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...

Full description

Bibliographic Details
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
Description
Summary: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.
ISSN:2078-2489