Andrés Torres

Partial Least Squares local calibration of a UV-visible spectrometer used for in situ measurements of COD and TSS concentrations in urban drainage systems.

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.

The Ecological Dynamics of Fecal Contamination and Salmonella Typhi and Salmonella Paratyphi A in Municipal Kathmandu Drinking Water

One of the UN sustainable development goals is to achieve universal access to safe and affordable drinking water by 2030. It is locations like Kathmandu, Nepal, a densely populated city in South Asia with endemic typhoid fever, where this goal is most pertinent. Aiming to understand the public health implications of water quality in Kathmandu we subjected weekly water samples from 10 sources for one year to a range of chemical and bacteriological analyses. We additionally aimed to detect the etiological agents of typhoid fever and longitudinally assess microbial diversity by 16S rRNA gene surveying. We found that the majority of water sources exhibited chemical and bacterial contamination exceeding WHO guidelines. Further analysis of the chemical and bacterial data indicated site-specific pollution, symptomatic of highly localized fecal contamination. Rainfall was found to be a key driver of this fecal contamination, correlating with nitrates and evidence of S. Typhi and S. Paratyphi A, for which DNA was detectable in 333 (77%) and 303 (70%) of 432 water samples, respectively. 16S rRNA gene surveying outlined a spectrum of fecal bacteria in the contaminated water, forming complex communities again displaying location-specific temporal signatures. Our data signify that the municipal water in Kathmandu is a predominant vehicle for the transmission of S. Typhi and S. Paratyphi A. This study represents the first extensive spatiotemporal investigation of water pollution in an endemic typhoid fever setting and implicates highly localized human waste as the major contributor to poor water quality in the Kathmandu Valley.

Benefits, limitations and uncertainty of in situ spectrometry

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.

Evaluation of uncertainties in settling velocities of particles in urban stormwater runoff.

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%.

Calibration of UV/Vis spectrophotometers: A review and comparison of different methods to estimate TSS and total and dissolved COD concentrations in sewers, WWTPs and rivers.

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.

Influence of Local Calibration on the Quality of Online Wet Weather Discharge Monitoring: Feedback From Five International Case Studies

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.

Method for outlier detection: a tool to assess the consistency between laboratory data and ultraviolet–visible absorbance spectra in wastewater samples

Reliable estimations of the evolution of water quality parameters by using in situ technologies make it possible to follow the operation of a wastewater treatment plant (WWTP), as well as improving the understanding and control of the operation, especially in the detection of disturbances. However, ultraviolet (UV)-Vis sensors have to be calibrated by means of a local fingerprint laboratory reference concentration-value data-set. The detection of outliers in these data-sets is therefore important. This paper presents a method for detecting outliers in UV-Vis absorbances coupled to water quality reference laboratory concentrations for samples used for calibration purposes. Application to samples from the influent of the San Fernando WWTP (Medellín, Colombia) is shown. After the removal of outliers, improvements in the predictability of the influent concentrations using absorbance spectra were found.

The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study

The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

Quality of Rainwater Runoff on Roofs and Its Relation to Uses and Rain Characteristics in the Villa Alexandra and Acacias Neighborhoods of Kennedy, Bogota, Colombia

AbstractIn Colombia, several communities with limited or uncertain access to drinking water services collect rainwater for various domestic uses. This paper presents the results of a water quality analysis of the rainwater runoff from roofs in Kennedy (Bogota) to evaluate the suitability of adapting this water to satisfy domestic uses in this district. Based on the high values of turbidity and biochemical oxygen demand, and on the high concentrations of total suspended solids and heavy metals found in the studied rainwater, it is concluded that the water samples are not suitable for any of the domestic uses currently employed by the citizenry. Nevertheless, a high spatial and temporal variability was detected, in addition to variability as a function of the roof material. In particular cases, the runoff water from roofs may be adapted as an alternative source for domestic uses in the district.

HERRAMIENTA DE ANÁLISIS MULTI-CRITERIO COMO SOPORTE PARA EL DISEÑO DEL PROGRAMA SOCIAL DE LA FACULTAD DE INGENIERÍA

El objetivo de esta investigacion es desarrollar una herramienta para el Analisis Multi-Criterio como soporte para la seleccion de la comunidad objetivo del Programa Social de la Facultad de Ingenieria (PROSOFI) de la Pontificia Universidad Javeriana de Bogota (Colombia). Esta herramienta utiliza el Analisis Multi-Criterio (AMC), el cual se basa en modelos de decision que contienen diferentes posibles soluciones. Para la evaluacion de cada una de las alternativas (diecinueve localidades y dos municipios) se propusieron siete criterios: ubicacion geografica, presencia previa en la comunidad, necesidades basicas insatisfechas, apoyo de instituciones, marginalidad, organizaciones sociales y elementos culturales. Las alternativas y los factores de ponderacion se definieron a partir de un trabajo participativo de la Facultad. Los resultados indican que las comunidades con mayor opcion son Usme y Ciudad Bolivar.