Pentti Paatero

18.1k total citations · 7 hit papers
74 papers, 13.2k citations indexed

About

Pentti Paatero is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, Pentti Paatero has authored 74 papers receiving a total of 13.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Atmospheric Science, 27 papers in Health, Toxicology and Mutagenesis and 17 papers in Environmental Engineering. Recurrent topics in Pentti Paatero's work include Atmospheric chemistry and aerosols (27 papers), Air Quality and Health Impacts (26 papers) and Air Quality Monitoring and Forecasting (14 papers). Pentti Paatero is often cited by papers focused on Atmospheric chemistry and aerosols (27 papers), Air Quality and Health Impacts (26 papers) and Air Quality Monitoring and Forecasting (14 papers). Pentti Paatero collaborates with scholars based in Finland, United States and Spain. Pentti Paatero's co-authors include Unto Tapper, Philip K. Hopke, Gary Norris, Shelly I. Eberly, Steve Brown, William C. Malm, James F. Sisler, Chak K. Chan, Ziad Ramadan and Xin‐Hua Song and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Pentti Paatero

73 papers receiving 12.7k citations

Hit Papers

Positive matrix factoriza... 1994 2026 2004 2015 1994 1997 1998 1999 2015 1000 2.0k 3.0k 4.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Positive matrix factorization: A non‐negative factor model with optimal utilization of error estimates of data values
    1994 4.3k citations Pentti Paatero, Unto Tapper Environmetrics profile →
  2. Least squares formulation of robust non-negative factor analysis
    1997 1.6k citations Pentti Paatero profile →
  3. Atmospheric aerosol over Alaska: 2. Elemental composition and sources
    1998 763 citations Philip K. Hopke, Pentti Paatero et al. Journal of Geophysical Research Atmospheres profile →
  4. The Multilinear Engine—A Table-Driven, Least Squares Program for Solving Multilinear Problems, Including then-Way Parallel Factor Analysis Model
    1999 563 citations Pentti Paatero profile →
  5. Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results
    2015 525 citations Steve Brown, Shelly I. Eberly et al. The Science of The Total Environment profile →
  6. Discarding or downweighting high-noise variables in factor analytic models
    2003 515 citations Pentti Paatero, Philip K. Hopke Analytica Chimica Acta profile →
  7. Methods for estimating uncertainty in factor analytic solutions
    2014 414 citations Pentti Paatero, Shelly I. Eberly et al. Atmospheric measurement techniques profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pentti Paatero Finland 36 8.8k 7.9k 4.0k 2.3k 1.7k 74 13.2k
Roland R. Draxler United States 42 4.9k 0.6× 9.4k 1.2× 2.8k 0.7× 801 0.4× 7.8k 4.6× 101 16.5k
Unto Tapper Finland 25 3.0k 0.3× 2.8k 0.4× 1.2k 0.3× 743 0.3× 736 0.4× 109 6.8k
Qi Zhang United States 67 8.3k 0.9× 11.1k 1.4× 2.6k 0.6× 1.4k 0.6× 4.9k 2.9× 301 14.8k
Ronald C. Henry United States 32 2.4k 0.3× 1.8k 0.2× 1.2k 0.3× 758 0.3× 459 0.3× 77 3.6k
Hartmut Herrmann Germany 78 9.1k 1.0× 15.4k 1.9× 2.8k 0.7× 915 0.4× 5.9k 3.4× 622 23.2k
David Griffith Australia 54 1.0k 0.1× 7.0k 0.9× 757 0.2× 316 0.1× 7.0k 4.1× 311 11.8k
Jun Wang United States 60 4.0k 0.5× 8.5k 1.1× 2.7k 0.7× 294 0.1× 8.2k 4.8× 384 12.7k
Xiaodong Li China 46 868 0.1× 1.3k 0.2× 1.2k 0.3× 105 0.0× 1.8k 1.1× 268 11.5k
Tianfeng Chai United States 28 759 0.1× 2.0k 0.3× 1.3k 0.3× 239 0.1× 2.0k 1.2× 60 6.6k
Zhanqing Li United States 81 6.5k 0.7× 18.3k 2.3× 4.4k 1.1× 436 0.2× 18.7k 11.0× 470 25.2k

Countries citing papers authored by Pentti Paatero

Since Specialization
Citations

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

Fields of papers citing papers by Pentti Paatero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pentti Paatero

This figure shows the co-authorship network connecting the top 25 collaborators of Pentti Paatero. A scholar is included among the top collaborators of Pentti Paatero 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 Pentti Paatero. Pentti Paatero 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.
Zhang, Yanjun, Otso Peräkylä, Chao Yan, et al.. (2020). Insights into atmospheric oxidation processes by performing factor analyses on subranges of mass spectra. Atmospheric chemistry and physics. 20(10). 5945–5961. 11 indexed citations
2.
Zhang, Yanjun, Otso Peräkylä, Chao Yan, et al.. (2019). A novel approach for simple statistical analysis of high-resolution mass spectra. Atmospheric measurement techniques. 12(7). 3761–3776. 20 indexed citations
3.
Brown, Steve, Shelly I. Eberly, Pentti Paatero, & Gary Norris. (2015). Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results. The Science of The Total Environment. 518-519. 626–635. 525 indexed citations breakdown →
4.
Paatero, Pentti, Shelly I. Eberly, Steve Brown, & Gary Norris. (2014). Methods for estimating uncertainty in factor analytic solutions. Atmospheric measurement techniques. 7(3). 781–797. 414 indexed citations breakdown →
5.
Brown, Steve, Taesam Lee, Gary Norris, et al.. (2012). Receptor modeling of near-roadway aerosol mass spectrometer data in Las Vegas, Nevada, with EPA PMF. Atmospheric chemistry and physics. 12(1). 309–325. 33 indexed citations
6.
Zhao, Weixiang, Philip K. Hopke, Gary Norris, Ron Williams, & Pentti Paatero. (2006). Source apportionment and analysis on ambient and personal exposure samples with a combined receptor model and an adaptive blank estimation strategy. Atmospheric Environment. 40(20). 3788–3801. 63 indexed citations
7.
Forastiere, Francesco, Massimo Stafoggia, Sally Picciotto, et al.. (2005). A Case-Crossover Analysis of Out-of-Hospital Coronary Deaths and Air Pollution in Rome, Italy. American Journal of Respiratory and Critical Care Medicine. 172(12). 1549–1555. 148 indexed citations
8.
Mar, Therese F., Kazuhiko Ito, Jane Q. Koenig, et al.. (2005). PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2.5 and daily mortality in Phoenix, AZ. Journal of Exposure Science & Environmental Epidemiology. 16(4). 311–320. 120 indexed citations
9.
Hopke, Philip K., Kazuhiko Ito, Therese F. Mar, et al.. (2005). PM source apportionment and health effects: 1. Intercomparison of source apportionment results. Journal of Exposure Science & Environmental Epidemiology. 16(3). 275–286. 218 indexed citations
10.
Yli‐Tuomi, Tarja, Philip K. Hopke, Pentti Paatero, et al.. (2003). Atmospheric aerosol over Finnish Arctic: source analysis by the multilinear engine and the potential source contribution function. Atmospheric Environment. 37(31). 4381–4392. 48 indexed citations
11.
Paatero, Pentti & Philip K. Hopke. (2003). Discarding or downweighting high-noise variables in factor analytic models. Analytica Chimica Acta. 490(1-2). 277–289. 515 indexed citations breakdown →
12.
Kim, Eugene, Philip K. Hopke, Pentti Paatero, & Eric S. Edgerton. (2003). Incorporation of parametric factors into multilinear receptor model studies of Atlanta aerosol. Atmospheric Environment. 37(36). 5009–5021. 50 indexed citations
13.
Hopke, Philip K., YuLong Xie, & Pentti Paatero. (1999). Mixed multiway analysis of airborne particle composition data. Journal of Chemometrics. 13(3-4). 343–352. 12 indexed citations
14.
Chan, Chak K., et al.. (1999). Application of positive matrix factorization in source apportionment of particulate pollutants in Hong Kong. Atmospheric Environment. 33(19). 3201–3212. 408 indexed citations
15.
Hopke, Philip K., YuLong Xie, & Pentti Paatero. (1999). <title>Mixed multiway analysis of airborne particle composition data</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3854. 36–42. 8 indexed citations
16.
Hopke, Philip K., et al.. (1998). Atmospheric aerosol over Alaska: 2. Elemental composition and sources. Journal of Geophysical Research Atmospheres. 103(D15). 19045–19057. 763 indexed citations breakdown →
17.
Juvela, M., K. Lehtinen, & Pentti Paatero. (1996). The use of positive matrix factorization in the analysis of molecular line spectra.. Monthly Notices of the Royal Astronomical Society. 280(2). 616–626. 15 indexed citations
18.
Paatero, Pentti & Unto Tapper. (1994). Positive matrix factorization: A non‐negative factor model with optimal utilization of error estimates of data values. Environmetrics. 5(2). 111–126. 4288 indexed citations breakdown →
19.
Hopke, Philip K. & Pentti Paatero. (1994). Extreme-value estimation applied to aerosol size distributions and related environmental problems. Journal of Research of the National Institute of Standards and Technology. 99(4). 361–361. 7 indexed citations
20.
Paatero, Pentti & T. Raunemaa. (1989). Analysis of CO2Thermograms by the New Extreme-Value Estimation (EVE) Deconvolution Principle. Aerosol Science and Technology. 10(2). 365–369. 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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