Shin Araki

504 total citations
16 papers, 381 citations indexed

About

Shin Araki is a scholar working on Health, Toxicology and Mutagenesis, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Shin Araki has authored 16 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Health, Toxicology and Mutagenesis, 11 papers in Atmospheric Science and 9 papers in Environmental Engineering. Recurrent topics in Shin Araki's work include Air Quality and Health Impacts (15 papers), Atmospheric chemistry and aerosols (11 papers) and Air Quality Monitoring and Forecasting (9 papers). Shin Araki is often cited by papers focused on Air Quality and Health Impacts (15 papers), Atmospheric chemistry and aerosols (11 papers) and Air Quality Monitoring and Forecasting (9 papers). Shin Araki collaborates with scholars based in Japan. Shin Araki's co-authors include Masayuki Shima, Hikari Shimadera, Akira Kondo, Tomohito Matsuo, Hiroshi Hayami, Syuichi Itahashi, Tatsuya Sakurai, Takehiro Michikawa, Hiroshi Nitta and Shoji F. Nakayama and has published in prestigious journals such as The Science of The Total Environment, Environmental Pollution and Atmospheric Environment.

In The Last Decade

Shin Araki

15 papers receiving 372 citations

Peers

Shin Araki

HTM

GPC

Tomohito Matsuo Japan

Flávia Noronha Dutra Ribeiro Brazil

Gabriel Yoshikazu Oukawa Brazil

Surat Bualert Thailand

Awkash Kumar India

F. Sezer Turalıoğlu Türkiye

Ana María Villalobos Chile

Hossein Malakooti Iran

Yvonne Scorgie Australia

Mingliang Ma China

Tomohito Matsuo Japan

Shin Araki

199 ×0.8

HTM

204 ×0.8

178 ×1.1

84 ×1.0

GPC

43 ×0.7

Citations per year, relative to Shin Araki Shin Araki (= 1×) peers Tomohito Matsuo

Countries citing papers authored by Shin Araki

Since Specialization

Citations

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

Fields of papers citing papers by Shin Araki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shin Araki

This figure shows the co-authorship network connecting the top 25 collaborators of Shin Araki. A scholar is included among the top collaborators of Shin Araki 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 Shin Araki. Shin Araki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

Araki, Shin, et al.. (2024). Long-term spatiotemporal variation of benzo[a]pyrene in Japan: Significant decrease in ambient concentrations, human exposure, and health risk. Environmental Pollution. 360. 124650–124650.

Nagai, Kei, Shin Araki, Toshimi Sairenchi, et al.. (2024). Particulate Matter and Incident Chronic Kidney Disease in Japan: The Ibaraki Prefectural Health Study (IPHS). JMA Journal. 7(3). 334–335. 1 indexed citations

Araki, Shin, et al.. (2024). Exposure to ambient fine particulate matter components during pregnancy and early childhood and its association with asthma, allergies, and sensitization in school-age children. Environmental Health and Preventive Medicine. 29(0). 34–34. 5 indexed citations

Shimadera, Hikari, et al.. (2023). Land use regression model established using Light Gradient Boosting Machine incorporating the WRF/CMAQ model for highly accurate spatiotemporal PM2.5 estimation in the central region of Thailand. Atmospheric Environment. 297. 119595–119595. 21 indexed citations

Yoda, Yoshiko, et al.. (2023). Association of air pollution exposure during pregnancy and early childhood with children's cognitive performance and behavior at age six. Environmental Research. 236(Pt 1). 116733–116733. 6 indexed citations

Araki, Shin, et al.. (2022). Predicting Daily PM2.5 Exposure with Spatially Invariant Accuracy Using Co-Existing Pollutant Concentrations as Predictors. Atmosphere. 13(5). 782–782. 6 indexed citations

Araki, Shin, Hikari Shimadera, & Masayuki Shima. (2022). Continuous estimations of daily PM2.5 chemical components from temporally sparse monitoring data using a machine learning approach. Atmospheric Pollution Research. 13(11). 101580–101580. 8 indexed citations

Araki, Shin, et al.. (2022). Incorporating Light Gradient Boosting Machine to land use regression model for estimating NO2 and PM2.5 levels in Kansai region, Japan. Environmental Modelling & Software. 155. 105447–105447. 48 indexed citations

Araki, Shin, Masayuki Shima, Takehiro Michikawa, et al.. (2021). Estimating monthly concentrations of ambient key air pollutants in Japan during 2010–2015 for a national-scale birth cohort. Environmental Pollution. 284. 117483–117483. 12 indexed citations

10.

Araki, Shin, et al.. (2021). An integrated model combining random forests and WRF/CMAQ model for high accuracy spatiotemporal PM2.5 predictions in the Kansai region of Japan. Atmospheric Environment. 262. 118620–118620. 47 indexed citations

11.

Itahashi, Syuichi, Tatsuya Sakurai, Hikari Shimadera, Shin Araki, & Hiroshi Hayami. (2021). Long-term trends of satellite-based fine-mode aerosol optical depth over the Seto Inland Sea, Japan, over two decades (2001–2020). Environmental Research Letters. 16(6). 64062–64062. 19 indexed citations

12.

Araki, Shin, et al.. (2020). Estimating historical PM2.5 exposures for three decades (1987–2016) in Japan using measurements of associated air pollutants and land use regression. Environmental Pollution. 263(Pt A). 114476–114476. 14 indexed citations

13.

Araki, Shin, et al.. (2018). Spatiotemporal land use random forest model for estimating metropolitan NO2 exposure in Japan. The Science of The Total Environment. 634. 1269–1277. 126 indexed citations

14.

Araki, Shin, et al.. (2017). Effect of spatial outliers on the regression modelling of air pollutant concentrations: A case study in Japan. Atmospheric Environment. 153. 83–93. 17 indexed citations

15.

Araki, Shin, et al.. (2015). Optimization of air monitoring networks using chemical transport model and search algorithm. Atmospheric Environment. 122. 22–30. 23 indexed citations

16.

Araki, Shin, et al.. (2014). Application of Regression Kriging to Air Pollutant Concentrations in Japan with High Spatial Resolution. Aerosol and Air Quality Research. 15(1). 234–241. 28 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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