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    红松人工林地表针叶可燃物燃烧PM2.5排放影响因子

    Influencing factors of PM2.5 emissions under the surface needle combustible combustion of Korean pine plantations

      摘要
    • 摘要:
      目的为研究森林火灾对大气环境中PM2.5的贡献量, 分析不同火环境下地表可燃物排放PM2.5的变化特征, 以期为森林火灾排放颗粒物污染提供依据。
      方法本实验以帽儿山地区红松人工林地表针叶可燃物为研究对象, 铺设不同可燃物载量和可燃物含水率组合方式的可燃物床层, 基于燃烧风洞实验室进行点烧实验192次, 并利用崂应2050型智能空气/TSP综合采样器定量测量不同风速条件下可燃物燃烧释放烟气中细颗粒污染物(PM2.5)浓度。
      结果在可燃物载量、可燃物含水率和风速的共同作用下, PM2.5质量浓度值有很大的变化区间, 最小值为166.7μg/m3, 最大值为7516μg/m3。各因子对PM2.5质量浓度的影响差异较明显, 从大到小的顺序为:可燃物载量＞风速＞可燃物含水率。通过多因素方差分析表明, 可燃物含水率与PM2.5质量浓度没有明显的相关性(P＞0.05), 可燃物载量和风速与PM2.5质量浓度相关关系显著(P＜0.05), 且可燃物载量与风速存在显著的交互作用(P＜0.05)。以双因素模型拟合PM2.5质量浓度预测模型, 可燃物载量和风速共同解释77%的PM2.5质量浓度变差。
      结论红松针叶燃烧对大气颗粒物污染有明显的贡献作用。PM2.5质量浓度对可燃物含水率、可燃物载量和风速的响应程度存在明显差异, 与可燃物载量和风速呈显著正相关, 与可燃物含水率关系不明显。本研究以可燃物载量和风速为预报因子构建的PM2.5质量浓度预测模型具有较高的精准度, 可以为估算森林火灾排放PM2.5质量浓度提供理论基础。

       

      Abstract:
      ObjectiveThis paper aims to study the contribution of forest fire to PM2.5 in atmospheric environment, and to analyze the changing characteristics of PM2.5 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 PM2.5 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 PM2.5 varied from 166.7 to 7516μg/m3. And the influence of various factors on PM2.5 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 PM2.5 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 PM2.5 mass concentration, it could accounted for 77% of the variance in PM2.5 mass concentration.
      ConclusionBurning pine needles have significant effects on particulate pollution in the atmosphere. The response degree of PM2.5 mass concentration to fuel moisture content, fuel load and wind speed exist significant differences. PM2.5 mass concentration with fuel load and wind speed have significant positive correlations. However, there is no manifest relation between PM2.5 mass concentration and fuel moisture content. The prediction model about PM2.5 mass concentration has high precision, which uses fuel load and wind speed as forecast factors. It can be the basic theory for estimating PM2.5 mass concentration emitted in forest fire.

       

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