Impact of climate and population changes on the increasing exposure to summertime compound hot extremes

Development, validation and reliability of scales and items for heat wave risk assessment of pregnant women

INTRODUCTION

The 1.2 °C rise of global ambient temperature since the pre-industrial era has led to an increase the intensity and frequency of heatwaves. Given the heightened vulnerability of pregnant women to heat stress, there is an urgent need for tools which accurately assess the knowledge, risk, and perception of pregnant woman toward heatwaves, enabling effective policy actions. In this research, we developed and validated tools to evaluate pregnant women's perceptions of heat wave risks and behaviors.

METHOD

We developed 50 items across seven constructs using the Health Belief Model, identified through a systematic literature review. The constructs comprised 8 Knowledge(K) items, 4 in Perceived Vulnerability (PV), 5 in Perceived Severity (PS), 6 in Perceived Benefit (PB), 4 in Perceived Barrier (PBa), 5 in Cue to Action(Cu) and 18 in Adaptation(A). Cognitive testing was performed with a separate group of pregnant women(n = 20). The tested tools were then administered to 120 pregnant women residing during the spring-summer 2023. Construct validation utilized exploratory factor analysis.

RESULTS

The Principal Axis Factoring Method was employed in the EFA with oblimin rotation for 51 items, considering communality > 0.20, and aiming to extract three factors. Across the three factors with Cronbach's alpha > 0.70, a total of 11 items were distributed. Factor 1 included Perceived Severity (PS1, PS2, PS3 and PS5); Factor 2 included Cue to Action (Cu1, Cu2, Cu3, and Cu4); and Factor 3 encompassed Perceived Vulnerability (PV1, PV2, PV4). Only two of the retained items had factor loadings > 0.50, namely PV4 and PS5. Consequently, the three constructs measuring Perceived Severity, Cues to Action, and Perceived Vulnerability using the HBM among pregnant women were deemed valid.

CONCLUSION

Our study has successfully validated a highly reliable tool which stands ready for application in assessing pregnant women's risk perception regarding heatwaves.

Investigating the impacts of climate change on hydroclimatic extremes in the Tar-Pamlico River basin, North Carolina

Evaluating the forthcoming impacts of climate change is important for formulating efficient and flexible approaches to water resource management. General Circulation Models (GCMs) are primary tools that enable scientists to study both past and potential future climate changes, as well as their impacts on policies and actions. In this work, we quantify the future projected impacts of hydroclimatic extremes on the coastal, risk-prone Tar-Pamlico River basin in North Carolina using GCMs from the Sixth International Coupled Model Intercomparison Project (CMIP6). These models incorporate projected future societal development scenarios (Shared Socioeconomic Pathways, SSPs) as defined in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Specifically, we have utilized historical residential expansion data, the Soil and Water Assessment Tool Plus (SWAT+), the Standardized Precipitation Index (SPI), and the Interquartile Range (IQR) method for analyzing extremes from 2024 to 2100. Our findings include: (1) a trend toward wetter conditions is identified with an increase in flood events toward 2100; (2) projected increases in the severity of flood peaks are found, quantified by a rise of 21% compared to the 2000-2020 period; (3) downstream regions are forecast to experience severe droughts up to 2044; and (4) low-lying and coastal regions are found as particularly susceptible to higher flood peaks and more frequent drought events between 2045 and 2100. This work provides valuable insights into the anticipated shifts in natural disaster patterns and supports decision-makers and authorities in promoting adaptive strategies and sustainable policies to address challenges posed by future climate changes in the Tar-Pamlico region and throughout the state of North Carolina, United States.

Spatiotemporal changes in future precipitation of Afghanistan for shared socioeconomic pathways

Global warming induces spatially heterogeneous changes in precipitation patterns, highlighting the need to assess these changes at regional scales. This assessment is particularly critical for Afghanistan, where agriculture serves as the primary livelihood for the population. New global climate model (GCM) simulations have recently been released for the recently established shared socioeconomic pathways (SSPs). This requires evaluating projected precipitation changes under these new scenarios and subsequent policy updates. This research employed six GCMs from the CMIP6 to project spatial and temporal precipitation changes across Afghanistan under all SSPs, including SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The employed GCMs were bias-corrected using the Global Precipitation Climatological Center's (GPCC) monthly gridded precipitation data with a 1.0° spatial resolution. Subsequently, the climate change factor was calculated to assess precipitation changes for both the near future (2020-2059) and the distant future (2060-2099). The bias-corrected projections' multi-model ensemble (MME) revealed increased precipitation across most of Afghanistan for SSPs with higher emissions scenarios. The bias-corrected simulations showed a substantial increase in summer precipitation of around 50%, projected under SSP1-1.9 in the southwestern region, while a decline of over 50% is projected in the northwestern region until 2100. The annual precipitation in the northwest region was projected to increase up to 15% for SSP1-2.6. SSP2-4.5 showed a projected annual precipitation increase of around 20% in the southwestern and certain eastern regions in the far future. Furthermore, a substantial rise of approximately 50% in summer precipitation under SSP3-7.0 is expected in the central and western regions in the far future. However, it is crucial to note that the projected changes exhibit considerable uncertainty among different GCMs.

Projected climate extremes over agro-climatic zones of Ganga River Basin under 1.5, 2, and 3° global warming levels

Recurring floods, droughts, heatwaves, and other hydro-meteorological extreme events are likely to be increased under the climate change scenarios. The increased risk of these extreme events might have more exposure to the population; thus, it is important to discuss such extreme events and their projected behavior under a changing climate scenario. In the present study, we have computed the extreme precipitation and temperature indices over the 10 agro-climatic zones falling under the Ganga River Basin (GRB)utilizing a high-resolution daily gridded temperature and precipitation multi-model ensembled CMIP6 dataset (0.25° × 0.25°) under global warming levels of 1.5 °C, 2 °C, and 3 °C. We found that the annual daily minimum temperature (TNN) showed a higher rise of about 67% than the maximum temperature (TXX) of 48% in GRB. The basin also experiences a greater increase in the frequency of warm nights (TN90P) of about 67.71% compared to warm days (TX90P) of 29.1% for the 3 °C global warming level. Along with extreme indices, the population exposed due to the impact of the extreme maximum temperature has also been analyzed for progressive warming levels. Population exposure to extreme temperature event (TXX) has been analyzed with 20-year return period using GEV distribution method. The study concludes that the exposed population to extreme temperature event experienced an increase from 46.99 to 52.16% for the whole Ganga Basin. Consecutive dry days (CDD) and consecutive wet days (CWD) both show a significant increasing trend, but CWD has a significant increase in the majority of the zones, while CDD shows a significant decreasing trend for some of the zones for three warming levels periods. Extreme climate indices help to understand the frequency and intensity of extreme weather events such as heavy rainfall, droughts, and heatwaves to develop early warning systems and adaptation strategies to mitigate such events.

Historic evolution of population exposure to heatwaves in Xinjiang Uygur Autonomous Region, China

Heatwaves have pronounced impacts on human health and the environment on a global scale. Although the characteristics of heatwaves has been well documented, there still remains a lack of dynamic studies of population exposure to heatwaves (PEH), particularly in the arid regions. In this study, we analyzed the spatio-temporal evolution characteristics of heatwaves and PEH in Xinjiang using the daily maximum temperature (Tmax), relative humidity (RH), and high-resolution gridded population datasets. The results revealed that the heatwaves in Xinjiang occur more continually and intensely from 1961 to 2020. Furthermore, there is substantial spatial heterogeneity of heatwaves with eastern part of the Tarim Basin, Turpan, and Hami been the most prone areas. The PEH in Xinjiang showed an increasing trend with high areas mainly in Kashgar, Aksu, Turpan, and Hotan. The increase in PEH is mainly contributed from population growth, climate change and their interaction. From 2001 to 2020, the climate effect contribution decreased by 8.5%, the contribution rate of population and interaction effects increased by 3.3% and 5.2%, respectively. This work provides a scientific basis for the development of policies to improve the resilience against hazards in arid regions.

How can urban parks be planned to maximize cooling effect in hot extremes? Linking maximum and accumulative perspectives

How to maximize the cooling effect of urban parks in hot extremes has been closely linked to well-beings of citizens. Few studies have quantified urban parks' cooling effect in hot extremes from both maximum and accumulative perspectives. Here, we explored 65 urban parks' cooling effect based on spatially continuous cooling curves using multiple satellite images of Greater Xi'an (34°06' ∼34°34' N, 108°33' ∼109°15' E), one of China's metropolises with frequent hot extremes during July and August in 2019 summer. From maximum perspective, the urban parks cool down as far as 151.4 m, and covering 63.62 ha area, circa five times their own area in hot extremes; from accumulative perspective, the average cooling intensity is 0.78 °C along the whole continuous cooling distance spectrum, accumulated as 153.87 °C•m. And the urban parks show stronger accumulative cooling effect in hot extremes than the relative moderate temperatures. The cooling range could be maximized in large parks with dense trees, also in complex-shaped parks with strong interaction with surrounding environment. Small parks such as neighborhood parks located in the densely populated area are with maximum efficiency, cooling down about nine times their own area, which could serve as highly efficient cooling networks. Enhancing vegetation growth and coupling both blue and green infrastructures are always effective to increase accumulative cooling intensity in hot extremes. Our findings provide nature-based solutions (NBS) to counteracting heat stresses from the intense and frequent hot extremes in the future, also helpful for energy saving in the continuing climate change scenario.

Effect and attributable burden of hot extremes on bacillary dysentery in 31 Chinese provincial capital cities

BACKGROUND

High atmospheric temperature has been associated with the occurrence of bacillary dysentery (BD). Recent studies have suggested that hot extremes may influence health outcomes, however, none have examined the association between hot extremes and BD risk, especially at the national level.

OBJECTIVES

To assess the effect and attributable burden of hot extremes on BD cases and to identify populations at high risk of BD.

METHODS

Daily incident BD data of 31 provincial capital cities from 2010 to 2018 were collected from the Chinese Center for Disease Control and Prevention, weather data was obtained from the fifth generation of the European Re-Analysis Dataset. Three types of hot extremes, including hot day, hot night, and hot day and night, were defined according to single or sequential occurrence of daytime hot and nighttime hot within 24 h. A two-stage analytical strategy combined with distributed lag non-linear models (DLNM) was used to evaluate city-specific associations and national pooled estimates.

RESULTS

Hot extremes were significantly associated with the risk of BD on lagged 1-6 days. The overall cumulative relative risk (RR) was 1.136 [95% confidence interval (CI): 1.022, 1.263] for hot day, 1.181 (95% CI: 1.019, 1.369) for hot night, and 1.154 (95% CI: 1.038, 1.283) for hot day and night. Northern residents, females, and children younger than or equal to 14 years old were vulnerable under hot night, southern residents were vulnerable under hot day, and males were vulnerable under hot day and night. 1.854% (95% CI: 1.294%, 2.205%) of BD cases can be attributable to hot extremes, among which, hot night accounted for a large proportion.

CONCLUSIONS

Hot extremes may significantly increase the incidence risk and disease burden of BD. Type-specific protective measures should be taken to reduce the risk of BD, especially in those we found to be particularly vulnerable.

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

South Asia is home to one of the fastest-growing populations in Asia, and human activities are leaving indelible marks on the land surface. Yet the likelihood of successive observed droughts in South Asia (SA) and its four subregions (R-1: semi-arid, R-2: arid, R-3: subtropical wet, and R-4: tropical wet and dry) remains poorly understood. Using the state-of-the-art self-calibrated Palmer Drought Severity Index (scPDSI), we examined the impact of different natural ocean variability modes on the evolution, severity, and magnitude of observed droughts across the four subregions that have distinct precipitation seasonality and cover key breadbaskets and highly vulnerable populations. The study revealed that dryness had significantly increased in R-1, R-2, and R-4 during 1981–2020. Temporal analysis revealed an increase in drought intensity for R-1 and R-4 since the 2000s, while a mixed behavior was observed in R-2 and R-3. Moreover, most of the sub-regions witnessed a substantial upsurge in annual precipitation, but a significant decrease in vapor pressure deficit (VPD) during 1981–2020. The increase in precipitation and the decline in VPD partially contributed to a significant rise in Normalized Difference Vegetation Index (NDVI) and a decrease in dryness. In contrast, a strong positive correlation was found between drought index and precipitation, and NDVI across R-1, R-2, and R-4, whereas temperature and VPD exhibited a negative correlation over these regions. No obvious link was detected with El-Niño Southern Oscillation (ENSO) events, or Indian Ocean Dipole (IOD) and drought evolution, as explored for certain regions of SA. The findings showed the possibility that the precipitation changes over these regions had an insignificant relationship with ENSO, IOD, and drought onset. Thus, the study results highlight the need for considering interactions within the longer climate system in describing observed drought risks rather than aiming at drivers from an individual perspective.

Projected urban exposure to extreme precipitation over South Asia

Urbanization is one of the pivotal aspects of socioeconomic advancement which is critically vulnerable to climatic extremes. Extreme precipitation and urbanization are largely interlinked. Estimating the extreme precipitation-induced urban area exposure is the fundamental aspect of urban risk assessment for precipitation-related floods. In this study, future urban area exposure to extreme precipitation and associated influential factors are investigated over South Asia under 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C global warming thresholds. In this regard, we used newly released 20 up-to-date climate models outputs, and five Integrated Assessment Models (IAMs) based urban land-use products under four combined scenarios of the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from the sixth phase of Coupled Model Intercomparison Project (CMIP6). Extreme precipitation is characterized by adopting 20-, 50-, and 100-year return periods of annual maximum daily precipitation. Results reveal a massive urban area expansion over South Asia which is the utmost by 186.4% under SSP3-7.0 than the reference period (1995-2014). The variations in projected urban areas mainly occur in Indo-Gangetic Plain (IGP) region among scenarios. In relative terms, extreme precipitation frequency and associated urban area exposure are prospective to increase with continued global warming. The exposed urban area varies 4.5- to 7.4-fold higher under different warming thresholds than the reference period. The leading increase is estimated (7.4-fold) under 4.0 °C. Notably, for global warming targets set out by the Paris Agreement (1.5 °C, and 2.0 °C), exposed urban area is intended to be 10.2% higher under 2.0 °C than 1.5 °C. Spatially, the exposed urban area will be dominant in the southeast region relative to the reference period. Importantly, the interaction effect (simultaneous change in climate-urban land) is the principal contributor to the changes in urban area exposure to extreme precipitation over South Asia. However, this study's findings strongly support the accomplishment of the Paris Agreement target and provide a scientific basis for formulating urban land-use policy interventions.

Health Risks to the Russian Population from Temperature Extremes at the Beginning of the XXI Century

Climate change and climate-sensitive disasters caused by climatic hazards have a significant and increasing direct and indirect impact on human health. Due to its vast area, complex geographical environment and various climatic conditions, Russia is one of the countries that suffers significantly from frequent climate hazards. This paper provides information about temperature extremes in Russia in the beginning of the 21st century, and their impact on human health. A literature search was conducted using the electronic databases Web of Science, Science Direct, Scopus, and e-Library, focusing on peer-reviewed journal articles published in English and in Russian from 2000 to 2021. The results are summarized in 16 studies, which are divided into location-based groups, including Moscow, Saint Petersburg and other large cities located in various climatic zones: in the Arctic, in Siberia and in the southern regions, in ultra-continental and monsoon climate. Heat waves in cities with a temperate continental climate lead to a significant increase in all-cause mortality than cold waves, compared with cities in other climatic zones. At the same time, in northern cities, in contrast to the southern regions and central Siberia, the influence of cold waves is more pronounced on mortality than heat waves. To adequately protect the population from the effects of temperature waves and to carry out preventive measures, it is necessary to know specific threshold values of air temperature in each city.

Increased high-temperature extremes and associated population exposure in Africa by the mid-21st century

Previous studies warned that heat extremes are likely to intensify and frequently occur in the future due to climate change. Apart from changing climate, the population's size and distribution contribute to the total changes in the population exposed to heat extremes. The present study uses the ensemble mean of global climate models from the Coupled Model Inter-comparison Project Phase six (CMIP6) and population projection to assess the future changes in high-temperature extremes and exposure to the population by the middle of this century (2041-2060) in Africa compared to the recent climate taken from 1991 to 2010. Two Shared Socioeconomic Pathways (SSPs), namely SSP2-4.5 and SSP5-8.5, are used. Changes in population exposure and its contributors are quantified at continental and for various sub-regions. The intensity of high-temperature extremes is anticipated to escalate between 0.25 to 1.8 °C and 0.6 to 4 °C under SSP2-4.5 and SSP5-8.5, respectively, with Sahara and West Southern Africa projected to warm faster than the rest of the regions. On average, warm days' frequency is also expected to upsurge under SSP2-4.5 (26-59%) and SSP5-8.5 (30-69%) relative to the recent climate. By the mid-21st century, continental population exposure is expected to upsurge by ~25% (28%) of the reference period under SSP2-4.5|SSP2 (SSP5-8.5|SSP5). The highest increase in exposure is expected in most parts of West Africa (WAF), followed by East Africa. The projected changes in continental exposure (~353.6 million person-days under SSP2-4.5|SSP2 and ~401.4 million person-days under SSP5-8.5|SSP5) are mainly due to the interaction effect. However, the climate's influence is more than the population, especially for WAF, South-East Africa and East Southern Africa. The study findings are vital for climate change adaptation.