Emerging technologies are expected to contribute to environmental sustainable development. However, throughout the development of novel technologies, it is unknown whether emerging technologies can lead to reduced environmental impacts compared to a potentially displaced mature technology. Additionally, process steps suspected to be environmental hotspots can be improved by process engineers early in the development of the emerging technology. In order to determine the environmental impacts of emerging technologies at an early stage of development, prospective life cycle assessment (LCA) should be performed. However, consistency in prospective LCA methodology is lacking. Therefore, this article develops a framework for a prospective LCA in order to overcome the methodological inconsistencies regarding prospective LCAs. The methodological framework was developed using literature on prospective LCAs of emerging technologies, and therefore, a literature review on prospective LCAs was conducted. We found 44 case studies, four review papers, and 17 papers on methodological guidance. Three main challenges for conducting prospective LCAs are identified: Comparability, data, and uncertainty challenges. The issues in defining the aim, functionality, and system boundaries of the prospective LCAs, as well as problems with specifying LCIA methodologies, comprise the comparability challenge. Data availability, quality, and scaling are issues within the data challenge. Finally, uncertainty exists as an overarching challenge when applying a prospective LCA. These three challenges are especially crucial for the prospective assessment of emerging technologies. However, this review also shows that within the methodological papers and case studies, several approaches exist to tackle these challenges. These approaches were systematically summarized within a framework to give guidance on how to overcome the issues when conducting prospective LCAs of emerging technologies. Accordingly, this framework is useful for LCA practitioners who are analyzing early-stage technologies. Nevertheless, further research is needed to develop appropriate scale-up schemes and to include uncertainty analyses for a more in-depth interpretation of results.
Summary
Previous studies showed that using carbon dioxide (CO2) as a raw material for chemical syntheses may provide an opportunity for achieving greenhouse gas (GHG) savings and a low‐carbon economy. Nevertheless, it is not clear whether carbon capture and utilization benefits the environment in terms of resource efficiency. We analyzed the production of methane, methanol, and synthesis gas as basic chemicals and derived polyoxymethylene, polyethylene, and polypropylene as polymers by calculating the output‐oriented indicator global warming impact (GWI) and the resource‐based indicators raw material input (RMI) and total material requirement (TMR) on a cradle‐to‐gate basis. As carbon source, we analyzed the capturing of CO2 from air, raw biogas, cement plants, lignite‐fired power, and municipal waste incineration plants. Wind power serves as an energy source for hydrogen production. Our data were derived from both industrial processes and process simulations. The results demonstrate that the analyzed CO2‐based process chains reduce the amount of GHG emissions in comparison to the conventional ones. At the same time, the CO2‐based process chains require an increased amount of (abiotic) resources. This trade‐off between decreased GHG emissions and increased resource use is assessed. The decision about whether or not to recycle CO2 into hydrocarbons depends largely on the source and amount of energy used to produce hydrogen.
CO2-based production technologies unveil the possibility
of sustainable production in the chemical industry. However, so-called
carbon capture and utilization (CCU) options do not inevitably lead
to improved environmental performance, which is especially uncertain
for emerging technologies compared to present production practices.
Thus, far, emerging CCU technologies have been environmentally assessed
with conventional life cycle assessment (LCA). Therefore, this study
aims to develop a methodology for applying prospective LCA to emerging
production technologies from the laboratory to industrial scale. The
developed four-step approach for implementing prospective LCA is applied
to the case of electrochemical formic acid (FA) production via supercritical
CO2 (scCO2) under consideration of different
reactor designs to guide process engineers from an environmental standpoint.
While using prospective LCA, the underlying modeling approach relies
on consequential LCA (cLCA). Fourteen out of the 15 analyzed impact
categories (IC) reveal lower environmental impacts for the scale-ups,
which are based on the best-case assumptions and on a flow-through
regime compared to the conventional FA production. Nevertheless, the
impacts of the scale-ups that are based on a batch reactor (BR) and
a three compartment cell (TCC) are higher than for the best case and
the flow-through reactor scale-up.
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