Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation
The article presents the results of studies of carbon dioxide flow in the territory of section No. 5 of the Eurasian Carbon Polygon (Russia, Republic of Bashkortostan). The gas analyzer Sniffer4D V2.0 (manufactured in Shenzhen, China) with an installed CO<sub>2</sub> sensor, quadrocopter...
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MDPI AG
2023-11-01
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author | Ekaterina Kulakova Elena Muravyova |
author_facet | Ekaterina Kulakova Elena Muravyova |
author_sort | Ekaterina Kulakova |
collection | DOAJ |
description | The article presents the results of studies of carbon dioxide flow in the territory of section No. 5 of the Eurasian Carbon Polygon (Russia, Republic of Bashkortostan). The gas analyzer Sniffer4D V2.0 (manufactured in Shenzhen, China) with an installed CO<sub>2</sub> sensor, quadrocopter DJI MATRICE 300 RTK (manufactured in Shenzhen, China) were used as control devices. The studies were carried out on a clear autumn day in conditions of green vegetation and on a frosty November day with snow cover. Statistical characteristics of experimental data arrays are calculated. Studies of the influence of temperature, humidity of atmospheric air on the current value of CO<sub>2</sub> have been carried out. Graphs of the distribution of carbon dioxide concentration in the atmospheric air of section No. 5 on autumn and winter days were obtained. It has been established that when building a model of CO<sub>2</sub> in the air, the parameters of the process of deposition by green vegetation should be considered. It was found that in winter, an increase in air humidity contributes to a decrease in gas concentration. At an ambient temperature of 21 °C, an increase in humidity leads to an increase in the concentration of carbon dioxide. |
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issn | 2078-2489 |
language | English |
last_indexed | 2024-03-09T16:45:08Z |
publishDate | 2023-11-01 |
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spelling | doaj.art-8bb1baf60499473b85bb168fb00750a42023-11-24T14:48:11ZengMDPI AGInformation2078-24892023-11-01141159110.3390/info14110591Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous VegetationEkaterina Kulakova0Elena Muravyova1Department of Automated Technological and Information Systems, Institute of Chemical Technology and Engineering, Ufa State Petroleum Technological University, Sterlitamak 453103, RussiaDepartment of Automated Technological and Information Systems, Institute of Chemical Technology and Engineering, Ufa State Petroleum Technological University, Sterlitamak 453103, RussiaThe article presents the results of studies of carbon dioxide flow in the territory of section No. 5 of the Eurasian Carbon Polygon (Russia, Republic of Bashkortostan). The gas analyzer Sniffer4D V2.0 (manufactured in Shenzhen, China) with an installed CO<sub>2</sub> sensor, quadrocopter DJI MATRICE 300 RTK (manufactured in Shenzhen, China) were used as control devices. The studies were carried out on a clear autumn day in conditions of green vegetation and on a frosty November day with snow cover. Statistical characteristics of experimental data arrays are calculated. Studies of the influence of temperature, humidity of atmospheric air on the current value of CO<sub>2</sub> have been carried out. Graphs of the distribution of carbon dioxide concentration in the atmospheric air of section No. 5 on autumn and winter days were obtained. It has been established that when building a model of CO<sub>2</sub> in the air, the parameters of the process of deposition by green vegetation should be considered. It was found that in winter, an increase in air humidity contributes to a decrease in gas concentration. At an ambient temperature of 21 °C, an increase in humidity leads to an increase in the concentration of carbon dioxide.https://www.mdpi.com/2078-2489/14/11/591airgreenhouse gascarbon dioxidecarbon landfillmodelsdistribution |
spellingShingle | Ekaterina Kulakova Elena Muravyova Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation Information air greenhouse gas carbon dioxide carbon landfill models distribution |
title | Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation |
title_full | Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation |
title_fullStr | Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation |
title_full_unstemmed | Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation |
title_short | Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation |
title_sort | machine learning in the analysis of carbon dioxide flow on a site with heterogeneous vegetation |
topic | air greenhouse gas carbon dioxide carbon landfill models distribution |
url | https://www.mdpi.com/2078-2489/14/11/591 |
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