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As Water Sensitive Urban Design (WSUD) is a key strategy in integrated urban water management worldwide, there is a need for robust monitoring of WSUD systems. Being economical and flexible for operation and communication, low-cost sensor systems show great potential to mainstream digital water management. Yet, such systems are insufficiently tested, casting doubt on the reliability of their measurements. Here, we document a robust testing approach for a pressure transducer water level low-cost sensor (KIT0139) and a traditional sensor (OTT PLS) in both laboratory and field conditions. We tested six different devices under three temperatures relevant to tropical climate: 25, 30, 35 °C and proposed a field calibration approach. Results reveal that the low-cost sensors were robust as the six individual devices performed consistently under different testing conditions. After calibration, low-cost sensors provided sufficient accuracy (±10mm) and precision for water levels more than 0.05m. While varying water flow direction did not significantly influence the performance, we showed that calibration should be done for individual devices. In addition, large (>5 °C) variations in water temperature and varying wet/dry conditions may also influence the performance of the low-cost sensors. The field calibration approach was validated in a 3-month experiment, confirming that this model of low-cost sensor can effectively replace traditional sensors in the field in tropical climates. Our study confirms that systematic and thorough testing is needed for low-cost sensors systems to realize their full potential for scientific-grade applications. We provide practical recommendations to conduct such testing from the laboratory to the field., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Perrine Hamel and Frederic Cherqui reports financial support was provided by MERLION (French embassy in Singapore and Nanyang Technological University). Perrine Hamel reports financial support was provided by Singapore National Research Foundation. Frederic Cherqui and Jean-Luc Bertrand-Krajewski reports financial support was provided by Rhône-Méditerranée-Corse Water Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s). Published by Elsevier Ltd.)

The RISMEAU project ( RISques liés aux résidus de Médicaments, biocides et antibiorésistance d'origine humaine et vétérinaire sur les ressources en EAU du bassin versant de l'Arve - Risks related to residues of pharmaceuticals and biocides, and antimicrobial resistance of human and veterinary origin on the water resources of the 2083 km 2 Arve catchment located in the French Alps) was implanted from 2018 to 2024 on the SIPIBEL observatory. It was devoted to the evaluation of (i) transfers of and processes related to pharmaceutical residues and biocides from both urban sludge and manure spread on fields as fertilisers, and (ii) the environmental impacts of land spreading, in particular the ecotoxicological risks and antimicrobial resistance dissemination. The methodology was based on the physico-chemical, ecotoxicological and antimicrobial resistance (AMR - assessed by molecular biology) characterisation of leachate and soil matrices samples, and focused on organic waste products application at locally representative agronomic rates. This dataset can be reused by other researchers for comparison with their own investigations on this emerging topic under different contexts and conditions, and may contribute to international reviews. The database includes in total 26,217 values, measured on 348 samples of organic waste products, soil, in situ lysimeter leachate, earthworms, plants with 3136 usual physico-chemical values, 15,469 values on pharmaceuticals and biocides concentrations, 6827 bioassay values (ecotoxicity and phytotoxicity) and 785 values of antimicrobial resistance indicators. The 348 samples have been collected from Nov. 2019 to Dec. 2022: 4 samples in 2019, 26 in 2020, 130 in 2021 and 188 in 2022. Regarding AMR, 96 assays coding for most abundant resistance genes in healthy humans, clinically relevant antibiotic resistance genes, biocide resistance genes, heavy metal genes, integrons (class I, II and III), and mobile genetic elements (transposase genes) have been carried out., (© 2024 The Author(s).)

Excitatory glutamatergic NMDA receptors (NMDARs) are key regulators of spinal pain processing, and yet the biophysical properties of NMDARs in dorsal horn nociceptive neurons remain poorly understood. Despite the clinical implications, it is unknown whether the molecular and functional properties of synaptic NMDAR responses are conserved between males and females or translate from rodents to humans. To address these translational gaps, we systematically compared individual and averaged excitatory synaptic responses from lamina I pain-processing neurons of adult Sprague-Dawley rats and human organ donors, including both sexes. By combining patch-clamp recordings of outward miniature excitatory postsynaptic currents with non-biased data analyses, we uncovered a wide range of decay constants of excitatory synaptic events within individual lamina I neurons. Decay constants of synaptic responses were distributed in a continuum from 1-20 ms to greater than 1000 ms, suggesting that individual lamina I neurons contain AMPA receptor (AMPAR)-only as well as GluN2A-, GluN2B- and GluN2D-NMDAR-dominated synaptic events. This intraneuronal heterogeneity in AMPAR- and NMDAR-mediated decay kinetics was observed across sex and species. However, we discovered an increased relative contribution of GluN2A-dominated NMDAR responses at human lamina I synapses compared with rodent synapses, suggesting a species difference relevant to NMDAR subunit-targeting therapeutic approaches. The conserved heterogeneity in decay rates of excitatory synaptic events within individual lamina I pain-processing neurons may enable synapse-specific forms of plasticity and sensory integration within dorsal horn nociceptive networks. KEY POINTS: Synaptic NMDA receptors (NMDARs) in spinal dorsal horn nociceptive neurons are key regulators of pain processing, but it is unknown whether their functional properties are conserved between males and females or translate from rodents to humans. In this study, we compared individual excitatory synaptic responses from lamina I pain-processing neurons of male and female adult Sprague-Dawley rats and human organ donors. Individual lamina I neurons from male and female rats and humans contain AMPA receptor-only as well as GluN2A, GluN2B- and GluN2D-NMDAR-dominated synaptic events. This may enable synapse-specific forms of plasticity and sensory integration within dorsal horn nociceptive networks. Human lamina I synapses have an increased relative contribution of GluN2A-dominated NMDAR responses compared with rodent synapses. These results uncover a species difference relevant to NMDAR subunit-targeting therapeutic approaches., (© 2024 The Author(s). The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.)

Preclinical assessments of pain have often relied upon behavioral measurements and anesthetized neurophysiological recordings. Current technologies enabling large-scale neural recordings, however, have the potential to unveil quantifiable pain signals in conscious animals for preclinical studies. Although pain processing is distributed across many brain regions, the anterior cingulate cortex (ACC) is of particular interest in isolating these signals given its suggested role in the affective ("unpleasant") component of pain. Here, we explored the utility of the ACC toward preclinical pain research using head-mounted miniaturized microscopes to record calcium transients in freely moving male mice expressing genetically encoded calcium indicator 6f (GCaMP6f) under the Thy1 promoter. We verified the expression of GCaMP6f in excitatory neurons and found no intrinsic behavioral differences in this model. Using a multimodal stimulation paradigm across naive, pain, and analgesic conditions, we found that while ACC population activity roughly scaled with stimulus intensity, single-cell representations were highly flexible. We found only low-magnitude increases in population activity after complete Freund's adjuvant (CFA) and insufficient evidence for the existence of a robust nociceptive ensemble in the ACC. However, we found a temporal sharpening of response durations and generalized increases in pairwise neural correlations in the presence of the mechanistically distinct analgesics gabapentin or ibuprofen after (but not before) CFA-induced inflammatory pain. This increase was not explainable by changes in locomotion alone. Taken together, these results highlight challenges in isolating distinct pain signals among flexible representations in the ACC but suggest a neurophysiological hallmark of analgesia after pain that generalizes to at least two analgesics., (Copyright © 2024 the authors.)

Sound urban water management relies on extensive and reliable monitoring of water infrastructure. As low-cost sensors and networks have become increasingly available for environmental monitoring, urban water researchers and practitioners must consider the benefits and disadvantages of such technologies. In this perspective paper, we highlight six technical and socio-technological considerations for low-cost monitoring technology to reach its full potential in the field of urban water management, including: technical barriers to implementation, complementarity with traditional sensing technologies, low-cost sensor reliability, added value of produced information, opportunities to democratize data collection, and economic and environmental costs of the technology. For each consideration, we present recent experiences from our own work and broader literature and identify future research needs to address current challenges. Our experience supports the strong potential of low-cost monitoring technology, in particular that it promotes extensive and innovative monitoring of urban water infrastructure. Future efforts should focus on more systematic documenting of experiences to lower barriers to designing, implementing, and testing of low-cost sensor networks, and on assessing the economic, social, and environmental costs and benefits of low-cost sensor deployments., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Perrine Hamel and Frederic Cherqui reports financial support was provided by MERLION (French embassy in Singapore and Nanyang Technological University). Perrine Hamel reports financial support was provided by Singapore National Research Foundation. Frederic Cherqui and Jean-Luc Bertrand-Krajewski reports financial support was provided by Rhône-Méditerranée-Corse Water Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Micropollutants are regularly detected at the outlets of wastewater treatment plants (WWTPs). Across urban and industrial WWTPs, monitoring directives only require assessment for a handful of chemicals via sampling methods that fail to capture the temporal variability in micropollutant discharge. In this study, we develop a biotest for real-time on-line monitoring of micropollutant discharge dynamics in WWTPs effluents. The selected biomonitoring device ToxMate uses videotracking of invertebrate movement, which was used to deduce avoidance behaviour of the amphipod Gammarus fossarum. Organism conditioning was set up to induce a state of minimal locomotor activity in basal conditions to maximise avoidance signal sensitivity to micropollutant spikes. We showed that with a standardised protocol, it was possible to minimise both overall movement and sensitivity to physio-chemical variations typical to WWTP effluents, as well as capture the spikes of two micropollutants upon exposure (copper and methomyl). Spikes in avoidance behaviour were consistently seen for the two chemicals, as well as a strong correlation between avoidance intensity and spiked concentration. A two-year effluent monitoring case study also illustrates how this biomonitoring method is suitable for real-time on-site monitoring, and shows a promising non-targeted approach for characterising complex micropollutant discharge variability at WWTP effluents, which today remains poorly understood., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: INRAE and the Viewpoint Company share in co-ownership one patent related to the ToxMate technology (patent #WO2018178585) and one patent related to the use of “minimal activity” approach in behavioural tracking in ecotoxicology (patent #WO2019016273). The authors AD, HQ, DN, OG & AC are listed as co-inventors for these two patents. The Viewpoint Company markets a biomonitoring service based on the ToxMate technology., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Green infrastructures (GIs) have in recent decades emerged as sustainable technologies for urban stormwater management, and numerous studies have been conducted to develop and improve hydrological models for GIs. This review aims to assess current practice in GI hydrological modelling, encompassing the selection of model structure, equations, model parametrization and testing, uncertainty analysis, sensitivity analysis, the selection of objective functions for model calibration, and the interpretation of modelling results. During a quantitative and qualitative analysis, based on a paper analysis methodology applied across a sample of 270 published studies, we found that the authors of GI modelling studies generally fail to justify their modelling choices and their alignments between modelling objectives and methods. Some practices, such as uncertainty analysis, were also found to be limited, despite their necessity being widely acknowledged by the scientific community and their application in other fields. In order to improve current GI modelling practice, the authors suggest the following: i) a framework, called STAMP, designed to promote the standardisation of the documentation of GI modelling studies, and ii) improvements in modelling tools for facilitating good practices, iii) the sharing of data for better model testing, iv) the evaluation of the suitability of hydrological equations for GI application, v) the publication of clear statements regarding model limitations and negative results., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

The large-scale deployment of low-cost monitoring systems has the potential to revolutionize the field of urban hydrology monitoring, bringing improved urban management, and a better living environment. Even though low-cost sensors emerged a few decades ago, versatile and cheap electronics like Arduino could give stormwater researchers a new opportunity to build their own monitoring systems to support their work. To find out sensors which are ready for low-cost stormwater monitoring systems, for the first time, we review the performance assessments of low-cost sensors for monitoring air humidity, wind speed, solar radiation, rainfall, water level, water flow, soil moisture, water pH, conductivity, turbidity, nitrogen, and phosphorus in a unified metrological framework considering numerous parameters. In general, as these low-cost sensors are not initially designed for scientific monitoring, there is extra work to make them suitable for in situ monitoring, to calibrate them, to validate their performance, and to connect them with open-source hardware for data transmission. We, therefore, call for international cooperation to develop uniform low-cost sensor production, interface, performance, calibration and system design, installation, and data validation guides which will greatly regulate and facilitate the sharing of experience and knowledge.

Pollution levels in stormwater vary significantly during rain events, with pollutant flushes carrying a major fraction of an event pollutant load in a short period. Understanding these flushes is thus essential for stormwater management. However, current studies mainly focus on describing the first flush or are limited by predetermined flush categories. This study provides a new perspective on the topic by applying data-driven approaches to categorise Mass Volume (MV) curves for TSS into distinct classes of flush tailored to specific monitoring location. Functional Data Analysis (FDA) was used to investigate the dynamics of MV curves in two large data sets, consisting of 343 measured events and 915 modelled events, respectively. Potential links between classes of MV curves and combinations of rain characteristics were explored through a priori clustering. This yielded correct class assignments for 23-63% of the events using different combinations of MV curve clustering and rainfall characteristics. This suggests that while global rainfall characteristics influence flush, they are not sufficient as sole explanatory variables of different flush phenomena, and additional explanatory variables are needed to assign MV curves into classes with a predictive power that is suitable for e.g. design of stormwater control measures. Our results highlight the great potential of the FDA methodology as a new approach for classifying, describing, and understanding pollutant flush signals in stormwater., (Copyright © 2022. Published by Elsevier Ltd.)

Historically, green infrastructure for stormwater management has been event-based designed. This study aims to realign the green infrastructure design strategies with principles for robust decision making, through the example of green roofs design with the variational method and exemplified using the Norwegian context of the 3-step approach (3SA) for stormwater management. The 3SA consists of planning solutions to handle day-to-day rain at site scale through infiltration (step 1) and detention (step 2), and extreme events with safe floodways (step 3). An innovative framework based on downscaling of rainfall timeseries is suggested as follows: (i) long duration continuous simulation for retention variation and day-to-day discharge, corresponding to step 1 in the 3SA; (ii) intensive sampling of local extreme events to estimate reliability and robustness of solutions, corresponding to steps 2 and 3 in the 3SA. Comparing the traditional variational method to Highly-Informed-Design-Evaluation-Strategy (HIDES), it was found that the variational method possibly leads to incorrect decisions while the suggested novel approach was found to give more informed and reliable results by suggesting a design based on both operating mode and failure mode. It allows to embed solutions within the urban water system by facilitating the link between the steps of the 3SA. Such a framework was found to be data-wise applicable in the Norwegian context.

The Bellecombe pilot site - SIPIBEL - was created in 2010 in order to study the characterisation, treatability and impacts of hospital effluents in an urban wastewater treatment plant. This pilot site is composed of: i) the Alpes Léman hospital (CHAL), opened in February 2012, ii) the Bellecombe wastewater treatment plant, with two separate treatment lines allowing to fully separate the hospital wastewater and the urban wastewater, and iii) the Arve River as the receiving water body and a tributary of the Rhône River and the Geneva aquifer. The database includes in total 48 439 values measured on 961 samples (raw and treated hospital and urban wastewater, activated sludge in aeration tanks, dried sludge after dewatering, river and groundwater, and a few additional campaigns in aerobic and anaerobic sewers) with 44 455 physico-chemistry values (including 15 pharmaceuticals and 14 related transformation products, biocides compounds, metals, organic micropollutants), 2 193 bioassay values (ecotoxicity), 1 679 microbiology values (including microorganisms and antibioresistance indicators) and 112 hydrobiology values., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2021 The Author(s). Published by Elsevier Inc.)

We investigated voltage-gated sodium channel (Na V 1) subunits that regulate action potential initiation in the nerve terminals of vagal nodose C-fibers innervating the esophagus. Extracellular single fiber recordings were made from the nodose C-fibers, with mechanically sensitive nerve terminals in the isolated innervated guinea pig esophagus. Na V 1 inhibitors were selectively delivered to the tissue-containing nerve terminals. Graded esophageal distention was used for mechanical stimulation. The Na V 1.7 inhibitor PF-05089771 nearly abolished action potential initiation in response to low levels of esophageal distention but only partially inhibited the response to higher levels of esophageal distention. The PF-05089771-insensitive component of the response progressively increased (up to ≈50%) with increasing esophageal distention and was abolished by tetrodotoxin (TTX). In addition to Na V 1.7, nodose C-fiber [transient receptor potential channel-vanilloid subfamily member 1 (TRPV1)-positive] neurons retrogradely labeled from the esophagus expressed mRNA for multiple TTX-sensitive Na V 1s. The group Na V 1.1, Na V 1.2, and Na V 1.3 inhibitor ICA-121431 inhibited but did not abolish the PF-05089771-insensitive component of the response to high level of esophageal distention. However, combination of ICA-121431 with compound 801, which also inhibits Na V 1.7 and Na V 1.6, nearly abolished the response to the high level of esophageal distention. Our data indicate that the action potential initiation in esophageal nodose C-fibers evoked by low (innocuous) levels of esophageal distention is mediated by Na V 1.7. However, the response evoked by higher (noxious) levels of esophageal distention has a progressively increasing Na V 1.7-independent component that involves multiple TTX-sensitive Na V 1s. The stimulus intensity-dependent recruitment of Na V 1s may offer novel opportunities for strategic targeting of Na V 1 subunits for inhibition of nociceptive signaling in visceral C-fibers. NEW & NOTEWORTHY We report that pharmacologically distinguishable voltage-gated sodium channels (Na V 1) mediate action potential initiation at low (innocuous) versus high (noxious) intensity of esophageal distention in nerve terminals of vagal nodose C-fibers. Action potential initiation at low intensity is entirely dependent on Na V 1.7; however, additional tetrodotoxin (TTX)-sensitive Na V 1s are recruited at higher intensity of distention. This is the first demonstration that Na V 1s underlying action potential initiation in visceral C-fibers depend on the intensity of the stimulus.

Pharmaceuticals are known contaminants of the environment. Assessing and managing the risk associated to this contamination has become an important field of study in environmental sciences. Accurately sampling and measuring pharmaceuticals concentrations in wastewater or in the environment is still costly and difficult. Thus only a few studies have looked at the temporal variability of the concentrations. In parallel, models have been proposed to predict the occurrence of pharmaceuticals. They usually assume that the loads of pharmaceuticals entering a wastewater treatment plant (WWTP) are proportional to the pharmaceuticals sales. However, most of the time, the results are difficult to interpret. The main problem with those models is the lack of data at WWTP. In this context, a stochastic model predicting daily and hourly loads is proposed to better understand the processes influencing the occurrence of pharmaceuticals in wastewater. Using accurate statistical pharmaceutical sales data, the mass consumed daily in the catchment is randomly picked from empirical probability density functions. Then, patients are randomly generated until the picked total mass is reached. For each patient, posology, metabolism and excretion rates of pharmaceuticals to the sewer system are randomly generated according to relevant literature data. In particular, time-use data are used to generate the time-use of patients to pick the times when patients consume pharmaceuticals and also when they excrete them in toilets. Applied to 9 molecules in a French catchment, results show that the model accurately and reliably predicts both the daily and hourly loads of pharmaceuticals at the inlet of the WWTP., (Copyright © 2020 Elsevier GmbH. All rights reserved.)

Current therapies for the treatment of chronic pain provide inadequate relief for millions of suffering patients, demonstrating the need for better therapies that will treat pain effectively and improve the quality of patient's lives. Better understanding of the mechanisms that mediate chronic pain is critical for developing drugs with improved clinical outcomes. Adenosine triphosphate (ATP) is a key modulator in nociceptive pathways. Release of ATP from injured tissue or sympathetic efferents has sensitizing effects on sensory neurons in the periphery, and presynaptic vesicular release of ATP from the central terminals can increase glutamate release thereby potentiating downstream central sensitization mechanisms, a condition thought to underlie many chronic pain conditions. The purinergic receptors on sensory nerves primarily responsible for ATP signaling are P2X3 and P2X2/3. Selective knockdown experiments, or inhibition with small molecules, demonstrate P2X3-containing receptors are key targets to modulate nociceptive signals. Preclinical studies have identified that P2X3-containing receptors are critical for sensory transduction for bladder function, and clinical studies have shown promise in treatment for bladder pain and pain associated with osteoarthritis. Further clinical characterization of antagonists to P2X3-containing receptors may lead to improved therapies in the treatment of chronic pain.

The assessment of micropollutants in urban wet weather discharges is essential to improve the knowledge of the impact of such discharges on receiving waters. This study assessed the quality of combined sewer overflows (CSOs) in Ecully (residential catchment) and stormwater runoff in Chassieu (industrial catchment) during rain events by providing data on occurrence and total event mean concentrations (EMC t ) of 34 priority substances (PS) (9 metals, 13 pesticides, 6 PAHs, 4 alkylphenols and 2 chlorobenzenes) in dissolved and particulate fractions. Over 34 substances monitored, 23 were quantified in urban wet weather discharges of both catchments. For both catchments, 9 metals and 6 PAHs monitored were always quantified, reflecting their ubiquitous presence. For other organic pollutants, only 5 pesticides were quantified and only 2 alkyphenols were measured solely in dissolved fraction. A significant site-to-site difference was observed for metals, PAHs and alkylphenols. The highest concentrations were measured in stormwater runoff in Chassieu vs. Ecully. On the contrary, the diuron concentrations were highest in CSO discharges in Ecully. Distribution of the PS between particulate and dissolved fractions provides information for urban stormwater practitioners. Most PS in urban wet weather discharges were mainly linked to particles (PAHs, Pb, Ti for example). The comparison between daily flows of wastewater treatment plants during dry weather and CSOs daily flows in Ecully showed that stormwater was the most important source of contamination for fluoranthene, benzo(b)fluoranthene and benzo(k)fluoranthene and 7 metals (As, Cr, Co, Cu, Pb, Ti and Zn) in receiving water bodies, but not for pesticides and alkylphenols., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Previously we reported that a group of inflammatory mediators significantly enhanced resurgent currents in dorsal root ganglion neurons. To understand the underlying intracellular signaling mechanism, we investigated the effects of inhibition of extracellular signal-regulated kinases and protein kinase C on the enhancing effects of inflammatory mediators on resurgent currents in rat dorsal root ganglion neurons. We found that the extracellular signal-regulated kinases inhibitor U0126 completely prevented the enhancing effects of the inflammatory mediators on both Tetrodotoxin-sensitive and Tetrodotoxin-resistant resurgent currents in both small and medium dorsal root ganglion neurons. U0126 substantially reduced repetitive firing in small dorsal root ganglion neurons exposed to inflammatory mediators, consistent with prevention of resurgent current amplitude increases. The protein kinase C inhibitor Bisindolylmaleimide I also showed attenuating effects on resurgent currents, although to a lesser extent compared to extracellular signal-regulated kinases inhibition. These results indicate a critical role of extracellular signal-regulated kinases signaling in modulating resurgent currents and membrane excitability in dorsal root ganglion neurons treated with inflammatory mediators. It is also suggested that targeting extracellular signal-regulated kinases-resurgent currents might be a useful strategy to reduce inflammatory pain.

The event mean concentrations (EMCs) that would have been obtained by four different stormwater sampling strategies are simulated by using total suspended solids (TSS) and flowrate time series (about one minute time-step and one year of data). These EMCs are compared to the reference EMCs calculated by considering the complete time series. The sampling strategies are assessed with datasets from four catchments: (i) Berlin, Germany, combined sewer overflow (CSO); (ii) Graz, Austria, CSO; (iii) Chassieu, France, separate sewer system; and (iv) Ecully, France, CSO. A sampling strategy in which samples are collected at constant time intervals over the rainfall event and sampling volumes are pre-set as proportional to the runoff volume discharged between two consecutive sample leads to the most representative results. Recommended sampling time intervals are of 5 min for Berlin and Chassieu (resp. 100 and 185 ha area) and 10 min for Graz and Ecully (resp. 335 and 245 ha area), with relative sampling errors between 7% and 20% and uncertainties in sampling errors of about 5%. Uncertainties related to sampling volumes, TSS laboratory analyses and beginning/ending of rainstorm events are reported as the most influent sources in the uncertainties of sampling errors and EMCs.

This work proposes a Bayesian non-informative reconstruction of virtual state variables in the representation of stormwater total suspended solids pollutographs by the traditional wash-off models, based on 255 rainfall events measured in a 185 ha French urban catchment. Results from event-based analyses revealed the missing representation of an essential process in the traditional rating curve (RC) model (simplest wash-off model) for 56% of the rainfall events. The unsatisfactory performances of the RC model are found to be not necessarily linked to antecedent dry weather conditions, as assumed by a great number of accumulation/wash-off models. Statistical tests suggest that non-representable rainfall events by the RC model are randomly distributed in time. The proposed Bayesian reconstructions of a potential process missed by the RC model exhibit a suitable identifiability at an intra-event scale. However, these reconstructions are not interpretable from the traditional accumulation/wash-off notions, i.e. in terms of a unique state of virtual available mass over the catchment that is decreasing over time, due to their high unrepeatability regarding their shape and their low prediction capacity for other rainfall events.

Quantifying pollutant loads from combined sewer overflows (CSOs) is necessary for assessing impacts of urban drainage on receiving water bodies. Based on data obtained at three adjacent CSO structures in the Louis Fargue catchment in Bordeaux, France, this study implements multiple linear regression (MLR) and random forest regression (RFR) approaches to develop statistical models for estimating emitted loads of total suspended solids (TSS). Comparison between hierarchical clustering selection and random selection of CSO events for model calibration is included in model development. The results indicate that selection of the model's explanatory variables depends on both the type of approach and the CSO structure. By using the cluster technique to select representative events for model calibration, model predictability is generally improved. For the available dataset, MLR may have advantages over RFR in terms of verification performance and lower range of error due to splitting events for calibration and verification. But RFR model uncertainty bands are considerably narrower than the MLR ones.

Hospital wastewater (HWW) receives increasing attention because of its specific composition and higher concentrations of some micropollutants. Better knowledge of HWW is needed in order to improve management strategies and to ensure the preservation of wastewater treatment efficiency and freshwater ecosystems. This context pushed forward the development of a pilot study site named Site Pilote de Bellecombe (SIPIBEL), which collects and treats HWW separately from urban wastewater, applying the same conventional treatment process. This particular configuration offers the opportunity for various scientific investigations. It enables to compare hospital and urban wastewater, the efficiency of the two parallel treatment lines, and the composition of the resulting hospital and urban treated effluents, as well as the evaluation of their effects on the environment. The study site takes into account environmental, economic, and social issues and promotes scientific and technical multidisciplinary actions. ᅟ.

The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective sampling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective sampling strategies. Results indicate that the random sampling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli. The differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and E. coli), indicating that there is little benefit in investing in collection of more than one sample per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R 2  = 0.49; P < 0.01) as well as the number of events required to achieve certain accuracy, and hence could be a promising surrogate for determining the sampling frequency needed to accurately estimate SMCs of pollutants., (Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.)

Little is known about the neuronal voltage-gated sodium channels (NaVs) that control neurotransmission in the parasympathetic nervous system. We evaluated the expression of the α subunits of each of the nine NaVs in human, guinea pig, and mouse airway parasympathetic ganglia. We combined this information with a pharmacological analysis of selective NaV blockers on parasympathetic contractions of isolated airway smooth muscle. As would be expected from previous studies, tetrodotoxin potently blocked the parasympathetic responses in the airways of each species. Gene expression analysis showed that that NaV 1.7 was virtually the only tetrodotoxin-sensitive NaV1 gene expressed in guinea pig and human airway parasympathetic ganglia, where mouse ganglia expressed NaV1.1, 1.3, and 1.7. Using selective pharmacological blockers supported the gene expression results, showing that blocking NaV1.7 alone can abolish the responses in guinea pig and human bronchi, but not in mouse airways. To block the responses in mouse airways requires that NaV1.7 along with NaV1.1 and/or NaV1.3 is blocked. These results may suggest novel indications for NaV1.7-blocking drugs, in which there is an overactive parasympathetic drive, such as in asthma. The data also raise the potential concern of antiparasympathetic side effects for systemic NaV1.7 blockers., (Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.)

UV/Vis spectrophotometers have been used for one decade to monitor water quality in various locations: sewers, rivers, wastewater treatment plants (WWTPs), tap water networks, etc. Resulting equivalent concentrations of interest can be estimated by three ways: i) by manufacturer global calibration; ii) by local calibration based on the provided global calibration and grab sampling; iii) by advanced calibration looking for relations between UV/Vis spectra and corresponding concentrations from grab sampling. However, no study has compared the applied methods so far. This collaborative work presents a comparison between five different methods. A Linear Regression (LR), Support Vector Machine (SVM), EVOlutionary algorithm method (EVO) and Partial Least Squares (PLS) have been applied on various data sets (sewers, rivers, WWTPs under dry, wet and all weather conditions) and for three water quality parameters: TSS, COD total and dissolved. Two criteria (r(2) and Root Mean Square Error RMSE) have been calculated - on calibration and verification data subsets - to evaluate accuracy and robustness of the applied methods. Values of criteria have then been statistically analysed for all and separated data sets. Non-consistent outcomes come through this study. According to the Kruskal-Wallis test and RMSEs, PLS and SVM seem to be the best methods. According to uncertainties in laboratory analysis and ranking of methods, LR and EVO appear more robust and sustainable for concentration estimations. Conclusions are mostly independent of water matrices, weather conditions or concentrations investigated., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A novel kinetics model that describes the dynamics of polycyclic aromatic hydrocarbons (PAHs) in contaminated soils is presented. The model includes two typical biodegradation pathways: the co-metabolic pathway using pseudo first order kinetics and the specific biodegradation pathway modeled using Monod kinetics. The sorption of PAHs to the solid soil occurs through bi-phasic fist order kinetics, and two types of non-extractible bounded residues are considered: the biogenic and the physically sequestrated into soil matrix. The PAH model was developed in Matlab, parameterized and tested successfully on batch experimental data using a Bayesian approach (DREAM). Preliminary results led to significant model simplifications. They also highlighted that the specific biodegradation pathway was the most efficient at explaining experimental data, as would be expected for an old industrial contaminated soil. Global analysis of sensitivity showed that the amount of PAHs ultimately degraded was mostly governed by physicochemical interactions rather than by biological activity., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Total suspended solid (TSS) measurements in urban drainage systems are required for several reasons. Aiming to assess uncertainties in the mean TSS concentration due to the influence of sampling intake vertical position and vertical concentration gradients in a sewer pipe, two methods are proposed: a simplified method based on a theoretical vertical concentration profile (SM) and a time series grouping method (TSM). SM is based on flow rate and water depth time series. TSM requires additional TSS time series as input data. All time series are from the Chassieu urban catchment in Lyon, France (time series from 2007 with 2-min time step, 89 rainfall events). The probability of measuring a TSS value lower than the mean TSS along the vertical cross section (TSS underestimation) is about 0.88 with SM and about 0.64 with TSM. TSM shows more realistic TSS underestimation values (about 39 %) than SM (about 269 %). Interquartile ranges (IQR) over the probability values indicate that SM is more uncertain (IQR = 0.08) than TSM (IQR = 0.02). Differences between the two methods are mainly due to simplifications in SM (absence of TSS measurements). SM assumes a significant asymmetry of the TSS concentration profile along the vertical axis in the cross section. This is compatible with the distribution of TSS measurements found in the TSM approach. The methods provide insights towards an indicator of the measurement performance and representativeness for a TSS sampling protocol.

This paper reports about experiences gathered from five online monitoring campaigns in the sewer systems of Berlin (Germany), Graz (Austria), Lyon (France) and Bogota (Colombia) using ultraviolet-visible (UV-VIS) spectrometers and turbidimeters. Online probes are useful for the measurement of highly dynamic processes, e.g. combined sewer overflows (CSO), storm events, and river impacts. The influence of local calibration on the quality of online chemical oxygen demand (COD) measurements of wet weather discharges has been assessed. Results underline the need to establish local calibration functions for both UV-VIS spectrometers and turbidimeters. It is suggested that practitioners calibrate locally their probes using at least 15-20 samples. However, these samples should be collected over several events and cover most of the natural variability of the measured concentration. For this reason, the use of automatic peristaltic samplers in parallel to online monitoring is recommended with short representative sampling campaigns during wet weather discharges. Using reliable calibration functions, COD loads of CSO and storm events can be estimated with a relative uncertainty of approximately 20%. If no local calibration is established, concentrations and loads are estimated with a high error rate, questioning the reliability and meaning of the online measurement. Similar results have been obtained for total suspended solids measurements.

Resurgent sodium currents likely play a role in modulating neuronal excitability. Here we studied whether protein kinase C (PKC) activation can increase resurgent currents produced by the human sodium channel hNav1.7. We found that a PKC agonist significantly enhanced hNav1.7-mediated resurgent currents and this was prevented by PKC antagonists. The enhancing effects were replicated by two phosphorylation-mimicking mutations and were prevented by a phosphorylation-deficient mutation at a conserved PKC phosphorylation site (Serine 1479). Our results suggest that PKC can increase sodium resurgent currents through phosphorylation of a conserved Serine residue located in the domain III-IV linker of sodium channels., (Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.)

Resurgent sodium currents contribute to the regeneration of action potentials and enhanced neuronal excitability. Tetrodotoxin-sensitive (TTX-S) resurgent currents have been described in many different neuron populations, including cerebellar and dorsal root ganglia (DRG) neurons. In most cases, sodium channel Nav1.6 is the major contributor to these TTX-S resurgent currents. Here we report a novel TTX-resistant (TTX-R) resurgent current recorded from rat DRG neurons. The TTX-R resurgent currents are similar to classic TTX-S resurgent currents in many respects, but not all. As with TTX-S resurgent currents, they are activated by membrane repolarization, inhibited by lidocaine, and enhanced by a peptide-mimetic of the β4 sodium channel subunit intracellular domain. However, the TTX-R resurgent currents exhibit much slower kinetics, occur at more depolarized voltages, and are sensitive to the Nav1.8 blocker A803467. Moreover, coimmunoprecipitation experiments from rat DRG lysates indicate the endogenous sodium channel β4 subunits associate with Nav1.8 in DRG neurons. These results suggest that slow TTX-R resurgent currents in DRG neurons are mediated by Nav1.8 and are generated by the same mechanism underlying TTX-S resurgent currents. We also show that both TTX-S and TTX-R resurgent currents in DRG neurons are enhanced by inflammatory mediators. Furthermore, the β4 peptide increased excitability of small DRG neurons in the presence of TTX. We propose that these slow TTX-R resurgent currents contribute to the membrane excitability of nociceptive DRG neurons under normal conditions and that enhancement of both types of resurgent currents by inflammatory mediators could contribute to sensory neuronal hyperexcitability associated with inflammatory pain., (Copyright © 2014 the authors 0270-6474/14/347190-08$15.00/0.)

Sedimentation is a common but complex phenomenon in the urban drainage system. The settling mechanisms involved in detention basins are still not well understood. The lack of knowledge on sediment transport and settling processes in actual detention basins is still an obstacle to the optimization of the design and the management of the stormwater detention basins. In order to well understand the sedimentation processes, in this paper, a new boundary condition as an attempt to represent the sedimentation processes based on particle tracking approach is presented. The proposed boundary condition is based on the assumption that the flow turbulent kinetic energy near the bottom plays an important role on the sedimentation processes. The simulated results show that the proposed boundary condition appears as a potential capability to identify the preferential sediment zones and to predict the trapping efficiency of the basin during storm events.

Designing vertical-flow constructed wetlands (VFCWs) to treat both rain events and dry weather flow is a complex task due to the stochastic nature of rain events. Dynamic models can help to improve design, but they usually prove difficult to handle for designers. This study focuses on the development of a simplified hydraulic model of French VFCWs using an empirical infiltration coefficient--infiltration capacity parameter (ICP). The model was fitted using 60-second-step data collected on two experimental French VFCW systems and compared with Hydrus 1D software. The model revealed a season-by-season evolution of the ICP that could be explained by the mechanical role of reeds. This simplified model makes it possible to define time-course shifts in ponding time and outlet flows. As ponding time hinders oxygen renewal, thus impacting nitrification and organic matter degradation, ponding time limits can be used to fix a reliable design when treating both dry and rain events.

Many field investigations have used continuous sensors (turbidimeters and/or ultraviolet (UV)-visible spectrophotometers) to estimate with a short time step pollutant concentrations in sewer systems. Few, if any, publications compare the performance of various sensors for the same set of samples. Different surrogate sensors (turbidity sensors, UV-visible spectrophotometer, pH meter, conductivity meter and microwave sensor) were tested to link concentrations of total suspended solids (TSS), total and dissolved chemical oxygen demand (COD), and sensors' outputs. In the combined sewer at the inlet of a wastewater treatment plant, 94 samples were collected during dry weather, 44 samples were collected during wet weather, and 165 samples were collected under both dry and wet weather conditions. From these samples, triplicate standard laboratory analyses were performed and corresponding sensors outputs were recorded. Two outlier detection methods were developed, based, respectively, on the Mahalanobis and Euclidean distances. Several hundred regression models were tested, and the best ones (according to the root mean square error criterion) are presented in order of decreasing performance. No sensor appears as the best one for all three investigated pollutants.

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

This paper presents one of the largest databases on the quality of urban wet weather discharges measured since the development of continuous in-sewer water quality sensors in the late 1990s. Five years of continuous turbidity measurements enabled the validation of 263 and 239 rainfall events, respectively on two experimental catchments in Lyon (France), Chassieu (185 ha separate sewer) and Ecully (245 ha combined sewer). Except for high rainfall events of summer and second half of winter, analysis of database representativeness showed that all seasons were relatively well represented. As a first analysis of the database, traditional tools used in the urban drainage field were applied to assess: i) statistics and analysis of distributions of TSS and COD events loads and event mean concentrations (EMCs) and ii) the correlations between these statistics and events characteristics and iii) M(V) curves describing the intra-event mass distribution. Results showed that: i) EMCs and loads were approximately log-normally distributed, with a clear impact from wastewater contribution in Ecully, ii) EMCs are not correlated with storm event characteristics, whereas loads have shown significant correlation with key storm event variables such as total event volume, rainfall depth, maximum rainfall intensity and discharge and iii) M(V) curves dynamic could be classified in three categories, however with no clear correlation with storm event characteristics. The visual analysis of continuous time series of TSS and COD pollutographs, derived from turbidity time series showed that event pollutographs were highly variable, due to complex interacting processes during and between events, and suggests that further progress in knowledge and modelling of urban wet weather pollutant loads and pollutographs should be based on more detailed analyses of continuous time series rather, than on the traditional single event approach., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Open-channel junctions are common occurrences in sewer networks and flow rate measurement often occurs near these singularities. Local flow structures are 3D, impact on the representativeness of the local flow measurements and thus lead to deviations in the flow rate estimation. The present study aims (i) to measure and simulate the flow pattern in a junction flow, (ii) to analyse the impact of the junction on the velocity distribution according to the distance from the junction and thus (iii) to evaluate the typical error derived from the computation of the flow rate close to the junction.

Atmospheric deposition plays an important role in environmental pollution and human health. However, very few information is available on the presence, in atmospheric particles, of organic priority substances in contrast to inorganic fraction. A method for the extraction and quantification of 20 priority organic substances listed in the European Water Framework Directive in atmospheric particles was developed. This method consists in a combination of gas chromatography coupled with mass spectrometry and ultra-high-pressure liquid chromatography coupled with tandem mass spectrometry and fluorescence. Optimized pressurized liquid extraction using a hexane/dichloromethane/isopropanol mixture was used as extraction procedure from atmospheric particulate matter. The influence of several extraction experimental factors related to the PLE was investigated. The optimized extraction method (80°C, 40 bar, 10 min, 1 cycle) exhibited average recoveries of target analytes higher than 62%. The method detection limits (MDL) were between 0.3 ng g(-1) and 83 ng g(-1). This extraction method, combined with sensitive analytical techniques, leads to satisfactory reliability, sensitivity, and accuracy. The method was applied to real samples, collected from two urban sites by an atmospheric sampling prototype developed in this study. The first results reveal a systematic presence of PAHs at high levels (ranging from 500 ng g(-1) to 10 μg g(-1)) and a variable and lower presence of pesticides at concentrations below 50 ng g(-1) in the samples., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Continuous high resolution long term turbidity measurements along with continuous discharge measurements are now recognised as an appropriate technique for the estimation of in sewer total suspended solids (TSS) and Chemical Oxygen Demand (COD) loads during storm events. In the combined system of the Ecully urban catchment (Lyon, France), this technique is implemented since 2003, with more than 200 storm events monitored. This paper presents a method for the estimation of the dry weather (DW) contribution to measured total TSS and COD event loads with special attention devoted to uncertainties assessment. The method accounts for the dynamics of both discharge and turbidity time series at two minutes time step. The study is based on 180 DW days monitored in 2007-2008. Three distinct classes of DW days were evidenced. Variability analysis and quantification showed that no seasonal effect and no trend over the year were detectable. The law of propagation of uncertainties is applicable for uncertainties estimation. The method has then been applied to all measured storm events. This study confirms the interest of long term continuous discharge and turbidity time series in sewer systems, especially in the perspective of wet weather quality modelling.

With the increasing implementation of continuous monitoring of both discharge and water quality in sewer systems, large data bases are now available. In order to manage large amounts of data and calculate various variables and indicators of interest it is necessary to apply automated methods for data processing. This paper deals with the processing of short time step turbidity time series to estimate TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) event loads in sewer systems during storm events and their associated uncertainties. The following steps are described: (i) sensor calibration, (ii) estimation of data uncertainties, (iii) correction of raw data, (iv) data pre-validation tests, (v) final validation, and (vi) calculation of TSS and COD event loads and estimation of their uncertainties. These steps have been implemented in an integrated software tool. Examples of results are given for a set of 33 storm events monitored in a stormwater separate sewer system.

An empirical model for TSS event mean concentrations in storm weather discharges has been derived from the analysis of data sets collected in two experimental catchments (Chassieu, separate system and Ecully, combined system) in Lyon, France. Preliminary tests have shown that the values of TSS EMCs were linked to the variable X =TP ×ADWP (TP rainfall depth, ADWP antecedent dry weather period) with two distinct behaviours under and above a threshold value of X named λ: EMCs are increasing if X < λ and are decreasing if X > λ. An empirical equation is proposed for both behaviours. A specific calibration method is used to calibrate λ while the 4 other parameters of the model are calibrated by means of the Levenberg-Marquardt algorithm. The calibration results obtained with 8 events in both sites indicate that the model calibration is satisfactory: Nash Sutcliffe coefficients are all above 0.7. Monte Carlo simulations indicate a low variability of the model parameters for both sites. The model verification with 5 events in Chassieu shows maximum levels of uncertainty of approximately 20%, equivalent to levels of uncertainty observed in the calibration phase.

Current marketed antiepileptic drugs (AEDs) consist of a variety of structural classes with different mechanisms of action. These agents typically have non-overlapping efficacy and side-effect profiles presenting multiple treatment options for the patient population. However, approximately 30% of seizure sufferers fail to respond to current therapies often because poorly tolerated side-effects limit adequate dosing. The scope of this review is to summarize selected advances in 2 nd and 3 rd generation AEDs as well as compounds in development with novel mechanisms of action.

Regression models are among the most frequently used models to estimate pollutants event mean concentrations (EMC) in wet weather discharges in urban catchments. Two main questions dealing with the calibration of EMC regression models are investigated: i) the sensitivity of models to the size and the content of data sets used for their calibration, ii) the change of modelling results when models are re-calibrated when data sets grow and change with time when new experimental data are collected. Based on an experimental data set of 64 rain events monitored in a densely urbanised catchment, four TSS EMC regression models (two log-linear and two linear models) with two or three explanatory variables have been derived and analysed. Model calibration with the iterative re-weighted least squares method is less sensitive and leads to more robust results than the ordinary least squares method. Three calibration options have been investigated: two options accounting for the chronological order of the observations, one option using random samples of events from the whole available data set. Results obtained with the best performing non linear model clearly indicate that the model is highly sensitive to the size and the content of the data set used for its calibration.

KCNQ2 (Kv7.2) and KCNQ3 (Kv7.3) are voltage-gated K(+) channel subunits that underlie the neuronal M current. In humans, mutations in these genes lead to a rare form of neonatal epilepsy (Biervert et al., 1998; Singh et al., 1998), suggesting that KCNQ2/Q3 channels may be attractive targets for novel antiepileptic drugs. In the present study, we have identified the compound N-(6-chloro-pyridin-3-yl)-3,4-difluoro-benzamide (ICA-27243) as a selective activator of the neuronal M current and KCNQ2/Q3 channels. In SH-SY5Y human neuroblastoma cells, ICA-27243 produced membrane potential hyperpolarization that could be prevented by coadministration with the M-current inhibitors 10,10-bis(4-pyridinylmethyl)-9(10H)-anthracenone dihydrochloride (XE-991) and linopirdine. ICA-27243 enhanced both (86)Rb(+) efflux (EC(50) = 0.2 microM) and whole-cell currents in Chinese hamster ovary cells stably expressing heteromultimeric KCNQ2/Q3 channels (EC(50) = 0.4 microM). Activation of KCNQ2/Q3 channels was associated with a hyperpolarizing shift of the voltage dependence of channel activation (V((1/2)) shift of -19 mV at 10 microM). In contrast, ICA-27243 was less effective at activating KCNQ4 and KCNQ3/Q5 and was selective over a wide range of neurotransmitter receptors and ion channels such as voltage-dependent sodium channels and GABA-gated chloride channels. ICA-27243 (1-10 microM) was found to reversibly suppress seizure-like activity in an ex vivo hippocampal slice model of epilepsy and demonstrated in vivo anticonvulsant activity (ED(50) = 8.4 mg/kg) in the mouse maximal electroshock epilepsy model. In conclusion, ICA-27243 represents the first member of a novel chemical class of selective KCNQ2/Q3 activators with anticonvulsant-like activity in experimental models of epilepsy.

Field experiments were carried out to contribute to the assessment of the VICAS protocol aiming to measure settling velocities of particles. Samples of deposited sediments have been taken in the Django Reinhardt stormwater detention and settling tank in Chassieu, France, using sediment traps located on the tank bottom. The first set of experiments was designed to assess the VICAS protocol in terms of mass balance and repeatability. A bias in the measurement of settling velocities distributions of deposited sediments (i.e. particles with high settling velocities) was suspected and confirmed by specific tests. Uncertainties in the final distribution curves have been evaluated by using Monte Carlo simulations and the law of propagation of uncertainties. All uncertainty calculations were implemented in a MatLab code named UVICAS used for each experiment. This code allows analysing the main sources of uncertainties and their evolution during experiments. Uncertainties in the final distribution curves decrease with increasing values of settling velocities and are lower than 1%., ((c) IWA Publishing 2008.)

Recent UV-visible spectrometers deliver on line and in situ absorbance spectra in wastewater or stormwater transported in urban drainage systems. After calibration with local data sets, spectra can be used to estimate pollutant concentrations. Calibration methods are usually based on PLS (Partial Least Squares) regression. Their most important difficulty lies in the identification of the number of both i) the latent vectors and ii) the independent variables. A method is proposed to identify these variables, based on an exhaustive tests procedure (Jackknife cross validation and matrix of prediction indicator). It was applied to estimate TSS (total suspended solids) or COD (chemical oxygen demand) concentrations at the inlet of a storage-settling tank in a stormwater separate sewer system, and compared to three other calibration methods used either for turbidity meters or UV-visible spectrometers. With the available calibration data set: i) the spectrometer gives results with better prediction quality than the turbidity meter, ii) for the spectrometer, local calibration gives better results than global calibration, iii) the proposed PLS method gives results with a similar order of magnitude in uncertainties as the manufacturer local calibration method, but is more open and transparent for the user. Similar results were obtained for a second data set.

In situ spectrometers are comparable robust instruments and can be operated long term with relatively low maintenance demand. The decisive factor for their applicability is the development of a medium and installation location specific correlation model, which estimates the concentration of the requested target parameter from the measured absorption values. In some cases it might turn out, that the development of a single site specific correlation model is not sufficient, due to frequent and substantial variations of the (waste) water composition.In order to assess the total uncertainty of in situ spectrometry, a comprehensive lab test was carried out. It includes a detailed investigation of the uncertainty of CODreference methods (DIN and small tube tests), a precision analysis of the absorption spectra and the impact of those two factors on the total uncertainty of the COD(EQ) correlation model., (IWA Publishing 2008.)

Turbidity monitoring is a valuable tool for operating sewer systems, but it is often considered as a somewhat tricky parameter for assessing water quality, because measured values depend on the model of sensor, and even on the operator. This paper details the main components of the uncertainty in turbidity measurements with a special focus on reproducibility, and provides guidelines for improving the reproducibility of measurements in wastewater relying on proper calibration procedures. Calibration appears to be the main source of uncertainties, and proper procedures must account for uncertainties in standard solutions as well as non linearity of the calibration curve. With such procedures, uncertainty and reproducibility of field measurement can be kept lower than 5% or 25 FAU. On the other hand, reproducibility has no meaning if different measuring principles (attenuation vs. nephelometry) or very different wavelengths are used., (IWA Publishing 2008.)

In urban drainage, stormwater quality models have been used by researchers and practitioners for more than 15 years. Most of them were initially developed for research purposes, and have been later on implemented in commercial software packages devoted to operational needs. This paper presents some epistemological problems and difficulties with practical consequences in the application of stormwater quality models, such as simplified representation of reality, scaling-up, over-parameterisation, transition from calibration to verification and prediction, etc. Two case studies (one to estimate pollutant loads at the outlet of a catchment, one to design a detention tank to reach a given pollutant interception efficiency), with simple and detailed stormwater quality models, illustrate some of the above problems. It is hard to find, if not impossible, an "optimum" or "best" unique set of parameters values. Model calibration and verification appear to dramatically depend on the data sets used for their calibration and verification. Compared to current practice, collecting more and reliable data is absolutely necessary.