<|im_start|>user
What is statistical interpolation in the context of a pollution exposure assessment?<|im_end|>
<|im_start|>assistant
Statistical interpolation is a method used in pollution exposure assessments to estimate pollutant concentrations at unmonitored locations based on data collected at monitored locations.

In a pollution exposure assessment, air quality monitoring stations are typically set up at various locations to measure concentrations of pollutants in the air. However, these stations are often sparse and may not cover all areas of interest. Statistical interpolation can be used to estimate pollutant concentrations at unmonitored locations by using a statistical model that accounts for the spatial relationships between the monitored locations and the unmonitored locations.

Statistical interpolation involves the use of geostatistical methods such as kriging, which is a technique that uses a weighted average of the pollutant concentrations at nearby monitoring stations to estimate the concentration at the unmonitored location. Kriging takes into account the spatial correlation between monitoring stations and uses this information to improve the accuracy of the estimates. Other interpolation methods such as inverse distance weighting and spline interpolation can also be used in pollution exposure assessments.<|im_end|>
