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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Burnet, J.-B., Habash, M., Hachad, M., Khanafer, Z., Prévost, M., Servais, P., Sylvestre, É., & Dorner, S. (2021). Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality. Water, 13(15), 2069 (12 pages). Available
Hachad, M., Burnet, J.-B., Sylvestre, É., Duy, S. V., Villemur, R., Sauvé, S., Prévost, M., Qiu, J., Pang, X., & Dorner, S. (2024). β-D-glucuronidase activity triggered monitoring of fecal contamination using microbial and chemical source tracking markers at drinking water intakes. Water Research, 254, 121374 (10 pages). Available
Hachad, M., Yarahmadi, H., Vo Duy, S., Sauvé, S., Prévost, M., & Dorner, S. (2022). Occurrence and partitioning behavior of E. coli and wastewater micropollutants following rainfall events. Resources, Environment and Sustainability, 9, 100067. External link
Hachad, M., Lanoue, M., Duy, S. V., Villemur, R., Sauvé, S., Prévost, M., & Dorner, S. (2022). Locating illicit discharges in storm sewers in urban areas using multi-parameter source tracking: Field validation of a toolbox composite index to prioritize high risk areas. Science of The Total Environment, 811, 152060 (10 pages). External link
Hachad, M. (2021). Priorisation des sources de contamination fécale en milieu urbain : pertinence de l'utilisation de marqueurs moléculaires et chimiques comme traceurs de rejets d'eaux usées [Ph.D. thesis, Polytechnique Montréal]. Available
Hajj-Mohamad, M., Hachad, M., Deschamps, G., Sauvé, S., Villemur, R., Blais, M.-A., Prévost, M., & Dorner, S. (2019). Fecal contamination of storm sewers: Evaluating wastewater micropollutants, human-specific Bacteroides 16S rRNA, and mitochondrial DNA genetic markers as alternative indicators of sewer cross connections. Science of The Total Environment, 659, 548-560. External link
Jayme, G., Liu, J.-L., Gálvez, J. H., Reiling, S. J., Celikkol-Aydin, S., N’Guessan, A., Lee, S., Chen, S.-H., Tsitouras, A., Sánchez-Quete, F., Maere, T., Goitom, E., Hachad, M., Mercier, É., Loeb, S. K., Vanrolleghem, P. A., Dorner, S., Delatolla, R., Shapiro, B. J., ... Snutch, T. P. (2024). Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater. Viruses, 16(9), 1495 (15 pages). Available
Le Cauchois, P., Doucet, S., Bouattour, O., McQuaid, N., Beral, H., Kõiv-Vainik, M., Bichai, F., McCarthy, D., St-Laurent, J., Dagenais, D., Bennekrela, N., Guerra, J., Hachad, M., Kammoun, R., & Dorner, S. (2025). Full-scale characterization of the effects of a bioretention system on water quality and quantity following the replacement of a mixed stormwater and combined sewer system. Blue-Green Systems, 7(1), 43-62. External link
Nguyen, T. L., Hachad, M., McQuaid, N., Krylova, K., Nguyen, H. T. L., Visentin, F., Burnet, J.-B., Quete, F. S., Maere, T., Tsitouras, A., Vanrolleghem, P., Frigon, D., Loeb, S., Dorner, S., & Goitom, E. (2025). Hydrological and physicochemical parameters associated with SARS-CoV-2 and pepper mild mottle virus wastewater concentrations for a large-combined sewer system. Journal of Water and Health, 15 pages. External link
Sylvestre, É., Prévost, M., Burnet, J.-B., Pang, X., Qiu, Y., Smeets, P., Medema, G., Hachad, M., & Dorner, S. (2021). Demonstrating the reduction of enteric viruses by drinking water treatment during snowmelt episodes in urban areas. Water Research X, 11. External link
Sylvestre, É., Burnet, J.-B., Dorner, S., Smeets, P., Medema, G., Villion, M., Hachad, M., & Prévost, M. (2021). Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources. Risk Analysis, 41(8), 1413-1426. External link
Sylvestre, É., Prévost, M., Burnet, J.-B., Smeets, P., Medema, G., Hachad, M., & Dorner, S. (2021). Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants. Water Research, 200, 10 pages. External link
Yarahmadi, H., Duy, S. V., Hachad, M., Dorner, S., Sauve, S., & Prévost, M. (2018). Seasonal variations of steroid hormones released by wastewater treatment plants to river water and sediments: Distribution between particulate and dissolved phases. Science of The Total Environment, 635, 144-155. External link
