Combination of multivariate data analysis and mixing modelling to assess tracer potential of contaminants of emerging concern in aquifers.

Collected evidence has shown that contaminants of emerging concern (CECs) in conjunction with more conventional tracers (major ions, nutrients, isotopes etc.) can be used to trace pollution origin in aquatic systems. However, in highly mixed aquifer systems signals obtained from conventional tracers overlap diminishing their potential to be used as tracers. In this study, we present an approach that incorporates multivariate statistical analysis (principal component analysis (PCA) and Kohonen's Self-Organizing Map method (SOM)) and mixing modelling to identify the most suitable CECs to be employed as anthropogenic tracers. The study area is located in the Besòs River Delta (Barcelona, NE Spain) and represents the highly mixed aquifer system. A one-year monthly based monitoring campaign was performed to collect the information about the concentrations of 105 CECs as well as major and minor ions in the river and along the groundwater flow. The dimensionality of the obtained dataset was reduced to 25 CECs, based on their estimated health risk effects, for multivariate data analysis. The obtained results showed the overlap of conventional tracers' signals obtained from PCA. In case of CECs, PCA revealed differences in their distributions allowing the differentiation of the roles of natural attenuation processes, local and regional flows on their occurrence in different parts of the aquifer. This was not possible to do using solely CECs' distribution profiles. SOMs provided the lacking information about the modality of the distribution of each CECs, revealing their ability to represent factors controlling the groundwater hydrochemistry, which assist in defining their tracer potential. Based on the obtained results four identified persistent CECs, two with unimodal (lamotrigine and 5-Desamino-5-oxo-lamotrigine) and two with bimodal (carbamazepine and diazepam (higher modality was not revealed)) distributions, were selected to run a mixing model to compare their tracer performance.

Shotgun proteomics to characterize wastewater proteins.

Classically, the characterization of wastewater components has been restricted to the measurement of indirect parameters (chemical and biological oxygen demand, total nitrogen) and small molecules of interest in epidemiology or for environmental control. Despite the fact that metaproteomics has provided important knowledge about the microbial communities in these waters, practically nothing is known about other non-microbial proteins transported in the wastewater. The method described here has allowed us to perform a large-scale characterization of the wastewater proteome. Wastewater protein profiles have shown to be very different in different collection sites probably reflecting their human population and industrial activities. We believe that wastewater proteomics is opening the doors to the discovery of new environmental and health biomarkers and the development of new, more effective monitoring devices for issues like monitorization of population health, pest control, or control of industry discharges. The method developed is relatively simple and combines procedures for the separation of the soluble and particulate fractions of wastewater and their concentration, and conventional shotgun proteomics using high-resolution mass spectrometry for protein identification. •Unprecedented method for wastewater proteome characterization.•Proteins as new potential biomarkers for sewage chemical-information mining, wastewater epidemiology and environmental monitoring.•Wastewater protein profiles reflect human and industrial activities.

SigSel: A MATLAB package for the pre and post-treatment of high-resolution mass spectrometry signals using the ROIMCR methodology.

The Regions of Interest Multivariate curve Resolution (ROIMCR) methodology has gained significance for analyzing mass spectrometry data. The new SigSel package improves the ROIMCR methodology by providing a filtering step to reduce computational costs and to identify chemical compounds giving low-intensity signals. SigSel allows the visualization and assessment of ROIMCR results and filters out components resolved as interferences and background noise. This improves the analysis of complex mixtures and facilitates the identification of chemical compounds for statistical or chemometrics analysis. SigSel has been tested using metabolomics samples of mussels exposed to the sulfamethoxazole antibiotic. It begins by analyzing the data according to their charge state, eliminating signals considered background noise, and reducing the size of the datasets. In the ROIMCR analysis, the resolution of 30 ROIMCR components was achieved. After evaluating these components, 24 were ultimately selected explaining 99.05% of the total data variance. From ROIMCR results, chemical annotation is performed using different methods: •Generating a list of signals and reanalyzing them in a data-dependent analysis.•Comparing the ROIMCR resolved mass spectra to those stored in online repositories.•Searching MS signals of chemical compounds in the ROIMCR resolved spectra profiles.

Sewage Protein Information Mining: Discovery of Large Biomolecules as Biomarkers of Population and Industrial Activities.

Wastewater-based epidemiology has been revealed as a powerful approach for surveying the health and lifestyle of a population. In this context, proteins have been proposed as potential biomarkers that complement the information provided by currently available methods. However, little is known about the range of molecular species and dynamics of proteins in wastewater and the information hidden in these protein profiles is still to be uncovered. In this study, we investigated the protein composition of wastewater from 10 municipalities in Catalonia with diverse populations and industrial activities at three different times of the year. The soluble fraction of this material was analyzed using liquid chromatography high-resolution tandem mass spectrometry using a shotgun proteomics approach. The complete proteomic profile, distribution among different organisms, and semiquantitative analysis of the main constituents are described. Excreta (urine and feces) from humans, and blood and other residues from livestock were identified as the two main protein sources. Our findings provide new insights into the characterization of wastewater proteomics that allow for the proposal of specific bioindicators for wastewater-based environmental monitoring. This includes human and animal population monitoring, most notably for rodent pest control (immunoglobulins (Igs) and amylases) and livestock processing industry monitoring (albumins).

Occurrence, data-based modelling, and risk assessment of emerging contaminants in an alluvial aquifer polluted by river recharge.

This research presents the occurrence and fate of 121 contaminants of emerging concern (CECs) in an urban aquifer polluted by river recharge through a data-base modelling. Afterwards, risk quotients (RQs) are computed to determine the risk posed by CECs to human health. To this end, groundwater and river water samples were collected in four campaigns conducted from February to May 2021. Results show that 46 CECs are ubiquitous in groundwater and their concentrations vary several orders of magnitude, ranging from below the limit of quantification to 44.5·103 ng/L for iopamidol. Transformation products (TPs) are usually detected at lower concentrations than those of the parent substances but there are some exceptions (i.e., fipronil sulphide, fipronil sulfone and O-desmethylvenlafaxine). River concentrations are higher than those detected in groundwater for some CECs, indicating the occurrence of natural attenuation processes when river water infiltrates the aquifer. A data-based advection-reaction modelling is proposed and tested for ca. 40 substances with detection frequencies higher than 90%. It provides useful quantitative information regarding the dynamic behaviour of the variables monitored, expressed in terms of characteristic length, entropy and synchronized state contribution. Finally, risk quotients (RQs) are used to assess the human health risk posed by the ubiquitous CECs in groundwater. Most CECs do not pose any risk to the different life stages considered, as the RQs evaluated are lower than 0.01. However, the pharmaceuticals valsartan and its TP valsartan acid show RQs higher than 1, indicating that these substances might be harmful to human beings.

Effects of sulfamethoxazole exposure on mussels (Mytilus galloprovincialis) metabolome using retrospective non-target high-resolution mass spectrometry and chemometric tools.

In this work, the Regions of Interest-Multivariate Curve Resolution (ROIMCR) method is proposed for the analysis of non-target metabolomics data. Samples from marine mussels (Mytilus galloprovincialis) exposed to a sublethal concentration (10 µg/L) of sulfamethoxazole (SMX) during 4 days in different seasonal conditions (summer and winter) were analyzed by High-Performance Liquid Chromatography - High-Resolution Mass Spectrometry (HPLC-HRMS) to study the effect of their exposure to SMX and the different seasonal conditions. The Regions of Interest (ROI) procedure has been applied for data filtering, compression, preprocessing and storage steps. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) is then applied to the previously MS ROI preprocessed data sets to resolve the elution profiles and spectral fingerprints of the chemical constituents of the analyzed samples. The peak areas of the elution profiles of the chemical constituents resolved by the combined ROIMCR procedure were analyzed by Principal Component Analysis (PCA) and samples were clustered according to their experimental seasonal and SMX exposure. The effects of the two investigated factors and of their interaction on the concentrations of the metabolites were statistically assessed by ANOVA simultaneous component analysis (ASCA). Both types of analyses, PCA clustering and ASCA, confirmed that the seasonal conditions (summer versus winter) produced larger effects than those produced by the exposure to SMX and by the interaction of these two factors. The concentration changes of 16 identified endogenous metabolites were validated individually using a Wilcoxon statistical test, which confirmed the presence of significant disturbances in the levels of some of these metabolites (free fatty acids, amino acids and nucleic acids), and indicated the possible alteration of six different biological pathways, affected by the investigated seasonal and SMX exposure factors.

An advection-reaction model of emerging contaminants in ground and surface waterbodies with known topology: a data-based approach.

A simple data-based advection-reaction (reactive transport) model applicable to both rivers and aquifers monitoring networks is proposed. It is built on (a) available monitoring data, and (b) graph-theoretical concepts, specifically making use of the Laplacian matrix to capture the network topology and the advection process. The method yields useful information regarding the dynamic spatial behavior of the variables monitored, expressed in terms of quantitative parameters like characteristic length, entropy, first-order decay constants, synchronization between sites, and the external inputs/outputs to the system. The model was tested in an unconfined shallow aquifer located in the lower Besòs River (Spain), in which 37 pharmaceutical compounds were monitored at 7 sites, alongside two campaigns (February and May 2021). Characteristic lengths were, on average, of the same order (24.5 m) as the mean distance between consecutive monitoring sites (33.6 m), thus reflecting an adequate monitoring network design. From an estimated mean advection velocity (0.24 m·h-1), first-order decay constants were calculated for each compound and campaign, with mean values of 0.025 h-1 (February) and 0.005 h-1 (May). Whereas entropy was generally slightly larger values in February than in May (mean values of 1.02 and 0.9 entropy units respectively), synchronization showed the opposite trend (mean values of 62.4% and 68.8% respectively). The input/output profiles were generally site-dependent, regardless of the compound, and campaign considered. • A new advection-reaction modeling approach directly based on experimental data obtained from monitoring campaigns together with the network topology is proposed. • The method yields new quantitative information regarding the dynamic behavior of the variables monitored, useful for both research and management purposes.

Contaminants of Emerging Concern (CECs): Occurrence and Fate in Aquatic Ecosystems.

Contaminants of emerging concern (CECs) are typically divided into chemicals, as they are properly called, and biological CECs, such as pathogens [...].

Retrospective mass spectrometric analysis of wastewater-fed mesocosms to assess the degradation of drugs and their human metabolites.

Temporary rivers become dependent on wastewater effluent for base flows, which severely impacts river ecosystems through exposure to elevated levels of nutrients, dissolved organic matter, and organic micropollutants. However, biodegradation processes occurring in these rivers can be enhanced by wastewater bacteria/biofilms. Here, we evaluated the attenuation of pharmaceuticals and their human metabolites performing retrospective analysis of 120 compounds (drugs, their metabolites and transformation products) in mesocosm channels loaded with wastewater effluents twice a week for a period of 31 days. Eighteen human metabolites and seven biotransformation products were identified with high level of confidence. Compounds were classified into five categories. Type-A: recalcitrant drugs and metabolites (diclofenac, carbamazepine and venlafaxine); Type-B: degradable drugs forming transformation products (TPs) (atenolol, sitagliptin, and valsartan); Type-C: drugs for which no known human metabolites or TPs were detected (atorvastatin, azithromycin, citalopram, clarithromycin, diltiazem, eprosartan, fluconazole, ketoprofen, lamotrigine, lormetazepam, metformin, telmisartan, and trimethoprim); Type-D: recalcitrant drug metabolites (4-hydroxy omeprazole sulfide, erythro/threo-hydrobupropion, and zolpidem carboxylic acid); Type-E: unstable metabolites whose parent drug was not detectable (norcocaine, benzolylecgonine, and erythromycin A enol ether). Noteworthy was the valsartan acid formation from valsartan with transient formation of TP-336.

Investigative monitoring of pesticide and nitrogen pollution sources in a complex multi-stressed catchment: The lower Llobregat River basin case study (Barcelona, Spain).

The management of the anthropogenic water cycle must ensure the preservation of the quality and quantity of water resources and their careful allocation to the different uses. Protection of water resources requires the control of pollution sources that may deteriorate them. This is a challenging task in multi-stressed catchments. This work presents an approach that combines pesticide occurrence patterns and stable isotope analyses of nitrogen (δ15N-NO3-, δ15N-NH4+), oxygen (δ18O-NO3-), and boron (δ11B) to discriminate the origin of pesticides and nitrogen-pollution to tackle this challenge. The approach has been applied to a Mediterranean sub-catchment subject to a variety of natural and anthropogenic pressures. Combining the results from both analytical approaches in selected locations of the basin, the urban/industrial activity was identified as the main pressure on the quality of the surface water resources, and to a large extent also on the groundwater resources, although agriculture may play also an important role, mainly in terms of nitrate and ammonium pollution. Total pesticide concentrations in surface waters were one order of magnitude higher than in groundwaters and believed to originate mainly from soil and/or sediments desorption processes and urban and industrial use, as they were mainly associated with treated wastewaters. These findings were supported by the stable isotope results that pointed to an organic origin of nitrate in surface waters and most groundwater samples. Ammonium pollution observed in some aquifer locations is probably generated by nitrate reduction. Overall, no significant attenuation processes could be inferred for nitrate pollution. The approach presented here exemplifies the investigative monitoring envisioned in the Water Framework Directive.

Priority and emerging organic microcontaminants in three Mediterranean river basins: Occurrence, spatial distribution, and identification of river basin specific pollutants.

There is a worldwide growing use of chemicals by our developed, industrialized, and technological society. More than 100,000 chemical substances are thus commonly used both by industry and households. Depending on the amount produced, physical-chemical properties, and mode of use, many of them may reach the environment and, notably, the aquatic receiving systems. This may result in undesirable and harmful side-effects on both the human and the ecosystem's health. Mediterranean rivers are largely different from Northern and Central European rivers in terms of hydrological regime, climate conditions (e.g. air temperature, solar irradiation, precipitation), and socio-economics (e.g. land use, tourism, crop types, etc.), with all these factors leading to differences in the relative importance of the environmental stressors, in the classes and levels of the pollutants found and their environmental fate. Furthermore, water scarcity might be critical in affecting water pollution because of the lowered dilution capacity of chemicals. This work provides raw chemical data from different families of microcontaminants identified in three selected Mediterranean rivers (the Sava, Evrotas, and Adige) collected during two sampling campaigns conducted in 2014 and 2015 in three different matrices, namely, water, sediments, and biota (fish). More than 200 organic micropollutants were analyzed, including relevant groups like pharmaceuticals, personal care products, perfluorinated compounds, pesticides, pyrethroid insecticides, flame retardants, and persistent organic pollutants. Data obtained were summarized with some basic statistics for all compound families and matrices analyzed. Observed occurrence and spatial patterns were interpreted both in terms of compound physical-chemical properties and local environmental pressures. Finally, their spatial distribution was examined and their ecotoxicological risk in the water phase was assessed. This allowed locating, at each basin, the most polluted sites ("hot spots") and identifying the respective river basin specific pollutants (RBSPs), prioritizing them in terms of the potential ecotoxicological risk posed to the aquatic ecosystems.

Occurrence of regulated pollutants in populated Mediterranean basins: Ecotoxicological risk and effects on biological quality.

Chemical stressors co-occur in mixtures into watercourses and this complicates predicting their effects on their ecological status. Our knowledge of river basin specific pollutants (RBSPs) is still limited, but it remains necessary to ensure the good chemical and ecological status. We performed an exercise on Mediterranean river sites exposed to urban and industrial pressures in order to, i) prioritize the occurring chemicals, ii) assessing the site's specific chemical risk (RQsite), and iii) relating the chemical risk to the biological quality, using as evidences invertebrates and diatom indices. Mediterranean rivers suffer from strong pressures which lead to a poor dilution ability, which makes the inhabiting biota highly vulnerable. The most frequent pollutants in the 89 sites surveyed included pharmaceutical products such as the antibiotics azithromycin, clarithromycin, and erythromycin, and the anti-inflammatory diclofenac, and products of industrial origin such as perfluorinated PFOS, nickel, and nonylphenol. Both the diatom index IPS and the macroinvertebrate index IBMWP hold strong negative correlations to RQsite, indicating a significant contribution of chemicals to biological impairment. Chemical contaminants (but not nutrients or dissolved organic carbon) were associated with significant changes to the taxonomic composition of invertebrate communities, but not to that of diatom communities. Our analyses indeed reveal that the impact of co-occurring chemicals translates onto negative effects in the biological quality. Our approach may be of use to evidence impacts on water resources and water quality in rivers under strong human pressure.

Quantification of ecological complexity and resilience from multivariate biological metrics datasets using singular value decomposition entropy.

The concept of resilience has become popular in many disciplines far beyond its original use in the field of ecology. Despite of its wide use, it has received different definitions not always coincident. Such ambiguity is still more evident in its quantitative characterization. Most of the available methods are heavily context dependent and often difficult to apply in the practice. Here, we propose to define and calculate resilience starting from the data matrices resulting from multivariate measurements of different biological metrics. •The resilience between two field scenarios (each one characterized by their corresponding datasets) can be conveniently captured as the difference between its respective data complexities.•Complexity is quantified by means of the entropy associated to the spectral distribution of the singular values of each data matrix.•The method proposed has been illustrated with a case study in which the resilience of a river (Ebro River, NE Spain) is calculated comparing six biological metrics associated to the phytoplankton, upstream and downstream to a series of large reservoirs that alter the natural river flow regime.

The response patterns of stream biofilms to urban sewage change with exposure time and dilution.

Urban wastewater inputs are a relevant pollution source to rivers, contributing a complex mixture of nutrients, organic matter and organic microcontaminants to these systems. Depending on their composition, WWTP effluents might perform either as enhancers (subsidizers) or inhibitors (stressors) of biological activities. In this study, we evaluated in which manner biofilms were affected by treated urban WWTP effluent, and how much they recovered after exposure was terminated. We used indoor artificial streams in a replicated regression design, which were operated for a total period of 56 days. During the first 33 days, artificial streams were fed with increasing concentration of treated effluents starting with non-contaminated water and ending with undiluted effluent. During the recovery phase, the artificial streams were fed with unpolluted water. Sewage effluents contained high concentrations of personal care products, pharmaceuticals, nutrients, and dissolved organic matter. Changes in community structure, biomass, and biofilm function were most pronounced in those biofilms exposed to 58% to 100% of WWTP effluent, moving from linear to quadratic or cubic response patterns. The return to initial conditions did not allow for complete biofilm recovery, but biofilms from the former medium diluted treatments were the most benefited (enhanced response), while those from the undiluted treatments showed higher stress (inhibited response). Our results indicated that the effects caused by WWTP effluent discharge on biofilm structure and function respond to the chemical pressure only in part, and that the biofilm dynamics (changes in community composition, increase in thickness) imprint particular response pathways over time.

River pollution by priority chemical substances under the Water Framework Directive: A provisional pan-European assessment.

In this paper, we build a preliminary inventory of dissolved phase water emissions of 36 of the 45 chemical priority substances under the European Union's Water Framework Directive. For point sources, we consider the European Pollutant Release and Transfer Register (E-PRTR) containing reported emissions from major industrial facilities. We consider all other sources as diffuse, and we estimate European average chemical emission factors from available measurements of dissolved phase concentrations, assuming simple emission patterns such as population and agricultural land. The emission inventory enables modelling concentrations, which have been compared with independent measurements. Due to the way they are estimated, they cannot withstand a point-by-point comparison. However, predicted concentrations exhibit a frequency distribution and order of magnitude compatible with observations, and match a fair proportion of independently reported exceedances of environmental quality standards for many of the substances studied. While apparently a preliminary picture based on crude simplifications, our representation suggests that simple drivers such as population and agriculture are useful to describe chemical pollution at European scale. From our preliminary inventory, E-PRTR industrial point emissions seem to account for a relatively small share of total emissions. Consequently, apart from specific measures such as upgrades to urban wastewater treatment plants in certain high impact areas, the management of priority substances may require a more strategic approach to emission control, addressing chemical use across sectors and the management of out-phased, legacy chemicals. At the same time, we advocate that improving emission inventories requires monitoring data reflecting the variability of emission patterns across Europe, as presently available monitoring data do not enable a catchment-specific estimation of emissions.

Effects of human-driven water stress on river ecosystems: a meta-analysis.

Human appropriation of water resources may induce water stress in freshwater ecosystems when ecosystem needs are not met. Intensive abstraction and regulation cause river ecosystems to shift towards non-natural flow regimes, which might have implications for their water quality, biological structure and functioning. We performed a meta-analysis of published studies to assess the potential effects of water stress on nutrients, microcontaminants, biological communities (bacteria, algae, invertebrates and fish), and ecosystem functions (organic matter breakdown, gross primary production and respiration). Despite the different nature of the flow regime changes, our meta-analysis showed significant effects of human-driven water stress, such as significant increases in algal biomass and metabolism and reduced invertebrate richness, abundance and density and organic matter decomposition. Water stress also significantly decreased phosphate concentration and increased the concentration of pharmaceutical compounds. The magnitude of significant effects was dependent on climate, rainfall regime, period of the year, river size and type of water stress. Among the different causes of water stress, flow regulation by dams produced the strongest effects, followed by water abstraction and channelization.

Shifts of environmental and phytoplankton variables in a regulated river: A spatial-driven analysis.

The longitudinal structure of the environmental and phytoplankton variables was investigated in the Ebro River (NE Spain), which is heavily affected by water abstraction and regulation. A first exploration indicated that the phytoplankton community did not resist the impact of reservoirs and barely recovered downstream of them. The spatial analysis showed that the responses of the phytoplankton and environmental variables were not uniform. The two set of variables revealed spatial variability discontinuities and river fragmentation upstream and downstream from the reservoirs. Reservoirs caused the replacement of spatially heterogeneous habitats by homogeneous spatially distributed water bodies, these new environmental conditions downstream benefiting the opportunist and cosmopolitan algal taxa. The application of a spatial auto-regression model to algal biomass (chlorophyll-a) permitted to capture the relevance and contribution of extra-local influences in the river ecosystem.

Using MALDI-TOF MS imaging and LC-HRMS for the investigation of the degradation of polycaprolactone diol exposed to different wastewater treatments.

Polymers are used in high amounts in a wide range of applications from biomedicine to industry. Because of the growing awareness of the increasing amounts of plastic wastes in the aquatic environment during recent years, the evaluation of their biodegradability deserves special attention. In the past, most efforts were dedicated to studying the biodegradation of polyesters in soil and compost, while very little research has been conducted on their fate in wastewater. Here, we assessed the ability of bacterial communities residing in the aerobic and denitrification tank from a wastewater treatment plant (WWTP) to degrade the polymeric ester polycaprolactone diol (PCLD; average molecular weight of 1250 Da). Following the incubation of the solid polymer in WWTP tanks, matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) was used to provide evidence for hydrolytic reactions and to study differences in the spatial degradation on the PCLD surface. It was demonstrated that regardless of the wastewater type, the chemical structure on the PCLD surface underwent modifications after 7 days of exposure. Apart from the parent PCLD peak series in MALDI-MSI mass spectra, the presence of a second oligomer series with mass peaks spaced by m/z 114 (as in PCLD) was observed. It was proposed to correspond to polycaprolactone (PCL) originating from the hydrolytic cleavage of the diethylene glycol from PCLD. Their ion masses were detected at m/z 104 below the PCLD peaks and their structures were proposed as PCL cyclized oligomers. Differences in the spatial distribution of low MW ions (<800) between the aerobic and denitrifying exposed samples in MALDI MSI were also noticeable. While the ions at m/z 221.1, 247.1 and 449.2 predominated in the aerobic exposed sample, those at m/z 475.5 and 677.4 were characteristic of the denitrifying one. The MALDI-MSI measurements in the low mass range were complemented with LC-HRMS analysis to determine plausible structures of the major degradation products. Ten transformation products (TPs) were detected in the denitrifying wastewater experiment, five of them were the result of ester hydrolysis forming caprolactone oligomers (TPs 220, 334, 448, 562, and 676) while the other series corresponded to formation of PCL chain with a terminal diethylene glycol, likewise formed by ester hydrolysis (TPs 246, 360, 474, 588, and 702). Graphical abstract Investigation of the polymer degradation in WWTPs by MALDI-MSI and LC-HRMS.

River ecosystem processes: A synthesis of approaches, criteria of use and sensitivity to environmental stressors.

River ecosystems are subject to multiple stressors that affect their structure and functioning. Ecosystem structure refers to characteristics such as channel form, water quality or the composition of biological communities, whereas ecosystem functioning refers to processes such as metabolism, organic matter decomposition or secondary production. Structure and functioning respond in contrasting and complementary ways to environmental stressors. Moreover, assessing the response of ecosystem functioning to stressors is critical to understand the effects on the ecosystem services that produce direct benefits to humans. Yet, there is more information on structural than on functional parameters, and despite the many approaches available to measure river ecosystem processes, structural approaches are more widely used, especially in management. One reason for this discrepancy is the lack of synthetic studies analyzing river ecosystem functioning in a way that is useful for both scientists and managers. Here, we present a synthesis of key river ecosystem processes, which provides a description of the main characteristics of each process, including criteria guiding their measurement as well as their respective sensitivity to stressors. We also discuss the current limitations, potential improvements and future steps that the use of functional measures in rivers needs to face.