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Trying to Link Personal Exposure Measurement and Population Exposure Modelling: A Test Case in Liège, Belgium

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Air Pollution Modeling and its Application XXVI (ITM 2018)

Abstract

Commonly, population exposure is evaluated by crossing data of atmospheric pollution and population density maps. The former are usually actual measurements or simulated concentrations; depending on the approach or the model resolution, very different patterns may appear both in space and time, so that conclusions can vary significantly. The latter are usually based on residency information, and for many of us, do not reflect the typical wanderings, thus actual exposure. With the rise of portable devices, we are given the unprecedented opportunity to measure pollutant concentrations at a high time rate and to know the exact location of a subject. Moreover, the increase of computational capacities allows one to perform operational runs at spatial and temporal resolutions of about 10 m and 1 h respectively. Furthermore, if the subject writes an activity log, it is also possible to discriminate indoor and outdoor situations. In this ongoing work, we investigate the discrepancy in the evaluation of population exposure when using, on one hand different pollutant concentration maps e.g. yearly, daily or hourly average values, more or less sophisticated and/or refined models, different information related to the population e.g. static or dynamic and on the other hand actual data. Our region of interest for this test case is the city of Liège in Belgium.

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References

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All participants involved in the “Personal exposure” part of the OIE project have signed a consent allowing us to use their personal information as well as the measurements they made with our instruments.

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Correspondence to Fabian Lenartz .

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Lenartz, F., Hutsemékers, V., Lefebvre, W. (2020). Trying to Link Personal Exposure Measurement and Population Exposure Modelling: A Test Case in Liège, Belgium. In: Mensink, C., Gong, W., Hakami, A. (eds) Air Pollution Modeling and its Application XXVI. ITM 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-22055-6_75

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