Mapping Wicked Problems: Poor Air Quality in the Pittsburgh Region
Assignment 1a from https://transitiondesignseminarcmu.net/
Introduction
For many people, the city of Pittsburgh was once synonymous with steel and smoke. Since Pittsburgh’s municipal incorporation in 1758, industrialization and manufacturing dominated its natural resources, economy, and cultural narrative. With the crash of steel in the 1970s and 80s, Pittsburgh has experienced an economic revitalization with the emergence of medical, educational, technology, and financial services sectors of its economy.
And yet, Pittsburgh is still counted among cities with the worst air quality in America. According to research compiled by the Breathe Project, Pittsburgh’s air quality was considered “not good” for 229 days in 2018 (two-thirds of the year). From 2016–2018, three regional air monitors reported particulate matter concentrations (PM 2.5) worse than 90% of the United States. Furthermore, air monitors show that Pittsburgh’s poor air quality is caused mostly by local sources such as manufacturing. These statistics contribute to Pittsburgh’s ranking among the top ten most polluted cities in the nation for year-round particle pollution. The effects of poor air quality threaten the environmental, human, and social health of the region.
Process
On the first day of class, our team selected poor air quality in Pittsburgh as the topic for our semester-long Transition Design seminar. We began researching this wicked problem in order to create a wicked problem map for Assignment 1a.
Individual Research
We began researching the issue of poor air quality individually, using the STEEP framework (the Social, Technological, Economic, Environmental, Political dimensions of an issue) as a loose guide. We sought to understand the basics: what is air quality, how is it measured, what contributes to poor air quality? We also wanted to begin documenting stakeholders from a local to global level. We intentionally took a broad view of the problem, pushing ourselves to find what boundaries, if any, might exist. We met periodically to share findings at a high level, refine our research questions, and identify potential new sources of information.
Team Activity
Meanwhile, we invested in ourselves as a team. Andrew led us in an activity designed to surface our individual values and help us get to know one another at the start of the project. We discussed our hopes, concerns, needs and wants in collaborating together. From there, we identified shared values that all four of us held, and discussed how we might support one another in values held by an individual. For example, we discussed how to achieve an appropriate balance between the values of flexibility and structure and what commitments we could make to each other to sustain that balance throughout the project.
Post-it Generation
After a few weeks of individual research, we were unleashed onto our project canvas for mapping our wicked problem. We decided to approach this assignment using analog tools, and met for a work session in which we generated as many data points as possible on post-it notes. From our individual research, we documented information and color-coded it using a different color of post-it for each category in the STEEP framework. This lead to the first of many conversations about how to classify dimensions of the problem: were health effects social or environmental? How would we account for industrial activities — were steel mills technological or economic?
Also, we found ourselves permeating the boundaries between issues and stakeholders tied up in our problem. We decided to incorporate stakeholders into our process of developing the wicked problem map because it helped us to enter into the issue space from a shared vantage point. We thought we would try it this way, and then follow with the stakeholder mapping activity, pulling from our documentation in the problem map.
Clustering
With the first round of documentation inevitably generating another round of questions, we broke with plans for another work session after time for additional research. Our next work session yielded additional data points across STEEP categories, followed by an affinity mapping activity. We began clustering ideas with similar themes and relationships. This mostly conformed to the STEEP framework, though there were some examples where different colored post-its co-mingled into a single category.
Digital Capture
With an initial set of grouped concepts and data points on the wall, we decided to transition to digital tools in order to more efficiently and flexibly capture the relationships between and among them. We decided to use Lucidchart because of its mapping features, which enable connections to be made and sustained between nodes even as nodes are moved around a canvas.
As we began tracing relationships of cause and effect, we realized that we needed to push our data points a little deeper. We needed to not only name an idea or actor, but characterize it in a way that enabled a connection to be drawn. This led us to another round of synthesis and iteration, where we focused on articulating underlying issues succinctly and concretely. From there, we were able to begin tracing relationships between both categories of ideas and individual ideas.
Adding Cause and Effect
As we drew connecting lines, we felt we were missing a clear visual representation for causes and effects. We discussed a few different ideas for how to incorporate visual cues into the map. Working on a printed draft, we sketched out underlying territories of primary and secondary causes, as well as effects. We felt this layered solution would convey these relationships at a high level.
Presentation
We presented a concise version of our process and our full draft of our wicked problem map in class for feedback.
We heard positive feedback on our territory mapping approach to representing causes and effects. We were pushed to provide more narrative about cause and effect to accompany the map, and to make some visual changes, including adding a key and making the colors of the STEEP categories clearer at the category level. We were also pushed to continue digging deeper into capturing the heart of an issue using complete sentences. After the presentations, we met to refine our thinking and our visuals and assign tasks to complete our first set of Medium posts.
Our Wicked Problem Map
Key Components
Our wicked problem map centers around the issue of poor air quality in the Pittsburgh area. The darker gray territory represents primary causes of air quality. The lighter gray territory represents secondary causes or enabling factors of poor air quality. The dotted lines represent effects of poor air quality.
Each component of the STEEP framework (Social, Technological, Environmental, Economic, and Political dimensions of the issue) have their own color. Concepts descend from high-level to more detailed as the saturation within a given color category decreases.
Narrative Pathway
We identified the primary cause of poor air quality to be particulate and gaseous emissions from human activity. Pittsburgh’s wealth of natural resources — including coal, natural gas, and river transportation routes — feeds the activities of industries like steel and petrochemicals. As people, raw materials, and goods travel further, the transportation and automotive industries release increasing diesel and vehicle exhaust emissions into the air. Macroeconomics and corporate priorities promote growth at all costs. Meanwhile, plant life — a natural air purifier — are threatened by this industrial and transportation activity, and their ability to purify the air decreases.
Secondary causes of poor air quality in Pittsburgh stem from or enable primary causes. Relationships among consumer mindsets (convenience, consumption), socio-economics, and personal habits (transportation choices, opting for green energy service providers) contribute to the extraction, production, and growth cycles in industry, which drive emissions up. Policy measures intended to regulate air quality and industrial activity indirectly enable the problem through their limited scope and a lack of strong enforcement. Permit and fine structures are common regulatory mechanisms to control industrial air emissions, though the authorized fines do not seem to be enough of a deterrent to drive meaningful change in industry. While electric vehicles are frequently positioned as a potential mitigating factor for improving air quality, their production methods and uneven adoption still contributes to poor air quality.
Effects of poor air quality in the Pittsburgh region are numerous. For human stakeholders, poor air quality is linked to increased incidences of cancer, respiratory illnesses, and cardiovascular illnesses. People who can afford to leave towns near industrial facilities often do, while disadvantaged and minority communities remain at risk for adverse health effects. For non-human stakeholders, poor air quality threatens natural habitats and contributes to the contamination of the water supply. Ecosystems suffer from a decrease in biodiversity and resilience.
And yet, it’s not all negative. The issue of poor air quality has resulted in emergent interventions from a technological and economic standpoint. For example, technologies mitigating air pollution include renewable energy and innovations in home heating and air purification. Another potential leverage point is citizen groups that have organized to fill gaps between policy inadequacies and a lack of corporate interest in ceasing emissions. Academic and non-profit research groups have identified simple interventions for monitoring emissions, like continuous video surveillance. Publishing data on major polluters in the region puts industrial stakeholders in the spotlight, with individuals reporting incidences of emissions violations in their area.
The Web of Connections: Three Types of Relationships
As we worked out the details of our map, we struggled with representing relationships between concepts using an exclusively linear structure. We identified three types of relationships in addition to the above narrative pathway to highlight non-linear connections amongst the ‘web of connections’ in our wicked problem map that we would like to discuss in more detail.
Interdependent Layers
There are many challenges in regulating air quality from a policy and governance perspective. The Clean Air Act is written and maintained at the federal level, which delegates responsibilities for enacting its provisions to states. The state of Pennsylvania in turn asks counties like Allegheny County to take action in managing regulation and enforcement of emissions. The layered structure of governance in the U.S. puts Pittsburgh at the top or the bottom of the stack, depending on your perspective. And yet, air quality is an issue of the commons. Pittsburgh is located in southwestern Pennsylvania, near the state borders to Ohio. Ohio may regulate air quality differently than Pennsylvania, which has the potential for spillover effects. The same can be true at the county level, where decisions made in nearby counties, such as hydraulic fracking and construction and operation of petrochemical facilities, also adversely affect air quality in Allegheny County while providing jobs for residents.
Loops
Looping cause-effect relationships exist within and across multiple STEEP categories. In the economy, for example, nature gives resources such as coal or natural gas to support the production and prosperity of the steel and petrochemical industries. While the trend of natural resources declining brings the crisis to the industry too, it harms the prospective production rate and profit, which would lead to multiple outcomes in the industry, eg. industrial innovation to increase efficiency. Something to note about looping relationships is that often the feedback loops are delayed: they do not all manifest quickly or in the same amount of time.
Chains
There are also direct cause-effect chains in the system, for example, the invasion of the non-native species Emerald Ash borer has brought about pest infections in the Pittsburgh region, causing huge destruction on the ash trees, thus affecting urban tree cover, which plays an important role as air purifiers. Another example: the U.S defense department’s Cannonsburg Disposal Site is the direct cause of high-level uranium deposits in the soil, which leads to radon gas, being one of the problematic compounds in impairing air quality in the Pittsburgh region.
