## Appendix A Image Processing for Compute Specific Surface Area
### Pumice Stones  
Two equations to estimate the surface area were (\(S\)) compared, Knud Thomsen Formulae (A1) and Dall Equation (A2) [48]. These equations approximate the geometry of a stone to a spheroid shape. \[S=4\pi\bigg{(}\frac{(\mathit{l}w)^{1.6075}+(\mathit{l}h)^{1.6075}+(\mathit{w}h)^ {1.6075}}{3}\bigg{)}^{\frac{1}{12.6075}}\] (A1)  
\[S=\frac{\pi}{3}(\mathit{l}w+\mathit{l}h+\mathit{w}h)\] (A2)  
where \(\mathit{l}\), \(\mathit{w}\) and \(\mathit{h}\) are the length, width and height of the stone. To select the best way to compute the surface area, a sample of 16 pumice stones of size 34.9-45.0 mm were randomly select. Each particle was cover with a single layer of aluminium foil (Figure 20a). The aluminium foil was then spread over a black background (Figure 20b) and photographs altogether with a template of 34.5 cm\({}^{2}\) of black area were taken to compute the surface area through image analysis. A photography of the stones wasalso taken and the shape of each stone images were approximate to an ellipse. Length and width of each stones were estimated using image processing and height were measured manually (Figure A3c). Both, stones and aluminium foil images, were binarized allowing to measure the number of black pixels of the black template to obtain a surface area per pixel conversion factor. The surface area of the aluminium foil (Figure A3d) were compute multiplying the number of pixels of the aluminium foil images by the conversion factor. The centroid of each stone were estimate using the _regionprops_ function of MATLAB(r). The major axis were found looking for the highest distance between to opposite points at the perimeter of each stone that connect a line passing through the centroid. The minor axis was defined as the perpendicular line to the mayor axis is passing through the centroid. The minor axis value was compute as the distance between the opposite points at the perimeter of each stone that belong to this line. The square root of the conversion factor was multiplied for each distance to convert pixels to cm units. An estimative of the surface area were obtained with each method: 603.19 cm\({}^{2}\) for the aluminium foil surface area, 640.80 cm\({}^{2}\) using Equation (A1) and 628.40 cm\({}^{2}\) with Equation (A2). When comparing the values obtaining with equations, these show percentage errors of 6.26% and 4.23%, respectively, in comparison with the aluminium foil surface area. Because Equation (A2) leads to smaller error it was used to compute the surface area of a large sample of 830 g of pumice stones oven dry of size 34.9-45.0 mm and 683.5 g of size 45.0-55.5 mm (Figure A3e,f), obtaining a surface area per mass unit of respectively. The specific surface area in m\({}^{-1}\) units was compute multiplying the surface area per mass unit by the weight of the material used to fill the pad and divided by the volume of the pad. Table A2 summarized the data used to compute the specific surface area of pad built. Figure A3: Sample of photographies and images used in the surface area compute process for the pumice stones. (**a**) Pumice stones of 3.5 to 4.5 mm cover with aluminium foil. (**b**) Photography of aluminium foil layers. (**c**) Ellipse approximation of each pumice stone for 34.9–45.0 mm size. (**d**) Binarized image of the aluminium foil layers. (**e**) Sample of photography for pumice stones of 34.9–45.0 mm size and template. (**f**) Sample of photography for pumice stones of 45.0–55.0 mm size and template. Figure 12: Temperature–Humidity Index at outlet par air conditions as a function of dry-bulb temperature of inlet air (\(T_{\text{{\tiny{dh}}}}\)), and relative humidity (\(\phi_{i}\)) for the pad studied. (**a**) Cellulose. (**b**) Small coconut shell (7.9–12.7 mm). (**c**) Big coconut shell (12.7–19.0 mm). (**d**) Burnt-clay bricks (12.7–19.0 mm). (**e**) Small pumice stones (34.9–45.0 mm). (**f**) Big pumice stones (45.0–55.5 mm).