Multivariate Monitoring of Surface Water Quality: Physico-Chemical, Microbiological and 3D Fluorescence Characterization

Abstract

The primary objective of this study is to explore a water quality database on two Mediterranean rivers (the Kadisha-Abou Ali and El Jaouz rivers—located in north Lebanon), considering their physicochemical, microbiological and fluorescence characteristics. Principal Component Analysis (PCA) was applied to the matrix gathering physicochemical and microbiological data while the Common Components and Specific Weight Analysis (CCSWA) or ComDim was used for fluorescence excitation-emission matrices (EEMs). This approach provided complementary and valuable information regarding water quality in such complex ecosystem. As highlighted by the PCA and ComDim scores, the Kadisha-Abou Ali River is highly influenced by anthropogenic activities because its watershed districts are intensively populated. This influence reveals the implication of organic and bacteriological parameters. To the contrary, the El Jaouz watershed is less inhabited and is characterized by mineral parameters, which determines its water quality. This work highlighted the relationship between fluorescence EEMs and major water quality parameters, enabling the selection of reliable water quality indicators for the studied rivers. The proposed methodology can surely be generalized to the monitoring of surface water quality in other rivers. Each customized water quality fingerprint should constantly be inspected in order to account for any emerging pollution.

Parasitic Contamination of Fresh Leafy Green Vegetables Sold in Northern Lebanon

“…and Staphylococcus aureus [ 8 , 34 , 36 ]. Importantly, the Kadisha-Abou Ali River situated in North Lebanon has been deemed one of the most heavily contaminated rivers in Lebanon, primarily due to human activities [ 37 , 38 ]. The water quality of this river has been reported to be at its worst in the Tripoli district, with pollution accumulation from the upstream flow exacerbated by local wastewater discharge [ 39 ].…”

Chemometrics-driven monitoring of cheese ripening: a multimodal spectroscopic and scanning electron microscopy investigation

“…Typically, 3D uorescence datasets are usually processed using multi-way methods such as PARAFAC or Tucker3 models. 31 Despite this, ComDim is still underutilized for multi-way datasets analysis, though it has shown promise in the analysis of 3D front face uorescence datasets in studies by Karoui et al 32 and Daou et al 33 Preliminary trials demonstrate that ComDim outperformed PARAFAC in discriminating between cheese group ages, leading to its selection for processing the 3D uorescence datasets.…”