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ammonium @lemmy.world
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Comments 105
Disaster is nearing. Mass displacement. Mass starvation. Mass death. It is all imminent. Do you understand?
  • While I get the sentiment and believe action is necessary, this is the wrong way to approach it. Panic is not the way we will solve this crisis.

    There's a way out, and if we get through we'll be in a better place than we've ever been. We need to mass invest in green technology. Solar, wind, nuclear, throw everything at it and see what sticks. Solar is already on the right track to save us, but it's better if it goes even faster and have a few back up plans.

  • 77% of Top Climate Scientists Think 2.5°C of Warming Is Coming—And They're Horrified
  • Yes, just solar. Hydro is bigger now, but it doesn't have the growing potential. Wind is currently also growing exponential, but I don't see it doing that for 20 more years. And even if it does, it doesn't really make a big difference since exponential + exponential is still exponential. If it grows as fast as solar that would mean we're just a few years ahead of the curve.

  • 77% of Top Climate Scientists Think 2.5°C of Warming Is Coming—And They're Horrified
  • Here you go, you'll need numpy, scipy and matplotlib:

    from scipy.optimize import curve_fit
    from matplotlib import pyplot as plt
    
    # 2010-2013 data from https://ourworldindata.org/renewable-energy [TWh]
    y = np.array([32, 63, 97, 132, 198, 256, 328, 445, 575, 659, 853, 1055, 1323, 1629])
    x = np.arange(0, len(y))
    
    # function we expect the data to fit
    fit_func = lambda x, a, b, c: a * np.exp2(b * x ) + c
    popt, _ = curve_fit(fit_func, x, y, maxfev=5000)
    
    fig, ax = plt.subplots()
    ax.scatter(x + 2010, y, label="Data", color="b", linestyle=":")
    ax.plot(x + 2010, fit_func(x, *popt), color="r", linewidth=3.0, linestyle="-", label='best fit curve: $y={0:.3f} * 2^{{{1:.3f}x}} + {2:.3f}$'.format(*popt))
    plt.legend()
    plt.show()
    

    Here's what I get, global solar energy generated doubles every ~3.5 (1/0.284) years.

  • 77% of Top Climate Scientists Think 2.5°C of Warming Is Coming—And They're Horrified
  • Exponential, it fits the curve very nicely. I can give you the python code if you want to. I got 2 decades for all energy usage, not only electricity, which is only one sixth of that.

    I just took the numbers for the whole world, that's easier to find and in the end the only thing that matters.

    The next few years are going to be interesting in my opinion. If we can make efuels cheaper than fossil fuels (look up Prometheus Fuels and Terraform Industries), we're going to jump even harder on solar and if production can keep up it will even grow faster.