← on nowhow it’s built · v0.1.0 · 2026-08-16
how it’s built
Every number on the front door comes from this page. Each channel has an ID, a version, a method, a range, a confidence grade and a named weakness. If you can rebuild a number from what is written here, the page is doing its job. If you can’t, or you find it wrong, the dispute link on every entry pays.
the rules
- every number is a model until it is a feed, and wears a badge saying which.
- every channel has a stable id, a version, a method, a range, a confidence grade and a named weakness.
- the big numbers count from midnight utc, worldwide, so everyone sees the same thing at the same second. the footer counts since you opened the page.
- birth-year screens compare the year you were born with now. your year never leaves your device.
- the site makes three closing statements and no others: because we stopped. because we vaccinated. if we stopped. (and, in your own ledger only: because you stopped.)
- no ledger is written where there is none: the ocean’s births, the farm share of resistance, the animals in a burger.
- human deaths never enter the animal total. animals killed for disease do.
- anyone who finds an error is credited, in public, with their name on the changelog. no money changes hands.
badges and grades
model · a rate derived from published statistics or estimates and run against the clock.
feed · a number read from a live source; the source is named. today only the fire channel (NASA FIRMS, via the site’s own worker); when the feed is not answering the page shows a question mark, never a guess.
count · recorded by an authority (FAO slaughter, IWC catch, USFWS pairs).
estimate · a published estimate built from records plus assumptions (fishcount, GBD, IUCN).
model · derived from other estimates (extinction rate, reservoir evaporation, your share).
projection · about the future; the time slider only.
the arithmetic
Per second = per year ÷ 31,557,600 (365.25 days). The big numbers multiply that by seconds since midnight UTC. Standing stock uses Little’s law: animals alive in the queue = deaths per second × typical days alive × 86,400. Average time left is half the typical life. Birth dates subtract typical days alive from today. Lifetime totals integrate a per-year table between your birth year and now, trapezoid rule, one step per year. The lottery is weighted by (deaths per second)0.4 for animals, a fixed weight for flows, humans and stills, a cap so no single channel outweighs the rest, a rule that no channel or name returns within 40 slots (about sixteen minutes), a floor so no animal channel waits more than about 3 hours, and the whale channel scheduled once every 25 hours, so it comes an hour later each day; the seed is the UTC slot number (24 seconds), so every visitor sees the same channel at once.
index
animals, farmed
LGR-001 v0.1.0modelcount
chickens Gallus gallus domesticus
killed by humans: 74 billion a year, so 2 345 a second. born to be killed: 82 billion a year, 2 598 a second.
alive right now, in the queue (Little's law: rate × 42 days): 8.5 billion. average time left: 21 days.
- method
- FAO slaughter statistics for chickens (meat birds plus spent layers), converted to per second. births = slaughter + typical shed mortality (4–6%) + male layer chicks culled at hatch (~7 billion/yr). standing stock by Little's law: rate × 42 days.
- range
- slaughter 70–78 billion/yr; births 78–86 billion/yr
- weakness
- FAO under-reports backyard slaughter in parts of Asia and Africa; hatchery culling has no official global series.
- becomes a feed
- USDA daily federally inspected slaughter (US share, then others)
- lines shown, with sources
- the gap is the male chicks, macerated on day one, and the ones that die in the shed. a chicken can live eight years. FAO slaughter; hatchery culling estimatesnine of every ten farmed land vertebrates killed for food are chickens. FAOthe broiler chicken bone will be the signature fossil of our age: more of them than of any bird that ever lived, in every landfill on earth. Bennett et al. 2018, Royal Society Open Science
- dispute
- dispute LGR-001 · corrections are credited
LGR-002 v0.1.0modelestimate
farmed shrimp Litopenaeus vannamei & others
killed by humans: 440 billion a year, so 13 943 a second. born to be killed: 800 billion a year, 25 350 a second.
alive right now, in the queue (Little's law: rate × 150 days): 181 billion. average time left: 75 days.
- method
- fishcount.org.uk estimate of farmed decapods, converted to per second. hatchery numbers are several times larger because most postlarvae die before harvest.
- range
- 250–600 billion/yr harvested
- weakness
- tonnage-to-count conversion depends on assumed mean weight at harvest; the site uses the midpoint.
- lines shown, with sources
- most hatchery larvae never reach the pond. fishcount.org.uk
- dispute
- dispute LGR-002 · corrections are credited
LGR-003 v0.1.0modelestimate
farmed fish many species
killed by humans: 124 billion a year, so 3 929 a second. born to be killed: 160 billion a year, 5 070 a second.
alive right now, in the queue (Little's law: rate × 540 days): 183 billion. average time left: 270 days.
- method
- fishcount.org.uk estimate of farmed finfish killed per year, tonnage divided by species mean weights.
- range
- 78–171 billion/yr
- weakness
- mean weights per species are themselves estimates; hatchery-to-harvest survival varies widely.
- lines shown, with sources
- most die by suffocation, on ice. fishcount.org.uk
- dispute
- dispute LGR-003 · corrections are credited
LGR-004 v0.1.0modelcount
ducks Anas platyrhynchos domesticus
killed by humans: 3.3 billion a year, so 105 a second. born to be killed: 3.5 billion a year, 111 a second.
alive right now, in the queue (Little's law: rate × 49 days): 443 million. average time left: 24.5 days.
- method
- FAO slaughter statistics.
- range
- 3.0–3.5 billion/yr
- weakness
- most ducks are slaughtered in China; reporting granularity is coarse.
- lines shown, with sources
- a duck can live ten years. FAO
- dispute
- dispute LGR-004 · corrections are credited
LGR-005 v0.1.0modelcount
pigs Sus scrofa domesticus
killed by humans: 1.5 billion a year, so 47.5 a second. born to be killed: 1.8 billion a year, 55.5 a second.
alive right now, in the queue (Little's law: rate × 180 days): 739 million. average time left: 90 days.
- method
- FAO slaughter statistics; births = slaughter plus pre-weaning mortality (~12–15%).
- range
- 1.4–1.6 billion/yr
- weakness
- pre-weaning mortality is taken from industry data in a few countries and applied globally.
- becomes a feed
- USDA daily slaughter
- lines shown, with sources
- about one in eight dies before weaning. a pig can live fifteen years. FAO; industry mortality data
- dispute
- dispute LGR-005 · corrections are credited
LGR-006 v0.1.0modelcount
rabbits Oryctolagus cuniculus
killed by humans: 900 million a year, so 28.5 a second. born to be killed: 1 billion a year, 31.7 a second.
alive right now, in the queue (Little's law: rate × 77 days): 190 million. average time left: 38.5 days.
- method
- FAO slaughter statistics.
- range
- 0.8–1.0 billion/yr
- weakness
- reporting is thin outside China and Europe.
- lines shown, with sources
- a rabbit can live nine years. FAO
- dispute
- dispute LGR-006 · corrections are credited
LGR-007 v0.1.0modelcount
geese Anser anser domesticus
killed by humans: 700 million a year, so 22.2 a second. born to be killed: 750 million a year, 23.8 a second.
alive right now, in the queue (Little's law: rate × 120 days): 230 million. average time left: 60 days.
- method
- FAO slaughter statistics.
- range
- 0.65–0.75 billion/yr
- weakness
- as ducks.
- lines shown, with sources
- a goose can live twenty years. FAO
- dispute
- dispute LGR-007 · corrections are credited
LGR-008 v0.1.0modelcount
turkeys Meleagris gallopavo
killed by humans: 650 million a year, so 20.6 a second. born to be killed: 700 million a year, 22.2 a second.
alive right now, in the queue (Little's law: rate × 120 days): 214 million. average time left: 60 days.
- method
- FAO slaughter statistics.
- range
- 0.6–0.7 billion/yr
- weakness
- none material.
- lines shown, with sources
- a turkey can live ten years. FAO
- dispute
- dispute LGR-008 · corrections are credited
LGR-009 v0.1.0modelcount
sheep Ovis aries
killed by humans: 620 million a year, so 19.6 a second. born to be killed: 700 million a year, 22.2 a second.
alive right now, in the queue (Little's law: rate × 210 days): 356 million. average time left: 105 days.
- method
- FAO slaughter statistics.
- range
- 0.58–0.65 billion/yr
- weakness
- informal slaughter under-reported.
- lines shown, with sources
- a sheep can live twelve years. FAO
- dispute
- dispute LGR-009 · corrections are credited
LGR-010 v0.1.0modelcount
goats Capra hircus
killed by humans: 500 million a year, so 15.8 a second. born to be killed: 560 million a year, 17.7 a second.
alive right now, in the queue (Little's law: rate × 120 days): 164 million. average time left: 60 days.
- method
- FAO slaughter statistics.
- range
- 0.45–0.55 billion/yr
- weakness
- informal slaughter under-reported.
- lines shown, with sources
- a goat can live fifteen years. FAO
- dispute
- dispute LGR-010 · corrections are credited
LGR-011 v0.1.0modelcount
cattle Bos taurus
killed by humans: 330 million a year, so 10.5 a second. born to be killed: 360 million a year, 11.4 a second.
alive right now, in the queue (Little's law: rate × 550 days): 497 million. average time left: 275 days.
- method
- FAO slaughter statistics; births = slaughter plus bobby calves and calf mortality. standing stock via Little's law counts the slaughter queue, not the breeding and dairy herd (~1.5 billion).
- range
- 0.30–0.35 billion/yr
- weakness
- the 'alive right now' figure excludes dairy and breeding animals by design and should be read as the queue.
- becomes a feed
- USDA daily slaughter
- lines shown, with sources
- the gap is mostly bobby calves: dairy farms’ male calves, killed young because they cannot make milk. see: bobby calves. a cow can live twenty years. FAO; dairy industry datain much of the tropics the pasture under the ones dying now was forest within their grandparents’ lifetime. Global Forest Watch; Pendrill et al. 2019
- dispute
- dispute LGR-011 · corrections are credited
LGR-012 v0.1.0modelcount
buffalo Bubalus bubalis
killed by humans: 30 million a year, so 0.951 a second. born to be killed: 33 million a year, 1.0 a second.
alive right now, in the queue (Little's law: rate × 730 days): 60 million. average time left: 365 days.
- method
- FAO slaughter statistics.
- range
- 25–35 million/yr
- weakness
- none material.
- lines shown, with sources
- a buffalo can live twenty-five years. FAO
- dispute
- dispute LGR-012 · corrections are credited
LGR-023 v0.1.0modelmodel
silkworms Bombyx mori · estimated
boiled alive in their cocoons: 1 trillion a year, so 31 688 a second. hatched for it: 1 trillion a year, 31 688 a second.
alive right now, in the queue (Little's law: rate × 40 days): 110 billion. average time left: 20 days.
- method
- Rethink Priorities 2023: silk tonnage × cocoons per kg. births ≈ deaths (nearly all reared are killed).
- range
- 420 billion–1 trillion/yr
- weakness
- cocoons-per-kg varies by strain; the site uses the top of the range. insects are counted on this ledger; some will object.
- lines shown, with sources
- about 6,600 cocoons for a kilogram of silk. the moth was domesticated five thousand years ago and can no longer fly. Rethink Priorities 2023; FAO / ISC silk statisticsif the ledger counts insects, and it does, this is among the largest channels on it. methodology note
- dispute
- dispute LGR-023 · corrections are credited
LGR-024 v0.1.0modelmodel
farmed insects crickets, mealworms, soldier fly larvae · estimated
killed: 1.2 trillion a year, so 38 026 a second. projected, a year, by 2030: ~5 trillion.
mostly for pet food, fish feed and chicken feed. not, mostly, for people.
- method
- Rethink Priorities 2023; Rowe 2020: farmed insects killed per year for food and feed, and 2030 projections.
- range
- 1–1.2 trillion/yr now; 4–5 trillion by 2030
- weakness
- industry data are sparse and growing fast; the projection is the industry's own.
- lines shown, with sources
- the newest ledger. it is growing faster than any other channel here. Rethink Priorities 2023; Rowe 2020
- dispute
- dispute LGR-024 · corrections are credited
animals, wild
LGR-013 v0.1.0modelestimate
wild-caught fish many species
killed by humans: 2 trillion a year, so 63 376 a second. born: no ledger.
no ledger. nobody counts the ocean’s births, only the taking.
- method
- fishcount.org.uk estimate: FAO capture tonnage divided by species mean weights.
- range
- 1.1–2.2 trillion/yr
- weakness
- the widest range on the site. excludes illegal, unreported and unregulated catch, which is substantial. the site uses ~2.0 trillion; the low end halves the number.
- becomes a feed
- Global Fishing Watch: every industrial vessel fishing right now, by name and flag
- lines shown, with sources
- about a tenth of what is caught is thrown back dead. FAO discards estimatesa third of assessed stocks are fished past what they can replace. FAO SOFIAabout 100,000 fishers die at sea every year. it is the deadliest job on earth, and some of the crews are not there by choice. FISH Safety Foundation 2022; ILO; EJFthe largest fishery on earth is one small fish, the peruvian anchoveta, and almost none of it is eaten by people. it is ground into meal for salmon, pigs and chickens. FAO; IFFO
- dispute
- dispute LGR-013 · corrections are credited
LGR-014 v0.1.0modelestimate
sharks Selachii
killed by humans: 100 million a year, so 3.2 a second. born: no ledger.
no ledger. nobody counts the ocean’s births, only the taking.
- method
- Worm et al. 2013 estimate of sharks killed per year across fisheries.
- range
- 63–273 million/yr
- weakness
- a decade old; more recent work (Worm et al. 2024) suggests mortality has not fallen despite regulation.
- lines shown, with sources
- many are killed for their fins alone. some species live longer than we do. Worm et al. 2013
- dispute
- dispute LGR-014 · corrections are credited
animals, taken not bred
LGR-015 v0.1.0modelestimate
dogs Canis familiaris
killed by humans: 30 million a year, so 0.951 a second. born: no ledger.
not bred for this. bought, worked, or taken.
- method
- Humane Society International estimates of dogs killed for meat, mostly in Asia.
- range
- 10–30 million/yr
- weakness
- no official statistics anywhere. treat as order of magnitude.
- lines shown, with sources
- estimates vary widely. most were young. HSI estimates
- dispute
- dispute LGR-015 · corrections are credited
LGR-016 v0.1.0modelcount
horses Equus caballus
killed by humans: 5 million a year, so 0.158 a second. born: no ledger.
not bred for this. bought, worked, or taken.
- method
- FAO slaughter statistics.
- range
- 4–6 million/yr
- weakness
- none material.
- lines shown, with sources
- often after a working life. a horse can live thirty years. FAOthe united states stopped slaughtering horses in 2007 and started shipping them: tens of thousands a year to mexico and canada. USDA export data; ASPCAracing: about one horse dies for every thousand starts. Jockey Club Equine Injury Database
- dispute
- dispute LGR-016 · corrections are credited
LGR-017 v0.1.0modelcount
camels Camelus dromedarius
killed by humans: 3 million a year, so 0.095 a second. born: no ledger.
not bred for this. bought, worked, or taken.
- method
- FAO slaughter statistics.
- range
- 2.5–3.5 million/yr
- weakness
- none material.
- lines shown, with sources
- a camel can live forty years. FAO
- dispute
- dispute LGR-017 · corrections are credited
LGR-018 v0.1.0modelestimate
cats and dogs in shelters · united states only, until the country layer
killed because nobody came: 920 000 a year, so 0.029 a second. taken in: 6.3 million a year, 0.200 a second.
the rest found someone. the world number is not counted anywhere.
- method
- ASPCA / Shelter Animals Count: dogs and cats killed in US shelters per year, and intake.
- range
- killed 0.7–1.0 million/yr; intake 5.5–6.5 million/yr
- weakness
- united states only; the site says so in the label. no global series exists.
- lines shown, with sources
- it was thirteen to twenty million a year in the 1970s. spay and neuter did most of it. HSUS; ASPCA; Shelter Animals Countmost are healthy. they die of a lack of room, and of someone. ASPCA
- dispute
- dispute LGR-018 · corrections are credited
LGR-020 v0.1.0modelestimate
pangolins the most trafficked wild mammal on earth
killed for scales and meat · estimated: 200 000 a year, so 6.34e-3 a second. what the scales are made of: fingernail.
keratin. the same protein as your nails and hair. no medicine has ever been shown to be in it.
- method
- Wildlife Justice Commission and TRAFFIC seizure analyses scaled to trade; Challender et al. 2020.
- range
- 100,000–400,000/yr; ~1 million 2000–2013
- weakness
- seizure-based; the true trade is larger by an unknown factor.
- lines shown, with sources
- china removed pangolin scales from its official pharmacopoeia in 2020. the trade continues. Wildlife Justice Commission 2020; Challender et al. 2020; TRAFFICabout a million were taken between 2000 and 2013. all eight species are now threatened. IUCN Pangolin Specialist Group
- dispute
- dispute LGR-020 · corrections are credited
LGR-021 v0.1.0modelestimate
songbirds killed illegally around the mediterranean
shot, netted, glued and trapped: 25 million a year, so 0.792 a second. of them, songbirds: no ledger.
most. blackcaps on lime sticks in cyprus, robins in italy, ortolans in the landes: kept in the dark, fattened, drowned in armagnac and eaten whole under a napkin. mitterrand’s last meal.
- method
- BirdLife International 2015 (Brochet et al.): illegal killing around the Mediterranean.
- range
- 11–36 million/yr
- weakness
- illegal by definition, so estimated from surveys and enforcement data; excludes legal hunting, which is larger.
- lines shown, with sources
- egypt about 5.7 million a year, italy 5.6, syria 3.9, lebanon 2.6, cyprus 2.3. the range is eleven to thirty-six million. BirdLife International 2015, Brochet et al.ortolans have been protected in france since 1999. about 30,000 a year are still taken. the european population fell 84% between 1980 and 2012. LPO; European Bird Census Councilcyprus cut its trapping by four fifths in three years once it started fining people. it is creeping back. BirdLife Cyprus
- dispute
- dispute LGR-021 · corrections are credited
LGR-022 v0.1.0modelestimate
donkeys Equus asinus · skinned for gelatin, eaten, worked
killed for their hides and meat: 5.9 million a year, so 0.187 a second. left in the world: 53 million.
at this rate, half of them in five years. the hides go to china for ejiao, a gelatin sold as a tonic. the meat is mostly the same animals. the families in africa who used them lose their transport.
- method
- The Donkey Sanctuary 2019/2022 estimates of hides entering the ejiao trade; world population from FAO.
- range
- 4.8–5.9 million/yr; population 44–53 million
- weakness
- trade is partly informal; the 'half in five years' line is a straight-line projection, stated as such.
- lines shown, with sources
- official statistics count about three to four million donkeys slaughtered for meat a year. the hide estimate is larger because much of the trade is informal, and most of the animals are both. there is no ledger for the ones worked to death. FAOSTAT; The Donkey Sanctuary 2019, 2022brazil, kenya and botswana banned the export. the trade moved. The Donkey Sanctuary 2019, 2022ejiao is boiled donkey skin. it is prescribed for anaemia and sold in cakes. Donkey Sanctuary; Ejiao trade reports
- dispute
- dispute LGR-022 · corrections are credited
LGR-025 v0.1.0modelcount (bled); estimate (deaths)
horseshoe crabs Limulus polyphemus · united states
bled for their blue blood: 650 000 a year, so 0.021 a second. died of it: 100 000 a year, 3.17e-3 a second.
the rest are put back in the sea, paler. the blood is blue because it carries copper, not iron.
- method
- ASMFC 2023 biomedical bleeding counts; mortality from Krisfalusi-Gannon et al. 2018.
- range
- bled 600,000–1,000,000/yr; mortality 10–30%
- weakness
- post-release mortality is estimated, not observed.
- lines shown, with sources
- every vaccine and every injectable drug on earth is tested for contamination with an extract of their blood, or, since 2020, with a synthetic copy that most companies still do not use. ASMFC 2023; Krisfalusi-Gannon et al. 2018; European Pharmacopoeia 2020they are 450 million years old. older than trees. methodology note
- dispute
- dispute LGR-025 · corrections are credited
LGR-026 v0.1.0modelestimate
seahorses Hippocampus
dried, for medicine and curios: 37 million a year, so 1.2 a second. left in the wild: no ledger.
no ledger. most are bycatch of shrimp trawls, sold on instead of thrown back.
- method
- Lawson et al. 2017 (Project Seahorse) trade estimate.
- range
- 20–37 million/yr
- weakness
- trade is largely undocumented; the figure is a decade old.
- lines shown, with sources
- the male carries the young. Project Seahorse; Lawson et al. 2017
- dispute
- dispute LGR-026 · corrections are credited
LGR-027 v0.1.0modelestimate
frogs for their legs · estimated
killed: 100 million a year, so 3.2 a second. left where they were taken: no ledger.
no ledger. most come wild from indonesia. when they go, the insects they ate stay, and pesticide use rises.
- method
- Auliya et al. 2016: EU import tonnage converted to individuals.
- range
- 80–200 million/yr (EU imports only)
- weakness
- conversion from tonnes to individuals depends on species mix; excludes domestic consumption in asia.
- lines shown, with sources
- europe imports about four thousand tonnes of frogs’ legs a year, france and belgium first. Auliya et al. 2016; EU trade data
- dispute
- dispute LGR-027 · corrections are credited
animals, the exception
LGR-028 v0.1.0modelcount (deaths); estimate (births)because we stopped.
whales Cetacea
killed by humans: 1 300 a year, so 4.12e-5 a second. born, free: 100 000 a year, 3.17e-3 a second.
the only ticking channel where the numbers diverge.
- method
- IWC catch records: commercial (Norway, Iceland, Japan) plus aboriginal subsistence takes. births from population size × birth rate.
- range
- deaths 1,000–1,600/yr; births 60,000–150,000/yr
- weakness
- birth number depends on population estimates that carry ±30% error.
- lines shown, with sources
- about three a day. many were older than you. IWC catch records
- dispute
- dispute LGR-028 · corrections are credited
animals, killed for disease
LGR-029 v0.1.0modelestimate
chickens, ducks, turkeys culled for bird flu · estimated
killed by humans: 120 million a year, so 3.8 a second. found infected: no ledger.
a fraction. if one bird tests positive the whole shed is killed. gassed, foamed, or the ventilation shut off. not eaten. buried or composted.
- method
- WOAH and national reports of birds culled in HPAI outbreaks, annualised over 2021–2025.
- range
- 50–200 million/yr, highly variable by year
- weakness
- outbreak years differ tenfold; the annual figure is an average, not a rate.
- lines shown, with sources
- over half a billion birds since 2021. the disease is a product of the sheds it is meant to protect: forty thousand near-identical birds in one room is how a virus learns. WOAH; USDA APHIS; Nature 2023in 2024 the same virus walked into american dairy herds, and then into people who milk them. CDC; USDA 2024-25these are on the animal ledger. they were killed by humans. nobody counts them as slaughter. methodology note
- dispute
- dispute LGR-029 · corrections are credited
LGR-030 v0.1.0modelcount
badgers Meles meles · england
killed to protect cattle from tuberculosis: 20 000 a year, so 6.34e-4 a second. cattle killed for tuberculosis, england: 25 000 a year, 7.92e-4 a second.
the same disease, both sides of the fence.
- method
- DEFRA cull returns for England, annualised; cattle figures are DEFRA bovine TB slaughter statistics for England.
- range
- badgers 10,000–35,000/yr; cattle 20,000–30,000/yr
- weakness
- the cull is being wound down; the rate will fall. whether it reduces bovine TB is scientifically contested and the site says so.
- lines shown, with sources
- about 230,000 badgers shot since 2013. whether it lowers tb in cattle is contested. the ledger is not. DEFRA; Godfray review 2018; Langton et al. 2022tuberculosis crosses from cattle to people in unpasteurised milk: about 140,000 human cases and 11,000 deaths a year, mostly where milk is not treated. WHO / OIE / FAO 2017
- dispute
- dispute LGR-030 · corrections are credited
animals, killed for sport
LGR-019 v0.1.0modelestimate
trophies animals killed for a trophy, traded across borders
trophies taken, all species: 170 000 a year, so 5.39e-3 a second. of them, threatened species: 20 000 a year, 6.34e-4 a second.
lions, elephants, leopards, rhinos, bears. most go to the united states.
- method
- IFAW 2016 analysis of CITES trade data: hunting trophies traded internationally 2004–2014, annualised; threatened-species share from the same.
- range
- 150,000–200,000/yr; threatened 15,000–25,000/yr
- weakness
- trade records undercount trophies kept in-country; the lion-farm figures are NGO estimates the south african government has broadly confirmed.
- lines shown, with sources
- about 8,000 lions live on south african breeding farms, more than twice the country’s wild lions. petted as cubs, walked with as juveniles, shot in enclosures, sold as skeletons. the government voted to end it in 2021. it has not ended. Born Free; Four Paws; EMS Foundation; DFFE 20211.7 million trophies crossed borders in a decade. about one in eight was from a threatened species. IFAW 2016; CITES trade database
- dispute
- dispute LGR-019 · corrections are credited
flows
LGR-031 v0.1.0modelcount
fertilizer nitrogen, phosphate, potash
spread, in kilograms: 190 billion a year, so 6 021 a second. lost to air and water, in kilograms: 95 billion a year, 3 010 a second.
about half never reaches a plant.
- method
- FAO fertilizer statistics: total N + P2O5 + K2O nutrient use. losses = 1 − nitrogen use efficiency (~50%).
- range
- 185–200 million tonnes/yr
- weakness
- 'lost to air and water' applies a nitrogen efficiency figure to total nutrients, which overstates phosphate and potash losses; the order of magnitude holds.
- lines shown, with sources
- a third of the world’s cropland grows food for animals, not people. FAO; Mottet et al. 2017the runoff makes dead zones. the one in the gulf of mexico covers thousands of square kilometres each summer. NOAAabout six tonnes a second, every second. FAO fertilizer statistics
- dispute
- dispute LGR-031 · corrections are credited
LGR-032 v0.1.0modelcount (tonnage); estimate (poisonings)
pesticides herbicides, insecticides, fungicides
applied, in kilograms: 3.7 billion a year, so 117 a second. people poisoned, survived: 385 million a year, 12.2 a second.
mostly farmworkers. mostly unreported.
- method
- FAO pesticide use statistics (active ingredient). poisonings from Boedeker et al. 2020.
- range
- 3.5–4.2 million tonnes/yr; poisonings 385 million/yr with wide CI
- weakness
- tonnage is not toxicity, and the site says so on screen. poisoning figure is a systematic review estimate.
- lines shown, with sources
- about 120 kilograms every second. FAO pesticide use statistics385 million people a year are poisoned by pesticides and live. about 11,000 don’t. Boedeker et al. 2020, BMC Public Healthparaquat is associated with parkinson’s disease. it is banned in the EU and manufactured there for export. Tanner et al. 2011; Unearthed 2020glyphosate is the most used pesticide on earth. the WHO’s cancer agency calls it probably carcinogenic. most regulators disagree. IARC 2015; EFSA; EPAa kilogram is not a kilogram. tonnage says nothing about toxicity. methodology note
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LGR-033 v0.1.0modelmodel
reservoirs evaporation from dammed water
evaporated, in cubic metres: 346 billion a year, so 10 964 a second. returned: no ledger.
no ledger. it goes to the sky, and comes down somewhere else, or not.
- method
- Tian et al. 2022 global reservoir evaporation estimate.
- range
- 250–400 km³/yr
- weakness
- depends on reservoir surface area and climate data; the livestock water share is from a different study (Mekonnen & Hoekstra).
- lines shown, with sources
- about eleven thousand cubic metres a second. roughly a third of agriculture’s water goes to animals. Tian et al. 2022; Mekonnen & Hoekstra 2012dammed water evaporates faster than the river it replaced. the loss is designed in. methodology note
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LGR-034 v0.1.0modelmodel
groundwater pumped faster than rain refills it
depleted, in cubic metres: 283 billion a year, so 8 968 a second. refilled: no ledger.
no ledger. some aquifers took ten thousand years to fill.
- method
- Wada et al. 2010 global groundwater depletion; corroborated by GRACE satellite gravimetry.
- range
- 200–300 km³/yr
- weakness
- regional depletion is well measured; global sums are less certain.
- lines shown, with sources
- about nine thousand cubic metres a second, mostly for irrigation: the north china plain, northwest india, the ogallala. Wada et al. 2010; GRACEseventy percent of all freshwater humans take goes to farming. FAO AQUASTAT
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LGR-035 v0.1.0modelcount
forest cleared, and coming back
cleared, in hectares: 10 million a year, so 0.317 a second. regrown, in hectares: 5.3 million a year, 0.168 a second.
about half. much of it is plantation. some of it is forest.
- method
- FAO Forest Resources Assessment 2020: gross deforestation and gross expansion, 2015–2020.
- range
- loss 9–11 Mha/yr; gain 5–6 Mha/yr
- weakness
- FAO relies on national reporting; satellite products (GFW) show higher loss. 'regrown' includes plantations.
- becomes a feed
- GLAD deforestation alerts, weekly
- lines shown, with sources
- net loss has fallen from about 7.8 million hectares a year in the 1990s to about 4.7 million now. slower. not stopped. FAO Forest Resources Assessment 2020the largest single cause of clearing is cattle. then soy, palm oil, and wood. Pendrill et al. 2019; Curtis et al. 2018, Scienceabandoned farmland grows back on its own. nobody plants new england. it came back when the farms left. Foster & Aber 2004; forest transition literature
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LGR-036 v0.1.0modelcount
foie gras ducks and geese, force-fed · already counted under ducks
force-fed: 40 million a year, so 1.3 a second. countries where it is illegal to make: over 20.
and legal in france, which makes three quarters of it. the eu bans it in principle and exempts it in practice.
- method
- CIFOG / EU production statistics: ducks and geese force-fed per year.
- range
- 35–45 million/yr
- weakness
- a subset of the ducks channel; explicitly not added to the total.
- lines shown, with sources
- a tube down the throat two or three times a day for about two weeks. the liver swells to ten times its size. the medical name is hepatic steatosis. EFSA 1998; CIFOGnot added to the total on this page: these ducks are already there. methodology note
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LGR-037 v0.1.0modelmodel
what cats kill birds and small mammals · united states only
killed by cats we keep or abandoned: 16 billion a year, so 507 a second. worldwide: no ledger.
no ledger. australia counts about a billion and a half a year. most countries do not count.
- method
- Loss, Will & Marra 2013 (US); Murphy et al. 2019 (australia). midpoint of a wide range.
- range
- US: 1.3–4 billion birds and 6.3–22 billion mammals/yr
- weakness
- the widest range on the animal side of the site; explicitly not counted in the killed-by-humans total.
- lines shown, with sources
- not killed by humans, so not in the total on this page. killed by animals we breed, keep and let go. the range is wide: one to four billion birds, six to twenty-two billion mammals, a year, in one country. Loss, Will & Marra 2013, Nature Communications; Murphy et al. 2019 (australia)unowned cats do most of it. the ones we abandoned. Loss et al. 2013
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LGR-038 v0.1.0modelcount (emissions); count (capture)
carbon carbon dioxide, tonnes
emitted: 41 billion a year, so 1 299 a second. captured by machines: 10 000 a year, 3.17e-4 a second.
direct air capture, all plants on earth. the ocean and the land take about half of the left column for free. the rest stays for centuries.
- method
- Global Carbon Budget 2024: fossil + land-use CO2. capture: IEA tracker of operating direct air capture.
- range
- emissions 39–42 Gt CO2/yr; DAC 0.005–0.05 Mt/yr
- weakness
- 'captured by machines' excludes CCS at point sources (~45 Mt/yr), which is a different thing; the site compares air to air.
- lines shown, with sources
- about a quarter to a third of the left column is the food system: the animals, the feed, the cleared land, the fertilizer. Global Carbon Project 2024; Crippa et al. 2021the largest carbon capture plant on earth removes in a year what the world emits in about ten seconds. Climeworks Mammoth; IEA DAC trackerevery second on this page: about as much co2 as thirty cars driving for a year. Global Carbon Project; EPA
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LGR-039 v0.1.0modelmodel
soil topsoil, tonnes
eroded from farmland: 24 billion a year, so 761 a second. formed: 1 billion a year, 31.7 a second.
about a twenty-fifth. soil forms at roughly a centimetre a century. ploughed land loses it at roughly a millimetre a year.
- method
- UNCCD/FAO figure of ~24 Gt/yr; Borrelli et al. 2017 (36 Gt water erosion). formation from Montgomery 2007 rates × cropland area.
- range
- eroded 20–36 Gt/yr; formed 0.5–2 Gt/yr
- weakness
- both sides are modeled; the ratio (about 25×) is more robust than either number.
- lines shown, with sources
- a third of the world’s soil is degraded. most of the loss is from tilled cropland, and most of the cropland grows feed and grain. FAO 2015 Status of the World’s Soil Resources; Borrelli et al. 2017the dust bowl was this, in one decade, in one place. it is happening everywhere, slowly. Montgomery 2007, Dirt
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LGR-040 v0.1.0modelestimate
mines tailings and mercury
mine waste, tonnes: 14 billion a year, so 444 a second. mercury into rivers, kilograms: 840 000 a year, 0.027 a second.
the largest source of mercury pollution on earth is not industry. it is fifteen to twenty million people panning gold with quicksilver.
- method
- tailings from global mine production and ore grades (Adiansyah et al. 2015; Global Tailings Review); mercury from UNEP Global Mercury Assessment 2018 (ASGM share).
- range
- tailings 10–14 Gt/yr; ASGM mercury 700–1,000 t/yr
- weakness
- tailings tonnage is derived, not reported; ASGM mercury is by nature informal.
- lines shown, with sources
- tailings are held behind about 30,000 dams. brumadinho, 2019: 270 dead in minutes. nobody counts all the dams. ICOLD; Global Tailings Review 2020a phone holds about sixty elements. each one came out of a hole. USGSthis page is served from machines built from those holes. methodology note
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LGR-041 v0.1.0modelestimate
data centres this page is running in one
electricity used, kilowatt-hours: 415 billion a year, so 13 151 a second. water evaporated to cool them: no ledger.
no ledger. most companies do not report it. one us estimate: seventeen billion gallons a year, in one country, direct use only.
- method
- IEA 2025 Energy and AI: 415 TWh in 2024, ~945 TWh projected 2030; water from LBNL 2024 US report.
- range
- 400–450 TWh/yr; water: US only, direct only
- weakness
- changing fast; the number should be a feed within a year. the site's own footprint is not measured, only acknowledged.
- lines shown, with sources
- about one and a half percent of the world’s electricity now, and the fastest-growing use of it. the projection is more than double by 2030, mostly for ai. IEA 2025 Energy and AI; LBNL 2024the ledger’s own share is small and not zero. it is not exempt from itself. methodology note
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LGR-042 v0.1.0modelestimate
concrete the most used substance on earth after water
poured, tonnes: 30 billion a year, so 951 a second. co2 from making the cement, tonnes: 2.5 billion a year, 79.2 a second.
about eight percent of the world’s emissions. if cement were a country it would be third.
- method
- USGS cement production (~4.1 Gt) scaled to concrete (~30 Gt); cement CO2 from GCP/Andrew.
- range
- concrete 25–33 Gt/yr; CO2 2.3–2.7 Gt/yr
- weakness
- concrete tonnage is inferred from cement; the 'weight of every living thing' comparison is Elhacham 2020 (biomass ~4 Gt wet).
- lines shown, with sources
- humans now pour more concrete each year than the weight of every living thing on earth. Elhacham et al. 2020, Nature; USGSsand is running out. the sand in deserts is the wrong shape. it is dredged from rivers and beaches, and the beaches go. UNEP 2019 Sand and Sustainability
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LGR-043 v0.1.0modelcount
shipping about 100,000 ships
fuel burned, tonnes: 300 million a year, so 9.5 a second. co2 from it, tonnes: 1 billion a year, 31.7 a second.
about three percent of the world’s. ninety percent of everything you own came by sea.
- method
- IMO Fourth GHG Study 2020: fuel and CO2; sulphur-cap warming from Yuan et al. 2024.
- range
- fuel 280–330 Mt/yr; CO2 0.9–1.1 Gt/yr
- weakness
- the warming effect of the sulphur cap is a modeled attribution, in the tens of hundredths of a degree over decades; stated as measurable, not large.
- lines shown, with sources
- in 2020 ships were made to cut the sulphur in their fuel by four fifths. the air over the sea got cleaner. the haze had been shading the ocean, and without it the ocean measurably warmed. cleaning one thing uncovered another. IMO 2020; Yuan et al. 2024, Communications Earth & Environmentmost of the tonnage is oil, coal, iron ore and grain. a good share of the grain is feed. UNCTAD Review of Maritime Transport
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LGR-044 v0.1.0modelestimate
cruise ships about 300 of them
sewage discharged, litres: 3.8 billion a year, so 120 a second. passengers at sea right now: ~600 000.
about thirty million a year, a week each. a large ship burns about the fuel of a small town.
- method
- EPA 2008 discharge assessment scaled to today's fleet; passenger numbers from CLIA; T&E 2019 for sulphur.
- range
- sewage 3–5 billion litres/yr; at-sea passengers 500,000–700,000
- weakness
- discharge is estimated from per-passenger figures, not measured at sea.
- lines shown, with sources
- one company’s fleet emitted ten times the sulphur oxides of all of europe’s cars in one year. Transport & Environment 2019the sewage is legal beyond twelve miles. most of it is treated. some of it is not. nobody is out there checking. US EPA 2008 cruise ship discharge assessment; Friends of the Earth
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LGR-045 v0.1.0modelestimate
manure from farmed animals, tonnes
produced: 3.5 billion a year, so 111 a second. human sewage, for scale: 500 million a year, 15.8 a second.
in the united states, livestock produce more than a hundred times the waste of people, and almost none of it is treated.
- method
- FAO livestock excretion estimates; US EPA for the livestock:human ratio; human sewage as an order-of-magnitude comparator.
- range
- 3–4 Gt/yr (fresh weight)
- weakness
- wet vs dry weight is a factor of several; the site uses fresh weight for both sides.
- lines shown, with sources
- it is where the ammonia comes from, and the ammonia is where much of the farm air pollution comes from, and the air pollution is on this ledger under humans. US EPA; Domingo et al. 2021spread on fields it is fertilizer. in lagoons it is a lake. when the lagoon breaks, the river dies. NC hurricane floyd 1999; EPA CAFO reports
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LGR-046 v0.1.0modelcount
solar kilowatt-hours
from the sun: 2 trillion a year, so 63 376 a second. from coal: 10.4 trillion a year, 329 556 a second.
coal is still the largest source of electricity on earth. solar is the fastest-growing source of energy in history.
- method
- Ember 2025: solar generation ~2,000 TWh (2024); coal ~10,400 TWh. panels/second from ~600 GW installed per year at ~400 W each.
- range
- solar 1,900–2,200 TWh; coal 10,000–10,700 TWh
- weakness
- annual figures; both are moving fast in opposite directions, so this channel dates quickly and should be a feed.
- lines shown, with sources
- about 47 solar panels are installed somewhere on earth every second. solar was about seven percent of the world’s electricity in 2024, up from one percent in 2015. Ember Global Electricity Review 2025; IEAa panel repays the energy that made it in one to two years and runs for twenty-five to thirty. it is not free. it wins anyway. Fraunhofer ISE PV Report 2024; IPCC AR5 Annex IIImost panels are made in china on a coal grid. that is where their carbon comes from, and it is falling as the grid does. IEA Special Report on Solar PV Supply Chains 2022
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LGR-047 v0.1.0modelcount
satellites the sky, being fenced
launched: 3 000 a year, so 9.51e-5 a second. working, in orbit right now: ~13 00.
most belong to one company. around them: 40,000 tracked pieces of debris, and over a million too small to track.
- method
- launch rate from recent years (Jonathan McDowell); active count from CelesTrak/UCS.
- range
- 2,500–3,500 launched/yr; 12,000–14,000 active
- weakness
- changes monthly; this is the channel most in need of a feed.
- becomes a feed
- Space-Track / CelesTrak, live catalogue
- lines shown, with sources
- this is the best-kept ledger on the site. every satellite is registered and tracked to the metre. we count the sky better than we count the sea. UN Registration Convention; Space-Track; CelesTrakalmost every number here comes from up there: the fires, the forest, the groundwater, the sea. the thing being counted is also the counter. NASA FIRMS; GRACE; Landsat; Copernicuswhen they fall, they burn, and leave aluminium oxide in the stratosphere. early evidence says it eats ozone. Ferreira et al. 2024, GRL; Murphy et al. 2023, PNASthe sky is getting brighter by about ten percent a year. a child born where 250 stars are visible will see about 100 by the time they are 18. Kyba et al. 2023, Science
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LGR-048 v0.1.0modelmodel
extinctions species gone for good
gone forever · modeled: 500 a year, so 1.58e-5 a second. recorded, since 1500: ~900.
no ledger. most species were never named, so most extinctions are never recorded. the two columns disagree by a factor of hundreds; that is the finding.
- method
- modeled rate set mid-literature (~500 species/yr); documented count from the IUCN Red List (EX + EW).
- range
- 100–30,000/yr depending on method; documented ~900 since 1500
- weakness
- the largest disagreement on the site, by design shown as two columns. the ticking number is a stand-in for a range that spans two orders of magnitude.
- lines shown, with sources
- the modeled rate runs from about a hundred a year to tens of thousands, depending on the method. this counter sits in the middle. the range is the honest number. Pimm et al. 2014; Ceballos et al. 2015; IUCN Red Liston land the leading cause is farming. at sea it is fishing. of threatened land vertebrates, most are threatened by agriculture. IPBES 2019; Tilman et al. 2017a million species are threatened with extinction, many within decades. IPBES 2019
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humans
LGR-049 v0.1.0modelestimate
humans Homo sapiens
died from pesticide poisoning: 11 000 a year, so 3.49e-4 a second. poisoned, survived: 385 million a year, 12.2 a second.
unintentional. the self-poisoning figure is larger and lives in the methodology, handled with care.
- method
- Boedeker et al. 2020: unintentional acute poisoning deaths.
- range
- ~11,000/yr; wide CI
- weakness
- excludes chronic disease and self-poisoning (110,000–168,000/yr, Mew et al. 2017), which lives here and not on the front door, handled with care.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- most are farmworkers in low and middle income countries. Boedeker et al. 2020
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LGR-050 v0.1.0modelmodel
humans Homo sapiens
died early from farm air pollution: 600 000 a year, so 0.019 a second. the livestock share: no ledger.
most of it. ammonia from manure and fertilizer becomes fine particulate.
- method
- agricultural share of PM2.5 mortality from Lelieveld et al. 2015; livestock share from Domingo et al. 2021 (US).
- range
- 400,000–800,000/yr
- weakness
- attribution models differ; the site uses the order of magnitude and says so.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- an estimate with a wide range. the point is the order of magnitude. Lelieveld et al. 2015; Domingo et al. 2021
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LGR-051 v0.1.0modelestimate
humans Homo sapiens
died early from breathing outdoor air: 4.7 million a year, so 0.149 a second. from cooking smoke, indoors: 3.1 million a year, 0.098 a second.
mostly women and children. mostly wood, dung and coal. about two billion people still cook this way.
- method
- State of Global Air 2024 / GBD 2021 for outdoor PM2.5 and household air pollution.
- range
- outdoor 4–5 million/yr; household 2.5–3.5 million/yr
- weakness
- none material for the totals; the food-system share is not quantified here.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- about eight million a year in all. more than malaria, tuberculosis and hiv together. State of Global Air 2024; WHOboth numbers are falling in most of the world and rising in south asia. the smoke moved. it did not go away. AQLI; State of Global Air 2024a share of delhi’s winter air is farmers burning rice stubble to plant wheat. that share is on this site’s ledger. IIT Kanpur; SAFAR; CREA
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LGR-052 v0.1.0modelestimate
humans Homo sapiens
killed by animals: 1 million a year, so 0.032 a second. killed by other humans, for scale: 460 000 a year, 0.015 a second.
the deadliest animal on earth is the mosquito, about seven hundred thousand a year. the second is us.
- method
- WHO and GBD 2019: malaria + dengue + other vector-borne (mosquito ~700k), snakebite, rabies, schistosomiasis, Chagas, leishmaniasis, large animals from incident databases.
- range
- 0.8–1.2 million/yr
- weakness
- attributes vector-borne disease deaths to the vector; the parasite does the killing. the large-animal counts are order of magnitude.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- snakes about a hundred thousand. dogs, by rabies, about sixty thousand. freshwater snails, by schistosomiasis, about twelve thousand. crocodiles about a thousand. hippos about five hundred. sharks about ten. WHO; GBD 2019; CrocBITE; ISAFsharks kill about ten people a year. people kill about a hundred million sharks. both are on this ledger. ISAF; Worm et al. 2013tsetse flies killed tens of thousands a year in the 1990s and fewer than a thousand now. because we treated, and because we trapped the flies. WHO sleeping sickness
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LGR-053 v0.1.0modelcount (homicide); estimate (conflict)
humans Homo sapiens
killed by other humans: 460 000 a year, so 0.015 a second. killed in armed conflict: 200 000 a year, 6.34e-3 a second.
the war count is always contested and always late. the murder count is only slightly better.
- method
- UNODC Global Study on Homicide (2021 data); conflict deaths from Uppsala/ACLED, annualised.
- range
- homicide 400,000–500,000/yr; conflict 100,000–300,000/yr
- weakness
- conflict counts lag by years and vary by source by a factor of two.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- about 250,000 people are shot dead a year, a third of them murdered, most of the rest by their own hand. eight in ten murder victims are men. so are most of the killers. UNODC Global Study on Homicide 2023; Naghavi et al. 2018at least 1,500 executions were recorded last year. china executes thousands and does not say. terrorism killed about eight thousand. Amnesty International 2024; Global Terrorism Index 2024
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LGR-054 v0.1.0modelcount
humans Homo sapiens
killed on the roads: 1.2 million a year, so 0.038 a second. of them, on foot or on a bicycle: 350 000 a year, 0.011 a second.
the leading cause of death for people aged five to twenty-nine. most of the dead are not in the cars.
- method
- WHO Global Status Report on Road Safety 2023; vulnerable-user share and alcohol share from the same.
- range
- 1.1–1.3 million/yr
- weakness
- many countries under-report; WHO models the gap.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- about a quarter of road deaths involve alcohol. in some countries a third. WHO Global Status Report on Road Safety 2023nine in ten road deaths are in low and middle income countries, which have six in ten of the vehicles. WHO 2023
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LGR-055 v0.1.0modelestimate
humans Homo sapiens
killed by tobacco: 8 million a year, so 0.254 a second. of them, from someone else’s smoke: 1.3 million a year, 0.041 a second.
the largest single preventable cause of death on earth. legal everywhere.
- method
- WHO tobacco fact sheet: >8 million/yr including ~1.3 million from second-hand smoke.
- range
- 7.5–8.5 million/yr
- weakness
- attributable-fraction estimate; the strongest such estimate in epidemiology.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- more than malaria, tuberculosis and hiv together, every year, and it is sold in shops. WHO tobacco fact sheet 2023smoking is falling almost everywhere. because we taxed it, banned it indoors, and stopped letting it advertise. slowly. WHO global tobacco trends 2024
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LGR-056 v0.1.0modelestimate
humans Homo sapiens
killed by alcohol: 2.6 million a year, so 0.082 a second. killed by other drugs: 600 000 a year, 0.019 a second.
one legal in most places, one mostly not. the ledger does not sort by law.
- method
- WHO Global Status Report on Alcohol 2024 (2.6M); UNODC World Drug Report for other drugs (~0.6M).
- range
- alcohol 2.4–3.0 million/yr; drugs 0.5–0.7 million/yr
- weakness
- attributable-fraction estimates; drug deaths are undercounted where they are criminal.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- alcohol kills about four times as many people as all illegal drugs together. WHO Global Status Report on Alcohol 2024; UNODC World Drug Reportoverdose deaths in the united states passed 100,000 a year in 2021, mostly fentanyl. they have started to fall. CDC WONDER
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LGR-057 v0.1.0modelestimate
humans Homo sapiens
died of infections passed by sex: 1.1 million a year, so 0.035 a second. newly infected with hiv: 1.3 million a year, 0.041 a second.
hiv about 630,000, cervical cancer from hpv about 350,000, syphilis and hepatitis the rest.
- method
- UNAIDS (HIV deaths ~630k), WHO/IARC (cervical cancer ~350k, nearly all HPV), WHO (syphilis, hepatitis B share).
- range
- 1.0–1.3 million/yr
- weakness
- attribution of hepatitis B deaths to sexual transmission is partial; the site counts a share.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- hiv came from chimpanzees, by bushmeat, around 1920. the animal ledger again. Worobey et al. 2008; Sharp & Hahn 2011the hpv vaccine is ending cervical cancer where it is used: in vaccinated scottish women, no cases at all. because we vaccinated. Palmer et al. 2024, JNCI; WHO cervical cancer elimination initiative
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LGR-058 v0.1.0modelestimate
humans Homo sapiens
killed by lead: 1.5 million a year, so 0.048 a second. the true number: no ledger.
no ledger. one recent estimate is 5.5 million, four times the old one. nobody is sure, and the range is the finding.
- method
- GBD 2019 (~0.9M) and Larsen & Sandahl 2023 (~5.5M cardiovascular); the site shows 1.5M and states the range as the finding.
- range
- 0.9–5.5 million/yr
- weakness
- the widest range on the human side of the site, by design shown as a dash for 'the true number'.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- leaded petrol was banned in the last country, algeria, in 2021. children’s blood lead has fallen about tenfold where it was banned. because we stopped. UNEP 2021; CDC NHANESit is still in old paint, old pipes, some spices, some pots, some cosmetics, and the batteries we recycle badly. Larsen & Sandahl 2023, Lancet Planetary Health; Pure Earth
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LGR-059 v0.1.0modelestimate
humans Homo sapiens
killed by dirty water and no toilet: 1.4 million a year, so 0.044 a second. of them, children under five: 395 000 a year, 0.013 a second.
diarrhoeal disease, mostly. water is a plumbing problem, and plumbing is a decision.
- method
- WHO burden of disease from inadequate WASH 2023 (1.4M); child share from the same.
- range
- 1.2–1.6 million/yr
- weakness
- attributable-fraction estimate; diarrhoeal deaths are also falling fast, so this dates.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- about 2 billion people drink water contaminated with faeces. about 3.5 billion have no safely managed toilet. WHO/UNICEF JMP 2023; WHO burden of disease from WASH 2023
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LGR-060 v0.1.0modelestimate
humans Homo sapiens
killed at work: 2.9 million a year, so 0.092 a second. of them, in accidents: 330 000 a year, 0.010 a second.
the rest is disease: dust, chemicals, heat, hours. most of it in the supply chains of things you own.
- method
- ILO 2023 estimates: ~2.9M work-related deaths incl. disease; ~330k accidents; fishing from FISH Safety Foundation 2022.
- range
- 2.6–3.2 million/yr
- weakness
- occupational disease attribution is modeled; the fishing figure is an NGO estimate several times the old official one.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- fishing is the deadliest job on earth: about 100,000 a year. mining, construction and farming follow. ILO 2023; FISH Safety Foundation 2022slaughterhouse workers are hurt at about twice the average rate. in the united states, an amputation about every week. US GAO 2016; OSHA severe injury reports
- dispute
- dispute LGR-060 · corrections are credited
LGR-061 v0.1.0modelestimate
humans Homo sapiens
died of hunger and its diseases: 9 million a year, so 0.285 a second. calories grown per person per day: ~2 900.
the world grows enough. about a third of the crop goes to animals, and most of what they eat does not come back as food.
- method
- widely used UN-based estimate of ~9 million hunger-related deaths/yr; calories per capita from FAO food balance sheets; feed share from Cassidy et al. 2013.
- range
- 7–11 million/yr
- weakness
- 'hunger-related' includes deaths where undernutrition is a contributing cause; the number is contested and the site rounds.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- about 25,000 a day, half of them children. it is not a shortage. it is a distribution. FAO SOFI 2024; UN WFP; Cassidy et al. 2013every channel on this site is one channel. methodology note
- dispute
- dispute LGR-061 · corrections are credited
LGR-062 v0.1.0modelmodel
humans Homo sapiens
killed by heat: 490 000 a year, so 0.016 a second. of them, from the warming we caused: 180 000 a year, 5.70e-3 a second.
about a third of heat deaths are now attributable to human warming. the share rises every year.
- method
- Zhao et al. 2021 (heat deaths ~490k); Vicedo-Cabrera et al. 2021 for the anthropogenic share (~37%).
- range
- 400,000–600,000/yr; attributable share 20–50%
- weakness
- attribution studies cover a subset of countries; the site applies the share globally.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- cold still kills more people than heat, about 4.6 million a year. that is falling. this is rising. Zhao et al. 2021, Lancet Planetary Health; Vicedo-Cabrera et al. 2021the people who die of heat are mostly old, poor, and outdoors: farm workers, builders, the unhoused. WHO; ILO
- dispute
- dispute LGR-062 · corrections are credited
LGR-063 v0.1.0modelestimate
humans Homo sapiens
died from drug-resistant infections: 1.3 million a year, so 0.040 a second. the share from farm antibiotics: no ledger.
no ledger. most of the world’s antibiotics go to animals. no one has measured what comes back.
- method
- Murray et al. 2022 (GRAM): deaths directly attributable to bacterial AMR, 2019.
- range
- 0.9–1.7 million/yr
- weakness
- the farm-antibiotic share is unquantified, and the site shows a dash rather than a number.
- becomes a feed
- OpenAQ, air in ten thousand cities right now
- lines shown, with sources
- 1.27 million deaths a year directly attributable to resistance. the farm share is unquantified, not zero. Murray et al. 2022; Van Boeckel et al. 2019
- dispute
- dispute LGR-063 · corrections are credited
feed
LGR-064 v0.1.0feed (stub)feed (stub)
the amazon active fires, last 24 hours · nasa firms
fires detected · feed not connected: ? (placeholder). lit on purpose: no ledger.
most. the forest does not burn on its own; it is cut, dried, and set alight for pasture and soy.
- method
- placeholder for NASA FIRMS active fire detections in the last 24 hours, Amazon biome.
- range
- hundreds (wet season) to tens of thousands (peak days)
- weakness
- a stand-in number until wired. clearly badged.
- becomes a feed
- NASA FIRMS, active fires every 3 hours
- lines shown, with sources
- this is the site’s first feed: satellite fire detections over the amazon in the last 24 hours, counted every three hours. when the feed is down or not yet wired, the number is a question mark, not a guess. NASA FIRMS (VIIRS); INPE; MapBiomas
- dispute
- dispute LGR-064 · corrections are credited
stills
LGR-065 v0.1.0modelcount
the sea global surface temperature
born 1950 -0.05 → 0.72 °C the sea is 0.77°C warmer than the day you were born. about a quarter to a third of the warming behind that is the food system.
born 1970 0.00 → 0.72 °C the sea is 0.72°C warmer than the day you were born. about a quarter to a third of the warming behind that is the food system.
born 1990 0.20 → 0.72 °C the sea is 0.52°C warmer than the day you were born. about a quarter to a third of the warming behind that is the food system.
born 2010 0.42 → 0.72 °C the sea is 0.30°C warmer than the day you were born. about a quarter to a third of the warming behind that is the food system.
- method
- global sea-surface temperature anomaly by year (HadSST/NOAA), difference between birth year and now.
- range
- ±0.05°C on any year's anomaly
- weakness
- food-system share of warming (a quarter to a third) is from emissions share (Crippa 2021), not a warming attribution study.
- becomes a feed
- NOAA OISST, daily
- dispute
- dispute LGR-065 · corrections are credited
LGR-066 v0.1.0modelcount
the ozone hole antarctic, peak area
born 1950 0 → 22 million km² there was no hole when you were born. it opened, peaked around 2000, and is closing. the montreal protocol, 1987. every country on earth signed it.
born 1970 0 → 22 million km² there was no hole when you were born. it opened, peaked around 2000, and is closing. the montreal protocol, 1987. every country on earth signed it.
born 1990 21 → 22 million km² it peaked around 2000 and is closing. it should be healed by about 2066. the montreal protocol, 1987. every country on earth signed it.
born 2010 22 → 22 million km² it peaked around 2000 and is closing. it should be healed by about 2066. the montreal protocol, 1987. every country on earth signed it.
- method
- NASA Ozone Watch maximum daily area by year; healing date from WMO 2022.
- range
- year-to-year variation ±5 million km²
- weakness
- a single-year value is noisy; the trend is not.
- dispute
- dispute LGR-066 · corrections are credited
LGR-067 v0.1.0modelestimate
humpback whales Megaptera novaeangliae
born 1950 32 878 → 84 000 individuals hunted to a few thousand by 1966. now over eighty thousand. commercial whaling stopped in 1966 for humpbacks, 1986 for nearly everything.
born 1970 7 500 → 84 000 individuals there are about 76 500 more than when you were born. commercial whaling stopped in 1966 for humpbacks, 1986 for nearly everything.
born 1990 20 000 → 84 000 individuals there are about 64 000 more than when you were born. commercial whaling stopped in 1966 for humpbacks, 1986 for nearly everything.
born 2010 60 000 → 84 000 individuals there are about 24 000 more than when you were born. commercial whaling stopped in 1966 for humpbacks, 1986 for nearly everything.
- method
- IUCN/IWC population estimates by decade, interpolated.
- range
- ±25% on any decade
- weakness
- decade anchors, interpolated. wants a proper series.
- dispute
- dispute LGR-067 · corrections are credited
LGR-068 v0.1.0modelcount
the aral sea once the fourth largest lake on earth
born 1950 68 000 → 8 000 km² it was drained for cotton. deliberately. within your lifetime. the rivers that fed it were diverted to irrigate cotton. it is the clearest example of a lake we chose to lose.
born 1970 60 000 → 8 000 km² it has lost 87% of its area since you were born. the rivers that fed it were diverted to irrigate cotton. it is the clearest example of a lake we chose to lose.
born 1990 37 000 → 8 000 km² it has lost 78% of its area since you were born. the rivers that fed it were diverted to irrigate cotton. it is the clearest example of a lake we chose to lose.
born 2010 14 000 → 8 000 km² it has lost 43% of its area since you were born. the rivers that fed it were diverted to irrigate cotton. it is the clearest example of a lake we chose to lose.
- method
- NASA Earth Observatory / UNEP surface area by decade.
- range
- ±10%
- weakness
- the sea has fragmented; 'area' is the sum of the remnants.
- dispute
- dispute LGR-068 · corrections are credited
LGR-069 v0.1.0modelcount
dead zones coastal waters too low in oxygen for animals
born 1950 40 → 700 known sites about 18× as many as when you were born. fertilizer and manure run to the sea, algae bloom, rot, and take the oxygen with them. the count roughly doubled every decade since the 1960s.
born 1970 87 → 700 known sites about 8× as many as when you were born. fertilizer and manure run to the sea, algae bloom, rot, and take the oxygen with them. the count roughly doubled every decade since the 1960s.
born 1990 305 → 700 known sites about 2× as many as when you were born. fertilizer and manure run to the sea, algae bloom, rot, and take the oxygen with them. the count roughly doubled every decade since the 1960s.
born 2010 500 → 700 known sites about 1× as many as when you were born. fertilizer and manure run to the sea, algae bloom, rot, and take the oxygen with them. the count roughly doubled every decade since the 1960s.
- method
- Diaz & Rosenberg 2008 counts by decade; Breitburg et al. 2018 for recent totals.
- range
- 500–700+ current sites depending on definition
- weakness
- a count of known sites rises with monitoring effort as well as with pollution.
- dispute
- dispute LGR-069 · corrections are credited
LGR-070 v0.1.0modelestimate
drug resistance deaths a year directly attributable
born 1950 ? → 1 200 000 deaths a year no ledger. nobody was counting when you were born. the first global estimate is for 1990. by 2050 the forecast is about 1.9 million a year, nearly double.
born 1970 ? → 1 200 000 deaths a year no ledger. nobody was counting when you were born. the first global estimate is for 1990. by 2050 the forecast is about 1.9 million a year, nearly double.
born 1990 1 000 000 → 1 200 000 deaths a year by 2050, about 1.9 million a year. nearly double. most of the world’s antibiotics by volume go to animals. the farm share of these deaths is unquantified, not zero.
born 2010 1 096 551 → 1 200 000 deaths a year by 2050, about 1.9 million a year. nearly double. most of the world’s antibiotics by volume go to animals. the farm share of these deaths is unquantified, not zero.
- method
- GRAM estimates 1990–2021; forecast to 2050 from Naghavi et al. 2024.
- range
- as above
- weakness
- no data before 1990, shown as a dash.
- dispute
- dispute LGR-070 · corrections are credited
LGR-071 v0.1.0modelcount
european bison Bison bonasus
born 1950 200 → 9 500 individuals about 48× as many as when you were born. the last wild one was shot in 1927. bred back from a dozen zoo animals and released into poland, belarus, romania, and now the netherlands and the uk.
born 1970 1 000 → 9 500 individuals about 10× as many as when you were born. the last wild one was shot in 1927. bred back from a dozen zoo animals and released into poland, belarus, romania, and now the netherlands and the uk.
born 1990 3 000 → 9 500 individuals about 3× as many as when you were born. the last wild one was shot in 1927. bred back from a dozen zoo animals and released into poland, belarus, romania, and now the netherlands and the uk.
born 2010 4 400 → 9 500 individuals about 2× as many as when you were born. the last wild one was shot in 1927. bred back from a dozen zoo animals and released into poland, belarus, romania, and now the netherlands and the uk.
- method
- European Bison Pedigree Book, decade anchors interpolated.
- range
- ±10%
- weakness
- interpolated between anchors.
- dispute
- dispute LGR-071 · corrections are credited
LGR-072 v0.1.0modelestimate
eurasian beavers Castor fiber
born 1950 20 000 → 1 500 000 individuals about 75× as many as when you were born. protected, then reintroduced across europe. they build the wetlands nobody else will.
born 1970 100 000 → 1 500 000 individuals about 15× as many as when you were born. protected, then reintroduced across europe. they build the wetlands nobody else will.
born 1990 400 000 → 1 500 000 individuals about 4× as many as when you were born. protected, then reintroduced across europe. they build the wetlands nobody else will.
born 2010 1 000 000 → 1 500 000 individuals about 2× as many as when you were born. protected, then reintroduced across europe. they build the wetlands nobody else will.
- method
- Halley, Saveljev & Rosell 2021 with earlier anchors.
- range
- ±25% on early decades
- weakness
- early-century numbers are reconstructions.
- dispute
- dispute LGR-072 · corrections are credited
LGR-073 v0.1.0modelestimate
wolves in europe Canis lupus
born 1950 8 000 → 23 000 individuals, excluding russia about 188% more than when you were born. they walked back into germany in 2000, the netherlands in 2018, belgium in 2018. nobody released them. legal protection, and empty land, was enough.
born 1970 8 000 → 23 000 individuals, excluding russia about 188% more than when you were born. they walked back into germany in 2000, the netherlands in 2018, belgium in 2018. nobody released them. legal protection, and empty land, was enough.
born 1990 12 000 → 23 000 individuals, excluding russia about 92% more than when you were born. they walked back into germany in 2000, the netherlands in 2018, belgium in 2018. nobody released them. legal protection, and empty land, was enough.
born 2010 14 000 → 23 000 individuals, excluding russia about 64% more than when you were born. they walked back into germany in 2000, the netherlands in 2018, belgium in 2018. nobody released them. legal protection, and empty land, was enough.
- method
- Chapron et al. 2014; LCIE 2023; excludes Russia.
- range
- ±15%
- weakness
- pre-1990 anchors are rough.
- dispute
- dispute LGR-073 · corrections are credited
LGR-074 v0.1.0modelcount
bald eagles Haliaeetus leucocephalus, lower 48 states
born 1950 417 → 71 400 breeding pairs 417 pairs in 1963. over seventy thousand now. DDT was banned in 1972. that was most of it.
born 1970 739 → 71 400 breeding pairs about 97× as many as when you were born. DDT was banned in 1972. that was most of it.
born 1990 3 000 → 71 400 breeding pairs about 24× as many as when you were born. DDT was banned in 1972. that was most of it.
born 2010 25 191 → 71 400 breeding pairs about 3× as many as when you were born. DDT was banned in 1972. that was most of it.
- method
- USFWS breeding-pair counts, lower 48 states.
- range
- ±10%
- weakness
- none material.
- dispute
- dispute LGR-074 · corrections are credited
LGR-075 v0.1.0modelcount
costa rica forest cover
born 1950 65 → 58 % of land when you were born the country was 65% forest. it fell to about a fifth by 1987. it is 58% now. a 1996 law banned clearing forest. farmers were paid to leave it standing. it worked.
born 1970 42 → 58 % of land the forest has come back over 16% of the country since you were born. a 1996 law banned clearing forest. farmers were paid to leave it standing. it worked.
born 1990 27 → 58 % of land the forest has come back over 31% of the country since you were born. a 1996 law banned clearing forest. farmers were paid to leave it standing. it worked.
born 2010 53 → 58 % of land the forest has come back over 5% of the country since you were born. a 1996 law banned clearing forest. farmers were paid to leave it standing. it worked.
- method
- FONAFIFO / SINAC forest cover by year.
- range
- ±5 percentage points
- weakness
- definitions of 'forest' changed over the century.
- dispute
- dispute LGR-075 · corrections are credited
LGR-076 v0.1.0modelcount
europe’s forests growing, not shrinking
everyone europe’s forests have grown by roughly the area of the united kingdom since 1990. nobody planted most of it. the farms left, and it came back. much of it is young and some of it is plantation. it is still forest, and it is still growing.
- method
- FAO FRA 2020, Europe incl. Russia, 1990–2020 change (~+22 Mha).
- range
- ±10%
- weakness
- 'roughly the UK' is a size analogy; the UK is 24 Mha.
- dispute
- dispute LGR-076 · corrections are credited
LGR-077 v0.1.0modelmodel
the land what comes back, if we stop
everyone without meat and dairy, the world’s farmland could shrink by about three quarters: an area the size of the united states, china, the european union and australia combined. most of it would go back to forest and grassland on its own. the regrowth could pull several hundred billion tonnes of carbon dioxide out of the air over the century. the land is not the problem. what we do on it is.
- method
- Poore & Nemecek 2018 (farmland reduction without animal products); Hayek et al. 2021 (carbon opportunity cost).
- range
- land −70 to −80%; carbon 330–550 Gt CO2
- weakness
- a scenario, not a prediction, and shown as 'if we stopped'.
- dispute
- dispute LGR-077 · corrections are credited
LGR-078 v0.1.0modelcount
satellites working, in orbit
born 1950 0 → 13 000 satellites there were none when you were born. the first went up in 1957. nearly all of it is one company. the orbit is a commons. it is being enclosed the way the land was, and nobody voted on it.
born 1970 200 → 13 000 satellites about 65× as many as when you were born. most of the increase is since 2019. nearly all of it is one company. the orbit is a commons. it is being enclosed the way the land was, and nobody voted on it.
born 1990 500 → 13 000 satellites about 26× as many as when you were born. most of the increase is since 2019. nearly all of it is one company. the orbit is a commons. it is being enclosed the way the land was, and nobody voted on it.
born 2010 1 000 → 13 000 satellites about 13× as many as when you were born. most of the increase is since 2019. nearly all of it is one company. the orbit is a commons. it is being enclosed the way the land was, and nobody voted on it.
- method
- active satellites by year, McDowell/UCS.
- range
- ±10%
- weakness
- none material.
- becomes a feed
- Space-Track / CelesTrak, live catalogue
- dispute
- dispute LGR-078 · corrections are credited
LGR-079 v0.1.0modelestimate
london’s air smoke and fine particulate, annual mean
born 1950 292 → 10 µg/m³ in december 1952 a smog killed about twelve thousand people in five days. the clean air act followed in 1956. the air is about fifty times cleaner than victorian london. coal was banned from the city’s grates. that was most of it. what is left comes from exhausts and, on bad days, from farms and fires far away.
born 1970 60 → 10 µg/m³ about 6× cleaner than when you were born. coal was banned from the city’s grates. that was most of it. what is left comes from exhausts and, on bad days, from farms and fires far away.
born 1990 25 → 10 µg/m³ about 2.5× cleaner than when you were born. coal was banned from the city’s grates. that was most of it. what is left comes from exhausts and, on bad days, from farms and fires far away.
born 2010 15 → 10 µg/m³ about 1.5× cleaner than when you were born. coal was banned from the city’s grates. that was most of it. what is left comes from exhausts and, on bad days, from farms and fires far away.
- method
- annual mean smoke (pre-1990) and PM2.5 (post-1990) in µg/m³, harmonised approximately from Fouquet 2011, Brimblecombe 1987 and DEFRA/LAQN.
- range
- ±30% on historical years
- weakness
- two different metrics stitched together; the shape is robust, the exact ratio is not.
- becomes a feed
- London Air Quality Network, hourly
- dispute
- dispute LGR-079 · corrections are credited
LGR-080 v0.1.0modelcount
the smoke where it went
everyone micrograms of smoke in each cubic metre of air, over a year. london, 1890: about 500. london now: about 10. beijing, 2013: about 100. beijing now: about 35. delhi now: about 100. lahore now: about 100. the same units, the same smoke. it did not go away. it moved to where the coal, the traffic and the crop fires are now. every city that cleaned its air did it the same way: it stopped burning the thing.
- method
- annual mean PM2.5 (or smoke) in µg/m³ for named cities and years.
- range
- ±20%
- weakness
- London 1890 is a reconstruction (Fouquet).
- becomes a feed
- OpenAQ
- dispute
- dispute LGR-080 · corrections are credited
LGR-081 v0.1.0modelcount (post-1988); estimate (pre-1988)
polio children paralysed by wild poliovirus, a year
born 1950 600 000 → 40 cases a year when you were born there was no vaccine. iron lungs. now: a few dozen cases a year, in two countries. it is the best ledger ever kept for a disease. every case of sudden paralysis in every country is investigated and typed. that is why the number can be trusted all the way down.
born 1970 450 000 → 40 cases a year about 450 000 a year when you were born. a few dozen now. it is the best ledger ever kept for a disease. every case of sudden paralysis in every country is investigated and typed. that is why the number can be trusted all the way down.
born 1990 252 000 → 40 cases a year about 252 000 a year when you were born. a few dozen now. it is the best ledger ever kept for a disease. every case of sudden paralysis in every country is investigated and typed. that is why the number can be trusted all the way down.
born 2010 1 352 → 40 cases a year about 1 352 a year when you were born. a few dozen now. it is the best ledger ever kept for a disease. every case of sudden paralysis in every country is investigated and typed. that is why the number can be trusted all the way down.
- method
- WHO/GPEI wild poliovirus paralytic cases by year; pre-1988 back-estimates.
- range
- pre-1988 ±50%
- weakness
- the pre-1988 numbers are estimates and labelled so.
- dispute
- dispute LGR-081 · corrections are credited
LGR-082 v0.1.0modelestimate
smallpox Variola
everyone smallpox killed about 300 million people in the twentieth century. it has killed nobody since 1978. the last natural case was a hospital cook in somalia, 1977. he lived. it is the only human disease we have ever finished.
- method
- WHO; Fenner et al. 1988.
- range
- 20th-century deaths 300–500 million
- weakness
- none material.
- dispute
- dispute LGR-082 · corrections are credited
LGR-083 v0.1.0modelestimate
measles a cattle virus, deaths a year
born 1950 2 600 000 → 110 000 deaths a year when you were born there was no vaccine and measles killed about two and a half million children a year. now about a hundred thousand. measles split from rinderpest, a cattle plague, around the sixth century BCE. we eradicated the cattle one. the human one is coming back where vaccination fell.
born 1970 2 600 000 → 110 000 deaths a year about 3 million a year when you were born. about 110 000 now. measles split from rinderpest, a cattle plague, around the sixth century BCE. we eradicated the cattle one. the human one is coming back where vaccination fell.
born 1990 1 100 000 → 110 000 deaths a year about 1 million a year when you were born. about 110 000 now. measles split from rinderpest, a cattle plague, around the sixth century BCE. we eradicated the cattle one. the human one is coming back where vaccination fell.
born 2010 140 000 → 110 000 deaths a year about 140 000 a year when you were born. about 110 000 now. measles split from rinderpest, a cattle plague, around the sixth century BCE. we eradicated the cattle one. the human one is coming back where vaccination fell.
- method
- WHO measles deaths by year; pre-1980 estimates.
- range
- ±30% on any year
- weakness
- pre-vaccine figures are estimates.
- dispute
- dispute LGR-083 · corrections are credited
LGR-084 v0.1.0modelcount
rinderpest the cattle plague, gone
everyone rinderpest killed cattle by the hundred million for three thousand years. in the 1890s it killed nine in ten in parts of africa and the people starved after them. it has killed nothing since 2001. declared eradicated in 2011. the second disease we ever finished, and the first that was not ours. measles is its child.
- method
- FAO/OIE eradication record.
- range
- n/a
- weakness
- none.
- dispute
- dispute LGR-084 · corrections are credited
LGR-085 v0.1.0modelcount
plague Yersinia pestis, still here
everyone the black death killed a third to a half of europe in four years, 1347 to 1351. it came from rodents, by flea. it is still here: about one to two thousand cases a year, in madagascar, congo, peru, and a few in the american west, from prairie dogs and squirrels. the disease never left the ground. what changed is a drug, streptomycin, 1947, and a ledger: every case is reported to the who within a day.
- method
- WHO reported cases; historical mortality from Bramanti et al. 2016.
- range
- 1,000–3,000 cases/yr
- weakness
- reporting varies; Madagascar dominates.
- dispute
- dispute LGR-085 · corrections are credited
LGR-086 v0.1.0modelcount
tuberculosis the deadliest infection on earth, deaths a year
born 1950 ? → 1 250 000 deaths a year no ledger before 1990. in victorian europe it was one death in seven. it still kills over a million people a year. it lives in cattle too. bovine tb crosses to people in raw milk. britain kills badgers and cattle by the tens of thousands a year to keep it out of the herd.
born 1970 ? → 1 250 000 deaths a year no ledger before 1990. in victorian europe it was one death in seven. it still kills over a million people a year. it lives in cattle too. bovine tb crosses to people in raw milk. britain kills badgers and cattle by the tens of thousands a year to keep it out of the herd.
born 1990 1 900 000 → 1 250 000 deaths a year about 2 million a year when you were born. about 1 million now. it is still the deadliest infection on earth. it lives in cattle too. bovine tb crosses to people in raw milk. britain kills badgers and cattle by the tens of thousands a year to keep it out of the herd.
born 2010 1 400 000 → 1 250 000 deaths a year about 1 million a year when you were born. about 1 million now. it is still the deadliest infection on earth. it lives in cattle too. bovine tb crosses to people in raw milk. britain kills badgers and cattle by the tens of thousands a year to keep it out of the herd.
- method
- WHO Global TB Report deaths by year (HIV-negative and positive).
- range
- ±10%
- weakness
- no global series before 1990.
- dispute
- dispute LGR-086 · corrections are credited
LGR-087 v0.1.0modelestimate
where diseases come from the animal ledger, again
everyone of the diseases we catch, about six in ten came from animals. of the new ones, three in four. measles from cattle. flu from birds and pigs. hiv from chimpanzees, by bushmeat. plague from rodents. covid, most likely, from a wildlife market. bird flu, now, from the sheds. the way we keep animals is the way we make diseases. every channel on this site is one channel.
- method
- Taylor et al. 2001 (61% zoonotic); Jones et al. 2008 (75% of emerging).
- range
- n/a
- weakness
- COVID origin stated as 'most likely' per Worobey et al. 2022; contested.
- dispute
- dispute LGR-087 · corrections are credited
LGR-088 v0.1.0modelestimate
blue whales Balaenoptera musculus
born 1950 47 777 → 15 000 individuals about 69% fewer than when you were born. about a quarter of a million before whaling. a few thousand by 1966. protected that year, everywhere.
born 1970 5 000 → 15 000 individuals about 3× as many as when you were born. about a quarter of a million before whaling. a few thousand by 1966. protected that year, everywhere.
born 1990 7 000 → 15 000 individuals about 2.1× as many as when you were born. about a quarter of a million before whaling. a few thousand by 1966. protected that year, everywhere.
born 2010 10 000 → 15 000 individuals about 1.5× as many as when you were born. about a quarter of a million before whaling. a few thousand by 1966. protected that year, everywhere.
- method
- IWC/IUCN by decade, interpolated.
- range
- ±40% on current global count
- weakness
- global count is poorly known; Antarctic population best studied.
- dispute
- dispute LGR-088 · corrections are credited
LGR-089 v0.1.0modelestimate
tigers Panthera tigris
born 1950 57 142 → 5 700 individuals about 90% fewer than when you were born. about a hundred thousand in 1900. the low was 2010. rising since, slowly, where the forest was left alone.
born 1970 40 000 → 5 700 individuals about 86% fewer than when you were born. about a hundred thousand in 1900. the low was 2010. rising since, slowly, where the forest was left alone.
born 1990 8 000 → 5 700 individuals about 29% fewer than when you were born. about a hundred thousand in 1900. the low was 2010. rising since, slowly, where the forest was left alone.
born 2010 3 200 → 5 700 individuals about 1.8× as many as when you were born. about a hundred thousand in 1900. the low was 2010. rising since, slowly, where the forest was left alone.
- method
- WWF/Global Tiger Forum counts; 1900 estimate.
- range
- ±15% now; ±50% in 1900
- weakness
- 1900 figure is a widely repeated estimate, not a count.
- dispute
- dispute LGR-089 · corrections are credited
LGR-090 v0.1.0modelcount
black rhinos Diceros bicornis
born 1950 100 000 → 6 500 individuals no count from the year you were born. the first is 1960: about 100 000. a hundred thousand in 1960. poached to 2,400 by 1995. climbing since. still poached.
born 1970 65 000 → 6 500 individuals about 90% fewer than when you were born. a hundred thousand in 1960. poached to 2,400 by 1995. climbing since. still poached.
born 1990 6 606 → 6 500 individuals about as many as when you were born. holding. a hundred thousand in 1960. poached to 2,400 by 1995. climbing since. still poached.
born 2010 4 880 → 6 500 individuals about 1.3× as many as when you were born. a hundred thousand in 1960. poached to 2,400 by 1995. climbing since. still poached.
- method
- IUCN AfRSG.
- range
- ±10%
- weakness
- none material.
- dispute
- dispute LGR-090 · corrections are credited
LGR-091 v0.1.0modelcount
african elephants Loxodonta
born 1950 3 489 795 → 415 000 individuals about 88% fewer than when you were born. ivory. then land: the farms took the corridors. the fall has slowed. it has not turned.
born 1970 1 979 591 → 415 000 individuals about 79% fewer than when you were born. ivory. then land: the farms took the corridors. the fall has slowed. it has not turned.
born 1990 594 444 → 415 000 individuals about 30% fewer than when you were born. ivory. then land: the farms took the corridors. the fall has slowed. it has not turned.
born 2010 471 666 → 415 000 individuals about 12% fewer than when you were born. ivory. then land: the farms took the corridors. the fall has slowed. it has not turned.
- method
- Great Elephant Census 2016; IUCN.
- range
- ±15%
- weakness
- forest elephants poorly counted.
- dispute
- dispute LGR-091 · corrections are credited
LGR-092 v0.1.0modelcount
giant pandas Ailuropoda melanoleuca
born 1950 1 100 → 1 900 individuals no count from the year you were born. the first is 1980: about 1 100. the bamboo forest was left standing. that was most of it. off the endangered list in 2016.
born 1970 1 100 → 1 900 individuals no count from the year you were born. the first is 1980: about 1 100. the bamboo forest was left standing. that was most of it. off the endangered list in 2016.
born 1990 1 306 → 1 900 individuals about 1.5× as many as when you were born. the bamboo forest was left standing. that was most of it. off the endangered list in 2016.
born 2010 1 756 → 1 900 individuals about 1.1× as many as when you were born. the bamboo forest was left standing. that was most of it. off the endangered list in 2016.
- method
- China national surveys.
- range
- ±10%
- weakness
- survey intervals of a decade.
- dispute
- dispute LGR-092 · corrections are credited
LGR-093 v0.1.0modelcount
mountain gorillas Gorilla beringei beringei
born 1950 254 → 1 100 individuals no count from the year you were born. the first is 1981: about 254. 254 in 1981. over a thousand now. the only great ape whose numbers are rising.
born 1970 254 → 1 100 individuals no count from the year you were born. the first is 1981: about 254. 254 in 1981. over a thousand now. the only great ape whose numbers are rising.
born 1990 305 → 1 100 individuals about 4× as many as when you were born. 254 in 1981. over a thousand now. the only great ape whose numbers are rising.
born 2010 480 → 1 100 individuals about 2.3× as many as when you were born. 254 in 1981. over a thousand now. the only great ape whose numbers are rising.
- method
- IUCN; Dian Fossey Fund census.
- range
- ±5%
- weakness
- none material.
- dispute
- dispute LGR-093 · corrections are credited
LGR-094 v0.1.0modelcount
kakapo Strigops habroptilus
born 1950 51 → 247 individuals no count from the year you were born. the first is 1995: about 51. 51 birds in 1995. every one has a name and a transmitter. it is the most watched species on earth.
born 1970 51 → 247 individuals no count from the year you were born. the first is 1995: about 51. 51 birds in 1995. every one has a name and a transmitter. it is the most watched species on earth.
born 1990 51 → 247 individuals no count from the year you were born. the first is 1995: about 51. 51 birds in 1995. every one has a name and a transmitter. it is the most watched species on earth.
born 2010 132 → 247 individuals about 1.9× as many as when you were born. 51 birds in 1995. every one has a name and a transmitter. it is the most watched species on earth.
- method
- NZ DOC; every bird known.
- range
- exact
- weakness
- none.
- dispute
- dispute LGR-094 · corrections are credited
LGR-095 v0.1.0modelestimate
vaquita Phocoena sinus
born 1950 567 → 8 individuals no count from the year you were born. the first is 1997: about 567. drowned in gillnets set for a fish whose swim bladder sells as medicine. fewer than ten left. it is on the food ledger too.
born 1970 567 → 8 individuals no count from the year you were born. the first is 1997: about 567. drowned in gillnets set for a fish whose swim bladder sells as medicine. fewer than ten left. it is on the food ledger too.
born 1990 567 → 8 individuals no count from the year you were born. the first is 1997: about 567. drowned in gillnets set for a fish whose swim bladder sells as medicine. fewer than ten left. it is on the food ledger too.
born 2010 192 → 8 individuals about 96% fewer than when you were born. drowned in gillnets set for a fish whose swim bladder sells as medicine. fewer than ten left. it is on the food ledger too.
- method
- CIRVA/IUCN acoustic and visual surveys.
- range
- 6–12 in recent years
- weakness
- none material; the number is small and the range is honest.
- dispute
- dispute LGR-095 · corrections are credited
LGR-096 v0.1.0modelmodel
your share if you eat meat, and roughly like the world average
born 1950 53 200 → 2.4 you have consumed a piece of at least 53 200 different living things: one for every meal with an animal in it, and probably many more, because a burger holds beef from dozens of cattle and no one can count that. about 1.9 tonnes of meat and 0.5 tonnes of fish have passed through your body. to feed you, on the world-average share, about 449 land animals and 21 964 sea animals were killed outright; eggs and dairy add about 82. one cow feeds a thousand meals, and you ate from a thousand cows. both counts are true. a us or australian eater: about three times the mass. once you tell the site your country it stops averaging you.
born 1970 39 200 → 1.9 you have consumed a piece of at least 39 200 different living things: one for every meal with an animal in it, and probably many more, because a burger holds beef from dozens of cattle and no one can count that. about 1.5 tonnes of meat and 0.4 tonnes of fish have passed through your body. to feed you, on the world-average share, about 395 land animals and 16 895 sea animals were killed outright; eggs and dairy add about 62. one cow feeds a thousand meals, and you ate from a thousand cows. both counts are true. a us or australian eater: about three times the mass. once you tell the site your country it stops averaging you.
born 1990 25 200 → 1.4 you have consumed a piece of at least 25 200 different living things: one for every meal with an animal in it, and probably many more, because a burger holds beef from dozens of cattle and no one can count that. about 1.0 tonnes of meat and 0.3 tonnes of fish have passed through your body. to feed you, on the world-average share, about 307 land animals and 11 240 sea animals were killed outright; eggs and dairy add about 41. one cow feeds a thousand meals, and you ate from a thousand cows. both counts are true. a us or australian eater: about three times the mass. once you tell the site your country it stops averaging you.
born 2010 11 200 → 0.7 you have consumed a piece of at least 11 200 different living things: one for every meal with an animal in it, and probably many more, because a burger holds beef from dozens of cattle and no one can count that. about 0.5 tonnes of meat and 0.2 tonnes of fish have passed through your body. to feed you, on the world-average share, about 159 land animals and 5 040 sea animals were killed outright; eggs and dairy add about 18. one cow feeds a thousand meals, and you ate from a thousand cows. both counts are true. a us or australian eater: about three times the mass. once you tell the site your country it stops averaging you.
- method
- meals: two of three with an animal in them (700/yr) as a floor for distinct animals consumed; mass from FAO food supply per capita by year × edible share; killed-outright from per-capita slaughter and catch by year.
- range
- meals ±30%; mass ±20%; sea count 1–2.2 trillion/yr basis
- weakness
- the distinct-animals count is a floor by construction; the true number is unknowable because meat is pooled. world average until a country is set.
- dispute
- dispute LGR-096 · corrections are credited
LGR-097 v0.1.0modelestimate
shelters dogs and cats killed in shelters · united states
born 1950 13 500 000 → 700 000 a year thirteen to twenty million a year in the 1970s. under a million now. spay and neuter did most of it. the rest was rooms, and people. still: under a million a year, healthy, because nobody came.
born 1970 13 500 000 → 700 000 a year about 95% fewer than when you were born. spay and neuter did most of it. the rest was rooms, and people. still: under a million a year, healthy, because nobody came.
born 1990 7 916 666 → 700 000 a year about 91% fewer than when you were born. spay and neuter did most of it. the rest was rooms, and people. still: under a million a year, healthy, because nobody came.
born 2010 2 771 428 → 700 000 a year about 75% fewer than when you were born. spay and neuter did most of it. the rest was rooms, and people. still: under a million a year, healthy, because nobody came.
- method
- HSUS/ASPCA/Shelter Animals Count decade anchors, interpolated.
- range
- ±30% on early decades
- weakness
- 1970s figures are ranges (13–20 million); the site uses the low end.
- dispute
- dispute LGR-097 · corrections are credited
LGR-098 v0.1.0modelestimate
lions and tigers more in cages than in the wild
everyone there are more tigers in cages than in the wild: about 5,500 wild; over 5,000 in the united states alone, thousands more on chinese farms. in south africa about 8,000 lions live on breeding farms, more than twice the country’s wild lions. lions are bred for the bullet: petted as cubs, shot as adults, boiled for bone. tigers are bred to be looked at, and in some countries boiled. neither is bred to be wild.
- method
- WWF wild tiger estimate; US captive tiger estimates (Nowell 2007, later NGO counts); Born Free / EMS Foundation for south african captive lions.
- range
- US captive tigers 5,000–10,000; SA captive lions 8,000–12,000
- weakness
- captive counts are NGO estimates; no registry exists in the US.
- dispute
- dispute LGR-098 · corrections are credited
LGR-099 v0.1.0modelestimate
vultures a cattle painkiller, a dog, a virus, a person
everyone india lost about 97 to 99% of its vultures in ten years to diclofenac, a painkiller given to cattle. carcasses lay uneaten. feral dogs multiplied on them. rabies followed. one estimate: about half a million extra human deaths in five years. diclofenac was banned for cattle in 2006. the vultures are coming back, slowly. every channel on this site is one channel.
- method
- Frank & Sudarshan 2024 (AER) mortality estimate; Green et al. 2004 for the diclofenac mechanism.
- range
- human deaths 400,000–600,000 over 2000–2005
- weakness
- a difference-in-differences estimate; causal, contested at the margins, large in any version.
- dispute
- dispute LGR-099 · corrections are credited
LGR-100 v0.1.0modelestimate
sparrows china, 1958
everyone china ordered its sparrows killed for eating grain. hundreds of millions were. the locusts the sparrows had eaten came instead. the famine that followed killed tens of millions of people, of many causes, this among them. the four pests campaign. the sparrow was replaced on the list by the bedbug in 1960.
- method
- historical: Shapiro 2001; Dikötter 2010.
- range
- n/a
- weakness
- the famine had many causes; the site says so.
- dispute
- dispute LGR-100 · corrections are credited
LGR-101 v0.1.0modelestimate
passenger pigeons Ectopistes migratorius
everyone three to five billion. the most numerous bird on earth. flocks a mile wide that took hours to pass. shot, netted and shipped by the barrel. the last one, martha, died in cincinnati zoo on the first of september, 1914. from the most numerous bird on earth to none in about fifty years. nobody thought it was possible until it was done.
- method
- Schorger 1955; Smithsonian.
- range
- 3–5 billion pre-decline
- weakness
- none material.
- dispute
- dispute LGR-101 · corrections are credited
LGR-102 v0.1.0modelcount
american bison Bison bison
born 1950 25 000 → 500 000 individuals about 20× as many as when you were born. from tens of millions to 325 in 1884. half a million now, and most of them are on ranches, for meat. about 30,000 are wild. saved by being farmed. that is either a rescue or a joke, and the ledger cannot tell you which.
born 1970 30 000 → 500 000 individuals about 16.7× as many as when you were born. from tens of millions to 325 in 1884. half a million now, and most of them are on ranches, for meat. about 30,000 are wild. saved by being farmed. that is either a rescue or a joke, and the ledger cannot tell you which.
born 1990 243 333 → 500 000 individuals about 2.1× as many as when you were born. from tens of millions to 325 in 1884. half a million now, and most of them are on ranches, for meat. about 30,000 are wild. saved by being farmed. that is either a rescue or a joke, and the ledger cannot tell you which.
born 2010 425 000 → 500 000 individuals about 1.2× as many as when you were born. from tens of millions to 325 in 1884. half a million now, and most of them are on ranches, for meat. about 30,000 are wild. saved by being farmed. that is either a rescue or a joke, and the ledger cannot tell you which.
- method
- Hornaday 1889 (325 in 1884); NPS and USDA census for later years, interpolated.
- range
- ±20% on early anchors
- weakness
- 'wild' vs 'ranched' is stated on screen; most of the recovery is ranched.
- dispute
- dispute LGR-102 · corrections are credited
LGR-103 v0.1.0modelcount
whale oil what saved them the first time
everyone petroleum saved the whales the first time. kerosene undercut whale oil for lamps in the 1860s and the yankee fleet went home. then diesel ships and the exploding harpoon nearly finished them a century later. the same fuel, twice, in opposite directions. the ledger does not have heroes.
- method
- historical: Starbuck 1878; Tønnessen & Johnsen 1982.
- range
- n/a
- weakness
- none material.
- dispute
- dispute LGR-103 · corrections are credited
LGR-104 v0.1.0modelestimate
ivory and plastic billiard balls
everyone billiard balls needed ivory. a $10,000 prize for a substitute produced celluloid in 1869, the first plastic. plastic was invented to save elephants. it now weighs about twice as much as every animal on earth combined. and elephants are still poached for ivory, about fifteen to twenty thousand a year.
- method
- Meikle 1995 (celluloid); Elhacham et al. 2020 (anthropogenic mass vs biomass); Geyer et al. 2017; CITES MIKE for poaching.
- range
- plastic ~8 Gt cumulative vs animal biomass ~4 Gt wet
- weakness
- the 'twice' compares cumulative plastic ever made with living animal mass; both are estimates.
- dispute
- dispute LGR-104 · corrections are credited
LGR-105 v0.1.0modelcount
the red in your yoghurt cochineal and lac
everyone the red in strawberry yoghurt, lipstick and campari was, until recently, crushed beetles: about 70,000 cochineal insects for a pound of dye. the shine on apples and jelly beans is shellac, from the lac bug. carmine is still legal and still used. it is listed as e120. it does not say bug.
- method
- FDA regulations on carmine; Reisenman 2015 on cochineal yield.
- range
- 70,000 insects per pound is the standard figure
- weakness
- many brands have switched to plant reds; 'until recently' is doing work.
- dispute
- dispute LGR-105 · corrections are credited
LGR-106 v0.1.0modelcount
almonds two million hives on flatbeds
everyone every february about two million beehives are trucked to california to pollinate almonds: most of the honeybees in the united states, on the interstate. beekeepers lose about 40% of their colonies a year and rebuild them by splitting. a third of what you eat, by variety, depends on a pollinator. most of them are not honeybees, and nobody trucks the wild ones anywhere.
- method
- USDA NASS pollination data; Bee Informed Partnership annual loss survey; Klein et al. 2007.
- range
- 1.8–2.5 million hives; 30–48% annual loss
- weakness
- 'a third of what you eat' is by crop variety, not calories, and the site says so.
- dispute
- dispute LGR-106 · corrections are credited
LGR-107 v0.1.0modelcount
cod newfoundland, 1992
everyone newfoundland’s cod were fished for five hundred years. they collapsed in 1992. thirty thousand people lost their work in a day. the moratorium is still mostly in force. the cod are still mostly not back. stopping too late is a different thing from stopping.
- method
- Hutchings & Myers 1994; DFO Canada.
- range
- n/a
- weakness
- a limited fishery reopened in 2024; 'mostly' carries that.
- dispute
- dispute LGR-107 · corrections are credited
LGR-108 v0.1.0modelestimate
lake victoria the nile perch
everyone the nile perch was put into lake victoria in the 1950s to improve the fishing. it ate about 200 species of fish that lived nowhere else. the perch is filleted for europe. the frames are dried and sold to the people who caught them. the largest extinction of vertebrates in modern times, and it was done on purpose, to help.
- method
- Witte et al. 1992; Pringle 2005.
- range
- ~200 endemic cichlids lost or presumed
- weakness
- some species survive in refugia; counts vary.
- dispute
- dispute LGR-108 · corrections are credited
LGR-109 v0.1.0modelestimate
bear bile about 12,000 bears
everyone about 12,000 bears live in cages in china and vietnam with a tube or an open wound in the gallbladder, milked for bile. the active ingredient, ursodeoxycholic acid, has been made in a laboratory since 1954 and is in every pharmacy. vietnam agreed to close its farms in 2017. china has not.
- method
- Animals Asia; Feng et al. 2009.
- range
- 10,000–12,000 bears
- weakness
- no registry; NGO counts.
- dispute
- dispute LGR-109 · corrections are credited
LGR-144 v0.1.0modelmodel
every roof if every suitable roof on earth had panels
everyone every suitable roof on earth would generate about 27,000 terawatt-hours a year: about as much electricity as the world uses. not every hour. the sun sets. that is the storage problem, and it is the whole problem. france made it law in 2023: any car park with more than eighty spaces gets a solar roof. the united states could make about two fifths of its electricity from roofs alone. no new land, no new holes.
- method
- Joshi et al. 2021: global rooftop PV technical potential ~27 PWh/yr; NREL 2016 for the US share.
- range
- technical potential 20–30 PWh/yr; economic potential lower
- weakness
- technical potential is not deliverable electricity: night, seasons and storage are the gap, and the screen says so.
- dispute
- dispute LGR-144 · corrections are credited
LGR-145 v0.1.0modelestimate
the cost of a panel what it takes, what it gives
everyone 20–50 → 820 a solar panel emits about 20 to 50 grams of co2 for every kilowatt-hour it will ever make, almost all of it before it is switched on. coal makes the same kilowatt-hour for about 820, gas for about 490. the panel repays its own energy in one to two years and runs for thirty. not zero, and the ledger will not pretend. about 78 million tonnes of dead panels by 2050, and a supply chain that runs through xinjiang. it still wins by a factor of ten to forty. both halves are true.
- method
- lifecycle CO2 per kWh from IPCC AR5 harmonized medians (PV ~48, falling toward ~20 in recent studies; coal 820; gas 490); energy payback from Fraunhofer ISE.
- range
- PV 15–60 gCO2/kWh depending on grid of manufacture and irradiance
- weakness
- lifecycle numbers depend on where the panel is made and where it is used; the ratio to coal is robust, the exact grams are not.
- dispute
- dispute LGR-145 · corrections are credited
LGR-146 v0.1.0modelestimate
the deadliest animals people killed a year, by animal
everyone mosquito 700,000 · human 460,000 · snake 100,000 · dog 59,000 · sandfly 25,000 · freshwater snail 12,000 · assassin bug 10,000 · scorpion 3,000 · crocodile 1,000 · hippo 500 · elephant 500 · lion 200 · wolf 10 · shark 10. the mosquito does it with a parasite and a virus. we do it with our hands. everything below the human is a rounding error next to the top two.
- method
- as the animals channel; the human figure is UNODC homicide.
- range
- n/a
- weakness
- the small counts (wolf, shark, lion) vary year to year by a factor of two.
- dispute
- dispute LGR-146 · corrections are credited
LGR-147 v0.1.0modelestimate
modern slavery about 50 million people, today
everyone about 50 million people are in slavery today: 28 million in forced labour, 22 million in forced marriage. more than at any point in history, by count. some of them are on the boats. forced labour in fishing is documented in the fleets that supply the fish channel. some of them picked the cotton. the ledger connects.
- method
- ILO / Walk Free / IOM Global Estimates of Modern Slavery 2022.
- range
- 45–55 million
- weakness
- survey-based estimates in a hidden population; the direction is not in doubt.
- dispute
- dispute LGR-147 · corrections are credited
LGR-148 v0.1.0modelestimate
bobby calves what a bobby is, and what happens to the sons
everyone a bobby calf is a dairy farm’s male calf, a few days old. a cow only gives milk after she has calved, so a dairy herd makes about a calf per cow per year, and half of them are sons: on the order of a hundred million male dairy calves a year, worldwide. none can make milk. dairy breeds grow too slowly for good beef. so almost all are killed young. in new zealand and australia, most within days: a few million bobby calves a year. in britain, tens of thousands a year were shot on the farm at birth until the industry stopped routine on-farm killing in 2023. in europe and north america, most go to veal at a few months, or to “dairy beef” within a year or two. a cow can live twenty years. her sons rarely see one. milk has a body count; it is just not the animal you are drinking from.
- method
- FAO dairy cow numbers (~270 million) × calving rate (~0.85) × half male; national figures from MPI NZ, Dairy Australia, AHDB.
- range
- 90–130 million male dairy calves/yr
- weakness
- the fate split (days / veal / dairy-beef) varies by country and is stated as such; 'almost all killed young' is true everywhere, the age is not.
- dispute
- dispute LGR-148 · corrections are credited
LGR-149 v0.1.0modelmodel
someone born in 1955 an average life so far, at the world average · if they eat meat
everyone 49 700 → 2.3 someone born in 1955 is about 71. if they eat meat, roughly like the world average, they have consumed a piece of at least 49 700 different living things, and about 1.8 tonnes of meat and 0.5 tonnes of fish have passed through them. to feed them, about 436 land animals and 20 714 sea animals were killed outright, and eggs and dairy add about 77. a us or australian eater of the same age: two to three times the animals, three times the mass. type your own year, top right, and the site stops averaging you.
- method
- as 'your share', for a fixed birth year: world-average per-capita slaughter, catch and food supply integrated from that year to now.
- range
- meals ±30%; mass ±20%; sea count on a 1–2.2 trillion/yr basis
- weakness
- a world-average person of that age; nobody is average. the point is the size, not the decimals.
- dispute
- dispute LGR-149 · corrections are credited
LGR-150 v0.1.0modelmodel
someone born in 1972 an average life so far, at the world average · if they eat meat
everyone 37 800 → 1.9 someone born in 1972 is about 54. if they eat meat, roughly like the world average, they have consumed a piece of at least 37 800 different living things, and about 1.5 tonnes of meat and 0.4 tonnes of fish have passed through them. to feed them, about 388 land animals and 16 360 sea animals were killed outright, and eggs and dairy add about 60. a us or australian eater of the same age: two to three times the animals, three times the mass. type your own year, top right, and the site stops averaging you.
- method
- as 'someone born in 1955'.
- range
- as above
- weakness
- as above.
- dispute
- dispute LGR-150 · corrections are credited
LGR-151 v0.1.0modelmodel
someone born in 1988 an average life so far, at the world average · if they eat meat
everyone 26 600 → 1.4 someone born in 1988 is about 38. if they eat meat, roughly like the world average, they have consumed a piece of at least 26 600 different living things, and about 1.1 tonnes of meat and 0.3 tonnes of fish have passed through them. to feed them, about 318 land animals and 11 836 sea animals were killed outright, and eggs and dairy add about 43. a us or australian eater of the same age: two to three times the animals, three times the mass. type your own year, top right, and the site stops averaging you.
- method
- as 'someone born in 1955'.
- range
- as above
- weakness
- as above.
- dispute
- dispute LGR-151 · corrections are credited
LGR-152 v0.1.0modelmodel
someone born in 2004 an average life so far, at the world average · if they eat meat
everyone 15 400 → 0.9 someone born in 2004 is about 22. if they eat meat, roughly like the world average, they have consumed a piece of at least 15 400 different living things, and about 0.7 tonnes of meat and 0.2 tonnes of fish have passed through them. to feed them, about 210 land animals and 6 942 sea animals were killed outright, and eggs and dairy add about 25. a us or australian eater of the same age: two to three times the animals, three times the mass. type your own year, top right, and the site stops averaging you.
- method
- as 'someone born in 1955'.
- range
- as above
- weakness
- as above.
- dispute
- dispute LGR-152 · corrections are credited
LGR-153 v0.1.0modelestimate
wild animals average change in monitored populations
born 1950 100 → 23 index, 1970 = 100 wild vertebrate populations are on average about 77% smaller than in 1970. before that, nobody was keeping the index. an average of population trends, not a count of animals. habitat loss to farming is the largest driver on land; fishing at sea.
born 1970 100 → 23 index, 1970 = 100 wild vertebrate populations are on average about 77% smaller than when you were born. an average of population trends, not a count of animals. habitat loss to farming is the largest driver on land; fishing at sea.
born 1990 59 → 23 index, 1970 = 100 wild vertebrate populations are on average about 61% smaller than when you were born. an average of population trends, not a count of animals. habitat loss to farming is the largest driver on land; fishing at sea.
born 2010 35 → 23 index, 1970 = 100 wild vertebrate populations are on average about 34% smaller than when you were born. an average of population trends, not a count of animals. habitat loss to farming is the largest driver on land; fishing at sea.
- method
- WWF Living Planet Index 2024, 1970 = 1, interpolated.
- range
- index CI roughly ±10 points
- weakness
- an average of population trends, not a count of animals; the site says so on screen.
- dispute
- dispute LGR-153 · corrections are credited
LGR-154 v0.1.0modelestimate
mammals, by weight everything with fur, warm blood and milk
everyone of all mammal life on earth, by weight: 62% is livestock. 34% is us. 4% is wild. chickens outweigh every wild bird on earth about three to one. this is not a model or a projection. it is a census.
- method
- Bar-On, Phillips & Milo 2018 biomass census.
- range
- ±10% on shares
- weakness
- none material.
- dispute
- dispute LGR-154 · corrections are credited
LGR-155 v0.1.0modelcount
wildfire the honest version
everyone there is less fire on earth than twenty years ago. that is true. it is not the whole story. africa: burned area down by roughly a quarter worldwide since the early 2000s, almost all of it savanna that became farmland and fenceline. fewer fires, more fields. western north america: forest area burned has more than doubled since the mid-1980s. warmer, drier, longer seasons. boreal canada and siberia: record carbon from fire in 2021 and 2023. the forest is burning hotter and further north. the amazon and cerrado: fires here are not weather. they are lit, to clear land for cattle and soy. the forest is here; the beef is elsewhere. fewer fires, and worse ones, in different places, for different reasons. this site will always show the region.
- method
- Andela et al. 2017 (global burned area trend); Abatzoglou & Williams 2016; Copernicus CAMS; INPE.
- range
- n/a
- weakness
- regional statements are summarised; each wants its own series.
- dispute
- dispute LGR-155 · corrections are credited
undefined v0.1.0modeln/a
model to feed the roadmap
everyone every number here is a model until it is a feed. the flips, in order: fires (NASA FIRMS), trawlers at sea right now (Global Fishing Watch), satellites (Space-Track), daily slaughter (USDA, then others), air in ten thousand cities (OpenAQ), the sea (NOAA, daily), forest alerts (GLAD). each channel wears a badge in the corner: model or feed. the site gets more true every month, and says so. anyone who finds an error in a number is credited, in public, with their name on the changelog.
- method
- the roadmap.
- range
- n/a
- weakness
- n/a
- dispute
- dispute undefined · corrections are credited
what one person can do
LGR-110 v0.1.0modelestimate
if you stopped eating meat one person, one year · world average · order of magnitude
everyone 0.8 → 800 000 tonnes co2e about 0.8 tonnes of co2e. about 10 land animals and 300 from the sea. about 0.4 hectares of land and 600,000 litres of water. a year, at the world average; a us or australian eater, about double. for scale: about 100% of a year without meat. this is the yardstick. every other screen in this set is measured against it.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017; Poore & Nemecek 2018; Vanham et al. 2013), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-110 · corrections are credited
LGR-111 v0.1.0modelestimate
if you ate half as much meat one person, one year · world average · order of magnitude
everyone 0.4 → 400 000 tonnes co2e about 0.4 tonnes of co2e, 5 land animals and 150 from the sea, a year. for scale: about 50% of a year without meat. half the meat is half the ledger. it is also the change most people actually make.
- method
- per-person, per-year estimate from the cited study (Poore & Nemecek 2018), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-111 · corrections are credited
LGR-112 v0.1.0modelestimate
if you skipped meat one day a week one person, one year · world average · order of magnitude
everyone 0.11 → 110 000 tonnes co2e about 0.11 tonnes of co2e, 1.5 land animals and 45 from the sea, a year. a seventh of the yardstick. for scale: about 14% of a year without meat. small and real. mostly it teaches you the other six days are a choice too.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-112 · corrections are credited
LGR-113 v0.1.0modelestimate
if you gave up beef and lamb only one person, one year · world average · order of magnitude
everyone 0.5 → 500 000 tonnes co2e about 0.5 tonnes of co2e and a quarter of a hectare of land, a year. and a small fraction of one cow. for scale: about 60% of a year without meat. beef is most of the carbon and almost none of the animals. chicken is the reverse. the ledger counts both.
- method
- per-person, per-year estimate from the cited study (Poore & Nemecek 2018), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-113 · corrections are credited
LGR-114 v0.1.0modelestimate
if you swapped beef for chicken one person, one year · world average · order of magnitude
everyone 0.4 → 400 000 tonnes co2e less about 0.4 tonnes less co2e a year. and about 20 more animals killed. one cow feeds a thousand meals; a chicken feeds six. for scale: about 50% of a year without meat. the ledger counts both. choose your unit.
- method
- per-person, per-year estimate from the cited study (Poore & Nemecek 2018; FAO), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-114 · corrections are credited
LGR-115 v0.1.0modelestimate
if you gave up dairy one person, one year · world average · order of magnitude
everyone 0.3 → 300 000 tonnes co2e about 0.3 tonnes of co2e a year, about 100,000 litres of water, and a share of a bobby calf: a dairy farm’s male calf, killed young because he cannot make milk. see: bobby calves. for scale: about 35% of a year without meat. the calves are the part nobody sees. a cow must calve to give milk; half the calves are sons; the sons go.
- method
- per-person, per-year estimate from the cited study (Poore & Nemecek 2018; Mekonnen & Hoekstra 2012), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-115 · corrections are credited
LGR-116 v0.1.0modelestimate
if you gave up shrimp one person, one year · world average · order of magnitude
everyone 55 → 55 million sea animals about 55 animals a year at the world average, and closer to 150 for an american. for scale: about 18% of a year without meat. one shrimp cocktail is more lives than a year of beef.
- method
- per-person, per-year estimate from the cited study (fishcount.org.uk; NOAA per-capita consumption), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-116 · corrections are credited
LGR-117 v0.1.0modelestimate
if you wasted no food one person, one year · world average · order of magnitude
everyone 0.3 → 300 000 tonnes co2e about 0.3 tonnes of co2e and about 74 kilograms of food a year. a third of all food is wasted. if food waste were a country it would be the third emitter. for scale: about 37% of a year without meat. the animals in the wasted meat died for nothing at all, and the ledger already counted them.
- method
- per-person, per-year estimate from the cited study (UNEP Food Waste Index 2021; FAO 2013), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-117 · corrections are credited
LGR-118 v0.1.0modelestimate
if you took one fewer long-haul flight a year one person, one year · world average · order of magnitude
everyone 1.6 → 2 million tonnes co2e about 1.6 tonnes of co2e. one return flight. twice a year without meat. for scale: about 200% of a year without meat. the largest single thing on this list that most people can do in an afternoon: not book it.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-118 · corrections are credited
LGR-119 v0.1.0modelestimate
if you flew economy instead of business one person, one year · world average · order of magnitude
everyone 1.1 → 1 million tonnes co2e a business seat is about three times an economy seat, by space. on a long-haul return that is about 1.1 tonnes of co2e saved. for scale: about 140% of a year without meat. the plane is going anyway. the seat is the share you buy.
- method
- per-person, per-year estimate from the cited study (ICAO carbon calculator; DEFRA factors), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-119 · corrections are credited
LGR-120 v0.1.0modelestimate
if you put solar on your roof one person, one year · world average · order of magnitude
everyone 2.4 → 2 million tonnes co2e a typical home system, about five kilowatts, makes about 6,000 kilowatt-hours a year: about 2.4 tonnes of co2e on an average grid. the same as living without a car. for scale: about 300% of a year without meat. on a coal grid, double that. on a hydro grid, almost nothing. it repays the carbon it took to make in one to two years and runs for thirty. see: the cost of a panel.
- method
- per-person, per-year estimate from the cited study (NREL PVWatts; IEA grid factors; Fraunhofer ISE 2024), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-120 · corrections are credited
LGR-121 v0.1.0modelestimate
if you lived without a car one person, one year · world average · order of magnitude
everyone 2.4 → 2 million tonnes co2e about 2.4 tonnes of co2e a year. three years without meat. for scale: about 300% of a year without meat. the biggest thing on this list. it depends entirely on where you live, and that is not your fault.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-121 · corrections are credited
LGR-122 v0.1.0modelestimate
if you drove ten kilometres less a week one person, one year · world average · order of magnitude
everyone 0.1 → 100 000 tonnes co2e about 0.1 tonnes of co2e a year. for scale: about 12% of a year without meat. a walk. a bus. a call instead.
- method
- per-person, per-year estimate from the cited study (DEFRA factors), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-122 · corrections are credited
LGR-123 v0.1.0modelestimate
if you switched to a real renewable electricity tariff one person, one year · world average · order of magnitude
everyone 1.5 → 2 million tonnes co2e about 1.5 tonnes of co2e a year, on an average grid. if the tariff is real. for scale: about 190% of a year without meat. some tariffs buy certificates and change nothing. ask what they build.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017; UK BEIS), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-123 · corrections are credited
LGR-124 v0.1.0modelestimate
if you insulated, or put in a heat pump one person, one year · world average · order of magnitude
everyone 2 → 2 million tonnes co2e one to three tonnes of co2e a year, for a house heated with gas or oil. for scale: about 250% of a year without meat. the biggest thing most people can do to a building. it costs money once and pays for years.
- method
- per-person, per-year estimate from the cited study (IEA; UK Energy Saving Trust), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-124 · corrections are credited
LGR-125 v0.1.0modelestimate
if you turned the thermostat down one degree one person, one year · world average · order of magnitude
everyone 0.1 → 100 000 tonnes co2e about 0.1 tonnes of co2e a year, per person, in a heated house. for scale: about 12% of a year without meat. wear a sweater instead.
- method
- per-person, per-year estimate from the cited study (UK Energy Saving Trust), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-125 · corrections are credited
LGR-126 v0.1.0modelestimate
if you hung the washing instead of using a dryer one person, one year · world average · order of magnitude
everyone 0.07 → 70 000 tonnes co2e about 70 kilograms of co2e a year, per person. for scale: about 9% of a year without meat. the dryer is the second-hungriest thing in the house after heating.
- method
- per-person, per-year estimate from the cited study (US DOE; Energy Star), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-126 · corrections are credited
LGR-127 v0.1.0modelestimate
if you washed clothes cold one person, one year · world average · order of magnitude
everyone 0.03 → 30 000 tonnes co2e about 30 kilograms of co2e a year. for scale: about 4% of a year without meat. ninety percent of the energy of a wash is heating the water. the clothes do not know.
- method
- per-person, per-year estimate from the cited study (US DOE), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-127 · corrections are credited
LGR-128 v0.1.0modelestimate
if you washed your hair one time fewer a week one person, one year · world average · order of magnitude
everyone 2 000 → 2 billion litres of water about 2,000 litres of water and about 25 kilograms of co2e a year. for scale: about 3% of a year without meat. the water is heated. that is where the carbon is.
- method
- per-person, per-year estimate from the cited study (EPA WaterSense; DEFRA factors), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-128 · corrections are credited
LGR-129 v0.1.0modelestimate
if you took showers a minute shorter one person, one year · world average · order of magnitude
everyone 3 300 → 3.3 billion litres of water about 3,300 litres of water and about 22 kilograms of co2e a year. for scale: about 3% of a year without meat. small. free. and in a dry place the water is the number that matters, not the carbon.
- method
- per-person, per-year estimate from the cited study (EPA WaterSense), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-129 · corrections are credited
LGR-130 v0.1.0modelestimate
if you turned the tap off while brushing one person, one year · world average · order of magnitude
everyone 8 700 → 8.7 billion litres of water about 8,700 litres of water a year. almost no carbon: it is cold water. for scale: about 0% of a year without meat on carbon. water, not carbon. this list has two currencies and this one is only in one of them.
- method
- per-person, per-year estimate from the cited study (EPA WaterSense), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-130 · corrections are credited
LGR-131 v0.1.0modelestimate
if you shook your hands dry instead of a paper towel one person, one year · world average · order of magnitude
everyone 16 → 16 million kilograms co2e about 2,000 towels and about 16 kilograms of co2e a year. for scale: about 2% of a year without meat. small. true. do it anyway; it is free, and it costs nothing to be honest about the size.
- method
- per-person, per-year estimate from the cited study (Gregory et al. 2011, MIT), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-131 · corrections are credited
LGR-132 v0.1.0modelestimate
if you used a refillable bottle one person, one year · world average · order of magnitude
everyone 15 → 15 million kilograms co2e about 150 bottles, 3 kilograms of plastic and about 15 kilograms of co2e a year. for scale: about 2% of a year without meat. the bottle is not the problem; it is one of the smaller ones. it is also the easiest.
- method
- per-person, per-year estimate from the cited study (Franklin Associates; DEFRA), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-132 · corrections are credited
LGR-133 v0.1.0modelestimate
if you kept your phone one more year one person, one year · world average · order of magnitude
everyone 30 → 30 million kilograms co2e about 30 kilograms of co2e a year, and about sixty elements left in the ground. for scale: about 4% of a year without meat. most of a phone’s footprint is making it, not using it. see: mines.
- method
- per-person, per-year estimate from the cited study (Apple / Fairphone LCAs; USGS), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-133 · corrections are credited
LGR-134 v0.1.0modelestimate
if you bought no new clothes for a year one person, one year · world average · order of magnitude
everyone 250 → 250 million kilograms co2e about 250 kilograms of co2e, and about 2,700 litres of water for every cotton t-shirt not bought. for scale: about 30% of a year without meat. the average garment is worn about seven times. second-hand counts as zero here.
- method
- per-person, per-year estimate from the cited study (Quantis 2018; WRAP; WWF), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-134 · corrections are credited
LGR-135 v0.1.0modelestimate
if you used a cotton tote instead of plastic bags one person, one year · world average · order of magnitude
everyone 0 → 0 a cotton bag has to be used about 7,000 times to beat a plastic bag on climate. organic cotton, about 20,000. for scale: about 0% of a year without meat on carbon. use the bag you already own until it falls apart, whatever it is made of. that is the whole trick.
- method
- per-person, per-year estimate from the cited study (Danish EPA 2018), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-135 · corrections are credited
LGR-136 v0.1.0modelestimate
if you ran the dishwasher full instead of washing by hand one person, one year · world average · order of magnitude
everyone 20 000 → 20 billion litres of water about 20,000 litres of water a year. a full machine uses about twelve litres; hands use sixty or more. for scale: about 2% of a year without meat. run the machine. full. this is one of the few places where the lazier thing is the better one.
- method
- per-person, per-year estimate from the cited study (Energy Star; Stamminger 2004), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-136 · corrections are credited
LGR-137 v0.1.0modelestimate
if you recycled everything one person, one year · world average · order of magnitude
everyone 0.2 → 200 000 tonnes co2e about 0.2 tonnes of co2e a year. for scale: about 26% of a year without meat. useful. less than the packaging suggests, and a quarter of a year without meat.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-137 · corrections are credited
LGR-138 v0.1.0modelestimate
if you ate local one person, one year · world average · order of magnitude
everyone 0.05 → 50 000 tonnes co2e about 0.05 tonnes of co2e a year. transport is about five percent of food’s footprint. for scale: about 6% of a year without meat. what you eat matters about ten times more than where it came from. local beef is beef.
- method
- per-person, per-year estimate from the cited study (Poore & Nemecek 2018), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-138 · corrections are credited
LGR-139 v0.1.0modelestimate
if you planted a tree one person, one year · world average · order of magnitude
everyone 20 → 20 million kilograms co2 a year, once grown about 20 kilograms of co2 a year, for decades, once it is grown. about a week of driving. for scale: about 3% of a year without meat. plant it anyway. plant many. do not plant it instead of the flight.
- method
- per-person, per-year estimate from the cited study (US Forest Service; Bastin et al. 2019 (and its critics)), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-139 · corrections are credited
LGR-140 v0.1.0modelestimate
if you composted one person, one year · world average · order of magnitude
everyone 50 → 50 million kilograms co2e about 50 kilograms of co2e a year: food in landfill makes methane, food in a heap makes soil. for scale: about 6% of a year without meat. see: soil.
- method
- per-person, per-year estimate from the cited study (US EPA WARM), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-140 · corrections are credited
LGR-141 v0.1.0modelestimate
if you switched the bulbs to led one person, one year · world average · order of magnitude
everyone 50 → 50 million kilograms co2e about 50 kilograms of co2e a year, per person, in a house that had not already. for scale: about 6% of a year without meat. nearly everyone already has. the easy ones get done first.
- method
- per-person, per-year estimate from the cited study (US DOE), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-141 · corrections are credited
LGR-142 v0.1.0modelestimate
if you kept your cat indoors one person, one year · world average · order of magnitude
everyone 40 → 40 million birds and small mammals on the order of dozens of birds and small mammals a year, per cat. not on the carbon ledger at all. for scale: about 0% of a year without meat on carbon. see: what cats kill. the cat is fine indoors. the birds are fine outdoors.
- method
- per-person, per-year estimate from the cited study (Loss et al. 2013; Kays et al. 2020), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-142 · corrections are credited
LGR-143 v0.1.0modelestimate
what one person can do, ranked tonnes of co2e a year, world average
everyone car-free 2.4 · solar on the roof 2.4 · insulate or heat pump 2 · one fewer long flight 1.6 · a real green tariff 1.5 · no meat 0.8 · no beef 0.5 · half the meat 0.4 · no food waste 0.3 · no dairy 0.3 · no new clothes 0.25 · recycle everything 0.2 · thermostat down 0.1 · hang the washing 0.07 · eat local 0.05 · compost 0.05 · led bulbs 0.05 · cold wash 0.03 · keep the phone 0.03 · hair, showers, towels, bottles, taps 0.02 and under. the top six are worth more than everything below them combined. the animals are a different ledger: no meat and no shrimp are the whole of it. the ledger does not tell you what to do. it tells you what it is worth.
- method
- per-person, per-year estimate from the cited study (Wynes & Nicholas 2017; Poore & Nemecek 2018; the sources on each screen), world-average where the study allows; the million-people column is straight multiplication. 'for scale' divides by 0.8 t CO2e, the meat-free yardstick.
- range
- roughly ±50%: households, grids and countries differ widely
- weakness
- a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- dispute
- dispute LGR-143 · corrections are credited
weaknesses
The page nobody expects. Where the data is thin, what was assumed, and what would change the number. Every entry links to its channel.
- chickens: FAO under-reports backyard slaughter in parts of Asia and Africa; hatchery culling has no official global series.
- farmed shrimp: tonnage-to-count conversion depends on assumed mean weight at harvest; the site uses the midpoint.
- farmed fish: mean weights per species are themselves estimates; hatchery-to-harvest survival varies widely.
- ducks: most ducks are slaughtered in China; reporting granularity is coarse.
- pigs: pre-weaning mortality is taken from industry data in a few countries and applied globally.
- rabbits: reporting is thin outside China and Europe.
- geese: as ducks.
- sheep: informal slaughter under-reported.
- goats: informal slaughter under-reported.
- cattle: the 'alive right now' figure excludes dairy and breeding animals by design and should be read as the queue.
- wild-caught fish: the widest range on the site. excludes illegal, unreported and unregulated catch, which is substantial. the site uses ~2.0 trillion; the low end halves the number.
- sharks: a decade old; more recent work (Worm et al. 2024) suggests mortality has not fallen despite regulation.
- dogs: no official statistics anywhere. treat as order of magnitude.
- cats and dogs: united states only; the site says so in the label. no global series exists.
- trophies: trade records undercount trophies kept in-country; the lion-farm figures are NGO estimates the south african government has broadly confirmed.
- pangolins: seizure-based; the true trade is larger by an unknown factor.
- songbirds: illegal by definition, so estimated from surveys and enforcement data; excludes legal hunting, which is larger.
- donkeys: trade is partly informal; the 'half in five years' line is a straight-line projection, stated as such.
- silkworms: cocoons-per-kg varies by strain; the site uses the top of the range. insects are counted on this ledger; some will object.
- farmed insects: industry data are sparse and growing fast; the projection is the industry's own.
- horseshoe crabs: post-release mortality is estimated, not observed.
- seahorses: trade is largely undocumented; the figure is a decade old.
- frogs: conversion from tonnes to individuals depends on species mix; excludes domestic consumption in asia.
- whales: birth number depends on population estimates that carry ±30% error.
- chickens, ducks, turkeys: outbreak years differ tenfold; the annual figure is an average, not a rate.
- badgers: the cull is being wound down; the rate will fall. whether it reduces bovine TB is scientifically contested and the site says so.
- fertilizer: 'lost to air and water' applies a nitrogen efficiency figure to total nutrients, which overstates phosphate and potash losses; the order of magnitude holds.
- pesticides: tonnage is not toxicity, and the site says so on screen. poisoning figure is a systematic review estimate.
- reservoirs: depends on reservoir surface area and climate data; the livestock water share is from a different study (Mekonnen & Hoekstra).
- groundwater: regional depletion is well measured; global sums are less certain.
- forest: FAO relies on national reporting; satellite products (GFW) show higher loss. 'regrown' includes plantations.
- foie gras: a subset of the ducks channel; explicitly not added to the total.
- what cats kill: the widest range on the animal side of the site; explicitly not counted in the killed-by-humans total.
- carbon: 'captured by machines' excludes CCS at point sources (~45 Mt/yr), which is a different thing; the site compares air to air.
- soil: both sides are modeled; the ratio (about 25×) is more robust than either number.
- mines: tailings tonnage is derived, not reported; ASGM mercury is by nature informal.
- data centres: changing fast; the number should be a feed within a year. the site's own footprint is not measured, only acknowledged.
- concrete: concrete tonnage is inferred from cement; the 'weight of every living thing' comparison is Elhacham 2020 (biomass ~4 Gt wet).
- shipping: the warming effect of the sulphur cap is a modeled attribution, in the tens of hundredths of a degree over decades; stated as measurable, not large.
- cruise ships: discharge is estimated from per-passenger figures, not measured at sea.
- manure: wet vs dry weight is a factor of several; the site uses fresh weight for both sides.
- solar: annual figures; both are moving fast in opposite directions, so this channel dates quickly and should be a feed.
- satellites: changes monthly; this is the channel most in need of a feed.
- extinctions: the largest disagreement on the site, by design shown as two columns. the ticking number is a stand-in for a range that spans two orders of magnitude.
- humans: excludes chronic disease and self-poisoning (110,000–168,000/yr, Mew et al. 2017), which lives here and not on the front door, handled with care.
- humans: attribution models differ; the site uses the order of magnitude and says so.
- humans: attributes vector-borne disease deaths to the vector; the parasite does the killing. the large-animal counts are order of magnitude.
- humans: conflict counts lag by years and vary by source by a factor of two.
- humans: many countries under-report; WHO models the gap.
- humans: attributable-fraction estimate; the strongest such estimate in epidemiology.
- humans: attributable-fraction estimates; drug deaths are undercounted where they are criminal.
- humans: attribution of hepatitis B deaths to sexual transmission is partial; the site counts a share.
- humans: the widest range on the human side of the site, by design shown as a dash for 'the true number'.
- humans: attributable-fraction estimate; diarrhoeal deaths are also falling fast, so this dates.
- humans: occupational disease attribution is modeled; the fishing figure is an NGO estimate several times the old official one.
- humans: 'hunger-related' includes deaths where undernutrition is a contributing cause; the number is contested and the site rounds.
- humans: attribution studies cover a subset of countries; the site applies the share globally.
- humans: the farm-antibiotic share is unquantified, and the site shows a dash rather than a number.
- the amazon: a stand-in number until wired. clearly badged.
- the sea: food-system share of warming (a quarter to a third) is from emissions share (Crippa 2021), not a warming attribution study.
- the ozone hole: a single-year value is noisy; the trend is not.
- humpback whales: decade anchors, interpolated. wants a proper series.
- the aral sea: the sea has fragmented; 'area' is the sum of the remnants.
- dead zones: a count of known sites rises with monitoring effort as well as with pollution.
- drug resistance: no data before 1990, shown as a dash.
- european bison: interpolated between anchors.
- eurasian beavers: early-century numbers are reconstructions.
- wolves in europe: pre-1990 anchors are rough.
- costa rica: definitions of 'forest' changed over the century.
- europe’s forests: 'roughly the UK' is a size analogy; the UK is 24 Mha.
- the land: a scenario, not a prediction, and shown as 'if we stopped'.
- london’s air: two different metrics stitched together; the shape is robust, the exact ratio is not.
- the smoke: London 1890 is a reconstruction (Fouquet).
- polio: the pre-1988 numbers are estimates and labelled so.
- measles: pre-vaccine figures are estimates.
- plague: reporting varies; Madagascar dominates.
- tuberculosis: no global series before 1990.
- where diseases come from: COVID origin stated as 'most likely' per Worobey et al. 2022; contested.
- blue whales: global count is poorly known; Antarctic population best studied.
- tigers: 1900 figure is a widely repeated estimate, not a count.
- african elephants: forest elephants poorly counted.
- giant pandas: survey intervals of a decade.
- your share: the distinct-animals count is a floor by construction; the true number is unknowable because meat is pooled. world average until a country is set.
- shelters: 1970s figures are ranges (13–20 million); the site uses the low end.
- lions and tigers: captive counts are NGO estimates; no registry exists in the US.
- vultures: a difference-in-differences estimate; causal, contested at the margins, large in any version.
- sparrows: the famine had many causes; the site says so.
- american bison: 'wild' vs 'ranched' is stated on screen; most of the recovery is ranched.
- ivory and plastic: the 'twice' compares cumulative plastic ever made with living animal mass; both are estimates.
- the red in your yoghurt: many brands have switched to plant reds; 'until recently' is doing work.
- almonds: 'a third of what you eat' is by crop variety, not calories, and the site says so.
- cod: a limited fishery reopened in 2024; 'mostly' carries that.
- lake victoria: some species survive in refugia; counts vary.
- bear bile: no registry; NGO counts.
- if you stopped eating meat: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you ate half as much meat: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you skipped meat one day a week: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you gave up beef and lamb only: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you swapped beef for chicken: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you gave up dairy: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you gave up shrimp: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you wasted no food: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you took one fewer long-haul flight a year: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you flew economy instead of business: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you put solar on your roof: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you lived without a car: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you drove ten kilometres less a week: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you switched to a real renewable electricity tariff: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you insulated, or put in a heat pump: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you turned the thermostat down one degree: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you hung the washing instead of using a dryer: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you washed clothes cold: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you washed your hair one time fewer a week: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you took showers a minute shorter: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you turned the tap off while brushing: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you shook your hands dry instead of a paper towel: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you used a refillable bottle: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you kept your phone one more year: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you bought no new clothes for a year: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you used a cotton tote instead of plastic bags: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you ran the dishwasher full instead of washing by hand: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you recycled everything: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you ate local: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you planted a tree: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you composted: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you switched the bulbs to led: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- if you kept your cat indoors: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- what one person can do, ranked: a world-average person. your number depends on where you live and how you already live; the country layer will narrow it. the ranking between actions is far more robust than any single figure.
- every roof: technical potential is not deliverable electricity: night, seasons and storage are the gap, and the screen says so.
- the cost of a panel: lifecycle numbers depend on where the panel is made and where it is used; the ratio to coal is robust, the exact grams are not.
- the deadliest animals: the small counts (wolf, shark, lion) vary year to year by a factor of two.
- modern slavery: survey-based estimates in a hidden population; the direction is not in doubt.
- bobby calves: the fate split (days / veal / dairy-beef) varies by country and is stated as such; 'almost all killed young' is true everywhere, the age is not.
- someone born in 1955: a world-average person of that age; nobody is average. the point is the size, not the decimals.
- someone born in 1972: as above.
- someone born in 1988: as above.
- someone born in 2004: as above.
- wild animals: an average of population trends, not a count of animals; the site says so on screen.
- wildfire: regional statements are summarised; each wants its own series.
one number the site does not tick
About 720,000 people a year die by suicide, and self-poisoning with pesticides is one of the commonest means worldwide, which is why the pesticide entries mention it. The front door does not run a counter for it. Every public-health body asks that suicide not be presented as a running tally or a spectacle, because how it is shown changes how often it happens; the ledger follows that guidance and lists the number here instead, once, with its source. If you are struggling, please talk to someone. A crisis line for your country is at findahelpline.com.
source: WHO suicide fact sheet 2024; Mew et al. 2017; WHO media guidelines on responsible reporting
corrections
Find a real error, a wrong unit, an outdated source, a better estimate with a citation, or a table anchor that is off, and write to the dispute address with the channel ID. If it changes a number, the change ships in the next version with your name on the changelog. That is the whole arrangement: no money changes hands in either direction, and no one is asked for any. Disagreements about framing are welcome too.
privacy
Your birth year, your country, and anything you type into the reverse ledger stay on your device, in your browser’s local storage, so the site remembers them next time. They are never sent anywhere. There is a “forget it” link beside the input. There are no tracking cookies, and there will not be: if a feature would need a consent banner, it does not get built. If you sign in to read the full entries, one cookie keeps you signed in, and that is all it does; signing out deletes it. We hold your email address to send you the link and to know you again. We never sell it, never use it for marketing, and do not write to you unless you ask. “Watching with you” counts tabs that pinged the site’s worker in the last 90 seconds using a random id that lives in that tab only; “visits since launch” is one integer. No IP addresses are kept. Location, if you offer it to the “here” channel, is used on your device and never sent.
changelog
v0.1.0 · 2026-08-16 · first public version of the ledger: 156 channels, 33 tables, one feed (fires), no corrections yet.
data
the whole ledger is one file,
channels.json (CC BY 4.0), for people who
sign in. everything in it is also on this page, in words, for everyone. the front door and this page are generated from it.