Use of mobile and passive badge air monitoring data for NOX and ozone air pollution spatial exposure prediction models.
J Expo Sci Environ Epidemiol
; 27(2): 184-192, 2017 03.
Article
in En
| MEDLINE
| ID: mdl-27005742
ABSTRACT
Air pollution exposure prediction models can make use of many types of air monitoring data. Fixed location passive samples typically measure concentrations averaged over several days to weeks. Mobile monitoring data can generate near continuous concentration measurements. It is not known whether mobile monitoring data are suitable for generating well-performing exposure prediction models or how they compare with other types of monitoring data in generating exposure models. Measurements from fixed site passive samplers and mobile monitoring platform were made over a 2-week period in Baltimore in the summer and winter months in 2012. Performance of exposure prediction models for long-term nitrogen oxides (NOX) and ozone (O3) concentrations were compared using a state-of-the-art approach for model development based on land use regression (LUR) and geostatistical smoothing. Model performance was evaluated using leave-one-out cross-validation (LOOCV). Models performed well using the mobile peak traffic monitoring data for both NOX and O3, with LOOCV R2s of 0.70 and 0.71, respectively, in the summer, and 0.90 and 0.58, respectively, in the winter. Models using 2-week passive samples for NOX had LOOCV R2s of 0.60 and 0.65 in the summer and winter months, respectively. The passive badge sampling data were not adequate for developing models for O3. Mobile air monitoring data can be used to successfully build well-performing LUR exposure prediction models for NOX and O3 and are a better source of data for these models than 2-week passive badge data.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Ozone
/
Environmental Monitoring
/
Air Pollutants
/
Air Pollution
/
Nitrogen Oxides
Type of study:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Country/Region as subject:
America do norte
Language:
En
Journal:
J Expo Sci Environ Epidemiol
Journal subject:
EPIDEMIOLOGIA
/
SAUDE AMBIENTAL
Year:
2017
Document type:
Article
Affiliation country:
China
Publication country:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
/
EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
/
US
/
USA