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Development and back-extrapolation of NO2 land use regression models for historic exposure assessment in Great Britain John Gulliver, Kees de Hoogh, Anna Hansell, and Danielle Vienneau Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es4008849 • Publication Date (Web): 13 Jun 2013 Downloaded from http://pubs.acs.org on June 21, 2013
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Development and back-extrapolation of NO2 land use regression models for historic
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exposure assessment in Great Britain
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John Gulliver1*, Kees de Hoogh1, Anna Hansell1,2, and Danielle Vienneau1,3,4
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1.Small Area Health Statistics Unit, MRC-HPA Centre for Environment and Health, School
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of Public Health, Imperial College London, St Mary’s campus, London, W2 1PG, UK.
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2. Imperial College Healthcare NHS Trust.
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3. Swiss Tropical and Public Health Institute, Basel, Switzerland.
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4. University of Basel, Basel, Switzerland.
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* Corresponding author:
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[email protected] 15
Tel: +44 (0)20 7594 5027
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Fax: +44 (0)20 7594 0768
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Small Area Health Statistics Unit, MRC-HPA Centre for Environment and Health, School of
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Public Health, Imperial College London, St Mary’s campus, London, W2 1PG, UK.
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Abstract
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Modelling historic air pollution exposures is often restricted by availability of monitored
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concentration data. We evaluated back-extrapolation of LUR models for annual mean NO2
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concentrations in Great Britain for up to 18 years earlier. LUR variables were created in a
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GIS using land cover and road network data summarized within buffers, site coordinates and
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altitude. Four models were developed for 2009 and for 2001 using 75% of monitoring sites
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(in different groupings) and evaluated on the remaining 25%. Variables selected were
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generally stable between models. Within year, hold-out validation yielded MSE-R2 (i.e. fit
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around the 1:1 line) values of 0.25~0.63 and 0.51~0.65 for 2001 and 2009, respectively.
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Back-extrapolation was conducted for 2009 and 2001 models to 1991 and for 2009 models to
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2001, adjusting to year using two background NO2 monitoring sites. Evaluation of back-
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extrapolated predictions used 100% of sites from an historic national NO2 diffusion tube
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network (n=451) for 1991, and 70 independent sites from automatic monitoring in 2001.
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Values of MSE-R2 for back-extrapolation to 1991 were 0.42~0.45 and 0.52~0.55 for 2001
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and 2009 models, respectively, but model performance varied by region. Back-extrapolation
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of LUR models appears valid for exposure assessment for NO2 back to 1991 for Great
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Britain.
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Keywords
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Air pollution modelling, back-extrapolation, exposure assessment, GIS, land use regression,
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nitrogen dioxide.
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1. INTRODUCTION
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While acute health effects of air pollution are well established, the number of available
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studies on long-term effects is more limited. In particular, few studies to date have examined
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health impacts of air pollution exposure over periods greater than 15 years, with some notable
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exceptions.1,2,3
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An important factor preventing more very long-term or life-course studies being conducted is
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not lack of health data or long running cohorts, but availability of relevant historic exposure
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data. There are rarely enough fixed-site air pollution monitors available in continuous
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operation and using similar monitoring techniques over time to permit use of these monitors
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alone.
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Dispersion and land use regression (LUR) models potentially offer better spatial and temporal
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resolution for historic exposure estimation. Dispersion modelling3,4,5 has the advantage of not
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requiring information from air pollution monitoring sites, but due to the general lack of
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historic information on local-scale emissions (i.e. < 1 km) spatial resolution may be limited.
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LUR on the other hand is relatively straightforward to apply over large geographical areas at
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fine resolution, as long as there is good quality information on proxies for source emissions
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(e.g. land cover, transport infrastructure, population etc.), but does require air pollution
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monitoring data to use in model development, which may not be readily available for earlier
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years.
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LUR is increasingly being used in epidemiological studies to predict yearly or seasonal
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changes in exposures to ambient air pollution for current or recent periods.6,7,8,9,10,11 Transfer
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of LUR models in either space or time potentially offers a novel option to estimate air
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pollution concentrations where input data are limited. The transfer of LUR models between
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cities12 and countries13 has recently been investigated. Only a few studies14,15,16 have been 4 ACS Paragon Plus Environment
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able to investigate whether it is possible to transfer (i.e. back-extrapolate) LUR models in
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time, and there are no previous examples of evaluating the back-extrapolation of national
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scale air pollution models prior to the year 2000. We previously were involved in developing
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LUR models for Great Britain for NO2 and PM10 in 2001,13 black smoke and SO2 models in
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1962, 1971, 1981 and 1991,17 and focal-sum EU-wide models of NO2 at 1km resolution for
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2001,18 using contemporary monitoring station data, as well as development of NO219 and
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PM metrics20 and their back-extrapolation to earlier years (not yet published in the open
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literature) for the multi-region ESCAPE project. However, for the ESCAPE project,
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evaluation (i.e. performance) of back-extrapolation was not possible due to a lack of
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monitoring sites prior to year 2000. The aim of this study is to evaluate the back-
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extrapolation of models developed for 2009 and 2001 to predict concentrations of NO2 for
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earlier years (1991 and 2001) making use of the national automatic NO2 monitoring network
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and data for 1991 from a historic NO2 diffusion tube network. The study takes advantage of
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data on land cover and roads from nearest available years in model development and back
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extrapolation.
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2. MATERIALS AND METHODS
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Monitored concentrations of NO2. NO2 is one of the main pollutants of health concern which
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continues to breach EU guideline levels at pollution hot-spots in Britain21 and can be viewed
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as a proxy for transport-related exposure.22
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This study takes advantage of data from the now obsolete national diffusion tube network23
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which had several hundred sites at the peak of its operation in the early 1990s; 1991(n=451)
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was chosen (source: AEA Technology via pers. comm.) for back-extrapolation in this study as
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the data were analysed by a single laboratory and there is good information on data quality. 5 ACS Paragon Plus Environment
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UK NO2 monitoring data are limited later in the 1990s following the transition to automatic
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monitoring (Automatic Urban and Rural Network (AURN): http://uk-
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air.defra.gov.uk/networks/network-info?view=aurn). Prior to 1996 there were less than 50
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AURN sites operating in the UK; by the late 1990s there were over 150, including sites made
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publically available from several local authority networks (e.g. Kent and Medway Air,
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Automatic London Network, Hertfordshire and Bedfordshire Air). Data on monitored
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concentrations for 2001 and 2009 were thus based on the AURN. Differences between
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automatic (i.e. chemiluminescence) and non-automatic (i.e. diffusion tubes) measurement
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methods for NO2 have been quantified and are expected to be small for longer (i.e. yearly)
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averaging times: comparison of 4-week average concentrations yielded a Pearson’s r of 0.99
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and systematic differences
