Who pollutes and who gets exposed to road traffic-related air pollution in the UK

In 2003, Gordon Mitchell and Danny Dorling published "An environmental justice analysis of British air quality", a widely cited paper that became a key reference in the environmental justice literature. Now, 16 years latter, a new paper by Joanna Barnes (Twitter), Tim Chatterton (Twitter) and James Longhurst update the original study with new data and more in depth analysis on the social inequalities in traffic-related pollution exposure and emission.

Barnes, J. H., Chatterton, T. J., and; Longhurst, J. W. (2019). Emissions vs exposure: Increasing injustice from road traffic-related air pollution in the United Kingdom. Transportation Research Part D: Transport and Environment, 73, 56-66.

Abstract:

This paper presents unique spatial analyses identifying substantial discrepancies in traffic-related emissions generation and exposure by socioeconomic and demographic groups. It demonstrates a compelling environmental and social injustice narrative with strong policy implications for the UK and beyond.

In the first instance, this research presents a decadal update for England and Wales to Mitchell and Dorling’s 2003 analysis of environmental justice in the UK. Using 2011 UK Government pollution and emissions data with 2011 UK Census socioeconomic and demographic data based on small area census geographies, this paper demonstrates a stronger relationship between age, poverty, road NOxemissions and exposure to NO2 concentrations. Areas with the highest proportions of under-fives and young adults, and poorer households, have the highest concentrations of traffic-related pollution.

In addition, exclusive access to UK annual vehicle safety inspection records (‘MOT’ tests) allowed annual private vehicle NOx emissions to be spatially attributed to registered keepers. Areal analysis against Census-based socioeconomic characteristics identified that households in the poorest areas emit the least NOxand PM, whilst the least poor areas emitted the highest, per km, vehicle emissions per household through having higher vehicle ownership, owning more diesel vehicles and driving further.

In conclusion, the analysis indicates that, despite more than a decade of air quality policy, environmental injustice of air pollution exposure has worsened. New evidence regarding the responsibility for generation of road traffic emissions provides a clear focus for policy development and targeted implementation.

Related post:

• Racial inequity in who pollutes and who gets exposed to pollution in the US

credit: Barnes et al 2019

Assorted links

1. 25% of students think they are in the top 1% of social skills. 94% of professors think their work is better than their peers. The Social Psychology of Biased Self-Assessment (ht Leo Monasterio)
   
   
2. What happened when New York City (randomly) increased street lighting? Crime fell by 36% as a direct result. HT John B. Holbein ‏, who is great at finding this kind of gems by the way.
   
   
3. Sacred Spaces: a series on modernist churches' by Thibaud Poirier, HT Darran Anderson
   
   
4. Interesting report comparing housing in London , New York City, Paris and Tokyo, by Jim Gleeson. Some key results summarized in this short thread.
   
   
5. The power of a single book. Beautiful metaphor for how ideas can have real impact
   
   
6. The data that was missing in your research: an incredibly detailed 3-D maps of the lunar surface
   
   
7. Microsoft Researchers trained a neural network to analyze satellite imagery and generate the footprints of 125,192,184 building in all 50 US states. The data are available on GitHub. Great coverage in the NYT, by Tim Wallace et al.

image credit: NYT

The suburbs of Mesa, Arizona

image credit: NYT

What The Simpsons got right about Transport Planning

Many of you will remember that "Marge vs the Monorail" episode of The Simpsons*. Juliet Eldred has written a hilarious and thoughtful Twitter thread about how this episode encapsulates a lot of the common issues in Transportation Asset Management faced by transport agencies. Good food for thought about the dynamics of policy decision making, the creation of white elephants, and how routine maintenance gets sidestepped by the  hype of 'new' technologies and capital investment. This story speaks a lot to recent transport projects worldwide, including the silly idea of Elon Musk's tunnel project.

* If you haven't watched it before, waste no more time. Watch it here. You're welcome :)

More evidence on the health benefits of active transport

“Women who averaged approx. 4400 steps/d had significantly lower mortality rates [..] compared with the least active women who took approx. 2700 steps/d; as more steps per day were accrued, mortality rates progressively decreased before leveling at approximately 7500 steps/d.”

This is from a new paper that just came out in JAMA (via Eric Topol). And yes, the authors are have addressed reverse causation bias. Read the methods section.

Fig. Dose-Response Association Between Mean Steps per Day and All-Cause Mortality

credit: I-Min Lee et al. 2019

My presentation at the 2019 ITF Summit

shameless self-promotion post  again 

Last week I was attending the 2019 International Transport Forum Summit, where I presented a paper on estimating the future accessibility impacts of transport project scenarios. The study also discusses the equity implications of travel-time threshold choice in cumulative opportunity metrics. Such a sexy topic, ah.

My presentation was recorded and you can watch it here (in case you really need to procrastinate on the work you should be doing now).

How congestion pricing works in London and how it could soon work in NYC

New York city is closer than ever to adopt congestion pricing. This could be a major change in how they address their transportation challenges and fund public transport. A team at Vox made an informative video about this, and they asked the sharp Nicole Badstuber (Twitter) to explain how congestion pricing works in London. London started charging private vehicles to enter the city center in 2003. Last month they enacted the London’s ultra-low emission zone, which adds another charge for most vehicles manufactured before 2015.

Biographical note: ITF/OECD award

Hi all. I am so glad to share that I have been honored with the 2019 Young Researcher of the Year Award, by the International Transport Forum (ITF/OECD). As I've said many times, this award speaks volumes about the generous guidance and support I have received from supervisors and colleagues at both Oxford and Ipea to conduct my research. Special thanks to my incredibly  demanding  supportive supervisors Tim Schwanen and David Banister. Thanks!

This is the award-winning paper, where I investigate the future impacts that different scenarios of a major BRT in Rio de Janeiro could have on access to employment opportunities for different income groups. The study also shows that the the equity assessment of transport projects based on accessibility estimates using cumulative opportunity measures with a single time threshold (the most common practice adopted by academic studies and transport agencies) can lead to misleading or partial conclusions. The preprint of the study is available for download here (it includes a spatial regression analysis that didn't make it into the paper because or reviewer #2).

Thanks to the award, I'll be attending the 2019 International Transport Forum Summit in Leipzig next week. The team at ITF will be Twitting about the Summit. I'll be presenting the paper on May 23rd at  5:15pm (local time). Apparently, it will be webcasted on Facebook Live.

Urban Picture

image credit: Filip Bogdan, Bucharest, 2007

The reasons two variables can be correlated

A concise illustration, by Thomas Lumley. This reminded me of this quite comprehensive list of some  ridiculous  spurious correlations.

image credit: Thomas Lumley

R Links

1. The ipumsr package helps import census and survey data from around the world integrated across time and space. I've mentioned IPUMS in the blog before. This is certainly among the most important, ambitious and succeeded open data projects in the world
   
   
2. A rather comphrensive comparison between data.table and dplyr syntaxes and funcitonalities ht via Mara Averick. I have to say I a strong preference for data.table because of computational performance. I also generally find the data.table syntax more easily readable than dplyr. There, I said.
   
   
3. Free Book with code: “Spatio-Temporal Statistics with R,” by Christopher K. Wikle, Andrew Zammit-Mangion, and Noel Cressie
   
   
4. brickr: a package to Build 3D LEGO models in R, by Ryan Timpe
   
   
5. trackeR: a package for handling running and cycling data from GPS-enabled tracking devices, by Hannah Frick
   
   
6. A Cheat Sheet on how to use the Reticulate package for interoperability between Python and R
   
   
7. How to create a gif of a spinning globe using R, by James Cheshire
   
   
8. The R package traveltime allows one to retrieve travel-time information from the Traveltime Platform API to create isochrone maps like these below. Great work by Thomas Russo.

image credit: Thomas Russo