Qinqin Kong
Postdoctoral Scholar, General Internal Medicine
Bio
I am currently a Postdoctoral Scholar in the Departments of Medicine and Health Policy at Stanford University, after earning a PhD in atmospheric science from Purdue University. My research interests lie at the intersection of climate change—particularly extreme heat—and human society. I aim to advance our understanding of the physical mechanisms, cascading impacts, and the effectiveness of potential mitigation strategies for human heat stress. My PhD research focused on how land-atmosphere interactions modulate heat stress, as well as the economic and energy impacts of increasing heat stress in the context of climate change. My postdoctoral research at Stanford evaluates the impact of heat stress on public health, especially human fertility, in low- and middle-income countries. My methodological areas of expertise include climate modeling, human biophysics modeling, and econometric modeling, which I am further developing at Stanford.
Honors & Awards
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NCAR ASP Summer Program NSF funded, NCAR (2023)
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June L. and Tan (Mark) Sun Chen Research Scholarship, Purdue University (2023)
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NASA Future Investigators in Earth and Space Science Technology, NASA (2022)
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Henry Silver Graduate Scholarship, Purdue University (2022)
All Publications
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Heat Stress Metrics for US Census Tracts 1998-2020.
Scientific data
2026
Abstract
Extreme heat exposure is a growing public health threat. Heat-health research has commonly used dry-bulb temperature to characterize heat exposure, partly due to limited availability of spatially explicit, public-health-aligned datasets that integrate multiple meteorological factors to quantify heat stress. We address this gap by providing hourly Heat Index (HI), Wet-Bulb Globe Temperature (WBGT), and Universal Thermal Climate Index (UTCI) for U.S. census tract boundaries across the contiguous United States from 1998-2020. Heat-stress fields were generated by integrating PRISM, ERA5-Land, and National Solar Radiation Database (NSRDB) products, with near-surface temperature and moisture fields reconstructed and ancillary variables interpolated to a harmonized 800-m grid. Heat-stress indices were computed using validated physical models and aggregated to census tracts using area- and population-weighted methods. Validation against station networks shows stable performance for sample year 2010 May-September, with air-temperature root mean squared error (RMSE) of 1.70 °C, Heat Index RMSE of 3.20 °C, WBGT RMSE of 2.90 °C, and UTCI RMSE of 3.26 °C. These tract-level hourly heat-stress datasets enable direct linkage with public health data.
View details for DOI 10.1038/s41597-026-06909-w
View details for PubMedID 41741487
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A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024.
Scientific data
2026
Abstract
Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the identification of life-threatening heat events. Ls is sensitive to soil moisture variability, improving assessments in agricultural regions. The CHI dataset supports indoor and outdoor applications and is sensitive to humidity, radiation, and wind. Covering the global land area from 60°S to 75°N and 180°W to 180°E, it provides a unique, long-term perspective on spatial and temporal trends in heat stress, which are critical for climate impact research and adaptation planning.
View details for DOI 10.1038/s41597-025-06519-y
View details for PubMedID 41540085
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Age and livability in a hotter climate.
EBioMedicine
2025; 122: 106020
Abstract
Men and women over the age of 65 years comprise the most vulnerable population to increasing heat events associated with climate change. One measure of risk involves the physiological determination of the boundary conditions between compensable (thermal balance possible) and uncompensable (continually rising core temperatures) heat strain. The PSU H.E.A.T. (Human Environmental Age Thresholds) Project conducted 273 human subject-based environmental chamber experiments designed to establish critical environmental limits for a cohort of men and women ranging in age from 65 to 92 yrs, both at rest and at a metabolic rate reflecting activities of daily living (i.e., "livability"). Each critical environmental limit comprises a combination of ambient temperature and relative humidity that reflects the upper extremes of livability for older adults. This review documents and provides an overview of the procedures and seminal findings from the project specific to adults over the age of 65 yrs. Predicted changes in the over-65-year-old population in the United States and the consequent impact of climate change projections on future livability are also presented.
View details for DOI 10.1016/j.ebiom.2025.106020
View details for PubMedID 41232236
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Migrant Laborers in India Face Increased Heat Stress Driven by Climate Warming and ENSO Variability
EARTHS FUTURE
2025; 13 (11)
View details for DOI 10.1029/2025EF006167
View details for Web of Science ID 001605906700001
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Spatial Patterns of Historical Changes in Human Heat Stress Disagree Across Metrics
GEOPHYSICAL RESEARCH LETTERS
2025; 52 (20)
View details for DOI 10.1029/2025GL117966
View details for Web of Science ID 001598643700001
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Heat stress causes economic and welfare disparities across agroecological zones in Burkina Faso.
Communications earth & environment
2025; 6 (1): 744
Abstract
Increased warming due to climate change can induce heat stress in humans and adversely affect labour productivity due to heat-related morbidity. Here, we use a simulation model to examine the effects of heat stress, through declined labour capacity under +1.5 °C and 3.5 °C warming scenarios on agriculture and welfare across the three agroecological zones (Sudanian, Sudano-Sahelian, and Sahelian) in Burkina Faso. In the two scenarios, domestic production declines, with outdoor labour-intensive sectors such as cropping and mining being the most affected, reducing gross domestic product by 9% and 20%, respectively. All households lose welfare in all scenarios except non-poor households in the +1.5 °C scenario. Across zones, crop production declines strongest in the crop-producing Sudanian and Sudano-Sahelian zones. In contrast, relative welfare losses are strongest for households in the Sahelian zone. The study highlights the most vulnerable sectors, household groups, and zones requiring urgent attention in heat stress adaptation and mitigation policies.
View details for DOI 10.1038/s43247-025-02650-1
View details for PubMedID 40937187
View details for PubMedCentralID PMC12420375
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A Linear Sensitivity Framework to Understand the Drivers of the Wet-Bulb Globe Temperature Changes
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2025; 130 (5)
View details for DOI 10.1029/2024JD042195
View details for Web of Science ID 001432871100001
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El Niño Enhances Exposure to Humid Heat Extremes With Regionally Varying Impacts During Eastern Versus Central Pacific Events
GEOPHYSICAL RESEARCH LETTERS
2025; 52 (4)
View details for DOI 10.1029/2024GL112387
View details for Web of Science ID 001420419200001
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A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics
SCIENTIFIC DATA
2025; 12 (1): 246
Abstract
Increasing heat stress with climate change will threaten human health and cause broad social and economic impacts. The evaluation of such impacts depends on a reliable dataset of heat stress projection. Here we present a global dataset of the future projection of dry-bulb, wet-bulb and wet-bulb globe temperature under 1-4°C of global warming levels compared with the preindustrial era using output from 16 CMIP6 global climate models (GCMs). The dataset was bias-corrected against ERA5 reanalysis by adding the GCM-simulated climate change signal onto ERA5 baseline (1950-1976) at 3-hourly frequency. The resulting datasets are provided at fine spatial (0.25° × 0.25°) and temporal (3-hourly) resolution. We validate the bias-correction approach and demonstrate that it substantially improves the GCMs' ability to reproduce both the annual average and entire range of quantiles for all metrics within an ERA5 reference climate state. We expect the dataset to benefit future work on estimating projected changes in both mean and extreme heat stress and assessing consequential health and social-economic impacts.
View details for DOI 10.1038/s41597-025-04527-6
View details for Web of Science ID 001421222600012
View details for PubMedID 39939321
View details for PubMedCentralID PMC11821900
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Mortality impacts of the most extreme heat events
NATURE REVIEWS EARTH & ENVIRONMENT
2025
View details for DOI 10.1038/s43017-024-00635-w
View details for Web of Science ID 001414216900001
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A New, Zero-Iteration Analytic Implementation of Wet-Bulb Globe Temperature: Development, Validation, and Comparison With Other Methods
GEOHEALTH
2024; 8 (10): e2024GH001068
Abstract
Wet-bulb globe temperature (WBGT)-a standard measure for workplace heat stress regulation-incorporates the complex, nonlinear interaction among temperature, humidity, wind and radiation. This complexity requires WBGT to be calculated iteratively following the recommended approach developed by Liljegren and colleagues. The need for iteration has limited the wide application of Liljegren's approach, and stimulated various simplified WBGT approximations that do not require iteration but are potentially seriously biased. By carefully examining the self-nonlinearities in Liljegren's model, we develop a zero-iteration analytic approximation of WBGT while maintaining sufficient accuracy and the physical basis of the original model. The new approximation slightly deviates from Liljegren's full model-by less than 1°C in 99% cases over 93% of global land area. The annual mean and 75%-99% percentiles of WBGT are also well represented with biases within ± 0.5 °C globally. This approximation is clearly more accurate than other commonly used WBGT approximations. Physical intuition can be developed on the processes controlling WBGT variations from an energy balance perspective. This may provide a basis for applying WBGT to understanding the physical control of heat stress.
View details for DOI 10.1029/2024GH001068
View details for Web of Science ID 001383292800001
View details for PubMedID 39350796
View details for PubMedCentralID PMC11439757
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Regimes of Soil Moisture-Wet-Bulb Temperature Coupling with Relevance to Moist Heat Stress
JOURNAL OF CLIMATE
2023; 36 (22): 7925-7942
View details for DOI 10.1175/JCLI-D-23-0132.1
View details for Web of Science ID 001092687500001
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The Poverty Impacts of Labor Heat Stress in West Africa Under a Warming Climate
EARTHS FUTURE
2022; 10 (11)
View details for DOI 10.1029/2022EF002777
View details for Web of Science ID 000879383700001
https://orcid.org/0000-0002-4593-3643