Article
Geography, Physical
Yu Zhang, Juanle Wang, Altansukh Ochir, Sonomdagva Chonokhuu, Chuluun Togtokh
Summary: According to SDG 15.3, frequent sand and dust storms on the Mongolian plateau pose a long-term challenge in preventing and controlling land degradation. This study utilized MODIS remote sensing data to monitor and analyze these events. Results show a decrease in the overall frequency of sand and dust storms, with the highest occurrence in the first decade. The cross-border regions between China and Mongolia, particularly in southern Mongolia, are identified as centers of high intensity. Precipitation exhibits a strong negative correlation with the affected area, and efforts by the Mongolian and Chinese governments in wind prevention and sand control contribute to regional restoration. Recommendations for policies regarding cross-border sandstorm responses are proposed.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Environmental Sciences
Olafur Jonasson, Alexander Ignatov, Boris Petrenko, Victor Pryamitsyn, Yury Kihai
Summary: The study performed a full-mission reanalysis of the sea surface temperature (SST) dataset from the MODIS sensors onboard Terra and Aqua satellites. The dataset met the accuracy and precision specifications and was evaluated through comparisons with in situ SST measurements.
Article
Environmental Sciences
Yehya Elsayed, Sofian Kanan, Ahmad Farhat
Summary: This study in the GCC region near two major airports reports seasonal variations in meteorological parameters, atmospheric dust, and dust-borne heavy metals concentrations. The concentrations of heavy metals, PM2.5, and PM10 fluctuated with meteorological conditions, with potential harm to human health. The chemical correlation between atmospheric dust and regional desert sand implies the localized origin of smaller dust particles.
ENVIRONMENTAL POLLUTION
(2021)
Article
Environmental Sciences
Yahui Che, Bofu Yu, Katherine Parsons, Cheryl Desha, Mohammad Ramezani
Summary: Validated dust and aerosol datasets are important for atmospheric research, and the MERRA-2 reanalysis product provides long-term, global coverage aerosol simulations. However, the validation of MERRA-2 has some limitations, and it is less well correlated with AERONET for dust aerosol optical depth (DAOD) compared to MODIS-DB. MODIS-DB AOD and DAOD can be used for areas away from AERONET sites in Australia with less dependence on AERONET data. MERRA-2 underestimates the magnitude and spatial extent of AOD, especially for thick dust plumes.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Environmental Sciences
Ruibo Li, Lin Sun, Huiyong Yu, Jing Wei, Xinpeng Tian
Summary: This study examined the historical changes of aerosols using AVHRR data, introducing mature MODIS vegetation index products (MYD13) to correct AVHRR NDVI for estimating AVHRR LSR and conducting aerosol retrieval.
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
(2021)
Article
Environmental Sciences
Mikalai Filonchyk, Michael Peterson
Summary: An intense dust storm in March 2021 originating from the Gobi Desert in Mongolia had a significant impact on northern, central, and eastern China, affecting air quality and visibility, and posing a threat to millions of lives.
Article
Environmental Sciences
Maryam Sorkheh, Hossein Mohammad Asgari, Isaac Zamani, Farshid Ghanbari
Summary: This study examined the relationship between dust sources and airborne bacteria by analyzing soil and air samples, and identified the main factors affecting airborne bacteria. The dominant species of bacteria was Bacillus. The findings can help decision-makers prioritize dust sources to control the adverse effects of dust.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Mehdi Jafari, Tayyebeh Mesbahzadeh, Reyhaneh Masoudi, Gholamreza Zehtabian, Mehdi Amouei Torkmahalleh
Summary: This research conducted statistical analyses on dusty days in Isfahan province over a 20-year period, identifying the main sources of dust to be the border area between Iraq and Syria. The study found that the spring season had the highest number of dusty days.
AIR QUALITY ATMOSPHERE AND HEALTH
(2021)
Article
Environmental Sciences
Zhimin Ma, Chunyu Dong, Kairong Lin, Yu Yan, Jianfeng Luo, Dingshen Jiang, Xiaohong Chen
Summary: By developing a simple and new data downscaling approach, we successfully created a high-resolution NDVI database on a global scale for monitoring the changes in vegetation ecosystems. Evaluation of the downscaled data showed similarities to the MODIS NDVI product in terms of accuracy. We also utilized the downscaled data to monitor NDVI changes in different plant types and locations with vegetation heterogeneity, as well as to study global vegetation trends over the past four decades.
Article
Environmental Sciences
Soodabeh Namdari, Ali Ibrahim Zghair Alnasrawi, Omid Ghorbanzadeh, Armin Sorooshian, Khalil Valizadeh Kamran, Pedram Ghamisi
Summary: Motivated by the lack of research on land cover and dust activity in the Middle East, this study explores the relationship between vegetation cover and dust emission in the region. The results show that the decrease in vegetation cover is closely related to increased dust intensity. The study also reveals spatial variability in the relationship between Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI) in different time periods.
Article
Geochemistry & Geophysics
Wei Wang, Alim Samat, Jilili Abuduwaili, Chen Wang, Philippe De Maeyer, Tim van de Voorde
Summary: This paper proposes an automatic SDS source identification method based on ERA5 surface wind direction and MODIS daily surface reflectance using remote sensing data. The method utilizes the zero-crossing edge detection algorithm to extract the dust plume edge and trace the point sources. The results show that the proposed method accurately and efficiently identifies SDS source points, making it crucial for dust risk assessment and desertification control.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Xing Wang, Zhengwei Yang, Huihui Feng, Jiuwei Zhao, Shuaiyi Shi, Lu Cheng
Summary: This study explores the possibility of using surveillance cameras as an alternative SDS monitor. A Multi-Stream Attention-aware Convolutional Neural Network (MA-CNN) is constructed to accurately observe SDS and achieves optimal performance among compared algorithms in real-world scenarios.
Article
Environmental Sciences
Zhang Jian, Zhou Chun-Hong, Gui Hai-Lin, Zhang Xiao-Ye
Summary: This study investigated the distribution of biological soil crust in sand and dust storm (SDS) source areas of Central and East Asia, finding varying coverage rates and the ability of biological soil crust to inhibit dust emission by increasing roughness length. The results showed a suppressive effect on dust flux, indicating the importance of considering the impact of biological crust in dust emission schemes in areas where coverage has improved.
ADVANCES IN CLIMATE CHANGE RESEARCH
(2021)
Article
Environmental Sciences
Wen Huo, Fan Yang, Ye Wu, XieFei Zhi, MeiQi Song, ChengLong Zhou, XingHua Yang, Ali MamtiMin, Qing He, Cong Wen, JiaCheng Gao, Lu Meng, Shunqi Hu
Summary: Dust storms and dust aerosols have a significant impact on environmental variation and climate change. The near-surface layer plays a crucial role in the upward transmission of dust aerosols. The topographic relief of natural dunes is important for wind-driven dust emission, transport, and deposition.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Soodabeh Namdari, Khalil Valizadeh Kamran, Armin Sorooshian
Summary: The dust storms in the Sistan region of East Iran are linked to northwest winds and occur more frequently in spring and summer. The study found a negative relationship between dust intensity (AOD) and wind speed, potentially due to changes in vegetation cover. Analysis also suggests a positive relationship between wind and dust, proposing effective thresholds for dust erosion based on wind speeds.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
