The cubic polynomial that fits the data is:

$P(x) = 0.00464x^3 - 0.3827x^2 + 9.0528x + 87.6524$

where $x$ is the number of years since 1930.

Would you like further details on how the regression was performed or any clarification on the results?

Here are 5 related questions for further exploration:

1. What does each coefficient in the cubic polynomial represent in this context?
2. How well does this cubic model fit the data?
3. Can we use this model to predict coal consumption beyond 1990?
4. What other types of regression models could be applied to this dataset?
5. How would the polynomial change if we added more recent data points?

Tip: When fitting a polynomial to data, always check the residuals to evaluate how well the model fits.