Chad Milando

667 total citations
34 papers, 409 citations indexed

About

Chad Milando is a scholar working on Health, Toxicology and Mutagenesis, Automotive Engineering and Environmental Engineering. According to data from OpenAlex, Chad Milando has authored 34 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Health, Toxicology and Mutagenesis, 9 papers in Automotive Engineering and 8 papers in Environmental Engineering. Recurrent topics in Chad Milando's work include Air Quality and Health Impacts (23 papers), Climate Change and Health Impacts (11 papers) and Vehicle emissions and performance (9 papers). Chad Milando is often cited by papers focused on Air Quality and Health Impacts (23 papers), Climate Change and Health Impacts (11 papers) and Vehicle emissions and performance (9 papers). Chad Milando collaborates with scholars based in United States, Canada and United Kingdom. Chad Milando's co-authors include Stuart Batterman, Sheena E. Martenies, Lexuan Zhong, Jonathan I. Levy, Lei Huang, M. Patricia Fabian, Bhramar Mukherjee, Gregory A. Wellenius, Lindsay J. Underhill and W. Stuart Dols and has published in prestigious journals such as JAMA, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Chad Milando

30 papers receiving 400 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chad Milando United States 13 304 110 68 52 44 34 409
Tsogtbaatar Byambaa Canada 8 263 0.9× 120 1.1× 31 0.5× 57 1.1× 36 0.8× 11 413
Ariadna Curto Spain 13 274 0.9× 88 0.8× 50 0.7× 61 1.2× 14 0.3× 22 481
Carlyn J. Matz Canada 7 436 1.4× 127 1.2× 53 0.8× 78 1.5× 74 1.7× 9 672
Michelle Laeremans Belgium 13 433 1.4× 158 1.4× 169 2.5× 118 2.3× 26 0.6× 17 697
Malek Bentayeb France 10 398 1.3× 111 1.0× 20 0.3× 81 1.6× 34 0.8× 13 533
Enkhjargal Gombojav Mongolia 11 383 1.3× 147 1.3× 42 0.6× 66 1.3× 50 1.1× 19 648
Juan Pablo Ramos-Bonilla Colombia 14 273 0.9× 79 0.7× 78 1.1× 28 0.5× 33 0.8× 34 504
Stephanie Gower Canada 8 239 0.8× 95 0.9× 24 0.4× 30 0.6× 24 0.5× 12 344
Jo Barnes United Kingdom 15 345 1.1× 126 1.1× 146 2.1× 63 1.2× 35 0.8× 55 673

Countries citing papers authored by Chad Milando

Since Specialization
Citations

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

Fields of papers citing papers by Chad Milando

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chad Milando

This figure shows the co-authorship network connecting the top 25 collaborators of Chad Milando. A scholar is included among the top collaborators of Chad Milando 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 Chad Milando. Chad Milando 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.
Milando, Chad, et al.. (2026). A vision for estimation of the instantaneous reproductive number. Epidemics. 54. 100885–100885.
2.
Milando, Chad, et al.. (2025). Filling the gaps in environmental justice data: the role of synthetic populations. Environment International. 204. 109790–109790.
3.
Milando, Chad, Kayoko Shioda, Guilherme Loureiro Werneck, et al.. (2025). Evaluating the contribution of weather variables to machine learning forecasts of visceral leishmaniasis in Brazil. PubMed. 3(4). 45012–45012.
4.
Maji, Kamal Jyoti, Yongtao Hu, A. Vaidyanathan, et al.. (2024). Prescribed burn related increases of population exposure to PM2.5 and O3 pollution in the southeastern US over 2013–2020. Environment International. 193. 109101–109101. 1 indexed citations
5.
Scammell, Madeleine K., et al.. (2024). Portable Air Cleaner Usage and Particulate Matter Exposure Reduction in an Environmental Justice Community: A Pilot Study. Environmental Health Insights. 18. 1447967835–1447967835. 1 indexed citations
6.
Milando, Chad, et al.. (2023). Simulating Energy Use, Indoor Temperatures, and Utility Cost Impacts Amidst a Warming Climate in a Multi-family Housing Model. Journal of Urban Health. 100(6). 1234–1245. 2 indexed citations
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Milando, Chad, et al.. (2022). Sensitivity of modeled residential fine particulate matter exposure to select building and source characteristics: A case study using public data in Boston, MA. The Science of The Total Environment. 840. 156625–156625. 2 indexed citations
10.
Childs, Ellen, et al.. (2021). MCR: Open-Source Software to Automate Compilation of Health Study Report-Back. International Journal of Environmental Research and Public Health. 18(11). 6104–6104. 5 indexed citations
11.
Milando, Chad, Maayan Yitshak‐Sade, Antonella Zanobetti, et al.. (2021). Modeling the impact of exposure reductions using multi-stressor epidemiology, exposure models, and synthetic microdata: an application to birthweight in two environmental justice communities. Journal of Exposure Science & Environmental Epidemiology. 31(3). 442–453. 2 indexed citations
12.
Batterman, Stuart, et al.. (2020). Enhancing Models and Measurements of Traffic-Related Air Pollutants for Health Studies Using Dispersion Modeling and Bayesian Data Fusion.. PubMed. 1–63. 5 indexed citations
13.
Milando, Chad, et al.. (2020). Spatiotemporal variations in traffic activity and their influence on air pollution levels in communities near highways. Atmospheric Environment. 242. 117758–117758. 20 indexed citations
14.
Milando, Chad & Stuart Batterman. (2018). Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan. Atmospheric Environment. 181. 135–144. 13 indexed citations
15.
Zhong, Lexuan, Stuart Batterman, & Chad Milando. (2018). VOC sources and exposures in nail salons: a pilot study in Michigan, USA. International Archives of Occupational and Environmental Health. 92(1). 141–153. 47 indexed citations
16.
Milando, Chad & Stuart Batterman. (2018). Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants. Atmospheric Environment. 182. 213–224. 27 indexed citations
17.
Martenies, Sheena E., Chad Milando, & Stuart Batterman. (2018). Air pollutant strategies to reduce adverse health impacts and health inequalities: a quantitative assessment for Detroit, Michigan. Air Quality Atmosphere & Health. 11(4). 409–422. 14 indexed citations
18.
Milando, Chad, Sheena E. Martenies, & Stuart Batterman. (2016). Assessing concentrations and health impacts of air quality management strategies: Framework for Rapid Emissions Scenario and Health impact ESTimation (FRESH-EST). Environment International. 94. 473–481. 10 indexed citations
19.
Milando, Chad, Lei Huang, & Stuart Batterman. (2016). Trends in PM2.5 emissions, concentrations and apportionments in Detroit and Chicago. Atmospheric Environment. 129. 197–209. 38 indexed citations
20.
Patton, Allison P., Chad Milando, John L. Durant, & Prashant Kumar. (2016). Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffic-Related Ultrafine Particles. Environmental Science & Technology. 51(1). 384–392. 20 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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2026