Effect of fire spread, flame characteristic, fire intensity on particulate matter 2.5 released from surface fuel combustion of Pinus koraiensis plantation– A laboratory simulation study

• Published in: Environment international 2022-08, Vol.166, p.107352-107352, Article 107352
• Main Authors: Ning, Jibin, Yang, Guang, Liu, Xinyuan, Geng, Daotong, Wang, Lixuan, Li, Zhaoguo, Zhang, Yunlin, Di, Xueying, Sun, Long, Yu, Hongzhou
• Format: Article
• Language: English
• Subjects: Fire behavior; Forest combustion; Pinus koraiensis; PM2.5; Random Forest
• ISSN: 0160-4120; 1873-6750
• DOI: 10.1016/j.envint.2022.107352

[Display omitted] PM2.5 is one of major pollutants emitted from forest fires. High PM2.5 concentration not only affects short-term human respiration health, but also poses a long-term threat to human cardiopulmonary functionality. Therefore, it is of great importance to quantitatively assess the PM2.5 released by forest combustion in forest fire studies. In this study we examine relationships between the PM2.5 concentration and environment and fuel characteristics laboratory experiments. In the experiments, fuel beds with controlled moisture contents and loads were first built; then 144 ignition experiments were conducted for various combinations of wind speeds using a wind tunnel device. Fire behavior characteristics and PM2.5 concentrations released from fuel combustion were measured and analyzed. The experimental results show that the relationship between fire characteristics, fire intensity and the influencing factors of wind speed, fuel moisture content, and fuel load can be explained by the fundamental theory of forest combustion. Although PM2.5 concentration rises with the increase of wind speed, the decrease of fuel moisture content, and the increase of fuel load, there appears to be a fuel load threshold for a given combination of wind speed and fuel moisture content that the increase of PM2.5 concentration decelerates quickly after the load passes the threshold value. After screening fire behavior characteristics that affect PM2.5 concentration, we found that fire line intensity and flame width are the ones with the strongest association with the concentration. With flame width as independent variable, we have built two regression models to predict PM2.5 and fire line intensity which are treated as dependent variable; the models have high accuracy with R2 = 0.92 for predicting PM2.5 and R2 = 0.97 for predicting fire line intensity. Study results can be used as reference to protect the health of forest fire fighters, and can be helpful for forest fire smoke management.