31:T462,In its [report](https://www.nature.org/content/dam/tnc/nature/en/documents/FINAL_TNC_Power_of_Place_National_Executive_Summary_5_2_2023.pdf), the Nature Conservancy describes two different futures in which the United States achieves net-zero carbon emissions by 2050. In one future — call it “business as usual” — wind and solar farms are built haphazardly, with little consideration for land impacts. In the other future, developers use land more efficiently. Business as usual would require 266,410 square miles — an area around the size of Texas — to fit all the solar panels and wind turbines, plus batteries to store electricity when sunlight and wind are unavailable and long-distance power lines to bring power from rural areas to towns and cities. The researchers used a statistical model to discover the suite of technologies that would minimize land impacts. A smarter strategy, they found, could slash that footprint by more than half, to 114,642 square miles — a little bigger than Arizona. That’s still a lot of land, but it would reduce the opportunities for conflict, the researchers said.32:T855,## Notes on the data The Nature Conservancy asked me to include the following notes and caveats: >> The energy system modeling builds renewable resources in each of 24 zones in the continental U.S. based on least cost projects to reach net-zero emissions. To study siting implications on natural lands and communities in detail, we 'downscale' the renewable build in each zone based on the statistical likelihood of using different parcels of land based on the patterns of historical build for wind and solar. This downscaled representation represents just one of many plausible scenarios for buildout and should not be seen as determinative at a local level nor should be used to recommend or prioritize development projects. >> The Nature Conservancy (TNC) developed these data and reserves all rights in the data provided. All data are provided as is. TNC makes no warranty as to the currency, completeness, accuracy or utility of any specific data. Data are for informational purposes and are not suitable for legal, engineering, or surveying purposes. Data do not represent an on-the ground survey and represent only the approximate relative location of feature boundaries. TNC shall not be held liable for improper or incorrect use of the data described and/or contained herein. Commercial use is prohibited. Any sale, commercial distribution, loan, or offering for use of these digital data, in whole or in part, or the use of these data to produce other GIS products and services with the intent to sell for a profit, is prohibited without the prior written consent of The Nature Conservancy (TNC). Sharing or redistributing the data (sub-licensing) to any third party is not allowed. Users must obtain a direct license by downloading the data themselves. The Nature Conservancy (TNC) shall be acknowledged as data contributors to any reports or other products derived from these data. Citation: Jones, R., G.C. Wu, E. Leslie, C. Hise, J. Fargione, N. Johnson, C. Hiltibran, L. Kalies, B. Cohen, J. Williams. 2023. Power of Place – National: Environmental and social impact score datasets. The Nature Conservancy.33:T701,map = () => { const wrapper = d3.create("div") .style("width", `${width}px`) .style("height", `${height}px`); wrapper.append("style").html(css); const canvas = wrapper.append("div") .attr("class", "raster") .append("canvas") .attr("width", width) .attr("height", height) .node() .getContext("2d") .drawImage(raster, 0, 0, width, height); const svg = wrapper.append("div") .attr("class", "vector") .append("svg") .attr("width", width) .attr("height", height); svg.append("path") .datum(conusInner) .attr("class", "inner") .attr("d", path); svg.append("path") .datum(conusOuter) .attr("class", "outer") .attr("d", path); const anno = svg.selectAll(".anno") .data(mapAnnotations) .join("g") .attr("class", "anno") .attr("transform", d => `translate(${projection(d.coordinates(width))})`); const annoTitle = anno.append("g") .attr("class", "anno-title") .attr("fill", d => d.color) .attr("text-anchor", d => d.textAnchor(width)); annoTitle.append("text") .attr("class", "bg") .html(d => d.titleHtml(width)); annoTitle.append("text") .attr("class", "fg") .html(d => d.titleHtml(width)); const annoDescription = anno.append("g") .attr("class", "anno-description") .attr("text-anchor", d => d.textAnchor(width)); annoDescription.append("text") .attr("class", "bg") .attr("dy", width <= 480 ? 14 : width <= 960 ? 16 : 18) .html(d => d.descriptionHtml(width)); annoDescription.append("text") .attr("class", "fg") .attr("dy", width <= 480 ? 14 : width <= 960 ? 16 : 18) .html(d => d.descriptionHtml(width)); return wrapper.node(); }34:T541,mapAnnotations = [ { color: "#8868d9", coordinates: ww => [ -95, 47 ], titleHtml: ww => "Wind", descriptionHtml: ww => "", textAnchor: ww => "start" }, { color: "#D6B46E", coordinates: ww => ww <= 768 ? [ -83.5, 27 ] : [ -83, 27 ], titleHtml: ww => "Solar", descriptionHtml: ww => "", textAnchor: ww => "end" }, { color: "#3a3a3a", coordinates: ww => ww <= 330 ? [ -82.5, 33.6 ] : ww <= 400 ? [ -82, 33.6 ] : ww <= 500 ? [ -81, 34 ] : ww <= 600 ? [ -80, 34.4 ] : ww <= 850 ? [ -79, 34.8 ] : [ -75.5, 36.8 ], titleHtml: ww => "Co-location", descriptionHtml: ww => ww <= 480 ? "Wind & solar" : ww <= 1200 ? "Wind and solar" : "Wind and solar together", textAnchor: ww => "start" }, { color: "#ea0017", coordinates: ww => ww <= 400 ? [-124, 43] : ww <= 480 ? [-119, 44] : ww <= 650 ? [-119, 44.5] : ww <= 768 ? [-119, 44.8] : ww <= 850 ? [ -120, 48.7 ] : [ -120, 48.2 ], titleHtml: ww => "Agrivoltaics", descriptionHtml: ww => ww <= 400 ? "Solar withfarmland" : ww <= 480 ? "Solar and farmlandtogether" : ww <= 650 ? "Solar and farmlandtogether" : "Solar and farmland together", textAnchor: ww => ww <= 400 ? "start" : "middle" }, ]35:[{"id":"3f34d47829851e750ca1eae26089ee99591652d26b2d4705c1eef7be396c4c71ef7dd25a0483c0ffe6a2dd7f8b6446f1658e8fac0f55e5ff41a9bbddfd064e53","href":"https://static.observableusercontent.com/files/3f34d47829851e750ca1eae26089ee99591652d26b2d4705c1eef7be396c4c71ef7dd25a0483c0ffe6a2dd7f8b6446f1658e8fac0f55e5ff41a9bbddfd064e53","name":"usTopo.json","type":"application/json","lastModified":1683554252778.25,"size":60898},{"id":"622fb78c4deee954a8a921ba558b2367200f95a5669e06d878d5364b094ae7dfe5420e3ff7b24febf6cb1fe1be4d7ba6fd21b3063f2e532bbfdca24e831af2e1","href":"https://static.observableusercontent.com/files/622fb78c4deee954a8a921ba558b2367200f95a5669e06d878d5364b094ae7dfe5420e3ff7b24febf6cb1fe1be4d7ba6fd21b3063f2e532bbfdca24e831af2e1","name":"c70percentreduction_2050.png","type":"image/png","lastModified":1683679469481.717,"size":381241},{"id":"096d4e504b5b56bd41a44ebde9f13682c80da5bb66de835b92c5c5767fb68cd16e45767217695216f9dc2b0f79a3020cd35fd22158a57dcaa29847a88c2a2d20","href":"https://static.observableusercontent.com/files/096d4e504b5b56bd41a44ebde9f13682c80da5bb66de835b92c5c5767fb68cd16e45767217695216f9dc2b0f79a3020cd35fd22158a57dcaa29847a88c2a2d20","name":"SAU_2050.png","type":"image/png","lastModified":1683665324850.211,"size":427032}] 2f:{"title":"Geographic footprint of solar and wind farms in a net-zero 2050","cells":[{"id":0,"value":"# Geographic footprint of solar and wind farms in a net-zero 2050","pinned":false,"hidden":false,"mode":"md"},{"id":256,"value":"This notebook contains a version of the map from [“We need an area the size of Texas for wind and solar. Here’s how to halve it.”](https://www.washingtonpost.com/climate-environment/interactive/2023/renewable-energy-land-use-wind-solar/), which appeared in The Washington Post on May 10, 2022.","pinned":false,"hidden":false,"mode":"md"},{"id":259,"value":"The geospatial data used to produce the map was provided to me by the Nature Conservancy. The files are too large too include in this notebook, but they are available upon request. Please see below for notes and caveats on the data.","pinned":false,"hidden":false,"mode":"md"},{"id":188,"value":"viewof scenario = Inputs.radio([\"Business as usual\", \"Reduced land impact\"], { label: \"Scenario:\", value: \"Business as usual\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":116,"value":"map()","pinned":false,"hidden":false,"mode":"ojs"},{"id":253,"value":"note()","pinned":false,"hidden":false,"mode":"ojs"},{"id":284,"value":"toc({ selector: \"h2\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":263,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":271,"value":"$32","pinned":false,"hidden":false,"mode":"md"},{"id":199,"value":"## Graphics","pinned":false,"hidden":false,"mode":"md"},{"id":79,"value":"$33","pinned":true,"hidden":false,"mode":"ojs"},{"id":244,"value":"note = () => d3.create(\"div\").style(\"color\", \"#666\").style(\"font-family\", franklinLight).style(\"font-size\", \"14px\").text(\"Note: “Reduced land impact” represents a 70% reduction in land impacts compared to business as usual\").node()","pinned":true,"hidden":false,"mode":"ojs"},{"id":153,"value":"## Style","pinned":false,"hidden":false,"mode":"md"},{"id":151,"value":"css = `\n.vector, .raster {\n position: absolute;\n}\n.inner, .outer {\n fill: none;\n stroke-linejoin: round;\n}\n.inner {\n stroke: #808080;\n stroke-opacity: 0.5;\n}\n.outer {\n stroke: #808080;\n}\n.anno {\n font-family: ${franklinLight};\n}\n.anno-title {\n font-size: ${width <= 400 ? 14 : width <= 480 ? 16 : width <= 960 ? 18 : 21}px;\n font-weight: bold;\n}\n.anno-description {\n font-size: ${width <= 480 ? 13: width <= 960 ? 14 : 16}px;\n}\n.anno .bg { \n fill: white;\n stroke: white;\n stroke-linejoin: round;\n stroke-opacity: 0.9;\n stroke-width: 6px; \n}\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":203,"value":"## Dimensions","pinned":false,"hidden":false,"mode":"md"},{"id":24,"value":"height = width * 0.631","pinned":true,"hidden":false,"mode":"ojs"},{"id":201,"value":"## Geo","pinned":false,"hidden":false,"mode":"md"},{"id":28,"value":"projection = d3.geoAlbers().fitSize([width, height], conusOuter)","pinned":true,"hidden":false,"mode":"ojs"},{"id":141,"value":"path = d3.geoPath(projection)","pinned":true,"hidden":false,"mode":"ojs"},{"id":32,"value":"conusTopo = FileAttachment(\"usTopo.json\").json()","pinned":true,"hidden":false,"mode":"ojs"},{"id":35,"value":"conusInner = topojson.mesh(conusTopo, conusTopo.objects.ne_50m_admin_1_states_provinces_lakes, (a, b) => a !== b)","pinned":true,"hidden":false,"mode":"ojs"},{"id":37,"value":"conusOuter = topojson.mesh(conusTopo, conusTopo.objects.ne_50m_admin_1_states_provinces_lakes, (a, b) => a === b)","pinned":true,"hidden":false,"mode":"ojs"},{"id":208,"value":"## Data","pinned":false,"hidden":false,"mode":"md"},{"id":205,"value":"$34","pinned":true,"hidden":false,"mode":"ojs"},{"id":163,"value":"images = ({\n \"Business as usual\": FileAttachment(\"SAU_2050.png\"),\n \"Reduced land impact\": FileAttachment(\"c70percentreduction_2050.png\")\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":70,"value":"raster = images[scenario].image()","pinned":true,"hidden":false,"mode":"ojs"},{"id":218,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs"},{"id":282,"value":"import { toc } from \"@harrystevens/toc\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":224,"value":"import { franklinLight } from \"@climatelab/fonts@44\"","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W35","stdlib":"1","titling":"auto"}