Urban Sacrifice Zone and Red Route Case Studies
Introduction: Urban sacrifice zones and red routes are two concepts that demonstrate the harm to communities when pollution is not just a cause of harm but enabled by other structural inequities from policy and planning.
Why this lesson is important: Air pollution does not occur in isolation. To create robust solutions that address the root political causes that lead to polluting infrastructure, we must encourage methods such as the ones showcased in these reports. Robust strategies also allow collaboration and unity between communities and those in different advocacies or sections of society.
Story: We begin with the Right to Pollute case study. The purpose of this data-led work was to bring attention to the idea that some people, institutions, or commercial operations are effectively given the right to pollute in certain neighborhoods. This lets people make more informed decisions when it comes to voting priorities for our shared health and climate change action points.
This ties into the concept of urban sacrifice zones—places that, through policy or commercial activity, become areas where pollution is considered more acceptable. These zones are formed through interactions between stakeholders, driven by national or commercial objectives that support this idea that some polluters are still part of the greater good. So then this community, this neighbourhood, this piece of land is going to be sacrificed to enable the wider community, city, or country to be able to produce what it needs to produce. We look at these right to pollute policies as they are environmentally damaging and they do end up having repercussions— even to those that feel like they have the right mitigations to the pollution.
But Right to Pollute policies are not neutral. They are conscious choices—legal, social, and cognitive frameworks that justify environmental harm. If we socially accept river pollution, the law only creates a boundary to dictate how much and in what context it is acceptable to pollute. But if we reject pollution socially, the law must adapt accordingly. Social acceptability sets the boundaries.
For this analysis, we used two datasets: the Index of Multiple Deprivation (IMD), which ranks areas by relative deprivation across the UK, and the UK National Atmospheric Emissions Inventory (NAEI), which lists permitted polluters and what they emit. By overlapping these datasets across the UK, we identified hotspots—areas where deprivation and pollution coincide. It’s not about proving one causes the other; it’s about seeing where two things happen together and asking why.
For example, in a place with significant deprivation and a high variety of polluters and pollutants, we can ask: what enables seven different types of polluters and 40 different pollutants to be allowed to be emitted in that specific place? Reflections on this kind of work can lead to better questions rather than jumping to conclusions declaring a place the “worst.”
We then move to the Red Routes case study, which focuses on arterial roads in London designated for commercial traffic in London that prioritize through-traffic over local journeys. In theory, this keeps lorries and delivery vehicles off smaller residential streets in neighbourhoods.
While seemingly efficient, Red Routes were not designed with future contexts in mind—particularly the rise of e-commerce and the sharp increase in vehicle usage. It's not that the residents living on these routes have chosen to be polluted and most likely they're not going to be able to just move—nor should they have to. Worse, we continue to build housing along these polluted routes. This is another way of enacting biological inequity. It’s not just that people are living next to pollution—they're systematically exposed to it through planning decisions.
For this analysis, we combined datasets including IMD, our own Stress Risk Score (covering air, noise, heat, and light pollution), census data on the elderly and youth, public transport accessibility, population density, proportion of Black, Asian, and minority ethnic (BAME) residents (a term we usually would prefer not to use as a blanket data set but was the category in the available data set), and car ownership.
This allowed us to break things down into health impact scenarios to make the data more relevant and understandable. For example, what does it mean for someone who’s neurodivergent to navigate a street in this context? We looked at susceptibility, local equity, race-based inequity, and transport patterns. This kind of analysis brings clarity to the lived experience of pollution.
We also looked at local equity, susceptibility, race-based inequity and car ownership to create matches between different data within the wider set that we used. Reflecting on this analysis leaves opportunity for more lived experience data to be acknowledged in understandings and the decisions made about place when we discuss pollution.
Even for your own descriptions and advocacy, it is worth experimenting with looking at where things happen at the same time. Or if you think that, ‘when something is enacted in our neighbourhood it's going to reduce our ability to get here, we're going to have less access to this,’ finding the data that actually supports that concern on a structural level can be the starting point for wider advocacy or narrowing down and saying, ‘this is where I want to tackle the problem. I care about the wider pollution but I'm not going to start just by using monitors, I'm going to start by questioning what methods of transport we actually use and why there are not as many restrictions on the red route that has been built into our neighbourhood.’
The wider takeaway from both studies is the value of experimenting with different datasets. Hopefully by now, it's clearer that air pollution alone—framed as just air quality—is too narrow and doesn't do justice to just how thorough and complicated our lives and environments are and why we're talking about health and justice.
Learning Points:
The purpose of this data led study is to bring attention to everyday people about those who have the right to pollute in their neighbourhoods, so that people can make more informed decisions when it comes to voting and priorities for our shared health and climate change action points.
We used the urban sacrifice zone data to engage people about the intentions and structures affecting their health in their environment.
This right to pollute work does not focus on causality, it takes the assumptions that pollution and deprivation both leave communities vulnerable to tie into to other ways susceptibility is enacted that may be more relatable.
This red route hot spot analysis that looks at the intersections of data such as deprivation, population density, pollution, transport accessibility and ethnicity leaves opportunity for more lived experience data to be acknowledged in the understandings and the decisions made about place when we discuss pollution.
Experimenting with different data sets at a macro level can support education and awareness to strategy at levels you wouldn’t intuit as individuals.
Segueing into the next Lesson theme: The final lesson in this module puts some of these learnings together to give guidance to how strategy and advocacy can be supported meaningfully by data. We'll review how to use data to tell a story or support your advocacy around community health.