# A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants
## 2 Processes
### Biodegradation/Bioremediation  
When organic pollutants enter the groundwater, they are subject to various processes that change their composition and physical properties. One of these is biodegradation, a process carried out mainly by fungi and bacteria, which is also an important process controlling the fate of organic pollutants in the subsurface [232; 233; 234; 235; 236]. The ability of bacteria to degrade even recalcitrant petroleum hydrocarbons has been known for many years [237; 238; 239]. The reasons why some organic pollutants are not bioavailable to organisms include their high hydrophobicity and their tendency to bind to soil particles in heterogeneous aquifers, the ageing of pollutant sources that are more solidified (amorphous forms are favoured for enhanced microbial degradation), aerobic or anaerobic conditions, pH, etc. [240; 241]. The effects of biodegradation also depend on the types of microbial strains, as different microorganisms react differently to pollution, and also on the level of pollution, as this process is dose-dependent [242; 243]. This adaptation could be achieved by selecting the most efficient strains [244; 245; 246], entrapment [247; 248] or encapsulation [249; 250; 251], genetic modification or engineering of microorganisms by spontaneous or induced mutation, gene cloning, the removal of cell walls, or the insertion of genes from other species [252]. It should be emphasised that both dead and living bacteria can be used to remove pollutants. In the case of dead biomass, the target pollutants can be immobilised by biosorption [253] (Section 2.4). The ultimate outcome of biodegradation/bioremediation processes is the conversion of organic pollutants into either simpler organic structures or into environmentally benign inorganic compounds such as carbon dioxide, water, and salts [254]. However, the biodegradation of certain organic substances, such as crude oil, can result in the formation of toxic carboxylic acids [255]. Bioremediation is widely regarded as a safe and relatively cost-effective method for removing pollutants from soil and groundwater. It is a versatile field technology that can be implemented either in situ or ex situ, characterized by rapid progress and a propensity for innovation [77; 256; 257]. Monitoring the effectiveness of bioremediation is critical to the successful treatment of contaminated sites, i.e., assessing when and how target concentrations are reached. It is also crucial from an economic and management perspective, as it enables authorities to make informed decisions about the management of contaminated sites. Ongoing bioremediation monitoring includes chemical measurements of contaminant degradation in soil and/or groundwater, including at the contaminant plume, but may also include measurements of soil respiration and potential metabolites. Microbiological techniques can also be used for microbial enumeration and biomarker assessment, as it is important to monitor bacterial activity during microbially enhanced processes [258; 259; 260]. Biological degradation and bacterial activity can be simulated with analytical and numeric models [75; 261]. The biokinetic models of biodegradation should include several processes, such as bacterial growth, decay, and respiration. The biokinetic parameters are usually derived from laboratory experiments, for example, from batch reactors. Since the biodegradation process is kinetic, it can be modelled as zero-order, first-order, instantaneous, Michaelis-Menten and Monod reactions. However, it is clear that the parameter values determined at laboratory scale are not readily transferable to full-scale groundwater modelling, as bacterial growth in reactors is rapid and limited by substrate depletion, and in full-scale models, other factors such as temperature, pH, substrate quality, toxicity, electron acceptor availability, and biosorption influence microbial growth [103; 262; 263; 264]. A novel approach to modelling biological processes is the use of artificial intelligence, such as neural networks.