In the past couple of months I’ve been able to combine work and my mapping hobby, working on a web site about air pollution in London. I’m going to be speaking about this at the October geomob meeting.
I’m lucky enough to live in one of Europe’s most polluted cities. Air pollution causes more early deaths than obesity and road collisions, and is only bested by smoking. The Mayor published some really good open data on pollution levels, which of course is incomprehensible to ordinary folk. So despite having a sense that it’s not the cleanest city, Londoners don’t know all that much about the problem or how it could be solved. We want to help change that.
Our first splash was a map showing the quantities of some major pollutants dropped on sections of roads across the capital, so Londoners could find out – how polluted is my road?
Lots of people loved that. The GLA’s GIS team did the mapping part, using our Ordnance Survey license and data to match pollution data up to ITN road sections. They also produced league tables for each borough, which we sent round to all the local papers. The Guardian featured it on their homepage and TimeOut blogged about it, driving many thousands to have a look.
Next, I checked a list of schools known to be within 150m of heavily polluted roads – there being strong scientific research to suggest a link between that proximity to pollution and higher rates of asthma in children. Currently there are estimated to be 1,148 schools suffering from this problem., revealed through fantastic work by the Campaign for Clean Air in London. We’ve mapped these, so you can see if your school is affected. This was really easy – turn the schools into GeoJSON and stick them into a Leaflet map, using the markercluster plugin to make it usable when zoomed out.
That wasn’t very difficult, but I think the map tells the story well – that this problem affects schools all over London, not just in the centre.
I’ve now been able to do some of the GIS work myself, and what fun it was! I’ve never had much call to really use Quantum GIS, but it’s a wonderful tool.
I was able to take raster files showing nitrogen dioxide concentrations across London from the London Atmospheric Emissions Inventory 2010, vectorise them, and filter them to find areas where levels were above legal limits. With this, I can then play around with other open data to see what lurks in areas suffering from illegally high levels of air pollution.
My first experiment was to clip this to London’s road network. I used the Overpass API to extract all the roads from OpenStreetMap (for some reason I can’t connect to OSM-GB at work of late). From this I was able to determine that in 2020, around 45% of London’s main road network is still expected to exceed legal limits. Nasty!
I was also able to determine that in seven years time, there will still be 928 schools near to heavily polluted roads. So thousands of young Londoners will spend their whole time in primary school breathing in illegally high levels of air pollution.
I then started to think: where do I go that means I’m next to main roads for long periods of time? Pubs, cafes, bus stops, parks. Well, these are all in OpenStreetMap as well!
I started with bus stops, because we have a pretty comprehensive dataset there after the NAPTAN import. I did all the GIS analysis, producing tables of data for boroughs and the like. But it was only when I used Maperitive to produce tiles for a slippy map that it struck me – there are still LOTS of duplicate nodes where someone has manually added the bus stop years ago, then we imported the NAPTAN stop. So actually OpenStreetMap is a completely useless source for bus stops.
I got around this by just downloading the original NAPTAN data and using that instead. But it’s a shame because NAPTAN is really inaccurate. Where OpenStreetMappers have added bus stops, or manually checked NAPTAN stops, the locations are much more precise. It would be great if we could try to clean this data up to remove duplicates. Perhaps over the winter meetups, Harry?
With this, I produced a snazzy web page showing info on London in 2020.
I haven’t tried pubs and cafes because our coverage is so patchy. One day there may be enough contributors for OpenStreetMap to have a really excellent geodatabase of these features. What an amazing resource that will be! Though I wouldn’t want to be put off some of my favourite pubs.
One final step I didn’t take was routing. I’d really like to see somebody integrate the pollution data with a routing engine, to try and find reasonably direct walking and cycling routes that keep you off the most polluted roads. I blogged about this last year, and I still think it would be both cool and genuinely useful.
My friend Robert also suggested a routing engine where the polluted roads are off-limits, and tiles without those roads drawn. Getting around today without using those roads at all would make for an interesting challenge!
All of this work has had quite an impact. Take this cutting from my local paper:
It was also the top story on BBC London News for the whole of Wednesday when Jenny Jones AM questioned the Mayor about our findings:
Now we just need to fix the problem.