Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.

Including satellite observations of nitrogen dioxide (NO2) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO2 samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) t...

Full description

Bibliographic Details
Main Authors: Knibbs, L., Coorey, C., Bechle, M., Cowie, C., Dirgawati, M., Heyworth, J., Marks, G., Marshall, J., Morawska, L., Pereira, Gavin, Hewson, M.
Format: Journal Article
Published: American Chemical Society 2016
Online Access:http://purl.org/au-research/grants/nhmrc/1036620
http://hdl.handle.net/20.500.11937/9591
_version_ 1848745993784262656
author Knibbs, L.
Coorey, C.
Bechle, M.
Cowie, C.
Dirgawati, M.
Heyworth, J.
Marks, G.
Marshall, J.
Morawska, L.
Pereira, Gavin
Hewson, M.
author_facet Knibbs, L.
Coorey, C.
Bechle, M.
Cowie, C.
Dirgawati, M.
Heyworth, J.
Marks, G.
Marshall, J.
Morawska, L.
Pereira, Gavin
Hewson, M.
author_sort Knibbs, L.
building Curtin Institutional Repository
collection Online Access
description Including satellite observations of nitrogen dioxide (NO2) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO2 samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) to assess the validity of annual mean NO2 estimates from existing national satellite-based LUR models (developed with 68 regulatory monitors). The samplers spanned roadside, urban near traffic (=100 m to a major road), and urban background (>100 m to a major road) locations. We evaluated model performance using R(2) (predicted NO2 regressed on independent measurements of NO2), mean-square-error R(2) (MSE-R(2)), RMSE, and bias. Our models captured up to 69% of spatial variability in NO2 at urban near-traffic and urban background locations, and up to 58% of variability at all validation sites, including roadside locations. The absolute agreement of measurements and predictions (measured by MSE-R(2)) was similar to their correlation (measured by R(2)). Few previous studies have performed independent evaluations of national satellite-based LUR models, and there is little information on the performance of models developed with a small number of NO2 monitors. We have demonstrated that such models are a valid approach for estimating NO2 exposures in Australian cities.
first_indexed 2025-11-14T06:26:11Z
format Journal Article
id curtin-20.500.11937-9591
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:26:11Z
publishDate 2016
publisher American Chemical Society
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-95912017-09-13T14:51:29Z Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers. Knibbs, L. Coorey, C. Bechle, M. Cowie, C. Dirgawati, M. Heyworth, J. Marks, G. Marshall, J. Morawska, L. Pereira, Gavin Hewson, M. Including satellite observations of nitrogen dioxide (NO2) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO2 samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) to assess the validity of annual mean NO2 estimates from existing national satellite-based LUR models (developed with 68 regulatory monitors). The samplers spanned roadside, urban near traffic (=100 m to a major road), and urban background (>100 m to a major road) locations. We evaluated model performance using R(2) (predicted NO2 regressed on independent measurements of NO2), mean-square-error R(2) (MSE-R(2)), RMSE, and bias. Our models captured up to 69% of spatial variability in NO2 at urban near-traffic and urban background locations, and up to 58% of variability at all validation sites, including roadside locations. The absolute agreement of measurements and predictions (measured by MSE-R(2)) was similar to their correlation (measured by R(2)). Few previous studies have performed independent evaluations of national satellite-based LUR models, and there is little information on the performance of models developed with a small number of NO2 monitors. We have demonstrated that such models are a valid approach for estimating NO2 exposures in Australian cities. 2016 Journal Article http://hdl.handle.net/20.500.11937/9591 10.1021/acs.est.6b03428 http://purl.org/au-research/grants/nhmrc/1036620 http://purl.org/au-research/grants/nhmrc/1003589 American Chemical Society restricted
spellingShingle Knibbs, L.
Coorey, C.
Bechle, M.
Cowie, C.
Dirgawati, M.
Heyworth, J.
Marks, G.
Marshall, J.
Morawska, L.
Pereira, Gavin
Hewson, M.
Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title_full Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title_fullStr Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title_full_unstemmed Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title_short Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
title_sort independent validation of national satellite-based land-use regression models for nitrogen dioxide using passive samplers.
url http://purl.org/au-research/grants/nhmrc/1036620
http://purl.org/au-research/grants/nhmrc/1036620
http://hdl.handle.net/20.500.11937/9591