Drivers of recent decline in dust activity over East Asia

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Nov. 19, 2022

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

Language: Английский

---

Long-Term Spatio-Temporal Analysis, Distribution, and Trends of Dust Events over Iran

Atmosphere, Journal Year: 2025, Volume and Issue: 16(3), P. 334 - 334

Published: March 16, 2025

This study provides a comprehensive evaluation of dust events over Iran, using synoptic data from 286 meteorological stations. The are classified according to codes as suspended and others (i.e., blowing dust, storms) based on their intensity with horizontal visibility ≤1, 3, 5, 10 km. Severe (visibility ≤ 1 km) (code 06) occurred primarily in the western parts while moderate or severe dominated south eastern thus revealing contrasting spatial distribution regarding type frequency events. Furthermore, distinct seasonality is revealed number events, since maximized SW Iran March July, highly associated Shamal winds, storms east April August. Zabol city, some stations along coast Arabian Sea impacted by this storm throughout year. Trend analysis notable increase during period 1994–2023, particularly part mostly attributed transboundary Mesopotamian plains. large activity 1994–2009 was followed decrease 2010s at many stations, differences were observed trends dust. An inverse correlation between precipitation anomalies observed, years abnormal (e.g., 2019; 138% increase) related substantial occurrence. Over an 11-year period, surface concentrations exceeded annual PM10 threshold 50 µg/m3 more than 800 days, maximum reaching up 1411 µg/m3. highlights urgent need for effective management strategies mitigate impacts air quality public health Iran.

Language: Английский

---

Heavy metals contamination status and health risk assessment of indoor and outdoor dust in Ahvaz and Zabol cities, Iran

Atmospheric Pollution Research, Journal Year: 2023, Volume and Issue: 14(4), P. 101727 - 101727

Published: March 22, 2023

Language: Английский

---

Dust and climate interactions in the Middle East: Spatio-temporal analysis of aerosol optical depth and climatic variables

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 927, P. 172176 - 172176

Published: April 2, 2024

The Middle East (ME) is grappling with an alarming increase in dust levels, measured as aerosol optical depth (AOD), which poses significant threats to air quality, human health, and ecological stability. This study aimed investigate correlations between climate non-climate driving factors AOD the ME over last four-decade (1980–2020), based on analysis of three variables: actual evapotranspiration (AET), potential (PET), precipitation (P). A comprehensive conducted discern patterns trends, a particular focus regions such Rub al-Khali, Ad-Dahna, An-Nafud Desert, southern Iraq, where consistently high levels were observed. 77 % area classified arid or semi-arid aridity index. Our results indicate upward trend Iran, Yemen, Saudi Arabia. We noted increasing AET Euphrates Tigris basin, northern-Iran, Nile region, along rising PET zones Syria. Conversely, P showed notable decrease northern-Iraq, Syria, southwestern southern-Turkey. Comparison long-term changes (10-year moving averages) consistent decreasing all regions. Utilizing Budyko space-based analysis, we found that climatic mainly influence much East, while non-climatic have strong impact certain areas like Tigris-basin, northern-Iran. experiences complex intricate interactions events their drivers. To address this issue, multi-system approach necessary, considers both Moreover, efficient control strategy should include soil water conservation, advanced monitoring, public awareness campaigns involve regional international collaboration.

Language: Английский

---

Tracing of Heavy Metals Embedded in Indoor Dust Particles from the Industrial City of Asaluyeh, South of Iran

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(13), P. 7905 - 7905

Published: June 28, 2022

Assessment of indoor air quality is especially important, since people spend substantial amounts time indoors, either at home or work. This study analyzes concentrations selected heavy metals in 40 dust samples obtained from houses the highly-industrialized Asaluyeh city, south Iran spring and summer seasons (20 each). Furthermore, health risk due to exposure pollution investigated for both children adults, a city with several oil refineries petrochemical industries. The chemical analysis revealed that followed order Cr > Ni Pb As Co Cd. A significant difference was observed potential toxic elements (PTEs) such as Cr, Ni, mean (±stdev) levels were 60.2 ± 9.1 mg kg−1, 5.6 2.7 kg−1 16.4 1.9 respectively, while significantly lower (17.6 9.7 3.0 1.7 13.5 2.4 respectively). Although hazard index (HI) values, which denote possibility non-carcinogenic household metals, generally low adults (HI < 1), carcinogenic risks arsenic chromium found be above safe limit 1 × 10−4 through ingestion pathway, indicating high cancer Asaluyeh, summer.

Language: Английский

---

Assessment of Rural Vulnerability to Sand and Dust Storms in Iran

Atmosphere, Journal Year: 2023, Volume and Issue: 14(2), P. 281 - 281

Published: Jan. 31, 2023

Climate-related hazards such as sand and dust storms (SDS) have various impacts on human health, socio-economy, environment, agroecosystems. Iran has been severely affected by domestic external SDS during the last two decades. Considering fragile economy of Iran’s rural areas strong dependence livelihood agroecosystems, cause serious damage to communities. Therefore, there is an urgent need conduct a vulnerability assessment for developing risk mitigation plans. In this study, components were formulated through geographic information system (GIS)-based integrated approach using composite indicators. By implementing GIS multiple-criteria decision analysis (GIS-MCDA) model socioeconomic remote sensing data, map was produced. Our results show that about 37% experienced high very levels SDS. Rural in southeast south Iran, especially Sistan Baluchestan Hormozgan provinces are more vulnerable The findings study provide basis disaster risk-reduction plans enabling authorities prioritize policies at provincial administrative scale Iran.

Language: Английский

---

Spatial Distribution of Particulate Matter in Iran from Internal Factors to the Role of Western Adjacent Countries from Political Governance to Environmental Governance

Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 8(1), P. 135 - 164

Published: Jan. 1, 2024

Language: Английский

---

Modeling land susceptibility to wind erosion hazards using LASSO regression and graph convolutional networks

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 11

Published: May 9, 2023

Predicting land susceptibility to wind erosion is necessary mitigate the negative impacts of on soil fertility, ecosystems, and human health. This study first attempt model hazards through application a novel approach, graph convolutional networks (GCNs), as deep learning models with Monte Carlo dropout. approach applied Semnan Province in arid central Iran, an area vulnerable dust storms climate change. We mapped 15 potential factors controlling erosion, including climatic variables, characteristics, lithology, vegetation cover, use, digital elevation (DEM), then least absolute shrinkage selection operator (LASSO) regression discriminate most important factors. constructed predictive by randomly selecting 70% 30% pixels, training validation datasets, respectively, focusing locations severe inventory map. The current LASSO identified eight out features (four property categories, speed, evaporation) Province. These were adopted into GCN model, which estimated that 15.5%, 19.8%, 33.2%, 31.4% total characterized low, moderate, high, very high respectively. under curve (AUC) SHapley Additive exPlanations (SHAP) game theory assess performance interpretability output, AUC values for datasets at 97.2% 97.25%, indicating excellent prediction. SHAP ranged between −0.3 0.4, while analyses revealed coarse clastic component, use effective output. Our results suggest this suite methods highly recommended future spatial prediction other environments around globe.

Language: Английский

---

A comprehensive investigation of the causes of drying and increasing saline dust in the Urmia Lake, northwest Iran, via ground and satellite observations, synoptic analysis and machine learning models

Ecological Informatics, Journal Year: 2023, Volume and Issue: 78, P. 102355 - 102355

Published: Oct. 24, 2023

Language: Английский

---

Quantifying the contribution of Middle Eastern dust sources to PM10 levels in Ahvaz, Southwest Iran

Atmospheric Research, Journal Year: 2023, Volume and Issue: 295, P. 106993 - 106993

Published: Sept. 15, 2023

Language: Английский

---