732 research outputs found
The Kyoto Policy Process in Perspective: Long-term Concentration Targets versus Short-term Emissions
Greenhouse gas emissions are believed to be the main reason of climate change. Thus, it is essential to limit and reduce emissions of greenhouse gases in order to stabilize climate. Short-term policies such as the Kyoto Protocol stipulate emission limitation or reduction commitments. However, it is also, if not more, important to keep an eye on the long-term effects of these policies since it takes decades to centuries to manifest the consequences of greenhouse gas emissions. And vice versa: it is a problem to translate long-term targets to near-term commitments that will allow reaching the given target.
This study is meant to serve as a vision paper. Building upon the preparatory detection of emission changes (emission signals) under the Kyoto Protocol, it addresses the problem of correcting allowable mid-term emission windows that have been suggested to link short-term emission commitments with long-term concentration targets. Correction of the emission windows accounts for our inappropriate knowledge of emissions at the scale of countries and the risk that true (unknown) emissions can exceed observed emissions. Not considering this risk can result in excluding low concentration targets in the long-term; that is, climate stabilization at a level that is not dangerous
Preparatory Signal Detection for the EU-25 Member States Under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2003)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004a), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex I countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and (total) uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal detection techniques and applied these to the Annex I countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex I countries comply with their committed emission targets in 2008-2012. The emissions path between the base year and commitment year/period is generally assumed to be a straight line, and the path of historical emissions is not taken into consideration.
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the old and new Member States of the European Union (EU). In contrast to the earlier study, the Member States' committed emission targets under the EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' committed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2003.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment; and (ii) the detectability of its target. Undershooting the committed EU target or EU-compatible, but detectable, target can decrease this risk. The Member States' linear path undershooting targets for the year 2003 are contrasted with their actual emission situation in that year, for which the distance-to-target indicator (DTI) is employed that has been introduced by the European Environment Agency.
In 2003 eleven EU-25 Member States exhibit a negative DTI and thus appear as potential sellers: Czech Republic, Estonia, France, Germany, Hungary, Lithuania, Latvia, Poland, Sweden, Slovakia and the UK. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5-10% and above rather than below excluding LUCF and Kyoto mechanisms, the Member States require considerable undershooting of their EU-compatible, but detectable, targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period are above their true EU reference lines. As of 2003, these conditions can only be met by seven new and two old Member States (ranked in terms of credibility): Lithuania, Latvia, Estonia, Poland, Hungary, Slovakia, Czech Republic, Germany and the United Kingdom, while two old Member States, France and Sweden, can only act as potential high-risk sellers. The other EU-25 Member States do not meet their linear path (base year--commitment year) undershooting targets in 2003, or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the linear path 2008/12 emission signal of the old EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to nondetectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
The value of observations for reduction of earthquake-induced loss of life on a global scale
Earthquakes on global scale cause considerable losses both in terms of economic impact and human lives. A proper coordination of disaster response activities requires observation of affected areas for evaluation of spatial distribution of damage. We use several freely available datasets including global seismic hazard assessment, data on population, gross domestic product, and urban areas to calculate expected loss of life based on rescue efficiency derived from an optimal rescue resource distribution model, which by design includes the observation capacity as a parameter. Despite of the high practical importance, the quantification of the "observation quality -- reduction of loss of life" relationship has not yet been performed for earthquakes on a global scale. Our validated quantitative results show that better Earth observations may potentially contribute to a global reduction of earthquake induced loss of life within the range 20%-90% from the "business as usual" level
Preparatory Signal Detection for the EU-27 Member States Under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2006)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration. An in-depth quantitative comparison of the four, plus two additional, preparatory signal analysis techniques has been prepared by Jonas et al. (2010).
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the study by Jonas et al. (2004), the Member States. agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2006.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition. Undershooting the agreed target or the compatible but detectable target can decrease this risk. The Member States' undershooting options and challenges as of 2006 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) initially introduced by the European Environment Agency. This indicator measures by how much the emissions of a Member State deviate from its linear emissions path between base year and target year.
In 2006 thirteen EU-27 Member States exhibit a negative DTPI (not counting Belgium with a DTPI ~= 0) and thus appear as potential sellers: Bulgaria, the Czech Republic, Estonia, France, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Sweden and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5.10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible but detectable targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2006, these conditions can only be met by ten (nine new and one old) Member States (ranked in terms of credibility): Estonia, Latvia, Lithuania, Bulgaria, Romania, Slovakia, Hungary, Poland, the Czech Republic and the United Kingdom; while three old Member States, Germany, Sweden and France, can only act as potential sellers with a higher risk. The other EU-27 Member States do not meet their linear path (base year--commitment year) undershooting targets as of 2005 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the 2008/12 emission reduction of the EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
Preparatory Signal Detection for the EU-27 Member States Under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2007)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration. An in-depth quantitative comparison of the four, plus two additional, preparatory signal analysis techniques has been prepared by Jonas et al. (2010).
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the study by Jonas et al. (2004), the Member States' agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2007.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition. Undershooting the agreed target or the compatible but detectable target can decrease this risk. The Member States' undershooting options and challenges as of 2007 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) initially introduced by the European Environment Agency. This indicator measures by how much the emissions of a Member State deviate from its linear emissions path between base year and target year.
In 2007, fourteen EU-27 Member States exhibit a negative DTPI and thus appear as potential sellers: Belgium, Bulgaria, Czech Republic, Estonia, France, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Sweden, and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5-10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible but detectable targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2007, these conditions can only be met by ten (nine new and one old) Member States (ranked in terms of credibility): Latvia, Lithuania, Estonia, Romania, Bulgaria, Slovakia, Hungary, Poland, the Czech Republic and the United Kingdom; while four Member States, Germany, Belgium, Sweden and France, can only act as potential sellers with a higher risk. The other EU-27 Member States do not meet their linear path (base year-commitment year) undershooting targets as of 2007 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the 2008/12 emission reduction of the EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ ПРОСТОРОВОЇ ІНВЕНТАРИЗАЦІЇ ПАРНИКОВИХ ГАЗІВ У ЕНЕРГЕТИЧНОМУ СЕКТОРІ СІЛЕЗЬКОГО ВОЄВОДСТВА
GIS technology of spatial inventory of greenhouse gases (carbon dioxide, methane, etc.) in the energy sector of Silesia Region in Poland has been presented. Georeferenced databases, GIS software, and international inventory methodologies have been used. The mathematical models for inventory of carbon dioxide, methane and other greenhouse gases during the combustion of fuel in the production of electricity, in the residential sector, industry, construction, and transport have beencreated. These models allow to obtain the spatial distribution of total emissions of greenhouse gases of Silesia Region, taking into account the contribution of each region in the overall processes of emission.Представлено геоінформаційні технології просторової інвентаризації парникових газів (двоокису вуглецю, метану та ін.) в енергетичному секторі в Сілезькому воєводстві Польщі. Використано георозподілені бази даних, програмне забезпечення геоінформаційної системи та міжнародні методології інвентаризації. Розроблено математичні моделі для інвентаризації двоокису вуглецю, метану та інших парникових газів в процесі спалювання палива на виробництво електроенергії, в житловому секторі, у промисловості та будівництві, на транспорті. Ці моделі дали змогу отримати просторовий розподіл сумарних викидів парникових газів Сілезького воєводства з врахуванням внеску кожного району в загальні процеси емісії
Exploratory Analysis of Highly Heterogeneous Document Collections
We present an effective multifaceted system for exploratory analysis of
highly heterogeneous document collections. Our system is based on intelligently
tagging individual documents in a purely automated fashion and exploiting these
tags in a powerful faceted browsing framework. Tagging strategies employed
include both unsupervised and supervised approaches based on machine learning
and natural language processing. As one of our key tagging strategies, we
introduce the KERA algorithm (Keyword Extraction for Reports and Articles).
KERA extracts topic-representative terms from individual documents in a purely
unsupervised fashion and is revealed to be significantly more effective than
state-of-the-art methods. Finally, we evaluate our system in its ability to
help users locate documents pertaining to military critical technologies buried
deep in a large heterogeneous sea of information.Comment: 9 pages; KDD 2013: 19th ACM SIGKDD Conference on Knowledge Discovery
and Data Minin
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