How uncertainty in estimation methods of residence-based exposure influences neighbourhood effect averaging

Keywords: air pollution, estimation methods, human mobility, the neighbourhood effect averaging problem (NEAP)
Session Type: Virtual Paper Abstract
Day: Tuesday
Session Start / End Time: 3/1/2022 05:20 PM (Eastern Time (US & Canada)) - 3/1/2022 06:40 PM (Eastern Time (US & Canada))
Room: Virtual 3

Abstract

The neighbourhood effect averaging problem (NEAP) is a fundamental methodological problem when researchers measure human exposure to environmental factors using residence-based exposure and ignoring human mobility. Due to the lack of dense monitor networks, previous studies tend to adopt residence-based estimation methods to assess human exposure to air pollution. Diverse air pollution data sources and models may generate different assessments of individual exposure. How uncertainty in the estimation of residence-based exposure affects the observation of the NEAP is seldom explored. Therefore, this research examines the different estimation models in the evaluation of individual residence-based exposure and NEAP in Hong Kong by measuring real-time exposure using portable sensors and GPS. The results show that different methods obtain distinct residence-based exposures for individuals. Even though the NEAP exists with different estimation methods, these methods would influence the extent of the NEAP. Both residence-based exposure and NEAP are sensitive to the exposure models, indicating the importance of reliable estimation of exposures to avoid potential bias.