Estimating Pollution Exposure in Data Sparse Areas: The HAPiNZ Approach
Accurate estimation of pollution exposure is essential in studying links between air pollution and health. In many places accurate monitored pollution data at appropriate spatial scales are not available and suitable emissions and meteorological data needed to run dispersion models may also not be available or appropriate. In such situations empirical models based on more available data can be of great use. This paper will present 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 (there are some 2000 of these, and each of the populated ones has 2-5,000 people). 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.