While mitigating carbon emissions often takes center stage in the clean energy transition, the shift away from a fossil fuel-driven energy system will also curb air pollution and, by extension, protect human health.
However, it is not so straightforward to draw a connection between a national policy aimed at promoting electric vehicle adoption, for example, and its impacts on local air quality and health outcomes in communities.
Wei Peng, an assistant professor of public and international affairs and the Andlinger Center for Energy and the Environment, recently led a perspective article in Nature Reviews Clean Technology that synthesizes her group’s decade-long work to model the air pollution and health impacts of the clean energy transition.
Alongside colleagues at Princeton, Penn State, the University of Maryland, the University of Texas at Austin, and Emory University, Peng argued that focusing solely on carbon emissions as a motivator for the energy transition could lead to missed opportunities for upholding environmental equity and building broader support for clean energy action.
In this Q&A, Peng, who is also a core faculty member at the Center for Policy Research on Energy and the Environment, is joined by two co-authors and graduate students in her group — Jinyu Shiwang and Carla Campos Morales — to discuss their efforts to incorporate health and equity into energy and environmental decision-making, ensuring their work supports not only a cleaner but also a more just energy future. Shiwang and Campos Morales are visiting graduate students in public and international affairs.
Q1: A common assumption is that the clean energy transition will not just lower greenhouse gas emissions, but that it will automatically lead to better air quality and health benefits. Is that actually true?
Wei Peng: It’s well-established that if we transition from coal to less-polluting energy sources, in almost every case, we’re going to have cleaner air and better health at a national level. But nobody really lives at that national average exposure level. Instead, most people care about their local air quality and the impact of the energy transition on their lives. And when we zoom in to the sub-national level, we find that the benefits often depend on the clean energy strategy. Some communities may experience significant air quality benefits, some may experience minimal benefits, and in some areas, there may be no net benefit at all.
Jinyu Shiwang: Take electric vehicles as an example. EVs are an important part of the low-carbon energy transition, but ultimately, how we manufacture EVs and how we get the electricity to run them can have significant impacts on local air pollution. We could see a reduction in urban air pollution as EVs become more common due to their lower tailpipe emissions. At the same time, the widespread adoption of EVs could actually spark air pollution hotspots in rural areas where fossil fuel power plants and EV manufacturing facilities are sited. While there may be a net increase in air quality and health benefits at a national or international scale, those benefits won’t be evenly distributed across communities.
Q2: How do you address the challenge of understanding the air quality and health impacts of energy policies that are often focused on greenhouse gas emissions?
Jinyu Shiwang: There is a whole cause-and-effect chain, where you start with the energy transition as an input and arrive at health impacts as an output. We first consider the impacts of an energy policy on overall energy demand, end uses, and production activities, modeling how different policies are likely to affect greenhouse gas emissions and air pollution levels. Typically, these models capture impacts at the national or state level, so we must downscale these broader patterns to simulate changes in local air pollution. Once we obtain the local air pollution outcome, we can finally integrate it with social and demographic data to arrive at a health impact assessment.
Wei Peng: Throughout the process, countless variables could have a major influence on both the emissions and health impacts. For instance, on the emissions side, we need to consider the types and quantities of air pollutants being produced and how those air pollutants will be transported. Precipitation, temperature, humidity, and regional weather patterns all have an impact on how air pollution is formed, transported, and broken down.
On the health impacts side, we need to think about exposure and vulnerability: how many people will be exposed to air pollution, and how many of those individuals belong to disproportionately impacted populations, such as the elderly and children? You could have high air pollution in an area with very few people, so the health burden might actually be very small. On the other hand, you could have low air pollution in a densely populated area or an area with more vulnerable populations and have much greater health impacts.
Q3: How do you move from modeling work to real-world policy impact?
Wei Peng: It’s impossible for a model to capture every single mechanism or process that could have an impact on health outcomes. So I think the best approach is to start by asking ourselves about the outcomes we want to achieve — who are the decision-makers, and what information do they care about most? It’s also important to prioritize actions within our control. Energy investors and local governments can decide where a power plant gets sited or how much we invest in electric vehicles, for example, but we don’t have much control over regional weather patterns as they are affected by the global climate system. So it makes more sense to treat the location of the power plant as a decision lever in our model and treat regional weather patterns as exogenous uncertainties.
Carla Campos Morales: Ultimately, the solutions need to be context-specific, because the beliefs and values of communities will influence the policies they will support. In the United States, for example, some states are fossil fuel hotspots. In these areas, the immediate focus may be on developing the supporting infrastructure and policies to allow for great levels of renewable energy deployment. But in other states with a lot of renewables, the best policy solution is going to be different and could focus on another sector entirely.
Jinyu Shiwang: I think placing a larger emphasis on the health impacts of the energy transition can build broad support for energy policies. Whereas mitigating greenhouse gases is a global challenge, better health outcomes are direct benefits that people can see for themselves. In fact, in countries like China and India, a strong push for the clean energy transition has come from the desire to combat local air pollution. I hope to see a greater effort to integrate health outcomes into energy decision-making.
Q4: What are the future directions for this type of modeling work?
Wei Peng: I think the models we have developed as a research community are sometimes too complex for most decision-makers to make sense of, and most of our results are too broad for a lot of audiences to use. We receive many questions from people in specific states or cities, asking us how to interpret our findings or apply them to their own situations. Instead of simply publishing our results and hoping policymakers use them, the best route forward is to identify states or other actors with windows of policy opportunity that we can support. They have specific problems to solve, and we have the expertise to adapt existing analytical tools to suit their decision-making needs. That way, it could be a mutual learning process, where we can learn from and help each other.
Carla Campos Morales: I also think there needs to be greater community engagement to guide our modeling and policy work. How can we work more closely with and incorporate insight from vulnerable populations and local communities when we’re designing and simulating policies? We need to think about designing energy policies with equity in mind, rather than assuming that equity will naturally emerge from the broader decarbonization effort. We cannot simply measure success in terms of tons of CO2 avoided.
The paper, “Effects of the low-carbon energy transition on air pollution and health,” was published June 2 in Nature Reviews Clean Technology. In addition to Peng, Shiwang, and Campos Morales, co-authors include Huilin Luo of Princeton University; Gokul Iyer of the University of Maryland, College Park; Mark Budolfson of the University of Texas at Austin; and Noah Scovronick of Emory University. The work was supported by the National Science Foundation, the Andlinger Center for Energy and the Environment, and the Princeton School of Public and International Affairs.