Ling Jin

1.2k total citations
54 papers, 905 citations indexed

About

Ling Jin is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Transportation. According to data from OpenAlex, Ling Jin has authored 54 papers receiving a total of 905 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Atmospheric Science, 12 papers in Health, Toxicology and Mutagenesis and 11 papers in Transportation. Recurrent topics in Ling Jin's work include Atmospheric chemistry and aerosols (15 papers), Air Quality and Health Impacts (10 papers) and Urban Transport and Accessibility (8 papers). Ling Jin is often cited by papers focused on Atmospheric chemistry and aerosols (15 papers), Air Quality and Health Impacts (10 papers) and Urban Transport and Accessibility (8 papers). Ling Jin collaborates with scholars based in United States, China and France. Ling Jin's co-authors include Nancy J. Brown, Corinne D. Scown, C. Anna Spurlock, Hanna Breunig, Annika Todd, Andrew Satchwell, Sarah Smith, Chelsea V. Preble, Thomas W. Kirchstetter and Robert A. Harley and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Environmental Science & Technology.

In The Last Decade

Ling Jin

50 papers receiving 874 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ling Jin United States 17 165 152 147 141 130 54 905
J. S. Pandey India 5 55 0.3× 131 0.9× 64 0.4× 57 0.4× 271 2.1× 19 662
Shan Guo China 16 58 0.4× 131 0.9× 75 0.5× 249 1.8× 803 6.2× 37 1.1k
Mazaher Moeinaddini Iran 11 48 0.3× 263 1.7× 57 0.4× 131 0.9× 242 1.9× 35 874
Xueyan Li China 15 45 0.3× 69 0.5× 107 0.7× 54 0.4× 63 0.5× 78 906
G. Banias Greece 21 44 0.3× 164 1.1× 64 0.4× 379 2.7× 133 1.0× 37 1.3k
W. Schoepp Austria 19 387 2.3× 544 3.6× 300 2.0× 43 0.3× 352 2.7× 65 1.2k
Davor Antanasijević Serbia 21 43 0.3× 270 1.8× 105 0.7× 108 0.8× 622 4.8× 50 1.4k
Yoshikuni Yoshida Japan 22 28 0.2× 170 1.1× 124 0.8× 269 1.9× 728 5.6× 93 1.6k
Viktor Pocajt Serbia 20 29 0.2× 196 1.3× 109 0.7× 108 0.8× 597 4.6× 41 1.2k

Countries citing papers authored by Ling Jin

Since Specialization
Citations

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

Fields of papers citing papers by Ling Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Jin. A scholar is included among the top collaborators of Ling Jin 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 Ling Jin. Ling Jin 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.
Sun, Bingrong, Venu Garikapati, Mohamed Amine Bouzaghrane, et al.. (2025). Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life. Transportation Research Record Journal of the Transportation Research Board. 2679(8). 214–232.
2.
Wang, Yuan, et al.. (2025). Temperature and stagnation effects on ozone sensitivity to NO x and VOC: an adjoint modeling study in central California. Atmospheric chemistry and physics. 25(23). 17651–17665.
3.
Hu, Zhaoping, et al.. (2025). DeepAir: deep learning and satellite imagery to estimate high-resolution PM2.5 at scale. Machine Learning Science and Technology. 6(1). 15057–15057. 2 indexed citations
4.
Jin, Ling, Xiaodan Xu, Yuhan Wang, et al.. (2024). Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 6(3). 1 indexed citations
5.
He, Yichao, Huili Wang, Yixuan Zheng, et al.. (2024). Revealing air quality impacts of the clean heating campaign in northern China. Energy Economics. 141. 108078–108078. 4 indexed citations
6.
Jin, Ling, et al.. (2023). Location-Specific Control of Precursor Emissions to Mitigate Photochemical Air Pollution. Environmental Science & Technology. 57(26). 9693–9701. 5 indexed citations
7.
Jin, Ling, Alina Lazar, Annika Todd, et al.. (2023). Gender Gaps in Mode Usage, Vehicle Ownership, and Spatial Mobility When Entering Parenthood: A Life Course Perspective. Systems. 11(6). 314–314. 7 indexed citations
8.
Jin, Ling, et al.. (2022). Responses of Photochemical Air Pollution in California’s San Joaquin Valley to Spatially and Temporally Resolved Changes in Precursor Emissions. Environmental Science & Technology. 56(11). 7074–7082. 5 indexed citations
9.
Nordahl, Sarah, Jay Devkota, Sarah Smith, et al.. (2020). Life-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management Strategies. Environmental Science & Technology. 54(15). 9200–9209. 126 indexed citations
10.
Jin, Ling, Alina Lazar, James W. Sears, et al.. (2020). Clustering Life Course to Understand the Heterogeneous Effects of Life Events, Gender, and Generation on Habitual Travel Modes. IEEE Access. 8. 190964–190980. 9 indexed citations
11.
Todd, Annika, Peter Cappers, C. Anna Spurlock, & Ling Jin. (2019). Spillover as a cause of bias in baseline evaluation methods for demand response programs. Applied Energy. 250. 344–357. 5 indexed citations
12.
Lazar, Alina, Ling Jin, C. Anna Spurlock, et al.. (2019). Evaluating the Effects of Missing Values and Mixed Data Types on Social Sequence Clustering Using t-SNE Visualization. Journal of Data and Information Quality. 11(2). 1–22. 8 indexed citations
13.
Breunig, Hanna, et al.. (2018). Dynamic Geospatial Modeling of the Building Stock To Project Urban Energy Demand. Environmental Science & Technology. 52(14). 7604–7613. 14 indexed citations
14.
Breunig, Hanna, et al.. (2018). Temporal and geographic drivers of biomass residues in California. Resources Conservation and Recycling. 139. 287–297. 17 indexed citations
15.
Breunig, Hanna, et al.. (2017). Bioenergy Potential from Food Waste in California. Environmental Science & Technology. 51(3). 1120–1128. 57 indexed citations
16.
Jin, Ling, Doris Lee, Alex Sim, et al.. (2017). Comparison of Clustering Techniques for Residential Energy Behavior using Smart Meter Data. eScholarship (California Digital Library). 32 indexed citations
17.
Jin, Ling. (2010). Seasonal versus Episodic Performance Evaluation for an Eulerian Photochemical\nAir Quality Model. eScholarship (California Digital Library). 17 indexed citations
18.
Jin, Ling, et al.. (2008). Sensitivity Analysis of Ozone Formation and Transport for a Central California Air Pollution Episode. Environmental Science & Technology. 42(10). 3683–3689. 32 indexed citations
19.
Jin, Ling, et al.. (2007). Direct sensitivity analysis of ozone formation and transport in California's San Joaquin Valley. AGU Fall Meeting Abstracts. 2007. 1 indexed citations
20.
Jin, Ling, Nancy J. Brown, S. Tonse, et al.. (2007). DIAGNOSTIC AND MECHANISTIC EVALUATIONS OF MM5-CMAQV4.6 FOR THE SUMMER 2000 CENTRAL CALIFORNIA OZONE STUDY. eScholarship (California Digital Library). 2006. 2 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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