Integrating concepts of population exposure into atmospheric dispersion models at different spatial scales, taking into account individual mobility

Stefan Reis, Massimo Vieno, Susanne Steinle, Edward Carnell, Rachel Beck, Mathew R. Heal, Hao Wu, Ruth Doherty, David Carruthers

Research output: Contribution to conferencePaperpeer-review

Abstract

The traditional approach of using static maps of residential population and annual average concentrations to determine population exposure levels is not capable of taking into account the spatial heterogeneity and the temporal variability of both ambient air pollutant concentrations, and the fact that populations are highly mobile. People spend substantial amounts of time at work places, schools, universities, often far away from their residence. In the United Kingdom, the 2011 census revealed that for some local authorities in the city of London, the population during a working day was tens of times larger than outside of working hours. This is, to a varying degree, the case in all urban areas. As pollution levels vary due to the temporal profile of emissions (driven by human activities), meteorology, physical transport and chemical transformation as well, applying state-of-the-art atmospheric chemistry transport models (ACTMs), integrated with the latest information on population distribution, offer the capability of quantifying human exposure in a dynamic fashion and with high spatial resolution. However, spatial and temporal resolution are related to at times substantial costs, in computing time, in the amount and degree of detail of input data required, and output data generated. For this reason, applying a nested approach with urban scale dispersion models (e.g. ADMS-Urban) within regional ACTMs (e.g. EMEP4UK) provides a suitable balance by providing the necessary resolution where it matters, while being efficient with regard to computing time and data needs overall. In this paper, we focus on two aspects, first, we introduce the state of work on integrating data from the 2011 census to generate a consistent, detailed population data product for ingestion in our air pollution models. Secondly, we demonstrate the approach taken for a one-way nesting of the ADMS-Urban model within EMEP4UK. Finally, we illustrate the direct relevance and application of this approach for the development of national air pollution control policies on the example of identifying options for reducing population exposure to fine particulate matter (PM2.5) in the United Kingdom. The research described here is work in progress, as the census 2011 data have only recently been made available. Data processing is currently being completed with the results being computed in time for both the submission of the final version of this paper, as well as for presentation at iEMSs in San Diego. This paper will be revised accordingly for final submission to include these results.

Original languageEnglish
Pages1061-1068
Number of pages8
Publication statusPublished - 1 Jan 2014
Event7th International Congress on Environmental Modelling and Software, iEMSs 2014 - San Diego, United States
Duration: 15 Jun 201419 Jun 2014

Conference

Conference7th International Congress on Environmental Modelling and Software, iEMSs 2014
Country/TerritoryUnited States
CitySan Diego
Period15/06/1419/06/14

Keywords

  • Air pollution
  • Atmospheric modeling
  • Health effects
  • Population exposure
  • Spatial analysis

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