Hyperlocal Environmental Data with a Mobile Platform
by An Wang / Massachusetts Institute of Technology
Available on 1 platform
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Description
Data collected from 2019 to 2022 using the City Scanner mobile platform from the MIT Senseable City Lab. The dataset includes hyperlocal measurements of particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), temperature, humidity, and detailed particle size distributions across 24 bins. Collection involved municipal vehicles in New York City, a mobile air laboratory in Boston, and taxis in Beirut.
Use Cases
Mapping hyperlocal air pollution hotspots based on latitude, longitude, and pollutant concentration readings.
Analyzing temporal trends in particulate matter and NO2 levels based on Unix timestamps spanning multiple years.
Studying particle size distribution patterns in urban environments based on the 24 particle count bins.
Correlating environmental conditions like temperature and humidity with pollutant concentrations mentioned in the description.
Strengths
Includes calibrated readings for multiple pollutants (PM1, PM2.5, PM10, NO2) with specified units (μg/m³, ppb).
Provides detailed particle size distribution data across 24 bins ranging from 0.35 to 40 μm.
Data collection spans multiple cities (New York, Boston, Beirut) and years (2019-2022).
Spatial data is provided via GPS-derived latitude and longitude coordinates in degrees.
Limitations
Row count and total dataset size are unknown, which may limit suitability assessment.
Column-level documentation beyond the listed fields is absent; field semantics for additional data must be inferred after download.
The last update date is unknown; freshness is unverified.
Provenance
Source
Massachusetts Institute of Technology Senseable City Lab, City Scanner platform.
Collection Method
Collected via mobile sensing platforms mounted on municipal vehicles, a mobile air laboratory, and taxis.
Time Range
2019-2022, with specific studies from October 2020 to December 2021 (NYC) and February to June 2022 (Boston and Beirut).
Geography
New York City (USA), Boston (USA), and Beirut (Lebanon).
Time field is in Unix time, requiring conversion for local time analysis.