A satellite view of aerosols in the climate system

Spatiotemporal analysis of sand and dust emission point sources detected from satellite imagery in Syria, Jordan, and Iraq

This study utilized MODIS true color satellite imagery to analyse blowing sand and dust events dynamics in the Middle East from 2010 to 2021, focusing on Syria, Iraq, and Jordan. A total of 4923 dust point sources were detected, with a significant concentration (~90 %) located within the Tigris-Euphrates Basin (Nearest Neighbor Ratio = 0.41, р < 0.001). Land cover analysis revealed that bare land, comprising most of the study area, was the predominant source of dust emissions. Wetlands, though only constituting about 1 % of the area, showed the highest frequency of dust sources per unit area, highlighting their role as critical dust emission hotspots. The study emphasizes the impact of drought and anthropogenic factors, such as poor land management, on blowing dust intensity. It suggests the necessity of strategic land management practices, including re-vegetation of arid areas, reducing soil exposure, and implementing wind erosion control measures. To effectively address the transboundary nature of dust emissions, the findings underscore the importance of fostering regional cooperation through mechanisms such as shared environmental monitoring and data exchange platforms, joint management of cross-border natural resources, and collaborative policy making.

Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States

Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data. We developed an innovative angle-dependent deep-learning model (ADLM) that accounts for angular diversity in dual-angle observations. The model captures aerosol properties observed from dual angles in the contiguous United States and explores the potential of Greenhouse gases Observing Satellite-2's (GOSAT-2) measurements to retrieve fAOD at a 460 m spatial resolution. The ADLM demonstrates a strong performance through rigorous validation against ground-based data, revealing small biases. By comparison, the official fAOD product from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Multiangle Imaging Spectroradiometer (MISR) during wildfire events is underestimated by more than 40% over western USA. This leads to significant differences in estimates of aerosol radiative forcing (ARF) from wildfires. The ADLM shows more than 20% stronger ARF than the MODIS, VIIRS, and MISR estimates, highlighting a greater impact of wildfire fAOD on Earth's energy balance.

Effects of urbanization on cloud-to-ground lightning strike frequency: a global perspective

Urbanization tends to increase local lightning frequency (i.e. the 'lightning enhancement' effect). Despite many urban areas showing lightning enhancement, the prevalence of these effects is unknown and the drivers underlying these patterns are poorly quantified. We conducted a global assessment of cloud-to-ground lightning flashes (lightning strikes) across 349 cities to evaluate how the likelihood and magnitude of lightning enhancement vary with geography, climate, air pollution, topography and urban development. The likelihood of exhibiting lightning enhancement increased with higher temperature and precipitation in urban areas relative to their natural surroundings (i.e. urban heat islands and elevated urban precipitation), higher regional lightning strike frequency, greater distance to water bodies and lower elevations. Lightning enhancement was stronger in cities with conspicuous heat islands and elevated urban precipitation effects, higher lightning strike frequency, larger urban areas and lower latitudes. The particularly strong effects of elevated urban temperature and precipitation indicate that these are dominant mechanisms by which cities cause local lightning enhancement.

Biomineralization for Reducing and Controlling Sand-Dust Storms

The sand-dust weather and sand-dust storms have become a serious environmental disaster worldwide. It is an important challenge to develop technologies for desert sand solidification in order to prevent and control sand-dust weather. The biomineralization technology for solidifying desert sands has been a novel method for reinforced soils in recent years. The biomineralization solidification sand field tests are completed at the Wuma Highway solidification section in the Tengger Desert. The superiority of the biomineralization for solidifying sands is verified by measuring the water storage capacity of different reinforcement zones including bare sand zone, plant zone, biomineralization solidifying sand zone, and biomineralization combined plant solidifying sand zone. Simultaneously, the molecular dynamics calculation analysis is used to verify the role of biomineralization solidifying sands in preventing sand-dust storms. All results demonstrate that the biomineralization solidification sand method is effective for controlling and preventing sandstorm disasters.

Evaluation and analysis of long-term MODIS MAIAC aerosol products in China

NASA has released the latest Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) Collection 6 (C6) and Collection 6.1 (C6.1) aerosol optical depth (AOD) products with 1 km spatial resolution. This study validated and compared C6 and C6.1 MAIAC AOD products with AERONET observations in terms of accuracy and stability, and analyzed the spatiotemporal characteristics of AOD at different scales in China. The results show that the overall accuracy of MAIAC products is good, with correlation coefficient (R) > 0.9, mean bias (BIAS) < 0.015, and the fraction within the expected error (EE) > 68 %. However, after the algorithm update, the accuracy of Terra MAIAC aerosol products C6.1 has significantly decreased. The accuracy of the products varies with the region. The accuracy of C6.1 in North China, Central East China, and West China, is comparable to or even exceeds that of C6, but performs poorly in South China. In addition, the stability of the updated C6.1 MAIAC aerosol products has not seen significantly improvement. The metrics of no product can all meet the stability goals of the Global Climate Observing System (GCOS, 0.02 per decade) in China. C6.1 improves the retrieval frequency in many regions and temporarily solves the problem of AOD discontinuity at the boundaries of different aerosol models in C6, but there are some fixed climatological AOD blocks (AOD = 0.014) in the eastern Tibetan Plateau region. Both C6 and C6.1 can capture similar annual variation characteristics of AOD to those observed at the AERONET sites. The study provides possible references for improving the MAIAC algorithm and building long-term stable aerosol records.

Long-term quantification of springtime aerosols over Saudi Arabia using multi-satellite remotely sensed data

A comprehensive analysis of aerosol characteristics over Saudi Arabia from 2005 to 2022, utilizing high-resolution satellite-based observations and reanalysis datasets, examining the distribution of aerosols and their subtypes across the three dimensions (temporal, spatial, and altitude based) for March, April, and May. This study focuses on the analysis of parameters such as aerosol optical depth (AOD), angstrom exponent (AE), absorption aerosol optical depth (AAOD), and Ultraviolet Aerosol Index (UVAI), revealing significant spatial disparities, with elevated aerosol concentrations in the central and eastern regions and comparatively lower concentrations along the western coastal areas. In this study, the spatial patterns and temporal trends are analyzed through trajectory modeling. The study also investigates the composition of aerosols in various Saudi cities. Aerosols prevailing in a dozen Saudi Arabian cities were systematically categorized into six sub-types, considering their particle size and UV-absorbing properties. Notably, two major aerosol sub-types, absorbing coarse (AC) aerosols (UVAI > 0.25, AE < 0.70) treated as mineral dust and absorbing mixed (AM) aerosols (0.70 < AE < 1.25) along with neutral fine (NF) particles (- 0.5 < UVAI < 0.25, AE > 1.25) treated as urban, predominate across the Kingdom of Saudi Arabia.

Determining the Aethalometer multiple scattering enhancement factor C from the filter loading parameter

Light-absorbing aerosols heat the atmosphere; an accurate quantification of their absorption coefficient is mandatory. However, standard reference instruments (CAPS, MAAP, PAX, PTAAM) are not always available at each measuring site around the world. By integrating all previous published studies concerning the Aethalometers, the AE33 filter loading parameter, provided by the dual-spot algorithm, were used to determine the multiple scattering enhancement factor from the Aethalometer itself (hereinafter CAE) on an yearly and a monthly basis. The method was developed in Milan, where Aethalometer measurements were compared with MAAP data; the comparison showed a good agreement in terms of equivalent black carbon (R2 = 0.93; slope = 1.02 and a negligible intercept = 0.12 μg m-3) leading to a yearly experimental multiple scattering enhancement factor of 2.51 ± 0.04 (hereinafter CMAAP). On a yearly time base the CAE values obtained using the new approach was 2.52 ± 0.01, corresponding to the experimental one (CMAAP). Considering the seasonal behavior, higher experimental CMAAP and computed CAE values were found in summer (2.83 ± 0.12) whereas, the lower ones in winter/early-spring (2.37 ± 0.03), in agreement with the single scattering albedo behavior in the Po Valley. Overall, the agreement between the experimental CMAAP and CAE showed a root mean squared error (RMSE) of just 0.038 on the CMAAP prediction, characterized by a slope close to 1 (1.001 ± 0.178), a negligible intercept (-0.002 ± 0.455) and a high degree of correlation (R2 = 0.955). From an environmental point of view, the application of a dynamic (space/time) determination of CAE increases the accuracy of the aerosol heating rate (compared to applying a fixed C value) up to 16 % solely in Milan, and to 114 % when applied in the Arctic at 80°N.

Transport and deposition of radionuclides from northern Africa to the southern Iberian Peninsula and the Canary Islands during the intense dust intrusions of March 2022

The present study focuses on the two consecutive and markedly intense Saharan dust intrusion episodes that greatly affected southern Spain (Málaga) and, to a lesser extent, the Canary Islands (Tenerife), in March 2022. These two episodes were the result of atypical meteorological conditions in the region and resulted in record levels of aerosols in the air at the Málaga location. The activity levels of various natural and artificial radionuclides (7Be, 210Pb, 40K, 137Cs, 239Pu, 240Pu, 239+240Pu) and radioactive indicators (gross alpha and gross beta) were impacted by these events and the results are described herein. These episodes caused, for example, the activities of 137Cs in aerosol samples at the Málaga monitoring station to reach the highest concentrations ever recorded since high-volume aerosol monitoring started at this site in 2009. A link between the activity levels of 137Cs, 40K and gross alpha in the atmospheric aerosols and daily PM10 concentrations during the episodes is also reported. In addition, isotopic ratios are discussed in the context of the source and destination of the various anthropogenic radionuclides measured. The atmospheric residence time of aerosols during these episodes is also evaluated because it concerns how intrusions to the Canary Islands should be analysed. Finally, for the first time, the concentrations of 137Cs deposition by rainwater during a Saharan dust intrusion are reported and the deposition rate of these radionuclides during these episodes is discussed.

Climate change and geo-environmental factors influencing desertification: a critical review

The problem of desertification (DSF) is one of the most severe environmental disasters which influence the overall condition of the environment. In Rio de Janeiro Earth Summit on Environment and Development (1922), DSF is defined as arid, semi-arid, and dry sub-humid induced LD and that is adopted at the UNEP's Nairobi ad hoc meeting in 1977. It has been seen that there is no variability in the trend of long-term rainfall, but the change has been found in the variability of temperature (avg. temp. 0-5 °C). There is no proof that the air pollution brought on by CO2 and other warming gases is the cause of this rise, which seems to be partially caused by urbanization. The two types of driving factors in DSF-CC (climate change) along with anthropogenic influences-must be compared in order to work and take action to stop DSF from spreading. The proportional contributions of human activity and CC to DSF have been extensively evaluated in this work from "qualitative, semi-quantitative, and quantitative" perspectives. In this study, we have tried to connect the drives of desertification to desertification-induced migration due to loss of biodiversity and agriculture failure. The authors discovered that several of the issues from the earlier studies persisted. The policy-makers should follow the proper SLM (soil and land management) through using the land. The afforestation with social forestry and consciousness among the people can reduce the spreading of the desertification (Badapalli et al. 2023). The green wall is also playing an important role to reduce the desertification. For instance, it was clear that assessments were subjective; they could not be readily replicated, and they always relied on administrative areas rather than being taken and displayed in a continuous space. This research is trying to fulfill the mentioned research gap with the help of the existing literatures related to this field.

Influence of industrial sustainability transition on air quality in a typical resource-exhausted city

The industrial transition of resource-exhausted cities is the focus of attention, and air quality has naturally become an important indicator to measure the sustainable development quality. Aerosol optical depth (AOD) is an important parameter to indicate air quality. This paper aimed to study the influence of industrial transition on air quality and provide a list of recommendations and management strategies for sustainable development in resource-exhausted cities. Results showed the secondary industry played important roles for economic development before 2015, however, it decreased after 2014, and the tertiary industry played more and more important roles from 2015. Analyses of the spatial distribution of AOD in each year showed that AOD was relatively higher in urban areas with concentrated population, and the threshold range of AOD value with high area ratio in spatial distribution decreased gradually, which was consistent with the analysis results of time series. Results of correlation analyses indicated that air temperature and land surface temperature were the main natural meteorological factors influencing AOD. Gross population, SO2 emission and the cultivated land area were the main socio-economic factors influencing AOD. It could be concluded that the industrial transition of the city has achieved good results, the economic structure has been gradually optimized and adjusted, and the air quality has gradually improved over industrial sustainability transition. Scientific exploitation, energy conservation, application of clean energy and industrial structure optimization would be effective measures for sustainable development.

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

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

Reducing shape errors in the discrete dipole approximation using effective media

The discrete dipole approximation (DDA) simulates optical properties of particles with any given shape based on the volume discretization. These calculations cost a large amount of time and memory to achieve high accuracy, especially for particles with large sizes and complex geometric structures, such as mixed black-carbon aerosol particles. We systematically study the smoothing of the DDA discretization using the effective medium approximation (EMA) for boundary dipoles. This approach is tested for optical simulations of spheres and coated black-carbon (BC) aggregates, using the Lorenz-Mie and multiple-sphere T-Matrix as references. For spheres, EMA significantly improves the DDA accuracy of integral scattering quantities (up to 60 times), when the dipole size is only several times smaller than the sphere diameter. In these cases, the application of the EMA is often comparable to halving the dipole size in the original DDA, thus reducing the simulation time by about an order of magnitude for the same accuracy. For a coated BC model based on transmission electron microscope observations, the EMA (specifically, the Maxwell Garnett variant) significantly improves the accuracy when the dipole size is larger than ¼ of the monomer diameter. For instance, the relative error of extinction efficiency is reduced from 4.7% to 0.3% when the dipole size equals that of the spherical monomer. Moreover, the EMA-DDA achieves the accuracy of 1% for extinction, absorption, and scattering efficiencies using three times larger dipoles than that with the original DDA, corresponding to about 30 times faster simulations.

Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations

Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50 g m-2). The distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.

Positive feedback to regional climate enhances African wildfires

Regional climate strongly regulates the occurrence of wildfires partly because drying of fuel load increases fires. The large amounts of aerosols released by wildfires can also strongly affect regional climate. Here we show positive feedback (a seasonal burned area enhancement of 7-17%) due to wildfire aerosol forcing in Africa found in the simulations using the interactive REgion-Specific ecosystem feedback Fire (RESFire) model in the Community Earth System Model (CESM). The positive feedback results partly from the transport of fire aerosols from burning (dry) to wet regions, reducing precipitation and drying fuel load to enhance fires toward the non-burning (wet) region. This internally self-enhanced burning is an important mechanism for the regulation of African ecosystems and for understanding African fire behaviors in a changing climate. A similar mechanism may also help sustain wildfires in other tropical regions.

Spectroscopy of cluster aerosol models: IR and UV spectra of hydrated glyoxylate with and without sea salt

Glyoxylic acid is formed in the troposphere by oxidation of organic molecules. In sea salt aerosols, it is expected to be present as glyoxylate, integrated into the salt environment and strongly interacting with water molecules. In water, glyoxylate is in equilibrium with its gem-diol form. To understand the influence of water and salt on the photophysics and photochemistry of glyoxylate, we generate small model clusters containing glyoxylate by electrospray ionization and study them by Fourier-Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry. We used infrared multiple photon dissociation spectroscopy and UV/vis photodissociation spectroscopy for structural characterization as well as quantum chemical calculations to model the spectra and dissociation patterns. Resonant absorption of infrared radiation leads to water evaporation, which indicates that water and glyoxylate are separate molecular entities in a significant fraction of the clusters, in line with the observed absorption of UV light in the actinic region. Hydration of glyoxylate leads to a change of the dihedral angle in the CHOCOO-·H2O complex, causing a slight redshift of the S1 ← S0 transition. However, the barriers for internal rotation are below 5 kJ mol-1, which explains the broad S1 ← S0 absorption extending from about 320 to 380 nm. Most importantly, hydration hinders dissociation in the S1 state, thus enhancing the quantum yield of fluorescence combined with water evaporation. No C-C bond photolysis is observed, but due to the limited signal-to-noise ratio, it cannot be ruled out. The quantum yield, however, will be relatively low. Fluorescence dominates the photophysics of glyoxylate embedded in the dry salt cluster, but the quantum yield shifts towards internal conversion upon addition of one or two water molecules.

Distribution and concentration pathway of particulate pollution during pandemic-induced lockdown in metropolitan cities in India

To characterize the pollutant dispersal across major metropolitan cities in India, daily particulate matter (PM10 and PM2.5) data for the study areas were collected from the National Air Quality Monitoring stations database provided by the Central Pollution Control Board (CPCB) of India. The data were analysed for three temporal ranges, i.e. before the pandemic-induced lockdown, during the lockdown, and after the upliftment of lockdown restrictions. For the purpose, the time scale ranged from 1st April to 31st May for the years 2019 (pre), 2020, and 2021 (post). Statistical distributions (lognormal, Weibull, and Gamma), aerosol optical thickness, and back trajectories were assessed for all three time periods. Most cities followed the lognormal distribution for PM2.5 during the lockdown period except Mumbai and Hyderabad. For PM10, all the regions followed the lognormal distribution. Delhi and Kolkata observed a maximum decline in particulate pollution of 41% and 52% for PM2.5 and 49% and 53% for PM10, respectively. Air mass back trajectory suggests local transmission of air mass during the lockdown period, and an undeniable decline in aerosol optical thickness was observed from the MODIS sensor. It can be concluded that statistical distribution analysis coupled with pollution models can be a counterpart in studying the dispersal and developing pollution abatement policies for specific sites. Moreover, incorporating remote sensing in pollution study can enhance the knowledge about the origin and movement of air parcels and can be helpful in taking decisions beforehand.

Retrieval uncertainty and consistency of Suomi-NPP VIIRS deep blue and dark target aerosol products under diverse aerosol loading scenarios over South Asia

Retrieval accuracy and stability of two operational aerosol retrieval algorithms, Deep Blue (DB) and Dark Target (DT), applied on Visible Infrared Imaging Radiometer Suite (VIIRS) on-board Suomi National Polar-orbiting Partnership (S-NPP) satellite were evaluated over South Asia. The region is reported to be highly challenging to accurate estimation of satellite-based aerosol optical properties due to variations in surface reflectance, complex aerosol system and regional meteorology. Performance of both algorithms were initially evaluated by comparing their ability to retrieve aerosol signal over the complex geographical region under specific air pollution emission scenario. Thereafter, retrieval accuracy was investigated against 10 AERONET sites across South Asia, selected based on their geography and predominance aerosol types, from year 2012-2021. Geo-spatial analysis indicates DB to efficiently retrieve fine aerosol features over bright arid surfaces, and for smoke/dust dominating events whereas DT was better to identify small fire events under dark vegetated surface. Both algorithms however, indicate unsatisfactory retrieval accuracy against AERONET having 56-59% of valid retrievals with high RMSE (0.30-0.33) and bias. Overall, DB slightly underpredicted AOD with -0.02 mean bias (MB) whereas DT overpredicted AOD (MB: 0.13), with seasonality in their retrieval efficiency against AERONET. Time-series analysis indicates stability in retrieving AOD and match-up number for both algorithms. Retrieval bias of DB and DT AOD against AERONET AOD under diverse aerosol loading, aerosol size, scattering/absorbing aerosol, and surface vegetation coverage scenarios revealed DT to be more influenced by these conditions. Error analysis indicates at low AOD (≤0.2), accuracy of both DB and DT were subject to underlying vegetation coverage. At AOD>0.2, DB performed well in retrieving coarse aerosols whereas DT was superior when fine aerosols dominated. Overall, accuracy of both VIIRS algorithms require further refinement to continue MODIS AOD legacy over South Asia.

Risk Assessment and Source Apportionment of Metals on Atmospheric Particulate Matter in a Suburban Background Area of Gran Canaria (Spain)

Concentration levels of 11 heavy metals were analyzed in PM10 and PM2.5 samples from a suburban area frequently affected by Saharan dust in which is located a school. The heavy metals risk assessment was carried out by the 2011 U.S. Environmental Protection Agency method, estimating the chronic and carcinogenic hazard levels both in adults and children. The highest level of chronic hazard was reached for Cr, with values of approximately 8 (PM10, adulthood), 2 (PM10, childhood) and 1.5 (PM2.5, adult age), significantly exceeding the limit value (equal to 1). Regarding the carcinogenic risk level, it was also high for Cr, with values between 10-3 and 10-1 for both study populations and particle size. For the rest of the studied metals, no health risk levels of concern were obtained. The positive matrix factorization method was used for the estimation of heavy metal emission sources apportionment. Non-exhaust vehicle emissions were the main source of Cr emissions under PM2.5, while industrial processes were the main source for PM10. Mineral dust and marine aerosol were common emission sources for both particles sizes-with different contributions. Vehicle emissions, construction and agricultural activities were the main emission sources for PM10, and fossil fuel combustion, road dust re-suspension and ammonium sulfate were for PM2.5. The results obtained in this study support the need to continue applying mitigation measures in suburban areas which are affected by nearby anthropogenic emissions, causing the consequent emission of materials hazardous to human health.

Trend relationship between mountain normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) across two decades: implication for water quality within the Lesotho Highlands, Drakensberg, South Africa

There are growing concerns on contribution of vegetation dynamics to atmospheric turbidity and quality of regional water towers. The study sought to determine the trends in the MODIS/TERRA-derived normalized difference vegetation index (NDVI) and aerosol optical depth (AOD) for Lesotho Highland over 2000-2020. The predictive relationship between the two variables was also examined using regression analysis. Irrespective of yearly AOD patterns, the AOD showed biphasic patterns peaking between mid-winter to early spring (July-October) (highest) and autumn (Feb-April) (next highest), and lowest in the summer (Nov-January). The monthly NDVI was largest in January-March (summer-early fall) with smaller values in winter and spring. This seasonality can be related to the peak of anthropogenic biomass combustion during the winter and strong winds during the spring and early summer. The AOD relationship with NDVI showed quadratic patterns peaking and plunging with changes in season. About 30-80% (R² = 0.3-0.8%) changes in annual AOD from 2000 to 2020 were explainable by the dynamics of NDVI indicating that increased NDVI contributes to about a 50% decrease in AOD in the Lesotho Highlands. However, an outlier trend was observed in 2007 (R² = 13%). Incidences of high AOD in months of high NDVI may be indicative of traveling aerosols, i.e., aerosols from non-local sources/activity. On the other hand, high AOD in months of low NDVI implicates local aerosol sources. Trend relationship studies on vegetation loss and AOD in mountain areas of other regions could improve knowledge of contaminant dynamics and risk implications for downstream populations.

Synergistic interactions of fine particles and radiative effects in modulating urban heat islands during winter haze event in a cold megacity of Northeast China

Severe air pollution and urban heat islands (UHI) intensity (UHII) are two challenging problems that have attracted wide attention in populated cities. However, previous studies mostly focused on the relationship between fine particulate matter (PM_2.5) and UHII, but how UHII responds to the interactions between radiative effects (direct effect (DE), indirect effect (IDE) with slope and shading effects (SSE)) and PM_2.5 during heavy pollution is still unclear, especially in the cold region. Therefore, this study explores the synergistic interactions between PM_2.5 and radiative effects in influencing UHII during a heavy pollution event in the cold-megacity of Harbin-China. Hence, we designed four scenarios: non-aerosol radiative feedback (NARF), DE, IDE, and combined effects (DE + IDE + SSE) in December 2018 (clear-episode) and December 2019 (heavy-haze-episode) using numerical modeling. The results showed that the radiative effects influenced the spatial distribution of PM_2.5 concentration leading to a mean drop in 2-m air-temperature by approximately 0.67 °C (downtown) and 1.48 °C (satellite-town) between the episodes. The diurnal-temporal variations revealed that the daytime and nighttime UHIIs were strengthened in the downtown during the heavy-haze-episode, while a reverse effect was observed in the satellite-town. Interestingly, during the heavy-haze-episode, the considerable difference between excellent and heavily polluted PM_2.5 levels showed a decrease in UHIIs (1.32 °C, 1.32 °C, 1.27 °C, and 1.20 °C) due to the radiative effects (NARF, DE, IDE, and (DE + IDE + SSE)), respectively. In assessing other pollutants' interactions with the radiative effects, PM₁₀ and NOx had a considerable impact on the UHII during the heavy-haze episode while O₃ and SO₂ were discovered to be very low in both episodes. Moreover, the SSE has uniquely influenced UHII, especially during the heavy-haze-episode. Therefore, insight from this study provides an understanding of how UHII responds uniquely in the cold region, which in turn could help to formulate effective policies and co-mitigation strategies for air pollution and UHI problems.

Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 2001-2018

East Africa (EA) suffers from the inadequate characterization of atmospheric aerosols, with far-reaching consequences of its inability to quantify precisely the impacts of these particles on regional climate. The current study aimed at characterizing absorption and radiative properties of aerosols using the long-term (2001-2018) AErosol RObotic NETwork (AERONET) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data over three environmentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD_{440 nm}), absorption Angstrom Exponent (AAE_{440-870 nm}), total effective radius (R_Eff), and total volume concentration (μm³/μm²) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols compared to the coarse-mode particles. The monthly variation in SSA_{440 nm} over EA explains the strength in absorption aerosols that range from moderate to strong absorbing aerosols. The aerosols exhibited significant variability over the study domain, with the dominance of absorbing fine-mode aerosols over Mbita accounting for ∼40 to ∼50 %, while weakly absorbing coarse-mode particles accounted for ∼8.2 % over Malindi. The study conclusively determined that Mbita was dominated by AAOD mainly from biomass burning in most of the months, whereas Malindi was coated with black carbon. The direct aerosol radiative forcing (DARF) retrieved from both the AERONET and MERRA-2 models showed strong cooling at the top of the atmosphere (TOA; -6 to -27 Wm^-2) and the bottom of the atmosphere (BOA, -7 to -66 Wm^-2). However, significant warming was noticed within the atmosphere (ATM; +14 to +76 Wm^-2), an indication of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and radiative characteristics over EA and can form the basis of other related studies over the domain and beyond.

Quantum enhanced radio detection and ranging with solid spins

The accurate radio frequency (RF) ranging and localizing of objects has benefited the researches including autonomous driving, the Internet of Things, and manufacturing. Quantum receivers have been proposed to detect the radio signal with ability that can outperform conventional measurement. As one of the most promising candidates, solid spin shows superior robustness, high spatial resolution and miniaturization. However, challenges arise from the moderate response to a high frequency RF signal. Here, by exploiting the coherent interaction between quantum sensor and RF field, we demonstrate quantum enhanced radio detection and ranging. The RF magnetic sensitivity is improved by three orders to 21 [Formula: see text], based on nanoscale quantum sensing and RF focusing. Further enhancing the response of spins to the target's position through multi-photon excitation, a ranging accuracy of 16 μm is realized with a GHz RF signal. The results pave the way for exploring quantum enhanced radar and communications with solid spins.

An assessment of aerosol optical depth over three AERONET sites in South Africa during the year 2020

It is important to notice that the world health organization (WHO) on  the 11th of March 2020,  declared COVID-19 a global pandemic and in response governments around the world introduced lockdowns that restricted human and traffic movements including South Africa. This pandemic resulted in a total lockdown from 26 March until 16 April 2020 in South Africa with expected  decrease in atmospheric aerosols. In this present study,  the aerosol optical depth (AOD) over Southern Africa based on ground-based remotely sensed data derived from three AERONET sites (Durban, Skukuza and Upington) during 2020 were used to detrermine the restriction resopnse on atmospheric aerosol pollution  The study used data from 2019, 2018 and 2017  as base years. The AERONET derived data was complemented with the HYSPLIT Model and NCEP/NCAR Reanalysis data. The study findings show that peak increase of AOD corresponds to Angstrom exponent (AE) enhancement for two sites Durban and Skukuza during winter (JJA) while the Upington site showed a different trend where peak AOD were observed in spring (SON). The study also observed the influence of long transport airmasses particularly those originating from the Atlantic and Indian ocean moreso for the Durban and Skukuza sites (summer and autumn) thus these sites received fresh marine aerosols however this was not the case for Upington which fell under the influence of short-range inland airmasses and was likely to receive anthropogenic and dust aerosols. The major results  suggest that the lockdowns did not translate into a significant decrease in AOD levels compared to previous immediate years. The results has presented restriction response of AOD over South Africa but additional analysis is required using more locations to compare results.

What Factors Dominate the Change of PM2.5 in the World from 2000 to 2019? A Study from Multi-Source Data

As the threat to human life and health from fine particulate matter (PM2.5) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM2.5 and exploring the drivers of PM2.5 are important tools for addressing the life-threatening health problems caused by PM2.5. In this study, we calculated the change in annual average global PM2.5 concentrations from 2000 to 2020 using the Theil-Sen median trend analysis method and reveal spatial and temporal trends in PM2.5 concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM2.5 concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM2.5 concentration, with significant decreases in PM2.5 concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM2.5 in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM2.5 concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM2.5 concentration, while an increase in NDVI can play an important role in the reduction in PM2.5 concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.

Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations

The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To ensure the reliability of their applications and build a scientific reference for the further optimization, it is imperative to conduct a comprehensive evaluation, especially for the unique size-resolved AOD products: small-size AOD (AOD_S, representing the contribution of fine-mode aerosols), medium-size AOD (AOD_M), and large-size AOD (AOD_L), and AOD_M+L represents the AOD part of coarse-mode aerosols. AErosol RObotic NETwork (AERONET) and MODerate-resolution Imaging Spectroradiometer (MODIS) Collection (C) 6.1 aerosol products from 2001 to 2020 are utilized for the validation, analysis, and inter-comparison, considering three spatial scales and four key factors. In general, MISR V23 aerosol products show a good accuracy compared with AERONET. The best performance for all AOD products appears in forest units (the highest R ~ 0.93, data percentage within Expected Error bounds, %EE > 93), related to the inactive human activity and dark underlying surface. Dependences of retrieval deviations illustrate that the performance of MISR AOD deteriorates as aerosol loading increases. Namely, with the increase of aerosols, total AOD (AOD_T) and AOD_S show increasing negative deviations, while increasing positive deviations are observed for AOD_M+L. This suggests that the Empirical Orthogonal Functions do not perform well in this situation, since numerous aerosol particles can obstruct the underlying reflection and reduce the surface spectral contrast. In addition, AOD_T and AOD_S often exhibit anomalous positive deviations in areas with low vegetation cover, such as deserts, revealing that MISR will overestimate aerosol content over bright surfaces and in environments dominated by coarse-mode particles. The above findings not only deepen the understanding of MISR aerosols products from multiple perspectives, but also provide useful information for the product improvement.

Characterization of columnar aerosol over a background site in Central Asia

Ground-based observational characterization of atmosphere aerosols over Central Asia is very limited. This study investigated the columnar aerosol characteristics over Issyk-Kul, Kyrgyzstan, a background site in Central Asia using the long-term (∼14 years: August 2007-November 2021) data acquired with the Cimel sunphotometer. The mean aerosol optical depth (AOD) and Ångström exponent (AE) during the observation period were 0.14 ± 0.10 and 1.19 ± 0.41, respectively. Both AOD and AE varied across seasons, with highest AOD in spring (0.17 ± 0.17). Regarding the aerosol types, clean continental aerosols were dominant type (65%), followed by mixed aerosols (∼19%), clean marine aerosols (∼14%), dust (0.8%), and urban/industrial and biomass burning aerosol (0.7%). The aerosol volume size distribution was bimodal indicating the influence of both anthropogenic and natural aerosols with clear dominance of coarse mode during the spring season. Mainly dust and mixed aerosols were present during high aerosol episodes while the coarse mode aerosol volume concentration was 7.5 (strong episodes) and ∼19 (extreme episodes) times higher than the whole period average. Aerosol over this background sites were from local and regional sources with some contribution of long-range transport.

Quaternary Ammonium Groups Modified Magnetic Cyclodextrin Polymers for Highly Efficient Dye Removal and Sterilization in Water Purification

Water recovery is a significant proposition for human survival and sustainable development, and we never stop searching for more efficient, easy-operating, low-cost and environmentally friendly methods to decontaminate water bodies. Herein, we combined the advantages of β-cyclodextrin (β-CD), magnetite nanoparticles (MNs), and two kinds of quaternary ammonium salts to synthesize two porous quaternary ammonium groups capped magnetic β-CD polymers (QMCDP1 and QMCDP2) to remove organic pollutants and eradicate pathogenic microorganisms effectively through a single implementation. In this setting, β-CD polymer (CDP) was utilized as the porous substrate material, while MNs endowed the materials with excellent magnetism enhancing recyclability in practical application scenarios, and the grafting of quaternary ammonium groups was beneficial for the adsorption of anionic dyes and sterilization. Both QMCDPs outperformed uncapped MCDPs in their adsorption ability of anionic pollutants, using methyl blue (MB) and orange G (OG) as model dyes. Additionally, QMCDP2, which was modified with longer alkyl chains than QMCDP1, exhibits superior bactericidal efficacy with a 99.47% removal rate for Staphylococcus aureus. Accordingly, this study provides some insights into designing a well-performed and easily recyclable adsorbent for simultaneous sterilization and adsorption of organic contaminants in wastewater.

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.

Analysis and Variation of the Maiac Aerosol Optical Depth in Underexplored Urbanized Area of National Capital Region, India

Aerosol monitoring is the emerging application field of satellite remote sensing. As a satellite-based indicator of aerosol concentration, aerosol optical depth (AOD) can aid in assessing the crucial effects of aerosols on the global environment. Among various satellite-based aerosol product, Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6), Multiangle Implementation of Atmospheric Correction (MAIAC) aerosol product (1 km resolution) has still untapped potential in Indian regions. Considering the importance of regional validation of such high-resolution aerosol product, the present study attempts to fill this gap by validating MAIAC aerosol estimates (AODMAIAC) in highly polluted districts (Faridabad, Ghaziabad, Gautam Budh Nagar, Gurugram) of National Capital Region (NCR) with heavy aerosol loading using limited AErosol RObotic NETwork (AERONET) observations obtained from AERONET sites at Amity University (AU) and Gual Pahari (GP). Such evaluation of satellite-retrieved aerosol product with ground data confirms its practicality based on retrieval errors (Expected Error (EE) values (EE = 0.05 + 15 %*AOD) (EE: 78.85 % at AU, 73.58 % at GP), root mean square error (RMSE) values (RMSE: 0.15 at AU, 0.24 at GP), and correlation coefficient (R) values (R: 0.86 at AU, 0.73 at GP). The seasonal variation in AOD over the study area from 2010-2019 reveals increasing trend of AOD in the monsoon and post-monsoon season due to natural and anthropogenic factors. In addition to contributing to a holistic assessment of MAIAC aerosol estimates as a recent, high-resolution aerosol product, present results provide a basis for further research into NCR aerosols.

Year-round observations of stable carbon isotopic composition of carboxylic acids, oxoacids and α-Dicarbonyls in fine aerosols at Tianjin, North China: Implications for origins and aging

To better understand the origins and photochemical processing (aging) of organic aerosols (OA), we studied fine aerosols (PM_2.5) collected at urban (Nankai District (ND)) and suburban (Haihe Education Park (HEP)) Tianjin, North China over a one-year period (2018-2019) for stable carbon isotopic composition (δ¹³C) of water-soluble diacids, oxoacids, α-dicarbonyls and fatty acids. Maleic (M, -18.3 ± 10.9‰ at ND and -23.5 ± 10.2‰ at HEP) and fumaric (F, -22.0 ± 12.1‰ at ND and -22.5 ± 10.5‰ at HEP) acids were found to be most enriched with ¹³C followed by oxalic acid (C₂, -24.7 ± 3.9‰ at ND and -25.9 ± 4.7‰ at HEP) during the campaign. Based on seasonal changes in δ¹³C of selected marker species: C₆ and C₉ diacids, phthalic, glyoxylic and pyruvic acids and glyoxal, and their comparison with the source signatures, we found that water-soluble OA in Tianjin were mainly originated from fossil fuel combustion and biomass burning emissions and were subjected for significant aging. The contribution from fossil fuel combustion including coal combustion was high in autumn and winter, especially at ND. Considering the enrichment of ¹³C in specific species together with linear relations of δ¹³C of selected species with their concentrations, with mass ratios and with the relative abundance of C₂ diacid, we inferred that the photochemical transformations of longer-chain diacids, oxidation of α-dicarbonyls (Gly and mGly), preferably in gas phase, were important in warm period (March-September), whereas the oxidation of Gly, mGly and other precursors in aqueous phase were major in cold period (October-February).

Accuracy, stability, and continuity of AVHRR, SeaWiFS, MODIS, and VIIRS deep blue long-term land aerosol retrieval in Asia

The deep blue (DB) aerosol algorithm applied to four satellite instruments, AVHRR, SeaWiFS, MODIS, and VIIRS, produced a long-term aerosol data set since 1989. This study first evaluated and compared the accuracy, stability, and continuity of four DB aerosol optical depth (AOD) products in Asia using AErosol RObotic NETwork measurements. Then, the regional AOD spatial distributions, coverages, and series trends are analyzed. The results show that VIIRS DB has the highest accuracy and stability, with an expected error (EE, ±(0.05 + 20%)) of 76.59% and stability of approximately 0.027 per decade. The performance of MODIS DB is slightly worse than that of VIIRS. However, their AOD pattern, coverage, and trend are comparable. The performance of AVHRR (EE = 58.10%) and the stability of SeaWiFS (0.093 per decade) are less good. Therefore, SeaWiFS DB data should be used with caution for trend analysis. The AOD accuracy and coverage together determine the AOD pattern and the continuity of multi-sensor data. In addition to consistent algorithm accuracy, it is necessary to consider the influences in sensor sampling and inappropriate-pixel screening schemes in the joint multi-sensor analysis. Encouragingly, although multiple DB products have different AOD averages of regional series, their changing trends are consistent. Error analysis shows that the AOD bias characteristic is different in different surface conditions. This indicates that the surface reflectance estimated by the DB algorithm using different techniques is divergent, which may be the direction for the improvement of the algorithm.

The synergistic effect of rising temperature and declining light boosts the dominance of bloom-forming cyanobacteria in spring

Global warming and eutrophication result in rising temperature and declining underwater light, respectively, which affect the shift of the phytoplankton community in spring. However, knowledge of how temperature and light synergistically impact phytoplankton community shifts and cyanobacterial dominance is limited. In this study, we performed a long-term data analysis and an outdoor mesocosm experiment to detect the synergistic effect of temperature and light on shift of phytoplankton community and dominance of bloom-forming cyanobacteria in Lake Taihu, China. The results showed that cyanobacterial biomass was boosted alone and jointly by increased temperature and decreased light levels (sunshine hours and light intensity), and the interaction might be more important than temperature or light levels independently. Chlorophyta biomass was driven by the joint effect of temperature and light levels. Bacillariophyta biomass was mainly affected by light levels, and decreased with declining light levels. Our results emphasize that the interactions of temperature and light have an important impact on the shift of the phytoplankton community in spring. Increasing temperature and declining underwater light boosted the flourishing of cyanobacteria, especially Microcystis, and were adverse to the development of diatoms in spring. Our findings contribute to an increased understanding of the effects of temperature and light on phytoplankton composition shifts and the development of cyanobacterial dominance in spring.

A Chemical Nanoreactor Based on a Levitated Nanoparticle in Vacuum

A single levitated nanoparticle is used as a nanoreactor for studying surface chemistry at the nanoscale. Optical levitation under controlled pressure, surrounding gas composition, and humidity provides extreme control over the nanoparticle, including dynamics, charge, and surface chemistry. Using a single nanoparticle avoids ensemble averages and allows studying how the presence of silanol groups at its surface affects the adsorption and desorption of water from the background gas with excellent spatial and temporal resolution. Herein, we demonstrate the potential of this versatile platform by studying the Zhuravlev model in silica particles. In contrast to standard methods, our system allowed the observation of an abrupt and irreversible change in scattering cross section, mass, and mechanical eigenfrequency during the dehydroxylation process, indicating changes in density, refractive index, and volume.

Anthropogenic Aerosols Effects on Ice Clouds: A Review

Since the ability of anthropogenic aerosols to act as ice nucleation particles has been recognized, the effect of anthropogenic aerosols on ice clouds has attracted increasing attentions. In recent years, some progress has been made in investigating the effects of anthropogenic aerosols on ice clouds. In this paper, we briefly review the study on the impact of anthropogenic aerosols on ice nuclei, properties and radiative forcing of ice clouds. Anthropogenic aerosols can form ice nuclei through homogeneous nucleation and heterogeneous nucleation. Convective strength can modulate the response of ice clouds to anthropogenic aerosols by affecting the nucleation activities. There have been large uncertainties in calculating the radiative forcing of anthropogenic aerosols on ice clouds in climate models. Further studies on the impact of anthropogenic aerosols on ice clouds are imperative to provide better parameterization schemes and reduce the uncertainties of aerosol indirect effects.

Comprehensive Validation and Comparison of Three VIIRS Aerosol Products over the Ocean on a Global Scale

Three parallel Visible/Infrared Imager Radiometer Suite (VIIRS) aerosol products (SOAR, NOAA, and AERDT) provided data since 2012. It is necessary to study the performances and advantages of different products. This study aims to analyze the accuracy and error of these products over the ocean and compare them with each other. The results show that the three VIIRS ocean aerosol retrievals (including total aerosol optical depth (AOD), fine mode fraction, Ångström exponent (AE), and fine AOD (AODF)) correlate well with AErosol RObotic NETwork (AERONET) retrievals (e.g., correlation >0.895 for AOD and >0.825 for AE), which are comparable to the newest moderate-resolution imaging spectro-radiometer (MODIS) retrievals. Overall, the SOAR retrievals with quality filtering have the best validation accuracy of all parameters. Therefore, it is more recommended to use. The differences in the annual AOD spatial patterns of different products are small (bias < 0.016), but their AE spatial patterns are evidently different (bias > 0.315), indicating the large uncertainty of VIIRS AE. Error analysis shows that the scattering angle and wind speed affect aerosol retrieval. Application of the non-spherical dust model may reduce the dependence of retrieval bias on the scattering angle. Overall, this study provides validation support for VIIRS products usage and possible algorithm improvements.

A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model

Aerosol optical and chemical properties play a major role in the retrieval of PM2.5 concentrations based on aerosol optical depth (AOD) data from satellites in the conventional semiempirical model (SEM). However, limited observation information hinders the high-resolution estimation of PM2.5. Therefore, a new method for evaluating near-surface PM2.5 at high spatial resolution is developed by coupling the SEM and the chemical transport model (CTM)-based numerical (CSEN) model. The numerical model can provide large-scale information for aerosol properties with high spatial resolution at a large scale based on emissions and meteorology, though it can still be biased in simulating absolute PM2.5 concentrations. Therefore, the two crucial aerosol characteristic parameters, including the coefficient integrated humidity effect (γ′) and the comprehensive reference value of aerosol properties (K) in SEM, have been redefined using the WRF-Chem numerical model. Improved model performance was observed for these results compared with the original SEM results. The monthly averaged correlation coefficients (R) by CSEN were 0.92, 0.82, 0.84, and 0.83 in January, April, July, and October, respectively, whereas those of the SEM were 0.80, 0.77, 0.72, and 0.72, respectively. All the statistical metrics of the model validation showed significant improvements in all seasons. The reduced biases of estimated PM2.5 by CSEN indicated the effect of hygroscopic growth and aerosol properties affected by the meteorology on the relationship between AOD and estimated PM2.5 concentrations, especially in winter and summer. The better performance of the CSEN model provides insight for air quality monitoring at different scales, which supplies important information for air pollution control policies and health impact analysis.

Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China

The Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue (DB) algorithm was developed for aerosol retrieval on bright surfaces. Although the global validation accuracy of the DB product is satisfactory, there are still some regions found to have very low accuracy. To this end, DB has updated the surface database in the latest version of the Collection 6.1 (C6.1) algorithm. Some studies have shown that DB aerosol optical depth (AOD) of the old version Collection 6 (C6) has been seriously underestimated in Northwestern China. However, the status of the new version of the C6.1 product in this region is still unknown. This study aims to comprehensively evaluate the performance of the MODIS DB product in Northwestern China. The DB AOD with high quality (Quality Flag = 2 or 3) was selected to validate against the 23 sites from the China Aerosol Remote Sensing Network (CARSNET) and Aerosol Robotic Network (AERONET) during the period 2002–2014. By the overall analysis, the results indicate that both C6 and C6.1 show significant underestimation with a large fraction of more than 54% of collocations falling below the Expected Error (EE = ±(0.05 + 20% AODground)) envelope and with a large negative Mean Bias (MB) of less than −0.14. Furthermore, the new C6.1 products failed to achieve reasonable improvements in the region of Northwestern China. Besides, C6.1 has slightly fewer collocations than C6 due that some pixels with systematic biases have been removed from the new surface reflectance database. From the analysis of the site scale, the scatter plot of C6.1 is similar to that of C6 in most sites. Furthermore, a significant underestimation of DB AOD was observed at most sites, with the most severe underestimation at two sites located in the Taklimakan Desert region. Among 23 sites in Northwestern China, there are only two sites where C6.1 has largely improved the underestimation of C6. Furthermore, it is interesting to note that there are also two sites where the accuracy of the new C6.1 has declined. Moreover, it is surprising that there is one site where a large overestimation was observed in C6 and improved in C6.1. Additionally, we found a constant value of about 0.05 for both C6 and C6.1 at several sites with low aerosol loading, which is an obvious artifact. The significant improvements of C6.1 were observed in the Middle East and Central Asia but not in most sites of Northwestern China. The results of this study will be beneficial to further improvements in the MODIS DB algorithm.

Prediction of Aerosol Extinction Coefficient in Coastal Areas of South China Based on Attention-BiLSTM

The aerosol extinction coefficient (AEC) characterises the attenuation of the light propagating in a turbid medium with suspended particles. Therefore, it is of great significance to carry out AEC prediction research using state-of-art neural network (NN) methods. The attention mechanism (AM) has become an indispensable part of NNs that focuses on input weight assignment. Traditional AM is used in time steps to help generate the outputs. To select important features of meteorological parameters (MP) that are helpful for forecasting, in this study, we apply AM to features instead of time steps. Then we propose a bidirectional long short-term memory (BiLSTM) NN based on AM to predict the AEC. The proposed method can remember information twice (i.e., forward and backward), which can provide more context for AEC forecasting. Finally, an in situ measured MP dataset is applied in the proposed model, which presents Maoming coastal area’s atmospheric conditions in November 2020. The experimental results show that the model proposed in this paper has higher accuracy compared with traditional NN, providing a novel solution to the AEC prediction problem for the current studies of marine aerosol.

An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends

As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.

Two-year systematic investigation reveals alterations induced on chemical and bacteriome profile of PM2.5 by African dust incursions to the Mediterranean atmosphere

PM_2.5 atmospheric samples were regularly collected between January 2013 and March 2015 at a central location of Eastern Mediterranean (Island of Crete) during African dust events (DES) and periods of absence of such episodes as controls (CS). The elemental composition and microbiome DES and CS were thoroughly investigated. Fifty-six major and trace elements were determined by inductively coupled plasma-mass spectrometry. Relative mass abundances (RMA) of major crustal elements and lanthanoids were higher in DES than in CS. Conversely in CS, RMAs were higher for most anthropogenic transition metals. Lanthanum-to-other lanthanoids concentration ratios for DES approached the corresponding reference values for continental crust and several African dust source regions, while in CS they exceeded these values. USEPA's UNMIX receptor model, applied in all PM_2.5 samples, established that African dust is the dominant contributing source (by 80%) followed by road dust/fuel oil emissions (17%) in the receptor area. Potential source contribution function (PSCF) identified dust hotspots in Tunisia, Libya and Egypt. The application of 16S rRNA gene amplicon sequencing revealed high variation of bacterial composition and diversity between DES and CS samples. Proteobacteria, Actinobacteria and Bacteroides were the most dominant in both DES and CS samples, representing ~88% of the total bacterial diversity. Cutibacterium, Tumebacillus and Sphingomonas dominated the CS samples, while Rhizobium and Brevundimonas were the most prevalent genera in DES. Mutual exclusion/co-occurrence network analysis indicated that Sphingomonas and Chryseobacterium exhibited the highest degrees of mutual exclusion in CS, while in DES the corresponding species were Brevundimonas, Delftia, Rubellimicrobium, Flavobacterium, Blastococcus, and Pseudarthrobacter. Some of these microorganisms are emerging global opportunistic pathogens and an increase in human exposure to them as a result of environmental changes, is inevitable.

The environmental impact of industrialization and foreign direct investment: empirical evidence from Asia-Pacific region

Environmental degradation has been the main distress in recent years due to the drastic effect of climate change. To determine the gone thorough impact of industrialization and foreign direct investment on environmental degradation, this study utilized panel data of 55 countries of the Asia-Pacific region from 1995 to 2020 and it applies an autoregressive distributed lag (ARDL) model. The results showed that FDI, in general, has a significant negative impact on the environment and causes to increase in methane and CO2 emissions. Moreover, industrialization has a positive and significant impact on the environment. However, the size of the impact is moderate. This study also concludes that in the Asia-Pacific region, the environment Kuznets curve (EKC) and pollution heaven (PH) hypothesis are accepted. Finally, this study suggests the strict implication of environmental guidelines or the adoption of a new policy would be the key to ensuring the quality of the environment. Furthermore, the results confirmed that most of the panel countries are developing countries and do not have strict environmental management guidelines.

Aerosol emissions and gravity waves of Taal volcano

The Taal volcano (14.0 N, 121.0 E) in Philippines erupted in January–February 2020, with a part of aerosols drifted northward and detected by a lidar system at Kaohsiung city (22.37 N, 120.15 E), Taiwan. The aerosol observed on Feb 11 is special for its high-altitude distributions at 4–7 km with discrete structures which can be resolved into a sinusoidal oscillation of ~ 30 min period, suggesting a case of wave event caused by the eruptions. We report in this paper the gravity wave generated by the volcanic eruptions and its effects on aerosol emissions. By studying the temperature and pressure data in the Taal region using radiosonde data, we found atmospheric gravity waves with powers correlated with the optical thickness (AOD) at 550 nm measured by the Moderate Resolution Imaging Spectrometer (MODIS) satellite. This study presents the first observation of modulation of the aerosol emissions by the volcanic gravity waves and a case of coupling of dynamics and chemistry.

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.

CALIOP-Based Quantification of Central Asian Dust Transport

Central Asia is one of the most important sources of mineral saline dust worldwide. A comprehensive understanding of Central Asian dust transport is essential for evaluating its impacts on human health, ecological safety, weather and climate. This study first puts forward an observation-based climatology of Central Asian dust transport flux by using the 3-D dust detection of Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP). The seasonal difference of transport flux and downstream contribution are evaluated and compared with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Central Asian dust can be transported not only southward in summer under the effect of the South Asian summer monsoon, but also eastward in other seasons under the control of the westerly jet. Additionally, the transport of Central Asian dust across the Pamir Plateau to the Tibetan Plateau is also non-negligible, especially during spring (with a transport flux rate of 150 kg m−1 day−1). The annual CALIOP-based downstream contribution of Central Asian dust to South Asian (164.01 Tg) is 2.1 times that to East Asia (78.36 Tg). This can be attributed to the blocking effect of the higher terrain between Central and East Asia. Additionally, the downstream contributions to South and East Asia from MERRA-2 are only 0.36 and 0.84 times that of CALIOP, respectively. This difference implies the overestimation of the wet and dry depositions of the model, especially in the low latitude zone. The quantification of the Central Asian dust transport allows a better understanding of the Central Asian dust cycle, and supports the calibration/validation of aerosol-related modules of regional and global climate models.

Monsoon-seasonal validation of MODIS aerosol optical depth and characterization using AERONET observation retrieve over Italy

This study used Angstrom Exponent (AE) relationship with Aerosol Optical Depth (AOD) obtained from space-based direct sky-radiometer of Moderate Resolution Imaging Spectroradiometer (MODIS) and direct Sun algorithm surface-based AERONET network (level 2.0 version 3) to evaluate monsoon season (June-September) aerosol optical depth and characterization at 7 Italy sites: IMAA_POTENZA (40.60N, 15.72E), ISPRA (45.80N, 8.62E), LAMPEDUSA (35.51N, 12.63E), MESSINA (38.19N, 15.56E), MODENA (44.63N, 10.94E), ROME_TOR_VERGATA (41.83N, 12.64E) and VENISE (45.31N, 12.50E) from 2010 to 2019. Standardized anomaly and the standard deviation ratio method of analysis to address the robustness of AE were identified to classify aerosols typing. The extracted monsoon AOD correlation between MODIS and AERONET is (r = 0.95) which is plausible to determine discrepancy in data handling. In order to remove large influence of annual cycle, the data were first detrend. The results show that standard deviation value > 1 indicates monthly dominance than climatology. The standardized anomaly records (-0.22 ± 0.13) for MODIS and AERONET AODs with corresponding correlation of (r = 0.96) in June. There is disparity in AOD data handling from MODIS in some periods, which could attribute that space-based interpretation, should be validated with ground-base observation over Italy. The fine mode aerosols due to high AE values interestingly present the characteristic of AOD dominance, but experience trans-seasonal change, where MODIS has weak correlation.

Assessment of Aerosol Optical Depth over Indian Subcontinent during COVID-19 lockdown (March-May 2020)

The COVID-19 pandemic has created a major threat to human beings and huge losses over the globe. In order to control the pandemic spread, almost all parts of the world imposed lockdown. The imposed lockdown drastically impacted on reduction in the atmospheric pollutions and also resulted in net decrease in aerosol optical depth (AOD) in the atmosphere. In this study, the reduction in the AOD during the COVID-19 lockdown over the Indian subcontinent is being assessed using the moderate resolution imaging spectroradiometer (MODIS) satellite data available in Giovanni version 4.34 developed by NASA. The long-term mean analysis is computed considering 20 years (i.e., 2000-2019) data on Terra platform with a temporal resolution of daily and monthly and spatial resolution of 1 degree. The dataset of AOD with a temporal resolution of monthly was used for investigation of AOD anomaly for March, April and May 2020, and the seasonal variation (March to May 2020) is also assessed. Similarly, the daily scale dataset was used to investigate the percentage change in AOD during pre-lockdown and lockdown period with respect to long-term mean. The key findings in the present study show that reduction in AOD level over Indian subcontinent is approximately 14.75% during the lockdown period with spatial variation in the magnitude from region to region. The level of AOD is greatly reduced in the northern part of India (~ 22.53%), whereas changes in the southern part of India are much less (~ -0.31%); this may be due to ongoing anthropogenic activities during the lockdown period in this region. Furthermore, a positive AOD anomaly was observed in the eastern and central regions of India (i.e., over the states of Odisha, Chhattisgarh, Telangana, Jharkhand, West Bengal, Part of Maharashtra and Karnataka). However, negative AOD anomaly was observed in the north and northwest regions of India, whereas not much change in the AOD anomaly in other parts of the country. The overall assessment of the AOD level shows a net decrease over the Indian subcontinent during the lockdown period, i.e., March to May 2020. This kind of assessment study will surely help the government for the sustainable policy decisions for atmospheric pollution control by implementing proper lockdown procedures over various parts of the country.

Neural Network AEROsol Retrieval for Geostationary Satellite (NNAeroG) Based on Temporal, Spatial and Spectral Measurements

Geostationary satellites observe the earth surface and atmosphere with a short repeat time, thus, providing aerosol parameters with high temporal resolution, which contributes to the air quality monitoring. Due to the limited information content in satellite data, and the coupling between the signals received from the surface and the atmosphere, the accurate retrieval of multiple aerosol parameters over land is difficult. With the strategy of taking full advantage of satellite measurement information, here we propose a neural network AEROsol retrieval framework for geostationary satellite (NNAeroG), which can potentially be applied to different instruments to obtain various aerosol parameters. NNAeroG was applied to the Advanced Himawari Imager on Himawari-8 and the results were evaluated versus independent ground-based sun photometer reference data. The aerosol optical depth, Ångström exponent and fine mode fraction produced by the NNAeroG method are significantly better than the official JAXA aerosol products. With spectral bands selection, the use of thermal infrared bands is meaningful for aerosol retrieval.

The Influence of Underlying Land Cover on the Accuracy of MODIS C6.1 Aerosol Products—A Case Study over the Yangtze River Delta Region of China

Due to the significant spatial variation of the performance of Moderate Resolution Imaging Spectrometer (MODIS) aerosol optical depth (AOD) retrievals, validation is very important for applications of MODIS AOD products at regional scales. This study presents a comparative analysis of Collection 6.1 MODIS AOD retrievals and ground measurements from five local sites and one Aerosol Robotic Network (AERONET) site in the Yangtze River Delta (YRD) region, which significantly complements the previous validation that utilized limited AERONET measurements. Generally, MODIS AOD retrievals showed a reasonable agreement with collocated ground measurements (R2 > 0.7), with 66% of Dark Target (DT) 10 km retrievals, 56% of Deep Blue (DB) 10 km retrievals, and 69% of DT 3 km retrievals falling within the expected error (EE = ±(0.05 + 0.2 × AOD)). Nevertheless, it was found that the DT AOD retrievals tended to be overestimated over urbanized and lakeside sites, while the DB AOD retrievals tended to be underestimated over all ground sites except for lakeside sites. Such patterns appeared to be linked with the systematic biases of the single-scattering albedo estimation in the AOD retrieval algorithms. Another significant finding of this study is that the uncertainties of the MODIS AOD retrievals were highly correlated with the land cover proportions of urbanized features and water (LCP_UW) in the surrounding region, especially for the DT products. An empirical correction method based on these correlations could substantially reduce the uncertainties of DT AOD products over high LCP_UW areas. The results not only highlight the significant impacts of both urban and water areas on the MODIS AOD retrieval algorithms but also create new possibilities to correct such impacts once the universal correlations between LCP_UW and the uncertainty measures are established.

Quantitatively Assessing the Contributions of Dust Aerosols to Direct Radiative Forcing Based on Remote Sensing and Numerical Simulation

Dust aerosols substantially impinge on the Earth’s climate by altering its energy balance, particularly over Northwest China, where dust storms occur frequently. However, the quantitative contributions of dust aerosols to direct radiative forcing (DRF) are not fully understood and warrant in-depth investigations. Taking a typical dust storm that happened during 9–12 April 2020 over Northwest China as an example, four simulation experiments based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) were designed, including a real scenario with dust emissions and three hypothetical scenarios without dust emissions, with dust emissions doubled, and with dust emissions reduced by half, to quantitatively evaluate the contributions of dust aerosols to DRF and then to surface temperature, with particular attention to the differences between daytime and nighttime. Moreover, multi-satellite observations were used to reveal the behavior of dust events and to evaluate the model performance. During the daytime, the net dust radiative forcing induced by dust aerosols was –3.76 W/m2 at the surface (SFC), 3.00 W/m2 in the atmosphere (ATM), and –0.76 W/m2 at the top of the atmosphere (TOA), and thus led to surface air temperature cooling by an average of –0.023 ℃ over Northwest China. During the nighttime, the net dust radiative forcing was 2.20 W/m2 at the SFC, –2.65 W/m2 in the ATM, and –0.45 W/m2 at the TOA, which then resulted in surface temperature warming by an average of 0.093 ℃ over Northwest China. These results highlight that the contribution of dust aerosols to DRF is greater during the daytime than that during the nighttime, while exhibiting the opposite impact on surface temperature, as dust can slow down the rate of surface temperature increases (decreases) by reducing (increasing) the surface energy during the daytime (nighttime). Our findings are critical to improving the understanding of the climate effects related to dust aerosols and provide scientific insights for coping with the corresponding disasters induced by dust storms in Northwest China.