Table 14.
Predictive models, independent and dependent variables, and performance indicators for applying biochar in removing different pollutants from water
| Feedstock | Target pollutant(s) | Optimisation approach | Parameters optimised | Optimised response variable(s) | Design performance indicators | References |
|---|---|---|---|---|---|---|
| Lolium perenne, Miscanthus x. giganteus, Fraxinus excelsior, Salix viminalis, Picea sitchensis | Zinc (II) | Taguchi design—L9 orthogonal array | Temperature, residence time, particle size, and gaseous atmosphere |
%Zinc adsorbed, Char yield and composition |
Analysis of variance | Hodgson et al. (2016) |
| Sewage sludge feedstock | Phosphate | Central composite design | Pyrolysis temperature and time | % Removal of phosphate, and pH | Analysis of variance, Fisher test value (F-value), probability value (P-value), R2 and R2-adjusted | Saadat et al. (2018) |
| Cattail (Typha latifolia) | Phosphorous | Box–Behnken design | Lanthanum weight content in total biomass weight (feedstock parameters), pyrolysis temperature and maintenance time (pyrolysis parameters) | % Phosphate removal efficiency | R2 and Analysis of variance | Xu et al. (2019) |
| Shredded wood comprising 20% volume of spruce/fir and 80% pine (stem of Pinus strobus without bark) | Lead (II) | Central composite design | Acidity of aqueous solution (pH), agitation time, adsorbent mass, and initial concentration of lead (II) | Biochar extraction efficiency (E (%)) and adsorption capacity (Q (mg g−1)) | R2 and R2-adjusted | Bardestani et al. (2019) |
| Paper sludge/wheat husks | 2,4-dichlorophenol | Box–Behnken design | pH, temperature, initial contaminant concentration, and time | Adsorption% | R2 and R2-adjusted, Analysis of variance | Kalderis et al. (2017) |
| Tea waste | Fluoride | Central composite design | Adsorbent dose, contact time, and temperature | % Fluoride removal | R2, coefficient of variation, F-value, and P-value | Roy et al. (2018) |
| Cassava Rind | Malachite green | Box–Behnken design | Adsorption temperature, dose of absorbent, and initial dye concentration | Amount of malachite green adsorbed per unit mass of the adsorbent | R2, coefficient of variation, F-value, and P-value | Beakou et al. (2017) |
| Prunus armeniaca stones | Lead (II), cadmium (II), nickel (II), naproxen, chlorophenols | Adsorbent dosage, pH initial contaminant concentration | Yield%, percentage of adsorbate removal and equilibrium adsorption capacity, qe | The root mean square error and sum of the squares of the errors | Turk Sekulic et al. (2018) | |
| Date pits | Tigecycline | Box–Behnken design | pH, adsorbent dose, initial drug concentration, and contact time | %Removal and adsorption capacity | R2 and R2-adjusted, R2 predicted, and analysis of variance | El-Azazy et al. (2021b) |
| Cow femur residues (bone char) | Fluoride | Fractional factorial design | Temperature, heating rate, and residence time | Yield%, and fluoride uptake (mg g−1) | Variance analysis | Rojas-Mayorga et al. (2013) |
| Pistachio nutshells and Aloe vera leaves | Sarafloxacin | Plackett–Burman design | pH, adsorbent dose, initial drug concentration, and contact time | %Removal and adsorption capacity | R2, R2-adjusted, R2-predicted, and analysis of variance | El-Azazy et al. (2020) |
| Olive stones | Clofazimine | Box–Behnken design | pH, adsorbent dose, initial drug concentration, and contact time | %Removal and adsorption capacity | R2 and R2-adjusted, R2-predicted, and analysis of variance | El-Azazy et al. (2021c) |
| Cow dung and sewage sludge | Methylene blue | Central composite design | Dose of biochar, initial methylene blue concentration, and the type of biochar | Breakthrough time | R2 and R2-adjusted, R2-predicted, and analysis of variance | Suárez‐Vázquez et al. (2021) |
| Soil, peat, and lignocellulosic material (straw) | Atrazine (pesticide) | Central composite design | The inlet atrazine concentration, flow rate and pH of the fixed-bed column packed with wheat straw, soil, and peat | % Removal and adsorption capacity | Analysis of variance, lack-of-fit | Levio-Raiman et al. (2021) |
| Sugar beet shreds | Copper (II) | Box–Behnken design | Concentration of the inlet solution, adsorbent dosage, and pH of the inlet solution | Breakthrough time | Analysis of variance and R2 | Blagojev et al. (2019) |
| Aegle marmelos Correa fruits | Ranitidine HCl | Box–Behnken design | Fixed-bed height, initial drug concentration, flow rate, and adsorbent particle size | % Removal | R2, R2-adjusted, R2-predicted, analysis of variance, lack-of-fit | Sivarajasekar et al. (2018) |
| Sugarcane bagasse | Zinc (II), copper (II) and nickel (II) | Central composite design | Initial adsorbent bed height, initial solute concentration, liquid flow rate, and airflow rate | % Removal | R2, R2-adjusted, R2-predicted, analysis of variance, lack-of-fit | Biswas et al. (2020) |
| Seaweed Ulva reticulata | Reactive Red 120 | Box–Behnken design | Biochar dose, initial dye concentration and pH | % Removal | R2, R2-adjusted, analysis of variance, lack-of-fit | Lenin Sundar et al. (2021) |
This mainly includes the design of experiment-based approaches