4.8 Article

Development and Back-Extrapolation of NO2 Land Use Regression Models for Historic Exposure Assessment in Great Britain

Journal

ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 47, Issue 14, Pages 7804-7811

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/es4008849

Keywords

-

Funding

  1. European Community [211250]
  2. U.K Medical Research Council
  3. Health Protection Agency
  4. Medical Research Council [G0801056, G0801056B] Funding Source: researchfish
  5. MRC [G0801056] Funding Source: UKRI

Ask authors/readers for more resources

Modeling historic air pollution exposures is often restricted by availability of monitored concentration data. We evaluated back-extrapolation of land use regression (LUR) models for annual mean NO2 concentrations in Great Britain for up to 18 years earlier. LUR variables were created in a geographic information system (GIS) using land cover and road network data summarized within buffers, site coordinates, and altitude. Four models were developed for 2009 and 2001 using 75% of monitoring sites (in different groupings) and evaluated on the remaining 25%. Variables selected were generally stable between models. Within year, hold-out validation yielded mean-squared-error-based R-2 (MSE-R-2) (i.e., fit around the 1:1 line) values of 0.250.63 and 0.510.65 for 2001 and 2009, respectively. Back-extrapolation was conducted for 2009 and 2001 models to 1991 and for 2009 models to 2001, adjusting to the year using two background NO2 monitoring sites. Evaluation of back-extrapolated predictions used 100% of sites from an historic national NO2 diffusion tube network (n = 451) for 1991 and 70 independent sites from automatic monitoring in 2001. Values of MSE-R-2 for back-extrapolation to 1991 were 0.420.45 and 0.520.55 for 2001 and 2009 models, respectively, but model performance varied by region. Back-extrapolation of LUR models appears valid for exposure assessment for NO2 back to 1991 for Great Britain.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available