Search Results (345)

Roadside green spaces function as critical ecological barriers in urban environments, and their plant communities play a key role in improving regional air quality. This study investigates typical roadside plant communities in southern Xinjiang, a region characterized by extreme aridity and frequent dust storms. By quantifying indicators such as dust retention capacity at both individual and community levels, together with leaf surface microstructural characteristics, we evaluate the comprehensive dust retention performance of different community configuration patterns. The results show that: (1) Among the studied species, Juniperus chinensis ‘Kaizuca’ exhibited the highest dust retention capacity per unit leaf area, followed by Juniperus chinensis L. and Rosa rugosa Thunb. Among trees, Platanus acerifolia (Aiton) Willd showed the greatest dust retention capacity per individual plant; among shrubs, Rosa rugosa Thunb. performed strongly, and among herbaceous species, Lolium perenne L. exhibited relatively high dust retention capacity. (2) Leaf dust retention is governed by the synergistic effects of multiple traits, including leaf aspect ratio, stomatal aspect ratio, stomatal protrusion, stomatal density, wax layer characteristics, and surface roughness. Leaf aspect ratio exerts a significant positive direct effect on dust retention, whereas stomatal aspect ratio shows a significant negative direct effect. (3) At the community level, the multi-layered tree–shrub–herbaceous configuration dominated by Platanus acerifolia (Aiton) Willd exhibited the strongest dust retention capacity, making it the most effective configuration for roadside green spaces. Overall, this study provides a robust theoretical framework and empirical evidence for the scientific selection and optimized configuration of roadside vegetation in arid regions, thereby supporting the sustainable improvement of urban roadside air quality in southern Xinjiang. Full article

Dust and sand storms occurring in northern China are strongly controlled by near-surface aerodynamics, yet the spatial heterogeneity of these processes remains poorly understood. We obtained field measurements of the wind above gobis, sandy surfaces, and dry lakebeds in the Hexi Corridor Desert and Heihe River Basin, and sandy surfaces in northern China. First, the slope of wind profile (a₁) reveals distinct drag reversal with increasing wind speed: under low winds, a₁ increases from sandy to dry lakebed to gobi surfaces, whereas under high winds, actively saltating sandy surfaces exhibit the highest a₁, surpassing gobi and dry lakebed. Second, the dynamic feedback between sediment transport and aerodynamics is clear: at below-threshold winds, friction velocity ($u_{*}$) and aerodynamic roughness length (z₀) are lowest for sand; however, as wind speed increases to initiate significant saltation, the sandy surface develops the highest $u_{*}$ and z₀, highlighting the dominant role of grain-borne roughness. Third, the focal height (z_f) shows regional disparity, varying by up to two orders of magnitude for both sandy and gobi surfaces, with a strong correlation to local gravel coverage. This work provides spatially explicit parameterizations of surface type, offering a physical basis for modeling dust emission and transport in northern China and similar arid regions globally. Such parameterizations are essential for developing reliable early warning systems and evidence-based land management strategies. These advances contribute directly to ecosystem sustainability and community resilience in vulnerable arid and semi-arid regions under climate change. Full article

Urban storm drain sediments (SDSs) accumulate heavy metals from building façades and road surfaces, yet the biogeochemical controls governing metal mobility remain poorly understood. This study investigated biotic and abiotic controls on metal mobility along the urban dust transport chain (Xiamen-Quanzhou-Zhangzhou, China), using four sample types—façade dust (FD), road-deposited sediment (RDS), SDS, and runoff suspended solids (RSS)—from nine sites across three functional zones. Metal concentrations (Pb, Cu, Zn, Cr, Cd), phosphorus fractions, and microbial functional genes were quantified to test the hypothesis that viral abundance indicators, rather than pH, are more strongly associated with metal mobility in near-neutral urban sediments. Results showed that SDS served as metal accumulation hotspots with enrichment factors of 2.0–2.3× relative to FD, while total phosphorus declined by 34% along the transport chain. Contrary to conventional expectations, pH exhibited weak correlation with Pb mobility (r = −0.21; 95% CI: −0.62 to 0.27), whereas the T4-type bacteriophage gene g23 showed strong positive correlation (r = 0.85, p < 0.01; 95% CI: 0.52–0.96). Partial least squares path modeling revealed that viral abundance (g23 gene copies) showed the strongest statistical association with metal mobility among biotic variables (β = +0.48, p < 0.001), mediated through phosphorus-supported microbial activity. The model explained 76% of variance in metal mobility, with phosphorus cycling positively influencing viral abundance (β = +0.28). These findings challenge the pH-centric paradigm of metal geochemistry and reveal a novel phosphorus-virus-metal coupling mechanism in urban environments. The textile industrial site QZ-2 exceeded chromium screening values by 45%, demonstrating the framework’s utility for pollution hotspot identification. Full article

This study investigated an intense and unusual summer transboundary dust storm event that occurred between 21 and 23 June 2024. By integrating remote sensing observations, reanalysis data, WRF-Chem simulations, and LAGRANTO trajectory tracking, we systematically revealed the dust emission, transport, deposition, and formation mechanisms of this event. The dust primarily originated from the Gobi region of southern Mongolia, where concentrations exceeded 10,000 µg m⁻³, and decayed exponentially as the Mongolian cyclone moved southeastward. Post border-crossing into China, the event transitioned to blowing and floating dust, with concentrations decreasing significantly. During transport, dry deposition dominated the source area and the frontal part of the transport path in the early stages, while wet deposition was associated with the precipitation system of the Mongolian cyclone and concentrated north and east of the cyclone’s track. On 21 June 2024, the average wind speed in the source region reached 11.35 ms⁻¹, the highest recorded in the past 45 years. This was attributed to surface anomalies, including reduced soil moisture, poor vegetation cover, higher temperatures, and decreased precipitation relative to the multi-year average. The comprehensive application of multi-source data and models in this work elucidates the full lifecycle of this rare summer dust event, providing scientific insights into the atmospheric processes governing extreme dust events and their transboundary impacts. Full article

Dust activity is controlled by multiple environmental factors and exhibits substantial spatiotemporal and interannual variability. In spring 2025, China experienced unusually frequent dust storms. Surface meteorological observations and PM₁₀ levels show that dust events in 2025 were the most frequent and intense of the last decade. The dust event analysis indicates a pronounced change in transport pathways, with affected regions extending to Central, Southwest, and South China. This differs markedly from the 2021 and 2023 events, which impacted northern China more broadly. Source attribution indicates that the Gobi Desert was the dominant contributor to downstream dust, accounting for 80.0%, 83.1%, and 78.6% of dust concentrations in North, Southwest, and South China, respectively. In addition, enhanced surface winds over the Gobi Desert were identified as the primary drivers of intensified dust emissions, while concurrent changes in precipitation, soil moisture, and vegetation cover played secondary roles. An anomalous low-pressure system over the Bohai–Yellow Sea facilitated northerly wind anomalies, enabling long-range southward dust transport from the Gobi Desert all the way to southern China. These findings improve our understanding of extreme dust events and emphasize the need to consider both emission strength and transport efficiency in regional air quality assessments. Full article

The Beijing–Tianjin–Hebei (BTH) region is a critical political and economic hub in China, which has long faced challenges related to atmospheric conditions. Traditional aerosol optical depth (AOD) monitoring methods suffer from issues of data discontinuity and gaps, limiting the ability for continuous long-term observation of aerosols. Aerosols have significant impacts on climate change and air quality, with AOD serving as a key indicator for characterizing atmospheric particulate concentration. Therefore, this study applied a machine learning model to improve all-day AOD estimation based on ground-level air quality and meteorological data, generating a long-term dataset spanning from 2018 to 2023. The results of the all-day AOD estimation method were evaluated through comparisons with Himawari-8, the Aerosol Robotic Network (AERONET), and the Copernicus Atmosphere Monitoring Service (CAMS). The estimated AOD demonstrated good agreement with AHI data, achieving an annual R² greater than 0.96 and RMSE less than 0.1. Spatially, the estimated AOD also showed strong consistency with AHI, AERONET, and CAMS. Additionally, the annual, seasonal, and hourly distribution characteristics of AOD from 2018 to 2023 were analyzed. Two typical cases of aerosol variation in the BTH region were selected and examined: a dust storm event in 2023 and changes during the Spring Festival in 2021. This method provides continuous data support for air pollution monitoring and control in the BTH region and offers valuable references for pollution prevention efforts. Full article

To address the challenge of forecasting power output from large-scale photovoltaic (PV) bases in desert regions during sand and dust storms, this paper proposes a hybrid data-physics driven prediction method. This approach utilizes satellite remote sensing to obtain regional irradiance data, transforming the traditional one-dimensional time-series forecasting into a two-dimensional spatiotemporal sequence prediction, thereby tracking the dynamic evolution of irradiance intensity under the influence of sand and dust. Firstly, a forecasting model based on a conditional variational autoencoder (CVAE) optimized with a recurrent state-space model (RSSM) is constructed to effectively capture both the deterministic trends and stochastic fluctuations in irradiance variation, providing a reliable input basis for power calculation. Secondly, at the physical modeling level, the model comprehensively considers the isotropic scattering characteristics and changes in sky clarity induced by sand and dust weather, establishing a physical mapping relationship from irradiance to PV output. This mitigates the constraint of scarce historical operational data in desert and sandy regions. This research provides a novel solution for regional-level PV power forecasting under extreme sand and dust weather, contributing to enhanced dispatchability and transmission stability of renewable energy bases during abrupt meteorological changes. Full article

To investigate the health risks of particulate matter during spring dust storms in Beijing, this study selected atmospheric particulate samples collected during a typical dust storm event in March 2021. The DNA damage rates induced by PM_2.5 and PM₁₀ were measured using the Plasmid Scission Assay (PSA) and were used as an indicator of their oxidative potential. Water-soluble heavy metal elements (WSHM) in the samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results indicate that due to the influence of the dust storm, the monthly average PM_2.5 mass concentration in March 2021 reached as high as 83 μg/m³, which could potentially raise the difficulty of air pollution control. It was found that during the dust storm event, PM_2.5 induced a higher DNA damage rate (mean 42.35% at an experimental dose of 200 μg/mL in the PSA) than PM₁₀ (mean 40.46% under the same experimental dosage). The DNA damage rates of dust storm particles showed a positive correlation trend (r = 0.60) with total WSHM concentrations. Exposure toxicity, calculated by multiplying the DNA damage rates under certain experimental PM doses by the PM mass concentrations, showed that the exposure risk of PM_2.5 during dust storms even exceeded that of PM_2.5 during haze events. This study reveals the potential toxicity and health risks associated with PM during dust storms, which calls for increased attention. Full article

In the spring of 2023, dust outbreaks were unusually active in East Asia, posing substantial risks to air quality. Accurately simulating dust storms is essential for improving regional dust prediction and impact assessment. In this study, we evaluated dust simulations over East Asia using different dust emission schemes in the FLEXDUST/FLEXPART model and quantified the regional dust budget. Overall, the GOCART (Goddard Chemistry Aerosol Radiation and Transport) scheme shows the highest skill among the evaluated schemes. Under mild dust conditions (300–1000 μg m⁻³), it yielded a mean PM₁₀ bias of −89.2 μg m⁻³, markedly smaller than those from other schemes/models (−450.2 to −265.6 μg m⁻³). It also better reproduced the dominant spatial patterns of dust optical depth over Xinjiang and Inner Mongolia, with lower errors and higher correlations. Budget diagnostics show that the Taklamakan and Gobi Deserts are net dust exporters (7.4 and 11.6 Tg, respectively), whereas East Asia exhibits a negative net external flux (−12.1 Tg). The comparable magnitudes of these terms underscore the role of inter-regional transport in shaping the East Asian dust budget. These results offer insights for improving dust emission schemes in the FLEXDUST/FLEXPART model, thereby enhancing dust simulations over East Asia. Full article

To date, dust storms and haze episodes have rarely been compared with pollution characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and particulate matter, as well as human health risks due to a lack of efficient data. In this study, we selected dust storms and haze episodes in East China during 2023, monitored the concentrations of PCDD/Fs in ambient air, further revealed the main characteristic variations in PCDD/Fs toxic equivalent (TEQ) concentration and congener distribution in ambient air, and assessed the human health risk posed by dust storms and haze episodes. The results show that the TEQ concentration of PCDD/Fs in ambient air was 147.6 fg-TEQ/m³ in haze episodes compared with 48.7 fg-TEQ/m³ for dust storms and 25.8 fg-TEQ/m³ for a good weather day. This indicates that the concentration for PCDD/Fs and PM_2.5 in haze episodes was 3.03 times and 0.733 times, respectively, compared with dust storms. Moreover, the variations for particulate matter of air pollution during 2022–2023, as well as the relationship between PCDD/Fs and PM_2.5 in East China was also systematically revealed. The results reveal that the concentration of PM_2.5 shows a positive correlation with PCDD/Fs. Furthermore, the human health risk of dust storms was also compared with haze episodes. Accordingly, this study could fill the knowledge gap of dust storms and haze episodes on the transmission of PCDD/Fs in the ambient air of East China and provide a scientific reference for monitoring and early warning of PCDD/Fs. Full article

Gravity waves (GWs) are an important dynamic process in the planetary atmosphere. They are typically excited by convection, topography, or other sources from the lower atmosphere and propagate upwards. The GWs have a significant effect on the global atmospheric circulation on Mars. However, the lack of high-resolution data from previous observations has resulted in an insufficient understanding of GWs in the Martian atmosphere, particularly in terms of its global distribution and long-term evolution characteristics at different altitudes. Based on multiple years of Mars Climate Sounder (MCS) limb observations on board the Mars Reconnaissance Orbiter (MRO), we conducted a detailed study of the global distribution, seasonal and interannual variations in Martian atmospheric GWs with vertical wavelengths ranging from 9 to 15 km at three different altitude ranges, i.e., the low-altitude range of 200–20 Pa (Lp, ~10–30 km), the mid-altitude range of 20–2 Pa (Mp, ~30–50 km), and the high-altitude range of 2–0.2 Pa (Hp, ~50–70 km). The results indicate complex regional and north–south differences, as well as night–day variations, in the spatial distribution of GWs. Particularly, a three-wave structure of the GW activity is observed over mountainous regions in the mid-to-low latitudes of the Northern Hemisphere. The peak longitude range of this structure closely matches the mountainous terrain. In addition, our results reveal the presence of bands of GW aggregations in the mid- to-high latitudes of the Northern Hemisphere in the Mp and Hp layers, which may be caused by the instability of the polar jet. There are also obvious seasonal and interannual variations in GW activities, which are related to topography, polar jets, and large dust storms. The interannual variations in GWs imply that, in addition to the well-known large seasonal dust storms, complex interannual variations in atmospheric activity over the polar jets and in the complex topography at mid-to-low latitudes on Mars may also exist, which deserve further studies in the future. Full article

This study utilizes backward trajectory cluster analysis, the Potential Source Contribution Function (PSCF), Concentration Weighted Trajectory (CWT), and a random forest model to investigate the pollution characteristics of PM_2.5 and PM₁₀ in the “Urumqi-Changji Hui Autonomous Prefecture-Shihezi-Wujiaqu (U-C-S)” urban agglomeration. Findings indicate that on an annual basis, higher PM_2.5 concentrations are observed in the central part of the “U-C-S” urban agglomeration, southern Wujiaqu, and the Shihezi area, whereas PM₁₀ concentrations are lower in the high-altitude regions of the Tianshan and Bogda Mountains. Seasonally, both PM_2.5 and PM₁₀ concentrations significantly increase during winter, with summer exhibiting the best air quality. On a monthly scale, Urumqi’s central urban area shows a marked rise in PM_2.5 concentrations during winter, attributed to coal heating and stable weather conditions. Weekly patterns reveal higher pollution levels on weekdays compared to weekends. Daily data show that PM_2.5 concentrations are notably higher in winter compared to other periods, while elevated PM₁₀ levels in spring are primarily due to dust storms. Cluster analysis indicates that seasonal airflow paths significantly influence particulate matter concentrations. PSCF and CWT analyses demonstrate that the most severe PM_2.5 pollution in winter is concentrated in the northern part of the Bayingolin Mongol Autonomous Prefecture, southern Yining City, and across all areas of Urumqi. The random forest model provides robust predictions of particulate matter concentrations, aiding in the understanding and mitigation of future pollution trends. This study offers valuable insights for atmospheric particulate matter pollution research in the Xinjiang region and serves as a reference for similar urban agglomerations. Full article

Free-space optical (FSO) communication systems offer fiber-like bandwidth, high security, and rapid deployment; however, their performance is highly susceptible to atmospheric impairments, such as dust storms, which can cause fading that degrades link reliability. In this study, we analyze the performance of FSO links under a dust-induced fading channel modeled as a Beta distribution channel. We derive an expression for the instantaneous signal-to-noise ratio (SNR) distribution. Using the SNR expression, we construct a general framework that yields closed-form formulas for fundamental performance measures such as outage probability, average bit-error rate (BER), and ergodic capacity. The analysis considers both intensity modulation/direct detection (IM/DD) and coherent detection techniques, encompassing typical modulation schemes including modulation formats such as on–off keying (OOK), M-ary phase-shift keying (M-PSK), and M-ary quadrature amplitude modulation (M-QAM). The results show that dust-induced fading penalizes all modulations, though coherent detection achieves better error performance than IM/DD at equivalent SNR. For example, a coherent receiver requires approximately 4.4 dB lower average SNR than an IM/DD system to achieve the same outage probability. Overall, the proposed unified framework shows that dust-induced fading can severely degrade the performance of FSO links, while also quantifying how network operators can trade off complexity and performance when choosing between coherent and IM/DD detection under realistic dust-storm conditions. Full article

In this paper, a novel model of dust storm intensity variations and its effects on earth–satellite link design for total attenuation prediction has been developed. The proposed model expresses the total dust-induced attenuation as a function of the empirically derived specific attenuation in (dB/km) and effective slant path distance. The formulation incorporates the vertical variation in dust storm intensity along the propagation path to more accurately represent the attenuation experienced by slant links. The effective slant path distance is obtained as a combination of a total slant path distance and an adjustment factor. The adjustment factor has been developed based on the visibility height model of the dust storm structure. The proposed model has been validated with one-year measured attenuation on 6.2 km and 7.6 km long microwave links operating at 21.2 GHz and 14.5 GHz, respectively. Full article

Yazd province in central Iran is highly prone to dust and sand storms, causing significant environmental, economic, and health impacts. This study investigates the spatiotemporal dynamics of dust storms in Yazd over 2003–2022 using ground-based meteorological station records and satellite-derived aerosol optical depth (AOD) data from MODIS (MYD08_D3 v6.1) at monthly, seasonal, and annual scales. Analysis of ten synoptic stations data revealed an increasing trend of ~0.5 dusty days/year, with the highest frequency in spring and winter, particularly from March to May. MODIS AOD data confirmed these patterns and showed a rising annual aerosol load, peaking in May. Spatial analysis indicated that central and northern regions are most affected, consistent across datasets. The increasing frequency and intensity of dust storms are driven by natural and anthropogenic factors, including regional drought, desertification, drying wetlands, land use changes, and transboundary dust transport (from Iraq, Syria, Saudi Arabia). These findings underscore the value of integrating in situ and remote sensing observations to monitor dust events. To mitigate impacts, policymakers should prioritize long-term environmental monitoring and interventions addressing both natural and human factors influencing dust emissions. This study provides actionable insights for decision-makers to enhance environmental resilience and protect public health in arid regions. Full article