Y. Ma

2.1k total citations · 1 hit paper
19 papers, 1.7k citations indexed

About

Y. Ma is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Mechanics of Materials. According to data from OpenAlex, Y. Ma has authored 19 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Atmospheric Science, 9 papers in Health, Toxicology and Mutagenesis and 6 papers in Mechanics of Materials. Recurrent topics in Y. Ma's work include Atmospheric chemistry and aerosols (10 papers), Air Quality and Health Impacts (9 papers) and Hydrocarbon exploration and reservoir analysis (6 papers). Y. Ma is often cited by papers focused on Atmospheric chemistry and aerosols (10 papers), Air Quality and Health Impacts (9 papers) and Hydrocarbon exploration and reservoir analysis (6 papers). Y. Ma collaborates with scholars based in China, United Kingdom and United States. Y. Ma's co-authors include Fengkui Duan, Kebin He, Z.-Y. Du, Jihua Tan, Fumo Yang, Qingguo Zhao, Yuan Cheng, Mei Zheng, Guenter Engling and Rodney J. Weber and has published in prestigious journals such as The Science of The Total Environment, Environmental Pollution and Environment International.

In The Last Decade

Y. Ma

19 papers receiving 1.7k citations

Hit Papers

Characteristics of PM 2.5 speciation in representative me... 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Y. Ma China 14 1.4k 1.3k 509 474 285 19 1.7k
Natalie J. Pekney United States 17 552 0.4× 596 0.5× 369 0.7× 341 0.7× 243 0.9× 34 1.1k
Steven D. Kohl United States 19 1.8k 1.3× 1.8k 1.4× 608 1.2× 569 1.2× 574 2.0× 32 2.3k
T. Pakkanen Finland 22 1.4k 1.0× 1.3k 1.0× 447 0.9× 481 1.0× 502 1.8× 44 2.0k
Ming Wang China 24 1.5k 1.1× 1.3k 1.0× 341 0.7× 741 1.6× 331 1.2× 70 2.0k
Stéphane Sauvage France 24 1.2k 0.9× 982 0.8× 336 0.7× 523 1.1× 313 1.1× 74 1.6k
Imre Salma Hungary 32 2.1k 1.5× 2.0k 1.6× 1.0k 2.0× 633 1.3× 533 1.9× 84 2.9k
M. Zavala United States 34 2.5k 1.9× 2.1k 1.7× 1.0k 2.0× 811 1.7× 604 2.1× 64 3.1k
Ying‐Kuang Hsu United States 10 615 0.5× 593 0.5× 398 0.8× 257 0.5× 160 0.6× 12 934
Ulla Makkonen Finland 22 1.0k 0.7× 969 0.8× 419 0.8× 338 0.7× 254 0.9× 46 1.5k
Caiqing Yan China 28 2.1k 1.6× 2.0k 1.5× 702 1.4× 615 1.3× 503 1.8× 70 2.7k

Countries citing papers authored by Y. Ma

Since Specialization
Citations

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

Fields of papers citing papers by Y. Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Y. Ma

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

All Works

19 of 19 papers shown
1.
Liu, Bo, Y. Ma, Qamar Yasin, et al.. (2025). Characterization of lacustrine shale oil reservoirs based on a hybrid deep learning model: A data-driven approach to predict lithofacies, vitrinite reflectance, and TOC. Marine and Petroleum Geology. 174. 107309–107309. 6 indexed citations
2.
Liu, Bo, Qamar Yasin, Ghulam Mohyuddin Sohail, et al.. (2023). Seismic characterization of fault and fractures in deep buried carbonate reservoirs using CNN-LSTM based deep neural networks. Geoenergy Science and Engineering. 229. 212126–212126. 12 indexed citations
3.
Yasin, Qamar, Bo Liu, Mengdi Sun, et al.. (2023). Automatic pore structure analysis in organic-rich shale using FIB-SEM and attention U-Net. Fuel. 358. 130161–130161. 24 indexed citations
4.
Song, Lianjun, You Wang, Jinkui Wang, et al.. (2023). Production of monoclonal antibody against tylosin and tilmicosin with homogeneous cross-reactivity and its application in lateral flow immunoassay. Microchimica Acta. 191(1). 42–42. 10 indexed citations
5.
Yang, Song, Y. Ma, Fengkui Duan, et al.. (2017). Characteristics and formation of typical winter haze in Handan, one of the most polluted cities in China. The Science of The Total Environment. 613-614. 1367–1375. 66 indexed citations
6.
Duan, Fengkui, Kebin He, Y. Ma, et al.. (2016). High molecular weight organic compounds (HMW-OCs) in severe winter haze: Direct observation and insights on the formation mechanism. Environmental Pollution. 218. 289–296. 26 indexed citations
7.
Ma, Y., et al.. (2016). Direct Liquefaction of Bamboo in Ethanol-Phenol Co- Solvent. BioResources. 11(4). 2 indexed citations
8.
Li, Long-yuan, et al.. (2014). PYROLYSIS KINETICS OF NORTH-KOREAN OIL SHALE; pp. 250–265. Oil Shale. 31(3). 250–265. 16 indexed citations
9.
Yue, Changtao, et al.. (2014). INFLUENCE OF RETORTING CONDITIONS ON THE PYROLYSIS OF YAOJIE OIL SHALE; pp. 66–78. Oil Shale. 31(1). 66–78. 25 indexed citations
10.
Cheng, Yuan, Guenter Engling, Kebin He, et al.. (2013). Biomass burning contribution to Beijing aerosol. Atmospheric chemistry and physics. 13(15). 7765–7781. 359 indexed citations
11.
Ma, Y., et al.. (2012). ANALYSIS AND IDENTIFICATION OF OXYGEN COMPOUNDS IN LONGKOU SHALE OIL AND SHENMU COAL TAR; pp. 322–333. Oil Shale. 29(4). 322–333. 17 indexed citations
12.
He, Kebin, Qing Zhao, Y. Ma, et al.. (2012). Spatial and seasonal variability of PM 2.5 acidity at two Chinese megacities: insights into the formation of secondary inorganic aerosols. Atmospheric chemistry and physics. 12(3). 1377–1395. 159 indexed citations
13.
Yang, Fumo, Jihua Tan, Zongbo Shi, et al.. (2012). Five-year record of atmospheric precipitation chemistry in urban Beijing, China. Atmospheric chemistry and physics. 12(4). 2025–2035. 63 indexed citations
14.
Shi, Yan, et al.. (2012). PYROLYSIS OF YAOJIE OIL SHALE IN A SANJIANG-TYPE PILOT-SCALE RETORT; pp. 368–375. Oil Shale. 29(4). 368–375. 10 indexed citations
15.
Yang, Fumo, Lin Huang, Fengkui Duan, et al.. (2011). Carbonaceous species in PM 2.5 at a pair of rural/urban sites in Beijing, 2005–2008. Atmospheric chemistry and physics. 11(15). 7893–7903. 65 indexed citations
16.
Yang, Fumo, Jihua Tan, Qingguo Zhao, et al.. (2011). Characteristics of PM 2.5 speciation in representative megacities and across China. Atmospheric chemistry and physics. 11(11). 5207–5219. 528 indexed citations breakdown →
17.
Zhao, Qing, Kebin He, Kenneth A. Rahn, et al.. (2010). Dust storms come to Central and Southwestern China, too: implications from a major dust event in Chongqing. Atmospheric chemistry and physics. 10(6). 2615–2630. 56 indexed citations
18.
Cheng, Yuan, Kebin He, Fengkui Duan, et al.. (2009). Measurement of semivolatile carbonaceous aerosols and its implications: A review. Environment International. 35(3). 674–681. 37 indexed citations
19.
He, Keyou, Y. Ma, Fan Yang, et al.. (2005). Concentration and chemical characteristics of PM2.5 in Beijing, China: 2001–2002. The Science of The Total Environment. 355(1-3). 264–275. 241 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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