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Comparison of Machine Learning and Land Use Regression for fine scale spatiotemporal estimation of ambient air pollution: Modeling ozone concentrations across the contiguous United States

PaperCitations, authors & open-access status

Comparison of Machine Learning and Land Use Regression for fine scale spatiotemporal estimation of ambient air pollution: Modeling ozone concentrations across the contiguous United States is a paper indexed in ScholarIQ from OpenAlex. ScholarIQ records 209 citations, 2020 year and gold oa status.

209
Citations
2020
Year
gold
OA Status

Related on ScholarIQ

Panos G. Georgopoulos
Author
Environment International
Journal
Air Quality and Health Impacts
Topic
Air Quality and Health Impacts
Topic
Air Quality Monitoring and Forecasting
Topic
Atmospheric chemistry and aerosols
Topic
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