To address the wide range of environmental problems, climate scientists must have the tools to accurately detect, measure, and analyze the substances that are often the source of most ecological issues.
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Although numerous microscopy tools have been used, their detection capabilities and capacity to distinguish between different chemical classes are often limited.
In recent years, Raman spectroscopy has emerged as a highly precise and unique tool capable of overcoming traditional microscopy techniques' common limitations to evaluate human activity's environmental impact. This article will explore Raman spectroscopy’s use in environmental science, as well as its applications, functionality, and impact.
What is Raman Spectroscopy?
Raman spectroscopy is a robust analytical technique that has emerged in the past decade as a key tool in many scientific fields. The technique is based on light scattering, and the specific scattered light measured is known as Raman Scattering, which is scattered at a different wavelength from the laser source. The scattering is indicative of the analyte’s chemical structure.
The spectrum produced by Raman scattering comprises several peaks that provide information on the scattered light’s wavelength position and intensity. The peaks correspond to chemical bonds such as C=C, C-H, and N-O bonds and groups of bonds such as lattice modes and benzene rings.1
The main advantage of Raman spectroscopy over other common analytical techniques, such as electron microscopy and gas chromatography, is its non-destructive nature. Other benefits include high sensitivity, minimal environmental footprint during analysis, and a lack of sample preparation.1,2
What are the Applications of Spectroscopy in Environmental Analysis?
Raman spectroscopy has emerged as a highly useful analytical technique with a wide range of applications in environmental science.
It can be used to detect environmental contaminants such as heavy metals and other ubiquitous toxic elements produced by industrial activities.2 This technique can detect air and water pollutants in real-time, providing a powerful addition to the environmental scientist’s analytical toolkit.
Raman spectroscopy can also be utilized in waste management applications to identify and categorize different types of plastic for recycling and monitor waste processing to improve efficiency.
Raman spectroscopy is pivotal in renewable energy research, particularly in analyzing batteries and solar cells to enhance their performance. It also contributes to biofuel production by examining catalytic processes. Additionally, this technique is employed in climate change studies to detect greenhouse gases in the atmosphere and investigate microplastics' environmental impact.
An emerging application for Raman spectroscopy combined with machine learning is its use to differentiate and fingerprint domestic sewage and landfill leachate. This advancement holds promise for enhancing waste treatment and remediation efforts within legacy waste management systems.3
Advantages of Raman Spectroscopy over Traditional Techniques
Raman spectroscopy offers a non-destructive advantage over traditional analytical methods in environmental science. Its lack of sample preparation requirements eliminates the need for harsh, potentially environmentally damaging chemicals.
Raman spectroscopy is also a highly sensitive analytical method that can easily differentiate between molecules and compounds within a sample. It can even differentiate chemical structures with atoms in different arrangements. It also provides real-time material diagnosis, saving time and increasing productivity. It is versatile across various states of matter.
Direct scanning saves time during analysis and the need for chemicals. Its non-destructive nature allows scientists to run samples multiple times. These same samples can even be used again in other tests.4
Its high precision and ability to detect relatively low quantities of analyte are also advantages in environmental monitoring, where there may be only traces of toxic chemicals that need to be detected. However, traditional Raman spectroscopy may not have a detection limit low enough for some environmental applications.
Surface Enhanced Raman Spectroscopy (SERS) is a technique with comparable sensitivity to mass spectrometry, another analytical technique that is widely applied in pollution monitoring. Mass spectrometry, however, is an expensive method that requires highly specialized experts to be used properly. SERS overcomes these limitations.2
Furthermore, environmental samples are typically complex, with several different compounds in varying concentrations, some of which can be extremely similar in composition and at minute levels. Differentiation capabilities mean that Raman spectroscopy can be used as part of the analytical toolkit for these types of samples.
What are the Limitations of Raman Spectroscopy?
There are, however, some challenges and limitations with this technique. Firstly, the Raman effect is typically weak, requiring highly sensitive and optimized equipment.
Secondly, impurities in the sample can cause inaccurate results. This is especially problematic in complex environmental samples, such as pollution. While Raman spectroscopy has good differentiation capabilities, they can be limited.
The lasers can cause issues with sample analysis through heating. This is caused by the intense laser radiation. In extreme cases, this can cover the Raman spectrum or destroy the sample.
Another barrier to adopting Raman spectroscopy in environmental laboratories is its relatively high initial cost and the need for specialized training to use the equipment. Laboratories may instead stick with more traditional and proven analytical techniques despite Raman spectroscopy’s potential benefits. This is especially true in smaller laboratories that may have limited budgets.
The technique also struggles with some complex samples, and spectral noise in Raman spectra can be an issue. While there are many challenges and limitations with Raman spectroscopy, some research and innovations have sought to overcome them and improve the technique’s performance.
Denoising algorithms can help avoid spectral noise. A recent research paper provides a systematic review of these algorithms and related applications.5
Other innovations, such as the use of AI and ML and the development of new techniques such as SERS, are helping researchers improve the suitability of Raman spectroscopy for environmental science and other scientific fields.
Future Prospects of Raman Spectroscopy
Artificial intelligence (AI) integration is a key innovation that could bring vast benefits to the field of Raman spectroscopy in the coming years. It would enhance the technique's capabilities along with related technologies such as machine learning and deep neural networks.
Another potential prospect is the development of portable Raman spectrometers that can be deployed in field studies. Drone-based spectrometers, which have already been researched for military applications, could also provide environmental scientists with powerful, portable analytical tools.6
In Summary
Raman spectroscopy is a powerful non-destructive analytical technique that can benefit environmental science in several applications, such as pollution monitoring, waste management, and sewage analysis. While challenges persist, research provides new innovations in this field that will make it more suitable for this crucial scientific application.
The versatility of Raman spectroscopy makes it an ideal part of the environmental scientist’s lab and field toolkit, but only continued innovation and research will help it reach its full potential in this area.
Read more about spectroscopy used in clean technology applications
References and Further Reading
- Horiba (2024) What is Raman Spectroscopy? [online] Available at: https://www.horiba.com/int/scientific/technologies/raman-imaging-and-spectroscopy/raman-spectroscopy/ (Accessed on 4 January 2025)
- Ong, T.T.X et al. (2020) Surface Enhanced Raman Spectroscopy in environmental analysis, monitoring and assessment Science of the Total Environment 720: 137601 [online] ScienceDirect. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0048969720311128 (Accessed on 4 January 2025)
- Wang, X et al. (2023) Fingerprinting and Differentiation of Landfill Leachate and Domestic Sewage in Surface Water with Machine Learning Based Surface Enhanced Raman Spectroscopy ACS ES&T Water 4:3 [online] ACS Publications. Available at: https://pubs.acs.org/doi/10.1021/acsestwater.3c00441 (Accessed on 4 January 2025)
- Pharmabeej (2024) Raman Spectroscopy Uses Advantages and Disadvantages [online] Pharmabeej.com. Available at: https://pharmabeej.com/raman-spectroscopy-uses-advantages-and-disadvantages/ (Accessed on 4 January 2025)
- Fang, S (2024) Recent progress and applications of Raman spectrum denoising algorithms in chemical and biological analyses: A review TrAC Trends in Analytical Chemistry 174: 117578 [online] ScienceDirect. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0165993624000608 (Accessed on 4 January 2025)
- Ren, W et al. (2023) An Unmanned Vehicle-Based Remote Raman System for Real-Time Trace Detection and Identification. Photonics 10(11) 1230 [online] MDPI. Available at: https://www.mdpi.com/2304-6732/10/11/1230 (Accessed on 4 January 2025)
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