883 resultados para Traffic emissions
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Reducing Emissions from Deforestation and Forest Degradation and enhancing forest carbon stocks (REDD+) is a performance-based payment mechanism currently being debated in international and national environmental policy and planning forums. As the mechanism is based on conditionality, payments must reflect land stewards’ level of compliance with carbon-efficient management practices. However, lack of clarity in land governance and carbon rights could undermine REDD+ implementation. Strategies are needed to avoid perverse incentives resulting from the commoditization of forest carbon stocks and, importantly, to identify and secure the rights of legitimate recipients of future REDD+ payments. We propose a landscape-level approach to address potential conflicts related to carbon tenure and REDD+ benefit sharing. We explore various land-tenure scenarios and their implications for carbon ownership in the context of a research site in northern Laos. Our case study shows that a combination of relevant scientific tools, knowledge, and participatory approaches can help avoid the marginalization of rural communities during the REDD+ process. The findings demonstrate that participatory land-use planning is an important step in ensuring that local communities are engaged in negotiating REDD+ schemes and that such negotiations are transparent. Local participation and agreements on land-use plans could provide a sound basis for developing efficient measurement, reporting, and verification systems for REDD+.
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The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.
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This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.
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In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.
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Recent downward revisions in the climate response to rising CO2 levels, and opportunities for reducing non-CO2 climate warming, have both been cited as evidence that the case for reducing CO2 emissions is less urgent than previously thought. Evaluating the impact of delay is complicated by the fact that CO2 emissions accumulate over time, so what happens after they peak is as relevant for long-term warming as the size and timing of the peak itself. Previous discussions have focused on how the rate of reduction required to meet any given temperature target rises asymptotically the later the emissions peak. Here we focus on a complementary question: how fast is peak CO2-induced warming increasing while mitigation is delayed, assuming no increase in rates of reduction after the emissions peak? We show that this peak-committed warming is increasing at the same rate as cumulative CO2 emissions, about 2% per year, much faster than observed warming, independent of the climate response.
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The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.
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Rapid changes in atmospheric methane (CH4), temperature and precipitation are documented by Greenland ice core data both for glacial times (the so called Dansgaard-Oeschger (D-O) events) as well as for a cooling event in the early Holocene (the 8.2 kyr event). The onsets of D-O warm events are paralleled by abrupt increases in CH4 by up to 250 ppb in a few decades. Vice versa, the 8.2 kyr event is accompanied by an intermittent decrease in CH4 of about 80 ppb over 150 yr. The abrupt CH4 changes are thought to mainly originate from source emission variations in tropical and boreal wet ecosystems, but complex process oriented bottom-up model estimates of the changes in these ecosystems during rapid climate changes are still missing. Here we present simulations of CH4 emissions from northern peatlands with the LPJ-Bern dynamic global vegetation model. The model represents CH4 production and oxidation in soils and transport by ebullition, through plant aerenchyma, and by diffusion. Parameters are tuned to represent site emission data as well as inversion-based estimates of northern wetland emissions. The model is forced with climate input data from freshwater hosing experiments using the NCAR CSM1.4 climate model to simulate an abrupt cooling event. A concentration reduction of ~10 ppb is simulated per degree K change of mean northern hemispheric surface temperature in peatlands. Peatland emissions are equally sensitive to both changes in temperature and in precipitation. If simulated changes are taken as an analogy to the 8.2 kyr event, boreal peatland emissions alone could only explain 23 of the 80 ppb decline in atmospheric methane concentration. This points to a significant contribution to source changes from low latitude and tropical wetlands to this event.
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During the last glacial cycle, greenhouse gas concentrations fluctuated on decadal and longer timescales. Concentrations of methane, as measured in polar ice cores, show a close connection with Northern Hemisphere temperature variability, but the contribution of the various methane sources and sinks to changes in concentration is still a matter of debate. Here we assess changes in methane cycling over the past 160,000 years by measurements of the carbon isotopic composition delta C-13 of methane in Antarctic ice cores from Dronning Maud Land and Vostok. We find that variations in the delta C-13 of methane are not generally correlated with changes in atmospheric methane concentration, but instead more closely correlated to atmospheric CO2 concentrations. We interpret this to reflect a climatic and CO2-related control on the isotopic signature of methane source material, such as ecosystem shifts in the seasonally inundated tropical wetlands that produce methane. In contrast, relatively stable delta C-13 values occurred during intervals of large changes in the atmospheric loading of methane. We suggest that most methane sources-most notably tropical wetlands-must have responded simultaneously to climate changes across these periods.
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Climate targets are designed to inform policies that would limit the magnitude and impacts of climate change caused by anthropogenic emissions of greenhouse gases and other substances. The target that is currently recognized by most world governments1 places a limit of two degrees Celsius on the global mean warming since preindustrial times. This would require large sustained reductions in carbon dioxide emissions during the twenty-first century and beyond2, 3, 4. Such a global temperature target, however, is not sufficient to control many other quantities, such as transient sea level rise5, ocean acidification6, 7 and net primary production on land8, 9. Here, using an Earth system model of intermediate complexity (EMIC) in an observation-informed Bayesian approach, we show that allowable carbon emissions are substantially reduced when multiple climate targets are set. We take into account uncertainties in physical and carbon cycle model parameters, radiative efficiencies10, climate sensitivity11 and carbon cycle feedbacks12, 13 along with a large set of observational constraints. Within this framework, we explore a broad range of economically feasible greenhouse gas scenarios from the integrated assessment community14, 15, 16, 17 to determine the likelihood of meeting a combination of specific global and regional targets under various assumptions. For any given likelihood of meeting a set of such targets, the allowable cumulative emissions are greatly reduced from those inferred from the temperature target alone. Therefore, temperature targets alone are unable to comprehensively limit the risks from anthropogenic emissions.
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Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.
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This article looks at the negotiations between Switzerland and Germany on air traffic regulation with the help of negotiation analysis tools. A number of factors pre-eminent in the literature on negotiation processes and outcomes are presented and critically assessed. In particular arguments of “power”, which are often insufficiently explored in analysing interstate cooperation, are brought back into the picture. The article argues that structural power best explains the negotiation results while domestic politics and information asymmetries both account for non-ratification of the treaty. Institutionalist arguments on the constraining effects of international norms and institutions as well as explanations focusing on negotiation skills are of minor importance. Moreover, the nature of the Swiss intra-governmental setting at the federal level did not encourage the Swiss negotiators to exploit all means during the different stages of the bargaining process. The article concludes by illuminating a number of policy observations in the broader context of Swiss foreign relations and indicating avenues for further research
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Radiocarbon offers a unique possibility for unambiguous source apportionment of carbonaceous particles due to a direct distinction of non-fossil and fossil carbon. In this work, particulate matter of different size fractions was collected at 4 sites in Switzerland to examine whether fine and coarse carbonaceous particles exhibit different fossil and contemporary sources. Elemental carbon (EC) and organic carbon (OC) as well as water-soluble OC (WSOC) and water-insoluble OC (WINSOC) were separated and determined for subsequent 14C measurement. In general, both fossil and non-fossil fractions in OC and EC were found more abundant in the fine than in the coarse mode. However, a substantial fraction (~20 ± 5%) of fossil EC was found in coarse particles, which could be attributed to traffic-induced non-exhaust emissions. The contribution of biomass burning to coarse-mode EC in winter was relatively high, which is likely associated to the coating of EC with organic and/or inorganic substances emitted from intensive wood burning. Further, fossil OC (i.e. from vehicle emissions) was found to be smaller than non-fossil OC due to the presence of primary biogenic OC and/or growing in size of wood-burning OC particles during aging processes. 14C content in WSOC indicated that the second organic carbon rather stems from non-fossil precursors for all samples. Interestingly, both fossil and non-fossil WINSOC concentrations were found to be higher in fine particles than in coarse particles in winter, which is likely due to primary wood burning emissions and/or secondary formation of WINSOC.
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The large, rapid increase in atmospheric N2O concentrations that occurred concurrent with the abrupt warming at the end of the Last Glacial period might have been the result of a reorganization in global biogeochemical cycles. To explore the sensitivity of nitrogen cycling in terrestrial ecosystems to abrupt warming, we combined a scenario of climate and vegetation composition change based on multiproxy data for the Oldest Dryas–Bølling abrupt warming event at Gerzensee, Switzerland, with a biogeochemical model that simulates terrestrial N uptake and release, including N2O emissions. As for many central European sites, the pollen record at the Gerzensee is remarkable for the abundant presence of the symbiotic nitrogen fixer Hippophaë rhamnoides (L.) during the abrupt warming that also marks the beginning of primary succession on immature glacial soils. Here we show that without additional nitrogen fixation, climate change results in a significant increase of N2O emissions of approximately factor 3.4 (from 6.4 ± 1.9 to 21.6 ± 5.9 mg N2O–N m− 2 yr− 1). Each additional 1000 mg m− 2 yr− 1 of nitrogen added to the ecosystem through N-fixation results in additional N2O emissions of 1.6 mg N2O–N m− 2 yr− 1 for the time with maximum H. rhamnoides coverage. Our results suggest that local reactions of emissions to abrupt climate change could have been considerably faster than the overall atmospheric concentration changes observed in polar ice. Nitrogen enrichment of soils due to the presence of symbiotic N-fixers during early primary succession not only facilitates the establishment of vegetation on soils in their initial stage of development, but can also have considerable influence on biogeochemical cycles and the release of reactive nitrogen trace gases to the atmosphere.
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Ice core measurements (H2O2 and CH4/HCHO) and modeling studies indicate a change in the oxidation capacity of the atmosphere since the onset of the Industrial Revolution due to increases in fossil fuel burning emissions [e. g., Lelieveld et al., 2002; Hauglustaine and Brasseur, 2001; Wang and Jacob, 1998; Staffelbach et al., 1991]. The mass-independent fractionation (MIF) in the oxygen isotopes of sulfate and nitrate from a Greenland ice core reveal that biomass-burning events in North America just prior to the Industrial Revolution significantly impacted the oxidation pathways of sulfur and nitrogen species deposited in Greenland ice. This finding highlights the importance of biomass-burning emissions for atmospheric chemistry in preindustrial North America and warrants the inclusion of this impact in modeling studies estimating changes in atmospheric oxidant chemistry since the Industrial Revolution, particularly when using paleo-oxidant data as a reference for model evaluation.