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Investigating uncertainties in trace gas emissions from boreal forest fires using MOPITT measurements of carbon monoxide and a global chemical transport model.

机译:使用MOPITT对一氧化碳的测量和全球化学传输模型,调查北方森林大火产生的微量气体排放的不确定性。

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Boreal forest fires are a significant contributor to atmospheric composition in the high northern hemisphere, and are highly variable both spatially and temporally. This study uses a new emissions model [Kasischke et al. , 2005] to generate input to the University of Maryland Chemical Transport Model [Allen et al., 1996], with the goal of examining and constraining the key uncertainties in current understanding of boreal forest fire behavior. Model outputs are compared with data from the MOPITT instrument as well as in situ measurements of CO. A case study of CO transport during the summer of 2000 is used to examine several key uncertainties in the emissions estimates, describing how current levels of uncertainty affect atmospheric composition and applying atmospheric measurements can be applied to constrain uncertainty. Source magnitudes determined by inverse methods were shown to be highly sensitive to the assumed injection properties. For the boreal forest in 2000, the best agreement with observations was obtained with a pressure-weighted profile of injection throughout the tropospheric column, but detailed examination of the results makes clear that any uniform parameterization of injection will be a significant source of error when applied globally. Comparison of simulated CO distributions from daily, weekly, and monthly aggregate emissions sources demonstrated that while model data sources produced a valid representation of emissions at weekly resolution, the atmospheric distribution outside the source region has very little sensitivity to temporal variability at scales finer than 30 days. Different estimates of burned area produced large differences in simulated patterns of atmospheric CO. The GBA-2000 global product and the data sources used by Kasischke et al. [2005] gave better agreement with atmospheric observations compared to the GLOBSCAR product. Comparison of different estimates of fuel consumption indicated that atmospheric measurements of CO have limited sensitivity to spatial variability in fuels, but that current fuels maps can improve agreement with atmospheric measurements. These results provide a clear indication of how atmospheric measurements can be used to test hypotheses generated by emissions models.
机译:北方森林火灾是北半球高空大气组成的重要因素,并且在空间和时间上变化很大。这项研究使用了新的排放模型[Kasischke等。 (2005年),以向马里兰大学化学运输模型[Allen等人,1996年]生成输入,目的是检验和限制当前对北方森林火灾行为的认识中的主要不确定性。将模型输出与来自MOPITT仪器的数据以及一氧化碳的现场测量结果进行了比较。以2000年夏季一氧化碳运输为例,研究了排放估算中的几个关键不确定性,描述了当前不确定性水平如何影响大气组成和应用大气测量值可用于约束不确定性。通过反演方法确定的震源幅度显示出对假定的注入特性高度敏感。对于2000年的北方森林,对流层中整个注入过程均采用压力加权的注入曲线,获得了与观测值的最佳一致性,但是对结果的详细检查表明,如果采用统一的注入参数化方法,则将成为重要的误差来源。全球。对来自每日,每周和每月总排放源的模拟CO分布的比较表明,尽管模型数据源以周分辨率有效地表示了排放量,但在小于30的尺度上,源区域以外的大气分布对时间变化的敏感性很小。天。不同的燃烧面积估计值在大气CO的模拟模式上产生了很大差异。GBA-2000全球产品和Kasischke等人使用的数据源。 [2005]与GLOBSCAR产品相比,它与大气观测结果具有更好的一致性。比较不同的燃料消耗估计值表明,大气中一氧化碳的测量对燃料空间变异性的敏感性有限,但是当前的燃料图可以改善与大气测量的一致性。这些结果清楚地表明了大气测量如何用于测试排放模型产生的假设。

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