Applying consumer responsibility principle in evaluating environmental load of carbon emissions

There is a need for a proper indicator in order to assess the environmental impact of international trade, therefore using the carbon footprint as an indicator can be relevant and useful. The aim of this study is to show from a methodological perspective how the carbon footprint, combined with input- output models can be used for analysing the impacts of international trade on the sustainable use of national resources in a country. The use of the input-output approach has the essential advantage of being able to track the transformation of goods through the economy. The study examines the environmental impact of consumption related to international trade, using the consumer responsibility principle. In this study the use of the carbon footprint and input-output methodology is shown on the example of the Hungarian consumption and the impact of international trade. Moving from a production- based approach in climate policy to a consumption-perspective principle and allocation, would also help to increase the efficiency of emission reduction targets and the evaluation of the ecological impacts of international trade.

Carbon emissions locked - in trade

In recent years there has been a growing concern about the emission trade balance of countries. It is due to the fact that countries with an open economy are active players in the international trade, though trade is not only a major factor in forging a country’s economic structure anymore, but it does contribute to the movement of embodied emissions beyond the country borders. This issue is especially relevant from the carbon accounting policy’s point of view, as it is known that the production-based principle is in effect now in the Kyoto agreement. The study aims at revealing the interdependence of countries on international trade and its environmental impacts, and how the carbon accounting method plays a crucial role in evaluating a country’s environmental performance and its role in the climate mitigation processes. The input-output models are used in the methodology, as they provide an appropriate framework for this kind of environmental accounting; the analysis shows an international comparison of four European countries (Germany, the United Kingdom, the Netherlands, and Hungary) with extended trading activities and carbon emissions. Moving from the production-based approach in the climate policy, to the consumptionperspective principle and allocation [15], it would also help increasing the efficiency of emission reduction targets and the evaluation of the sustainability dimension and its impacts of international trade. The results of the study have shown that there is an importance of distinction between the two emission allocation approaches, both from global and local level point of view.

Applying consumer responsibility principle in evaluating environmental load of carbon emissions

There is a need for a proper indicator in order to assess the environmental impact of international trade, therefore using the carbon footprint as an indicator can be relevant and useful. The aim of this study is to show from a methodological perspective how the carbon footprint, combined with input- output models can be used for analysing the impacts of international trade on the sustainable use of national resources in a country. The use of the input-output approach has the essential advantage of being able to track the transformation of goods through the economy. The study examines the environmental impact of consumption related to international trade, using the consumer responsibility principle. In this study the use of the carbon footprint and input-output methodology is shown on the example of the Hungarian consumption and the impact of international trade. Moving from a production- based approach in climate policy to a consumption-perspective principle and allocation, would also help to increase the efficiency of emission reduction targets and the evaluation of the ecological impacts of international trade.

A villamos erőművek szén-dioxid-kibocsátásának modellezése reálopciók segítségével = Modelling of the carbon dioxide emissions of a power plant, using real options

A szerző egy, a szennyezőanyag-kibocsátás európai kereskedelmi rendszerében megfelelésre kötelezett gázturbinás erőmű szén-dioxid-kibocsátását modellezi négy termékre (völgy- és csúcsidőszaki áramár, gázár, kibocsátási kvóta) vonatkozó reálopciós modell segítségével. A profitmaximalizáló erőmű csak abban az esetben termel és szennyez, ha a megtermelt áramon realizálható fedezete pozitív. A jövőbeli időszak összesített szén-dioxid-kibocsátása megfeleltethető európai típusú bináris különbözetopciók összegének. A modell keretein belül a szén-dioxid-kibocsátás várható értékét és sűrűségfüggvényét becsülhetjük, az utóbbi segítségével a szén-dioxid-kibocsátási pozíció kockáztatott értékét határozhatjuk meg, amely az erőmű számára előírt megfelelési kötelezettség teljesítésének adott konfidenciaszint melletti költségét jelenti. A sztochasztikus modellben az alaptermékek geometriai Ornstein-Uhlenbeck-folyamatot követnek. Ezt illesztette a szerző a német energiatőzsdéről származó publikus piaci adatokra. A szimulációs modellre támaszkodva megvizsgálta, hogy a különböző technológiai és piaci tényezők ceteris paribus megváltozása milyen hatással van a megfelelés költségére, a kockáztatott értékére. ______ The carbon-dioxide emissions of an EU Emissions Trading System participant, gas-fuelled power generator are modelled by using real options for four underlying instruments (peak and off-peak electricity, gas, emission quota). This profit-maximizing power plant operates and emits pollution only if its profit (spread) on energy produced is positive. The future emissions can be estimated by a sum of European binary-spread options. Based on the real-option model, the expected value of emissions and its probability-density function can be deducted. Also calculable is the Value at Risk of emission quota position, which gives the cost of compliance at a given confidence level. To model the prices of the four underlying instruments, the geometric Ornstein-Uhlenbeck process is supposed and matched to public available price data from EEX. Based on the simulation model, the effects of various technological and market factors are analysed for the emissions level and the cost of compliance.

Essays on emissions trading markets

This dissertation is a collection of three economics essays on different aspects of carbon emission trading markets. The first essay analyzes the dynamic optimal emission control strategies of two nations. With a potential to become the largest buyer under the Kyoto Protocol, the US is assumed to be a monopsony, whereas with a large number of tradable permits on hand Russia is assumed to be a monopoly. Optimal costs of emission control programs are estimated for both the countries under four different market scenarios: non-cooperative no trade, US monopsony, Russia monopoly, and cooperative trading. The US monopsony scenario is found to be the most Pareto cost efficient. The Pareto efficient outcome, however, would require the US to make side payments to Russia, which will even out the differences in the cost savings from cooperative behavior. The second essay analyzes the price dynamics of the Chicago Climate Exchange (CCX), a voluntary emissions trading market. By examining the volatility in market returns using AR-GARCH and Markov switching models, the study associates the market price fluctuations with two different political regimes of the US government. Further, the study also identifies a high volatility in the returns few months before the market collapse. Three possible regulatory and market-based forces are identified as probable causes of market volatility and its ultimate collapse. Organizers of other voluntary markets in the US and worldwide may closely watch for these regime switching forces in order to overcome emission market crashes. The third essay compares excess skewness and kurtosis in carbon prices between CCX and EU ETS (European Union Emission Trading Scheme) Phase I and II markets, by examining the tail behavior when market expectations exceed the threshold level. Dynamic extreme value theory is used to find out the mean price exceedence of the threshold levels and estimate the risk loss. The calculated risk measures suggest that CCX and EU ETS Phase I are extremely immature markets for a risk investor, whereas EU ETS Phase II is a more stable market that could develop as a mature carbon market in future years.

Estimating Global “Blue Carbon” Emissions from Conversion and Degradation of Vegetated Coastal Ecosystems

Recent attention has focused on the high rates of annual carbon sequestration in vegetated coastal ecosystems—marshes, mangroves, and seagrasses—that may be lost with habitat destruction (‘conversion’). Relatively unappreciated, however, is that conversion of these coastal ecosystems also impacts very large pools of previously-sequestered carbon. Residing mostly in sediments, this ‘blue carbon’ can be released to the atmosphere when these ecosystems are converted or degraded. Here we provide the first global estimates of this impact and evaluate its economic implications. Combining the best available data on global area, land-use conversion rates, and near-surface carbon stocks in each of the three ecosystems, using an uncertainty-propagation approach, we estimate that 0.15–1.02 Pg (billion tons) of carbon dioxide are being released annually, several times higher than previous estimates that account only for lost sequestration. These emissions are equivalent to 3–19% of those from deforestation globally, and result in economic damages of $US 6–42 billion annually. The largest sources of uncertainty in these estimates stems from limited certitude in global area and rates of land-use conversion, but research is also needed on the fates of ecosystem carbon upon conversion. Currently, carbon emissions from the conversion of vegetated coastal ecosystems are not included in emissions accounting or carbon market protocols, but this analysis suggests they may be disproportionally important to both. Although the relevant science supporting these initial estimates will need to be refined in coming years, it is clear that policies encouraging the sustainable management of coastal ecosystems could significantly reduce carbon emissions from the land-use sector, in addition to sustaining the well-recognized ecosystem services of coastal habitats.

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

Decoupling of Greenhouse Gas Emissions from Global Agricultural Production : 1970 - 2050

This article is protected by copyright. All rights reserved. Acknowledgements We thank Tamara Ben-Ari and Jean-Francois Soussana, from INRA in France, for their valuable contributions to the early development stage of this project. We also owe great acknowledge to Prof. Ib Skovgaard, University of Copenhagen, for giving essential assistance in developing the methods for decomposing emission changes. We also thank the Centre for Regional Change in the Earth System (CRES, www.cres-centre.dk) and the Department of Plant- and Environmental Sciences, University of Copenhagen, for funding the work.

Biophysical and economic limits to negative CO2 emissions

The views expressed herein are those of the authors, and do not represent those of a particular governmental agency or interagency body. This analysis was initiated at a Global Carbon Project meeting on NETs in Laxenburg, Austria, in April 2013 and contributes to the MaGNET program (http://www.cger.nies.go.jp/gcp/magnet.html). G.P.P. was supported by the Norwegian Research Council (236296). C.D.J. was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). J.G.C. acknowledges support from the Australian Climate Change Science Program. E.Ka. and Y.Y. were supported by the ERTDF (S-10) from the Ministry of the Environment, Japan.

The potential for land sparing to offset greenhouse gas emissions from agriculture

This research was funded by the Cambridge Conservation Initiative Collaborative Fund for Conservation, and we thank its major sponsor Arcadia. We thank J. Bruinsma for the provision of demand data, the CEH for the provision of soil data and J. Spencer for invaluable discussions. A.L. was supported by a Gates Cambridge Scholarship. T.B., K.G. and J.P. acknowledge BBSRC funding through grant BBS/E/C/00005198.

Spatially explicit estimates of N2O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management

Acknowledgements We are grateful to Stefan Seibert for advice on reconciling the Monfreda datasets of yield and area and the Portmann dataset for irrigated area of rice. We thank Deepak Ray and Jonathan Foley for helpful comments. Research support to J.G. K.C., N.M, and P.W. was primarily provided by the Gordon and Betty Moore Foundation and the Institute on Environment, with additional support from NSF Hydrologic Sciences grant 1521210 for N.M., and additional support to J.G. and P.W. whose efforts contribute to Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1). M.H. was supported by CSIRO's OCE Science Leaders Programme and the Agriculture Flagship. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Reducing emissions from agriculture to meet the 2°C target

Peer reviewed

Agricultural production and greenhouse gas emissions from world regions-The major trends over 40 years

Acknowledgements: We thank Dr. Tamara Ben-Ari and Dr. Jean-Francois Soussana, from INRA in France, for their valuable contributions to the early development stage of this project. We also owe great thanks to Prof. Ib Skovgaard, University of Copenhagen, for giving essential assistance in developing the methods for decomposing emission changes. We also thank the Centre for Regional Change in the Earth System (CRES, www.cres-centre.dk), and the University of Copenhagen for funding the work.

Increasing beef production won’t reduce emissions

BP is supported by a grant from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) through the Brazilian Science without Borders programme (number 88881.068115/2014-01). He thanks Luciana Leite de Araújo for suggesting the topic of this letter.

Modelling nitrous oxide emissions from mown-grass and grain-cropping systems : Testing and sensitivity analysis of DailyDayCent using high frequency measurements

The lead author, Nimai Senapati (Post doc), was funded by the European community’s Seventh Framework programme (FP2012-2015) under grant agreement no. 262060 (ExpeER). The research leading to these results has received funding principally from the ANR (ANR-11-INBS-0001), AllEnvi, CNRS-INSU. We would like to thank the National Research Infrastructure ‘Agro-écosystèmes, Cycles Biogéochimique et Biodiversité (SOERE-ACBB http://www.soere-acbb.com/fr/) for their support in field experiment. We are deeply indebted to Christophe deBerranger, Xavier Charrier for their substantial technical assistance and Patricia Laville for her valuables suggestion regarding N2O flux estimation.