3e:null 3f:["$","title",null,{"children":"Slide viewer | MARGO Climate framework | Observable"}] 45:T5e0,slide_viewer = (slides, default_slide_id = 0) => { const back = html``; const next = html``; const wrapped_slides = slides.map( s => html`

${s}

` ); const container = html`

${wrapped_slides}

`; const node = html`${container}

${back}${next}

`; const set_slide_index = new_index => { const new_index_clamped = Math.max( 0, Math.min(slides.length - 1, new_index) ); if (node.value !== new_index_clamped) { node.value = new_index_clamped; node.dispatchEvent(new CustomEvent("input")); container.style.marginLeft = "calc(" + -new_index_clamped * 85 + "% + 1em)"; back.disabled = new_index_clamped === 0; next.disabled = new_index_clamped === slides.length - 1; } }; set_slide_index(default_slide_id); back.onclick = () => { set_slide_index(node.value - 1); }; next.onclick = () => { set_slide_index(node.value + 1); }; wrapped_slides.forEach((s, i) => { s.onclick = () => { set_slide_index(i); }; }); return node; }46:[] 43:{"id":"099591c5cb0e381b","slug":"slide-viewer","title":"Slide viewer","thumbnail":"b2759f1e64f0a07ee8e0d5dbb5a8cd06fa9f191c75304ea2f144824218e39a34","access_level":"public","create_time":"$D2021-01-02T16:35:04.905Z","update_time":"$D2021-01-06T17:15:50.693Z","view_time":null,"first_public_time":"$D2021-01-02T17:16:16.416Z","has_unpublished_edits":null,"fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"d50c1b9be1f36075","login":"margo","name":"MARGO Climate framework","avatar_url":"https://avatars-next.observableusercontent.com/8b992c689b5bb260e9385dac0fab6d33f5989a7d6e9db4a92a7b583d85e915b9","tier":"starter_2024","bio":""},"version":113,"publish_version":113,"role":null,"authored":false,"authors":[{"type":"individual","id":"6aca374b28a4bb6d","login":"olivier_plas_123456","name":"","avatar_url":null,"tier":null,"bio":""}],"members":[{"type":"individual","id":"b6cde2fab5c6f5fa","login":"fonsp","name":"Fons van der Plas","avatar_url":"https://avatars-next.observableusercontent.com/edacdd0fa6b6c876851449177905d972d41fe02bd327094b210ded28d855f3c8","tier":null,"role":"editor"},{"type":"individual","id":"d422e4aa2a202591","login":"hdrake","name":"Henri Drake","avatar_url":"https://avatars-next.observableusercontent.com/c4c5a96da46ec3a1fba92ef8f3f8ed3aa98139a5c7c0afbb07d11d7e817e8e00","tier":null,"role":"editor"}],"comments":[{"id":"2ea1134a6c745f24","reply_to_id":null,"content":"So awesome !! I searched for this many times in OHQ.\n\nCan you add a license to this notebook so I can consider including for my notebooks/blog?","create_time":"$D2023-09-01T17:59:34.203Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"fca367047a53a31f","login":"declann","name":"Declan Naughton","avatar_url":"https://avatars-next.observableusercontent.com/b36edfd0f90184ac4c0a8d8726969fe861a1d1fe9417e998413c8a47e6163983","tier":null}}],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Slide viewer","cells":[{"id":0,"value":"md`# Slide viewer`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"viewof slide_index = slide_viewer(cool_slides)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":67,"value":"slide_index","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"$45","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"cool_slides = [a, b, c]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"a = md`### 1. The benefits of avoiding climate suffering\n\nIn the absence of climate action, temperatures would rise over 4.5ºC over preindustrial levels (1800 to 1850 average), causing catastrophic climate impacts. MARGO attempts to quantify this suffering by translating the degree of warming into economic damages (in $ / year). The grey curve below shows how climate damages rise over time, as a percentage of the World Gross Domestic Product (WGDP) in that year, due to uncontrolled temperature increases.\n`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"b = md`### 2. How much does emissions mitigation cost?\n\nUnfortunately, mitigating CO₂ emissions also carries a cost. In MARGO, these costs are proportional to the amount by which CO₂ emissions are reduced, and are presently set to $30 per metric ton of CO₂.\n\n`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"c = md`### 3. Cost-benefit analysis\n\nIn the cost-benefit analysis, one scenario emerges as the most beneficial, or *optimal*, scenario: the one with the *maximum net present benefits*.\n\nIn the plot below, drag around the blue dot and see which emissions mitigation scenarios yields the most net present benefits!\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W46","stdlib":"1"}} 44:"$43:body"