TY - JOUR
T1 - An empirical model for estimating census unit population exposure in areas lacking air quality monitoring
AU - Kingham, Simon
AU - Fisher, Gavin
AU - Hales, Simon
AU - Wilson, Ionara
AU - Bartie, Phil
PY - 2008
Y1 - 2008
N2 - This study presents the methods and results of part of the HAPiNZ (Health and Air Pollution in New Zealand) study. A part of this project was to produce accurate measures of pollution exposure for the entire population of New Zealand living in urban areas. Suitable data are limited in most parts of New Zealand with some areas having no monitoring at all. As a result, this project has developed an empirical model to estimate annual exposure values for the whole country down to the census area unit level. This uses surrogate emission indicators and meteorological variables. Data sources used include census data on domestic heating, industrial emissions estimates, vehicle kilometres travelled and meteorological measurements. These were used to calculate annual exposure estimates and were then compared to monitored data for the areas where monitoring data were available. Results show a good association between the model estimates and the monitored data, enabling advanced health effects assessments for the country's entire urban population.
AB - This study presents the methods and results of part of the HAPiNZ (Health and Air Pollution in New Zealand) study. A part of this project was to produce accurate measures of pollution exposure for the entire population of New Zealand living in urban areas. Suitable data are limited in most parts of New Zealand with some areas having no monitoring at all. As a result, this project has developed an empirical model to estimate annual exposure values for the whole country down to the census area unit level. This uses surrogate emission indicators and meteorological variables. Data sources used include census data on domestic heating, industrial emissions estimates, vehicle kilometres travelled and meteorological measurements. These were used to calculate annual exposure estimates and were then compared to monitored data for the areas where monitoring data were available. Results show a good association between the model estimates and the monitored data, enabling advanced health effects assessments for the country's entire urban population.
KW - air pollution exposure empirical model regression
UR - https://www.scopus.com/pages/publications/39549114316
U2 - 10.1038/sj.jes.7500584
DO - 10.1038/sj.jes.7500584
M3 - Article
C2 - 17668011
SN - 1559-0631
VL - 18
SP - 200
EP - 210
JO - Journal of Exposure Science and Environmental Epidemiology
JF - Journal of Exposure Science and Environmental Epidemiology
IS - 2
ER -