Abstract

In this paper, a regionally disaggregated global energy system model with a detailed treatment of the whole chain of CO₂ capture and storage (CCS) is used to derive the cost-optimal global pattern of CO₂ sequestration in regional detail over the period 2010-2050 under the target of halving global energy-related CO₂ emissions in 2050 compared to the 2005 level. The major conclusions are the following. First, enhanced coalbed methane recovery will become a key early opportunity for CO₂ sequestration, so coalrich regions such as the US, China, and India will play a leading role in global CO₂ sequestration. Enhanced oil recovery will also have a participation in global CO₂ sequestration from the initial stage of CCS deployment, which may be applied mainly in China, southeastern Asia, and West Africa in 2030 and mainly in the Middle East in 2050. Second, CO₂ sequestration will be carried out in an increasing number of world regions over time. In particular, CCS will be deployed extensively in today’s developing countries. Third, an increasing amount of the captured CO₂ will be stored in aquifers in many parts of the world due to their abundant and widespread availability and their low cost. It is shown that the share of aquifers in global CO₂ sequestration reaches 82.0% in 2050.

Keywords

CO₂ Sequestration; Simulation; Optimization; Global Energy System Model

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1. INTRODUCTION

Avoiding dangerous climate change is an increasingly formidable challenge. CO₂ capture and storage (CCS) is now recognized as an important option for mitigating climate change. Research, development, and demonstration for CCS are ongoing not only in developed countries, but also in at least 19 developing countries. Although it has been indicated that CCS has advantages over other CO₂ mitigation options in terms of CO₂ emissions reduction potential and cost-effectiveness (e.g., [1,2]), there are still major hurdles to widespread deployment of CCS. First of all, it must be proven that CO₂ can be permanently and safely stored underground. Second, public acceptance of storing CO₂ underground must be gained.

Under these circumstances, identifying in advance the future likely CO₂ storage sites is considered to be highly useful in overcoming the above two hurdles. This is because much time and effort can be spent on better understanding the geological properties of potential CO₂ storage sites, on giving potential host communities for CO₂ storage sites a detailed explanation on the necessity, scope, and safety of the CO₂ storage project, and on building a reliable relationship with them. Also, taking into account that an important feature of CCS is that it is capital intensive, this would help all stakeholders (including governments, utilities, and CCS industries) make rational decisions on CCS infrastructure design.

Thus, the purpose of this paper is to derive the costoptimal global pattern of CO₂ sequestration in regional detail over the period to 2050 under a stringent CO₂ emissions reduction constraint (i.e., a halving of global energy-related CO₂ emissions in 2050 compared to the 2005 level). The cost-optimal global pattern of interregional CO₂ transportation to CO₂ storage sites is also drawn and analyzed under this constraint. These analyses are done by using the global energy system model REDGEM70 (an acronym for a REgionally Disaggregated Global Energy Model with 70 regions) [3,4], which treats the whole chain of CCS in detail.

2. METHODOLOGY

2.1. Overview of the REDGEM70 Model

REDGEM70 is a technology-rich, bottom-up global energy systems optimization model formulated as an intertemporal linear programming problem. Figure 1 schematically illustrates the structure of the model. With a 5% discount rate, the model is designed to determine the cost-optimal energy strategy (e.g., the cost-optimal

choice of technology options) from 2010 to 2050 at 10-year intervals for each of 70 world regions so that total discounted energy system costs are minimized under constraints on the satisfaction of exogenously given energy end-use demands, the availability of primary energy resources, material and energy balances, the maximum growth rates of new technologies, etc. In the model, price-induced energy demand reductions and energy efficiency improvements, fuel switching to less carbonintensive fuels, and CCS in geologic formations are the three options for CO₂ emissions reduction.

Furthermore, in the current version of the model used in this study, there is also a constraint that global energyrelated CO₂ emissions in 2050 are to be halved compared to the 2005 level. This constraint is the same as that given in the International Energy Agency’s BLUE Map scenario [1,5]. The model has a full flexibility in where CO₂ emissions reduction is achieved to meet this constraint.

Figure 2 shows how the 70 world regions are defined in REDGEM70. These 70 regions are categorized into “energy production and consumption regions” and “energy production regions”. The whole world was first divided into the 48 energy production and consumption regions to which future energy end-use demands are allocated. The 22 energy production regions, which are defined as geographical points, were then distinguished from the energy production and consumption regions to represent the geographical characteristics of the areas endowed with large amounts of fossil energy resources. While the 48 energy production and consumption regions cover the global final energy consumption, all the energy-related activities except final energy consumption are conducted in each of the two region types in the model. Such a detailed regional disaggregation enables the explicit consideration of regional characteristics in terms of energy resource supply, energy demands, CO₂ storage capacity, geography, and climate.

Future trajectories for energy end-use demands were estimated as a function of those for socio-economic driving forces such as population and income in the intermediate B2 scenario developed by [6]. Allocation of the energy end-use demand estimates to the 48 energy production and consumption regions was done by using countryand state-level statistics/estimates (and projections if available) on population, income, geography, energy use by type, and transport activity by mode, and by taking into account the underlying storyline of the B2 scenario that regional diversity might be somewhat preserved throughout the 21st century.

Assumptions on the availability and extraction cost of fossil energy resources are taken from [7]. For biomass resources, REDGEM70 considers not only terrestrial biomass (such as energy crops and modern fuelwood), but also waste biomass. The availability of these biomass resources and excess cropland that can be used for energy purposes without conflicting with other biomass uses such as food production was estimated for each region and each time point. They were estimated assuming that biomass is produced in a sustainable way so that biomass-derived energy carriers can be regarded as carbon neutral. Data for these biomass resources (e.g., resource availability, yields per hectare of land, and supply costs) are provided in [8]. These resource availability estimates were then allocated to the 70 model regions by using country-, state-, and site-level statistics/estimates.

2.2. CCS Sector

In REDGEM70 as shown in Figure 1, the CO₂ generated from power plants (excluding those used for on-site CHP production and biomass-fired steam-cycle power generation), synthetic fuels production plants (excluding those used for converting stranded gas and decentralized small-scale hydrogen production), ethanol production plants, oil/FT refinery plants, and industrial processes can be captured for subsequent sequestration in geologic formations. It is assumed that the captured CO₂ is transported intraregionally (and interregionally if needed) to a storage site and then stored in geologic formations. Data for CO₂ capture technologies are provided in [8,9]. The costs of all types of CO₂ capture technologies, which represent the bulk of the overall CCS costs, are assumed to be reduced by 15.6% from 2010 to 2050 [10].

The cost of intraregionally transporting the captured CO₂ from fossil-fueled plants to a storage site was estimated to be 24.1 US $₂₀₀₇ per tonne of carbon, assuming that it is transported intraregionally through 250 km of pipeline [8,10]. On the other hand, due to the dispersed nature of biomass feedstocks, the intraregional transportation of the captured CO₂ from biomass-fueled plants to a storage site is assumed to suffer from diseconomies of small scale. Based on [8], the cost of intraregionally transporting the captured CO₂ from biomass-fueled plants to a storage site was estimated to be in the range of 59.0 - 95.4 US $₂₀₀₇ per tonne of carbon depending on secondary energy carriers produced from biomass.

REDGEM70 treats the interregional transportation of CO₂ between representative cities/sites in the 70 model regions and is able to determine its cost-optimal evolution path. Figure 3 shows the interregional CO₂ transportation costs as a function of transportation distance for each mode. In advance of model simulations, possible interregional transportation routes were given between representative cities/sites in the 70 model regions and their distances were calculated using geographic information system (GIS) land cover data, GIS land use data, and land elevation data. Thus, the cost of transporting a tonne of carbon between every couple of representative cities/sites in the 70 model regions is an input to the model.

The geologic CO₂ sequestration options included are enhanced oil recovery (EOR), enhanced coalbed methane recovery (ECBMR), depleted gas-field disposal, and aquifer disposal. Table 1 shows the input data for CO₂ sequestration options. In addition to CO₂ sequestration costs listed in Table 1, a monitoring cost of 0.864 US $₂₀₀₇ per tonne of carbon stored is assumed to be required [13].

Figure 4 shows the regional distribution of CO₂ storage capacity. The regional distribution of CO₂ storage capacity in aquifers was derived from data reported in

Conflicts of Interest

The authors declare no conflicts of interest.

References