World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
47
Citations
22933
World Ranking
5655
National Ranking
2052

Arlindo da Silva 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 Arlindo da Silva 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: 165 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Arlindo da Silva 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 Arlindo da Silva 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: 47 D-Index — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Overview

Arlindo da Silva is affiliated with the Goddard Space Flight Center in the United States and has a research profile focused on atmospheric science and environmental science. Their work spans several interconnected disciplines, including global and planetary change, atmospheric science, and environmental impacts linked to aerosols and gases.

Their research topics cover a broad range of subjects related to atmospheric chemistry and aerosols, atmospheric aerosols and clouds, atmospheric and environmental gas dynamics, atmospheric ozone and climate, fire effects on ecosystems, air quality and health impacts, and aeolian processes and effects.

Some of the recent publications by Arlindo da Silva include:

  • Six global biomass burning emission datasets: intercomparison and application in one global aerosol model, 2020, Atmospheric chemistry and physics
  • An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol-cloud-radiation interactions in the southeast Atlantic basin, 2021, Atmospheric chemistry and physics
  • How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, 2020, Atmospheric chemistry and physics
  • Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations, 2020, Atmospheric chemistry and physics
  • Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016, 2020, Atmospheric chemistry and physics

Frequent co-authors collaborating with Arlindo da Silva include Peter R. Colarco, Jens Redemann, Mian Chin, Pablo E. Saide, and R. A. Ferrare.

The primary venues where Arlindo da Silva has published are:

  • Atmospheric chemistry and physics
  • Zenodo (CERN European Organization for Nuclear Research)
  • Journal of Geophysical Research Atmospheres
  • Geoscientific model development
  • Bulletin of the American Meteorological Society

Their main fields of study are Environmental Science and Earth and Planetary Sciences, with a concentration in subfields such as Global and Planetary Change, Atmospheric Science, Health, Toxicology and Mutagenesis, Radiology, Nuclear Medicine and Imaging, and Earth-Surface Processes.

Best Publications

  • The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

    Ronald Gelaro;Will McCarty;Max J. Suárez;Max J. Suárez;Ricardo Todling

  • MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications

    Michele M. Rienecker;Max J. Suarez;Ronald Gelaro;Ricardo Todling

  • Online simulations of global aerosol distributions in the NASA GEOS‐4 model and comparisons to satellite and ground‐based aerosol optical depth

    Peter Colarco;Arlindo da Silva;Mian Chin;Thomas Diehl;Thomas Diehl

  • The architecture of the Earth System Modeling Framework

    Unknown

  • Data assimilation in the presence of forecast bias

    Dick P. Dee;Arlindo M. Da Silva

  • Assessing the Effects of Data Selection with the DAO Physical-Space Statistical Analysis System*

    Stephen E. Cohn;Arlindo da Silva;Jing Guo;Meta Sienkiewicz

  • Decadal and interannual SST variability in the tropical Atlantic Ocean

    James A. Carton;Xianhe Cao;Benjamin S. Giese;Arlindo M. Da Silva

  • 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

  • The Quick Fire Emissions Dataset (QFED): Documentation of Versions 2.1, 2.2 and 2.4

    Randal D. Koster;Anton S. Darmenov;Arlindo M. da Silva

  • Design and Implementation of Components in the Earth System Modeling Framework

    Nancy Collins;Gerhard Theurich;Cecelia Deluca;Max Suarez

  • An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin

    Jens Redemann;Robert Wood;Paquita Zuidema;Sarah J. Doherty

  • Maximum-Likelihood Estimation of Forecast and Observation Error Covariance Parameters. Part I: Methodology

    Dick P. Dee;Arlindo M. da Silva

  • Satellite-based estimates of ground-level fine particulate matter during extreme events: A case study of the Moscow fires in 2010

    Aaron van Donkelaar;Randall V. Martin;Randall V. Martin;Robert C. Levy;Arlindo M. da Silva

  • Moisture budget of the bimodal pattern of the summer circulation over South America

    Dirceu L. Herdies;Dirceu L. Herdies;Arlindo da Silva;Maria A. F. Silva Dias;Rosana Nieto Ferreira

  • MODIS aerosol optical depth observations over urban areas in Pakistan: quantity and quality of the data for air quality monitoring

    Pawan Gupta;Pawan Gupta;Maudood N. Khan;Arlindo da Silva;Falguni Patadia;Falguni Patadia

  • How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America

    Therese S. Carter;Colette L. Heald;Jose L. Jimenez;Pedro Campuzano-Jost

  • The Choice of Variable for Atmospheric Moisture Analysis

    Dick P. Dee;Arlindo M. da Silva

  • Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations

    Alexander Ukhov;Suleiman Mostamandi;Arlindo Da Silva;J. Flemming

  • Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP).

    Peng Xian;Jeffrey S. Reid;Edward J. Hyer;Charles R. Sampson

  • Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Sensors

    Arthur Y. Hou;Sara Q. Zhang;Arlindo M. da Silva;William S. Olson

  • Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion

    Pablo E Saide;David A Peterson;Arlindo da Silva;Bruce Anderson

  • Sensitivity of mesoscale modeling of smoke direct radiative effect to the emission inventory: a case study in northern sub-Saharan African region

    Feng Zhang;Feng Zhang;Jun Wang;Charles Ichoku;Edward J. Hyer

  • Assimilation of SSM/I-Derived Surface Rainfall and Total Precipitable Water for Improving the GEOS Analysis for Climate Studies

    Arthur Y. Hou;David V. Ledvina;Arlindo M. da Silva;Sara Q. Zhang

  • A new global anthropogenic SO 2 emission inventory for the last decade: a mosaic of satellite-derived and bottom-up emissions

    Fei Liu;Fei Liu;Sungyeon Choi;Can Li;Can Li;Vitali E. Fioletov

Frequent Co-Authors

Peter R. Colarco
Peter R. Colarco Goddard Space Flight Center
Pablo E. Saide
Pablo E. Saide University of California, Los Angeles
Kyu-Myong Kim
Kyu-Myong Kim Goddard Space Flight Center
Richard A. Ferrare
Richard A. Ferrare Langley Research Center
Mian Chin
Mian Chin Goddard Space Flight Center
Pinhas Alpert
Pinhas Alpert Tel Aviv University
Gregory R. Carmichael
Gregory R. Carmichael University of Iowa
Robert C. Levy
Robert C. Levy Goddard Space Flight Center
Brent N. Holben
Brent N. Holben Goddard Space Flight Center
Michael G. Bosilovich
Michael G. Bosilovich Goddard Space Flight Center

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Exploring these diverse yet interconnected pathways helps students tailor their education to their career goals within the broad scope of Environmental Sciences.

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