Equity and modeling in sustainability science: Examples and opportunities throughout the process.

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

COVID-19 public transit precautions: Trade-offs between risk reduction and costs.

Public transit has received scrutiny as a vector for spreading COVID-19 with much of the literature finding correlations between transit ridership and COVID-19 rates by assessing the role that transportation plays as a vector for human mobility in COVID-19 spread. However, most studies do not directly measure the risk of contracting COVID-19 inside the public transit vehicle. We fill a gap in the literature by comparing the risk and social costs across several modes of transportation. We develop a framework to estimate the spread of COVID-19 on transit using the bus system in Pittsburgh. We find that some trips have demand that exceed their COVID-19 passenger limit, where the driver must decide between: (1) leaving a passenger without a ride or (2) allowing them on the bus and increasing COVID-19 risk. We consider five alternatives for alleviating overcapacity: allow crowding, additional buses, longer buses as substitutes, Transportation Network Company (TNC) rides, or Autonomous Vehicles (AVs) for passed-by passengers. We use transit ridership and COVID-19 data from the spring of 2020 by combining transportation data and an epidemiological model of COVID-19 stochastically in a Monte Carlo Analysis. Our results show that 4% of county cases were contracted on the bus or from a bus rider, and a disproportionate amount (52%) were from overcapacity trips. The risk of contracting COVID-19 on the bus was low but worth mitigating. A cost-benefit analysis reveals that dispatching AVs or longer buses yield the lowest societal costs of $45 and $46 million, respectively compared to allowing crowding ($59 million).

Air pollution disparities and equality assessments of US national decarbonization strategies.

Energy transitions and decarbonization require rapid changes to a nation's electricity generation mix. There are many feasible decarbonization pathways for the electricity sector, yet there is vast uncertainty about how these pathways will advance or derail the nation's energy equality goals. We present a framework for investigating how decarbonization pathways, driven by a least-cost paradigm, will impact air pollution inequality across vulnerable groups (e.g., low-income, minorities) in the US. We find that if no decarbonization policies are implemented, Black and high-poverty communities may be burdened with 0.19-0.22 µg/m3 higher PM2.5 concentrations than the national average during the energy transition. National mandates requiring more than 80% deployment of renewable or low-carbon technologies achieve equality of air pollution concentrations across all demographic groups. Thus, if least-cost optimization capacity expansion models remain the dominant decision-making paradigm, strict low-carbon or renewable energy technology mandates will have the greatest likelihood of achieving national distributional energy equality. Decarbonization is essential to achieving climate goals, but myopic decarbonization policies that ignore co-pollutants may leave Black and high-poverty communities up to 26-34% higher PM2.5 exposure than national averages over the energy transition.

A Path Toward Systemic Equity in Life Cycle Assessment and Decision-Making: Standardizing Sociodemographic Data Practices.

Social equity has been a concept of interest for many years, gaining increased focus from energy and environmental communities. The equitable development, collection, and reporting of sociodemographic data (e.g., data related to socioeconomic status, race, and ethnicity) are needed to help meet several of the United Nations Sustainable Development Goals (i.e., Affordable and Clean Energy; Reduce Inequalities; Peace, Justice and Strong Institutions; and Partnerships for the Goals). Yet, there has not been a consolidation of relevant concepts and application framing in energy and environmental life cycle assessment and decision-making practices. Our study aims to help fill this gap by consolidating existing knowledge on relevant equity applications, providing examples of sociodemographic data needs, and presenting a path toward a more holistic equity administration. In this critique, we present a framework for integrating equity in energy and environmental research and practitioner settings, which we call systemic equity. Systemic equity requires the simultaneous and effective administration of resources (i.e., distributive equity), policies (i.e., procedural equity), and addressing the cultural needs of the systematically marginalized (i.e., recognitional equity). To help provide common language and shared understanding for when equity is ineffectively administered, we present ostensible equity (i.e., when resource and policy needs are met, but cultural needs are inadequately met), aspirational equity (i.e., when policy and cultural needs are met, but resources are inadequate), and exploitational equity (i.e., when resource and cultural needs are met, but policies are inadequate). We close by establishing an adaptive 10-step process for developing standard sociodemographic data practices. The systemic equity framework and 10-step process are translatable to other practitioner and research communities. Nonetheless, energy and environmental scientists, in collaboration with transdisciplinary stakeholders, should administer this framework and process urgently.

Unveiling hidden energy poverty using the energy equity gap.

Income-based energy poverty metrics ignore people's behavior patterns, particularly reducing energy consumption to limit financial stress. We investigate energy-limiting behavior in low-income households using a residential electricity consumption dataset. We first determine the outdoor temperature at which households start using cooling systems, the inflection temperature. Our relative energy poverty metric, the energy equity gap, is defined as the difference in the inflection temperatures between low and high-income groups. In our study region, we estimate the energy equity gap to be between 4.7-7.5 °F (2.6-4.2 °C). Within a sample of 4577 households, we found 86 energy-poor and 214 energy-insecure households. In contrast, the income-based energy poverty metric, energy burden (10% threshold), identified 141 households as energy-insecure. Only three households overlap between our energy equity gap and the income-based measure. Thus, the energy equity gap reveals a hidden but complementary aspect of energy poverty and insecurity.

Inequitable and heterogeneous impacts on electricity consumption from COVID-19 mitigation measures.

The COVID-19 pandemic has exacerbated energy insecurity and economic hardship among vulnerable populations. This paper provides robust empirical evidence of the degree to which COVID-19 mitigation measures, especially the mandates of school closure and limiting business operations, have impacted electricity consumption behavior in low-income and ethnic minority groups in the United States. We use a regression discontinuity design applied to individual-consumer-level high-frequency smart meter data in Arizona and Illinois to highlight the disparities in mitigation measure impacts. We find that the mandates of school closures and limiting business operations increase residential electricity consumption by 4-5%, but reduce commercial electricity consumption by 5-8%. Considerable heterogeneity is observed across income and race: low-income and ethnic-minority populations experience a larger electricity consumption increase, reflecting the disproportionate impact of COVID-19 on electricity insecurity in the residential sector. Policies that address energy insecurity, especially during the pandemic, become essentially important.