An interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty

In this study, an IFTSP (interval-fuzzy two-stage stochastic programming) method is developed for planning carbon dioxide (CO₂) emission trading under uncertainty. The developed IFTSP incorporates techniques of interval fuzzy linear programming and two-stage stochastic programming within a general optimization framework, which can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions and discrete intervals. The IFTSP cannot only tackle uncertainties expressed as probabilistic distributions and discrete intervals, but also provide an effective linkage between the pre-regulated CO₂ mitigation policies and the associated economic implications. The developed model is applied to a case study of CO₂-emission trading planning of industry systems under uncertainty, where three trading schemes are considered based on different trading participants. The results indicate that reasonable solutions have been generated. They are help for supporting: (a) formulation of desired GHG (greenhouse gas) mitigation policies under various economic and system-reliability constraints, (b) selection of the desired CO₂-emission trading pattern, and (c) in-depth analysis of tradeoffs among system benefit, satisfaction degree, and CO₂ mitigation under multiple uncertainties.     

Potential for reduction of CO2 emissions and a low-carbon scenario for the Brazilian industrial sector

This study discusses the potential for reducing carbon dioxide (CO₂) emissions from energy use by the Brazilian industrial sector in a low-carbon scenario over a horizon until 2030. It evaluates the main mitigation measures, the quantities of this gas avoided and the respective abatement costs. In relation to a benchmark scenario projected for 2030, the reduction of CO₂ emissions estimated here can reach 43%, by adopting energy-efficiency measures, materials recycling and cogeneration, shifting from fossil fuels to renewables or less polluting energy sources and eliminating the use of biomass from deforestation. The set of measures studied here would bring emissions reductions of nearly 1.5 billion tCO₂ over a period of 20 years (2010–2030). This would require huge investments, but the majority of them would have significant economic return and negative abatement costs. However, in many cases there would be low economic attractiveness and higher abatement costs, thus requiring more effective incentives. Brazil is already carrying out various actions toward the mitigation measures proposed here, but there are still substantial barriers to realize this potential. Therefore, a collective effort from both the public and private sectors is needed for the country to achieve this low-carbon scenario.     

Clean energy scenarios for Australia

Australia, a major producer and user of coal, has the highest per capita greenhouse gas emissions in the industrialised world. This study investigates whether in theory such a ‘fossil-fuel dependent’ country could achieve a 50% reduction in CO₂ emissions from stationary energy by 2040, compared with its 2001 emissions. To do this scenarios are developed, using a combination of forecasting and backcasting methods, under conditions of continuing economic growth and a restriction to the use of existing commercial technologies with small improvements. The principal scenario achieves the above target by implementing on the demand-side a medium-level of efficient energy use and substantial solar hot water together with a supply side combination of mainly natural gas, bioenergy and wind power. In doing so the scenario also achieves a 78% reduction in CO₂ emissions from electricity. Within the large uncertainties in future prices, it is possible that the economic savings from efficient energy use could pay for all or a large part of the additional costs of renewable energy.     

A human needs approach to reducing atmospheric carbon

Recent research has shown that once CO₂ has been emitted to the atmosphere, it will take centuries for natural removal. Clearly, the longer we delay deep reductions in CO₂, the greater the risk that total greenhouse gas emissions will exceed prudent limits for avoiding dangerous anthropogenic change. We evaluate the three possible technical approaches for climate change mitigation: emission reduction methods, post-emission draw down of CO₂ from the atmosphere, and geoengineering. We find that the first two approaches are unlikely to deliver the timely reductions in CO₂ needed, while geoengineering methods either deliver too little or are too risky. Given the deep uncertainties in both future climate prediction and energy availability, it seems safest to actively plan for a much lower energy future. We propose a general ‘shrink and share’ approach to reductions in both fossil-fuel use and carbon emissions, with basic human needs satisfaction replacing economic growth as the focus for economic activity. Only with deep cuts in energy and carbon can we avoid burdening future generations with the high energy costs of air capture.     

A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty

In this study, a two-stage inexact-stochastic programming (TISP) method is developed for planning carbon dioxide (CO₂) emission trading under uncertainty. The developed TISP incorporates techniques of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) within a general optimization framework. The TISP can not only tackle uncertainties expressed as probabilistic distributions and discrete intervals, but also provide an effective linkage between the pre-regulated greenhouse gas (GHG) management policies and the associated economic implications. The developed method is applied to a case study of energy systems and CO₂ emission trading planning under uncertainty. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired GHG abatement policies under various economic and system-reliability constraints.     

Analysis of CO2 emissions reduction potential in secondary production and semi-fabrication of non-ferrous metals

Industrial sector growth in developing countries requires the provision of alternatives to guarantee sustainable development. Improving energy efficiency and fuel switching are two measures to reduce CO₂ emissions in the industrial sector, with natural gas and low-carbon electricity as the most feasible options in the short term. In this work, a linear programming optimization model has been developed to study the potential of energy efficiency improvement and fuel substitution for CO₂ emissions reduction, at national level in the non-ferrous metals industry. The energy resource/end-use device allocation problem in secondary metal production and semi-fabrication has been modeled. Using this model, the particular case of Colombia, where low-carbon electricity is available, has been studied. By improving energy efficiency, energy use and CO₂ emissions can be reduced significantly, 73% and 72%, respectively, at negative costs. Further CO₂ emissions reductions, up to 88%, are possible with fuel switching to low-carbon electricity, increasing the costs for the energy system; however, cost reductions caused by energy efficiency improvement outweigh cost increments of fuel switching. Benefits achieved with fuel substitution using low-carbon electricity can be lost if hydropower is not available; in such a case, efficient natural gas-fired end-use devices are preferable.     

Incorporating uncertainty analysis into life cycle estimates of greenhouse gas emissions from biomass production

Before further investments are made in utilizing biomass as a source of renewable energy, both policy makers and the energy industry need estimates of the net greenhouse gas (GHG) reductions expected from substituting biobased fuels for fossil fuels. Such GHG reductions depend greatly on how the biomass is cultivated, transported, processed, and converted into fuel or electricity. Any policy aiming to reduce GHGs with biomass-based energy must account for uncertainties in emissions at each stage of production, or else it risks yielding marginal reductions, if any, while potentially imposing great costs.This paper provides a framework for incorporating uncertainty analysis specifically into estimates of the life cycle GHG emissions from the production of biomass. We outline the sources of uncertainty, discuss the implications of uncertainty and variability on the limits of life cycle assessment (LCA) models, and provide a guide for practitioners to best practices in modeling these uncertainties. The suite of techniques described herein can be used to improve the understanding and the representation of the uncertainties associated with emissions estimates, thus enabling improved decision making with respect to the use of biomass for energy and fuel production.     

Reducing the greenhouse gas footprint of shale gas

Shale gas is viewed by many as a global energy game-changer. However, serious concerns exist that shale gas generates more greenhouse gas emissions than does coal. In this work the related published data are reviewed and a reassessment is made. It is shown that the greenhouse gas effect of shale gas is less than that of coal over long term if the higher power generation efficiency of shale gas is taken into account. In short term, the greenhouse gas effect of shale gas can be lowered to the level of that of coal if methane emissions are kept low using existing technologies. Further reducing the greenhouse gas effect of shale gas by storing CO₂ in depleted shale gas reservoirs is also discussed, with the conclusion that more CO₂ than the equivalent CO₂ emitted by the extracted shale gas could be stored in the reservoirs at significantly reduced cost.     

Energy efficiency improvements in ammonia production—perspectives and uncertainties

The paper discusses the energy consumption and energy saving potential for a major energy-intensive product in the chemical industry-ammonia, based on technologies currently in use and possible process improvements. The paper consists of four parts. In the first part, mainly references to various ammonia production technologies are given. Energy consumption, emissions and saving potentials are discussed in the second part. Thereby, the situation in Europe, the US and India is highlighted and various data sources are compared. In the third part of the paper, a novel approach for modeling energy efficiency improvements is described that accounts for uncertainties and unobserved heterogeneity in the production processes. Besides new investments, revamping investments are also included in the modeling and the development of the production stock is accounted for. Finally, in the fourth part, this approach is applied to the modeling of energy efficiency improvements and CO₂ emission reductions in ammonia production. Thereby, considerable improvements in specific energy use and CO₂ emissions are found in the reference scenario, yet under the assumption of high oil and gas prices, a partial switch to coal based technologies is expected which lowers notably the CO₂ efficiency. Introduction of a CO₂ penalty under a certificate trading or other regime is on contrary found to foster energy efficiency and the use of low carbon technologies.     

Sectoral CO2 emission reductions in Turkey: Preparing for DOHA 2020

In this study, CO₂ emissions in different sectors in Turkey were examined in order to serve as a foundation for planning future reduction of greenhouse gas emissions. These reductions are being planned in accordance with the Kyoto Protocol, of which Turkey is a signatory, and which was re-examined by the Doha Climate Change Conference in 2009. For this purpose, variation of the total factor efficiencies of CO₂ emissions per capita for many developed and developing countries including Turkey (35 countries in total) were examined by data envelopment analysis and Malmquist Index approaches. It was aimed to determine the sectors in Turkey that should be the primary foci for reductions of CO₂ emissions and which actions might be taken before Doha 2020 oriented towards reductions in CO₂ emissions in these sectors. Meanwhile, current regulations and perspectives for greenhouse gas plans developed within the scope of Vision 2023 were discussed.     

Assessing the role of renewable energy policies in landfill gas to energy projects

Methane (CH₄) is the second most prevalent greenhouse gas and has a global warming potential at least 28 times as high as carbon dioxide (CO₂). In the United States, Municipal Solid Waste (MSW) landfills are reported to be the third-largest source of human-made methane emissions, responsible for 18% of methane emissions in 2011. Capturing landfill gas (LFG) for use as an energy source for electricity or heat produces alternative energy as well as environmental benefits. A host of federal and state policies encourage the development of landfill gas to energy (LFGE) projects. This research provides the first systematic economic assessment of the role of these policies on adoption decisions. Results suggest that Renewable Portfolio Standards and investment tax credits have contributed to the development of these projects, accounting for 13 of 277 projects during our data period from 1991 to 2010. These policy-induced projects lead to 10.4 MMTCO₂e reductions in greenhouse gas emissions and a net benefit of $41.8 million.     

An optimization methodology for identifying robust process integration investments under uncertainty

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures.     

Electricity savings and CO2 emissions reduction in buildings sector: How important the network losses are in the calculation?

The increase of CO₂ emissions and the emerging climate change are the most serious environmental problems nowadays and limit economic development. This increase is mainly attributed to the growing world population and the related growth in energy demand, which results in the vast consumption of fossil fuels in the power generation sector. Significant actions for the implementation of energy saving measures have been adopted worldwide for reducing greenhouse gas emissions. CO₂ calculators have been developed to evaluate the effectiveness of these measures, relating energy to CO₂ emissions. These calculators include in most cases the entire power system. The purpose of this work was to evaluate the role of the electricity networks' losses in the actual CO₂ reduction potential, following the implementation of energy saving measures, in relation to the network's voltage level in which the infrastructure is connected. Buildings are representative due to their volume and to different voltage levels of power supply. The work presented was conducted in the framework of the Intelligent Energy Europe Programme entitled Bottom Up to Kyoto (BUtK), as a part of an evaluation of the CO₂ emissions' reduction potential through energy savings measures in 6 municipalities of EU's New Member States.     

Emissions reduction scenarios in the Argentinean Energy Sector

In this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO₂ emission savings of the energy sector in Argentina over the 2010–2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic cost of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO₂ price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO₂ price leverages additional investments in hydropower. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO₂ price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts an 11.3% reduction. The main reasons for this difference include varying assumptions about technology cost and availability, CO₂ storage capacity, and the ability to import bioenergy. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. According to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.     

Benefits of using an optimization methodology for identifying robust process integration investments under uncertainty—A pulp mill example

This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO₂ emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Strömberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO₂ emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.     

Review of policies and measures for energy efficiency in industry sector

Energy efficiency in industry plays key roles in improving energy security, environmental sustainability and economic performance. It is particularly important in strategies to mitigate climate change. The evidence of great potential for cost-effective efficiency-derived reductions in industrial energy use and greenhouse gas (GHG) emissions have prompted governments to implement numerous policies and measures aimed at improving their manufacturing industries’ energy efficiency. What can be learned from these many and varied initiatives? This paper provides foundation for policy analysis for enhancing energy efficiency and conservation in industry, by surveying more than 300 policies, encompassing about 570 measures, implemented by governments in IEA countries, Brazil, China, India, Mexico, Russia and South Africa. It outlines the measures’ main features, their incidence of use, and their connections with specific technical actions and key stakeholders (i.e., how and where measures affect the energy efficiency of industry). It also examines the key features underlying the measures’ success: (1) potential to reduce energy use and CO₂ emissions cost-efficiently; (2) ease of policy development, execution and assessment and (3) ancillary societal effects.     

A decomposition analysis of CO2 emissions from energy use: Turkish case

Environmental problems, especially “climate change” due to significant increase in anthropogenic greenhouse gases, have been on the agenda since 1980s. Among the greenhouse gases, carbon dioxide (CO₂) is the most important one and is responsible for more than 60% of the greenhouse effect. The objective of this study is to identify the factors that contribute to changes in CO₂ emissions for the Turkish economy by utilizing Log Mean Divisia Index (LMDI) method developed by Ang (2005) [Ang, B.W., 2005. The LMDI approach to decomposition analysis: a practical guide. Energy Policy 33, 867–871]. Turkish economy is divided into three aggregated sectors, namely agriculture, industry and services, and energy sources used by these sectors are aggregated into four groups: solid fuels, petroleum, natural gas and electricity. This study covers the period 1970–2006, which enables us to investigate the effects of different macroeconomic policies on carbon dioxide emissions through changes in shares of industries and use of different energy sources. Our analysis shows that the main component that determines the changes in CO₂ emissions of the Turkish economy is the economic activity. Even though important changes in the structure of the economy during 1970–2006 period are observed, structure effect is not a significant factor in changes in CO₂ emissions, however intensity effect is.     

An innovative indicator of carbon dioxide emissions for developing countries: A study of Taiwan

Ever since the Kyoto Protocol entered into force, the issues of climate change and greenhouse gas (GHG) emissions have drawn more and more attention globally. However, the major concern of the Kyoto Protocol to reduce the overall GHG emissions might be inaccessible for most developing countries, which rely heavily on the energy-intensive industries for exports and economic growth. In this study, an innovative indicator of net carbon dioxide (CO₂) emissions, which excludes the emissions corresponding to the exports, is proposed to explicitly reveal domestic situations of developing countries. By introducing the indicator of net CO₂ emissions to top five energy-intensive industries in Taiwan, the analysis indicates that the increase in CO₂ emissions from 1999 to 2004 is mostly contributed by the expanded exports rather than the domestic demand. The distinct growth patterns of the apparent and net CO₂ emissions also imply the transformation of the industrial sector. It is expected that, for developing countries, the concept of net emissions may not only serve as a proper interim target during the process of international negotiations over GHG reductions but also highlights the prominence of addressing the emissions from the industrial sector as the top priority.