While some see carbon capture, utilization, and storage (CCUS) as crucial for cost-effective decarbonization, it faces opposition based on air pollution and equity concerns. To understand this cost-air pollution tradeoff, we simulate the potential impacts of allowing CCUS deployment in the U.S. power sector under plausible climate policies. We show the existence of this tradeoff critically depends on the underlying policy, which affects the type of generation CCUS could displace: under a policy that incentivizes coal generation, CCUS might improve health outcomes and reduce costs. When we disaggregate our results, we find that the air pollution (PM2.5) effects of allowing CCUS, positive or negative, are largest for Black and low-income populations. We show allowing CCUS can yield energy-cost savings, particularly benefiting lower-income communities. Our sensitivity analyses highlight the effects of uncertainties on costs and benefits. Overall, this paper contributes to our understanding of broader distributional consequences of allowing CCUS.

Drawing on collective experience from ten collaborative research projects focused on the Global South, we identify three major challenges that impede the translation of research on sustainability and resilience into better-informed choices by individuals and policy-makers that in turn can support transformation to a sustainable future. The three challenges comprise: (i) converting knowledge produced during research projects into successful knowledge application; (ii) scaling up knowledge in time when research projects are short-term and potential impacts are long-term; and (iii) scaling up knowledge across space, from local research sites to larger-scale or even global impact. Some potential pathways for funding agencies to overcome these challenges include providing targeted prolonged funding for dissemination and outreach, and facilitating collaboration and coordination across different sites, research teams, and partner organizations. By systematically documenting these challenges, we hope to pave the way for further innovations in the research cycle.

A common flood shock can produce divergent neighborhood trajectories. Using Hurricane Sandy data, difference-in-differences, and machine-learning treatment-effect classification, I find that the average property price decline masks a gradient from large, persistent losses to modestly positive estimates relative to controls. The pattern extends to non-inundated properties in heavily flooded tracts; it does not align with damage severity; and broad rebuilding and disaster assistance are not similarly ordered. Instead, divergence is associated with changes in neighborhood social composition and private adaptation. Climate shocks can therefore reinforce spatial inequality through unequal neighborhood adjustment.

This is a substantially revised version of a paper previously circulated under the title "Surge of Inequality: How Different Neighborhoods React to Flooding."

Informal settlements house over a billion people worldwide and continue to expand into high-risk areas, such as steep riverbanks, often lacking adequate drainage and sewage systems. However, little is known about the economic livelihoods of residents in these settlements and how they are shaped by flooding, a risk exacerbated by climate change and population growth. To address this gap, we compile a detailed dataset on housing-market dynamics in Kibera, a large informal settlement in Africa, and develop fine-grained flood-risk maps. Preliminary results reveal sorting along flood risk: high-flood-risk properties are rented by lower-income households, who tend to have shorter residency durations, while rents change non-monotonically with flood risk. These patterns are consistent with some degree of information asymmetry about flood risk between property owners and tenants. This study sheds light on the interactions between environmental hazards and housing markets in informal settlements.

Flood losses are commonly characterized using whether and how deeply a location floods, although flooding also differs in how rapidly water rises and how long high water levels persist. Whether these additional dimensions contain economically relevant information remains poorly understood, in part because floods are difficult to measure consistently at high spatial and temporal resolution. We combine 3-hourly, 250-m hydrological reanalysis from the National Water Model with National Flood Insurance Program claims across ten states along the Mississippi River from 2010 to 2022. The resulting flood measures align with independent stream-gauge and disaster-declaration records, and capture loss-relevant variation beyond that contained in satellite-derived flood maps and event catalogs. In regressions with tract and year-month fixed effects, rate of rise retains explanatory information for both claim occurrence and claim severity when considered alongside depth and duration. Adding rate of rise also improves out-of-sample prediction, particularly for claim occurrence. For claim severity, average predictive gains are modest, but they increase markedly with rate of rise among relatively shallow floods. These results show that how flooding develops over time contains information about economic losses that is not captured by depth alone. As climate change is projected to intensify short-duration extreme precipitation, incorporating flood dynamics may become increasingly important for characterizing and predicting flood risk.

The vast majority of climate impact studies focus on the relationships between local climate variables—such as temperature, precipitation, or hurricanes—and local outcomes. But climate change impact projections may systematically underestimate total impacts if they do not account for the ways in which local outcomes depend on more distant climate events, for example through upstream rainfall in major river basins. In the Niger Inland Delta, in Mali, agriculture depends almost entirely on the availability of surface water through an annual flood following the rain season in the Guinean highlands, located hundreds of kilometers away. We construct a temporal series of flood extent using remotely sensed imagery, combined with household survey data on the timing and location of births and infant deaths across Mali. Exploiting quasi-random spatial and temporal variation in annual surface water availability, we find that larger extents of local surface water at the time of birth lower the probability of children dying before they turn one. Our results highlight the importance of accounting for the impacts of a changing climate that take place over large spatial scales.

Almost one million households are evicted annually in the United States. The consequences of eviction can be dire, including reduced future earnings and access to credit. Understanding the drivers of eviction has thus become a pressing policy question. I use data on the near-universe of court-ordered evictions in the United States to expose an environmental cause of evictions. Specifically, I show that cold winter shocks increase eviction rates—particularly in counties that are poorer and have lower rates of White population—and hence contribute to encroachment of poverty. I present evidence consistent with two mechanisms driving this effect. The first is energy prices: higher heating fuel prices aggravate the effect of cold temperatures on evictions. The second is a labor channel: effects are driven by counties with larger employment shares in more weather-exposed industries, such as construction and agriculture, particularly if wages in these industries experience negative growth shocks. Overall, this paper increases our understanding of how environmental shocks can exacerbate economic inequality.

The global challenge of internal displacement, exacerbated by conflict, climate-induced natural hazards and disasters, requires innovative and collaborative approaches to ensure effective responses. As of 2025, displacement continues to surge globally – with 3.7 million people uprooted within Ukraine due to conflict, 18.8 million internally displaced across the Horn of Africa by drought and violence and millions more affected annually in South and South-East Asia, where disasters like cyclones triggered at least 1.8 million displacements in 2023 alone. These figures are a stark reminder of the need for timely, accurate and spatially detailed data and accessible ways to process it to inform humanitarian action and policy. Using Ukraine and Pakistan as case studies this research provides analysis that compares digital trace data with traditional humanitarian data sources. This report, a collaboration between the Geographic Data Science Lab at the University of Liverpool and the International Organization for Migration’s (IOM) Displacement Tracking Matrix (DTM), examines how traditional data sources can be effectively integrated with emerging digital trace data – such as GPS and social media – to enhance the monitoring of displacement in humanitarian settings.

Environmental policymakers in the United States are giving increasing attention to reducing the burden on Americans who face both environmental and economic disadvantages. This study considers an important part of the burden: the concentration of airborne fine particulate matter (PM2.5) due to emissions from the nation’s power sector. Using a highly detailed simulation model of the US power sector paired with a model of PM2.5 formation and dispersion, the study projects some of the environmental and economic effects of nationwide implementation of different policies to reduce power plants’ contributions to PM2.5 in environmentally overburdened, disadvantaged communities (EO DACs). Effects from reduced ground-level ozone also are addressed. Results are compared with a policy that is not geographically targeted—a national price on power sector carbon dioxide (CO2) emissions. In addition to the effects on EO DACs, we project the effects for all Americans, Black Americans, Hispanic Americans, Americans in the lowest income quintile, and Americans in highly environmentally burdened (not necessarily disadvantaged) areas. The national power sector CO2 emissions price is the most cost-effective policy for reducing premature mortality from PM2.5 exposure in EO DACs. The other policies, which are geographically targeted toward reducing burdens in EO DACs, have the unintended consequence of increasing PM2.5 exposure in some of those areas.

More than a billion people live in densely-populated informal settlements worldwide. Crowded living conditions and limited resources may render these populations vulnerable to the health and economic effects of the COVID-19 pandemic. Representative and longitudinal survey data are needed to accurately measure impacts in these populations, but such data are scarce. Using satellite data and spatial sampling to ensure representativeness, we use longitudinal survey data on 1,033 households comprising 3,681 individuals collected pre- and post-pandemic to measure the economic effects of the COVID-19 pandemic households in six areas of the informal settlement of Kibera, Nairobi. The economic impacts are sizable and long-lasting. Household incomes declined at the start of the pandemic by 59% (95% CI: 50% to 69%) and remained 21% (95% CI: 13% to 28%) below the baseline level after six months. Respondents primarily attributed these declines in income to fewer labor market opportunities or lower demand for services, rather than the direct health impacts of the pandemic. The findings raise serious concerns about the welfare consequences of the COVID-19 pandemic for residents of informal settlements.

To achieve ambitious environmental justice goals such as those set by the Biden administration, agencies will need a toolkit for assessing and weighing the distributional effects of policy options. Focusing on environmental justice, this report outlines procedures and methodologies that the Office of Management and Budget (OMB) could apply to account for equity in the regulatory review process. The report recommends that OMB: instruct agencies to conduct more granular analysis of impacts; provide guidance on how to conduct such assessments; direct agencies on how to incorporate the results of such analysis into decisionmaking; and facilitate a whole-of-government pursuit of equity to transcend individual agencies' narrow mandates and cumulatively assess the distributional effects of policies enacted by many agencies.