(525f) Comparison of Processes for Producing OME1 – an Efficient, Economic, and Sustainable E-Fuel?

The transport sector contributes more than 20% of
the worldwide greenhouse gas (GHG) emissions and thus requires substantial
emission reductions. In this regard, a promising alternative to fossil fuels
are e-fuels produced from regenerative electricity, water, and CO₂. Utilizing
CO₂ from direct air capture, industrial point sources, or biomass
processing allows replacing virgin fossil carbon sources. At the same time, some
e-fuels exhibit superior combustion characteristics compared to conventional
fuels. The e-fuel OME₁ has outstanding combustion characteristics
for diesel engines: Alternating carbon-oxygen bonds avoid soot formation and
thereby increase engine efficiency, while keeping nitrogen oxide formation at
low levels [1]. OME₁ can be produced as e-fuel by simply replacing
its raw material fossil methanol by e-methanol [2]; however, such a
production concept is energetically inefficient compared to other e-fuels [3].
In order to overcome this energetic drawback, more efficient production
processes are required.

In this study, we consider four OME₁ synthesis
routes: the established [3], oxidative [4], reductive [5], and dehydrogenative
[6] one. Each route is based on methanol from CO₂ hydrogenation but
differ in the further reaction pathway. As the detail of process knowledge
varies considerably between the four OME₁ routes, a comprehensive
comparison is challenging. Therefore, we compare the routes on three levels
according to the hierarchical methodology shown in Figure 1.

Fig. 1: Hierarchical
comparison methodology.

On Level 1, the raw material consumption for each
synthesis route is calculated using stoichiometric mass balances (i.e.,
assuming no byproducts and complete recycling of unreacted educts or
intermediates). On Level 2, we translate each synthesis route into a process
concept by considering experimental data regarding reaction conditions and
product composition. The use of intermediate-fidelity models [7] enables the computation
of the overall minimum energy demand. Finally, on Level 3, we use rigorous
models in order to gain more insight into each process concept. These models allow
rigorous optimization and a more detailed analysis of their performance.

For the comparison, we introduce three
performance indicators: exergy efficiency, production cost, and GHG emissions. The
exergy efficiency analysis takes into account all material and energy streams
available on the respective hierarchy level. The production cost considers both
operation and capital cost on the most detailed level, whereas only raw
material consumption is considered on the lowest level. On each hierarchy
level, we further conduct a life-cycle assessment for all process concepts in order
to calculate their GHG emissions. Finally, we extend these analyses by
comparing the results for OME₁ to other e-fuels.

Acknowledgement

The authors gratefully acknowledge funding by the German
Federal Ministry of Education and Research (BMFB) within the Kopernikus Project
P2X: Flexible use of renewable resources – exploration, validation, and
implementation of ‘Power-to-X’ concepts.

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