All fits had R 2 >0.85, the residuals satisfied normality assumptions as determined by the D'Agostino-Pearson omnibus normality test, and the model was determined to be adequate by the replicates test. 𝑘 𝑑 and its uncertainty was computed by a combination of bootstrapping and nonlinear least-squares regression in MATLAB R2020b by randomly sampling a value for the straw thickness (ℎ 0 ) from a normal distribution defined by the mean and standard deviation of the measured thickness (Table ) and fitting the relative mass loss data (Table ) using the sampled value for thickness. The foamed CDA straw thickness was lognormally distributed; thus, it was log10 transformed (mean = -0.7647; standard deviation = 0.1301) to meet normality criteria. The random sampling and fitting process was repeated 5000 times, during which, for each fit, a value of 𝑘 𝑑 was sampled from a normal distribution defined by the respective fit 𝑘 𝑑 and its standard error. Thus, we generated 5000 values of 𝑘 𝑑 based on the uncertainty of the thickness measurement and the relative mass loss data. Similarly, we generated 100,000 values of projected environmental lifetime (𝑡 𝐿 ) for each straw according to Equation 4. This process was carried out by random sampling 100,000 values of 𝑘 𝑑 and ℎ 0 from a normal distribution defined by their mean and standard deviation (Figures ). The thickness of the foamed CDA straw was sampled the same way as for the regression analysis. Increasing the sampling number by ten times did not change the mean and variation of sampled ℎ 0 , 𝑘 𝑑 , and 𝑡 𝐿 .