Seyedali Mousavinezhad

773 total citations
22 papers, 498 citations indexed

About

Seyedali Mousavinezhad is a scholar working on Health, Toxicology and Mutagenesis, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Seyedali Mousavinezhad has authored 22 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Health, Toxicology and Mutagenesis, 14 papers in Atmospheric Science and 10 papers in Environmental Engineering. Recurrent topics in Seyedali Mousavinezhad's work include Air Quality and Health Impacts (15 papers), Atmospheric chemistry and aerosols (13 papers) and Air Quality Monitoring and Forecasting (10 papers). Seyedali Mousavinezhad is often cited by papers focused on Air Quality and Health Impacts (15 papers), Atmospheric chemistry and aerosols (13 papers) and Air Quality Monitoring and Forecasting (10 papers). Seyedali Mousavinezhad collaborates with scholars based in United States, South Korea and Canada. Seyedali Mousavinezhad's co-authors include Yunsoo Choi, Masoud Ghahremanloo, Yannic Lops, Arman Pouyaei, Jia Jung, Jincheol Park, Davyda Hammond, Ahmed Khan Salman, Daiwen Kang and Hyun Cheol Kim and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and Environmental Pollution.

In The Last Decade

Seyedali Mousavinezhad

21 papers receiving 489 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seyedali Mousavinezhad United States 12 329 312 272 192 28 22 498
Gongda Lu United Kingdom 8 376 1.1× 220 0.7× 203 0.7× 262 1.4× 33 1.2× 13 500
Abhinandan Ghosh India 12 263 0.8× 241 0.8× 91 0.3× 162 0.8× 43 1.5× 20 406
Xin Zuo China 8 290 0.9× 245 0.8× 177 0.7× 127 0.7× 37 1.3× 14 409
Lidan Zhu China 12 431 1.3× 477 1.5× 239 0.9× 187 1.0× 54 1.9× 24 593
Balakrishnaiah Gugamsetty India 9 270 0.8× 249 0.8× 149 0.5× 160 0.8× 50 1.8× 15 397
Luyu Chang China 13 507 1.5× 611 2.0× 280 1.0× 319 1.7× 92 3.3× 19 746
Aditi Rathod India 11 313 1.0× 185 0.6× 169 0.6× 268 1.4× 20 0.7× 18 422
Xiaoqin Shi United States 9 650 2.0× 420 1.3× 356 1.3× 640 3.3× 31 1.1× 10 859
Shuhui Xue China 3 411 1.2× 157 0.5× 218 0.8× 387 2.0× 19 0.7× 7 545
Jinxi Hua China 8 261 0.8× 107 0.3× 176 0.6× 135 0.7× 46 1.6× 10 316

Countries citing papers authored by Seyedali Mousavinezhad

Since Specialization
Citations

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

Fields of papers citing papers by Seyedali Mousavinezhad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seyedali Mousavinezhad

This figure shows the co-authorship network connecting the top 25 collaborators of Seyedali Mousavinezhad. A scholar is included among the top collaborators of Seyedali Mousavinezhad 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 Seyedali Mousavinezhad. Seyedali Mousavinezhad 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.
2.
Ghahremanloo, Masoud, et al.. (2025). Using multi-satellite observations to constrain ammonia emissions and unlock their potential over open water. Scientific Reports. 15(1). 26784–26784.
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Salman, Ahmed Khan, et al.. (2023). Deep learning based emulator for simulating CMAQ surface NO2 levels over the CONUS. Atmospheric Environment. 316. 120192–120192. 11 indexed citations
7.
Mousavinezhad, Seyedali, et al.. (2023). Surface ozone trends and related mortality across the climate regions of the contiguous United States during the most recent climate period, 1991–2020. Atmospheric Environment. 300. 119693–119693. 12 indexed citations
8.
Lops, Yannic, Masoud Ghahremanloo, Arman Pouyaei, et al.. (2023). Spatiotemporal estimation of TROPOMI NO2 column with depthwise partial convolutional neural network. Neural Computing and Applications. 35(21). 15667–15678. 6 indexed citations
9.
Hataf, Nader & Seyedali Mousavinezhad. (2023). Evaluating municipal solid wastes shear strength parameters to assess landfill slope stability. International Journal of Environment and Waste Management. 31(3). 273–273. 2 indexed citations
10.
Ghahremanloo, Masoud, Yannic Lops, Yunsoo Choi, Seyedali Mousavinezhad, & Jia Jung. (2023). A Coupled Deep Learning Model for Estimating Surface NO2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States. Journal of Geophysical Research Atmospheres. 128(2). 12 indexed citations
11.
Lops, Yannic, et al.. (2023). Development of Deep Convolutional Neural Network Ensemble Models for 36-Month ENSO Forecasts. Asia-Pacific Journal of Atmospheric Sciences. 59(5). 597–605. 6 indexed citations
12.
Pouyaei, Arman, et al.. (2023). Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights From WRF‐Chem/DART Assimilation of OMI NO2, HCHO, and MODIS AOD Retrievals. Journal of Geophysical Research Atmospheres. 128(11). 9 indexed citations
13.
Ghahremanloo, Masoud, et al.. (2022). Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter. Environmental Pollution. 310. 119863–119863. 34 indexed citations
14.
Ghahremanloo, Masoud, Yannic Lops, Yunsoo Choi, et al.. (2022). A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach. Atmospheric Environment. 272. 118944–118944. 35 indexed citations
15.
Jung, Jia, Yunsoo Choi, Seyedali Mousavinezhad, et al.. (2022). Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NOx and VOC emissions using satellite observation. Atmospheric Research. 270. 106076–106076. 26 indexed citations
16.
Park, Jincheol, Jia Jung, Yunsoo Choi, Seyedali Mousavinezhad, & Arman Pouyaei. (2022). The sensitivities of ozone and PM2.5 concentrations to the satellite-derived leaf area index over East Asia and its neighboring seas in the WRF-CMAQ modeling system. Environmental Pollution. 306. 119419–119419. 15 indexed citations
17.
Pouyaei, Arman, et al.. (2022). Investigating the long-range transport of particulate matter in East Asia: Introducing a new Lagrangian diagnostic tool. Atmospheric Environment. 278. 119096–119096. 14 indexed citations
18.
Jung, Jia, Yunsoo Choi, Amir H. Souri, et al.. (2022). The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia. Journal of Geophysical Research Atmospheres. 127(5). 18 indexed citations
19.
Mousavinezhad, Seyedali, et al.. (2021). A comprehensive investigation of surface ozone pollution in China, 2015–2019: Separating the contributions from meteorology and precursor emissions. Atmospheric Research. 257. 105599–105599. 136 indexed citations
20.
Ghahremanloo, Masoud, Yannic Lops, Yunsoo Choi, & Seyedali Mousavinezhad. (2020). Impact of the COVID-19 outbreak on air pollution levels in East Asia. The Science of The Total Environment. 754. 142226–142226. 128 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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