Iasonas
Ioannou
a,
Ángel
Galán-Martín
bc,
Javier
Pérez-Ramírez
*a and
Gonzalo
Guillén-Gosálbez
*a
aInstitute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 1, 8093 Zürich, Switzerland. E-mail: jpr@chem.ethz.ch; gonzalo.guillen.gosalbez@chem.ethz.ch
bDepartment of Chemical, Environmental and Materials Engineering, Universidad de Jaén, Campus Las Lagunillas s/n, 23071 Jaén, Spain
cCenter for Advanced Studies in Earth Sciences, Energy and Environment. Universidad de Jaén, Campus Las Lagunillas s/n, 23071 Jaén, Spain
First published on 31st August 2022
Carbon capture and utilisation (CCU) provides an appealing framework to turn carbon emissions into valuable fuels and chemicals. However, given the vast energy required to activate the CO2 molecule, CCU may have implications on sustainable development that are still poorly understood due to the narrow scope of current carbon footprint-oriented assessments lacking absolute sustainability thresholds. To bridge this gap, we developed a power-chemicals nexus model to look into the future and understand how we could produce 22 net-zero bulk chemicals of crucial importance in a sustainable manner by integrating fossil, CCU routes and power technologies, often assessed separately. We evaluated the environmental performance of these technologies in terms of their contribution to 5 Sustainable Development Goals (SDGs), using 16 life cycle assessment metrics and 9 planetary boundaries (PB) to quantify and interpret the impact values. We found that fossil chemicals could hamper the attainment of SDG 3 on good health and well-being and SDG 13 on climate change. CCU could help meet SDG 13 but would damage other SDGs due to burden-shifting to human health, water scarcity, and minerals and metals depletion impacts. The collateral damage could be mitigated by judiciously combining fossil and CCU routes with carbon-negative power sources guided by optimisation models incorporating SDGs-based performance criteria explicitly. Our work highlights the importance of embracing the SDGs in technology development to sensibly support the low-carbon energy and chemicals transition.
Broader contextCombatting climate change is currently driving sustainable technology development. However, emerging technologies, like carbon capture and utilisation (CCU), may have substantial repercussions on our socio-economic systems and the environment beyond global warming. In 2015, the United Nations put forward 17 Sustainable Development Goals (SDGs) to measure the progress made towards sustainable development. These goals are often evaluated at the national level, while studies applying them to the assessment of emerging low-carbon technologies are very scarce and often qualitative. Here we apply for the first time the SDGs framework to quantitatively evaluate the broad implications of transforming CO2 into key chemicals on sustainable development, elucidating whether efforts to meet the climate action SDG 13 could hamper other SDGs due to burden-shifting. Our large-scale analysis of CCU, which explicitly models the power-chemicals nexus and uses 9 PBs to contextualise the SDGs performance, underscores the importance of evaluating impacts beyond SDG 13 on climate action to avoid myopic solutions eroding our ability to live sustainably. Overall, this study unfolds new avenues to include SDG-based metrics in quantitative assessments in science and engineering while quantifying the potential collateral damage of CCU on sustainable development. |
Technology development for sustainable energy and chemicals provision currently focuses primarily on combatting climate change, which falls within the realm of SDG 13 (climate change action). Accordingly, emerging technologies are often only assessed in terms of their carbon footprint, quantified following life cycle assessment principles (LCA).3–6 These widespread LCA studies omit impacts beyond climate change or evaluate them via indicators that lack impact thresholds, making them hardly interpretable from a global sustainability viewpoint.3,7,8 Consequently, the extent to which future low-carbon technological roadmaps improving SDG 13 could contribute to other dimensions of sustainable development remains unclear because their performance in other SDGs, often evaluated at the national rather than at the technological level,9,10 is overlooked.
Here we argue that SDGs-based assessments of emerging technologies are critical to avoid low-carbon pathways shifting burdens across sustainability dimensions. With this spirit, we focus on studying the broad implications of carbon capture and utilisation (CCU) – a growing trend in low-carbon fuels and chemicals production – on the SDGs attainment. CCU could help curb emissions while creating economic value,11 yet its vast energy requirements are today a major obstacle.12 Notably, the increase in energy demand will require skilled labour for the installation and operation of the power system,13,14 which will impact SDG 4 (quality education) and 8 (decent work and economic growth), respectively. Substantial ongoing research focuses on electro- and thermocatalytic routes converting CO2 into a range of chemicals and fuels, including methanol, formic acid, and ethylene, among others.15 Extensive literature evaluated CCU routes focusing on single technologies or a small subset of them,15–18 omitting their links with the power mix and applying conventional LCA metrics limited in scope, e.g., carbon footprint and fossil resources depletion.7,19,20 However, recent qualitative studies highlighting trade-offs between SDGs in CCU,21 also found in food22 and energy23 systems, and micro-plastics,24 stress the importance of measuring the potential undesired adverse effects of CCU on the SDGs attainment, as we do here.
Until recently, the lack of suitable metrics prevented the use of SDGs in technology-oriented assessments. However, the recent concept of absolute sustainability,25 which allows incorporating the planet's carrying capacity into LCA-based PBs indicators, has unfolded new avenues to perform PBs-SDGs studies26 of emerging technologies. Notably, LCA approaches based on absolute sustainability have started to emerge in past years,27,28 most of them building on the works by Rockstrom et al. (2009)29 and Steffen et al. (2015),30 who defined 9 planetary boundaries (PBs) for humanity to operate the planet safely. These LCA-PB-based assessments provide a reference to interpret the system's performance considering the Earth's carrying capacity,31 which allows contextualising the LCA results from an absolute sustainability and SDGs perspective. Along these lines, Sala et al.25 introduced an LCA-PB-based assessment that combines the Environmental Footprint (EF) LCA method adopted at the EU level32 and the updated LANCA model33,34 with the SDGs framework. This approach essentially mapped 16 LCA impact categories to 5 SDGs and 9 PBs, incorporating absolute sustainability concepts in decision-making. Despite these advances, to our best knowledge, SDG-based methods were never applied to assess low-carbon technologies, including CCU.
Here we capitalise on absolute sustainability methods to expand our limited knowledge of how deploying CCU on a large scale could affect the attainment of SDG 8 and a set of 5 SDGs that can be directly linked to the system's economic and environmental performance, respectively. For this purpose, we built a model of the future chemical industry integrating fossil and CCU routes (Fig. 1) with a tailored power mix to identify carbon-neutral roadmaps according to different criteria and constraints (related to several SDGs) to minimise the system's (i) total cost or (ii) overall transgression level. We found that cost-effective CCU solutions to attain carbon neutrality in 2050 could hamper our ability to meet several SDGs. However, this collateral damage could be mitigated by judiciously combining fossil and renewable-carbon technologies to maximise the SDGs performance. Overall, our analysis highlights the need to incorporate the SDGs into decision-making for technology development and meet SDG 13 on climate change in a more sustainable way.
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Fig. 1 CHEMZERO identifies optimal low-carbon roadmaps for the chemical industry by integrating power and chemical production technologies. The model includes the LCA impact categories of the Environmental Footprint (EF) method, which are connected to 5 SDGs and 9 PBs via an LCA-based PBs-SDGs approach.25 The LCA-based PBs-SDGs method considers 5 SDGs, SDG 3 (good health and well-being), 6 (clean water and sanitation), and 13–15 (climate action, life below water, and life on land, respectively). These SDGs are closely linked to standard LCA indicators, as opposed to others with weaker links to engineering decisions and inherently more qualitative. |
The CO2 raw material for CCU can be sourced from SR-HB37,38 (at 25.0 $ t−1) using a CO2 stream often consumed in urea production,39 or from direct air capture (DAC) by implementing Climeworks’ technology projected to 2050.40 Furthermore, CHEMZERO concurrently optimises the power mix linked to the chemical system following previous work by some of us.41 The bespoke energy system, which powers the eH2, DAC, MeOH, MTO, and MTA, includes both (i) state-of-the-art power technologies and (ii) combined heat and power (CHP) facilities. The system's energy availability is ensured by balancing both intermittent and firm technologies.42
Producing eH2 requires substantial resources, e.g., minerals and metals, which might become scarce,43 constraining the technologies’ potential and deployment. Hence, our model constrains the gradual deployment of power technologies using diffusion rates to capture exogenous factors limiting the speed of deployment (e.g., market forces or social acceptance barriers) and considers resource availability constraints (related to SDG 7). The power technologies considered include oil, coal, natural gas, and bioenergy with and without carbon capture and storage (BECCS), wind (onshore and offshore), solar (photovoltaic, PV), geothermal, nuclear, and hydropower reservoirs. We provide in Section S1.2 of the ESI† information further details on the latter generation technologies. BECCS, alone or integrated with CHP,44 can deliver carbon-negative electricity but requires geological storage capacity to store the CO2 permanently. Furthermore, we assume that CHP plants could satisfy the heat demand (i.e., steam) of the industrial processes and DAC, while purge streams from MeOH production could provide extra heat,17,45 diminishing the natural gas requirements (aligned with SDG 12).
CHEMZERO is formulated as a linear programming (LP) model that seeks pathways towards carbon neutrality subject to various technical, costs and impact-related constraints (eqn (1)). Hence, the model reflects the ambition of making the chemical industry carbon-neutral by the first half of the 21st century, as supported by the European Chemical Industry Council.46 This overall goal could be met at minimum cost by solving the model below.
![]() | (1) |
![]() | (2) |
![]() | (3) |
![]() | (4) |
To draw meaningful conclusions, we study both the aggregated indicator SUSTindex and the transgression level in each individual metric, taking the Earth's carrying capacity as a reference to interpret the results from an absolute sustainability viewpoint. As discussed later, these transgression levels are employed as a proxy for SDGs performance.
![]() | (5) |
![]() | (6) |
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Fig. 3 Transgression of the total safe operating space (SOS, i.e., maximum limit defined on the LCA metrics) for the BAU (brown area), CHEMZEROcost (blue area) and CHEMZEROsust (cyan area) solutions (top), and breakdown of impacts for the latter systems (bottom). The mapping of the LCA indicators and the SDGs of human health (SDG 3), clean water and sanitation (SDG 6), climate change (SDG 13), life below water (SDG 14), and life on land (SDG 15) is based on the work by Sala et al.25 Furthermore, the environmental breakdown is presented based on 9 contributors, namely (1) net CO2 emissions, (2) particulate matter (<2.5 μm) emissions, (3) nitrogen oxides emissions – where (1), (2), and (3) are emitted directly in the chemical processes – (4) grid electricity – consumed directly in the conventional chemical processes – (5) electricity from the CHEMZERO mix, mainly to generate eH2, (6) heat from natural gas, (7) heat from BECCS – both (6) and (7) are consumed directly in the chemical processes and DAC – (8) cooling water – consumed directly in the chemical processes – and (9) other activities, which include inputs of fossil-based resources (or inputs of other nature), and direct emissions to air and water that are not covered in the previously mentioned categories. The environmental impacts are classified according to their quality level as recommended by the European Commission's Joint Research Centre.53,54 |
Moving to the CCU routes, we find that CHEMZEROcost improves the climate change metric and the aggregated index greatly (SUSTindex = 7.3), yet, it leads to significant burden-shifting. Notably, this solution worsens 14 out of the 16 LCA indicators (Fig. 3 – top – blue area), some of them quite substantially, which highlights the perils of myopic cost-effective climate change mitigation strategies. Notably, CHEMZEROcost would make it easier to fulfil SDG 13, but still hamper attaining SDG 3 while also exerting significant pressure on SDGs 6 and 15, seemingly non-critical in the BAU solution (<4.0%). Here, the climate change impact would be zero as imposed in the model (GHG neutrality). However, because this solution would consume fossil resources and a high amount of energy, it would still show a significant transgression in resource depletion – energy – (40.3%). Arguably, this should not be of concern, as CCU and carbon-negative electricity would offset (on a cradle-to-gate basis) the carbon emissions linked to fossil resources usage, as discussed later, while the environmental damage is 17.9% lower than the BAU. This transgression level is followed by particulate matter (21.1%, quality level I), non-cancer human health effects (15.1%, quality level II/III – medium-to-high uncertainty), both linked to SDG 3, resource depletion – mineral and metals – (10.5%, quality level III), related to SDG 15, and water scarcity (9.0%, quality level III), connected to SDG 6.
The CHEMZEROsust solution (Fig. 3 – top – cyan area) alleviates the collateral damage substantially, improving CHEMZEROcost in 13 indicators simultaneously, attaining the best SUSTindex (5.9 vs. 7.3 and 9.2); however, it outperforms the BAU in only 5 metrics. SDGs 6 and 15 would become much less critical in this solution due to the improvements in resource depletion – mineral and metals – (4.1% vs. 10.5%, quality level III), and water scarcity (5.1% vs. 9.0%, quality level III), but meeting SDGs 3 would still be challenging due to its high non-cancer human toxicity (quality level II/III) and particulate matter (quality level I) impact (11.5% and 18.1%, respectively).
The impact breakdown (Fig. 3 – bottom) reveals that many damage categories worsen when deploying CCU because of its large energy requirements. While both CCU solutions consume vast amounts of power, CHEMZEROsust often outperforms CHEMZEROcost due its lower energy consumption, the shift from onshore to offshore wind turbines, and the avoidance of solar panels (Fig. 5, further details on the power mix impacts in Table S7 and Fig. S1 of the ESI†). Focusing on the individual SDGs, particulate matter (SDG 3), critical in all the solutions, is linked in the BAU to the lumped term other activities, followed by the direct release of particulates – below 2 μm – and NOx from the chemical processes and power and heat consumption. In the alternative CCU solutions, the contribution of the power mix is also very significant. The latter causes most of the impact in the human toxicity non-cancer category, which is particularly severe in the CHEMZEROcost solution. Water scarcity (SDG 6), mostly linked to the evaporation losses from the cooling towers in the BAU, worsens in the alternative solutions due to the additional MeOH plants requiring substantial cooling and the hydropower facilities in the power system (Fig. 3, 4 and Fig. S1, ESI†). Climate change (SDG 13) is mostly linked to direct fossil CO2 emissions and power and heat supply in the BAU, while these emissions are offset in the carbon-neutral solutions by consuming DAC CO2 and carbon-negative electricity and heat. Finally, resource depletion – mineral and metals – (SDG 15) worsens in the CCU solutions due, again, to the contribution of the bespoke mix (Table S7, ESI†).
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Fig. 5 Annual power generation and breakdown for the global anthropogenic activities in 2050, as forecasted in the world energy outlook,38 and power generation from the bespoke mixes of the CHEMZEROcost and CHEMZEROsust (primary axis) their respective carbon footprint (secondary axis). |
The BAU solution produces ammonia via SR-HB, and the platform chemicals (ethylene, propylene, benzene, toluene, and xylenes) through cracking, subsequently transforming them into 15 chemicals via conventional routes. In contrast, CHEMZEROcost uses CO2 captured in the Haber–Bosch plants and from the air (0.6 and 1.2 GtCO2, respectively) to produce green MeOH and convert it into olefins via MTO. This solution increases the annual production of methanol by 6.7-fold relative to the BAU, where the majority is produced from the green MeOH process. MTO plants convert most of this methanol into ethylene and propylene, whose demand is mainly covered by the methanolic route (∼70%). Conversely, aromatics are entirely produced via fossil-based cracking since the MTA process is not selected. 231.7 Mt of eH2 are consumed exclusively for green methanol synthesis, and a significant amount of it is lost in the MeOH and MTO processes due to the wastewater by-product.
CHEMZERO sust makes less use of CCU and deploys the green HB process. This solution substantially reduces the amount of methanol produced (from 1433.0 to 636.9 Mt) and the capacity of the MTO process, fully operated with green MeOH. It generates most of the ethylene and propylene from fossil carbon (>75%) and produces all the ammonia via the green HB process, avoiding the CO2 by-product and consuming 43.7% of the 215.0 Mt of eH2 (the rest used for green MeOH synthesis). The carbon feedstock is entirely sourced from DAC plants (0.9 Gt), while the MTA process is again omitted. Hence, using carbon-negative electricity for green ammonia synthesis allows attaining carbon neutrality despite increasing the amount of fossil olefins and reducing the DAC capacity. Finally, the quantity of the co-produced wastewater is reduced significantly.
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Fig. 6 Merit order of chemicals, indicating the CO2 avoidance cost (primary axis) of each chemical (bars) and the total chemical system (black arrow). In addition, we also show the forecasted removal cost, rather than the avoidance cost, for DACCS and BECCS (light orange and green arrow, respectively).57 We further provide the total cost (secondary axis) for the respective solution (red dash line) and the BAU (black dashed line) to meet the 2050's annual avoidance target, equal to 4.0 Gt of CO2eq. The merit order depicts the sequence of the chemical's appeal in the two solutions, replacing the fossil-based pathways entirely, or partially (hybrid), with their renewable alternative to attain a carbon-neutral operation for the chemical system. The avoidance cost is calculated based on eqn (5) and (6). The transition to a carbon-neutral production of the two solutions will require a premium of 16.5 and 33.0% for the CHEMZEROcost and CHEMZEROsust solution, respectively, which can be translated in terms of a CO2 avoidance cost that ranges between 81.9–155.9 $ tCO2eq−1. Benzene, toluene, and xylenes are not represented since the cracking process is not substituted in any of the two solutions. |
This cost is mainly linked to the high energy requirements and the levelised cost of electricity of the carbon-negative energy system covering primarily the eH2 needs (58.4–90.1 $ MW h−1, resulting in eH2 at 2.6–4.0 $ kgH2−1). Moreover, the CO2 feedstock cost would be 62.5 $ tCO2−1 in CHEMZEROcost, which is comparable to the current capture costs in coal and natural gas plants (36–53 and 48–111 $ tCO2−1, respectively).56 Notably, the required premium results in an avoidance cost of 81.9 $ tCO2eq−1, which is cheaper than the forecasted DACCS and BECCS removal costs (i.e., 100.0–300.0, and 100.0–200.0 $ tCO2−1, respectively).57CHEMZEROsust would increase the CO2 feedstock and avoidance cost to 88.7$ tCO2−1 and 155.9 $ tCO2eq−1, respectively, and thus, still remain competitive against DACCS and BECCS. The merit order plots show that most of the avoidance is associated with chemicals with a very large demand, such as ammonia, methanol and polymers (i.e., >190 Mt year−1). The order of the chemicals in the figure depends on the solution, where the avoidance cost of the chemicals increases when moving from CHEMZEROcost to CHEMZEROsust. Low-carbon ammonia emerges as particularly attractive in CHEMZEROcost, even displaying a negative avoidance cost due to the CO2 feedstock it provides (via SR-HB coupled with CCU). In contrast, it shows a higher avoidance potential in CHEMZEROsust for a significantly higher avoidance cost since it consumes a vast amount of carbon negative eH2.
Analysing the carbon storage capacity required by CCU vs. that of NETs, we find that the BAU directly emits (at the production sites, Fig. 4) 2.2 Gt of CO2 (and 4.0 GtCO2eq on a life cycle basis). In contrast, CHEMZEROcost and CHEMZEROsust directly emit 1.2 and 1.3 Gt year−1 of CO2, respectively, which are essentially compensated by the carbon-negative electricity from BECCS and the DAC CO2, making chemicals carbon neutral from cradle-to-gate. Notably, the CCU solutions would need to store 1.63 GtCO2 year−1 (in CHEMZEROcost) and 1.56 GtCO2 year−1 (in CHEMZEROsust) from BECCS in 2050 to reach carbon neutrality. In contrast, making fossil chemicals carbon neutral from cradle-to-gate via CCS coupled with existing infrastructure or NETs (e.g., DACCS and BECCS) would require at least 4.0 GtCO2 year−1 of geological storage capacity. This value corresponds to the GHG footprint of the fossil chemical system, as shown in Fig. 6.
The chemical sector has been a key driver of economic growth (i.e., 7% of the world GDP in 2019),58 and it remains unclear how the estimated 311.0–620.5 B$2019 year−1 needed to become carbon neutral would affect its performance. Nonetheless, global inaction in climate change mitigation would also require substantial worldwide investments for climate adaptation to the 2 °C of warming, i.e., 140.0–300.0 B$2021 year−1 in 2030 and 280.0–500.0 B$2021 year−1 in 2050.59 From a broader perspective, the UN reported that 265.0 B$2017 year−1 would be required to achieve globally SDGs 1 (no poverty) and 2 (zero hunger) by 2030.60 At the same time, meeting SDG 3 in 67 low- and middle-income countries (representing 95% of this group population) would need 274.0–371.0 B$2014 year−1 of additional health spending.61 Moreover, regarding SDG 5 (gender equality), the cost of a lower female employment rate in 2013 in the EU was estimated to be 370.0 B€2013 (491.0 B$2013),62 accounting for (i) resource and (ii) public finance costs. Hence, the investment for attaining carbon neutrality in the chemical sector, based on the technologies considered here, would be similar to those needed for meeting some SDGs at the global or European level. Notwithstanding this, the chemical sector should drastically reduce its fossil carbon emissions to operate sustainably, more so considering that the safe operating space should be shared among all economic sectors.
Lastly, we repeated the calculations including three additional technologies, less mature but which may play a role in the future power mix, i.e., concentrated solar power, solar photovoltaics integrated with utility-scale battery storage, and wind photovoltaics integrated with utility-scale battery storage (Section S2.6 in ESI†). We found that the results would not vary substantially (≤0.2% change in cost and 2.3–12.9% in transgression, obtaining very similar portfolios). Moreover, we also conducted a sensitivity analysis on key model parameters, identifying the production cost of the chemicals, the levelised cost of electricity, and the water electrolysis efficiency as the most influential parameters, always obtaining similar solutions and insights (Section 2.4 in ESI†). Finally, using price elasticities, we investigated the extent to which the demand of chemicals would drop due to the cost increase in the carbon-neutral designs (Section 2.5 in ESI†). We found that the effect of price elasticities is low, leading to very similar demands. Besides, subsidies on low carbon chemicals would result in lower prices and lower demand changes.
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Fig. 7 Summary of the SDGs performance of the three solutions. Bars on SDGs 3, 6, 13, 14 and 15 represent the maximum transgression across the LCA indicators within the respective SDG as depicted in Fig. 3 (i.e., considering the thresholds defined for each of them), while the bar on SDG 8 depict the total cost. |
Moreover, CCU impacts could be further reduced by lowering the energy requirements. Mechanical and chemical recycling of polymers into monomers (or syngas) could curtail the fossil and renewable-carbon demand for chemicals and, consequently, the electrolytic hydrogen (and energy) needs.63 Additionally, biomass could be used as a source of chemicals, via syngas generation or tailored synthesis routes to, e.g., biopolymers, further decreasing the carbon, hydrogen and energy requirements. Furthermore, improving power technologies like solar panels and windmills by, e.g., optimising their supply chains and recycling existing and alternative construction materials, could further mitigate impacts. Lastly, optimising water consumption and product yields, possibly via direct electro routes with high efficiencies not relying on green methanol as an intermediate, could also further improve the environmental appeal of CCU.
From a technical viewpoint, integrating fossil technologies with CCU, DAC and BECCS seems the way forward to attain carbon neutrality with balanced economic and SDGs performance. DAC and BECCS have not been deployed at scale yet, so early adoption of these technologies will be essential to overcome technical and socio-political barriers.64
Attaining carbon neutrality via CCU will very likely require governments' financial support through subsidies (Fig. 6 and 7). However, under carbon neutrality constraints, CCU might be economically competitive with DACCS and BECCS, with the added advantage of requiring much less geological storage. Although the latter has been estimated at 2082 GtCO2,65 it will have to be shared among all sectors and NETs, creating intense global and regional competition for this limited resource.
Overall, our work highlights the inherent trade-offs between SDGs faced in technology development for sustainable energy and chemicals provision, which reinforces the need to embrace a range of sustainability metrics beyond the global warming impact in current assessments. In this context, LCAs based on the SDGs and PBs concepts provide a comprehensive framework to perform such evaluations and guide research and policy-making more sensibly.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2ee01153k |
This journal is © The Royal Society of Chemistry 2023 |