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

Ning, Jibin; Yang, Guang; Liu, Xinyuan; Geng, Daotong; Wang, Lixuan; Li, Zhaoguo; Zhang, Yunlin; Di, Xueying; Sun, Lei; Yu, Huan

doi:10.1016/j.envint.2022.107352

Cited by 7 publications

(2 citation statements)

References 79 publications

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“…The fuel moisture content was set to 5, 10, and 15%, for a total of three levels, to maintain the fuel in the open flame combustion condition. The dry fuel weight and moisture needed for various fuel loads and moisture contents were calculated using the fuel moisture content calculation formula (Ning et al 2022). The quantitative moisture was then quickly and evenly sprayed onto the fuel surface using a spray bottle and then immediately transferred to a sealed box for 24 h to allow the moisture to be fully absorbed.…”

Section: Fuel Pre-treatmentmentioning

confidence: 99%

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Geng,

Yang,

Ning

et al. 2024

Int. J. Wildland Fire

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Background The prediction accuracy for the rate of surface fire spread varies in different regions; thus, increasing the prediction accuracy for local fuel types to reduce the destructive consequences of fire is critically needed. Aims The objective of this study is to improve the Rothermel model’s accuracy in predicting the ROS for surface fuel burning in planted forests of Pinus koraiensis in the eastern mountains of north-east China. Methods Fuel beds with various fuel loads and moisture content was constructed on a laboratory burning bed, 276 combustion experiments were performed under multiple slope conditions, and the ROS data from the combustion experiments were used to modify the related parameters in the Rothermel model. Results The surface fire spread rate in Pinus koraiensis plantations was directly predicted using the Rothermel model but had significant errors. The Rothermel model after modification predicted the following: MRE = 25.09%, MAE = 0.46 m min−1, and R2 = 0.80. Conclusion The prediction accuracy of the Rothermel model was greatly enhanced through parameter tuning based on in-lab combustion experiments Implications This study provides a method for the local application of the Rothermel model in China and helps with forest fire fighting and management in China.

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Section: Fuel Pre-treatmentmentioning

confidence: 99%

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Geng,

Yang,

Ning

et al. 2024

Int. J. Wildland Fire

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“…In the city of Guanajuato, characterized by a semiwarm and temperate climate type, wildfires typically occur during dry periods, and the warm periods occur in March, April, and May (Barret & Esquivel, 2013;Farfán et al, 2021;Pérez-Verdin et al, 2013). The extent and intensity of a wildfire are directly influenced by vegetation types, weather conditions, and the amount of fuel consumed per unit of the area (Ning et al, 2022;Petrie et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Effects of meteorological variables and dry seasonal months on PM2.5 concentration in non-industrial cities: the case of Guanajuato city

Zamorategui Molina,

Delgado Galván,

Villalobos Pérez

et al. 2024

Acta Universitaria

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Annual, seasonal, and monthly average variations in PM2.5 concentration were analyzed in relation to meteorological parameters and recorded wildfires in the city of Guanajuato from 2016 to 2020. The annual variations in average PM2.5 concentration exhibited a direct relationship between temperature and wind speed, with averages of 12.5 and 12.7, slightly exceeding the maximum allowed limits in 2019 and 2020, respectively. Seasonal average variations in PM2.5 concentration showed an inverse relationship with wind speed, precipitation, and relative humidity. Anthropogenic wildfires occurring during warm-dry months were positively related to the increase in PM2.5 concentrations. Low PM2.5 concentrations were found to be related to periods of high wind speed, high precipitation, and high relative humidity.

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Smoke exposure levels prediction following laboratory combustion of Pinus koraiensis plantation surface fuel

Ning

Yang

Zhang

et al. 2023

Science of The Total Environment

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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

Cited by 7 publications

References 79 publications

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Modification of the Rothermel model parameters – the rate of surface fire spread of Pinus koraiensis needles under no-wind and various slope conditions

Effects of meteorological variables and dry seasonal months on PM2.5 concentration in non-industrial cities: the case of Guanajuato city

Smoke exposure levels prediction following laboratory combustion of Pinus koraiensis plantation surface fuel

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