World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
40
Citations
4370
World Ranking
8196
National Ranking
365

Karine Sartelet 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 Karine Sartelet 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: 128 publications — 29th percentile

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

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

Karine Sartelet 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 Karine Sartelet 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: 40 D-Index — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Overview

Karine Sartelet is affiliated with École des Ponts ParisTech in France. Their research primarily focuses on environmental science and earth and planetary sciences, with particular attention to subfields such as health, toxicology and mutagenesis, atmospheric science, automotive engineering, environmental engineering, and global and planetary change.

Their work covers several main topics including air quality and health impacts, atmospheric chemistry and aerosols, vehicle emissions and performance, wind and air flow studies, air quality monitoring and forecasting, atmospheric aerosols and clouds, and atmospheric ozone and climate.

Frequent publication venues for Sartelet include:

  • Atmospheric chemistry and physics
  • Geoscientific model development
  • Atmospheric Environment
  • Atmosphere
  • The Science of The Total Environment

Recent papers authored or co-authored by Karine Sartelet include:

  • "SSH-Aerosol v1.1: A Modular Box Model to Simulate the Evolution of Primary and Secondary Aerosols," 2020, Atmosphere
  • "Nonstationary modeling of NO 2, NO and NO x in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach," 2020, Atmospheric chemistry and physics
  • "Diesel, petrol or electric vehicles: What choices to improve urban air quality in the Ile-de-France region? A simulation platform and case study," 2020, Atmospheric Environment
  • "Simulation of primary and secondary particles in the streets of Paris using MUNICH," 2020, Faraday Discussions
  • "Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)," 2021, Geoscientific model development

Their frequent co-authors include:

  • Youngseob Kim
  • Lya Lugon
  • Florian Couvidat
  • Alice Maison
  • Cédric Flageul

Sartelet's research often addresses the dynamics of air pollutants and particulate matter, particularly within urban environments such as Paris. Models like the Street-in-Grid and MUNICH have been used to study the interactions and evolution of aerosols and vehicle emissions, reflecting their interest in the coupling of local and regional air quality scales.

Their contributions engage with understanding the impacts of different vehicle technologies on urban air quality and the behaviors of primary and secondary aerosols. Their expertise in atmospheric chemistry and aerosols aligns with their focus on environmental and health impacts associated with air pollution.

Best Publications

  • Technical Note: The air quality modeling system Polyphemus

    Vivien Mallet;Vivien Mallet;D. Quélo;B. Sportisse;B. Sportisse;M. Ahmed de Biasi;M. Ahmed de Biasi

  • Operational model evaluation for particulate matter in Europe and North America in the context of AQMEII

    Efisio Solazzo;Roberto Bianconi;Guido Pirovano;Volker Matthias

  • Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

    Efisio Solazzo;Roberto Bianconi;Robert Vautard;K. Wyat Appel

  • Impact of biogenic emissions on air quality over Europe and North America

    Karine N. Sartelet;Florian Couvidat;Christian Seigneur;Yelva Roustan

  • MICS-Asia II: The model intercomparison study for Asia Phase II methodology and overview of findings

    G.R. Carmichael;T. Sakurai;D. Streets;Y. Hozumi

  • Simulation of aerosols and gas-phase species over Europe with the POLYPHEMUS system: Part I-Model-to-data comparison for 2001

    K.N. Sartelet;E. Debry;K. Fahey;Y. Roustan

  • Technical Note: A new SIze REsolved Aerosol Model (SIREAM)

    E. Debry;K. Fahey;K. Sartelet;B. Sportisse

  • A hydrophilic/hydrophobic organic (H2O) aerosol model: Development, evaluation and sensitivity analysis

    Florian Couvidat;Édouard Debry;Karine Sartelet;Christian Seigneur

  • Evaluation of the Weather Research and Forecast/Urban Model Over Greater Paris

    Youngseob Kim;Karine Sartelet;Jean-Christophe Raut;Patrick Chazette

  • SSH-Aerosol v1.1: A Modular Box Model to Simulate the Evolution of Primary and Secondary Aerosols

    Karine Sartelet;Florian Couvidat;Zhizhao Wang;Cédric Flageul

  • Modeling secondary organic aerosol in an urban area: application to Paris, France

    Florian Couvidat;Youngseob Kim;Karine Sartelet;Christian Seigneur

  • MICS-Asia II: Model intercomparison and evaluation of ozone and relevant species

    Z. Han;T. Sakurai;H. Ueda;G. R. Carmichael

  • Emission of intermediate, semi and low volatile organic compounds from traffic and their impact on secondary organic aerosol concentrations over Greater Paris

    K. Sartelet;S. Zhu;S. Zhu;S. Moukhtar;M. André

  • Comparison of different gas-phase mechanisms and aerosol modules for simulating particulate matter formation.

    Youngseob Kim;Florian Couvidat;Karine Sartelet;Christian Seigneur

  • Formation of secondary aerosols over Europe: comparison of two gas-phase chemical mechanisms

    Y. Kim;K. Sartelet;C. Seigneur

  • MICS-Asia II : Model inter-comparison and evaluation of acid deposition

    Zifa Wang;Fuying Xie;T. Sakurai;H. Ueda

  • Simulation of aerosols and gas-phase species over Europe with the Polyphemus system. Part II: Model sensitivity analysis for 2001

    Yelva Roustan;Karine Sartelet;Maryline Tombette;Edouard Debry

  • Comparison of lidar-derived PM 10 with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

    P. Royer;P. Chazette;K. Sartelet;Q. J. Zhang

  • Modeling of photolysis rates over Europe: impact on chemical gaseous species and aerosols

    E. Real;K. Sartelet

  • Modelling aerosol number distributions from a vehicle exhaust with an aerosol CFD model

    B. Albriet;K.N. Sartelet;S. Lacour;B. Carissimo

  • Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

    E. Solazzo;R. Bianconi;G. Pirovano;M. D. Moran

  • Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin

    Y. Wang;Y. Wang;Y. Wang;K. N. Sartelet;M. Bocquet;M. Bocquet;P. Chazette

  • The Secondary Organic Aerosol Processor (SOAP v1.0) model: a unified model with different ranges of complexity based on the molecular surrogate approach

    F. Couvidat;K. Sartelet

Frequent Co-Authors

Christian Seigneur
Christian Seigneur École des Ponts ParisTech
Agnès Borbon
Agnès Borbon Centre national de la recherche scientifique, CNRS
Matthias Beekmann
Matthias Beekmann Paris-Est Créteil University
Karine Sellegri
Karine Sellegri University of Clermont Auvergne
François Dulac
François Dulac French Alternative Energies and Atomic Energy Commission (CEA)
Yang Zhang
Yang Zhang Northeastern University
Paola Formenti
Paola Formenti Centre national de la recherche scientifique, CNRS
Marc Bocquet
Marc Bocquet École des Ponts ParisTech
Bertrand Bessagnet
Bertrand Bessagnet École Normale Supérieure
Patrick Chazette
Patrick Chazette French Alternative Energies and Atomic Energy Commission (CEA)

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