Nitrogen Dioxide (NO2) (NO2 Supplementary...
The national NO2 (ppb) land use regression model was developed from 2006 national air pollution surveillance (NAPS) monitoring data, following methods reported in Hystad et al. (2011) (see Required Citation below). Background and regional components were estimated in the LUR using satellite-derived NO2 estimates and geographic variables, while local scale variation was modeled using deterministic gradients. The final LUR model includes: road length within 10 km; 2005-2011 satellite NO2 estimates; area of industrial land use within 2 km; and summer rainfall. This model explained 73% of the variation in NAPS measurements with a root mean square error (RMSE) of 2.9 ppb. Local scale variation was modeled using deterministic gradient from the literature and kernel density measures and added to the final LUR model results to produce the final NO2 estimates in this dataset. Dr. Perry Hystad (Oregon State University) produced the final estimates for all unique locations of DMTI Spatial Inc. single link postal codes active at any time between 1983 and 2015. Annual measured NO2 levels from National Air Pollution Surveillance monitoring stations for 24 Census Divisions have been used to produce the estimated levels for 1984 through 2012. based on the modelled values. (See NO2 Supplementary Methods Documentation, in Supporting Documentation). (THESE DATA ARE ALSO AVAILABLE AS MONTHLY METRICS).
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Additional Information
| Field | Value |
|---|---|
| Data last updated | September 18, 2023 |
| Metadata last updated | April 12, 2024 |
| Created | September 18, 2023 |
| Format | |
| License | License not specified |
| Datastore active | False |
| Datastore contains all records of source file | False |
| Has views | False |
| Id | c9bf916d-dc4e-4604-baea-d694de611af1 |
| Package id | 88a07048-06e9-4025-95c2-958bc093661e |
| Position | 0 |
| State | active |