Influencing factors of PM_2.5 emissions under the surface needle combustible combustion of Korean pine plantations

ObjectiveThis paper aims to study the contribution of forest fire to PM_2.5 in atmospheric environment, and to analyze the changing characteristics of PM_2.5 under different fire environment, so as to provide a basis for forest fire particle matter emission pollution.

MethodFuel beds composed of pine needles collected from Korean pine plantations were constructed with varied loading and fuel moisture contents. The mass concentration of PM_2.5 was monitored using the tape of 2050 intelligent integrated sampler for air/TSP in the course of 192 burning experiments under varied wind speeds.

ResultThe mass concentration of PM_2.5 varied from 166.7 to 7516μg/m³. And the influence of various factors on PM_2.5 was in the order of forest fuel load > wind speed > moisture content. ANOVA showed that in addition to the moisture content, forest fuel load as well as wind speed were correlated significantly (P < 0.05) with PM_2.5 mass concentration, and there was a significant interaction between forest fuel load and wind speed (P < 0.05). Using forest fuel load and wind speed to match the prediction model of PM_2.5 mass concentration, it could accounted for 77% of the variance in PM_2.5 mass concentration.

ConclusionBurning pine needles have significant effects on particulate pollution in the atmosphere. The response degree of PM_2.5 mass concentration to fuel moisture content, fuel load and wind speed exist significant differences. PM_2.5 mass concentration with fuel load and wind speed have significant positive correlations. However, there is no manifest relation between PM_2.5 mass concentration and fuel moisture content. The prediction model about PM_2.5 mass concentration has high precision, which uses fuel load and wind speed as forecast factors. It can be the basic theory for estimating PM_2.5 mass concentration emitted in forest fire.