Jhaber Dahsan Yacoub Study of hydraulic conductivity and pollutant transport parameters in a municipal solid waste disposal area Bauru 2024 Jhaber Dahsan Yacoub Study of hydraulic conductivity and pollutant transport parameters in a municipal solid waste disposal area Thesis submitted to the São Paulo State University – Unesp, Engineering College at Bauru as a partial fulfillment of the requirements for obtaining the degree of Doctor in Civil and Environmental Engineering. Dr. Roger Augusto Rodrigues Advisor Dr. Heraldo Luiz Giacheti Co – Advisor Bauru 2024 List of Figures 1.1 Identification of studies through databases. . . . . . . . . . . . . . . . . . . . 10 1.2 Number of publications by country involving the terms searched and the authors selected between 2019 and 2022. . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.3 Division into clusters with the predominant keywords identified in the databases from the works previously selected. . . . . . . . . . . . . . . . . . . . . . . . 13 1.4 Programs used for the simulations or validation of simulations involving the transport of contaminants from the works selected between 2019 and 2022. . 33 1.5 Main tracers used by the authors of the papers picked between 2019 and 2022. 35 1.6 Predominant group of chemical compounds utilized in the period under review. 36 1.7 Different simulation times applied by the authors. . . . . . . . . . . . . . . . 38 1.8 Tracer groups’ occurrences in the most frequently reported types of simulations during the analyzed period. . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.1 Location of the municipality of Bauru, Brazil. Study area and collection of sandstone samples at the Bauru’s MSW disposal site. . . . . . . . . . . . . . 60 2.2 Upper Cretaceous stratigraphy of the Bauru basin in southern Brazil (adapted from Batezelli, 2017). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 2.3 Crawler bulldozer supporting the collection of sandstone samples. . . . . . . 62 2.4 Sandstone removed and identified. . . . . . . . . . . . . . . . . . . . . . . . . 63 2.5 Sandstone outcrop profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 2.6 Detail of a sandstone sample composed of two predominant colors. . . . . . . 65 i 2.7 Preparation of the samples selected by predominant color for the particle size test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 2.8 Sedimentation (hydrometer) stage with and without the use of deflocculant. 67 2.9 Washing the material to be sieved. Despite having few fines, the sandstone could retain water on the 0.075 mm sieve. . . . . . . . . . . . . . . . . . . . 68 2.10 Liquidity and plasticity limits exemplified by the brown sandstone sample . . 69 2.11 Methylene blue test to identify the activity of the clay fraction present in the sandstone under study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 2.12 First attempt at molding the specimen. . . . . . . . . . . . . . . . . . . . . . 71 2.13 Sample being prepared for trial with a bench drill. . . . . . . . . . . . . . . . 71 2.14 Bench drill proved helpful, but there was a short spindle stroke when removing the specimens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 2.15 Cutting the samples with a circular saw to prepare them for another configura- tion with enough spindle stroke to remove the specimens. . . . . . . . . . . . 73 2.16 Final setting with a diamond hollow core drill adapted to have enough stroke to remove the sandstone specimens. . . . . . . . . . . . . . . . . . . . . . . . 73 2.17 Longitudinal and transverse core samples. . . . . . . . . . . . . . . . . . . . 74 2.18 Evolution of the rock core extracted using the several techniques presented above. 75 2.19 Specimen’s top and bottom preparation by removing the coarse layer. . . . . 75 2.20 Fine polishing of sandstone rock sample using the specimen grinding machine. 76 2.21 Sandstone specimens completed and identified for testing. . . . . . . . . . . . 77 2.22 Pre-drying the specimens in the oven. . . . . . . . . . . . . . . . . . . . . . . 78 2.23 Cooling the specimens to room temperature in a desiccator. . . . . . . . . . 79 2.24 Test layout to obtain Young’s modulus. . . . . . . . . . . . . . . . . . . . . . 80 2.25 Tensile strength in diametrical compression according to the ASTM C496/C496M (2017) standard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 2.26 Specimens suitable for the diametral compression test as recommended by ASTM D3967 (2016). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 2.27 Molding of the specimens for the direct shear tests. . . . . . . . . . . . . . . 83 ii 2.28 Gray and brown sandstone samples in the molds for direct shear testing before grinding the top and bottom. . . . . . . . . . . . . . . . . . . . . . . . . . . 84 2.29 Samples used to obtain the envelope. Apparatus for the direct shear test. . . 85 2.30 Direct shear machine and data acquisition system. . . . . . . . . . . . . . . . 86 2.31 Gray and brown sandstone samples in the molds for oedometer testing before grinding the top and bottom. . . . . . . . . . . . . . . . . . . . . . . . . . . 88 2.32 Gray and brown sandstone ready for the oedometer test . . . . . . . . . . . . 89 2.33 Sandstone positioned in the oedometer test camera. Pre-wetting process of the sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 2.34 Cylindrical specimen positioned in the permeability test chamber. . . . . . . 91 2.35 Flexible wall permeameter running three tests. . . . . . . . . . . . . . . . . . 92 2.36 Sandstone samples during the capillary saturation and air-drying stages for the soil water retention curve. . . . . . . . . . . . . . . . . . . . . . . . . . . 93 2.37 Saturation of porous stones with high air intake. Haines’ funnel with test in progress. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 2.38 Particle size distribution of gray and brown sandstones with and without deflocculant. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 2.39 Scanning electron microscopy (SEM) of the gray sample in combination with energy-dispersive X-ray spectroscopy (EDS). . . . . . . . . . . . . . . . . . . 98 2.40 Scanning electron microscopy (SEM) of the brown sample in combination with energy-dispersive X-ray spectroscopy (EDS). . . . . . . . . . . . . . . . . . . 99 2.41 Specimen before and after the diametral compression test following the recom- mendations of ASTM D3967 (2016). . . . . . . . . . . . . . . . . . . . . . . . 102 2.42 Core samples after failure by tensile by diametral compression. . . . . . . . . 103 2.43 Stress-strain curve used to calculate the diametral compressive tensile strength according to the ASTM D3967 (2016) standard. . . . . . . . . . . . . . . . . 104 2.44 Stress-strain curve used to calculate the diametral compressive tensile strength according to the ASTM D3967 (2016) standard (continuation). . . . . . . . . 105 iii 2.45 Stress-strain curve used to calculate the diametral compressive tensile strength according to the ASTM D3967 (2016) standard (continuation). . . . . . . . . 106 2.46 Stress-strain curve used to calculate the diametral compressive tensile strength according to the standard ASTM C496/C496M (2017). . . . . . . . . . . . . 109 2.47 Brown and gray sandstone after failure when subjected to the direct shear test.112 2.48 Volumetric variation of gray sandstone samples in the saturation stage. . . . 114 2.49 Volumetric variation of gray sandstone samples in the consolidation stage. . 115 2.50 Vertical and horizontal deformations of gray sandstone samples under shear stage conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 2.51 Stress-strain behavior of the gray sandstone cores required to establish the strength envelope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 2.52 Strength envelope of gray sandstone based on the Mohr-Coulomb criterion. . 118 2.53 Volumetric variation of brown sandstone samples in the saturation stage. . . 120 2.54 Volumetric variation of brown sandstone samples in the consolidation stage. 121 2.55 Vertical and horizontal deformations of brown sandstone samples under shear stage conditions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 2.56 Stress-strain behavior of the brown sandstone cores required to establish the strength envelope. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 2.57 Strength envelope of brown sandstone based on the Mohr-Coulomb criterion. 124 2.58 Compression-decompression cycles of the specimens to determine Young’s modulus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 2.59 Relationship between UCS and elastic modulus. . . . . . . . . . . . . . . . . 129 2.60 Normalized void ratio versus vertical stress curves applied to brown and grey sandstone in natural and saturated conditions. . . . . . . . . . . . . . . . . . 130 2.61 Determination of the expansion pressure of gray and brown sandstones using the saturated oedometer test. . . . . . . . . . . . . . . . . . . . . . . . . . . 131 2.62 Fracture in a gray sandstone sample caused by the expansion of the material exposed to saturation by capillarity. . . . . . . . . . . . . . . . . . . . . . . . 132 iv 2.63 Hydraulic conductivity obtained with constant pressure at the bottom of the specimens in unconsolidated and consolidated gray sandstone samples at 40, 80, 160, and 320 kPa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 2.64 Hydraulic conductivity obtained with constant pressure at the bottom of the specimens in unconsolidated and consolidated brown sandstone samples at 20, 40, 80, 160, and 320 kPa. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 2.65 Hydraulic conductivity values of the consolidated gray sample at 320 kPa with gradients of 25, 50, 100, 200, and 400. . . . . . . . . . . . . . . . . . . . . . . 139 2.66 Hydraulic conductivity determined with constant pressure at the top of the gray sample consolidated at 320 kPa for gradients of 25, 50, 100 and 200. . . 140 2.67 Hydraulic conductivity obtained by dividing the pressure between the top and bottom of the specimen for consolidated gray sandstone at 320 kPa for gradients of 25, 50, 100, 200, and 400. . . . . . . . . . . . . . . . . . . . . . . 141 2.68 Hydraulic conductivity of the gray sandstone sample taken horizontally under the confining pressures of 20, 40, 80, 260, and 320 kPa, following the standard methodology adopted here. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 2.69 Hydraulic conductivity of the brown sandstone sample taken horizontally under the confining pressures of 20, 40, 80, 260, and 320 kPa, following the standard methodology adopted here. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 2.70 Variation in hydraulic conductivity, void ratio, and effective stresses of gray sandstone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 2.71 Variation in hydraulic conductivity, void ratio, and effective stresses of brown sandstone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 2.72 Soil water retention curve (SWRC) of sandstone and the estimation of unsatu- rated hydraulic conductivity of gray and brown sandstones. . . . . . . . . . . 150 3.1 Location of the municipality of Bauru in the center-west of the State of São Paulo. Soil (Unesp Bauru) and rock (Bauru’s MSW disposal site) sample sites. 170 v 3.2 Grain size distribution and soil index properties with depth for the Unesp Bauru site (adapted from Fernandes et al., 2022). . . . . . . . . . . . . . . . 171 3.3 Set used for molding the soil specimens. . . . . . . . . . . . . . . . . . . . . 172 3.4 Trimming devices used to molded the soil specimens. . . . . . . . . . . . . . 173 3.5 Arrangement of the specimen for the tests. . . . . . . . . . . . . . . . . . . . 174 3.6 Sandstone sample cutting process. . . . . . . . . . . . . . . . . . . . . . . . . 175 3.7 Assembly of the diamond hollow core drill used to remove cylindrical rock samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 3.8 The specimen grinding machine polishes the top and bottom of sandstone samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 3.9 Specimens ready for testing. . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 3.10 Sandstone specimen in the test chamber. . . . . . . . . . . . . . . . . . . . . 179 3.11 Sandstone core sample setup for testing. . . . . . . . . . . . . . . . . . . . . 180 3.12 Materials used to prepare the specimens for the permeability, column and leaching tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 3.13 The flexible wall permeameter consists of the data acquisition system, main and secondary panels, reservoir, and test chambers. . . . . . . . . . . . . . . 183 3.14 Permeability test schematic drawing. . . . . . . . . . . . . . . . . . . . . . . 184 3.15 Column test schematic drawing. . . . . . . . . . . . . . . . . . . . . . . . . . 186 3.16 Arrangement of the test chamber in the center with the upstream (left) and downstream (right) pressure interfaces, as well as the solution gathered for analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 3.17 Leaching test schematic drawing. . . . . . . . . . . . . . . . . . . . . . . . . 189 3.18 Characteristic breakthrough curve of the column test (adapted from Thu et al., 2023). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 3.19 Characteristic leaching breakthrough curve of the leaching test (adapted from Thu et al., 2023). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 3.20 Variation in hydraulic conductivity with soil confinement at the depths under study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 vi 3.21 Sandstone’s hydraulic conductivity values and volume variation as a function of applied confinement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 3.22 Variation in the values of hydraulic conductivity and void ratio of the soil at a depth of 1 m and of the sandstone as a function of the confinement applied. Negative values indicate a decrease. . . . . . . . . . . . . . . . . . . . . . . . 197 3.23 Hydraulic conductivity and void ratio of the soil along the depth. . . . . . . 198 3.24 Soil hydraulic conductivity of the 1, 4, and 7 m depths. . . . . . . . . . . . . 199 3.25 Soil hydraulic conductivity of the 11, 13, and 16 m depths. . . . . . . . . . . 200 3.26 Hydraulic conductivity along the soil profile with the defined ranges of values of the mean (golden line), first and third quartiles (dotted red line) for the depths of 1, 4, and 7 m, as well as for 11, 13, and 16 m. . . . . . . . . . . . . 201 3.27 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 20 kPa and 1 m depth. 203 3.28 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 40 kPa and 4 m depth. 204 3.29 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 80 kPa and 4 m depth. 204 3.30 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 160 kPa and 7 m depth. 205 3.31 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 320 kPa and 7 m depth. 205 3.32 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 160 kPa and 11 m depth. 206 3.33 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 320 kPa and 11 m depth. 206 3.34 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 160 kPa and 13 m depth. 207 3.35 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 320 kPa and 13 m depth. 207 vii 3.36 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 160 kPa and 16 m depth. 208 3.37 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on soil consolidated at 320 kPa and 16 m depth. 208 3.38 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on sandstone consolidated at 160 kPa. . . . . 209 3.39 Breakthrough curve with experimental results and analytical curve fitting for the column and leaching tests on sandstone consolidated at 320 kPa. . . . . 209 3.40 Void ratio and hydraulic conductivity using NaCl along the soil profile. . . . 211 3.41 Hydraulic conductivity of soil from 1 to 7 m depth as a function of void ratio using column and leaching tests. . . . . . . . . . . . . . . . . . . . . . . . . . 212 3.42 Hydraulic conductivity of soil from 11 to 16 m depth as a function of void ratio using column and leaching tests. . . . . . . . . . . . . . . . . . . . . . . . . . 213 3.43 Variation in the hydraulic conductivity of the soil subjected to column and leaching tests using NaCl as a tracer. The average value is in golden, and the first and third quartiles are dashed red. . . . . . . . . . . . . . . . . . . . . . 214 3.44 Hydraulic conductivity data of sandstone confined at 160 and 320 kPa as a function of pore volumes using NaCl as a tracer. . . . . . . . . . . . . . . . . 216 3.45 Dispersivity as a function of Péclet number from column and leaching tests in soil and sandstone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 3.46 Dispersivity values from column and leaching tests along the soil profile. . . 222 3.47 Dispersivity along the soil profile with the defined ranges of mean values (golden line), first and third quartiles (dotted red line) for the depths of 1, 4, and 7 m, as well as for 11, 13, and 16 m. . . . . . . . . . . . . . . . . . . . . . . . . . 223 3.48 Hydrodynamic dispersion of soil and sandstone as a function of Péclet number. 224 3.49 Results of hydrodynamic dispersion along the soil profile, as determined by column and leaching tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 3.50 Hydrodynamic dispersion along the profile with the mean values (golden line) and first and third quartiles (dashed red line) for the column test. . . . . . . 226 viii 3.51 Hydrodynamic dispersion along the profile with the mean values (golden line) and first and third quartiles (dashed red line) for the leaching test. . . . . . . 227 3.52 Relationship between Dh/Do versus Péclet number (*Data sourced adapted from Von Rosenberg (1956), Carberry & Bretton (1958), Blackwell et al. (1959), and Raimondi et al. (1959) apud Perkins & Johnston (1963) related to uniform sand or beads.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 3.53 Retardation factor of soil and sandstone as a function of the Péclet number for column and leaching tests considering the results of the Lapidus & Amundson (1952) analytical fit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 3.54 Column test retardation factors along the soil profile achieved by different meth- ods, with the average value represented by the golden line and the interquartile range by the red dashed lines. . . . . . . . . . . . . . . . . . . . . . . . . . . 230 3.55 Leaching test retardation factors along the soil profile achieved by different methods, with the average value represented by the golden line and the in- terquartile range by the red dashed lines. . . . . . . . . . . . . . . . . . . . . 231 3.56 Soil and sandstone partition coefficient as a function of the Péclet number based on the analytical fit of Lapidus & Amundson (1952). . . . . . . . . . . 233 3.57 Mean column test partition coefficient (golden line) and interquartile distance (red dash lines) along the soil profile achieved by different methods. . . . . . 234 3.58 Mean leaching test partition coefficient (golden line) and interquartile distance (red dash lines) along the soil profile achieved by different methods. . . . . . 235 3.59 Arrival time of NaCl with confinement along the depth of the soil profile studied.238 3.60 Breakthrough time of NaCl with confinement along the depth of the soil profile studied. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 3.61 Pick time of NaCl with confinement along the depth of the soil profile studied. 240 3.62 First leaching time of NaCl with confinement along the depth of the soil profile studied. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 3.63 Leaching breakthrough time of NaCl with confinement along the depth of the soil profile studied. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 ix 3.64 Leaching time of NaCl with confinement along the depth of the soil profile studied. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 3.65 Breakthrough curve of manganese, nickel, and lead percolating through sand- stone as a function of time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 3.66 Breakthrough curve of manganese, nickel, and lead percolating through sand- stone as a function of pore volume. . . . . . . . . . . . . . . . . . . . . . . . 248 3.67 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 1 m depth consolidated at 20 kPa. . . . . . . . 261 3.68 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 4 m depth consolidated at 40 kPa. . . . . . . . 262 3.69 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 4 m depth consolidated at 80 kPa. . . . . . . . 262 3.70 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 7 m depth consolidated at 80 kPa. . . . . . . . 263 3.71 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 7 m depth consolidated at 160 kPa. . . . . . . 263 3.72 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 11 m depth consolidated at 160 kPa. . . . . . . 264 3.73 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 11 m depth consolidated at 320 kPa. . . . . . . 264 3.74 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 13 m depth consolidated at 160 kPa. . . . . . . 265 3.75 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 13 m depth consolidated at 320 kPa. . . . . . . 265 3.76 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 16 m depth consolidated at 160 kPa. . . . . . . 266 3.77 Validation of the fit of the analytical curve with the experimental column and leaching data from the soil at 7 m depth consolidated at 320 kPa. . . . . . . 266 x 3.78 Validation of the fit of the analytical curve with the experimental column and leaching data from the sandstone consolidated at 160 kPa. . . . . . . . . . . 267 3.79 Validation of the fit of the analytical curve with the experimental column and leaching data from the sandstone consolidated at 320 kPa. . . . . . . . . . . 267 3.80 Box plot with soil hydraulic conductivity values at 1, 4 and 7 m depth. . . . 268 3.81 Box plot with soil hydraulic conductivity values at 11, 13 and 16 m depth. . 269 3.82 Box plot of the hydraulic conductivity of the soil from 1 to 7 m depth, consid- ering the column and leaching tests. . . . . . . . . . . . . . . . . . . . . . . . 270 3.83 Box plot of the hydraulic conductivity of the soil from 11 to 16 m depth, considering the column and leaching tests. . . . . . . . . . . . . . . . . . . . 271 3.84 Box plot with soil dispersivity values from 1 to 7 m depth using column and leaching data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 3.85 Box plot with soil dispersivity values from 11 to 16 m depth using column and leaching data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 3.86 Box plot of the soil profile’s hydrodynamic dispersion values considering the column test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 3.87 Box plot of the soil profile’s hydrodynamic dispersion values considering the leaching test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 3.88 Box plot with the retardation factor values from the column test for the soil profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 3.89 Box plot with the retardation factor values from the leaching test for the soil profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 3.90 Box plot with the partition coefficient values considering the column test for soil from 1 to 7 m depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 3.91 Box plot with the partition coefficient values considering the column test for soil from 11 to 16 m depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 3.92 Box plot with the partition coefficient values considering the leaching test for soil from 1 to 7 m depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 xi 3.93 Box plot with the partition coefficient values considering the leaching test for soil from 11 to 16 m depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 4.1 Overview of Bauru’s MSW disposal site. . . . . . . . . . . . . . . . . . . . . 303 4.2 Analyzed sections of Bauru’s MSW disposal site. . . . . . . . . . . . . . . . . 304 4.3 Illustrative section of the solid waste pit, highlighting the elements analyzed throughout the work. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 4.4 North-south profile of the studied site (adapted from Mondelli, 2008). . . . . 311 4.5 East-west profile of the studied site (adapted from Mondelli, 2008). . . . . . 312 4.6 Initial conditions of the N-S section. . . . . . . . . . . . . . . . . . . . . . . . 314 4.7 Initial conditions of the E-W section. . . . . . . . . . . . . . . . . . . . . . . 314 4.8 N-S section boundary conditions. . . . . . . . . . . . . . . . . . . . . . . . . 315 4.9 E-W section boundary conditions. . . . . . . . . . . . . . . . . . . . . . . . . 315 4.10 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 1 m depth consolidated at 20 kPa. . . . . . . . 317 4.11 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 4 m depth consolidated at 40 kPa. . . . . . . . 317 4.12 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 4 m depth consolidated at 80 kPa. . . . . . . . 318 4.13 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 7 m depth consolidated at 80 kPa. . . . . . . . 318 4.14 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 7 m depth consolidated at 160 kPa. . . . . . . 319 4.15 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 11 m depth consolidated at 160 kPa. . . . . . 319 4.16 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 11 m depth consolidated at 320 kPa. . . . . . 320 4.17 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 13 m depth consolidated at 160 kPa. . . . . . 320 xii 4.18 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 13 m depth consolidated at 320 kPa. . . . . . 321 4.19 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 16 m depth consolidated at 160 kPa. . . . . . 321 4.20 Numerical fitting with the experimental and analytical data from column and leaching tests from the soil at 16 m depth consolidated at 320 kPa. . . . . . 322 4.21 Numerical fitting with the experimental and analytical data from column and leaching tests from the sandstone consolidated at 160 kPa. . . . . . . . . . . 322 4.22 Numerical fitting with the experimental and analytical data from column and leaching tests from the sandstone consolidated at 320 kPa. . . . . . . . . . . 323 4.23 Experimental, analytical, and numerical arrival times. . . . . . . . . . . . . . 324 4.24 Experimental, analytical, and numerical breakthrough times. . . . . . . . . . 325 4.25 Experimental, analytical, and numerical pick times. . . . . . . . . . . . . . . 326 4.26 Experimental, analytical, and numerical first leaching times. . . . . . . . . . 327 4.27 Experimental, analytical, and numerical leaching breakthrough times. . . . . 328 4.28 Experimental, analytical, and numerical leaching times. . . . . . . . . . . . . 329 4.29 Results of the 1-year simulation with a 0.3 m leachate head for the representative north-south profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 4.30 Results of the 10-year simulation with a 0.3 m leachate head for the represen- tative north-south profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 4.31 Results of the 100-year simulation with a 0.3 m leachate head for the represen- tative north-south profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 4.32 Variation of the relative concentration with the horizontal distance for 0.3 m of leachate head, considering 1, 10, and 100 years in a study of the (a) surface, (b) middle, and (c) the base of the north-south profile. . . . . . . . . . . . . 332 4.33 Relative concentration with depth for 1, 10, and 100 years of simulation of the left waste pit of the north-south profile, considering 0.3 m of leachate head. . 334 4.34 Relative concentration with depth for 1, 10, and 100 years of simulation of the middle waste pit of the north-south profile, considering 0.3 m of leachate head. 336 xiii 4.35 Relative concentration with depth for 1, 10, and 100 years of simulation of the right waste pit of the north-south profile, considering 0.3 m of leachate head. 338 4.36 Variation of relative concentration with horizontal distance for 0.3, 0.6, and 1.2 m leachate height (a) in the middle of the N-S pit after 10 years of simulation, (b) in the middle of the N-S pit after 100 years of simulation, and (c) at the base of the N-S pit after 100 years of simulation. . . . . . . . . . . . . . . . . 340 4.37 Relative concentration with depth resulting of the left waste pit N-S profile for leachate heads of 0.3, 0.6, and 1.2 m from (a) a 10-year simulation, and (b) a 100-year simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342 4.38 Relative concentration with depth resulting in (a) a 10-year simulation and (b) a 100-year simulation in the middle waste pit N-S profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 4.39 Relative concentration with depth resulting from (a) a 10-year simulation and (b) a 100-year simulation of the right waste pit N-S profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 4.40 Breakthrough curve for the N-S waste pit at the left slope, with leachate heads of 0.3, 0.6, and 1.2 m at horizons (a) colluvium, (b) residual soil, (c) in the middle of the sandstone, and (d) in the sandstone base. . . . . . . . . . . . . 349 4.41 Breakthrough curve (a) in the middle of the sandstone and (b) in the sandstone base at the center of the N-S waste pit with leachate heads of 0.3, 0.6, and 1.2 m.350 4.42 Breakthrough curve (a) in the middle of the sandstone and (b) in the sandstone base at the right slope of the N-S waste pit with leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 4.43 Results of the 1-year simulation with a 0.3 m leachate head for the representative east-west profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 4.44 Results of the 10-year simulation with a 0.3 m leachate head for the represen- tative east-west profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 4.45 Results of the 100-year simulation with a 0.3 m leachate head for the represen- tative east-west profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 xiv 4.46 Variation of the relative concentration with the horizontal distance for 0.3 m of leachate head, considering 1, 10, and 100 years in a study of (a) the surface, (b) the middle, and (c) the base of the north-south profile. . . . . . . . . . . 357 4.47 Relative concentration with depth for 1, 10, and 100 years of simulation of the left waste pit of the east-west profile, considering 0.3 m of leachate head. . . 359 4.48 Relative concentration with depth for 1, 10, and 100 years of simulation of the middle waste pit of the east-west profile, considering 0.3 m of leachate head. 361 4.49 Relative concentration with depth for 1, 10, and 100 years of simulation of the right waste pit of the east-west profile, considering 0.3 m of leachate head. . 363 4.50 Variation of relative concentration with horizontal distance for 0.3, 0.6, and 1.2 m leachate height in the middle of the E-W pit after (a) 10 years of simulation, (b) 100 years of simulation, and (c) at the base of the E-W pit after 100 years of simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 4.51 Relative concentration with depth resulting from a 10-year simulation of the left waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . 367 4.52 Relative concentration with depth resulting from a 100-year simulation of the left waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . 368 4.53 Relative concentration with depth resulting from a 10-year simulation in the middle waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . 370 4.54 Relative concentration with depth resulting from a 100-year simulation in the middle waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . 371 4.55 Relative concentration with depth resulting from a 10-year simulation of the right waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . 373 4.56 Relative concentration with depth resulting from a 100-year simulation of the right waste pit E-W profile for leachate heads of 0.3, 0.6, and 1.2 m. . . . . . 374 4.57 Breakthrough curve on the left slope of the E-W waste with leachate heads of 0.3, 0.6, and 1.2 m for (a) colluvium, (b) residual soil, (c) the middle of sandstone, and (d) the sandstone base. . . . . . . . . . . . . . . . . . . . . . 376 xv 4.58 Breakthrough curve (a) in the residual soil in the center, (b) in the middle of the sandstone, and (c) in the sandstone base of the E-W waste pit with leaching heights of 0.3, 0.6, and 1.2 m. . . . . . . . . . . . . . . . . . . . . . 378 4.59 Breakthrough curve at the right slope of the E-W waste pit, with leaching heights of 0.3, 0.6, and 1.2 m in (a) colluvium, (b) the middle of sandstone, and (c) the sandstone base. . . . . . . . . . . . . . . . . . . . . . . . . . . . 380 4.60 Comparison of the resistivity results adapted from Mondelli et al. (2007) (above) and simulated profiles (below) with a 1.2 m leachate head in the N-S section. 386 4.61 Comparison of the resistivity results adapted from Lago et al. (2006) (above) and simulated profiles (below) with a 1.2 m leachate head in the E-W section. 387 4.62 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 1 m depth consolidated at 20 kPa. . . . . . 393 4.63 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 1 m depth consolidated at 20 kPa. . . . . . 394 4.64 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 4 m depth consolidated at 40 kPa. . . . . . 394 4.65 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 4 m depth consolidated at 40 kPa. . . . . . 395 4.66 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 4 m depth consolidated at 80 kPa. . . . . . 395 4.67 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 4 m depth consolidated at 80 kPa. . . . . . 396 4.68 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 7 m depth consolidated at 80 kPa. . . . . . 396 4.69 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 7 m depth consolidated at 80 kPa. . . . . . 397 4.70 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 7 m depth consolidated at 160 kPa. . . . . 397 xvi 4.71 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 7 m depth consolidated at 160 kPa. . . . . 398 4.72 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 11 m depth consolidated at 160 kPa. . . . 398 4.73 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 11 m depth consolidated at 160 kPa. . . . 399 4.74 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 11 m depth consolidated at 320 kPa. . . . 399 4.75 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 11 m depth consolidated at 320 kPa. . . . 400 4.76 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 13 m depth consolidated at 160 kPa. . . . 400 4.77 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 13 m depth consolidated at 160 kPa. . . . 401 4.78 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 13 m depth consolidated at 320 kPa. . . . 401 4.79 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 13 m depth consolidated at 320 kPa. . . . 402 4.80 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 16 m depth consolidated at 160 kPa. . . . 402 4.81 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 16 m depth consolidated at 160 kPa. . . . 403 4.82 Numerical validation with column test through experimental data (left) and analytical (right) from the soil at 16 m depth consolidated at 320 kPa. . . . 403 4.83 Numerical validation with leaching test through experimental data (left) and analytical (right) from the soil at 16 m depth consolidated at 320 kPa. . . . 404 4.84 Numerical validation with column test through experimental data (left) and analytical (right) from the sandstone consolidated at 160 kPa. . . . . . . . . 404 xvii 4.85 Numerical validation with leaching test through experimental data (left) and analytical (right) from the sandstone consolidated at 160 kPa. . . . . . . . . 405 4.86 Numerical validation with column test through experimental data (left) and analytical (right) from the sandstone consolidated at 320 kPa. . . . . . . . . 405 4.87 Numerical validation with leaching test through experimental data (left) and analytical (right) from the sandstone consolidated at 320 kPa. . . . . . . . . 406 4.88 Variation of the relative concentration with the horizontal distance for 0.6 m of leachate head, considering 1, 10, and 100 years in a study of (a) the surface, (b) the middle, and (c) the base of the N-S profile. . . . . . . . . . . . . . . . 407 4.89 Relative concentration with depth for 1, 10, and 100 years of simulation of (a) the left, (b) the middle, and (c) the right waste pit of the N-S profile, considering 0.6 m of leachate head. . . . . . . . . . . . . . . . . . . . . . . . 408 4.90 Variation of the relative concentration with the horizontal distance for 1.2 m of leachate head, considering 1, 10, and 100 years in a study of (a) the surface, (b) the middle, and (c) the base of the N-S profile. . . . . . . . . . . . . . . . 409 4.91 Relative concentration with depth for 1, 10, and 100 years of simulation of (a) the left, (b) the middle, and (c) the right waste pit of the N-S profile, considering 1.2 m of leachate head. . . . . . . . . . . . . . . . . . . . . . . . 410 4.92 Breakthrough curves (a) in the middle of the residual at the center, (b) in the colluvium on the right slope, and (c) in the residual on the right slope of the N-S waste pit, with leachate heads of 0.3, 0.6, and 1.2 m. . . . . . . . . . . . 411 4.93 Variation of the relative concentration with the horizontal distance for 0.6 m of leachate head, considering 1, 10, and 100 years in a study (a) of the middle and (b) profile base of the E-W profile. . . . . . . . . . . . . . . . . . . . . . 412 4.94 Relative concentration with depth for 1, 10, and 100 years of simulation of (a) the left, (b) the middle, and (c) the right waste pit of the E-W profile, considering 0.6 m of leachate head. . . . . . . . . . . . . . . . . . . . . . . . 413 xviii 4.95 Variation of the relative concentration with the horizontal distance for 1.2 m of leachate head, considering 1, 10, and 100 years in a study of (a) the middle and (b) the base of the E-W profile. . . . . . . . . . . . . . . . . . . . . . . . 414 4.96 Relative concentration with depth for 1, 10, and 100 years of simulation of (a) the left, (b) the middle, and (c) the right waste pit of the E-W profile, considering 1.2 m of leachate head. . . . . . . . . . . . . . . . . . . . . . . . 415 xix List of Tables 1.1 Authors with the highest number of citations until March 2022. . . . . . . . 11 1.2 General characteristics of the studies selected between 2019 and 2022. . . . . 15 1.3 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.4 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.5 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.6 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.7 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 1.8 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.9 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.10 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 1.11 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 xx 1.12 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 1.13 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.14 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.15 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 1.16 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.17 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.18 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 1.19 The general characteristics of the studies selected between 2019 and 2022 (continuation). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 2.1 Sandstone characterization tests. . . . . . . . . . . . . . . . . . . . . . . . . 67 2.2 Technological tests employed to obtain the UCS, elastic modulus, tensile strength by diametrical compression, direct shear, and hydraulic conductivity. 94 2.3 Distribution of medium and fine sand, silt, and clay percentages in gray and brown sandstones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 2.4 Results of the Atterberg limits and the unified soil classification system for both sandstones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 2.5 Results of the methylene blue test, including cation exchange capacity (CEC), specific surface area (SA), value of methylene blue adsorbed (BV), and activity index of the clay fraction (Acb). . . . . . . . . . . . . . . . . . . . . . . . . . 97 2.6 Initial index properties of the sandstone used to determine the Young’s modulus and UCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 xxi 2.7 Uniaxial compressive strength of the specimens used to get Young’s modulus. 101 2.8 Uniaxial compressive strength considering the specimens used to get the Young’s modulus, within the range of ± 20% of the mean. . . . . . . . . . . . . . . . 101 2.9 Initial index properties of the sandstone used to determined the tensile strength by diametral compression. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 2.10 Results for tensile strength in diametrical compression (σt), thickness/diameter ratio (t/ϕ), and compressive strength (σc) according to the ASTM D3967 (2016) standard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 2.11 Data reported by Table 2.10 considering valid results. . . . . . . . . . . . . . 108 2.12 Results for tensile strength in diametrical compression (σt), length/diameter ra- tio (L/ϕ), and compressive strength (σc) according to the ASTM C496/C496M (2017) standard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 2.13 Data reported by Table 2.12 considering valid results. . . . . . . . . . . . . . 110 2.14 Initial index properties of the gray sandstone used to determine the shear strength. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 2.15 Initial index properties of the brown sandstone used to determine the shear strength. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 2.16 Summary of volumetric variations due to the saturation and consolidation stages of the gray and brown sandstones. . . . . . . . . . . . . . . . . . . . . 125 2.17 Values of normal stress (σ), peak shear strength (τp), residual shear strength (τr), ratio between the two, friction angle (ϕ) and cohesion (c) of the gray and brown specimens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 2.18 Results of the five core samples used to determine Young’s modulus and UCS from the same test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 2.19 Valid Young’s modulus and UCS values reported by Table 2.18. . . . . . . . 128 2.20 Results of the different authors’ UCS, E, and TS. Blank spaces refer to the absence of information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 2.21 Results of the different authors’ UCS, E, and TS. Blank spaces refer to the absence of information (continued). . . . . . . . . . . . . . . . . . . . . . . . 135 xxii 2.22 Results of the different authors’ c and ϕ. Blank spaces refer to the absence of information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 2.23 Initial index properties of the sandstones used for the anisotropy test. . . . . 143 2.24 Gray and brown sandstone average hydraulic conductivities in the vertical (kv) and horizontal (kh) directions and its percentage variation (∆) concerning the unconsolidated condition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 2.25 Overview of the void ratio of the gray and brown sandstone samples in the vertical (ev) and horizontal (eh) directions, as well as their percentage variation (∆) about the unconsolidated sample. . . . . . . . . . . . . . . . . . . . . . . 148 2.26 SWRC parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 2.27 Saturated hydraulic conductivity values reported by other authors, determined by different methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 3.1 Initial index properties of the soil at the depths tested. . . . . . . . . . . . . 194 3.2 Initial index properties of the gray and brown sandstone. . . . . . . . . . . . 194 3.3 Summary of the soil’s hydraulic conductivity and seepage velocity determined using permeability, column and leaching tests. . . . . . . . . . . . . . . . . . 218 3.4 Sandstone’s average values of hydraulic conductivity and seepage velocity with different flowing fluids. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 3.5 Summary of the transport parameters determined in this work. The letters C and L indicate the column and leaching tests. Their absence suggests data for both. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 3.6 Initial index properties of the sandstone used for the column test with a multi-ionic heavy metals solution. . . . . . . . . . . . . . . . . . . . . . . . . 246 3.7 Transport parameters ascertained by various researchers using different tracers in similar soils to those utilized in this study. . . . . . . . . . . . . . . . . . . 252 3.8 Transport parameters ascertained by various researchers using different tracers in similar soils to those utilized in this study (continued). . . . . . . . . . . . 253 xxiii 3.9 Transport parameters ascertained by various researchers using different tracers in similar soils to those utilized in this study (continued). . . . . . . . . . . . 254 3.10 Transport parameters ascertained by various researchers using different tracers in similar soils to those utilized in this study (continued). . . . . . . . . . . . 255 3.11 Transport parameters ascertained by various researchers using different tracers and sandstones. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 3.12 Transport parameters ascertained by various researchers using different tracers and sandstones (continued). . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 3.13 Transport parameters ascertained by various researchers using different tracers and sandstones (continued). . . . . . . . . . . . . . . . . . . . . . . . . . . . 258 3.14 Transport parameters ascertained by various researchers using different tracers and sandstones (continued). . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 4.1 Young’s moduli used to validate the simulation with previous tests on soil and sandstone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 4.2 Properties of the materials used in the simulations. . . . . . . . . . . . . . . 307 4.3 Initial conditions for the simulations. . . . . . . . . . . . . . . . . . . . . . . 313 4.4 Simulation boundary conditions. . . . . . . . . . . . . . . . . . . . . . . . . . 313 4.5 An overview of the breakthrough curve results from the N-S colluvium horizon.353 4.6 An overview of the breakthrough curve results from the N-S residual horizon. 353 4.7 An overview of the breakthrough curve results from the N-S sandstone. . . . 354 4.8 An overview of the breakthrough curve results from the E-W colluvium horizon.383 4.9 An overview of the breakthrough curve results from the E-W residual horizon. 383 4.10 An overview of the breakthrough curve results from the E-W sandstone. . . . 384 4.11 Concentration of heavy metals in monitoring wells near the sections under study.391 xxiv Contents List of Figures i List of Tables xx Abstract 1 Introduction 2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1 Analysis of the current scenario of contaminant transport in municipal solid waste disposal sites 5 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 Material and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.1 Information sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.2 Search strategy and selection process . . . . . . . . . . . . . . . . . . 9 1.2.3 Eligibility criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3.1 Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3.2 Bibliometric analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2 Hydraulic and geomechanical characteristics of tropical sandstone: a labo- xxv ratory approach 55 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 2.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 2.2.1 Studied area and sampling . . . . . . . . . . . . . . . . . . . . . . . . 59 2.2.2 Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 2.2.3 Cylindrical specimen molding process . . . . . . . . . . . . . . . . . . 70 2.2.4 Uniaxial compression strength and Young’s modulus . . . . . . . . . 78 2.2.5 Diametral compression . . . . . . . . . . . . . . . . . . . . . . . . . . 81 2.2.6 Direct shear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 2.2.7 Compressebility – oedometer test . . . . . . . . . . . . . . . . . . . . 87 2.2.8 Permeability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 2.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 2.3.1 Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 2.3.2 Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 2.3.3 Stiffness and deformability . . . . . . . . . . . . . . . . . . . . . . . . 127 2.3.4 Hydraulic conductivity . . . . . . . . . . . . . . . . . . . . . . . . . . 137 2.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 3 Laboratory investigation of hydraulic and contaminant transport parameters from a municipal solid waste disposal site 165 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 3.2 Material and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 3.2.1 Studied sites and sampling . . . . . . . . . . . . . . . . . . . . . . . . 169 3.2.2 Specimens preparation . . . . . . . . . . . . . . . . . . . . . . . . . . 172 3.2.3 Permeability tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 3.2.4 Column tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 3.2.5 Leaching tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 3.2.6 Contaminant transport parameters . . . . . . . . . . . . . . . . . . . 190 xxvi 3.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 3.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 3.5 Supplementary material A – Data validation . . . . . . . . . . . . . . . . . . 261 3.6 Supplementary material B – Box plot data . . . . . . . . . . . . . . . . . . . 268 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 4 Study of pollutant transport at a municipal solid waste disposal site using the CODE_BRIGHT program 298 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 4.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 4.2.1 Study site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 4.2.2 Experimental data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 4.2.3 Numerical model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 4.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 4.3.1 Model validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 4.3.2 N-S – 0.3 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 4.3.3 N-S – Same layer, different heads and years . . . . . . . . . . . . . . 339 4.3.4 N-S – BTCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 4.3.5 E-W – 0.3 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 4.3.6 E-W – Same layer, different heads and years . . . . . . . . . . . . . . 364 4.3.7 E-W – BTCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 4.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 4.5 Supplementary material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 4.5.1 Model validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 4.5.2 N-S – 0.6 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 4.5.3 N-S – 1.2 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409 4.5.4 N-S – Colluvium and residual BTCs . . . . . . . . . . . . . . . . . . 411 4.5.5 E-W – 0.6 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412 4.5.6 E-W – 1.2 m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 xxvii References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 Final Considerations 424 Overall conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 xxviii Abstract Municipal solid waste (MSW) disposal sites play a vital role in waste management but pose significant environmental risks due to the transport of contaminants into soil and groundwater. This work examines these risks through an integrative study comprising experimental, analyt- ical, and numerical analyses. A detailed experimental investigation of the tropical soil profile and weathered sandstone near Brazil’s Bauru MSW disposal site revealed key geotechnical and hydraulic properties influencing contaminant transport, including anisotropic permeability and expansive behaviors attributed to clay minerals. Laboratory column tests using the non-reactive tracer NaCl and heavy metals (Mn, Ni, Pb) identified hydraulic conductivity (k), dispersivity (α), hydrodynamic dispersion (Dh), retardation factor (Rd), and partition coefficient (Kd) as critical parameters. Numerical simulations using CODE_BRIGHT eval- uated the fate and transport of contaminants in Bauru’s MSW disposal site’s North-South and East-West profiles over 1, 10, and 100 years under varying leachate heads. Results show that increased leachate head accelerates breakthrough times, with horizontal flow dominating permeable soil horizons. The East-West profile exhibited greater vulnerability to contaminant migration, though sandstone layers provided some attenuation. These findings underscore the importance of integrating field data, laboratory experiments, and modeling to enhance MSW disposal site management strategies, mitigate contamination risks, and safeguard environmen- tal resources. Keywords: Bauru’s MSW disposal site; Weathered sandstone; Tropical soil; Contaminant transport; Numerical simulations. 1 Introduction Municipal solid waste disposal sites are integral to modern waste management systems but present significant environmental risks due to the potential for contaminant transport into surrounding soil and groundwater. This issue is particularly pressing in increasing urbanization and growing global waste volumes. The environmental impact of MSW disposal sites is especially concerning when contaminants, such as heavy metals, organic compounds, and gases, migrate through the soil and water systems, posing long-term threats to ecosystems and public health. There is a growing need to refine and enhance numerical and analytical models that simulate contaminant transport in MSW disposal sites. Different numerical and analytical models are increasingly applied but require continuous improvement to predict long-term contaminant behavior accurately. Furthermore, the interaction of contaminants with different geological formations, e.g., tropical soils and sandstones, introduces complexities in how contaminants migrate. Studies on soil and rock properties, such as strength, stiffness, deformability, and hydraulic conductivity, are essential for understanding contaminant spread. Long-term contaminant behavior in MSW disposal sites, particularly over 100 years in a natural attenuation context, must be understood more. Contaminants can reach critical levels when there are no interventions, posing long-term environmental risks. Moreover, the integration between laboratory data and modeling efforts is beneficial and necessary to improve predictions’ reliability. This interdisciplinary collaboration is vital for managing contaminant transport risks and making informed decisions regarding MSW disposal site operations and remediation efforts. 2 Introduction In this context, this work was motivated by the following questions: 1. What are the leading software programs, periods covered, and tracers used to simulate the transport of contaminants in MSW disposal sites? 2. How does weathered sandstone near an MSW disposal site behave regarding strength, deformability, and permeability? 3. What are the primary contaminant transport parameters and their variation in a tropical sandy soil profile and an outcropping sandstone as a function of confinement pressure and depth? 4. Using the previous laboratory parameters, how would the contamination plume spread with different leachate heads in other periods? Objectives This thesis aims to advance the study of Bauru’s MSW disposal site by determining crucial new laboratory data on the transport of contaminants in tropical sandy soil and the outcropping sandstone around the MSW disposal site, as well as to estimate the sandstone’s hydromechanical parameters to support and validate numerical analyses and, through them, extrapolates the MSW disposal site’s behavior concerning the natural attenuation of the contamination plume. Thesis presentation The thesis has been divided into four main chapters to address these concerns. Recent research has focused on improving the accuracy and reliability of contaminant transport models in MSW disposal sites. Chapter 1 reviews advancements in modeling approaches and presents widely used tools like COMSOL Multiphysics, MODFLOW, and POLLUTE. These models simulate contaminants’ spatial and temporal distribution, providing 3 Introduction critical insights into the dynamics of heavy metals, inorganic tracers, and organic compounds in MSW disposal site environments. Integrating field and laboratory data with numerical models is crucial to refining our understanding of MSW disposal site behavior and mitigating potential environmental risks. In addition to the challenge of modeling contaminant transport, the mechanical and hydraulic behavior of soils and rock formations surrounding MSW disposal sites plays a crucial role in determining how contaminants move through these environments. Chapter 2 investigates the properties of weathered sandstone in tropical regions, highlighting the outcome of uniaxial compressive strength and Young’s modulus and underscoring the differences in permeability and shear strength between gray and brown sandstones. The influence of mineral composition, consolidation pressures, and anisotropy on water flow through these formations offers essential insights into their capacity to contain or allow the spread of contaminants. Chapter 3 explores MSW disposal site-related contamination by examining the hydraulic properties of tropical soils and bedrock near Bauru’s MSW disposal site in Brazil. By studying key transport parameters, such as hydraulic conductivity, dispersivity, hydrodynamic dispersion, partition coefficient, and retardation factors, this chapter provides an understanding of how NaCl, as a non-reactive tracer, migrates through soil profiles and bedrock under varying stresses and depths. Furthermore, it also presents the transport of Mn, Ni, and Pb in unconsolidated sandstones to assess the sandstone’s ability to retain these critical contaminants. These findings offer essential data for future numerical modeling and decision-making in Bauru’s MSW disposal site. Lastly, Chapter 4 focuses on numerical simulations of contaminant transport from Bauru’s MSW disposal site in Brazil, using NaCl to project the long-term environmental impact over 100 years. The study underscores the significance of hydraulic leachate heads in accelerating breakthrough times, particularly in heterogeneous geological formations like tropical soil and sandstone. The findings stress the need for intervention to prevent critical contamination levels from threatening local water resources and ecosystems long term. 4 Chapter 1 Analysis of the current scenario of contaminant transport in municipal solid waste disposal sites Abstract Municipal solid waste (MSW) disposal sites are essential components of waste management systems, but they pose significant environmental risks due to the potential for contaminant transport through soil and groundwater. This paper analyzes the state of contaminant transport in MSW disposal sites, focusing on studies published between 2019 and January 2022, focusing on state-of-the-art modeling approaches and the most frequently studied contaminants. The review emphasizes the application of advanced numerical and analytical modeling techniques. COMSOL Multiphysics was used in 26% of the analyzed studies, MOD- FLOW in 23%, and POLLUTE in 13%, reflecting their growing importance in simulating complex contaminant transport phenomena in MSW disposal sites. The findings highlight the primary use of these models for simulating the spatial distribution of contaminants over varying time frames, with 100, 10, and 20-year periods being the most frequently employed by authors. Heavy metals, comprising 41% of all tracers, were the most commonly studied contaminants, with lead (Pb), copper (Cu), chromium (Cr), cadmium (Cd), and zinc (Zn) being the most prevalent. Inorganic tracers, such as chlorine (Cl), chlorides, and ammonium (NH4), along with non-heavy metals, accounted for 26%, while organic compounds like toluene, dichloromethane, and benzene comprised 24% of the tracers. Methane (CH4) was the primary gas tracer, representing 9% of the simulation tracers. This study emphasizes the importance of integrating field and laboratory data with numerical and analytical models to improve the accuracy and reliability of predictions. It calls for continuous refinement of these models, considering the inherent complexities of MSW disposal sites, to manage contaminant transport risks better and contribute to developing more sustainable waste management practices. Keywords: MSW disposal sites; Analytical and numerical modeling; Contaminant transport; Organic and inorganic tracers; Heavy metals. 6 Chapter 1 Introduction 1.1 Introduction Efforts towards waste reduction, reuse, and recycling are primarily directed at preventing it from being immediately considered final waste and transported to MSW disposal sites without undergoing prior stages of treatment. The goal is to extract or add value to the waste, reducing the overall waste volume in MSW disposal sites, especially in regions with limited disposal capacity, such as large urban centers. This approach is crucial in mitigating the environmental impact of waste and promoting sustainable waste management practices (Daniel, 1993; Malusis & Shackelford, 2004; Varank et al., 2011). Despite concerted efforts, MSW continues to be widely disposed of in sanitary landfills, controlled landfills, and dumps, making them one of the leading sources of environmental pollution and a significant risk to human health (Rowe & Barakat, 2021; Shackelford & Jefferis, 2018). In addition, MSW in countries with less economic capacity is often mixed with hazardous waste, such as Health Services Waste (HSW) and Industrial Waste (IW), leading to increased waste volume and improper disposal methods that exacerbate the environmental and health impacts (Mondelli et al., 2007, 2012; Samadder et al., 2017). The typical result of these cases is a gradient of pollutant concentration in the physical environment, with the highest concentrations close to the polluting sources. Flora, fauna, and human beings can be exposed to and contaminated by heavy metals by consuming them in food or water (Hamer, 2003; Bakis & Tuncan, 2011; Gworek et al., 2016). Chronic exposure to heavy metals is associated with severe damage to human health, such as exposure to lead (kidney and brain damage, anemia, insomnia, irritability, concentration, and learning disorders), cadmium (damage to kidneys, lungs, and bones), mercury (damage to the nervous system, lungs, and development of fetuses) and arsenic (disorders of the central nervous and cardiovascular systems, polyneuropathy, increased risk of cancer) (Järup, 2003). Thus, many studies on contaminant transport have been centered around heavy metals, frequently found in the leachate produced by MSW (Dong et al., 2020; Garg et al., 2020; Sun et al., 2020; He et al., 2022; Yong et al., 2022). Nevertheless, researchers have also focused on other organic and inorganic pollutants, pharmaceuticals, and personal care 7 Chapter 1 Introduction products. Each of these substances has unique migration profile trends and a range of transport parameters (Chen et al., 2019; Divya et al., 2020; Lin & Yeh, 2020; Ding et al., 2021; Peng et al., 2021; Wu et al., 2021; Yu et al., 2021; Yan et al., 2022). It is important to note that applying engineering techniques to prevent or contain soil and water contamination, such as using liners and clay to create a barrier against transport by advection, does not entirely prevent the transport of contaminants by molecular diffusion. Factors such as the composition of the waste and the leachate, the water content in the soils, the position of the water table, the stage of decomposition of the waste, the degradation of geomembranes, the heterogeneity of the physical environment, climatic factors, the gases generation, and the consolidation of the mass of waste, among others, suggest a complex flow behavior in porous media. Therefore, it is necessary to consider these factors while implementing any remediation strategy (Feng et al., 2019; Ozelim et al., 2021; Yu et al., 2021). Another critical phenomenon inside MWS disposal sites due to biochemical reactions is the accumulation and diffusion of heat generated. Wang et al. (2017) comment that the internal temperature of MWS disposal sites can reach 55°C to 60°C, affecting geomembranes, hydraulic conductivity, and sorption of clays. Given the aforementioned complexity, one way to evaluate the behavior and fate of contaminants in soil, rock, air, and water is through laboratory and field tests aimed at determining parameters that help interpret and obtain analytical and numerical models that can describe this behavior and predict the performance of MWS disposal sites over time. Therefore, this work aims to investigate cases reported in the literature that pro- vide enlightenment on analytical and numerical modeling and better analyze the primary pollutants/tracers to understand the migration of contamination plumes in MWS disposal sites. 8 Chapter 1 Material and Methods 1.2 Material and Methods 1.2.1 Information sources This study conducted a literature review following the modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) report for systematic reviews by Page et al. (2021a,b). The construction and visualization of bibliometric networks employing VOSviewer software version 1.6.18. In January 2022, a literature search was carried out utilizing the Web of Science, Scopus, and SciELO databases. The search strategy involved the following keywords: "contam- inant transport" AND "landfill" OR "landfills" AND "municipal solid waste" OR "MSW." For the Brazilian SciELO database, the search incorporated the Portuguese keywords: "transporte de contaminantes" E "aterro" OU "aterros" E "resíduos sólidos urbanos" OU "RSU." 1.2.2 Search strategy and selection process After identifying the documents in the databases, filters were made using the databases’ automation tools: (i) year of publication, (ii) book chapters, and conferences. Duplicate studies were then removed using Zotero 6.0.1 software. Finally, the papers were screened to determine their adherence to the review’s objective. This screening process involved three stages: title, abstract, and full text. The analysis was conducted following the inclusion and exclusion eligibility criteria. 1.2.3 Eligibility criteria The selected studies were limited to papers published between 2019 and 2022 that reported on the transportation of contaminants in MSW disposal sites, specifically in English or Portuguese. To ensure the quality and relevance of the studies, exclusion criteria were applied for conference papers, systematic literature reviews, book chapters, duplicate papers, studies unrelated to the transportation of contaminants in landfills, and documents in languages other than English or Portuguese, as exemplified by Figure 1.1. 9 Chapter 1 Material and Methods Figure 1.1: Identification of studies through databases. 10 Chapter 1 Results and discussion 1.3 Results and Discussion 1.3.1 Database The literature search returned 1504 documents that were screened for eligibility. Of these, 1331 were excluded during the filters in the databases themselves, followed by 51 papers due to duplicate documents between the databases. After screening the titles and abstracts and reading the complete text, 72 papers were subtracted, resulting in 50 studies, as shown in Figure 1.1. The authors with the highest number of citations during the period under review are detailed in Table 1.1. Table 1.1: Authors with the highest number of citations until March 2022. Scopus Web of Science Reference Citations Reference Citations Sun et al. (2020) 43 Sun et al. (2020) 40 Nika et al. (2020) 24 Chen et al. (2019) 25 Abbas et al. (2019) 19 Divya et al. (2020) 15 Feng et al. (2019) 16 Jarsjö et al. (2020) 15 Garg et al. (2020) 15 Abbas et al. (2019) 15 1.3.2 Bibliometric analysis Figure 1.2 depicts that of the 50 papers reported in the period analyzed, 37.5% were from China, 10.7% from the UK, 7.1% from Brazil and India, and 5.4% from Canada, while Egypt, Italy, and Sweden 3.6% each. Notably, China had the highest contribution and the most authors with multiple institutional affiliations, with four double citations. The United Kingdom and the Kingdom of Saudi Arabia followed, each mentioned by the primary author once. Figure 1.3 shows the connections related to each cluster of keywords. The keywords can be classified into four clusters: blue for "diffusion", red for "transport", green for "soil", and yellow for "contaminant transport". All the above start from "landfill". 11 Chapter 1 Results and discussion Figure 1.2: Number of publications by country involving the terms searched and the authors selected between 2019 and 2022. The words "landfill" and "diffusion" are highlighted in blue. As mentioned above, transport by diffusion is widely studied in MSW disposal sites since attempts to reduce advection by installing low-permeability liners do not prevent transport by diffusion. Thinking of a landfill with protective liners, not surprisingly, the words "geomembrane" and "composite liner" also belong to the blue cluster. Other critical words highlighted are "porous media", "advection", "consolidation", and "analytical solution". All are closely related, but the last one stands out, in which authors have sought to update analytical solutions for contaminant transport already established in the literature that incorporate different parameters for different engineering solutions. The yellow "contaminant transport" cluster features "municipal solid waste" and performance more prominently and "adsorption" less prominently. Perhaps because the keywords "transport" and "diffusion" exemplify different transport mechanisms or because of the complexity involved in the transport of contaminants, the keywords remained more general in the yellow cluster, as there is no doubt that the transport of pollutants in municipal solid waste depends on its performance. And its performance relies on a series of factors 12 Chapter 1 Results and discussion Figure 1.3: Division into clusters with the predominant keywords identified in the databases from the works previously selected. such as "leachate", "flow", "hydraulic conductivity", "sorption", "advection", "diffusion", and "composite liner", among others that were part of other clusters, but which are also related to "contaminant transport", "performance" and "municipal solid waste", perhaps only summarized by the keyword "performance" in the yellow cluster. The presence of the keywords "migration", "flow", "coefficients", and "hydraulic conductivity" in the green set "soil" is noticeable in almost all of the papers dealing with the migration of contaminants in porous media, both in manuscripts dealing with more conservative situations that do not involve chemical and attenuation processes, and those involving various other factors such as those dealt with by the other keywords "sorption", "degradation", and "biodegradation". This shows how wide-ranging the situations linked to the transport of contaminants through the soil and the considerations that authors need to make, with various factors acting concurrently, whether in the definition of parameters, which 13 Chapter 1 Results and discussion transport mechanism can be considered dominant in a given situation, and which can be disregarded, whether there is chemical, biological, of retardation, attenuation or transport. These previous factors explain the challenges facing contaminant transport and attenuation mechanisms in the physical environment. Finally, the red with the main keyword "transportation" focuses on the impacts generated on the physical environment due to the various transportation mechanisms, par- ticularly on water resources, exemplified by the keywords "water" and "groundwater". The keywords related to the impact on water resources include "leachate", "landfill leachate", "contaminants", "contamination", "groundwater contamination", "quality", "heavy metal" and "pollution". These words illuminate the authors’ concerns about surface and groundwater contamination. "Quality" can refer to both leachate and water quality. "Heavy metal" also stands out as one of the main components targeted by the research. This set of keywords also includes "clay", site, simulation, and removal, which can be related to managing and/or remediation of contaminated areas. In short, keywords can be grouped into: • Blue set: diffusion, containment barriers and analytical solutions; • Yellow set: an overview of contaminant transport; • Green set: transport mechanisms and soil attenuation; • Red set: impact of contaminants on water resources. Tables 1.2 to 1.19 contain information on the 50 papers analyzed within the specified period. The tables present details regarding the computer programs utilized for simulating contaminant transport, as well as for validating the models put forth by the respective authors. Additionally, the tables outline the tracers under investigation, their initial concentrations, and the simulation durations as reported in the papers. 14 C hapter 1 R esults and discussion Table 1.2: General characteristics of the studies selected between 2019 and 2022. Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Ahmed et al. (2019) MODFLOW Pb, Cr, Cu, and Ni Pb: 0.305 mg/L Cr: 1.840 mg/L Cu: 0.602 mg/L Ni: 1.225 mg/L From 30 days to 1 year Bortone et al. (2019) COMSOL Multiphysics Benzene Toluene Benzene: 9 µg/L Toluene: 60 µg/L 5, 15, 20, and 100 years Chen et al. (2019) Development of an analytical solution, validated through the HYDRUS-1D program Acetone 100 µg/L 2, 5, and 10 years for model verification with experimental 50 years for model verification with HYDRUS 1D. Up to 1000 years for behavior prediction de Oliveira et al. (2019) MPHMTP (Multiphase Heat and Mass Transfer Program) TiO2, SiO2, CuO, and ZnO 250, 500, 750, 1000, 1500, 2000, 4000, 6000, and 8000 mg/L 700 min Dominijanni & Man- assero (2019) Development of an- alytical solutions Toluene The authors do not in- form the initial value of the concentration, they used the relative concentration Authors’ focus was spatial rather than temporal, involving various configurations for land- fill liners Feng & Jin (2019) MODFLOW (2000) Sulfate ions 5000 mg/L 16 years. From January 2015 to December 2030 15 C hapter 1 R esults and discussion Table 1.3: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Feng et al. (2019) Authors present an- alytical solution for the transport of or- ganic contaminants in different engineer- ing liner configura- tions Toluene 1 mg/L Up to 1000 years (time needed to reach the breakthrough curve) Fonseca et al. (2019) Use of semi- analytical solution in pure diffusion and sorption tests Cl, K, Na, and NH4 Cl: 4157.8 mg/L K: 1525 mg/L Na: 2625 mg/L NH4: 357.06 mg/L 1.06, 2.01, and 3.07 days Naveen et al. (2019) fluidyn-Pollusol Iron 100 mg/L From 25 hours to 60 days Rowe & Abdelrazek (2019) SEEP/W CTRAN/W POLLUTE Chloride 1500 mg/L (for 150,000 t/ha) and 2500 mg/L (for 250,000 t/ha) 250 years Samad et al. (2019) MODFLOW Cd, Cr, Hg, Pb, and Zn Not mentioned Investigated the spatial distri- bution Shu et al. (2019) Proposal of a method to calcu- late the analytical breakthrough time. Validated with Dtransu 2D soft- ware Chemical Oxygen Demand (COD) 20 mg/L 50 years 16 C hapter 1 R esults and discussion Table 1.4: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Slavinskienė et al. (2019) Microsoft Excel add-in module XLSTAT for statis- tical analysis NH4, Fe, K, and Cl Not reported Focus was on attenuation dis- tance in different aquifers Uddh Söderberg et al. (2019) Visual MINTEQ As, Cd, Pb, and Sb The authors used vari- ous average concentra- tions depending on the depth sampled. The highest concentra- tions were found in the 0 to 1.5 m depth inter- val, reported here: As: 140 mg/kg Cd: 13 mg/kg Pb:1700 mg/kg Sb: 38 mg/kg 100 years Xie et al. (2019) COMSOL Multiphysics, used to compare with the proposed analytical solution Methane gas Not available The focus of the work was depth, but there was a simu- lation with 10 days in order to ascertain the time to reach the steady-state 17 C hapter 1 R esults and discussion Table 1.5: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Balbarini et al. (2020) COMSOL Multiphysics 13 key pharmaceu- ticals (mainly sulfon- amides, barbitu- rates, and ethyl urethane) The authors noted that not enough data was available to conduct numerical simulations. There- fore, they opted to simulate the local hydrogeology and in- vestigate groundwater flow combined with statistical analyses of pharmaceutical contaminant concen- trations The work centered on the par- ticular distribution of the con- tamination plume towards the Grindsted stream Ding et al. (2020) Development of two analytical models with cutoff walls. COMSOL Multiphysics to validate the model Toluene 1 mg/L to validate the model. A function that varies with depth (z) was used for the simulations: C=Cin,max × exp(-(z- µ)/2σ2). The authors assigned a maximum concentration of 10 mg/L (Cin,max) and a breakthrough con- centration of 1 mg/L (Ccw,max). The breakthrough time was set at the ratio Ccw,max/Cin,max=0.1 2 years to validate with ana- lytical model and 100 years to validate with COMSOL Multi- physics. 200 years of simulation implementing analytical models 18 C hapter 1 R esults and discussion Table 1.6: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Divya et al. (2020) MODFLOW Chloride 100 mg/L 1 year (2017–2018) Dong et al. (2020) Development of own framework Chromium 30.65 mg/m3 for the source and 10 mg/m3 for other areas 6 years. From 2010 to 2015 Faisal et al. (2020) COMSOL multiphysics Cd 50 mg/L 100 years Fandiño et al. (2020) MODFLOW Cr, Cu, Pb, and Zn Cr (mg/L) RL 0.64, ET < 0.05; Cu (mg/L) RL 0.65, ET < 0.03 RT; Pb (mg/L) RL 0.40, ET 0.20; Zn (mg/L) RL 2.80, ET 0.05. RL: the concentration of raw leachate. ET: the concentration of ef- fluent treatment sys- tem. 50 years Feng et al. (2020) Study of an analyt- ical model with ex- perimental data Multicomponent gas (CH4, O2, CO2, and N2) The authors consid- ered the concentration of each component at the landfill gas source: CH4: 20.72 mol/m3 O2: 0 mol/m3 CO2: 20.72 mol/m3 N2: 0 mol/m3 The authors analyzed contami- nation by depth 19 C hapter 1 R esults and discussion Table 1.7: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Francisca & Glat- stein (2020) The authors devel- oped two transport models: high and low permeability lin- ers The paper does not specify the metals used in the pro- posed analytical so- lution, but uses ex- perimental results for Cd, Cu and Pb for the modeling 1 mg/L Modeling of reactive filters and permeable reactive barriers: 150 years. Modeling of bottom liners in landfills: 1400 years to evaluate different hydraulic conductivities. 250 years for the same hydraulic conductivity and different hydraulic heads (leaching heights) Garg et al. (2020) MATLAB Chlorides, Zn, Fe, Pb, and Cu Chloride: 4000 ppm Zn: 3.2 ppm Fe: 73.6 ppm Pb: 19.4 ppm Cu: 62.6 ppm 100 years Guarena et al. (2020) Proposal for an an- alytical solution NaCl The work only reports the zero concentration downstream of the sim- ulated landfill The authors do not verify the variation over time. They com- pared the relative concentra- tions of the leachate pond with the contamination downstream of the landfill, using various combinations of materials as landfill liners 20 C hapter 1 R esults and discussion Table 1.8: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Hagan & Darko (2020) MODFLOW There was no specific study of a pollutant but a hydrogeologi- cal study. The flow velocity was investigated and associated with the potential transport of contaminants The authors did not in- vestigate a specific pol- lutant From 7 to 833 years Hassanzadeh et al. (2020) Development of a computer model us- ing UFV (upwind finite-volume) Cl–, Na–, K+, and Total Organic Car- bon (TOC) The authors mention the concentrations in the leachate, but do not specify those used in the simulations. Na: 2541 mg/L K: 5166 mg/L Cl: 3456 mg/L TOC: 1783 mg/L Work focuses on the vertical and horizontal spread of the contamination plume Jarsjö et al. (2020) MODFLOW Pb and As Concentration in soil: Pb: 780 mg/kg As: 2300 mg/kg Concentration in wa- ter: Pb:0.0781 and 0.0071 g/m3 As (V): 3.4 g/m3 As (III): 77.0 g/m3 41 years 21 C hapter 1 R esults and discussion Table 1.9: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Lin & Yeh (2020) The authors devel- oped an analytical model. They com- pared it with a fi- nite difference solu- tion and other exist- ing models. How- ever, they suggest using MATLAB or Mathematica soft- ware to implement the model presented The research was validated by two studies. For the first one, the work does not specify the tracer when validating with the research by Chen et al. (2019). When validating with the work of Park et al. (2012), it uses 5 VOCs (volatile organic compounds): dichloromethane, methyl tertiary- butyl ether, tri- chloroethylene, toluene, and chlorobenzene with constant concentra- tion co: 0.1 kg/m3 The authors used rela- tive C/Cpeak concen- tration when validat- ing with the work of Chen et al. (2019). VOCs: 0.1 kg/m3 1, 5, and 10 years to validate with Chen et al. (2019), with 100 years for parameter sensi- tivity analysis. 400 days to compare with Park et al. (2012) 22 C hapter 1 R esults and discussion Table 1.10: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Mahallei & Badv (2020) POLLUTE Chlorine The authors used different mixtures of sand and bentonite. In the validation stage, each test was carried out in duplicate with different initial concen- trations: 3% bentonite and 97% sand: 1825 mg/L and 2085 mg/L 6% bentonite and 94% sand: 1975 and 1900 mg/L 3% brick clay, 12% bentonite and 85% sand: 10200 mg/L for both No information on the initial concentration in the simulation by depth 45 s to validate with the numer- ical solution provided by POLLUTE. After validation, the authors aimed to simulate the variation in concentration by depth along the soil profile 23 C hapter 1 R esults and discussion Table 1.11: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time McWatters et al. (2020) POLLUTE Aroclor - PCB (polychlorinated biphenyl) Several situations to validate the modeling Situation 1 (Influence of leachate concentra- tion): Different con- centrations were an- alyzed to adjust the modeling, up to the limit value of 240 ug/L Situation 2: (Influ- ence of variable Darcy velocity and leachate collected) co:8 ug/L (specimen A) and co:50 ug/L (specimen B) provided the most rea- sonable comparison be- tween the model and the concentrations ob- served in the CCL Situation 3: Influence of increasing leachate heads For cell 1, based on the insights from the mod- eling in scenarios 1 and 2, the modeling of sce- nario 3 was based on co:8 ug/L (sample A) and 50 ug/L (sample B). * Up to 25 years for parameter fitting and model validation Up to 6000 years in simulations 24 C hapter 1 R esults and discussion Table 1.12: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time McWatters et al. (2020) - continuation *Concentrations used in the modeling of each cell: 3 ug/L; 8 ug/L; 50 ug/L; 60 ug/L; 160 ug/L; 192 ug/L. Podlasek et al. (2020) HELP (Hydrologic Evaluation of Land- fill Performance) for modeling the unsaturated area MODFLOW 2005 and MT3DMS for modeling the saturated region and contaminant transport Ammonium and ni- trate ions 80 kg N/ha (kg of nutrient per hectare) 5 years for the hydrological bal- ance Up to 20 years for simulation Pu et al. (2020) Developing an analytical solution. CST3 and POLLUTE to check the analytical solution Benzene 100 ug/L Up to 100 years to validate the analytical solution Between 200, 300, and 1000 years, depending on the simulated boundary condi- tion 25 C hapter 1 R esults and discussion Table 1.13: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Ding et al. (2021) Development of an analytical model COMSOL to com- pare with the pro- posed analytical so- lution The authors simu- late four scenarios. For each one, they exemplify a type of pollutant, but they don’t make it clear whether they use them in the simulations Scenario 1. Finite pulse injection to simulate pesticides Scenario 2. De- scribe sewage leaking from tanks and/or pipes Scenario 3. Simu- lating the decay of radioactive contam- inants Scenario 4. Cou- pled with the situation of instant contaminant injec- tion with leakage Authors have varied the rate of contam- inant injection and the number of injec- tion points as pollu- tant sources From 1000 to 1500 days depend- ing on the simulated condition 26 C hapter 1 R esults and discussion Table 1.14: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time El-Mathana et al. (2021) The Groundwater Modeling System (GMS) and MODFLOW Total Dissolved Solids (TDS) Lead, Boron, Ni- trate, Manganese, and Chemical Oxygen Demand (COD) * 20 years to calibrate the model and 100 years of simulation * Tracer Concentration Study area (mg/L) Pond (mg/L) IsmailiaCanal (mg/L) Dumpsite (mg/L) TDS: 200 500 300 30000 COD: 2 2 10 10000 Nitrate: 0.5 0.5 1.5 2 Manganese: 0.2 0.5 0.25 1 Boron: 0 0 0.28 2 Lead: 0 0 0.065 0.02 27 C hapter 1 R esults and discussion Table 1.15: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Ma et al. (2021) MATLAB Dissolved organic matter (DOM) There was no initial concentration Samples were collected from monitoring wells at 12 landfills and ana- lyzed by fluorescence The simulations focused on identifying the spread of DOM in different origins Ozelim et al. (2021) Development of an analytical solution using Python Copper and zinc The authors use var- ious initial concentra- tions for validation. In the re- sult called “properly modeling the sorption isotherm” by the authors, the ini- tial concentration was 800 mg/L 104 hours Peng et al. (2021) New analytical model for organic contaminant trans- port. COMSOL Multiphysics for model validation Toluene 0.054 mol/m3 1000 years 28 C hapter 1 R esults and discussion Table 1.16: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation Time Rowe & Barakat (2021) Two approaches: us- ing the POLLUTE V7 an- alytical model and the SEEP/W and CTRAN/W finite element numerical solutions Perfluorooctane sulfonate (PFOS) Case study I - varying transmissivity: co:4800 ng/L Case study II - vary- ing the initial concen- tration co (mg/L): 4800, 160, 740, 1670 Case I (years): 220, 215, 135, and 170 Case II A (years): 220, 510, 345, 280 Case II B (years): 135, 245, 185, 160 Singh & Rajput (2021) Application of the analytical solution in three case stud- ies. No computer pro- gram was provided Not reported Case 1: background concentration: 0.1 mg/L pollutant concentra- tion: 1 mg/L Case 2: background concentration: 0.1 mg/L for the first layer, and 0.001 mg/L for the second one pollutant concentra- tion: 1 mg/L Case 3 background concentration: 0.1 mg/L for the first layer, and 0.001 mg/L for the second and third layers pollutant concentra- tion: 1 mg/L Case 1: 2 and 3 years Case 2: from 1 to 5 years Case 3: 2 years29 C hapter 1 R esults and discussion Table 1.17: The general characteristics of the studies selected between 2019 and 2022 (continuation). Reference Computational Program Pollutant/Target Tracer Tracer Concentration Simulation