Spatial distribution of particulate matter 2.5 released from surface fuel combustion of Pinus koraiensis - A laboratory simulation study.

High concentration particulate matter 2.5 released from forest fires, in addition to direct burns and asphyxia, PM2.5 is one of the main pollutants which threaten the safety of forest fire fighter. Therefore, to assess spatial distribution of PM2.5, a simulation study was conducted. Fuel beds with different moisture contents and loads were constructed. 144 times burning experiments were carried out under different wind speeds by using wind tunnel device. PM2.5 particles at different spatial points were collected and calculated. The results show that, in the two of three variables interaction between wind speed, fuel load, and, except fuel moisture content, wind speed and fuel load are positively correlated with the PM2.5 concentrations. From PM2.5 concentration which collected at each point in the horizontal and vertical directions, the overall trend is that PM2.5 concentration increases along the horizontal downwind direction (C and D higer than A and B) and the vertical upward direction (A and C higer than B and D) Based on BP neural network, the spatial distribution model of PM2.5 concentration with single hidden layer was established. The prediction accuracy of modeling samples and validation samples is balanced when hidden layer node is 5. This study will help to make reference for PM2.5 occupational exposure standards, forest fire smoke management and forest fire management in China.