, we compared the aerosol vertical profile observations to a one-dimensional radiative transfer model in two metropolitan climate sensible hot-spots in Europe, namely the Po Valley and Benelux, to investigate the variability of the aerosol radiative effects over ten years. The same analysis is carried out as reference on the Sahara desert region, considered subject just to natural local emission. Our findings show the efficacy of emission reduction policies implemented at government level in strongly urbanized regions. The total atmospheric column aerosol load reduction (not observed in Sahara desert region) in Po Valley and Benelux can be associated with: (i) an increase of the energy flux at the surface via direct effects confirmed also by long term surface temperature observations, (ii) a general decrease of the atmospheric column, and likely (iii) an increase in surface temperatures during a ten-year period. Summarizing, the analysis, based on the decade 2007–2016, clearly show an increase of solar irradiation under cloud-free conditions at the surface of +3.6 % and +16.6% for the Po Valley and Benelux, respectively, and a reduction of −9.0% for the Sahara Desert.

Analyses of Namibian Seasonal Salt Pan Crust Dynamics and Climatic Drivers Using Landsat 8 Time-Series and Ground Data

Salt pans are highly dynamic environments that are difficult to study by in situ methods because of their harsh climatic conditions and large spatial areas. Remote sensing can help to elucidate their environmental dynamics and provide important constraints regarding their sedimentological, mineralogical, and hydrological evolution. This study utilizes spaceborne multitemporal multispectral optical data combined with spectral endmembers to document spatial distribution of surface crust types over time on the Omongwa pan located in the Namibian Kalahari. For this purpose, 49 surface samples were collected for spectral and mineralogical characterization during three field campaigns (2014–2016) reflecting different seasons and surface conditions of the salt pan. An approach was developed to allow the spatiotemporal analysis of the salt pan crust dynamics in a dense time-series consisting of 77 Landsat 8 cloud-free scenes between 2014 and 2017, covering at least three major wet–dry cycles. The established spectral analysis technique Sequential Maximum Angle Convex Cone (SMACC) extraction method was used to derive image endmembers from the Landsat time-series stack. Evaluation of the extracted endmember set revealed that the multispectral data allowed the differentiation of four endmembers associated with mineralogical mixtures of the crust’s composition in dry conditions and three endmembers associated with flooded or muddy pan conditions. The dry crust endmember spectra have been identified in relation to visible, near infrared, and short-wave infrared (VNIR–SWIR) spectroscopy and X-ray diffraction (XRD) analyses of the collected surface samples. According these results, the spectral endmembers are interpreted as efflorescent halite crust, mixed halite–gypsum crust, mixed calcite quartz sepiolite crust, and gypsum crust. For each Landsat scene the spatial distribution of these crust types was mapped with the Spectral Angle Mapper (SAM) method and significant spatiotemporal dynamics of the major surface crust types were observed. Further, the surface crust dynamics were analyzed in comparison with the pan’s moisture regime and other climatic parameters. The results show that the crust dynamics are mainly driven by flooding events in the wet season, but are also influenced by temperature and aeolian activity in the dry season. The approach utilized in this study combines the advantages of multitemporal satellite data for temporal event characterization with advantages from hyperspectral methods for the image and ground data analyses that allow improved mineralogical differentiation and characterization.

Urban Health Related Air Quality Indicators over the Middle East and North Africa Countries Using Multiple Satellites and AERONET Data

Air pollution is reported as one of the most severe environmental problems in the Middle East and North Africa (MENA) region. Remotely sensed data from newly available TROPOMI - TROPOspheric Monitoring Instrument on board Sentinel-5 Precursor, shows an annual mean of high-resolution maps of selected air quality indicators (NO2, CO, O3, and UVAI) of the MENA countries for the first time. The correlation analysis among the aforementioned indicators show the coherency of the air pollutants in urban areas. Multi-year data from the Aerosol Robotic Network (AERONET) stations from nine MENA countries are utilized here to study the aerosol optical depth (AOD) and Ångström exponent (AE) with other available observations. Additionally, a total of 65 different machine learning models of four categories, namely: linear regression, ensemble, decision tree, and deep neural network (DNN), were built from multiple data sources (MODIS, MISR, OMI, and MERRA-2) to predict the best usable AOD product as compared to AERONET data. DNN validates well against AERONET data and proves to be the best model to generate optimized aerosol products when the ground observations are insufficient. This approach can improve the knowledge of air pollutant variability and intensity in the MENA region for decision makers to operate proper mitigation strategies.

Identification of Dust Sources in a Saharan Dust Hot-Spot and Their Implementation in a Dust-Emission Model

Although mineral dust plays a key role in the Earth’s climate system and in climate and weather prediction, models still have difficulties in predicting the amount and distribution of mineral dust in the atmosphere. One reason for this is the limited understanding of the distribution of dust sources and their behavior with respect to their spatiotemporal variability in activity. For a better estimation of the atmospheric dust load, this paper presents an approach to localize dust sources and thereby estimate the sediment supply for a study area centered on the Aïr Massif in Niger with a north–south extent of 16 ∘ –22 ∘ N and an east–west extent of 4 ∘ –12 ∘ E. This approach uses optical Sentinel-2 data at visible and near infrared wavelengths together with HydroSHEDS flow accumulation data to localize ephemeral riverbeds. Visible channels from Sentinel-2 data are used to detect sand sheets and dunes. The identified sediment supply map was compared to the dust source activation frequency derived from the analysis of Desert-Dust-RGB imagery from the Meteosat Second Generation series of satellites. This comparison reveals the strong connection between dust activity, prevailing meteorology and sediment supply. In a second step, the sediment supply information was implemented in a dust-emission model. The simulated emission flux shows how much the model results benefit from the updated sediment supply information in localizing the main dust sources and in retrieving the seasonality of dust activity from these sources. The described approach to characterize dust sources can be implemented in other regional model studies, or even globally, and can thereby help to get a more accurate picture of dust source distribution and a more realistic estimation of the atmospheric dust load.

Sources and levels of particulate matter in North African and Sub-Saharan cities: a literature review

In order to assess the significance of PM in ambient air, it is necessary to evaluate their physical and chemical characteristics as well as identify their major emission sources. On a global scale, particulate matter in the atmosphere arises mainly from the combustion process of motorized vehicles, but natural sources are still considered as the major contributors. In Africa, PM emissions differ from those in developed countries; human activities such as biomass burning in households, poor household waste management, and the high number of diesel-powered vehicles are the predominant anthropogenic sources. Natural contributions are also observed. Saharan dust and savanna fires are the most common atmospheric natural sources of particulate matter. The present literature review gives an overview of the status of air quality in African cities and highlights the various sources of particulate matter emissions and local human activities specific to each African region. This could likely serve as a reference to evaluate the current air quality in this region and will be a useful tool in the future to develop pollution mitigation strategies at the source. Recommendations are proposed in the conclusion in order to reduce emissions from their sources, taking into account the low-income African countries.

Aerosol Absorption: Progress Towards Global and Regional Constraints

PURPOSE OF REVIEW

Some aerosols absorb solar radiation, altering cloud properties, atmospheric stability and circulation dynamics, and the water cycle. Here we review recent progress towards global and regional constraints on aerosol absorption from observations and modeling, considering physical properties and combined approaches crucial for understanding the total (natural and anthropogenic) influences of aerosols on the climate.

RECENT FINDINGS

We emphasize developments in black carbon absorption alteration due to coating and ageing, brown carbon characterization, dust composition, absorbing aerosol above cloud, source modeling and size distributions, and validation of high-resolution modeling against a range of observations.

SUMMARY

Both observations and modeling of total aerosol absorption, absorbing aerosol optical depths and single scattering albedo, as well as the vertical distribution of atmospheric absorption, still suffer from uncertainties and unknowns significant for climate applications. We offer a roadmap of developments needed to bring the field substantially forward.

Dust as a tipping element: the Bodele Depression, Chad

Dust plays a vital role in climate and biophysical feedbacks in the Earth system. One source of dust, the Bodélé Depression in Chad, is estimated to produce about half the mineral aerosols emitted from the Sahara, which is the world's largest source. By using a variety of new remote sensing data, regional modeling, trajectory models, chemical analyses of dust, and future climate simulations, we investigate the current and past sensitivity of the Bodélé. We show that minor adjustments to small features of the atmospheric circulation, such as the Bodélé Low-Level Jet, could profoundly alter the behavior of this feature. Dust production during the mid-Holocene ceased completely from this key source region. Although subject to a great deal of uncertainty, some simulations of the 21st century indicate the potential for a substantial increase in dust production by the end of the century in comparison with current values.

Dust storms: recent developments

Dust storms have a number of impacts upon the environment including radiative forcing, and biogeochemical cycling. They transport material over many thousands of kilometres. They also have a range of impacts on humans, not least on human health. In recent years the identification of source areas for dust storms has been an important area or research, with the Sahara (especially Bodélé) and western China being recognised as the strongest sources globally. Another major development has been the recognition of the degree to which dust storm activity has varied at a range of time scales, millennial, century, decadal, annual and seasonal.