Welcome to visit Scientia Silvae Sinicae,Today is

Scientia Silvae Sinicae ›› 2022, Vol. 58 ›› Issue (3): 97-106.doi: 10.11707/j.1001-7488.20220311

Previous Articles     Next Articles

Quality and Influencing Factors of Particulate Matter Released by Surface Fuel Combustion in Korean Pine Plantation

Xinyuan Liu,Guang Yang*,Jibin Ning,Daotong Geng,Hongzhou Yu,Xueying Di   

  1. School of Forestry, Northeast Forestry University Key Laboratory of Sustainable Forest Ecosystem Management of Ministry of Education Harbin 150040
  • Received:2021-02-05 Online:2022-03-25 Published:2022-06-02
  • Contact: Guang Yang

Abstract:

Objective: Based on the indoor burning experiment carried out in the combustion wind tunnel laboratory, the particle size distribution and variation characteristics of the particulate matter released by surface fuel combustion in Korean pine plantation were quantitatively revealed, which would provide reference for the particulate matter released by forest fire. Method: The Korean pine plantation in the eastern mountainous area of Northeast China was selected as the object, and the fuel bed with different wind speed, fuel load and fuel moisture content was constructed. Based on 108 ignition experiments in the combustion wind tunnel laboratory, real-time monitoring was carried out by using the dissolved aerosol monitor (TSI Dust Trak 8533, USA), and random forest algorithm was used to establish a prediction model for particles of different sizes. Result: Wind speed was one of the most important factors affecting the mass of the four particle matter sizes. PM1 was most affected by wind speed (37.207%) and temperature (25.651%), and was least affected by fuel moisture content (8.304%); PM2.5 was most affected by wind speed (43.293%) and fuel load (22.855%), and was least affected by combustion efficiency (7.509%); PM4 was the most affected by wind speed (43.552%) and fuel load (21.225%), and was least affected by fuel moisture content (6.841%); PM10 was most affected by wind speed (40.832%) and fuel load (23.337%), and was least affected by fuel moisture content (6.946%). The R2 of prediction models for PM1、PM2.5、PM4、PM10 based on the random forest algorithm were 0.804, 0.810, 0.806 and 0.812, respectively. Conclusion: The mass of particulate matter is positively correlated with wind speed, fuel load, fuel moisture content, and combustion efficiency (>80%), and negatively correlated with temperature and relative humidity. In general, the random forest algorithm can be used to better analyze the complex relationships between various variables and the mass of particulate matter. The observed range of particulate matter released from surface fuel combustion in Korean pine plantation is 1.72-56.04 g, and the predicted range is 5.67-36.33 g, which provides a data basis for the establishment of pollution source emission inventories and occupational exposure standards for fire-fighting practitioners.

Key words: Korean pine plantation, combustion, particulates, wind speed, random forest

CLC Number: