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Can we get rid of uncertainties in GHG inventories?

机译:我们可以摆脱温室气体库存的不确定性吗?

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Uncertainties in typical GHG emission inventories are dominated by the contribution from the non-CO_2 gases. The sources of these gases can be complex and emissions variable in space and time and the estimates can contain large systematic errors due to lack of knowledge. The available data indicate that the uncertainty in overall emission level can be highly influenced by the uncertainty in nitrous oxide from agricultural soils. The trend uncertainty can be influenced by gases where the emission level is changing rapidly, even if their contribution to total emissions is small, e.g. HFCs and N_2O from road transport. The uncertainty in emission inventories can be estimated by methodologies at different levels of sophistication. While simple error propagation can be used to roughly assess the uncertainty in emission level, the trend uncertainty needs to be modelled, taking into account correlations between parameters in the base and end year. Both these methodologies require assessments of the uncertainties in individual parameters. These are often based on expert judgments and may be rather subjective. This means that uncertainty estimates of inventories not necessarily are comparable. The typical uncertainty in the total emission level of high quality inventories is higher than desired for scientific and policy use of inventories, more than 10 % (excluding LUCF). The few available studies indicate that the trend uncertainty can be higher than desired for assessing compliance with the Kyoto protocol, about 4-5 percentage points. It is expected that the uncertainty of emission estimates from individual sources can be reduced in the future by better scientific knowledge and improvements in inventory methodologies. In most inventories the gain is highest by reducing the uncertainty of the non-CO_2 gases. This will reduce the overall uncertainty in emission level, but only to some extent the uncertainty in the trend.
机译:典型的温室气体排放库存的不确定性是由非CO_2气体的贡献为主。这些气体的来源可以是复杂的,并且空间和时间的排放变量,并且由于缺乏知识,估计可以包含大量的系统误差。可用数据表明整体排放水平的不确定性可以受到来自农业土壤中氧化氮的不确定性的影响。趋势不确定性可能受到排放水平迅速变化的气体的影响,即使它们对总排放的贡献很小,例如,也是如此。公路运输的HFCS和N_2O。排放清单中的不确定性可以通过不同程度的复杂性的方法估算。虽然可以使用简单的错误传播来大致评估发射水平的不确定性,但需要建模趋势不确定性,以考虑基本年份和结束年度的参数之间的相关性。这两种方法都需要评估个别参数的不确定性。这些通常基于专家判断,并且可能是非常主观的。这意味着对库存不一定是可比性的不确定性估计。高质量清单总排放水平的典型不确定性高于库存和对库存的科学和政策使用,超过10%(不包括Lucf)。少数可用研究表明,评估京都议定书遵守约4-5个百分点,趋势不确定度可能高于期望。预计,未来可以通过更好的科学知识和库存方法的改进,减少来自个别来源的排放估计的不确定性。在大多数库存中,通过降低非CO_2气体的不确定性,增益最高。这将减少排放水平的总体不确定性,但只在某种程度上只是趋势的不确定性。

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