#ourworldindata — Public Fediverse posts

“Whoever oppresses the poor shows contempt for their Maker, but whoever is kind to the needy honors God”*…

It’s easy to feel hope in the advances that the world has made in eraditcating extreme poverty over the last several decades. But as Max Roser writes, unless the poorest economies start growing, this period of progress against the worst form of poverty is over…

In the last decades, the world has made fantastic progress against extreme poverty. In 1990, 2.3 billion people lived in extreme poverty. Since then, the number of extremely poor people has declined by 1.5 billion people.

This means on any average day in the last 35 years, about 115,000 people left extreme poverty behind.1 Leaving the very worst poverty behind doesn’t mean a life free of want, but it does mean a big change. Additional income matters most for those who have the least. It means having the chance to leave hunger behind, to gain access to clean water, to access better healthcare, and to have at least some electricity — for light at night and perhaps even to cook and heat.

Can we expect this rapid progress to continue?

Unfortunately, we cannot. Based on current trends, progress against extreme poverty will come to a halt. As we’ll see, the number of people in extreme poverty is projected to decline, from 831 million people in 2025 to 793 million people in 2030. After 2030, the number of extremely poor people is expected to increase.

To understand why the rapid progress against deep poverty will not continue into the future, we need to know why the world made progress in the past.

Extreme poverty declined in the last three decades because, back in the 1990s, the majority of the poorest people on the planet lived in countries that subsequently achieved very fast economic growth. In Indonesia and China, more than two-thirds of the population lived in extreme poverty. But these economies then grew rapidly, so that by today, the share has declined to less than 10%. Other large Asian countries — including India, Pakistan, Bangladesh, and the Philippines — also achieved strong growth, and as a consequence, the share living in extreme poverty declined rapidly. Much of the progress happened in Asia, but conditions in other regions improved too: the share living in extreme poverty also declined in Ghana, Cape Verde, Cameroon, Panama, Bolivia, Mexico, Brazil, and many other countries.

This chart shows the economic change in these countries over the past decades. As incomes increased, the share of people in extreme poverty declined.

Share of population living in extreme poverty vs. GDP per capita, 1990 to 2024 (World Bank, Eurostat, OECD, IMF)

What is different today is that the majority of the world’s poorest people are stuck in economies that have been stagnating for a long time.Consider the case of Madagascar. In the long run, the country has not seen any growth at all: GDP per capita in Madagascar is about the same today as it was in 1950. As a consequence, the number of people in extreme poverty increased in line with the country’s population growth. In richer countries, it is possible to reduce poverty by reducing inequality through redistribution, but a country like Madagascar cannot reduce its share of people in extreme poverty through redistribution. This is because the mean income is lower than the poverty line; if everyone had the same income, everyone would be living in extreme poverty.

The situation is similar in other countries, as the chart below shows: in the Democratic Republic of Congo, Mozambique, Malawi, Burundi, and the Central African Republic, more than half of the population lives in extreme poverty. As their economies have stagnated, the deep poverty that most people live in has remained largely unchanged for decades.

This is why we have to expect the end of progress against extreme poverty based on current trends. If the poorest economies remain stagnant, hundreds of millions of people will continue to live in extreme poverty.

Share of population living in extreme poverty, 1992-2022 (World Bank)

I’m always skeptical when people say that we are at a juncture in history where the future looks much different than the past. But when it comes to the fight against extreme poverty, I fear it is true. Today, the majority of the world’s poorest people are living in economies that have not achieved economic growth in the recent past… Based on current trends, we have to expect the end of progress against extreme poverty…

… It’s no news that we should expect an end to progress against extreme poverty. This article is an update of an article I published in 2019, in which I wrote the same: the fact that the poorest economies are not growing means that the rapid progress against extreme poverty seen in the last decades will end.

Although this prospect has been known for years, it has hardly received the attention it deserves. Progress against extreme poverty was one of humanity’s most outstanding achievements of the past decades — the end of it would be one of the very worst realities of the coming ones.

Importantly, however, these projections are not predictions; their purpose is not to describe what the world in 2030 or 2040 will certainly look like. These projections describe what we have to expect based on current trends; they tell us about our present world rather than the reality of tomorrow. Current trends don’t have to become future facts: many countries left extreme poverty behind in the past, because they had a moment at which they broke out of stagnation.

What these projections tell us, however, is that if the poorest countries do not start to grow, a very bleak future is ahead of us: a future in which extreme poverty remains the reality for hundreds of millions for many years to come…

Eminently worth reading in full– and acting on: “The end of progress against extreme poverty?” from @maxroser.bsky.social and @ourworldindata.org.

* Proverbs 14:31, NIV

###

As we put our shoulders to the wheel, we might spare a thought for a man who contributed mightily to our capacity to feed humanity, Kenneth V. Thimann; he died on this date in 1997. A microbiologist, he was a pioneer in plant physiology (especially the hormones that control the development of plants). Building on the thinking of Frits Went, he identified the first plant hormone to be discovered– the first auxin, a class of growth hormones, and revealed its chemical structure– which proved very important to agriculture and its yields.

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Indians are living 13 years less than the Japanese: Expert flags 7 unhealthy reasons for this

If you’ve ever looked at global life expectancy charts, one thing jumps out: the Japanese are winning at longevity. On average, a person in Japan lives…
#Japan #JP #JapanNews #indianlifestyle #Japanese #Japanesediet #Japanesenews #lifeexpectancy #longevity #news #OurWorldinData
https://www.alojapan.com/1381128/indians-are-living-13-years-less-than-the-japanese-expert-flags-7-unhealthy-reasons-for-this/

Indians are living 13 years less than the Japanese: Expert flags 7 unhealthy reasons for this

If you’ve ever looked at global life expectancy charts, one thing jumps out: the Japanese are winning at longevity. On average, a person in Japan lives…
#Japan #JP #JapanNews #indianlifestyle #Japanese #Japanesediet #Japanesenews #lifeexpectancy #longevity #news #OurWorldinData
https://www.alojapan.com/1381128/indians-are-living-13-years-less-than-the-japanese-expert-flags-7-unhealthy-reasons-for-this/

https://www.alojapan.com/1381128/indians-are-living-13-years-less-than-the-japanese-expert-flags-7-unhealthy-reasons-for-this/ Indians are living 13 years less than the Japanese: Expert flags 7 unhealthy reasons for this #IndianLifestyle #Japan #JapanNews #Japanese #JapaneseDiet #JapaneseNews #LifeExpectancy #longevity #news #OurWorldInData If you’ve ever looked at global life expectancy charts, one thing jumps out: the Japanese are winning at longevity. On average, a person in Japan lives around 85 years, while in India, life expectancy hovers near 72 years (Our Wor

https://www.alojapan.com/1381128/indians-are-living-13-years-less-than-the-japanese-expert-flags-7-unhealthy-reasons-for-this/ Indians are living 13 years less than the Japanese: Expert flags 7 unhealthy reasons for this #IndianLifestyle #Japan #JapanNews #Japanese #JapaneseDiet #JapaneseNews #LifeExpectancy #longevity #news #OurWorldInData If you’ve ever looked at global life expectancy charts, one thing jumps out: the Japanese are winning at longevity. On average, a person in Japan lives around 85 years, while in India, life expectancy hovers near 72 years (Our Wor

"[Hannah Ritchie] In this article, I’ll focus on how Wolbachia can be used against dengue fever. I'll examine how this innovative new method works, how effective it is in reducing transmission, and how it can be rolled out across the tropics to protect as many people as possible."

https://ourworldindata.org/wolbachia-neglected-tropical-diseases

#OurWorldInData #Diseases #Mosquitoes #Wolbachia #Health #Dengue

The 20 year lag is quite something. It tells a story. That's some patience, before seeing the impact on the population at large!

"Smoking was a 20th-century problem. [..] it became steadily more common. By the 1960s, it was extremely widespread: on average, American adults [bought] more than 10 cigarettes every day."

https://ourworldindata.org/smoking-big-problem-in-brief

#OurWorldInData #OWID #opendata #smoking #lungcancer

How much warming in the middle #Miocene 15million years ago came from methane?
Methane is not constrained at all for the Miocene.
But I did the maths –yet I also warn you: I am maths dyslexic. 😁

tldr: with assumed 10 times more wetlands than today and all of the remaining landmass assumed to be like today's tiny "wild rest",
CH4 emissions were 2124 Mt per year.
Which amounted to 6608 ppb CH4 in the atmosphere which in itself caused +2.1°C .

CO2 in 15Ma is not well constrained either. (see below)
I calculate 560ppm to have contributed 3°C (current science working theory for ECS ±1).

So methane 2.1°C and CO2 3°C on their own, omitting all other climate factors, caused +5.1°C in the Miocene.

The breakdown of the numbers follows. With links.

# CO2:

Hoenisch et al 2023 published meticulously revised CO2 values from global #d13C proxies https://paleo-co2.org , their considered-best proxies are all oceanic in origin.

The chart #1 of 1milion years 15 million years ago, shows #Hoenisch ' s CO2 proxies as the horizontal lines. I chose to fill the gaps with repeated values between the rare data points. So each line segment really is only 1 data point at its right-most end.

560 ppm CO2 seems an okay guess, no?

#CH4 #methane

@Peters_Glen did a cool chart, more intuitive than the one in #AR6, I think. See pic 2 or his tweet where he plots the various greenhouse gases with their warming contribution 2010-2019: https://x.com/Peters_Glen/status/1431873249449680901

The average CH4 concentration in the decade 2010-2019 was 1840ppb (NOAA) and caused +0.51°C as per Glen's chart.

From Glen's chart follows my secret methane formula 😁
1 Mt methane <=> 3.111 ppb <=> 0.001 ºC

If emissions in 15Ma were 2124 Mt CH4 (see #landmass below), it resulted in 2.12°C at a concentration of 6608 ppb.

#Landmass

According to the Global Methane Budget by #GlobalCarbonProject : https://essd.copernicus.org/articles/12/1561/2020/

emissions from the "wild rest" 2008-2017 were 222 Mt CH4 annually . See picture 3.

The wild rest today is 54mio km2, according to #OurWorldInData https://ourworldindata.org/global-land-for-agriculture

Wild rest: 222 Mt CH4 from 54mio km2 = 4.1 t CH4 / km2.

Emissions from wetlands 2008-2017 were 180Mt CH4 (Tg=Mt) .
They cover 4.37% of the total land mass: https://ourworldindata.org/grapher/coverage-of-wetlands?tab=chart&country=~OWID_WRL
4.37% of 141mio km2 total is:
Wetlands 6.2mio km2.

Wetlands: 180 Mt from 6.2 km2 = 30 t CH4 / km2.

In 15Ma Miocene, 10 times more wetlands would have been
62 mio km2.
And
wild rest 79 mio km2.

wetlands 62mio km2 times 30t CH4 = 1800 Mt CH4
wild rest 79 mio km2 times 4.1t CH4 = 324 Mt CH4.

Wetlands plus wild rest:
1800 Mt + 324 Mt = 2124 Mt CH4

secret methane formula:
1 Mt methane <=> 3.111 ppb <=> 0.001 ºC

2124 Mt <=> 6608 ppb <=> 2.12°C

Why do I assume that wetlands were 10x more than today, tho? Why not 15, 20 or 5 times more?

Dunno. Well, humans have unwetted lotsa wetlands since the invention of agriculture in the #Holocene. (Btw, the area of today's dried peatland alone emits 2Gt CO2 per year. See table on dried wetland areas and their emissions GHG:
https://www.nature.com/articles/s41467-020-15499-z/tables/2 #Günther et al 2020, based on IPCC guidelines for wetlands https://www.ipcc.ch/publication/2013-supplement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories-wetlands/ )

Hard to tell what area was covered by wetlands in the previous interglacial 126thsd years ago.

And in the middle Miocene, 15Ma?

My thinking goes like this:
The #Sahara was still forested 15Ma. As was the Gobi Desert probably. The prairies in the US were still forested, even #Greenland and #Antarctica. Northern #Russia had much more land mass back then, too.

Some of the different vegetation compared to pre-Holocene was due to different topography: the Rockies and Alpes were much, much lower, the high mountain ranges in East Asia didn't exist. #Australia was 15° further South. See also #Steinthordottir et al 2021 in "Miocene The Future Of The Past https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020PA004037
And the whole special Miocene issue:
https://agupubs.onlinelibrary.wiley.com/doi/toc/10.1002/(ISSN)2572-4525.Miocene1

All land area had gap-less biomes growing. Mostly forests. What do forests do? Away from the coast, within the continents, forests control the hydrological cycle, how much evaporates and how much it rains. All biomes do, but forests most.
The more forests there are, the more it rains. Uninterrupted plant cover with its propagating rain cycle hinders deserts from forming in the heart of the continents, too.

Also, air holds 7% more water per 1°C warming, raising the potential rain amount.

Now, if it rains a lot, and depending on the topography, land is inundated temporary, seasonally or permanently, methane-producing microbes in the soil get to work presto, eat carbon and fart CH4.
The warmer it is, the more the microbes work.

But why 10x more wetlands?
Why not 7 or 15x?
Dunno. 10 feels right. And 6608ppb is nicely close to a guesstimate of mine that mid Miocene CH4 concentration cd have been 7000 ppb.
Maybe 400ppb came from huge animals, happily roaming among giant trees.
Brazil's Giant Sloth? The "wild rest" in the Miocene was HUGE! And cute.
#FridaysForFuture
#anloCH4

For those who seek #goodnews amidst #ClimateCrisis and #catastrophe:
Some #scientists collect #BestPractice examples of #disasters avoided:
https://disastersavoided.com/map-view
(via @ourworldindata: https://ourworldindata.org/the-world-has-become-more-resilient-to-disasters-but-investment-is-needed-to-save-more-lives )
#disastersavoided #flood #drought #OurWorldInData

"It's not as if we have to find the big #CO2 emitters; we already know where they are. Unlike #methane, which is fugitive - it shows up in places and at times you don't necessarily expect - we know where the large #PowerPlants 🏭 are in the world; we know where the aluminium smelters are. So, this is more about being able to verify 🛰️ #emissions." https://www.bbc.com/news/science-environment-64473574

General info by #NASA :
https://climate.nasa.gov
https://climate.nasa.gov/vital-signs/carbon-dioxide

#ESA on #GHGSat 🛰️ :
https://earth.esa.int/eogateway/news/how-scientists-use-space-data-to-help-advance-the-energy-transition

#Statistics 📊 by #OurWorldInData https://ourworldindata.org/co2-emissions

#Satellites #SpaceScience

bel outil qui vient de sortir pour comparer les futurs énergétiques des différents scénarios. vous pouvez y comparer les mix énergétiques et électriques, l'énergie primaire et finale, récupérer les données en format json, comparer l'empreinte carbone et la demande en métaux critiques des différentes trajectoires. ça s'appelle #Metawatt, c'est porté par un bénévole qui reprend les données de différents rapports, Thimothée Jaussoin, le tout à source ouverte :

https://metawatt.fr

#giec #rte #ademe #belfort #cop27 #negawatt #climat #chatbongaz #sortirDesFossiles #snbc #carbon4 #urgenceClimatique #énergie #opendata #ourworldindata

A good explanation by Our World In Data of what the various death rates mean and how to interpret the ones for COVID-19 correctly.

"We’ll discuss the “case fatality rate”, the “crude mortality rate”, and the “infection fatality rate”, and why they’re all different."

https://ourworldindata.org/covid-mortality-risk

#COVID19 #OurWorldInData #Statistics #DeathRates

@jeroenpraat
While reducing #meatConsumption to pre-1950's levels is good to strive towards, we have found that reducing #populationGrowth, or reversing it, will help us to reduce emissions.

Often these discussions devolve into wanting to deny meat to the newly-developed and developing world, due to our #overconsumption.

We are also weary of #OurWorldInData. We distinctly remember something less honest about them from years ago.

@OchotonidKnight

According to Our World in Data, "Peak population growth was reached in 1968". Since then the growth rate has dropped even as the world's human population increases, but at a slower rate. In the future, "it will be low fertility [that] keeps population changes small."

#Statistics #OurWorldInData #HumanPopulation

https://ourworldindata.org/world-population-growth-past-future