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Static and dynamic models of daily commute in Israel

Rakefet Shafran-NatanIlan Levy, David Broday

This project aims at estimating more accurately the exposure of commuters, based on their daytime location (work, school, leisure, etc.), their residence address, and a statistically estimated trajectory they may have taken while commuting between their residence and daytime locations. Our (naïve) hypothesis is that higher exposure occurs during daytime, whereas in most studies exposure is calculated solely based on the residential location. The exposure is estimated using residence and school/work addresses database of 1.3 million children and 400,000 adults (CBS data). In Year 5, the spatiotemporal model for NO2 (project No. 2) was exploited to enable a finer estimation of exposure during commute. A commute model was developed for children (age 6-18; N=1,300,000 children) and adults (age 24-65; N=400,000 workers) separately. The model imitates daily time-activity patterns of children and adults in Israel, and estimates the exposure at different locations during the course of their daily activity. The pollutant concentrations account for the daily ambient pollutant concentration variation, and “accumulated” exposure is estimated at different time-periods by accounting for varying typical (yet hypothetical) activity-location daily behavior. In particular, we used extensive spatial analysis in order to estimate exposure for each child or adult at five locations and time points throughout the course of the day: at residence during the evening and the night; during travel time (commute) from home to work or school; while at the workplace or school; during travel from work or school back home; and during leisure. Two manuscripts that describe this work are under preparation. The first presents the differences in exposure at the two major daily activities/locations: residence vs. schools or workplace. The second examines the distribution of daily exposure for the two populations mentioned above while accounting for their daily activity patterns, and compare these results to the common approach of accounting only for the residential location.