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Deliverable 3 (linked to output 1). Health impacts #18
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@Robinlovelace Exposure layer uploaded into releases of net <- merge_directed_graph(net) %>% dodgr_to_sf() It has columns for:
I'm not yet sure how the The only real additional assumption made in all of that was applying a Gaussian dispersal kernel to vehicular emissions, for which I entirely arbitrarily chose a width of 20 metres. |
Great, could you try integrating that into |
Exposure is already simply embedded as an additional column on the existing data, so there's just a single file. The units are something I'm working on - it's very interesting pondering that, and something I'm very interesting in getting WHO feedback on. It essentially boils down to a discrepancy between most current approaches to modelling exposure, which are inherently and utterly individual-based, and so derive a variety of means to assess individual exposure. Those units on the network are, however, not individual units, rather they are aggregated across the entire population. Is exposing 1,000 people to 1/1,000th the amount of pollution ultimately as "harmful" as exposing 1 person to 1 unit of pollution? That kind of collective or aggregate approach to air pollution effects is rarely explicitly considered, obviously because the data needs are analagously 1,000 times greater. Until then ... we just need to think a slight bit harder about what those kind of units might actually mean. |
Good questions. I think estimates of air pollution levels in standard units, e.g. in units used in WHO guidelines, is a good place to start: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health From there time/severity distributions could be created for different pollutants I imagine. But agree will be good to get feedback on this. |
the output of the previous stages will be combined to enable comparison of scenarios, extending from the calibration procedure underlying HEAT and other methods used in similar tools, such as the Propensity to Cycle Tool.
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