14 resultados para emissions reporting

em Indian Institute of Science - Bangalore - Índia


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Location management problem that arise in mobile computing networks is addressed. One method used in location management is to designate sonic of the cells in the network as "reporting cells". The other cells in the network are "non-reporting cells". Finding an optimal set of reporting cells (or reporting cell configuration) for a given network. is a difficult combinatorial optimization problem. In fact this is shown to be an NP-complete problem. in an earlier study. In this paper, we use the selective paging strategy and use an ant colony optimization method to obtain the best/optimal set of reporting cells for a given a network.

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A decentralized emission inventories are prepared for road transport sector of India in order to design and implement suitable technologies and policies for appropriate mitigation measures. Globalization and liberalization policies of the government in 90's have increased the number of road vehicles nearly 92.6% from 1980-1981 to 2003-2004. These vehicles mainly consume non-renewable fossil fuels, and are a major contributor of green house gases, particularly CO2 emission. This paper focuses on the statewise road transport emissions (CO2, CH4, CO, N-x, N2O, SO2, PM and HC) using region specific mass emission factors for each type of vehicles. The country level emissions (CO2, CH4, CO, NOx, N2O, SO2 and NMVOC) are calculated for railways, shipping and airway, based on fuel types. In India, transport sector emits an estimated 258.10 Tg Of CO2, of which 94.5% was contributed by road transport (2003-2004). Among all the states and Union Territories, Maharashtra's contribution is the largest, 28.85 Tg (11.8%) Of CO2, followed by Tamil Nadu 26.41 Tg(10.8%), Gujarat 23.31 Tg(9.6%), Uttar Pradesh 17.42 Tg(7.1%), Rajasthan 15.17 Tg (6.22%) and, Karnataka 15.09 Tg (6.19%). These six states account for 51.8% of the CO2 emissions from road transport.

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Analysts have identified four related questions that need to be asked and answered before agreements to respond to global warming will be possible.1 Which countries bear responsibility for causing the problem? What quantities and mix of greenhouse gases should each country be allowed to emit? Which countries have the resources to do something about the problem? Where are the best opportunities for undertaking projects to respond to the problem? Failure to distinguish among these four questions, or willingness to accept superficial answers, promotes unnecessary controversy.

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This paper contains an analysis of the technical options in agriculture for reducing greenhouse-gas emissions and increasing sinks, arising from three distinct mechanisms: (i) increasing carbon sinks in soil organic matter and above-ground biomass; (ii) avoiding carbon emissions from farms by reducing direct and indirect energy use; and (iii) increasing renewable-energy production from biomass that either substitutes for consumption of fossil fuels or replaces inefficient burning of fuelwood or crop residues, and so avoids carbon emissions, together with use of biogas digesters and improved cookstoves. We then review best-practice sustainable agriculture and renewable-resource-management projects and initiatives in China and India, and analyse the annual net sinks being created by these projects, and the potential market value of the carbon sequestered. We conclude with a summary of the policy and institutional conditions and reforms required for adoption of best sustainability practice in the agricultural sector to achieve the desired reductions in emissions and increases in sinks. A review of 40 sustainable agriculture and renewable-resource-management projects in China and India under the three mechanisms estimated a carbon mitigation potential of 64.8 MtC yr(-1) from 5.5 Mha. The potential income for carbon mitigation is $324 million at $5 per tonne of carbon. The potential exists to increase this by orders of magnitude, and so contribute significantly to greenhouse-gas abatement. Most agricultural mitigation options also provide several ancillary benefits. However, there are many technical, financial, policy, legal and institutional barriers to overcome.

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A decentralized emission inventories are prepared for road transport sector of India in order to design and implement suitable technologies and policies for appropriate mitigation measures. Globalization and liberalization policies of the government in 90's have increased the number of road vehicles nearly 92.6% from 1980–1981 to 2003–2004. These vehicles mainly consume non-renewable fossil fuels, and are a major contributor of green house gases, particularly CO2 emission. This paper focuses on the statewise road transport emissions (CO2, CH4, CO, NOx, N2O, SO2, PM and HC), using region specific mass emission factors for each type of vehicles. The country level emissions (CO2, CH4, CO, NOx, N2O, SO2 and NMVOC) are calculated for railways, shipping and airway, based on fuel types. In India, transport sector emits an estimated 258.10 Tg of CO2, of which 94.5% was contributed by road transport (2003–2004). Among all the states and Union Territories, Maharashtra's contribution is the largest, 28.85 Tg (11.8%) of CO2, followed by Tamil Nadu 26.41 Tg (10.8%), Gujarat 23.31 Tg (9.6%), Uttar Pradesh 17.42 Tg (7.1%), Rajasthan 15.17 Tg (6.22%) and, Karnataka 15.09 Tg (6.19%). These six states account for 51.8% of the CO2 emissions from road transport.

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The acoustic emission technique is used for monitoring the fatigue crack growth in plain concrete beams under three-point loading. Variable amplitude loading with step-wise increase in the maximum load is applied. The fatigue crack growth is continuously monitored using six acoustic sensors. The results of load, displacement, crack mouth opening displacement, acoustic events, and acoustic energy are simultaneously acquired during the test. It is seen that a Paris law type of relationship exists between the rate of increase of acoustic emission count per cycle and the stress intensity factor range. Using b-value analysis, different stages of fatigue fracture is explained. (C) 2012 Elsevier Ltd. All rights reserved.

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This research article describes the large scale fabrication of ZnO nanorods of various shapes on Si(100) substrate, by using metalorganic precursor of Zn in solutions with microwave as the source of energy. This is a low temperature, environmental friendly and rapid thin film deposition process, where ZnO nanorods (1-3 mu m length) were grown only in 1-5 min of microwave irradiation. All as-synthesized nanorods are of single crystalline grown along the < 0001 > crystallographic direction. The coated nanorods were found to be highly dense having a thickness of similar to 1-3 mu m over the entire area 20 mm x 20 mm of the substrate. The ZnO thin film comprising of nanorods exhibits good adhesion with the substrate. A possible mechanism for the initial nucleation and growth of ZnO is discussed. A cross over from a strong visible light emission to an enhanced UV emission is observed, when the nature of the surfactants are varied from polymeric to ionic and nonionic. The position of the chromaticity coordinates in yellow region of the color space gives an impression of white light generation from these coatings by exciting with a blue laser.

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As System-on-Chip (SoC) designs migrate to 28nm process node and beyond, the electromagnetic (EM) co-interactions of the Chip-Package-Printed Circuit Board (PCB) becomes critical and require accurate and efficient characterization and verification. In this paper a fast, scalable, and parallelized boundary element based integral EM solutions to Maxwell equations is presented. The accuracy of the full-wave formulation, for complete EM characterization, has been validated on both canonical structures and real-world 3-D system (viz. Chip + Package + PCB). Good correlation between numerical simulation and measurement has been achieved. A few examples of the applicability of the formulation to high speed digital and analog serial interfaces on a 45nm SoC are also presented.

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Two atmospheric inversions (one fine-resolved and one process-discriminating) and a process-based model for land surface exchanges are brought together to analyse the variations of methane emissions from 1990 to 2009. A focus is put on the role of natural wetlands and on the years 2000-2006, a period of stable atmospheric concentrations. From 1990 to 2000, the top-down and bottom-up visions agree on the time-phasing of global total and wetland emission anomalies. The process-discriminating inversion indicates that wetlands dominate the time-variability of methane emissions (90% of the total variability). The contribution of tropical wetlands to the anomalies is found to be large, especially during the post-Pinatubo years (global negative anomalies with minima between -41 and -19 Tg yr(-1) in 1992) and during the alternate 1997-1998 El-Nino/1998-1999 La-Nina (maximal anomalies in tropical regions between +16 and +22 Tg yr(-1) for the inversions and anomalies due to tropical wetlands between +12 and +17 Tg yr(-1) for the process-based model). Between 2000 and 2006, during the stagnation of methane concentrations in the atmosphere, the top-down and bottom-up approaches agree on the fact that South America is the main region contributing to anomalies in natural wetland emissions, but they disagree on the sign and magnitude of the flux trend in the Amazon basin. A negative trend (-3.9 +/- 1.3 Tg yr(-1)) is inferred by the process-discriminating inversion whereas a positive trend (+1.3 +/- 0.3 Tg yr(-1)) is found by the process model. Although processed-based models have their own caveats and may not take into account all processes, the positive trend found by the B-U approach is considered more likely because it is a robust feature of the process-based model, consistent with analysed precipitations and the satellite-derived extent of inundated areas. On the contrary, the surface-data based inversions lack constraints for South America. This result suggests the need for a re-interpretation of the large increase found in anthropogenic methane inventories after 2000.

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Periodic estimation, monitoring and reporting on area under forest and plantation types and afforestation rates are critical to forest and biodiversity conservation, sustainable forest management and for meeting international commitments. This article is aimed at assessing the adequacy of the current monitoring and reporting approach adopted in India in the context of new challenges of conservation and reporting to international conventions and agencies. The analysis shows that the current mode of monitoring and reporting of forest area is inadequate to meet the national and international requirements. India could be potentially over-reporting the area under forests by including many non-forest tree categories such as commercial plantations of coconut, cashew, coffee and rubber, and fruit orchards. India may also be under-reporting deforestation by reporting only gross forest area at the state and national levels. There is a need for monitoring and reporting of forest cover, deforestation and afforestation rates according to categories such as (i) natural/primary forest, (ii) secondary/degraded forests, (iii) forest plantations, (iv) commercial plantations, (v) fruit orchards and (vi) scattered trees.

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This paper considers cooperative spectrum sensing algorithms for Cognitive Radios which focus on reducing the number of samples to make a reliable detection. We propose algorithms based on decentralized sequential hypothesis testing in which the Cognitive Radios sequentially collect the observations, make local decisions and send them to the fusion center for further processing to make a final decision on spectrum usage. The reporting channel between the Cognitive Radios and the fusion center is assumed more realistically as a Multiple Access Channel (MAC) with receiver noise. Furthermore the communication for reporting is limited, thereby reducing the communication cost. We start with an algorithm where the fusion center uses an SPRT-like (Sequential Probability Ratio Test) procedure and theoretically analyze its performance. Asymptotically, its performance is close to the optimal centralized test without fusion center noise. We further modify this algorithm to improve its performance at practical operating points. Later we generalize these algorithms to handle uncertainties in SNR and fading. (C) 2014 Elsevier B.V. All rights reserved.

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In this second of the two-part study, the results of the Tank-to-Wheels study reported in the first part are combined with Well-to-Tank results in this paper to provide a comprehensive Well-to-Wheels energy consumption and greenhouse gas emissions evaluation of automotive fuels in India. The results indicate that liquid fuels derived from petroleum have Well-to-Tank efficiencies in the range of 75-85% with liquefied petroleum gas being the most efficient fuel in the Well-to-Tank stage with 85% efficiency. Electricity has the lowest efficiency of 20% which is mainly attributed due to its dependence on coal and 25.4% losses during transmission and distribution. The complete Well-to-Wheels results show diesel vehicles to be the most efficient among all configurations, specifically the diesel-powered split hybrid electric vehicle. Hydrogen engine configurations are the least efficient due to low efficiency of production of hydrogen from natural gas. Hybridizing electric vehicles reduces the Well-to-Wheels greenhouse gas emissions substantially with split hybrid configuration being the most efficient. Electric vehicles do not offer any significant improvement over gasoline-powered configurations; however a shift towards renewable sources for power generation and reduction in losses during transmission and distribution can make it a feasible option in the future. (C) 2015 Elsevier Ltd. All rights reserved.

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Hydrogen peroxide (H2O2) is a key reactive oxygen species and a messenger in cellular signal transduction apart from playing a vital role in many biological processes in living organisms. In this article, we present phenyl boronic acid-functionalized quinone-cyanine (QCy-BA) in combination with AT-rich DNA (exogenous or endogenous cellular DNA), i.e., QCy-BA subset of DNA as a stimuli-responsive NIR fluorescence probe for measuring in vitro levels of H2O2. In response to cellular H2O2 stimulus, QCy-BA converts into QCy-DT, a one-donor-two-acceptor (D2A) system that exhibits switch-on NIR fluorescence upon binding to the DNA minor groove. Fluorescence studies on the combination probe QCy-BA subset of DNA showed strong NIR fluorescence selectively in the presence of H2O2. Furthermore, glucose oxidase (GOx) assay confirmed the high efficiency of the combination probe QCy-BA subset of DNA for probing H2O2 generated in situ through GOx-mediated glucose oxidation. Quantitative analysis through fluorescence plate reader, flow cytometry and live imaging approaches showed that QCy-BA is a promising probe to detect the normal as well as elevated levels of H2O2 produced by EGF/Nox pathways and post-genotoxic stress in both primary and senescent cells. Overall, QCy-BA, in combination with exogenous or cellular DNA, is a versatile probe to quantify and image H2O2 in normal and disease-associated cells.