Population dynamics modify urban residents' exposure to extreme temperatures across the United States

Unveiling community adaptations to extreme heat events using mobile phone location data

The escalating frequency, duration, and intensity of extreme heat events have posed a significant threat to human society in recent decades. Understanding the dynamic patterns of human mobility under extreme heat will contribute to accurately assessing the risk of extreme heat exposure. This study leverages an emerging geospatial data source, anonymous cell phone location data, to investigate how people in different communities adapt travel behaviors responding to extreme heat events. Taking the Greater Houston Metropolitan Area as an example, we develop two indices, the Mobility Disruption Index (MDI) and the Activity Time Shift Index (ATSI), to quantify diurnal mobility changes and activity time shift patterns at the city and intra-urban scales. The results reveal that human mobility decreases significantly in the daytime of extreme heat events in Houston while the proportion of activity after 8 p.m. is increased, accompanied with a delay in travel time in the evening. Moreover, these mobility-decreasing and activity-delaying effects exhibited substantial spatial heterogeneity across census block groups. Causality analysis using the Geographical Convergent Cross Mapping (GCCM) model combined with correlation analyses indicates that people in areas with a high proportion of minorities and poverty are less able to adopt heat adaptation strategies to avoid the risk of heat exposure. These findings highlight the fact that besides the physical aspect of environmental justice on heat exposure, the inequity lies in the population's capacity and knowledge to adapt to extreme heat. This research is the first of the kind that quantifies multi-level mobility for extreme heat responses, and sheds light on a new facade to plan and implement heat mitigations and adaptation strategies beyond the traditional approaches.

Urban heatwave, green spaces, and mental health: A review based on environmental health risk assessment framework

Utilizing the framework of environmental health risk assessment and healing, the article reviews the effectiveness and potential of green space systems in mitigating the impact of high temperatures, promoting mental health, and improving the risk characteristics of high-temperature heat waves. We utilized CiteSpace software to conduct a time-zone analysis of the relationship between heatwaves, green spaces, and health using clustered data from 2001 to 2023. This study evaluates the role of green space systems in mitigating high temperatures and enhancing mental health within the environmental health risk assessment framework. Using CiteSpace software, we analyzed literature from 2001 to 2023, focusing on the interactions among heatwaves, green spaces, and health. Our results indicate that most existing research concentrates on hazard identification, with insufficient exploration of the dose-response relationships between green spaces and temperature reduction. Quantitative studies on green space design and spatial optimization are scarce, and guidance on effective configurations remains limited. Additionally, the health impacts of heatwaves vary by region, with a noticeable imbalance in research focus; Asia and Africa, in particular, are underrepresented in studies addressing heatwave effects. We conclude that effective mitigation strategies require: (1) a comprehensive environmental health risk assessment framework that integrates advanced methods like big data analysis and geospatial simulations to improve green space planning and design; (2) further theoretical exploration into the mechanisms by which green spaces regulate temperature and mental health, including detailed analysis of spatiotemporal patterns and the functional optimization of green space structures; and (3) the development of robust parameterized design guidance based on specific therapeutic dosages (green space stimulus) to optimize configurations and enhance the effectiveness of green spaces in mitigating adverse mental health impacts from deteriorating thermal environments. Future research should prioritize underrepresented regions, focusing on exposure levels, dose-response relationships, and high-temperature warning systems while fostering multidisciplinary collaboration to develop effective urban planning and climate adaptation strategies.

Spectrally engineered textile for radiative cooling against urban heat islands

Radiative cooling textiles hold promise for achieving personal thermal comfort under increasing global temperature. However, urban areas have heat island effects that largely diminish the effectiveness of cooling textiles as wearable fabrics because they absorb emitted radiation from the ground and nearby buildings. We developed a mid-infrared spectrally selective hierarchical fabric (SSHF) with emissivity greatly dominant in the atmospheric transmission window through molecular design, minimizing the net heat gain from the surroundings. The SSHF features a high solar spectrum reflectivity of 0.97 owing to strong Mie scattering from the nano-micro hybrid fibrous structure. The SSHF is 2.3°C cooler than a solar-reflecting broadband emitter when placed vertically in simulated outdoor urban scenarios during the day and also has excellent wearable properties.

The potential of urban irrigation for counteracting carbon-climate feedback

Global climate changes, especially the rise of global mean temperature due to the increased carbon dioxide (CO2) concentration, can, in turn, result in higher anthropogenic and biogenic greenhouse gas emissions. This potentially leads to a positive loop of climate-carbon feedback in the Earth's climate system, which calls for sustainable environmental strategies that can mitigate both heat and carbon emissions, such as urban greening. In this study, we investigate the impact of urban irrigation over green spaces on ambient temperatures and CO2 exchange across major cities in the contiguous United States. Our modeling results indicate that the carbon release from urban ecosystem respiration is reduced by evaporative cooling in humid climate, but promoted in arid/semi-arid regions due to increased soil moisture. The irrigation-induced environmental co-benefit in heat and carbon mitigation is, in general, positively correlated with urban greening fraction and has the potential to help counteract climate-carbon feedback in the built environment.

Heat exposure assessment based on high-resolution spatio-temporal data of population dynamics and temperature variations

Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population data, fluctuating temperature, and the exposure-response relationship between temperature and health to construct an advanced heat exposure assessment framework predicated on a population dynamic model. We analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions in Beijing, a major city in China. Our findings highlight significant intra-day population movement between urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity between dynamic population-weighted temperature and average temperature is most pronounced at night. Our research provides a more comprehensive understanding of real urban population heat exposure levels and can furnish city administrators with more scientifically rigorous evidence.

The inequality labor loss risk from future urban warming and adaptation strategies

Heat-induced labor loss is a major economic cost related to climate change. Here, we use hourly heat stress data modeled with a regional climate model to investigate the heat-induced labor loss in 231 Chinese cities. Results indicate that future urban heat stress is projected to cause an increase in labor losses exceeding 0.20% of the total account gross domestic product (GDP) per year by the 2050s relative to the 2010s. In this process, certain lower-paid sectors could be disproportionately impacted. The implementation of various urban adaptation strategies could offset 10% of the additional economic loss per year and help reduce the inequality-related impact on lower-paid sectors. So future urban warming can not only damage cities as a whole but can also contribute to income inequality. The implication of adaptation strategies should be considered in regard to not only cooling requirements but also environmental justice.

New study investigates heat-induced labor loss in 231 Chinese cities, finding that lower-paid sectors could be disproportionately affected in coming decades, although adaptation measures may mitigate inequality related impacts.

Amplified risk of compound heat stress-dry spells in Urban India

Compound warm-dry spells over land, which is expected to occur more frequently and expected to cover a much larger spatial extent in a warming climate, result from the simultaneous or successive occurrence of extreme heatwaves, low precipitation, and synoptic conditions, e.g., low surface wind speeds. While changing patterns of weather and climate extremes cannot be ameliorated, effective mitigation requires an understanding of the multivariate nature of interacting drivers that influence the occurrence frequency and predictability of these extremes. However, risk assessments are often focused on univariate statistics, incorporating either extreme temperature or low precipitation; or at the most bivariate statistics considering concurrence of temperature versus precipitation, without accounting for synoptic conditions influencing their joint dependency. Based on station-based daily meteorological records from 23 urban and peri-urban locations of India, covering the 1970-2018 period, this study identifies four distinct regions that show temporal clustering of the timing of heatwaves. Further, combining joint probability distributions of interacting drivers, this analysis explored compound warm-dry potentials that result from the co-occurrence of warmer temperature, scarcer precipitation, and synoptic wind patterns. The results reveal 50-year severe heat stress solely based on the temperature at each location tends to be more frequent and is expected to become 5 to 17-year compound warm-dry events considering interdependence between attributes. Notably, considering dependence among drivers, a median 6-fold amplification (ranging from 3 to 10-fold) in compound warm-dry spell frequency is apparent relative to the expected annual number of a local (univariate) 50-year severe heatwave episode, indicating warming-induced desiccation is already underway over most of the urbanized areas of the country.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00382-022-06324-y.

Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review

Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases—PubMed, Web of Science, and Scopus—with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.

Mortality and morbidity of asthma and chronic obstructive pulmonary disease associated with ambient environment in metropolitans in Taiwan

Background

This study investigated risks of mortality from and morbidity (emergency room visits (ERVs) and outpatient visits) of asthma and chronic obstructive pulmonary disease (COPD) associated with extreme temperatures, fine particulate matter (PM_2.5), and ozone (O₃) by sex, and age, from 2005 to 2016 in 6 metropolitan cities in Taiwan.

Methods

The distributed lag non-linear model was employed to assess age (0–18, 19–39, 40–64, and 65 years and above), sex-cause-specific deaths, ERVs, and outpatient visits associated with extreme high (99^th percentile) and low (5^th percentile) temperatures and PM_2.5 and O₃ concentrations at 90^th percentile. Random-effects meta-analysis was adopted to investigate cause-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the whole studied areas.

Results

Only the mortality risk of COPD in the elderly men was significantly associated with the extreme low temperatures. Exposure to the 90^th percentile PM_2.5 was associated with outpatient visits for asthma in 0–18 years old boys [RR = 1.15 (95% CI: 1.09–1.22)]. Meanwhile, significant elevation of ERVs of asthma for females aged 40–64 years was associated with exposure to ozone, with the highest RR of 1.21 (95% CI: 1.05–1.39).

Conclusions

This study identified vulnerable subpopulations who were at risk to extreme events associated with ambient environments deserving further evaluation for adaptation.

Social Sensing of Heatwaves

Heatwaves cause thousands of deaths every year, yet the social impacts of heat are poorly measured. Temperature alone is not sufficient to measure impacts and “heatwaves” are defined differently in different cities/countries. This study used data from the microblogging platform Twitter to detect different scales of response and varying attitudes to heatwaves within the United Kingdom (UK), the United States of America (US) and Australia. At the country scale, the volume of heat-related Twitter activity increased exponentially as temperature increased. The initial social reaction differed between countries, with a larger response to heatwaves elicited from the UK than from Australia, despite the comparatively milder conditions in the UK. Language analysis reveals that the UK user population typically responds with concern for individual wellbeing and discomfort, whereas Australian and US users typically focus on the environmental consequences. At the city scale, differing responses are seen in London, Sydney and New York on governmentally defined heatwave days; sentiment changes predictably in London and New York over a 24-h period, while sentiment is more constant in Sydney. This study shows that social media data can provide robust observations of public response to heat, suggesting that social sensing of heatwaves might be useful for preparedness and mitigation.

Synergies between urban heat island and heat waves in Seoul: The role of wind speed and land use characteristics

The effects of heat waves (HW) are more pronounced in urban areas than in rural areas due to the additive effect of the urban heat island (UHI) phenomenon. However, the synergies between UHI and HW are still an open scientific question and have only been quantified for a few metropolitan cities. In the current study, we explore the synergies between UHI and HW in Seoul city. We consider summertime data from two non-consecutive years (i.e., 2012 and 2016) and ten automatic weather stations. Our results show that UHI is more intense during HW periods than non-heat wave (NHW) periods (i.e., normal summer background conditions), with a maximum UHI difference of 3.30°C and 4.50°C, between HW and NHW periods, in 2012 and 2016 respectively. Our results also show substantial variations in the synergies between UHI and HW due to land use characteristics and synoptic weather conditions; the synergies were relatively more intense in densely built areas and under low wind speed conditions. Our results contribute to our understanding of thermal risks posed by HW in urban areas and, subsequently, the health risks on urban populations. Moreover, they are of significant importance to emergency relief providers as a resource allocation guideline, for instance, regarding which areas and time of the day to prioritize during HW periods in Seoul.

Critical risk determination method of energy-flow network for urban electricity system under extreme heat wave impact

The extreme high temperature weather event caused by global warming has increased the risk of urban electric power supply. Critical risk determination method is useful to the system risk prevention and adaptive strategy formulation. Based on analyzing the failure mechanism of power supply under heat wave impact, the paper put forward the method framework of energy-flow network on electric power system risk evaluation. There are three parts in the framework including energy-flow chart analysis of power supply and consumption, establishment and network analysis of Gephi visualization network, and matrix diagram evaluation of node importance. The visualized network of power system with different years and electricity input from external area were established and compared in the case study of Beijing in China. The analysis results showed that the network structure stability of the power system decreased slightly, which was due to the node energy flow becoming high imbalance such as power input from external area, local power generation and energy consumption. For risk prevention, power infrastructures should focus on the high-voltage transmission and distribution facilities and 500 kV hub substations. Meanwhile, to electric power generation and supply, natural gas supply and power supply from Inner Mongolia Autonomous Region played the key roles. And power consumption should focus on the tertiary industry and living consumption.

Variable Urbanization Warming Effects across Metropolitans of China and Relevant Driving Factors

Urbanization is mainly characterized by the expansion of impervious surface (IS) and hence modifies hydrothermal properties of the urbanized areas. This process results in rising land surface temperature (LST) of the urbanized regions, i.e., urban heat island (UHI). Previous studies mainly focused on relations between LST and IS over individual city. However, because of the spatial heterogeneity of UHI from individual cities to urban agglomerations and the influence of relevant differences in climate background across urban agglomerations, the spatial-temporal scale independence of the IS-LST relationship still needs further investigation. In this case, based on Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS) remote sensing image and multi-source remote sensing data, we extracted IS using VrNIR-BI (Visible red and NIR-based built-up Index) and calculated IS density across three major urban agglomerations across eastern China, i.e., the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) to investigate the IS-LST relations on different spatial and temporal scales and clarify the driving factors of LST. We find varying warming effects of IS on LST in diurnal and seasonal sense at different time scales. Specifically, the IS has stronger impacts on increase of LST during daytime than during nighttime and stronger impacts on increase of LST during summer than during winter. On different spatial scales, more significant enhancing effects of IS on LST can be observed across individual city than urban agglomerations. The Pearson correlation coefficient (r) between IS and LST at the individual urbanized region can be as high as 0.94, indicating that IS can well reflect LST changes within individual urbanized region. However, relationships between IS and LST indicate nonlinear effects of IS on LST. Because of differences in spatial scales, latitudes, and local climates, we depicted piecewise linear relations between IS and LST across BTH when the IS density was above 10% to 17%. Meanwhile, linear relations still stand between IS density and LST across YRD and PRD. Besides, the differences in the IS-LST relations across urban agglomeration indicate more significant enhancing effects of IS on LST across PRD than YRD and BTH. These findings help to enhance human understanding of the warming effects of urbanization or UHI at different spatial and temporal scales and is of scientific and practical merits for scientific urban planning.

The Association between Air Temperature and Mortality in Two Brazilian Health Regions

Air temperature, both cold and hot, has impacts on mortality and morbidities, which are exacerbated by poor health service and protection responses, particularly in under-developed countries. This study was designed to analyze the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil (Florianopolis and Recife), between 2005 and 2014. The association between temperature and mortality was performed through the fitting of a quasi-Poisson non-linear lag distributed model. The association between air temperature and mortality was identified for both regions. The results showed that temperature exerted influence on both general mortality indicators and specific causes, with hot and cold temperatures bringing different impacts to the studied regions. Cerebrovascular and cardiovascular deaths were more sensitive to cold temperatures for Florianopolis and Recife, respectively. Based on the application of the very-well documented state-of-the-art methodology, it was possible to conclude that there was evidence that extreme air temperature influenced general and specific deaths. These results highlighted the importance of consolidating evidence and research in tropical countries such as Brazil as a way of understanding climate change and its impacts on health indicators.

Disaster Risk Science: A Geographical Perspective and a Research Framework

In this article, we recall the United Nations’ 30-year journey in disaster risk reduction strategy and framework, review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives, and summarize the framework and contents of disaster risk science research. The object of disaster risk science research is the “disaster system” consisting of hazard, the geographical environment, and exposed units, with features of regionality, interconnectedness, coupling, and complexity. Environmental stability, hazard threat, and socioeconomic vulnerability together determine the way that disasters are formed, establish the spatial extent of disaster impact, and generate the scale of losses. In the formation of a disaster, a conducive environment is the prerequisite, a hazard is the necessary condition, and socioeconomic exposure is the sufficient condition. The geographical environment affects local hazard intensity and therefore can change the pattern of loss distribution. Regional multi-hazard, disaster chain, and disaster compound could induce complex impacts, amplifying or attenuating hazard intensity and changing the scope of affected areas. In the light of research progress, particularly in the context of China, we propose a three-layer disaster risk science disciplinary structure, which contains three pillars (disaster science, disaster technology, and disaster governance), nine core areas, and 27 research fields. Based on these elements, we discuss the frontiers in disaster risk science research.