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Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

机译:从固定式和移动来源开发波兰温室气体排放的高分辨率空间清单

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Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO2, CH4, N2O, SO2, NMVOC) as well as total emissions in the CO2-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.
机译:国家或省级水平的温室气体(GHG)库存包括总排放以及许多人类活动类别的排放,但需要空间明确的温室气体排放库存。因此,本研究的目的是概述一种用于在波兰展示的高分辨率空间显式排放库存的方法。温室气体排放来源被分为点,线和面积类型,然后组合以计算总排放量。我们创建了IPCC指南所涵盖的所有类别的各类经济活动的传染媒介地图,使用有关公司,行政地图,冠路盖和其他可用数据的官方信息。我们创建了将这些数据的分解到诸如发射源等基本对象的级别的算法。使用的算法取决于调查中经济活动的类别。我们计算了碳,氮硫和其他温室气体化合物的排放(例如,CO 2,CH 4,N 2 O,SO2,NMVOC)以及CO 2当量的总排放。仅在最后阶段创建网格数据,以呈现来自所有类别的非常多样化的源的总结排放。在我们的方法中,保留了有关相应排放来源行政分配的信息,这使得最终结果可以将最终结果汇总到包括市内的不同行政水平,这是使用传统的网格排放方法无法实现的。我们证明可以选择任何网格尺寸以匹配空间库存的目的,但在该示例中不小于100米,这对应于输入数据集的典雅分辨率。然后,我们考虑了统计数据,热值和排放因子的不确定性,具有对称和不对称(Lognormal)分布。使用Monte Carlo方法,使用95%置信区间表示的不确定性,估计高点型排放来源,省份和分部。这样的方法是灵活的,只要数据可用,并且可以应用于其他国家。

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