A holistic platform for accelerating sorbent-based carbon capture.

Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specific source-sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design3 and engineers on optimizing processes4,5, which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant's lifetime, is typically one of the final steps6. Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

The metabolic potential of plastics as biotechnological carbon sources - Review and targets for the future.

The plastic crisis requires drastic measures, especially for the plastics' end-of-life. Mixed plastic fractions are currently difficult to recycle, but microbial metabolism might open new pathways. With new technologies for degradation of plastics to oligo- and monomers, these carbon sources can be used in biotechnology for the upcycling of plastic waste to valuable products, such as bioplastics and biosurfactants. We briefly summarize well-known monomer degradation pathways and computed their theoretical yields for industrially interesting products. With this information in hand, we calculated replacement scenarios of existing fossil-based synthesis routes for the same products. Thereby, we highlight fossil-based products for which plastic monomers might be attractive alternative carbon sources. Notably, not the highest yield of product on substrate of the biochemical route, but rather the (in-)efficiency of the petrochemical routes (i.e., carbon, energy use) determines the potential of biochemical plastic upcycling. Our results might serve as a guide for future metabolic engineering efforts towards a sustainable plastic economy.

What Shall We Do with Steel Mill Off-Gas: Polygeneration Systems Minimizing Greenhouse Gas Emissions.

Both the global steel and chemical industries contribute largely to industrial greenhouse gas (GHG) emissions. For both industries, GHG emissions are strongly related to the consumption of fossil resources. While the chemical industry often releases GHGs as direct process emissions, steel mills globally produce 1.78 Gt of off-gases each year, which are currently combusted for subsequent heat and electricity generation. However, these steel mill off-gases consist of high value compounds, which also can be utilized as feedstock for chemical production and thereby reduce fossil resource consumption and thus GHG emissions. In the present work, we determine climate-optimal utilization pathways for steel mill off-gases. We combine a nonlinear, disjunctive model of the steel mill off-gas separation system with a large-scale linear model of the chemical industry to perform environmental optimization. The results show that the climate-optimal utilization of steel mill off-gases depends on electricity's carbon footprint: For the current electricity grid mix, methane, hydrogen, and synthesis gas are recovered as feedstocks for conventional chemical production and enable a methanol-based chemical industry. For low electricity footprints in the future, the separation of steel mill off-gases supports CO2-based production processes in the chemical industry, supplying up to 30% of the required CO2. By coupling the global steel and chemical industry, industrial GHG emissions can be reduced by up to 79 Mt CO2-equivalents per year. These reductions provide up to 4.5% additional GHG savings compared to a stand-alone optimization of the two industries, showing a limited potential for this industrial symbiosis.

Climate change mitigation potential of carbon capture and utilization in the chemical industry.

Chemical production is set to become the single largest driver of global oil consumption by 2030. To reduce oil consumption and resulting greenhouse gas (GHG) emissions, carbon dioxide can be captured from stacks or air and utilized as alternative carbon source for chemicals. Here, we show that carbon capture and utilization (CCU) has the technical potential to decouple chemical production from fossil resources, reducing annual GHG emissions by up to 3.5 Gt CO2-eq in 2030. Exploiting this potential, however, requires more than 18.1 PWh of low-carbon electricity, corresponding to 55% of the projected global electricity production in 2030. Most large-scale CCU technologies are found to be less efficient in reducing GHG emissions per unit low-carbon electricity when benchmarked to power-to-X efficiencies reported for other large-scale applications including electro-mobility (e-mobility) and heat pumps. Once and where these other demands are satisfied, CCU in the chemical industry could efficiently contribute to climate change mitigation.

Renewable carbon feedstock for polymers: environmental benefits from synergistic use of biomass and CO2.

Polymer production is a major source of greenhouse gas (GHG) emissions. To reduce GHG emissions, the polymer industry needs to shift towards renewable carbon feedstocks such as biomass and CO2. Both feedstocks have been shown to reduce GHG emissions in polymer production, however often at the expense of increased utilization of the limited resources biomass and renewable electricity. Here, we explore synergetic effects between biomass and CO2 utilization to reduce both GHG emissions and renewable resource use. For this purpose, we use life cycle assessment (LCA) to quantify the environmental benefits of the combined utilization of biomass and CO2 in the polyurethane supply chain. Our results show that the combined utilization reduces GHG emissions by 13% more than the individual utilization of either biomass or CO2. The synergies between bio- and CO2-based production save about 25% of the limited resources biomass and renewable electricity. The synergistic use of biomass and CO2 also reduces burden shifting from climate change to other environmental impacts, e.g., metal depletion or land use. Our results show how the combined utilization of biomass and CO2 in polymer supply chains reduces both GHG emissions and resource use by exploiting synergies between the feedstocks.

From Unavoidable CO2 Source to CO2 Sink? A Cement Industry Based on CO2 Mineralization.

The cement industry emits 7% of the global anthropogenic greenhouse gas (GHG) emissions. Reducing the GHG emissions of the cement industry is challenging since cement production stoichiometrically generates CO2 during calcination of limestone. In this work, we propose a pathway towards a carbon-neutral cement industry using CO2 mineralization. CO2 mineralization converts CO2 into a thermodynamically stable solid and byproducts that can potentially substitute cement. Hence, CO2 mineralization could reduce the carbon footprint of the cement industry via two mechanisms: (1) capturing and storing CO2 from the flue gas of the cement plant, and (2) reducing clinker usage by substituting cement. However, CO2 mineralization also generates GHG emissions due to the energy required for overcoming the slow reaction kinetics. We, therefore, analyze the carbon footprint of the combined CO2 mineralization and cement production based on life cycle assessment. Our results show that combined CO2 mineralization and cement production using today's energy mix could reduce the carbon footprint of the cement industry by 44% or even up to 85% considering the theoretical potential. Low-carbon energy or higher blending of mineralization products in cement could enable production of carbon-neutral blended cement. With direct air capture, the blended cement could even become carbon-negative. Thus, our results suggest that developing processes and products for combined CO2 mineralization and cement production could transform the cement industry from an unavoidable CO2 source to a CO2 sink.

Sustainable Conversion of Carbon Dioxide: An Integrated Review of Catalysis and Life Cycle Assessment.

CO2 conversion covers a wide range of possible application areas from fuels to bulk and commodity chemicals and even to specialty products with biological activity such as pharmaceuticals. In the present review, we discuss selected examples in these areas in a combined analysis of the state-of-the-art of synthetic methodologies and processes with their life cycle assessment. Thereby, we attempted to assess the potential to reduce the environmental footprint in these application fields relative to the current petrochemical value chain. This analysis and discussion differs significantly from a viewpoint on CO2 utilization as a measure for global CO2 mitigation. Whereas the latter focuses on reducing the end-of-pipe problem "CO2 emissions" from todays' industries, the approach taken here tries to identify opportunities by exploiting a novel feedstock that avoids the utilization of fossil resource in transition toward more sustainable future production. Thus, the motivation to develop CO2-based chemistry does not depend primarily on the absolute amount of CO2 emissions that can be remediated by a single technology. Rather, CO2-based chemistry is stimulated by the significance of the relative improvement in carbon balance and other critical factors defining the environmental impact of chemical production in all relevant sectors in accord with the principles of green chemistry.

OCTP: A Tool for On-the-Fly Calculation of Transport Properties of Fluids with the Order- n Algorithm in LAMMPS.

We present a new plugin for LAMMPS for on-the-fly computation of transport properties (OCTP) in equilibrium molecular dynamics. OCTP computes the self- and Maxwell-Stefan diffusivities, bulk and shear viscosities, and thermal conductivities of pure fluids and mixtures in a single simulation. OCTP is the first implementation in LAMMPS that uses the Einstein relations combined with the order- n algorithm for the efficient sampling of dynamic variables. OCTP has low computational requirements and is easy to use because it follows the native input file format of LAMMPS. A tool for calculating the radial distribution function (RDF) of the fluid beyond the cutoff radius, while taking into account the system size effects, is also part of the new plugin. The RDFs computed from OCTP are needed to obtain the thermodynamic factor, which relates Maxwell-Stefan and Fick diffusivities. To demonstrate the efficiency of the new plugin, the transport properties of an equimolar mixture of water-methanol were computed at 298 K and 1 bar.

Enrichment of methanol inside pNIPAM gels in the cononsolvency-induced collapse.

Crosslinked poly-N-isopropylacrylamide (pNIPAM) gels adapt to their environment by a unique transition from a flexible, swollen macromolecular network to a collapsed particle. pNIPAM gels are swollen in both, pure water and pure methanol (MeOH). However, a drastic volume loss is observed in mixtures of water and methanol over a wide composition range. This effect is referred to as cononsolvency. Cononsolvency couples the volume phase transition to the transport of the cosolvent into the polymeric network. So far, the mechanisms underlying cononsolvency have not been fully elucidated. To obtain insights on cononsolvency, Raman microspectroscopy was applied to capture spatially resolved spectra distinguishing between the surroundings and the inside of the gel. Here, we used Indirect Hard Modelling (IHM) for the spectral analysis. Mass balancing allowed the calculation of the solvent composition inside the pNIPAM gel. The results show an increased methanol fraction inside the collapsed gel as compared to its surroundings. Furthermore, the sensitivity of the vibrational bands of methanol to its local hydrogen bonding environment allow to derive information about the molecular interactions. The methanol peak shifts measured inside the gel point towards donor-type hydrogen bonds between methanol and the peptide group of pNIPAM in the cononsolvency-induced collapse. The presented data should enhance our understanding of cononsolvency.

Aquatic toxicity of biofuel candidates on Daphnia magna.

The increasing need for carbon-neutral, low-emission transportation sector has led to the development of advanced biofuels with tailor-made production and combustion processes. Even though the large-scale deployment of these advanced biofuels also increases the risk for their release into the environment, their toxic potency remains largely unknown. To identify hazardous biofuel candidates as early as possible, the fuel development process can be expanded by "Green Toxicology". To demonstrate such early Green Toxicology testing, this study investigates the aquatic toxicity for the two biofuel candidates 2-methyltetrahydrofuran (2-MTHF) and 2-methylfuran (2-MF) on Daphnia magna. We performed the prolonged acute immobilisation assay (96 h) and the D. magna reproduction test. 2-MF induced acute effects on D. magna that were two orders of magnitude stronger than those of 2-MTHF. Furthermore, both substances affected the growth and reproductive output of D. magna in a 21 d reproduction test, with 2-MF already inducing effects with concentrations one to two orders of magnitude lower than those of 2-MTHF. Thus, our assessment of the aquatic toxicity suggests that further biofuel development should focus on 2-MTHF. Furthermore, the acute immobilisation test with D. magna was identified as a promising tool for a rapid and sensitive "Green Toxicology" screening of further biofuel candidates.

Second-Order Analytical Uncertainty Analysis in Life Cycle Assessment.

Life cycle assessment (LCA) results are inevitably subject to uncertainties. Since the complete elimination of uncertainties is impossible, LCA results should be complemented by an uncertainty analysis. However, the approaches currently used for uncertainty analysis have some shortcomings: statistical uncertainty analysis via Monte Carlo simulations are inherently uncertain due to their statistical nature and can become computationally inefficient for large systems; analytical approaches use a linear approximation to the uncertainty by a first-order Taylor series expansion and thus, they are only precise for small input uncertainties. In this article, we refine the analytical uncertainty analysis by a more precise, second-order Taylor series expansion. The presented approach considers uncertainties from process data, allocation, and characterization factors. We illustrate the refined approach for hydrogen production from methane-cracking. The production system contains a recycling loop leading to nonlinearities. By varying the strength of the loop, we analyze the precision of the first- and second-order analytical uncertainty approaches by comparing analytical variances to variances from statistical Monte Carlo simulations. For the case without loops, the second-order approach is practically exact. In all cases, the second-order Taylor series approach is more precise than the first-order approach, in particular for large uncertainties and for production systems with nonlinearities, for example, from loops. For analytical uncertainty analysis, we recommend using the second-order approach since it is more precise and still computationally cheap.

Stochastic Technology Choice Model for Consequential Life Cycle Assessment.

Discussions on Consequential Life Cycle Assessment (CLCA) have relied largely on partial or general equilibrium models. Such models are useful for integrating market effects into CLCA, but also have well-recognized limitations such as the poor granularity of the sectoral definition and the assumption of perfect oversight by all economic agents. Building on the Rectangular-Choice-of-Technology (RCOT) model, this study proposes a new modeling approach for CLCA, the Technology Choice Model (TCM). In this approach, the RCOT model is adapted for its use in CLCA and extended to incorporate parameter uncertainties and suboptimal decisions due to market imperfections and information asymmetry in a stochastic setting. In a case study on rice production, we demonstrate that the proposed approach allows modeling of complex production technology mixes and their expected environmental outcomes under uncertainty, at a high level of detail. Incorporating the effect of production constraints, uncertainty, and suboptimal decisions by economic agents significantly affects technology mixes and associated greenhouse gas (GHG) emissions of the system under study. The case study also shows the model's ability to determine both the average and marginal environmental impacts of a product in response to changes in the quantity of final demand.

Selecting CO2 Sources for CO2 Utilization by Environmental-Merit-Order Curves.

Capture and utilization of CO2 as alternative carbon feedstock for fuels, chemicals, and materials aims at reducing greenhouse gas emissions and fossil resource use. For capture of CO2, a large variety of CO2 sources exists. Since they emit much more CO2 than the expected demand for CO2 utilization, the environmentally most favorable CO2 sources should be selected. For this purpose, we introduce the environmental-merit-order (EMO) curve to rank CO2 sources according to their environmental impacts over the available CO2 supply. To determine the environmental impacts of CO2 capture, compression and transport, we conducted a comprehensive literature study for the energy demands of CO2 supply, and constructed a database for CO2 sources in Europe. Mapping these CO2 sources reveals that CO2 transport distances are usually small. Thus, neglecting transport in a first step, we find that environmental impacts are minimized by capturing CO2 first from chemical plants and natural gas processing, then from paper mills, power plants, and iron and steel plants. In a second step, we computed regional EMO curves considering transport and country-specific impacts for energy supply. Building upon regional EMO curves, we identify favorable locations for CO2 utilization with lowest environmental impacts of CO2 supply, so-called CO2 oases.

Nitrogen-Based Fuels: A Power-to-Fuel-to-Power Analysis.

What are the fuels of the future? Seven representative carbon- and nitrogen-based fuels are evaluated on an energy basis in a power-to-fuel-to-power analysis as possible future chemical hydrogen-storage media. It is intriguing to consider that a nitrogen economy, where hydrogen obtained from water splitting is chemically stored on abundant nitrogen in the form of a nontoxic and safe nitrogen-based alternative fuel, is energetically feasible.

Environmental potential of carbon dioxide utilization in the polyurethane supply chain.

Potential environmental benefits have been identified for the utilization of carbon dioxide (CO2) as a feedstock for polyurethanes (PUR). CO2 can be utilized in the PUR supply chain in a wide variety of ways ranging from direct CO2 utilization for polyols as a PUR precursor, to indirect CO2 utilization for basic chemicals in the PUR supply chain. In this paper, we present a systematic exploration and environmental evaluation of all direct and indirect CO2 utilization options for flexible and rigid PUR foams. The analysis is based on an LCA-based PUR supply chain optimization model using linear programming to identify PUR production with minimal environmental impacts. The direct utilization of CO2 for polyols allows for large specific impact reductions of up to 4 kg CO2-eq. and 2 kg oil-eq. per kg CO2 utilized, but the amounts of CO2 that can be utilized are limited to 0.30 kg CO2 per kg PUR. The amount of CO2 utilized can be increased to up to 1.7 kg CO2 per kg PUR by indirect CO2 utilization in the PUR supply chain. Indirect CO2 utilization requires hydrogen (H2). The environmental impacts of H2 production strongly affect the impact of indirect CO2 utilization in PUR. To achieve optimal environmental performance under the current fossil-based H2 generation, PUR production can only utilize much less CO2 than theoretically possible. Thus, utilizing as much CO2 in the PUR supply chain as possible is not always environmentally optimal. Clean H2 production is required to exploit the full CO2 utilization potential for environmental impact reduction in PUR production.

Industry-Cost-Curve Approach for Modeling the Environmental Impact of Introducing New Technologies in Life Cycle Assessment.

The environmental costs and benefits of introducing a new technology depend not only on the technology itself, but also on the responses of the market where substitution or displacement of competing technologies may occur. An internationally accepted method taking both technological and market-mediated effects into account, however, is still lacking in life cycle assessment (LCA). For the introduction of a new technology, we here present a new approach for modeling the environmental impacts within the framework of LCA. Our approach is motivated by consequential life cycle assessment (CLCA) and aims to contribute to the discussion on how to operationalize consequential thinking in LCA practice. In our approach, we focus on new technologies producing homogeneous products such as chemicals or raw materials. We employ the industry cost-curve (ICC) for modeling market-mediated effects. Thereby, we can determine substitution effects at a level of granularity sufficient to distinguish between competing technologies. In our approach, a new technology alters the ICC potentially replacing the highest-cost producer(s). The technologies that remain competitive after the new technology's introduction determine the new environmental impact profile of the product. We apply our approach in a case study on a new technology for chlor-alkali electrolysis to be introduced in Germany.