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Urban–Rural Disparities in Air Quality Responses to Traffic Changes in a Megacity of China Revealed Using Machine Learning

https://doi.org/10.1021/acs.estlett.2c00246
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A data-driven method of traffic emissions mapping with land use random forest models
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City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region
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Exploring ozone pollution in Chengdu, southwestern China: A case study from radical chemistry to O3-VOC-NOx sensitivity
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Long-term trends in urban NO2 concentrations and associated paediatric asthma incidence: estimates from global datasets
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Novel Method for Ozone Isopleth Construction and Diagnosis for the Ozone Control Strategy of Chinese Cities
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Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China
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Impacts of Traffic Reductions Associated With COVID‐19 on Southern California Air Quality
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Health benefits of on-road transportation pollution control programs in China
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From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model
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Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns
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PM 2.5 polluters disproportionately and systemically affect people of color in the United States
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Effects of COVID-19 lockdowns on fine particulate matter concentrations
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Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Interpretable Stepwise Multiple Linear Regression Model for Ozone Concentration Prediction
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Bolstering integrity in environmental data science and machine learning requires understanding socioecological inequity
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Multi-routine-data driven spatio-temporal short-term predictions for surface ozone in China
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Status of near-road air quality monitoring stations and data application
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Determinants of traffic-related BC and PM1 exposure variability in urban functional zones
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Carbon mitigation and health effects of fleet electrification in China’s Yangtze River Delta
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An estimate of global cardiovascular mortality burden attributable to ambient ozone exposure reveals urban-rural environmental injustice
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From black-box prediction to probabilistic risk management: An explainable machine learning framework for traffic-related NO2 pollution in mountainous tourist cities
inferred← citeshttps://doi.org/10.1021/acs.est.3c07545openalex-snapshot
Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment
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Unveiling the HONO Offsetting Effect: Rethinking NO x Emission Controls during Urban Ozone Pollution Episodes
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High Spatiotemporal Resolution Inventory Finely Depicts the Rebound Characteristics of Greenhouse Gas Emissions from Vehicles in Beijing after the COVID-19 Epidemic
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Drivers of the Changing Urban and Rural Surface Ozone Differences in China: Reducing Emissions or Warming Cities
inferred← citeshttps://doi.org/10.1038/s41597-023-02034-0openalex-snapshot
Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy
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FuXi-Air: air quality forecasting based on emission-meteorology-pollutant multimodal machine learning
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