To put it brutally it's because on Hacker News and probably your social circle, there are too many people whose social status and income depends on being clever, or at least the perception of being clever. This leads us to seriously over-index on things that look like science or data analysis, without even being able to see alternatives that in my experience easily occur to the less (over?) educated.
Consider this article. It's actually a good case in point. The article can be summarized like this:
1. In the 1970s there were these modellers who predicted disaster. Lots of very influential and educated people took them uber-seriously and thought the Limits To Growth was proof positive that everything needed to change.
2. The model turned out to be useless and the disaster it predicted never happened, because the numbers it used for natural resource availability were garbage.
3. This major error did not reduce the modellers confidence in what they were doing (this seems to be a common theme with modellers). Instead they just doubled the number of natural resources and kept on going. That sounds rather arbitrary and not like a real fix to me, but alright. The new models indicated that nothing makes much of a difference for decades (until 2020), conveniently making the predictions unfalsifiable on any timeline that the original authors may have cared about.
4. Now a new researcher has published a new paper on these models, which also says nothing useful. We read that the models "aren't terribly enlightening" because we don't have any data past 2020 yet so which scenario we're supposedly in cannot be determined.
5. Despite all the above, the author concludes that "the most important takeaway from these models is that we need to take definitive action".
Wrong! A rational person can conclude nothing from the evidence in the article. Given that we can only judge the models by prior performance, we should anticipate that the models are probably wrong again. Moreover, the model scenarios don't have any probabilities attached to them and are described in sufficiently vague terms that nobody would ever be able to conclude which scenario we actually followed, again, making it an exercise in stargazing, not science.
Therefore, we cannot actually say we've "known for at least 50 years that our current pattern of consumption is not sustainable". We've known no such thing. The conclusions of the article and many of the commenters here seem like motivated reasoning as a consequence - or at least, it's certainly not Bayesian reasoning!
Invariably, the nature of a difficult situation is that they're difficult to get out of, so we tend to be very interested in avoiding difficult situations. This is why people are so interested in avoiding climate change, rather than waiting for more real-time data about how much climate change actually sucks so they can update their Bayesian priors and "avoid climate change when it happens again."
One now obscure reason for this is that back in the 1970s people didn't believe in global warming and the term "climate change" didn't exist as we know it today. Climatologists were worried about global cooling instead. At that point their records showed a generalized decline in temperature from the 1940s onwards and they believed it might continue indefinitely, leading to a new ice age. This was taken quite seriously, as newspaper records from the time show.
These days it can be hard to understand why they thought that, because if you get a modern graph of the long term temperature record it doesn't show this cooling effect. The reason is that climatologists have repeatedly issued new versions of the historical time series, each time reducing the extent to which this cooling period can be seen. The differences between versions are the extent to which models are allowed to modify the raw data. The climatologists do this because they are very certain in their theories, but a long period of cooling in the 20th century is not compatible with them, and thus they look for reasons why the data must be wrong. When they come up with such a reason it gets merged into the model and the next version "corrects" for it.
Modern graphs show basically no cooling, leading to some people concluding that the belief in global cooling was some sort of fringe belief, or even an urban legend, because obviously, how could they have thought that when no such cooling is visible.
Given the long track record of educated people having near unshakeable confidence in models even in the face of failed predictions (of which World3 is a salient example), this progressive replacement of measured historical data with synthetic data is well worth pondering deeply.
The one that always gets me is how people expect us to even develop those new technologies. With what energy? The ones we're running out of? The ones that are already more and more expensive to find?
And the fact that we'll be doing that...during increasing droughts and extreme weather...water shortages...crop shortages or even widespread failures...the associated political instability...refugee crises far beyond what we've experienced in recent years...all while the population grows...
And that doesn't even mention the fact that, just as when a privileged group of people lose that privilege and call it persecution, those of us in the developed world will see any drop in the standard of living as more extreme than it necessarily actually is. I fully expect right wing terrorism to increase; even now they're running around screaming about "Jews replacing them" -- what happens when their lives get very clearly worse? Who do you think they'll blame and how will they respond?
I could go on.
That's just, like, 1% of the different angles and interplaying variables involved. It's enormously complex, but all paths lead to serious instability, perhaps societal collapse.
Solar panels, batteries, and wind mills are comparatively easy to produce at ridiculous volumes. They’re a cheaper, faster and cleaner solution.
Buildings are also “adapted for each location”, but there is still an entire corpus of standardized techniques to do that that massively reduces costs compared to literally solving the problem from scratch at each site.
And why is it the case that “we don’t have the skilled people to do that”? If people value it, they’ll pay for it- and people can learn new skills in response to market need / pay - there is no predetermined number of “ad-tech software engineers” for example, they were “created” by the people themselves responding to market forces (pay)
Maybe you could have a universally implantable design, and maybe you could train people with the relevant skillset. The point is: we haven’t, and we aren’t, so other ways of generating green power are easier and cheaper. Nuclear will play a role for sure (the climate crisis is such that we need to do all the things) but it won’t cover more than 10% of our energy needs. I would be glad to get a rosier outlook on nuclear though.
>Nuclear power is the largest source of electricity in France, with a generation of 379.5 TWh, or 70.6%
https://en.wikipedia.org/wiki/Nuclear_power_in_France
>France is Europe’s biggest net electricity exporter in 2019, says report
>French electricity costs are just 59% of German electricity prices.
https://www.nsenergybusiness.com/features/electricity-export...
>Nuclear power in Germany accounted for 11.63% of electricity supply in 2017
https://en.wikipedia.org/wiki/Nuclear_power_in_France
>German power export surplus shrank 46.2% in 2020
https://www.reuters.com/article/germany-electricity-statisti...
Just look at China, with ~50 nuclear plants (just 5% of energy production), while they have thousands of coal plants. It's practically impossible that they can shift to a reusable carbon-neutral energy production methods.
Also, China can build a hundred coal plants in a year, but there's no way it can do that with nuclear.
The realistic picture is that growth cannot be sustained and there will be dire consequences due to other factors too.
(climate change, migration, wet bulb temperatures, crop failures, people being too good at capitalism, etc.)
Compared to all the construction China has done in the past 50 years, it doesn't seem that difficult a target.
> Also, China can build a hundred coal plants in a year, but there's no way it can do that with nuclear.
That isn't a law of nature. They can build hundreds of plants of any type in a year.
The dream was "power too cheap to meter". Didn't come true back then, and it turns out after you account for safety systems like a containment building and backup cooling, it's far more expensive than alternatives.
To make things worse, making nuclear remotely profitable relies on running it as close to 24/7 as possible. Given that renewables exist and produce cheaper power, nuclear only gets to offer anything when renewables aren't working, which makes it even more expensive.
Economically, it's extremely risky. Why risk billions on a plant that might profit 20 years down the line, when you could build solar or wind faster, and profit faster?
Politically, it's not great because construction times are very long, so any politician that starts building them probably won't be there to see the benefit, and may have their work stopped by a successor.
Practically, we can't build it fast enough. It's a big, complex, specialized tasks that few people do because there's not much market.
> The saddest aspect of life right now is that science gathers knowledge faster than society gathers wisdom.
Nuclear can be safe but look at the failures of the USSR on Chernobyl to see how it depends completely on a country's culture and willingness to pay for this safety. Or even Fukushima, in a country very risk-averse and rich, corners were still cut even with the responsible engineer calling out that the sea walls were too low.
Should we trust governments around the world that each single one of them will keep their nuclear power plants safe for the foreseeable future until we can move away from it (let's say 50-100 years)?
I'm on the camp that no, we can't.