Danlu Chen

2.1k total citations · 1 hit paper
16 papers, 1.5k citations indexed

About

Danlu Chen is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, Danlu Chen has authored 16 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Atmospheric Science, 10 papers in Health, Toxicology and Mutagenesis and 7 papers in Environmental Engineering. Recurrent topics in Danlu Chen's work include Atmospheric chemistry and aerosols (11 papers), Air Quality and Health Impacts (10 papers) and Air Quality Monitoring and Forecasting (6 papers). Danlu Chen is often cited by papers focused on Atmospheric chemistry and aerosols (11 papers), Air Quality and Health Impacts (10 papers) and Air Quality Monitoring and Forecasting (6 papers). Danlu Chen collaborates with scholars based in China, United States and Netherlands. Danlu Chen's co-authors include Ziyue Chen, Bingbo Gao, Yan Zhuang, Ruiyuan Li, Bin He, Bing Xu, Jun Cai, Nianliang Cheng, Бин Чэн and Mei‐Po Kwan and has published in prestigious journals such as Journal of Hazardous Materials, Journal of Cleaner Production and Environmental Pollution.

In The Last Decade

Danlu Chen

14 papers receiving 1.5k citations

Hit Papers

Influence of meteorologic... 2020 2026 2022 2024 2020 100 200 300 400
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. Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism
    2020 481 citations Ziyue Chen, Danlu Chen et al. Environment International profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Danlu Chen 1.1k 981 773 415 167 16 1.5k
Hongli Liu 875 0.8× 902 0.9× 556 0.7× 601 1.4× 108 0.6× 56 1.5k
Shixian Zhai 1.5k 1.4× 1.6k 1.7× 910 1.2× 751 1.8× 214 1.3× 44 2.2k
S. D. Attri 918 0.8× 1.0k 1.0× 435 0.6× 760 1.8× 137 0.8× 37 1.5k
Qi Fan 815 0.7× 1.0k 1.0× 471 0.6× 545 1.3× 112 0.7× 58 1.4k
Nianliang Cheng 1.1k 1.0× 1.1k 1.1× 726 0.9× 382 0.9× 217 1.3× 41 1.5k
Daiying Yin 888 0.8× 832 0.8× 463 0.6× 353 0.9× 135 0.8× 29 1.1k
Jun‐ichi Kurokawa 720 0.6× 1.2k 1.3× 250 0.3× 733 1.8× 174 1.0× 25 1.5k
Rita Yuri Ynoue 1.0k 0.9× 780 0.8× 457 0.6× 374 0.9× 489 2.9× 49 1.4k
Zhaoxin Dong 657 0.6× 568 0.6× 375 0.5× 181 0.4× 176 1.1× 35 926
Alexander de Meij 523 0.5× 1.1k 1.1× 259 0.3× 812 2.0× 144 0.9× 45 1.4k

Countries citing papers authored by Danlu Chen

Since Specialization
Citations

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

Fields of papers citing papers by Danlu Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danlu Chen

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

All Works

16 of 16 papers shown
1.
2.
Liu, Zhixiong, Feng Feng, Danlu Chen, et al.. (2024). A novel bio-based fluorescent N, P-CDs@CMC/PEI composite hydrogel for sensitive detection and efficient capture of toxic heavy metal ions. Journal of Hazardous Materials. 474. 134757–134757. 27 indexed citations
3.
Chen, Danlu, Manchun Li, Ruiyuan Li, et al.. (2021). Estimating the impact of ground ozone concentrations on crop yields across China from 2014 to 2018: A multi-model comparison. Environmental Pollution. 283. 117099–117099. 28 indexed citations
4.
Chen, Ziyue, Danlu Chen, Chuanfeng Zhao, et al.. (2020). Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism. Environment International. 139. 105558–105558. 481 indexed citations breakdown →
5.
Li, Ruiyuan, Ziyue Chen, Bingbo Gao, et al.. (2020). Phenology-based classification of crop species and rotation types using fused MODIS and Landsat data: The comparison of a random-forest-based model and a decision-rule-based model. Soil and Tillage Research. 206. 104838–104838. 58 indexed citations
6.
7.
Chen, Ziyue, Danlu Chen, Mei‐Po Kwan, et al.. (2019). The control of anthropogenic emissions contributed to 80 % of the decrease in PM 2.5 concentrations in Beijing from 2013 to 2017. Atmospheric chemistry and physics. 19(21). 13519–13533. 106 indexed citations
8.
Chen, Ziyue, Ruiyuan Li, Danlu Chen, et al.. (2019). Understanding the causal influence of major meteorological factors on ground ozone concentrations across China. Journal of Cleaner Production. 242. 118498–118498. 115 indexed citations
9.
Cheng, Nianliang, Ruiyuan Li, Chunxue Xu, et al.. (2019). Ground ozone variations at an urban and a rural station in Beijing from 2006 to 2017: Trend, meteorological influences and formation regimes. Journal of Cleaner Production. 235. 11–20. 103 indexed citations
10.
Chen, Ziyue, Xiaoming Xie, Jun Cai, et al.. (2018). Understanding meteorological influences on PM 2.5 concentrations across China: a temporal and spatial perspective. Atmospheric chemistry and physics. 18(8). 5343–5358. 198 indexed citations
11.
Chen, Ziyue, Yan Zhuang, Xiaoming Xie, et al.. (2018). Understanding long-term variations of meteorological influences on ground ozone concentrations in Beijing During 2006–2016. Environmental Pollution. 245. 29–37. 130 indexed citations
12.
Zhuang, Yan, Danlu Chen, Ruiyuan Li, et al.. (2018). Understanding the Influence of Crop Residue Burning on PM2.5 and PM10 Concentrations in China from 2013 to 2017 Using MODIS Data. International Journal of Environmental Research and Public Health. 15(7). 1504–1504. 20 indexed citations
13.
Chen, Ziyue, Danlu Chen, Xiaoming Xie, et al.. (2018). Spatial self-aggregation effects and national division of city-level PM2.5 concentrations in China based on spatio-temporal clustering. Journal of Cleaner Production. 207. 875–881. 42 indexed citations
14.
Zhuang, Yan, Ruiyuan Li, Hao Yang, et al.. (2018). Understanding Temporal and Spatial Distribution of Crop Residue Burning in China from 2003 to 2017 Using MODIS Data. Remote Sensing. 10(3). 390–390. 55 indexed citations
15.
Chen, Ziyue, Danlu Chen, Yan Zhuang, et al.. (2017). Examining the Influence of Crop Residue Burning on Local PM2.5 Concentrations in Heilongjiang Province Using Ground Observation and Remote Sensing Data. Remote Sensing. 9(10). 971–971. 9 indexed citations
16.
Fu, Jie, Danlu Chen, Miao Liu, et al.. (2016). Deep Reinforcement Learning for Accelerating the Convergence Rate. arXiv (Cornell University).

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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