I was doing some research on Canada’s climate targets recently, and came across this chart, presented as part of Canada’s Intended Nationally Determined Contribution (INDC) under the Paris Agreement:


Looks good right? Certainly it conveys a message that Canada’s well on track, and that the target for 2030 is ambitious (compared to a business as usual pathway). Climate change solved, eh?

But the chart is an epic example of misdirection. Here’s another chart that pulls the same trick, this time from the Government’s Climate Change website, and apparently designed to make the 2030 target look bravely ambitious:


So I downloaded the data and produced my own chart, with a little more perspective added. I wanted to address several ways in which the above charts represent propaganda, rather than evidence:

  • By cutting off the Y axis at 500 Mt, the chart hides the real long-term evidence-based goal for climate policy: zero emissions;
  • Canada has consistently failed to meet any of it’s climate targets in the past, while the chart seems to imply we’re doing rather well;
  • The chart conflates two different measures. The curves showing actual emissions exclude net removal from forestry (officially known as Land Use, Land Use Change, and Forestry LULUCF), while Canada fully intends to include this in its accounting for achieving the 2030 target. So if you plot the target on the same chart with emissions, honesty dictates you should adjust the target accordingly.

Here’s my “full perspective” chart. Note that the first target shown here in grey was once Liberal party policy in the early 1990s; the remainder were official federal government targets. Each is linked to the year they were first proposed. The “fair effort” for Canada comes from ClimateActionTracker’s analysis:


The correct long term target for carbon emissions is, of course zero. Every tonne of CO2 emitted makes the problem worse, and there’s no magic fairy that removes these greenhouse gases from the atmosphere once we’ve emitted them. So until we get to zero emissions, we’re making the problem worse, and the planet keeps warming. Worse still, the only plausible pathways to keep us below the UN’s upper limit of 2°C of warming requires us to do even better than this: we have to go carbon negative before the end of the century.

Misleading charts from the government of Canada won’t help us get on the right track.

I’m a bit of an Information Visualization junkie. I love good well presented data (I’m a fan of Tufte) and I dislike visualizations that are badly presented and/or misleading. I posted last week about various graphs showing relationships between urban density and transportation fuel consumption, some of which were hideous, some elegant, and some possibly misleading. I bemoaned the lack of access to the raw data, and a lively discussion followed about the believability of the relationship plotted on the graphs.

Yesterday I came across an interesting case, in the leaflet distributed to Torontonians from the city council, showing revenue and expenditure data. From a data visualization point of view, it looks like a series of poor choices were made, and I’m glad someone cared enough to point them out. But when you interpret these choices in the context of a right-wing Mayor who was elected on a tax-cutting, pro-car, anti-transit platform, it would appear these weren’t just mistakes – they were part of deliberate (if subtle) attempt to mislead:

  • The leaflet shows a pie chart of revenue sources (in $billions) along side a pie chart of capital expenditure (in $millions), setting up a false impression that transit projects gobble up the majority of the city’s budget. The deception is enhanced by the fact that the largest segments in each pie are the same colour, and of a similar size. A quick glance therefore leaves the impression that nearly all our property taxes go to the Toronto Transit Commision.
  • The leaflet fails to distinguish between gross and net expenditure. So a bar chart of budget items shows that the TTC (at $1.5 billion) is by far the most expensive item, followed by employment and social services. But the net cost of the TTC to the city is only about $0.5 billion, because most of its costs come from fares, while employment and social services are largely funded by the province. If you look at net costs (which is what most homeowners expect in answer to the question “how does the city spend our property taxes?”), the Police Service is by far the biggest item.

It’s the steady drip drip drip of this kind of misinformation that allows certain politicians to generate support for cutting budgets for transit and social services. Surely we should be investing in the kinds of community programs that reduce crime, so that we can trim that massive policing budget?

Here’s the chart on (gross) expenditures that they used:


and here’s the chart they should have used:


I spent a little time this afternoon trying to get hold of data. I guess I have high expectations that the web should deliver what I want instantly; in the old days it would have taken a few days in the library to track down the data sets I needed, and then a few weeks waiting for it on inter-library loan. In some respects, things haven’t changed much, although now it just means you hit the paywall faster. Here’s today’s tale…

It began with a post by George Monbiot on how we’ll have to make cities much more dense if we are to cut down their energy needs. George then tweeted about a fabulous graph from the UNEP which illustrates the point nicely:

In which Toronto holds an interesting position compared to other North American cities. Anyway, someone then pointed out that this data is a little old – it’s based on a classic study by Newman and Kenworthy from the 1980’s. So now the hunt begins: is there an updated version of this anywhere, and if not, can I get hold of the data to create it?

Luke Devlin tweeted out a newer version, published in 2009, based on data from the UITP Mobility in Cities Database, which has data from around the year 2001:

However, this graph is pretty ugly, and has none of the cities labelled. So, methinks that would be easy to fix – all I need is the data. Unfortunately the database (on CD-ROM – how quaint!) costs €1,200. And I’d have to wait for it to arrive. Surely someone has this online for free? No? After all, I only want to use one indicator…

Okay, so the data hunt is on. Population density data is easy to get hold of – wikipedia has plenty of it. In exploring this a little, I find some wikified concerns expressed about the original graph, and a whole can of worms about how exactly you compute population density for a city (tl;dr: it depends where you think the city boundaries are).

A little more googling turns up a fascinating 2003 paper “Transport Energy Use and Greenhouse Gases in Urban Passenger Transport Systems: A Study of 84 Global Cities” (by the same Kenworthy), which has a graph of exactly the data I need:

But of course, it points me back at the same UITP dataset for the actual numbers. Darn.

Then there’s a UNEP report dated March 2011, “Technologies for Climate Change Mitigation – Transport Sector“, which uses the same data, but actually does plot the graph I’m after:

It’s a little better than the previous version, but still doesn’t label the individual cities (which one is Toronto??). And of course, although the report is dated 2011, it’s still the same 2001 dataset from UITP.

So where else might I get data like this? A little more googling and I hit what looks like the jackpot: An extensive list of resources on transportation statistics. Unfortunately, the only one that seems to have the transport data by city is the UITP dataset. Back to that paywall again.

In the meantime, I seem to have launch George Monbiot off into an investigation of the academic publishing racket, exploring why the results of publicly funded research is invariably behind a paywall:

I look forward to reading his blog post on that topic. Meanwhile, I’m off to track down someone on campus who might already have the UITP CD-ROM…

Update 4-Jul-2011: Chris Kennedy sent me his 2009 paper in which he did a detailed analysis for 10 cites, with an update of the density vs transport energy consumption curve. He tells me he has the energy data for more cities, but not the density data, as this is very hard to do consistently. Oh, and silly me – I’d already blogged this, together with Chris’ graph last year. Here’s Chris’s graph. He says “The logarithm of urbanized density has a statistically significant fit (t stat ) -10.26) against the logarithm of GHG emissions from transportation fuels with an R2 of 0.93 (Table 2). The logarithm of average personal income is statistically insignificant (t stat ) -0.35).” (p7299)

Chris also tells me the IEA report on the world’s energy, due out later this year, will chapter on cities, with an update of the graph.