29:null 2a:["$","title",null,{"children":"Is it worth it? Embodied + Operational Carbon emission graph | Ramon Weber | Observable"}] 2f:Tf54,graph = { const svg = d3.select(DOM.svg(width, height)); const g = svg.append("g") .attr("transform", `translate(${margin.left}, ${margin.top})`); g.append("g") .call(xAxis) .attr("transform", `translate(0, ${chartHeight})`); g.append("g") .call(yAxis); // dashed line for global emissions svg.append('path') .attr('d', d3.line()([[x(intersection_x)+margin.left, margin.top], [x(intersection_x)+margin.left, height-20]])) .attr('stroke', 'black') //.style("stroke", "#ddd") .style("stroke-dasharray", "4,4") // with multiple points defined, if you leave out fill:none, //x(d.year)) // .y(d => y(d.value)); // the overlapping space defined by the points is filled with // the default value of 'black' .attr('fill', 'none'); svg.append("circle") .attr("fill","grey") // #cab6b6 // af6767 .attr("stroke","black") .attr("stroke-width",2) .attr("r",6) .attr("cx",x(intersection_x)+margin.left) .attr("cy",y(intersection_y)+margin.top); svg.append("text") .attr("class", "y label") .attr("text-anchor", "middle") .attr("x", x(intersection_x)+margin.left) //-height/2) .attr("y", y(intersection_y)+margin.top - 20) //.attr("dy", ".75em") .attr("transform", "rotate(-00)") .text("Building upgrades amortized in " + d3.format(".0f")(intersection_x)) .style("font-size", width/75) // .style("font-size", "15px") .style("font-family", "monospace"); g.selectAll(".line") .data(lineData) .enter().append("path") .attr("d", d => lineGenerator(d.data)) .attr("fill-opacity","1") .style("fill", "none") .style("stroke", d => d.light) .style("stroke-width", 2) .style("stroke-linejoin", "round"); g.selectAll(".line") .data(lineData) .enter().append("path") .attr("d", d => areaGenerator(d.data)) .style("fill", d => d.light) ///("fill", d => d.surface ) //"none") .style("stroke", d => d.light) .style("stroke-width", 0) .style("stroke-linejoin", "round") .attr("fill-opacity","0.25"); // text label for the y axis svg.append("text") .attr("class", "y label") .attr("text-anchor", "middle") .attr("x", -height/2) .attr("y", 15) //.attr("dy", ".75em") .attr("transform", "rotate(-90)") .text("yearly emissions from the building [tCO2/a]") .style("font-size", "10px") .style("font-family", "monospace"); const valueLabel = g.selectAll(".label") .data(lineData) .enter().append("g") .attr("class", "label") .attr("transform", d => `translate(${x(last(d.data).year)}, ${y(last(d.data).value)})`); valueLabel.append("circle") .attr("r", 4) .style("stroke", "white") .style("fill", d => d.light); // text label for last value valueLabel.append("text") //.text(d => d3.format(",.2f") (last(d.data).value ) + d.sum) /// formats to 2 after comma .attr("dy", 5) .attr("dx", 10) .style("font-family", "monospace") .style("fill", d => d.dark); // text label for sum in GtCarbon valueLabel.append("text") .text(d => d3.format(",.1f")(d.total) + " tCO2") /// formats to 2 after comma .attr("dy", 5) .attr("dx", 10) .style("font-family", "monospace") .style("fill", d => d.dark); valueLabel.append("text") .text(d => (d.text)) .attr("dy", -15) .attr("dx", 10) .style("font-family", "monospace") .style("font-size", "14px") .style("fill", d => d.dark); const zeroLabel = g.selectAll(".label") .data(lineData) .enter().append("g") .attr("class", "label") .attr("transform", d => `translate(${x(last(d.data).year)}, ${y(last(d.data).value)})`); valueLabel.append("circle") .attr("r", 4) .style("stroke", "white") .style("fill", d => d.light); yield svg.node(); }30:T440,reference_scenario = { let reference_scenario = [] // OUTPUTS tonnes of CO2 total // inputs are in kg CO2 and m2 // define inputs let emb_current = (emb_reference/1000)*area_of_building; let op_current = (op_reference/1000)*area_of_building; // Emission Scenario based on business as usual // Values Operational Carbon let emissions_current = 0; let emissions_2020 = 0; //tCO2 let construction_time = 2; let construction_emissions_temp = emb_current/construction_time; let data_out = []; // Compute array for "Annual emissions existing buildings" and "Annual emissions of new buildings" for (let i = 0; i < num_years; i++) { //------------------------------------------ // 01 OPERATIONAL EMISSIONS if (i==0) { emissions_current = 0; } else if (i <= construction_time) { emissions_current += construction_emissions_temp; } else { emissions_current += op_current; } reference_scenario.push(emissions_current); } return reference_scenario; //reference_scenario; }31:T41c,new_scenario = { let new_scenario = [] // OUTPUTS tonnes of CO2 total // inputs are in kg CO2 and m2 // define inputs let emb_current = (emb_new/1000)*area_of_building; let op_current = (op_new/1000)*area_of_building; // Emission Scenario based on business as usual // Values Operational Carbon let emissions_current = 0; let emissions_2020 = 0; //tCO2 let construction_time = 2; let construction_emissions_temp = emb_current/construction_time; let data_out = []; // Compute array for "Annual emissions existing buildings" and "Annual emissions of new buildings" for (let i = 0; i < num_years; i++) { //------------------------------------------ // 01 OPERATIONAL EMISSIONS if (i==0) { emissions_current = 0; } else if (i <= construction_time) { emissions_current += construction_emissions_temp; } else { emissions_current += op_current; } new_scenario.push(emissions_current); } return new_scenario; //reference_scenario; }32:Tea0,business_as_usual = { let business_as_usual = [] // Emission Scenario based on business as usual // Values Operational Carbon let emissions_2020 = 14.8; //GtCO2 let emissions_temp_existing = 14.8; //GtCO2 let emissions_temp_new = 0; let renovation_rate = 1; let world_floor_area_2020 = 235; // in billion m2 let world_floor_area_2050 = 461; // in billion m2 let world_floor_area_additional_total = world_floor_area_2050 - world_floor_area_2020; let world_floor_area_additional_per_year = world_floor_area_additional_total/30; let annual_emissions_existing = []; let annual_emissions_new_buildings = []; // Additional values for embodied carbon let embodied_carbon_average_newbuild = 410; // kgCO2/m2 let embodied_carbon_average_retrofit = 205; // kgCO2/m2 let world_floor_areas = []; let embodied_carbon_from_renovation_list = []; let embodied_list = []; let data_out = []; // Compute array for "Annual emissions existing buildings" and "Annual emissions of new buildings" for (let i = 0; i < num_years; i++) { //------------------------------------------ // 01 OPERATIONAL EMISSIONS // Existing Buildings // renovation efficiency linear increase from 50 to 100 in 20 years and then capped at 100 let renovation_efficiency = 50+2.5*(i); if (renovation_efficiency>= 100){ renovation_efficiency = 100 } //------------------------------------------ // New Construction let percentage_of_new_buildings_built = (1/30); let efficiency_new_buildings = 1-(i*(1/30)); if (efficiency_new_buildings <= 0){ efficiency_new_buildings = 0; } let emissions_new = emissions_2020*percentage_of_new_buildings_built*efficiency_new_buildings; // Annual Emissions of renovated buildings are lower and will be subtracted from the existing buildings let emissions_existing = emissions_temp_existing; if (i!=0){ emissions_existing = emissions_temp_existing - emissions_2020*(renovation_rate/100)*(renovation_efficiency/100)+emissions_new; } emissions_temp_existing = emissions_existing; annual_emissions_existing.push(emissions_existing); let emissions_operational = emissions_existing; //------------------------------------------ // 02 EMBODIED EMISSIONS let current_total_floor_area= world_floor_area_2020 + i*world_floor_area_additional_per_year; if (current_total_floor_area > world_floor_area_2050){ current_total_floor_area = world_floor_area_2050; } world_floor_areas.push(current_total_floor_area) // Embodied: additional from retrofits let world_renovation_area = (renovation_rate/100)*current_total_floor_area; let embodied_carbon_from_renovation = (world_renovation_area*embodied_carbon_average_retrofit*1000000000)/1000000000000; // conversion of m2 in billion m2 for renovation area and kg to Gt embodied_carbon_from_renovation_list.push(embodied_carbon_from_renovation) // Embodied: additional from new builds let embodied_from_new_build = (world_floor_area_additional_per_year*embodied_carbon_average_newbuild*1000000000)/1000000000000; let embodied_carbon = embodied_from_new_build+embodied_carbon_from_renovation; embodied_list.push(embodied_carbon); //------------------------------------------ // 03 COMBINED EMISSION let annual_growth_ec_op = embodied_carbon+emissions_operational; business_as_usual.push(annual_growth_ec_op); } // Returns total annual growth of both existing and new constructions //let business_as_usual = annual_emissions_new_buildings + annual_emissions_existing; // emissions_existing; //+ emissions_new; return business_as_usual; //business_as_usual; }33:[] 2d:{"id":"b7a7c190a54b6a28","slug":null,"title":"Is it worth it? Embodied + Operational Carbon emission graph","thumbnail":"1991640c5af20ca6e6c7f509aec84d5db695d537b01709df5c329c87a078bf02","access_level":"public","create_time":"$D2023-01-17T22:32:05.944Z","update_time":"$D2023-02-01T17:33:51.943Z","view_time":null,"first_public_time":"$D2023-01-17T22:32:05.944Z","fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"280d7d4386f5e4e2","login":"ramonweber","name":"Ramon Weber","avatar_url":"https://avatars-next.observableusercontent.com/c1f14d352821ad2289a2885c10bad45e4269bfbdefcc88485d1f39605eddd031","tier":"starter_2024"},"version":3069,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"4eeef0da6313879c","login":"ramonweber","name":"Ramon Weber","avatar_url":"https://avatars-next.observableusercontent.com/c1f14d352821ad2289a2885c10bad45e4269bfbdefcc88485d1f39605eddd031","tier":null}],"members":[{"type":"individual","id":"4eeef0da6313879c","login":"ramonweber","name":"Ramon Weber","avatar_url":"https://avatars-next.observableusercontent.com/c1f14d352821ad2289a2885c10bad45e4269bfbdefcc88485d1f39605eddd031","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"Is it worth it? Embodied + Operational Carbon emission graph","cells":[{"id":634,"value":"# Is it worth it? Embodied + Operational Carbon emission graph\nLast Updated 2021.06.21","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2516,"value":"html`

Global floor areas and operational emissions are based on projections by the International Energy Agency.

` ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2686,"value":"viewof heading_text = {\n return html`

The renovation rate of existing buildings can be adjusted with the slider below and is currently at ${renovation_rate_improved} %.

(the estimated current rate is 1%)

`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2800,"value":"viewof area_of_building = slider({\n min: 10,\n max: 10000.0,\n step: 10,\n value: 500,\n description: \"Total area of building [m2]\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2757,"value":"viewof emb_reference = slider({\n min: 50,\n max: 200,\n step: 0.5,\n value: 75,\n description: \"Reference embodied carbon of building [kgCO2/m2]\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2765,"value":"viewof op_reference = slider({\n min: 1,\n max: 5,\n step: 0.5,\n value: 4,\n description: \"Reference operational emissions [kgCO2/m2]\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2763,"value":"viewof emb_new = slider({\n min: 50,\n max: 200,\n step: 0.5,\n value: 75,\n description: \"NEW embodied carbon of building [kgCO2/m2]\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2774,"value":"viewof op_new = slider({\n min: 1,\n max: 5,\n step: 0.5,\n value: 3,\n description: \"NEW operational emissions [kgCO2/m2]\" \n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2907,"value":"intersection_x = {\n let intersection_x = 0\n\n let emb_ref = (emb_reference/1000)*area_of_building;\n let op_ref = (op_reference/1000)*area_of_building;\n\n let emb_n = (emb_new/1000)*area_of_building;\n let op_n = (op_new/1000)*area_of_building;\n //op_current = (op_reference/1000)*area_of_building\n // gleichung referenz\n \n intersection_x = (emb_ref - emb_n) / (op_n - op_ref); \n // add construction time\n intersection_x += 2022;\n return intersection_x;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2934,"value":"intersection_y = {\n let intersection_y = 0\n\n let emb_ref = (emb_reference/1000)*area_of_building;\n let op_ref = (op_reference/1000)*area_of_building;\n\n let emb_n = (emb_new/1000)*area_of_building;\n let op_n = (op_new/1000)*area_of_building;\n \n let x_sel = intersection_x-2022;\n\n intersection_y = op_ref*x_sel+emb_ref;\n //intersection_y = op_n*x_sel+emb_n; \n return intersection_y;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1929,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":725,"value":"# Define \"Scenarios\"","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2780,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2789,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":88,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":104,"value":"years = {\n let years = [];\n for (let i = year_start; i < year_end; i++) { \n //let str1 = String(i);\n //let str2 = \"-01-01\";\n //let str = str1.concat(str2);\n //years.push(Date(str))\n years.push(i);\n }\n return years;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":310,"value":"# Create correct Data Structure for Graph ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":308,"value":"data = {\nvar data = [] \n// Adds all business as usual and years into data structure for graph\nfor (let i = 0; i < years.length; ++i) {\n let item = {\n \"year\": years[i],\n \"annual_reference_scenario\": reference_scenario[i],\n \"annual_new_scenario\": new_scenario[i]\n }\n data.push(item)\n}\n return data\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":112,"value":"# Appendix","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2442,"value":"**Formatting templates**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":117,"value":"margin = ({top: 50, right: 180, bottom: 20, left: 50})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":120,"value":"height = width * 0.5 ;","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1814,"value":"chartWidth = width - margin.left - margin.right;","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1816,"value":"chartHeight = height - margin.top - margin.bottom;","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2446,"value":"**Axis Generators**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2843,"value":"max_scale_y = {\n \n let max_scale_y = 0;\n\n if (new_scenario[new_scenario.length - 1] > reference_scenario[reference_scenario.length - 1])\n {\n max_scale_y = new_scenario[new_scenario.length - 1];\n } else\n {\n max_scale_y = reference_scenario[reference_scenario.length - 1];\n }\n\n max_scale_y = max_scale_y*1.5;\n \n return max_scale_y;\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":345,"value":"x = d3.scaleLinear()\n .domain(d3.extent(data, d => d.year))\n .range([0, chartWidth])\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":374,"value":"y = d3.scaleLinear()\n .domain([0, max_scale_y]) //.domain([0, 100000]) //d3.max(data , d => d.annual_emissions_business_as_usual)]) /// d.annual_emissions = select annual emissions from data //.domain([0, 100]) \n .range([chartHeight, 0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":192,"value":"xAxis = g => g\n .attr(\"transform\", `translate(0,${0})`)\n .call(d3.axisBottom(x).ticks(width / 80).tickSizeOuter(0).tickFormat(d3.format(\"d\")))\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":188,"value":"yAxis = g => g\n .attr(\"transform\", `translate(${0},${0})`) //(${margin.left},${margin.top})`)\n .call(d3.axisLeft(y).tickValues(d3.range(0, max_scale_y, max_scale_y/20))) //ticks(height / 40))\n //.call(g => g.select(\".domain\").remove())\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2465,"value":"**Global Variables**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1022,"value":"year_start = 2020;","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1024,"value":"year_end = 2051;","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1026,"value":"num_years = year_end-year_start;","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1030,"value":"additional_floorarea_per_year = 6.8484848","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2162,"value":"sum_reference_scenario = reference_scenario.reduce(function(a, b) { return a + b; }, 0);","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2813,"value":"sum_new_scenario = new_scenario.reduce(function(a, b) { return a + b; }, 0);","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2471,"value":"**Data Wrangling**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1546,"value":"lineData = parseLineData(data)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1742,"value":"flatData = parseFlatData(data)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1764,"value":"lineGenerator = d3.line()\n .x(d => x(d.year))\n .y(d => y(d.value));","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1941,"value":"areaGenerator = d3.area()\n .x(d => x(d.year))\n .y0(y(0))\n .y1(d => y(d.value));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1724,"value":"parseLineData = data => {\n const output = [];\n \n let i = 0;\n for (let col in data[0]){\n if (i > 0) {\n let o = {\n key: col, \n light: colors[col].light,\n dark: colors[col].dark,\n text: colors[col].text,\n total: colors[col].total,\n data: []\n };\n \n for (let i0 = 0, l0 = data.length; i0 < l0; i0++){\n let d0 = data[i0];\n \n o.data.push({\n year: d0.year,\n value: d0[col]\n });\n }\n \n output.push(o);\n }\n i++;\n }\n \n return output;\n} ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1735,"value":"parseFlatData = data => {\n const output = [],\n columns = [];\n \n let i = 0;\n for (let col in data[0]){\n columns.push(col);\n if (i > 0) {\n for (let i0 = 0, l0 = data.length; i0 < l0; i0++){\n let d0 = data[i0];\n \n output.push({\n year: d0.year,\n value: d0[col],\n key: col,\n colors: colors[col]\n });\n }\n\n }\n i++;\n }\n \n output.columns = columns;\n return output; \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2478,"value":"**Per Line properties Color / Labels**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1725,"value":"colors = ({\n annual_new_scenario: {\n light: \"#1e6f4f\", //\"#af6767\",\n dark: \"3e5d53\", //\"#af6767\",\n surface: \"58b390\", //\"#cab6b6\",\n text: \"New Scenario\",\n total: sum_new_scenario\n },\n annual_reference_scenario: {\n light: \"#146989\", //\"#a6cee3\", 146989 1e6f4f\n dark: \"#0e475c\",// \"#1f78b4\" 0e475c 3e5d53\n surface: \"#6fa6bb\", //6fa6bb 58b390\n text: \"Reference Scenario\",\n total: sum_reference_scenario\n },\n // annual_emissions_net_zero_op_ec: {\n // light: \"#1e6f4f\", //\"#fdbf6f\",\n // dark: \"#3e5d53\",//\"#ff7f00\"\n // surface: \"#58b390\",\n // text: \"Net Zero OC and EC\",\n // total: sum_net_zero_op_ec\n //},\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1523,"value":"last = array => array[array.length - 1]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2460,"value":"**Import**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"d3 = require(\"d3\");","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":614,"value":"import {slider} from '@jashkenas/inputs'","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1754,"value":"geometric = require(\"geometric@1\");","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1788,"value":"arr = require(\"arraygeous@0\");","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 2e:"$2d:body"