Search Results (338)

Cyprus is located between Europe, Asia and Africa, and its location is vulnerable to dust transport from the Sahara Desert, wildfire smoke particles from surrounding regions, and other anthropogenic emissions caused by several factors, mostly due to business activities on harbor areas. Moreover, the country suffers from heavy traffic conditions caused by the limited public transportation system in Cyprus. Therefore, taking into consideration the country’s geographic location, heavy commercial activities, and lack of good public transportation system, Cyprus is exposed to dust episodes and high anthropogenic emissions associated with multiple health and environmental issues. Therefore, continuous and qualitative air quality monitoring is essential. The Department of Labor Inspection of Cyprus (DLI) has established an air quality monitoring network that consists of 11 stations at strategic geographic locations covering rural, residential, traffic and industrial zones. This network measures the following pollutants: nitrogen oxide, nitrogen dioxide, sulfur dioxide, ozone, carbon monoxide, particulate matter 2.5, and particulate matter 10. This case study compares and evaluates the agreement between Copernicus Atmosphere Monitoring Service (CAMS) air quality products and ground-truth data from the DLI air quality network. The study period spans from January to December 2024. This study focuses on the following three pollutants: particulate matter 2.5, particulate matter 10, and ozone, using Ensemble Median, EMEP, and CHIMERE near-real-time model data provided by CAMS. A data analysis was performed to identify the agreement and the error rate between those two datasets (i.e., ground-truth air quality data and CAMS air quality data). In addition, this study assesses the reliability of assimilated datasets from CAMS across rural, residential, traffic and industrial zones. The results showcase how CAMS near-real-time analysis data can supplement air quality monitoring in locations without the availability of ground-truth data. Full article

Air quality is a vital factor for safeguarding public and environmental health. Particulate matter (i.e., PM2.5 and PM10) and nitrogen dioxide are among the most harmful air pollutants leading to severe health risks such as respiratory and cardiovascular diseases, while also affecting the environment negatively by contributing to the formation of acid rains and ground level ozone. The European Union has introduced new thresholds on those pollutants to be met by the year 2030, taking into consideration the guidelines set by the World Health Organization, aiming for a healthier environment for humans and living species. Cyprus is an island that is vulnerable to those pollutants mostly due to its geographic location, facilitating shipping activities and dust transport from Sahara Desert, and the methods used to produce electricity which primarily rely on petroleum products. Furthermore, the country suffers from heavy traffic conditions, making it susceptible to high levels of nitrogen dioxide. Thus, the projection of air pollutants according to different scenarios based on regulations and policies of the European Union are necessary towards clean air and better practices. The Screening for High Emission Reduction Potential on Air (SHERPA) is a tool developed by the European Commission which allows the simulation of emission reduction scenarios and their effect on the following key pollutants: NO, NO₂, O₃, PM2.5, PM10. This study aims to assess the potential of the SHERPA simulation tool to support air quality related decision and policy planning in Cyprus to ensure that the country will remain within the thresholds that will be applicable in 2030. Full article

This study analyzes the spatiotemporal characteristics of PM₁₀ across 53 Asian dust events that affected the Korean Peninsula between January 2019 and June 2024. Self-Organizing Map (SOM) analysis was applied to sea level pressure and 850 hPa wind fields from the NCEP/DOE Reanalysis II dataset, classifying synoptic patterns into four distinct clusters. Cluster 1, associated with a deep low over Manchuria and strong westerly inflow, produced the highest PM₁₀ concentrations and the longest durations across most regions, with sharp afternoon peaks and the highest skewness values, and was mainly sourced from the Gobi Desert. Cluster 2 featured a high–low pressure dipole, generating localized impacts in northwestern regions and shorter durations, with moderate afternoon increases, originating primarily from the Gobi Desert and Inner Mongolia. Cluster 3, linked to a low east of Japan, resulted in elevated PM₁₀ mainly in central and southeastern regions, with peaks often occurring earlier in the day, and was associated with Manchurian dust sources. Cluster 4 exhibited a straight northwesterly flow with the high shifted eastward, producing moderate but spatially widespread concentrations and relatively consistent afternoon peaks, also linked to Manchurian sources. These results suggest that integrating synoptic pattern classification into dust forecasting can improve accuracy, enable early recognition of high-concentration events, and support the development of timely and region-specific warning strategies. Full article

Soiling is one of the main performance risks for bifacial photovoltaic (PV) technology, particularly in arid environments such as the Atacama Desert, where dust is deposited asymmetrically on the front and rear surfaces of the modules. This study evaluates one year (July 2022 to June 2023) of soiling behavior in bifacial modules installed in fixed-tilt and horizontal single-axis tracking (HSAT) configurations, enabling a comparison to be made between static and moving structures. The average dust accumulation was found to be 0.33 mg/cm² on the front surface and 0.15 mg/cm² on the rear surface of the fixed modules. In contrast, the respective values for the HSAT systems were found to be lower at 0.25 mg/cm² and 0.035 mg/cm². These differences resulted in performance losses of 5.8% for fixed modules and 3.7% for HSAT systems. Microstructural analysis revealed that wetting and drying cycles had formed dense, cemented layers on the front surface of fixed modules, whereas tracking modules exhibited looser deposits. Natural cleaning events, such as fog, dew and frost, only provided partial and temporary mitigation. These findings demonstrate that bifaciality introduces differentiated soiling dynamics between the front and rear surfaces, emphasizing the importance of tailored cleaning strategies and the integration of monitoring systems that consider bifacial gain as a key operational parameter. These insights are crucial for developing predictive models and cost-effective O&M strategies in large-scale bifacial PV deployments under desert conditions. Full article

This study used reanalysis and lidar observations to investigate nocturnal downslope wind events in the Taklimakan desert, revealing their vertical structure, influencing factors, climatology, and impacts on boundary layer dynamics and dust emissions. 125 events were detected along the northern slope of the Kunlun Mountains, impacting Minfeng. Due to its weakness after onset, downslope flow is deflected horizontally when it encounters the opposing synoptic winds. The continued radiative cooling, dense air drainage, and adiabatic warming intensify downslope flow as the night progresses, causing it to gradually sink and overcome the opposing synoptic winds. Downslope wind events typically occur between an hour before and two hours after sunset, with the strongest occurring at or before sunset due to the longer period of radiative cooling and the coincidence with early evening instability conditions. Strong events occur under weak stability conditions as a stable atmosphere with a strong inversion layer can inhibit sinking motion. Most events, even the strongest ones, occur under dry conditions due to enhanced radiative cooling. Mechanical turbulence occurs when downslope flow hits the surface, whereas thermal turbulence occurs when warmer, downslope air weakens the lower atmosphere’s temperature inversion. Downslope wind events significantly raise dust emissions in the Taklimakan desert. Full article

This study presents a mathematical model to describe the transmission dynamics of asthma, explicitly accounting for the impact of dust waves and airborne particulate matter in the environment, recognized as key triggers of asthma exacerbations. The model incorporates a single endemic equilibrium point, which is shown to be locally asymptotically stable. To mitigate the burden of asthma, we employed the Pontryagin Maximum Principle within an optimal control framework, incorporating three time-dependent intervention strategies: vaccination, treatment, and avoidance of environmental triggers such as dust exposure. The model was numerically solved using the fourth-order Runge–Kutta method in conjunction with a forward–backward sweep algorithm to investigate the effects of various control combinations on the prevalence of asthma. Additionally, a comprehensive cost-effectiveness analysis was conducted to evaluate the economic viability of each strategy. The results indicate that the combined application of vaccination and treatment is the most cost-effective approach among the strategies analyzed, significantly reducing the number of asthma cases at minimal cost. All simulations and numerical experiments were performed to validate the theoretical findings and quantify the effectiveness of the proposed interventions under realistic environmental conditions driven by dust activity. The model highlights the importance of integrated medical and environmental control policies in mitigating asthma outbreaks, particularly in regions frequently exposed to dust storms. Full article

Microbiome studies report a decrease in diversity associated with active infections. Under the endozoan hypothesis, Coccidioides can inhabit a host without causing disease. In this study, we describe and compare the lung mycobiome of Coccidioides-positive and -negative samples obtained from wildlife. If Coccidioides is not causing infection, we predict there will be no differences in the mycobiome between positive and negative samples. Lung samples were obtained from mammals previously trapped in Tucson, Arizona, USA (n = 26), and Mesa, Arizona, USA (n = 14). Samples were screened for Coccidioides with CocciDx, and mycobiome was characterized through Illumina-based amplicon sequencing of the internal transcribed spacer 2 (ITS2). We compared alpha and beta diversity of the mycobiome to assess the effects of Coccidioides’ presence and host taxonomy. A greater number of reads were captured from Tucson samples (114,706.4 ± 57,945.8) than from Mesa (384.9 ± 953.5); however, Mesa (16.8 ± 8.8) and Tucson (12 ± 7.8) had a similar number of fungal genera per sample. CocciDx detected Coccidioides in more samples than the ITS2 amplicon sequencing. All samples from Mesa and five from Tucson tested positive for Coccidioides. Therefore, Mesa samples were excluded from statistical analysis. No difference in alpha and beta diversity was associated with Coccidioides presence, which is consistent with the endozoan hypothesis. Host taxonomy had a significant effect on beta diversity. This effect is likely driven by host behavioral and physiological differences. Full article

Isotopic investigations focused on determining the mobility and provenance of ancient human civilizations and sourcing of archeological artifacts continue to gain prominence in archeology. Most studies focus on the premise that the geographic variation in isotope systems of interest (e.g., Sr, Pb, Nd, O) in the natural environment is recorded in both human hard tissues of local individuals and raw materials sourced for artifacts within the same region. The introduction of multi-collection–inductively coupled plasma mass spectrometry (MC-ICP-MS) and laser ablation systems are techniques that consume smaller sample sizes compared to previous mass spectrometric approaches due to their higher ionization efficiency and increased sensitivity. This development has facilitated the isotopic measurement of trace elements present at low abundances (e.g., Pb, Nd, <1-to-low ppm range) particularly in human tooth enamel. Accurate interpretation of any isotope ratio measurement for the proveniencing of such low-abundance samples requires the adequate evaluation of post-mortem diagenetic alteration. A synopsis of practices currently in use for identifying post-mortem alteration in human archeological samples is discussed here. Post-mortem shifts in radiogenic isotope signatures resulting from secondary alteration are distinct from those potentially related to the impact of climate change on the bioavailable budgets for these elements. This topic is of interest to the archeological community and discussed here in the context of Holocene-aged samples from burial sites within the Nile River Valley System, and preferred dust source areas from the neighboring Sahara Desert. Full article

Soil fugitive dust (SFD) emissions pose a significant threat to both human health and the environment, highlighting the need for accurate and reliable estimation and assessment in the desert regions of northwest China. This study used climate, soil, and vegetation data from Bayingolin Prefecture (2001–2022) and applied the WEQ model to analyze temporal and spatial variations in total suspended particulate (TSP), PM₁₀, and PM_2.5 emissions and their driving factors. The region exhibited high emission factors for TSP, PM₁₀, and PM_2.5, averaging 55.46 t km⁻² a⁻¹, 27.73 t km⁻² a⁻¹, and 4.14 t km⁻² a⁻¹, respectively, with pronounced spatial heterogeneity and the highest values observed in Yuli, Qiemo, and Ruoqiang. The annual average emissions of TSP, PM₁₀, and PM_2.5 were 3.23 × 10⁷ t, 1.61 × 10⁷ t, and 2.41 × 10⁶ t, respectively. Bare land was the dominant source, contributing 72.55% of TSP emissions. Both total emissions and emission factors showed an overall upward trend, reaching their lowest point around 2012, followed by significant increases in most counties during 2012–2022. Annual precipitation, wind speed, and temperature were identified as the primary climatic drivers of soil dust emissions across all counties, and their influences exhibited pronounced spatial heterogeneity in Bazhou. In Ruoqiang, Bohu, Korla, and Qiemo, dust emissions are mainly limited by precipitation, although dry conditions and sparse vegetation can amplify the role of wind. In Heshuo, Hejing, and Yanqi, stable vegetation helps to lessen wind’s impact. In Yuli, wind speed and temperature are the main drivers, whereas in Luntai, precipitation and temperature are both important constraints. These findings highlight the need to consider emission intensity, land use, or surface condition changes, and the potential benefits of increasing vegetation cover in severely desertified areas when formulating regional dust mitigation strategies. Full article

Dust aerosols can influence climate change, the ecological environment, human health, etc. and are one of the most important factors causing global change. The specific contributions of dust events, gusts, and dust devils to dust emission remain unclear in many regions. In this study, we quantified dust emissions generated by dust events, gusts, and dust devils in the center of the Taklimakan Desert of northwestern China and investigated their respective contributions to atmospheric dust aerosols. The results illustrated that monthly dust emissions and the dust emission time for dust events, gusts, and dust devils peaked in July, August, and June, respectively, and the average monthly contributions to dust emissions were 48.2, 10.6, and 41.2% and those to emission time were 60.5, 25.5, and 14.0%, respectively. Although the dust emissions for the dust event were comparable to the sum of gusts and dust devils, the average value of AOD corresponding to the dust event was roughly 2.5 times higher than that of a non-dust day. The results presented in this study not only highlight the undeniable contribution of gusts and dust devils to dust emissions but also indicate that the specific contributions to atmospheric dust aerosols from gusts and dust devils remain uncertain. Full article

Clean and safe air quality is essential for public health, yet particulate matter (PM) significantly degrades air quality and poses serious health risks. The Gulf Cooperation Council (GCC) countries are particularly vulnerable to frequent and intense dust storms due to their vast desert landscapes. This study presents the first health risk assessment of carcinogenic and non-carcinogenic risks associated with exposure to PM2.5 and PM10 bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) based on air quality data collected during the years of 2016–2018 near Dubai International Airport and Abu Dhabi International Airport. The results reveal no significant carcinogenic risks for lead (Pb), cobalt (Co), nickel (Ni), and chromium (Cr). Additionally, AI-based regression analysis was applied to time-series dust monitoring data to enhance predictive capabilities in environmental monitoring systems. The estimated incremental lifetime cancer risk (ILCR) from PAH exposure exceeded the acceptable threshold (10⁻⁶) in several samples at both locations. The relationship between visibility and key environmental variables—PM1, PM2.5, PM10, total suspended particles (TSPs), wind speed, air pressure, and air temperature—was modeled using three machine learning algorithms: linear regression, support vector machine (SVM) with a radial basis function (RBF) kernel, and artificial neural networks (ANNs). Among these, SVM with an RBF kernel showed the highest accuracy in predicting visibility, effectively integrating meteorological data and particulate matter variables. These findings highlight the potential of machine learning models for environmental monitoring and the need for continued assessments of air quality and its health implications in the region. Full article

Since dust aerosols are one of the major pollutants in Georgia, it is important to study the aeolian desert dust (ADD) invasion to Georgia from the neighboring deserts to find out its contribution to the dust pollution problem. Therefore, the main objective of this study is to investigate the history, frequency and routes of ADD invasions to the Caucasus (Georgia) using modern models and technologies for 1.5 years. Using WRF-Chem/dust, CAMS and HYSPLIT mathematical models; MODIS satellite images; and PM10 field data, 38 cases of not strong ADD invasions to Georgia were found, and two typical cases are presented and analyzed in this paper. The results of the modeling studies from 15 March 2023 to 15 September 2024 showed that the WRF-Chem/dust (GOCART) v.4.5.1 model simulated the ADD transport to Georgia from the surrounding deserts quite well. Daily monitoring of ADD migration routes showed that in the easternmost region of Georgia (the most vinicultural and agricultural region), the number of ADD invasions was approximately three times higher than in other regions of Georgia, which is a novelty of this study due to the lack of ground dust measurement stations in the easternmost region of Georgia. Full article

Ponderosa pine (Pinus ponderosa Lawson & C. Lawson) forests in the western United States have experienced reduced fire frequency since Euro-American settlement, usually because of successful fire suppression policies and even without such human impacts at remote sites in the Great Basin and Mojave Deserts. In an effort to improve our understanding of long-term environmental dynamics in sky-island ecosystems, we developed tree-ring chronologies from ponderosa pines located in the Sheep Mountain Range of southern Nevada, inside the Desert National Wildlife Refuge (DNWR). After comparing those dendrochronological records with other ones available for the south-central Great Basin, we analyzed their climatic response using station-recorded monthly precipitation and air temperature data from 1950 to 2024. The main climatic signal was December through May total precipitation, which was then reconstructed at annual resolution over the past five centuries, from 1490 to 2011 CE. The mean episode duration was 2.6 years, and the maximum drought duration was 11 years (1924–1934; the “Dust Bowl” period), while the longest episode, 19 years (1905–1923), is known throughout North America as the “early 1900s pluvial”. By quantifying multi-annual dry and wet episodes, the period since DNWR establishment was placed in a long-term dendroclimatic framework, allowing us to estimate the potential drought resilience of its unique, tree-dominated environments. Full article

Aerosols play a critical role in modulating the land–atmosphere energy balance, influencing regional climate dynamics, and affecting air quality. Xinjiang, a typical arid and semi-arid region in China, frequently experiences dust events and complex aerosol transport processes. This study provides a comprehensive analysis of the spatiotemporal evolution and potential source regions of aerosols in Xinjiang from 2005 to 2023, based on Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (MCD19A2), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) vertical profiles, ground-based PM_2.5 and PM₁₀ concentrations, MERRA-2 and ERA5 reanalysis datasets, and HYSPLIT backward trajectory simulations. The results reveal pronounced spatial and temporal heterogeneity in aerosol optical depth (AOD). In Northern Xinjiang (NXJ), AOD exhibits relatively small seasonal variation with a wintertime peak, while Southern Xinjiang (SXJ) shows significant seasonal and interannual variability, characterized by high AOD in spring and a minimum in winter, without a clear long-term trend. Dust is the dominant aerosol type, accounting for 96.74% of total aerosol content, and AOD levels are consistently higher in SXJ than in NXJ. During winter, aerosols are primarily deposited in the near-surface layer as a result of local and short-range transport processes, whereas in spring, long-range transport at higher altitudes becomes more prominent. In NXJ, air masses are primarily sourced from local regions and Central Asia, with stronger pollution levels observed in winter. In contrast, springtime pollution in Kashgar is mainly influenced by dust emissions from the Taklamakan Desert, exceeding winter levels. These findings provide important scientific insights for atmospheric environment management and the development of targeted dust mitigation strategies in arid regions. Full article

This study investigates the impact of desert dust on precipitation patterns using multi-model simulations. Dust-based processes of formation/removal of ice nuclei (IN) and cloud condensation nuclei (CCN) are investigated by using both the online access model WRF-CHIMERE and the online integrated model WRF-Chem. Comparisons of model predictions with rainfall measurements (GRISO: Spatial Interpolation Generator from Rainfall Observations) over the Italian peninsula show the models’ ability to reproduce heavy orographic precipitation in alpine regions. To quantify the impact of the mineral dust transport concomitant to the atmospheric river (AR) on cloud formation, a sensitivity study is performed by using the WRF-CHIMERE model (i) by setting dust concentrations to zero and (ii) by modifying the settings of the Thompson Aerosol-Aware microphysics scheme. Statistical comparisons revealed that WRF-CHIMERE outperformed WRF-Chem. It achieved a correlation coefficient of up to 0.77, mean bias (MB) between +3.56 and +5.01 mm/day, and lower RMSE and MAE values (~32 mm and ~22 mm, respectively). Conversely, WRF-Chem displayed a substantial underestimation, with an MB of −25.22 mm/day and higher RMSE and MAE values. Our findings show that, despite general agreement in spatial precipitation patterns, both models significantly underestimated the peak daily rainfall in pre-alpine regions (e.g., 216 mm observed at Malga Valine vs. 130–140 mm simulated, corresponding to a 35–40% underestimation). Although important instantaneous changes in precipitation and temperature were modeled at a local scale, no significant total changes in precipitation or air temperature averaged over the entire domain were observed. These results underline the complexity of aerosol–cloud interactions and the need for improved parameterizations in coupled meteorological models. Full article