27:null 28:["$","title",null,{"children":"A Global Crisis, An Unequal Responsibility | Laia's | Observable"}] 2d:T7ed,Plot.plot({ width: 800, height: 160, marginLeft: 160, marginRight: 80, x: { axis: false, label: null, domain: [0, 100] }, y: { domain: ["Population", "Historical CO₂ emissions"], // 🔁 ordre invertit label: null }, color: { domain: ["Rich countries", "All others", "International transport"], range: ["#d8b365", "#5ab4ac", "#dddddd"] }, marks: [ // 🔸 Barres apilades Plot.barX(barData, { x: "percent", y: "categoria", fill: "group" }), // 🔹 Percentatges centrats Plot.text(barData.filter(d => d.group !== "International transport"), { x: (d, i, data) => { const prev = data .slice(0, i) .filter(e => e.categoria === d.categoria) .reduce((a, b) => a + b.percent, 0); return prev + d.percent / 2; }, y: "categoria", text: d => `${d.percent}%`, fontSize: 13, fill: "black", fontWeight: "normal", textAnchor: "middle", lineAnchor: "middle" }), // 🔠 Etiquetes de grups (una sola vegada, alineades amb barres de Population) Plot.text( [ { categoria: "Population", x: 6, text: "Rich countries", align: "end" }, { categoria: "Population", x: 12 + 44, text: "All others", align: "start" } ], { x: "x", y: "categoria", text: "text", fontSize: 13, fontWeight: "bold", fill: "black", textAnchor: d => d.align, lineAnchor: "bottom", dy: -40 } ), // 🔸 Etiqueta petita per "International transport" Plot.text( [ { categoria: "Historical CO₂ emissions", x: 100.5, text: "International\ntransport" } ], { x: "x", y: "categoria", text: "text", fontSize: 10, fontWeight: "normal", fill: "black", textAnchor: "start", lineAnchor: "bottom", dy: 5 } ) ] })2e:T65f,Plot.plot({ width, height: 640, x: { axis: null }, y: { axis: null }, marks: [ // 🔳 Rectangles (ara per annex2) Plot.rect(emissionsLeaves, { x1: "x0", x2: "x1", y1: "y0", y2: "y1", fill: d => d.data.name === "International Transport" ? "#CCCCCC" : colorsAnnex2[d.data.annex2], stroke: "white", strokeWidth: 0.5, title: d => `${d.data.name}\n${d.data.percent.toFixed(1)}%` + (d.data.region ? `\n${d.data.region}` : ""), tip: true }), // 🔠 Països destacats amb negreta i mida gran Plot.text( emissionsLeaves.filter(d => ["USA", "Germany", "China", "Russia"].includes(d.data.name) && (d.x1 - d.x0) * (d.y1 - d.y0) > areaThreshold ), { x: d => d.x0 + 4, y: d => d.y0 + 10, text: d => `${d.data.name} ${d.data.percent.toFixed(1)}%`, textAnchor: "start", lineAnchor: "top", rotate: d => (d.x1 - d.x0 < d.y1 - d.y0 ? -90 : 0), fill: "black", fontSize: 14, fontWeight: "bold" } ), // 🔤 Resta de països Plot.text( emissionsLeaves.filter( d => !["Saudi Arabia", "Netherlands", "USA", "Germany", "China", "Russia"].includes(d.data.name) && (d.x1 - d.x0) * (d.y1 - d.y0) > areaThreshold ), { x: d => d.x0 + 4, y: d => d.y0 + 8, text: d => `${d.data.name} ${d.data.percent.toFixed(1)}%`, textAnchor: "start", lineAnchor: "top", rotate: d => (d.x1 - d.x0 < d.y1 - d.y0 ? -90 : 0), fill: "black", fontSize: 10 } ) ] })2f:T778,Plot.plot({ width, height: 600, marginLeft: 50, marginRight: 35, marginBottom: 40, x: { domain: [1850, 2025], ticks: [1850, 1900, 1950, 2000, 2020], tickFormat: d => d.toString() }, y: { ticks: [], grid: true }, color: { domain: ordreApilat, range: ordreApilat.map(d => colorsStackedAnnex[d]), legend: false }, marks: [ // Àrees apilades Plot.areaY(emissionsApilades, { x: "year", y: "emissions", z: "group", fill: "group", order: ordreApilat }), // Línies blanques als contorns Plot.lineY(contornsApilats, { x: "year", y: "emissions", z: "group", stroke: "white", strokeWidth: 0.8 }), // línies curtes a la dreta per referència visual Plot.line( [10, 20, 30].map(y => [ {x: 2020, y}, {x: 2024, y} ]).flatMap((seg, i) => seg.map(p => ({...p, id: i}))), { x: "x", y: "y", stroke: "#aaa", strokeDasharray: "4,2", strokeWidth: 1, z: "id" } ), // Etiquetes de les línies Plot.text( [10, 20, 30].map(y => ({ y, text: `${y}` })), { x: 2024, y: "y", text: "text", fill: "#555", textAnchor: "start", dx: 6, dy: 4, fontSize: 11, } ), // 🆕 Etiqueta "Gt CO₂" Plot.text( [{ x: 2020, y: 35, text: "↑ Gt CO₂" }], { x: "x", y: "y", text: "text", fontSize: 13, fill: "#333", fontWeight: "bold", textAnchor: "start" } ), // Etiquetes dels grups al final del gràfic Plot.text(labelsStacked, { x: "x", y: "y", text: "text", fontSize: d => d.fontSize, fontWeight: d => d.fontWeight, fill: "#111", dx: d => d.dx, dy: d => d.dy, textAnchor: d => d.textAnchor }) ] })30:T74e,mapaEmissions = { const variable = ordenarPer.includes("Total") ? "emissions" : "perCapita"; const dadesFiltrades = dadesPerMapa.filter( d => d[variable] != null && d.lat != null && d.lon != null ); return Plot.plot({ width, height: 480, projection: { type: "equal-earth", rotate: [-10, 0] }, r: { domain: d3.extent(dadesFiltrades, d => d[variable]), range: variable === "emissions" ? [2, 40] : [2, 20] }, color: { domain: colorBy === "region" ? regionEntries.map(([region]) => region) : [true, false], range: colorBy === "region" ? regionEntries.map(([_, color]) => color) : [colorsAnnex2.true, colorsAnnex2.false], legend: true, label: colorBy === "region" ? "Regió" : "Country group", tickFormat: colorBy === "region" ? undefined : d => labelAnnex2[d] }, marks: [ Plot.geo(landMap, { fill: "#f3f3f3" }), Plot.geo(countriesMap, { stroke: "#ccc", strokeWidth: 0.8 }), Plot.circle(dadesFiltrades, { x: d => d.lon, y: d => d.lat, r: d => d[variable], fill: colorBy === "region" ? d => d.region : d => d.annex2, stroke: colorBy === "region" ? d => d.region : d => d.annex2, fillOpacity: 0.2, strokeWidth: 0.8, title: d => { const annex = d.annex2 === true ? "Rich" : "All others"; const percent = d.emissions && emissionsTotalsPeriode > 0 ? (d.emissions / emissionsTotalsPeriode) * 100 : null; if (variable === "emissions") { return `${d.country} Regió: ${d.region} Emissions: ${(d.emissions / 1e3).toFixed(1)} Gt CO₂ % of global total for the selected period: ${percent.toFixed(1)}%`; } else { return `${d.country} Regió: ${d.region} Emissions per capita: ${d.perCapita.toFixed(2)} t CO₂`; } }, tip: true }) ] }); }31:T561,

A broken promise: $100 billion in climate finance remains unmet In 2009, wealthy nations pledged to mobilize US $100 billion annually by 2020 to help poorer countries adapt to and mitigate climate change. Yet by 2020, they had delivered only about **$83 billion**—a significant shortfall. Even today, climate funding remains far behind the needs of the most vulnerable. [Carbon Brief](https://www.carbonbrief.org/rich-countries-met-100bn-climate-finance-goal-by-relabelling-existing-aid/?utm_source=chatgpt.com) [Viquipèdia](https://en.wikipedia.org/wiki/Climate_finance?utm_source=chatgpt.com) Despite growing urgency, **a lasting “loss & damage” fund**—to compensate countries suffering irreversible climate harm—*failed to materialize at COP26*. Only Scotland offered a token pledge (~£2.7 million), highlighting the global risk of broken climate promises. [Reuters](https://www.reuters.com/business/cop/vulnerable-states-call-climate-loss-damage-deal-bare-minimum-2021-11-12/?utm_source=chatgpt.com) This isn’t just about money—it’s about **trust, justice, and responsibility** on a warming planet.

32:Tdad,function normalizeCountryToAlpha3(name) { if (!name) return null; // Normalitza i neteja encoding const clean = name.trim().toLowerCase() .replace(/[’‘]/g, "'") // Cometes rares a cometes simples .replace(/[éèêë]/g, "e") // E amb accent a e .replace(/[àáâãäå]/g, "a") // A amb accent a .replace(/[ïîíì]/g, "i") // I amb accent a i .replace(/[òóôõö]/g, "o") // O amb accent a o .replace(/[ç]/g, "c") // Cedilla a c .replace(/[üúùû]/g, "u") // U amb accent a u .replace(/�/g, "") // Elimina el caràcter error d’encoding // Mapping manual robust i geo-aware (només països presents al geojson) const manualFixes = { // Encodings i variants + geojson ok "bonaire, saint eustatius and saba": "BES", "bonaire sint eustatius and saba": "BES", // variant sense coma "cape verde": "CPV", // geojson: "Cabo Verde" "cote d'ivoire": "CIV", // geojson: "Côte d’Ivoire" "cote divoire": "CIV", // encoding normalitzat "christmas island": "CXR", "curacao": "CUW", // geojson: "Curaçao" "curaao": "CUW", // encoding error "faeroe islands": "FRO", // geojson: "Faroe Islands" "micronesia (federated states of)": "FSM", // geojson: "Micronesia (Fed. States of)" "micronesia (country)": "FSM", // variant "democratic republic of congo": "COD", // geojson: "Democratic Republic of the Congo" "east timor": "TLS", // geojson: "Timor-Leste" "falkland islands": "FLK", // geojson: "Falkland Islands (Malvinas)" "hong kong": "HKG", // geojson: "China, Hong Kong SAR" "laos": "LAO", // geojson: "Lao People's Democratic Republic" "macao": "MAC", // geojson: "China, Macao SAR" "macau": "MAC", // variant "moldova": "MDA", // geojson: "Republic of Moldova" "reunion": "REU", // geojson: "Réunion" "taiwan": "TWN", "tanzania": "TZA", // geojson: "United Republic of Tanzania" "usa": "USA", // geojson: "United States of America" "united states": "USA", "vatican": "VAT", // geojson: "Holy See" "venezuela": "VEN", // geojson: "Venezuela (Bolivarian Republic of)" "vietnam": "VNM", // geojson: "Viet Nam" "wallis and futuna": "WLF", // geojson: "Wallis and Futuna Islands" "eswatini": "SWZ", // geojson: "Eswatini" "swaziland": "SWZ", // nom anterior "czech republic": "CZE", // geojson: "Czechia" "north korea": "PRK", // geojson: "Democratic People’s Republic of Korea" "south korea": "KOR", // geojson: "Republic of Korea" "iran": "IRN", // geojson: "Iran (Islamic Republic of)" "bolivia": "BOL", // geojson: "Bolivia (Plurinational State of)" "syria": "SYR", // geojson: "Syrian Arab Republic" "russia": "RUS", // geojson: "Russian Federation" "brunei": "BRN", // geojson: "Brunei Darussalam" // Variants d’encoding típics: "c�te d'ivoire": "CIV", "cura�ao": "CUW", "r�union": "REU", "C�te d'ivoire": "CIV", // error d'encoding Côte d'Ivoire "R�union": "REU" // error d'encoding Réunion // Si detectes nous casos, afegeix-los aquí }; // Primer busca mapping directe al geojson (countryNameToAlpha3) return countryNameToAlpha3[clean] || manualFixes[clean] || null; }33:T5d1,dadesPerMapa = { let anys; if (anySeleccionat === "Historic Total (1850-2020)") { anys = d3.range(1850, 2021); } else if (typeof anySeleccionat === "string" && anySeleccionat.includes("–")) { const [inici, fi] = anySeleccionat.split("–").map(Number); anys = d3.range(inici, fi + 1); } else if (typeof anySeleccionat === "number") { anys = [anySeleccionat]; } else { return []; } const dadesFiltrades = dadesPerCapita.filter(d => anys.includes(d.year)); const perPais = d3.rollups( dadesFiltrades, v => { const totalEmissions = d3.sum(v, d => d.emissions); const totalPoblacio = d3.sum(v, d => { return d.perCapita ? (d.emissions * 1e6) / d.perCapita : 0; }); const perCapita = totalPoblacio > 0 ? (totalEmissions * 1e6) / totalPoblacio : null; return { emissions: totalEmissions, perCapita, annex2: v[0].annex2, region: v[0].region, country: v[0].country, id: v[0].id }; }, d => d.id ); const dades = perPais .map(([id, d]) => ({ id, ...d })) .filter(d => d.perCapita !== null && d.emissions !== null); // 🔁 Afegim lat/lon des de emissionsAllFinalGeo return dades.map(d => { const ref = emissionsAllFinalGeo.find(e => e.id === d.id && e.lat != null && e.lon != null); return { ...d, lat: ref?.lat ?? null, lon: ref?.lon ?? null }; }).filter(d => d.lat !== null && d.lon !== null); }34:T5e3,dadesAgregades = { let anys; if (anySeleccionat === "Historic Total (1850-2020)") { anys = d3.range(1850, 2021); // inclou tots els anys } else if (typeof anySeleccionat === "string" && anySeleccionat.includes("–")) { const [inici, fi] = anySeleccionat.split("–").map(Number); anys = d3.range(inici, fi + 1); } else if (typeof anySeleccionat === "number") { anys = [anySeleccionat]; } else { return []; // fallback } const dadesFiltrades = dadesPerCapita.filter(d => anys.includes(d.year)); const perPais = d3.rollups( dadesFiltrades, v => { const totalEmissions = d3.sum(v, d => d.emissions); const totalPoblacio = d3.sum(v, d => { // evitem divisions per 0 return d.perCapita ? (d.emissions * 1e6) / d.perCapita : 0; }); const perCapita = totalPoblacio > 0 ? (totalEmissions * 1e6) / totalPoblacio : null; return { emissions: totalEmissions, perCapita, annex2: v[0].annex2, region: v[0].region }; }, d => d.country ); const ordenat = perPais .map(([country, d]) => ({ country, emissions: d.emissions, perCapita: d.perCapita, annex2: d.annex2, region: d.region })) .filter(d => d.perCapita !== null); return ordenarPer === "Total CO2 Emissions" ? ordenat.sort((a, b) => d3.descending(a.emissions, b.emissions)).slice(0, 15) : ordenat.sort((a, b) => d3.descending(a.perCapita, b.perCapita)).slice(0, 15); }35:T467,plotTotal = Plot.plot({ width: 450, height: 500, marginLeft: 120, marginRight: 1, x: { label: "Total CO₂ emissions (GtCO₂)", domain: [0, d3.max(dadesOrdenades, d => d.emissions / 1000) * 1.1], ticks: 3, tickFormat: d => d < 1 ? d.toFixed(1) : d.toFixed(0) }, y: { domain: dadesOrdenades.map(d => d.country).reverse(), label: null, ticks: [] // ❌ eliminem les etiquetes originals }, marks: [ Plot.barX(dadesOrdenades, { x: d => d.emissions / 1000, // en GtCO₂ y: "country", fill: colorEmissions, title: d => `${d.country} — ${d.region}`, tip: true }), Plot.text(dadesOrdenades, { x: d => d.emissions / 1000 + 0.02, y: "country", text: d => `${(d.emissions / 1000).toFixed(1)}`, fill: "#333", textAnchor: "start", fontSize: 13 }), // 🆕 Etiquetes de país personalitzades (a l’esquerra) Plot.text(dadesOrdenades, { x: 0, y: "country", text: d => d.country, textAnchor: "end", dx: -6, fontSize: 12, fontWeight: "bold", fill: "#666" }) ] })36:[{"id":"5f73ea1bd650cb059a2cdc279c7581967e9c1f11398adc1e473bbdbb1e471c287965ac05f5d8a2c6b06fae3348afe61ba291e16da51eafe2e9c442bbf3700def","href":"https://static.observableusercontent.com/files/5f73ea1bd650cb059a2cdc279c7581967e9c1f11398adc1e473bbdbb1e471c287965ac05f5d8a2c6b06fae3348afe61ba291e16da51eafe2e9c442bbf3700def","name":"emissions.csv","type":"text/csv","lastModified":1753561686041.86,"size":1493942},{"id":"b323686a1e4fb17bbbbcced3e87894d0069d898719b53f1cb8740bacf55e6c2423d943e588cdd5e6c544bdceb606ac5aa21b257aae3d2a0cd2fbb189a3fdfad0","href":"https://static.observableusercontent.com/files/b323686a1e4fb17bbbbcced3e87894d0069d898719b53f1cb8740bacf55e6c2423d943e588cdd5e6c544bdceb606ac5aa21b257aae3d2a0cd2fbb189a3fdfad0","name":"population.csv","type":"text/csv","lastModified":1753561847348.648,"size":1568453},{"id":"0f8ddda02b56f3e99969aeac2ec07d97de7afab72f3a3243cd60a0e8a121362f0c1ef345882846504b0e9771d2f6c78ced5152bb595ec841ca6ec4ab7651491f","href":"https://static.observableusercontent.com/files/0f8ddda02b56f3e99969aeac2ec07d97de7afab72f3a3243cd60a0e8a121362f0c1ef345882846504b0e9771d2f6c78ced5152bb595ec841ca6ec4ab7651491f","name":"stk-country.json","type":"application/json","lastModified":1753562033694.428,"size":33007}] 2b:{"id":"766f4accea949641","slug":null,"title":"A Global Crisis, An Unequal Responsibility","thumbnail":"dfa73f6c5e708c83e6323f8c202e13b9020c25d00fac582ce3ad63dc8f2c4fb6","access_level":"public","create_time":"$D2025-07-26T20:28:06.041Z","update_time":"$D2025-07-29T15:37:12.752Z","view_time":null,"first_public_time":"$D2025-07-28T18:51:35.777Z","has_unpublished_edits":null,"fork":{"id":"0d59c8d4d5bb3927","slug":"dia-25-challenge-setmanal","title":"Dia 25 — Challenge setmanal! 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","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":955,"value":"Climate change is a global emergency, but its causes — and consequences — are not equally shared.\n\nSome countries have contributed far more than others to the greenhouse gas emissions heating the planet. Others, often with the fewest resources, are suffering the most from its impacts.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1318,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":962,"value":"## Who Has Caused the Problem?\n\n**Rich countries are responsible for nearly half of all historical emissions, despite having a small share of the global population.**\n\nThe industrialized nations of the so-called *Annex II* group — including the United States, Canada, Japan, and much of Western Europe — make up only about **12% of the world’s population** today. \nYet, over the last 170 years, they have produced **around 50% of the greenhouse gases** that drive global warming.\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":966,"value":"
\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":342,"value":"$2d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1416,"value":"\n

\n Comparison of total historical emissions from Annex II vs the rest of the world.\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":968,"value":"
\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":964,"value":"## Where Are the Emissions Concentrated?\n\n

\n**A handful of countries are responsible for the vast majority of historical emissions.**\n

\n\nWhile global warming is a planetary issue, its historical causes are far from evenly spread. \nA small number of countries account for a disproportionately large share of total emissions since 1850.\n\nThe treemap below shows each country's contribution to cumulative emissions. \n- **Size** represents total emissions. \n- **Color** indicates whether a country belongs to the *Annex II* group of developed economies.\n\nTogether, these two dimensions offer a clearer view of how climate responsibility is distributed.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":977,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":985,"value":"html`

\n\n \n

\n 23 rich, developed countries\n \n are responsible for half of all historical CO₂ emissions.\n \n

\n\n \n

\n More than 150 other countries\n \n are responsible for the other half.\n \n

\n\n

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":234,"value":"$2e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1271,"value":"
\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1188,"value":"## How Has the Global Emissions Landscape Changed?\n\nHistorical emissions were once dominated by early industrial powers. \nBut since the mid-20th century, the world’s major emitters have shifted.\n\n- **The United States and Europe** led global emissions throughout the 19th and early 20th centuries.\n- Since the 2000s, **China**, **India**, and other fast-growing economies have taken on a much larger share.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1274,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":569,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":666,"value":"\n\n

United States / Developed countries

China / Other countries

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1277,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1197,"value":"This chart shows how the **emissions burden has gradually moved East and South** — raising new questions about who bears responsibility for cutting emissions now.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1063,"value":"

\n While some countries have already built prosperity on carbon, others now face pressure to cut emissions — despite having contributed far less.\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1279,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1181,"value":"## Who Emits the Most Today?\n\nWhile some countries are historically responsible for most emissions, others are now leading today’s output — and the picture changes depending on how you measure it.\n\n- **In absolute terms**, China, the United States, and India emit the most CO₂ today.\n- **Per capita**, small oil-producing nations like **Qatar**, **New Caledonia**, **Mongolia**, and **Kuwait** lead the rankings — far above larger economies.\n\nThis contrast raises a central question in climate negotiations: \n**Should responsibility be measured by total output or by individual contribution?**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1303,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1306,"value":"This chart shows the top 15 CO₂-emitting countries depending on whether you sort by total emissions or emissions per capita. Select a year or time period to explore how different metrics shift the global picture.
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1301,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":732,"value":"

\n Total CO₂ emissions, ${formatFranges(anySeleccionat)}\n

\n ${plotTotal}\n

\n Per capita, ${formatFranges(anySeleccionat)}\n

\n ${plotPerCapita}\n

`","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":796,"value":"
\n

\n Note: For time periods, the per capita average is calculated by dividing the total accumulated emissions by the sum of the population for each year within the selected range. This is not equivalent to the average of annual per capita values.\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":857,"value":"viewof ordenarPer = Inputs.radio([\"Total CO2 Emissions (GtCO2)\", \"Per capita (tCO2)\"], {\n label: html`Sort by`,\n value: \"Total CO2 Emissions (GtCO2)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":835,"value":"viewof anySeleccionat = Inputs.select(franges, {\n label: html`Select a period or year`,\n value: 2020,\n format: formatFranges\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1295,"value":"
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1476,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1172,"value":"
\n## What now?\n### Who should act, and who should pay?\n\nWe’ve seen how responsibility for carbon emissions is deeply unequal — shaped by history, population, and economic development. But now comes the hardest part: deciding what’s fair in a warming world.\n\nUse the tools above to explore different ways of looking at emissions by country, region, time period, and metric — and see how the story changes depending on what lens you choose.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1219,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":213,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":0,"value":"# Dia 25 — Challenge setmanal! _Remaking_ un NYT","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"### EXERCISI\n🎯 Objectiu: Refem i millorem la història visual publicada per _The New York Times_ sobre **[responsabilitat climàtica](https://www.nytimes.com/interactive/2021/11/12/climate/cop26-emissions-compensation.html)**. A partir de les dades obertes, crearem una nova narrativa, menys textual, més interactiva i amb més visualitzacions.\n\nDades: _The Global Carbon Project’s fossil CO2 emissions dataset_. \n\nJa hem preprocessat les dades afegint les columnes `region` i `annex2` (que indica si es tracta d’un país ric). A la columna year, el valor `all` correspon a la suma de les `emissions` de tots els anys, així us estalvieu haver de fer un `reduce` manual.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":126,"value":"emissions = await FileAttachment(\"emissions.csv\").csv({typed: \"auto\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"emissions","database":"$undefined"},{"id":115,"value":"*Documentació*: \n- [Dia 10 Inputs](https://observablehq.com/d/1179256a165b0152?collection=@fndvit/retech)\n- [Dia 16 Interacció](https://observablehq.com/d/15f3e9d79e7a6125?collection=@fndvit/retech)\n- [Dia 22 – Beeswarms, treemaps i diagrames de Sankey](https://observablehq.com/@fndvit/dia-22-beeswarms-treemaps-i-diagrames-de-sankey?collection=@fndvit/retech)\n- Dia 25 Mapes\n- [Llibreria Plot](https://observablehq.com/plot/what-is-plot)\n- d3 [Hierarchies](https://d3js.org/d3-hierarchy/hierarchy) and [Treemap](https://d3js.org/d3-hierarchy/treemap)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":20,"value":"PAS 1 — Prepara les dades:\n- Tria una estrategia: filtra un sol any (com 2019 o 2021), o la suma de les emissions de tots els anys disponibles.\n- Crea la estructura jeràrquica: _root_ > _region_ > _country_, on cada país té els valors d’emissions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":48,"value":"PAS 2 — Dibuixa un treemap de les emissions totals per país, agrupades per regió:\n- L’àrea de cada rectangle ha de ser proporcional a les emissions.\n- El color ha de reflectir si el país és ric o no (Annex II de l'UNFCCC).\n- Afegeix `tip` per mostrar la informació detallada de cada país.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":39,"value":"PAS 3 — La història original no té cap mapa: tria un mapa de coropletes o de símbols proporcionals depenent del tipus de variable que vulguis mostrar.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":55,"value":"PAS 4 — Afegeix la resta de visualitzacions que ja existeixen al projecte original.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":51,"value":"PAS 5 — Incorpora interacció. Fes que totes les visualitzacions es coordinin entre si segons la selecció de l’usuari.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":42,"value":"PAS 6 — L’original és molt textual: crea seccions visuals breus, amb 1–2 frases per insight, i una visualització que ho recolzi.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":697,"value":"### Afegim dades de la població per a fer el càlcul d'emissions per càpita","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":137,"value":"populationRaw = await FileAttachment(\"population.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"populationRaw","database":"$undefined"},{"id":1342,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":405,"value":"### per al gràfic de barres","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":340,"value":"barData = [\n { categoria: \"Population\", group: \"Rich countries\", percent: 12 },\n { categoria: \"Population\", group: \"All others\", percent: 88 },\n\n { categoria: \"Historical CO₂ emissions\", group: \"Rich countries\", percent: 50 },\n { categoria: \"Historical CO₂ emissions\", group: \"All others\", percent: 48 },\n { categoria: \"Historical CO₂ emissions\", group: \"International transport\", percent: 2 }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":215,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":397,"value":"### per al Treemap","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":219,"value":"historical_emissions = emissions\n .filter(d => d.year === \"all\" && d.country !== \"Global\")\n .map(d => ({\n country: d.country,\n emissions: d.emissions,\n annex2: d.annex2,\n region: d.region\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":222,"value":"historical_emissions_percent = {\n const totalEmissions = d3.sum(\n emissions.filter(d => d.year === \"all\" && d.country !== \"Global\"),\n d => d.emissions\n );\n\n return emissions\n .filter(d => d.year === \"all\" && d.country !== \"Global\")\n .map(d => {\n const emissions = d.emissions;\n return {\n country: d.country,\n id: d.id,\n emissions,\n percent: (emissions / totalEmissions) * 100,\n annex2: d.annex2,\n region: d.region\n };\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":225,"value":"emissionsTreemapData = {\n const grouped = d3.groups(\n historical_emissions_percent,\n d => d.annex2 ? \"Annex II (rich)\" : \"Non-Annex II\",\n d => d.region\n );\n\n // Ordenem perquè \"Annex II (rich)\" vagi primer\n const orderedGrouped = grouped.sort(([a], [b]) => {\n if (a === \"Annex II (rich)\") return -1;\n if (b === \"Annex II (rich)\") return 1;\n return 0;\n });\n\n return {\n name: \"root\",\n children: orderedGrouped.map(([annexGroup, regions]) => ({\n name: annexGroup,\n children: regions.map(([regionName, countries]) => ({\n name: regionName,\n children: countries.map(d => ({\n name: d.country,\n value: d.emissions,\n id: d.id, // ⬅️ afegim id\n emissions: d.emissions, // ⬅️ per al tooltip\n region: d.region, // ⬅️ per al tooltip\n percent: d.percent,\n annex2: d.annex2 // ⬅️ per al tooltip\n }))\n }))\n }))\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":228,"value":"emissionsLeaves = {\n const root = d3.hierarchy(emissionsTreemapData).sum((d) => d.value);\n\n d3.treemap()\n .tile(d3.treemapSquarify)\n .size([width, width / 2])\n .padding((node) => {\n if (node.depth === 1) return 7; // Més espai entre \"Annex II\" i \"Non-Annex II\"\n if (node.depth === 2) return 0.6; // Menys espai entre regions\n return 0.2; // Separació entre països\n })\n .round(true)(root);\n\n return root.leaves();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":231,"value":"areaThreshold = 1900;","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1236,"value":"countries = stkCountry.map(d => ({\n country: d.value.country,\n alpha3: d.value.alpha3,\n region: d.value.region,\n lat: d.value.lat,\n lon: d.value.lon\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1234,"value":"//Diccionari ràpid de nom → alpha3\ncountryNameToAlpha3 = Object.fromEntries(\n countries.map(d => [d.country.toLowerCase(), d.alpha3])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1240,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1243,"value":"emissionsClean = emissions\n .map(d => ({\n ...d,\n alpha3: normalizeCountryToAlpha3(d.Country || d.country)\n }))\n .filter(d => d.alpha3); // <-- aquí filtrem només països mapejats!","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1246,"value":"emissionsNoAlpha = Array.from(new Set(\n emissionsClean.filter(d => !d.alpha3).map(d => d.Country || d.country)\n))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1249,"value":"populationClean = populationRaw\n .filter(d => d.Entity)\n .map(d => ({\n ...d,\n alpha3: normalizeCountryToAlpha3(d.Entity)\n }))\n .filter(d => d.alpha3); // <-- també aquí filtrem!","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1252,"value":"populationNoAlpha = Array.from(new Set(\n populationClean.filter(d => !d.alpha3).map(d => d.Entity)\n))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1254,"value":"countryAlpha3ToName = Object.fromEntries(\n countries.map(d => [d.alpha3, d.country])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1258,"value":"emissionsFiltered = emissionsClean\n.filter(d => countryAlpha3ToName[d.alpha3])\n.map(d => ({\n ...d,\n country: countryAlpha3ToName[d.alpha3] // Sobreescriu el nom original!\n }));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1261,"value":"populationFiltered = populationClean\n.filter(d => countryAlpha3ToName[d.alpha3])\n.map(d => ({\n ...d,\n country: countryAlpha3ToName[d.alpha3] // Sobreescriu el nom original!\n }));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"population = populationFiltered\n .map(d => ({\n country: d[\"Entity\"]?.trim?.(),\n iso3: d[\"Code\"]?.trim?.(),\n year: d[\"Year\"]?.toString(),\n population: +d[\"Population (historical)\"] // ja és un número\n }))\n .filter(d => d.iso3 && +d.year >= 1850 && +d.year <= 2020);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":142,"value":"populationWithAll = [\n ...population,\n ...Array.from(\n d3.group(population, d => d.iso3),\n ([iso3, rows]) => ({\n country: rows[0].country,\n iso3,\n year: \"all\",\n population: d3.mean(rows, d => d.population)\n })\n )\n];","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":144,"value":"emissionsWithPopulation = emissions.map(d => {\n const pop = populationWithAll.find(p => p.iso3 === d.id && p.year === d.year);\n return {\n ...d,\n population: pop?.population ?? null,\n emissionsPerCapita: pop?.population ? d.emissions / pop.population : null\n };\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":148,"value":"emissionsAll = emissionsWithPopulation.filter(d => d.year === \"all\");","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1344,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":389,"value":"### per al mapa","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":159,"value":"stkCountry = FileAttachment(\"stk-country.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1465,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1488,"value":"emissionsTotalsPeriode = d3.sum(dadesPerMapa, d => d.emissions)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":162,"value":"// Llista de codis a excloure (no tenen dades vàlides o són agregats)\ncodisAExcloure = new Set([\"\", \" \", \"ATA\", \"CXR\", \"PCZ\", \"KSV\", \"XIT\", \"WLD\"]); ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"// Dataset filtrat només amb dades \"all\" i excloent els codis invàlids\nemissionsAllFiltrat = emissionsWithPopulation\n .filter(d => d.year === \"all\" && !codisAExcloure.has(d.id?.trim()));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":168,"value":"lookupCoords = Object.fromEntries(\n stkCountry.map(d => [d.key, { lat: d.value.lat, lon: d.value.lon }])\n);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":171,"value":"emissionsAllFiltratGeo = emissionsAllFiltrat.map(d => {\n const coords = lookupCoords[d.id?.trim()];\n return {\n ...d,\n lat: coords?.lat ?? null,\n lon: coords?.lon ?? null\n };\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":174,"value":"emissionsAllFiltratGeo.filter(d => d.id === \"KNA\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":239,"value":"import {\n land50m as landMap,\n countries50m as countriesMap\n} from \"@visionscarto/geo\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":179,"value":"codisAfegits = new Set([\"PSE\", \"TWN\"]);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":177,"value":"emissionsAllFiltratGeoNet = emissionsAllFiltratGeo.filter(\n d => !(codisAfegits.has(d.id) || d.country === \"St. Kitts-Nevis-Anguilla\")\n);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":185,"value":"emissionsAddicionalsSenseCoords = [...codisAfegits].map(id => {\n const d = emissionsAll.find(e => e.id === id);\n return { ...d }; // fem una còpia nova per evitar referència\n});\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":188,"value":"coordenadesManuals = ({\n \"PSE\": { lat: 31.9522, lon: 35.2332 },\n \"TWN\": { lat: 23.6978, lon: 120.9605 }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":191,"value":"emissionsAddicionals = emissionsAddicionalsSenseCoords.map(d => {\n const coords = coordenadesManuals[d.id?.trim()];\n return {\n ...d,\n lat: coords?.lat ?? null,\n lon: coords?.lon ?? null\n };\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":194,"value":"emissionsAllFinal = [...emissionsAllFiltratGeoNet, ...emissionsAddicionals];","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":197,"value":"emissionsAllFinal.filter(d => !d.region)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":200,"value":"correccionsManuals = ({\n \"CIV\": { country: \"Côte d'Ivoire\", region: \"Africa\" },\n \"CUW\": { country: \"Curaçao\", region: \"Americas\" },\n \"PLW\": { country: \"Palau\", region: \"Oceania\" },\n \"REU\": { country: \"Réunion\", region: \"Africa\" },\n \"KNA\": { country: \"Saint Kitts and Nevis\", region: \"Americas\" }\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":204,"value":"emissionsAllFinalGeo = emissionsAllFinal.map(d => {\n const fix = correccionsManuals[d.id];\n return {\n ...d,\n country: fix?.country ?? d.country,\n region: fix?.region ?? d.region ?? \"Sense regió\"\n };\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":324,"value":"totalEmissions = d3.sum(\n emissionsAllFinalGeo.filter(d =>\n d.year === \"all\" && d.population && d.emissions\n ),\n d => d.emissions\n);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":305,"value":"dadesFiltrades = emissionsAllFinalGeo\n .filter(d => d.year === \"all\" && d.population && d.emissions)\n .filter(d => colorBy === \"annex2\" ? d.annex2 !== undefined : true)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":312,"value":"regionEntries = Object.entries(colorsRegions).filter(([k]) => k !== \"\");","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":336,"value":"percentById = Object.fromEntries(\n historical_emissions_percent.map(d => [d.id, d.percent])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1385,"value":"labelAnnex2 = ({\n true: \"Developed\",\n false: \"All others\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1398,"value":"colorBy = \"annex2\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1347,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":409,"value":"### Per al gràfic d'àrea","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":563,"value":"comprovacioGrups = {\n const dadesFiltrades = emissions.filter(d => d.year !== \"all\");\n\n // Noms normalitzats per a detecció\n const grupsDestacats = new Set([\n \"USA\",\n \"European Union (27)\",\n \"United Kingdom\",\n \"Russia\",\n \"China\",\n \"India\"\n ].map(nom => nom.trim().toLowerCase()));\n\n const grups = {\n \"Other developed\": new Set(),\n \"Rest of world\": new Set()\n };\n\n for (const d of dadesFiltrades) {\n const nom = d.country.trim();\n const norm = nom.toLowerCase();\n\n if ([\"USA\", \"European Union (27)\", \"United Kingdom\", \"Russia\", \"China\", \"India\"].includes(nom)) continue;\n\n if (d.annex2 === true && !grupsDestacats.has(norm)) {\n grups[\"Other developed\"].add(nom);\n } else if (!grupsDestacats.has(norm)) {\n grups[\"Rest of world\"].add(nom);\n }\n }\n\n return {\n \"Other developed\": Array.from(grups[\"Other developed\"]).sort(),\n \"Rest of world\": Array.from(grups[\"Rest of world\"]).sort()\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":566,"value":"païsosUE = new Set([\n \"Austria\", \"Belgium\", \"Bulgaria\", \"Croatia\", \"Cyprus\", \"Czechia\",\n \"Denmark\", \"Estonia\", \"Finland\", \"France\", \"Germany\", \"Greece\",\n \"Hungary\", \"Ireland\", \"Italy\", \"Latvia\", \"Lithuania\", \"Luxembourg\",\n \"Malta\", \"Netherlands\", \"Poland\", \"Portugal\", \"Romania\",\n \"Slovakia\", \"Slovenia\", \"Spain\", \"Sweden\"\n]);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":484,"value":"emissionsApilades = {\n const dadesFiltrades = emissions.filter(d => d.year !== \"all\");\n\n return Array.from(d3.group(dadesFiltrades, d => d.year, d => {\n if (d.country === \"USA\") return \"United States\";\n if (d.country === \"Russia\") return \"Russia\";\n if (d.country === \"China\") return \"China\";\n if (d.country === \"India\") return \"India\";\n\n if (d.country === \"United Kingdom\" || païsosUE.has(d.country))\n return \"European Union and United Kingdom\";\n\n if (d.annex2 === true) return \"Other developed\";\n return \"Rest of world\";\n })).flatMap(([year, grupMap]) =>\n Array.from(grupMap, ([group, rows]) => ({\n year: +year,\n group,\n emissions: d3.sum(rows, r => r.emissions) / 1000 // Mt → Gt\n }))\n ).sort((a, b) => a.year - b.year);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":455,"value":"ordreApilat = [\n \"United States\",\n \"European Union and United Kingdom\",\n \"Other developed\",\n \"Russia\",\n \"China\",\n \"India\",\n \"Rest of world\"\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":533,"value":"contornsApilats = {\n const grups = ordreApilat;\n const anys = Array.from(new Set(emissionsApilades.map(d => d.year))).sort((a, b) => a - b);\n\n // Inicialitzem un mapa d’acumulació per any\n const acumulat = new Map(anys.map(y => [y, 0]));\n\n // Per cada grup, calculem la suma acumulada\n return grups.flatMap(group => {\n return anys.map(year => {\n const trobat = emissionsApilades.find(d => d.group === group && d.year === year);\n const y0 = acumulat.get(year);\n const y1 = y0 + (trobat?.emissions ?? 0);\n acumulat.set(year, y1); // actualitzem acumulat\n\n return {\n year,\n group,\n emissions: y1\n };\n });\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":586,"value":"labelsStacked = [\n { text: \"United States\", x: 2000, y: 3, dx: 6, dy: 3, fontSize: 14 },\n { text: \"European Union and United Kingdom\", x: 1994, y: 7.5, dx: 6, dy: 3, fontSize: 10 },\n { text: \"Other developed\", x: 2003, y: 10.8, dx: 6, dy: 3, fontSize: 10 },\n { text: \"Russia\", x: 1990, y: 12.3, dx: 6, dy: 3, fontSize: 10 },\n { text: \"China\", x: 2010, y: 17, dx: 6, dy: 3, fontSize: 14 },\n { text: \"India\", x: 2015, y: 23.8, dx: 6, dy: 3, fontSize: 10 },\n { text: \"Rest of world\", x: 2012, y: 26.8, dx: 6, dy: 3, fontSize: 10 }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1349,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":701,"value":"### Per al ranking Top 15 interactiu amb filtratge per any i mètrica d'emissions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1438,"value":"// 🔄 Netegem i unim les dades per any\ndadesPerCapita = {\n const emissionsFiltrades = emissions.filter(d => d.year !== \"all\");\n const poblacioFiltrada = populationRaw.filter(d => +d.Year >= 1850 && +d.Year <= 2020);\n\n const poblacioPerPaisAny = new Map(\n poblacioFiltrada.map(d => [`${d.Code}-${+d.Year}`, +d[\"Population (historical)\"]])\n );\n\n return emissionsFiltrades.map(d => {\n const any = +d.year;\n const poblacio = poblacioPerPaisAny.get(`${d.id}-${any}`);\n const perCapita = poblacio ? (+d.emissions * 1e6) / poblacio : null;\n return {\n country: d.country,\n id: d.id,\n region: d.region,\n annex2: d.annex2,\n year: any,\n emissions: +d.emissions,\n perCapita\n };\n }).filter(d => d.perCapita !== null);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":709,"value":"anysDisponibles = [\"Tots els anys\", ...Array.from(new Set(dadesPerCapita.map(d => d.year))).sort((a, b) => a - b)];","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":717,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":794,"value":"diagnosticUSA = {\n const pais = \"USA\";\n\n // Filtra totes les dades per país (dadesPerCapita)\n const dadesUSA = dadesPerCapita.filter(d => d.id === pais);\n\n // Suma d’emissions en milions de tones (MtCO₂)\n const emissionsTotals = d3.sum(dadesUSA, d => d.emissions); // ja està en MtCO₂\n\n // Suma de població estimada a partir de per capita\n const poblacioTotal = d3.sum(dadesUSA, d =>\n d.perCapita ? (d.emissions * 1e6) / d.perCapita : 0\n );\n\n // Per capita recalculat\n const perCapita = poblacioTotal > 0 ? (emissionsTotals * 1e6) / poblacioTotal : null;\n\n return {\n país: pais,\n emissionsTotals: emissionsTotals.toFixed(1) + \" MtCO₂\",\n poblacioTotal: (poblacioTotal / 1e6).toFixed(1) + \" milions\",\n perCapita: perCapita?.toFixed(2) + \" tCO₂\"\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":740,"value":"dadesOrdenades = {\n const key = ordenarPer === \"Per capita (tCO2)\" ? \"perCapita\" : \"emissions\";\n return dadesAgregades\n .slice()\n .sort((a, b) => d3.ascending(a[key], b[key]));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1519,"value":"dadesOrdenadesTotals = {\n return dadesAgregades\n .slice()\n .filter(d => d.emissions != null)\n .sort((a, b) => d3.descending(a.emissions, b.emissions))\n .slice(0, 15);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1522,"value":"dadesOrdenadesPerCapita = {\n return dadesAgregades\n .slice()\n .filter(d => d.perCapita != null)\n .sort((a, b) => d3.descending(a.perCapita, b.perCapita))\n .slice(0, 15);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":833,"value":"franges = [\n \"Historic Total (1850-2020)\",\n \"1850–1900\",\n \"1901–1945\",\n \"1946–1972\",\n \"1973–1990\",\n \"1991–2005\",\n \"2006–2020\",\n ...Array.from(new Set(dadesPerCapita.map(d => d.year))).sort((a, b) => a - b)\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":837,"value":"formatFranges = d =>\n d === \"Tots els anys\"\n ? \"(1850–2020)\"\n : typeof d === \"number\"\n ? d.toString()\n : d; // manté format per franges","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":734,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":736,"value":"plotPerCapita = Plot.plot({\n width: 450,\n height: 500,\n marginLeft: 10,\n marginRight: 20,\n x: {\n label: \"Per capita (tCO₂)\",\n domain: [0, d3.max(dadesOrdenades, d => d.perCapita) * 1.1],\n tickFormat: d => d.toFixed(0)\n },\n y: {\n domain: dadesOrdenades.map(d => d.country).reverse(),\n label: null\n },\n marks: [\n Plot.barX(dadesOrdenades, {\n x: \"perCapita\",\n y: \"country\",\n fill: colorPerCapita,\n title: d => `${d.country} — ${d.region}`,\n tip: true\n }),\n Plot.text(dadesOrdenades, {\n x: d => d.perCapita + 0.2,\n y: \"country\",\n text: d => d.perCapita.toFixed(1), // 🔁 només número\n fill: \"#333\",\n textAnchor: \"start\",\n fontSize: 13\n }),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1351,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":392,"value":"### Color","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":207,"value":"colorsRegions = ({\n Africa: \"#a6611a\", \n Americas: \"#dfc27d\", \n Asia: \"#5ab4ac\", \n Europe: \"#01665e\", \n Oceania: \"#003c30\",\n \"\": \"#CCCCCC\" // gris per defecte\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":210,"value":"colorsAnnex2 = ({\n true: \"#d8b365\",\n false: \"#5ab4ac\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":431,"value":"colorsStackedAnnex = ({\n \"United States\": colorsAnnex2.true,\n \"European Union and United Kingdom\": colorsAnnex2.true + \"AA\",\n \"Other developed\": colorsAnnex2.true + \"AA\",\n \n \"China\": colorsAnnex2.false,\n \"Russia\": colorsAnnex2.false + \"AA\",\n \"India\": colorsAnnex2.false + \"AA\",\n \"Rest of world\": colorsAnnex2.false + \"AA\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":725,"value":"colorEmissions = \"#d8b365\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":728,"value":"colorPerCapita = \"#5ab4ac\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1","titling":"auto"}} 2c:"$2b:body"