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Pollution of surface waters is a worldwide problem for people and wildlife. Remediation and phytoremediation approaches can offer a solution to deal with specific scenarios. Lemna minor, commonly known as duckweed, can absorb and accumulate pollutants in its biomass. To evaluate if L. minor could be applied for phytoremediation purposes, it is necessary to further investigate its remediation capability and to identify which parameters affect the remediation process. Such a model must include both plant growth and pollutant exchange. A remediation model based on a robust experimental study can help to evaluate L. minor as a proper remediation strategy and to predict the outcome of a L. minor based remediation system. To set up this model, this paper focusses on a detailed experimental study and a comprehensive mathematical modelling approach to represent L. minor growth as a function of biomass, temperature, light irradiation and variable nutrient concentrations. The influence of environmental conditions on L. minor growth was studied, by composing 7 days growth curves. Plants were grown under predefined environmental conditions (25°C, 14h photoperiod, 220 μmol m -2 s -1 light intensity and a modified Hoagland solution with 23.94 mg N L -1 and 3.10 mg P L -1 (N:P ratio of 7.73)) as standard for all experiments. The influence of different temperatures (6, 10, 15, 20, 25, 30 and 35°C), light intensities (63, 118, 170, 220 and 262 μmol m -2 s -1 ), photoperiods (12h and 14h) and N:P ratios (1.18, 3.36, 7.73 and 29.57) were tested in the model. As a result, a growth model was optimised using separate datasets for temperature, light intensity, photoperiod and nutrients and validated by further integrated testing. The growth model is a stable platform for application in phytoremediation of radionuclides in contaminated water, to be extended in future studies with information of pollutant uptake, pollutant-nutrient interactions and transfer to the biomass., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Bioremediation is a soil clean-up technique which exploits the metabolic capacity of microorganisms to degrade soil contaminants. A model was developed to simulate the ex situ bioremediation of a diesel-contaminated soil in a bio-slurry reactor inoculated with a diesel-degrading bacterial strain. Mass transfer processes involving desorption of diesel from soil to water and volatilization of diesel from water, and biodegradation by the bacterial inoculant were included in the model by using Weibull sigmoid kinetics and logistic/Monod kinetics respectively. Model parameters were estimated in batch-based abiotic and biodegradation experiments. Sensitivity analysis revealed the importance of maintaining a high bacterial density in the system for maximum bioremediation efficiency. The model was validated using a pilot bioreactor monitored for 528 h, which removed almost 90% of the diesel present in the system. The results revealed the capacity of the model to predict the bioremediation efficiency under different scenarios by adapting the input parameters to each system., (Copyright © 2019 Elsevier Ltd. All rights reserved.)