Spatial GHG inventory at the regional level: accounting for uncertainty

Bun, Rostyslav; Hamal, K.; Gusti, M.; Bun, A.

doi:10.1007/s10584-010-9907-5

Cited by 34 publications

(10 citation statements)

References 9 publications

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“…For emissions of CH4 and N2O, we estimate uncertainties of 32% and 42%, respectively, for 24OECD90 countries and 57% and 93% for the other countries. These are based on the default uncertainty estimates of IPCC (2006) and in line with Bun et al (2010). Observation-based verification of European CH4 and N2O emissions using inverse modelling (e.g.…”

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confidence: 99%

EDGAR v4.3.2 Global Atlas of the three major Greenhouse Gas Emissions for the period 1970–2012

Janssens-Maenhout

Crippa

Guizzardi³

et al. 2017

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2 use, land-use change and forestry (LULUCF) sector (including forest and savannah burning). Unlike the activities of the LULUCF sector, which are typically estimated top-down from less certain land-use observations, all these activities are estimated bottom-up from standard annual statistics of fuel, products, waste, crops or livestock. We present country-specific emission totals and analyse the trends and variations in emissions of the largest emitting countries together with the EU in more detail, to uncover the effect of changes in human 5 activities with time on each of the gases. The GWP-100 weighted global total GHG emission trend is predominantly determined by the global CO2 trend and in particular, by fuel markets trends, geopolitical changes and financial crises rather than population changes. We also evaluate the uncertainty in emissions for different sectors and three groups of countries (the OECD countries of 1990, the countries with economies in transition in 1990 and the remaining non-Annex I countries). Even though large progress has been made on emission 10 inventory compilation, the uncertainty in global total GHG emissions has not decreased, because of the increasing share of emissions from countries with less developed statistical infrastructure and secondly the decreasing share of emissions from the activities (e.g. coal power plants) for which relatively accurate information is available. Finally, we discuss changes in geospatial distribution with a focus on hot spots and megacities using gridded information. Data is presented online for each source category with annual and monthly 15 global emissions grid-maps of 0.1x0.1 resolution and can be freely accessed from the EDGAR website

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confidence: 99%

EDGAR v4.3.2 Global Atlas of the three major Greenhouse Gas Emissions for the period 1970–2012

Janssens-Maenhout

Crippa

Guizzardi³

et al. 2017

Preprint

123

115

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“…In order to model the influence of CH 4 emissions on atmospheric concentrations, spatially explicit inventories are needed in addition to total national emissions (Bun et al, 2010). To disaggregate emissions to a higher spatial resolution, detailed knowledge of the location and the activity of each source is required, leading to additional uncertainty (Ciais et al, 2010).…”

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Anthropogenic and natural methane fluxes in Switzerland synthesized within a spatially explicit inventory

et al. 2014

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Abstract. We present the first high-resolution (500 m × 500 m) gridded methane (CH 4 ) emission inventory for Switzerland, which integrates 90 % of the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH 4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH 4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH 4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process-or area-specific emission factors. In Switzerland, the highest CH 4 emissions in 2011 originated from the agricultural sector (150 Gg CH 4 yr −1 ), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH 4 yr −1 ) mainly from landfills and the energy sector (12 Gg CH 4 yr −1 ), which was dominated by emissions from natural gas distribution. Compared with the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH 4 yr −1 ), making up only 3 % of the total emissions in Switzerland. CH 4 fluxes from agricultural soils were estimated to be not significantly different from zero (between −1.5 and 0 Gg CH 4 yr −1 ), while forest soils are a CH 4 sink (approx. −2.8 Gg CH 4 yr −1 ), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and an European (TNO/MACC) CH 4 inventory. This new spatially explicit emission inventory for Switzerland will provide valuable input for regional-scale atmospheric modeling and inverse source estimation.

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“…It is recommended that these tools are used when national GHG inventories are being conducted. However, as shown by Bun et al (2010), these are too general and in many cases too simplified to reflect reality, resulting in a GHG inventory that is perceptibly different from "the truth." This inaccuracy adds to the inventory's inherent uncertainty, which results from imprecision.…”

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Verification of compliance with GHG emission targets: annex B countries

et al. 2010

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The focus of this study is on the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. Preparatory signal detection is a measure that should be taken prior to/during negotiation of the Protocol. It allows the ranking of countries under the Protocol according to their realized versus their agreed emission changes and in terms of both certainty and credibility. Controlling GHGs is affected by uncertainty and may be costly. Thus, knowing whether each nation is doing its part is in the public interest. At present, however, countries to the United Nations Framework Convention on Climate Change (UNFCCC) are obliged to include in the reporting of their annual inventories direct or alternative estimates of the uncertainty associated with these, consistent with the Intergovernmental Panel on Climate Change's (IPCC) good practice guidance reports. As a consequence, inventory uncertainty is monitored, but not regulated, under the Kyoto Protocol. Although uncertainties are becoming increasingly available, monitored emissions and uncertainties are still dealt with separately. In our study we analyze estimates of both emission changes and uncertainties to advance the evaluation of countries and their performance under the Protocol. Our analysis allows supply and demand of emissions credits to be examined in consideration of uncertainty. For the purpose of our exercise, we make use of the Undershooting and Verification Time concept described by Jonas et al. (Clim Change

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Spatial GHG inventory at the regional level: accounting for uncertainty

Cited by 34 publications

References 9 publications

EDGAR v4.3.2 Global Atlas of the three major Greenhouse Gas Emissions for the period 1970–2012

EDGAR v4.3.2 Global Atlas of the three major Greenhouse Gas Emissions for the period 1970–2012

Anthropogenic and natural methane fluxes in Switzerland synthesized within a spatially explicit inventory

Verification of compliance with GHG emission targets: annex B countries

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