Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City.
Spectral gamma ray borehole logging data can yield insights into the physical properties of lake sediments, serving as a valuable proxy for assessing climate and environmental changes. The presence of tephra layers resulting from volcanic ash deposition is not related to climate and environmental co...
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| Format: | Article |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0315331 |
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| author | Mehrdad Sardar Abadi Christian Zeeden Arne Ulfers Alex Susan Meyer Thomas Wonik Mexidrill team |
| author_facet | Mehrdad Sardar Abadi Christian Zeeden Arne Ulfers Alex Susan Meyer Thomas Wonik Mexidrill team |
| author_sort | Mehrdad Sardar Abadi |
| collection | DOAJ |
| description | Spectral gamma ray borehole logging data can yield insights into the physical properties of lake sediments, serving as a valuable proxy for assessing climate and environmental changes. The presence of tephra layers resulting from volcanic ash deposition is not related to climate and environmental conditions. As a result, these layers pose challenges when attempting to analyze paleoclimate and environmental time series. Gamma rays are composed of photons, which are elementary particles of electromagnetic radiation. Tephra layers emit photons at specific energy levels that create a distinct pattern in their gamma-ray energy spectrum. The gamma-ray signature of tephra layers varies depending on the stage of the volcanic eruption. Additionally, there is a significant difference between the gamma-ray signature emitted by tephra layers and that of the background lake sediments. A composite signature can be used to predict tephra layers from background sediments by combining several gamma-ray signatures of tephra layers at different depths. We propose five-step protocol for detecting tephra layers within sediments through the utilization of gamma-ray spectroscopy. This protocol is based on a combination of physical aspects of gamma-ray spectroscopy and geological information specific to the lake system being studied. A subset of the training dataset is used, consisting of known tephra and non-tephra layers. The protocol involves identifying similarities between known tephra layers, analyzing differences in gamma-ray signals between tephra and non-tephra layers, and studying the composition of energy channels at various depths within the training dataset. Multiple linear regression models are used to predict the relationship between the composition of tephra layers as a dependent variable and the constituent energy channels of the gamma-ray signal as independent variables. The proposed protocol has the potential to accurately detect and identify thick tephra layers (> 10 cm in thickness) based on the rate of spectral gamma ray measurement in sedimentary sequences. This approach could enhance stratigraphic resolution by enabling finer subdivision of layers in an interior basin. |
| format | Article |
| id | doaj-art-c6cde2abda3b4cf78cd6ca6878bf1c7a |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj-art-c6cde2abda3b4cf78cd6ca6878bf1c7a2025-01-17T05:31:52ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031533110.1371/journal.pone.0315331Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City.Mehrdad Sardar AbadiChristian ZeedenArne UlfersAlex Susan MeyerThomas WonikMexidrill teamSpectral gamma ray borehole logging data can yield insights into the physical properties of lake sediments, serving as a valuable proxy for assessing climate and environmental changes. The presence of tephra layers resulting from volcanic ash deposition is not related to climate and environmental conditions. As a result, these layers pose challenges when attempting to analyze paleoclimate and environmental time series. Gamma rays are composed of photons, which are elementary particles of electromagnetic radiation. Tephra layers emit photons at specific energy levels that create a distinct pattern in their gamma-ray energy spectrum. The gamma-ray signature of tephra layers varies depending on the stage of the volcanic eruption. Additionally, there is a significant difference between the gamma-ray signature emitted by tephra layers and that of the background lake sediments. A composite signature can be used to predict tephra layers from background sediments by combining several gamma-ray signatures of tephra layers at different depths. We propose five-step protocol for detecting tephra layers within sediments through the utilization of gamma-ray spectroscopy. This protocol is based on a combination of physical aspects of gamma-ray spectroscopy and geological information specific to the lake system being studied. A subset of the training dataset is used, consisting of known tephra and non-tephra layers. The protocol involves identifying similarities between known tephra layers, analyzing differences in gamma-ray signals between tephra and non-tephra layers, and studying the composition of energy channels at various depths within the training dataset. Multiple linear regression models are used to predict the relationship between the composition of tephra layers as a dependent variable and the constituent energy channels of the gamma-ray signal as independent variables. The proposed protocol has the potential to accurately detect and identify thick tephra layers (> 10 cm in thickness) based on the rate of spectral gamma ray measurement in sedimentary sequences. This approach could enhance stratigraphic resolution by enabling finer subdivision of layers in an interior basin.https://doi.org/10.1371/journal.pone.0315331 |
| spellingShingle | Mehrdad Sardar Abadi Christian Zeeden Arne Ulfers Alex Susan Meyer Thomas Wonik Mexidrill team Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. PLoS ONE |
| title | Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. |
| title_full | Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. |
| title_fullStr | Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. |
| title_full_unstemmed | Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. |
| title_short | Predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data: An example from Lake Chalco, Mexico City. |
| title_sort | predicting the presence of tephra layers in lacustrine deposits using spectral gamma ray data an example from lake chalco mexico city |
| url | https://doi.org/10.1371/journal.pone.0315331 |
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