Water Resources and Industry

This file contains the raw data from the EPPI reviewer software concerning methodologies employed to evaluate the sustainability of water use in industry.

Experimental data for paper "Capability evaluation of real-time inline COD detection technique for dynamic water footprint management in the beverage manufacturing industry". Data comprises UV-Vis absorption spectra, and chemical digestion COD measurements, on samples of wastewater taken from a beverage factory. Article abstract: This paper reports the development of a real-time inline Chemical Oxygen Demand (COD) detection technique in a beverage manufacturing plant in England and the evaluation of its capability for dynamic Water Footprint (WF) management. The inline technique employed Ultraviolet–Visible (UV-VIS) spectroscopy and Moving Window Partial Least Squares (mwPLS), which was then applied to calculating Grey WF for the production activities in the plant, referred to here as WFrt. A traditional offline COD measurement method was also utilised for the Grey WF calculation, to act as the reference method, referred to here as WFtrad. In a method-comparison study (Bland-Altman Plot), the results showed that WFrt detected the order of magnitude variation of WFtrad, and WFtrad was on average between 0.897 and 1.243 times WFrt with no systematic bias. This indicates that WFrt may be used for both short-time frame (minutes to hours) WF monitoring and long-term (weeks to months) analysis of trends and the effect of WF optimisation strategies.

Experimental data for paper "Capability evaluation of real-time inline COD detection technique for dynamic water footprint management in the beverage manufacturing industry". Data comprises UV-Vis absorption spectra, and chemical digestion COD measurements, on samples of wastewater taken from a beverage factory. Article abstract: This paper reports the development of a real-time inline Chemical Oxygen Demand (COD) detection technique in a beverage manufacturing plant in England and the evaluation of its capability for dynamic Water Footprint (WF) management. The inline technique employed Ultraviolet–Visible (UV-VIS) spectroscopy and Moving Window Partial Least Squares (mwPLS), which was then applied to calculating Grey WF for the production activities in the plant, referred to here as WFrt. A traditional offline COD measurement method was also utilised for the Grey WF calculation, to act as the reference method, referred to here as WFtrad. In a method-comparison study (Bland-Altman Plot), the results showed that WFrt detected the order of magnitude variation of WFtrad, and WFtrad was on average between 0.897 and 1.243 times WFrt with no systematic bias. This indicates that WFrt may be used for both short-time frame (minutes to hours) WF monitoring and long-term (weeks to months) analysis of trends and the effect of WF optimisation strategies.

Experimental data for paper "Capability evaluation of real-time inline COD detection technique for dynamic water footprint management in the beverage manufacturing industry". Data comprises UV-Vis absorption spectra, and chemical digestion COD measurements, on samples of wastewater taken from a beverage factory. Article abstract: This paper reports the development of a real-time inline Chemical Oxygen Demand (COD) detection technique in a beverage manufacturing plant in England and the evaluation of its capability for dynamic Water Footprint (WF) management. The inline technique employed Ultraviolet–Visible (UV-VIS) spectroscopy and Moving Window Partial Least Squares (mwPLS), which was then applied to calculating Grey WF for the production activities in the plant, referred to here as WFrt. A traditional offline COD measurement method was also utilised for the Grey WF calculation, to act as the reference method, referred to here as WFtrad. In a method-comparison study (Bland-Altman Plot), the results showed that WFrt detected the order of magnitude variation of WFtrad, and WFtrad was on average between 0.897 and 1.243 times WFrt with no systematic bias. This indicates that WFrt may be used for both short-time frame (minutes to hours) WF monitoring and long-term (weeks to months) analysis of trends and the effect of WF optimisation strategies.