Masoud Ghahremanloo

2.0k total citations · 1 hit paper
27 papers, 1.4k citations indexed

About

Masoud Ghahremanloo is a scholar working on Environmental Engineering, Health, Toxicology and Mutagenesis and Atmospheric Science. According to data from OpenAlex, Masoud Ghahremanloo has authored 27 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Environmental Engineering, 19 papers in Health, Toxicology and Mutagenesis and 16 papers in Atmospheric Science. Recurrent topics in Masoud Ghahremanloo's work include Air Quality and Health Impacts (19 papers), Air Quality Monitoring and Forecasting (18 papers) and Atmospheric chemistry and aerosols (13 papers). Masoud Ghahremanloo is often cited by papers focused on Air Quality and Health Impacts (19 papers), Air Quality Monitoring and Forecasting (18 papers) and Atmospheric chemistry and aerosols (13 papers). Masoud Ghahremanloo collaborates with scholars based in United States, Iran and Canada. Masoud Ghahremanloo's co-authors include Yunsoo Choi, Seyedali Mousavinezhad, Meisam Amani, Yannic Lops, Armin Moghimi, Seyed Ali Ahmadi, Arsalan Ghorbanian, Brian Brisco, Mohammad Kakooei and Sahel Mahdavi and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and Environmental Pollution.

In The Last Decade

Masoud Ghahremanloo

24 papers receiving 1.3k citations

Hit Papers

Google Earth Engine Cloud Computing Platform for Remote S... 2020 2026 2022 2024 2020 200 400 600
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. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review
    2020 701 citations Meisam Amani, Arsalan Ghorbanian et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masoud Ghahremanloo United States 13 612 593 536 443 315 27 1.4k
Liang Zhai China 16 510 0.8× 581 1.0× 412 0.8× 487 1.1× 245 0.8× 44 1.4k
Fei Meng China 20 544 0.9× 706 1.2× 398 0.7× 328 0.7× 258 0.8× 84 1.4k
Tangao Hu China 19 515 0.8× 709 1.2× 352 0.7× 236 0.5× 259 0.8× 58 1.2k
Matamyo Simwanda Zambia 15 473 0.8× 687 1.2× 250 0.5× 252 0.6× 378 1.2× 26 1.2k
Azad Rasul Iraq 13 600 1.0× 492 0.8× 226 0.4× 272 0.6× 165 0.5× 32 896
Dongjie Fu China 20 509 0.8× 735 1.2× 288 0.5× 191 0.4× 496 1.6× 58 1.4k
Faisal Mumtaz China 22 554 0.9× 808 1.4× 321 0.6× 176 0.4× 512 1.6× 56 1.4k
Tengyun Hu China 14 606 1.0× 1.1k 1.9× 359 0.7× 356 0.8× 293 0.9× 22 1.5k
Luca Congedo Italy 16 457 0.7× 574 1.0× 164 0.3× 261 0.6× 251 0.8× 29 1.0k

Countries citing papers authored by Masoud Ghahremanloo

Since Specialization
Citations

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

Fields of papers citing papers by Masoud Ghahremanloo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masoud Ghahremanloo

This figure shows the co-authorship network connecting the top 25 collaborators of Masoud Ghahremanloo. A scholar is included among the top collaborators of Masoud Ghahremanloo 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 Masoud Ghahremanloo. Masoud Ghahremanloo 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.
Ghahremanloo, Masoud, Caroline R. Nowlan, Gonzalo González Abad, et al.. (2025). Comprehensive Analysis of Bias in TEMPO NO2 Column Densities Through Pandora Observations. Journal of Geophysical Research Atmospheres. 130(15). e2025JD044150–e2025JD044150.
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.
3.
Ghahremanloo, Masoud, et al.. (2025). Deep learning calibration model for PurpleAir PM2.5 measurements: Comprehensive Investigation of the PurpleAir network. Atmospheric Environment. 348. 121118–121118.
4.
5.
Choi, Yunsoo, et al.. (2024). Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ+. The Science of The Total Environment. 946. 174158–174158. 6 indexed citations
6.
Ghahremanloo, Masoud, et al.. (2024). Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations. Environment International. 190. 108818–108818. 6 indexed citations
7.
Ghahremanloo, Masoud, Yunsoo Choi, & Yannic Lops. (2023). Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States. Environmental Pollution. 326. 121508–121508. 20 indexed citations
8.
9.
Ghahremanloo, Masoud, Yunsoo Choi, & Yannic Lops. (2023). Deep Learning Mapping of Surface Mda8 Ozone: The Impact of Predictor Variables on Ozone Levels Over the Contiguous United States. SSRN Electronic Journal. 1 indexed citations
10.
Choi, Yunsoo, et al.. (2023). An Intercomparison of Deep-Learning Methods for Super-Resolution Bias-Correction (SRBC) of Indian Summer Monsoon Rainfall (ISMR) Using CORDEX-SA Simulations. Asia-Pacific Journal of Atmospheric Sciences. 59(4). 495–508. 9 indexed citations
11.
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
12.
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
13.
Motlagh, Majid Shafiepour, et al.. (2023). Current Status and Future Forecast of Short-lived Climate-Forced Ozone in Tehran, Iran, derived from Ground-Based and Satellite Observations. Water Air & Soil Pollution. 234(2). 134–134. 11 indexed citations
14.
15.
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
16.
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
17.
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
18.
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
19.
Amani, Meisam, Arsalan Ghorbanian, Seyed Ali Ahmadi, et al.. (2020). Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 5326–5350. 701 indexed citations breakdown →
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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