In a recent Spacing article, called Pollution and the fall and rise of urbanism, Dylan Reid argues that one of the reasons why urbanism declined in the 20th century was because of industrial pollution. (There are, of course, other contributing factors beyond just pollution.)

This article is the first time I have come across a study supporting the widely held belief that pollution and prevailing windows are the reasons for why the east sides of many former industrial cities are poorer than the west sides. Here is more on that from the article:

People recognized and understood that pollution had an impact on them, and they tried to avoid it if they could afford to do so. Have you noticed, for example, how in so many cities (Toronto included), the east side is poorer than the west side? It’s because the prevailing winds in Europe and North America are west to east, and they blow pollution to the east side. A fascinating study by economists Stephan Heblich, Alex Trew and Yanos Zylbergerg quantified this effect, identifying how 19th century pollution was dispersed eastwards and showing that the most polluted areas were also the poorest. 

What the authors discovered is that not only did pollution cause a geographic sorting based on wealth, but that there’s also a certain degree of persistence to it. This makes sense if you think about it. Pollution in our cities has waned significantly and yet here we are still remarking and talking about east vs. west.

It goes to show you just how long lasting the impacts of our city building decisions can be.

This is an interesting study from a team of AI researchers at Stanford. What they did was use car images taken directly from Google Street View (so images of cars parked on-street) to predict income levels, racial makeup, educational attainment, and voting patterns at the zip code and precinct level.

Admittedly, it’s not a perfect survey, but when they compared their findings to actual or previously collected data (such as from the American Community Survey), it turns out that their study was actually remarkably accurate. Google Street View allowed them to survey 22 million cars, or about 8% of all cars in the US.

Here are some of the things they found:

-  Toyota and Honda vehicles are strongly associated with Asian neighborhoods.

- Buick, Oldsmobile, and Chrysler vehicles are strongly associated with black neighborhoods.

- Pickup trucks, Volkswagens and Aston Martins are strongly associated with white neighborhoods.

Interestingly enough, the ratio of pickup trucks to sedans, alone, is a pretty reliable indicator of voting patterns. If a neighborhood has more pickup trucks than sedans, there’s an 82% chance it voted Republican in the last election.

Perhaps this isn’t all that surprising given that car purchases are highly symbolic. But given that the American Community Survey costs $250 million a year to administer, this study is a good preview of what cheaper and more realtime data collection might look like.