World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
43
Citations
5991
World Ranking
7200
National Ranking
711

Shaocai Yu 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 Shaocai Yu 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: 282 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: 26 scientists 501–510 publications: 17 scientists 511–520 publications: 19 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 681–689 publications: 4 scientists 690+ publications: 100 scientists
41 publications 690+

This scientist: 121 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 690 publications or more.

Shaocai Yu 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 Shaocai Yu 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: 198 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: 20 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: 9 scientists 126+ D-Index: 92 scientists
30 D-Index 126+

This scientist: 43 D-Index — 29th percentile

29% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 126 D-Index or more.

Overview

Shaocai Yu is a researcher affiliated with Zhejiang University in China, focusing primarily on environmental science and earth and planetary sciences. Their body of work spans multiple interconnected disciplines related to atmospheric processes, air quality, and environmental impacts.

The scientist's main fields of study include:

  • Environmental Science
  • Earth and Planetary Sciences

Within these broader fields, their subfields of study involve:

  • Atmospheric Science
  • Health, Toxicology and Mutagenesis
  • Environmental Engineering
  • Global and Planetary Change
  • Automotive Engineering

Shaocai Yu's research topics cover a range of air quality and atmospheric chemistry issues, including:

  • Air Quality and Health Impacts
  • Atmospheric chemistry and aerosols
  • Air Quality Monitoring and Forecasting
  • Vehicle emissions and performance
  • Atmospheric Ozone and Climate
  • Atmospheric and Environmental Gas Dynamics
  • Atmospheric aerosols and clouds

The frequent publication venues where their work appears include:

  • Atmospheric chemistry and physics
  • Environmental Chemistry Letters
  • Atmosphere
  • Environmental Science & Technology
  • The Science of The Total Environment

Collaboration is a notable aspect of their research, working often with the following co-authors:

  • Mengying Li
  • Daniel Rosenfeld
  • Zhe Song
  • Pengfei Li
  • John H. Seinfeld

Some of Shaocai Yu's recent papers include:

  • "Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality," 2020, Environmental Chemistry Letters
  • "Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China," 2021, One Earth
  • "Large scale control of surface ozone by relative humidity observed during warm seasons in China," 2021, Environmental Chemistry Letters
  • "City-level air quality improvement in the Beijing-Tianjin-Hebei region from 2016/17 to 2017/18 heating seasons: Attributions and process analysis," 2021, Environmental Pollution
  • "Relative effects of open biomass burning and open crop straw burning on haze formation over central and eastern China: modeling study driven by constrained emissions," 2020, Atmospheric chemistry and physics

Best Publications

  • Aerosol-driven droplet concentrations dominate coverage and water of oceanic low level clouds

    Daniel Rosenfeld;Daniel Rosenfeld;Yannian Zhu;Minghuai Wang;Youtong Zheng

  • New unbiased symmetric metrics for evaluation of air quality models

    Shaocai Yu;Brian Eder;Robin Dennis;Shao-Hang Chu

  • Role of organic acids formic, acetic, pyruvic and / oxalic in the formation of cloud condensation / nuclei CCN : a review

    Shaocai Yu

  • A performance evaluation of the 2004 release of Models-3 CMAQ

    Brian K. Eder;Shaocai Yu

  • Primary and secondary organic aerosols over the United States: estimates on the basis of observed organic carbon (OC) and elemental carbon (EC), and air quality modeled primary OC/EC ratios

    Shaocai Yu;Robin L. Dennis;Prakash V. Bhave;Brian K. Eder

  • Evaluation of several PM2.5 forecast models using data collected during the ICARTT/NEAQS 2004 field study

    S. McKeen;S. H. Chung;J. Wilczak;G. Grell

  • An operational evaluation of the Eta-CMAQ air quality forecast model

    Brian Eder;Daiwen Kang;Rohit Mathur;Shaocai Yu

  • An assessment of the ability of three‐dimensional air quality models with current thermodynamic equilibrium models to predict aerosol NO3−

    Shaocai Yu;Shaocai Yu;Robin Dennis;Robin Dennis;Shawn Roselle;Shawn Roselle;Athanasios Nenes

  • Reinstate regional transport of PM2.5 as a major cause of severe haze in Beijing

    Pengfei Li;Renchang Yan;Shaocai Yu;Si Wang

  • Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis

    S. Yu;R. Mathur;J. Pleim;D. Wong

  • Seasonal and regional variations of primary and secondary organic aerosols over the continental United States: semi-empirical estimates and model evaluation.

    Shaocai Yu;Prakash V. Bhave;Robin L. Dennis;Rohit Mathur

  • Evaluation of real‐time PM2.5 forecasts and process analysis for PM2.5 formation over the eastern United States using the Eta‐CMAQ forecast model during the 2004 ICARTT study

    Shaocai Yu;Rohit Mathur;Kenneth Schere;Daiwen Kang

  • Spatial and temporal distributions of air pollutant emissions from open crop straw and biomass burnings in China from 2002 to 2016

    Khalid Mehmood;Shucheng Chang;Shaocai Yu;Shaocai Yu;Liqiang Wang

  • Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality.

    Liqiang Wang;Mengying Li;Shaocai Yu;Shaocai Yu;Xue Chen

  • Bias adjustment techniques for improving ozone air quality forecasts

    Daiwen Kang;Rohit Mathur;S. Trivikrama Rao;Shaocai Yu

  • A detailed evaluation of the Eta-CMAQ forecast model performance for O3, its related precursors, and meteorological parameters during the 2004 ICARTT study

    Shaocai Yu;Rohit Mathur;Kenneth Schere;Daiwen Kang

  • The impact of chemical lateral boundary conditions on CMAQ predictions of tropospheric ozone over the continental United States

    Youhua Tang;Youhua Tang;Pius Lee;Marina Tsidulko;Ho Chun Huang

  • Attribution of the United States "warming hole": aerosol indirect effect and precipitable water vapor.

    Shaocai Yu;Kiran Alapaty;Rohit Mathur;Jonathan Pleim

  • Assessment of the wintertime performance of developmental particulate matter forecasts with the Eta-Community Multiscale Air Quality modeling system

    Rohit Mathur;Shaocai Yu;Daiwen Kang;Kenneth L. Schere

  • A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

    Brian Eder;Daiwen Kang;Rohit Mathur;Jon Pleim

  • Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

    Liqiang Wang;Xue Chen;Yibo Zhang;Mengying Li

  • Large scale control of surface ozone by relative humidity observed during warm seasons in China

    Mengying Li;Shaocai Yu;Shaocai Yu;Xue Chen;Zhen Li

  • An Operational Evaluation of ETA-CMAQ Air Quality Forecast Model

    Unknown

Frequent Co-Authors

Weiping Liu
Weiping Liu Zhejiang University
Rohit Mathur
Rohit Mathur Environmental Protection Agency
Daniel Rosenfeld
Daniel Rosenfeld Hebrew University of Jerusalem
John H. Seinfeld
John H. Seinfeld California Institute of Technology
Daiwen Kang
Daiwen Kang Environmental Protection Agency
Daniel Tong
Daniel Tong George Mason University
Jonathan E. Pleim
Jonathan E. Pleim Environmental Protection Agency
Robin L. Dennis
Robin L. Dennis Environmental Protection Agency
George Pouliot
George Pouliot Environmental Protection Agency
Yang Zhang
Yang Zhang Northeastern University

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