Technology adoption at the PoR chlorine cluster

A study on the effect of market & behavioural barriers on technology adoption at the Port of Rotterdam chlorine cluster

Master Thesis (2022)
Author(s)

L.H.D. Oei (TU Delft - Technology, Policy and Management)

Contributor(s)

E. J.L. Chappin – Mentor (TU Delft - Energy and Industry)

Pieter Bots – Graduation committee member (TU Delft - Policy Analysis)

Y.O. Sağdur – Coach

Faculty
Technology, Policy and Management
Copyright
© 2022 Laurens Oei
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Laurens Oei
Graduation Date
02-11-2022
Awarding Institution
Delft University of Technology
Programme
Complex Systems Engineering and Management (CoSEM)
Faculty
Technology, Policy and Management
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Abstract

In order for the Netherlands
to reach CO2 neutrality by 2050, large investments in zero emission
technologies are needed. These investments would comprise out of renewable
energy generation, higher energy efficiency alternatives and electrification of
end uses. Although climate mitigation has become an ever growing societal
concern since the ratification of "het klimaatakkoord", progress in
the industrial sector has been seriously lagging in the Netherlands. In 2021
the reduction of CO2 emissions in the Netherlands stagnated and the emissions
of the industrial sector actually slightly rose. So too in the Port of
Rotterdam, where the chlorine cluster is not showing any significant CO2
reductions. There are several potential explanations why there is a gap between
what should be invested and what actually is invested. They define the gap as,
’the apparent reality that some technologies that would pay off for adopters
are, nevertheless, not adopted’. So, why do decision makers under invest in
zero emission technologies? The explanations of fall into two broad categories:

•Market barriers

•Behavioural barriers



Following the problem situation, this thesis
focused on researching to what extent market & behavioural barriers
contribute to the investment gap in the Port of Rotterdam Chlorine cluster, by
incorporating both market and behavioural barriers in a quantitative investment
model. The incorporation of these barriers in the model result in a range of
investment types, some of them non-optimal and varying in perspectives on
valuing the future. By simulating technology adoption under the assumption of
this range of varying configurations of market and behavioural barriers, it is
possible to determine the effect of those two categories of barriers on
technology adoption at the PoR chlorine cluster. The obtained insights of this
research feed into the larger study of quantitative decision models for the
industrial sector. Where the following main research question is answered:

What is the effect of market and behavioural
barriers on zero emission technology adoption at the PoR chlorine cluster?



To answer the main research question, the model
represents the PoR chlorine cluster on a highly detailed level and bases it's
technical system's configuration on a thorough plant-process-product &
zero-emission technology inventarisation. These two inventarisations give the
current and possible future configuration of the PoR chlorine cluster's
technical system. Consequently, this makes it possible to explicitly model the
technology stock at the chlorine cluster and determine technology adoption on
an asset level. The market & behavioural barriers are represented by 8
evaluation types. These evaluation types represent 8 varying configurations of
the market & behavioural barriers. Consequently, a scenario analysis was
conducted with the model.

The scenario analysis resulted in transition
pathways, total CO2 emissions and total cash flows between 2022-2050. The model
results show that the incorporation of market and behavioural barriers lead to
postponed adoption of zero emission technology adoption. This is reflected by
the lower number of years that these alternatives are installed between 2022
and 2050. The lower adoption lead to an increase of 288% total CO2 emissions
between 2022-2050, compared to the optimal solution. Underneath, the key
findings from the model results are presented…









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