Analysis of forest fire dangers of the Bryansk region in the zones of radioactive contamination and beyond

The purpose of the study is to analyze the forest fire dangers of the Bryansk region forests, taking into account their radioactive contamination and potential risks for forestry workers involved in forest fires extinguishing. Significant areas of radioactive contamination of forests with a predominance of sites belonging to the classes of high and very high natural fire danger, restrictions on economic activity and a long fire-hazardous period contribute to the occurrence of radioactive forest fires. The analysis of the combined data on forest fires and radioactive contamination of forest areas showed that most forest fires occur outside the zones of radioactive contamination and are not radioactive. The largest number of fires occurs at the beginning of the fire season. Radioactive forest fires in most cases arise from the burning of dry grassy vegetation, as a result of the transition from lands of other categories and through the fault of the population. The average effective dose of additional radiation per a workday can be estimated at 1.96 μSv, and the maximum at ~ 15.4 μSv. Most fires are extinguished in the early stages and do not have time to cover large areas. It indicates the effective work of the forest fire service

Authors

Institutions

Publication Details

Journal
Radiacionnaâ gigiena
Published
2024-10-07
DOI
https://doi.org/10.21514/1998-426x-2024-17-3-133-141
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of forest fire dangers of the Bryansk region in the zones of radioactive contamination and beyond

А. И. Радин, А. Н. Раздайводин, T. A. Marchenko
Radiacionnaâ gigiena
Fire effects on ecosystems
article

Analysis of forest fire dangers of the Bryansk region in the zones of radioactive contamination and beyond

А. И. Радин, А. Н. Раздайводин, T. A. Marchenko
article en

Abstract

The purpose of the study is to analyze the forest fire dangers of the Bryansk region forests, taking into account their radioactive contamination and potential risks for forestry workers involved in forest fires extinguishing. Significant areas of radioactive contamination of forests with a predominance of sites belonging to the classes of high and very high natural fire danger, restrictions on economic activity and a long fire-hazardous period contribute to the occurrence of radioactive forest fires. The analysis of the combined data on forest fires and radioactive contamination of forest areas showed that most forest fires occur outside the zones of radioactive contamination and are not radioactive. The largest number of fires occurs at the beginning of the fire season. Radioactive forest fires in most cases arise from the burning of dry grassy vegetation, as a result of the transition from lands of other categories and through the fault of the population. The average effective dose of additional radiation per a workday can be estimated at 1.96 μSv, and the maximum at ~ 15.4 μSv. Most fires are extinguished in the early stages and do not have time to cover large areas. It indicates the effective work of the forest fire service

Radiacionnaâ gigienaVol. 17(3)
Ministry of Emergency Situations (RU), Bauman Moscow State Technical University (RU), Institute of Forestry (RS), Research Institute of Forestry (CN), All-Russian Research Institute for Silviculture and Mechanization of Forestry (RU)
Life in Land
Openalex Percentile: Top 84%
Fire effects on ecosystems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.