This paper studies the oil spill, which occurred in the Norilsk and Taimyr region of Russia due to the collapse of the fuel tank at the power station on May 29, 2020. We monitored the snow, ice, water, vegetation and wetland of the region using data from the Multi-Spectral Instruments (MSI) of Sentinel-2 satellite. We analyzed the spectral band absorptions of Sentinel-2 data acquired before, during and after the incident, developed true and false-color composites (FCC), decorrelated spectral bands and used the indices, i.e. Snow Water Index (SWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The results of decorrelated spectral bands 3, 8, and 11 of Sentinel-2 well confirmed the results of SWI, NDWI, NDVI, and FCC images showing the intensive snow and ice melt between May 21 and 31, 2020. We used Sentinel-2 results, field photographs, analysis of the 1980-2020 daily air temperature and precipitation data, permafrost observations and modeling to explore the hypothesis that either the long-term dynamics of the frozen ground, changing climate and environmental factors, or abnormal weather conditions may have caused or contributed to the collapse of the oil tank.
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http://dx.doi.org/10.1038/s41598-021-83260-7 | DOI Listing |
Mar Environ Res
December 2024
School of Fishery, Zhejiang Ocean University, Zhoushan, 316022, China.
Marine oil spills lead to intertidal sediment pollution, causing benthic bioaccumulation and toxicity. However, relatively few studies have been conducted on the effects of crude oil sediment pollution on benthos. In this study, Sinonovacula constricta was used as the research object in a sediment environment to study the accumulation and elimination effects of S.
View Article and Find Full Text PDFEnviron Int
December 2024
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China; State Environmental Protection Key Laboratory of Estuarine and Coastal Environment, Chinese Research Academy of Environmental Science, Beijing 100012, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China. Electronic address:
Identifying and differentiating human activities is crucial for effectively preventing the threats posed by environmental pollution to aquatic ecosystems and human health. Machine learning (ML) is a powerful analytical tool for tracking human impacts on river ecosystems based on high-through datasets. This study employed an ML framework and 16S rRNA sequencing data to reveal microbial dynamics and trace human activities across China.
View Article and Find Full Text PDFFront Biosci (Elite Ed)
November 2024
Advanced Institute of Technology and Innovation (IATI), 50751-310 Recife, Pernambuco, Brazil.
Background: This study aimed to produce, characterize, and apply a biosurfactant as a bioremediation tool for oil-contaminated coastal environments.
Methods: The biosurfactant was produced in a medium containing 5.0% corn steep liquor and 1.
Front Biosci (Elite Ed)
October 2024
Department of Environmental Biotechnology, Biotechnology Research Center, Al-Nahrain University, 10018 Baghdad, Iraq.
Background: Contamination with crude oil and hydrocarbons has become a global threat. Such threats have urged us to invent solutions to deal with this dilemma. However, chemical treatment comes with limited benefits.
View Article and Find Full Text PDFBioresour Technol
December 2024
Research Institute of Petroleum Exploration and Development, PetroChina, Beijing 100083, China.
The rapid growth of global energy demand accelerates the development of sustainable, clean, and renewable energy sources. Biohydrogen production, driven by functional microorganisms, offers a promising solution. Multiple species of bacteria, fungi, microalgae, and archaea were able to produce hydrogen.
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