Targeted implementation of cool roofs for equitable urban adaptation to extreme heat

The Imperative for Hazard- and Place-Specific Assessment of Heat Vulnerability

BACKGROUND

Representing vulnerability is crucial for informing targeted interventions, but existing vulnerability conceptualizations are too general for heat hazard-specific and place-specific relevance. Examining the key decision criteria centering around data choices, selection of input variables, methodological approaches, and theoretical conceptualizations are integral to progressing toward hazard-specific and place-specific vulnerability assessment. Moreover, decisions touching on Geographic Information Science (GIScience)-related issues (e.g., the implications of scale choices and accounting for contextual effects) impact how people who are at risk for adverse heat-health outcomes are represented. In turn, these representations influence how critical interventions are implemented. Given the prospects of increases in adverse heat-health outcomes associated with planetary and urban warming, it is crucial to examine how the representation of heat vulnerability can be enhanced for tailored interventions.

OBJECTIVE

This commentary examines the assumptions underpinning the decision criteria for heat vulnerability analysis and identifies associated implications while recommending priority future research. Reorienting general hazard conceptualizations to reflect contextual, heat-specific nuances is crucial for attenuating heat-related health outcomes.

DISCUSSION

Heat vulnerability studies lack consistent decision criteria, which undermines progress toward hazard-specific and place-specific vulnerability relevance. Some of these limitations are attributable to the persistent application of general, all-hazards conceptualizations to hazard-specific studies. Moreover, inconsistent decision criteria undermine the replicability and validity of studies and propagate uncertainty while compromising progress toward standardized, consistent, scalable approaches and testing of existing assumptions that could strengthen heat vulnerability theory. Given GIScience technologies are central to representing spatial patterns of vulnerability, the epistemological foundation of vulnerability theory can be strengthened when GIScience concepts (e.g., the operational scale of social-environmental determinants of health and assumptions underpinning spatial relationships) are considered during vulnerability representation.

CONCLUSION

Examining decision criteria for heat vulnerability assessment is crucial to identifying optimal sets of heat-specific and place-specific risk indicators, thereby enhancing the representation of vulnerability. https://doi.org/10.1289/EHP14801.

A Socio-spatial Model of the Risk of Hospitalization from Vulnerability to High Temperatures

Urban heat islands and climate change create increasingly hot environments that pose a threat to the health of the public in urban areas throughout the planet. In Maricopa County, Arizona, --- the hottest metropolitan area in the United States---we have previously shown that the effects of heat on mortality are greater in the social and built environments of low-income and communities of color (predominantly Hispanic/Latinx and Black neighborhoods). In this analysis of morbidity data from Maricopa County, we examined the relationship between heat-related hospitalization and summertime daily maximum air temperatures in groups defined at the census block group level as being at high, medium, or low vulnerability based on a Heat Vulnerability Index that was derived from socio-economic and built-environment data. For all three categories of census block group heat vulnerability, we identified 26°C as the daily maximum air temperature threshold beyond which heat-related hospitalization risk increased rapidly with each 1 °C increase in temperature. Compared to this baseline temperature, the relative risk of hospitalization was greatest in the high vulnerability census block groups and least in the low vulnerability census block groups with intermediate increases in the medium vulnerability census block groups. Specifically, with 26°C as the referent, the relative risks of heat-related hospitalization increased from 0.97 at 27°C to 15.71 at 46°C in the low vulnerability group, from 1.03 at 27°C to 53.97 at 46°C in the medium vulnerability group, and from 1.09 at 27°C to 162.46 at 46°C in the high vulnerability group. Our research helps identify areas with high heat population sensitivity and exposure that can be targeted for adaptation with policies and investments, which include, for example, improving public health safety nets and outcomes, access to affordable energy-efficient housing and health care, energy justice, and modifications to cool the urban built environment. Our hospitalization risk estimates can be incorporated into quantitative risk assessments of heat-related morbidity in Maricopa County.

Investigating the cooling effect of urban lakes from the perspective of their characteristics and surrounding landscapes: A case study of 82 urban lakes in China

In the context of global climate change, the increasing frequency of extreme heat events has exacerbated urban thermal issues, affecting the quality of life and posing a serious challenge to the sustainable development of cities. Urban lakes are regarded as effective nature-based solutions for alleviating outdoor thermal environments. In this study, the cooling intensity and extent of 82 urban lakes with their surrounding cooling landscapes across China were quantified based on land surface temperature (LST). eXtreme Gradient Boosting (XGBoost) models were constructed to analyze the indicators of cooling intensity and extent. Furthermore, SHapley Additive exPlanations (SHAP) and partial dependency plots (PDP) were used to interpret the models. The results, measured based on LST, showed that the cooling intensity ranged from 2.87 to 14.10 °C, and the cooling extent spanned from 150 to 1085 m. In terms of overall contribution of all the indicators, lake indices had the most significant impact on cooling intensity, accounting for 33.78 % of the total contribution. Landscape indicators had the most significant impact on the cooling extent, accounting for 67.78 % of the total contribution. Regarding the influence of specific factors, Lake_area played a key role in enhancing cooling intensity, increasing it by up to 0.8 °C when the lake area exceeded 5 km2. In contrast, the patch density of buildings was the primary factor reducing cooling intensity, with a potential decrease of up to 0.6 °C when its value was >20 patches/km2. As for the cooling extent, when the lake area reached 0.5 km2, the cooling extent expanded by approximately 200 m. However, when patch density of cropland exceeded 15 patches/km2, the cooling extent decreased by approximately 500 m. The results provided insights for urban planners regarding the design of urban lakes and their surrounding landscapes to achieve sustainable development.

NPCC4: New York City climate risk information 2022-observations and projections

New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up-to-date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the "hot model" problem. NPCC4 expects to establish new projections-of-record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models.

NPCC4: Tail risk, climate drivers of extreme heat, and new methods for extreme event projections

We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the "hot models" associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large-scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure.

Prioritizing social vulnerability in urban heat mitigation

We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city's demographic composition and physical structure. The study results show that while urban trees may yield less cooling impact (0.27 K of Universal Thermal Climate Index in daytime) relative to cool roofs (0.30 K), the urban trees strategy can emerge as an effective approach for enhancing community resilience in heat stress-related outcomes. Social vulnerability-based heat mitigation was reviewed as vulnerability-weighted daily cumulative heat stress change. The results underscore: (i) importance of considering the community resilience when evaluating heat mitigation impact and (ii) the need to assess planting spaces for urban trees, rooftop areas, and neighborhood vulnerability when designing community-oriented urban overheating mitigation strategies.

Impact of tent shade on heat exposures and simulated heat strain for people experiencing homelessness

Concurrent increases in homelessness and heat intensity, duration, and frequency translate to an urban heat risk trap for the unsheltered population. Homelessness is both a driver and consequence of poor health, co-creating distinct geographies with various risk factors that exacerbate heat vulnerability. We tested the efficacy of different tent shadings over identical tents often observed in the Phoenix area (white bedsheet, mylar, tarp, and aluminum foil) and compared them to a control tent (uncovered) and ambient conditions. We monitored all meteorological variables at all six locations, notably Mean Radiant Temperature (MRT). The in-tent microclimate variability was applied to complete statistical and physiological modeling including substance use on heat strain. Findings indicate that tent shadings resulted in significantly lower in-tent MRT during the day (p < 0.05), but exacerbated in-tent thermal risk during the night compared to the control tent and ambient conditions. Furthermore, we found evidence that the temperature metric matters, and using only either MRT or air temperature (Tair) to assess "heat" could lead to inconsistent conclusions about in-tent microclimate. Interactions between shade types and time significantly amplified in-tent thermal risk. Physiological modeling indicates a higher risk of heat strain (core temperature beyond 40˚C) for people using substances. Decision makers should promote testing different heat intervening strategies toward realizing effective means of protecting human life and preventing heat illnesses. This study illuminates the need for an interdisciplinary approach to studying tents as shelters that considers the total heat load with heat strain modeling.

Smart roofs featuring predictive control: An upgrade for mitigating precipitation extreme-induced pluvial floods

In the face of escalating urban pluvial floods exacerbated by climate change, conventional roof systems fall short of effectively managing precipitation extremes. This paper introduces a smart predictive solution: the Smart Internal Drainage Roof (SIDR) system, which leverages forecasted data to enhance the mitigation of pluvial floods in Central Business District (CBD) areas. Unlike traditional approaches, SIDRs utilize a synergistic combination of Rule-based Control (RBC) and Model Predictive Control (MPC) algorithms, tailored to optimize the operational efficiency of both grey and green roofs. Within the examined 1.3 km2 area in Beijing, China, SIDRs, covering 11% of the site, decreased total flooded areas by 30%-50% and eliminated 60%-100% of high-risk zones during three actual events. Moreover, SIDRs streamlined outflow processes without extending discharge time and reduced flood duration at a high-risk underpass by more than half. The SIDR's distinct features, including a high control resolution of 5 min, integration with existing waterproofs, and advanced 2D dynamic runoff visualization, position it as a scalable and cost-efficient upgrade in urban flood resilience strategies.

The effects of cool roofs on health, environmental, and economic outcomes in rural Africa: study protocol for a community-based cluster randomized controlled trial

BACKGROUND

High ambient air temperatures in Africa pose significant health and behavioral challenges in populations with limited access to cooling adaptations. The built environment can exacerbate heat exposure, making passive home cooling adaptations a potential method for protecting occupants against indoor heat exposure.

METHODS

We are conducting a 2-year community-based stratified cluster randomized controlled trial (cRCT) implementing sunlight-reflecting roof coatings, known as "cool roofs," as a climate change adaptation intervention for passive indoor home cooling. Our primary research objective is to investigate the effects of cool roofs on health, indoor climate, economic, and behavioral outcomes in rural Burkina Faso. This cRCT is nested in the Nouna Health and Demographic Surveillance System (HDSS), a population-based dynamic cohort study of all people living in a geographically contiguous area covering 59 villages, 14305 households and 28610 individuals. We recruited 1200 participants, one woman and one man, each in 600 households in 25 villages in the Nouna HDSS. We stratified our sample by (i) village and (ii) two prevalent roof types in this area of Burkina Faso: mud brick and tin. We randomized the same number of people (12) and homes (6) in each stratum 1:1 to receiving vs. not receiving the cool roof. We are collecting outcome data on one primary endpoint - heart rate, (a measure of heat stress) and 22 secondary outcomes encompassing indoor climate parameters, blood pressure, body temperature, heat-related outcomes, blood glucose, sleep, cognition, mental health, health facility utilization, economic and productivity outcomes, mosquito count, life satisfaction, gender-based violence, and food consumption. We followed all participants for 2 years, conducting monthly home visits to collect objective and subjective outcomes. Approximately 12% of participants (n = 152) used smartwatches to continuously measure endpoints including heart rate, sleep and activity.

DISCUSSION

Our study demonstrates the potential of large-scale cRCTs to evaluate novel climate change adaptation interventions and provide evidence supporting investments in heat resilience in sub-Saharan Africa. By conducting this research, we will contribute to better policies and interventions to help climate-vulnerable populations ward off the detrimental effects of extreme indoor heat on health.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS) DRKS00023207. Registered on April 19, 2021.

Spatially Explicit Correction of Simulated Urban Air Temperatures Using Crowdsourced Data

Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather sensors (PWSs) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that carefully quality-checked PWS data not only improve urban climate models' evaluation but can also serve for bias correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and south-east England during the hot summer of 2018 with the Weather Research and Forecasting (WRF) Model and its building Effect parameterization with the building energy model (BEP-BEM) activated, we evaluated the modeled temperatures against 402 urban PWSs and showcased a heterogeneous spatial distribution of the model's cool bias that was not captured using official weather stations only. This finding indicated a need for spatially explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models' biases in each urban grid cell. This bias-correction technique is the first to consider that modeled urban temperatures follow a nonlinear spatially heterogeneous bias that is decorrelated from urban fraction. Our results showed that the bias correction was beneficial to bias correct daily minimum, daily mean, and daily maximum temperatures in the cities. We recommend that urban climate modelers further investigate the use of quality-checked PWSs for model evaluation and derive a framework for bias correction of urban climate simulations that can serve urban climate impact studies.

The role of climate change and urban development on compound dry-hot extremes across US cities

Compound dry-hot extreme (CDHE) events pose greater risks to the environment, society, and human health than their univariate counterparts. Here, we project decadal-length changes in the frequency and duration of CDHE events for major U.S. cities during the 21st century. Using the Weather Research and Forecasting (WRF) model coupled to an urban canopy parameterization, we find a considerable increase in the frequency and duration of future CDHE events across all U.S. major cities under the compound effect of high-intensity GHG- and urban development-induced warming. Our results indicate that while GHG-induced warming is the primary driver of the increased frequency and duration of CDHE events, urban development amplifies this effect and should not be neglected. Furthermore, We show that the highest frequency amplification of major CDHE events is expected for U.S. cities across the Great Plains South, Southwest, and the southern part of the Northwest National Climate Assessment regions.

Compound Heat Vulnerability in the Record-Breaking Hot Summer of 2022 over the Yangtze River Delta Region

Hourly meteorological data and multisource socioeconomic data collected in the Yangtze River Delta (YRD) region were used to analyze its heat vulnerability during the record-breaking hot summer of 2022 in both daytime and nighttime. Over forty consecutive days, daytime temperatures exceeded 40 °C, and 58.4% of the YRD region experienced 400 h with temperatures hotter than 26 °C during the nighttime. Only 7.5% of the YRD region was under low heat risk during both daytime and nighttime. Strong heat risk combined with strong heat sensitivity and weak heat adaptability led to strong heat vulnerability during both daytime and nighttime in most areas (72.6%). Inhomogeneity in heat sensitivity and heat adaptability further aggravated the heterogeneity of heat vulnerability, leading to compound heat vulnerability in most regions. The ratios of heat-vulnerable areas generated by multiple causes were 67.7% and 79.3% during daytime and nighttime, respectively. For Zhejiang and Shanghai, projects designed to decrease the urban heat island effect and lower the local heat sensitivity are most important. For Jiangsu and Anhui, measures aiming to decrease the urban heat island effect and improve heat adaptability are most important. It is urgent to take efficient measures to address heat vulnerability during both daytime and nighttime.

PanoMRT: Panoramic infrared thermography to model human thermal exposure and comfort

As summer heat waves become the new normal worldwide, modeling human thermal exposure and comfort to assess and mitigate urban overheating is crucial to uphold livability in cities. We introduce PanoMRT, an open source human-biometeorological model to calculate Mean Radiant Temperature (T_MRT), Physiologically Equivalent Temperature (PET), and the Universal Thermal Climate Index (UTCI) from thermal equirectangular 360° panoramas and standard weather information (air temperature, relative humidity, wind speed). We validated the model for hot, dry, clear summer days in Tempe, Arizona, USA with in-situ observations using a FLIR Duo Pro R thermal camera on a rotating arm and the mobile human-biometeorological instrument platform MaRTy. We observed and modeled T_MRT and thermal comfort for 19 sites with varying ground cover (grass, concrete, asphalt), sky view factor, exposure (sun, shade), and shade type (engineered, natural) six times per day. PanoMRT performed well with a Root Mean Square Error (RMSE) of 4.1 °C for T_MRT, 2.6 °C for PET, and 1.2 °C for UTCI, meeting the accuracy requirement of ±5 °C set in the ISO 7726 standard for heat and cold stress studies. RayMan reference model runs without measured surface temperature forcing reveal that accurate longwave radiative flux estimations are crucial to meet the ±5 °C threshold, particularly for shaded locations and during midday when surface temperatures peak and longwave modeling errors are largest. This study demonstrates the importance of spatially resolved 3D surface temperature data for thermal exposure and comfort modeling to capture complex longwave radiation exposure patterns resulting from heterogeneity in built configuration and material radiative and thermal properties in the built environment.

Revisiting regional variation in the age-related reduction in sweat rate during passive heat stress

Aging is associated with attenuated sweat gland function, which has been suggested to occur in a peripheral-to-central manner. However, evidence supporting this hypothesis remains equivocal. We revisited this hypothesis by evaluating the sweat rate across the limbs and trunk in young and older men during whole-body, passive heating. A water-perfused suit was used to raise and clamp esophageal temperature at 0.6°C (low-heat strain) and 1.2°C (moderate-heat strain) above baseline in 14 young (24 (SD 5) years) and 15 older (69 (4) years) men. Sweat rate was measured at multiple sites on the trunk (chest, abdomen) and limbs (biceps, forearm, quadriceps, calf) using ventilated capsules (3.8 cm² ). Sweat rates, expressed as the average of 5 min of stable sweating at low- and moderate-heat strain, were compared between groups (young, older) and regions (trunk, limbs) within each level of heat strain using a linear mixed-effects model with nested intercepts (sites nested within region nested within participant). At low-heat strain, the age-related reduction in sweat rate (older-young values) was greater at the trunk (0.65 mg/cm² /min [95% CI 0.44, 0.86]) compared to the limbs (0.42 mg/cm² /min [0.22, 0.62]; interaction: p = 0.010). At moderate-heat strain, sweat rate was lower in older compared to young (main effect: p = 0.025), albeit that reduction did not differ between regions (interaction: p = 0.888). We conclude that, contrary to previous suggestions, the age-related decline in sweat rate was greater at the trunk compared to the limbs at low-heat strain, with no evidence of regional variation in that age-related decline at moderate-heat strain.