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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Main Authors: Ekaterina Kulakova, Elena Muravyova
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/14/11/591
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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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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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