Weather and the City: Machine Learning for Predicting and Attributing Fine Scale Air Quality to Meteorological and Urban Determinants

Keyphrases

• Machine Learning 100%
• Air Quality 100%
• Pollutants 100%
• Urban Characteristics 100%
• Urban Weather 66%
• Urban Areas 33%
• Global Concern 33%
• Wind Speed 33%
• Health Implications 33%
• Elemental Carbon 33%
• Weather Conditions 33%
• New York City 33%
• Urban Planning 33%
• Air Pollution 33%
• Traffic-related 33%
• Planning Policy 33%
• Urban Design 33%
• Vehicular Emissions 33%
• Regression Analysis 33%
• Planning Design 33%
• Particulate Matter 2.5 (PM2.5) 33%
• Spatial Analysis 33%
• Mean Absolute Error 33%
• Nitrogen Oxides 33%
• Urban Policy 33%
• Prediction Strategy 33%
• Urban Form 33%
• Mitigation Strategies 33%
• Spatial Prediction 33%
• Learning Gradients 33%
• Urban Fabric 33%
• Meteorological Conditions 33%
• Carbon Oxides 33%
• Urban Air Quality 33%
• Sulfur Dioxide SO2 33%
• Urban Function 33%
• Daily Maximum Temperature 33%
• Temporal Mapping 33%
• Weather Factors 33%
• Non-traffic 33%
• Secondary Formation 33%
• Urban Features 33%
• Formation Pathway 33%
• Elemental Nitrogen 33%
• Gradient Boosting Regression 33%
• Urban Morphology 33%

Earth and Planetary Sciences

• Machine Learning 100%
• Air Quality 100%
• Wind Velocity 50%
• Emissions 50%
• Weather Condition 50%
• New York 50%
• Air Pollution 50%
• Particular Matter 2.5 50%
• Sulphur Dioxide 50%
• Nitrogen Oxide 50%
• Spatial Analysis 50%
• Urban Planning 50%
• Urban Design 50%
• Urban Air Quality 50%
• Urban Morphology 50%
• Urban Policy 50%