Meredith Franklin

Associate Professor

University of Toronto

Canada

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About

Meredith Franklin is an Associate Professor at the University of Toronto, Canada. Her research focuses on air quality assessment, machine learning applications in health, and the impact of electric vehicles on public health. Recent articles highlight her work on predicting PM2.5 levels, evaluating traffic noise, and improving aerosol data generation through advanced modeling techniques.

Articles (15)

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2025

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2025

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2025

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2024

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2023

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2022

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2022

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2021

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2021

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2021

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2020

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2020

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2020

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2020

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2020

Collaborators (10)

Jill Johnston

Associate Professor

University of Southern California

UNITED STATES

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Gabriel Filippelli

Professor

Indiana University-Purdue University Indianapolis

UNITED STATES

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Yang Liu

Distinguished Professor and Chair

Emory University

UNITED STATES

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Kenan Li

Assistant Professor

Saint Louis University

UNITED STATES

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thanh nguyen

Ivan Racheff Professor in Civil and Environmental Engineering

University of Illinois System

UNITED STATES

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Jose Luis Ambite

Associate Research Professor

University of Southern California

UNITED STATES

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Harshit Gujral

Research and Teaching Assistant

University of Toronto

CANADA

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Steve Easterbrook

Professor

University of Toronto

CANADA

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Karen A. Hudson-Edwards

Professor in Sustainable Mining

University of Exeter Cornwall Campus

UNITED KINGDOM

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Amira Aker

Boston University

UNITED STATES

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Meredith Franklin

Research Interests

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Articles (15)

Eighteen years of daily PM2.5 predictions (2005–2022) for a region of western Canada: Machine learning and satellite inputs for applications in rural health

Analysis of Flaring Activity at Liquefied Natural Gas (LNG) Export Facilities Worldwide

Emerging evidence for the impact of Electric Vehicle sales on childhood asthma: Can ZEV mandates help?

Thank You to Our GeoHealth 2023 Reviewers

Improving air quality assessment using physics-inspired deep graph learning

Estimating traffic noise over a large urban area: An evaluation of methods

Generating Fine-Scale Aerosol Data through Downscaling with an Artificial Neural Network Enhanced with Transfer Learning

W-TSS: A Wavelet-Based Algorithm for Discovering Time Series Shapelets

Temporal and Spatial Autocorrelation as Determinants of Regional AOD-PM2.5 Model Performance in the Middle East

Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging

Environmental Justice Dimensions of Oil and Gas Flaring in South Texas: Disproportionate Exposure among Hispanic communities

Predicting Fine Spatial Scale Traffic Noise Using Mobile Measurements and Machine Learning

Satellite-Derived PM2.5 Composition and Its Differential Effect on Children’s Lung Function

Estimating exposure to hydrogen sulfide from animal husbandry operations using satellite ammonia as a proxy: Methodology demonstration

Spatiotemporal Characteristics of the Association between AOD and PM over the California Central Valley

Collaborators (10)

Jill Johnston

Gabriel Filippelli

Yang Liu

Kenan Li

thanh nguyen

Jose Luis Ambite

Harshit Gujral

Steve Easterbrook

Karen A. Hudson-Edwards

Amira Aker

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