Eva Webster

2.2k total citations
40 papers, 1.7k citations indexed

About

Eva Webster is a scholar working on Health, Toxicology and Mutagenesis, Environmental Chemistry and Pollution. According to data from OpenAlex, Eva Webster has authored 40 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Health, Toxicology and Mutagenesis, 15 papers in Environmental Chemistry and 12 papers in Pollution. Recurrent topics in Eva Webster's work include Toxic Organic Pollutants Impact (30 papers), Atmospheric chemistry and aerosols (12 papers) and Per- and polyfluoroalkyl substances research (12 papers). Eva Webster is often cited by papers focused on Toxic Organic Pollutants Impact (30 papers), Atmospheric chemistry and aerosols (12 papers) and Per- and polyfluoroalkyl substances research (12 papers). Eva Webster collaborates with scholars based in Canada, United States and Italy. Eva Webster's co-authors include Don Mackay, David Ellis, Frank Wania, Donald Mackay, Andreas Beyer, Michael Matthies, Darcy C. Burns, Hongxia Li, Colin J. B. Harvey and John P. Smol and has published in prestigious journals such as Environmental Science & Technology, Water Research and Chemosphere.

In The Last Decade

Eva Webster

40 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eva Webster Canada 16 1.2k 663 582 391 133 40 1.7k
Sara Valsecchi Italy 31 1.6k 1.3× 1.3k 2.0× 744 1.3× 572 1.5× 104 0.8× 73 2.5k
Sarah B. Gewurtz Canada 29 1.8k 1.4× 529 0.8× 352 0.6× 654 1.7× 267 2.0× 60 2.2k
Eric Braekevelt Canada 20 1.7k 1.3× 700 1.1× 500 0.9× 405 1.0× 137 1.0× 27 2.0k
Joel D. Blair Canada 9 1.5k 1.2× 585 0.9× 312 0.5× 481 1.2× 237 1.8× 10 1.8k
Claudia Müller Switzerland 18 721 0.6× 667 1.0× 650 1.1× 251 0.6× 86 0.6× 22 1.3k
Sum Chi Lee Canada 17 1.8k 1.5× 721 1.1× 870 1.5× 456 1.2× 42 0.3× 31 2.4k
Bo Yuan China 32 2.0k 1.6× 423 0.6× 195 0.3× 614 1.6× 147 1.1× 65 2.6k
Axel Möller Germany 29 2.5k 2.1× 1.2k 1.7× 1.2k 2.0× 763 2.0× 58 0.4× 34 2.9k
Fiona Wong Canada 26 1.4k 1.1× 478 0.7× 386 0.7× 474 1.2× 77 0.6× 38 1.8k
Colin P. Thackray United States 21 1.3k 1.0× 443 0.7× 529 0.9× 192 0.5× 248 1.9× 30 1.7k

Countries citing papers authored by Eva Webster

Since Specialization
Citations

This map shows the geographic impact of Eva Webster'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 Eva Webster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Webster more than expected).

Fields of papers citing papers by Eva Webster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eva Webster. 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 Eva Webster. The network helps show where Eva Webster may publish in the future.

Co-authorship network of co-authors of Eva Webster

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Webster. A scholar is included among the top collaborators of Eva Webster 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 Eva Webster. Eva Webster 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.
Okeme, Joseph O., Eva Webster, J. Mark Parnis, & Miriam L. Diamond. (2016). Approaches for estimating PUF-air partitions coefficient for semi-volatile organic compounds: A critical comparison. Chemosphere. 168. 199–204. 14 indexed citations
2.
3.
Webster, Eva & David Ellis. (2012). Estimating chemical biotransformation rates from food web concentrations. Chemosphere. 87(4). 404–412. 5 indexed citations
4.
Webster, Eva & David Ellis. (2011). Equilibrium modeling: A pathway to understanding observed perfluorocarboxylic and perfluorosulfonic acid behavior. Environmental Toxicology and Chemistry. 30(10). 2229–2236. 12 indexed citations
5.
Ellis, David & Eva Webster. (2009). Response to Comment on “Aerosol Enrichment of the Surfactant PFO and Mediation of the Water−Air Transport of Gaseous PFOA”. Environmental Science & Technology. 43(4). 1234–1235. 11 indexed citations
6.
Ellis, David, et al.. (2008). Aerosol Enrichment of the Surfactant PFO and Mediation of the Water−Air Transport of Gaseous PFOA. Environmental Science & Technology. 42(11). 3969–3974. 165 indexed citations
7.
Seth, Rajesh, Eva Webster, & Donald Mackay. (2007). Continued development of a mass balance model of chemical fate in a sewage treatment plant. Water Research. 42(3). 595–604. 33 indexed citations
8.
Lasenby, David C., et al.. (2007). An exploration of the role of mysids in benthic-pelagic coupling and biomagnification using a dynamic bioaccumulation model. Environmental Toxicology and Chemistry. 26(6). 1224–1232. 13 indexed citations
9.
Harvey, Colin J. B., Don Mackay, & Eva Webster. (2007). Can the unit world model concept be applied to hazard assessment of both organic chemicals and metal ions?. Environmental Toxicology and Chemistry. 26(10). 2129–2142. 12 indexed citations
10.
Arnot, Jon A., et al.. (2006). Screening Level Risk Assessment Model for Chemical Fate and Effects in the Environment. Environmental Science & Technology. 40(7). 2316–2323. 109 indexed citations
11.
Foster, Karen L., et al.. (2006). The role of multimedia mass balance models for assessing the effects of volatile organic compound emissions on urban air quality. Atmospheric Environment. 40(16). 2986–2994. 11 indexed citations
12.
Mackay, Donald & Eva Webster. (2005). Environmental Persistence of Chemicals. Environmental Science and Pollution Research. 13(1). 43–49. 25 indexed citations
13.
Mackay, Donald, et al.. (2005). Chemical Partitioning to Foliage: The Contribution and Legacy of Davide Calamari. Environmental Science and Pollution Research. 13(1). 2–8. 11 indexed citations
14.
Webster, Eva, Christina Cowan‐Ellsberry, & L.S. McCarty. (2004). Putting science into persistence, bioaccumulation, and toxicity evaluations. Environmental Toxicology and Chemistry. 23(10). 2473–2482. 4 indexed citations
15.
Mackay, Don, Eva Webster, David Woodfine, et al.. (2003). Towards Consistent Evaluation of the Persistence of Organic, Inorganic and Metallic Substances. Human and Ecological Risk Assessment An International Journal. 9(6). 1445–1474. 9 indexed citations
16.
Webster, Eva, et al.. (2003). Regional differences in chemical fate model outcome. Chemosphere. 55(10). 1361–1376. 38 indexed citations
17.
Mackay, Don, et al.. (2003). The role of QSARs and fate models in chemical hazard and risk assessment. QSAR & Combinatorial Science. 22(1). 106–112. 14 indexed citations
18.
Gouin, Todd, Don Mackay, Eva Webster, & Frank Wania. (2000). Screening Chemicals for Persistence in the Environment. Environmental Science & Technology. 34(5). 881–884. 92 indexed citations
19.
Webster, Eva, et al.. (1999). Equilibrium Lipid Partitioning Concentrations as a Multi-Media Synoptic Indicator of Contaminant Levels and Trends in Aquatic Ecosystems. Journal of Great Lakes Research. 25(2). 318–329. 25 indexed citations
20.
Mackay, Don & Eva Webster. (1998). Linking emissions to prevailing concentrations—exposure on a local scale. Environmetrics. 9(5). 541–553. 1 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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