About

Ian Sue Wing is a Professor in the Department of Earth & Environment at Boston University. His research focuses on the integration of top-down and bottom-up modeling approaches to analyze energy technology details within computable general equilibrium (CGE) simulations for energy and climate policy analysis. His work addresses the implications of international trade and technology transmission for carbon leakage, economic and technological uncertainties related to the costs of U.S. climate stewardship, and the impacts of climate change on agriculture, energy, and water resources. Additionally, he models the impacts of disasters and extreme events at regional scales, contributing to a comprehensive understanding of environmental and economic interactions under climate change scenarios. Professor Sue Wing teaches courses on environmental policy analysis and U.S. environmental policy, reflecting his expertise in the economic evaluation of environmental policies and climate change mitigation strategies.

Research topics

• Geography
• Economics
• Ecology
• Environmental science
• Computer Science
• Natural resource economics
• Business
• Biology
• Meteorology
• Engineering
• Actuarial science
• Climatology
• Econometrics
• Environmental health

Selected publications

• Temperature and Emergency Department Visits: Present-Day Associations and Future Projections

  Research Square · 2025-10-09

  preprintOpen access
  PublisherOA PDFDOI

• The impact of air conditioning on residential electricity consumption across world countries

  Journal of Environmental Economics and Management · 2025-02-04 · 18 citations

  articleOpen accessSenior author

  We provide a first globally-relevant assessment of the electricity consumption consequences of households' adaptation to ambient heat through air conditioning (AC). We use household survey data from 25 countries within a discrete-continuous choice empirical framework to model households' joint air conditioning adoption and utilization decisions, and combine the estimated responses with scenarios of socioeconomic, demographic, and climatic change to project air conditioning prevalence and cooling electricity demand circa mid-century. We find that air conditioning ownership increases households' electricity consumption by 36%, on average, but the effect is heterogeneous, varying with weather conditions, income and country contexts, revealing the importance of behaviors, practices, climate, and technologies. Compared to the other drivers of electricity consumption, air conditioning has the leading marginal effect, also accounting for a significant share of household budgets. By 2050, the overall effect is a net increase in global yearly residential cooling electricity to 976-1393 TWh, with an additional 670-956 Mt of CO2 emissions, and associated social costs of $124-177 billion. Our findings highlight cooling energy expenditure as an emerging indicator of energy poverty as the climate warms, and provide an initial quantification of the economic and environmental risks associated with air conditioning as an adaptation to climate change.

  PublisherDOI

• Economic and Environmental Consequences of Future Technological Progress in Buildings

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Adaptation Technology Choice and Implications for Heat-Related Health Risk

  Econstor (Econstor) · 2025-01-01

  otherSenior author

  This paper investigates the consequences of inequality in access to heat adaptation, examining the effectiveness of alternative cooling technologies in mitigating mortality associated with extreme heat in India for the period 2014-2019. Our empirical results highlight a critical trade-off in heat adaptation. Air conditioning is highly effective in moderating heat-related mortality, but it is expensive, with generally low ownership that tends to be restricted to high-income cities. Conversely, many Indian households, including low-income ones, purchase evaporative coolers, which are much cheaper but do not provide robust protection against humid heat. Exploring the mechanisms, we show that coolers' limited effectiveness is due to their inability to operate in the humid ambient conditions that prevail over the Indian subcontinent for much of the year, and the small amount of indoor temperatures reduction they provide. Our findings provide the first evidence that income-driven differences in adaptation technology choice translate into unequal health risks under rising heat exposure, potentially reinforcing existing socioeconomic disparities.

  Publisher

• A US heat disaster? Intersection of social vulnerability and temperature extremes exacerbated by mid-century climate change and population shifts

  Environmental Research Health · 2025-02-21 · 1 citations

  articleOpen access

  Abstract Future impacts of climate change-driven increases in extreme heat exposure on population health will be driven both by the frequency and intensity of future heat, as well as changes in the size and vulnerability of affected communities. Given indications of spatial persistence of social vulnerability across the US, we explore the implications for heat exposures of the most vulnerable populations due to mid-century climate change. Population heat exposure is estimated by combining heat hazard with population growth projections. Specifically, median projected acute (95% maximum temperature), extreme (hot days, daily maximum heat index >40 °C), and chronic (cooling degree days) heat hazard are assessed in contemporary (1995–2014) and projected (2041–2060) epochs across 25+ climate models under three climate scenarios against 2020 social vulnerability index (SVI). By mid-century, increases in both chronic and extreme heat will be concentrated in the South region. Population is expected to grow faster in census tracts at the high and low extrema of the SVI. The intersection of these projected future trends suggests that the intensity and exacerbation of heat exposures due to climate change will not be evenly distributed across the population. Individuals who are most vulnerable today will face disproportionately larger heat exposures circa mid-century. Populations in high SVI areas will both increase in size and experience the largest increases in extreme heat exposure. Spatial aggregation masks fine scale changes. While cities and counties with concentrations of vulnerable populations will face rightward shifts in the tails of their temperature across the US, extreme and especially chronic population heat exposures will be concentrated in a swath stretching across southern US states. The magnitude of population heat exposure changes and their intersection with underlying vulnerability require action to focus adaptation resources on resilience to extreme heat.

  PublisherDOI

• Stakeholder-Based Tool for the Analysis of Regional Risk

  Natural Hazards Review · 2025-05-13 · 2 citations

  articleOpen access

  This paper presents the Stakeholder-Based Tool for the Analysis of Regional Risk (STARR), a dynamic, stochastic computational framework designed to inform the creation and analysis of government policies for regional disaster risk management. STARR consists of seven interacting modules. Three describe the decision-making of, respectively, government agencies, insurers, and households; four (hazard, damage and loss, buildings, economy) describe the natural, built, and economic environments in which those decisions are made. The tool is intended to (1) support policymaking by facilitating development, evaluation, and comparison of possible disaster risk management policies; (2) facilitate understanding of the dynamic system of regional disaster risk management, including interactions among stakeholder actions and the effects of changes in the context or assumptions; and (3) guide future research in a way that tightly integrates social science, physical science, and engineering contributions, demonstrating the interrelation among research advances, building on previous research, and identifying lingering gaps in knowledge. Just as regional loss estimation or catastrophe (cat) models have guided a generation of disaster risk analysis research, by extending such loss models to be dynamic and to include stakeholder decision-making modules, the STARR framework can facilitate future disaster research and practice in a way that acknowledges the decision-making required to make real change and thus overcomes some of the barriers preventing implementation of risk reduction strategies in the real world. Although it is possible to extend the framework to consider other hazards and stakeholders, STARR currently focuses on hurricanes and on households and housing.

  PublisherOA PDFDOI

• Downscaled CMIP5 projections of physical fire risk understate historical trends

  Environmental Research Letters · 2025-06-26 · 3 citations

  articleOpen accessCorresponding

  Abstract Reliable projections of wildfire risk are important for multi-sector impacts analysis. Statistically downscaled and bias-corrected Earth system model ensemble products are routinely used to analyze regional physical wildfire risk, but evaluations of historical observed trends and variability are lacking. Here, we evaluate physical fire risk over the western United States using the Canadian Forest Fire Weather Index (FWI) by comparing model outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), statistically downscaled via the Multivariate Adaptive Constructed Analogs (MACA) approach, against the observational target dataset gridMET, a gridded high-resolution surface meteorological product. We analyze multidecadal trends and interannual variability in seasonal average FWI for the historical period and future projections under two emissions scenarios, and we compare MACA-CMIP5 ensemble results with a simple time series model that generates historical and future projections of seasonal FWI based on bootstrapping observed historical trends and variability. Our findings indicate that MACA-CMIP5 accurately captures the magnitude and spatial patterns of seasonally averaged FWI but tends to underestimate historical decadal trends. We show that future increases in fire risk may be underestimated relative to the simple time series model that projects historical variability into the future. We also highlight that model biases in relative humidity contribute significantly to model-data differences. Our results underscore the importance of historical hindcasting exercises for informing broader multi-sector applications.

  PublisherDOI

• The effects of residential air conditioning and social vulnerability on heat-related hospitalizations in California

  Environment International · 2025-07-05 · 3 citations

  articleOpen access

  • We developed new, spatially resolved estimates of residential air conditioning (AC) prevalence across 27 California cities • We evaluated co-variation in AC prevalence and overall social vulnerability index (SVI) and observed a weak correlation between AC prevalence and overall SVI. • AC prevalence modified the association between extreme heat and hospitalizations for all-cause, heat-related illnesses, cardiovascular diseases, respiratory diseases, and mental disorders. Lack of access to cool spaces is considered to be a key determinant of heat vulnerability. However, assessments of the moderating effect of access to cooling on heat health outcomes have typically used spatially coarse estimates of residential air conditioning (AC) prevalence. Here we estimate patterns of inter- and intra-urban AC ownership across 1,582 zip code tabulation areas (ZCTAs) in 27 California cities, use the results to assess the covariation between AC and social vulnerability, and examine how AC prevalence and social vulnerability modify the association between extreme heat and morbidity. Our approach combines Census records, the CDC Social Vulnerability Index (SVI), meteorological variables, and hospital admissions across the 2012–2019 warm season from the California Department of Health Care Access and Information. We first construct individual- and ZCTA-level estimates of residential AC prevalence, which we then compare with SVI between and within metro areas and separately assess their effect modification on all-cause and cause-specific morbidity using a space–time-stratified case-crossover design with conditional Poisson regression models. We found that AC prevalence is weakly positively correlated with social vulnerability (r = 0.15) across the state and weakly negatively correlated within cities (r = −0.25). We found evidence of effect modification from AC prevalence on associations between extreme heat and all-cause (RR 1.04 (1.03, 1.05) for low AC versus RR 1.01 (1.00, 1.02) for high AC) as well as some cause-specific hospitalizations (e.g., heat-related illness: RR 1.42 (1.32, 1.52) for low AC versus 1.21 (1.11, 1.32) for high AC). Importantly, we find that residential AC reduces – but does not eliminate – the risks of adverse heat health outcomes.

  PublisherDOI

• A Method to estimate the economy-wide consequences of widespread, long duration electric power interruptions

  Nature Communications · 2025-04-08 · 2 citations

  articleOpen access1st authorCorresponding

  We partnered with a utility in the U.S. state of Illinois to develop and pilot an approach to estimate the economic impacts of widespread, long duration (WLD) power interruptions. We surveyed their customers about hypothetical blackouts, identifying and classifying mitigating/resilience behaviors and quantifying their costs and benefits. Survey results are scaled up to the broader regional economy, and used to drive a computational general equilibrium (CGE) simulation of the effects of power interruptions and attendant customer responses (e.g., relocation, backup generation). Impacts are severe: 1-, 3-, and 14-day interruptions reduce the utility service area’s three-month GDP by $1.8 Bn (1.3%), $3.7 Bn (2.6%) and $15.2 Bn (10.4%), respectively, with losses driven overwhelmingly by disequilibrium responses to shortages as opposed to price signals (71%–88%). Doubling backup power penetration moderates GDP losses by 11%–14%, and is relatively least beneficial during the longest interruption duration. Results highlight previously unquantified economic losses that can potentially be avoided by investments in power system resilience. Recent catastrophic weather events across the U.S.—and abroad—have brought the issue of electricity reliability and resilience to the forefront of energy and environmental policy discussions. This manuscript documents an approach to estimate the economic impacts of widespread, long duration (WLD) power interruptions.

  PublisherOA PDFDOI

• Author Correction: Inequalities in global residential cooling energy use to 2050

  Nature Communications · 2024-10-31 · 1 citations

  erratumOpen accessSenior author
  PublisherOA PDFDOI

Frequent coauthors

• Enrica De Cian

  42 shared

• Anne Wein

  18 shared

• Adam Rose

  University of Southern California

  17 shared

• Giacomo Falchetta

  RFF-CMCC European Institute on Economics and the Environment

  16 shared

• Dan Wei

  Xi'an University of Technology

  16 shared

• Filippo Pavanello

  Ca' Foscari University of Venice

  12 shared

• C. Gately

  Planetary Science Institute

  10 shared

• Deborah Carr

  Center for Innovation

  9 shared

Education

• Ph.D.

  Massachusetts Institute of Technology