Mohammed Kebir

Imen-Kahina Benramdhan

Noureddine Nasrallah

Hichem Tahraoui
email: tahraoui.hichem@univ-medea.dz

Nadia Baït

Houssine Benaissa

Rachid Ameraoui

Jie Zhang
email: jie.zhang@newcastle.ac.uk

Aymen Amin Assadi
email: aymen.assadi@ensc-rennes.fr

Lotfi Mouni

Nadia Bait

Abdeltif Amrane
email: abdeltif.amrane@univ-rennes1.fr

Surface response modeling of homogeneous photo Fenton Fe(III

Keywords:

Introduction

The food industry sector consumes a significant amount of water, resulting in a considerable level of pollution in the aquatic environment due to its discharged wastewater, which is heavily contaminated with colors [START_REF] Compton | Food processing industry energy and water consumption in the Pacific northwest[END_REF]. Moreover, these discharges pose a major health hazard as most dyes are harmful to humans and environment. The treatment of such wastewater presents a significant challenge, particularly for developing countries that lack the necessary tools to incorporate sustainable development concepts effectively [START_REF] Obaideen | The role of wastewater treatment in achieving sustainable development goals (SDGs) and sustainability guideline[END_REF]. Dyes, with their complex chemical structures and the presence of aromatic rings with inorganic ions, are resistant to biodegradation under aerobic conditions [START_REF] Pham | Investigating bio-inspired degradation of toxic dyes using potential multi-enzyme producing extremophiles[END_REF]. Consequently, their aqueous effluents require special treatment due to their unique impact on the natural environment, including toxicity from the parent product and potential by-products [START_REF] Zhang | Brønsted-acid sites promoted degradation of phthalate esters over MnO2: mineralization enhancement and aquatic toxicity assessment[END_REF]. These harmful contaminants need to be removed, and numerous biological, chemical and physical processes are employed for this purpose. However, traditional treatments such as adsorption on activated carbon or natural biosorbents, membrane processes, coagulation-flocculation, and chemical oxidations have disadvantages. For example, they transfer and concentrate the pollutants in one aqueous phase, leading to the formation of concentrated sludge [START_REF] Koul | Application of natural coagulants in water treatment: a sustainable alternative to chemicals[END_REF]. Consequently, this creates a secondary waste problem. Among all the approaches that can be used, the photo-Fenton as a part of the advanced oxidation processes (AOPs) appears to be the process of choosing among all the possible treatment approaches for decontaminating aqueous organic effluents since they allow for total pollutant degradation with producing water and carbon dioxide while also lowering the effluent's overall toxicity [START_REF] Clarizia | Homogeneous photo-Fenton processes at near neutral pH: a review[END_REF][START_REF] Ertürk | Reductant free green synthesis of magnetically recyclable MnFe2O4@ SiO2-Ag core-shell nanocatalyst for the direct reduction of organic dye pollutants[END_REF].

Among the other advantages that encourage the choice of a water treatment process is: effectiveness and simplicity of operation with the possibility of using a wide range of light wavelengths (UV-Vis regions), in order to achieve this objective, natural sunlight is a prejudicial choice and represents a cheap source of energy [START_REF] Navarro | Ferrite formation from photo-Fenton treated wastewater[END_REF].

Comparing the photo Fenton system with other water treatment processes, it has been shown that the use of photo Fenton has the advantage of not forming sludge, being very safe and easy to implement. In addition, it has the advantage of fast reaction.

The photo-Fenton reactions are non-selective reactive oxidizing species-based technologies that enable the oxidation of a wide variety of organic contaminants with pH ranging from 2 to 4. However, a drawback of the photo-Fenton process is the precipitation of ferric oxyhydroxide [START_REF] Benramdane | Optimization of the artificial neuronal network for the degradation and mineralization of amoxicillin photoinduced by the complex ferrioxalate with a gradual and progressive approach of the ligand[END_REF]. The hydroxyl radical is the most often utilized oxidant due to its high reactivity (E • = 2.73 V). In both the homogeneous and heterogeneous phases, POAs exhibit a diversity of oxidation types [START_REF] Zhang | Distinguishing homogeneous advanced oxidation processes in bulk water from heterogeneous surface reactions in organic oxidation[END_REF].

Additionally, in the photo-Fenton process, the regeneration of Fe 2+ ions is best promoted in the presence of certain organic acids chelates such as carboxylates, hydroxy carboxylates of amino polycarboxylates and natural organic acids. The main role of these chelates is integrated into the coordination with Fe 3+ ions, thus inducing a photochemical reduction of Fe 3+ to Fe 2+ through ligand-to-metal charge transfer to generate Fe 2+ ions [START_REF] Xu | Improvement of Fe2+/peroxymonosulfate oxidation of organic pollutants by promoting Fe2+ regeneration with visible light driven g-C3N4 photocatalysis[END_REF].

These characteristics have stimulated the use of ferrioxalate in the photo-Fenton reaction with important advantages of reducing operating costs and making the photo-Fenton process very attractive for various water treatment applications. This is because the ferric-oxalate complex absorbs light energy strongly between 250 and 550 nm and limits the consumption of chemical products, providing a high quantum yield and ensuring the regeneration of ferrous iron and additional production of HO radicals [START_REF] Liu | Extending semiconductor-based photo-Fenton reaction to circumneutral pH using chelating agents: the overlooked role of pH on the reduction mechanism of Fe3+[END_REF].

On the other hand, ferrioxalate complexes allow the formation of stable complexes between ferric ions and organic species in the contaminated solution. In addition, iron precipitation is inhibited even at near-neutral pH in the presence of the ferrioxalate complex. This last point is of great interest when treating industrial effluents loaded with coloring pollutants, where the pH is generally close to neutral or alkaline [START_REF] Doumic | Enhancement of a solar photo-Fenton reaction by using ferrioxalate complexes for the treatment of a synthetic cotton-textile dyeing wastewater[END_REF][START_REF] Ye | Mineralization of pentachlorophenol by ferrioxalate-assisted solar photo-Fenton process at mild pH[END_REF].

In this work, we were interested in the removal of SG detergent dye, which poses a serious problem of water contamination due to the activity of local industry, and in our knowledge, no research has been found for the SG dye degradation by photo-Fenton process before.

However, in the study of the oxidation of the SG dye with the modified photo-Fenton homogeneous system, the reaction is done between the complex Fe(III) and a ligand under a sunlight source of irradiation as follows [START_REF] Benramdane | Optimization of the artificial neuronal network for the degradation and mineralization of amoxicillin photoinduced by the complex ferrioxalate with a gradual and progressive approach of the ligand[END_REF]:

Fe 3+ (C 2 O 4 ) n (3-2n) + hv→Fe 2+ + (n -1) C 2 O 4 2-+ C 2 O 4 2- (1)
While the second process of the modified photo Fenton oxidation reaction is based on the complex consisting of Fe(II), the organic ligand and the oxidant H 2 O 2 , the mixture is irradiated with a sunlight source, according to the following reaction:

Fe 2+ C 2 O 4 + H 2 O 2 + hv→Fe 3+I (C 2 O 4 ) + + OH • + OH (2)
In this way, the strategy focused in this study shows that SG organic dye widely used in the food industry, iron ligands and sunlight can potentially be used in the modified photo-Fenton treatment process to prevent iron precipitation at a neutral pH range.

A study of the parameters influencing the photo Fenton process was undertaken as well as the influence of the addition of inorganic ions and scavengers in order to approach the real effluent and to obtain a complete SG degradation and mineralization.

Moreover, a Box-Behnken statistical experiment design based on response surface analysis was applied for this context, by considering the operating parameters as the independent variables and the rate of photodegradation and mineralization as dependent variables [START_REF] Garg | Optimization methodology based on neural networks and box-behnken design applied to photocatalysis of acid red 114 dye[END_REF]. The kinetics of photodegradation and mineralization are also investigated.

We were interested in textile dyes because they pose a real problem of water contamination due to the activity of local industry, and their degradation has received scant attention in the literature. Among all the approaches that can be used in advanced oxidation processes (AOPs), photo-Fenton appears to be the process of choice among all the possible treatment approaches for contaminated aqueous effluents since they allow for total pollutant degradation while also lowering the effluent's overall toxicity. The creation of active and non-specific species such as hydroxyl radicals is at the heart of AOPs. Photocatalysis looks to be one of the most cost-effective methods for achieving organic compound mineralization.

Additionally, this study aims to investigate the utilization of statistical analysis tools and response surface methodology for the optimization of the SG degradation process. The developed model is used to identify the optimal parameters that enhance the degradation process efficiency and yield valuable insights, despite the complexities associated with the modified photo-Fenton degradation system. The obtained optimal parameters are validated through experiments.

The paper is organized as follows. Section 2 introduces the materials and methods. Detailed results are given and discussed in Section 3. Some concluding remarks are drawn in Section 4.

Materials and methods

Chemicals

The chemicals reagents used in this study are Sodium bicarbonate NaHCO 3 (>99%, Sigma Aldrich), Sodium chloride NaCl (>99 Ultra-pure water was used to prepare solutions with high-purity. The dye is provided by an industrial food company, and a stock solution of initial SG dye concentration was prepared and used during all the experimental runs. A known concentration of H 2 O 2 solution was prepared with distilled water by dilution of 30% w/v of stock solution and stored in amber-colored light-resistant glass bottles. All chemical substances are used without modification as received from the supplier.

Analytical methods

To determine the SG dye concentration of each sample throughout the photo-Fenton reaction time, a Shimadzu spectrophotometer analyzer (UV -1800, Japan) at a maximum wavelength of λ = 520 nm was used and a HANNA pH meter is used to measure the pH levels of the solution.

In addition, the COD of samples at different operating conditions was also analyzed by the closed reflux titrimetric method to estimate the mineralization of SG dye [START_REF] Dissanayake | Mineralization of persistent azo dye pollutants by a microaerophilic tropical lake sediment mixed bacterial consortium[END_REF]. The following formula (3 &nd 4)are used to calculate the dye removal yield by degradation and mineralization:

R% = ( C o -C t C o ) x 100 (3)
Where; C o and C t are the SG dye concentrations (mg/L) in the aqueous solutions before and after the reaction, respectively.

COD%

= ( COD o -COD t COD o ) x 100 (4)
Where; COD o and COD t are the initial and at time (t) chemical oxygen demand of liquid SG dye (mg O 2 / L), respectively.

Box-Benhken design

The Box-Behnken design (BBD), introduced by Box and Behnken in 1960, is a procedure to establish a statistical model within the framework of response surface methodology (RSM). This empirical model, in the form of a quadratic model, establishes a relationship between experimental factors and the resulting outcomes. [START_REF] Bouchelkia | Jujube stones based highly efficient activated carbon for methylene blue adsorption: kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches[END_REF].

To determine the number of experiments (N) required for BBD, the following formula is employed: N = 2 K⋅(K -1) + Co. Here, K represents the number of factors, as discussed by Ferreira et al. in 2007 and Co signifies the number of repetitions of the center point. It is important to note that all factors are assigned three coded levels: low (-1), medium (0), and high (+1). To fit the experimental data to a second-order polynomial eq. ( 5) and identify the relevant model terms, a non-linear regression analysis is conducted.

Y = В o + ∑ k i В i x i + ∑ k i В ii x 2 + ∑ k ij В ij x i x j + E (5)
In the above equation, Y represents the dependent variable, which denotes the SG uptake. The number of independent variables, or factors, is represented by k. Each independent variable is denoted by x i , corresponding to its coded level. The regression coefficient at the center point is denoted as β o , B i represents the linear coefficient for the ith independent variable, B ii represents the quadratic coefficients for the ith variable, and B ij signifies the second-order interaction coefficient between the ith and the jth independent variables. The term E denotes the error component within the model. The works by Das and Das in 2014 and Shahbazi et al. in 2020 provide further insight into these variables and coefficients [START_REF] Bouchelkia | Jujube stones based highly efficient activated carbon for methylene blue adsorption: kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches[END_REF]. In order to examine the effect of independent parameters X i and their interactions on a quantity of interest of the process Y (yield), called response on the rate of photodegradation in (%) and mineralization (%) of the SG dye and to optimize the operating conditions, the response surface methodology (RSM) was employed. Coded values of factors are usually used and the relationship between the actual values and the coded values is defined as:

x i = X i -X 0 ΔX i (6)
Where X i is the actual value of the ith variable; x i is the coded value of X i ; X o is the actual value of X i at the center point, and Δ X i is the step change [START_REF] Bouchelkia | Jujube stones based highly efficient activated carbon for methylene blue adsorption: kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches[END_REF].

In this study, the BBD technique was used for two distinct processes. In the first process, the efficiency of the complex (Fe(III)/Lig) for the degradation of food colorings was tested. For this purpose, three independent parameters were chosen and they are: the Fe(III) concentration (X 1 ), the molar ratio between ligand and iron (Lig/Fe(III)) (X 2 ), and the dye concentration (X 3 ). The second process was used to evaluate the efficiency of the complex (Fe(II)/Lig) in the degradation of food colorings. In this case, four independent factors were selected: X 1 : the concentration of Fe(II), X 2 : the molar ratio between the ligand and the iron (R = Lig/Fe(III)), X 3 : the concentration of the dye and X 4 : the H 2 O 2 concentration. In both experimental designs, the rate of degradation (R %) and the yield of mineralization (COD%) were used as response variables (Y). Table 1 summarizes the factors with their delimited study ranges for the two processes. The intervals of each parameter were fixed after preliminary tests. The JMP program (JMP® Pro 13.0.0) was used to perform the statistical analysis.

In order to evaluate the efficiency of the BBD models of each output for the two processes, statistical criteria were used to evaluate the performance of the models with a confidence level of 95%. An analysis of variance (ANOVA) was conducted to determine the statistical capabilities of the generated models. Several variables and tools were considered to assess model fit, including probability (P-value), Fisher-test (Fvalue), Coefficient of Variance (C.V), Coefficient of Determination (R 2 ), Adjusted Coefficient of Determination (R adj 2 ), and Root Mean Square Error (RMSE) for the BBD models [START_REF] Tahraoui | Predicting the concentration of sulfate (SO42-) in drinking water using artificial neural networks: a case study: Médéa-Algeria, Desalin[END_REF][START_REF] Tahraoui | Modeling the organic matter of water using the decision tree coupled with bootstrap aggregated and least-squares boosting[END_REF][START_REF] Tahraoui | Prediction of the bicarbonate amount in drinking water in the region of Médéa using artificial neural network modelling[END_REF][START_REF] Bousselma | Artificial intelligence and mathematical modelling of the drying kinetics of pre-treated whole apricots[END_REF][START_REF] Yahoum | Experimental analysis and neural network modeling of the rheological behavior of xanthan gum and its derivatives[END_REF][START_REF] Zamouche | Predictive model based on K-nearest neighbor coupled with the gray wolf optimizer algorithm (KNN_GWO) for estimating the amount of phenol adsorption on powdered activated carbon[END_REF][START_REF] Zamouche | Optimization and prediction of stability of emulsified liquid membrane (ELM): artificial neural network[END_REF][START_REF] Tahraoui | Predicting the concentration of sulfate using machine learning methods[END_REF][START_REF] Hadadi | Aleppo pine seeds (Pinus halepensis Mill.) as a promising novel green coagulant for the removal of Congo red dye: optimization via machine learning algorithm[END_REF][START_REF] Tahraoui | Advancing water quality research: K-nearest neighbor coupled with the improved Grey wolf optimizer algorithm model unveils new possibilities for dry residue prediction[END_REF]. The F value indicates the variation in responses, which can be assessed by a regression equation. Meanwhile, the P value determines the statistical significance of the developed models. A P value <5% is considered significant and the model fits the modified photo-Fenton reaction, while a P value >5% indicates model inadequacy [START_REF] Bouchelkia | Jujube stones based highly efficient activated carbon for methylene blue adsorption: kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches[END_REF][START_REF] Tahraoui | Mixed Coagulant-Flocculant Optimization for Pharmaceutical Effluent Pretreatment Using Response Surface Methodology and Gaussian Process Regression[END_REF][START_REF] Nedjhioui | Designing an efficient surfactant-polymer-oil-electrolyte system: a multi-objective optimization study[END_REF][START_REF] Tahraoui | Optimisation and prediction of the coagulant dose for the elimination of organic micropollutants based on turbidity[END_REF][START_REF] Imessaoudene | Adsorption performance of zeolite for the removal of Congo red dye: factorial design experiments[END_REF].

Results

Homogeneous photo-Fenton system

Before approaching the study of the removal of the SG dye in homogeneous modified photo-Fenton, operative information and conclusions are necessary to be obtained from the photodegradation study of the SG dye with a reference to the homogeneous system that uses dissolved iron.

Photo-Fenton evalution of possible reactions

It is known that the photo-Fenton reaction occurs with different reactive radicals such as OH*, O 2 *, H 2 O 2 * HO 2 * and iron (Fe(II), Fe(III)), meanwhile other reactions can occur simultaneously, and quickly inhibiting the photo-Fenton reaction [START_REF] Luna | Photo-Fenton oxidation of phenol and organochlorides (2,4-DCP and 2,4-D) in aqueous alkaline medium with high chloride concentration[END_REF].

In order to check possible undesirable parasitic reactions during the aforementioned processes, preliminary tests were carried out for SG dye with Fe(III), SG dye with Fe(II) and SG dye with a ligand. For this purpose, 20 mg/L of SG dye concentration was taken. The photolysis reaction experiment of the SG dye solution was also examined, followed by other tests in the dark in the presence of P/Fe(II), P/Lig and P/Fe(III). The results obtained are presented in terms of reduced concentration and are shown in Fig. 1.

The evolution of SG dye reduced concentration with time is shown in Fig. 1. It can be seen that the reduced concentration value for different reactions and transformation of the SG dye under sunlight irradiation remained constant during all the experiments. These results revealed that no reaction could take place and influence the photo-Fenton oxidation process of the SG dye [START_REF] Hussain | Catalytic activity of metals in heterogeneous Fentonlike oxidation of wastewater contaminants: a review[END_REF]. Moreover, the fixed concentration of SG dye demonstrates high stability against the photolysis reaction and confirms their resistance to degradation in natural wastewater.

Influence of light sources nature

Light energy or irradiation is an important factor affecting water treatment efficiency. Thus, using a clean, sustainable energy and considering environmental and economic factors is crucial.

To better evaluate the contribution of the type of light sources in modified photo-Fenton oxidation mechanisms, UVA and LED as artificial light sources and sunlight as natural radiation were tested as excitation energy sources for both systems of photo-Fenton reaction Fe(III)/Lig and Fe(II)/Lig. The obtained results of the SG dye yield photo-Fenten degradation for different light sources are shown Fig. 2a andb. From Fig. 2, it can clearly be observed that the rate of photo-Fenton degradation kinetics and the yield rate change from one light source to another. Regarding the process involving the complex of (Fe(III)/Lig) the UV light source has a 20% photo-Fenton degradation yield followed by 78% of LED light. However, the sunlight source gives interesting kinetics and a high yield record of 98%.

For other processes involving the complex (Fe(II)/Lig), we noticed the same trend in the (Fe(III)/Lig) system, with a marginal increase in the case of using UV light at the beginning of the reaction [START_REF] Ghoul | Fe (III)-citrate enhanced sunlight-driven photocatalysis of aqueous carbamazepine[END_REF][START_REF] Girón-Navarro | A solar photoFenton process with calcium peroxide from eggshell and ferrioxalate complexes for the degradation of the commercial herbicide 2,4-D in water[END_REF], the kinetics is faster than LED light but a degradation rate is 32%, for LED light the kinetics is slower at the beginning compared to UV light. After 1 h:30 min of reaction, the degradation yield under LED light is 50% becoming higher than that under UV light. The comparison of these results shows that sunlight is better and gives a very fast kinetics and a yield higher than 70%. This finding is a powerful motivation for encouraging to exploit sunlight source as a renewable energy during all our work for both (Fe(III)/Lig) and (Fe(II)/Lig) systems [START_REF] Girón-Navarro | A solar photoFenton process with calcium peroxide from eggshell and ferrioxalate complexes for the degradation of the commercial herbicide 2,4-D in water[END_REF].

The primary factor contributing to the enhanced degradation and mineralization rate observed in sunlight-exposed experiments, as opposed to those irradiated with UV or visible light, can be attributed to the photoreduction of Fe(III)/complexes, resulting in the fast production of Fe(II) and *OH. Therefore, the generation of O 2 * -throughout several reactions from the O 2 present contributes in the yielding of degradation rate [START_REF] Ye | Mineralization of pentachlorophenol by ferrioxalate-assisted solar photo-Fenton process at mild pH[END_REF]. Additionally, the photodecarboxylation of Fe(III) by-product complexes formed during the degradation of SG also plays a role in this process. Moreover, Ferrioxalate is a photosensitive complex that is able to absorb light in wide solar spectrum range up to 550 nm with high quantum yield [START_REF] Doumic | Enhancement of a solar photo-Fenton reaction by using ferrioxalate complexes for the treatment of a synthetic cotton-textile dyeing wastewater[END_REF].

The BBD analysis

The main objective of the experimental design is to determine, with a minimum number of experiments, the effects of different parameters or factors Xi and their interactions on a process variable of interest Y (yield), called the response. In this work, the optimization of SG food dye degradation was performed on two complexes, namely (Fe(III)/Lig) and (Fe(II)/Lig), using the BBD approach. In both cases, the impacts of various factors, including the initial concentration of iron (0.15-0.25 mM), the molar ratio between the ligand and iron (1-3), and the dye concentration (10-20 mg/L), were investigated. In the case of the (Fe (II)/Lig) complex, an additional independent parameter, the H 2 O 2 concentration (0.05-0.15 mM), was incorporated. Statistical analysis of the data was conducted using the JMP software (version 13 pro). The experimental trials' results, along with the corresponding experimental of the percentage of contribution of each factor and predicted values, are presented in Tables 2 and3, where R% and COD% represent the rate of degradation and the rate of mineralization, respectively.

The photo-Fenton process for the system (Fe(III)/Lig) shows a high percentage of response in terms of degradation or mineralization rate for all the three factors. The best results as optimization presented in Table 2 are 0.25 mM of Fe(III), molar ratio R = (Fe(III)/Oxydant) =2 and SG concentration 10 mg/L. In addition, Table 2 shows that the predicted values are close to those observed in all the experiments, for both degradation and mineralization.

The values of the SG degradation rate (R%) ranged from 77.95% to 99.64% and the values of mineralization (COD%) change from 72.89 to 98.02%, respectively as mentioned in Table 2 for the process Fe(II)/Lig and process Fe(III)/Lig.

Additionally, according to Table 3, the experimental values for the efficiencies of mineralization and degradation were 99.68% and 98.66%, respectively, whereas the corresponding predicted values were 101.80% and 99.23%, respectively.

The estimated equations consider the independent variables, their mutual interactions, and their quadratic influence are given by eqs. 7 and 8 for the (Fe(III)/Lig) and (Fe(II)/Lig) complexes, respectively.

Subsequently, the parameters with high explanatory power (PR < 5%) were selected and indicated in Table 4 with an asterisk symbol '*'. Conversely, the remaining parameters with PR > 5% were eliminated [START_REF] Bouchelkia | Jujube stones based highly efficient activated carbon for methylene blue adsorption: kinetics and isotherms modeling, thermodynamics and mechanism study, optimization via response surface methodology and machine learning approaches[END_REF][START_REF] Tahraoui | Mixed Coagulant-Flocculant Optimization for Pharmaceutical Effluent Pretreatment Using Response Surface Methodology and Gaussian Process Regression[END_REF][START_REF] Tahraoui | Optimisation and prediction of the coagulant dose for the elimination of organic micropollutants based on turbidity[END_REF], and the models are represented by the equations provided in Table 5.

In the case of (Fe(III)/Lig) complex, the parameters that are not considered statistically significant (Prob >5%) are the interaction between X1 and X3, the quadratic effect of X1, and the quadratic effect of X3 in the dye degradation model (Table .4.1.1). In the COD model, the parameters X3, the interaction between X1 and X3, the quadratic effect of X1, and the quadratic effect of X3 are found to be non-significant (Table .4.1.2). Meanwhile, in the (Fe(II)/Lig) complex, certain parameters are found to be statistically non-significant (Prob >5%). Specifically, in the R model, the non-significant parameters include the interaction between X1 and X3, the interaction between X2 and X3, and the interaction between X2 and X4 (Table .4.2.1). On the other hand, in the COD model, the non-significant parameters are X3 and X4, along with the following interactions: X1X3, X2X3, X1X4, X2X4, and X3*X4 (Table

Mineralization.

After eliminating the variables with low explanatory power, there was a slight decrease in the coefficients of determination, but the equation became more simplified.

The plotting of the experimental values against the predicted data derived from the model equation would also show if the regression models fit with the data. Fig. 3 shows a straight correlation line between the observed data and the model predictions with high agreement between them. As a result, we may say that the quadratic polynomial model accurately depicts the relationship between the predictor and response variables. Moreover, these coefficients indicate moderately positive correlations within the model (Fig. 3). The probability was determined to be strictly below 0.5%, confirming that the model is extremely significant. Additionally, the significance level of P-value and F Ratio values, which assess the statistical significance of the regression

Y = β o + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 1 X 2 + β 5 X 1 X 3 + β 6 X 2 X 3 + β 7 X 2 1 + β 8 X 2 2 + β 9 X 2 3 ( 7
)
Y = β o + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + β 5 X 1 X 2 + β 6 X 1 X 3 + β 7 X 2 X 3 + β 8 X 1 X 4 + β 9 X 2 X 4 + β 10 X 3 X 4 + β 11 X 2 1 + β 12 X 2 2 + β 13 X 2 3 + β 14 X 2 4 (8
models, were calculated. A high F value coupled with a low P-value indicates the statistical significance of the model [START_REF] Panahi | Removal of cephalexin from artificial wastewater by mesoporous silica materials using box-Behnken response surface methodology, Desalin, Desalin[END_REF].

The significance of the determination coefficient (R 2 ) comes in its ability to indicate the level of adequacy of a generated model, as it corresponds to the ratio of the explained variation by the model to the overall variance [START_REF] Nath | Optimization of oven toasting for improving crispness and other quality attributes of ready to eat potato-soy snack using response surface methodology[END_REF]. Moreover, the adequacy of the model in accurately representing the experimental data may be determined by assessing the proximity of the R 2 value to the unity, as stated by [START_REF] Garba | Process optimization of K2C2O4-activated carbon from Prosopis africana seed hulls using response surface methodology[END_REF] [START_REF] Garba | Process optimization of K2C2O4-activated carbon from Prosopis africana seed hulls using response surface methodology[END_REF]. It is observed that the R 2 values for eq. 7, and eq. 8 were higher than 0.96, as shown in Table 5. These findings suggested that the experimental factors examined account for about 96% of the degradation and mineralization rate of the SG dye. The R 2 coefficient values demonstrate a strong and satisfactory level of concordance with the modified R 2 values, hence substantiating the statistical significance of the model.

The developed models through BBD have the capability to analyze the influence of predictors, their interactions, and their terms on the response variable simultaneously as presented in Table 4. Notably, the coefficients assigned to the individual factors within the model enable the assessment of their individual impact on the response.

Response surface analysis

The BBD was used to study the effect of the operating parameters for each complex on food dye degradation [START_REF] Lefnaoui | Investigation and optimization of formulation factors of a hydrogel network based on kappa carrageenan-pregelatinized starch blend using an experimental design[END_REF]. Response surface analysis is a set of mathematical and statistical techniques for improving and optimizing processes through the use of a large number of designed experiments [START_REF] Zaher | Photo-catalytic degradation of phenol wastewater: optimization using response surface methodology, Egypt[END_REF]. Response surface analysis is a useful way to determine the effects, to investigate the relationship between multiple variables and the selected response variable. The individual effects and interactions of the predictor variables of each process are discussed below.

Effect of parameters on R%

Complex (Fe(III)/Lig

). In the context of complex (Fe(III)/Lig) analysis for SG dye degradation (R model), the results can be interpreted based on the following points. Each parameter corresponds to a βi value given in Table 4. Generally, where a negative βi value indicates a negative effect of such parameter on the SG degradation and represents an antagonistic effect. Thus, when the parameter increases, the degradation rate decreases, and conversely, when the parameter decreases, the degradation rate increases. On the other hand, a positive value of βi indicating their positive effect of the parameter on the SG degradation rate and represents a synergistic effect. Also, this means that when the parameter increases, the degradation rate also increases, and when the parameter decreases, the rate efficiency of degradation decreases. First, the probability values (Prob) must be taken into account to assess the significance of the parameters. When the value of Prob is >0.05, this indicates a non-significant effect of the parameter on SG dye removal degradation. On the other hand, when the value of Prob is <0.05, this confirms that the parameter is statistically significant.

On the basis of static data, this study demonstrates that the significant parameters influencing the elimination of SG by photo-Fenton degradation using the (Fe(III)/Lig) complex are X1 (Fe(III) concentration), X2 (ratio = Lig/Fe(III)), X3 (P: SG dye concentration), X1X2 (the interaction between X1 and X2), X2X3 (the interaction between X2 and X3) and X2^2 (the quadratic effect of X2) (Table 4). These parameters exert a significant positive effects on SG degradation. It is important to note that the other parameters are not considered significant in this model, which suggests that they do not have a major influence on the degradation of the SG dye.

For the degradation rate, by examining the specific results of the significant parameters, it is observed that some parameters had positive "βi" values (Table 4), which revealed a significant and positive effect on SG degradation rate. The parameters X1 and X2 present a βi values of 1.635 and 6.48375 (Table 4), respectively, suggesting that an increase in X1 (Fe(III)) and X2 of Lig/Fe(III) would lead to an increase in the SG degradation rate (Fig. 4a).

On the other hand, some parameters have negative βi values, which means that they had a negative effect on the SG degradation. For example, the parameter X3 corresponding to SG concentration has a βi value of -2.85875 (Table 4), implying that an increase in X3 would lead to a decrease in the rate of SG dye degradation (Fig. 4b). Moreover, the interaction between X1 and X2 (parameter X1X2) shows a βi value of -2.4075 (Table 4), indicating a strong negative effect on the degradation of the dye (Fig. 4a). It is important to note that the interaction between X2 and X3 (parameter X2X3) also has a significant positive effect (Fig. 4b), with a βi value of 3.34 (Table 4).

From the obtained result shown in Table 4, the quadratic effect of X2 (the parameter X2^2) was also observed through a βi value of -5.328333 (Table 4). This negative value indicates the adverse effect of this variable on the degradation process (Figs. 4a andb). As X2 increases, the rate of dye degradation decreases, Meanwhile, a further increase of X2, the SG rate degradation begins to increase again. This may indicate a synergistic effect and an optimal point where X2 has the greatest impact on SG dye degradation.

It may be concluded from this study which highlights several important parameters in the degradation of the SG dye with the complex (Fe(III)/Lig) had a significant positive effect among them X1, X2, X3 and X2^2.

Complex (Fe(II)/Lig

). This part evaluates the surface responses analysis in the case of (Fe(II)/Lig) complex used for the SG dye rate degradation (R model) on the photo-Fenton process to evaluate the significance of potential interactions between independent variables and model responses, to determine the significance of the effect of each independent variable based on the F values and the probability of accuracy of the results with prob. > F. From Table 4, the parameters with Prob results <0.05 demonstrate significant parameters influencing SG degradation rate. Among the significant parameters are X1 (Fe(II) Concentration), X2 (ratio = Lig/Fe(II)), X3 (P SG dye Concentration), X4 (H 2 O 2 Concentration), the interaction between X1 and X2 (X1X2), the interaction between X1 and X4 (X1X4), the interaction between X3 and X4 (X3X4), the quadratic effect of X1 (X1X1), the quadratic effect of X2 (X2X2), the quadratic effect of X3 (X3X3) and the quadratic effect of X4 (X4*X4) (Table 4). These parameters exert significant effects on SG degradation rate, whether positive or negative. The effect of each parameter can be evaluated by referring to the corresponding βi values (Table 4).

Table 4 shows that X1 has a βi value of 6.4080218, suggesting that an increase in X1 would lead to enhancing the SG degradation rate (Fig. 5a Table 4 Model parameters and analysis of the BBD models for the two complexes. andb). Similar tendence have been observed for X3 and X4, which exhibit a βi values of 1.4647436 and 1.1710871, respectively (Table 4), confirming its strong positive effect on dye degradation (Fig. 5c).

On the other hand, the parameters exhbit negative βi values of -1.397363 such as X2 (Table 4), which means that they have a negative effect on dye degradation and implying that an increase in X2 would lead to a decrease in the degradation rate of SG dye (Fig. 5a). Moreover, the interaction between X1 and X4 (X1*X4) has a significant negative effect (Fig. 5b), with a βi value of -3.84375 (Table 4).

Furthermore, the interactions X1X2 and X3X4 and the quadratic effects of X1X1, X2X2, X3X3 and X4X4 are also statistically significant. The interaction between X1 and X2 (X1X2) and between X3 and X4 (X3X4) have a βi values of 2.0140452 and 1.59375, respectively (Table 4), indicating a significant positive effect of this interaction on SG degradation reaction (Fig. 5a,c). Meanwhile, the interaction between X1 and X4 (X1*X4) has a significant negative effect (Fig. 5b), with βi value of -3.84375 (Table 4).

The quadratic effect of X1 (X1X1) and X3 (X3X3) have a value of βi of -5.219975 and -3.084979, respectively (Table 4), suggesting a nonlinear relationship between X1, X3 and the SG degradation rate (Fig. 5a,5b and5c). Also, this finding denoting that there is an optimal value of X3 to maximize the degradation rate. Similarly, the quadratic effect of X2 (X2X2) displays a βi value of 2.3751778 (Table 4), due to this fact it's indicating a nonlinear relationship between X2 and SG degradation rate (Fig. 5a). Finally, the quadratic effect of X4 (X4X4) shows a value of βi of -3.084979 (Table 4), also demonstrating a nonlinear relationship between X4 and SG degradation rate (Fig. 5b andc). Consequently, this was evidence to note that this quadratic effect inhibited the degradation rate of SG.

In summary, the present examination of the recently obtained data revealed the importance and the significance of certain factors in the degradation rate of SG dye for the system of (Fe(II)/Lig) complex.

Effect of parameters on COD %

3.5.2.1. Complex (Fe(III)/Lig). The response surface methodology was applied to reveal the effect of the independent variables and the interaction between them with aim to predict the SG mineralization rate COD % (COD model) in the case of using the complex (Fe(III)/Lig), the variables considered are Fe(III) concentration (X1), molar ratio Lig/Fe(III) (X2) and SG dye concentration (X3). The analysis was conducted by preparing 3D response surface plot and the normal of probability "Prob" revealed the satisfactory with the significance of parameters that impact the SG mineralization rate. The obtained results indicated that the level of statistical significance of parameters including: X1, X2, the interaction between X1 and X2 (X1X2), the interaction between X2 and X3 (X2X3), and the quadratic effect of X2 (X2X2) (Table 4). Therefore, these parameters exert significant effects on SG mineralization rate, whether positive or negative. The effect of each parameter can be evaluated by referring to the corresponding "βi" value (Table 4).

By examining the specific results of the significant parameters, it is observed that certain parameters have positive "βi" values, indicating a significant factors and positive effect on the SG rate of mineralization. For example, X1 and X2 have a "βi" values of 2.65 and 6.4 (Table 4), suggesting that this parameters are promoting factor in the process of photo-Fenton, an increase in X1 and X2 would lead to enhanced the SG mineralization rate (Fig. 6a) confirming its significant positive effect on dye mineralization (Fig. 6a andb).

It should be mentioned that the interactions between the parameters X1X2 and X2X3 are also significant. The interaction between X1 and X2 (X1X2) and X2 (X2X2) have a "βi" value of -4.8875 and -6.920417 (Table 4), demonstrating a significant effect of this interaction in SG mineralization rate (Fig. 6a) and suggesting a non-linear relationship between X2 and SG mineralization rate (Fig. 6a andb), the interaction between X2 and X3 (X2X3) presents a "βi" value of 5.3525 (Table 4), confirming its significant effect on the SG mineralization rate (Fig. 6b).

Then, the quadratic effect of X2 (X2X2) is also significant, it gives a "βi" value of -6.920417 (Table 4), this result. It is important to note that Fig. 4. Effects of operating factors and their interactions on the SG degradation rate by the (Fe(III)/Lig) complex: a) interaction between X1 and X2 and b) interaction between X2 and X3. this quadratic effect has a negative impact on the SG of mineralization rate.

Finally, the analysis performed with response surface methodology for the reaction of mineralization of SG dye by the complex (Fe(III)/Lig), indicated its suitable analyzing the effect of various variables and confirmed the role of some factors in improving the SG mineralization.

Complex (Fe(II)/Lig

). The study of surface response modeling of the SG mineralization reaction with the complex (Fe(II)/Lig) (COD model), this technique was used to study and optimize the SG photo-Fenton degradation processes under sunlight irradiation. Therfore, the use of probability "Prob" value for comparing the significant parameters that could be influence positively or negatively the SG mineralization rate.

The analysis of results showed that the significant parameters include X1, X2, the interaction between X1 and X2 (X1X2), the quadratic effect of X1 (X1X1), the quadratic effect of X2 (X2X2), the quadratic effect of X3 (X3X3) and the quadratic effect of X4 (X4X4) (Table 4). In addition, these parameters play significant effects on SG mineralization rate, whether positive or negative. The effect of each parameter can be evaluated by referring to the corresponding "βi" values (Table 4).

Furthermore, X1, X2 exhbit a "βi" values of 1.2575 and 6.2083333, respectively (Table 4), suggesting that an increase in X1 and X2 would lead to an increase in the SG rate of mineralization (Fig. 7a) this confirming its significant positive effect on the SG mineralization rate (Fig. 7a).

Also, it may be noticed, another significant effect, with a value of "βi" of 1.3525 (Table 4) for the interaction between X1 and X2 (X1X2) suggested that this interaction is associated with a positive effect on SG mineralization (Fig. 7a), and a simultaneous increase in X1 and X2 will further favours the mineralization rate of SG.

Next, the SG mineralization (Fig. 7a), the quadratic effects of X1 (X1X1), X2 (X2X2), X3 (X3X3) and X4 (X4X4) are also significant. For example, the quadratic effect of X1 (X1X1) had a "βi" value of 3.1229167 indicated a nonlinear relationship between the varaibles X1 and SG mineralization rate. Likewise, the quadratic effect of X2 (X2X2) exhibits a "βi" value of 6.1116667 (Table 4), also revealed a non-linear relationship between X2 and the SG mineralization rate (Fig. 7a). Similar, the quadratic effects of X3 (X3X3) and X4 (X4X4) also have significant values (Fig. 7b), with "βi" values of 4.0204167 and 2.0116667, respectively (Table 4).

Finally, the data analysis with surface response methodology for the modified homogeneous photo-Fenton mineralization reaction of SG dye by the complex (Fe(II)/Lig), demonstrated their validity, suitability and determined the significant parameters with positive effect and those with negative effect on the mineralization reaction.

Multi-objective optimization and validation

In this study, two primary objectives were defined for the optimization process. The first objective, labeled "Removal Efficiency," measures the percentage of SG dye removed through the photo-Fenton process. The second objective, named "Chemical Oxygen Demand Reduction," quantifies the percentage reduction in chemical oxygen demand, which serves as an indicator of the degradation of organic pollutants in water. Both objectives were considered equally important, each receiving a weighting of 50% in the optimization process. Thus, the weighted sum of these objectives was used as a single guiding objective.

To determine the optimal parameters for the (Fe(II)/Lig) and (Fe (III)/Lig) complexes in the context of SG dye removal via homogeneous photo-Fenton reaction, a specific optimization method was employed. This method is known as "Multi-Objective Grey Wolf Optimizer" (MOGWO). MOGWO is an extension of the Grey Wolf Optimizer (GWO) algorithm tailored for solving optimization problems with multiple objectives [START_REF] Tahraoui | Mixed Coagulant-Flocculant Optimization for Pharmaceutical Effluent Pretreatment Using Response Surface Methodology and Gaussian Process Regression[END_REF][START_REF] Nedjhioui | Designing an efficient surfactant-polymer-oil-electrolyte system: a multi-objective optimization study[END_REF][START_REF] Lefnaoui | Investigation and optimization of formulation factors of a hydrogel network based on kappa carrageenan-pregelatinized starch blend using an experimental design[END_REF]. Its primary aim is to find a set of efficient solutions known as "Pareto-optimal solutions," which represent trade-offs between the different objectives. To achieve this, MOGWO employs search mechanisms inspired by the hunting behavior and social hierarchy of grey wolves. It explores the solution space to converge towards the Pareto front, where optimal solutions balancing the objectives are found [START_REF] Zaher | Photo-catalytic degradation of phenol wastewater: optimization using response surface methodology, Egypt[END_REF][START_REF] Srivastav | Multiobjective Grey Wolf optimization based allocation of SVC in power system[END_REF]. What sets MOGWO apart is its ability to provide a diverse array of solutions within the objective space, offering decision-makers a range of options for decision-making. It also utilizes operators such as alpha, beta, and delta wolf movements to navigate the search space and select non-dominated solutions.

A critical step following the acquisition of optimal parameter values through MOGWO was laboratory validation. This validation phase had two primary objectives. First, it aimed to confirm the efficiency and accuracy of the models obtained during the optimization, thus ensuring the relevance of theoretical results in practical settings. Additionally, the validation step played a crucial role in selecting the most effective complex among the available choices (Fe(II)/Lig or Fe(III)/Lig) for use in the SG dye removal process via the photo-Fenton reaction. It, therefore, had a significant impact on decision-making for the realworld application of the process. The obtained optimal parameter settings are given in Table 6, where their experimental validation results are also given. The experimental validation results show an exceptional degradation and mineralization case of the SG contaminant for both complexes, resulting in nearly perfect treatment efficiency (almost 100%). Furthermore, the obtained error was around 5%, affirming the effectiveness and robustness of the models developed through BBD. These findings underscore the remarkable performance and reliability of the optimized conditions, reinforcing their potential for successful implementation in realindustrial settings.

Interface for optimization and prediction

In pursuit of delivering a practical solution for the implementation of multi-objective optimization (MOO) and the prediction of key parameters such as R%, COD%, and processing efficiency for various complexes, we have developed a user-friendly interface utilizing MATLAB's guide framework. This interface, as illustrated in Fig. 8, has been further transformed into an executable application tailored for the Windows operating system. This versatile application presents a valuable and accessible means to forecast outcomes by allowing users to select input values corresponding to the specific type of complex defined by the BBD. It empowers users to discover a MOO solution by identifying the optimal input values for each complex, achieved through the utilization of the MOGWO algorithm. By virtue of this application, individuals seeking to anticipate results and fine-tune parameters for each complex can now do so in a highly customized manner, tailored to their distinct requirements. The user-friendly interface simplifies the process, enabling users to obtain precise predictions and determine optimal parameters. This capability is invaluable for informed decision-making concerning the degradation of dyes, offering practical solutions and insights for a wide range of applications.

nfluence of H 2 O 2 concentration

To better understand the effect of the initial concentration of H 2 O 2 on the kinetics of photo-Fenton oxidation of the SG dye degradation or mineralization, the production, as well as the consumption of hydrogen peroxide, were carried out according to different initial concentrations of H 2 O 2 (0,15-0.3 and 0.45 mM.) while keeping the initial concentrations of SG and Fe(III) constant at free pH. All these results obtained are represented in Figs. 9 and10.

From the results depicted in Fig. 9, it was observed that for a concentration of 0.15 mM a slightly fast kinetics occurred, with a similar yield of discoloration with the control reaction. However, for concentrations of 0.3 mM and 0.45 mM H 2 O 2 , it was noted that the yield decreased slightly when the degradation kinetics became slow, this indicated that above the concentration of 0.15 mM seemed to be inhibited. Moreover, the H 2 O 2 in this case plays the role of an inhibiting agent at an excess of concentration and it can react with the hydroxyl radicals generated during the photo-Fenton reaction to compete with the oxidant, it may promote secondary reactions that consume H 2 O 2 and therefore inhibit the SG degradation according to the following reaction [START_REF] Buxton | Critical review of rate constants for reactions of hydrated electrons, hydrogen atoms and hydroxyl radicals (⋅OH/⋅O -) in aqueous solution[END_REF]:

H 2 O 2 + -OH 2 O 2 + -OH ↔ HO 2-+ H 2 O k = 3 × 10 7 7 mol -1 .L.S -1 (13)
Hence 0.15 mM of H 2 O 2 was noticed as an appropriate concentration with the optimal conditions: 0.15 mM of Fe(III) and a molar ratio of 2, with an initial SG dye pollutant concentration of 10 mg/L. H 2 O 2 can be produced in solution, with the following pattern. We can see in Fig. 11 that the consumption of H 2 O 2 can be successful because of its in situ production.

Effects of ions for the two processes involved (Fe(III)/Lig) and (Fe (II)/Lig)

The composition of renal effluents is very complex and may contain a wide range of organic and inorganic ions in varying concentrations. The presence of these ions may affect the concentration of hydroxyl radicals during a photo-Fenton reaction and may retard or inhibit the degradation activity of the pollutant [START_REF] Machulek | Photolysis of ferric ions in the presence of sulfate or chloride ions: implications for the photo-Fenton process[END_REF].

In this part of the work, we have evaluated the effect of some inorganic and inorganic ions that existed in salts form on the photo-Fenton oxidation of SG dye, the salts used are sodium chlorides NaCl, sodium sulfates Na 2 SO 4 , sodium bicarbonates NaHCO 3 and potassium nitrates KNO 3 at different concentrations 10, 50 and 100 mM. However, the other operating conditions are kept fixed at 0.15 mM of Fe(III), 2 of molar ratio and 10 mg/L of SG dye pollutant concertation for both cases, the complex (Fe(III)/Lig) as well as, a Fe(II)/Lig concentration of 0.2 mM, a molar ratio of 2, an H 2 O 2 concentration of 0.15 mM and a pollutant concertation of 10 mg/L. The effect of ions on the rate of photo-Fenton efficiency is summarized in Fig. 12.

The effect rate efficiency of sulfate, chloride, bicarbonate and nitrate ions with different concentrations on the photo-Fenton degradation of SG dye is presented in Fig. 12. As can be observed an overall effect of a decrease in the photo-Fenton activity for the degradation of GS dye in all added ions, this behavior can be explained by the reaction of ions with the formed hydroxyl radicals. In addition, chloride, sulfate and nitrate form a complex with Fe(II) and Fe(III) enabling to produce of hydroxyl radicals.

According to Fig. 12, concerning the complex (Fe(III)/Lig), a nonsignificant effect was observed for the sulfates. However, for the other ions a rather important inhibition was reported especially for the bicarbonates, it was noticed a decrease in the photodegradation yield of 86.29% for the concentration of 100 mM. On the other hand, for the chloride and the nitrate, a decrease of 22.32% and 15.12% respectively was noted for the same dye SG initial concentration (100 mM).

Concerning the system of complex (Fe(II)/Lig), a slight inhibition of 1.79% was marked for chlorides at a concentration of 100 mM. However, the same observations were noted for the first complex with the bicarbonate had a drastic inhibition with a decrease of 91% in photodegradation yield for 100 mM concentration.

Moreover, the addition of chloride ions up to 100 mM tends to influence the photodegradation activity. In similar cases, when chloride ions are added to the solution, they act as a scavenger by trapping the hydroxyl radicals [START_REF] Liao | Hydroxyl radical scavenging role of chloride and bicarbonate ions in the H2O2/UV process[END_REF]. This trend can be explained by the reaction with radical hydroxyl as mentioned by the following reaction [START_REF] Devi | Effect of chloride and sulfate ions on the advanced photo Fenton and modified photo Fenton degradation process of alizarin red S[END_REF]:

HO˙+ Cl -→ClOH k = 4.3 × 10 9 M -1 s -1 (14)
The photo-Fenton degradation of the SG dye was considerably decreased in the presence of bicarbonate ion HCO 3 -, this can be explained by the hydroxyl scavenging properties of carbonates ions. In addition, bicarbonate of sodium is a more stable ion that can play a role in changing pH medium. Hence, another produced radical CO 3

•-in the scavenging reaction [START_REF] Garg | Optimization methodology based on neural networks and box-behnken design applied to photocatalysis of acid red 114 dye[END_REF] in the hydroxyl radical (OH • ) has lower photocatalytic reactivity than hydroxyl radical [START_REF] Khan | Kinetic and thermodynamic study of oxidative degradation of acid yellow 17 dye by Fenton-like process: effect of HCO3-, CO32-, Cl-and SO42-on dye degradation[END_REF].

HO˙+ HCO 3-→CO 3-˙+ H 2 O k = 8.5 × 10 6 M -1 s -1 (15)

Effect of scavengers

The previous studies of photo-Fenton reaction investigated the effect of different scavengers as an important reagent in the reaction system to confirm the intervention of different active radicals.

To study the influence of the presence of scavengers in the photo-Fenton oxidation of SG dye in the case of complex (Fe(III)/Lig and (Fe (II)/Lig complexes, we used isopropanol (Isop), chloroform (chlor) and their mixture. According to previous studies, isopropanol reacts with hydroxyl radicals with a reaction rate of 1.9 × 10 9 M-1 s -1 [START_REF] Cheng | Degradation of reactive brilliant red X-3B by photo-Fenton-like process: effects of water chemistry factors and degradation mechanism[END_REF]. For the superoxide radicals, the scavenger used is chloroform which reacts with O 2

-with a reaction rate of 9.6 × 10 8 M -1 s -1 , thereby it can also react with HO • with a reaction rate of 7 × 10 6 M -1 s -1 [START_REF] Vavilapalli | Enhanced photo-Fenton and photoelectrochemical activities in nitrogen doped brownmillerite KBiFe2O5[END_REF]. The obtained results are illustrated in Fig. 13a andb:

The effect of isopropanol, chloride and the mixture isopro+ chlor on the photo-Fenton reaction of SG dye is investigated in Fig. 13 for both the complex (Fe(III)/Lig) and the complex (Fe(II)/Lig) cases.

It is noted that with the addition of the two scavengers at the beginning of the reaction for a concentration of 1 mol a significant inhibition was noticed. This can be explained by the fact that the elimination of our SG dye is due on one hand to the production of hydroxyl radicals with a percentage of 40.2% and on the other hand to superoxide radicals with a percentage of 24.7%, for the first system of complex (Fe (III)/Lig) and a percentage of 80. 7% is reached with a production of 14.7% of hydroxyl radicals and superoxide radicals with the second system of complex (Fe(II)/Lig). However, the remaining photo-Fenton degradation percentage can be due to the oxalate radicals produced in situ during the reaction in both processes [START_REF] Hu | The attractive efficiency contributed by the in-situ reactivation of ferrous oxalate in heterogeneous Fenton process[END_REF].

Kinetic study of the degradation of GS dye with complex (Fe(III)/ Lig) and (Fe(II)/Lig) system

In this part, to determine the degradation kinetics of SG dye by modified photo-Fenton oxidation for the system with complexes (Fe (III)/Lig) and (Fe(II)/Lig), respectively. Moreover, the first-order and second-order kinetics models given by the eqs. (11 and 12) are applied and analyzed using the coefficient of determination (R 2 ) value [START_REF] Ramírez-Carranza | Effect of Fe (II) concentration on metronidazole degradation by Fenton process: performance and kinetic study[END_REF]. Thereafter, the model with the best fit of experiment data was selected.

For the complex (Fe(III)/Lig): SG dye concentration: 10 mg/L, Fe(III) concentration: 0.15 mM, Molar ratio: 2, For the complex (Fe(II)/Lig): SG dye concentration: 10 mg/L, Fe(II) concentration: 0.2 mM, Molar ratio: 2 and H 2 O 2 : 0.15 mM.

C t = C o -e k1t ( 16
)
1

/ C t = 1 C o -k 2 t ( 17
)
Where; Ct is the concentration at time t, Co is the initial SG dye concentration, t is the reaction time, and k1, and k2 are the first and second-order reaction kinetic rate constants, respectively. The various obtained kinetic parameters and regression coefficients (R 2 ) for each reaction model were analyzed, and the results are presented in Table 7.

The photo-Fenton reaction rate constants are calculated from the slope of the kinetic model plots. Examining the data 7 and according to the comparison of the R 2 values of the plots, it was revealed that the modified photo-Fenton reaction of the SG dye follows the second-order kinetic model for Fe(III)/Lig and Fe(II)/Lig complexes with an R 2 of 96.84% and 97.2% respectively. We can conclude that the decolorization kinetics is well presented by the second-order model in the two studied processes. Further, the kinetics constant of second-order reaction k 2 was notably influenced by the nature of the complex. This investigation may associated with the generation of OH* radical which is highly produced with ferrioxalate complex (Fe(III)/Lig) [START_REF] Nour | Heterogeneous Fenton oxidation with natural clay for textile Levafix dark blue dye removal from aqueous effluent[END_REF]; Finally, several additional studies found in the literature corroborate our finding that the photo-Fenton reaction proceeds according to second-order kinetics.

Conclusion

This research study focused on the removal efficiency of SG food dye degradation by a modified homogenous photo-Fenton process under a sustainable natural light source. The influence of various operating conditions such as light source, Fe(II)/(III) concentrations, oxalic acid concentration as ligand, pH medium and hydrogen peroxide concentration were investigated in detail. It was observed that the first important results obtained from preliminary tests confirmed the absence of undesirable reactions, while sunlight proved its efficiency for improving the degradation rate of SG dye which decreased the cost of energy consumption.

It should be mentioned that the classical photo-Fenton reaction is favorable at an acidic medium (pH = 3). However, the addition of oxalic acid demonstrated that this reaction could be performed in a wide range of pH close to the neutrality and it depends only on the initial SG dye concentration, iron catalyst amount, ligand concentration and hydrogen peroxide concentration. In addition, the obtained results proved that both complexes of Fe(II)/lig and Fe(III)/Lig demonstrated their efficiency for the SG degradation removal with a slight enhancement for Fe (III)/Lig complex. Under sunlight, the ferrioxalate complex can be photo-activated and lead to a reduction of the Fe(III) to Fe(II) initiating the generation of radicals through the reaction with hydrogen peroxide. The Box-Benhken experimental design (BBD) was applied for developing a mathematical model and optimizing the photo-Fenton process to get more insight information. BBD is combined with response surface methodology to reveal the effect of independent variables and their interactions on the response variables. The effect of ions such as chloride, nitrate and bicarbonate was also determined in the performed experiments. It was found that some ions exhibited an important inhibition role in the degradation reaction and reduced the generating rate of hydroxyl radicals from photo-Fenton reagents. For the bicarbonates, it was noticed the SG degradation yield decreased by 9.76% and 3.96% for Fe(III)/lig and Fe(II)/lig complexes, respectively. On the other hand, for the chloride 73.73% and 93.17% reduction in the SG degradation yield was observed for Fe(III)/lig and Fe(II)/lig complexes, respectively, and the reductions under nitrate are 80.93% and 94.7% for Fe(III)/lig and Fe(II)/lig, respectively. The same behavior is obtained by adding isopropanol which plays the role of electron acceptors such as H 2 O 2 . These findings are highly encouraging for the use of the modified photo-Fenton process for the removal of organic pollutants from effluent to protect the aquatic environment.

CRediT authorship contribution statement

Mohammed Kebir: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation,

Fig. 1 .Fig. 2 .

 12 Fig. 1. Degradation rate of SG dye during photolysis and (P + Lig), (P+ Fe(II)) and (P + Fe(III)) without light. [P]o = 20 mg./L, [Lig]o = 0.3 mM, [Fe(II)]o = 0.1 mM, [Fe(III)]o = 0.1 mM.

  .

  Photodegradation.

Fig. 3 .

 3 Fig. 3. Relation between the observed values and those estimated by the BBD models For (Fe(III)/Lig) and (Fe(II)/Lig) complexes: (a) R% degradation and (b) COD % mineralization.

Fig. 5 .

 5 Fig. 5. Effects of operating factors and their interactions on the degradation of the dye under Complex (Fe(II)/Lig): a) interaction between X1 and X2, b) interaction between X1 and X4, and c) interaction between X3 and X4.

Fig. 7 .

 7 Fig. 7. Effects of operating factors and their interactions on the mineralization of the SG dye under Complex (Fe(II)/Lig): a) interaction between X1 and X2, and b) interaction between X3 and X4.

Fig. 6 .

 6 Fig. 6. Effects of operating factors and their interactions on the mineralization of the SG dye under Complex (Fe(III)/Lig): a) interaction between X1 and X2, and b) interaction between X2 and X3.

Fig. 8 .Fig. 9 .Fig. 10 .

 8910 Fig. 8. Application based on an interface of MATLAB for MOO (MOGWO), and prediction R%, COD % and processing efficiency using BBD by the two complexes.

Fig. 11 .Fig. 12 .

 1112 Fig. 11. Scheme of the cycle of the Fe(III)-oxalate complex under the effect of light with the formation of H 2 O 2 [43].

Fig. 13 .

 13 Fig. 13. Photo-fenton degradation of SG in the presence of scavengers for both complexes, a: Case of the (Fe(III)/Lig) complex, b: Case of the (Fe(II)/Lig) complex for time = 30 min [VS]o = 10 mg/L, [Fe(II)]o = [Fe(III)]o = 0.2 mM, R = 2, [H 2 O 2 ]o = 0.15 mM, [isop]o = [chlor]o = 1 M.

  .5%, Fluka), Oxalic acid C 2 H 2 O 4 (≥99%, Merk), Isopropanol C 3 H 8 O (>98%, Merck), Hydrogen peroxide H 2 O 2 (30% w/v, Sigma-Aldric), 1.10 Phenolphthalein C 12 H 8 O 2 (99%, Biochem), Sodium acetate C 2 H 3 NaO (99.99%, Merck), Iron sulfate FeSO 4 ⋅7 H 2 O (>99, Merck), Potassium fluoride KF (98%, Fichersci), Hydrochloric acid HCl (37%, Sigma-Aldrich), Sulfuric acid H 2 SO 4 (98%, Merck), Humic acid C 9 H 8 Na 2 O (>98%, Thermo Scientific), Chloroform CHCl 3 (Merck), Sodium sulfite Na 2 SO 3 (98%, Sigma Aldrich), Potassium nitrate KNO 3 (>98%, Sigma Aldrich), and Potassium permanganate KMnO 4 (99%, Sigma Aldrich).

  Several studies, including those by Ferreira et al. in 2007, Witek-Krowiak et al. in 2014, and Sadhukhan et al. in 2016, have utilized BBD to analyze and interpret experimental data

Table 1

 1 Factors and study area for both processes (Fe(III)/Lig) and (Fe(II)/Lig).

		Fe(III)/Lig			Fe(II)/Lig
	Level	-1	0	1	-1	0	1
	X 1 (mM) X 2 (Fe 2+ /Oxy)	0.15 1	0.2 2	0.25 3	0.15 1	0.2 2	0.25 3
	X 3 (mg/L)	10	15	20	10	15	20
	X 4 (mM)				0.05	0.1	0.15

Table 3

 3 Experimental and predicted response for SG degradation and mineralization under Box-Benhken design of experiments for the process Fer(II)/Lig.

	N	X 1	X 2	X	X 4	R%	Predicted	COD	Predicted COD
							R%	%	%
	1	-1	-1		0	93.37	91.78	84.66	84.30
	2	-1	0	-1	0	81.88	82.13	87.33	86.316
	3	-1	0		-1	76.63	77.89	85.33	85.10
	4	-1	0		1	88.75	87.93	85.33	85.01
	5	-1	0		0	80.5	81.87	86.66	87.82
	6	-1	1		0	85.46	84.96	93.25	94.03
	7	0	-1	-1	0	96.35	96.55	84	84.02
	8	0	-1		-1	97.5	96.04	84	84.21
	9	0	-1		1	99.12	100.59	81.16	81.98
	10	0	-1		0	97.92	98.26	86.33	86.18
	11	0	0	-1	-1	82.88	84.19	87.33	88.70
	12	0	0	-1	1	93.5	93.97	84.88	85.72
	13	0	0		0	97.63	97.63	81.33	81.18
	14	0	0		0	97.63	97.63	79.88	81.18
	15	0	0		0	97.63	97.63	82.33	81.18
	16	0	0		-1	94.5	94.56	87.44	86.81
	17	0	0		1	90.25	89.47	88.77	87.61
	18	0	1	-1	0	93.43	92.54	99.16	98.60
	19	0	1		-1	96.92	95.45	95.83	95.49
	20	0	1		1	94.10	95.58	95.25	95.53
	21	0	1		0	97.43	96.68	97.16	96.44
	22	1	-1		0	99.54	100.57	84.66	84.11
	23	1	0	-1	0	93.13	91.76	91	90.33
	24	1	0		-1	98.13	98.40	89	88.63
	25	1	0		1	94.88	93.06	87	86.53
	26	1	0		0	98.13	97.88	87.33	88.83
	27	1	1		0	99.67	101.80	98.66	99.23

Table 2

 2 Experimental and predicted response for SG degradation and mineralization under Box-Benhken design with (Fe(III)/Lig) complex.

	N	X 1	X 2	X 3	R%	Predicted	COD%	Predicted COD%
						R%
	1	-	0	1	93.63	91.77	90.92	90.88
	2	-	0	-1	98.75	99.44	95.83	96.45
	3		1	-1	99.47	101.13	94.17	98.05
	4		1	1	98.25	98.05	97.33	92.96
	5		0	0	97.25	81.32	96.00	74.23
	6		0	-1	99.64	89.41	95.50	89.31
	7		0	0	97.25	97.13	96.00	96.67
	8	-	-1	0	81.25	97.13	72.89	96.67
	9		-1	-1	92.53	97.13	92.83	96.67
	10		0	1	97.69	99.10	98.00	96.81
	11		0	0	96.88	97.56	98.02	92.33
	12		-1	0	90.13	79.37	89.89	75.79
	13	-	1	0	98.38	92.14	96.22	88.37
	14		-1	1	77.95	96.99	74.58	97.38
	15		1	0	97.63	99.06	93.67	99.29

Table 6

 6 The obtained optimum conditions and experimental validation.

		R (%)	COD (%)	(R (%) + COD (%))/2
			(Fe(III)/Lig)
	• X1 = 0.15 mM, X2 = 3, and X3 = 20 mg/L
	Experimental	98.73	99.87	99.30
	Predicted response	99.53	103.74	101.63
	Error	0.8	3.87	2.33
			(Fe(II)/Lig)
	• X1 = 0.25 mM, X2 = 3, and X3 = 20 mg/L and X4 = 0.05 mM
	Experimental	99.63	99.92	99.77
	Predicted response	102.58	105.26	103.92
	Error	2.95	5.34	4.14

Table 7

 7 The analyses of the kinetic models applied for the two complexes (Fe(III)/Lig) (Fe(II)/Lig).

		Complex Fe(III)/Lig		Complex Fe(II)/Lig
		1st order	2nd order	1st order	2nd order
	R 2	0.6854	0.9684	0.5306	0.972
	Rate kinetic k	k 1 = 0.4894 (1/ min)	k 2 = 0.1447 (L./mg min)	k 1 = 0.1686 (1/ min)	k 2 = 0.126 (L./mg min)

Data availability

Data will be made available on request.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Michael Jakob

Stavros Afionis

Max Åhman

Angelo Antoci

Marlene Arens

Fernando Ascensão

Harro Van Asselt

Nicolai Baumert

Simone Borghesi

Claire Brunel

Justin Caron

Aaron Cosbey

Susanne Droege

Alecia Evans

Gianluca Iannucci

Magnus Jiborn

Astrid Kander

Viktoras Kulionis

Arik Levinson

Jaime De Melo

Tom Moerenhout

Alessandro Monti

Maria Panezi

Philippe Quirion

Lutz Sager

Marco Sakai

Juan Sesmero

Mauro Sodini

Jean-Marc Solleder

Cleo Verkuijl

Valentin Vogl

Leonie Wenz

Sven Willner

How trade policy can support the climate agenda

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Economic analysis has produced ample insights on how international trade and climate policy interact (1). Trade presents both opportunities and obstacles, and invites the question of how domestic climate policies can be effective in a global economy integrated through international trade. Particularly problematic is the potential relocation of production to regions with low climate standards. Measures to level the playing field, such as border carbon adjustments (BCAs), may be justified for specific emissions-intensive and trade-exposed sectors but need to be well-targeted, carefully navigating tensions that can arise between the desire to respect global trade rules and the need to elaborate and implement effective national climate policies. The conformity of specific trade measures with international trade and climate change law is not entirely clear. Yet, clarity is needed to ensure that the industry actors affected will find the rules predictable and be able to adhere to them.

On the one hand, international trade can reduce emissions by providing incentives for countries with technological know-how to specialize in the production of clean goods and services, and countries with high renewable-energy potential to specialize in the clean production of energy-intensive goods. It can also accelerate the transfer and diffusion of clean technologies. Economic integration can enhance resilience to climate change by allowing regions affected by extreme weather to procure goods from unaffected trade partners (2), thus reducing price swings. It can also promote adaptation to slow-onset events by shifting production of affected sectors to regions experiencing lower climate-related productivity losses or even productivity gains.

On the other hand, current trade policies do not provide incentives for trade in clean products. For reasons unrelated to climate policy, they instead favor carbon-intensive imports. Raw materials and industries producing intermediate goods are the highest emitters of CO2 per unit of value added. Yet, they face much lower tariffs and nontariff barriers (NTBs) compared to more complex products with lower carbon intensities, mainly because of counterlobbying by downstream industries. This bias has been shown to be equivalent to a negative carbon price of about US$90 per tonne of CO2 on average (3)-the opposite of what a climate-supportive trade regime would require.

Differences in climate change mitigation costs across world regions could be decisive for the implementation of effective climate policies. Emissions resulting from the crossborder transport of goods are on average modest relative to emissions resulting from production. But carbon leakage through relocation of production from high-to low-regulation jurisdictions would be problematic.

The mere anticipation of this type of carbon leakage could render ambitious emission targets politically difficult, if unmatched by other countries. Without clear and obvious benefits for the climate, governments will not be willing to sacrifice the competitiveness of key industries and jobs.

Yet the risk of trade-driven carbon leakage across the whole economy is generally found to be limited. Because of frictions to trade and because energy often constitutes a small share of overall costs, most industries would need very high carbon prices to justify relocation. Thus, leakage should not be used as a pretext to avoid ambitious climate policy or protect domestic industry from imports as it does not substantially compromise the possibility of unilaterally reducing global emissions (4).

Clubs and Adjustments

The current debate on trade and climate change mainly revolves around border carbon adjustments. Recently, the European Commission laid out a proposal for a BCA that would impose the carbon costs borne by European Union (EU) producers on imports from countries with less stringent climate policies. The proposal is designed to levy the carbon price prevailing in the EU Emissions Trading System on imports of iron and steel products, fertilizers, aluminum, cement, and electricity (5). Export rebates, which could help domestic industries compete on a level playing field on the world market but which might violate international trade rules (6), are not part of the EU proposal. Canada and the United Kingdom are actively considering BCA regimes. Likewise, legislators in the United States have proposed border measures adjusting for differences in the costs of environmental regulation, not only carbon pricing.

The rules of the World Trade Organization (WTO) have received criticism for constraining the design of BCA schemes. Nevertheless, adhering to this set of rules facilitates conducting economic transactions across national boundaries. Countries will hence need to carefully navigate the tensions that can arise between the desire to respect global trade rules and the need to elaborate and implement effective national climate policies.

In addition to leveling the playing field, BCAs could constitute an important strategic instrument to deter free-riders who do not contribute to the global public good of climate change mitigation (7). Current efforts to reduce dependence on fossil fuel imports could increase political support for BCAs against exporters of fossil fuels and energy-intensive products. Yet, BCAs might put a substantial burden on other, especially low-income countries. Such inequitable outcomes would go against the United Nations Framework Convention on Climate Change (UNFCCC) principle of "common but differentiated responsibilities and respective capabilities." Political tensions and retaliation by trade partners would result in high economic costs and might also sour international relations to a degree that makes it harder to achieve progress in international climate cooperation. For instance, the European Commission expects that implementation of the proposed BCA will trigger a response by trade partners but remains agnostic as to the nature of this response.

BCAs could also be considered by a club of like-minded countries to confer favorable market access on members of the club, but trade barriers for those outside of it. The German G7 Presidency has vowed to advance the formation of a climate club of countries with comparable climate policies. Jointly adopted harmonized BCAs or other trade restrictions could be a key element of a climate club (8). Harmonizing climate-related trade measures across countries with very different economic situations and climate policy ambitions, however, faces severe limitations. First, as WTO rules demand that foreign producers are not treated less favorably than domestic ones, the carbon price applied to imports cannot exceed the domestic carbon price level. As current carbon prices in, say, the EU and China differ by about a factor of 10, a common BCA in both jurisdictions would need to be set at no more than the Chinese level, which would be insufficient to protect EU producers from carbon leakage. Second, US participation in a climate club is especially important, because the US constitutes the world's largest economy and secondlargest emitter. However, adopting a carbon price in the US faces major political and legal obstacles. Owing to the legal provisions of the WTO, BCAs can only adjust for policies that put a price on carbon emissions, but not for the costs of other types of regulation, such as renewable portfolio standards. The possibility for a WTO-consistent BCA thus seems unlikely in the US. Third, very different approaches to carbon pricing in different countriesfor instance, regarding covered sectors, the instrument used (carbon tax or emission trading), and whether domestic carbon prices are reimbursed to exporters-would further complicate crosscountry harmonization of BCAs (9).

Making Trade Work for Climate

BCAs are unlikely to provide sufficient incentives for joining a climate club, except for those few countries with substantial export shares in the sectors to be covered by a BCA. BCAs will thus have limited potential to force trade partners to adopt climate measures. In addition to the "stick" of a BCA, a climate club also needs "carrots" to make club membership attractive. A balanced mix of BCAs as enablers for ambitious national climate policies and positive incentives to ramp up climate action could help harmonize the trade and climate agendas.

A diplomatic BCA agenda BCAs can ease opposition against climate policy from domestic industries at risk of carbon leakage. Any BCA should, however, be designed in a way that is least trade-restrictive to trade partners that are subject to this policy. The WTO rules generally favor open communication and multilateral efforts to reach negotiated solutions prior to the adoption of unilateral trade measures. Thus, international coordination helps align national climate policies with the WTO regime (10).

Barriers to trade of clean technologies

Imports of environmental goods and services are subject to trade barriers in many nations. Some major economies apply tariffs of less than 3% (green bars) on almost all imports of environmental goods. For others, however, a substantial fraction of such imports is subject to tariffs of more than 3% and in some cases even more than 10% (orange bars) (14).

GRAPHIC: K. FRANKLIN/SCIENCE

Trade policies adopted for environmental reasons can be compatible with the WTO's nondiscrimination principles under certain strict requirements. Even if a BCA violates the WTO's nondiscrimination rules, it can qualify for an exemption depending, in part, on whether countries engage in good faith efforts with their trade partners before adopting a BCA. Countries need to show that unilateral action was necessary or a last resort after having attempted to coordinate with trading partners. Consultations under the UNFCCC or WTO umbrella, as well as bilateral efforts, may satisfy this requirement. The WTO agreements also contain numerous transparency provisions with which a BCA regime needs to comply. This is particularly the case with respect to the purpose, the data used for calculations of the BCA, default values, exemptions and revenue use, and the review and phase-out criteria of the BCA. BCAs have so far not been tested before the WTO dispute settlement mechanism. Prior diplomatic efforts, even-handed application, and transparent administration could substantially increase the chances of a BCA regime to survive WTO scrutiny.

Use the WTO regime to reform and phase out fossil fuel subsidies

In 2020, global fossil fuel subsidies of US$351 billion constituted an important barrier for climate change mitigation (11). The WTO is in a good position to help promote fossil fuel subsidy reform. Given the trade effects of such subsidies, and following the example of ongoing talks on fisheries subsidies, the WTO's extensive rules on subsidies can help tackle fossil fuel subsidies, even though the WTO's dispute settlement system is currently not fully functional. Specifically, the WTO can strengthen transparency through improved notification by its members, counternotification by other members, and by addressing fossil fuel subsidy reform in the Trade Policy Review Mechanism, a system under which WTO members peer-review their trade policies.

New rules-which could consist of an amendment of the Agreement on Subsidies and Countervailing Measures (ASCM) or a stand-alone agreement modeled after the proposed agreement on fisheries subsidies-could define a new category of prohibited subsidies. This may be limited to a subset of fossil fuel subsidies based on their trade and/or environmental effects and take into account the challenges faced by developing countries in subsidy reform (12). As changing (or agreeing to new) multilateral rules is challenging, progressive member states could push ahead with a plurilateral agreement, as some are doing in the context of the Agreement on Climate Change, Trade and Sustainability being negotiated by New Zealand, Costa Rica, Fiji, Iceland, Norway, and Switzerland.

Clear rules for settlement of disputes on renewable energy technologies

Lower trade barriers for climate-friendly goods decrease mitigation costs and could facilitate the achievement of more ambitious climate targets. As the international trade regime requires nondiscriminatory treatment of foreign products and producers, it also has the potential to accelerate the diffusion of clean energy technologies. A case in point is the successful legal challenges that have been raised against local content requirements in renewable energy support schemes. Such discriminatory tools require sourcing a certain share of value added from domestic producers, thereby favoring the latter over foreign firms and hampering global competition in the renewable energy sector, which may raise the costs of emission reductions. At the same time, such arrangements can also help establish competitive innovation capabilities and increase support for climate policies by domestic interest groups. Current geopolitical tensions and the concern about depending on imports of critical materials from authoritarian regimes could result in increased adoption of local content requirement schemes.

Temporary and adaptable local content requirements subject to regular assessment cycles might constitute a compromise between open markets for clean technologies and policy space for climate measures appropriate for the respective national context. To make the trade regime work for the climate, it will require a clear set of criteria to assess the compatibility of domestic support schemes for clean technologies with WTO principles.

Gaps can be identified in other areas that hinder the expansion of trade in renewable energy and green technologies. Examples include the lack of exceptions for climatefriendly subsidies under the ASCM, and the insufficiency of international trade rules to limit trade barriers for green technologies. Addressing such shortcomings through reform of the relevant WTO rules would be highly beneficial for trade in renewable energy and other climate-friendly technologies (13).

Expand efforts to achieve an agreement on environmental goods and services

The agenda to lower trade barriers for clean energy technologies should focus on tariff reductions for environmental goods, which are often still subject to high tariffs (see the figure) adopted to protect domestic industries from foreign competition. Environmental goods on average face higher trade barriers than less complex but more carbon-intensive products.

Negotiations on reducing tariffs on environmental goods have floundered for two decades, even though tariffs were already low among countries engaging in negotiations toward an Environmental Goods Agreement. Many are small "nuisance tariffs" (<3%) that could easily be removed to jumpstart the process for such an agreement ( 14). This effort could be extended to higher tariffs and a longer list of goods that would include Environmentally Preferable Products. These include products that have been produced with lower environmental impacts than their conventional counterparts, such as organic food or sustainably grown timber products.

Packaging and labeling requirements or technical standards and norms can impose substantial NTBs for trade in environmental goods. NTBs related to labor market regulations, such as visa and work permit requirements, may hamper trade in environmental services-for instance, for the sustainable management of energy, water, and forest resources. Therefore, NTBs, which are difficult to detect and sometimes protectionist in intent, should be included in the agenda for mutual recognition.

Explore the potential of green materials clubs

Conditioning technology transfers to abatement efforts may strengthen incentives to join a climate club. A club of like-minded countries could go beyond imposing BCAs on nonmembers and also consider broader cooperation by implementing common green industrial policies, such as low-carbon requirements for climate-intensive globally traded basic materials, such as iron, steel, aluminum, cement, or fertilizers (15). The activities of a green materials club should start at relatively low ambition by developing long-term deep decarbonization visions or roadmaps for energy-intensive industries. In a second step, dedicated support for research, development, and diffusion of technologies and infrastructure planning can be applied in a harmonized manner by club members. More research is needed to gain a more comprehensive understanding of how technologies and policies can be adapted to specific country contexts.

The carrot for joining such a club, and thus adopting green industrial policies, would be getting access to future niche markets for green basic materials, in addition to avoiding (or at least reducing) the stick of BCAs. A green materials club could take on the form of a plurilateral agreement by a subset of early movers under the WTO. Coordinated efforts by a coalition of countries that are leaders in clean technologies would help establish such a green materials club. This would create a critical mass of participants to render the benefits of club membership attractive.

Unexploited Potential

Global trade has often been portrayed as an obstacle for climate policy, as it enables firms to move to export from regions with less ambitious environmental regulations. Such relocation of carbonintensive production can be addressed by BCAs. Trade restrictions, however, can also bring along protectionist elements and only provide limited incentives for other countries to ramp up their climate ambition. BCAs need to be designed carefully according to clear and transparent rules in close dialogue with key trade partners to prevent political tensions that could imperil the entire climate agenda far beyond trade-related issues.

Trade policies supporting the climate agenda will need to pay particular attention to climate impacts on trade and the implications of climate-friendly trade for low-income countries. To support them, trade finance, investment, and aid for trade should be scaled up in areas related to climate change mitigation and adaptation, and additional research will be required to inform policy design.

Beyond unilateral policy approaches that include BCAs, the WTO regime offers a series of options to make the trade regime work for the climate. Unfortunately, up to now, this potential has not been exploited by WTO member states. The options discussed above will face substantial political obstacles. Yet growing awareness of the urgency to transform the global economy toward climate neutrality could give new impetus for restructuring the trade regime in a way that supports climate goals.

Acknowledgments

We thank H. Colyer for language editing and A. Bosio for supporting the preparation of the manuscript.