Po‐Lun Ma

9.0k total citations · 1 hit paper
117 papers, 3.7k citations indexed

About

Po‐Lun Ma is a scholar working on Atmospheric Science, Global and Planetary Change and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Po‐Lun Ma has authored 117 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Atmospheric Science, 102 papers in Global and Planetary Change and 8 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Po‐Lun Ma's work include Atmospheric chemistry and aerosols (70 papers), Atmospheric aerosols and clouds (69 papers) and Climate variability and models (48 papers). Po‐Lun Ma is often cited by papers focused on Atmospheric chemistry and aerosols (70 papers), Atmospheric aerosols and clouds (69 papers) and Climate variability and models (48 papers). Po‐Lun Ma collaborates with scholars based in United States, China and Germany. Po‐Lun Ma's co-authors include Philip J. Rasch, Hailong Wang, Balwinder Singh, R. C. Easter, S. J. Ghan, Xiaohong Liu, Jin‐Ho Yoon, Simone Tilmes, Kai Zhang and Yun Qian and has published in prestigious journals such as Nature Communications, Journal of Geophysical Research Atmospheres and Scientific Reports.

In The Last Decade

Po‐Lun Ma

104 papers receiving 3.6k citations

Hit Papers

Description and evaluation of a new four-mode version of ... 2016 2026 2019 2022 2016 100 200 300
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. Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model
    2016 391 citations Xiaohong Liu, Po‐Lun Ma et al. Geoscientific model development profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Po‐Lun Ma United States 33 3.4k 3.1k 615 181 146 117 3.7k
A. Jayaraman India 31 2.6k 0.8× 2.4k 0.8× 553 0.9× 240 1.3× 103 0.7× 98 3.0k
William I. Gustafson United States 29 3.3k 1.0× 2.9k 0.9× 848 1.4× 373 2.1× 52 0.4× 83 3.6k
Jens Redemann United States 40 4.5k 1.3× 4.4k 1.4× 660 1.1× 198 1.1× 139 1.0× 136 4.8k
Andreas Herber Germany 34 3.5k 1.0× 2.9k 0.9× 468 0.8× 144 0.8× 123 0.8× 135 3.7k
Y. Shinozuka United States 27 3.6k 1.1× 3.1k 1.0× 1.2k 1.9× 294 1.6× 53 0.4× 51 3.8k
Anton Darmenov United States 20 2.3k 0.7× 2.3k 0.7× 551 0.9× 273 1.5× 64 0.4× 42 2.7k
Annica M. L. Ekman Sweden 32 2.8k 0.8× 2.6k 0.9× 277 0.5× 96 0.5× 134 0.9× 121 3.0k
Jean‐François Léon France 26 2.9k 0.9× 2.8k 0.9× 479 0.8× 215 1.2× 76 0.5× 61 3.3k
Hannele Korhonen Finland 32 2.8k 0.8× 2.3k 0.7× 1.2k 1.9× 353 2.0× 110 0.8× 97 3.1k
G. Pandithurai India 33 3.0k 0.9× 2.8k 0.9× 731 1.2× 361 2.0× 50 0.3× 175 3.4k

Countries citing papers authored by Po‐Lun Ma

Since Specialization
Citations

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

Fields of papers citing papers by Po‐Lun Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Po‐Lun Ma. 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 Po‐Lun Ma. The network helps show where Po‐Lun Ma may publish in the future.

Co-authorship network of co-authors of Po‐Lun Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Po‐Lun Ma. A scholar is included among the top collaborators of Po‐Lun Ma 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 Po‐Lun Ma. Po‐Lun Ma 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.
Zhang, Yike, Zengyi Ma, Chunming Dong, et al.. (2025). Distribution and migration of pollutant elements during municipal solid waste incineration fly ash melting in a pilot-scale furnace. Journal of Environmental Management. 379. 124808–124808.
2.
Kang, Litai, Roger Marchand, Po‐Lun Ma, et al.. (2025). Impacts of DMS Emissions and Chemistry on E3SMv2 Simulated Cloud Droplet Numbers and Aerosol Concentrations Over the Southern Ocean. Journal of Advances in Modeling Earth Systems. 17(5).
3.
Fierce, Laura, R. C. Easter, Po‐Lun Ma, et al.. (2024). Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions. Journal of Aerosol Science. 181. 106388–106388. 1 indexed citations
4.
Zhang, Kai, Jianfeng Li, Balwinder Singh, et al.. (2024). Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model. Geoscientific model development. 17(8). 3507–3532.
5.
Ma, Po‐Lun, et al.. (2023). Emulating aerosol optics with randomly generated neural networks. Geoscientific model development. 16(9). 2355–2370. 4 indexed citations
6.
Huang, Meng, Po‐Lun Ma, Nathaniel W. Chaney, et al.. (2022). Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime. Geoscientific model development. 15(16). 6371–6384. 8 indexed citations
7.
Hao, Dalei, Gautam Bisht, Meng Huang, et al.. (2022). Impacts of Sub‐Grid Topographic Representations on Surface Energy Balance and Boundary Conditions in the E3SM Land Model: A Case Study in Sierra Nevada. Journal of Advances in Modeling Earth Systems. 14(4). 22 indexed citations
8.
Zheng, Zhonghua, Matthew West, Lei Zhao, et al.. (2021). Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model. Atmospheric chemistry and physics. 21(23). 17727–17741. 11 indexed citations
9.
Mülmenstädt, Johannes, Edward Gryspeerdt, Marc Salzmann, et al.. (2019). Separating radiative forcing by aerosol–cloud interactions and rapid cloud adjustments in the ECHAM–HAMMOZ aerosol–climate model using the method of partial radiative perturbations. Atmospheric chemistry and physics. 19(24). 15415–15429. 19 indexed citations
10.
Wu, Mingxuan, Xiaohong Liu, Leiming Zhang, et al.. (2018). Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5. Journal of Advances in Modeling Earth Systems. 10(5). 1150–1171. 33 indexed citations
11.
Zhang, Kai, Philip J. Rasch, Mark A. Taylor, et al.. (2018). Impact of numerical choices on water conservation in the E3SM Atmosphere Model version 1 (EAMv1). Geoscientific model development. 11(5). 1971–1988. 23 indexed citations
12.
13.
Song, Hua, Zhibo Zhang, Po‐Lun Ma, S. J. Ghan, & Minghuai Wang. (2018). The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models. Geoscientific model development. 11(8). 3147–3158. 15 indexed citations
14.
Yang, Yang, Hailong Wang, Steven J. Smith, Po‐Lun Ma, & Philip J. Rasch. (2017). Source attribution of black carbon and its direct radiative forcing in China. Atmospheric chemistry and physics. 17(6). 4319–4336. 78 indexed citations
15.
Fan, Tianyi, Xiaohong Liu, Po‐Lun Ma, et al.. (2016). Impact of a new emission inventory on CAM5 simulations of aerosolsand aerosol radiative effects in eastern China. 2 indexed citations
16.
Tilmes, Simone, Jean‐François Lamarque, L. K. Emmons, et al.. (2015). Description and evaluation of tropospheric chemistry and aerosols in the Community Earth System Model (CESM1.2). Geoscientific model development. 8(5). 1395–1426. 150 indexed citations
17.
Zhang, Kai, Hui Wan, Xiaohong Liu, et al.. (2014). Technical Note: On the use of nudging for aerosol–climate model intercomparison studies. Atmospheric chemistry and physics. 14(16). 8631–8645. 119 indexed citations
18.
Ma, Po‐Lun, P. J. Rasch, R. C. Easter, et al.. (2014). Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study. Geoscientific model development. 7(3). 755–778. 65 indexed citations
19.
Liu, Xiaohong, Yun Qian, Jin‐Ho Yoon, et al.. (2013). A sensitivity study of radiative fluxes at the top of atmosphere to cloud-microphysics and aerosol parameters in the community atmosphere model CAM5. Atmospheric chemistry and physics. 13(21). 10969–10987. 64 indexed citations
20.
Zhao, C., Xiaohong Liu, Yun Qian, et al.. (2012). Sensitivity of Radiative Fluxes at Top of Atmosphere to Cloud-Microphysics and Aerosol Parameters in the Community Atmosphere Model (CAM5). AGU Fall Meeting Abstracts. 2012. 1 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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