Ian Longley

1.7k citations
46 papers · 1.2k · 1 hit paper · h-index 20

Impact in

Papers in

Ian Longley

45 papers receiving 1.2k citations

Hit Papers

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023 2024 · 56 citations
560+1Years since publication1020304050

Peers

Ian Longley
Comparison fields: 5 of 90
  • Health, Toxicology and Mutagenesis 861
  • Environmental Engineering 609
  • Speech and Hearing 220
  • Automotive Engineering 293
  • Atmospheric Science 351
Replace Nadège Blond with:
Nadège Blond France
Ulaş İm Denmark
Alessandro Bigi Italy
Perry Davy New Zealand
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Countries citing papers authored by Ian Longley

Since Specialization
Citations

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

Fields of papers citing papers by Ian Longley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ian Longley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ian Longley Line = papers co-authored together Ian Longley links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012162
2 2018104
3 201379
4 200470
5 200764
6 201464
7 200363
8
A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023
Hit paper breakdown →
202456
9 201948
10 202046
11 200843
12 201535
13 200334
14 200433
15 200031
16 201628
17 200627
18 200426
19 202021
20 200521

About Ian Longley

Ian Longley is a scholar working on Health, Toxicology and Mutagenesis, Environmental Engineering, Automotive Engineering, Atmospheric Science and Transportation, having authored 46 papers that have together received 1.2k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (34 papers), Vehicle emissions and performance (14 papers), Urban Transport and Accessibility (12 papers), Atmospheric chemistry and aerosols (12 papers), Wind and Air Flow Studies (10 papers), Noise Effects and Management (10 papers), Air Quality Monitoring and Forecasting (8 papers) and Climate Change and Health Impacts (6 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (861 citations), Environmental Engineering (609 citations), Speech and Hearing (220 citations), Automotive Engineering (293 citations) and Atmospheric Science (351 citations). Ian Longley has collaborated with scholars based in New Zealand, United Kingdom and United States. Frequent co-authors include Jennifer Salmond, M. W. Gallagher, Simon Kingham, Woodrow Pattinson, J. R. Dorsey, Kim N. Dirks, Xuying Ma, Jay Gao, Demetrios Gatziolis and Geoffrey H. Donovan. Their work appears in journals such as Atmospheric Environment, The Science of The Total Environment, Air Quality Atmosphere & Health, Atmospheric chemistry and physics and Environmental Science & Technology.

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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