Energy Impact
Calculator

The one-sentence version for a class: every way of making clean electricity works, but they demand wildly different amounts of land, materials, storage, and time, and this tool lets students see those trade-offs for their own country or state.

Three classroom exercises, 10–15 minutes each.

1. The reliability trade. Set your country (or US state). Run "All solar," then "All nuclear." Compare the Storage & Firming section between the two. Discuss: why does one mix need batteries and overbuilding while the other needs none? What does the "Firm it" toggle change, and what does that tell you about the difference between energy and reliable power?

2. The land question. Run "Jacobson 100% (renewables only)," then "Study consensus 2050," then "France style (70% nuclear)," then "All nuclear," watching only the land section. The map comparison changes from countries to counties. Discuss: is land the right thing to minimize? Who decides what land gets used? Check the wind note — should we count the space between turbines?

3. What did France actually do? Pick your region, choose "Rebuild the entire grid," and use the France-style preset. France did roughly this between 1974 and 1990. Compare the build time shown to those 16 years. Then check the record-book table in Methodology: which country holds each record, and when? What do the dates tell you about whether the barrier is physics or politics?

Terms your students will hit: see the plain-language glossary in Methodology & sources below. Every number in this tool traces to a linked source there. Print any scenario as a one-pager with the button in the Share section.

Data as of July 2026. Electricity data: EI Statistical Review 2025 (full-year 2025). Built by Generation Atomic, a 501(c)(3) growing the movement for the atomic energy of today and tomorrow. Questions or corrections: gena@generationatomic.org.

Electricity data: Energy Institute Statistical Review of World Energy (2025 generation by fuel, by country). Non-electric fossil energy is each region's oil, gas, and coal consumption minus the share burned in power plants, from the same source.

Nuclear land & multi-unit sites: The 0.15 km²/TWh/yr nuclear figure is Lovering’s mean across 59 operating US stations. It covers the fenced plant site, not the wider emergency planning zone, which is a regulatory radius rather than occupied land. People live, farm and work inside EPZs today. That paper’s median is lower still at 0.071, and its authors call US plants an upper bound because most other nuclear countries put more reactors on a single site. This tool takes the mean because the mean is what the authors recommend for scale-up questions: building more of a source means building its land-hungry examples alongside its efficient ones. Because a reactor’s site scales sublinearly with capacity, multi-unit stations use far less land per TWh than single units, and siting four reactors together barely enlarges the footprint of one. Real fleets cluster their units, so the effective number is often below even this.

Land: Land-use intensity of real operating sites from Lovering, Swain, Blomqvist & Hernandez (2022), PLOS ONE, in km² per TWh per year: nuclear 0.15 for the fenced site, or the site plus its emergency planning zone if you switch that on, onshore wind 0.4 direct or 99 with full project spacing, switchable in the Land section, utility solar 19 blended with rooftop at 0.5 on the rooftop-share slider (default 40% rooftop, roughly the world split today), hydro 14, geothermal 1.4, gas w/ CCS 1.3. Biomass defaults to dedicated energy crops at 580 km²/TWh/yr, the honest figure for biomass scaled as a grid resource, since Lovering finds dedicated biomass is the single most land-hungry source, with a median of 58,000 ha/TWh/yr, four orders of magnitude above nuclear. Switching the feedstock to waste and residue in Advanced drops it to 0.15, because burning leftovers claims no dedicated land. Nuclear takes that paper’s mean of 15 ha/TWh/yr rather than its lower median of 7.1, for the reason set out in the multi-unit note above. One further number from the same survey: the Chernobyl and Fukushima exclusion zones, divided by every terawatt-hour nuclear has ever generated, add 3.9 ha/TWh/yr, or 0.039 km², so the two worst accidents in the industry’s history barely move its land intensity.

Plant lifetime: Nuclear defaults to 80 years. US reactors originally licensed for 40 years have been receiving subsequent renewals to 80, several already hold them, and lifetime-extension programmes are running across Europe and Asia, so 80 is the realistic planning life for a plant built today rather than an optimistic one. The 60-year option in Advanced gives the more conservative first-renewal figure if you want it, and 40 shows the as-designed licence. Lifetime here sets the rebuild rate, meaning how much capacity must be replaced each year to hold output indefinitely: at 80 years nuclear replaces a little over 1% of its fleet annually, against 3.3% for solar at 30 years and 5% for wind at 20. It does not change build materials, because a reactor licensed for 80 years contains the same steel and concrete as one licensed for 60.

Where the wind and solar lifetimes come from: solar is held at 30 years, the project lifetime NREL's 2024 Annual Technology Baseline uses for utility-scale PV, over which it models roughly 0.5–0.7% annual degradation. Modules now carry 30-year warranties, so the older 25-year convention understates them. Wind is held at 20 years, the IEC 61400 design life and close to when operators in practice repower rather than refurbish; life-extension to 25 or 30 years is increasingly common, so 20 is the conservative end for wind in the same way 80 is the optimistic end for nuclear. Both figures set the rebuild rate only. Build materials are unaffected, because each technology's published material intensity is converted at the lifetime its own source assumed, not at the lifetime set here.

Unabated gas in the mix: Gas without carbon capture is offered as a slider because almost every real grid that calls itself clean still leans on it, and hiding that would flatter every scenario here. Choosing it does what it does in reality: emissions rise (490 g CO₂/kWh against nuclear's 6 and solar's 29) while the battery bill falls, because gas is dispatchable and can cover a wind lull that would otherwise need storage. The tool models that by sizing storage and overbuild on the wind-and-solar share net of the gas share, which is the simple and transparent version of how peakers actually firm a grid. It is deliberately generous to gas on one point and harsh on another: generous because it credits gas with firming on an energy-share basis when what really matters is available capacity, and harsh because it charges gas its full lifecycle carbon with no allowance for future capture. Gas is also excluded from the nuclear load-following penalty, since a gas fleet is flexible by design. Every clean-grid claim in the results should be read with the gas share in mind: a mix that is a fifth gas is not a clean grid, it is a mostly-clean grid with a fossil backstop, and the carbon number will say so.

Emergency planning zones: The default counts nuclear's fenced site, because an EPZ is a planning boundary rather than occupied land: people live, farm and work inside them, and none of that land is withdrawn from use. Because critics nonetheless cite it as nuclear's footprint, the Land section offers the option, sized to the reactor actually selected rather than to a single legacy figure. The familiar 10-mile ring comes from NUREG-0396, issued in 1978 and sized around the large reactors of that era. Modern assessments are much smaller: Huang et al. (2011), Atomic Energy Science and Technology 45(12), put the AP1000 outer plume EPZ at 7 km with a 3 km inner zone. The regulator has since moved past deciding this one licence at a time. In November 2023 the NRC issued a final rule creating 10 CFR 50.160, a performance-based emergency-preparedness framework for small modular reactors and other new technologies, with Regulatory Guide 1.242 issued alongside it. Among its provisions is a scalable method for sizing the plume exposure pathway EPZ, so a design whose accident consequences stay onsite can end its zone at the site boundary. That is codified regulation, not an exemption granted case by case. NUREG-0654 had already allowed about 5 miles for reactors under 250 MWt, and work on high-temperature gas reactors concludes the zone can equal the exclusion-area boundary outright. The tool therefore uses roughly 9 km² per TWh per year for a large modern reactor and effectively nothing for SMRs and microreactors, with the 1978 ring available in Advanced for anyone who wants the number usually quoted at them. Where that lands: even counting the modern EPZ in full, a nuclear grid still occupies less land than an equivalent solar one.

Transmission: Now included, and it is the piece most tools leave out. Remote, diffuse generation needs new high-voltage corridors; plants sited at existing grid nodes, frequently retiring coal sites with interconnection already in place, need only a short spur. The model counts 500 kV circuits using Princeton Net-Zero America's own downscaling convention of one circuit per 3.5 GW of corridor capacity, MISO's 2024 Transmission Cost Estimation Guide figure of roughly $2.67 million per km for single-circuit 500 kV, and a right-of-way about 61 m wide. Corridor length is the honest uncertainty, so it is a visible assumption rather than a buried one: 200 km for remote wind and solar, 25 km for plants at existing nodes, adjustable in Advanced by half or double, or switchable off entirely. The result tracks the published literature in direction and rough scale: a wind-and-solar grid needs tens of times the new line a nuclear one does, and transmission lands at roughly 5 to 6% of capital cost for variable-heavy mixes against well under 1% for firm ones. Net-Zero America finds US high-voltage capacity must grow about 60% by 2030 and roughly triple by 2050 in its renewables-led pathway, while its constrained-renewables pathway, which leans on tripling nuclear, needs substantially less. Treat the absolute kilometre figures as indicative and the ratio between mixes as the point. The asymmetry is the substance: wind and solar are diffuse and often remote, while nuclear can usually reuse an existing grid node, frequently a retiring coal site with interconnection already built.

Where new nuclear is illegal: Eight US states hold statewide moratoriums as of July 2026: California, Hawaii, Maine, Massachusetts, Minnesota, Oregon, Rhode Island and Vermont. Some are outright bans, some need a public vote, some wait on a federal waste repository. Connecticut and New York restrict only certain sites. Abroad the tool flags bans in Australia, Austria, Denmark, Ireland, Italy, New Zealand and Switzerland, and phase-outs in Germany, Spain and Taiwan. The default flags the restriction and builds the scenario anyway, because these laws keep moving: six US states have repealed theirs since 2016, Illinois and New Jersey in 2026. Advanced can enforce them instead. This is the most perishable data in the tool, so check the date before quoting it.

Capturing the grid’s own carbon: Solid-sorbent direct air capture runs at roughly 2 MWh per tonne of CO₂ once the heat to regenerate the sorbent is counted, which is the middle of the published range for commercial designs and well above the 0.5 to 1 MWh some vendors project for later generations. One megatonne removed therefore costs two terawatt-hours. The toggle sizes capture to the lifecycle emissions of the grid being built, so a mix is asked to clean up after itself rather than after some allocated share of a global removal target that would need an allocation rule this tool has no business inventing. The part worth sitting with is the feedback. Capture plants draw from the grid they are cleaning, and that electricity carries the grid’s own carbon, so removing one tonne means removing rather more than one tonne. Written out, capture equals gross emissions divided by (1 minus 2 MWh/t times the grid’s intensity in tonnes per MWh). That series converges only while the grid sits below 500 g/kWh. Above it, every capture plant emits more than it removes and no quantity of them closes the gap, which is why the tool refuses to print a number there. None of that is an assumption anyone chose. It falls out of the arithmetic, and it is the reason capture is a companion to a clean grid rather than a substitute for one. Two things this does not yet model: the capital cost of the capture plants themselves, which is separate from the generation they need, and geological storage capacity for what comes out.

Desalination: The toggle in Step 2 adds the electricity to desalinate 100 litres per person per day at 4.0 kWh per cubic metre, which works out to roughly 0.146 TWh a year per million people. That figure is the middle of the range for real full-scale seawater reverse-osmosis plants including pre- and post-treatment, which run 3.5 to 4.5 kWh/m³; a survey of 39 operating facilities averaged 4.13, while best-in-class extra-large plants reach about 2.8 and an experimental record has broken 2.0. At world scale that is about 1,035 TWh, near 3% of current generation; for a single water-scarce country it is a few TWh. The control only appears where there is saltwater to desalinate, so it is hidden for landlocked countries and inland US states. Azerbaijan, Kazakhstan and Turkmenistan keep it despite being landlocked from the ocean, because the Caspian is saline and desalination there is long established: Kazakhstan’s Aktau plant ran on the BN-350 fast reactor from 1973. It is a control rather than a footnote because water scarcity is one of the clearest cases for firm, sited-anywhere power. Buongiorno’s group at MIT makes the specific case: a seawater reverse-osmosis plant collocated with an existing reactor gets low-cost electricity, can share the station’s existing seawater intake and outfall, and carries no operating carbon footprint. Because RO is electrically driven rather than thermal, it also retrofits onto plants already built, which is not true of the older thermal desalination processes. Two limits worth stating: the figure covers drinking and household water only, so irrigation volumes would be far larger, and it assumes seawater RO rather than brackish or thermal processes, which have different energy profiles. The demand is added on top of the grid being replaced, so it raises the build rather than reshuffling it.

Cost basis: Every capital cost is overnight capital cost in 2024 US dollars per kilowatt: the cost to build, excluding interest during construction, grid connection and transmission. All technologies are quoted the same way so comparisons between them are apples to apples. The nuclear ladder was rebuilt against the post-Vogtle literature rather than pre-Vogtle projections. Vogtle 3 and 4 realised roughly $17,500/kW as a genuine first-of-a-kind after a supply chain and workforce that had stopped building reactors. MIT's Center for Advanced Nuclear Energy Systems (Shirvan, 2024) puts the next AP1000 at $8,300 to $10,375/kW and the Nth-of-a-kind at $4,625/kW after 10 to 20 units; Idaho National Laboratory (2025) models the intervening learning curve explicitly at $10,000, $7,800 and $6,200/kW for the second, third and fourth two-unit plants, with build times falling from 7 to 5.5 years. The default sits at the DOE Liftoff NOAK figure of $4,700/kW, which is within 2% of MIT's independent NOAK estimate, but the honest point is that the default is a mature-fleet number and the next plant will not cost it. If you are arguing about the plant being built now rather than the fiftieth, select one of the near-term figures. Financing matters enormously for capital-heavy, slow-building plants, so a levelised cost would treat nuclear less kindly than an overnight figure does; overnight cost is reported because it maps onto physical build effort rather than one country's interest rates. Storage is costed separately per kilowatt-hour installed.

Materials: Tonnes per GWh of lifetime generation, anchored to US DOE Quadrennial Technology Review (2015) as updated by Wang et al., Breakthrough Institute (2023). Fleet build mass = intensity × annual generation × the reference lifetime each published intensity was normalised to. Those references are not the operating lives used elsewhere in the tool; they are the denominators baked into the source figures, and they are fixed on purpose. For nuclear that denominator is 60 years even though the tool assumes an 80-year operating life, because changing how long a reactor runs alters how often it must be rebuilt, not how much steel and concrete went into building it once. Uranium fuel shown as annual demand versus world mine production.

Critical minerals: The materials section shows two lists that drill down rather than compete. The first is the whole build by tonnage, with every critical mineral collapsed into a single Critical minerals (all) row, so the scale stays consistent and concrete and steel appear as the bulk of the mass they genuinely are. The second list opens that row up. It is measured in years of current world mine output rather than tonnage, because within the criticals the tonnages span four orders of magnitude and a straight tonnage bar would bury silver beside copper the same way concrete buries everything else. Years of world output is also the constraint that actually binds: a build needing three years of global silver supply cannot simply buy it in a year. Intensities come from the IEA's critical-minerals work, whose per-technology intensities originate in The Role of Critical Minerals in Clean Energy Transitions (2021) and are now maintained through the annual Global Critical Minerals Outlook (2025 edition), converted from its kilograms-per-megawatt figures using each technology's capacity factor and reference lifetime; the conversion reproduces the IEA's published totals closely (onshore wind about 10,000 kg/MW, solar about 7,000, nuclear about 5,000 to 6,000). Steel, aluminium, glass and polymers sit in the bulk list because the IEA deliberately excludes them from its critical scope. Battery minerals (lithium, graphite, cobalt, and part of the nickel, manganese and copper) are driven by installed storage rather than generation, using an LFP-leaning blend of roughly 0.1 kg of lithium per kWh, since that is where a wind-and-solar grid's mineral demand concentrates. Copper appears once, on its original DOE and Breakthrough Institute intensity with battery copper added, rather than being counted from both sources. Hydro, geothermal, biomass and gas with CCS are not broken out in the IEA's headline comparison, so they use the nearest documented analogue and should be read as estimates. World output figures are USGS-order annual production; concrete is the finished material, roughly eight times cement tonnage. One caveat is stated on screen too: chromium, nickel, manganese and molybdenum are alloying metals already contained in the steel tonnage above, so the two lists are a drill-down, not a sum to be added together.

Breeder reactors & uranium supply: The default once-through fuel cycle uses only the ~0.7% of natural uranium that is U-235. Fast breeder reactors convert the abundant U-238 into fuel, extracting on the order of 60× more energy per tonne mined and able to run down existing spent-fuel and depleted-uranium stockpiles; the tool cuts uranium demand accordingly and raises nuclear capital cost about 20%. Breeders work (Russia's BN-800 runs commercially) but have a thin and costly track record (France's Superphénix, the US IFR), so treat the option as a what-if, not a deployed baseline. Separately, uranium from seawater has been demonstrated at laboratory scale and would make the resource effectively limitless; its higher extraction cost (~$400–1,000/kg versus roughly $130 today) barely moves the delivered electricity price because fuel is a small share of nuclear's cost. Both are off by default.

Carbon: Lifecycle medians, g CO₂/kWh: nuclear 6, wind 14, solar 29, hydro 15, geothermal 19, gas w/ CCS 130, unabated gas 490, coal 820, oil 650. Nuclear’s figure comes from the UN Economic Commission for Europe’s Carbon Neutrality in the UNECE Region: Integrated Life-cycle Assessment of Electricity Sources, whose final March 2022 edition puts nuclear at 5.1 to 6.4 g CO₂e/kWh, the lowest of any technology it assessed. The rest are IPCC AR5 medians, cross-checked against the same report. UNECE issued a corrigendum in July 2022 correcting the land-use figures in that report, where biomass in the background electricity mix had inflated silicon PV; the greenhouse-gas results were untouched, and the land numbers here come from Lovering rather than UNECE in any case. Biomass defaults to 230, the IPCC AR5 lifecycle median that reflects dedicated-crop cultivation, fertilizer N₂O, and land-use change; switching to waste and residue feedstock in Advanced drops it to 34. Biomass carbon is genuinely contested, and counting it as low-carbon at all assumes the harvested carbon regrows, which can take decades.

Carbon beyond the grid: When a scenario replaces fuels outside the power sector, the avoided-CO₂ figure credits that displaced thermal fossil energy at a blended 180 g CO₂ per kWh of fuel burned, net of the emissions of the clean electricity that replaces it. The blend spans transport oil, heating and industrial gas, and industrial coal, and is anchored so that world-scale figures reproduce the roughly 23,000 Mt of annual CO₂ that comes from non-power fossil use. This is why switching on fuels-beyond-the-grid roughly triples the carbon a scenario abates: most fossil carbon is not burned in power stations. Direct electrification is far cheaper in energy terms than synthesising fuel, needing about 40% of the original thermal energy against roughly 220% for power-to-liquids, so the electrified share is the single biggest lever on how much generation the scenario demands.

Build pace: Each technology builds at the fastest 5-year national pace on record: the largest 5-year rise in annual generation, divided across those five years, per person at the time (period population — measuring the achievement as it happened), recomputed from the 2026 EI Statistical Review (full-year 2025), countries ≥5M people, with 3-year smoothing on hydro to stop a wet year scoring as construction. Population is derived from EI's own figures so there is one source per number. Geothermal and biomass come from the OWID composite (Ember, EI and IRENA) because EI reports them in a single combined column with no usable history. Because pace is per-capita, bigger regions automatically get proportionally bigger workforces; the Advanced mobilisation setting scales ×0.5–×3, and a second Advanced setting chooses which record length to hold each source to. Technologies build in parallel; "years to build" is the slowest lane. The record book, generated from the same table the model reads:

Beyond the grid: Fossil fuel burned outside the power sector (transport, heat, industry — measured here as fuel energy) is replaced two ways. A share (default 50%, adjustable) is directly electrified. Electricity delivers the same service on far less energy because it skips combustion's heat-engine losses: an EV uses roughly 30% of the fuel energy a petrol car burns, a heat pump about 30% of a furnace's. The tool captures this with a service-efficiency factor (default 0.40× across a mixed set of end uses; selectable down to 0.30× for transport-and-heat-heavy regions or up to 0.55× for heavy industry, where high-temperature process heat gains little from electrification). This is the same efficiency credit Lazard and others apply when comparing electric to combustion end uses — and it is why direct electrification, wherever it is possible, beats making synthetic fuel. The remaining share becomes synfuels: fuel energy ÷ power-to-fuel efficiency (default 45%; published power-to-liquid chains run 40–50%, ICCT models ~52%, pure hydrogen 65–70%). Two honest caveats a critic will raise: high-temp industrial heat and some heavy transport are genuinely hard to electrify, which is what the adjustable industrial setting is for; and wind and solar, being electricity already, never pay a heat-to-electricity conversion at all — their advantage over thermal generation on this front is real and is reflected in the fact that every clean source here is counted by delivered electricity, not fuel-energy-in.

Jobs: Operations jobs per MW are literature-anchored estimates in the tradition of Rutovitz, Dominish & Downes (2015, for Greenpeace/ISF), the most widely-cited global source for energy employment factors. The nuclear figure (0.7 jobs/MW, generation plus fuel cycle) reproduces the US Energy & Employment Report 2025's actual combined total for nuclear generation and fuel (67,900 jobs) applied to the current US fleet almost exactly — the closest independent check available. Solar and wind use lower permanent-operations factors than some advocacy sources cite, because utility-scale plants need very little ongoing staff once built: a large solar farm runs with a handful of technicians, so its permanent employment per unit of energy is well below nuclear's (this tool shows roughly 35 permanent jobs per TWh for solar and 55 for wind, against about 90 for nuclear). Most solar and wind employment is one-time construction and manufacturing, which is counted separately as job-years, not permanent jobs. The other technologies' factors follow the same literature but haven't each been re-verified against USEER line items; treat them as reasonable estimates. Construction and manufacturing job-years per MW built come from the same source family.

Ending energy poverty: When enabled, the build is sized so every person in the region reaches a target annual electricity use. The world today averages roughly 4,000 kWh per person per year, but that hides enormous inequality: North Americans use about 12,400, Europeans about 6,000, and much of the global South only a few hundred. Targets offered: a "modern decent living" floor (3,500 kWh, in the spirit of the Rockefeller Foundation's Modern Energy Minimum and related decent-living-standard work), the European level (6,000 kWh, a developed standard without North America's air-conditioning and large-home intensity), and the US level (12,385 kWh). The uplift is added to the clean build target on top of any demand-growth multiplier; regions already above the target see no change. This is the honest scale of the climate-and-development problem together: decarbonizing while also lifting billions out of energy poverty is a far bigger build than decarbonizing today's grid alone.

Finishing the build by a date: The slider in Step 2 sets a completion year, and the year sets how much demand the grid has to serve when it opens. The curve runs through three published points: today at the 2025 end, 1.45× by 2035, which is the IEA World Energy Outlook range of 40 to 50% global electricity demand growth, and 2× by 2050, where full-electrification scenarios converge. Years in between are interpolated, which is close to the shape the underlying projections draw anyway. Data-centre and AI load is already inside those trajectories, since the IEA builds its demand outlook on its own AI forecast, so there is no separate data-centre toggle to add on top and double-count. Growth lands on the electric build target; the fuels-beyond-the-grid target stays tied to today’s fuel use. Picking a date cuts both ways, which is the point of making it one control. A later year buys build time and costs you a bigger grid. An earlier one shrinks the grid and shortens the runway, and the note under the slider says plainly whether the mix you have chosen can be built in the years remaining, at the pace that mix assumes.

Capital cost: Overnight costs per kW from the EIA/Sargent & Lundy Capital Cost and Performance Characteristics report (2025-2026 vintage) and the AEO2026 Electricity Market Module assumptions. Wind $1,500/kW and solar $1,400/kW match EIA's current modeling inputs. Nuclear defaults to the DOE Pathways to Commercial Liftoff Nth-of-a-kind cost ($3,600/kW after 10–20 deployments of a standard design; the same report puts a well-executed first-of-a-kind at $6,200/kW and NOAK AP1000s at $4,700/kW). Advanced offers the actual Vogtle 3&4 cost ($15,700/kW), DOE's projected fourth AP1000 ($6,200/kW), the Barakah turnkey price (~$4,300/kW), and domestic Chinese (~$2,800/kW, Hualong One) and Korean (~$2,300/kW, APR1400) builds — the proven costs where nuclear construction never stopped. Solar and wind get parallel options: US EIA inputs (default), IRENA global weighted averages (~$800 and ~$1,150/kW), and lowest-market costs. Rooftop solar automatically switches to ~$2,700/kW (NREL residential/commercial blend) and offshore wind to ~$4,000/kW with a 45% capacity factor and no land footprint. Gas + CCS uses EIA/Sargent & Lundy's combined-cycle with 90% carbon capture (~$3,000/kW); note no such plant runs commercially at scale, so treat it as an engineering estimate rather than a market price. Investment figures are overnight capital only — no financing, fuel, or operating costs.

Why firm capacity is modelled at all: The premise behind this tool's firming penalty is not ours. Sepulveda, Jenkins, de Sisternes & Lester (2018), Joule 2(11), evaluated nearly 1,000 decarbonisation cases and found that availability of firm low-carbon resources, nuclear among them, reduces the cost of a fully decarbonised grid by 10 to 62%, that below 50 g CO₂/kWh they lower costs in the vast majority of cases, and that across every case examined the least-cost path to clean electricity includes at least one firm resource. Their conclusion that batteries and demand flexibility do not obviate the value of firm capacity is what justifies charging wind and solar for storage and overbuild here rather than assuming those problems away. Buongiorno et al. (2018), the MIT Energy Initiative's Future of Nuclear Energy in a Carbon-Constrained World, reaches the same place from the cost side: excluding nuclear from low-carbon scenarios drives the average cost of electricity up significantly.

Firm grids and storage: Above ~70% firm share, a grid still has to meet a daily demand swing, and there are two real ways to do it. It can load-follow, throttling reactors down at night so the fleet's capacity factor falls and more nameplate is built to cover peaks (France does this). Or it can run the plants flat-out and store the surplus, banking cheap overnight output and returning it at the peak, which is precisely why several pumped-hydro stations were built alongside nuclear plants in the 1970s and 80s. This tool costs both paths and, by default, picks the cheaper for the scenario (override in Advanced). Storing the surplus keeps nuclear's capacity factor high and usually shortens the build. Crucially, a firm grid needs only a daily shift of a few hours, an order of magnitude less storage than a wind-and-solar grid, which must ride out multi-day weather droughts. Storage, in other words, helps nuclear too; it just needs far less of it.

Storage & firming: When "Firm it" is on, battery storage and wind/solar overbuild scale with the variable share of delivered power, interpolated between anchor points from Tong, Farnham, Duan, Zhou, Geng, Lei, Davis & Caldeira (2021, Nature Communications), which extends the earlier US-only Shaner, Davis, Lewis & Caldeira (2018) to 42 countries. Their figures: wind and solar sized to annual mean demand, with no storage, meet 72–91% of hourly demand (mean 83%); with 12 hours of storage, 83–94% (mean 90%); at 1.5× generation and 12 hours, 89–100% (mean 98%). Beyond that the requirement rises steeply. They also give the exchange rate between the two levers this model uses, which is why it carries both: a 10% increase in excess generation is worth about 3.9 hours of storage. Shaner's US numbers behind the curve's shape: three weeks of storage for the US is 227 TWh, $23 trillion at $100/kWh, and 3.4× generation with no storage buys about the same reliability as 1× with 12 hours.

Why storage does not simply replace firm generation: Sepulveda, Jenkins, Edington, Mallapragada & Lester (2021, Nature Energy) mapped the design space directly. Long-duration storage has to reach an energy-capacity cost of $20/kWh or less to cut electricity system costs by 10%, and $1/kWh or less to fully displace firm low-carbon generation, with the useful durations exceeding 100 hours. Today's utility batteries are around $300/kWh installed. That gap, not a preference, is why this tool charges variable sources for firming rather than assuming it away.

The gap in this curve, with a number on it: Ruhnau & Qvist (2022, Environmental Research Letters) optimised a 100% renewable Germany across 35 weather years instead of one, and found 56 TWh of storage — about 36 TWh electricity-equivalent, roughly 24 days of average load, some 7% of annual demand — with a single weather year understating the requirement by about half. The curve here tops out at 150 hours, or 6.25 days, at 100% variable share, so at the tail it is low by roughly a factor of four on a multi-year basis. It is deliberately not simply raised: their answer is dominated by hydrogen at chemical-storage prices, and this model prices every kWh as a battery, so quoting 24 days at $300/kWh would be a larger error than the one it corrected. Read the storage figures here as the short-duration, single-weather-year case, and treat them as a floor. Real systems would also add transmission and demand response this model omits, which push the other way.

What the cost-optimal literature says instead: worth knowing because it looks like a contradiction and is not. The 2024 Nature Communications work on long-duration storage value finds cost-optimal durations of only 6–10 hours in solar-dominant systems and 10–20 hours in wind-dominant ones, and that seasonal operation only pays below about $5/kWh. Those studies optimise cost while accepting some unserved energy and leaning on transmission; the figures above are what reliability alone demands. Both are true, and they answer different questions. Battery cost defaults to $300/kWh installed (NREL 2025 utility-scale 4-hour benchmark ≈ $334/kWh; leading projects ≈ $125–150). The storage figure is total energy capacity of any duration mix. Synfuel electricity is treated as flexible demand that needs no firming.

Pay & public revenue: Wages anchored to BLS OEWS May 2024 medians (nuclear reactor operators $123,380, nuclear technicians $104,240, power plant operators $103,600, wind techs $62,580, solar installers $51,860); each technology gets a plant-wide average. Tax estimate is deliberately rough: 25% of payroll (combined income and payroll taxes) plus 0.5% of capital cost per year as a property-tax proxy — consistent with reported single-plant figures like nuclear stations paying tens of millions a year to local counties.

Why geothermal's build pace is so low: At 100 kWh per person per year, geothermal has the weakest record of any source in the table, roughly a seventh of nuclear's. That is a fact about demand, not about difficulty. Installed geothermal worldwide has been small enough that, as the Society of Petroleum Engineers puts it, few drilling contractors or service companies could sustain themselves on geothermal work alone, so no country has ever mounted a crash programme. Two things suggest the ceiling is much higher. Iceland added new geothermal generation at roughly 1,970 kWh per person per year between 2004 and 2009, about twenty times the figure used here and more than double nuclear's record, though from a population of 300,000 that does not straightforwardly scale. And the constraint is drilling capacity, which is fungible with oil and gas: a typical geothermal well supports 6 to 10 MW, and enhanced-geothermal developers are now completing deep, 400 °F-plus wells in about three weeks using standard oilfield rigs and shale-basin drill bits, on a demonstrated 35% learning curve. Redirecting something like a third of global oil-and-gas drilling to geothermal would sustain roughly the pace assumed here, so 100 is best read as "a serious but not wartime effort" rather than a physical wall. The tool keeps the historical figure because every other technology's pace is derived the same way, and hand-raising one source on a promissory argument would undermine the comparison. Use the mobilisation multiplier in Advanced to explore faster.

Lives saved: Mortality per TWh from Our World in Data (Ritchie), building on Markandya & Wilkinson (2007, The Lancet) and Sovacool et al.: coal 24.6 deaths/TWh, oil 18.4, gas 2.8, biomass 4.6, hydro 1.3, wind 0.04, nuclear 0.03, solar 0.02. Note the nuclear figure includes Chernobyl and Fukushima, where nearly all deaths came from the evacuation — a policy decision — rather than radiation, so 0.03 is conservative against nuclear. Two different denominators, and it matters. Every figure above is deaths per TWh of electricity generated. Fuel burned outside the power sector has no electricity to divide by, so it is counted per TWh of fuel energy, at a blended 12 deaths per thermal TWh. The two are not comparable as printed. Convert the power figures to fuel energy and coal power is about 9.4 deaths per thermal TWh (24.6 at 38% plant efficiency), oil power about 7.0, gas power about 1.4. So 12 sits above every power-sector fuel on a common basis, and deliberately: a tailpipe or a domestic boiler has no 200-metre stack, no flue-gas desulphurisation, no selective catalytic reduction and no baghouse, and it emits in the street rather than downwind of one. Exposure per unit of fuel is far higher outside the power sector than inside it. The 12 is also a floor against the epidemiology, as set out below.
What the synfuel itself does. The 12 is the harm of the fuel being displaced, not a charge against synthetic fuel. But the tool used to credit all of it whenever fuels-beyond-the-grid was switched on, which quietly assumed a synthetic fuel burns harmlessly. It does not. Transport & Environment ran three e-petrol blends through a Mercedes A180 on WLTC and RDE cycles: particle number fell 81–97%, but NOx was unchanged, particulate mass was unchanged, carbon monoxide rose up to threefold on cold starts and ammonia doubled on some blends. Because fossil-combustion mortality is driven by PM2.5, primary and secondary, and secondary PM forms from exactly the NOx and ammonia that do not improve, most of the harm survives the fuel swap. The genuine gains are sulphur, which is large for marine fuel, heating oil and industrial coal and small for road diesel that is already ultra-low-sulphur, and hydrogen for process heat, where particulates go to zero. So the credit is now split: the directly electrified share (default 50%) removes combustion outright, and the synfuel share is credited at half the harm avoided by default, adjustable to none or all under “synfuel air quality” in Advanced and reported in the non-default banner. At world scale the default cuts lives saved by roughly a quarter against the old all-or-nothing treatment. If you think a paraffinic fuel with no sulphur and no aromatics deserves full credit, the switch is there and the scenario will say you used it.

Flexibility, both directions: Wind and solar above ~30% of delivered power pay in storage and overbuild (see above). Nuclear and geothermal above ~70% pay too: reactors must load-follow, France-style, so fleet capacity factor slides from 90% toward the grid's load factor (~62% at 100% share), and the extra capacity to cover peaks is built and counted. Synfuels lift the penalty for everyone — flexible electrolysis absorbs the off-peak power. No technology gets a free pass on the shape of demand.

SMR & microreactor economics: Switching reactor size also switches the capital-cost menu, because small reactors sacrifice the economies of scale that make large plants cheaper per kW. The evidence so far is sobering: NuScale's cancelled Idaho project reached roughly $21,600/kW, higher per kW than Vogtle. Vendor NOAK targets are lower (IEA 2025 puts EU SMRs near $10,000/kW; independent bottom-up work by Asuega et al. 2023 spans $4,300–6,400/kW), and the tool offers that full range with a mid-estimate default. Microreactors are costlier and more speculative still, with credible figures from about $6,700/kW (Oklo's NRC filing) up to $25,000/kW. The theory that factory production drives costs down is sound but unproven; only three SMRs were operating worldwide as of 2024, too few to show the learning effects proponents expect. Treat every small-reactor cost here as a scenario input, not a market price.

SMR land: Selecting SMRs or microreactors also shrinks the fenced-site land per unit (×0.5 and ×0.3 of the large-reactor figure), reflecting the smaller emergency planning zones these designs pursue on the strength of passive safety, smaller radioactive source terms, and below-grade siting. The direction is what vendors and the NRC's now-final SMR emergency-planning rule point toward; the exact factors are illustrative, not certified, since few of these plants are built and licensed yet.

SMR materials: Large-reactor material intensities are the default. Selecting SMRs applies ×1.6 to structural materials and microreactors ×3, reflecting the surface-to-volume penalty of small cores (direction supported by Krall, Macfarlane & Ewing 2022, PNAS, and UC Berkeley's per-MW commodity comparisons), with genuinely large error bars — some designs like the BWRX-300 target less concrete per MW than large plants. Fuel scales with generation, not with the multiplier.

Fossil jobs displaced: ~127 jobs per TWh of fossil electricity displaced (USEER 2025 generation jobs plus the power-sector share of coal, gas, and oil fuel-supply jobs, divided by US fossil generation) and ~38 jobs per thermal TWh of non-electric fossil fuel displaced by synfuels. US-derived factors applied globally as a rough proxy. Synfuel-plant jobs created are not counted, so the net-jobs figure is conservative for synfuel scenarios.

Plain-language glossary: A TWh (terawatt-hour) is a billion kWh — enough electricity for about 90,000 US homes for a year. Capacity factor is the share of the time a plant effectively runs at full power (nuclear ~90%, solar ~20%). Overbuild means building more wind and solar than demand needs so there's enough on weak days; the surplus on good days is curtailed (thrown away). Firming is everything that turns variable power into reliable power: storage, overbuild, flexible demand. Load-following is a plant ramping down when demand drops — France's reactors do it nightly. Overnight cost is construction cost excluding financing, as if built overnight. NOAK (Nth-of-a-kind) is the cost after a design has been built enough times to get good at it. gCO₂/kWh measures how dirty each unit of electricity is, over the full life cycle.

Build pace in small export regions: The build-time metric divides the job by a region's own population, using the fastest per-person build any nation has achieved. That works for countries and self-contained grids, but it distorts small-population energy exporters: Wyoming generates roughly 69,000 kWh per resident, over five times the US average, because it ships coal power to other states. Paced against its ~590,000 residents, replacing that output looks like it takes generations. The number is honest arithmetic but the framing is wrong for an exporter; in reality neighboring states, which consume that power, would build alongside it. There's no clean per-region fix without labor-force and trade data the tool doesn't carry, so the results flag it in plain language instead.

Generation, not consumption: Every figure here is built on electricity generated inside a region, not electricity consumed there. Regions that import much of their power look small: the District of Columbia generates almost nothing because it buys nearly all its electricity from neighboring states, and any net importer shows a grid smaller than what it actually uses. The model asks what it would take to build clean generation equal to what a region produces from fossil fuels today, which is the honest question for a builder. Cross-border imports and exports, and the transmission that carries them, are not modeled.

Nuclear operating life: Replacement rates assume plants run 80 years before rebuild, the subsequent-renewal term US reactors are now being cleared for, adjustable from 40 up to 100 in Advanced. At 80 years a fleet replaces a little over 1% of itself annually, against 3.3% for solar at 30 years and 5% for wind at 20. Solar's 30 years is NREL's 2024 ATB project lifetime for utility-scale PV; wind's 20 is the IEC 61400 design life. Other technologies use their own service lives. None of those are user-adjustable yet, since nuclear longevity is the figure most often disputed.

The Ontario-style preset mirrors the clean half of the grid Ontario actually runs: roughly half nuclear, about a quarter hydro, and the rest wind, solar and a little biomass, with no geothermal. Ontario decarbonised to over 90% clean and phased out coal entirely by 2014, largely on the strength of its CANDU fleet. One honest gap: Ontario still burns natural gas for a single-digit share of its electricity, mostly for peaking, and the mix builder here only offers clean sources, so that gas is renormalised across the clean ones rather than shown. Read the preset as “Ontario’s clean mix, scaled to carry the whole grid” rather than as a literal copy of its dispatch.

Why land differs so much between mixes: on your current region and land conventions, France style (70% nuclear) comes to …, against … for the study-consensus default. Two things drive the gap. Wind is the biggest land user in the tool at 99 km²/TWh once full project spacing is counted, so how much wind a mix carries dominates its land figure more than any other choice. Hydro at 14 km²/TWh is also geographically capped, so a mix leaning on it can hit a country's river ceiling before it hits a land ceiling. One honest caveat on all of this: counting wind at full project area is arguably harsh, because most of the spacing between turbines stays farmable. The toggle in the Land section switches wind to its pads-and-roads footprint, and it moves the wind-heavy mixes further than anything else in the tool.

Hydro potential ceiling: Because hydro cannot simply be scaled up anywhere the way solar panels or reactors can, the tool checks each scenario's hydro against a per-country feasibility ceiling: the sum of a nation's existing hydro generation plus its remaining economically feasible potential (from Gernaat et al., Nature Energy 2017, a high-resolution assessment of 3.8 million potential sites, cross-checked against IHA and IEA current-generation figures). When a mix asks for more hydro than that ceiling allows, a warning appears in the results. The ceiling is a physical-and-economic limit, not an environmental endorsement; many feasible sites carry serious ecological and displacement costs. For US states the ceiling is measured rather than approximated. It is each state's current hydro generation plus two ORNL assessments for the Department of Energy that cover disjoint resources and so add: new stream-reach development on rivers carrying no hydro today (Kao et al. 2014, DOE/EE-1063, Table ES.2), plus turbines added to existing dams that have no powerhouse (Hadjerioua et al. 2012, DOE/EE-0711, Table 4, capacity converted at the 42.6% capacity factor implied by that study's own 12.1 GW and 45 TWh national totals). Summed with existing generation this puts the United States at about 770 TWh a year, and the national figure is computed as the sum of the fifty states so that picking “United States” and picking every state cannot disagree. Three caveats a reviewer should have. This is the unrestricted stream-reach total of 460 TWh; excluding reaches close to national parks, wild and scenic rivers and wilderness areas cuts it to 347 TWh, which would put the US near 640. That exclusion is policy rather than physics and this ceiling is meant to be physical, so the larger figure is used, and the report's per-state exclusion-adjusted table is not machine-readable while its national haircut is far too uneven to apply as a flat percentage. Alaska carries no ORNL generation estimate, only 4,723 MW of capacity derived by a different method from the lower 48, converted here at 50% because Alaskan flow is snowmelt-driven, below ORNL's 53–71% range for the other states. And a 2024 reassessment cuts national non-powered-dam potential from 12.1 GW to 4.1 GW on tighter screening but publishes no state table, so that term is an upper bound. Note the definitional asymmetry this creates: countries carry Gernaat's economic potential while US states carry ORNL's technical potential, which is the looser of the two. The US ceiling is therefore more permissive than France's, which cuts against this tool's own framing rather than for it. Washington and Alaska are the states this most changes: both can now carry their whole grid on water, which is close to the truth and was not what the old placeholder said. One thing the tool does not model: hydro's seasonal and drought variability. Real hydro output swings with rainfall and snowmelt, and dry years (recent examples in Brazil, Zambia, and China) have forced grids back onto fossil backup. The tool treats hydro as steady annual generation, so it modestly overstates hydro's firmness in drought-prone regions.

The Study-consensus 2050 preset (the default) reflects the central range of US deep-decarbonization studies (Princeton Net-Zero America; NREL's 100% Clean Electricity by 2035; MIT/Sepulveda et al.): solar and wind carry most energy, firm resources — nuclear, geothermal, hydro, a little gas with capture — carry reliability. The all-nuclear, all-solar, and all-wind presets are bounding thought experiments, not proposals; they exist to show where the edges are.

The Jacobson 100% renewables-only preset: Mark Z. Jacobson at Stanford is the most prominent researcher arguing the world can run on wind, water and sunlight with no nuclear at all, so his roadmap sits in the mix list as he published it rather than as a strawman. The shares come from Table 7 of the 150-country study (Jacobson, Sambor, Fan, Mühlbauer & DiBari, 2025), which reports the share of all-sector end-use demand each generator meets across a LOADMATCH run that matches supply to demand every 30 seconds through 2050 to 2052. Onshore wind at 33.19% and offshore at 11.53% become the 45% wind here. Rooftop PV 15.16%, utility PV 33.63%, concentrated solar 0.035% and solar thermal heat 0.416% become 49% solar. Hydro 4.52% with wave and tidal folded in becomes 5%, and geothermal electricity plus geothermal heat becomes 1%. Nuclear, bioenergy, carbon capture and blue hydrogen are excluded, which he states openly in every paper and defends on grounds of cost, build time, weapons proliferation and meltdown risk. The preset shows nuclear at zero because that is his position, not because this tool decided it for him.

Where Jacobson and this tool disagree: Storage and overbuild, and the gap is enormous. Run his mix across the whole world grid under this tool's default curves and it asks for roughly 280 TWh of storage and 1.92× overbuild. His own simulation of essentially the same mix reports 40.4 TWh of electricity storage (32.3 TWh of batteries, 8.0 of pumped hydro, 0.12 of concentrated-solar phase-change) and 16.6% curtailment, which is 1.20× overbuild. Advanced carries a switch, “Storage & overbuild basis”, that swaps this tool's curves for his figures so the same mix can be read both ways. Three assumptions do most of the work. He treats 5,356 GW of his 8,962 GW of average demand as flexible, mostly hydrogen production, industrial process heat and building heating and cooling, so well over half the load can chase the weather instead of being chased by it. He builds about 770 TWh of heat and cold storage, underground thermal stores, hot water tanks and firebrick heat batteries, roughly twenty times his battery fleet, and this tool neither sizes nor prices any of it. He also counts existing hydro reservoirs, 1,588 TWh of them, as dispatchable storage discharging at up to 1,262 GW. This tool's curves come from studies that model a mostly inflexible grid buying reliability with batteries and overbuild, the conservative reading. Both positions are defensible. The useful summary is that his low storage number is a claim about demand flexibility as much as a claim about supply.

What Jacobson assumes about demand and land: His 2050 world uses 54.2% less end-use energy than business as usual. The breakdown is 37.0 points from the higher work-to-energy ratio of electricity over combustion, 10.6 from no longer mining, shipping and refining fuels (uranium included), and 6.6 from efficiency beyond the reference case. Electricity demand still rises 1.85×. Set this tool to rebuild the whole grid and electrify everything beyond it and it sizes about 82,400 TWh a year against his 78,500, roughly 5% apart. The two are not measuring the same year, since his figure follows population and economic growth out to 2050 while this tool electrifies today's energy, so read that as a sanity check rather than as agreement. Land is where the two genuinely part. He reports 0.18% of the 150 countries' land as footprint and 0.39% as spacing between turbines, which he treats as farmable and multi-use. That spacing works out at about 15 km² per TWh a year of new onshore wind. This tool's default is 99 km²/TWh, the roughly 3 W/m² array density in the wind-resource literature, with a toggle in the Land section for the pads-and-roads footprint instead. One convention is worth a factor of six on the headline land number, so the choice sits in front of you rather than buried in the model. His capacity factors are close to this tool's: onshore wind 38.1% against 35%, blended PV 20.5% against 20%. Geothermal is the outlier at 61% against 85%.

Lives saved, and why this figure is a floor: electricity mortality uses deaths per TWh of generation from Markandya & Wilkinson via Our World in Data (coal 24.6, oil 18.4, gas 2.8, biomass 4.6, hydro 1.3, nuclear 0.03, wind 0.04, solar 0.02), which covers accidents and air pollution across the full fuel chain. Fossil fuel burned outside the power sector is counted separately, at a blended 12 deaths per thermal TWh of fuel energy rather than per TWh of electricity, and only when "replace fuels beyond the grid" is switched on. Of that, the directly electrified share is credited in full and the synfuel share at half by default, because synthetic fuels burn without sulphur but with essentially unchanged NOx and particulate mass. That second term is where most of the harm sits: at full global replacement it supplies about 1.5 million of the roughly 1.8 million lives a year, because transport, heating, industry and cooking burn several times more fossil energy than power stations do.
Set that against the epidemiological literature. The WHO's often-quoted 7 million deaths a year covers all air pollution, indoor and outdoor, of which a large share is household biomass and coal cooking rather than anything a grid build touches. For fossil fuels specifically, Lelieveld et al. (2019) put it at 3.6 million a year and Vohra et al. (2021) at 8.7 million, a 2.4× spread between two peer-reviewed papers driven almost entirely by which concentration-response function they choose. This tool's implied total is below both: matching Lelieveld would need about 26 deaths per thermal TWh instead of 12, and matching Vohra about 67. We keep the low number on purpose. All of these are attributable deaths from relative-risk models rather than counted bodies, and a tool that reaches for the largest available estimate is easy to dismiss.

Future demand: by default this scales with the finish year on a curve anchored at ×1.45 by 2035 and ×2.00 by 2050, interpolated linearly. The 2035 anchor sits inside IEA WEO 2025's finding that peak electricity demand rises around 40% by 2035 under Stated Policies; the 2050 doubling is the range deep-electrification studies land in once transport, heat and industry move onto the grid. That curve is a default, not a claim: Advanced → Future demand basis switches it to flat at today's level, or to any growth figure you want, and the implied compound annual rate is shown next to it. Demand growth is applied to the whole grid before the mix is sized, so it scales land, materials, capital and build time together.

Transmission is priced, with caveats: corridors are sized at 3.5 GW a circuit over a default 200 km for remote wind, solar and hydro and 25 km for plants at existing grid nodes, at $2.67M/km with 0.061 km² of right-of-way per km, all adjustable in Advanced. Not modelled: distribution-network reinforcement, interconnection queues, or the politics of siting a corridor. An earlier version of this paragraph said no transmission was priced at all, which stopped being true when it was added.

What this model leaves out: Grid operating costs, financing costs, and fuel costs (beyond uranium tonnage) are also excluded; the investment figure is overnight capital only.

Geothermal in today's grid: Existing generation now separates geothermal from biomass. For countries this uses OWID's non-biofuel other-renewables series, which is over 98% geothermal worldwide (the remainder is wave and tidal); for US states it uses EIA's utility-scale geothermal. This matters because the two are nothing alike: geothermal is firm, low-carbon (19 g CO₂/kWh) and safe, while biomass carries roughly 230 g and far more land. It matters most for grids like Iceland, Kenya, New Zealand and the Philippines, where what looks like biomass in aggregated data is overwhelmingly geothermal.

US states: Generation by fuel from EIA-923 2024 final data (utility-scale plants; small-scale rooftop solar, about 75 TWh nationally, is not included). Populations from Census Bureau 2024 estimates. Non-electric fossil energy is apportioned from the national total by population share, an approximation, since energy-heavy industrial states burn more than their share. Note that the 51 state rows sum to about 4,314 TWh while the "United States" country row reads 4,772 TWh. The two come from different sources (EIA utility-scale versus the Energy Institute's national series), and the roughly 10% gap is mostly small-scale rooftop solar plus reporting-boundary differences. Pick one level or the other for a given comparison rather than mixing them.

Where the thumb could be — read this before arguing with the results: Defaults that favor nuclear: costs assume Nth-of-a-kind AP1000s ($4,700/kW), not the first-of-a-kind reality; build paces are all-time records; wind is counted at full project area while nuclear's exclusion zone is not counted; nuclear's site land is the measured mean of operating stations rather than a padded round number. Defaults that work against nuclear: the mortality rate includes Chernobyl and the Fukushima evacuation; reactors above 70% grid share pay a load-following capacity penalty; uranium is assumed 100% freshly mined, no recycling; and the storage curve treats the grid as mostly inflexible, which is the assumption Jacobson's roadmap disputes hardest, so his own storage and overbuild figures are selectable in Advanced and are documented above. Every one of these is one click away from its opposite in Advanced. That's the point.

Every constant lives in one labeled block at the top of this file's script, so numbers are easy to audit and update.