Fernando Valero

1.3k total citations
41 papers, 968 citations indexed

About

Fernando Valero is a scholar working on Water Science and Technology, Health, Toxicology and Mutagenesis and Biomedical Engineering. According to data from OpenAlex, Fernando Valero has authored 41 papers receiving a total of 968 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Water Science and Technology, 13 papers in Health, Toxicology and Mutagenesis and 7 papers in Biomedical Engineering. Recurrent topics in Fernando Valero's work include Water Treatment and Disinfection (12 papers), Membrane Separation Technologies (7 papers) and Membrane-based Ion Separation Techniques (6 papers). Fernando Valero is often cited by papers focused on Water Treatment and Disinfection (12 papers), Membrane Separation Technologies (7 papers) and Membrane-based Ion Separation Techniques (6 papers). Fernando Valero collaborates with scholars based in Spain, United States and Denmark. Fernando Valero's co-authors include F. Lucena, Cristina Postigo, Juan Jofre, José Luis Cortina, C. Aladjem, E. Larrotcha, Sandra Casas, Mónica Reig, Maite Muniesa and J. Jofre and has published in prestigious journals such as The Science of The Total Environment, Water Research and Journal of Hazardous Materials.

In The Last Decade

Fernando Valero

37 papers receiving 939 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fernando Valero Spain 16 445 252 241 149 135 41 968
Maria Petala Greece 20 271 0.6× 305 1.2× 232 1.0× 158 1.1× 321 2.4× 50 1.1k
Saad Jasim Canada 19 609 1.4× 251 1.0× 256 1.1× 172 1.2× 349 2.6× 33 1.1k
Emmanuel Van Houtte Belgium 15 415 0.9× 146 0.6× 180 0.7× 169 1.1× 164 1.2× 25 870
Wolfgang Uhl Germany 20 495 1.1× 381 1.5× 204 0.8× 174 1.2× 225 1.7× 57 966
Bradley M. Coffey United States 14 422 0.9× 387 1.5× 145 0.6× 137 0.9× 148 1.1× 17 769
Liv Fiksdal Norway 15 507 1.1× 224 0.9× 317 1.3× 86 0.6× 121 0.9× 22 1.0k
Christoph Koch Germany 18 349 0.8× 362 1.4× 66 0.3× 113 0.8× 184 1.4× 25 1.1k
Shane Rogers United States 20 185 0.4× 178 0.7× 155 0.6× 110 0.7× 188 1.4× 37 915
Xuan Guo China 22 356 0.8× 148 0.6× 169 0.7× 269 1.8× 471 3.5× 88 1.5k
Santanu Mukherjee India 23 385 0.9× 161 0.6× 189 0.8× 225 1.5× 433 3.2× 61 1.4k

Countries citing papers authored by Fernando Valero

Since Specialization
Citations

This map shows the geographic impact of Fernando Valero's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fernando Valero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Valero more than expected).

Fields of papers citing papers by Fernando Valero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Valero. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fernando Valero. The network helps show where Fernando Valero may publish in the future.

Co-authorship network of co-authors of Fernando Valero

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Valero. A scholar is included among the top collaborators of Fernando Valero based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fernando Valero. Fernando Valero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aguilera, Esteban, et al.. (2025). Beyond point predictions: Quantifying uncertainty in E. coli ML-based monitoring. Journal of Water Process Engineering. 78. 108734–108734.
2.
Cabrera‐Codony, Alba, et al.. (2024). In-depth analysis of natural organic matter fractions in drinking water treatment performance: Fate and role of humic substances in trihalomethanes formation potential. The Science of The Total Environment. 954. 176600–176600. 4 indexed citations
3.
Daunis‐i‐Estadella, Pepus, et al.. (2022). NOM fractionation by HPSEC-DAD-OCD for predicting trihalomethane disinfection by-product formation potential in full-scale drinking water treatment plants. Water Research. 227. 119314–119314. 7 indexed citations
4.
Valero, Fernando. (2022). La gestión de la pandemia de COVID-19 en las residencias geriátricas de Cataluña. Vacunas. 23(2). 77–88. 2 indexed citations
5.
Expósito, Nora, et al.. (2022). Screening of microplastics in water and sludge lines of a drinking water treatment plant in Catalonia, Spain. Water Research. 225. 119185–119185. 46 indexed citations
6.
Rodríguez, José Javier, et al.. (2020). Control of primary disinfection in a drinking water treatment plant based on a fuzzy inference system. Process Safety and Environmental Protection. 145. 63–70. 23 indexed citations
7.
Gracenea, Mercedes, et al.. (2020). Assessment of dead-end ultrafiltration for the detection and quantification of microbial indicators and pathogens in the drinking water treatment processes. International Journal of Hygiene and Environmental Health. 230. 113628–113628. 11 indexed citations
8.
Poch, Manel, et al.. (2020). Benchmarking empirical models for THMs formation in drinking water systems: An application for decision support in Barcelona, Spain. The Science of The Total Environment. 763. 144197–144197. 16 indexed citations
9.
Postigo, Cristina, et al.. (2018). Chemical characterization and relative toxicity assessment of disinfection byproduct mixtures in a large drinking water supply network. Journal of Hazardous Materials. 359. 166–173. 61 indexed citations
10.
Cortina, José Luis, et al.. (2014). Flavour assessment of blends between desalinated and conventionally treated sources. Desalination and Water Treatment. 53(13). 3466–3474. 7 indexed citations
11.
Valero, Fernando, et al.. (2013). Estudio de la incidencia de listeriosis en España. Gaceta Sanitaria. 28(1). 74–76. 9 indexed citations
12.
Valero, Fernando. (2009). En busca del origen de los farmacéuticos titulares. Gaceta Sanitaria. 23(1). 72–75.
13.
Valero, Fernando, et al.. (2007). Estudio de las torres de refrigeración asociadas a brotes comunitarios de legionelosis. Gaceta Sanitaria. 21(4). 357–360. 1 indexed citations
14.
15.
Valero, Fernando, et al.. (2005). Occurrence of Cryptosporidium spp. oocysts in raw and treated sewage and river water in north-eastern Spain. Journal of Applied Microbiology. 99(6). 1455–1462. 71 indexed citations
16.
Fernández-Turiel, J. L., et al.. (2003). Spatial and Seasonal Variations of Water Quality in a Mediterranean Catchment: The Llobregat River (NE Spain). Environmental Geochemistry and Health. 25(4). 453–474. 37 indexed citations
17.
Muniesa, Maite, et al.. (2002). Removal and inactivation of indicator bacteriophages in fresh waters. Journal of Applied Microbiology. 92(2). 338–347. 95 indexed citations
18.
Valero, Fernando, Rafael de la Torre, Alan R. Boobis, Sandra Murray, & Jordi Segura. (1990). Assay of caffeine metabolism in vitro by human liver microsomes using radio-high-performance liquid chromatography. Journal of Pharmaceutical and Biomedical Analysis. 8(8-12). 783–787. 7 indexed citations
19.
Nove, Alec & Fernando Valero. (1987). La economia del socialismo factible. Medical Entomology and Zoology. 4 indexed citations
20.
Ven, Cornelis P. van de & Fernando Valero. (1981). El espacio en arquitectura: la evolución de una idea nueva en la teoría e historia de los movimientos modernos. Dialnet (Universidad de la Rioja). 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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