Sustainable Wastewater Treatment via Advanced Hybrid Oxidation and Biofiltration Processes: Environmental Modeling, Process Performance, and Optimization

1. Introduction

Sustainable wastewater management is one of the most significant environmental challenges of this century, particularly in fragile and water-scarce areas such as arid and semi-arid regions [1,2]. Rapid urbanization, population growth, and increased industrialization have led to a massive explosion in the volume and complexity of liquid waste, which is teeming with recalcitrant organic pollutants, pathogens, nutrients, and emerging micropollutants such as pharmaceuticals and endocrine disruptors [3,4]. These pollutants are causing an ongoing deterioration of aquatic ecosystems, altering microbial biodiversity, and affecting surface and groundwater quality [1,5].

Conventional activated sludge processes are also considered insufficient for these resistant compounds, although effective for typical organic loads [6]. Hybrid technologies that combine advanced oxidation processes (AOP) with biofiltration represent a promising alternative capable of breaking down recalcitrant pollutants, in addition to stabilizing wastewater while improving biodegradation [4,7]. This synergy between radical reactions (•OH, O₃, H₂O₂, TiO₂) and biological processes enables reductions of over 90% in oxygen demand and fine pollutants, while also working to reduce residual toxicity [8,9]. Despite all this, the literature in this field remains fragmented: most studies are limited to a few isolated processes, in the laboratory or under temperate climates [10,11]. Some studies analyze the integrated environmental performance of these systems in arid contexts, nor their ability to adapt to water and heat stress [12,13]. This gap also compromises the possibility of transferring the results to regions such as southwestern Algeria, where the use of treated water is important to ensure water security [14,15].

To address this gap, we conducted a systematic review according to the PRISMA 2020 protocol [16], which identified and compared the performance evaluations of hybrid AOP_biofiltration systems for works published between 2015 and 2026. Its main objective is to analyze its purification efficiency, its impact on the arid environment, and its sustainability [17]. Our approach is based on methodological rigor and transparency, with the objective of providing a critical synthesis of technological advances, leading to the formulation of recommendations for future wastewater treatment plants operating underin extreme climatic conditions, and to a direct contribution to the achievement of Sustainable Development Goals 6 and 13 of the United Nations.

2. Materials and Methods

2.1. Methodological Framework

In this study, we adopted the PRISMA 2020 methodology (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), which ensures rigor, transparency, and accuracy in the reproduction of systematic reviews [16,18]. This was achieved through a protocol that consists four steps: identification, selection, eligibility, and inclusion. The search was carried out between 2015 and 2026 using the Web of Science, Scopus, ScienceDirect, SpringerLink, PubMed and Google Scholar databases. Keywords combined with Boolean operators (“AND”, “OR”) were also used:

(“Wastewater treatment” or “sewage treatment”) and (“Advanced oxidation processes” or “AOPs” or “Fenton” or “ozonation” or “Photocatalysis”) and (“Biofiltration” or “Biofilter”) and (“Hybrid process” or “Integrated system”) and (“Sustainability” or “Reuse” or “Environmental impact”).

2.2. Inclusion and Exclusion Criteria

Precise scientific criteria were adopted to select specific studies prior to the analysis phase, to ensure the comparability and relevance of the results.

Table 1. Methodological framework for the selection of documentary sources: inclusion and exclusion.

Category	Inclusion criteria	Exclusion criteria
Document type	Peer-reviewed articles, systematic reviews and technical reports	Unassessed communications, chapters without data, grey literature
Period	2015 – 2026	Before 2015
Language	English or French	Other languages
Thematic	Special studies on hybrid AOP-biofiltration processes for wastewater treatment.	Studies dealing with a single process (AOP or isolated biofiltration)
Experimental data	Quantitative results on COD, BOD, nutrients, micropollutants, or ecological impacts	Studies without quantitative data
Environmental context	Studies in temperate, arid or semi-arid climates	Studies without ecological link or environmental assessment

Table 1. Methodological framework for the selection of documentary sources: inclusion and exclusion.

Category	Inclusion criteria	Exclusion criteria
Document type	Peer-reviewed articles, systematic reviews and technical reports	Unassessed communications, chapters without data, grey literature
Period	2015 – 2026	Before 2015
Language	English or French	Other languages
Thematic	Special studies on hybrid AOP-biofiltration processes for wastewater treatment.	Studies dealing with a single process (AOP or isolated biofiltration)
Experimental data	Quantitative results on COD, BOD, nutrients, micropollutants, or ecological impacts	Studies without quantitative data
Environmental context	Studies in temperate, arid or semi-arid climates	Studies without ecological link or environmental assessment

2.3. Selection Process

We identified 1,248 articles. After removing duplicates (312), 936 publications underwent an initial screening based on their title and abstract. Subsequently, 226 articles were evaluated using the full text and only 78 studies were retained for final analysis.

Figure 1 presents the 2020 PRISMA diagram, which illustrates the entire selection process. The use of this protocol reduced selection bias and ensured balanced coverage of experimental, analytical, and modeling approaches [18,19].

2.4. Data Analysis and Classification

The grouped studies were selected according to three analytical criteria:

1. Treatment performance (BOD removal, COD removal, nutrient and micropollutant absorption);

2. Environmental assessment (residual toxicity, biodegradability, and carbon footprint);

3. Technical and economic viability (potential for energy consumption, maintenance and reuse).

The OriginPro 2023b and RStudio 2024 software were used for data standardization and synthesis. A multi-criteria approach was adopted for performance classification, inspired by the integrated environmental assessment framework [1,2].

The main radical-generating reactions are illustrated below:

H₂O₂+hυ→2⋅OH

O₃+H₂O→2⋅OH+O₂

Fe²⁺+H₂O₂→Fe³⁺+OH⁻+⋅OH (Fenton’s reaction)

These radicals attack the C–C, C–H, C–O, and C–N bonds of organic molecules, triggering a chain reaction that leads to the complete mineralization of pollutants into CO₂ and H₂O (Belarbi et al., 2026). This is why AOPs are particularly well suited to wastewater containing compounds that are not biodegradable or toxic to microorganisms [18,20].

3. Results

3.1. AOP Processes

3.1.1. Main Techniques

Several AOP variants have been developed to generate hydroxyl radicals, depending on the physicochemical conditions of the water [17].

a) Ozonation (O₃)

The ozonation process is based on the catalytic decomposition of ozone into hydroxyl radicals. It is effective for the decomposition of phenols, pharmaceuticals, and dyes [9]. However, it requires careful and rigorous monitoring of temperature and pH.

b) Fenton and Photo-Fenton Processes

The Fenton process combines Fe²⁺ and H₂O₂, generating radicals according to the reaction:

Fe²⁺ + H₂O₂ → Fe³⁺ + OH⁻ + OH⁻

Photo-Fenton technology, using a solar energy source or ultraviolet radiation, regenerates ferrous iron and improves the reaction kinetics. These processes are very economical and extremely effective for treating hospital and agroindustrial wastewater [21].

c) UV/H₂O₂

UV irradiation acts by decomposing hydrogen peroxide to release hydroxyl radicals. This method is simple, efficient, and catalyst-free, but its energy consumption is high when large quantities are used [22].

d) TiO2 photocatalysis

UV-activated titanium dioxide (TiO₂) is used in heterogeneous photocatalysis, promoting the photocatalytic generation of photoinduced electrons and holes, leading to the formation of hydroxyl radicals. This technology is stable, reusable, and ideally suited for the treatment of complex wastewater [23].

e) Peroxone O₃ + H₂O₂

This process generates highly oxidized hydroxyl radicals, ensuring rapid degradation of mixed micropollutants (88–97%) with moderate energy consumption (25–45 W/L⁻¹). It is considered a highly effective pretreatment before biofiltration in hybrid AOP–biofiltration systems [21,24].

Table 1. Average degradation efficiencies of the main AOPs according to the type of pollutant.

Type of AOP process	Targeted pollutants	Average degradation rate (%)	Purification time (min)	Reference
Ozonation (O3)	Phenols, dyes, hormones	85–95	30–60	[25]
Fenton / Photo-Fenton	Antibiotics, COD, PFOA	90–98	40–80	[21]
UV/H2O2	Pesticides, chlorinated solvents	75–90	30–50	[22]
TiO2 Photocatalysis	Microplastics, endocrine disruptors	80–96	60–120	[25]
O3 + H2O2 (peroxone process)	Mixed micropollutants	88–97	25–45	[24]

Table 1. Average degradation efficiencies of the main AOPs according to the type of pollutant.

Type of AOP process	Targeted pollutants	Average degradation rate (%)	Purification time (min)	Reference
Ozonation (O3)	Phenols, dyes, hormones	85–95	30–60	[25]
Fenton / Photo-Fenton	Antibiotics, COD, PFOA	90–98	40–80	[21]
UV/H2O2	Pesticides, chlorinated solvents	75–90	30–50	[22]
TiO2 Photocatalysis	Microplastics, endocrine disruptors	80–96	60–120	[25]
O3 + H2O2 (peroxone process)	Mixed micropollutants	88–97	25–45	[24]

3.1.2. Environmental and Technological Limitations

Despite its effectiveness, AOPs have objectives that impose several constraints, particularly operational and environmental ones.

• High energy consumption, especially for UV/H₂O₂ systems and photocatalytic processes, which require continuous and powerful light sources [1,26].
• Formation of certain toxic byproducts resulting from incomplete reactions, such as aldehydes, bromates, or carboxylic acids [27,28].
• Operating and maintenance costs: Chemical reagents (H₂O₂, O₃) and catalyst regeneration contribute to increased operating costs [14,29].
• Limited effectiveness in heavily contaminated wastewater, where natural organic matter acts as a radical scavenger, thus reducing the overall efficiency of the process [30].

Therefore, despite the effectiveness of AOP processes in primary degradation, their integration with biological processes such as biofiltration remains essential to ensure complete mineralization, reduce toxicity, and contribute to the sustainability of treatment [19,22].

3.2. Biofiltration in Granular Support

3.2.1. Principle and Operation

The biofiltration process generally relies on the development of microbial biofilms attached to granular supports such as sand, activated carbon, biochar, or zeolite [31]. These biofilms decompose dissolved organic matter as wastewater passes through the filter layer. The main biochemical reactions follow Monod-type kinetics [30].

The following figure (Figure 2) illustrates the biofiltration process of raw water rich in organic matter and microorganisms, using a fixed biomass biofilm layer supported by a granular substrate, as well as the treated water obtained at the outlet.

The growth of microorganisms (nitrifying bacteria, heterotrophic bacteria, as well as protozoa and fungi) on the surface of the substrate occurs in successive layers [32], forming a biofilm capable of decomposing dissolved organic matter and nutrients. (NH₄⁺, NO₃⁻, PO₄³⁻).

In general, the kinetics of hydrolysis follow a Monod model, analogous to the Michaelis-Menten law in enzymology:

$$v={\displaystyle \frac{v_{max}.S}{K_s.S}}$$

Where:

• v = rate of degradation of organic matter degradation (mg·L⁻¹·h⁻¹),
• v_max = maximum microbial growth rate,
• S = concentration of the organic substrate (mg·L⁻¹),
• KS = half-saturation constant (mg·L⁻¹).

This equation allows us to model the relationship between the substrate concentration (biodegradable organic matter) and the rate of biodegradation in the biofilm. The overall reaction can be simplified using the following relationship:

$$\mathrm{O}\mathrm{r}\mathrm{g}\mathrm{a}\mathrm{n}\mathrm{i}\mathrm{c}\mathrm{ }\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{t}\mathrm{e}\mathrm{r}+{\mathrm{O}}_2\stackrel{\mathrm{m}\mathrm{i}\mathrm{c}\mathrm{r}\mathrm{o}\mathrm{o}\mathrm{r}\mathrm{g}\mathrm{a}\mathrm{n}\mathrm{i}\mathrm{s}\mathrm{m}\mathrm{s}}{\to }{\mathrm{C}\mathrm{O}}_2+{\mathrm{H}}_2\mathrm{O}+\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s}$$

The granular support therefore plays a triple role: it provides an adhesion surface, promotes oxygen transport, and stabilizes the biofilm against hydraulic fluctuations [32].

3.2.2. Influencing Parameters

The efficiency of biofiltration depends on several factors, including hydraulic, physicochemical, and biological factors [33].

• Hydraulic contact time (HCT): The optimal time is between 20 and 60 minutes, as it promotes exchanges between the substrate and the biofilms and also improves BOD₅ degradation [32].
• Temperature: The reaction rate increases to 30-35 ° C and then decreases.
• COD/BOD₅ ratio: < 2, indicating the ease of biodegradation of organic matter; however, the decomposition is slow.
• Support typeType: The roughness, specific surface area of the substrate, and porosity of the biofilm affect the density and stability of the biofilm.
• Oxygenation: A dissolved oxygen concentration between 1 and 3 mg·L⁻¹ is necessary to maintain effective nitrification.
• Volumetric loading: If the volumetric loading exceeds 2 kg BOD₅·m⁻³·d⁻¹, this can lead to biofilm separation, resulting in decreased purification efficiency [32].

3.2.3. Performance and Durability

The removal performance varies depending on the material used and the operating conditions. Table 2 summarizes the average removal rates of different biofiltration media used in domestic wastewater treatment, based on recent studies.

What distinguishes activated carbon and biochar is their large specific surface area, as well as their resistance to clogging and the increased lifespan of the biofilm. In addition to their high absorption capacity, they contribute to improved removal of microorganisms such as pesticides and pharmaceuticals [22]. In the long term, the durability of biofilms depends on regular hydraulic maintenance (blockage prevention and backwashing) with periodic renewal of the support, which is carried out by thermal or chemical processes [37].

3.3. Mechanism of Chemical-Biological Synergy

The combination of biofiltration and advanced oxidation processes (AOPs) relies on two complementary mechanisms: rapid chemical oxidation through hydroxyl radicals (•OH), immediately followed by biodegradation carried out by microorganisms attached to a granular support [38]. During the initial phase, the AOPs (ozonation, photo-Fenton, TiO₂ photocatalysis, plus UV/H₂O₂) convert resistant compounds into a series of more biodegradable intermediates, resulting in an increase in the BOD₅/COD ratio, the main indicator of biodegradability [22]. Subsequently, these partially oxidized products serve as substrates that can be absorbed by nonnutritive biofilm bacteria, thus ensuring their final mineralization into CO₂, H₂O, and biomass [39].

$$\mathrm{C}\mathrm{o}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}\mathrm{x}\mathrm{ }\mathrm{o}\mathrm{r}\mathrm{g}\mathrm{a}\mathrm{n}\mathrm{i}\mathrm{c}\mathrm{ }\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{d}\mathrm{s}\begin{array}{c}\stackrel{•OH}{\to }\\ {AOP}_s\end{array}Biodegradable\mathrm{ }intermediates\begin{array}{c}\stackrel{ensymatic\mathrm{ }activity}{\to }\\ biofilm\end{array}{\mathrm{C}\mathrm{O}}_2+{\mathrm{H}}_2\mathrm{O}+\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s}$$

This biochemical synergy helps reduce the toxicity of pretreated water, stabilizes pH, and limits the production of residual sludge [40,41]. Microbial biofilms also complement the treatment process by removing nutrients (phosphorus and nitrogen), resulting in wastewater that can be reused in agriculture or discharged into a controlled environment [42].

3.3.1. Case Studies and Overall Performance

Several large-scale experimental studies confirm the effectiveness of the AOP-biofiltration combination in different climatic contexts:

• Europe (Germany, France): The ozone and bioactivated carbon (BAC) systems contributed to the removal of more than 90% of total residues of pharmaceuticals, pesticides, and endocrine disruptors [43].
• North Africa (Algeria, Morocco): Photo-Fenton biofiltration techniques have shown COD efficiencies >95% for dyes and phenolic compounds under solar irradiation [44,45].
• Asia (China and India): TiO₂/UV + biochar systems have contributed to an 85–92% reduction in TOC with moderate energy consumption [46].

The figure below (Figure 5) presents a conceptual diagram of the AOP-biofiltration coupling, illustrating preoxidation with the formation of biodegradable media in addition to the final biofiltration.

3.3.2. Economic and Energy Analysis

Although the initial investment costs of hybrid systems are high, their superior performance and reduced sludge production make them among the most efficient and cost-effective technologies in the medium and long term [47]. Energy requirements vary depending on the oxidation process and the size of the installation [36,48].

Table 3. Techno-economic evaluation of hybrid AOP systems for wastewater treatment.

Hybrid system	Main AOP process	Elimination efficiency (%)	Energy consumption (kWh/m3)	Treatment cost (€/m3)	Reference
O3 + Organic activated charcoal	Ozonation	90–95	0,35–0,50	0,25–0,40	[49]
Photo-Fenton + Biofilter Sand	Solar Photo-Fenton	93–96	0,20–0,30	0,18–0,28	[15]
UV/H2O2 + Activated charcoal	UV Photolysis	88–92	0,40–0,55	0,30–0,45	[50]
TiO2/UV + Biochar biofilter	Photocatalysis	85–90	0,25–0,38	0,22–0,32	[51]

Table 3. Techno-economic evaluation of hybrid AOP systems for wastewater treatment.

Hybrid system	Main AOP process	Elimination efficiency (%)	Energy consumption (kWh/m3)	Treatment cost (€/m3)	Reference
O3 + Organic activated charcoal	Ozonation	90–95	0,35–0,50	0,25–0,40	[49]
Photo-Fenton + Biofilter Sand	Solar Photo-Fenton	93–96	0,20–0,30	0,18–0,28	[15]
UV/H2O2 + Activated charcoal	UV Photolysis	88–92	0,40–0,55	0,30–0,45	[50]
TiO2/UV + Biochar biofilter	Photocatalysis	85–90	0,25–0,38	0,22–0,32	[51]

The study shows that AOP biofiltration systems have high disinfection efficiency, exceeding 90%, with moderate energy consumption and low sludge production, resulting in competitive economic value, which is important and appropriate, particularly for developing countries and arid regions.

The following table (Table 4) presents a comparative analysis of the performance of the main hybrid AOP-biofiltration systems mentioned in the literature. It also highlights the cost-effectiveness of the different technologies, their energy requirements, their technological maturity, and their applicability depending on the climatic context.

The table above demonstrates the effectiveness of advanced hybrid biological treatment systems, which achieve an removal rate of over 90% with moderate energy consumption, proving their efficiency and importance in the sustainable treatment of wastewater.

3.4. Environmental Assessment and Sustainability

3.4.1. Life Cycle Assessment (LCA) and Carbon Footprint

The complete life cycle assessment (LCA) process is crucial to assess the environmental impacts of AOP biofiltration technology compared to conventional biological treatments [51].

The entire operational cycle must be considered, from the production of chemical reagents (ozone, H₂O₂, catalysts) through energy consumption and sludge production to the discharge of treated water [51].

The main impact categories considered according to ISO 14040 and 14044 are:

• Global Warming Potential (GWP),
• Eutrophication,
• Acidification,
• Aquatic ecotoxicity.

Hybrid AOP biofiltration systems reduce the global warming potential (GWP) by approximately 40% compared to using AOP alone, due to lower energy and chemical consumption within the biological filter [54]. One factor contributing to the overall improved sustainability of this technology is the reuse of treated wastewater for irrigation or industrial uses [23,53].

The main factors contributing to the carbon footprint are the following:

• Energy demand for the production of ozone or UV radiation production;
• Consumption of reagents (H₂O₂, Fe²⁺, catalysts);
• Sludge treatment;
• Maintenance and transport activities.

Integration of renewable energy, such as solar power and biogas, reduces emissions to less than 0.4 kg CO₂ eq/m³ of treated water [50,55].

3.4.2. Contribution to Sustainable Development Goals (SDGs)

Hybrid AOP-biofiltration systems contribute effectively and directly to the achievement of many Sustainable Development Goals (SDGs) of the United Nations, such as:

• SDG 6 - Clean water and sanitation: The goal is to produce high-quality wastewater free of micropollutants, pathogens, and pharmaceuticals and to promote the safe reuse of wastewater [56].
• SDG 12 – Rationalize consumption and production: Work toward the recovery of byproducts (energy, heat and sludge) and promote the reduction of chemical waste, in accordance with the principles of the circular economy [55,56].
• SDG 13 - Combating– climate change: Work toward reducing energy consumption and promoting the integration of low-carbon processes (solar photocatalytic conversion, ozonation optimization) [57].

According to the United Nations Water Committee (2024), the combination and synergy of AOPs and biofiltration processes constitute a key innovation for the sustainable and economical management of wastewater in arid and semi-arid regions.

The following figure (Figure 6) presents the basic steps of the life cycle assessment (LCA) process of the AOP–biofiltration system and the extent of its contributions to achieving the Sustainable Development Goals (Objections 6 and 13), and also highlights the carbon flux rate, energy savings, and positive impacts on the local environment.

3.4.3. Comparison with Conventional Activated Sludge Processes

The combination of AOP and biofiltration offers numerous environmental and operational advantages compared to its traditional counterparts, such as activated sludge (AS) [55].

Table 5. Comparative evaluation of energy, environmental, and operational parameters between conventional wastewater treatment processes and AOP–biofiltration.

Setting	Activated sludge (CAS)	AOP–Biofiltration
Energy consumption	0,7 – 1,2 kWh/m3	0,4 – 0,8 kWh/m3
Sludge production	High (40–60 g MES/m3)	Weak (15–25 g MES/m3)
Micropollutant removal	Limited (< 50%)	Excellent (> 90%)
Effluent reuse	Average	Raised (irrigation, industrial use)
GHG emissions (CH4, N2O)	Important	Reduced (controlled oxidation, less aeration)
Process stability	Sensitive to toxic substances	Improved (pre-oxidation of recalcitrant compounds)

(Source: [18,58,59].

Table 5. Comparative evaluation of energy, environmental, and operational parameters between conventional wastewater treatment processes and AOP–biofiltration.

Setting	Activated sludge (CAS)	AOP–Biofiltration
Energy consumption	0,7 – 1,2 kWh/m3	0,4 – 0,8 kWh/m3
Sludge production	High (40–60 g MES/m3)	Weak (15–25 g MES/m3)
Micropollutant removal	Limited (< 50%)	Excellent (> 90%)
Effluent reuse	Average	Raised (irrigation, industrial use)
GHG emissions (CH4, N2O)	Important	Reduced (controlled oxidation, less aeration)
Process stability	Sensitive to toxic substances	Improved (pre-oxidation of recalcitrant compounds)

(Source: [18,58,59].

Therefore, from an environmental and economic perspective, the AOP–biofiltration process is efficient and energy-saving, with a significantly reduced carbon footprint, and is part of a circular and sustainable economy [58].

As such, it is considered an innovative and high-performing solution for wastewater treatment in areas with limited water resources [59].

3.5. Modelling of the Hybrid AOP–Biofiltration System

3.5.1. Objectives of the Model

Through this modeling, we aim to simulate and predict the performance of a hybrid system that combines advanced oxidation processes (AOPs) with biofiltration [29,60].

Allows for:

• Simulation of the effect of operating parameters – oxidant dosage, contact time, pH, hydraulic contact time (HCT) – on the efficiency of COD and micropollutant removal [8];
• The optimization process of the AOP biofilter sequence aims to maximize biodegradability (BOD₅/COD) while also streamlining energy consumption and sludge production [26];
• Providing a predictive framework for determining the size and capacity of facilities subject to water, heat, and load constraints, particularly in arid and semi-arid regions [26].

3.5.2. Model for the AOP Phase

We assume that in the oxidation phase, there is a decrease in the concentration of pollutant (or COD) C(t) according to a pseudo-first-order kinetic model [26].

$${\displaystyle \frac{dC}{dt}}=-k_{AOP}.C$$

where:

• C = pollutant concentration (mg/L) at time t;
• kAOP = apparent rate constant (min⁻¹), which varies depending on the process (ozone, Fenton, UV/H₂O₂) and operating conditions [33].

The following figure (Figure 7) illustrates the temporal evolution of the pollutant concentration during the AOP step and also highlights the degradation rate obtained under the photo-Fenton process conditions.

Analytical solution:

$$C\left(t\right)=C_0.e^{-k_{AOP}.t}$$

With: C0 being the initial concentration at the start of the AOP phase.

It is also advantageous to offer increased biodegradability after AOP [26]:

$$f_{BD}={\left.{\displaystyle \frac{{BOD}_5}{COD}}\right|}_{Before\mathrm{ }AOP}$$

It can also be determined that the resulting biodegradable fraction is directly proportional to the concentration remaining after AOP:

$$S_0=f_{BD}.C\left(t_1\right)$$

Here t1 is the contact time in the AOP step.

3.5.3. Model for the Biofiltration Phase

We adopted a Monod-type model for the biological phase (biofilms on a granular support) [26].

$$r={\displaystyle \frac{v_{max}.S}{K_s+S}}$$

Given that:

• r = consumption rate of the biodegradable substrate (mg·L⁻¹·h⁻¹);
• v_max = maximum consumption rate (mg·L⁻¹·h⁻¹)
• KS = half-saturation constant (mg·L⁻¹);
• S = concentration of biodegradable substrate at the biofiltration inlet (mg·L⁻¹).

The mass balance in the biofilter can be formulated as follows:

$${\displaystyle \frac{dS}{dt}}=-{\displaystyle \frac{v_{max}.S}{K_s+S}}-k_d.S$$

where k_d is the biofilm deactivation or loss coefficient (h⁻¹).

As can be seen in the following figure (Figure 8), the substrate concentration decreases considerably, confirming the biodegradation capacity and efficiency predicted by the Monod model.

3.5.4. Coupling AOP + Biofiltration

Following the hybrid frameworks proposed by [61], we sequentially combine the overall model between the two phases (AOP + biofiltration).

1. AOP phase (duration t₁):

$$C_1=C_0.e^{-k_{AOP}.t_1}$$

2. Biofilter inlet:

$$S_0=f_{BD}.C_1$$

3. Biofiltration phase (duration t₂): solve the previous differential equation for S(t) on [0, t2]. This gives us Sfinal.

4. Overall removal efficiency (COD or equivalent):

$$\mathrm{ɳ}={\displaystyle \frac{C_0-S_{final}}{C_0}}\times 100\mathrm{\%}$$

This integrated approach is consistent with modern biologically coupled therapy (BPT-biological) models [27,61].

The figure below (Figure 9) presents a multiaxis comparison of elemental sensitivity, which indicates that kBPT and vmax exert the most significant influence on elimination efficiency.

3.5.5. Simulation and Validation

- Propose a simulation that includes several typical scenarios:

• Scenario A: AOP = ozonation, kAOP = 0.05 min⁻¹, t₁ = 30 min; biofilter, vmax = 1.5 mg / L h, KS = 20 mg/L, t₂ = 60 min.
• Scenario B: AOP = photo-Fenton, kAOP = 0.08 min⁻¹, t₁ = 40 min; biofilter, vmax = 2.0 mg / L h, KS = 15 mg/L, t₂ = 45 min.

3.5.6. Performance Indicators and Model Outputs

Among the indicators that will be extracted using the model are:

• overall efficiency η (in %);
• Biodegradability gain:

$$G_B={\displaystyle \frac{{\left(\raisebox{1ex}{${BOD}_5$}\!\left/ \!\raisebox{-1ex}{$COD$}\right.\right)}_{final}}{{\left(\raisebox{1ex}{${BOD}_5$}\!\left/ \!\raisebox{-1ex}{$COD$}\right.\right)}_{initial}}}$$

• Specific energy consumption (approximation):

$$E_{sp}={\displaystyle \frac{P\times t_{tot}}{V_{ttreated}}}$$

where P is the power (kW), ttot = t₁ + t₂ (h) and Vtreated (m³).

• The process for estimating the sludge produced or the biomass (useful for comparison with conventional systems): based on Vmax and biological yield [62].

3.5.7. Scientific Contribution of Modeling

• It enables a mechanistic understanding of the biochemical synergy process in hybrid AOP-biofiltration processes [37];
• It also allows for the estimation and preliminary sizing of installations adapted to arid regions with limited water and energy resources [26];
• Offers a tool to streamline energy consumption and improve economics, in accordance with the principles of the circular economy and the Sustainable Development Goals 6 and 13 [26];
• It also paves the way for the integration of artificial intelligence (neural networks, hybrid mechanistic/data-driven models) and digital twins for real-time control [63].

3.5.8. Limitations and Future Work

• The model considers a linear sequence of biofiltration of AOP, without integrating the inhibitory effects associated with secondary oxidation products or potential reactions [27].
• There is variation in kinetic parameters (kₐₒₚ, vₘₐₓ, Kₛ, kd, fBD) depending on effluent quality, granular support, temperature, and climate, which requires local calibration in arid environments [64].
• The energy and economic aspects remain simplified; a life cycle assessment (LCA) process is recommended in addition to multicriteria optimization [8,47].
• The integration of hybrid mechanistic/data-driven models (artificial neural networks, machine learning) allows us to obtain adaptive control in order to cope with load variations, difficult conditions, and hydraulic fluctuations [64].

4. Discussion

4.1. Strengths and Advantages of the AOP-Biofiltration Combination

Combining advanced oxidation processes (AOP) and biological filtration in granular media offers several significant environmental, technical, and operational advantages. This combination also ensures the easy and efficient removal of persistent micropollutants and biodegradable organic matter, thanks to the conversion of complex compounds into intermediates that microbial biofilms can more easily absorb [1,6]. This approach contributes to improving and sustaining treatment: biofiltration reduces the chemical requirements and energy consumption of wastewater treatment plants, and the reuse of treated water provides important support for circular water management [1].

Therefore, this process is highly adaptable: thermal treatment processes (ozonation, UV/H₂O₂, and TiO₂-photocatalysis) can be modified according to the quality of raw water, and biofilters based on local materials (sand, activated carbon, zeolite and biochar) offer an economical, sustainable, and context-appropriate solution in resource-limited areas [14,52].

4.2. Technical, Economic and Environmental Limitations

Despite its capabilities and high performance, the AOP biofiltration system still suffers from several limitations. From an energy perspective, organic thermal treatment processes - such as ozonation and UV treatments - require high electricity consumption (0.4 to 0.8 kWh/m³), which limits their sustainability when the energy source is fossil fuels [14]. From an operational standpoint, biofilter maintenance still presents several challenges, including media saturation, low pressure, biological clogging, and the need for periodic backwashing or regeneration, which increases operating costs and reduces treatment sustainability [65]. Environmentally, the formation of oxidized by-products (bromates, aldehydes, and carboxylic acids) can generate residual toxins if the oxidation conditions are not controlled [64]. Finally, large-scale validation remains limited: most studies are still experimental or conducted in the laboratory [53]. Tests under real-world conditions are still needed to confirm the effectiveness of the process in the face of variations in load, temperature, and turbidity [66].

4.3. Research Gaps

Despite the significant volume of research dedicated to the study of AOP-biofiltration systems, several scientific gaps remain that hinder their widespread adoption, particularly in arid and semi-arid regions. Most of these studies and research remain confined to laboratories or experimental fields, and long-term performance data under real-world conditions are still scarce [7,19,53]. Furthermore, the lack of standardized protocols for evaluating treatment performance and the absence of consistent indicators make direct comparison between studies and the quantitative standardization of results difficult [17,21].

Furthermore, the processing products derived from AOPs and their residual toxicity are still not sufficiently studied, although several studies have indicated the potential for the formation of harmful oxidized byproducts in the long term [22,28,40]. In addition, the interactions between the structure of microbial communities and prechemical oxidation within biofilms, as well as their potential effects on the stability and robustness of the process, are still not well understood [32,33,64].

In addition to all this, technical and economic analyses and life cycle assessments (LCAs) are often context-specific and simplified, hindering the generalization of findings to other climatic regions [47,54,55]. Finally, despite the growing interest in artificial intelligence, practical applications of predictive simulation models, artificial intelligence, and digital twins for improving and controlling AOP-biofiltration systems in real time remain considerably limited [14,60,61]. Addressing these shortcomings is a crucial step in developing AOP-biofiltration systems into robust, reliable, and economically viable technologies for sustainable wastewater management in arid environments.

4.4. Future Prospects

The main objectives of future research on the AOP biofiltration system are to improve its technological and environmental efficiency, as well as its energy savings [20].

1. Energy Optimization – Combining renewable energy sources (solar photovoltaics, photovoltaic ozonation, and microturbines) can lead to a 50% reduction in the electrical energy consumption of AOPs [27].

2. Artificial intelligence (AI) – Intelligent monitoring systems based on machine learning have the ability to predict water quality, improve oxidant dosing, and detect biofilter anomalies, contributing to greater stability and operational independence [62].

3. Real-time sensors and control devices – These devices can continuously monitor critical parameters (BOD, COD, turbidity, redox potential, pH and heavy metals), allowing dynamic process control [29].

4. Valorization of by-products – The recovery process of bioactive carbon, the reuse of stabilized sludge, and the conversion of organic waste to biogas are objectives that pave the way for a zero waste approach within a sustainable circular economy [5].

To summarize the main findings and demonstrate the interaction between innovation, governance, and sustainability, the conceptual diagram (Figure 10) presents an integrated view of the combined organic sludge treatment (AOP) and biofiltration system.

This figure illustrates how technological advancements, environmental management, and informed decision-making can work together to improve wastewater treatment efficiency, thus strengthening long-term environmental resilience.

By addressing all the gaps, the AOP biofiltration process has become a next-generation technology that combines modern innovations in bioefficiency, operational intelligence, and environmental resilience [33], and aligns with the objectives of sustainable water management and reuse in the face of climate change and water scarcity [15].

5. Conclusions

This study highlights the significant potential of AOP biofiltration technology to address the main challenges of sustainable water management in arid and semi-arid regions. The results demonstrate improved wastewater quality, with a significant reduction in chemical oxygen demand, microorganisms, and pathogens, exceeding the performance of conventional biological processes.

From an environmental perspective, this combination helps conserve limited water resources, reduces the environmental footprint of wastewater treatment plants, and promotes safe reuse of treated water in the agricultural and industrial sectors. From a social perspective, this technology strengthens resilience to climate change and supports Sustainable Development Goals 6 and 13 through integrated and responsible water management.

Despite all this, several challenges remain, including high short-term energy consumption, complex maintenance, and the need for large-scale validation. Future research should focus on improving energy efficiency, developing sustainable biofiltration materials and membranes, and integrating artificial intelligence for real-time control and predictive maintenance.

Finally, policymakers should be encouraged to support the deployment of these technologies through incentives, targeted funding, and appropriate regulations. Researchers should also strengthen multidisciplinary collaboration involving engineering, the environment, and data science to accelerate the transition to smart, energy-efficient, and environmentally friendly wastewater treatment systems.