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A comparison of 95% confidence intervals for the solution of the 1D advection-diffusion model obtained using CLT via the EA and debiasing ap- proaches, over a range of parameter values at t = 5, x = 0 . 9, is given in Table 1, along with the average time taken to obtain each estimate. For the EA approach, the confidence interval is constructed from 1000 replicates of ˆ u ( x, t ), each obtained using 10 000 simulations, and for debiasing 1000 repli- cates of u ‡ ( x, t ), each obtained using N † = 10000. The halting value for the debiasing approach is drawn from a geometric distribution with parameter 0.45. 

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Over the entire parameter range the EA approach has a lower work- variance product, showing that it is a more efficient approach than debiasing in this case. With regards to EA approaches, Brownian motion is a poor proposal when the P´ eclet number (proportional to b ⧸ a ) is large, leading to a large rejection rate. As can be seen in Table 1, as the P´ eclet number in- creases, the computational expense of obtaining the estimate increases, owing to the low acceptance rate of the proposed paths. This limitation is shared 

