diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Intro.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Intro.ipynb
index 7dc02673..cb660f85 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Intro.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Intro.ipynb
@@ -37,7 +37,7 @@
     "execution": {}
    },
    "source": [
-    "## TODO Day Learning Objectives"
+    "## Day Learning Objectives"
    ]
   },
   {
@@ -47,10 +47,9 @@
     "execution": {}
    },
    "source": [
-    "1. Describe the logic behind the socioeconomic pathway framework, and explain how the pathways differ from one another in both climate and socioeconomic variables using CMIP6 data and integrated assessment modeling results, respectively (building off of W2D1).\n",
-    "2. Examine the strengths and weaknesses of integrated assessment modeling practice and compare models whose results are included in the IPCC reports and understand how these results impact the report’s conclusions.\n",
-    "3. Examine the socioeconomic factors at the origin of anthropogenic warming and a *Just Transition*.\n",
-    "\n"
+    "1. Describe the motivation behind the Shared Socioeconomic Pathway (SSP) framework, and explain how the 5 pathways differ from one another in both climate and socioeconomic aspects using CMIP6 data and integrated assessment modeling results, respectively.\n",
+    "2. Examine the strengths and weaknesses of SSP-focussed integrated assessment modeling practice and understand how these support and weaken the IPCC report’s conclusions, respectively.\n",
+    "3. Examine the socioeconomic factors at the origin of anthropogenic warming and a *Just Transition*."
    ]
   }
  ],
@@ -81,7 +80,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial1.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial1.ipynb
index ee54a884..1c259f07 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial1.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial1.ipynb
@@ -59,9 +59,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "368d0c90-ae7e-43d9-ada7-ad42c75f5f95",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import\n",
@@ -73,8 +71,7 @@
    "execution_count": null,
    "id": "f831d869-6072-44f2-8568-ddf04ace1abb",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -103,8 +100,7 @@
    "execution_count": null,
    "id": "6db786f8-e5c4-42a9-9837-e41027b9ad4d",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -122,8 +118,7 @@
    "execution_count": null,
    "id": "e11e3bbb-ce8f-4404-8d04-b6f86d4a9ea9",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -151,8 +146,7 @@
    "execution_count": null,
    "id": "ea9d553f-c3eb-4723-a922-e81f97e1e3ba",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -210,8 +204,7 @@
    "execution_count": null,
    "id": "e3fe59d0-0e89-48ec-b652-2ec007d4c6f3",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -224,8 +217,7 @@
    "execution_count": null,
    "id": "52ca5582-816c-423c-9ed7-cda1c7319731",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -244,8 +236,7 @@
    "execution_count": null,
    "id": "f9b620a1-41ec-4ded-a186-7f598ceaa045",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -280,8 +271,7 @@
    "execution_count": null,
    "id": "9c6b2260-bdb0-4d7b-a07d-41551d5ccf92",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -362,9 +352,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "30a81fb8-c21b-490c-9297-a6705f114957",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -391,8 +379,7 @@
    "execution_count": null,
    "id": "2523a1bd-56cc-4594-b6d6-fa84288cadfb",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -405,8 +392,7 @@
    "execution_count": null,
    "id": "05df13b5-14ce-4515-aaae-7cc9e3765445",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -418,7 +404,6 @@
     "\n",
     "download_link = f\"https://img.climateinteractive.org/2019/09/EnROADS-one-page-guide-to-control-panel-v11-dec-2021.pdf\"\n",
     "render_link = f\"https://img.climateinteractive.org/2019/09/EnROADS-one-page-guide-to-control-panel-v11-dec-2021.pdf\"\n",
-    "# @markdown\n",
     "out = widgets.Output()\n",
     "with out:\n",
     "    print(f\"If you want to download a cheatsheet for the En-ROADS Control Panel:\\n{download_link}\")\n",
@@ -447,9 +432,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "b17595a7-b326-4edb-9f80-b8e21f1d4e5e",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -473,8 +456,7 @@
    "execution_count": null,
    "id": "39410eaf-5020-4646-a821-b90df4c361f7",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -539,7 +521,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial2.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial2.ipynb
index 6e110806..6ceaa9c9 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial2.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial2.ipynb
@@ -263,7 +263,7 @@
     "\n",
     "You might already have clicked through the toggles at the top of the control panel of En-ROADS and tried the different *Views* (Main graphs, Kaya graphs, Miniature graphs). Select now the **Kaya graphs** view and reset the simulator (click on the anti-clockwise circular arrow to 'Reset all policies & assumptions' or just reload the page/model [here](https://en-roads.climateinteractive.org/)).\n",
     "\n",
-    "The Kaya graphs depict four drivers of growth in carbon dioxide emissions from energy use, which reflects about two-thirds of all greenhouse gas emissions (the remaining third of emissions are from land use changes and other gases, such as methane (CH4) and nitrous oxide (N2O), which are not considered here). The corresponding equation, the so-called [***Kaya identity***](https://en.wikipedia.org/wiki/Kaya_identity) below was developed by Yoichi Kaya:\n",
+    "The Kaya graphs depict four drivers of growth in carbon dioxide emissions from energy use, which reflects about two-thirds of all greenhouse gas emissions (the remaining third of emissions are from land use changes and other gases, such as methane (CH$_4$) and nitrous oxide (N$_2$O), which are not considered here). The corresponding equation, the so-called [***Kaya identity***](https://en.wikipedia.org/wiki/Kaya_identity) below was developed by Yoichi Kaya:\n",
     "\n",
     "***CO$_2$ Emissions from Energy = Global Population × GDP per Capita × Energy Intensity of GDP × Carbon Intensity of Energy***\n",
     "\n",
@@ -608,7 +608,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial3.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial3.ipynb
index c80f26fb..2a3bf926 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial3.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial3.ipynb
@@ -43,7 +43,7 @@
    "source": [
     "# Tutorial Objectives\n",
     "\n",
-    "*Estimated timing of tutorial:* 15 minutes\n",
+    "*Estimated timing of tutorial:* 20 minutes\n",
     "\n",
     "The last tutorials covered the necessity for an energy transition to tackle the climate emergency and many solutions at once. As emissions accumulate, it becomes substantially harder to succeed the longer we take to make big changes. This tutorial explores the temporal dimension of action, here policies, by using the Climate Solution Simulator named [En-ROADS](https://www.climateinteractive.org/en-roads/).\n",
     "\n",
@@ -56,9 +56,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "062c4b1a-6239-4644-a0dd-03fe1342fe99",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import\n",
@@ -70,8 +68,7 @@
    "execution_count": null,
    "id": "33ac31c0-ac52-447a-82d7-aec0b98dc6e6",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -100,8 +97,7 @@
    "execution_count": null,
    "id": "8b4722fe-cbd5-484a-be6d-96ed7aafbf62",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -119,8 +115,7 @@
    "execution_count": null,
    "id": "053ee0ea-d704-45c8-8b4b-aad17216710d",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -148,8 +143,7 @@
    "execution_count": null,
    "id": "5b50c362",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -208,8 +202,7 @@
    "execution_count": null,
    "id": "74b1c5e6-ed8f-4ca8-bbab-a0a6c417dced",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -222,8 +215,7 @@
    "execution_count": null,
    "id": "703ee8f2",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -242,8 +234,7 @@
    "execution_count": null,
    "id": "9fd96992-bab2-4494-aeb5-997cc8689746",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -297,9 +288,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c97e6d3d-1718-479b-a19a-ffc6a082347b",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -320,8 +309,7 @@
    "execution_count": null,
    "id": "867fc0d6-6802-4d3d-888b-be960ffd54e8",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -338,7 +326,7 @@
    "source": [
     "# Summary\n",
     "\n",
-    "In this tutorial, we discussed the temporal dimension of the carbon price implementation in order to understand why no policy might be a silver bullet to solve all problems but comes with various ethical and political implications. At last, we discussed a few limitations of the En-ROADs model approach."
+    "In this tutorial, we discussed the temporal dimension of the carbon price implementation in order to understand why no policy might be a silver bullet to solve all problems but comes with various ethical and political implications. "
    ]
   },
   {
@@ -386,7 +374,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial4.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial4.ipynb
index c0c11f54..7600707f 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial4.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial4.ipynb
@@ -38,6 +38,8 @@
    "source": [
     "# Tutorial Objectives\n",
     "\n",
+    "*Estimated timing of tutorial:* 35 minutes\n",
+    "\n",
     "In this tutorial, you will learn about Integrated Assessment Models (IAMs), a class of models that combine climatology, economics, and social science, reflecting the intertwined nature of these domains in addressing climate change. Based on these models the IPCC established the socioeconomic pathway framework. You are going to learn how these pathways differ from one another in both climate and socioeconomic variables as well as assumptions.\n",
     "\n",
     "After finishing this tutorial, you will know how to \n",
@@ -60,9 +62,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )"
@@ -72,7 +72,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1460,
      "status": "ok",
@@ -103,8 +102,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -132,8 +130,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -153,7 +150,6 @@
     "code_folding": [
      0
     ],
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -188,7 +184,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -246,8 +241,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -260,7 +254,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -284,8 +277,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -309,7 +301,7 @@
     "jp-MarkdownHeadingCollapsed": true
    },
    "source": [
-    "In this, and subsequent, tutorials, you will explore Integrated Assessment Models (IAMs) which are the standard class of models used to make climate change projections. IAMs couple a climate model with an economic model, allowing us to evaluate the two-way coupling between economic productivity and climate change severity. IAMs can also account for changes that result from mitigation efforts, which lessen anthropogenic emissions.\n",
+    "In this, and the subsequent, tutorial, you will explore Integrated Assessment Models (IAMs) which are the standard class of models used to make climate change projections. IAMs couple a climate model with an economic model, allowing us to evaluate the two-way coupling between economic productivity and climate change severity. IAMs can also account for changes that result from mitigation efforts, which lessen anthropogenic emissions.\n",
     "\n",
     "Let's start by investigating some IAM model output.\n",
     "\n",
@@ -332,9 +324,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Load SSP data from .csv file\n",
@@ -359,9 +349,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "print(df.SCENARIO.unique())      # print all scenarios\n",
@@ -385,8 +373,8 @@
     "- and **forcing** (`'Diagnostics|MAGICC6|Forcing'`).\n",
     "\n",
     "- As a `REGION`, we choose the `'World'`,\n",
-    "- and our `SCENARIO`s are called `'SSP1-26'` and `'SSP5-85'`.\n",
-    "-  The model of choice for the former scenario is by convention `'IMAGE'` and `'REMIND-MAGPIE'` for the latter, respectively.\n",
+    "- and our `SCENARIO`s are called `'SSP1-Baseline'` and `'SSP5-Baseline'`.\n",
+    "- The model of choice for the former scenario is by convention `'IMAGE'` and `'REMIND-MAGPIE'` for the latter, respectively.\n",
     "\n",
     "A function named `get_SSPs_for_variable()` applies all this generally and is hidden in the next cell. Please execute it, such that the subsequent cells can make use of it. If you are interested in its procedure and want to adjust it, don't forget to save a copy beforehand."
    ]
@@ -395,8 +383,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -447,9 +434,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# put variables of interest in a list\n",
@@ -457,7 +442,7 @@
     "# create new names for structured data series and axes labels\n",
     "val_name = ['GDP (billion US$/yr)', 'Emissions (Mt CO$_2$/yr)',  'Energy use (EJ/yr)', 'Forcing (W/m$^2$)']\n",
     "# choose scenarios of interest and a color for plotting\n",
-    "scenarios = ['SSP1-26', 'SSP5-Baseline']\n",
+    "scenarios = ['SSP1-Baseline', 'SSP5-Baseline']\n",
     "colors = ['darkblue','darkorange']\n",
     "\n",
     "# init figure and axis\n",
@@ -496,7 +481,7 @@
     "\n",
     "Our plots show that the SSP5-Baseline scenario exhibits very high levels of energy use, and emissions (due to fossil fuel exploitation), it marks the upper end of the scenarios in several dimensions (cf. [Kriegler et al. (2014)](https://doi.org/10.1016/j.gloenvcha.2016.05.015)). \n",
     "\n",
-    "The SSP1-26 scenario contrarily caps the increase of energy use by 2030, combined with other actions leading to decreasing emissions and subsequently a decreasing forcing for the second half of the century. However, economic growth continues with half the slope of SSP5-Baseline. In summary, it is the most optimistic projection: we transition to a global society of sustainability-focused growth."
+    "The SSP1-Baseline scenario contrarily caps the increase of energy use by 2030, combined with other actions leading to decreasing emissions and subsequently a decreasing forcing for the second half of the century. However, economic growth continues with half the slope of SSP5-Baseline. In summary, it is the most optimistic projection: we transition to a global society of sustainability-focused growth."
    ]
   },
   {
@@ -566,9 +551,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# put variables of interest in a list\n",
@@ -576,7 +559,7 @@
     "# create new names for structured data series and plot labels\n",
     "val_name = ['Population\\n(millions)', 'GDP (billion US$/yr)']\n",
     "# choose scenarios of interest and a color for plotting\n",
-    "scenarios = ['SSP1-26', 'SSP5-Baseline']\n",
+    "scenarios = ['SSP1-Baseline', 'SSP5-Baseline']\n",
     "colors = ['darkblue','darkorange']\n",
     "\n",
     "# init figure and axis\n",
@@ -620,7 +603,7 @@
     "execution": {}
    },
    "source": [
-    "# Section 1.3: Differences of SSP1 and SSP5\n",
+    "## Section 1.4: Differences of SSP1 and SSP5\n",
     "\n",
     "Major differences are visible when you contrast emissions and assume direct causation with ecosystem health. Increasing emissions then translate into decreasing ecosystem health."
    ]
@@ -631,7 +614,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding exercise 1.3\n",
+    "## Coding exercise 1.4\n",
     "\n",
     "1. Choose two variables to emphasize ecosystem health differences in the SSP1 and SSP5 scenarios and assign them to `vars`. Then assign axis labels with the correct units for plotting to the `val_name` variable.\n",
     "2. Explain to your pod why the chosen variables emphasize a difference in the scenarios and describe this difference based on your current knowledge of the narratives."
@@ -640,9 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# put two variables of interest in a list\n",
@@ -650,7 +631,7 @@
     "# create new names for structured data series and plot labels\n",
     "val_name = ...\n",
     "# choose scenarios of interest and a color for plotting\n",
-    "scenarios = ['SSP1-26', 'SSP5-Baseline']\n",
+    "scenarios = ['SSP1-Baseline', 'SSP5-Baseline']\n",
     "colors = ['darkblue','darkorange']\n",
     "\n",
     "#################################################\n",
@@ -691,9 +672,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -703,7 +682,7 @@
     "# create new names for structured data series and plot labels\n",
     "val_name = ['Emissions\\n(Mt CO$_2$/yr)','Land covered by\\nforest (million ha)']\n",
     "# choose scenarios of interest and a color for plotting\n",
-    "scenarios = ['SSP1-26', 'SSP5-Baseline']\n",
+    "scenarios = ['SSP1-Baseline', 'SSP5-Baseline']\n",
     "colors = ['darkblue','darkorange']\n",
     "\n",
     "\n",
@@ -736,9 +715,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -758,13 +735,12 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
-    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_3\")"
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_4\")"
    ]
   },
   {
@@ -789,7 +765,7 @@
     "\n",
     "It is possible to download the SSP data used in this tutorial, when you provide an email address, from [this IIASA database](https://tntcat.iiasa.ac.at/SspDb/dsd), where all data from the main simulations of the IAMs used in the [IPCC reports](https://www.ipcc.ch/reports/) is freely available.\n",
     "\n",
-    "Find a summary of all SSP narratives in this paper by [Oneill et al. (2017)](https://doi.org/10.1016/j.gloenvcha.2015.01.004).\n",
+    "Find a summary of all SSP narratives in this paper by [O'Neill et al. (2017)](https://doi.org/10.1016/j.gloenvcha.2015.01.004).\n",
     "\n",
     "Find even more information in\n",
     "\n",
@@ -825,7 +801,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial5.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial5.ipynb
index 5c257785..b505eb3a 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial5.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial5.ipynb
@@ -22,11 +22,11 @@
     "\n",
     "**Content creators:** Paul Heubel, Maximilian Puelma Touzel\n",
     "\n",
-    "**Content reviewers:**   Jenna Pearson, Chi Zhang, Ohad Zivan\n",
+    "**Content reviewers:**   Jenna Pearson, Ohad Zivan\n",
     "\n",
-    "**Content editors:** Paul Heubel, Jenna Pearson, Chi Zhang, Ohad Zivan\n",
+    "**Content editors:** Paul Heubel, Jenna Pearson, Ohad Zivan\n",
     "\n",
-    "**Production editors:** Wesley Banfield, Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan\n",
+    "**Production editors:** Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan\n",
     "\n",
     "**Our 2024 Sponsors:** CMIP, NFDI4Earth"
    ]
@@ -40,22 +40,25 @@
    "source": [
     "# Tutorial objectives\n",
     "\n",
-    "* "
+    "*Estimated timing of tutorial:* 25 minutes\n",
+    "\n",
+    "In this tutorial, you discuss the narratives of the SSP framework and step back to reflect on the framework's assumptions and their consequences for modeling socioeconomics and climate futures. It further emphasizes how equity aspects need to be thought of when solving the climate crisis.\n",
+    "\n",
+    "After working through this Tutorial you know how to \n",
+    "\n",
+    "* map Shared Socioeconomic Pathways in a feature space of equality and environmental health,\n",
+    "* reflect on narratives when discussing future scenarios and their socioeconomic implications."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "1af3e766-b9c3-4bf8-815c-4087e7811925",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "#import dicelib  # https://github.com/mptouzel/PyDICE"
+    "import matplotlib.pyplot as plt"
    ]
   },
   {
@@ -63,8 +66,7 @@
    "execution_count": null,
    "id": "bf05ea3d-be91-4007-b4dd-210179c2f6f1",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -93,8 +95,7 @@
    "execution_count": null,
    "id": "e7392de8-f946-453b-bedf-8a07c705ee7f",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -112,8 +113,7 @@
    "execution_count": null,
    "id": "6c10210c-a3d9-4996-a3d3-4bafa4b72637",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -141,8 +141,7 @@
    "execution_count": null,
    "id": "80412217-b5a7-4fed-b29e-b8751eb8c847",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -201,8 +200,7 @@
    "execution_count": null,
    "id": "ddbb472a-a055-4f48-800b-ec9ac36cb3c6",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -215,8 +213,7 @@
    "execution_count": null,
    "id": "2dc2f6c1-637b-4506-a667-45750dd7fbe5",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -230,6 +227,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "693f9f9c-c8c0-4118-99cd-a9ccf1f55766",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Mapping_the_Narrative_Space_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c7ce6e92-a46d-437a-9e03-c5b80eb63474",
@@ -243,14 +251,14 @@
     "\n",
     "Let's begin with a brief recall of the IAM features:\n",
     "\n",
-    "- IAMs resolve the economy spatially, in contrast, the toy model En-ROADs for example, which we applied in Tutorial 1 to 3, aggregates all variables and is non-spatial.\n",
+    "- IAMs resolve the economy spatially, in contrast, the toy model En-ROADS for example, which we applied in Tutorial 1 to 3, aggregates all variables and is non-spatial.\n",
     "- Like En-ROADS, the world models used in IAMs usually have *exogeneous* (externally set) times series for variables, in addition to fixed world system parameters. These exogenous variables are assumed to be under our society's control (e.g. mitigation). \n",
     "- IAMs come equipped with an objective function (a formula that calculates the quantity to be optimized). This function returns the value of a projected future obtained from running the world model under a given climate policy. This value is defined by the time series of these exogenous variables. In this sense, the objective function is what defines \"good\" in \"good climate policy\". \n",
     "- The computation in an IAM is then an optimization of this objective as a function of the time series of these exogenous variables over some fixed time window.\n",
     "\n",
     "Most IAMs are based on *Neo-classical economics* (also referred to as \"establishment economics\"). This is an approach to economics that makes particular assumptions. For example, it is assumed that production, consumption, and valuation of goods and services are driven solely by the supply and demand model. One fundamental concept is *utility* (i.e. economic value), which is not only central to economics but also to decision theory as a whole, which is a research field that mathematically formalizes the activity of *planning* (planning here means selecting strategies based on how they are expected to play out given a model that takes those strategies and projects forward into the future).\n",
     "\n",
-    "As we want to discuss the background of IAM economics, you are going to reflect on these particular *Neo-classical* assumptions."
+    "Six of the most well-established IAMs have been chosen to represent a certain SSP narrative as discussed by Max in the video. Their simulations result in energy use and emissions characteristics for the respective SSP. These narratives try to describe broad socioeconomic trends that are plausible while reflecting worlds in which mitigation and adaptation challenges vary from low to very high.\n"
    ]
   },
   {
@@ -262,7 +270,7 @@
    "source": [
     "## Questions 1\n",
     "\n",
-    "As a follow-up to its presentation in the tutorial video, try now to place all 5 SSP narratives in the three-dimensional feature space yourself. You can use the SSP narrative names as a hint.\n",
+    "As a repetition and a follow-up of the tutorial video, try now to place all 5 SSP narratives in the three-dimensional feature space of ***Intra-nation equality***, ***Inter-nation equality***, and ***Environmental Health*** yourself. You can use the SSP narrative names as a hint.\n",
     "\n",
     "* SSP1: Sustainability\n",
     "* SSP2: Middle of the road\n",
@@ -270,6 +278,8 @@
     "* SSP4: A road divided\n",
     "* SSP5: Fossil Fueled development\n",
     "\n",
+    "As an additional hint, you might want to check out detailed SSP summaries in the 'SSP narratives' section in [this Carbon Brief article](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/).\n",
+    "\n",
     "Which were easy to place? Which were harder? What made them easy or hard to place? Discuss with your pod.\n"
    ]
   },
@@ -277,17 +287,39 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a7b00ec8-495f-4e07-ab13-989dd26b2c92",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "'''\n",
-    "Guidance for TAs: The solution is already given in the slides, to further discuss these slides, please read the detailed SSP summaries in the 'SSP narratives' section from the carbon brief website under https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/\n",
+    "The solution is already given in the slides, to further discuss these slides, please read the detailed SSP summaries in the 'SSP narratives' section from the carbon brief website under https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/\n",
     "'''"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "11591351-d85d-4737-835d-b1ca218f1354",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97a7001b-1122-4f8c-9ef9-b42b03823f21",
+   "metadata": {},
+   "source": [
+    "This feature space is one way to dissect the narratives that underlie the SSPs. \n",
+    "\n",
+    "A consideration of the future socio-economic situation in the light of the resulting challenges is also fruitful. For example, low challenges to mitigation and adaptation due to rapid technological development, relative global equality of income and focus on environmental sustainability arise in SSP1. SSP4, on the other hand, features similarly low challenges to mitigation due to its rapid technological development, but high challenges to climate adaptation due to persistent inequality and poverty in many parts of the world (cf. [Carbon Brief Explainer, Hausfather, 2018](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/)). \n",
+    "Note that mitigation and adaptation responses are not implemented in the SSPs, such that other studies can assess the effects of policies and of impacts by comparing outcomes to those in the reference SSPs. Hence, a large number of studies investigate a variety of policies and projected risks (cf. [O'Neill et al., 2020](https://www.nature.com/articles/s41558-020-00952-0)).\n",
+    "\n",
+    "Let us finally summarize a few advantages and disadvantages of the SSP framework in general."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "35fa283c-f214-45a4-9b45-bf263d989f74",
@@ -297,26 +329,45 @@
    "source": [
     "## Questions 2\n",
     "\n",
-    "The SSP framework. Take a minute to list the strengths and weaknesses of the scenario approach to socio-economic climate projections. \n"
+    "The SSP framework. Take a minute to list the strengths and weaknesses of the scenario approach to socio-economic climate projections you can think of. \n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "c8f40968-8d7a-487f-aeb3-b901ebfe53fd",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "\n",
     "'''\n",
-    "Strength: SSPs are an approach that nicely balances (biased) expert opinion with more objective (but perhaps inaccurate) models.\n",
-    "Weakness: even larger set of assumptions/complexity gives over confidence?\n",
+    "Strengths: SSPs are an approach that nicely balances (biased) expert opinion with more objective (but perhaps inaccurate) models. The framework underlines the importance of baseline assumptions on resulting emissions and temperatures. \n",
+    "There is now more than one baseline/business-as-usual scenario, however, these scenarios result in at least 3.1°C warming (and up to 5.1°C) by 2100. \n",
+    "With the framework, one is easily able to model climate policies and compare them to the benchmark futures. It furthermore allows for climate change-related research globally across research communities and is extendable to other scales, sectors, and issue areas. \n",
+    "Global narrative extensions can be produced and applied in key sectors to support quantitative projections from e.g. energy and land-use models, and projections from IAMs. \n",
+    "\n",
+    "...\n",
+    "\n",
+    "Weaknesses: An even larger set of assumptions/complexity leads to overconfidence while complexity and uncertainty are increased. It is not easy to apply SSPs regionally. \n",
+    "Futures with non-neo-classical economics like no or limited growth in high-income countries or scenarios oriented around eco-communalism are not represented in the SSPs. \n",
+    "There might also be plausible futures that are under-represented including those driven by disruptive events, whether technological, social, political, or environmental, e.g. implications of violent conflicts, the crossing of biophysical and social tipping points or unexpectedly rapid technological innovation; for example, in artificial intelligence or energy efficiency.\n",
+    "...\n",
+    "cf. e.g https://www.nature.com/articles/s41558-020-00952-0\n",
     "'''"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "041ce3f4-15b5-48e5-b810-3194f27f5766",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "28c0a077-c9a0-42d9-ada6-e8b835668c3b",
@@ -324,17 +375,23 @@
     "execution": {}
    },
    "source": [
-    "# Summary"
+    "# Summary\n",
+    "\n",
+    "In this tutorial, you discussed the narratives of the SSP framework and stepped back to reflect on the framework's assumptions and their consequences for modeling socioeconomics and climate futures. It helps to prepare a thoughtful development of your own climate scenario via En-ROADS in the next tutorial. Equality aspects, prerequisites and socioeconomic necessities as well as other implications need to be thought of when solving the climate crisis."
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
-   "id": "9e904e57-b6b9-4ee8-aefb-140dce3c93c2",
-   "metadata": {
-    "execution": {}
-   },
+   "id": "3469e417-cb2e-49a8-82bc-0b600337244c",
+   "metadata": {},
    "source": [
-    "# Resources"
+    "# Resources\n",
+    "\n",
+    "- [Carbon Brief Explainer: How ‘Shared Socioeconomic Pathways’ explore future climate change, Hausfather, 2018](https://www.carbonbrief.org/explainer-how-shared-socioeconomic-pathways-explore-future-climate-change/)\n",
+    "- [The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Riahi et al., Global Environmental Change 42, 169-180 (2017). doi.org/10.1016/j.gloenvcha.2015.01.004](https://doi.org/10.1016/j.gloenvcha.2015.01.004)\n",
+    "- [O’Neill, B.C., Carter, T.R., Ebi, K. et al. Achievements and needs for the climate change scenario framework. Nat. Clim. Chang. 10, 1074–1084 (2020). doi.org/10.1038/s41558-020-00952-0](https://doi.org/10.1038/s41558-020-00952-0)\n",
+    "- [En-ROADS documentation](https://docs.climateinteractive.org/projects/en-roads/en/latest/index.html)"
    ]
   }
  ],
@@ -365,7 +422,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial6.ipynb b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial6.ipynb
index abd0c7ff..8b2c1e24 100644
--- a/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial6.ipynb
+++ b/tutorials/W2D2_TheSocioeconomicsofClimateChange/W2D2_Tutorial6.ipynb
@@ -56,8 +56,7 @@
    "execution_count": null,
    "id": "7550a995-8abf-45a7-83fe-4eb7565d43f4",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -86,8 +85,7 @@
    "execution_count": null,
    "id": "b591486d-dff5-4dc6-b83b-1125977a7758",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -140,6 +138,18 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8e98eb20-8e63-4a64-a9b3-47c2f0ee7383",
+   "metadata": {},
+   "source": [
+    "# Section 1: CO$_2$ Removal\n",
+    "\n",
+    "While substantial emissions mitigations are necessary to reduce future climate suffering, they can not make up for the hundreds of billions of tons of CO$_2$ that humans have already emitted. However, both natural and technological methods for removing CO$_2$ from the atmosphere exist. Although they are presently miniscule compared to the tens-of-gigatons scale of global emissions, some experts expect that CO$_2$ removal methods will play a key role in the future once major mitigation goals have been accomplished. \n",
+    "\n",
+    "Video 1 briefly explains how Carbon Removal is addressed in EN-ROADS. Keep its representation in mind for the following exercises."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a516e969-8b67-4f8a-9d39-061770ffb4c9",
@@ -174,8 +184,7 @@
    "execution_count": null,
    "id": "d485bbc9-f179-4516-bc51-eb34211e8255",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -211,7 +220,9 @@
     "- [En-ROADS User Guide PDF](https://docs.climateinteractive.org/projects/en-roads/en/latest/en-roads-user-guide.pdf)\n",
     "- [Guided Assignment - Simulating Climate Futures in En-ROADS: Short Version](https://www.climateinteractive.org/guided-assignment/)\n",
     "\n",
-    "**A Planetary Crisis Planning Computer Game**\n",
+    "**Planetary Crisis Planning Computer Games**\n",
+    "Play the games listed below to explore alternative societal futures\n",
+    "- [The Climate Game](https://ig.ft.com/climate-game/)\n",
     "- [Half Earth Socialism](https://play.half.earth/).\n"
    ]
   }
@@ -243,7 +254,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,