Atmospheric Resuspension of Microplastics from Bare Soil Regions

Microplastics (MPs) are emerging as an atmospheric pollutant. Here, we present a method of estimating MP resuspension with mineral dust in bare soil based on reported MP mass in soils, their enrichment in suspended dust relative to soil, and a mineral dust resuspension scheme. Using the estimated resuspensions, we simulate the global atmospheric MP transport and deposition using the dispersion model FLEXPART for two particle shape scenarios, spheres, and fibers. We estimate the uncertainties using a Monte Carlo technique that varies input data parameters within their reported ranges. The total MP resuspensions are estimated at about 104 (48-110) tonnes yr-1. We find that bare soils in West Asia and North Africa are the main source regions. FLEXPART results show that fibers have higher concentrations in the atmosphere and are dispersed more widely than spheres. Annually, 75 (43-83) tonnes of microfibers are deposited on land and 29 (18-33) tonnes in the oceans. Resuspended MPs can even reach remote regions, such as the Arctic. The results suggest that areas with bare soils can be an important MP source; however, further research on the factors that affect resuspension is needed.

Direct mitigation of secondary organic aerosol particulate pollutants by multiphase photocatalysis

Particulate matter represents one of the most severe air pollutants globally. Organic aerosol (OA) comprises 30-70 % of submicron particle mass in urban areas. An effective way to mitigate OA particulate pollutants is to reduce the formation of secondary organic aerosol (SOA). Here, we studied the effect of titanium dioxide (TiO2) photocatalytic seeds on the formation and mitigation of SOA particles from α-pinene or toluene oxidation in chamber. For the first time, we discovered that under ultraviolet (UV) irradiation, the presence of TiO2 directly removed internally mixed α-pinene SOA mass by 53.7 % within 200 mins, and also directly removed SOA matter in an externally mixed state that is not in direct contact with TiO2 surface: the mass of externally mixed α-pinene SOA was reduced by 21.9 % within 81 mins, and the toluene SOA mass was reduced by 46.6 % in 145mins. In addition, the presence of TiO2 effectively inhibited the formation of SOA particles with a SOA mass yield of zero. This study brings up an innovative concept for air pollution control - the direct photocatalytic degradation of OA with aid of TiO2-based photocatalysts. Our novel findings will potentially bring practical applications in air pollution abatement and regional, even global aerosol-climate interactions.

Arctic amplification-induced decline in West and South Asia dust warrants stronger antidesertification toward carbon neutrality

Dust loading in West and South Asia has been a major environmental issue due to its negative effects on air quality, food security, energy supply and public health, as well as on regional and global weather and climate. Yet a robust understanding of its recent changes and future projection remains unclear. On the basis of several high-quality remote sensing products, we detect a consistently decreasing trend of dust loading in West and South Asia over the last two decades. In contrast to previous studies emphasizing the role of local land use changes, here, we attribute the regional dust decline to the continuous intensification of Arctic amplification driven by anthropogenic global warming. Arctic amplification results in anomalous mid-latitude atmospheric circulation, particularly a deepened trough stretching from West Siberia to Northeast India, which inhibits both dust emissions and their downstream transports. Large ensemble climate model simulations further support the dominant role of greenhouse gases induced Arctic amplification in modulating dust loading over West and South Asia. Future projections under different emission scenarios imply potential adverse effects of carbon neutrality in leading to higher regional dust loading and thus highlight the importance of stronger anti-desertification counter-actions such as reforestation and irrigation management.

Air pollution analysis in Northwestern South America: A new Lagrangian framework

This study examines the spatiotemporal variations of PM2.5, PM10, SO2, O3, NO, and NO2 concentrations in Northwestern South America (NWSA). We assess the efficacy of existing policies, identify underlying phenomena, and highlight areas for further research. Significant findings have emerged by analyzing reanalysis and in-situ data, employing the WRF-Chem model, and utilizing a new Lagrangian framework designed to overcome some drawbacks common to analysis of pollution Long-Range Transport. Wildfires in the first half of the year and volcanic activity (for SO2) in July-August contribute to over 90 % of the pollutant's advection, leading to high pollution levels in urban areas. SO2 volcanic emissions contribute to secondary PM, explaining the peak in PM concentrations in Cali in July. In the second half of the year, pollutant behavior varies based on factors such as city characteristics, vehicular-volume, air temperature, wind speed, and boundary layer height, and O3 is influenced by solar radiation and the NO/NO2 ratio. Diurnal variations of PM and NOx correlate with vehicular density, SO2 with industrial activity, and O3 depends on solar radiation. Trend analysis reveals decreasing PM10 levels except in three Cundinamarca cities and Cali suggesting the need to implement/evaluate control plans in those locations. Although data is limited, NO and NO2 levels show an increasing trend due to the rising number of vehicles. SO2 levels are decreasing, except in Cali, potentially influenced by the nearby industrial and polluted city of Yumbo. O3 displays a downward trend in most cities, except Bogotá, due to the NO/NO2 ratio favoring O3 increase. These findings provide a starting point for further research to deepen our understanding of NWSA air pollution. Such investigations are essential before modifying existing policies or enacting new ones. Collaborative efforts at the international, regional, and inter-city levels are crucial for effective air quality management.

Long-term variations of global dust emissions and climate control

Dust discharged from the surface into the air has an important impact on global climate change, the ecological environment, and human health. However, the spatiotemporal variations of global dust emissions and the climate control of dust emissions from different dust sources in recent decades are still unclear. This study explores the spatiotemporal variations of global dust emissions from 1980 to 2020 based on the MERRA-2 dust emissions dataset and provides a detailed investigation of the interannual variations of dust emissions from major dust sources in the world and their contribution to the global dust cycle. On this basis, the association between global dust emissions and average wind speed (AWS), surface air temperature (SAT), precipitation (Ppt), relative humidity (RH), soil evaporation (SE), soil moisture (SM), and solar radiation (SR) were explored. In particular, the comparative importance of these climatic factors and their combined structures on dust emissions from different dust sources. The results show that North Africa contributed the most to global dust emissions, contributing 58% of the total global emissions, while South Africa and North America contributed the least to global dust emissions, at less than 1%, respectively. Classification and Regression Tree (CART) analysis shows that SR was the major factor affecting the dust emissions of Australia, East Asia, South America, and Central Asia. AWS was the major factor influencing dust emissions in North Africa and South Asia. SAT, RH, and SM were the major factors affecting dust emissions in West Asia, North America, and South Africa, respectively. There were great differences in the climatic factors combinations on dust emissions intensity in different dust sources. These findings assist us in better understanding the control of climatic factors on dust emissions from global dust sources and have important scientific significance for accurately predicting dust events and reducing disaster risks.

The influence of dust on extreme precipitation at a large city in North China

In recent decades, the Beijing-Tianjin-Hebei city cluster is experiencing rapid urbanization along with economic booming. Meanwhile, these cities are suffering the influence of extreme precipitation and dust storms. In this study, the impact of dust aerosol on extreme precipitation that occurred in Beijing during 19-21 July 2016 is investigated using both satellite retrievals and Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model simulations. Results reveal that the dust particles can increase extreme precipitation by promoting the formation of ice clouds and enhancing convections. The dust is lifted into the upper troposphere (>10 km) via strong convection and affects the physical process of precipitation after long-range transport. It further transforms the supercooled water into the middle and high levels of ice nuclei (IN). These promote the formation of ice clouds according to the decreased effective radius of IN and increased ice water path, respectively. Along with sufficient water vapor transport and strong convergence, the formation of IN could release more latent heat and further strengthen convection development. Thus, the precipitation amount in southern Beijing is almost enhanced by 40 % (>80 mm). This study will provide a deep insight into understanding the causes of urban extreme precipitation.

Saharan, Aral-Caspian and Middle East dust travels to Finland (1980-2022)

Studies on atmospheric dust and long-range transport of mineral dust have been a focus of atmospheric science in recent years. With its wide range of direct and indirect effects, mineral dust is one of the most uncertain elements in the mechanisms of climate change, and a deeper understanding of its role is essential for understanding future processes. The aim of our research was to provide the first systematic data on the so far episodically documented northward transport mineral dust from arid-semiarid areas. So, in this paper, we present dust storm events from lower latitudes reaching the Finnish atmosphere, based on the MERRA-2 model Dust Column Mass Density data and after a multistep verification procedure using independent data source. In total, 86 long-range dust storm events were identified between 1980 and 2022, when air masses loaded with dust reached Finland. Based on backward-trajectories different sources were identified: 59 were Saharan, 22 were Aral-Caspian, and five were associated with Middle Eastern source areas. Considerable variation in inter-annual frequencies was observed among the source areas, which may be due to changes in circulation conditions and the effects of human activity (agriculture and land use changes in Aral Sea region). There is a clear maximum of dust events in spring (60%), followed by summer and autumn (where 10 of the 11 autumn episodes were from the Sahara). However, the number and proportion of scarce winter events have more than doubled since 2010 compared to the preceding 30 years, but no autumn events were registered during this period. This clear temporal variation coincides with changes in dust transport observed in other regions of Europe, driven by greater atmospheric meridionality associated with climate change and driven by reduced temperature difference between low and high latitudes due to enhanced temperature increases at Arctic regions.

Aerosol-CCN characteristics and dynamics associated with a pre-monsoon dust storm over a high-altitude site in Western Ghats, India

Aerosol-CCN characteristics and dynamics during a pre-monsoon dust storm (April 6-11, 2015) over a high-altitude site ((17.92°N, 73.66°E, and 1348 m above mean sea level (MSL)) in Western Ghats, India, has been studied using ground-based observations, satellite, and reanalysis datasets. Spatial distribution of dust surface mass concentration along with the back trajectory analysis showed the Arabian Desert area (Rub-Al-khali desert) as the source region and strong westerly winds transported the dust particles toward the Indian subcontinent. High values noticed in the surface PM10 (PM2.5), i.e., ~ 450 (~ 130) µg m-3, MODIS AOD550nm (0.6), and MERRA 2 dust surface mass concentration (5 × 10-7 kg m-3) along MODIS true color images confirmed the dust storm event on April 6, 2015 over the observational site. Size-segregated aerosol number concentration measured from ground-based observations showed the dominance of Aitken, accumulation, and coarse mode particles during dust period. CCN concentrations at 0.1, 0.3, 0.5, 0.7, and 0.9% SS were analyzed. A low value of CCN concentration and activation fraction (~ 0.3) near surface was noticed during dust storm day, suggesting insoluble mineral dust particle being transported. Analyzed vertical velocity during pre-dust period showed downdraft between 900 and 750 hPa, suggesting dust transport from upper altitudes toward the observational site. WRF-Chem model simulation also captured the dust storm event, and the results are in good agreement with the observation with a significance of 95% confidence level.

Comparison of the heterogeneous reaction of NO2 on the surface of clay minerals and desert dust particles

Mineral particles in air could provide atmospheric chemical reaction interface for gaseous substances and participate in atmospheric chemical reaction process, and affecting the status and levels of gaseous pollutants in air. However, differences of the heterogenous reaction on the surface minerals particles are not very clear. Considering main mineral composition of ambient particles was from dust emission, therefore, typical clay minerals (chlorite, illite) and desert particles (Taklimakan Desert) were selected to analysize chemical reaction of NO2, one of major gaseous pollutants, on mineral particles by using of In-situ DRIFTS (diffuse reflectance infrared Fourier transform spectroscopy) under different condition. And In situ near-ambient pressure X-ray photoelectron spectroscopy (In situ NAP-XPS) was employed to investigate iron (one of the major metals) species variation on the surface of mineral dust particles during the heterogeneous reactions. Our data show that humidity controlled by deuterium oxide (D2O) has a greater effect on chemical reactions compared to light and temperature. Under dry conditions, the amount of heterogeneous reaction products of NO2 on the particles shows Xiaotang dust > chlorite > illite > Tazhong dust regardless of dark or light conditions. In contrast, under humidity conditions, the order of nitrate product quantity under moderate conditions was chlorite > illite > Xiaotang dust > Tazhong dust. In situ NAP-XPS results demonstrate that specie variation of the Fe could promote the heterogenous reactions. These data could provide useful information for understanding the formation mechanism of nitrate aerosols and removal of nitrogen oxides in the atmosphere.

Impact of coronavirus-driven reduction in aerosols on precipitation in the western United States

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine due to the shutdown of industries, drastically reduced traffic, and lockdowns. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during early 2020. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ∼0.5 °C) and generally lower snow amounts but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of the coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

Dust emission response to precipitation and temperature anomalies under different climatic conditions

The dust-drought nexus has received more attention in recent years, particularly in light of global warming. This study aims to better understand the interacting role of temperature and precipitation climatology on global dust emission. Simulated global arid regions' dust emissions from 11 CMIP6 Earth System Models (ESMs) (65 years from 1950 to 2014) and MERRA2 reanalysis (41 years from 1980 to 2020) are analyzed. We calculate dust emission sensitivity to precipitation and temperature using multiple linear regression with near-surface (10 m) wind speed, precipitation, and 2 m air temperature as predictors. The results show that simulated dust emission from most models is significantly correlated with precipitation and temperature over large arid dust source regions. All ESMs show both positive and negative dust emission sensitivity to precipitation (β_P) and temperature (β_T). The climatological mean state affects the strength of the relationships. The precipitation sensitivity is larger over the cold regions while the temperature sensitivity is larger in wet regions. The precipitation sensitivity symmetrically increases with latitude due to the variability of temperature with latitude. Future changes to mean temperature and precipitation have competing effects on dust emission and are likely to alter the hemispheric balance of atmospheric dust.

Atmospheric nourishment of global ocean ecosystems

Over the vast open ocean, vital nutrients for phytoplankton growth in the sunlit surface layer are largely provided through physical transport from deep waters, but some nutrients are also provided through atmospheric deposition of desert dust. The extent and magnitude of dust-mediated effects on surface ocean ecosystems have been difficult to estimate globally. In this work, we use global satellite ocean color products to demonstrate widespread responses to atmospheric dust deposition across a diverse continuum of phytoplankton nutritional conditions. The observed responses vary regionally, with some areas exhibiting substantial changes in phytoplankton biomass, whereas in other areas, the response reflects a change in physiological status or health. Climate-driven changes in atmospheric aerosols will alter the relative importance of this nutrient source.

A multi-objective framework to select numerical options in air quality prediction models: A case study on dust storm modeling

Numerical weather prediction models are very important tools in predicting severe weather phenomena such as dust storms. However, the prediction accuracy in these models depends on the options considered in the modeling. In this study, a multi-objective framework is presented to determine the optimal options of the weather research forecasting with chemistry (WRF-Chem) model. For this purpose, a severe dust storm that occurred in the center of Iran is considered and the effect of 10 options including grid (computational domain size, modeling start time, horizontal, vertical and temporal resolution), physical (initial conditions, boundary layer and land surface schemes) and chemical options (dust emission schemes and dust source functions) are investigated. In general, the results showed that the WRF-Chem model has a high ability to model dust storms, but its results depend on the options considered in the modeling. Evaluation of grid options showed that inappropriate selection of domain size and modeling start time can lead to the failure in dust storm forecasting. Also, the land surface scheme has the greatest impact on dust concentration among the physical options. In addition, chemical options have the greatest impact on the dust storm forecasting as well. Based on the proposed multi-objective framework, the optimal options for dust storm modeling were determined. The proposed approach is comprehensive and can be used for other atmospheric/air quality modeling.

Dust dominates the summer melting of glacier ablation zones on the northeastern Tibetan Plateau

Dust and black carbon (BC) can darken snow and ice surface and play pivotal roles in glacier mass loss. Thus, a quantitative assessment of their contributions to glacier summer melting is critical. During the summer of 2018, surface snow and ice were sampled, and the albedo and mass balance were continuously measured in the ablation zone of Laohugou Glacier No. 12 in the western Qilian Mountains. The physical properties of dust and BC were measured in the laboratory, and their impacts on glacier surface albedo reduction and melting were simulated. The results indicate that the ice surface in the ablation zone was enriched with substantial amounts of particles, and the average particle concentrations of these samples were hundreds of times higher than those of fresh snow. The BC mass absorption cross-sections (MACs) ranged from 3.1 m² g^-1 at 550 nm for dirty ice to 4.6 m² g^-1 for fresh snow, largely owing to meltwater percolation and particle collapse. The spectral variations in dust MACs were significantly different in the visible light bands and near-infrared bands from those in the other areas. Moreover, the two-layer surface energy and mass balance model with the new albedo parameterization formula was validated and agreed well with the experimental measurements of spectral albedo, broadband albedo, and mass balance. BC and dust combined resulted in 26.7 % and 54.4 % of the total mass loss on the cleaner and dirtier (particle enriched) surfaces in the ablation zone, respectively, compared to particle-free surfaces, and although both impurities played vital roles, dust was the more prominent factor in accelerating glacier melting on the northeastern Tibetan Plateau. This study emphasizes the importance of dust in cryosphere changes where Tibetan glaciers are strongly affected by Asian dust deposition.

Magneto-chemical characterisation of Saharan dust deposited on snow in Poland

Recent research has convincingly shown the advantages of combining environmental magnetism and geochemical analyses for the proxy estimation of anthropogenic pollution due to their atmospheric deposition in local environments. Few studies have also focused on anthropogenic particles deposited on snow. However, papers reporting on Sahara dust particles deposited on snow in central Europe and which involve magnetic methods are missing. To the best of our knowledge, this is the first study investigating the magnetic features of the SDE recorded in snowfall in this part of Europe (i.e. Poland). Our aim was to provide the magnetic characteristics and chemical elemental compositions of a snow horizon containing Saharan dust deposited near the Polish Jakuszyce meteorological station during a snowfall event that occurred from the 1st to the February 7, 2021. Samples of snow with and without Saharan dust were analysed with respect to iron oxide contents (magnetic susceptibility, hysteresis loop, magnetic remanence acquisition) and compared with chemical compositions. Our results revealed the presence of both ferrimagnetic magnetite and antiferromagnetic hematite in the dust-enriched horizon, and the diamagnetic behaviour of the reference layer consisting of 'pure' snow. The samples recorded the presence of geogenic elements such as Al, Fe, Mn, and Ti, anthropogenic elements such as As, Co, Cr, Cu, Ni, Pb, and Zn, and nutrients including Ca and K. The total concentrations of geogenic elements, nutrients, and anthropogenic elements in the snow samples with deposited Saharan dust were, respectively, >3700, >320, and >110 times greater than in the samples without Saharan dust. These findings may serve as reference data for a variety of environmental magnetic studies.

Emission, transport, deposition, chemical and radiative impacts of mineral dust during severe dust storm periods in March 2021 over East Asia

A Regional Air Quality Model System (named RAQMS) coupled with a developed dust model driven by WRF was applied to synthetically investigate the emission, transport, deposition, budget, and chemical and radiative effects of mineral dust during the severe dust storm periods of 10-31 March 2021. Model results were validated against a variety of ground, vertical and satellite observations, which demonstrated a generally good model ability in reproducing meteorological variables, particulate matter and compositions, and aerosol optical properties. The first dust storm (DS1), which was the severest one since 2010 was originated from the Gobi Desert in southern Mongolia on 14 March, with the dust emission flux reaching 2785 μg m^-2 s^-1 and the maximum dust concentration exceeding 18,000 μg m^-3 in the dust deflation region. This dust storm resulted in remarkably high hourly PM₁₀ observations up to 7506 μg m^-3, 1887 μg m^-3, and 2704 μg m^-3 in Beijing, Tianjin, and Shijiazhuang on 15 March, respectively, and led to a maximum decrease in surface shortwave radiation up to 313.4 W m^-2 (72 %) in Beijing. The second dust storm (DS2) broke out in the deserts of eastern Mongolia, with lower dust emission than the first one. The extinction of shortwave radiation by dust aerosols led to a reduction in photolysis rate and consequently decreases in O₃ and secondary aerosol concentrations over the North China Plain (NCP), whereas total sulfate and nitrate concentrations consistently increased due to heterogeneous reactions on dust surfaces over the middle reaches of the Yellow River and the NCP region during DS1. Sulfate and nitrate formation through heterogeneous reactions were enhanced in the dust backflow on 16-17 March by approximately 18 % and 24 % on average in the NCP. Heterogeneous reactions and photolysis rate reduction by mineral dust jointly led to average changes in sulfate, nitrate, ammonium, and secondary organic aerosol (SOA) concentrations by 13.0 %, 13.5 %, -12.3 %, and -4.4 %, respectively, in the NCP region during DS1, larger than the changes in the Yangtze River Delta (YRD). The maximum dry deposition settled in the 7-11 μm size range in downwind land and ocean areas, while wet deposition peaked in the 4.7-7 μm size range in the entire domain. Wet deposition was approximately twice the dry deposition over mainland China except for dust source regions. During 10-31 March, the total dust emission, dry and wet depositions were estimated to be 31.4 Tg, 13.78 Tg and 4.75 Tg, respectively, with remaining 12.87 Tg of dust aerosols (41 % of the dust emission) suspending in the atmosphere or transporting to other continents and oceans.

Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing

Quantitative estimations of atmospheric aerosol absorption are rather uncertain due to the lack of reliable information about the global distribution. Because the information about aerosol properties is commonly provided by single-viewing photometric satellite sensors that are not sensitive to aerosol absorption. Consequently, the uncertainty in aerosol radiative forcing remains one of the largest in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC AR5 and AR6). Here, we use multi-angular polarimeters (MAP) to provide constraints on emission of absorbing aerosol species and estimate global aerosol absorption optical depth (AAOD) and its climate effect. Our estimate of modern-era mid-visible AAOD is 0.0070 that is higher than IPCC by a factor of 1.3-1.8. The black carbon instantaneous direct radiative forcing (BC DRF) is +0.33 W/m² [+0.17, +0.54]. The MAP constraint narrows the 95% confidence interval of BC DRF by a factor of 2 and boosts confidence in its spatial distribution.

Drivers of recent decline in dust activity over East Asia

It is essential to understand the factors driving the recent decline of dust activity in East Asia for future dust projections. Using a physically-based dust emission model, here we show that the weakening of surface wind and the increasing of vegetation cover and soil moisture have all contributed to the decline in dust activity during 2001 to 2017. The relative contributions of these three factors to the dust emission reduction during 2010-2017 relative to 2001 are 46%, 30%, and 24%, respectively. Much (78%) of the dust emission reduction is from barren lands, and a small fraction (4.6%) of the reduction is attributed to grassland vegetation increase that is partly ascribed to the ecological restoration. This suggests that the ecological restoration plays a minor role in the decline of dust activity. Rather, the decline is mainly driven by climatic factors, with the weakening of surface wind playing the dominant role.

Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000

PM_2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM_2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM_2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM_2.5 data. PM_2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM_2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM_2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.

Black carbon and dust alter the response of mountain snow cover under climate change

By darkening the snow surface, mineral dust and black carbon (BC) deposition enhances snowmelt and triggers numerous feedbacks. Assessments of their long-term impact at the regional scale are still largely missing despite the environmental and socio-economic implications of snow cover changes. Here we show, using numerical simulations, that dust and BC deposition advanced snowmelt by 17 ± 6 days on average in the French Alps and the Pyrenees over the 1979–2018 period. BC and dust also advanced by 10-15 days the peak melt water runoff, a substantial effect on the timing of water resources availability. We also demonstrate that the decrease in BC deposition since the 1980s moderates the impact of current warming on snow cover decline. Hence, accounting for changes in light-absorbing particles deposition is required to improve the accuracy of snow cover reanalyses and climate projections, that are crucial for better understanding the past and future evolution of mountain social-ecological systems.

Black carbon and dust deposition advanced the end of the snow season by 17 days on average over the last 40 years in the French Alps and the Pyrenees. The warming-induced snow cover decline was partly offset by decreases in black carbon deposition observed since the 1980s.

Anthropogenic pollutants could enhance aridity in the vicinity of the Taklimakan Desert: A case study

With the intensification of human activities, the mixture of anthropogenic pollutants and natural dust aerosols in the vicinity of the Taklimakan Desert (TD) has become a new uncertainty in the weather and climate system. In this study, using a Weather Research and Forecasting model version 4.0 with the Thompson aerosol-aware microphysics scheme, we investigated the impact of anthropogenic aerosols on clouds and precipitation in an atmospheric environment with abundant dust aerosols in the vicinity of the TD. Our findings indicate that anthropogenic aerosols can increase cloud droplet number concentrations in the vicinity of the TD, and the maximum percentage increase can reach 50 %. In addition, the effective radius of water clouds decreases significantly due to anthropogenic aerosols, which means that more numerous but smaller cloud droplets are formed with enhanced anthropogenic aerosol loading under a dusty background. Meanwhile, anthropogenic aerosols can decrease raindrops below 650 hPa, graupel and snow particles, causing less precipitation in the dusty atmosphere surrounding the TD. Furthermore, the anthropogenic aerosol-induced changes in daily precipitation accumulation are also large, with a regionally averaged maximum reduction of up to 4.2 %. Therefore, anthropogenic aerosols are an important factor that exacerbates aridity in the vicinity of the TD, and there is an urgent need to control anthropogenic pollutants around the TD.

Application of Artificial Intelligence Models for Aeolian Dust Prediction at Different Temporal Scales: A Case with Limited Climatic Data

Accurately predicting ambient dust plays a crucial role in air quality management and hazard mitigation. Dust emission is a complex, non-linear response to several climatic variables. This study explores the accuracy of Artificial Intelligence (AI) models: an adaptive-network-based fuzzy inference system (ANFIS) and a multi-layered perceptron artificial neural network (mlp-NN), over the Southwestern United States (SWUS), based on the observed dust data from IMPROVE stations. The ambient fine dust (PM2.5) and coarse dust (PM10) concentrations on monthly and seasonal timescales from 1990–2020 are modeled using average daily maximum wind speed (W), average precipitation (P), and average air temperature (T) available from the North American Regional Reanalysis (NARR) dataset. The model’s performance is measured using correlation (r), root mean square error (RMSE), and percentage bias (% BIAS). The ANFIS model generally performs better than the mlp-NN model in predicting regional dustiness over the SWUS region, with r = 0.77 and 0.83 for monthly and seasonal fine dust, respectively. AI models perform better in predicting regional dustiness on a seasonal timescale than the monthly timescale for both fine dust and coarse dust. AI models better predict fine dust than coarse dust on both monthly and seasonal timescales. Compared to precipitation, air temperature is the more important predictor of regional dustiness on both monthly and seasonal timescales. The relative importance of air temperature is higher on the monthly timescale than the seasonal timescale for PM2.5 and vice versa for PM10. The findings of this study demonstrate that the AI models can predict monthly and seasonal fine and coarse dust, based on the limited climatic data, with good accuracy and with potential implications for research in data sparse regions.

Greenland Ice Core Record of Last Glacial Dust Sources and Atmospheric Circulation

Abrupt and large-scale climate changes have occurred repeatedly and within decades during the last glaciation. These events, where dramatic warming occurs over decades, are well represented in both Greenland ice core mineral dust and temperature records, suggesting a causal link. However, the feedbacks between atmospheric dust and climate change during these Dansgaard-Oeschger events are poorly known and the processes driving changes in atmospheric dust emission and transport remain elusive. Constraining dust provenance is key to resolving these gaps. Here, we present a multi-technique analysis of Greenland dust provenance using novel and established, source diagnostic isotopic tracers as well as results from a regional climate model including dust cycle simulations. We show that the existing dominant model for the provenance of Greenland dust as sourced from combined East Asian dust and Pacific volcanics is not supported. Rather, our clay mineralogical and Hf-Sr-Nd and D/H isotopic analyses from last glacial Greenland dust and an extensive range of Northern Hemisphere potential dust sources reveal three most likely scenarios (in order of probability): direct dust sourcing from the Taklimakan Desert in western China, direct sourcing from European glacial sources, or a mix of dust originating from Europe and North Africa. Furthermore, our regional climate modeling demonstrates the plausibility of European or mixed European/North African sources for the first time. We suggest that the origin of dust to Greenland is potentially more complex than previously recognized, demonstrating more uncertainty in our understanding dust climate feedbacks during abrupt events than previously understood.

Spatiotemporal variation in soil degradation and economic damage caused by wind erosion in Northwest China

Wind erosion causes significant dust emissions in northwest China, resulting in large amounts of soil organic matter and nutrient losses. It has a significant impact on air quality, climate change, vegetation growth, and economic growth at the regional scale. In this work, the Weather Research Forecasting with Chemistry atmospheric chemical transport model was used to simulate the temporal and spatial processes of dust emissions in northwest China from 1980 to 2015. The temporal and spatial variation characteristics of the loss of soil organic matter and nutrients (total nitrogen and total phosphorus) due to dust emissions, and the economic damage from wind erosion, were simulated and calculated. Spatial patterns of soil organic matter and nutrient losses are consistent with dust emission rates across the research region. The average annual dust emissions were approximately 65.17 million tons, with losses of soil organic matter, total nitrogen, and total phosphorus resulting from dust emissions of 531,494 tons, 30,754 tons, and 37,095 tons, respectively. In addition, the average annual economic loss caused by wind erosion was 309.25 million yuan in northwest China during the entire study period. This research is valuable for understanding the role of wind erosion on the carbon and nutrient cycles and the mechanism of soil degradation in northwest China and estimating the economic impacts of wind erosion.

Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital

The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM_2.5 and PM₁₀) virtually ineffective during April to May 2021. The air quality remained not only unabated but also was marred by some unusual extreme pollution events. SAFAR-framework model simulations with different sensitivity experiments were conducted using the newly developed lockdown emission inventory to understand various processes responsible for these anomalies in PM. Model results well captured the magnitude and variations of the observed PM before and after the lockdown but significantly underestimated their levels in the initial period of lockdown followed by the first high pollution event when the mortality counts were at their peak (∼400 deaths/day). It is believed that an unaccounted emission source was playing a leading role after balancing off the impact of curtailed lockdown emissions. The model suggests that the unprecedented surge in PM₁₀ (690 μg/m³) on May 23, 2021, though Delhi was still under lockdown, was associated with large-scale dust transport originating from the north west part of India combined with the thunderstorm. The rainfall and local dust lifting played decisive roles in other unusual events. Obtained results and the proposed interpretation are likely to enhance our understanding and envisaged to help policymakers to frame suitable strategies in such kinds of emergencies in the future.

Snow Albedo Feedbacks Enhance Snow Impurity-Induced Radiative Forcing in the Sierra Nevada

This study employs a fully coupled meteorology-chemistry-snow model to investigate the impacts of light-absorbing particles (LAPs) on snow darkening in the Sierra Nevada. After comprehensive evaluation with spatially and temporally complete satellite retrievals, the model shows that LAPs in snow reduce snow albedo by 0.013 (0-0.045) in the Sierra Nevada during the ablation season (April-July), producing a midday mean radiative forcing of 4.5 W m^-2 which increases to 15-22 W m^-2 in July. LAPs in snow accelerate snow aging processes and reduce snow cover fraction, which doubles the albedo change and radiative forcing caused by LAPs. The impurity-induced snow darkening effects decrease snow water equivalent and snow depth by 20 and 70 mm in June in the Sierra Nevada bighorn sheep habitat. The earlier snowmelt reduces root-zone soil water content by 20%, deteriorating the forage productivity and playing a negative role in the survival of bighorn sheep.

Antecedent Soil Moisture Conditions Influenced Vertical Dust Flux: A Case Study in Iran Using WRF-Chem Model

Soil moisture is one of the most important parameters affecting dust emission flux. This study was conducted to investigate the effects of soil moisture on vertical dust flux in the central plateau region of Iran. In this study, the WRF-Chem (Weather Research and Forecast with Chemistry) model, with the GOCART (Global Ozone Chemistry Aerosol Radiation and Transport) scheme, was used to estimate the dust emission flux during a major storm from 19 to 21 July 2015, and to discriminate between dust sources. The results showed that the Kyrgyz deserts in Turkmenistan, the Arabian deserts in Saudi Arabia, the deserts of Iraq, and the Helmand region in Afghanistan are sources of foreign dust. Additionally, the central desert plain was identified as an internal dust source, where the dust level reached 7000 µg m−2 s−1. The results of WRF-Chem simulation were verified with reanalysis data from MERRA2 and AERONET data from Natanz station, which showed good agreement with the simulation. Based on the GLDAS reanalysis, soil moisture content varied between 2.6% and 34%. Linear and nonlinear regression of vertical dust flux values and soil moisture showed nonlinear behavior following the exponential function, with a correlation coefficient of 0.8 and a strong negative association between soil moisture and vertical dust flux.

Aerosol Nutrients and Their Biological Influence on the Northwest Pacific Ocean (NWPO) and Its Marginal Seas

Simple Summary

With intensifying human activities in the past decades, East Asia has recorded increasingly severe air pollution and become the second largest aerosol source on earth. The large quantity of aerosol emissions is not only a major health threat to humans, but can also be transported for a long distance and deposited in downwind seas and oceans. The aerosol contains major ions, heavy metals, and organic matters that are important external nutrients in upper oceans and potentially influence marine microbes and biogeochemical cycles. Therefore, the role of atmospheric deposition to oceans has received growing attention in recent years. In this paper, the current state of knowledge on the atmospheric nutrients and the biological effect of East Asian aerosol deposition on the northwest Pacific Ocean are reviewed, which could help us better understand the comprehensive influence of East Asian aerosols on marine ecosystems, and give insights into future research directions, especially under the future scenarios of changing human activities and climate.

Abstract

Atmospheric deposition is recognized as a significant source of nutrients in the surface ocean. The East Asia region is among the largest sources of aerosol emissions in the world, due to its large industrial, agricultural, and energy production. Thus, East Asian aerosols contain a large proportion of anthropogenic particles that are characterized by small size, complex composition, and high nutrient dissolution, resulting in important influences on marine microbes and biogeochemical cycles in the downwind areas of the northwest Pacific Ocean (NWPO). By using remote sensing, modeling, and incubation experimental methods, enhanced primary production due to the East Asian aerosol input has been observed in the NWPO, with subsequent promotion and inhibition impacts on different phytoplankton taxa. Changes of bacterial activity and diversity also occur in response to aerosol input. The impact of East Asian aerosol loadings is closely related to the amount and composition of the aerosol deposition as well as the hydrological condition of the receiving seawater. Here, we review the current state of knowledge on the atmospheric nutrients and the effects of the East Asian aerosols on microbes in the NWPO region. Future research perspectives are also proposed.

Development of a Dust Source Map for WRF-Chem Model Based on MODIS NDVI

We present the development of a physically-based dust source map for the GOCART-AFWA dust module in WRF-Chem model. The new parameterization is based on MODIS-NDVI and an updated emission strength map is computed every 15 days from the latest satellite observations. Modeling simulations for the period April–May 2017 over the Mediterranean, north Africa, and the Middle East are compared with observations of AOD at 31 AERONET stations. The new module is capable of reproducing the dust sources at finer detail. The overall performance of the model is improved, especially for stronger dust episodes with AOD > 0.25. For this threshold the model BIAS decreases from −0.20 to −0.02, the RMSE from 0.38 to 0.30, the Correlation Coefficient improves from 0.21 to 0.47, the fractional gross error (FGE) from 0.62 to 0.40, and the mean fractional bias (MFB) from −0.49 to −0.08. Similar improvement is also found for the lower AOD thresholds (>0.0 and >0.1), especially for the stations in Europe, the Mediterranean, Sahel, the Middle East, and Arabian Peninsula, which are mostly affected by dust transport during the experimental period. An overprediction of AOD, compared to the original dust-source scheme, is found for some stations in the Sahara desert, the Atlantic Ocean, and the Iberian Peninsula. In total, 124 out of the 170 statistical scores that are calculated indicate improvement of model performance.

Efficient Atmospheric Transport of Microplastics over Asia and Adjacent Oceans

We developed a regional atmospheric transport model for microplastics (MPs, 10 μm to 5 mm in size) over Asia and the adjacent Pacific and Indian oceans, accounting for MPs' size- and shape-dependent aerodynamics. The model was driven by tuned atmospheric emissions of MPs from the land and the ocean, and the simulations were evaluated against coastal (n = 19) and marine (n = 56) observations. Our tuned atmospheric emissions of MPs from Asia and the adjacent oceans were 310 Gg y^-1 (1 Gg = 1 kton) and 60 Gg y^-1, respectively. MP lines and fragments may be transported in the atmosphere >1000 km; MP pellets in our model mostly deposited near-source. We estimated that 1.4% of the MP mass emitted into the Asian atmosphere deposited into the oceans via atmospheric transport; the rest deposited over land. The resulting net atmospheric transported MP flux from Asia into the oceans was 3.9 Gg y^-1, twice as large as a previous estimate for the riverine-transported MP flux from Asia into the oceans. The uncertainty of our simulated atmospheric MP budget was between factors of 3 and 7. Our work highlighted the impacts of the size and morphology on the aerodynamics of MPs and the importance of atmospheric transport in the source-to-sink relationship of global MP pollution.

Analyses of a Lake Dust Source in the Middle East through Models Performance

Drying lakes have become a new source of dust, causing severe problems in surrounding areas. From 2000 to 2017, a statistical study was conducted on Lake Urmia in Iran in the Middle East. The results indicated a significant increase in the annual number of dusty days in stations around the lake and the mean annual aerosol optical depth (AOD) at 550 nm. The sharp decrease in annual snowfall rate over the Lake Urmia area since 2007 has been linked to the lake’s decreasing water level and drying. During a dust storm event from 27 October to 31 October 2017, a local dust storm originated from Lake Urmia before another large-scale dust storm originated from the An-Nafud desert. According to MODIS true-color images, dust particles were lifted from Lake Urmia and transported eastward to the Caspian Sea and the HYSPLIT model. The comparison of the four models under the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) revealed that the models overestimated surface dust concentrations compared to ground-based PM10 measurements. Nevertheless, the NOAA/WRF-Chem and DREAMABOL models simulated higher dust concentrations during the dust period. More emphasis should be placed on the development of dust models for SDS-WAS models in Lake Urmia.

Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations

This study examines the performance of a data assimilation and forecasting system that simultaneously assimilates satellite aerosol optical depth (AOD) and ground-based PM10 and PM2.5 observations into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The data assimilation case for the surface PM10 and PM2.5 concentrations exhibits a higher consistency with the observed data by showing more correlation coefficients than the no-assimilation case. The data assimilation also shows beneficial impacts on the PM10 and PM2.5 forecasts for South Korea for up to 24 h from the updated initial condition. This study also finds deficiencies in data assimilation and forecasts, as the model shows a pronounced seasonal dependence of forecasting accuracy, on which the seasonal changes in regional atmospheric circulation patterns have a significant impact. In spring, the forecast accuracy decreases due to large uncertainties in natural dust transport from the continent by north-westerlies, while the model performs reasonably well in terms of anthropogenic emission and transport in winter. When the south-westerlies prevail in summer, the forecast accuracy increases with the overall reduction in ambient concentration. The forecasts also show significant accuracy degradation as the lead time increases because of systematic model biases. A simple statistical correction that adjusts the mean and variance of the forecast outputs to resemble those in the observed distribution can maintain the forecast skill at a practically useful level for lead times of more than a day. For a categorical forecast, the skill score of the data assimilation run increased by up to 37% compared to that of the case with no assimilation, and the skill score was further improved by 10% through bias correction.

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM_2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM_2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

15-Year Analysis of Direct Effects of Total and Dust Aerosols in Solar Radiation/Energy over the Mediterranean Basin

The direct radiative effects of atmospheric aerosols are essential for climate, as well as for other societal areas, such as the energy sector. The goal of the present study is to exploit the newly developed ModIs Dust AeroSol (MIDAS) dataset for quantifying the direct effects on the downwelling surface solar irradiance (DSSI), induced by the total and dust aerosol amounts, under clear-sky conditions and the associated impacts on solar energy for the broader Mediterranean Basin, over the period 2003–2017. Aerosol optical depth (AOD) and dust optical depth (DOD) derived by the MIDAS dataset, along with additional aerosol and dust optical properties and atmospheric variables, were used as inputs to radiative transfer modeling to simulate DSSI components. A 15-year climatology of AOD, DOD and clear-sky global horizontal irradiation (GHI) and direct normal irradiation (DNI) was derived. The spatial and temporal variability of the aerosol and dust effects on the different DSSI components was assessed. Aerosol attenuation of annual GHI and DNI were 1–13% and 5–47%, respectively. Over North Africa and the Middle East, attenuation by dust was found to contribute 45–90% to the overall attenuation by aerosols. The GHI and DNI attenuation during extreme dust episodes reached 12% and 44%, respectively, over particular areas. After 2008, attenuation of DSSI by aerosols became weaker mainly because of changes in the amount of dust. Sensitivity analysis using different AOD/DOD inputs from Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset revealed that using CAMS products leads to underestimation of the aerosol and dust radiative effects compared to MIDAS, mainly because the former underestimates DOD.

Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations

The backscattering optical properties of an ensemble of randomly oriented dust particles at a wavelength of 355 nm were comprehensively studied by examining the invariant imbedding T-matrix results of the super-spheroid dust model. In particular, we focused on the lidar ratio ( S ) and depolarization ratio ( δ ) relations of dust aerosols to aid interpretation of data from the Atmospheric Lidar (ATLID) instrument that will be onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite. Super-spheroid models with various aspect ratios ( α ), roundness parameters ( n ) , and refractive indices were investigated over a wide range of particle sizes and compared to the observation data of the National Aeronautics and Space Administration (NASA) Langley 355-nm airborne high spectral resolution lidar. We found that super-spheroid dust particles with different sets of n and α could be used to model almost the entire range of the observed joint distributions of S and δ . The S - δ relation could effectively discriminate among dust particle types. The observed S and δ values with the largest population density were best covered by models with n > 2, especially by those with n varying from 2.4 to 3.0.

Progress in Dust Modelling, Global Dust Budgets, and Soil Organic Carbon Dynamics

Dust emission is an important corollary of the soil degradation process in arid and semi-arid areas worldwide. Soil organic carbon (SOC) is the main terrestrial pool in the carbon cycle, and dust emission redistributes SOC within terrestrial ecosystems and to the atmosphere and oceans. This redistribution plays an important role in the global carbon cycle. Herein, we present a systematic review of dust modelling, global dust budgets, and the effects of dust emission on SOC dynamics. Focusing on selected dust models developed in the past five decades at different spatio-temporal scales, we discuss the global dust sources, sinks, and budgets identified by these models and the effect of dust emissions on SOC dynamics. We obtain the following conclusions: (1) dust models have made considerable progress, but there are still some uncertainties; (2) a set of parameters should be developed for the use of dust models in different regions, and direct anthropogenic dust should be considered in dust emission estimations; and (3) the involvement of dust emission in the carbon cycle models is crucial for improving the accuracy of carbon assessment.

A Coupled BRDF CO2 Retrieval Method for the GF-5 GMI and Improvements in the Correction of Atmospheric Scattering

The Greenhouse Gases Monitoring Instrument (GMI), on board the Chinese Gaofen-5 (GF-5) satellite, provides rich observation data for the global remote sensing of atmospheric CO2. To meet the high-precision satellite retrieval needs of atmospheric CO2, this paper designs a coupled bidirectional reflectance distribution function (BRDF) CO2 retrieval (CBCR) method, which describes the surface reflectance characteristics by the BRDF, corrects for atmospheric scattering based on full physics retrieval theory, and ensures the stable retrieval of multiple parameters and atmospheric CO2 by enriching prior constraints. Theoretical analysis shows that the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics is significantly related to the aerosol optical depth (AOD), solar zenith angle (SZA), and viewing zenith angle (VZA). The validation of GMI CO2 retrievals shows that the CBCR method significantly reduced the influence of the surface bidirectional reflectance characteristics under high AOD and high SZA conditions, decreased the atmospheric CO2 retrieval error from 0.58 ± 5.64 ppm to −1.33 ± 3.13 ppm, and increased the correlation with the temporal variation of actual atmospheric CO2 from 34.7 to 76.8%. Our CBCR method can correct the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics on atmospheric CO2 retrieval, and this work demonstrates that describing the surface reflectance characteristics by using BRDF is a promising idea in the field of satellite CO2 retrievals.

Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates

The Weather Research and Forecasting (WRF) model is used to investigate convection–aerosol interactions in the United Arab Emirates (UAE) for a summertime convective event. Both an idealized and climatological aerosol distributions are considered. The convection on 14 August 2013 was triggered by the low-level convergence of the cyclonic circulation associated with the Arabian Heat Low (AHL) and the daytime sea-breeze circulation. Numerical experiments reveal a high sensitivity to aerosol properties. In particular, replacing 20% of the rural aerosols by carbonaceous particles has a comparable impact on the surface radiative fluxes to increasing the aerosol loading by a factor of 10. In both cases, the UAE-averaged net shortwave flux is reduced by ~90 W m−2 while the net longwave flux increases by ~51 W m−2. However, when the aerosol composition is changed, WRF generates 20% more precipitation than when the aerosol loading is increased, due to a broader and weaker AHL. The surface downward and upward shortwave and upward longwave radiation fluxes are found to scale linearly with the aerosol loading. An increase in the amount of aerosols also leads to drier conditions and a delay in the onset of convection due to changes in the AHL.

Exploring dust heterogeneous chemistry over China: Insights from field observation and GEOS-Chem simulation

Dust heterogeneous chemistry plays an important role in tropospheric chemistry, but its parameterization in numerical models is often quite simplified, which hampers accurate prediction of particulate matter and its chemical component. In this study, we investigate the evolution of dust heterogeneous chemical process and its potential impacts on gaseous and aerosol components during a dust pollution episode from March 27 to April 2, 2015 over North China. Based on field measurements, the significant role of relative humidity (RH) in dust heterogeneous chemistry is found and a RH-dependent parameterization for uptake coefficients of HNO₃ and SO₂ is incorporated in GEOS-Chem to reproduce the dust heterogeneous chemical process. During the study period, observed dust sulfate (DSO4) and dust nitrate (DNIT) exhibit maximum concentrations of 9.1 and 22.8 μg m^-3 respectively, accompanied by high RH and gaseous precursor concentrations. DSO4 concentrations are positively related to RH. The observed dust sulfate oxidation ratio (DSOR) is elevated evidently with increased RH, especially when RH is higher than ~40%, implying that enhanced RH could promote heterogeneous oxidation of SO₂ to DSO4. Model simulation shows that when incorporating the RH-dependent parameterization, DNIT and DSO4 are generally well captured and the model performance of total sulfate oxidation ratio (TSOR) and total nitrate oxidation ratio (TNOR) are improved. High contribution of DNIT and DSO4 are found to be located over the regions close to source areas (>60%) and downwind regions (>40%), respectively. Sensitivity results show that SO₂ and HNO₃ reduce by 2-24 μg m^-3 and 1-18 μg m^-3 when considering dust heterogeneous impacts, thus leading to reduction in non-dust sulfate and non-dust nitrate concentrations. As a result, simulated NH₃ increases and ammonium reduces by more than 20%. Our study indicates that the contribution of heterogeneous reactions to sulfate formation is 20-30% over North China.

Dust Characterization and Its Potential Impact during the 2014–2015 Fogo Volcano Eruption (Cape Verde)

Fogo (Fogo Island) is the youngest and most active volcano of Cape Verde. The last eruption occurred in 2014–2015. Aiming to assess the dust sources that impacted the air quality during the present study period, fresh lava samples were collected, while Saharan dust intrusions and transport were modeled. Rooftop dust was also collected on the island dwellings and a mineralogical and chemical characterization was undertaken. Air quality monitors were used to obtain concentrations of atmospheric particulate matter (PM) and gaseous pollutants. The mineralogical constitution was assessed by XRD and Electron Microprobe. The pseudototal chemical concentration was performed by XRF, ICP-MS and SEM; the latter includes particles morphology. During the study, WRF-CHIMERE results showed the intrusion of desert dust which affected the air quality. Lava was classified as tephritic to basanitic, with high potassium content. The Pollution Load Index for rooftop dust was >1 in all samples, suggesting an enrichment. Higher values were found in dust size fraction <63 µm, with contamination factor pointing to high enrichment of As, Ni and Pb, and very high enrichment of Cd. The non-carcinogenic hazard estimated for children suggested that health problems may arise. The carcinogenic risk was above the target risk, mostly due to As > Pb > Co. Ingestion was the main exposure route. PM10 concentrations exceeded the 24-h mean of 50 µg/m3 recommended by WHO. Nevertheless, TVOCs displayed levels lower than guidelines. The highest levels of CO2 were recorded in more populated villages and farthest from the volcano.

Evaluation of Nine Operational Models in Forecasting Different Types of Synoptic Dust Events in the Middle East

This study investigates four types of synoptic dust events in the Middle East region, including cyclonic, pre-frontal, post-frontal and Shamal dust storms. For each of these types, three intense and pervasive dust events are analyzed from a synoptic meteorological and numerical simulation perspective. The performance of 9 operational dust models in forecasting these dust events in the Middle East is qualitatively and quantitatively evaluated against Terra-MODIS observations and AERONET measurements during the dust events. The comparison of model AOD outputs with Terra-MODIS retrievals reveals that despite the significant discrepancies, all models have a relatively acceptable performance in forecasting the AOD patterns in the Middle East. The models enable to represent the high AODs along the dust plumes, although they underestimate them, especially for cyclonic dust storms. In general, the outputs of the NASA-GEOS and DREAM8-MACC models present greater similarity with the satellite and AERONET observations in most of the cases, also exhibiting the highest correlation coefficient, although it is difficult to introduce a single model as the best for all cases. Model AOD predictions over the AERONET stations showed that DREAM8-MACC exhibited the highest R2 of 0.78, followed by NASA_GEOS model (R2 = 0.74), which both initially use MODIS data assimilation. Although the outputs of all models correspond to valid time more than 24 h after the initial time, the effect of data assimilation on increasing the accuracy is important. The different dust emission schemes, soil and vegetation mapping, initial and boundary meteorological conditions and spatial resolution between the models, are the main factors influencing the differences in forecasting the dust AODs in the Middle East.

Aerosol as a critical factor causing forecast biases of air temperature in global numerical weather prediction models

Weather prediction is essential to the daily life of human beings. Current numerical weather prediction models such as the Global Forecast System (GFS) are still subject to substantial forecast biases and rarely consider the impact of atmospheric aerosol, despite the consensus that aerosol is one of the most important sources of uncertainty in the climate system. Here we demonstrate that atmospheric aerosol is one of the important drivers biasing daily temperature prediction. By comparing observations and the GFS prediction, we find that the monthly-averaged bias in the 24-h temperature forecast varies between ± 1.5 °C in regions influenced by atmospheric aerosol. The biases depend on the properties of aerosol, the underlying land surface, and aerosol-cloud interactions over oceans. It is also revealed that forecast errors are rapidly magnified over time in regions featuring high aerosol loadings. Our study provides direct "observational" evidence of aerosol's impacts on daily weather forecast, and bridges the gaps between the weather forecast and climate science regarding the understanding of the impact of atmospheric aerosol.

Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor?

Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.

Numerical Simulation of Tehran Dust Storm on 2 June 2014: A Case Study of Agricultural Abandoned Lands as Emission Sources

On 2 June 2014, at about 13 UTC, a dust storm arrived in Tehran as a severe hazard that caused injures, deaths, failures in power supply, and traffic disruption. Such an extreme event is not considered as common for the Tehran area, which has raised the question of the dust storm’s origin and the need for increasing citizens’ preparedness during such events. The analysis of the observational data and numerical simulations using coupled dust-atmospheric models showed that intensive convective activity occurred over the south and southwest of Tehran, which produced cold downdrafts and, consequently, high-velocity surface winds. Different dust source masks were used as an input for model hindcasts of the event (forecasts of the past event) to show the capability of the numerical models to perform high-quality forecasts in such events and to expand the knowledge on the storm’s formation and progression. In addition to the proven capability of the models, if engaged in operational use to contribute to the establishment of an early warning system for dust storms, another conclusion appeared as a highlight of this research: abandoned agricultural areas south of Tehran were responsible for over 50% of the airborne dust concentration within the dust storm that surged through Tehran. Such a dust source in the numerical simulation produced a PM10 surface dust concentration of several thousand μm/m3, which classifies it as a dust source hot-spot. The produced evidence indivisibly links issues of land degradation, extreme weather, environmental protection, and health and safety.

Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response

The World Health Organization estimates that around 7 million people die every year from exposure to fine particles (PM2.5) inpolluted air. Here, the number of premature deaths in Europe from different diseases associated to the ambient exposure to PM2.5 have here been studied both for present (1991-2010) and future periods (2031-2050, RCP8.5 scenario). This contribution combines different state-of-the-art approaches (use of high-resolution climate/chemistry simulations over Europe for providing air quality data; use of different baseline mortality data for specific European regions; inclusion of future population projections and dynamical changes for 2050 obtained from the United Nations (UN) Population Projections or use of non-linear exposure-response functions) to estimate the premature mortality due to PM2.5. The mortality endpoints included in this study are Lung Cancer (LC), Chronic Obstructive Pulmonary Disease (COPD), Cerebrovascular Disease (CEV), Ischemic Heart Disease (IHD), Lower Respiratory Infection (LRI) and other Non-Communicable Diseases (other NCDs). Different risk ratio and baseline mortalities for each disease end each age range have been estimated individually. The results indicate that the annual excess mortality rate from fine particulate matter in Europe is 904,000 [95% confidence interval (95% CI) 733,100-1,067,800], increasing by 73% in 2050s (1,560,000; 95% CI 1,260,000-1,840,000); meanwhile population decreases from 808 to 806 million according to the UN estimations. The results show that IHD is the main cause of premature mortality in Europe associated to PM2.5 (around 48%) both for the present and future periods. Despite several marked regional differences, premature deaths associated to all the endpoints included in this study will increase in the future period due to the climate penalty but especially because of changes in the population projected and its aging.

Marginal warming associated with a COVID-19 quarantine and the implications for disease transmission

During January-February 2020, parts of China faced restricted mobility under COVID-19 quarantines, which have been associated with improved air quality. Because particulate pollutants scatter, diffuse, and absorb incoming solar radiation, a net negative radiative forcing, decreased air pollution can yield surface warming. As such, this study (1) documents the evolution of China's January-February 2020 air temperature and concurrent particulate changes; (2) determines the temperature response related to reduced particulates during the COVID-19 quarantine (C19Q); and (3) discusses the conceptual implications for temperature-dependent disease transmission. C19Q particulate evolution is monitored using satellite analyses, and concurrent temperature anomalies are diagnosed using surface stations and Aqua AIRS imagery. Meanwhile, two WRF-Chem simulations are forced by normal emissions and the satellite-based urban aerosol changes, respectively. Urban aerosols decreased from 27.1% of pre-C19Q aerosols to only 17.5% during C19Q. WRF-Chem resolved ~0.2 °C warming across east-central China, that represented a minor, though statistically significant contribution to C19Q temperature anomalies. The largest area of warming is concentrated south of Chengdu and Wuhan where temperatures increased between +0.2-0.3 °C. The results of this study are important for understanding the anthropogenic forcing on regional meteorology. Epidemiologically, the marginal, yet persistent, warming during C19Q may retard temperature-dependent disease transmission, possibly including SARS-CoV-2.

Saharan dust and giant quartz particle transport towards Iceland

Mineral dust emissions from Saharan sources have an impact on the atmospheric environment and sedimentary units in distant regions. Here, we present the first systematic observations of long-range Saharan dust transport towards Iceland. Fifteen Saharan dust episodes were identified to have occurred between 2008 and 2020 based on aerosol optical depth data, backward trajectories and numerical models. Icelandic samples from the local dust sources were compared with deposited dust from two severe Saharan dust events in terms of their granulometric and mineralogical characteristics. The episodes were associated with enhanced meridional atmospheric flow patterns driven by unusual meandering jets. Strong winds were able to carry large Saharan quartz particles (> 100 µm) towards Iceland. Our results confirm the atmospheric pathways of Saharan dust towards the Arctic, and identify new northward meridional long-ranged transport of giant dust particles from the Sahara, including the first evidence of their deposition in Iceland as previously predicted by models.

Strong links between Saharan dust fluxes, monsoon strength, and North Atlantic climate during the last 5000 years

Despite the multiple impacts of mineral aerosols on global and regional climate and the primary climatic control on atmospheric dust fluxes, dust-climate feedbacks remain poorly constrained, particularly at submillennial time scales, hampering regional and global climate models. We reconstruct Saharan dust fluxes over Western Europe for the last 5000 years, by means of speleothem strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) and karst modeling. The record reveals a long-term increase in Saharan dust flux, consistent with progressive North Africa aridification and strengthening of Northern Hemisphere latitudinal climatic gradients. On shorter, centennial to millennial scales, it shows broad variations in dust fluxes, in tune with North Atlantic ocean-atmosphere patterns and with monsoonal variability. Dust fluxes rapidly increase before (and peaks at) Late Holocene multidecadal- to century-scale cold climate events, including those around 4200, 2800, and 1500 years before present, suggesting the operation of previously unknown strong dust-climate negative feedbacks preceding these episodes.