Commit 40a7157f authored by Markus Millinger's avatar Markus Millinger

Minor changes to manuscript and a comment in the code to adapt

parent 29e4e88f
......@@ -124,7 +124,7 @@ biomass \sep power-to-x \sep energy system \sep LCA \sep sector coupling \sep in
%Ancillary data table required for subversion of the codebase. Kindly replace examples in right column with the correct information about your current code, and leave the left column as it is.
\begin{table*}[H]
\begin{table}[H]
\begin{tabular}{|l|p{6.5cm}|p{8.5cm}|}
\hline
\textbf{Nr.} & \textbf{Code metadata description} & \textbf{Please fill in this column} \\
......@@ -150,7 +150,7 @@ C9 & Support email for questions & \href{mailto:markus.millinger@ufz.de}{markus.
\end{tabular}
\caption{Code metadata (mandatory)}
\label{}
\end{table*}
\end{table}
\linenumbers
......@@ -278,7 +278,7 @@ This results in a pareto analysis of cost-optimal fuel deployment at different G
As can be seen in the example for the transport sector, the model chooses at what time-point changes between runs at different targets occur. For instance, at the maximal GHG-target, some capacities of BeetEtOH (sugar beet-based bioethanol) are only used for a few years. At a slightly lower target, these overcapacities do not emerge. Also, PBtL (Power-to-Biomass-to-Liquid) is less deployed, in order to fully disappear at lower targets. With decreasing targets, the diversity of options decreases, and currently common options are less deployed. Electric vehicles appear across all targets and can thus be seen as the most robust option in the example.
The combination of detailed cost and GHG emission calculations as well as system competition enables a systems perspective on different options, as the resource use is optimized taking all renewable competitions into account. A merit order plot shows the resulting GHG abatement costs and potentials of different options given feedstock and demand restrictions under competition (Figure \ref{fig:meritOrderGHG_S1})
The combination of detailed cost and GHG emission calculations as well as system competition enables a systems perspective on different options, as the resource use is optimized taking all renewable competitions into account. A merit order plot shows the resulting GHG abatement costs and potentials of different options given feedstock and demand restrictions under competition (Figure \ref{fig:meritOrderGHG_S1}). \textbf{Explain graph!}
\begin{figure*}[h!]
\centering
......
......@@ -80,7 +80,7 @@ for scenario = 1:noScenarios
g.landMax = 10^6.*linspace(1,0,s.runTime); %ha
end
%Choose weather year - current data includes 2016-18 (year 1-3)
%Automate this! Choose weather year - current data includes 2016-18 (year 1-3)
s.weatherYear = 3;
%Calculation of hourly residual load and other power metrics
......
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