Global aeolian dust variations and trends: a revisit of dust event and visibility observations from surface weather stations

This study revisits the use of horizontal visibility and manually reported present weather (ww) records from the NOAA Integrated Surface Database (ISD) for characterizing the aeolian dust variability and recent trends over the globe and three largest source regions (North Africa, Middle East, and East Asia). Due to its qualitative nature, ww is combined with visibility to derive a new variable, VI, which has higher correlations with the dust emission and burden from satellite observations and global aerosol reanalyses than does the dust event frequency (FR) derived from ww only. Both FR and VI capture the intensive dust activity associated with the prolonged North American drought during the 1950s and Sahelian drought during the 1980s. Correlation analysis suggests soil moisture has a lagged effect on the global dustiness, with a maximum r = −0.3 when soil moisture leads VI by 14 months. Through a critical assessment of the ww continuity and ww-visibility consistency of various report types in ISD, the SYNOP data are used for global dust trend detection from 1986 to 2019. Globally, FR and VI decreased at a rate of −0.23 % yr−1 and −8.0 × 10−4 km−1 yr−1, respectively, from 1986 to 1996/1997 when dust reached a minimum, followed by a slower rebound at a rate of 0.085 % yr−1 and 1.9 × 10−4 km−1 yr−1, respectively. The nonlinear behavior of global dustiness is qualitatively consistent with satellite observations and global aerosol reanalyses. Regionally, North Africa experienced increased dust activity during the past decade after staying below average for most of the 1990s–2000s, in response to reduced soil moisture and increased wind speed following the transition of North Atlantic Oscillation (NAO) from strong negative to recurring positive phases since 2011. In the Middle East, dust has been increasing since 1998 due to a prolonged drought in the Tigris-Euphrates basin associated with strong negative Pacific Decadal Oscillation (PDO) phases. As PDO turned positive and weak negative after 2015, the amelioration of drought has led to decreased dust activity in recent years. The dust variability in East Asia is primarily driven by wind speed, which explains the dust decline from 1986 to 1997, and the absence of dust trends during the past two decades. This study constitutes an initial effort of creating a homogenized weather station-based dust-climate dataset in support of wind erosion monitoring, dust source mapping, and dust-climate analysis at local to global scales

Impact of Deadly Dust Storms (May 2018) on Air Quality, Meteorological, and Atmospheric Parameters Over the Northern Parts of India

The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and the Thar desert located in north‐western India. In the year 2018, month of May, three back‐to‐back major dust storms occurred that caused massive damage, loss of human lives, and loss to property and had an impact on air quality and human health. In this paper, we combine observations from ground stations, satellites, and radiosonde networks to assess the impact of dust events in the month of May 2018, on meteorological parameters, aerosol properties, and air quality. We observed widespread changes associated with aerosol loadings, humidity, and vertical advection patterns with displacements of major trace and greenhouse gasses. We also notice drastic changes in suspended particulate matter concentrations, all of which can have significant ramifications in terms of human health and changes in weather pattern

Monitoring the impact of desert dust outbreaks for air quality for health studies

We review the major features of desert dust outbreaks that are relevant to the assessment of dust impacts upon human health. Our ultimate goal is to provide scientific guidance for the acquisition of relevant population exposure information for epidemiological studies tackling the short and long term health effects of desert dust. We first describe the source regions and the typical levels of dust particles in regions close and far away from the source areas, along with their size, composition, and bio-aerosol load. We then describe the processes by which dust may become mixed with anthropogenic particulate matter (PM) and/or alter its load in receptor areas. Short term health effects are found during desert dust episodes in different regions of the world, but in a number of cases the results differ when it comes to associate the effects to the bulk PM, the desert dust-PM, or non-desert dust-PM. These differences are likely due to the different monitoring strategies applied in the epidemiological studies, and to the differences on atmospheric and emission (natural and anthropogenic) patterns of desert dust around the world. We finally propose methods to allow the discrimination of health effects by PM fraction during dust outbreaks, and a strategy to implement desert dust alert and monitoring systems for health studies and air quality management.The systematic review was funded by WHO with as part of a Grant Agreement with Ministry of Foreign Affairs, Norway. Thanks are also given to the Spanish Ministry for the Ecological Transition for long term support in the last 2 decades to our projects on African dust effects on air quality over Spain; to the Spanish Ministry of Science, Innovation and Universities and FEDER Funds for the HOUSE project (CGL2016-78594-R), and to the Generalitat de Catalunya (AGAUR 2017 SGR41). Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal program (grant RYC-2015-18690) of the Spanish Ministry of Science, Innovation and Universities.Peer ReviewedPostprint (published version

Aeolian dust deposition rates in south-western Iran

The annual atmospheric dust-load originating in the so-called Dust Belt ‎, which ranges from the ‎Sahara desert and the Arabian peninsula to the arid lowlands of Central Asia and the deserts of ‎northern China, impacts the air quality and the climate worldwide. Iran as a whole, and especially the ‎southwestern regions of the country, most affected by dust, with frequent dust storms characterized ‎by annual mean concentrations of more than 100 µg/m³ of suspended dust. Although aeolian dust is a ‎highly relevant problem in Iran, there is a lack of comprehensive regional studies on this topic. The ‎central aim of the study presented here is therefore the spatiotemporal analyses and classification of ‎dust events, the chemical composition of the dust, and the connections between regional and seasonal ‎climate variation and dust deposition rates in four sub-regions of Iran. This comprehensive approach is ‎based on the maximum mean dust concentration and the seasonality of dust events. The results are ‎provided new and valuable insights into the dust deposition and its related processes in the study area.‎ The study area covers 8.43% of Iran (about 117,000 km2), located between 45°30′00″ E 35°00′00″ N ‎and 49°30′00″ E 30°00′00″ N including Kermanshah, Lorestan and Khuzestan. The fieldwork area is ‎characterized by the rolling mountainous terrain about 4000 m above sea level (a.s.l) in the north and ‎east, plains and marshlands in the south. Study area has also located in dry climate and hot summer ‎conditions in the south, cold and hot desert climates in the west. The studies on aeolian dust in ‎southwestern Iran are based solely on ground deposition rates from 2014 to 2017‎‏.‏ To address the connections between the Ground observation of dust Deposition Rates (GDR), climate ‎zones, and weather patterns, a comparative analysis with various data sets was conducted. Both ‎gravimetric and directional dust samplers (10 each) were installed to record the monthly GDR between ‎‎2014 and 2017. The sampler design was deliberately kept simple to ensure long-term durability and ‎easy maintenance. The collected dust samples were analyzed for their chemical composition using ‎Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The ten sampling sites were also classified ‎by their land use / land cover (LULC) for a more detailed data interpretation. The observation data ‎during two typical dust cases (spring 2014 and winter 2015), have furthermore been compared with ‎the spatiotemporal dust concentration and dust load over the study area. Comparing the results of the ‎monthly mean Aerosol Optical Thickness (AOT) derived from the Moderate Resolution Imaging ‎Spectroradiometer (MODIS) and GDR data, using enhancement algorithms were applied in order to ‎investigate the spatiotemporal distribution of dust events. To demonstrate the aerosol movement, a ‎HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used for tracing the ‎investigated dust events. The time-space consistency between AOT and GDR, in agreement with the ‎HYSPLIT model output was the basis for an improved estimation of the dust deposition rate from ‎separate thickness layers. Finally, by comparing the high temporal and maximum seasonal deposition ‎rates, using MODIS and GDR data, the impact of the regional climate on the deposition rates of ‎aeolian dust was assessed, which allows insights in potential future dust emission scenarios in times of ‎climate change. ‎ A major finding shows the impact of dust events on the environment and considers the influence of ‎geographical factors, such as weathering, and climate pattern over aeolian dust deposition rates. In ‎more detail, finding to address the first objective suggested that contributors of the elemental ‎concentrations are associated with elements emanating from local industrial and commercial activities ‎‎(Cr, V, and Cd). The dominant variables (K, Zn) strongly influence the aerosol composition values and ‎represent the dust transport route. Inter –element relationships shows that the highest proportion (80%) ‎of dust samples subjected to Airborne Metals Regulations are formed under local and regional ‎conditions. Besides, the analyses indicate that the WRF-Chem model adequately simulates the ‎evolution, spatial distribution and load of dust over the study area. Hence, the model performance has ‎been evaluated by GDR. It showed different values of GDR highly depending on LULC pattern. Due to ‎the fact, that there is no way to isolate each individual area from the effects of either anthropogenic ‎sources or natural weathering processes, developing guidance on the priorities of expanding projects ‎and preventative actions towards potential dust deposition from natural and dominant sources may be ‎a subject of institutional interest. ‎ The results of direct measurements of dust deposition, which are typically made by passive sampling ‎techniques (ground-based observations), along with analyzed data from AOT, represent the second ‎objective to understand the spatiotemporal pattern of the points with the same variation. The ‎corresponding points headed to find moving air mass trajectories, using HYSPLIT were proven to be a ‎discriminator of their local and regional origin of aeolian dust. Furthermore, the seasonal deposition rate ‎varied from 8.4 g/m2/month in the summer to 3.5 g/m2/month in the spring. Despite all the advances ‎of AOT, under certain circumstances, the ground-based solutions were able to represent aerosol ‎conditions over the research area, tested in the southwestern regions of Iran. And that is when the low ‎number of observations is a commonly acknowledged drawback of GDR.‎ In addition, the peak of the seasonal deposition rates (t/km2/month) occurred in [arid desert hot-BWh, ‎‎8.4], [arid steppe hot-BSh, 6.6], and [hot and dry summer-Csa, 3.5] climate regions. Thus, the third ‎objective response was‏ ‏detected as the highest deposition rates of dust BWh >BSh >Csa throughout ‎the year, once the annual mean deposition rates (t/km2/year) are 100.80 for [BWh], 79.27 for [BSh], ‎and 39.60 for [Csa]. The knowledge gained on the dust deposition processes, together with the ‎feedback from the climate pattern, will provide insights into the records of data for developing new ‎sources, deposition rates and their climate offsets. Taking this in mind, having information about the ‎ground deposition rates in the study region could make the estimations more accurate, while finding an ‎appropriate algorithm is necessary to enhance the affected areas exposed to the dust. In order to ‎assess the impact of dust events on human health, environment and the damage to the various ‎business sectors of the country’s economy, additional studies with adequate modelling tools are ‎needed. ‎ Due to this date, the data holding organizations are somewhat reluctant to make their data available to ‎other parties. This work is also a step toward an institutional suggestion to gain benefit from information ‎exchange amongst data holding organizations, providers and users. The need for capacity building and ‎strong policy for implementing user-friendly geo information portal‏ ‏is essential.

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

East Asian Study of Tropospheric Aerosols and their Impact on Regional Clouds, Precipitation, and Climate (EAST-AIR_(CPC))

Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions

Global assessment of sand and dust storms

The specific objectives of the assessment are to: 1) Synthesise and highlight the environmental and socio-economic causes and impacts of SDS, as well as available technical measures for their mitigation, at the local, regional and global levels; 2) Show how the mitigation of SDS can yield multiple sustainable development benefits; 3) Synthesize information on current policy responses for mitigating SDS and 4) Present options for an improved strategy for mitigating SDS at the local, regional and global levels, building on existing institutions and agreements

Determining ground-level composition and concentration of particulate matter across regional areas using the Himawari-8 satellite

Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar orbiting imagers, which means that aerosol is only derived during the daytime, and only once or twice per day. Sub-hourly, infrared (IR), geostationary data, such as the ten-minute data from Himawari-8, are required to monitor these events to ensure that sporadic dust events can be continually observed and quantified. Newer quantification methods using geostationary data have focussed on detecting the presence, or absence, of a dust event. However, limited attention has been paid to the determination of composition, and particle size, using IR wavelengths exclusively. More appropriate IR methods are required to quantify and classify aerosol composition in order to improve the understanding of source impacts. The primary research objectives were investigated through a series of scientific papers centred on aspects deemed critical to successfully determining ground-level concentrations. A literature review of surface particulate monitoring of dust events using geostationary satellite remote sensing was undertaken to understand the theory and limitations in the current methodology. The review identified (amongst other findings) the reliance on visible wavelengths and the lack of temporal resolution in polar-orbiting satellite data. As a result of this, a duststorm was investigated to determine how rapidly the storm passed and what temporal data resolution is required to monitor these and other similar events. Various IR dust indices were investigated to determine which are optimum for determining spectral change. These indices were then used to qualify and quantitate dust events, and the methodology was validated against three severe air quality events of a dust storm; smoke from prescribed burns; and an ozone smog incident. The study identified that continuous geostationary temporal resolution is critical in the determination of concentration. The Himawari-8 spatial resolution of 2 km is slightly coarse and further spatial aggregation or cloud masking would be detrimental to determining concentrations. Five dual-band BTD combinations, using all IR wavelengths, maximises the identification of compositional differences, atmospheric stability, and cloud cover and this improves the estimated accuracy. Preliminary validation suggests that atmospheric stability, cloud height, relative humidity, PM2.5, PM10, NO, NO2, and O3 appear to produce plausible plumes but that aerosol speciation (soil, sea-spray, fires, vehicles, and secondary sulfates) and SO2 require further investigation. The research described in the thesis details the processes adopted for the development and implementation of an integrated approach to using geostationary remote sensing data to quantify population exposure (who), qualify the concentration and composition (what), assess the temporal (when) and spatial (where) concentration distributions, to determine the source (why) of aerosols contribution to resulting ground-level concentration