High resolution spatial inventory of GHG emissions emissions from stationary and mobile sources in Poland: summarized results and uncertainty analysis

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/32618 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/32618 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/32618 archive 353 disk0/00/01/18/86 2016-02-10 11:54:58 2021-08-27 17:25:51 2016-02-10 11:54:58 book_section show 1 Bun R. Nahorski Z. Horabik-Pyzel J. Danylo O. 8670 Charkovska N. Topylko P. Halushchak M. 8746 Lesiv M. 8477 0000-0001-9846-3342 Striamets O. High resolution spatial inventory of GHG emissions emissions from stationary and mobile sources in Poland: summarized results and uncertainty analysis pub prog_esm prog_asa 4th International Workshop on Uncertainty in Atmospheric Emissions Greenhouse gases (GHG) inventories at national or regional levels include the total emissions and emissions for many categories of economic activity. The aim of our research is to analyze the high resolution spatial distributions of emissions for all categories of economic activity in Poland. GHG emission sources are classified into point-, line- and area-type sources. We created maps of such sources for all categories of economic activities covered by IPCC Guidelines, using official information of companies, administrative maps, Corine Land Cover maps, and other available data. The worst resolution is for area-type sources (100 m). We used statistical data at the lowest level as possible (regions, districts, and municipalities). We created the algorithms for these data disaggregation to the level of elementary objects for GHG spatial inventory. These algorithms depend on category of economic activity and cover all categories under investigation. We analyzed emissions of CO2, CH4, N2O, SO2, NMVOC, and others, and we calculated the total emissions in CO2-equivalent. We used a grid to calculate the summarizing emissions from the all categories. The grid size depends on the aim of spatial inventory, but it can't be less than 100 m. For uncertainty analysis we used uncertainty of statistical data, uncertainty of calorific values, and uncertainty of emission factors, with symmetric and asymmetric (lognormal) distributions. On this basis and using Monte-Carlo method the 95% confidence intervals of results' uncertainties were estimated for big point-type emission source, the regions, and the subsectors. 2015 published Systems Research Institute, Polish Academy of Sciences http://www.ibspan.waw.pl/unws2015/index.php?go=presentations 59 1309 181 public paper Warsaw, Poland 41-48 4th International Workshop on Uncertainty in Atmospheric Emissions Cracow, Poland 7-9 October 2015 workshop FALSE 83-894-7557-X Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland FALSE no info:eu-repo/semantics/bookPart