The economics of bioenergy with carbon capture and storage (BECCS) deployment in a 1.5 °C or 2 °C world
Introduction
Negative emissions technologies (NETs) are valuable in scenarios leading to global warming of 2 °C, and indispensable in meeting the more stringent target of 1.5 °C (de Coninck and Revi, 2018). As a result, the majority of scenarios consistent with these targets feature some form of negative emissions technologies, mainly in the form of afforestation and land use management (AFOLU) and bioenergy with carbon capture and storage (BECCS), while other NETs, like direct air capture or enhanced weathering of minerals, can also be considered (Rogelj et al., 2018). The type of NET deployed, and the scale to which they are deployed, depends on the assumptions made in the models, including, but not limited to, demand-response, level of behavioral change, timing and intensity of climate mitigation action, and NET technology availability and cost. In the most recent IPCC report on global warming of 1.5 °C, BECCS and AFOLU are the main NETs, and the level of annual negative emissions varies from a couple of gigatonnes of CO2 per year 100% met by AFOLU in a low energy demand scenario, to up to 23 GtCO2/yr 90% met by BECCS in a fossil-fuel intensive scenario (Huppmann et al., 2018a, Huppmann et al., 2018a, Huppmann et al., 2018b).
However, the large-scale deployment of these land-based NETs have raised concerns about their environmental (Smith et al., 2016, Fajardy and Mac Dowell, 2017, Fajardy et al., 2018, Harper et al., 2018, Heck et al., 2018) and economic (Kreidenweis et al., 2016, Muratori et al., 2016) implications. From an environmental perspective, there are concerns related to sustainable biomass, land use change, biodiversity loss and water use, among others. While bioenergy can be sourced from wastes and residues that do not have a direct impact on land use, they are estimated to be available at a low scale relative to global primary energy use (Slade et al., 2014, Pour et al., 2018). In addition, using wastes and residues for bioenergy may lead to other environmental concerns, such as soil erosion and other land degradation. Due to higher biomass potential, projections of large-scale deployment of BECCS usually relies on second-generation energy crops and wood from managed forestry (Winchester and Reilly, 2015, Heck et al., 2018). Assessing how much such bioenergy could be sustainably produced without trespassing on planetary boundaries, or contradicting Sustainable Development Goals (SDGs), has been subject to scrutiny, but remains uncertain (Bauen et al., 2010, Beringer et al., 2011, Slade et al., 2014, Creutzig et al., 2015). Ranges of technical bioenergy potential as wide as 100–900 EJ/yr by 2050 can be found in the literature, but there tends to be an agreement towards the lower bound of the ranges, around 100 EJ/yr, when it comes to sustainable potential (see Creutzig et al., 2015, for a review of a large number of studies that quantifies the range for the high agreement among researchers). Disagreements and uncertainty around sustainable removal rate of residues, area of sustainable forestry, land available for bioenergy production and present and future bioenergy yields explain this wide range. Estimating future crop yields is particularly challenging, since most second-generation crops considered by models, such as perennial grasses or woody crops, have only been deployed at the local/experimental level. Based on historical trends in crop yield increase, regular and bioenergy crop yield improvement rates between 0.6% and 3.5% have been considered in the literature (Fisher, et al., 2002, FAO, 2009, Paltsev et al., 2009, Smith et al., 2013, Winchester and Reilly, 2015), assuming a combination of technical change and land management.
Land allocation for bioenergy production have direct impacts on land use change i.e. bioenergy production replaces or displaces other land uses, such as crop or pasture land or natural forests or grassland. There are carbon emissions associated with these direct and indirect land use changes (Harper et al., 2018). With higher yields, less land is needed to produce the same amount of bioenergy crops, and, under the ceteris paribus assumption, less land use changes need to occur, resulting in less land use change emissions. However, higher yields would affect prices and the overall bioenergy production. The magnitudes of change would determine the ultimate impact on emissions.
From an economic perspective, there is concern that land-based NETs such as BECCS could cause increases in food and agricultural commodity prices through competition for land (Lotze-Campen et al., 2013, Rulli et al., 2016, IPCC, 2019). Several studies suggest that the large scale deployment of land-based mitigation strategies, such as bioenergy, BECCS and afforestation, could have a substantial effect on food prices (Kreidenweis et al., 2016, Muratori et al., 2016, Wiltshire, 2016, Popp et al., 2017, Hasegawa et al., 2018). Hasegawa et al. (2018) showed that land-based climate change mitigation strategies would have a more negative effect on food security than climate change itself. Reviewing five Shared Socio-Economic Pathways (SSP), Popp et al. (2017) quantified that climate mitigation policies could lead to an increase in food prices by 110% by 2100. The impact of increased afforestation on food prices was also investigated, with a study showing that afforestation at the scale of 2850 million hectares (Mha) of forested area (to meet a 2 °C target) could lead to a fourfold increase of the food index by 2100 (Kreidenweis et al., 2016).
There are, however, complex interactions to consider between all technologies within the mitigation portfolio, and it can be useful to decouple climate change mitigation strategies in order to isolate the individual impact of each technology on the economy. For example, Muratori et al. (2016) looked at the particular impact of BECCS and CCS on carbon prices, energy trade, commodity trade and commodity prices, by comparing a 2 °C scenario with and without CCS in any form. They found that, while the deployment of bioenergy led to an increase in food prices when CCS was not available, the deployment of BECCS however, allowed for a more efficient use of the biomass by providing the additional service of negative emissions, thereby decreasing the carbon price and relieving pressure on land. Adding CCS to both fossil and biogenic emissions in the mitigation portfolio therefore decreased food prices as compared with a 2 °C scenario without CCS. However, this study did not decouple the effects of BECCS and fossil-based CCS. The model setting in Muratori et al. (2016) did not include the feedback of policies on GDP levels and food prices on food consumption.
Bauer et al. (2018) explore the results from several integrated assessment models in terms of large-scale deployment of bioenergy for achieving long-run climate goals. They found that although much bioenergy is used in combination with CCS, BECCS is not necessarily the driver of bioenergy use. Abandoning BECCS leads to bioenergy reallocation to technologies without CCS.
Our paper extends the literature by integrating several components which are crucial for a comprehensive representation of BECCS technology, including land availability, endogenous land use change, endogenous impacts of policies on GDP, endogenous prices and their effects on the resulting sectoral consumption, direct and indirect land use change emissions, bio-crop production and transport, biomass conversion to electricity with CO2 capture, transport and underground storage of CO2 and the competition of BECCS with other low-carbon technologies. Our approach explicitly represents land use decisions, constraints on land use, and transition costs. To get an integrated analysis of the implications of BECCS, we explore what happens to food prices and land use if BECCS technology is available and trace the associated changes to the energy and economic systems in order to stay at 1.5 °C or 2 °C. We explore not only the effects of increasing bioenergy production, but also the compensating effects of lower carbon prices. This study also investigates different BECCS revenue scenarios to discuss the importance of carbon removal revenues relative to bioelectricity revenues in order to unpack the drivers of BECCS deployment. Finally, our paper also adds to the literature with an exploration of the 1.5 °C target by providing a comparison of climate mitigation scenarios leading to 2 °C and 1.5 °C with and without BECCS.
Section snippets
The EPPA framework
The EPPA model is a multi-region, multi-sector dynamic model of the global economy, capturing the linkages between sectors and regions of the global economy, with a particular focus on energy (Paltsev et al., 2005, Chen et al., 2017). We represent a BECCS technology, explicitly accounting for the energy, land and other costs of producing and transporting the biomass, converting it to electricity, and capturing and storing the emissions. The version of the model used for this paper includes
BECCS within the energy system
First, we explore how the availability or otherwise of BECCS influences the evolution of global energy consumption and supply on a trajectory compatible with 1.5/2 °C scenarios. Fig. 1 presents the primary energy use in the five different scenarios (with the 2 °C scenarios shown as non-transparent and the 1.5 °C scenarios as transparent). In the BAU, global energy consumption grows from approximately 550 EJ in 2005 to up to 1200 EJ in 2100, with a predominance of fossil fuels, accounting for
Discussion and conclusions
The results of this study are a quantification of the potential scale of BECCS deployment and its impact on the economy when considering technology and economics, but excluding sustainability/environmental, political and societal aspects. A key takeaway is that BECCS has the economic potential to be a significant climate mitigation technology. The model accounts for all major components of the BECCS process, including land availability, crop production and transport, biomass conversion to
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors thank Imperial College London for the funding of a President’s PhD Scholarship, as well as the Greenhouse Gas Removal (GGR) grant, funded by the Natural Environment Research Council (NERC), under grant NE/P019900/1. The EPPA model used in this study is supported by an international consortium of government, industry and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change (see the list at: https://globalchange.mit.edu/sponsors/current).
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