Mohit Dalvi

5.9k total citations
26 papers, 1.1k citations indexed

About

Mohit Dalvi is a scholar working on Atmospheric Science, Global and Planetary Change and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Mohit Dalvi has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Atmospheric Science, 24 papers in Global and Planetary Change and 5 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Mohit Dalvi's work include Atmospheric chemistry and aerosols (19 papers), Atmospheric and Environmental Gas Dynamics (12 papers) and Atmospheric Ozone and Climate (12 papers). Mohit Dalvi is often cited by papers focused on Atmospheric chemistry and aerosols (19 papers), Atmospheric and Environmental Gas Dynamics (12 papers) and Atmospheric Ozone and Climate (12 papers). Mohit Dalvi collaborates with scholars based in United Kingdom, United States and India. Mohit Dalvi's co-authors include Fiona M. O’Connor, Akshara Kaginalkar, K. S. Carslaw, G. W. Mann, Amit P. Kesarkar, Nathan Luke Abraham, Nicolas Bellouin, Olaf Morgenstern, Matthew T. Woodhouse and Peter Braesicke and has published in prestigious journals such as Geophysical Research Letters, Atmospheric Environment and Atmospheric chemistry and physics.

In The Last Decade

Mohit Dalvi

26 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mohit Dalvi United Kingdom 17 892 794 257 157 46 26 1.1k
Dohyeong Kim South Korea 8 1.2k 1.3× 1.0k 1.3× 293 1.1× 87 0.6× 44 1.0× 14 1.4k
Imran A. Girach India 18 728 0.8× 582 0.7× 337 1.3× 191 1.2× 22 0.5× 50 890
Anne‐Marlene Blechschmidt Germany 12 861 1.0× 802 1.0× 259 1.0× 166 1.1× 29 0.6× 17 1.1k
А. И. Скороход Russia 18 721 0.8× 614 0.8× 304 1.2× 168 1.1× 44 1.0× 77 923
Cheng‐Hsuan Lu United States 18 910 1.0× 850 1.1× 215 0.8× 309 2.0× 43 0.9× 51 1.2k
Luke Jones United Kingdom 7 776 0.9× 760 1.0× 267 1.0× 166 1.1× 21 0.5× 14 991
David Sills Canada 21 810 0.9× 648 0.8× 195 0.8× 291 1.9× 31 0.7× 60 978
Niku Kivekäs Finland 15 937 1.1× 794 1.0× 328 1.3× 102 0.6× 47 1.0× 27 1.0k
Anke Roiger Germany 22 1.2k 1.4× 1.0k 1.3× 236 0.9× 194 1.2× 73 1.6× 59 1.5k
H. J. Eskes Netherlands 15 1.7k 1.9× 1.4k 1.7× 541 2.1× 252 1.6× 70 1.5× 20 1.9k

Countries citing papers authored by Mohit Dalvi

Since Specialization
Citations

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

Fields of papers citing papers by Mohit Dalvi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohit Dalvi

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

All Works

20 of 20 papers shown
1.
Henry, Matthew, Ewa Bednarz, Douglas G. MacMartin, et al.. (2024). Identifying Climate Impacts From Different Stratospheric Aerosol Injection Strategies in UKESM1. Earth s Future. 12(3). 13 indexed citations
2.
Henry, Matthew, Jim Haywood, Andy Jones, et al.. (2023). Comparison of UKESM1 and CESM2 simulations using the same multi-target stratospheric aerosol injection strategy. Atmospheric chemistry and physics. 23(20). 13369–13385. 27 indexed citations
3.
Turnock, Steven T., Robert J. Allen, Alexander T. Archibald, et al.. (2022). The Future Climate and Air Quality Response From Different Near‐Term Climate Forcer, Climate, and Land‐Use Scenarios Using UKESM1. Earth s Future. 10(8). 8 indexed citations
4.
Jones, Anthony C., Adrian Hill, Samuel Rémy, et al.. (2021). Exploring the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office's Unified Model. Atmospheric chemistry and physics. 21(20). 15901–15927. 16 indexed citations
5.
Ming, Alison, V. Holly L. Winton, James Keeble, et al.. (2020). Stratospheric Ozone Changes From Explosive Tropical Volcanoes: Modeling and Ice Core Constraints. Journal of Geophysical Research Atmospheres. 125(11). 16 indexed citations
6.
Turnock, Steven T., G. W. Mann, Matthew T. Woodhouse, et al.. (2019). The Impact of Changes in Cloud Water pH on Aerosol Radiative Forcing. Geophysical Research Letters. 46(7). 4039–4048. 34 indexed citations
7.
Gordon, Hamish, Paul R. Field, Steven J. Abel, et al.. (2018). Large simulated radiative effects of smoke in the south-east Atlantic. Atmospheric chemistry and physics. 18(20). 15261–15289. 63 indexed citations
8.
Abraham, Nathan Luke, Alexander T. Archibald, Paul Cresswell, et al.. (2018). Using a virtual machine environment for developing, testing, and training for the UM-UKCA composition-climate model, using Unified Model version 10.9 and above. Geoscientific model development. 11(9). 3647–3657. 3 indexed citations
9.
Mann, G. W., et al.. (2017). Spatial and temporal CCN variations in convection-permitting aerosol microphysics simulations in an idealised marine tropical domain. Atmospheric chemistry and physics. 17(5). 3371–3384. 8 indexed citations
10.
Neal, Lucy, Mohit Dalvi, Gerd Folberth, et al.. (2017). A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM. Geoscientific model development. 10(11). 3941–3962. 16 indexed citations
11.
Johnson, Ben, Jim Haywood, Justin M. Langridge, et al.. (2016). Evaluation of biomass burning aerosols in the HadGEM3 climate model with observations from the SAMBBA field campaign. Atmospheric chemistry and physics. 16(22). 14657–14685. 40 indexed citations
12.
Turnock, Steven T., D. V. Spracklen, K. S. Carslaw, et al.. (2015). Modelled and observed changes in aerosols and surface solar radiation over Europe between 1960 and 2009. Atmospheric chemistry and physics. 15(16). 9477–9500. 65 indexed citations
13.
Dhomse, Sandip, Kathryn Emmerson, G. W. Mann, et al.. (2014). Aerosol microphysics simulations of the Mt.~Pinatubo eruption with the UM-UKCA composition-climate model. Atmospheric chemistry and physics. 14(20). 11221–11246. 67 indexed citations
14.
O’Connor, Fiona M., C. E. Johnson, Olaf Morgenstern, et al.. (2014). Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere. Geoscientific model development. 7(1). 41–91. 190 indexed citations
15.
Hayman, Garry, Fiona M. O’Connor, Mohit Dalvi, et al.. (2014). Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data. Atmospheric chemistry and physics. 14(23). 13257–13280. 16 indexed citations
16.
Bellouin, Nicolas, G. W. Mann, Matthew T. Woodhouse, et al.. (2013). Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model. Atmospheric chemistry and physics. 13(6). 3027–3044. 82 indexed citations
17.
Kaginalkar, Akshara, et al.. (2013). Study of the Indian summer monsoon using WRF–ROMS regional coupled model simulations. Atmospheric Science Letters. 14(1). 20–27. 36 indexed citations
18.
Telford, P., Nathan Luke Abraham, Alexander T. Archibald, et al.. (2013). Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3). Geoscientific model development. 6(1). 161–177. 63 indexed citations
19.
Savage, Nick, Paul Agnew, Carlos Ordóñez, et al.. (2013). Air quality modelling using the Met Office Unified Model (AQUM OS24-26): model description and initial evaluation. Geoscientific model development. 6(2). 353–372. 86 indexed citations
20.
Savage, Nick, Paul Agnew, Carlos Ordóñez, et al.. (2012). Air quality modelling using the Met Office Unified Model: model description and initial evaluation. 4 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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