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Wastewater treatment is a serious environmental and economic challenge. The infrastructure involved in water treatment is often costly, with utility companies in England and Wales investing over £2.1 billion in 2013 and 2014 alone to ensure safe drinking water1, with the total energy consumption of wastewater treatment over 30 terawatt-hours a year across the US.2
Part of the challenge and costs associated with wastewater treatment are not just electricity consumption, but the complexity of the treatment process itself. Wastewater can contain contaminants from many different sources, making it challenging to find general solutions for contaminant identification and removal.
Typical contaminants include inorganic sources, such as carbon dioxide and carbonic acid salts3, particular matter and debris, and even hydrocarbon species, particularly if the wastewater comes from water used in oil refinement.
Ideally, a wastewater plant needs rapid online analysis, capable of continually monitoring a wide range of physical and chemical species to make eco-friendly wastewater. Any analytical device needs to be capable of detecting even small concentrations of pollutants, as certain chemical species can be devastating for human health or the environment in even trace quantities.
HYDROPTICS Project
To address the need for pervasive and online water quality monitoring, the HYDROPTICS project was established as part of the European Union’s Horizon 2020 project.4
Consisting of 10 project partners, led by the Switzerland-based Alpes Lasers, the HYDROOPTICS project started in 2019 to make a device capable of monitoring water quality as part of the oil refinement process as a way of increasing the competitiveness of the EU oil industry sector.5
At present, the EU has a crude oil refining capacity of more than 15 million barrels a day, but there is a constant need for process refinement and improvements in efficiency.
Water quality is an essential part of this, both in terms of maximizing the efficiency of the refinement process and limiting the ecological damage that oil-contaminated wastewater could cause. The risks posed by potentially contaminated water leaks from oil refineries means there is strict legislation concerning the content of wastewater from plants, with careful monitoring of the chemical species and other contaminants present.6
With the aim of having a prototype ready by 2023, the consortium is drawing on advances in hyperspectral imaging and mid-IR lasers to make rapid and highly sensitive analysis a possibility.
Quantum Cascade Lasers
At the heart of the proposed HYDROPTICS device for the detection of oil-in-water, is a quantum cascade laser that Alpes Lasers specializes in. Quantum cascade lasers (QCLs) use particular types of semiconductor materials as the gain medium and typically emit in the mid-infrared to terahertz region of the electromagnetic spectrum.
QCLs are typically very robust lasers, and their emission wavelength is tuned by varying the number of semiconductor layers in the active medium, unlike standard diode lasers where the bandgap of the semiconductor material dictates the emission wavelength.
Alpes Lasers has developed a way of using QCLs and their excellent mid-IR emission to produce frequency combs from the laser, rather than a narrow emission bandwidth.
Frequency combs have spectra consisting of discrete, equally spaced lines that can span an extensive bandwidth range. They have been commonly employed in metrology measurements and for rapid molecular sensing, with chip-based devices now capable of performing real-time measurements.7
The HYDROPTICS team intends to exploit the unique properties of using two QCL frequency combs as part of a hyperspectral imaging scheme, where a full range of spectra frequencies is recorded for detection of the unique fingerprints of oil components in water.
The use of two lasers, rather than a single one, has already made it possible to identify the oil content in water in minutes, rather than hours using reference samples.
Find out more about lasers available on the market today
Process Optimization
However, for maximal process optimization, detection alone is not enough. There needs to be a feedback system involved, where the recorded information from the spectrometer is integrated with automated process control. Alpes Lasers and the HYDROPTICS team are also working on machine learning methods to do just that more effectively as part of the ultra-sensitive sensor and laser systems in the device being developed.
The idea is to use artificial intelligence to improve the detection rate of the device, which will be continually sampling the wastewater. There is no need for additional sample preparation as the device can be deployed online. Hyperspectral imaging is used, where each pixel on the detector contains not just spatial information but full spectral imaging as well. This means there is a considerable amount of sample information collected, which is then automatically processed using machine learning methods.
The machine learning algorithm should be continually optimized while the device is regularly collecting new data.
Eco-Friendly Wastewater
The team is confident that the device is not just useful for the oil refinement and wastewater industries, but will instead offer a significant improvement in the molecular detection in liquids and gases. This can be applied to other systems such as food analysis and quality control.
By bringing together experts in the development of QCLs at Alpes Lasers and partners in industrial oil refineries, the HYDROPTICS device has a vital role to play in ensuring contaminated wastewater is made safe and eco-friendly.
References and Further Reading
- UK Government (2019), Water and Treated Water https://www.gov.uk/government/publications/water-and-treated-water/water-and-treated-water (accessed 16 August 2020)
- Water Research Foundation (2013) Electricity Use and Management in the Municipal Water Supply and Wastewater Industries, https://www.sciencetheearth.com/uploads/2/4/6/5/24658156/electricity_use_and_management_in_the_municipal_water_supply_and_wastewater_industries.pdf, (accessed 16 August 2020)
- Volk, C., Wood, L., Johnson, B., Robinson, J., Zhu, H. W., & Kaplan, L. (2002). Monitoring dissolved organic carbon in surface and drinking waters. Journal of Environmental Monitoring, 4(1), 43–47. https://doi.org/10.1039/b107768f
- Alpes Lasers (2020) HYDROOPTICS, https://www.alpeslasers.ch/?a=36,154,199, (accessed 16 August 2020)
- HYDROPTICS (2020) HYDROPTICS, https://hydroptics.eu/ (accessed 16 August 2020)
- Mike Spence (2015) Water Use and Trends in emission to water from EU refineries, https://www.concawe.eu/wp-content/uploads/2017/01/3_FINAL_Concawe-symposium-water-use-and-effluent-trends-20-02-15.pdf, (accessed 16 August 2020)
- Picqué, N., & Hänsch, T. W. (2019). Frequency comb spectroscopy. Nature Photonics, 13(3), 146–157. https://doi.org/10.1038/s41566-018-0347-5
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