Optimal allocation of carbon credits to emitting agents in a carbon economy

Reduction of carbon emissions is of paramount importance in the context of global warming. Countries and global companies are now engaged in understanding systematic ways of achieving well defined emission targets. In fact, carbon credits have become significant and strategic instruments of finance for countries and global companies. In this paper, we formulate and suggest a solution to the carbon allocation problem, which involves determining a cost minimizing allocation of carbon credits among different emitting agents. We address this challenge in the context of a global company which is faced with the challenge of determining an allocation of carbon credit caps among its divisions in a cost effective way. The problem is formulated as a reverse auction problem where the company plays the role of a buyer or carbon planning authority and the different divisions within the company are the emitting agents that specify cost curves for carbon credit reductions. Two natural variants of the problem: (a) with unlimited budget and (b) with limited budget are considered. Suitable assumptions are made on the cost curves and in each of the two cases we show that the resulting problem formulation is a knapsack problem that can be solved optimally using a greedy heuristic. The solution of the allocation problem provides critical decision support to global companies engaged seriously in green programs.

The role of sustainable agriculture and renewable-resource management in reducing greenhouse-gas emissions and increasing sinks in China and India

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.

Mechanism design problems in carbon economics

Reduction of carbon emissions is of paramount importance in the context of global warming and climate change. Countries and global companies are now engaged in understanding systematic ways of solving carbon economics problems, aimed ultimately at achieving well defined emission targets. This paper proposes mechanism design as an approach to solving carbon economics problems. The paper first introduces carbon economics issues in the world today and next focuses on carbon economics problems facing global industries. The paper identifies four problems faced by global industries: carbon credit allocation (CCA), carbon credit buying (CCB), carbon credit selling (CCS), and carbon credit exchange (CCE). It is argued that these problems are best addressed as mechanism design problems. The discipline of mechanism design is founded on game theory and is concerned with settings where a social planner faces the problem of aggregating the announced preferences of multiple agents into a collective decision, when the actual preferences are not known publicly. The paper provides an overview of mechanism design and presents the challenges involved in designing mechanisms with desirable properties. To illustrate the application of mechanism design in carbon economics,the paper describes in detail one specific problem, the carbon credit allocation problem.

Decentralised carbon footprint analysis for opting climate change mitigation strategies in India

Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

Model projections for household energy use in India

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO(2) emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO(2) emissions via increased electricity use. (C) 2011 Elsevier Ltd. All rights reserved.

Queuing theoretic and information theoretic capacity of energy harvesting sensor nodes

Energy harvesting sensor networks provide near perpetual operation and reduce carbon emissions thereby supporting `green communication'. We study such a sensor node powered with an energy harvesting source. We obtain energy management policies that are throughput optimal. We also obtain delay-optimal policies. Next we obtain the Shannon capacity of such a system. Further we combine the information theoretic and queuing theoretic approaches to obtain the Shannon capacity of an energy harvesting sensor node with a data queue. Then we generalize these results to models with fading and energy consumption in activities other than transmission.

Mechanism design for green, truthful procurement auctions

Auction based mechanisms have become popular in industrial procurement settings. These mechanisms minimize the cost of procurement and at the same time achieve desirable properties such as truthful bidding by the suppliers. In this paper, we investigate the design of truthful procurement auctions taking into account an additional important issue namely carbon emissions. In particular, we focus on the following procurement problem: A buyer wishes to source multiple units of a homogeneous item from several competing suppliers who offer volume discount bids and who also provide emission curves that specify the cost of emissions as a function of volume of supply. We assume that emission curves are reported truthfully since that information is easily verifiable through standard sources. First we formulate the volume discount procurement auction problem with emission constraints under the assumption that the suppliers are honest (that is they report production costs truthfully). Next we describe a mechanism design formulation for green procurement with strategic suppliers. Our numerical experimentation shows that emission constraints can significantly alter sourcing decisions and affect the procurement costs dramatically. To the best of our knowledge, this is the first effort in explicitly taking into account carbon emissions in planning procurement auctions.

Simplified theory of carrier back-scattering in semiconducting carbon nanotubes: A Kane's model approach

We present a simplified yet analytical formulation of the carrier backscattering coefficient for zig-zag semiconducting single walled carbon nanotubes under diffusive regime. The electron-phonon scattering rate for longitudinal acoustic, optical, and zone-boundary phonon emissions for both inter- and intrasubband transition rates have been derived using Kane's nonparabolic energy subband model.The expressions for the mean free path and diffusive resistance have been formulated incorporating the aforementioned phonon scattering. Appropriate overlap function in Fermi's golden rule has been incorporated for a more general approach. The effect of energy subbands on low and high bias zones for the onset of longitudinal acoustic, optical, and zone-boundary phonon emissions and absorption have been analytically addressed. 90% transmission of the carriers from the source to the drain at 400 K for a 5 mu m long nanotube at 105 V m(-1) has been exhibited. The analytical results are in good agreement with the available experimental data. (c) 2010 American Institute of Physics.

Electron field emission from sp (2)-induced insulating to metallic behaviour of amorphous carbon (a-C) films

The influence of concentration and size of sp (2) cluster on the transport properties and electron field emissions of amorphous carbon films have been investigated. The observed insulating to metallic behaviour from reduced activation energy derived from transport measurement and threshold field for electron emission of a-C films can be explained in terms of improvements in the connectivity between sp (2) clusters. The connectivity is resulted by the cluster concentration and size. The concentration and size of sp (2) content cluster is regulated by the coalescence of carbon globules into clusters, which evolves with deposition conditions.

CO2-fertilization and potential future terrestrial carbon uptake in India

There is huge knowledge gap in our understanding of many terrestrial carbon cycle processes. In this paper, we investigate the bounds on terrestrial carbon uptake over India that arises solely due to CO (2) -fertilization. For this purpose, we use a terrestrial carbon cycle model and consider two extreme scenarios: unlimited CO2-fertilization is allowed for the terrestrial vegetation with CO2 concentration level at 735 ppm in one case, and CO2-fertilization is capped at year 1975 levels for another simulation. Our simulations show that, under equilibrium conditions, modeled carbon stocks in natural potential vegetation increase by 17 Gt-C with unlimited fertilization for CO2 levels and climate change corresponding to the end of 21st century but they decline by 5.5 Gt-C if fertilization is limited at 1975 levels of CO2 concentration. The carbon stock changes are dominated by forests. The area covered by natural potential forests increases by about 36% in the unlimited fertilization case but decreases by 15% in the fertilization-capped case. Thus, the assumption regarding CO2-fertilization has the potential to alter the sign of terrestrial carbon uptake over India. Our model simulations also imply that the maximum potential terrestrial sequestration over India, under equilibrium conditions and best case scenario of unlimited CO2-fertilization, is only 18% of the 21st century SRES A2 scenarios emissions from India. The limited uptake potential of the natural potential vegetation suggests that reduction of CO2 emissions and afforestation programs should be top priorities.

Potential and economics of forestry options for carbon sequestration in India

There is a need to understand the carbon (C) sequestration potential of the forestry option and its financial implications for each country.In India the C emissions from deforestation are estimated to be nearly offset by C sequestration in forests under succession and tree plantations. India has nearly succeeded in stabilizing the area under forests and has adequate forest conservation strategies. Biomass demands for softwood, hardwood and firewood are estimated to double or treble by the year 2020. A set of forestry options were developed to meet the projected biomass needs, and keeping in mind the features of land categories available, three scenarios were developed: potential; demand-driven; and programme-driven scenarios. Adoption of the demand-driven scenario, targeted at meeting the projected biomass needs, is estimated to sequester 78 Mt of C annually after accounting for all emissions resulting from clearfelling and end use of biomass. The demand-driven scenario is estimated to offset 50% of national C emission at 1990 level. The cost per t of C sequestered for forestry options is lower than the energy options considered. The annual investment required for implementing the demand-driven scenario is estimated to be US$ 2.1 billion for six years and is shown to be feasible. Among forestry options, the ranking based on investment cost per t of C sequestered from least cost to highest cost is; natural regeneration-agro-forestry-enhanced natural regeneration (< US$ 2.5/t C)-timber-community-softwood forestry (US$ 3.3 to 7.3 per t of C).

Macro-economic analysis of forestry options on carbon sequestration in India

The forestry sector provides a number of climate change mitigation options. Apart from this ecological benefit, it has significant social and economic relevance. Implementation of forestry options requires large investments and sustained long-term planning. Thus there is a need for a detailed analysis of forestry options to understand their implications on stock and flow of carbon, required investments, value of forest wealth, contribution to GNP and livelihood, demand management, employment and foreign trade. There is a need to evaluate the additional spending on forestry by analysing the environmental (particularly carbon abatement), social and economic benefits. The biomass needs for India are expected to increase by two to three times by 2020. Depending upon the forest types, ownership patterns and land use patterns, feasible forestry options are identified. It is found among many supply options to be feasible to meet the 'demand based needs' with a mix of management options, species choices and organisational set up. A comparative static framework is used to analyze the macro-economic impacts. Forestry accounts for 1.84% of GNP in India. It is characterized by significant forward industrial linkages and least backward linkage. Forestry generates about 36 million person years of employment annually. India imports Rs. 15 billion worth of forest based materials annually. Implementation of the demand based forestry options can lead to a number of ecological, economic and institutional changes. The notable ones are: enhancement of C stock from 9578 to 17 094 Mt and a net annual C-sequestration from 73 to 149 Mt after accounting for all emissions; a trebling of the output of forestry sector from Rs. 49 billion to Rs. 146 billion annually; an increase in GDP contribution of forestry from Rs. 32 billion to Rs. 105 billion over a period of 35 years; an increase in annual employment level by 23 million person years, emergence of forestry as a net contributor of foreign exchange through trading of forestry products; and an increase in economic value of forest capital stock by Rs. 7260 billion with a cost benefit analysis showing forestry as a profitable option. Implementation of forestry options calls for an understanding of current forest policies and barriers which are analyzed and a number of policy options are suggested. (C) 1997 Elsevier Science B.V.

A strategy-proof and budget-balanced mechanism for carbon footprint reduction by global companies

The problem addressed in this paper is concerned with an important issue faced by any green aware global company to keep its emissions within a prescribed cap. The specific problem is to allocate carbon reductions to its different divisions and supply chain partners in achieving a required target of reductions in its carbon reduction program. The problem becomes a challenging one since the divisions and supply chain partners, being autonomous, may exhibit strategic behavior. We use a standard mechanism design approach to solve this problem. While designing a mechanism for the emission reduction allocation problem, the key properties that need to be satisfied are dominant strategy incentive compatibility (DSIC) (also called strategy-proofness), strict budget balance (SBB), and allocative efficiency (AE). Mechanism design theory has shown that it is not possible to achieve the above three properties simultaneously. In the literature, a mechanism that satisfies DSIC and AE has recently been proposed in this context, keeping the budget imbalance minimal. Motivated by the observation that SBB is an important requirement, in this paper, we propose a mechanism that satisfies DSIC and SBB with slight compromise in allocative efficiency. Our experimentation with a stylized case study shows that the proposed mechanism performs satisfactorily and provides an attractive alternative mechanism for carbon footprint reduction by global companies.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Economic tradeoffs in mitigation, due to different atmospheric lifetimes of CO2 and black carbon

Tradeoffs are examined between mitigating black carbon (BC) and carbon dioxide (CO2) for limiting peak global mean warming, using the following set of methods. A two-box climate model is used to simulate temperatures of the atmosphere and ocean for different rates of mitigation. Mitigation rates for BC and CO2 are characterized by respective timescales for e-folding reduction in emissions intensity of gross global product. There are respective emissions models that force the box model. Lastly there is a simple economics model, with cost of mitigation varying inversely with emission intensity. Constant mitigation timescale corresponds to mitigation at a constant annual rate, for example an e-folding timescale of 40 years corresponds to 2.5% reduction each year. Discounted present cost depends only on respective mitigation timescale and respective mitigation cost at present levels of emission intensity. Least-cost mitigation is posed as choosing respective e-folding timescales, to minimize total mitigation cost under a temperature constraint (e.g. within 2 degrees C above preindustrial). Peak warming is more sensitive to mitigation timescale for CO2 than for BC. Therefore rapid mitigation of CO2 emission intensity is essential to limiting peak warming, but simultaneous mitigation of BC can reduce total mitigation expenditure. (c) 2015 Elsevier B.V. All rights reserved.