Monitoring pollution and its impact on water quality using innovative tools
ECG Bulletin January 2024
Water quality monitoring traditionally relied on spot sampling and standard analytical techniques. But with engineering design, additive manufacturing, and multidisciplinary research teams, we can see the potential to move from the lab into the field. However, this takes time and requires testing and scaling prototypes to prove new technologies in areas of chemical and biosensing. We are at a critical time for investment in sensor development to improve and indeed change how we monitor water into the future and make better decisions on aquatic system protection.
Monitoring water quality is driven by legislation, such as the Water Framework Directive (WFD)[1] in Europe, the Clean Water Act[2] in Canada, the Australian Water Act [3] and the US Clean Water Act[4] in the United States. To obtain more information about water quality, monitoring and sampling must be carried out frequently. Continuous monitoring can overcome the problem of frequency by providing long-term measurement, sampling and collection of data[5].
A number of aquatic systems are dependent on the quality of the water for survival[6]. A wide range of sensors exist for water monitoring which allow both in situ and on site operation. Portable test units or instruments can complement or validate data for in situ sensors or are used to provide spatial resolution. Such instruments can provide information on pollution source tracking and screening of water samples, and are available for biological or chemical parameters[7,8]. However, they fail in terms of being able to provide
data at sufficient temporal frequency.
A number of aquatic systems are dependent on the quality of the water for survival[6]. A wide range of sensors exist for water monitoring which allow both in situ and on site operation. Portable test units or instruments can complement or validate data for in situ sensors or are used to provide spatial resolution. Such instruments can provide information on pollution source tracking and screening of water samples, and are available for biological or chemical parameters[7,8]. However, they fail in terms of being able to provide
data at sufficient temporal frequency.
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Autonomous sensors can provide real-time or near-real- time data (Figure 1) at good temporal frequency, facilitating decision support in a timely fashion.
Sensors can provide extensive baseline data and an improved understanding of water quality changes and trends over time and space. These, what we call, off-the- shelf sensors can provide valuable data but are generally non-specific for target analytes of interest. Taking an assay from the laboratory to the field requires years of development and rigorous validation. |
Figure 1. A real-time dataset from autonomous sensors measuring turbidity, temperature, salinity and water depth.
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There are some great examples in the literature of chemical assays used in portable or hand-held sensors technologies. Figure 2 shows an example of a phosphate analyser based on the blue method, developed for phosphate determination in a catchment in an agricultural area.
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Future digital challenge for water
With in situ – autonomous sensing becoming increasingly used, technological development in the field is moving forward swiftly with a growth in optical sensors. These sensors work on principles of fluorescence, scatter and absorption with low to affordable capital and operational costs, extended life-time, and increasing availability for a wide range of parameters. Wet-chemistry based sensors are used traditionally where analytical precision and accuracy is required and currently where no alternative sensors exist (i.e. nutrient or metal speciation) while multiparameter sensors still remain the go-to for environmental applications. The trend is likely where we will see lower cost sensors, increasingly specialised and easier to integrate and maintain. In this time of data-driven models, increased volumes of data and its availability from in situ and remote sensors is needed for the development of novel artificial intelligence (AI) and machine learning (ML) methods, which in turn will provide novel models and data treatment algorithms. |
Figure 2. Demonstrating the portable phosphate analyser which uses centrifugal microfluidics, in a
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Growing climate- related events
With increasing environmental pressure due to global climate change, increases in global population and the need for sustainable obtained resources, water resources management is critical.
Water monitoring networks and their designs are fundamental to the management of catchment/ watershed systems and are the first step in providing decision support to stakeholders.
To be fit-for-purpose, monitoring has to be carried out in a cost-effective way and allow implementation at larger spatial scales.
Rapid developments of in situ water quality monitoring instrumentation and remote sensing (aerial and satellite) have the potential to drive progress towards more cost- effective sensor networks at catchment scale. However, a significant expansion in research and development in chemical and biosensing capability Is needed before we see the transformation needed in moving from the laboratory to the field. This kind of transformation is needed if we are to meet a Zero Pollution goal in this decade.
With increasing environmental pressure due to global climate change, increases in global population and the need for sustainable obtained resources, water resources management is critical.
Water monitoring networks and their designs are fundamental to the management of catchment/ watershed systems and are the first step in providing decision support to stakeholders.
To be fit-for-purpose, monitoring has to be carried out in a cost-effective way and allow implementation at larger spatial scales.
Rapid developments of in situ water quality monitoring instrumentation and remote sensing (aerial and satellite) have the potential to drive progress towards more cost- effective sensor networks at catchment scale. However, a significant expansion in research and development in chemical and biosensing capability Is needed before we see the transformation needed in moving from the laboratory to the field. This kind of transformation is needed if we are to meet a Zero Pollution goal in this decade.
References
- L. Carvalho, E. B. Mackay, A. C. Cardoso, A. Baattrup-Pedersen, S. Birk, K. L. Blackstock, G. Borics, A. Borja, C. K. Feld, M. T. Ferreira, L. Globevnik, B. Grizzetti, S. Hendry, D. Hering, M. Kelly, S. Langaas, K. Meissner, Y. Panagopoulos, E. Penning, J. Rouillard, S. Sabater, U. Schmedtje, B. M. Spears, M. Venohr, W. van de Bund and A. L. Solheim, Science of The Total Environment, 2019, 658 , 1228 – 1238 . https://doi.org/10.1016/ j.scitotenv.2018.12.255.
- L. Collins, D. McGregor, S. Allen, C. Murray and C. Metcalfe, Water (Basel), 2017, 9, 550. https://doi.org/ 10.3390/w9070550.
- M. Papas, Water (Basel), 2018, 10, 1649.https:// doi.org/10.3390/w10111649.
- D. A. Keiser and J. S. Shapiro, Q. J. Econ., 2019, 134, 349–396. https://doi.org/10.1093/qje/qjy019.
- D. V. Chapman, C. Bradley, G. M. Gettel, I. G. Hatvani, T. Hein, J. Kovács, I. Liska, D. M. Oliver, P. Tanos, B. Trásy and G. Várbíró, Environ Sci. Policy, 2016, 64, 141–154.
- G. S. Bilotta and R. E. Brazier, Water Res, 2008, 42, 2849–2861. https://doi.org/ 10.1016/j.watres.2008.03.018.
- C. Toth and G. Jóźków, I S P R S J o u r n a l o f Photogrammetry and Remote Sensing, 2016, 115, 22–36.
- https://doi.org/10.1016/j.isprsjprs.2015.10.004.
B. Heery, C. Briciu-Burghina, D. Zhang, G. Duffy, D. Brabazon, N. O’Connor and F. Regan, Talanta, 2016, 148, 7 5 – 8 3 . https://doi.org/10.1016/ j.talanta.2015.10.035.
