World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
71
Citations
16046
World Ranking
1615
National Ranking
684

Jun Wang publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Jun Wang sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 289 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Jun Wang D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Jun Wang sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 71 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Jun Wang is a researcher affiliated with the University of Iowa in the United States. Their work is primarily situated within the fields of Environmental Science and Earth and Planetary Sciences, with a strong focus on Atmospheric Science and related subfields.

Their main research topics cover various aspects of atmospheric chemistry and aerosols, including:

  • Atmospheric chemistry and aerosols
  • Atmospheric aerosols and clouds
  • Atmospheric and Environmental Gas Dynamics
  • Air Quality and Health Impacts
  • Atmospheric Ozone and Climate
  • Air Quality Monitoring and Forecasting
  • Climate variability and models

Jun Wang has contributed to several recent papers published in notable scientific journals. Some of the key publications include:

  • Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China, 2021, Remote Sensing of Environment
  • Evaluation of the ERA5 reanalysis precipitation dataset over Chinese Mainland, 2020, Journal of Hydrology
  • Six global biomass burning emission datasets: intercomparison and application in one global aerosol model, 2020, Atmospheric chemistry and physics
  • Ground-level gaseous pollutants (NO2, SO2, and CO) in China: daily seamless mapping and spatiotemporal variations, 2023, Atmospheric chemistry and physics
  • Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence, 2022, Environmental Science & Technology

The publication venues where Jun Wang frequently publishes include:

  • Harvard Dataverse
  • Atmospheric chemistry and physics
  • Journal of Geophysical Research Atmospheres
  • Zenodo (CERN European Organization for Nuclear Research)
  • SSRN Electronic Journal

Jun Wang often collaborates with several other researchers, reflecting a network of frequent co-authors, which include:

  • Daven K. Henze
  • Zhen Qu
  • Meng Zhou
  • Nicolas Theys
  • Jing Wei

Overall, Jun Wang's body of work reflects a comprehensive engagement with the study of atmospheric processes, pollution mapping, emission datasets, and the application of artificial intelligence for environmental monitoring. Their research contributes to a better understanding of air quality variations and the implications of atmospheric chemicals on health and climate.

Best Publications

  • Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies

    Jun Wang;Sundar A. Christopher

  • Satellite remote sensing of particulate matter and air quality assessment over global cities

    Pawan Gupta;Sundar A. Christopher;Jun Wang;Robert Gehrig

  • Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

    Jing Wei;Jing Wei;Zhanqing Li;Ke Li;Russell R. Dickerson

  • Tropospheric emissions: Monitoring of pollution (TEMPO)

    P. Zoogman;X. Liu;R.M. Suleiman;W.F. Pennington

  • Observing and understanding the Southeast Asian aerosol system by remote sensing: An initial review and analysis for the Seven Southeast Asian Studies (7SEAS) program

    Jeffrey S. Reid;Edward J. Hyer;Randall S. Johnson;Brent N. Holben

  • Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program

    J.S. Reid;E.J. Hyer;E.M. Prins;D.L. Westphal

  • Global budget and radiative forcing of black carbon aerosol: Constraints from pole-to-pole (HIPPO) observations across the Pacific

    Qiaoqiao Wang;Daniel James Jacob;J. Ryan Spackman;Anne E. Perring;Anne E. Perring

  • Intercomparison of SCIAMACHY and OMI Tropospheric NO2 Columns: Observing the Diurnal Evolution of Chemistry and Emissions from Space

    K. Folkert Boersma;K. Folkert Boersma;Daniel J. Jacob;Henk J. Eskes;Robert W. Pinder

  • Six global biomass burning emission datasets: intercomparison and application in one global aerosol model

    Xiaohua Pan;Xiaohua Pan;Charles Ichoku;Mian Chin;Huisheng Bian;Huisheng Bian

  • Origin and radiative forcing of black carbon transported to the Himalayas and Tibetan Plateau

    M. Kopacz;Denise Leonore Mauzerall;J. Wang;E. M. Leibensperger

  • Variation in the urban vegetation, surface temperature, air temperature nexus.

    Sheri A. Shiflett;Liyin L. Liang;Liyin L. Liang;Steven M. Crum;Gudina L. Feyisa

  • Synthesis of satellite (MODIS), aircraft (ICARTT), and surface (IMPROVE, EPA-AQS, AERONET) aerosol observations over eastern North America to improve MODIS aerosol retrievals and constrain surface aerosol concentrations and sources

    Easan Drury;Easan Drury;Daniel James Jacob;Robert J. D. Spurr;Jun Wang

  • NCEP Climate Forecast System Reanalysis (CFSR) 6-hourly Products, January 1979 to December 2010

    Suranjana Saha;Shrinivas Moorthi;Hua-Lu Pan;Xingren Wu

  • Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over land from satellite observation

    Zhengqiang Li;Weizhen Hou;Jin Hong;Fengxun Zheng

  • An overview of the Amazonian Aerosol Characterization Experiment 2008 (AMAZE-08)

    S. T. Martin;M. O. Andreae;D. Althausen;P. Artaxo

  • Mesoscale modeling of Central American smoke transport to the United States: 1. “Top-down” assessment of emission strength and diurnal variation impacts

    Jun Wang;Jun Wang;Sundar A. Christopher;U. S. Nair;Jeffrey S. Reid

  • Multidecadal trends in aerosol radiative forcing over the Arctic: Contribution of changes in anthropogenic aerosol to Arctic warming since 1980

    Thomas J. Breider;Loretta J. Mickley;Daniel J. Jacob;Cui Ge

  • Himawari-8-derived diurnal variations in ground-level PM 2.5 pollution across China using the fast space-time Light Gradient Boosting Machine (LightGBM)

    Jing Wei;Jing Wei;Jing Wei;Zhanqing Li;Rachel T. Pinker;Jun Wang

  • Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region

    P. Y. Oikawa;C. Ge;J. Wang;J. R. Eberwein

  • Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

    David J. Diner;Stacey W. Boland;Michael Brauer;Carol Bruegge

  • Optimal estimation for global ground-level fine particulate matter concentrations

    Aaron van Donkelaar;Randall V. Martin;Randall V. Martin;Robert J. D. Spurr;Easan Drury

Frequent Co-Authors

Jeffrey S. Reid
Jeffrey S. Reid United States Naval Research Laboratory
Sundar A. Christopher
Sundar A. Christopher University of Alabama in Huntsville
Edward J. Hyer
Edward J. Hyer United States Naval Research Laboratory
Daniel J. Jacob
Daniel J. Jacob Harvard University
Daven K. Henze
Daven K. Henze University of Colorado Boulder
Charles Ichoku
Charles Ichoku Goddard Space Flight Center
Xiangao Xia
Xiangao Xia Chinese Academy of Sciences
Randall V. Martin
Randall V. Martin Washington University in St. Louis
Robert Spurr
Robert Spurr Harvard University
Nickolay A. Krotkov
Nickolay A. Krotkov Goddard Space Flight Center

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