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

Forest Certification in Papua New Guinea

abstract In Papua New Guinea (PNG), 97 percent of the land and forest resources are customary owned and constitute some of the most important assets that sustain livelihoods. As a result, people have a direct relationship with both. With the introduction of commercial logging, landowners have been marginalized in decision-making concerning their forest resources. Forest resource owners continue to have to deal with the negative consequences of decisions made by others. While such individuals are interested in forest certification because they think it can be a solution to the ongoing problems related to large-scale logging, they do not have the economic, technical and resource capacity to undertake it. The high cost of forest certification precludes implementation in PNG, meaning that forest management that is economically viable, socially beneficial and environmentally sound cannot be achieved using this tool. The Papua New Guinea Government, through the National Forest Authority's administrative arm, the National Forest Service, is aware of certification, but most large-scale logging companies show no interest. These companies can be attracted to certification if there is a price premium, market demand, and the costs of getting certified are affordable. There is a need too for greater publicity about forest certification so that stakeholders can make an informed choice. Forest certification in PNG will require continued assistance if it is to promote change from unscrupulous forest management to improved certified practices. Medium-and small-scale producers are very interested in FSC forest certification and are working on it; only community-managed forests are certified in PNG

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

Taking advantage of the UNFCCC Kyoto Policy Process: What can we learn about learning?

Learning is difficult to anticipate when it happen instantaneously, e.g. in the context of innovations [2]. However, even if learning is anticipated to happen continuously, it is difficult to grasp, e.g. when it occurs outside well-defined lab conditions, because adequate monitoring had not been put in place. Our study is retrospective. It focuses on the emissions of greenhouse gases (GHGs)that had been reported by countries (Parties) under the Kyoto Protocol (KP) to the United Nations Framework on Climate Change (UNFCCC). Discussions range widely on (i) whether the KP is considered a failure [6] or a success [5] ; and (ii) whether international climate policy should transit from a centralized model of governance to a 'hybrid' decentralized approach that combines country-level mitigation pledges with common principles for accounting and monitoring [1] . Emissions of GHGs - in the following we refer to CO2 emissions from burning fossil fuels at country level, particularly in the case of Austria - provide a perfect means to study learning in a globally relevant context. We are not aware of a similar data treasure of global relevance. Our mode of grasping learning is novel, i.e. it may have been referred to in general but, to the best of our knowledge, had not been quantifed so far. (That is, we consider the KP a success story potentially and advocate for the hybrid decentralized approach.) Learning requires 'measuring' differences or deviations. Here we follow Marland et al. [3] who discuss this issue in the context of emissions accounting: 'Many of the countries and organizations that make estimates of CO2 emissions provide annual updates in which they add another year of data to the time series and revise the estimates for earlier years. Revisions may reflect revised or more complete energy data and ... more complete and detailed understanding of the emissions processes and emissions coefficients. In short, we expect revisions to reflect learning and a convergence toward more complete and accurate estimates.' The United Nations Framework Convention on Climate Change (UNFCCC)requires exactly this to be done. Each year UNFCCC signatory countries are obliged to provide an annual inventory of emissions (and removals) of specified GHGs from five sectors (energy; industrial processes and product use; agriculture; land use, land use change and forestry; and waste) and revisit the emissions (and removals) for all previous years, back to the country specified base years (or periods). These data are made available by means of a database [4]. The time series of revised emission estimates reflect learning, but they are 'contaminated' by (i) structural change (e.g., when a coal-power plant is substituted by a gas-power plant); (ii) changes in consumption; and, rare but possible, (iii)methodological changes in surveying emission related activities. De-trending time series of revised emission estimates allows this contamination to be isolated by country, for which we provide three approaches: (I) parametric approach employing polynomial trend; (II) non-parametric approach employing smoothing splines; and (III) approach in which the most recent estimate is used as trend. That is, after de-trending for each year we are left with a set of revisions that reflect 'pure'(uncontaminated) learning which, is expected to be independent of the year under consideration (i.e., identical from year to year). However, we are confronted with two non-negligible problems (P): (P.1) the problem of small numbers - the remaining differences in emissions are small (before and after de-trending); and (P.2) the problem of non-monotonic learning - our knowledge of emission-generating activities and emission factors may not become more accurate from revision to revision

PEMBUATAN FILTER AIR UNTUK MENJERNIHKAN AIR BAKU

Abstrak: Air yang dikonsumsi manusia haruslah memenuhi indikator fisika, kimia, dan biologi, agar tidak emnimbulkan gangguan kesehatan. Mn dan Fe adalah indikator kimiawi air, yang apabila dikonsumsi diatas batas aman, maka akan menimbulkan penyakit bagi manusia. Masalah yang dihadapi oleh mitra kegiatan ini adalah air baku yang tercemar Mn dan Fe dalam jumlah yang cukup besar (2) Tujuan pengabdian ini adalah untuk memberikan solusi pengolahan air melalui desain alat penjernih air dengan metode aerasi filtrasi (3) Metode kegiatan ini yaitu tahapan pra kegiatan dimana tim melakukan persiapan keperluan pengabmas, pelaksanaan kegiatan, dan tahap evaluasi yaitu tim melakukan pengukuran parameter fisik air. Serta disosialisasikan tentang cara perawatan alat, meliputi pencucian pasir, serta pemeliharaan sambungan pipa, shoer, dan keran, pada masyarakat yang menjadi sasaran. Kegiatan ini melibatkan mitra Desa Tualango yang terdiri dari 5 orang aparat Des, 20 orang masyarakat, dan 1 orang petugas Puskesmas. Evaluasi pasca pelaksanaan kegiatan dilakukan sebanyak 2 kali yang meliputi perawatan serta perbaikan alat, serta pengukuran hasil olahan dari alat. Hasil yang dicapai pada kegiatan ini, adalah diperolehnya air baku masyarakat yang memenuhi syarat fisik (tidak berbau, berwarna, dan berasa) dengan persentase 100% setelah dilakukan pengolahan dengan alat yang digunakan. Sementara, untuk perawatan alat penjernih telah diajarkan pada masyarakat pada saat tahapan sosialisasi .Abstract: Water consumed by humans must meet physical, chemical, and biological indicators, so as not to cause health problems. Mn and Fe are chemical indicators of water, which if consumed above the safe limit, it will cause disease for humans. The problem faced by partners in this activity is raw water that is contaminated with Mn and Fe in large enough quantities (2) The purpose of this service is to provide water treatment solutions through the design of water purification equipment with aeration filtration method (3) The method of this activity is the pre-processing stage. An activity where the team prepares for the needs of community service, implementation of activities, and the evaluation stage, where the team measures the physical parameters of water. As well as being socialized on how to maintain tools, including sand washing, as well as maintenance of pipe connections, shoers, and faucets, to the target community. This activity involved Tualango Village partners consisting of 5 village officials, 20 community members, and 1 Puskesmas officer. Post-implementation evaluation activities were carried out 2 times which included maintenance and repair of tools, as well as measurement of the processed results of the tools. The result achieved in this activity is the obtaining of community raw water that meets physical requirements (odorless, colorless, and tasteless) with a percentage of 100% after processing with the equipment used. Meanwhile, the maintenance of the purifier has been taught to the community during the socialization stage