National Land Use Regression Model for NO2 Using Street View Imagery and Satellite Observations

M Qi, K Dixit, JD Marshall, W Zhang… - … Science & Technology, 2022 - ACS Publications
Land use regression (LUR) models are widely applied to estimate intra-urban air pollution
concentrations. National-scale LURs typically employ predictors from multiple curated …

Prediction of short-term ultrafine particle exposures using real-time street-level images paired with air quality measurements

J Xu, M Zhang, A Ganji, K Mallinen… - Environmental …, 2022 - ACS Publications
Within-city ultrafine particle (UFP) concentrations vary sharply since they are influenced by
various factors. We developed prediction models for short-term UFP exposures using street …

National empirical models of air pollution using microscale measures of the urban environment

T Lu, JD Marshall, W Zhang, P Hystad… - Environmental …, 2021 - ACS Publications
National-scale empirical models of air pollution (eg, Land Use Regression) rely on predictor
variables (eg, population density, land cover) at different geographic scales. These models …

[HTML][HTML] Predicting spatial variations in annual average outdoor ultrafine particle concentrations in Montreal and Toronto, Canada: Integrating land use regression and …

M Lloyd, A Ganji, J Xu, A Venuta, L Simon… - Environment …, 2023 - Elsevier
Background Concentrations of outdoor ultrafine particles (UFP;< 0.1 µm) and black carbon
(BC) can vary greatly within cities and long-term exposures to these pollutants have been …

Predicting within-city spatial variations in outdoor ultrafine particle and black carbon concentrations in Bucaramanga, Colombia: a hybrid approach using open-source …

M Lloyd, E Carter, FG Diaz… - Environmental …, 2021 - ACS Publications
Outdoor ultrafine particles (UFP,< 0.1 μm) and black carbon (BC) vary greatly within cities
and may have adverse impacts on human health. In this study, we used a hybrid approach …

Urban air-quality estimation using visual cues and a deep convolutional neural network in bengaluru (bangalore), india

A Feldman, S Kendler, J Marshall… - Environmental …, 2023 - ACS Publications
Mobile monitoring provides robust measurements of air pollution. However, resource
constraints often limit the number of measurements so that assessments cannot be obtained …

[HTML][HTML] Surveillance-image-based outdoor air quality monitoring

X Wang, M Wang, X Liu, Y Mao, Y Chen… - Environmental Science and …, 2024 - Elsevier
Air pollution threatens human health, necessitating effective and convenient air quality
monitoring. Recently, there has been a growing interest in using camera images for air …

[HTML][HTML] Long-Term Exposure to Outdoor Ultrafine Particles and Black Carbon and Effects on Mortality in Montreal and Toronto, Canada

S Weichenthal, M Lloyd, A Ganji… - Research Reports …, 2024 - pmc.ncbi.nlm.nih.gov
BACKGROUND There remain important limitations and challenges when estimating long-
term air pollution exposure for use in epidemiological studies. In 2019, the Health Effects …

What you see is what you breathe? estimating air pollution spatial variation using Street-Level imagery

E Suel, M Sorek-Hamer, I Moise, M Von Pohle… - Remote sensing, 2022 - mdpi.com
High spatial resolution information on urban air pollution levels is unavailable in many areas
globally, partially due to the high input data needs of existing estimation approaches. We …

High-Precision Microscale Particulate Matter Prediction in Diverse Environments Using a Long Short-Term Memory Neural Network and Street View Imagery

X Liu, X Zhang, R Wang, Y Liu… - … science & technology, 2024 - ACS Publications
In this study, we propose a novel long short-term memory (LSTM) neural network model that
leverages color features (HSV: hue, saturation, value) extracted from street images to …