This blog was written by Chester Ling, a DDL Student Research Assistant and undergraduate student in Environmental Earth Systems Science at Nanyang Technological University in Singapore.
When I first came across the concept of measuring equity and resilience, I wondered: How do you quantify an intangible social construct? Even if you do not have a solid knowledge of academic research or analysis methods, you can imagine the difficulty in measuring a qualitative concept, like equity, as compared to more directly quantifiable ones, like temperature or income. Through my time working at the Data-Driven EnviroLab (DDL), I’ve learned that quantifying the abstraction of equity and resilience is difficult, but possible. I hope to share some of these findings and enlighten you on what I’ve learned about some of today’s most pressing issues related to measuring humanity’s progress towards equality, and consequently, achieving sustainable development in the near future.
Introducing a social equity index — UESI
About three months ago, I started work on one of DDL’s long-standing projects, the Urban Environmental and Social Inclusion Index (UESI). It is the only spatially explicit metric and framework to address and assess cities’ progress towards Sustainable Development (SDG) Goal #11 — Sustainable Cities and Communities. To put it simply, the UESI measures and assesses how different cities are tackling a few key issues in sustainability: transportation, tree cover, air pollution, water quality, climate change, and social equity. As a pioneer in measuring urban sustainability, there are a few characteristics that set it apart from other indices. Notably, the index looks at sustainability indicators from neighborhood to neighborhood, giving you a finer view of how these indicators can unequally impact a city; it measures nearly 300 cities globally; and, the data is aggregated across economic, environmental, and social metrics to demonstrate how these systems are interconnected and correlated.
Quantifying social equity with Lorenz curves
As part of my work on the UESI, I was introduced to Glenn Sheriff, an Associate Professor in the School of Politics and Global Studies at Arizona State University and a long-time DDL collaborator on the UESI. He gave a guest lecture at DDL in July on the distributive equity of environmental costs and benefits in U.S. cities. Prof. Sheriff’s experience at the U.S. Environmental Protection Agency on environmental justice metrics inspired the UESI’s adaptation of Lorenz and equity curves. These tools enabled us to analyze and assess the distribution of environmental costs and benefits across different socio-economic or cultural backgrounds in our target cities.
The Lorenz curve was originally developed by economists in the 1900s. But in recent history, it has been useful in other fields like public health and environmental equity. Here is how it works: income distribution is plotted according to what percentage of total income is held by the cumulative percentage of the population. If income is distributed evenly amongst the population, a line of perfect equity (shown as the Line of Equality in Figure 1) is achieved: a 45-degree diagonal. In reality, we often observe a deviation from the perfectly equitable scenario, where the curved line represents an unequal distribution of income amongst a population. When the curve falls below the line of equity, there is a disproportionate share of people who are poor as compared to those who are wealthy. Referencing the image above, the difference in equity between the two curves can then be quantified through a ratio of the gray area — A, over the total area of A + B, where B is the blue area under the Lorenz curve.
The UESI methodology applies the same concept to develop an Environmental Concentration Index, which measures the distribution of environmental harm, like air pollution, or a benefit, like tree cover or access to public transit, in addition to income. Check out more examples of these equity curves under the UESI City Profile page. You may learn a few surprising things about your city as you explore.
Beyond equity curves — Resilience
Resilience as a measure of sustainability is also a strategic focus for researchers at DDL and beyond.
To understand resilience, we have to understand risk, or in this case, disaster risk. I was first introduced to this concept by my research supervisor, David Lallemant, Principal Investigator and Founder of Disaster Analytics for Society Lab (DASL) at Nanyang Technological University in Singapore. Disaster risk research is defined through 3 main components: hazard, exposure, and vulnerability. According to Understanding Risk, hazards refer to a chance event that brings harm and destruction (e.g. earthquakes and floods), exposure is the physical attributes and characteristics of the impacted communities and assets, and vulnerability is the additional susceptibility of impacted assets. See more detailed explanations of these terms here. It was then I realised that disaster risks and impacts could be qualitatively measured and analysed across different communities, paving the way for us to study the resilience of communities towards these risk events.
Cross-cutting impacts of environmental risks
After learning more about environmental resilience, social equity, and distributive justice, I began to wonder whether different stakeholders and communities are equally impacted by hazard events. Fortunately, Scott Langford, a Public Affairs Postdoctoral Researcher at Arizona State University, shed some light on this issue when he dropped by DDL to share his work on how community banks can help improve post-disaster resilience.
There is wide consensus that minority groups are often exposed to disproportionate levels of risk due to a combination of social, economic, and cultural factors. This is evident across environmental risk topics, including climate change-induced warming, air quality and pollution, and public health phenomena such as COVID-19.
Scott’s preliminary research further explores post-disaster recovery responses to environmental hazards and how community-based finance strengthens the economic resilience of disaster-hit neighborhoods. It seems that smallholder financial institutions such as community banks and credit unions play a large role in helping communities to be more resilient, particularly after natural disasters or public health crises. This finding has profound implications as it provides evidence that environmental risks have socioeconomic consequences, and hence justify various ground-up finance and microeconomic initiatives like just banking and community banking. For example, he hypothesized that relationship lending, or transactions between borrowers and lenders based on social relationships, is a better strategy for credit intermediation and strengthens the economic resilience of recovering communities through the provisioning of better financial support and welfare services. Exploring these complexities in the interconnected and cross-cutting relationships across the disciplines related to sustainability is one of the most interesting and fulfilling components of the research we do every day.
Progress towards a sustainable future will not be possible without understanding strategic themes such as risks, resilience, and equity. However, DDL’s projects aimed at providing insights on climate-related topics are only a small component of a vast ecosystem of sustainability pioneers and purpose-driven changemakers. With the Global Stocktake and COP28 on the horizon, the need for a comprehensive and accurate assessment of our sustainability journey is critical. Efforts in assessing our headway in achieving the purpose of the Paris Agreement and other long-term goals must be supported by a wide range of stakeholders, including policymakers, companies, academia, and investors. The time for us to make a difference is now.