Abstract Title: | Handheld liquid chromatography for field-based analysis |
Presenter Name: | Dr Ali Salehi-Reyhani |
Company/Organisation: | Imperial College London |
Country: | United Kingdom |
Abstract Information :
Polycyclic aromatic hydrocarbons (PAHs) are considered priority hazardous substances due to their carcinogenic activity and risk to public health. Strict regulations are in place limiting their release into the environment, but enforcement is hampered by a lack of adequate field-testing procedure, instead relying on sending samples to centralised analytical facilities. Reliably monitoring levels of PAHs in the field is a challenge, owing to the lack of field-deployable analytical methods able to separate, identify, and quantify the complex mixtures in which PAHs are typically observed. We present efforts to develop a field-based approach to analyse a wide range of environmentally important PAHs, independent of centralised/lab-based facilities. We report the development of a hand portable HPLC instrument with a UV–vis spectral detector, providing an extra dimension to output data, with chromatographic performance and stability which compare favourably with a typical lab-based commercial instrument. We also demonstrate that the new capabilities offered by this instrument (3D time-resolved spectral data, rather than 2D single-wavelength absorbance data) may be exploited to analyse a chromatographically challenging mixture of PAHs. Analytes are identified based on their distinctive absorption spectra using a ‘fingerprinting’ approach which is independent of retention times. We also showed that the 3D data provided by our system allowed us to detect and characterise features that would otherwise remain hidden, using spectral deconvolution and chemometric approaches. We are able to identify 100% of the 24 PAHs tested, including full coverage of the United States Environmental Protection Agency priority pollutant list. We anticipate the platform to enable more sophisticated analytical measurements, supporting real-time decision making in the field.