952 resultados para GHGs Emissions


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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.

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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.

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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.

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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.

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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.

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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.

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Peer reviewed

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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.

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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.

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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.

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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.

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China has achieved significant progress in terms of economic and social developments since implementation of reform and open policy in 1978. However, the rapid speed of economic growth in China has also resulted in high energy consumption and serious environmental problems, which hindering the sustainability of China's economic growth. This paper provides a framework for measuring eco-efficiency with CO2 emissions in Chinese manufacturing industries. We introduce a global Malmquist-Luenberger productivity index (GMLPI) that can handle undesirable factors within Data Envelopment Analysis (DEA). This study suggested after regulations imposed by the Chinese government, in the last stage of the analysis, i.e. during 2011–2012, the contemporaneous frontier shifts towards the global technology frontier in the direction of more desirable outputs and less undesirable outputs, i.e. producing less CO2 emissions, but the GMLPI drops slightly. This is an indication that the Chinese government needs to implement more policy regulations in order to maintain productivity index while reducing CO2 emissions.

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Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as

`biological valves' in regulating the anthropogenic emissions of atmospheric aerosol

particles and greenhouse gases (GHGs) as responses to their surrounding environments.

While the signicance of quantifying the exchange rates of GHGs and atmospheric

aerosol particles between the terrestrial biosphere and the atmosphere is

hardly questioned in many scientic elds, the progress in improving model predictability,

data interpretation or the combination of the two remains impeded by

the lack of precise framework elucidating their dynamic transport processes over a

wide range of spatiotemporal scales. The diculty in developing prognostic modeling

tools to quantify the source or sink strength of these atmospheric substances

can be further magnied by the fact that the climate system is also sensitive to the

feedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,

the emergent need is to reduce uncertainties when assessing this complex and dynamic

feedback cycle that is necessary to support the decisions of mitigation and

adaptation policies associated with human activities (e.g., anthropogenic emission

controls and land use managements) under current and future climate regimes.

With the goal to improve the predictions for the biosphere-atmosphere exchange

of biologically active gases and atmospheric aerosol particles, the main focus of this

dissertation is on revising and up-scaling the biotic and abiotic transport processes

from leaf to canopy scales. The validity of previous modeling studies in determining

iv

the exchange rate of gases and particles is evaluated with detailed descriptions of their

limitations. Mechanistic-based modeling approaches along with empirical studies

across dierent scales are employed to rene the mathematical descriptions of surface

conductance responsible for gas and particle exchanges as commonly adopted by all

operational models. Specically, how variation in horizontal leaf area density within

the vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributes

and thereby the ultrane particle collection eciency at the leaf/branch scale

is explored using wind tunnel experiments with interpretations by a porous media

model and a scaling analysis. A multi-layered and size-resolved second-order closure

model combined with particle

uxes and concentration measurements within and

above a forest is used to explore the particle transport processes within the canopy

sub-layer and the partitioning of particle deposition onto canopy medium and forest

oor. For gases, a modeling framework accounting for the leaf-level boundary layer

eects on the stomatal pathway for gas exchange is proposed and combined with sap

ux measurements in a wind tunnel to assess how leaf-level transpiration varies with

increasing wind speed. How exogenous environmental conditions and endogenous

soil-root-stem-leaf hydraulic and eco-physiological properties impact the above- and

below-ground water dynamics in the soil-plant system and shape plant responses

to droughts is assessed by a porous media model that accommodates the transient

water

ow within the plant vascular system and is coupled with the aforementioned

leaf-level gas exchange model and soil-root interaction model. It should be noted

that tackling all aspects of potential issues causing uncertainties in forecasting the

feedback cycle between terrestrial ecosystem and the climate is unrealistic in a single

dissertation but further research questions and opportunities based on the foundation

derived from this dissertation are also brie

y discussed.

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Secondary organic aerosol (SOA) accounts for a dominant fraction of the submicron atmospheric particle mass, but knowledge of the formation, composition and climate effects of SOA is incomplete and limits our understanding of overall aerosol effects in the atmosphere. Organic oligomers were discovered as dominant components in SOA over a decade ago in laboratory experiments and have since been proposed to play a dominant role in many aerosol processes. However, it remains unclear whether oligomers are relevant under ambient atmospheric conditions because they are often not clearly observed in field samples. Here we resolve this long-standing discrepancy by showing that elevated SOA mass is one of the key drivers of oligomer formation in the ambient atmosphere and laboratory experiments. We show for the first time that a specific organic compound class in aerosols, oligomers, is strongly correlated with cloud condensation nuclei (CCN) activities of SOA particles. These findings might have important implications for future climate scenarios where increased temperatures cause higher biogenic volatile organic compound (VOC) emissions, which in turn lead to higher SOA mass formation and significant changes in SOA composition. Such processes would need to be considered in climate models for a realistic representation of future aerosol-climate-biosphere feedbacks.

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Thirty-six 12-month-old hill hoggets were used in a 2 genotype (18 Scottish Blackface vs. 18 Swaledale×Scottish Blackface)×3 diet (fresh vs. ensiled vs. pelleted ryegrass) factorial design experiment to evaluate the effects of hogget genotype and forage type on enteric methane (CH4) emissions and nitrogen (N) utilisation. The hoggets were offered 3 diets ad libitum with no concentrate supplementation in a single period study with 6 hoggets for each of the 6 genotype×diet combinations (n=6). Fresh ryegrass was harvested daily in the morning. Pelleted ryegrass was sourced from a commercial supplier (Aylescott Driers & Feeds, Burrington, UK) and the ryegrass silage was ensiled with Ecosyl (Lactobacillus plantarum, Volac International Limited, Hertfordshire, UK) as an additive. The hoggets were housed in individual pens for at least 14 d before being transferred to individual respiration chambers for a further 4 d with feed intake, faeces and urine outputs and CH4 emissions measured. There was no significant interaction between genotype and forage type on any parameter evaluated. Sheep offered pelleted grass had greater feed intake (e.g. DM, energy and N) but less energy and nutrient apparent digestibility (e.g. DM, N and neutral detergent fibre (NDF)) than those given fresh grass or grass silage (P<0.001). Feeding pelleted grass, rather than fresh grass or grass silage, reduced enteric CH4 emissions as a proportion of DM intake and gross energy (GE) intake (P<0.01). Sheep offered fresh grass had a significantly lower acid detergent fibre (ADF) apparent digestibility, and CH4 energy output (CH4-E) as a proportion of GE intake than those offered grass silage (P<0.001). There was no significant difference, in CH4 emission rate or N utilisation efficiency when compared between Scottish Blackface and Swaledale × Scottish Blackface. Linear and multiple regression techniques were used to develop relationships between CH4 emissions or N excretion and dietary and animal variables using data from sheep offered fresh ryegrass and grass silage. The equation relating CH4-E (MJ/d) to GE intake (GEI, MJ/d), energy apparent digestibility (DE/GE) and metabolisability (ME/GE) resulted in a high r2 (CH4-E=0.074 GEI+9.2 DE/GE−10.2 ME/GE−0.37, r2=0.93). N intake (NI) was the best predictor for manure N excretion (Manure N=0.66 NI+0.96, r2=0.85). The use of these relationships can potentially improve the precision and decrease the uncertainty in predicting CH4 emissions and N excretion for sheep production systems managed under the current feeding conditions.