Florent Dumont

Emy Ponsardin

Guillaume Bernadat

Sylvia Cohen-Kaminsky

A simplified methodology workflow to make reproducible omic bioanalysis

Keywords:

come

Source of variability

The aim of an experimentation and its analysis is to find biological insights by reducing technical noises to better estimate the individual variability coming from the biodiversity of a population. Statistics quantify this variability in an undirected way by using a subset of the population, thus, the p-value computed starting from the sample size and the observed fold-change can only say if the sample size is large enough to correctly represent the population variability to consider that a difference exists. Consequently, observatories use statistical methods as a standard and produce descriptors incorporating a quantified risk, which enables them to conclude regarding the presence or absence of a phenomenon at a biological level, and possibly compare their conclusions with other results obtained under close conditions.

Each step of a complete omic analysis workflow presents its source of variability. Fig1. Illustrate and sum up the source of variability that one could meet at each step of an omic project. First, the experimental step asks for an appropriate design of the number of treatment factors, the number of levels by factor, and the number of samples by level. The more sample we have by groups, the more we can avoid confusing variables with the help of contingency tables to see sample distribution across all factors' level combinations. It is also important to know if samples are linked by pairing (i.e., two measurements on the same subject) or by nested factors (i.e., when the design requires combination levels between two factors with no subjects). The last case to consider is about the interaction between two factors that could be included in the model, enabling to distinguish a synergy from a cumulative effect. All these cases cover a major part of experimental design and can be modeled by analysis of variance. The next step is to pass sample extracts in a high-throughput device, which is already known to have some variability across instrument models and host platforms. At this step, formatted files including device parameters, metadata, metrics, raw data signals, and possibly systemic biases are available. Because of the diversity in omic technologies, bioinformatic preprocessing methodologies and tools are varied and numerous. For example, bioinformatic practices are very different in getting the numerical matrix containing raw signals when dealing with mass spectrometry .raw files or .fastq sequencing files. Preprocessing also includes raw data normalization procedures, which aim at increasing signal/noise ratio and make data more comparable by deleting systemic biases from samples or variables. At this step, three tables are generally accessible for omic bioanalysis: the normalized data file and the sample information file including experimental, phenotypic, clinical and design factors for biostatistics. The third table is an annotation file including at least a Symbol column and an identifier column matching with variables.

All methodologies described above have their contribution to variability in an omic project. Here, we automate the two final steps called bioanalysis corresponding to biostatistics and functional integration procedures. The aim of standardizing bioanalysis is to use biologically interpreted results to have quality indicators that will help understanding and standardizing upstream experimental biases and ultimately emancipate from variables with little latitude such as device types, parameters and plateform practices. Here, we chose an unfiltered published data set [1] to test our omic workflow and see its capacities to generate reproducible and interpretable biological results in one go on a laptop.

Material and methods

First, the workflow used descriptive statistical tools for quality controls: histogram and boxplot for distribution across samples, PCA and HCA for outliers and relevant factors, Fratio barplot for ANOVA model.

As mentioned above, we apply a classical analysis of variance for differential analysis of data. ANOVA belongs to the linear model test family and is a simple and useful way to adjust for most experimental designs. It allows keeping all samples in the same statistical model, which holds statistical power for residual variance estimation and enables comparing biological and technical factor variability from one to another. It also increases fold-change contrast between comparisons because, in the ANOVA context, means are computed as a linear combination using the variance estimation across treatment groups in accordance with the experimental design. Furthermore, we implemented the remove batch effect function from the limma package [2], thus allowing deletion of technical bias that was correctly balanced across factor combinations during sample preparation and guaranteed a better feature selection and clustering for downstream analysis.

For annotation tasks, symbols are automatically re-annotated using synonym checking to avoid information loss. We also integrated the NBCI orthologs gene database to open functional enrichment analysis for species that have identified ortholog genes in human. Consequently, we created additional annotation packages to update all bibliographic data simultaneously, improve results reproducibility, and decrease computing time. Annotation databases include NCBI gene [3] for 11 species,1 NCBI orthologs [3], Ensembl [4], and Uniprot [START_REF] Uniprot | The Universal Protein Knowledgebase in 2023[END_REF]. Gene sets databases include MSigDB [6,7] and the Gene ontology [START_REF]The Gene Ontology knowledgebase in 2023[END_REF]. StringDB [9] is used for interaction network. Dependency packages providing notably language extensions, parallel processing, analytical technique-specific, clustering, functional analysis and graphing functions have been used [2,.

Fig. 2 shows all biostatistics and functional analysis tasks realized by the omic() function workflow.

Results

Application example: re-analysis of the published dataset GSE65055 As a positive control, we reproduced the enrichment analysis of transcriptomic analysis carried out on aneuploidy samples for trisomy 13, 18, 21 and the associated control samples [1] (https://pubmed.ncbi.nlm.nih.gov/27283765/).

The study infers that "overall genome expression profiles highlighted changes in the expression of a subset of genes in trisomic chromosomes, while the majority of transcriptional changes concerned genes located on euploid chromosomes." [1] (Fig. 2) Quality controls "We therefore chose only to compare expression profiles produced from the same type of sample to avoid any confusion between aneuploidy effect and cell-type specific differences." "Lastly, we compared five trisomy 21 chorionic villus samples with four euploid chorionic villus samples." [1] As explained in the publication above, one outlier sample was removed from chorionic tissue (GSM1586484), and we divided the experimental design into two ANOVA models for each tissue type because of the heterogeneity. Fig. 4. shows the replication of these two observations using the data processing matrix available from GEO.

Differential analysis

As illustrated in Fig. 5., in order to reproduce the differential analysis, we started from the same unfiltered matrix and chose to apply a unique 2-ways ANOVA model including ANEUPLOIDY and TISSUE factors instead of the two separated analyses as described above.

Enrichment analysis

As shown in Fig. 6, we reproduced enrichment results starting from unfiltered matrix data using the same thresholds (p-value < 0.05 and fold-change > 1.5). Here, using MSigDB positional gene set collection corresponding to human chromosome cytogenetic bands, we found the best enrichments and p-values for aneuploid chromosomes corresponding to the up-dysregulated list of genes.

We observed that few other gene set cytobands give significative enrichment scores for euploid chromosomes. More precisely, starting from 299 gene sets in the we obtained 10 significative gene sets for trisomic chromosomes and 3 for others (chr4q32, chr14q24, chr17q21). These results validate the re-analysis of the dataset and workflow capabilities to produce relevant biological interpretations starting from unfiltered data.

Discussion

The R package we have developed aimed at showing that it was possible to automate and integrate classical biostatistical and functional omic analysis available for a dozen of current biological models, as well as illustrating the advantages of shortening and alleviating the process leading up to biological interpretation.

Starting simply from an unfiltered normalized data table and its experimental design, one easy-to-use function enabled generating a complete (unsupervised and supervised) analysis. Results contain PCA and HCA plots, which allow observation of the distribution of samples across treatment groups without a priori, as well as ANOVA F ratio barplot, which helps evaluating quality of model adjustment with the experimental design.

By interrogating classical biological and medical knowledge databases based on relevant features at several threshold levels and displaying results using simple infographics, we hope to have contributed some form of one-stop computer-aided biological interpretation. By leveraging ortholog information for extra species, we are also trying to provide tools that facilitate reasoning beyond the classic rodent and human models.

Output is organized in a directory with an unchanged structure between runs (favoring open, easyto-read and reusable file formats), while attempting to capture input parameters and database versions, as well as recording graphics and tables produced to facilitate focus on significant information. One can, therefore, change a unique parameter and quickly determine its influence on results from the biological standpoint.

Typically, outliers can be detected/excluded, and unexpected batch factor can be added to the ANOVA model, before the analysis is re-run at little cost, which facilitates comparison of results based on biological interpretation. Moreover, all discriminant patterns generated at several threshold levels can be easily compared simultaneously at the functional level, which allows one to be about the influence of statical thresholding on biological interpretation.

(Parts of) our package could also prove helpful to control and prepare data for other workflows. For example, when removing a batch effect (or matching factor) according to the experimental design is required, the unballasted matrix ready for downstream analysis can be retrieved from the results directory.

Regarding annotation and species, symbols are automatically annotated using synonym checking, and functional analysis can be carried out for all species that have identified ortholog genes in the human NCBI gene database.

Conclusion

In the context of multi-omic data analysis, we found no such tools gathering current biostatistical and functional analysis tasks in the same workflow to produce biologically enriched results locally in one go. We attempted to fill this gap with a R package containing a single, easy-to-use function requiring only an unfiltered normalized data table and the corresponding experimental design. We expect this tool to create a higher level of experimentation regarding the data processing phase, thereby facilitating and improving the optimisation of related parameters and contributing to maximize scientific yield of input data.

Install

For users interested in using the software immediately: binary packages and instructions for installing are currently available from: https://www.ipsit.universite-paris-saclay.fr/?-bioinfo-(a https://fdumbioinfo.r-universe.dev subdomain is in progress).

For developers/biostatisticians: source files and instructions for building (update annotations) and installing packages are available from Zenodo: https://doi.org/10.5281/zenodo.10013866.

Bos taurus, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Gallus gallus, Homo sapiens, Mus musculus, Pan troglodytes, Rattus norvegicus, Sus scrofa, Xenopus tropicalis.

Acknowledgements

We thank Claudine Deloménie for helpful discussions and testing the MOAL package, Paul Savescu for testing MOAL and developing future features for helping results interpretation, and Françoise Cormier for her help in testing MOAL and interpretating biological results, all from the IPSIT (Ingénierie et Plateformes au Service de l'Innovation Thérapeutique) team. IPSIT belongs to Université-Paris-Saclay. IPSIT is a UMS (Unité Mixte de Service US31 Inserm, UAR3679 CNRS), which brings together technological platforms. IPSIT intends to be firmly at the interface of chemistry, biology, and medicine, establishing the link between the pathological target and the drug. Thanks to Laura Samrani for help testing topGO biological results analysis from UMR-S 996 at Paris-Saclay University. The Migale Bioinformatics facility, GaBi @BRIDGe (Université Paris-Saclay, INRAE, 78350, Jouy-en-Josas, France) platform and UPSay IT department are gratefully acknowledged for computational resources, technical support and/or statistical advice.

Abbreviations

PCA: Principal Component Analysis, AHC: Ascendant Hierarchical Clustering, ANOVA: analysis of variance


Seungah Lee

Ruben Salvador

Angeliki Kritikakou

Olivier Sentieys

Julien Galizzi

Emmanuel Casseau

High-Level Synthesis-Based On-board Payload Data Processing considering the Roofline Model

Keywords: On-board processing, FFT, System-on-Chip (SoC), FPGA, High-level synthesis (HLS), Roofline performance model

On-board payload data processing can be performed by developing space-qualified heterogeneous Multiprocessor Systemon-Chips (MPSoCs). We present key compute-intensive payload algorithms, based on a survey with space science researchers, including the two-dimensional Fast Fourier Transform (2-D FFT). Also, we propose to perform design space exploration by combining the roofline performance model with High-Level Synthesis (HLS) for hardware accelerator architecture design. The roofline model visualizes the limits of a given architecture regarding Input/Output (I/O) bandwidth and computational performance, along with the achieved performance for different implementations. HLS is an interesting option in developing FPGA-based onboard processing applications for payload teams that need to adjust architecture specifications through design reviews and have limited expertise in Hardware Description Languages (HDLs). In this paper, we focus on an FPGA-based MPSoC thanks to recently released radiation-hardened heterogeneous embedded platforms.

I. INTRODUCTION

Satellites embark payload sensors that require data processing to obtain data products so that payload data processing designates a series of processing for a payload. Payload data processing has traditionally been performed on the ground, after the downlink of raw data, due to the lack of high-performance processors tolerant to radiation [START_REF] Montealegre | In-flight reconfigurable FPGA-based space systems[END_REF]. However, with recent space-qualified heterogeneous Multiprocessor System-on-Chips (MPSoCs), high-performance on-board processing is expected. Migrating ground-based data processing pipelines to on-board systems can significantly increase system autonomy and decrease monitoring and detection latency.

The purpose of this work is to explore the possibility of such migration by leveraging the recent heterogeneous accelerator architectures integrating a Field-Programmable Gate Array (FPGA) with Arm processors for both scientific missions and NewSpace, such as space exploration and Earth observation. To achieve that, the first step is to identify the most important candidates for payload data processing to be moved on board. More precisely, we perform a survey on on-board embedded systems (Table I) and payload processing algorithms regarding recent and near-future missions, in which European research institutes are involved. Based on this survey, we selected as a case study the most recurring payload algorithm found, i.e., the Fast Fourier Transform (FFT).

Most current missions with FFT on-board implementations focus on the one-dimensional (1-D) FFT. There are few cases of 2-D FFT implementations on space-qualified processors, which, however, have low performance with long latency. One reason is that the processor, usually paired with small on-chip memories, requires a significant amount of external memory access. To address this limitation, application-specific hardware accelerators can be used for compute-intensive algorithms, including the 2-D FFT. However, such implementations should efficiently meet the restricted on-board resources and maintain design productivity close to software-only implementations. Therefore, we propose a Design Space Exploration (DSE) approach, where we combine the roofline performance model [START_REF] Williams | Roofline: an insightful visual performance model for multicore architectures[END_REF] with High-Level Synthesis (HLS)-based hardware design. On the one hand, the roofline performance model allows us to bound accelerator architectures considering memory access, application, and architecture constraints [START_REF] Siracusa | A comprehensive methodology to optimize fpga designs via the roofline model[END_REF]. On the other hand, HLS enables the exploration of various hardware designs effectively. Specifications using the C++ language, combined with HLS, make hardware design less complex compared to using a Hardware Description Language (HDL), as high-level descriptions can be interpreted to create digital hardware with the same functionality. Considering recently developed hardware architectures, we propose using Commercial Off-The-Shelf (COTS) heterogeneous embedded systems. Specifically, we use the Xilinx Zynq UltraScale+ MPSoC as an initial target after reviewing the specifications of radiation-hardened heterogeneous embedded platforms recently released, e.g., NG-Ultra and Versal [START_REF] Ibellaatti | HERMES: qualification of High pErformance pRogrammable Microprocessor and dEvelopment of Software ecosystem[END_REF], [START_REF] Perryman | Evaluation of Xilinx Versal Architecture for Next-Gen Edge Computing in Space[END_REF].

II. ON-BOARD DATA PROCESSING ALGORITHMS FOR SCIENTIFIC MISSIONS AND NEWSPACE: THE FFT CASE

We surveyed current on-board and ground processing algorithms to identify the trends of on-board data processing and the expected needs of future missions. Besides, in collaboration with scientific payload teams, we identified and prioritized compute-intensive algorithms applicable to several types of payloads, depicted in Table II. These algorithms are challenging and thus hardly executed on an existing radiation-hardened On-Board Computer (OBC) with flight heritage. According to our survey, the 2-D FFT is widely used in diverse applications, including Synthesis Aperture Radar (SAR) [START_REF] Wiehle | Synthetic Aperture Radar Image Formation and Processing on an MPSoC[END_REF] and space telescopes [START_REF] Smith | Distributed computing architecture for image-based wavefront sensing and 2D FFTs[END_REF]. Therefore, we selected the 2-D FFT as a case study based on the computational requirements of payloads, such as image size and data accuracy. The 2-D FFT can be a demanding algorithm due to its column-wise processing step or transpose, which can easily become a computational and memory bottleneck [START_REF] Yu | FPGA Architecture for 2D Discrete Fourier Transform Based on 2D Decomposition for Large-sized Data[END_REF].

The Fourier transform is a transformation converting a time-domain function f (x) to a frequency-domain function f (ξ) and its general expression can be described using the infinite integral of integration given by:

f (ξ) = ∞ -∞ f (x)e -j2πξx dx (1)
X(k) = N -1 n=0 x(n)e -j2πkn N (2)
Similarly, for an N × N matrix of signals x(n 1 , n 2 ) where n 1 , n 2 = 0, 1, . . . , N -1, the 2-D DFT results X(k 1 , k 2 ) are defined as below regarding the frequency k 1 and k 2 , where k 1 , k 2 = 0, 1, . . . , N -1.

X(k 1 , k 2 ) = N -1 n1=0 N -1 n2=0 x(n 1 , n 2 ) • e -j2π(k 1 n 1 +k 2 n 2 ) N (3)
From the above equations, we can derive that the complexity of DFT is O(N 2 ) for the 1-D DFT and O(N 3 ) for the 2-D DFT.

As the DFT computation is slow, there have been several attempts to increase DFT performance: this is how the FFT was devised. The FFT is an algorithm for calculating the DFT efficiently by reducing the computational complexity. The Cooley-Tukey algorithm is the most popular FFT algorithm, which breaks down the summation recursively into a certain number called radix [START_REF] Cooley | An algorithm for the machine calculation of complex Fourier series[END_REF]. The radix determines the number of arithmetic operations of FFT which is consequently relevant to the computational cost of FFT. In this paper, we focus on the radix-4 FFT considering the library implemented in section IV as a use case. For instance, we deal with the N-point Decimation-In-Time (DIT) radix-4 FFT which separates the summation notation of (2) into 4 different terms (n = 4m, 4m + 1, 4m + 2, 4m + 3) where the upper limit of summations is N 4 -1. The summation can be represented as follows:

X(k) = N 4 -1 m=0 x(4m)e -j2πk(4m) N + N 4 -1 m=0 x(4m + 1)e -j2πk(4m+1) N + N 4 -1 m=0 x(4m + 2)e -j2πk(4m+2) N + N 4 -1 m=0 x(4m + 3)e -j2πk(4m+3) N (4)
Considering the symmetry of the exponential factors, we can simplify the exponential terms into twiddle factors

W k N = e -j2πk N
which are represented in the butterfly operations in the context of the Cooley-Tukey FFT algorithm. The butterfly operation is a unit of the FFT and the total number of butterflies of radix-R FFT is the multiplication of the number of stages (log R N ) and the number of input data divided by radix ( N R ), thus the total number of butterflies is N R log R N . Based on this definition, each radix-4 FFT butterfly has 3 complex multiplications and 8 complex additions as shown in Fig. 1. For the radix-4 FFT, the total number of complex multiplications is 3 N 4 log 4 N , and the total number of complex additions/subtractions is 2N log 4 N . If we want to use the hardware composed of only real operators, such as FPGAs, understanding real arithmetic operations is also necessary, as the hardware cannot perform complex operations directly. The total number of real multiplications is 3N log 4 N and the number of real additions/subtractions is 11 2 N log 4 N [START_REF] Neuenfeld | Design of optimized radix-2 and radix-4 butterflies from FFT with decimation in time[END_REF]. Based on the required number of real operations, we

III. DSE METHODOLOGY

DSE helps to navigate the space of possible design solutions by formulating the design problem as a multi-objective optimization problem, which considers latency, area, and power [START_REF] Schafer | High-Level Synthesis Design Space Exploration: Past, Present, and Future[END_REF]. By associating the roofline model with designs achieved from HLS, we explore several hardware accelerator designs on an FPGA and analyze their suitability for scientific missions and NewSpace.

A. Roofline model

The roofline model characterizes designs using the limits of bandwidth and performance on a given architecture [START_REF] Williams | Roofline: an insightful visual performance model for multicore architectures[END_REF]. Even though the original roofline model is appropriate to von Neumann architectures, namely multicore Central Processing Unit (CPU) architectures and Graphics Processing Unit (GPU), the model has been extended for FPGAs considering their reconfigurable characteristics [START_REF] Da Silva Gomes | Performance modeling for FPGAs: extending the roofline model with high-level synthesis tools[END_REF].

The FPGA roofline model, drawn as a log-log scale in Fig. 2, is based on two ceilings that present the limits of a given architecture: i) Input/Output (I/O) bandwidth ceiling and ii) computational ceiling. Consequently, any application implementation is bounded either by the I/O bandwidth ceiling (memory-bound) or the computational ceiling (compute-bound). The computational ceiling is calculated using the total number of specific computational resources, the number of required resources per arithmetic operation, and the maximum clock frequency. If an FPGA reads data from external memory to perform processing, the I/O bandwidth ceiling depends on the external memory and its relevant interface. In other words, the one with smaller bandwidth becomes the I/O bandwidth of a given system. For external memory, its bandwidth is the multiplication of memory data rate and memory channel bit-width. In the case of an interface, the bandwidth is the multiplication of clock frequency, transfer data bit-width, and the number of interface ports.

We can also indicate the implementations of a kernel, corresponding to each point in Fig. 2, to see whether any ceilings bound the design. In this context, the kernel defines a routine running on a hardware accelerator such as an FPGA, which is distinguished from an application executed on a CPU. The x-axis value of an implementation is the computational intensity, which is the number of total operations divided by the number of total data bytes accessed, and the y-axis value is the performance, represented as the number of operations divided by execution time.

B. HLS-based hardware accelerators

We use HLS based on C/C++ instead of using traditional HDLs for the design of hardware accelerators. Comparatively, HLS enables the simpler generation of different designs meeting the application's constraints faster and easier. To generate efficient hardware accelerators, HLS codes must be optimized accordingly. This requires refactoring an initial, functional C/C++ code carefully and using appropriate pragmas and directives to help the compiler generate hardware that efficiently uses the available memory and computational resources of FPGA for a considered application [START_REF] Schafer | High-Level Synthesis Design Space Exploration: Past, Present, and Future[END_REF], [START_REF] Cong | FPGA HLS Today: Successes, Challenges, and Opportunities[END_REF]. Overall, HLS is both efficient and promising, simplifying the development not only of hardware but also of software-hardware co-design. Each HLS tool provides a large list of pragmas and directives that help users to perform the fine-tuning of their architecture. In this paper, the HLS tool we use is Vitis HLS from AMD-Xilinx. We present frequently used pragmas and directives below, which are later used in section IV-D [START_REF]Vitis High-Level Synthesis User Guide (UG1399)[END_REF], [START_REF] Kastner | Parallel Programming for FPGAs[END_REF]: loop unrolling, loop pipelining, task pipelining, and array partitioning.

Loop unrolling unrolls a loop and executes all or some iterations of one loop in parallel (full unroll or partial unroll). This pragma decreases intervals and latency by enhancing parallelism, whereas it increases resource utilization. The interval is the number of clock cycles between two loop iterations in a row. Vitis HLS provides #pragma HLS unroll, which allows full unroll without any syntax option and enables partial unroll with the option factor=N, where N is the number of loop bodies replicated.

Loop pipelining enables the concurrent execution of operations at the cycle level so that it decreases the initiation interval (II) for a loop. The II indicates the number of clock cycles spent before starting the next loop iteration [START_REF] Fingeroff | High-level Synthesis: Blue Book[END_REF]. Thus an II=1 means a new loop iteration is started every clock cycle. This reduces intervals and latency, increasing the minimum amount of resources. Vitis HLS has #pragma HLS pipeline which tries the minimum II (i.e., 1) unless the syntax option II=N is statically specified for the number of II.

Task pipelining allows functions and loops to perform concurrent executions of coarse-grained operations taking a number of clock cycles, improving the general throughput of the architecture. Unlike the loop pipelining dealing with cycle-level pipelines, the behavior of relevant functions and loops cannot be statically scheduled. Users can utilize #pragma HLS dataflow for task-level pipelining in Vitis HLS.

Array partitioning subdivides an array into several smaller arrays. Arrays are stored on FPGA block RAMs (BRAM), which have single or dual ports. If a user implements only one large memory and needs to read and write multiple times, the small number of ports can drop throughput. However, this problem can be solved by partitioning a large memory into smaller memories or registers: the increased number of ports can then enhance throughput. #pragma HLS array_partition in Vitis HLS is defined with an array variable name and a partition type.

As a result, combining the roofline performance model and HLS-based design techniques enables developers to rapidly generate and evaluate processing architectures with different performance/resource trade-offs, reducing the time to prototype implementations [START_REF] Siracusa | A comprehensive methodology to optimize fpga designs via the roofline model[END_REF]. Such an approach is suitable for payload teams where instrumentation specifications change depending on the mission and design review and where human resources are limited for developing on-board processing applications using an HDL.

IV. DSE USE-CASE: THE 2-D FFT

We present the FPGA roofline model and relevant DSE based on Vitis HLS targeting the Xilinx Zynq UltraScale+ ZCU102 evaluation board and the 2-D FFT as a use case.

A. Algorithm requirements

We selected the 2-D FFT considering its necessity in the space science community (Table II). More precisely, we selected the SVOM ECLAIRs code-masked telescope to extract technical requirements. The ECLAIRs telescope embarks a LEON3-based on-board payload control unit, processing the image trigger algorithm every 20.48 sec. The algorithm includes the deconvolution of 200×200-sized images based on the 2-D FFT which takes around 2 sec per image on board [START_REF] Schanne | A Scientific Trigger Unit for space-based real-time gamma ray burst detection I -Scientific software model and simulations[END_REF], [START_REF] Dagoneau | Détection de sursauts gamma ultra-longs et traitement d'images embarqué pour le télescope spatial SVOM/ECLAIRs[END_REF]. Assuming that the 2-D FFT per image accounts for at least 5% of execution time, we set 100 ms as the time requirement in this paper. For data precision, we use single-precision floating-point data and 27-bit fixed-point data. The floating-point arithmetic operations are frequently used in astronomy as it is suitable for high-accuracy data and software implementation. However, not every Digital Signal Processing (DSP) block of FPGA implements floating-point support naturally. In other words, multiple DSP blocks can be required to perform floating-point computations depending on the FPGA model. For fixed-point computations, we use the maximum size of fixed-point data whose arithmetic operation fits in one of the DSP blocks available in the device contained in the board used in this paper, so we can balance resource utilization and acceptable data bit-width. C. Theoretical FPGA roofline model Fig. 4 depicts the obtained FPGA roofline model considering the hardware specifications of the ZCU102 board. As complex FFT computation on an FPGA requires real multiplications and real additions, we only consider DSP blocks as a computational resource type in this study [START_REF] Diakite | OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration[END_REF].

First, the theoretical maximum computational ceiling is based on the total number of DSP blocks and their maximum frequency [START_REF]Zynq UltraScale+ MPSoC Data Sheet: DC and AC Switching Characteristics (DS925)[END_REF], assuming a DSP block handles one operation (op). The theoretical computational ceiling C th is:

C th = 2520 DSP blocks × 775 MHz × 1 op/DSP block = 1953 Gops/sec (5)
FPGAs are reconfigurable platforms that can implement different custom processing architectures. As a result, the ceilings in FPGA rooflines are not unique when one considers realistic occupations achievable by synthesis tools (which do not reach 100%), so they can change depending on the reasonable amount of resource usage and the maximum achieved frequency. Thus, we compute more realistic maximum computational ceilings determined by the 80% of DSP block utilization following the Register Transfer Level (RTL) synthesis guideline of Vitis HLS and 250 MHz frequency based on the synthesis reports on the 2-D FFT design provided by Vitis HLS. Moreover, we need to consider the number of required DSP blocks per operation, depending on the data type and the data bit-width. If input fixed-point data require only one DSP block for an operation, computational ceiling C f ix is:

C f ix = 2016 DSP blocks × 250 MHz × 1 op/DSP block = 504 Gops/sec (6)
As said before, a single-precision floating-point arithmetic operation requires more than one DSP block, especially the floating-point multiplication used in this paper requires 3 DSP blocks per floating-point operation (Flop) based on a Vitis HLS report. The computational ceiling of single-precision floating-point operation C f p is:

C f p = 2016 DSP blocks × 250 MHz ×
1 Flop 3 DSP blocks = 168 GFlops/sec [START_REF] Bruijne | Detecting stars, galaxies, and asteroids with Gaia[END_REF] In addition, the three FPGA memory interfaces are taken into account for the I/O bandwidth ceiling: i) PS DDR4 to PS, ii) AXI interface between PS and PL, and iii) PL DDR4 to PL. In this study, we consider hardware accelerators whose input data are initially stored in the PS DDR4 and controlled by the PS. Therefore, the I/O bandwidth ceiling is the smaller value between the PS DDR4 bandwidth and PS-PL AXI interface [START_REF] Calore | Performance assessment of FPGAs as HPC accelerators using the FPGA Empirical Roofline[END_REF]. The PS DDR4 bandwidth (BW P S DDR4 ) is the multiplication of DDR transfer rate and DDR width [START_REF]Zynq UltraScale+ MPSoC Data Sheet: DC and AC Switching Characteristics (DS925)[END_REF]. The Zynq Ultrascale+ has 4 AXI ports [START_REF] Manev | Unexpected Diversity: Quantitative Memory Analysis for Zynq UltraScale+ Systems[END_REF], and the AXI bandwidth (BW AXI ) depends on the clock frequency, transfer data bit-width, and the number of used ports. i.e., the I/O bandwidth ceiling BW is calculated as follows:

D. Parallelism and pipelining

We designed the 2-D FFT to compute both the row-wise FFT and the column-wise FFT by reading all the input data stored in PS DDR4 in the beginning and using only on-chip memory during the FFT, as the FFT size per data set (256 × 256 and 64 × 64) fits in the BRAM of the platform1 . As a reference, we used the Super Sample data Rate (SSR) 2-D FFT provided by the Xilinx open-source HLS-based DSP library [START_REF]Vitis Accelerated Libraries[END_REF] by optimizing HLS pragmas and configuring the radix-4 FFT. The original reference features high parallelism and pipelining appropriate to low-latency applications. For example, the reference includes full loop unrolling using #pragma HLS unroll with #pragma HLS array_partition and task pipelining through #pragma HLS dataflow to maximize throughput. However, the library should be modified for the ZCU102 board as the reference design targets Xilinx data center boards, which have larger resources and a different type of on-chip memory. For instance, as Zynq UltraScale+ ZU9EG does not include Ultra RAM (URAM), the #pragma HLS resource with the URAM option is removed. Moreover, the floating-point design results in over 100% of DSP block utilization with the FFT size 256 × 256, so we modified pragmas such as #pragma HLS pipeline.

E. FPGA roofline model for the 2-D FFT

We performed RTL synthesis after C synthesis, which shows more realistic results by including placement and routing. Table IV shows the RTL synthesis results on the optimized cases. The floating-point designs use more than 4 times of DSP blocks because a single-precision floating-point multiplication requires 3 DSP blocks per operation. The BRAM utilization is higher with fixed-point data than with floating-point data because we increased the II using #pragma HLS pipeline for the floating-point application. The modification makes the number of DSP blocks fit in the given platform. Thus, we recommend using the maximum fixed-point data available in a DSP block for resource efficiency in the case of an actual space-qualified MPSoC, which has fewer resources than industrial-grade products. Fig. 5 illustrates the 2-D FFT roofline model and the accelerator designs, with different data types and FFT sizes, based on the RTL synthesis results of the input data sets. In this case, the computational intensity of kernel is calculated with the number of multiplications of the radix-4 2-D FFT algorithm and the input data accessed through the AXI interface. In addition, the performance of each design is the ratio between the number of multiplications and the total execution latency. For example, for the fixed-point design with the FFT size 256 × 256, the total latency is 1.5 ms. In addition, the total latency for single-precision floating-point data is 3 ms. The I/O bandwidth ceiling is achieved using the 4 AXI ports. The computational ceilings are obtained from the DSP block utilization, the implemented frequency, and the number of required DSP blocks per multiplication with the given data type. As depicted in the figure, all the designs are under the I/O bandwidth ceiling.

Although the accelerator architectures are highly pipelined and satisfy the algorithm requirements in terms of time, data accuracy, and image size, the performance of the designs is far from the ceiling. This signifies that the platform is oversized or that the FFT code does not efficiently use the available resources, e.g., non-operational behaviors in the FFT code consume significant latency. The used 2-D FFT designs perform matrix transpose between the row-wise FFT and the column-wise FFT to avoid column-wise memory accesses which can be a computational bottleneck. However, the transpose requires memory transfers three times [START_REF] Yu | FPGA Architecture for 2D Discrete Fourier Transform Based on 2D Decomposition for Large-sized Data[END_REF], which stalls operations and increases the total latency. Therefore, there is some scope to improve the efficiency of the accelerator architecture by optimizing the memory accesses of the 2-D FFT.

V. CONCLUSION

We present the payload data processing hardware used in the last decade and near-future missions to analyze the on-board processing trends. Considering the performance of state-of-the-art space-qualified MPSoCs, it is expected to migrate payload data processing pipelines partially to on-board systems. The survey on key algorithms reflects the needs of payload teams, so it can be helpful for the space engineering community to prepare high-performance on-board processing for future missions. We propose combining the roofline model with HLS-based DSE to conduct performance analysis. We finally suggest the roofline of 2-D FFT on the Xilinx Zynq UltraScale+ ZCU102 evaluation board with HLS synthesis results as a case study. The results show the 2-D FFT takes less than 5 ms of latency satisfying the given input data requirements, which are 20 times faster than the assumed time requirement. This significant processing time improvement can be a major factor to consider on-board data processing in future missions.

Fig. 1 .

 1 Fig. 1. Butterfly of the DIT radix-4 FFT

Fig. 2 .

 2 Fig.2. Roofline model[START_REF] Da Silva Gomes | Performance modeling for FPGAs: extending the roofline model with high-level synthesis tools[END_REF]

Fig. 3 .

 3 Fig. 3. ZCU102 evaluation board configuration

Fig. 4 .

 4 Fig. 4. Theoretical roofline model of ZCU102 PL based on DSP blocks. The roofline model describes computational ceilings (red and green) and I/O bandwidth ceilings (blue). As the given FPGA does not support floating-point arithmetic, users should consider the number of DSP blocks per operation (green).

8 ) 4 = 16 GB/sec ( 9 )

 84169 BW P S DDR4 = 2133 MT/sec × 64 bits/transfer = 17.064 GB/sec (BW AXI = 250 MHz × 128 bits × BW = min(BW P S DDR4 , BW AXI )= 16 GB/sec[START_REF] Ibellaatti | HERMES: qualification of High pErformance pRogrammable Microprocessor and dEvelopment of Software ecosystem[END_REF]

Fig. 5 .

 5 Fig. 5. Roofline model of ZCU102 PL based on DSP blocks. The roofline model consists of the I/O bandwidth ceiling (blue) and the computational ceilings (red and green) based on the RTL synthesis results of 2-D FFT with the FFT size 256 × 256. The designs present the results of different FFT sizes and data types.

TABLE I PAYLOAD

 I DATA PROCESSING HARDWARE EXAMPLES USED FOR THE LAST 10 YEARS AND NEAR-FUTURE MISSIONS

	Mission	Launch year	Payload data processing hardware	Ref.
			GR712RC LEON3FT ASIC,
	PLATO	2026*	MDPA LEON2FT ASIC,	[2]
			LEON3FT with RTAX2000 FPGA
	JUICE	2023	GR712RC LEON3FT ASIC	[3]
	Solar Orbiter	2020	LEON3FT with RTAX4000 FPGA	[4]
	CHEOPS	2019	GR712RC LEON3FT ASIC	[5]
	BepiColombo	2018	HIREC-MIPS-HR5000 CPU,	[6]
			RTAX2000 FPGA
	Gaia	2013	Custom pre-processing board,	[7]
			SCS750 PowerPC board
		*Estimated launch schedule

TABLE IV RESOURCE

 IV UTILIZATION OF THE 2-D FFT RTL SYNTHESIS RESULTS INCLUDING PLACEMENT AND ROUTING

	FFT size	64 x 64	256x256
	Data type	27-bit FxP	FP32	27-bit FxP	FP32
	DSP blocks	196 (7.8%)	928 (37%)	308 (12%)	1276 (51%)
	BRAM	48 (2.6%)	32 (1.8%)	618 (34%)	528 (29%)
	LUT	58843 (21%)	109870 (40%)	89508 (33%)	157710 (58%)
	FF	82129 (15%)	199467 (36%)	103394 (19%)	262969 (51%)
	Frequency	225 MHz	227 MHz	224 MHz	217 MHz

At this stage of the work, we focus on the computing performance inside the accelerator. So we consider all data fit in on-chip memory, i.e., I/O bandwidth to access data stored in off-chip memory does not limit the performance

ACKNOWLEDGMENT

The authors thank Mickaël Bruno and Clément Coggiola at CNES for assistance in prioritizing space scientific algorithms. We also thank several research institutes including CNES, LESIA (Laboratory of Space Studies and Instrumentation in Astrophysics) of the Paris Observatory/CNRS, IJCLab (Laboratoire de Physique des 2 infinis Irène Joliot-Curie) of IN2P3 (National Institute of Nuclear and Particle Physics), and LPC2E (Laboratoire de Physique et de Chimie de l'Environnement et de l'Espace) for participation in our survey to collect payload data processing algorithms.


Anaëlle Gabet

Christine De Brauer

Gilles Mailhot

Marcello Brigante

Hélène Métivier
email: helene.metivier@insa-lyon.fr

Pilot-scale assessment of the viability of UVA radiation for H2O2 or S2O82-activation in advanced oxidation processes

Keywords: AOPs, micropollutants, photolysis, pilot scale, UVA radiation, wastewater

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Water scarcity is about to be one of the major challenges of the next decades. The European Union Water Framework Directive adopted in 2000 aims at protecting the quality and the quantity of water bodies in the European Union. Although significant improvements were observed within the last decades regarding the quality of water bodies, the presence of anthropogenic micropollutants in surface and ground waters is increasingly reported.

Wastewater treatment plants (WWTPs), whether they are conventional or wetlands, are one of the major gateways of micropollutants to the environment because a large panel of compounds is refractory to the treatments that are commonly used. As a consequence, effluents are released to the environment with micropollutants at concentrations up to several tens of µg L -1 [START_REF] Gallé | An immission perspective of emerging micropollutant pressure in Luxembourgish surface waters : A simple evaluation scheme for wastewater impact assessment[END_REF][START_REF] Luo | A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment[END_REF][START_REF] Pasquini | Occurrence of eight household micropollutants in urban wastewater and their fate in a wastewater treatment plant. Statistical evaluation[END_REF]. Improving the removal of micropollutants in WWTPs by the use of appropriate treatments would allow the discharge of water of better quality. Moreover, it could promote effluent reuse for crop fields irrigation or industrial use for example and decrease the pressure on aquatic environments.

In France, more than 90% of the WWTPs are small and medium-sized (< 10,000 population equivalent) and around 40% are equipped by nature-based processes such as constructed wetlands (CWs) [START_REF]Portail assainissement collectif[END_REF]. These plants have different human and technical resources and therefore different needs compared to large-scale urban WWTPs. They require cheap, reliable and lowmaintenance processes. Among the existing treatments for micropollutants, photoactivated advanced oxidation processes (AOPs) seem to meet these criteria. They consist in the generation of highly oxidising species such as HO • ( = 2.80 V/SHE at 25 °C) by the photolysis of an oxidant precursor (typically H 2 O 2 ). The abilities of the UVC/H 2 O 2 process have been widely reported. Cédat et al. [START_REF] Cédat | Are UV photolysis and UV/H2O2 process efficient to treat estrogens in waters? Chemical and biological assessment at pilot scale[END_REF] observed the complete degradation of a mixture of three estrogens (5 µM each spiked in a WWTP effluent) and of their estrogenic activity and estimated the cost of the technology to be under 0.20 € m -3 . However, UVC radiation is generally produced by mercury lamps which are quite energy consuming. In the UVC/H 2 O 2 process, Cédat et al. [START_REF] Cédat | Are UV photolysis and UV/H2O2 process efficient to treat estrogens in waters? Chemical and biological assessment at pilot scale[END_REF] estimated that electricity would represent from 14 to 38% of the total treatment cost. Moreover, H 2 O 2 supply is another significant expenditure item since it was estimated to represent from 47 to 62% of the total cost.

With a view to optimising the efficiency/cost ratio of the AOP, alternatives to the UVC/H 2 O 2 treatment were presented in the literature. For example, the abilities of S 2 O 8 2-as an oxidant precursor to generate two sulfate radicals (SO 4

•-

) ( = 2.5 -3.1 V/SHE at 25 °C, depending on the solution pH) by photolysis have been widely shown [START_REF] Chen | Biological assessments of a mixture of endocrine disruptors at environmentally relevant concentrations in water following UV/H2O2 oxidation[END_REF][START_REF] Song | A mini review of activated methods to persulfate-based advanced oxidation process[END_REF][START_REF] Zhang | Impact of Chloride Ions on UV/H 2 O 2 and UV/Persulfate Advanced Oxidation Processes[END_REF].

Then, another alternative is the use of solar light as a UV source. Incident solar radiation on earth is a free and renewable energy, composed of 95% of UVA and 5% of UVB and it was previously reported in the literature that UVA radiation is able to photolyse H 2 O 2 and S 2 O 8 2- [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF][START_REF] Moreira | Solar treatment (H2O2, TiO2-P25 and GO-TiO2 photocatalysis, photo-Fenton) of organic micropollutants, human pathogen indicators, antibiotic resistant bacteria and related genes in urban wastewater[END_REF]. Fernandes et al. [START_REF] Fernandes | On the performance of distinct electrochemical and solar-based advanced oxidation processes to mineralize the insecticide imidacloprid[END_REF] also recently demonstrated that natural solar radiation is efficient in activating these oxidant precursors. Kowalska et al. [START_REF] Kowalska | Removal of carbamazepine, diclofenac and trimethoprim by solar driven advanced oxidation processes in a compound triangular collector based reactor : A comparison between homogeneous and heterogeneous processes[END_REF] and Moreira et al. [START_REF] Moreira | Solar treatment (H2O2, TiO2-P25 and GO-TiO2 photocatalysis, photo-Fenton) of organic micropollutants, human pathogen indicators, antibiotic resistant bacteria and related genes in urban wastewater[END_REF] observed complete degradation of carbamazepine and diclofenac in spiked effluents under solar radiation coupled to H 2 O 2 . Finally, Rizzo et al. [START_REF] Rizzo | Antibiotic contaminated water treated by photo driven advanced oxidation processes : Ultraviolet/H2O2 vs ultraviolet/peracetic acid[END_REF] and Velo-Gala et al. [START_REF] Velo-Gala | Advanced Oxidation Processes based on the use of UVC and simulated solar radiation to remove the antibiotic tinidazole from water[END_REF] both compared the efficiency of a solar simulator to UVC radiation for the activation of H 2 O 2 in order to degrade antibiotics in small volumes (0.5 and 6 L respectively). In both studies, the lower efficiency of solar light compared to UVC radiation was concluded. However, the reported degradation rates were time-dependent and no comparison of the energy required (UV fluence) in each process was made.

Since UVA radiation constitute the majority of solar UV, it seems essential to evaluate their abilities for the activation of oxidant precursors in AOPs. . H 2 O 2 was chosen for its ease of implementation and the large number of studies identified in the literature. S 2 O 8 2-was studied for its high efficiency with the aim of assessing whether its use could balance the expected loss of efficiency when replacing UVC by UVA radiation. For technical reasons, mercury lamps were used for the production of both types of radiation, allowing UV fluence calculation and comparison. Three estrogens, namely estrone (E1), 17β-estradiol (E2) and 17α-ethinylestradiol (EE2), were first chosen as model pollutants for process efficiency assessment. According to Ilyas and van Hullebusch [START_REF] Ilyas | Performance comparison of different types of constructed wetlands for the removal of pharmaceuticals and their transformation products: a review[END_REF], they are removed from 30 to 80% in constructed wetlands, due to biodegradation, plant uptake and adsorption, leading to concentrations from ng L -1 to several µg L -1 in the released effluent. Similar degradation rates are also achieved in conventional WWTPs [START_REF] Janex-Habibi | Reduction of endocrine disruptor emissions in the environment : The benefit of wastewater treatment[END_REF][START_REF] Schilirò | The endocrine disrupting activity of surface waters and of wastewater treatment plant effluents in relation to chlorination[END_REF]. Nevertheless, their occurrence in surface waters and river sediments as well as their ecotoxicity at environmental concentrations have been widely reported [START_REF] Adeel | Environmental impact of estrogens on human, animal and plant life : A critical review[END_REF]. Finally, a mixture of ibuprofen, (IBU), naproxen (NAP) and diclofenac (DCF), three commonly detected non-steroidal antiinflammatory drugs, allowed to confirm the results on another type of micropollutants.

Materials and methods

Chemicals and reagents

Estrone (E1), 17β-estradiol (E2 Acetonitrile (ACN) was supplied by VWR Chemicals (HPLC grade). Ultrapure water was obtained from a milli-Q system. Formic acid was purchased from Chimie-plus Laboratoires.

Irradiation experiments

Description of the laboratory pilot

The experimental set-up has previously been described in the literature [START_REF] Cédat | Are UV photolysis and UV/H2O2 process efficient to treat estrogens in waters? Chemical and biological assessment at pilot scale[END_REF] and is reproduced Figure 1. It is composed of a 50-L glass tank linked to a 1.12-L UV reactor (COMAP) by a centrifugal pump. In the reactor, the UV lamp is protected by a quartz tube and the effluent flows through a 1-cm layer around the tube. Effluent recirculation allows to increase the contact time between the targets and the lamp and thus the UV fluence. Low pressure mercury lamps (Philips) were used for the generation of UVC and UVA radiation.

The UVC lamp was monochromatic while the UVA lamp was polychromatic and emits from 345 to 410 nm with a maximum at 365 nm (Figure SM1). Their technical features are presented in Table 1. The UVCalc®2A software (Bolton Photosciences Inc., Canada) was used for UV fluence calculations. On the advice of the software designer and given its narrow emission spectra, the UVA lamp was considered monochromatic. After calculation, a correction factor of 0.88 for UVC radiation [START_REF] Cédat | Are UV photolysis and UV/H2O2 process efficient to treat estrogens in waters? Chemical and biological assessment at pilot scale[END_REF] and 0.82 for UVA radiation (software designer recommendations) was applied.

Matrix composition

Main physico-chemical parameters of the matrices used to investigate the degradation of micropollutants are presented in Table 2. Drinking water collected directly to tap (Villeurbanne, France) was first used as a simple matrix. Then, WWTP effluents were collected in 30-L plastic containers at the outlet of a conventional WWTP equipped by an activated sludge treatment (Feyssine, Villeurbanne, France) with a capacity of 300,000 population equivalent. Samples were collected in the morning and used within 30 hours.

Experimental procedures

The laboratory pilot was used to determine the photolysis constants of the oxidant precursors, the photolysis first order rate constants of the estrogens and the overall pseudo-first order degradation rate constant of the estrogens or of the pharmaceuticals obtained through the experiments. Experimental procedures were quite similar and operating conditions are summarized in Table 3. The experimental set-up was filled in to 20 ± 0.5 L with the matrix.

Then, recirculation flow was set at 20 ± 0.5 L min -1 , the UV lamp was pre-heated during 10 minutes and the temperature was adjusted and stabilised at 22 ± 2 °C. After pre-heating, the lamp was turned off and the solution was spiked with 3 estrogens or 3 pharmaceuticals at .

After addition of the reagents, the solution was homogenised for 2 minutes and the lamp was turned on to start the experiment. 5 mL were withdrawn before the start and at the end of each experiment to measure the transmittance of the solution by UV-visible spectrophotometry.

During estrogen photolysis and AOP experiments, 1 mL of sample was withdrawn at fixed time intervals for micropollutant quantification by UHPLC. During H 2 O 2 or S 2 O 8 2-photolysis experiments, the volume of samples was extended to 5 mL to determine their concentrations using a UV-visible spectrophotometer.

In any case, variations between the initial and the final volume were under 0.25% during experiments.

Micropollutant quantification

Samples were filtered before analysis through 0.45 µm PVDF filters (Millex HV). Analysis were performed with an UHPLC ultimate 3000+ (Thermo Fischer) system equipped with a X-Bridge BEH column (75 × 4.6 mm × 2.5 µm) and coupled to a diode array detector. The mobile phase was a mixture of acetonitrile (ACN) and milli-Q water both acidified with 0.1% formic acid running in isocratic mode at 1.5 mL min -1 . One method was used to analyse the estrogens and another to analyse the mixture of pharmaceuticals. They are both described in Table 4. Limits of detection (LOD) were determined by calculation and limits of quantification were calculated as 3.3 × LOD. All the samples were analysed in duplicate.

Examples of typical chromatograms are available in Figure SM2. UV fluence (F, mJ cm -2 ) corresponds to the total radiant energy incident from all directions onto an infinitesimally small sphere of cross-sectional area dA, divided by dA according to Bolton and Stefan [START_REF] Bolton | Fundamental photochemical approach to the concepts of fluence (UV dose) and electrical energy efficiency in photochemical degradation reactions[END_REF]. In the studied system, the infinitesimally small sphere of crosssectional area can be considered to be the targeted micropollutants or the oxidant precursors.

UV fluence is based on the characteristics of the lamp but also on the structure of the system and on the transmittance of the effluent. Thus, it allows to compare different lamps, processes or effluents. In the present study, UV fluence was used as a reference unit for degradation rates.

Degradation rate constants

Photolysis of the estrogens and of the oxidant precursors followed first order rates that were fitted by the following equation:

, where and are respectively the initial concentration and the concentration at UV fluence F of the compound of interest (µM) and the photolysis first order rate constant (cm 2 mJ -1 ) which depends on the UV fluence received by the effluent.

In AOPs, micropollutant degradation followed pseudo-first order rates. Targets can be degraded by both photolysis and oxidation by the free radicals. In the present study, the radicals are HO Linden [START_REF] Sharpless | Experimental and Model Comparisons of Low-and Medium-Pressure Hg Lamps for the Direct and H 2 O 2 Assisted UV Photodegradation of N -Nitrosodimethylamine in Simulated Drinking Water[END_REF] :

, where is the pseudo-first order rate constant of radical-based oxidation and is the overall pseudo-first order rate constant. depends on both the steady-state concentration of the radical and on the second order reaction rate between the oxidative radical and the compound of interest [START_REF] Shu | Pilot-scale UV/H2O2 advanced oxidation process for municipal reuse water : Assessing micropollutant degradation and estrogenic impacts on goldfish (Carassius auratus L.)[END_REF]. In the present study, values were determined from UV-based AOP experiments and values were calculated as the difference between and .

The error bars associated to degradation constants equal to 3σ, derived from the scattering of the experimental data around the fit curves (intra-series variability).

Electrical energy per order

The Electrical Energy per Order ( ) is the electrical energy (kWh) necessary to reduce the concentration of a contaminant by one order of magnitude in one m 3 of effluent [START_REF] Bolton | Figures-of merit for the technical development and application of advanced oxidation processes for both electric and solar driven systems[END_REF] [START_REF] Bolton | Figures-of merit for the technical development and application of advanced oxidation processes for both electric and solar driven systems[END_REF]. It is often calculated according to the following equation [START_REF] Sindelar | Evaluating UV/H 2 O 2 , UV/percarbonate, and UV/perborate for natural organic matter reduction from alternative water sources[END_REF][START_REF] Vishnuganth | Photocatalytic degradation of carbofuran by TiO 2 -coated activated carbon: Model for kinetic, electrical energy per order and economic analysis[END_REF]:

, where is the lamp power (kW), is the time of irradiation (h), V is the volume of treated effluent (L), and are the initial and final concentrations of the target molecule (expressed in µmol L -1 in this paper). This quantity is a useful indicator for comparing photoactivated processes. It is generally considered that a photoactivated process may be economically feasible if its value is less than 10 kWh m -3 order -1 [START_REF] Andrews | UV oxidation for drinking waterfeasibility studies for addressing specific water quality issues[END_REF].

Experimental data used to calculate can be seen in Table SM1, only values are presented in the Results and discussion section.

Results and discussion

Estrogen and oxidant precursor photolysis

The molar absorption coefficient (Ɛ  ) and the quantum yield (Φ λ ) are the two parameters that account for the photolysis efficiency of a compound. The molar absorption coefficient governs the absorption of a photon by the molecule at the wavelength of interest and the photolysis quantum yield (number of photolysed molecules divided by the number of photons absorbed) depends on the photochemical change that follows photon absorption [START_REF] Hokanson | A photolysis coefficient for characterizing the response of aqueous constituents to photolysis[END_REF]. Thus, the photolysis quantum yield influences the quantum yield for the generation of photolysis byproducts. In the present paper, the modelling of degradation kinetics is not based on these two parameters, but they are used to comment qualitatively on the degradation constants calculated from experimental data. ) so that the ratio Φ 365nm (HO • )/ Φ 365nm (SO 4

•-

) can be considered greater than 1.9

for the comparison of quantum yields for the two radicals under UVA. Under UVC, the ratio Φ 254nm (HO • )/ Φ 254nm (SO 4

•-

) equals 0.8. 0.96 ± 0.04 [27] 0.5 ± 0.1 [27] UVC (254 nm) 1.15 ± 0.05 [28] 1.4 ± 0.1 [29]

Photolysis rate constants of the oxidant precursors

As seen in Figure 2, molar absorption coefficients follow the same trend in the UV range for both H 2 O 2 and S 2 O 8 2-: they are not significant between 400 and 350 nm and increase exponentially from 350 to 200 nm. According to Table 5, both oxidant precursors allow higher quantum yields for the production of free radicals under UVC than under UVA radiation. Therefore, although it was reported in the literature that UVA radiation is efficient

UVC UVA UVB

for their activation [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF][START_REF] Moreira | Tertiary treatment of a municipal wastewater toward pharmaceuticals removal by chemical and electrochemical advanced oxidation processes[END_REF], faster photolysis is expected under UVC radiation for both molecules.

At 254 nm, the molar absorption coefficient of S 2 O 8 2-is 1.4 times higher than that of H 2 O 2 and the quantum yield for the production of SO 4

•-is 1.2 times higher than that of HO • (Table 5). Therefore, faster production of SO •-is expected to be faster than that of HO • regardless of the wavelength.

Photolysis of the estrogens

According to Figure 2, E1, E2 and EE2 molar absorption coefficients are very similar at all wavelengths. They have a similar absorption band from 300 to 250 nm and molar absorption coefficients increase exponentially in a similar way from 250 to 200 nm. However, at 254 nm, Ɛ is 1.5 times higher for E1 than for E2 and EE2. Moreover, according to Huang et al. [START_REF] Huang | Photodegradation of free estrogens driven by UV light : Effects of operation mode and water matrix[END_REF],

E1 has a 3 to 4 time higher quantum yield than E2 and EE2 at 254 nm. Therefore, faster photolysis of E1 is expected compared to that of E2 and EE2 at this wavelength. At 365 nm, molar absorption coefficients are not significant for the three estrogens and to the best of our knowledge, their quantum yields at this wavelength were not reported in the literature.

Table 7 depicts the first order rate constants of E1, E2 and EE2 in the pilot (experimental data in the form of C/C 0 curves can be seen in Figure SM3 and Figure SM4 for UVA and UVC respectively). First of all, the estrogens were photolysed under UVA radiation despite very low molar absorption coefficients. Constants are of the same order of magnitude for the three estrogens, ranging from 8.4 × 10 -6 to 1.9 × 10 -5 cm 2 mJ -1 for E1 and EE2 respectively. They reflect very slow photolysis and less than 2% of the initial concentrations are degraded at 1000 mJ.cm 2 , the maximum relevant UV fluence in AOPs [START_REF] Rosenfeldt | Degradation of endocrine disrupting chemicals bisphenol A, ethinyl estradiol, and estradiol during UV photolysis and advanced oxidation processes[END_REF], corresponding to 41 min in the pilot. Then, higher photolysis rates of the three estrogens were observed under UVC radiation. E2 and EE2 photolysis are 3 to 4 times faster and that of E1 is 113 times faster. As seen previously, faster photolysis of E1 under UVC radiation was expected given its higher Ɛ 254nm and Φ 254nm values. Nevertheless, the photolysis remains slow under UVC radiation with only 3 to 4% degradation for E2 and EE2 at 1000 mJ cm 2 , whereas E1 was degraded by 62%.

If photolysis may take part in the global degradation of estrogens during AOPs, UV irradiation cannot be considered as an effective treatment, whether it is under UVA or UVC radiation. These considerations are confirmed by the values of reported in Table 7: with UVA, it takes between one hundred and four hundred kWh to reduce the concentration of each estrogen in a m 3 of drinking water by an order of magnitude, which far exceeds the energy consumption compatible with economic feasibility. With UVC, lower values are obtained, of the order of several tens for E2 and EE2, which remains higher than the threshold value of 10 kWh m -3 order -1 , even if photolysis alone could be economically viable for E1 hormone degradation.

Estrogen degradation in drinking water in various AOPs

Pseudo-first order rate constants ( ) of the estrogens in drinking water were calculated from experimental data (available as C/C 0 curves in Figure SM3 and Figure SM4 for UVA and UVC respectively) and are shown Table 8 as well as associated oxidation constants calculated as the difference between and (reported in Table 7). The contribution of oxidation to the global degradation of the targets ( ) was also calculated and is presented in Table 8, the complement to 100 corresponding to the contribution of photolysis. In the UVA/H 2 O 2 process, goes from 2.2 ± 0.2 × 10 -5 to 3.5 ± 0.3 × 10 -5 cm 2 mJ -1 with 46 to 64% of the degradation achieved by oxidation. These close results are attributed to similar photolysis constants of the estrogens (Table 7) and similar second order rate constants (from 1.8 to 2.9 × 10 10 M -1 s -1 ) between HO • and the estrogens [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF]. When using S 2 O 8

2-

, values increase by 89 ± 1% and are similar between the estrogens, ranging from 2.1 to 3.0 × 10 -4 cm 2 mJ -1 , due to close second order rate constants (from 1.8 to 4.1 × 10 9 M -1 s -1 ) between SO 4

•-and the estrogens [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF]. This increase is attributed to higher thanks to faster photolysis of S 2 O 8 2-compared to H 2 O 2 ( 1.2) (see Table 6). As a consequence, the contribution of oxidation increases, being equal to or greater than 93%.

Under UVC radiation, the degradation of the estrogens is accelerated. In the presence of H 2 O 2 , are from 27 to 77 times higher than those obtained under UVA. In addition to faster estrogen photolysis, H 2 O 2 photolysis is 3.5 times faster under UVC than under UVA (Table 7). and are similar with a contribution of oxidation reaching 95 and 94% respectively. However, is almost twice as high as and . It is observed that are of the same order of magnitude for the three estrogens, from 7.2 to 8.9 × 10 -4 cm 2 mJ -1 .

Therefore, faster degradation of E1 is attributed to its high photosensitivity under UVC radiation. Similar trends are observed with the use of S 2 O 8 2-

: are from 39 to 52 times higher under UVC radiation due to faster oxidation. For E2 and EE2, the increase in is so high that becomes negligible. Regarding E1, remains noticeable (about 10% of total degradation). However, a lower leads to similar than that of E2 and EE2. Finally, oxidation plays a major role in E2 and EE2 degradation under UVC regardless of the oxidant precursor whereas the predominant phenomenon in the degradation of E1 varies depending on the oxidant precursor.

Estrogen degradation rates at 1000 mJ cm -2 are reported in process.

The values of calculated for estrogens degradation in drinking water shown in Table 9 lead to the same conclusions. Using UVC whatever the free radical precursor seems to be economically feasible with values between 0 and 2 kWh m -3 order -1 . So it seems worthwhile to study the UVC-based AOPs with a complex matrix such as WWTP effluent, even if these conditions may be less favorable. With the UVA/S 2 O 8 2-process, values are a little bit higher, in the upper range of acceptable values. It is therefore important to determine whether the switch to real matrix leads to a significant increase in values or not. Finally, values obtained with the UVA/H 2 O 2 process are around hundred for the three estrogens in drinking water, so there is no point in going any further with this process.

Process comparison in a WWTP effluent

After the study of UV-based AOPs in a simple matrix, it is necessary to implement them in a real matrix. Real effluents may indeed contain species that absorb UV radiations, react with radical precursors and/or with free radicals, leading to poorer performance of the process. Furthermore, it has been shown that photolysis and oxidation are compound dependent. Thus, it seems interesting to assess the degradation of another kind of micropollutants. This part, dedicated to the degradation of micropollutants in spiked WWTP effluents, firstly focuses on the estrogens and then on a mixture of three pharmaceuticals.

Estrogen degradation

WWTP effluent 1 collected at the outlet of a conventional treatment plant (see Table 2 for more details) and spiked with the three estrogens was used to assess the performance of the UVA/S 2 O 8 2-, UVC/H 2 O 2 and UVC/S 2 O 8 2-processes (see Table 3 for operating conditions).

Pseudo-first order degradation rate constants of the estrogens are presented and compared to those measured in drinking water in Figure 3 (data is available in Table SM2, experimental data is available as C/C 0 curves in Figure SM5).

First of all, estrogen degradation rates in WWTP effluent follow the same behaviours as In the literature, the reactivity of H 2 O 2 and S 2 O 8 2-with the WWTP effluent components (mainly organic matter and inorganic anions) was not reported to be significant. The inhibition in a WWTP effluent is rather probably due to the scavenging of the oxidative radicals by the organic matter and inorganic anions such as Cl -, NO 3 -and HCO 3 - [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF][START_REF] Ma | Impacts of inorganic anions and natural organic matter on thermally activated persulfate oxidation of BTEX in water[END_REF][START_REF] Olmez-Hanci | S2O82-/UV-C and H2O2/UV-C treatment of Bisphenol A : Assessment of toxicity, estrogenic activity, degradation products and results in real water[END_REF].

described
Results obtained in the present study suggest that the scavenging of the radicals by the matrix components is stronger for SO 4

•-than for HO • . In both matrices under study, carbonate concentrations are similar. However, the total organic carbon of the effluent is 7.5 mg C L -1 whereas that of drinking water is not significant (< 0.5 mg C L -1 ). In addition, conductivity, chloride and nitrate concentrations are 2.3, 10 and 4.2 times higher in the WWTP effluent respectively. These differences in matrix composition could indeed induce HO • and SO 4

•-

scavenging. Wang and Wang [START_REF] Wang | Effect of inorganic anions on the performance of advanced oxidation processes for degradation of organic contaminants[END_REF] reported in a literature review that both radicals have similar second order reaction rate constants with HCO 3 -(9 × 10 6 M -1 s -1 ), that Cl -have negligible effect and that NO 3 -could have a scavenging impact, although its second order reaction rate with HO• is not reported and that with SO 4 • -is negligible ( = 2.1 M -1 s -1 ). Therefore, the significant decrease in efficiency of S 2 O 8 2-observed in the present study under both types of radiation could rather be attributed to radical scavenging by organic matter, which would be stronger for SO 4 • -than for HO•. This inhibition is governed by the competition between the micropollutants of interest and organic matter to react with the radicals. Second order rate constants between the radicals and the organic matter were not determined in the present study. However, Lutze et al. [START_REF] Lutze | Degradation of Chlorotriazine Pesticides by Sulfate Radicals and the Influence of Organic Matter[END_REF] reported higher reaction rates of natural organic matter with HO• than with SO 4 • -but they only considered humic acids whereas it was previously reported in the literature that the composition of organic matter in WWTP effluents has a large variation range which also includes fulvic acids, hydrophilic acids, bases and neutral or hydrophobic neutrals for example [START_REF] Imai | Characterization of dissolved organic matter in effluents from wastewater treatment plants[END_REF][START_REF] Ma | Characterization of isolated fractions of dissolved organic matter from natural waters and a wastewater effluent[END_REF][START_REF] Yu | Effect of effluent organic matter on the adsorption of perfluorinated compounds onto activated carbon[END_REF]. Regarding the reactivity between the estrogens and the radicals, Gabet et al. [START_REF] Gabet | Hydrogen peroxide and persulfate activation using UVA-UVB radiation : Degradation of estrogenic compounds and application in sewage treatment plant waters[END_REF] previously reported that second order rate constants are lower with SO 4 • -(from 1.8 × 10 9 to 4.1 × 10 9 M -1 s -1 ) than with HO• (from 1.8 × 10 10 to 2.9 × 10 10 M -1 s -1 ). As a consequence, SO 4 • -is more likely to be scavenged by organic matter than HO•, depending on their second order reaction rates with the organic matter involved. Unsurprisingly, the values reported in Table 9 show that the electrical energy required to reduce estrogens concentrations by one order of magnitude increases when aqueous matrix becomes more complex (from drinking water to WWTP effluent). However, UVC-based processes still exhibit values lower than 10 kWh m -3 order -1 and even lower than For the two processes that use persulfate ions as radical precursors, values increase by a factor of between 5 and 8 as a result of the matrix change, whether with UVA or UVC, whereas this factor is around 1.5 for UVC/H 2 O 2 . As seen above based on kinetics considerations, the switch to a real matrix also reduces the performance of persulfate based AOPs more than that of H 2 O 2 based ones.

Pharmaceutical degradation

WWTP effluent 2 collected at the outlet of the same conventional treatment plant (see Table 2 for more details) was spiked with a mixture of three pharmaceuticals, namely ibuprofen processes were carried out in the same conditions as previously. Pseudo-first order degradation rates of the mixture of pharmaceuticals are depicted in Figure 4 (data is available in Table SM3 and experimental data is available as C/C 0 curves in Figure SM6).

In all the processes, are significantly different between the three compounds and their ranking is similar in the three processes: Firstly, the difference in degradation rates between the three pharmaceuticals is going to be discussed. Under UVC radiation, DFC is highly photolysable: Fu et al. [START_REF] Fu | Degradation of three nonsteroidal anti-inflammatory drugs by UV/persulfate : Degradation mechanisms, efficiency in effluents disposal[END_REF] reported a high photolysis rate of DCF with 92% degradation after 600 s of exposure in their system whereas NAP and IBU were degraded by 52 and 28% respectively. Under UVA radiation, low photolysis is expected in view of the global degradation results reported in Figure 4.

< < .
However, it has not been studied, to the best of our knowledge. Regarding oxidation, second order rate constants ( ) all are of the same order of magnitude (Table 10). However, they follow the same trend as : those of DCF are equal to or higher than those of NAP which are higher than those of IBU. Therefore, the differences in pseudo-first order degradation rates between the pharmaceuticals are attributed to both their different photo-sensitivities and their second order rate constants with HO• and SO 4 • -.

Table 10. Second order reaction constants between the radicals and IBU, NAP and DCF.

IBU NAP DCF (M -1 s -1 ) 5.57 × 10 9 [41] 9.05 × 10 9 [42] 9.29 × 10 9 [43] (M -1 s -1 )

1.32 × 10 9 [41] 5.64 × 10 9 [42] 9.2 × 10 9 [44] Regarding process efficiency, faster degradation under UVC radiation is attributed to both faster pharmaceutical photolysis and radical generation. Moreover, as seen previously, better degradation in the presence of S 2 O 8 2-is attributed to the faster generation of SO . This is due to which is more than 4 times higher than .

The same trend is observed with NAP whose second order rate constant is 1.6 times higher with HO• compared to SO 4 • -. However, the competition between the different species or the faster generation of SO a given AOP, the ratios vary from 7 to 20 in the case of pharmaceuticals attesting a high degree of variability depending on the molecules, whereas they were much less dispersed, from 1.4 to 2.0, in the case of hormones which have fairly similar molecular structures. Removal efficiencies at 1000 mJ cm -2 in the three processes are depicted in Table SM2 for estrogens and in Table SM3 for the pharmaceuticals.

The UVA/S 2 O 8 2-process only allowed weak degradation of the model micropollutants. The estrogens were not degraded by more than 6% and the pharmaceuticals by 17%. On the other hand, UVC radiation allowed satisfactory or good removal efficiencies at 1000 mJ cm -2 , depending on the model micropollutant and the oxidant precursor. In the presence of H 2 O 2 , the estrogens were degraded from 43 to 71% and IBU, NAP and DCF were degraded by 66, 75 and 100% respectively. In the presence of S 2 O 8 2-, the three estrogens underwent better degradation with removal efficiencies reaching 90 ± 1%. NAP also underwent better degradation and was almost completely degraded (99%) and DCF was still completely removed, whereas IBU was only degraded by 58%, which is slightly poorer than the degradation performances allowed by the UVC/H 2 O 2 process, due to a lower , as discussed in section 3.3.2. As a consequence, the better performances of the UVC/S 2 O 8 2-are clear for the estrogens and NAP. However, both UVC processes are comparable for the degradation of DCF which is mainly photodegraded and IBU reaches slightly higher degradation in the presence of H 2 O 2 , depicting the importance of the nature of the target in the process efficiency assessment.

In Switzerland, where a regulation regarding the removal of micropollutants in WWTPs is applicable, it imposes 80% removal on a selection of micropollutants over the complete treatment process. In the present study, the UVC/S 2 O 8 2-process provides alone such degradation for 5 of the 6 studied compounds and although the UVC/H 2 O 2 process does not allow such performances, it could significantly increase the overall micropollutant removal in a WWTP when used as a tertiary treatment.

Conclusion

The The is a useful tool to compare AOPs, and especially to compare UVA-and UVCprocesses. Nevertheless, it should be completed by another parameter that would enable a fair comparison of radical precursors to be integrated in a technico-economical indicator. For example, the price of a reagent is not the only parameter that induces cost, its implementation has also to be taken into account. However, in view of the experiences carried out in the present study, a more detailed technical and economic approach seems premature.

Finally, if the use of mercury-based UVA lamps is ruled out by the results of the present study, there are other UVA radiation sources that could allow for the implementation of less energy consuming processes and for the consideration of UV fluences greater than 1000 mJ cm -2 (defined for UVC mercury-based lamps). UVA-light emitting diodes (LEDs) are one of them. LEDs have been an emerging light source over the past years and they are known for their high energy efficiency, robustness, clean composition and potential for long lifetimes [START_REF] Autin | Evaluation of a UV-light emitting diodes unit for the removal of micropollutants in water for low energy advanced oxidation processes[END_REF]. UVA-LEDs are particularly interesting because they can be up to 15 times more energy efficient than UVA mercury lamps [START_REF] Rodríguez-Chueca | Photocatalytic discolouration of Reactive Black 5 by UV-A LEDs and solar radiation[END_REF], on the contrary to UVC-LEDs which have low energy efficiency [START_REF] Matafonova | Recent advances in application of UV lightemitting diodes for degrading organic pollutants in water through advanced oxidation processes : A review[END_REF]. Another solution for UVA-based processes are solar-driven systems that would allow considering greater energy requirements to reach complete degradation of the targets because solar light is a free and clean energy. However, their major drawback remains process implementation: despite the availability of solar light concentrator, designing a system able to provide appropriate UV fluence for the degradation of micropollutants with solar radiation remains nowadays challenging.

Declaration of Competing Interest

All authors declare no conflict of interest. 2).

Figure SM5. AOPs for estrogens degradation in WWTP effluent.

Initial concentration of estrogens: 5 µM each; initial concentration of radical precursor (hydrogen peroxide (H2O2) or persulphate ions (PS)): 1 mM; aqueous matrix is WWTP effluent 1 (Table 2).

Figure 1 .

 1 Figure 1. Schematic diagram of the pilot used, reproduced from Cédat et al., 2016. 1) Glass tank; 2) pump; 3) flow meter; 4) and 6) sampling points; 5) UV reactor; 7) UV intensity control; 8) temperature control.

Figure 2 .

 2 Figure 2. Molar absorption coefficients (Ɛ) of E1, E2 and EE2 and of H 2 O 2 and S 2 O 8 2-in the UV range at circumneutral pH.

Figure 3 .

 3 Figure 3. Pseudo-first order degradation rate constants of E1, E2 and EE2 (5 µM) in a WWTP effluent compared to those in drinking water, H 2 O 2 or S 2 O 8 2-= 1 mM.

(

  IBU), naproxen (NAP) and diclofenac (DCF). The UVA/S 2

Figure SM1 .

 SM1 Figure SM1. UVA lamp emission spectrum (Philips).

Figure SM2 .

 SM2 Figure SM2.Examples of typical chromatogram for a) estrogens and b) pharmaceuticals..

Figure

  Figure SM3. UVA-based processes for estrogens degradation in drinking water.

Figure SM4 .

 SM4 Figure SM4. UVC-based processes for estrogens degradation in drinking water.

Figure SM6 .

 SM6 Figure SM6. AOPs for pharmaceuticals degradation in WWTP effluent.

  To the best of our knowledge, no previous study has compared UVA to UVC radiation for the photo-activation of H 2 O 2 and

	S 2 O 8 2-.
	In the present work, an intermediate-scale laboratory pilot (maximum capacity of 50 L) was
	used to compare UVA to UVC radiation for the activation of H 2 O 2 or S 2 O 8 2-

Table

Table 2 .

 2 Main physico-chemical parameters of drinking water and WWTP effluents.

	Drinking water	WWTP effluent 1	WWTP effluent 2

Table 3 .

 3 Operating conditions in the pilot.

		Photolysis experiments	UV-based AOP experiments
		Oxidant precursors	Estrogens	Estrogens	Pharmaceuticals
	Total volume			20 ± 0.5 L
	Recirculation flow rate			20 ± 0.5 L min -1
	Solution	Drinking water Drinking water	Drinking water or WWTP1	WWTP2
	Micropollutants	None	E1 + E2 + EE2 5 µM each	E1 + E2 + EE2 5 µM each	IBU + NAP + DCF 5 µM each
	Oxidant precursor	H 2 O 2 or S 2 O 8 5 mM	2-	None	H 2 O 2 or S 2 O 8 2-1 mM	2-H 2 O 2 or S 2 O 8 1 mM
	Methanol	0.5% V/V		None	None	None
	2.3. Sample analysis
	2.3.1. UV-visible spectrophotometry
	A Shimadzu 2450 UV-visible spectrophotometer was used to:
	-measure transmittances at 254 nm and 365 nm (required for UV fluence calculation),
	-acquire the UV-visible spectra of the micropollutants and of the oxidant precursors,
	-quantify H 2 O 2 and S 2 O 8 2-during photolysis constant determination, using
	measurements carried out at 240 nm (Ɛ 240nm = 38.1 L mol -1 cm -1 ) and 230 nm (Ɛ 230nm = 38.6 L
	mol -1 cm -1 ) for H 2 O 2 and S 2 O 8 2-respectively.

Table 4 .

 4 UHPLC method parameters for micropollutant quantification.

	UHPLC method	Estrogen method Pharmaceutical method
	Pollutant	E1	E2 EE2 IBU	NAP	DCF
	Mobile phase ACN/H 2 O		50/50		60/40
	Injection volume (µL)		40		20
	Column temperature (°C)		40		40
	Detection wavelength (nm)		280	226	226	281
	Retention times (min)	1.91 1.44 1.71 2.02	1.17	1.76
	Limit of detection (µM)	0.28 0.25 0.26 0.12	0.10	0.09
	2.4. Data processing
	2.4.1. UV fluence

  , generated by the homolytic cleavage of H 2 O 2 or S 2 O 8 2-respectively (each of them generates two identical radicals). The two modes of degradation can be distinguished in the following pseudo-first order rate equation, as proposed by Sharpless et

• or SO 4

•-

Table 5

 5

				Ɛ (M -1 cm -1 )		Φ (mol ein -1 )
		H 2 O 2 S 2 O 8	2-	E1	E2	EE2	HO •	SO 4 •-
	UVA	< 0.3 < 0.5	< 10	< 10	< 10	UVA
	(365 nm)						(351 nm)

. Molar absorption coefficients (Ɛ) of estrogens and oxidant precursors and quantum yields for radical production (Φ) from the photolysis of oxidant precursors under UVC and UVA.

Table 6

 6

	4	•-is expected. At 365 nm, a higher quantum yield for

. As expected, they are higher under UVC than under UVA radiation (3.5 and 8.8 times for H 2 O 2 and S 2 O 8 2-respectively), causing faster generation of the subsequent free radicals under UVC radiation. The photolysis of S 2 O 8 2-is about 1.2 and 3.4 times faster than that of H 2 O 2 , under UVA and UVC radiation respectively. Therefore, the generation of SO

  [START_REF]Portail assainissement collectif[END_REF]

Table 6

 6

		. Photolysis first order rate constants (	of H 2 O 2 and S 2 O 8 2-in the system.
			(cm 2 mJ -1 )
		H 2 O 2	S 2 O 8 2-
	UVA	4.36 ± 0.30 × 10 -5	5.25 ± 0.51 × 10 -5
	UVC	1.54 ± 0.02 × 10 -4	4.61 ± 0.26 × 10 -4

Table 7

 7

		. Photolysis of E1, E2 and EE2 in the system:	and	values.
			E1		E2	EE2
		UVA	8.4 ± 3.0 × 10 -6	1.2 ± 0.2 × 10 -5	1.9 ± 0.1 × 10 -5
	(cm 2 mJ -1 )	UVC	9.6 ± 0.5 × 10 -4	4.8 ± 0.3 × 10 -5	6.4 ± 0.2 × 10 -5
		UVA	424.8		223.5	145.9
	(kWh m -3 order -1 )	UVC	2.1		47.1	31.8

Table 8 .

 8 Pseudo-first order degradation constants ( ) of E1, E2 and EE2 in the different processes with the associated oxidation constants ( ) and their degradation rates at 1000 mj.cm -2 .

	Radiation type	Oxidant precursor	Estrogen	Rate constants (cm 2 mJ -1 )		Degradation at 1000 mJ cm -2 (%)
				E1	2.2 × 10 -5	1.4 × 10 -5	64	2.2
		H 2 O 2	E2	3.3 × 10 -5	2.0 × 10 -5	61	3.2
	UVA			EE2 E1	3.5 × 10 -5 2.1 × 10 -4	1.6 × 10 -5 2.1 × 10 -4	46 100	3.4 19
		S 2 O 8	2-	E2	2.8 × 10 -4	2.7 × 10 -4	96	24
				EE2	3.0 × 10 -4	2.8 × 10 -4	93	26
				E1	1.7 × 10 -3	7.2 × 10 -4	42	81
		H 2 O 2	E2	9.4 × 10 -4	8.9 × 10 -4	95	61
	UVC			EE2 E1	9.5 × 10 -4 1.1 × 10 -2	8.9 × 10 -4 1.0 × 10 -2	94 91	61 100
		S 2 O 8	2-	E2	1.1 × 10 -2	1.1 × 10 -2	100	100
				EE2	1.1 × 10 -2	1.1 × 10 -2	100	100

Table 8

 8

	. With UVC/S 2 O 8 2-
	2 O 8	2-

, the three estrogens are fully degraded. On the other hand, the UVA/H 2 O 2 process provides less than 4% degradation at 1000 mJ cm -2 and does not seem viable. As a consequence, it was not studied in the following parts of the work. Contrasted results are observed with UVA/S

Table 9 .

 9 Values of for estrogens degradation by photooxidation in different matrices.

	Radiation type	Oxidant precursor	Estrogen	(kWh m -3 order -1 ) Drinking WWTP	Ratio
				water	effluent
			E1	126.6	-	-
		H 2 O 2	E2	81.3	-	-
	UVA		EE2 E1	84.4 10.3	-59.8	-5.8
		S 2 O 8 2-	E2	7.6	55.1	7.2
			EE2	7.3	49.4	6.7
			E1	1.3	2.1	1.6
		H 2 O 2	E2	2.2	3.5	1.6
	UVC		EE2 E1	2.1 0.2	3.2 0.9	1.5 5.0
		S 2 O 8 2-	E2	0.1	0.9	7.7
			EE2	0.1	0.9	7.1

  [START_REF]Portail assainissement collectif[END_REF]

  [START_REF]Portail assainissement collectif[END_REF]

  • -allows NAP to be degraded faster in the UVC/S 2 O 8 2-process compared to UVC/H 2 O 2 .

	Figure 4. Pseudo-first order degradation rate constants of IBU, NAP and DCF (5 µM) in a WWTP effluent, H 2 O 2 or S 2 O 8 2-= 1 mM.
	calculated for the degradation of pharmaceuticals are shown in Table 11. As already seen
	with estrogens, UVC-based AOPs exhibit more favorable values of	(lower than 10 kWh
	m -3 order -) than UVA-based one. With persulphate ions as radical precursor and irrespective
	of UV radiation energy, the	of IBU is significantly higher than that of NAP and DCF,
	which are of the same order of magnitude.	obtained from UVC/H 2 O 2 experiments are less
	contrasted. It is worth noticing that when comparing the highest and the lowest	values for

Table 11 .

 11 Values of for pharmaceuticals degradation by photooxidation in WWTP effluent 2.

	10
		8
	x10	6
	-1 )
	mJ
	k' (cm²	4
		2
		0
		IBU	NAP	DCF	IBU	NAP	DCF	IBU	NAP	DCF
		UVA -persulfate	UVC -hydrogen peroxide	UVC -persulfate

  following main conclusions can be drawn from this study about the feasibility of replacing UVC by UVA in AOPs to degrade micropollutant. Firstly, experiments carried out in drinking water as a simplified matrix with a mixture of estrogens showed that UVA is less efficient than UVC in photolyzing both the radical precursors (H 2 O 2 or S 2 O 8

	Since the efficiency of a radical precursor is both compound-and matrix-dependent, further
	experiments on a larger panel of micropollutants would be required in order to confirm S 2 O 8 2-
	better efficiency.
			2-) and targeted
	compounds, which results in lower degradation rates as well as poorer performance at a given
	UV fluence. Based on	calculations, UVA/H 2 O 2 seems not economically feasible unlike
	other AOPs.
	Experiments carried out with estrogens-or pharmaceuticals-spiked WWTP effluents showed
	that in the presence of a complex matrix, the UVA/S 2 O 8 2-process is no longer feasible with
	values of	higher than threshold value. For all AOPs, performance decreases drastically in
	WWTP matrix, but the UVC-based processes remain economically feasible with satisfactory
	micropollutant degradation. Persulphate ions still provide better degradation performances
	than H 2 O 2 , even though inhibition due to matrix change, expressed as a % relative to drinking
	water, is stronger, showing a higher scavenging effect of SO 4 • -than of HO• by organic matter.

Supplementary Materials Pilot-scale assessment of the viability of UVA radiation for H 2 O 2 or S 2 O 8 2- activation in advanced oxidation processes

  Anaëlle Gabet1,2 , Christine de Brauer 1 , Gilles Mailhot 2 , Marcello Brigante 2 , Hélène Métivier 1 1 Univ Lyon, INSA Lyon, DEEP, EA7429, 69621 Villeurbanne, France 2 Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut de Chimie de Clermont-Ferrand, F-63000 Clermont-Ferrand, France

*corresponding author: helene.metivier@insa-lyon.fr

Table 2 )

 2 Table SM1. Estimates of for micropollutant reduction by photolysis or different AOPs.

	Matrix	Radiation type	Oxidant precursor	Time (min)	Target molecule	(µM)	(µM)	(kWh m -3 order -1 )
					Estrogens
					E1	4.09	3.82	424.8
		UVA	None	420	E2	4.60	4.04	223.5
					EE2	4.38	3.59	145.9
					E1	4.21	0.05	2.1
		UVC	None	90	E2	4.29	3.52	47.1
					EE2	4.49	3.35	31.8
	water Drinking	UVA	H 2 O 2 S 2 O 8 2-	420 240	E1 E2 EE2 E1 E2 EE2	4.20 4.50 4.57 4.32 4.51 4.61	3.34 3.15 3.24 0.87 0.51 0.48	126.6 81.3 84.4 10.3 7.6 7.3
					E1	4.72	0.44	1.3
			H 2 O 2	30	E2	4.86	1.17	2.2
		UVC			EE2 E1	4.75 3.99	1.09 0.25	2.1 0.2
			S 2 O 8 2-	5	E2	4.26	0.06	0.1
					EE2	5.35	0.09	0.1
					E1	4.38	2.89	59.8
	effluent 1	UVA	2 H 2 O 2 S 2 O 8	360 60	E2 EE2 E1 E2	4.38 4.78 4.75 4.85	2.79 2.89 0.23 0.81	55.1 49.4 2.1 3.5
	WWTP	UVC	S 2 O 8 2-	7	EE2 E1 E2	5.07 4.1 4.34	0.71 1.89 1.99	3.2 0.9 0.9
					EE2	4.78	2.14	0.9
				Pharmaceuticals
					IBU	5.42	4.79	203.1
	effluent 2	UVA	2-S 2 O 8 H 2 O 2	360 15	NAP DCF IBU NAP	4.71 4.34 5.70 5.38	1.62 0.87 2.67 2.18	23.3 15.5 2.1 1.7
	WWTP	UVC	S 2 O 8 2-	5	DCF IBU NAP	4.70 5.15 4.03	0.03 4.53 1.38	0.3 4.0 0.5
					DCF	4.03	0.46	0.2

Table SM2 .

 SM2 Pseudo-first order degradation constants of E1, E2 and EE2 in the different processes with two different matrices and the degradation rates at 1000 mJ cm -2 in WWTP effluent 1.

				Drinking water		WWTP effluent 1
	Radiation type	Oxidant precursor	Estrogen	Rate constants k' (cm 2 mJ -1 )	Degradation at 1000 mJ cm -2 (%)
			E1	2.1 × 10 -4	5.2 × 10 -5	5
	UVA	S 2 O 8 2-	E2	2.8 × 10 -4	5.5 × 10 -5	5
			EE2	3.0 × 10 -4	6.3 × 10 -5	6
			E1	1.7 × 10 -3	1.2 × 10 -3	71
		H 2 O 2	E2	9.4 × 10 -4	6.6 × 10 -4	48
	UVC		EE2 E1	9.5 × 10 -4 1.1 × 10 -2	8.4 × 10 -4 2.3 × 10 -3	43 90
		S 2 O 8 2-	E2	1.1 × 10 -2	2.3 × 10 -3	90
			EE2	1.1 × 10 -2	2.4 × 10 -3	91

Table SM3 .

 SM3 Pseudo-first order degradation constants of IBU, NAP and DCF in the different processes with WWTP effluent 2 as a matrix and the degradation rates at 1000 mJ cm -2 .

	Radiation type	Oxidant precursor	Pharmaceuticals	Rate constants k' (cm 2 mJ -1 )	Degradation at 1000 mJ cm -2 (%)
				IBU	1.7 × 10 -5	2
	UVA	S 2 O 8	2-	NAP	1.3 × 10 -4	13
				DCF	1.8 × 10 -4	17
				IBU	1.1 × 10 -3	66
		H 2 O 2	NAP	1.4 × 10 -3	75
	UVC			DCF IBU	7.7 × 10 -3 8.7 × 10 -4	100 58
		S 2 O 8	2-	NAP	5.1 × 10 -3	99
				DCF	1.0 × 10 -2	100

Acknowledgements

The authors wish to acknowledge the financial support of the "Région Auvergne-Rhône-Alpes" for their financial support through the "Pack Ambition Recherche". This work was performed within the framework of the EUR H2O'Lyon (ANR-17-EURE-0018) of Université de Lyon (UdL), within the program "Investissements d'Avenir" operated by the French National Research Agency (ANR). This work was also supported by the "Federation des Recherches en Environnement" through the CPER "Environnement" founded by the "Région Auvergne," the French government and FEDER from European community.