981 resultados para Global emissions


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This study elucidated the shadow price of greenhouse gas (GHG) emissions for 1,024 international companies worldwide that were surveyed from 15 industries in 37 major countries. Our results indicate that the shadow price of GHG at the firm level is much higher than indicated in previous studies. The higher shadow price was found in this study as a result of the use of Scope 3 GHG emissions data. The results of this research indicate that a firm would carry a high cost of GHG emissions if Scope 3 GHG emissions were the focus of the discussion of corporate social responsibility. In addition, such shadow prices were determined to differ substantially among countries, among sectors, and within sectors. Although a number of studies have calculated the shadow price of GHG emissions, these studies have employed country-level or industry-level data or a small sample of firm-level data in one country. This new data from a worldwide firm analysis of the shadow price of GHG emissions can play an important role in developing climate policy and promoting sustainable development.

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Emissions trading schemes have been introduced throughout the world in order to achieve an environmental end. In the pursuit of reducing greenhouse gas emissions, these schemes will have a direct impact on the global economy. This book examines the details of emissions trading schemes through the lens of the World Trade Organization (WTO) law. Emissions trading schemes both implemented and proposed will be deconstructed to understand whether they will have a single uniform legal status within the WTO law, or indeed whether the legal status of the units of trade will differ on a case-by-case basis. This book examines non-discrimination provisions and exceptions within four significant WTO ‘covered agreements’. This analysis will be undertaken with a goal to understand how emissions trading scheme measures may be labelled and treated by WTO dispute settlement bodies. Moreover, the narrative of this publication demonstrates where decisions must be made by WTO Members in relation to the legal treatment of emissions trading units and liabilities. The aim of the book is to consider the issues associated with emissions trading that arise within the existing WTO law. This monograph will consider emissions trading schemes through the lens of WTO law to establish how these schemes will be defined, where they may potentially breach the non-discrimination provisions of the law and, whether the WTO law should be amended through Member agreement in order to accommodate these schemes. The book is an adaptation of a PhD thesis, which is an analysis of one emissions trading framework – the Australian Clean Energy Package – using WTO law as the theoretical framework. The aim of the proposed monograph is to increase the scope of analysis from the Clean Energy Package to emissions trading schemes more generally. It is envisaged that to do this effectively, examples of frameworks that have been proposed and implemented by various WTO members must be used as case studies for both WTO compliance and non-compliance.

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Aircraft black carbon (BC) emissions contribute to climate forcing, but few estimates of BC emitted by aircraft at cruise exist. For the majority of aircraft engines the only BC-related measurement available is smoke number (SN)-a filter based optical method designed to measure near-ground plume visibility, not mass. While the first order approximation (FOA3) technique has been developed to estimate BC mass emissions normalized by fuel burn [EI(BC)] from SN, it is shown that it underestimates EI(BC) by >90% in 35% of directly measured cases (R(2) = -0.10). As there are no plans to measure BC emissions from all existing certified engines-which will be in service for several decades-it is necessary to estimate EI(BC) for existing aircraft on the ground and at cruise. An alternative method, called FOX, that is independent of the SN is developed to estimate BC emissions. Estimates of EI(BC) at ground level are significantly improved (R(2) = 0.68), whereas estimates at cruise are within 30% of measurements. Implementing this approach for global civil aviation estimated aircraft BC emissions are revised upward by a factor of ~3. Direct radiative forcing (RF) due to aviation BC emissions is estimated to be ~9.5 mW/m(2), equivalent to ~1/3 of the current RF due to aviation CO2 emissions.

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We present in two parts an assessment of global manufacturing. In the first part, we review economic development, pollution, and carbon emissions from a country perspective, tracking the rise of China and other developing countries. The results show not only a rise in the economic fortunes of the newly industrializing nations, but also a significant rise in global pollution, particularly air pollution and CO2 emissions largely from coal use, which alter and even reverse previous global trends. In the second part, we change perspective and quantitatively evaluate two important technical strategies to reduce pollution and carbon emissions: energy efficiency and materials recycling. We subdivide the manufacturing sector on the basis of the five major subsectors that dominate energy use and carbon emissions: (a) iron and steel, (b) cement, (c) plastics, (d) paper, and (e) aluminum. The analysis identifies technical constraints on these strategies, but by combined and aggressive action, industry should be able to balance increases in demand with these technical improvements. The result would be high but relatively flat energy use and carbon emissions. The review closes by demonstrating the consequences of extrapolating trends in production and carbon emissions and suggesting two options for further environmental improvements, materials efficiency, and demand reduction. © 2013 by Annual Reviews. All rights reserved.

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New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997-2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997-2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 PgC year-1 with significant interannual variability during 1997-2001 (2.8 Pg Cyear-1 in 1998 and 1.6 PgC year-1 in 2001). Globally, emissions during 2002-2007 were rela-tively constant (around 2.1 Pg C year-1) before declining in 2008 (1.7 Pg Cyear-1) and 2009 (1.5 PgC year-1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002-2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001-2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 PgC year-1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series. © 2010 Author(s).

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Carbon dioxide (CO2) transfer from inland waters to the atmosphere, known as CO2 evasion, is a component of the global carbon cycle. Global estimates of CO2 evasion have been hampered, however, by the lack of a framework for estimating the inland water surface area and gas transfer velocity and by the absence of a global CO2 database. Here we report regional variations in global inland water surface area, dissolved CO2 and gas transfer velocity. We obtain global CO2 evasion rates of 1.8petagrams of carbon (Pg C) per year from streams and rivers and 0.32Pg Cyr-1 from lakes and reservoirs, where the upper and lower limits are respectively the 5th and 95th confidence interval percentiles. The resulting global evasion rate of 2.1 Pg Cyr-1 is higher than previous estimates owing to a larger stream and river evasion rate. Our analysis predicts global hotspots in stream and river evasion, with about 70 per cent of the flux occurring over just 20 per cent of the land surface. The source of inland water CO2 is still not known with certainty and new studies are needed to research the mechanisms controlling CO2 evasion globally. © 2013 Macmillan Publishers Limited. All rights reserved.

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Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.

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The global temperature response to increasing atmospheric CO2 is often quantified by metrics such as equilibrium climate sensitivity and transient climate response1. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO2 emissions. Climate–carbon modelling experiments have shown that: (1) the warming per unit CO2 emitted does not depend on the background CO2 concentration2; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions3, 4, 5; and (3) the temperature response to a pulse of CO2 is approximately constant on timescales of decades to centuries3, 6, 7, 8. Here we generalize these results and show that the carbon–climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO2 concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0–2.1 °C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate–carbon models. Uncertainty in land-use CO2 emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate–carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate–carbon feedbacks into a single quantity, the CCR allows CO2-induced global mean temperature change to be inferred directly from cumulative carbon emissions.

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Recent advances in understanding have made it possible to relate global precipitation changes directly to emissions of particular gases and aerosols that influence climate. Using these advances, new indices are developed here called the Global Precipitation-change Potential for pulse (GPP_P) and sustained (GPP_S) emissions, which measure the precipitation change per unit mass of emissions. The GPP can be used as a metric to compare the effects of different emissions. This is akin to the global warming potential (GWP) and the global temperature-change potential (GTP) which are used to place emissions on a common scale. Hence the GPP provides an additional perspective of the relative or absolute effects of emissions. It is however recognised that precipitation changes are predicted to be highly variable in size and sign between different regions and this limits the usefulness of a purely global metric. The GPP_P and GPP_S formulation consists of two terms, one dependent on the surface temperature change and the other dependent on the atmospheric component of the radiative forcing. For some forcing agents, and notably for CO2, these two terms oppose each other – as the forcing and temperature perturbations have different timescales, even the sign of the absolute GPP_P and GPP_S varies with time, and the opposing terms can make values sensitive to uncertainties in input parameters. This makes the choice of CO2 as a reference gas problematic, especially for the GPP_S at time horizons less than about 60 years. In addition, few studies have presented results for the surface/atmosphere partitioning of different forcings, leading to more uncertainty in quantifying the GPP than the GWP or GTP. Values of the GPP_P and GPP_S for five long- and short-lived forcing agents (CO2, CH4, N2O, sulphate and black carbon – BC) are presented, using illustrative values of required parameters. The resulting precipitation changes are given as the change at a specific time horizon (and hence they are end-point metrics) but it is noted that the GPPS can also be interpreted as the time-integrated effect of a pulse emission. Using CO2 as a references gas, the GPP_P and GPP_S for the non-CO2 species are larger than the corresponding GTP values. For BC emissions, the atmospheric forcing is sufficiently strong that the GPP_S is opposite in sign to the GTP_S. The sensitivity of these values to a number of input parameters is explored. The GPP can also be used to evaluate the contribution of different emissions to precipitation change during or after a period of emissions. As an illustration, the precipitation changes resulting from emissions in 2008 (using the GPP_P) and emissions sustained at 2008 levels (using the GPP_S) are presented. These indicate that for periods of 20 years (after the 2008 emissions) and 50 years (for sustained emissions at 2008 levels) methane is the dominant driver of positive precipitation changes due to those emissions. For sustained emissions, the sum of the effect of the five species included here does not become positive until after 50 years, by which time the global surface temperature increase exceeds 1 K.

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rnNitric oxide (NO) is important for several chemical processes in the atmosphere. Together with nitrogen dioxide (NO2 ) it is better known as nitrogen oxide (NOx ). NOx is crucial for the production and destruction of ozone. In several reactions it catalyzes the oxidation of methane and volatile organic compounds (VOCs) and in this context it is involved in the cycling of the hydroxyl radical (OH). OH is a reactive radical, capable of oxidizing most organic species. Therefore, OH is also called the “detergent” of the atmosphere. Nitric oxide originates from several sources: fossil fuel combustion, biomass burning, lightning and soils. Fossil fuel combustion is the largest source. The others are, depending on the reviewed literature, generally comparable to each other. The individual sources show a different temporal and spatial pattern in their magnitude of emission. Fossil fuel combustion is important in densely populated places, where NO from other sources is less important. In contrast NO emissions from soils (hereafter SNOx) or biomass burning are the dominant source of NOx in remote regions.rnBy applying an atmospheric chemistry global climate model (AC-GCM) I demonstrate that SNOx is responsible for a significant part of NOx in the atmosphere. Furthermore, it increases the O3 and OH mixing ratio substantially, leading to a ∼10% increase in the oxidizing efficiency of the atmosphere. Interestingly, through reduced O3 and OH mixing ratios in simulations without SNOx, the lifetime of NOx increases in regions with other dominating sources of NOx