31:T60d,viewof intro_text = { return html`

Welcome the future building emissions calculator. This interactive website presents an interactive model that estimates future greenhouse gas (GHG) emissions of the global building stock until 2050 for three scenarios, Business as usual Operational Carbon (OC) Operational Carbon (OC) and Embodied Carbon (EC). The first two scenarios estimate long-term carbon emissions from building operations only whereas the last scenario also includes emission related to building construction, the embodied carbon. The user can set a number of assumptions as to how the global climate and building stock are going to develop. Model outputs show resulting annual carbon emissions until 2050 as well as whether a scenario manages to stay under carbon budget set by the IPCC. The purpose of the calculator is to provide a sense of the enormity of the task of making the global building stock carbon neutral over the coming decades…

(Global floor areas and operational emissions are based on projections by the International Energy Agency. The carbon budget and emissions scenarios are based on SIMP6 Pathways.)

` }32:T10fa,chart = { const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]); // creates regular bars svg.append("g") .selectAll("rect") .data(bar_data) .join("rect") .attr("x", (d, i) => x_bar(i)) .attr("y", d => y_bar(d.value)) .attr("height", d => y_bar(0) - y_bar(d.value)) .attr("width", x_bar.bandwidth()) .style("stroke", d => d.light) .attr("fill-opacity","1.0") .attr("fill", d => d.color1); // color); // create overlay bars for the ones that are too big svg.append("g") .selectAll("rect") .data(bar_data) .join("rect") .attr("x", (d, i) => x_bar(i)) .attr("y", d => y_bar(d.value)) .attr("height", d => y_bar(emissions_for_buildings) - y_bar(d.value)) .attr("width", x_bar.bandwidth()) .style("stroke", d => d.light) .attr("fill-opacity","0.5") .attr("fill","white"); // color); //.attr("fill", d => d.color1); // color); // dashed line for global emissions svg.append('path') .attr('d', d3.line()([[margin.left, y_bar(emissions_for_buildings)], [width-margin.right, y_bar(emissions_for_buildings)]])) .attr('stroke', 'black') //.style("stroke", "#ddd") .style("stroke-dasharray", "4,4") // with multiple points defined, if you leave out fill:none, // the overlapping space defined by the points is filled with // the default value of 'black' .attr('fill', 'none'); svg.append("text") .attr("class", "y label") .attr("text-anchor", "middle") .attr("x", width/2 - 30) //-height/2) .attr("y", y_bar(emissions_for_buildings) - 10) //.attr("dy", ".75em") .attr("transform", "rotate(-00)") .text("Allowable Emissions from the Built Environment [GtCO2]") .style("font-size", width/75) // .style("font-size", "15px") .style("font-family", "monospace"); svg.append("text") .attr("class", "y label") .attr("text-anchor", "middle") .attr("x", -height/2) .attr("y", 10) //.attr("dy", ".75em") .attr("transform", "rotate(-90)") .text("Cummulative Emissions from the Built Environment until 2050 [GtCO2]") .style("font-size", "10px") .style("font-family", "monospace"); // labels for each bar, number carbon svg.append("g") .attr("fill", "#b76565") .attr("text-anchor", "start") .attr("font-family", "monospace") .attr("font-size", 12) .selectAll("text") .data(bar_data) .join("text") .attr("x", (d, i) => x_bar(i) + 10 ) .attr("y", height - 30) // location top of bar .attr("y", d => y_bar(d.value)+30) .text(d => d3.format(",.1f")(d.diff) + " GtCO2") .style("font-size", width/50) //.style("font-size", "20px") .call(text => text.filter(d => (d.diff) > 0) // short bars .text(d => "+" + d3.format(",.1f")(d.diff) + " GtCO2") //.attr("dx", +4) .attr("fill", "white") .attr("text-anchor", "start")); // labels for each bar, goal reached? svg.append("g") .attr("fill", "#b76565") .attr("text-anchor", "start") .attr("font-family", "monospace") .attr("font-size", width/80) //.attr("font-size", 13) .selectAll("text") .data(bar_data) .join("text") .attr("x", (d, i) => x_bar(i) + 10 ) .attr("y", height - 50) // location top of bar .attr("y", d => y_bar(d.value) - 15) .text(d => "Goal not reached by") .call(text => text.filter(d => (d.diff) > 0) // short bars .text(d => "Goal reached by") //.attr("dx", + 4) .attr("fill", "white") .attr("text-anchor", "start")); // ✓ goal reached? svg.append("g") .attr("fill", "#b76565") .attr("text-anchor", "start") .attr("font-family", "monospace") .attr("font-size", width/10) //.attr("font-size", "100") .selectAll("text") .data(bar_data) .join("text") .attr("x", (d, i) => x_bar(i) + 10 ) .attr("y", height - 75) // location top of bar .attr("y", d => y_bar(d.value) - 15) .text(d => "X") .call(text => text.filter(d => (d.diff) > 0) // short bars .text(d => "✓") //.attr("dx", + 4) .attr("fill", "white") .attr("text-anchor", "start")); svg.append("g") .call(xAxis_bar); svg.append("g") .call(yAxis_bar); return svg.node(); } 33:Tab4,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, ${chartHeight})`); g.append("g") .call(yAxis); g.selectAll(".line") .data(lineData) .enter().append("path") .attr("d", d => lineGenerator(d.data)) .attr("fill-opacity","1") .style("fill", "none") .style("stroke", d => d.light) .style("stroke-width", 2) .style("stroke-linejoin", "round"); g.selectAll(".line") .data(lineData) .enter().append("path") .attr("d", d => areaGenerator(d.data)) .style("fill", d => d.light) ///("fill", d => d.surface ) //"none") .style("stroke", d => d.light) .style("stroke-width", 0) .style("stroke-linejoin", "round") .attr("fill-opacity","0.25"); // text label for the y axis svg.append("text") .attr("class", "y label") .attr("text-anchor", "middle") .attr("x", -height/2) .attr("y", 15) //.attr("dy", ".75em") .attr("transform", "rotate(-90)") .text("Yearly Emissions from the Built Environment [GtCO2/a]") .style("font-size", "10px") .style("font-family", "monospace"); const valueLabel = g.selectAll(".label") .data(lineData) .enter().append("g") .attr("class", "label") .attr("transform", d => `translate(${x(last(d.data).year)}, ${y(last(d.data).value)})`); valueLabel.append("circle") .attr("r", 4) .style("stroke", "white") .style("fill", d => d.light); // text label for last value valueLabel.append("text") //.text(d => d3.format(",.2f") (last(d.data).value ) + d.sum) /// formats to 2 after comma .attr("dy", 5) .attr("dx", 10) .style("font-family", "monospace") .style("fill", d => d.dark); // text label for sum in GtCarbon valueLabel.append("text") .text(d => d3.format(",.1f")(d.total) + " GtCO2") /// formats to 2 after comma .attr("dy", 5) .attr("dx", 10) .style("font-family", "monospace") .style("fill", d => d.dark); valueLabel.append("text") .text(d => (d.text)) .attr("dy", -15) .attr("dx", 10) .style("font-family", "monospace") .style("font-size", "14px") .style("fill", d => d.dark); const zeroLabel = g.selectAll(".label") .data(lineData) .enter().append("g") .attr("class", "label") .attr("transform", d => `translate(${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(); }34:T957,SSP_scenarios = [ "- Sustainability. The world shifts gradually, but pervasively, toward a more sustainable path, emphasizing more inclusive development that respects perceived environmental boundaries. Driven by an increasing commitment to achieving development goals, inequality is reduced both across and within countries. Consumption is oriented toward low material growth and lower resource and energy intensity.", "- Middle of the Road. The world follows a path in which social, economic, and technological trends do not shift markedly from historical patterns. Development and income growth proceeds unevenly, with some countries making relatively good progress while others fall short of expectations. Global and national institutions work toward but make slow progress in achieving sustainable development goals. ", "- Regional Rivalry. A resurgent nationalism, concerns about competitiveness and security, and regional conflicts push countries to increasingly focus on domestic or, at most, regional issues. Countries focus on achieving energy and food security goals within their own regions at the expense of broader-based development. A low international priority for addressing environmental concerns leads to strong environmental degradation in some regions.", "- Inequality. Highly unequal investments in human capital, combined with increasing disparities in economic opportunity and political power, lead to increasing inequalities and stratification both across and within countries. The globally connected energy sector diversifies, with investments in both carbon-intensive fuels like coal and unconventional oil, but also low-carbon energy sources. Environmental policies focus on local issues around middle and high income areas.", "- Fossil-fueled Development. The push for economic and social development is coupled with the exploitation of abundant fossil fuel resources and the adoption of resource and energy intensive lifestyles around the world. All these factors lead to rapid growth of the global economy, while global population peaks and declines in the 21st century. There is faith in the ability to effectively manage social and ecological systems, including by geo-engineering if necessary." ] // Riahi et al 2017 https://www.sciencedirect.com/science/article/pii/S095937801630068135:Teaa,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 = (226/235)*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; }36:T154e,net_zero_op = { let net_zero_op = [] // Emission Scenario based on Path to Net Zero Scenario for operational energy // Changes compared to business as usual are: // 1. linear increase of retrofit rate to 5% (or as specified by slider) by 2030 // 2. Increase of renovation efficiency by 5% instead 2.5%, reaching 100 percent efficiency by 2030 (instead of 2040) // 3. Change of efficiency_new_buildings to as defined by sliders embodied_neutral // changes highlighted in code as: /// CHANGE FROM BUSINESS AS USUAL SCENARIO // 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 annual_renovation_rate = []; 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 10! years and then capped at 100 let renovation_efficiency = 50+5*(i); /// 2. CHANGE FROM BUSINESS AS USUAL SCENARIO if (renovation_efficiency>= 100){ renovation_efficiency = 100 } // increase renovation_rate to new_renovation rate linearly until 2030 let renovation_rate_new = renovation_rate + ((renovation_rate_improved-renovation_rate)/10)*i; if (renovation_rate_new >= renovation_rate_improved){ renovation_rate_new = renovation_rate_improved; } annual_renovation_rate.push(renovation_rate_new) /// 1. CHANGE FROM BUSINESS AS USUAL SCENARIO //------------------------------------------ // New Construction let percentage_of_new_buildings_built = (1/30); // ------------------------- // Inserted slider for change when efficiency measures for new construction are implemented let operational_efficiency_ratio = 0; let years_for_operational_zero = operational_neutral[1] - operational_neutral[0]; if (years_for_operational_zero < 1){ operational_efficiency_ratio = 1; } else { operational_efficiency_ratio = 1/years_for_operational_zero; } let efficiency_new_buildings = 1; if (i > (operational_neutral[0]-year_start) ){ efficiency_new_buildings = 1-(i*(operational_efficiency_ratio)); } // ------------------------- //let efficiency_new_buildings = 1-(i*(1/10)); /// 3. CHANGE FROM BUSINESS AS USUAL SCENARIO if (efficiency_new_buildings <= 0){ efficiency_new_buildings = 0; } let emissions_new = (226/235)*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_new/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_new/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; // cap at 0. if (annual_growth_ec_op < 0){ annual_growth_ec_op = 0; } net_zero_op.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 net_zero_op; // net_zero_op; //business_as_usual; }37:T1a51,net_zero_op_ec = { let net_zero_op_ec = [] // Emission Scenario based on Path to Net Zero Scenario for operational energy // Changes compared to business as usual are: // 1. linear increase of retrofit rate to 5% (or as specified by slider) by 2030 // 2. Increase of renovation efficiency by 5% instead 2.5%, reaching 100 percent efficiency by 2030 (instead of 2040) // 3. Change of efficiency_new_buildings to as defined by sliders embodied_neutral // 4. linear embodied carbon decrease for newbuilds from 410 to 0 and retrofit from 205 to 0 from 2030-2040 // changes highlighted in code as: /// CHANGE FROM BUSINESS AS USUAL SCENARIO // 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 annual_renovation_rate = []; let data_out = []; let embodied_carbon_efficiency = 1; let efficiency_list = []; // 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 10! years and then capped at 100 let renovation_efficiency = 50+5*(i); /// 2. CHANGE FROM BUSINESS AS USUAL SCENARIO if (renovation_efficiency>= 100){ renovation_efficiency = 100 } // increase renovation_rate to new_renovation rate linearly until 2030 let renovation_rate_new = renovation_rate + ((renovation_rate_improved-renovation_rate)/10)*i; if (renovation_rate_new >= renovation_rate_improved){ renovation_rate_new = renovation_rate_improved; } annual_renovation_rate.push(renovation_rate_new) /// 1. CHANGE FROM BUSINESS AS USUAL SCENARIO //------------------------------------------ // New Construction let percentage_of_new_buildings_built = (1/30); // ------------------------- // Inserted slider for change when efficiency measures for new construction are implemented let operational_efficiency_ratio = 0; let years_for_operational_zero = operational_neutral[1] - operational_neutral[0]; if (years_for_operational_zero < 1){ operational_efficiency_ratio = 1; } else { operational_efficiency_ratio = 1/years_for_operational_zero; } let efficiency_new_buildings = 1; if (i > (operational_neutral[0]-year_start) ){ efficiency_new_buildings = 1-(i*(operational_efficiency_ratio)); } // ------------------------- /// 3. CHANGE FROM BUSINESS AS USUAL SCENARIO //let efficiency_new_buildings = 1-(i*(operational_efficiency_ratio)); // let efficiency_new_buildings = 1-(i*(1/10)); if (efficiency_new_buildings <= 0){ efficiency_new_buildings = 0; } let emissions_new = (226/235)*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_new/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 // embodied carbon goes towards zero from 2030 and gets capped at 0 let embodied_efficiency_ratio = 0; let years_for_embodied_zero = embodied_neutral[1] - embodied_neutral[0]; if (years_for_embodied_zero < 1){ embodied_efficiency_ratio = 1; } else { embodied_efficiency_ratio = 1/years_for_embodied_zero; } if (i > (embodied_neutral[0]-year_start) ){ embodied_carbon_efficiency -= embodied_efficiency_ratio; } /// EDITED: old below---------------------- // if (i>(2030-year_start)){ //embodied_carbon_efficiency-=0.1; //} if (embodied_carbon_efficiency <=0){ embodied_carbon_efficiency = 0; } embodied_carbon_average_newbuild *= embodied_carbon_efficiency; embodied_carbon_average_retrofit *= embodied_carbon_efficiency; efficiency_list.push(embodied_carbon_efficiency); // ------------------------------------ // calculate floor area per year for EC 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_new/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; // cap at 0. if (annual_growth_ec_op < 0){ annual_growth_ec_op = 0; } net_zero_op_ec.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 net_zero_op_ec;// net_zero_op_ec;//net_zero_op; // net_zero_op; //business_as_usual; }38:[] 2f:{"title":"Building Emission Scenarios 2020 - 2050","cells":[{"id":634,"value":"# Building Emission Scenarios 2020 - 2050 \nLast Updated 2021.08.19","pinned":false,"hidden":false,"mode":"md"},{"id":3393,"value":"viewof intro_text0 = {\n return html`

\n39% of global carbon emissions can be attributed to the building sector\n[1],\n\n\nmaking the built environment both a challenge and an opportunity to mitigate climate change. At the same time, humans spend 90% of their lives in buildings, which makes indoor comfort a cornerstone of human wellbeing. Given this pivotal role that buildings play, we must address the task of reducing building-related global CO2 emissions to zero by 2050 while developing technologies that support healthy indoor environmental conditions for all humans. International organizations and many countries have set the goal of net zero emissions for all industries by 2050 to avoid the climate catastrophe. \n

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2735,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":3048,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1929,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":2789,"value":"viewof scenario_text = {\n return html`

You can choose a different emission scenario with the slider below. Currently emission scenario SSP-${emission_scenario} is selected. Resulting in cummulative emissions of ${SSP_cummulative_emissions[emission_scenario-1]} GtCO2 until 2050. The SSP-${emission_scenario} scenario will result in a predicted temperature increase of ${SSP_cummulative_temp_2100[emission_scenario-1]}°C until 2100.

(Please note: SSP-1 is the only scenario that has the probability to reach the UN-Climate goals and avoid a global climate crisis)

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2845,"value":"viewof emission_scenario = slider({\n min: 1,\n max: 5,\n step: 1,\n value: 1,\n title: 'Emission Scenario',\n description: \"Choose SSP-Scenario\" \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3296,"value":"viewof ssp_text = {\n return html`

\n\nSSP-${emission_scenario}\n\n${SSP_scenarios[emission_scenario-1]}

\nScenario narrative from Riahi et al 2017.

\n`\n}\n\n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":2918,"value":"viewof buildings_emissions = {\n return html`

If we assume ${emissions_buildings_ratio} % of those emissions can be used by the built environment this results in a carbon budget of ${emissions_for_buildings} GtCO2 for the built environment until 2050.

\n\n

(Please note: The 38% is based on the current share of the global carbon budget of buildings.)

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"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} %.

\n\n

(Please Note: Even though current retrofit rates are assumed to be around 1% not all of those are energy retrofits. This means in reality the actual retrofit rate is most likely significantly lower. In our simplified model we assume that all retrofits are energy retrofits and after a renovation a building is net zero.)

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2633,"value":"viewof renovation_rate_improved = slider({\n min: 0.1,\n max: 6.0,\n step: 0.1,\n value: 1,\n title: 'Renovation Rate',\n description: \"Choose renovation rate of existing buildings [%] (current 1%)\" \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2764,"value":"viewof carbon_text = {\n return html`

We can adjust when we assume our buildings to be Net Zero in terms of operational and embodied carbon. We assume the measures to make operation of buildings to be Net Zero will be implemented in ${operational_neutral[0]} and all new construction will have Zero Operational Carbon Emissions by ${operational_neutral[1]}. We further assume new measures against embodied carbon emissions will be implemented in ${embodied_neutral[0]} and all new construction will have Zero Embodied Carbon Emissions by ${embodied_neutral[1]}

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2758,"value":"viewof embodied_end = slider({\n min: 2020,\n max: 2050,\n step: 1,\n value: 2040,\n title: 'Embodied Carbon Neutral by:',\n description: \"Choose until when the embodied carbon mitigation strategies for all new construction are complete by\" \n})\n\n/*\n viewof embodied_neutral = rangeSlider({\n min: year_start,\n max: year_end-1,\n step: 1,\n value: this ? this.value : [2020, 2040],\n //value: year_start+10,\n description: \"Start and end year of linear decrease of embodied carbon to zero\",\n title: 'Embodied Carbon'\n})\n*/","pinned":false,"hidden":false,"mode":"ojs"},{"id":3031,"value":"viewof operational_end = slider({\n min: 2020,\n max: 2050,\n step: 1,\n value: 2040,\n title: 'Operational Carbon Neutral by:',\n description: \"Choose until when the operational carbon mitigation strategies for all new construction are complete by\" \n})\n\n/*\n viewof operational_neutral = rangeSlider({\n min: year_start,\n max: year_end-1,\n step: 1,\n value: this ? this.value : [2020, 2040],\n //value: year_start+10,\n description: \"Start and end year of linear decrease of operational carbon to zero\",\n title: 'Operational Carbon',\n})\n*/\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":3440,"value":"--------------------------------------------------------------------------","pinned":false,"hidden":false,"mode":"md"},{"id":3474,"value":"import {columns} from \"@bcardiff/observable-columns\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":3472,"value":"import {embed} from \"@observablehq/auto-resizing-embed\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":3447,"value":"--------------------------------------------------------------------------\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":725,"value":"# CODE","pinned":false,"hidden":false,"mode":"md"},{"id":3427,"value":"operational_neutral = [2020, operational_end]","pinned":false,"hidden":false,"mode":"ojs"},{"id":3425,"value":"embodied_neutral = [2020, embodied_end]","pinned":false,"hidden":false,"mode":"ojs"},{"id":2926,"value":"emissions_buildings_ratio = 38\n/*\n viewof emissions_buildings_ratio = slider({\n min: 1,\n max: 99,\n step: 1,\n value: 38,\n title: 'Carbon Budget Building Ratio',\n description: \"Choose % of global carbon budget used for the built environment (currently 38%)\" \n})\n*/\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":3051,"value":"bar_data = [{name: \"Business as usual\", value: sum_business_as_usual, diff: (emissions_for_buildings-sum_business_as_usual), color1:\"#ebd9d9\"}, {name: \"Net Zero Operational\", value: sum_net_zero_op, diff: (emissions_for_buildings-sum_net_zero_op), color1:\"#b5bcc4\"},{name: \"Net Zero Operational and Embodied\", value: sum_net_zero_op_ec, diff: (emissions_for_buildings-sum_net_zero_op_ec), color1:\"#8ea9a7\"}]","pinned":false,"hidden":false,"mode":"ojs"},{"id":3172,"value":"bar_goals_data = [{name: \"Business as usual\", value: sum_business_as_usual, color1:\"#ebd9d9\"}, {name: \"Net Zero Operational\", value: sum_net_zero_op, color1:\"#b5bcc4\"},{name: \"Net Zero Operational and Embodied\", value: sum_net_zero_op_ec, color1:\"#8ea9a7\"}]","pinned":false,"hidden":false,"mode":"ojs"},{"id":3053,"value":"path_data = [{name: \"Business as usual\", value: emissions_for_buildings, color1:\"#af6767\"}, {name: \"Net Zero Operational\", value: emissions_for_buildings, color1:\"#146989\"},{name: \"Net Zero Operational and Embodied\", value: emissions_for_buildings, color1:\"#1e6f4f\"}]","pinned":false,"hidden":false,"mode":"ojs"},{"id":3075,"value":"y_bar_max_scale = {\n var temp_max = d3.max(bar_data, d => d.value)\n if (emissions_for_buildings > temp_max){\n var emissions_new = emissions_for_buildings + 200\n return emissions_new\n }\n var emissions_2 = temp_max + 200\n return emissions_2\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3054,"value":"line = d3.line()\n .defined(d => !isNaN(d.value))\n .x(d => x_bar(d.name))\n .y(d => y_bar(d.value))","pinned":false,"hidden":false,"mode":"ojs"},{"id":3058,"value":"x_bar = d3.scaleBand()\n .domain(d3.range(bar_data.length))\n .range([margin.left, width - margin.right])\n .padding(0.1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3060,"value":"y_bar = d3.scaleLinear()\n //.domain([0, d3.max(data, d => d.value)]).nice()\n .domain([0,y_bar_max_scale]).nice() // d3.max(bar_data, d => d.value)]).nice()\n .range([height - margin.bottom, margin.top])","pinned":false,"hidden":false,"mode":"ojs"},{"id":3062,"value":"xAxis_bar = g => g\n .attr(\"transform\", `translate(0,${height - margin.bottom})`)\n .call(d3.axisBottom(x_bar).tickFormat(i => bar_data[i].name).tickSizeOuter(0))","pinned":true,"hidden":false,"mode":"ojs"},{"id":3063,"value":"yAxis_bar = g => g\n .attr(\"transform\", `translate(${margin.left},0)`)\n .call(d3.axisLeft(y_bar).ticks(null, bar_data.format))\n //.call(g => g.select(\".domain\").remove())\n .call(g => g.append(\"text\")\n .attr(\"x\", -margin.left)\n .attr(\"y\", 10)\n .attr(\"fill\", \"currentColor\")\n .attr(\"text-anchor\", \"start\")\n .text(bar_data.y))","pinned":true,"hidden":false,"mode":"ojs"},{"id":3302,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2933,"value":"emissions_for_buildings = ((emissions_buildings_ratio/100)*SSP_cummulative_emissions[emission_scenario-1]).toFixed(2)","pinned":false,"hidden":false,"mode":"ojs"},{"id":88,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1238,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":1276,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"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"},{"id":2853,"value":"SSP_cummulative_emissions = [930.2, 1339.9, 1414.1, 1705.9, 1939.3]\n// Data extracted from SSP Scenarios https://gmd.copernicus.org/preprints/gmd-2018-266/gmd-2018-266.pdf","pinned":false,"hidden":false,"mode":"ojs"},{"id":2953,"value":"SSP_cummulative_temp_2100 = [1.73, 2.68, 3.24, 4.09, 4.86]","pinned":true,"hidden":false,"mode":"ojs"},{"id":2877,"value":"SSP_temperatures = [SSP_1_temperatures, SSP_2_temperatures, SSP_3_temperatures, SSP_4_temperatures, SSP_5_temperatures ]\n// Data extracted from SSP Scenarios https://gmd.copernicus.org/preprints/gmd-2018-266/gmd-2018-266.pdf","pinned":false,"hidden":false,"mode":"ojs"},{"id":2857,"value":"SSP_1_temperatures = [1.273912,1.296137,1.318361,1.340586,1.36281,1.385035,1.40726,1.429484,1.451709,1.473933,1.496158,1.512821,1.529485,1.546149,1.562812,1.579476,1.59614,1.612803,1.629467,1.646131,1.662794,1.67264,1.682487,1.692333,1.702179,1.712025,1.721871,1.731718,1.741564,1.75141,1.761256\n]\n// Data extracted from SSP Scenarios https://gmd.copernicus.org/preprints/gmd-2018-266/gmd-2018-266.pdf","pinned":false,"hidden":false,"mode":"ojs"},{"id":2860,"value":"SSP_2_temperatures = [1.284759,1.308747,1.332734,1.356721,1.380709,1.404696,1.428683,1.452671,1.476658,1.500645,1.524633,1.550541,1.576449,1.602357,1.628266,1.654174,1.680082,1.70599,1.731898,1.757807,1.783715,1.80707,1.830426,1.853781,1.877137,1.900492,1.923847,1.947203,1.970558,1.993914,2.017269]\n// Data extracted from SSP Scenarios https://gmd.copernicus.org/preprints/gmd-2018-266/gmd-2018-266.pdf","pinned":false,"hidden":false,"mode":"ojs"},{"id":2866,"value":"SSP_3_temperatures = [1.289229,1.317288,1.345347,1.373406,1.401464,1.429523,1.457582,1.485641,1.513699,1.541758,1.569817,1.600509,1.631201,1.661894,1.692586,1.723278,1.753971,1.784663,1.815355,1.846048,1.87674,1.905985,1.935231,1.964476,1.993721,2.022966,2.052212,2.081457,2.110702,2.139948,2.169193]\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2868,"value":"SSP_4_temperatures = [1.276119,1.305462,1.334806,1.364149,1.393492,1.422836,1.452179,1.481523,1.510866,1.54021,1.569553,1.602851,1.636149,1.669447,1.702745,1.736043,1.769341,1.802639,1.835938,1.869236,1.902534,1.93596,1.969386,2.002812,2.036238,2.069663,2.103089,2.136515,2.169941,2.203367,2.236793\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":2870,"value":"SSP_5_temperatures = [1.305352,1.33737,1.369388,1.401407,1.433425,1.465443,1.497462,1.52948,1.561498,1.593517,1.625535,1.662518,1.699501,1.736484,1.773467,1.810451,1.847434,1.884417,1.9214,1.958383,1.995366,2.0371,2.078833,2.120567,2.1623,2.204034,2.245768,2.287501,2.329235,2.370968,2.412702\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":310,"value":"# Create correct Data Structure for Graph ","pinned":false,"hidden":false,"mode":"md"},{"id":2891,"value":"data0 = {\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 \"SSP-1\": SSP_1_temperatures[i],\n \"SSP-2\": SSP_2_temperatures[i],\n \"SSP-3\": SSP_3_temperatures[i],\n \"SSP-4\": SSP_4_temperatures[i],\n \"SSP-5\": SSP_5_temperatures[i]\n }\n data.push(item)\n}\n return data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"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_emissions_business_as_usual\": business_as_usual[i],\n \"annual_emissions_net_zero_op\": net_zero_op[i],\n \"annual_emissions_net_zero_op_ec\": net_zero_op_ec[i] \n }\n data.push(item)\n}\n return data\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":112,"value":"# Appendix","pinned":true,"hidden":false,"mode":"md"},{"id":2442,"value":"**Formatting templates**","pinned":false,"hidden":false,"mode":"md"},{"id":117,"value":"margin = ({top: 50, right: 180, bottom: 20, left: 50})","pinned":false,"hidden":false,"mode":"ojs"},{"id":120,"value":"height = width * 0.5 ;","pinned":false,"hidden":false,"mode":"ojs"},{"id":1814,"value":"chartWidth = width - margin.left - margin.right;","pinned":false,"hidden":false,"mode":"ojs"},{"id":1816,"value":"chartHeight = height - margin.top - margin.bottom;","pinned":false,"hidden":false,"mode":"ojs"},{"id":2446,"value":"**Axis Generators**","pinned":false,"hidden":false,"mode":"md"},{"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"},{"id":374,"value":"y = d3.scaleLinear()\n .domain([0, 25]) //d3.max(data , d => d.annual_emissions_business_as_usual)]) /// d.annual_emissions = select annual emissions from data\n .range([chartHeight, 0])","pinned":false,"hidden":false,"mode":"ojs"},{"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"},{"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, 30, 5))) //ticks(height / 40))\n //.call(g => g.select(\".domain\").remove())\n ","pinned":false,"hidden":false,"mode":"ojs"},{"id":2465,"value":"**Global Variables**","pinned":false,"hidden":false,"mode":"md"},{"id":1022,"value":"year_start = 2020;","pinned":true,"hidden":false,"mode":"ojs"},{"id":1024,"value":"year_end = 2051;","pinned":true,"hidden":false,"mode":"ojs"},{"id":1026,"value":"num_years = year_end-year_start;","pinned":true,"hidden":false,"mode":"ojs"},{"id":1030,"value":"additional_floorarea_per_year = 6.8484848","pinned":false,"hidden":false,"mode":"ojs"},{"id":2162,"value":"sum_business_as_usual = business_as_usual.reduce(function(a, b) { return a + b; }, 0);","pinned":true,"hidden":false,"mode":"ojs"},{"id":2169,"value":"sum_net_zero_op = net_zero_op.reduce(function(a, b) { return a + b; }, 0);","pinned":true,"hidden":false,"mode":"ojs"},{"id":2185,"value":"sum_net_zero_op_ec = net_zero_op_ec.reduce(function(a, b) { return a + b; }, 0);","pinned":true,"hidden":false,"mode":"ojs"},{"id":2471,"value":"**Data Wrangling**","pinned":false,"hidden":false,"mode":"md"},{"id":1546,"value":"lineData = parseLineData(data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1742,"value":"flatData = parseFlatData(data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1764,"value":"lineGenerator = d3.line()\n .x(d => x(d.year))\n .y(d => y(d.value));","pinned":false,"hidden":false,"mode":"ojs"},{"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"},{"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"},{"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"},{"id":2478,"value":"**Per Line properties Color / Labels**","pinned":false,"hidden":false,"mode":"md"},{"id":1725,"value":"colors = ({\n annual_emissions_business_as_usual: {\n light: \"#af6767\",\n dark: \"#af6767\",\n surface: \"#cab6b6\",\n text: \"Business as usual\",\n total: sum_business_as_usual\n },\n annual_emissions_net_zero_op: {\n light: \"#146989\", //\"#a6cee3\", \n dark: \"#0e475c\",// \"#1f78b4\"\n surface: \"#6fa6bb\",\n text: \"Net Zero OC\",\n total: sum_net_zero_op\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":true,"hidden":false,"mode":"ojs"},{"id":1523,"value":"last = array => array[array.length - 1]","pinned":true,"hidden":false,"mode":"ojs"},{"id":2460,"value":"**Import**","pinned":false,"hidden":false,"mode":"md"},{"id":116,"value":"d3 = require(\"d3\");","pinned":false,"hidden":false,"mode":"ojs"},{"id":614,"value":"import {slider} from '@jashkenas/inputs'","pinned":true,"hidden":false,"mode":"ojs"},{"id":3021,"value":"import {rangeSlider} from '@mootari/range-slider'","pinned":true,"hidden":false,"mode":"ojs"},{"id":1754,"value":"geometric = require(\"geometric@1\");","pinned":true,"hidden":false,"mode":"ojs"},{"id":1788,"value":"arr = require(\"arraygeous@0\");","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W38","stdlib":"1","titling":"auto"}