Nathan Pavlovic

727 total citations
32 papers, 482 citations indexed

About

Nathan Pavlovic is a scholar working on Health, Toxicology and Mutagenesis, Global and Planetary Change and Pollution. According to data from OpenAlex, Nathan Pavlovic has authored 32 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Health, Toxicology and Mutagenesis, 8 papers in Global and Planetary Change and 7 papers in Pollution. Recurrent topics in Nathan Pavlovic's work include Air Quality and Health Impacts (22 papers), Climate Change and Health Impacts (11 papers) and Energy and Environment Impacts (7 papers). Nathan Pavlovic is often cited by papers focused on Air Quality and Health Impacts (22 papers), Climate Change and Health Impacts (11 papers) and Energy and Environment Impacts (7 papers). Nathan Pavlovic collaborates with scholars based in United States, China and Australia. Nathan Pavlovic's co-authors include Frederick Lurmann, Rima Habre, Carrie V. Breton, Frank D. Gilliland, Meredith Franklin, Mariam Girguis, Jun Wu, Sandrah P. Eckel, Anny H. Xiang and Zhanghua Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Nathan Pavlovic

29 papers receiving 473 citations

Peers

Nathan Pavlovic

HTM

GPC

POLLU

Baixiang Feng China

Sereeter Lodoysamba Mongolia

Moa K. Sporre Sweden

Rod Simpson Australia

Johnathan Rush United States

Teerachai Amnuaylojaroen Thailand

Silas Bergen United States

Wenchao Han China

Ville-Veikko Paunu Finland

Jia Coco Liu United States

Baixiang Feng China

Nathan Pavlovic

432 ×1.4

HTM

160 ×1.0

GPC

98 ×0.7

59 ×0.5

70 ×1.4

POLLU

Citations per year, relative to Nathan Pavlovic Nathan Pavlovic (= 1×) peers Baixiang Feng

Countries citing papers authored by Nathan Pavlovic

Since Specialization

Citations

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

Fields of papers citing papers by Nathan Pavlovic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan Pavlovic

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

All Works

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20 of 20 papers shown

Liu, Yisi, Xu Yan, Nathan Pavlovic, et al.. (2025). Adverse Birth Outcomes Associated with Heat Stress and Wildfire Smoke Exposure During Preconception and Pregnancy. Environmental Science & Technology. 59(25). 12458–12471.

Lurmann, Frederick, Nathan Pavlovic, Jun Wu, et al.. (2025). Knowledge-informed deep learning to mitigate bias in joint air pollutant prediction. Environment International. 206. 109915–109915.

Qiu, Chenyu, Jiayuan Hao, Jiawen Liao, et al.. (2025). Maternal metabolomics linking prenatal exposure to fine particulate matter and birth weight: a cross-sectional analysis of the MADRES cohort. Environmental Health. 24(1). 14–14. 2 indexed citations

Niu, Zhongzheng, Sandrah P. Eckel, Claudia M. Toledo‐Corral, et al.. (2024). Prenatal exposure to ambient air pollution and persistent postpartum depression. The Science of The Total Environment. 953. 176089–176089. 2 indexed citations

Garcia, Erika, Scott A. West, Steve Howland, et al.. (2024). Childhood Air Pollution Exposure Associated with Self-reported Bronchitic Symptoms in Adulthood. American Journal of Respiratory and Critical Care Medicine. 210(8). 1025–1034. 4 indexed citations

Chavez, Thomas, Sandrah P. Eckel, Tingyu Yang, et al.. (2024). Joint effects of traffic-related air pollution and hypertensive disorders of pregnancy on maternal postpartum depressive and anxiety symptoms. Journal of Exposure Science & Environmental Epidemiology. 35(2). 278–287. 2 indexed citations

Petrick, Lauren, Jiawen Liao, Nathan Pavlovic, et al.. (2024). Dysregulated metabolic pathways associated with air pollution exposure and the risk of autism: Evidence from epidemiological studies. Environmental Pollution. 361. 124729–124729. 5 indexed citations

Habre, Rima, Xu Yan, Steve Howland, et al.. (2024). Impact of childhood exposure to traffic related air pollution on adult cardiometabolic health: Exploring the role of perceived stress. Environmental Research. 263(Pt 2). 120130–120130. 2 indexed citations

Niu, Zhongzheng, Rima Habre, Tingyu Yang, et al.. (2024). Increased Risk of Gestational Hypertension by Periconceptional Exposure to Ambient Air Pollution and Effect Modification by Prenatal Depression. Hypertension. 81(6). 1285–1295. 3 indexed citations

10.

Johnson, Mark R., Sandrah P. Eckel, W. James Gauderman, et al.. (2023). Prenatal ambient air pollution exposure and child weight trajectories from the 3rd trimester of pregnancy to 2 years of age: a cohort study. BMC Medicine. 21(1). 341–341. 11 indexed citations

11.

McClure, Crystal D., et al.. (2023). Consistent, high-accuracy mapping of daily and sub-daily wildfire growth with satellite observations. International Journal of Wildland Fire. 32(5). 694–708. 11 indexed citations

12.

Niu, Zhongzheng, Rima Habre, Tingyu Yang, et al.. (2023). Preconceptional and prenatal exposure to air pollutants and risk of gestational diabetes in the MADRES prospective pregnancy cohort study. The Lancet Regional Health - Americas. 25. 100575–100575. 17 indexed citations

13.

Niu, Zhongzheng, Rima Habre, Thomas Chavez, et al.. (2022). Association Between Ambient Air Pollution and Birth Weight by Maternal Individual- and Neighborhood-Level Stressors. JAMA Network Open. 5(10). e2238174–e2238174. 35 indexed citations

14.

Yan, Xu, Li Yi, Thomas Chavez, et al.. (2022). The impact of GPS-derived activity spaces on personal PM2.5 exposures in the MADRES cohort. Environmental Research. 214(Pt 2). 114029–114029. 18 indexed citations

15.

Habre, Rima, Zhongzheng Niu, Tingyu Yang, et al.. (2022). Identifying pre-conception and pre-natal periods in which ambient air pollution exposure affects fetal growth in the predominately Hispanic MADRES cohort. Environmental Health. 21(1). 115–115. 5 indexed citations

16.

Chen, Zhanghua, Brian Z. Huang, Margo A. Sidell, et al.. (2021). Near-roadway air pollution associated with COVID-19 severity and mortality – Multiethnic cohort study in Southern California. Environment International. 157. 106862–106862. 21 indexed citations

17.

Carter, Sarah, Jane C. Lin, Yu‐Hsiang Shu, et al.. (2021). In utero exposure to near-roadway air pollution and autism spectrum disorder in children. Environment International. 158. 106898–106898. 37 indexed citations

18.

Li, Lianfa, Mariam Girguis, Frederick Lurmann, et al.. (2020). Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke. Environment International. 145. 106143–106143. 72 indexed citations

19.

Mukherjee, Anondo, et al.. (2019). Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors. Sensors. 19(21). 4701–4701. 31 indexed citations

20.

Franklin, Meredith, Mariam Girguis, Frederick Lurmann, et al.. (2019). Spatiotemporal imputation of MAIAC AOD using deep learning with downscaling. Remote Sensing of Environment. 237. 111584–111584. 94 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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