Article
Geography, Physical
Alex R. Aves, Laura E. Revell, Sally Gaw, Helena Ruffell, Alex Schuddeboom, Ngaire E. Wotherspoon, Michelle LaRue, Adrian J. McDonald
Summary: Airborne microplastics have been identified in various remote environments, but there is a lack of data in the Southern Hemisphere, particularly in Antarctica. This study collected snow samples from 19 sites in the Ross Island region of Antarctica and confirmed the presence of microplastics using micro-Fourier transform infrared spectroscopy (mu FTIR). The results showed that all Antarctic snow samples contained microplastics, with an average concentration of 29 particles L-1. The most common type of microplastic was fibers, and the most common polymer was polyethylene terephthalate (PET). The study also found that the microplastics could have been transported over long distances of up to 6000 km and could have local sources from nearby research stations.
Article
Geosciences, Multidisciplinary
Mojtaba Zeraatpisheh, Younes Garosi, Hamid Reza Owliaie, Shamsollah Ayoubi, Ruhollah Taghizadeh-Mehrjardi, Thomas Scholten, Ming Xu
Summary: In this study, the performance of predicting soil organic carbon (SOC) in an arid agroecosystem in Iran using different datasets and machine learning algorithms was compared. The results showed that the Cubist model performed the best with the MCC dataset and the combined dataset of MCC and remote sensing time-series (RST), while the RF model showed better results for the RST dataset. Soil properties were found to be the main factors influencing SOC variation in the MCC and combined datasets, while NDVI was the most controlling factor in the RST dataset. The study suggested that time-series vegetation indices may not significantly improve SOC prediction accuracy, but combining MCC and RST datasets could produce SOC spatial maps with lower uncertainty.
Review
Computer Science, Interdisciplinary Applications
Shui-Hua Jiang, Jinsong Huang, D. Griffiths, Zhi-Ping Deng
Summary: The spatial variability of soil properties has been largely overlooked in traditional slope stability analyses. However, in the past two decades, an increasing number of research papers have focused on explicitly modeling this variability. The first phase of research primarily emphasized the importance of including spatial variability in probabilistic slope stability analysis, while the second phase witnessed rapid developments in quantitative risk assessment, computational efficiency improvement, and the utilization of site investigation and field monitoring data. This review aims to summarize these advances to guide future research directions.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Geosciences, Multidisciplinary
Anne J. Hoek van Dijke, Martin Herold, Kaniska Mallick, Imme Benedict, Miriam Machwitz, Martin Schlerf, Agnes Pranindita, Jolanda J. E. Theeuwen, Jean-Francois Bastin, Adriaan J. Teuling
Summary: Global tree restoration can have complex and regionally variable impacts on water availability, with tree-cover expansion leading to both increased evaporation and enhanced precipitation. The effects on water availability can vary greatly, with some regions experiencing an increase in water availability while others face a decrease.
Article
Engineering, Geological
Liangkun Wang, Weixing Shi, Ying Zhou
Summary: The study applied an adaptive-passive eddy current pendulum TMD (APEC-PTMD) to address the frequency detuning issue of traditional TMDs, which can adapt to the structural dominant frequency in buildings with different soil types and has better aseismic protection effect.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2022)
Article
Environmental Sciences
Lan Wang-Erlandsson, Arne Tobian, Ruud J. van der Ent, Ingo Fetzer, Sofie te Wierik, Miina Porkka, Arie Staal, Fernando Jaramillo, Heindriken Dahlmann, Chandrakant Singh, Peter Greve, Dieter Gerten, Patrick W. Keys, Tom Gleeson, Sarah E. Cornell, Will Steffen, Xuemei Bai, Johan Rockstrom
Summary: This Perspective proposes the addition of a green water planetary boundary based on root-zone soil moisture and demonstrates that widespread green water modifications now present increasing risks to Earth system resilience.
NATURE REVIEWS EARTH & ENVIRONMENT
(2022)
Article
Engineering, Geological
Kok-Kwang Phoon, Wengang Zhang
Summary: This paper introduces the application of machine learning in geotechnical engineering and proposes a data-centric agenda for geotechnics. It highlights the importance of data-driven site characterization and identifies challenges such as ugly data and explainable site recognition.
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2023)
Article
Engineering, Geological
Haiqing Yang, Kanglei Song, Jiayuan Zhou
Summary: This study aims to establish an automatic prediction model for geological conditions based on the operational data of TBM. By using clustering analysis and classifier model selection, a geological prediction model was successfully constructed. Among the input parameters of the model, the total thrust force, penetration rate, and ratio of thrust to torque have the greatest influence on the prediction of ground conditions.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)
Article
Engineering, Civil
Jintao Xu, Ziqiang Ma, Songkun Yan, Jie Peng
Summary: The study found that satellite-based precipitation products generally outperform model-based products, but the latter perform better in high-latitude regions and winter. ERA5 and ERA5-Land show similar spatio-temporal patterns and have their own advantages. Satellite products perform best in subregions of subtropical and tropical monsoon climate.
JOURNAL OF HYDROLOGY
(2022)
Review
Environmental Sciences
Anna M. Irrgang, Mette Bendixen, Louise M. Farquharson, Alisa Baranskaya, Li H. Erikson, Ann E. Gibbs, Stanislav A. Ogorodov, Pier Paul Overduin, Hugues Lantuit, Mikhail N. Grigoriev, Benjamin M. Jones
Summary: Arctic coasts are facing increasing erosion and flooding due to decreasing sea ice, thawing permafrost, and rising sea levels. This review examines the changes in Arctic coastal morphodynamics and discusses their broader impacts on Arctic systems. Climate change has a significant impact on Arctic coasts, including the loss of permafrost, sea ice, and glaciers, as well as rising sea levels. However, assessing the influence of anthropogenic warming on Arctic coastal dynamics is challenging due to limited availability of data. Despite this challenge, understanding these changes is critical as the majority of permafrost coasts are erosive, and erosion and flooding are projected to intensify.
NATURE REVIEWS EARTH & ENVIRONMENT
(2022)
Article
Geosciences, Multidisciplinary
Jia-Ting Lin, Panthalingal K. Rajesh, Charles C. H. Lin, Min-Yang Chou, Jann-Yenq Liu, Jia Yue, Tung-Yuan Hsiao, Ho-Fang Tsai, Hoi-Man Chao, Mu-Min Kung
Summary: The explosive eruption of the Hunga-Tonga volcano in the southwest Pacific on January 15, 2022 triggered global atmospheric disturbances, with surface air pressure waves and concentric traveling ionosphere disturbances observed. These disturbances propagated through space and interhemispheric coupling, reaching different locations at different times.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Engineering, Environmental
Forrest S. Melton, Justin Huntington, Robyn Grimm, Jamie Herring, Maurice Hall, Dana Rollison, Tyler Erickson, Richard Allen, Martha Anderson, Joshua B. Fisher, Ayse Kilic, Gabriel B. Senay, John Volk, Christopher Hain, Lee Johnson, Anderson Ruhoff, Philip Blankenau, Matt Bromley, Will Carrara, Britta Daudert, Conor Doherty, Christian Dunkerly, MacKenzie Friedrichs, Alberto Guzman, Gregory Halverson, Jody Hansen, Jordan Harding, Yanghui Kang, David Ketchum, Blake Minor, Charles Morton, Samuel Ortega-Salazar, Thomas Ott, Mutlu Ozdogan, Peter M. ReVelle, Mitch Schull, Carlos Wang, Yun Yang, Ray G. Anderson
Summary: The lack of consistent, accurate information on evapotranspiration and consumptive use of water by irrigated agriculture is a key issue in water management in the western United States and other arid agricultural regions. Recent advances in remote sensing of ET have led to the development of various mapping methods, with the OpenET project aiming to develop a system for generating and distributing ET data.
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2022)
Review
Geography, Physical
F. Nex, C. Armenakis, M. Cramer, D. A. Cucci, M. Gerke, E. Honkavaara, A. Kukko, C. Persello, J. Skaloud
Summary: This paper reviews best practices for the use of UAVs in remote sensing and mapping applications, emphasizes the need for interdisciplinary research, explores the future trends and impacts of UAVs in photogrammetry and remote sensing.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Ayesha Shafique, Guo Cao, Zia Khan, Muhammad Asad, Muhammad Aslam
Summary: This review discusses the importance of change detection in the context of remote sensing technology and the application of deep learning techniques. Deep learning has shown significant success in change detection, outperforming traditional methods, and is considered as the future direction of development.
Review
Geosciences, Multidisciplinary
Yong Li, Songqi Pan, Shuzheng Ning, Longyi Shao, Zhenhua Jing, Zhuangsen Wang
Summary: Coal and its derivatives are crucial for stable energy supply and economic development in China. The study of coal measure metallogeny is important for promoting the transition of coal from fuel to raw materials and achieving high-quality development.
SCIENCE CHINA-EARTH SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Lei Zhang, Mengqian Huang, Mingxue Li, Shuo Lu, Xiaochuan Yuan, Jinghua Li
Summary: Mining of upper multilayers in deep coal seams generates cyclic loading-unloading stresses in bottom layers, which improve permeability and enhance coalbed methane gas drainage. Testing showed that permeability increased approximately by 5.8 times after loading-unloading cyclic tests. Different numbers of loading-unloading cycles produced similar fracturing effects, with the largest effect occurring within the effective stress range of 4 to 11 MPa.
NATURAL RESOURCES RESEARCH
(2022)
Article
Energy & Fuels
Ma Yongsheng, Cai Xunyu, Yun Lu, Li Zongjie, Li Huili, Deng Shang, Zhao Peirong
Summary: This review provides a systematic summary of the exploration and development process of the Shunbei ultra-deep carbonate oil and gas field in the Tarim Basin, and highlights the progress of exploration and development technologies during China's 13th Five-Year Plan. It offers important guidance for the exploration and development of ultra-deep marine carbonate reservoirs in China and abroad.
PETROLEUM EXPLORATION AND DEVELOPMENT
(2022)
Article
Geosciences, Multidisciplinary
Andrea L. Moreno-Rios, Lesly P. Tejeda-Benitez, Ciro F. Bustillo-Lecompte
Summary: Air pollution caused by particulate matter is a major threat to human health, especially in large cities. The size, composition, and toxicity of these particles vary. Ultrafine particles have a greater impact on human health as they can enter the lungs and vital organs, leading to diseases. In addition, particulate matter pollution is associated with respiratory conditions, genotoxicity, mutagenicity, and carcinogenicity.
GEOSCIENCE FRONTIERS
(2022)
Article
Geosciences, Multidisciplinary
Zhengjian Xu, Yang Wang, Shu Jiang, Chao Fang, Luofu Liu, Kangjun Wu, Qun Luo, Xin Li, Yingying Chen
Summary: The research in lacustrine rift basins in Eastern China found that the organic matter in deep formations mainly comes from a mix of aquatic microorganisms and higher plant materials, with higher plant materials being dominant. The bio-productivity was moderate to high, the paleoclimate was mainly cold and semi-humid to semi-arid, lake salinity ranged from fresh to brackish-water, and redox conditions were sub-reducing to sub-oxidizing. The dilution degree was strongest in the Yingcheng shale, followed by the Shahezi and Huoshiling formations.
MARINE AND PETROLEUM GEOLOGY
(2022)
Article
Environmental Sciences
Alireza Arabameri, Subodh Chandra Pal, Fatemeh Rezaie, Rabin Chakrabortty, Asish Saha, Thomas Blaschke, Mariano Di Napoli, Omid Ghorbanzadeh, Phuong Thao Thi Ngo
Summary: This paper explores the predictive capacity of different approaches to landslide susceptibility modeling using artificial intelligence. The results show that the CDT-Multiboost model is the excellent model with high accuracy and is effective for improving spatial prediction of landslide susceptibility.
GEOCARTO INTERNATIONAL
(2022)
