CO2 Capture and Storage with Leakage in an Energy-Climate Model

Geological CO₂ capture and storage (CCS) is among the main near-term contenders for addressing the problem of global climate change. Even in a baseline scenario, with no comprehensive international climate policy, a moderate level of CCS technology is expected to be deployed, given the economic benefits associated with enhanced oil and gas recovery. With stringent climate change control, CCS technologies will probably be installed on an industrial scale. Geologically stored CO₂, however, may leak back to the atmosphere, which could render CCS ineffective as climate change reduction option. This article presents a long-term energy scenario study for Europe, in which we assess the significance for climate policy making of leakage of CO₂ artificially stored in underground geological formations. A detailed sensitivity analysis is performed for the CO₂ leakage rate with the bottom-up energy systems model MARKAL, enriched for this purpose with a large set of CO₂ capture technologies (in the power sector, industry, and for the production of hydrogen) and storage options (among which enhanced oil and gas recovery, enhanced coal bed methane recovery, depleted fossil fuel fields, and aquifers). Through a series of model runs, we confirm that a leakage rate of 0.1%/year seems acceptable for CCS to constitute a meaningful climate change mitigation option, whereas one of 1%/year is not. CCS is essentially no option to achieve CO₂ emission reductions when the leakage rate is as high as 1%/year, so more reductions need to be achieved through the use of renewables or nuclear power, or in sectors like industry and transport. We calculate that under strict climate control policy, the cumulative captured and geologically stored CO₂ by 2100 in the electricity sector, when the leakage rate is 0.1%/year, amounts to about 45,000 MtCO₂. Only a little over 10,000 MtCO₂ cumulative power-generation-related emissions are captured and stored underground by the end of the century when the leakage rate is 1%/year. Overall marginal CO₂ abatement costs increase from a few €/tCO₂ today to well over 150 €/tCO₂ in 2100, under an atmospheric CO₂ concentration constraint of 550 ppmv. Carbon costs in 2100 turn out to be about 40 €/tCO₂ higher when the annual leakage rate is 1%/year in comparison to when there is no CO₂ leakage. Irrespective of whether CCS deployment is affected by gradual CO₂ seepage, the annual welfare loss in Europe induced by the implementation of policies preventing “dangerous anthropogenic interference with the climate system” (under our assumption, implying a climate stabilisation target of 550 ppmv CO₂ concentration) remains below 0.5% of GDP during the entire century.

An Integrated Assessment by Models for Energy Systems Analysis and Life-Cycle Assessment with a Case Study of Advanced Fossil-Fired Power Plants in China

We developed an integrated assessment (IA) using models for energy systems analysis and life-cycle assessment (LCA). Based on this assessment framework, we developed cost-benefit analysis (CBA) case studies for a hypothetical project designed to introduce advanced fossil-fired power generation technologies in China. Our MARKAL model for Japan confirmed that radical reductions (i.e., 80 % by 2050) of carbon dioxide (CO₂) could be attained from energy systems alone and that credit for emission allowances was required. We evaluated life-cycle costs and emissions of carbon dioxide, sulfur oxide, and nitrogen oxide gases for the energy technologies using an LCA model. Further, we applied a power generation planning model for six Chinese grids to provide a power mix structure, potentially producing credit by installing fossil-fired power generation technology and by using baseline grid emission factors with an average cost of electricity. Finally, by using dynamic emission reductions and additional costs from the two models, we conducted case studies of CBA for a hypothetical project to install the technologies in China. This was accomplished by evaluating emission reductions in monetary terms and by applying a life-cycle impact assessment model. A unique feature of our IA is its dynamic (time-varying) assessment of costs and benefits.     

Development of environmental impact monitoring protocol for offshore carbon capture and storage (CCS): A biological perspective

Offshore geologic storage of carbon dioxide (CO₂), known as offshore carbon capture and sequestration (CCS), has been under active investigation as a safe, effective mitigation option for reducing CO₂ levels from anthropogenic fossil fuel burning and climate change. Along with increasing trends in implementation plans and related logistics on offshore CCS, thorough risk assessment (i.e. environmental impact monitoring) needs to be conducted to evaluate potential risks, such as CO₂ gas leakage at injection sites. Gas leaks from offshore CCS may affect the physiology of marine organisms and disrupt certain ecosystem functions, thereby posing an environmental risk. Here, we synthesize current knowledge on environmental impact monitoring of offshore CCS with an emphasis on biological aspects and provide suggestions for better practice. Based on our critical review of preexisting literatures, this paper: 1) discusses key variables sensitive to or indicative of gas leakage by summarizing physico-chemical and ecological variables measured from previous monitoring cruises on offshore CCS; 2) lists ecosystem and organism responses to a similar environmental condition to CO₂ leakage and associated impacts, such as ocean acidification and hypercapnia, to predict how they serve as responsive indicators of short- and long-term gas exposure, and 3) discusses the designs of the artificial gas release experiments in fields and the best model simulation to produce realistic leakage scenarios in marine ecosystems. Based on our analysis, we suggest that proper incorporation of biological aspects will provide successful and robust long-term monitoring strategies with earlier detection of gas leakage, thus reducing the risks associated with offshore CCS.     

Combining policy instruments for sustainable energy systems: An assessment with the GMM model

An assessment of the impact of an illustrative portfolio of policy instruments that address different sustainability concerns in the global energy system in areas of climate change, air pollution and introduction of renewable-energy resources is conducted. The effects of a policy set containing three instruments, implemented either individually or in combination, were examined. The policy instruments under examination in this work include: Cap-and-Trade policies imposing a CO₂ emission reduction target on the global energy system, a renewable portfolio standard that forces a minimum share of renewable electricity generation, and the internalisation of external costs of power generation associated with local pollution. Implementation of these policy instruments significantly changes the structure and environmental performance of the energy sector, and particularly the structure of the electric-generation sector. The positive effects are amplified when the policy instruments are simultaneously applied, illustrating the potential for synergies between these energy-policy domains. The analysis has been conducted with the multi-regional, energy-system Global MARKAL Model (GMM), a “bottom-up” partial-equilibrium model that provides a detailed representation of energy technologies and endogenizes technology learning. ^★A preliminary version of this paper has been presented at the 6th IAEE European Energy Conference on “Modelling in Energy Economics and Policy”, 1–3 September 2004, ETH Zürich, Switzerland.     

Electricity and emission-permits trade as a means of curbing CO2 emissions in the Nordic countries

The four Nordic countries Sweden, Denmark, Finland and Norway have fully integrated electricity grids, implying that electricity trade hitherto has accounted for a crucial part of each country’s power balance. Electricity trade also provides cost-efficient opportunities for the Nordic countries to either jointly or separately fulfil their CO₂ obligations. Assuming the targets that were agreed upon in (the aftermath of) the Kyoto negotiations in 1997, and establishing scenarios where CO₂-emission-permits trade among the Nordic countries is allowed, it is shown that the value of emission trading is somewhat larger than the corresponding value of electricity trade. Furthermore, if both electricity and emission permits can be traded on a common Nordic market this can lead to amplified economic benefits yielding a gain that exceeds the sum of the separate values of electricity and emission permits trade. It is also shown that the additional costs of fulfilling the Kyoto protocol are small compared to the total costs of the Nordic energy system. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modeling a Carbon Capture,Transport, and Storage Infrastructure for Europe

In this paper, we develop a model to analyze the economics of carbon capture, transport, and storage (CCTS) in the wake of expected rising CO₂ prices. We present a scalable mixed integer, multiperiod, welfare-optimizing network model for Europe, called CCTS-Mod. The model incorporates endogenous decisions on carbon capture, pipeline and storage investments, as well as capture, flow and injection quantities based on given costs, CO₂ prices, storage capacities, and point source emissions. Given full information about future costs of CCTS-technology, and CO₂ prices, the model determines a cost minimizing strategy on whether to purchase CO₂ certificates, or to abate the CO₂ through investments into a CCTS-chain on a site by site basis. We apply the model to analyze different scenarios for the deployment of CCTS in Europe, e.g., under high and low CO₂ prices, respectively. We find that beyond CO₂ prices of €50 per t, CCTS can contribute to the decarbonization of Europe’s industry sectors, as long as one assumes sufficient storage capacities (onshore and/or offshore). We find that CCTS is only viable for the power sector if the CO₂ certificate price exceeds €75 per t.     

Energy forecasting and atmospheric CO2 perspectives: two worlds ignore each other

Macroeconomic models predict that the global primary energy demand will increase by a factor of 2–4 by the year 2050. In contrast, climate analyses made by the IPCC claim that CO₂ emissions in 2050 should not exceed the values of 1990 or even be 20% lower. By 2100 emissions should be reduced to one third of the present value. The common wisdom to deal with these opposing trends is the concept of de-carbonization, i.e., the continuous decrease of the carbon emission per unit energy utilization. De-carbonization rates needed to compensate for the growing demand while keeping the CO₂-emissions constant should at least be 2% per year compared to actual values of 0.3%. The potential of different de-carbonization rate measures is analyzed. It is argued that the goal can only be met if per capita energy utilization in the industrialized countries is significantly reduced from their typical level of 5000–10 000 W. As a realistic target we suggest 2000 Watt per capita, the present global average. This would leave expansion capacity for the developing countries which presently have per capita demand between 300 and 1000 W. Based on the example of Switzerland it is shown that the two key issues to attain this goal are the quality of buildings and the demand for mobility. It is concluded that the conversion of the present energy system into a 2000 W system is neither limited by technology nor by finances but by the acceptance of a new life style in which energy is used more efficiently and more intelligently than today. This revised version was published online in July 2006 with corrections to the Cover Date.     

Environmental impact of electricity relocation: A quasi-natural experiment from interregional electricity transmission

Pollutants such as sulfur would concentrate in the source regions and thus the localized impacts are more obvious. Local balance of electricity by transporting coal has resulted in dense concentration of coal-fired power plants in load centers and caused severe environmental problems. Electricity relocation through interregional transmission is another choice for energy transportation to achieve electricity balance across regions and pollution mitigation. Using interregional electricity transmission (IRET) lines in China as a quasi-natural experiment, this paper assesses the environmental impact of electricity relocation. In the assessment, the grid organization of “province as executor” in China is considered because it affects the sphere of IRET's influence on pollution mitigation. Here we show the environmental benefits of electricity relocation. We find that, electricity relocation through interregional transmission leads to the growth rate of sulfur dioxide (SO₂) emission decreasing 7% in landing areas and Sichuan province benefits most from electricity relocation. It is interesting that there is no significant increase of SO₂ emission growth rate in sending areas compared to counterfactuals if there had no IRET due to more integration of clean energy and improved emission efficiency in sending areas. Placebo study and robustness check show that the results are quite convincing. Therefore, IRET provides an appealing choice for China's environmental control in eastern region, and it is not necessarily at the cost of pollution in western region. The methodology can be applied to assess the environmental impacts of other program or policy elsewhere.     

Advancing Energy Access Modelling with Geographic Information System Data

One of the main goals in pursuing sustainable development is to provide universal access to modern energy services, notably through the use of off-grid renewable energy technologies. To date, integrated assessment models (IAMs) poorly address energy access targets. In the context of research dedicated to energy scenarios and climate change mitigation in Africa, we attempt to advance the representation of energy access in one such IAM by using GIS data. In a case study for Ethiopia with the TIAM-ECN model, we demonstrate that by enriching an IAM with information derived from GIS databases, insights are obtained that better capture the dynamics of energy access developments, in comparison to conventional IAM analysis of energy technology deployment pathways. When duly accounting for the geographical spread in demography and technology costs in a developing country, we find that many people may gain access to electricity in remote areas thanks to the availability of affordable off-grid power production options that render expensive grid extensions unnecessary. This effect is not explicitly accounted for in most traditional IAMs. By the middle of the century, off-grid technologies could provide affordable electricity to 70% of the Ethiopian population, based almost entirely on renewable sources such as wind, solar and hydropower.     

Robust Energy Portfolios Under Climate Policy and Socioeconomic Uncertainty

Concerning the stabilization of greenhouse gases, the UNFCCC prescribes measures to anticipate, prevent, or minimize the causes of climate change and mitigate their adverse effects. Such measures should be cost-effective and scientific uncertainty should not be used as a reason for postponing them. However, in the light of uncertainty about climate sensitivity and other underlying parameters, it is difficult to assess the importance of different technologies in achieving robust long-term climate risk mitigation. One example currently debated in this context is biomass energy, which can be used to produce both carbon-neutral energy carriers, e.g., electricity, and at the same time offer a permanent CO₂ sink by capturing carbon from the biomass at the conversion facility and permanently storing it. We use the GGI Scenario Database IIASA [3] as a point of departure for deriving optimal technology portfolios across different socioeconomic scenarios for a range of stabilization targets, focusing, in particular, on new, low-emission scenarios. More precisely, the dynamics underlying technology adoption and operational decisions are analyzed in a real options model, the output of which then informs the portfolio optimization. In this way, we determine the importance of different energy technologies in meeting specific stabilization targets under different circumstances (i.e., under different socioeconomic scenarios), providing valuable insight to policymakers about the incentive mechanisms needed to achieve robust long-term climate risk mitigation.     

Decadal emission estimates of carbon dioxide,sulfur dioxide,and nitric oxide emissions from coal burning in electric power generation plants in India

This study aims to estimate the emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitric oxide (NO) for coal combustion in thermal power plants in India using plant-specific emission factors during the period of 2001/02 to 2009/10. The mass emission factors have been theoretically calculated using the basic principles of combustion under representative prevailing operating conditions in the plants and fuel composition. The results show that from 2001/02 to 2009/10 period, total CO₂ emissions have increased from 324 to 499 Mt/year; SO₂ emissions have increased from 2,519 to 3,840 kt/year; and NO emissions have increased from 948 to 1,539 kt/year from the Indian coal-fired power plants. National average emissions per unit of electricity from the power plants do not show a noticeable improvement during this period. Emission efficiencies for new plants that use improved technology are found to be better than those of old plants. As per these estimates, the national average of CO₂ emissions per unit of electricity varies between 0.91 and 0.95 kg/kWh while SO₂ and NO emissions vary in the range of 6.9 to 7.3 and 2.8 to 2.9 g/kWh, respectively. Yamunagar plant in Haryana state showed the highest emission efficiencies with CO₂ emissions as 0.58 kg/kWh, SO₂ emissions as 3.87 g/kWh, and NO emissions as 1.78 g/kWh, while the Faridabad plant has the lowest emission efficiencies with CO₂ emissions as 1.5 kg/kWh, SO₂ emissions as 10.56 g/kWh, and NO emissions as 4.85 g/kWh. Emission values at other plants vary between the values of these two plants.     

Decentralized control of units in smart grids for the support of renewable energy supply

Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced by a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10¹⁰⁰ feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets.     

The Impact of Uncertainty in Climate Targets and CO2 Storage Availability on Long-Term Emissions Abatement

A major characteristic of our global interactive climate-energy system is the large uncertainty that exists with respect to both future environmental requirements and the means available for fulfilling these. Potentially, a key technology for leading the transition from the current fossil fuel-dominated energy system to a more sustainable one is carbon dioxide capture and storage. Uncertainties exist, however, concerning the large-scale implementability of this technology, such as related to the regional availability of storage sites for the captured CO₂. We analyze these uncertainties from an integrated assessment perspective by using the bottom-up model TIAM-ECN and by studying a set of scenarios that cover a range of different climate targets and technology futures. Our study consists of two main approaches: (1) a sensitivity analysis through the investigation of a number of scenarios under perfect foresight decision making and (2) a stochastic programming exercise that allows for simultaneously considering a set of potential future states-of-the-world. We find that, if a stringent climate (forcing) target is a possibility, it dominates the solution: if deep CO₂ emission reductions are not started as soon as possible, the target may become unreachable. Attaining a stringent climate target comes in any case at a disproportionally high price, which indicates that adaptation measures or climate damages might be preferable to the high mitigation costs such a target implies.     

Global warming implications of facade parameters: A life cycle assessment of residential buildings in Bahrain

On a global scale, the Gulf Corporation Council Countries (GCCC), including Bahrain, are amongst the top countries in terms of carbon dioxide emissions per capita. Building authority in Bahrain has set a target of 40% reduction of electricity consumption and associated CO₂ emissions to be achieved by using facade parameters. This work evaluates how the life cycle CO₂ emissions of buildings are affected by facade parameters. The main focus is placed on direct and indirect CO₂ emissions from three contributors, namely, chemical reactions during production processes (Pco₂), embodied energy (Eco₂) and operational energy (OPco₂). By means of the life cycle assessment (LCA) methodology, it has been possible to show that the greatest environmental impact occurs during the operational phase (80–90%). However, embodied CO₂ emissions are an important factor that needs to be brought into the systems used for appraisal of projects, and hence into the design decisions made in developing projects. The assessment shows that masonry blocks are responsible for 70–90% of the total CO₂ emissions of facade construction, mainly due to their physical characteristics. The highest Pco₂ emissions factors are those of window elements, particularly aluminium frames. However, their contribution of CO₂ emissions depends largely on the number and size of windows. Each square metre of glazing is able to increase the total CO₂ emissions by almost 30% when compared with the same areas of opaque walls. The use of autoclaved aerated concrete (AAC) walls reduces the total life cycle CO₂ emissions by almost 5.2% when compared with ordinary walls, while the use of thermal insulation with concrete wall reduces CO₂ emissions by 1.2%. The outcome of this work offers to the building industry a reliable indicator of the environmental impact of residential facade parameters.     

Economic and environmental impacts of photovoltaic power with the declining subsidy rate in China

Photovoltaic (PV) power is expected to play an important role in reducing global warming and improving energy security. China promotes PV power development by implementing feed-in tariff policies. However, the economic and environmental impacts of substituting coal-fired electricity with PV power, particularly as the subsidy rate declines, are not well-known. This study estimates the economic and environmental impacts in different cases and scenarios by combining life-cycle assessment with input-output analysis. Results indicate that substituting PV power for coal-fired electricity has negative impacts on employment, household income, and tax revenue. Although this substitution can promote economic growth when PV power generation is subsidised, the impact of the substitution on GDP will gradually decline as the subsidy rate is reduced and finally becomes negative. Assuming that the levelized cost of PV power declines following the learning curve, the same results will hold even if PV power generation becomes profitable in the future. Despite its negative impacts on employment, household income and tax revenue, the substitution has huge external values. Therefore, policies are needed to internalise the external value and address the economic impacts of the substitution.     

Institutional quality and environmental sustainability: The role of freedom of press in most freedom of press countries

Despite the fact that there are several attempts in the literature of environmental economics to identify the key determinants of environmental degradation particularly CO₂ emissions, little attention has been given to institutional factors, especially the influence of freedom of press has not been scrutinized. This study therefore is undertaking to close the gap and examine the impact of freedom of the press on CO₂ emissions. The study draws data from 10 countries indexed as the most freedom of press countries from 1993‐ to 2016 due to the availability of data on freedom of press and examines it using the technique of pooled mean group (PMG) belonging to the panel autoregressive distributed lag model. The study further applies the second generation techniques of cross-sectional dependence test, Westerlund cointegration-ECM test to account for cross-sectional dependence of the panel. The main finding of the study indicates that freedom of the press has the capacity to reduce CO₂ emissions in most freedom of press countries. In addition, the result confirms the existence of an inverted U-shaped curve between CO₂ emissions and per capita GDP, validating the environmental Kuznets curve (EKC) hypothesis. Energy use and foreign direct investment as control variables contribute to rising CO₂ emissions in most freedom of press countries. In this regards, the study recommends that freedom of the press should be improved upon through the channel of institutional quality, symmetry, efficiency and reputation effects in order to reduce the incidence of CO₂ emissions.     

典型燃煤电厂机组二氧化碳排放测试及核算研究

为验证二氧化碳排放量的测试技术适用性及可行性,获取燃煤电厂机组碳排放特征,系统比较不同测试方法之间碳排放量的差异,对某典型火电机组二氧化碳排放开展测试,结果表明,不同测试原理及设备二氧化碳排放实测体积分数均较为接近。测试机组CO₂实测体积分数为11.28%～14.21%,与负荷变化呈一定的正相关关系,不同负荷下基准氧含量(体积分数6%)基本无变化。测试机组排放量与负荷正相关,使用了缺省值的指南排放量最高,与其他方法排放量相对偏差均值为31.6%;使用入炉煤实测数据的指南排放量差异不大,相对偏差为0.1%;使用入炉煤实测数据的2版指南排放量高于直接测量法,相对偏差均值为4.9%;直接测量各类方法间相对偏差均值为1.0%,其中在线法与手工法间相对偏差均值为1.2%。CO₂排放强度与负荷负相关,实验条件下,机组负荷越高,碳排放强度越低。     

Modelling and assessing inter-regional trade of CO2 emission reduction units

A cost-efficient way to allocate carbon dioxide (CO₂) emission reductions among countries or regions is to harmonise their marginal reduction costs. This could be achieved by a market of emission reduction units (ERUs). To model such a market, we use a multi-regional MARKAL-MACRO model. It gives insights into the consequences of co-ordinating CO₂ abatement on regional energy systems and economies. As a numerical application, we assess the establishment of a market of ERUs among three European countries for curbing their CO₂ emissions.     

Investments in Power Generation Under Uncertainty—a MIP Specification and Large-Scale Application for EU

Investments in power generation constitute a typical budget allocation problem in the context of multiple objectives, while all factors influencing investor’s decisions for power plants are subject to considerable uncertainties. The paper introduces a multi-objective stochastic model designed to optimize budget allocation decisions for power generation in the context of risk aversion taking into account several sources of uncertainty, especially with regard to volatility of fossil fuel and electricity prices, technological costs, and climate policy variability. Probability distributions for uncertain factors influencing investment decisions are directly derived from the stochastic global energy model PROMETHEUS and thus they take into account complex interactions between variables in the systemic context. In order to fully incorporate stochastic characteristics of the problem, the model is specified as an optimization problem in which the probability that an objective exceeds a given threshold is maximized (risk aversion) subject to a set of deterministic and probabilistic constraints. The model is formulated as a mixed integer program providing complete flexibility on the joint distributions of rates of return of technologies competing for investments, as it can handle non-symmetric distributions and take automatically into account complex covariance patterns as emerging from comprehensive PROMETHEUS stochastic results. The analysis shows that risk is a crucial factor for power generation investments with investors not opting for technologies subject to uncertainty related to climate policies and fossil fuel prices. On the other hand, combination of options with negative covariance tends to benefit in the context of risk-hedging behavior.     

The Kyoto Protocol and non-CO2 Greenhouse Gases and Carbon Sinks

Many trace constituents other than carbon dioxide affect the radiative budget of the atmosphere. The existing international agreement to limit greenhouse gases, the Kyoto Protocol, includes carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF₆) and credit for some carbon sinks. We investigate technological options for reducing emissions of these gases and the economic implications of including other greenhouse gases and sinks in the climate change control policy. We conduct an integreated assessment of costs using the MIT Emissions Prediction and Policy Analysis (EPPA) model combined with estimates of abatement costs for non-CO₂ greenhouse gases and sinks. We find that failure to take advantage of the other gas and sink flexibility would nearly double aggregate Annex B costs. Including all the GHGs and sinks is actually cheaper than if only CO₂ had been included in the Protocol and their inclusion achieves greater overall abatement. There remains considerable uncertainty in these estimates, the magnitude of the savings depends heavily on reference projections of emissions, for example, but these uncertainties do not change the overall conclusion that non-CO₂ GHGs are an important part of a climate control policy.