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

2008 ◽  
Vol 57 (4) ◽  
pp. 581-588 ◽  
Author(s):  
A. Torres ◽  
J.-L. Bertrand-Krajewski
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Urban Drainage ◽  
Local Calibration ◽  
Data Set ◽  
Drainage Systems ◽  
Calibration Methods ◽  
Urban Drainage Systems ◽  
Uv Visible

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.

scholarly journals Portable XRF Quick-Scan Mapping for Potential Toxic Elements Pollutants in Sustainable Urban Drainage Systems: A Methodological Approach

Sci ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 46
Author(s):  
Guri Venvik ◽  
Floris C. Boogaard
Keyword(s):  
Green Infrastructure ◽  
Urban Areas ◽  
Toxic Elements ◽  
Urban Drainage ◽  
Runoff Water ◽  
Portable Xrf ◽  
Potential Toxic Elements ◽  
Drainage Systems ◽  
Urban Drainage Systems

Sustainable urban drainage systems (SuDS) such as swales are designed to collect, store and infiltrate a large amount of surface runoff water during heavy rainfall. Stormwater is known to transport pollutants, such as particle-bound Potential Toxic Elements (PTE), which are known to often accumulate in the topsoil. A portable XRF instrument (pXRF) is used to provide in situ spatial characterization of soil pollutants, specifically lead (Pb), zink (Zn) and copper (Cu). The method uses pXRF measurements of PTE along profiles with set intervals (1 meter) to cover the swale with cross-sections, across the inlet, the deepest point and the outlet. Soil samples are collected, and the In-Situ measurements are verified by the results from laboratory analyses. Stormwater is here shown to be the transporting media for the pollutants, so it is of importance to investigate areas most prone to flooding and infiltration. This quick scan method is time and cost-efficient, easy to execute and the results are comparable to any known (inter)national threshold criteria for polluted soils. The results are of great importance for all stakeholders in cities that are involved in climate adaptation and implementing green infrastructure in urban areas. However, too little is still known about the long-term functioning of the soil-based SuDS facilities.

scholarly journals Portable XRF Quick-Scan Mapping for Potential Toxic Elements Pollutants in Sustainable urban Drainage Systems: A Methodological Approach

Sci ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 34
Author(s):  
Guri Venvik ◽  
Floris C. Boogaard
Keyword(s):  
Green Infrastructure ◽  
Urban Areas ◽  
Toxic Elements ◽  
Urban Drainage ◽  
Runoff Water ◽  
Portable Xrf ◽  
Potential Toxic Elements ◽  
Drainage Systems ◽  
Urban Drainage Systems

Sustainable urban drainage systems (SuDS) such as swales are designed to collect, store and infiltrate a large amount of surface runoff water during heavy rainfall. Stormwater is known to transport pollutants, such as particle-bound Potential Toxic Elements (PTE), which are known to often accumulate in the topsoil. A portable XRF instrument (pXRF) is used to provide in situ spatial characterization of soil pollutants, specifically lead (Pb), zink (Zn) and copper (Cu). The method uses pXRF measurements of PTE along profiles with set intervals (1 m) to cover the swale with cross-sections, across the inlet, the deepest point and the outlet. Soil samples are collected, and the In-Situ measurements are verified by the results from laboratory analyses. Stormwater is here shown to be the transporting media for the pollutants, so it is of importance to investigate areas most prone to flooding and infiltration. This quick scan method is time and cost-efficient, easy to execute and the results are comparable to any known (inter)national threshold criteria for polluted soils. The results are of great importance for all stakeholders in cities that are involved in climate adaptation and implementing green infrastructure in urban areas. However, too little is still known about the long-term functioning of the soil-based SuDS facilities.

A Calibration Tutorial for Spectral Data. Part 2. Partial Least Squares Regression Using Matlab and Some Neural Network Results

1996 ◽  
Vol 4 (1) ◽  
pp. 243-255 ◽  
Author(s):  
Paul Geladi ◽  
Harald Martens ◽  
Lubomir Hadjiiski ◽  
Philip Hopke
Keyword(s):  
Neural Network ◽  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variable ◽  
Degree Of Approximation ◽  
Successive Approximations ◽  
Data Set ◽  
Calibration Methods ◽  
Data Pretreatment ◽  
Latent Variable Regression

Part 1 explained multiplicative scatter correction (MSC), the building of a principal component regression (PCR) model and how the test data can be used in prediction. Emphasis was on data pretreatment for linearistion and on spectral/chemical interpretation of the results. Part 2 discusses partial least squares (PLS or PLSR) regression. The data set prepared in Part 1 is also used here. Details on data pretreatment are, therefore, not repeated. Some details of PLS modeling are explained using the calculations of the example. Also, the interpretation of the PLS model gets some attention. Neural network calculation results are included for comparison. Artifical neural networks (ANN) are non-linear, so linearisation is not considered necessary. Latent variable regression methods such as PLS and PCR and ANNs are all successive approximations to the unknown function y = f(x) that forms the basis of all calibration methods. In latent variable regression, the rank of the model determines the degree of approximation. In ANNs, the number of hidden nodes and the number of iterations determine the degree of approximation.

scholarly journals Portable XRF Quick-Scan Mapping for Potential Toxic Elements Pollutants in Sustainable urban Drainage Systems: A Methodological Approach

Sci ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 21 ◽  
Author(s):  
Guri Venvik ◽  
Floris C. Boogaard
Keyword(s):  
Green Infrastructure ◽  
Urban Areas ◽  
Toxic Elements ◽  
Urban Drainage ◽  
Runoff Water ◽  
Portable Xrf ◽  
Potential Toxic Elements ◽  
Drainage Systems ◽  
Urban Drainage Systems

Sustainable urban drainage systems (SuDS) such as swales are designed to collect, store and infiltrate a large amount of surface runoff water during heavy rainfall. Stormwater is known to transport pollutants, such as particle-bound Potential Toxic Elements (PTE), which are known to often accumulate in the topsoil. A portable XRF instrument (pXRF) is used to provide in situ spatial characterization of soil pollutants, specifically lead (Pb), zink (Zn) and copper (Cu). The method uses pXRF measurements of PTE along profiles with set intervals (1 m) to cover the swale with cross-sections, across the inlet, the deepest point and the outlet. Soil samples are collected, and the In-Situ measurements are verified by the results from laboratory analyses. Stormwater is here shown to be the transporting media for the pollutants, so it is of importance to investigate areas most prone to flooding and infiltration. This quick scan method is time and cost-efficient, easy to execute and the results are comparable to any known (inter)national threshold criteria for polluted soils. The results are of great importance for all stakeholders in cities that are involved in climate adaptation and implementing green infrastructure in urban areas. However, too little is still known about the long-term functioning of the soil-based SuDS facilities.

scholarly journals Portable XRF Quick-Scan Mapping for Potential Toxic Elements Pollutants in Sustainable Urban Drainage Systems: A Methodological Approach

Sci ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 64
Author(s):  
Guri Venvik ◽  
Floris C. Boogaard
Keyword(s):  
Green Infrastructure ◽  
Urban Areas ◽  
Toxic Elements ◽  
Urban Drainage ◽  
Runoff Water ◽  
Portable Xrf ◽  
Potential Toxic Elements ◽  
Drainage Systems ◽  
Urban Drainage Systems

Sustainable urban drainage systems (SuDS) such as swales are designed to collect, store and infiltrate a large amount of surface runoff water during heavy rainfall. Stormwater is known to transport pollutants, such as particle-bound Potential Toxic Elements (PTE), which are known to often accumulate in the topsoil. A portable XRF instrument (pXRF) is used to provide in situ spatial characterization of soil pollutants, specifically lead (Pb), zink (Zn) and copper (Cu). The method uses pXRF measurements of PTE along profiles with set intervals (1 m) to cover the swale with cross-sections, across the inlet, the deepest point and the outlet. Soil samples are collected, and the In-Situ measurements are verified by the results from laboratory analyses. Stormwater is here shown to be the transporting media for the pollutants, so it is of importance to investigate areas most prone to flooding and infiltration. This quick scan method is time and cost-efficient, easy to execute and the results are comparable to any known (inter)national threshold criteria for polluted soils. The results are of great importance for all stakeholders in cities that are involved in climate adaptation and implementing green infrastructure in urban areas. However, too little is still known about the long-term functioning of the soil-based SuDS facilities.

scholarly journals The Bellinge data set: open data and models for community-wide urban drainage systems research

2021 ◽  
Author(s):  
Agnethe Nedergaard Pedersen ◽  
Jonas Wied Pedersen ◽  
Antonio Vigueras-Rodriguez ◽  
Annette Brink-Kjær ◽  
Morten Borup ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Open Data ◽  
Drainage System ◽  
Simulation Models ◽  
Urban Drainage ◽  
Data Set ◽  
Urban Drainage System ◽  
Drainage Systems ◽  
Systems Research ◽  
Urban Drainage Systems

Abstract. This paper describes a comprehensive and unique open-access data set for research within hydrological and hydraulic modelling of urban drainage systems. The data comes from a mainly combined urban drainage system covering a 1.7 km2 area in the town of Bellinge, a suburb to the city of Odense, Denmark. The data set consists of up to 10 years of observations (2010–2020) from 13 level meters, one flow meter, one position-sensor and four power sensors in the system, along with rainfall data from three rain gauges and two weather radars (X- and C-band), and meteorological data from a nearby weather station. The system characteristics of the urban drainage system (information about manholes, pipes etc.) can be found in the data set along with characteristics of the surface area (contour lines etc.). Two detailed hydrodynamic, distributed urban drainage models of the system are provided in the software systems Mike Urban and EPA SWMM. The two simulation models generally show similar responses, but systematic differences are present since the models have not been calibrated. With this data set we provide a useful case that enables independent testing and replication of results from future scientific developments and innovation within urban hydrology and urban drainage system research. The data set can be downloaded from https://doi.org/10.11583/DTU.c.5029124, (Pedersen et al., 2021a). 

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