Peter Wind

4.7k total citations · 1 hit paper
56 papers, 1.5k citations indexed

About

Peter Wind is a scholar working on Atomic and Molecular Physics, and Optics, Atmospheric Science and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Peter Wind has authored 56 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Atomic and Molecular Physics, and Optics, 21 papers in Atmospheric Science and 14 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Peter Wind's work include Atmospheric chemistry and aerosols (21 papers), Advanced Chemical Physics Studies (17 papers) and Air Quality and Health Impacts (14 papers). Peter Wind is often cited by papers focused on Atmospheric chemistry and aerosols (21 papers), Advanced Chemical Physics Studies (17 papers) and Air Quality and Health Impacts (14 papers). Peter Wind collaborates with scholars based in Norway, France and Sweden. Peter Wind's co-authors include David Simpson, Á. Nyíri, Michael Gauss, Hilde Fagerli, I. Røeggen, Álvaro Valdebenito, R. W. Bergstrom, V. S. Semeena, J.-P. Tuovinen and Svetlana Tsyro and has published in prestigious journals such as The Journal of Chemical Physics, Physical review. B, Condensed matter and Physical Review B.

In The Last Decade

Peter Wind

56 papers receiving 1.5k citations

Hit Papers

The EMEP MSC-W chemical transport model – technical descr... 2012 2026 2016 2021 2012 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Wind Norway 18 890 684 415 258 250 56 1.5k
Jared D. Smith United States 19 940 1.1× 642 0.9× 290 0.7× 187 0.7× 371 1.5× 42 1.8k
Antti Lauri Finland 13 1.9k 2.1× 993 1.5× 1.1k 2.6× 264 1.0× 135 0.5× 25 2.2k
Juliane L. Fry United States 23 1.9k 2.2× 1.2k 1.8× 711 1.7× 398 1.5× 75 0.3× 47 2.3k
K. C. Clemitshaw United Kingdom 23 1.6k 1.8× 667 1.0× 542 1.3× 424 1.6× 146 0.6× 50 1.9k
G. Schuster Germany 25 1.3k 1.4× 780 1.1× 448 1.1× 225 0.9× 132 0.5× 72 1.9k
C. A. Cardelino United States 21 1.7k 1.9× 988 1.4× 803 1.9× 576 2.2× 48 0.2× 34 2.1k
P. S. Stevens United States 31 2.3k 2.6× 1.2k 1.8× 714 1.7× 654 2.5× 249 1.0× 99 3.0k
H. A. Wiebe Canada 28 2.0k 2.2× 724 1.1× 1.1k 2.5× 370 1.4× 65 0.3× 66 2.3k
O. W. Wingenter United States 22 1.4k 1.6× 432 0.6× 730 1.8× 163 0.6× 73 0.3× 37 1.6k

Countries citing papers authored by Peter Wind

Since Specialization
Citations

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

Fields of papers citing papers by Peter Wind

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Wind

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Wind. A scholar is included among the top collaborators of Peter Wind 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 Peter Wind. Peter Wind 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.
Denby, Bruce, Gregor Kiesewetter, Á. Nyíri, et al.. (2024). Sub-grid Variability and its Impact on Exposure in Regional Scale Air Quality and Integrated Assessment Models: Application of the uEMEP Downscaling Model. Atmospheric Environment. 333. 120586–120586. 2 indexed citations
2.
Tantardini, Christian, et al.. (2024). Scalar Relativistic Effects with Multiwavelets: Implementation and Benchmark. Journal of Chemical Theory and Computation. 20(2). 728–737. 3 indexed citations
3.
Wind, Peter, et al.. (2023). Quantifying Intramolecular Basis Set Superposition Errors. Journal of Chemical Theory and Computation. 19(17). 5863–5871. 7 indexed citations
4.
Ge, Yao, Massimo Vieno, David S. Stevenson, Peter Wind, & Mathew R. Heal. (2023). Global sensitivities of reactive N and S gas and particle concentrations and deposition to precursor emissions reductions. Atmospheric chemistry and physics. 23(11). 6083–6112. 8 indexed citations
5.
Wind, Peter, et al.. (2022). MRChem Multiresolution Analysis Code for Molecular Electronic Structure Calculations: Performance and Scaling Properties. Journal of Chemical Theory and Computation. 19(1). 137–146. 14 indexed citations
6.
Wind, Peter, et al.. (2022). Kinetic energy-free Hartree–Fock equations: an integral formulation. Journal of Mathematical Chemistry. 61(2). 343–361. 1 indexed citations
7.
Ge, Yao, Massimo Vieno, David S. Stevenson, Peter Wind, & Mathew R. Heal. (2022). A new assessment of global and regional budgets, fluxes, and lifetimes of atmospheric reactive N and S gases and aerosols. Atmospheric chemistry and physics. 22(12). 8343–8368. 12 indexed citations
8.
Wind, Peter, et al.. (2021). Multiwavelets applied to metal–ligand interactions: Energies free from basis set errors. The Journal of Chemical Physics. 154(21). 214302–214302. 7 indexed citations
9.
Wind, Peter, et al.. (2020). Static Polarizabilities at the Basis Set Limit: A Benchmark of 124 Species. Journal of Chemical Theory and Computation. 16(8). 4874–4882. 31 indexed citations
10.
Denby, Bruce, Michael Gauss, Peter Wind, et al.. (2020). Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model. Geoscientific model development. 13(12). 6303–6323. 24 indexed citations
11.
Pommier, Matthieu, Hilde Fagerli, Michael Gauss, et al.. (2017). Impact of regional climate change and future emission scenarios on surface O3 and PM2.5 over India. EGU General Assembly Conference Abstracts. 13491. 1 indexed citations
12.
Steensen, Birthe Marie, Michael Schulz, Peter Wind, Álvaro Valdebenito, & Hilde Fagerli. (2017). The operational eEMEP model for volcanic SO 2 and ash forecasting. 1 indexed citations
13.
Simpson, David, Camilla Andersson, Jesper Heile Christensen, et al.. (2014). Impacts of climate and emission changes on nitrogen deposition in Europe: a multi-model study. Atmospheric chemistry and physics. 14(13). 6995–7017. 83 indexed citations
14.
Tsyro, Svetlana, et al.. (2014). Updates to the EMEP/MSC-W model. Lund University Publications (Lund University). 2 indexed citations
15.
Jusélius, Jonas, et al.. (2014). Adaptive order polynomial algorithm in a multiwavelet representation scheme. Applied Numerical Mathematics. 92. 40–53. 6 indexed citations
16.
Wind, Peter & Rasmus Ejrnæs. (2014). Danmarks truede arter. Aarhus University Press eBooks. 1 indexed citations
17.
Langner, Joakim, Magnuz Engardt, Alexander Baklanov, et al.. (2012). A multi-model study of impacts of climate change on surface ozone in Europe. Atmospheric chemistry and physics. 12(21). 10423–10440. 83 indexed citations
18.
Simpson, David, Anna Benedictow, R. W. Bergstrom, et al.. (2012). The EMEP MSC-W chemical transport model – Part 1: Model description. 21 indexed citations
19.
Vieno, Massimo, Anthony J. Dore, David S. Stevenson, et al.. (2010). Modelling surface ozone during the 2003 heat-wave in the UK. Atmospheric chemistry and physics. 10(16). 7963–7978. 141 indexed citations
20.
Vieno, Massimo, Anthony J. Dore, David S. Stevenson, et al.. (2009). Modelling surface ozone during the 2003 heat wave in the UK. University of Zagreb University Computing Centre (SRCE). 43. 83–87. 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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