Search Results (22)

Heatwaves (HWs) are becoming more frequent and severe, posing a significant threat to human health. Studies have shown that extreme heat, whether as incremental temperature increases or prolonged HWs, is associated with an increased risk of heat-related illnesses. However, there is still limited understanding of how these impacts unfold in Brazil, given its unique social, environmental, and health-system contexts. I this perspective article, we explore the effects of HWs on human physiology, examine the social and biological factors that contribute to heat stress, and identify vulnerable populations at disproportionate risk. We also discuss the potential consequences of extreme heat in other aspects of society, such as agriculture and energy, and assess the challenges of strengthening resilience in Brazil’s health sector. Our key contribution are to make visible the hidden burden of heat-related mortality, to examine how fragmented governance constrains the adaptive capacity of Brazil’s health sector, and to reflect on pathways to strengthen resilience to heatwaves. Full article

Good solutions for sustainable development promote social, ecological, and economic aspects in synergistic ways. Wind energy projects have a large potential to achieve this, if their locations are carefully selected. On the contrary, placing wind turbines inside forest areas with high biodiversity, cultural significance, and recreational use generates conflicts between different dimensions of sustainability, and between supporters and opponents of such projects. The resulting green-versus-green dilemma involves a conflict between idealism and pragmatism, as incorporated in literature by the personalities of Don Quixote and Sancho Panza. Sustainable solutions require both aspects as well as realism. Forest areas have crucial climate benefits ranging from the absorption of CO₂ and other emissions, providing shade and cooling during heatwaves to the storage of humidity and water. Climate change is not solely a problem of rising temperature. It also involves changes in humidity and precipitation, and the related problems of desertification and deforestation. Accordingly, a strategy of deforestation for hosting wind farms seems questionable. Instead, constructing wind turbines with energy storage capacities on deserted ground and using their economic and energetic gains for a subsequent afforestation of the surrounding land would achieve synergetic sustainability benefits for biodiversity, human wellbeing, and the climate. Full article

An important aspect of a well-designed urban form is supporting active school travel by adolescents, as it has positive effects on physical activity, healthy lifestyles, and reducing vehicle-related carbon emissions. To achieve this, it is necessary to provide sufficient shading and fewer detours on home–school routes, especially in an era of frequent heatwaves. Analyzing the school travel environment at the city scale is essential for identifying practical solutions and informing comprehensive urban policy-making. This study proposes a framework for investigating, assessing, and intervening in home–school routes in Nanjing, China, emphasizing a dual assessment of commuting routes based on the pedestrian detour ratio and shading ratio. This work reveals that approximately 34% of middle school households in Nanjing face challenges in walking to and from school, with only 24.18% of walking routes offering fewer detours and sufficient shade. We advocate reengineering urban forms by reducing barriers to facilitate shortcuts, thereby providing school-age students with better access to cooler and healthier environments, aiming to promote walking and reduce car dependence. The findings may encourage more families to engage in active commuting and serve as a lever to drive school decarbonization and combat climate warming. Our work, with transferability to other cities, can assist urban designers in piloting urban (re)form incrementally and pragmatically to promote sustainable urban agendas. Full article

Introduction: The increase in average air temperature and multiple extreme weather events, such as heatwaves and droughts, pose significant health risks to humans. This scoping review aims to examine the current state of the existing literature concerning the potential relationship between substance abuse and climate change, along with the aspects it encompasses. Material and methods: The review followed PRISMA guidelines for methodological rigor, aiming to identify studies on drug abuse. Searches were conducted across the primary databases using specific search strings. Quality assessment involved evaluating the research question’s clarity, search strategy transparency, consistency in applying the inclusion/exclusion criteria, and reliability of data extraction. Results: Most studies were conducted in the USA. They included observational and retrospective quantitative studies, as well as qualitative and prospective observational ones. Research examined the correlation between extreme weather and some substance abuse. All studies analyzed the adverse effects of climate change, especially heatwaves, on both physiological and pathological levels. Conclusions: The scoping review notes the scarcity of studies about the correlation between substance abuse and climate change, and emphasizes the threats faced by individuals with substance abuse and mental health disorders due to climate change. Full article

Marine heatwaves (MHWs) are known to pose a threat to aquatic ecosystems and coastal communities and, as a result, they receive significant attention nowadays, thus motivating our scientific interest in better understanding the regional patterns of these events. In this study, we analyze MHWs in the SE part of the Baltic Sea, defining them as anomalously warm water events, where the water temperature exceeds the 90th percentile threshold of the corresponding calendar day for at least five or more consecutive days. Our study is based on a combination of long-term (1993–2023) in situ data, field measurements, and satellite-derived sea surface temperature data during the warm (May–August) period. Study results suggest that although short-lived (5–9 days) MHW events typically dominate throughout the analyzed period, the occurrences of longer (more than three weeks) and more intense MHWs have increased in our study region in the recent decade. The heatwaves are observed both in coastal and open waters, with SST anomalies up to around 5–6 °C above the 90th percentile threshold during extreme events, extending thermal influence as deep as 20 m during prolonged and more intense events. We believe that the results of this study contribute to a better understanding of MHW patterns in the study region, which is important from an ecological and socio-economic point of view, providing valuable insights for human health aspects as well. Full article

Human-induced climate change has profound effects on extreme events, particularly those linked to global warming, such as heatwaves, droughts, and wildfires. These events disrupt ecosystems, emphasizing the imperative to understand the interactions among them to gauge the risks faced by vulnerable communities. Vulnerability levels vary primarily based on a community’s resources. Rural areas, especially in the Mediterranean region of Europe, are experiencing acute depopulation, creating a complex situation affecting various aspects of society, from economic declines to cultural heritage loss. Population decline in rural regions weakens resources, leading to the abandonment of built environments, fostering desertification, and elevating the risk of wildfires. Communities undergoing this deterioration process become exceptionally vulnerable, especially when dealing with and recovering from extreme natural phenomena. This review offers insights into the dynamics of these hazards and the predominant challenges in rural areas. By focusing on a topic that has received limited attention, the aim is to inform future research initiatives, ultimately improving risk assessment and mitigation strategies for these vulnerable communities. Full article

Recognizing the growing trend of the urban population and the undeniable fact of global and regional climate change, it becomes increasingly important to explore how we can improve the livability of our cities not only in the distant future but also in the next few years. A critical aspect of this endeavor involves studying how we can effectively mitigate human heat load in urban areas. In our research, in the case of a medium-sized city (Szeged, Hungary), we examined the effect of surface modifications caused by vegetation on human thermal perception during the day and night of two heatwave days. To achieve this, we used the MUKLIMO_3 micro-scale climate model to simulate the thermal climate of Szeged, while the thermal load was assessed with the perceived temperature calculated by the Klima-Michel model. Our analysis also relied on the local climate zone (LCZ) system to describe the original land cover and the additional urban green spaces in the study area. We scrutinized the effects of added vegetation of different types and densities, as well as the presence of protective forests surrounding the city. Our findings revealed that the effect of the added vegetation can only be detected on the modified surfaces and in their immediate vicinity. Notably, dense urban greenery resulted in up to a 2–3 °C reduction in perceived temperature in certain areas during the daytime, highlighting the profound impact of targeted green space development. In addition, it is crucial to consider the airflow-blocking effect of woody vegetation, which can increase thermal load by 1–3 °C in the areas located in a downwind direction. Therefore, the changing regional climatic conditions (e.g., wind direction) and the development of the right type and location of urban green areas deserve special attention during modern urban planning processes. Full article

Global aquaculture growth will most probably face specific conditions derived from climate change. In fact, the most severe impacts of these changes will be suffered by aquatic populations in restrictive circumstances, such as current aquaculture locations, which represent a perfect model to study global warming effects. Although the impact of temperature on fish reproduction has been characterized in many aspects, this study was focused on recreating more realistic models of global warming, particularly considering heatwave phenomena, in order to decipher its effects on male gametes (spermatozoa). For this purpose, thermal stress via a heatwave simulation (mimicking a natural occurring heatwave, from 24 to 30 °C) was induced in adult tench (Tinca tinca) males and compared with a control group (55.02 ± 16.44 g of average body wet weight). The impact of the thermal stress induced by this climate change event was assessed using cellular and molecular approaches. After the heatwave recreation, a multiparametric analysis of sperm quality, including some traditional parameters (such as sperm motility) and new ones (focus on redox balance and sperm quality biomarkers), was performed. Although sperm concentration and the volume produced were not affected, the results showed a significant deleterious effect on motility parameters (e.g., reduced progressive motility and total motility during the first minute post-activation). Furthermore, the sperm produced under the thermal stress induced by this heatwave simulation exhibited an increased ROS content in spermatic cells, confirming the negative effect that this thermal stress model (heatwave recreation) might have had on sperm quality. More importantly, the expression of some known sperm quality and fertilization markers was decreased in males exposed to thermal stress. This present study not only unveils the potential effects of climate change in contemporary and future fish farming populations (and their underlying mechanisms) but also provides insights on how to mitigate and/or avoid thermal stress due to heatwave events. Full article

Climate change is expected to significantly affect countries in Southern Europe and the Mediterranean Basin, causing higher-than-average temperature increases, considerable reductions in rainfall and water runoff, and extreme events such as heatwaves. These pose severe threats to local energy systems, requiring a reliable and quantitative risk analysis. A methodological approach is thus proposed which covers both energy supply and demand, utilizing the latest climate projections under different greenhouse gas emissions scenarios and an appropriate scale for each energy form. For energy supply technologies, risks are assessed through statistical regression models and/or mathematical equations correlating climatic parameters with energy productivity. To analyze climate risks for energy demand, bottom–up models were developed, integrating both behavioral and policy aspects which are often considered in a very limited way. The results show that climate change will mainly affect electricity generation from hydroelectric and thermal power plants, with variations depending on the plants’ locations and uncertainties associated with precipitation and runoff changes. The climate risks for solar and wind energy were found to be low. Energy consumption will also be affected, but the range of risks depends on the ambition and the effectiveness of measures for upgrading the thermal performance of buildings and the intensity of climate change. Full article

Heatwave (HW) number (HWN), frequency (HWF), duration (HWD), magnitude (HWM), and amplitude (HWA) are key aspects for interpreting and understanding HW characteristics worldwide. Most previous HW studies over the Kingdom of Saudi Arabia (KSA) focused only on the temperature extremes, so this study aims to assess the decadal changes, anomalies, and spatiotemporal variations in the five HW aspects over KSA during the last four decades (1982–2021) using the ClimPACT2 software. Daily gridded (0.25° × 0.25°) maximum (TX) and minimum (TN) temperatures from the ECMWF-ERA5 reanalysis dataset were used to compute these heat wave (HW) aspects. The HW aspects were derived in ClimPACT2 using the Excess Heat Factor (EHF), the 90th percentile of TX (TX90), and the 90th percentile of TN (TN90), all based on the reference climate period of 1982–2011. The results showed that the decadal sum and anomaly of the five HW aspects increased gradually during the last four decades (1982–2021). The three indices showed that the maximum decadal sum of HWN (42 events), HWF (255 days), and HWD (145 days) occurred in the last decade. Additionally, the last decade has the maximum decadal sum of HWM (175–463 °C) and HWA (189–471 °C) as derived from TX90 and TN90, which is confirmed by EHF, with ranges of 7–58 and 15–185 °C², respectively. Finally, the periods 2015–2021 and 1984–1986 recorded the highest and lowest values of annual HW aspects, respectively, across the study period. Full article

Soil moisture (SM) is an indicator of the moisture status of the land surface, which is useful for monitoring extreme weather events. Representative global SM datasets include the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP), the Global Land Data Assimilation System (GLDAS), and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), but due to their low spatial resolutions, none of these datasets well describe SM changes in local areas, and they tend to have a low accuracy. Machine learning (ML)-based SM predictions have demonstrated high accuracy, but obtaining semi-real-time SM information remains challenging, and the dependence of the validation accuracy on the data sampling method used, such as random or yearly sampling, has led to uncertainties. In this study, we aimed to develop an ML-based model for real-time SM estimation that can capture local-scale variabilities in SM and have reliable accuracy, regardless of the sampling method. This study was conducted in South Korea, and satellite image data, numerical weather prediction (NWP) data, and topographic data provided within one day were used as the input data. For SM modeling, 13 input variables affecting the surface SM status were selected: 10- and 20-day cumulative standardized precipitation indexes (SPI10 and SPI20), a normalized difference vegetation index (NDVI), downward shortwave radiation (DSR), air temperature (Tair), land surface temperature (LST), soil temperature (Tsoil), relative humidity (RH), latent heat flux (LE), slope, elevation, topographic ruggedness index (TRI), and aspect. Then, SM models based on random forest (RF) and automated machine learning (AutoML) were constructed, trained, and validated using random sampling and leave-one-year-out (LOYO) cross-validation. The RF- and AutoML-based SM models had significantly high accuracy rates based on comparisons with in situ SM (mean absolute error (MAE) = 2.212–4.132%; mean bias error (MBE) = −0.110–0.136%; root mean square error (RMSE) = 3.186–5.384%; correlation coefficient (CC) = 0.732–0.913), while the AutoML-based SM model tended to have a higher accuracy than the RF-based SM model, regardless of the data sampling method used. In addition, when compared to in situ SM data, the SM models demonstrated the highest accuracy, outperforming both GLDAS and ERA5 SM data and well representing changes in the dryness/wetness of the land surface according to meteorological events (heatwave, drought, and rainfall). The SM models proposed in this study can, thus, offer semi-real-time SM data, aiding in the monitoring of moisture changes in the land surface, as well as short-term meteorological disasters, like flash droughts or floods. Full article

With ongoing global warming, heatwave-related disasters are on the rise, exerting a multifaceted impact on both the natural ecosystem and human society. While temperature has been extensively studied in the effects of extreme heat on human health, humidity has often been ignored. It is crucial to consider the combined influence of temperature and humidity when assessing heatwave risks and safeguarding human well-being. This study, leveraging remote sensing products and reanalysis data, presented the first analysis of the spatiotemporal variations in global human-perceived heatwaves on a seasonal scale from 2000 to 2020, and further employed the Random Forest (RF) regression model to quantitatively assess the explanatory power of seven driving factors. The study found that since the 21st century (1) changes in Heat Index (HI) have varied significantly worldwide, with the majority of regions witnessing an increase, particularly at higher latitudes. The largest HI-increasing area was observed in the second quarter (S2), while the overall HI increase peaked in the third quarter (S3); (2) except for the decreasing area of none-risk regions, the regions under all other risk levels expanded (the proportion of high-risk areas in the world increased from 2.97% to 3.69% in S2, and from 0.04% to 0.35% in the fourth quarter (S4)); (3) aspect demonstrated the greatest explanatory power for the global heatwave distribution (0.69–0.76), followed by land-use coverage (LUCC, 0.48–0.55) and precipitation (0.16–0.43), while the explanatory power of slope and nighttime light (NTL) was rather low; (4) over the years, the explanatory power of each factor for heatwave distribution underwent a minor decrease without significant trend, but exhibited seasonal periodicity. Climatic factors and LUCC were most impactful in the first quarter (S1), while DEM and other human factors dominated in S2; and (5) interaction factors showed no significant trends over the years, but the explanatory power of DEM and slope increased notably when interacting with climate factor, aspect, and LUCC, respectively. The interactions between the aspect and LUCC with precipitation yielded the highest explanatory power (above 0.85) across all interactions. To effectively tackle heatwave risks, it is suggested to concentrate on high-latitude regions, reinforce land use and urban planning with eco-friendly strategies, scrutinize the interplay between precipitation and heatwaves, capitalize on topographic data for devising well-informed prevention measures, and tailor response strategies to accommodate seasonal fluctuations. This study offers valuable insights for enhancing climate change adaptation, disaster prevention, and mitigation strategies, ultimately contributing to the alleviation of extreme heatwaves and risk reduction. Full article

Background: This study aims to investigate the current impacts of extreme temperature and heatwaves on human health in terms of both mortality and morbidity. This systematic review analyzed the impact of heatwaves on mortality, morbidity, and the associated vulnerability factors, focusing on the sensitivity component. Methods: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow checklist. Four databases (Scopus, Web of Science, EBSCOhost, PubMed) were searched for articles published from 2012 to 2022. Those eligible were evaluated using the Navigation Guide Systematic Review framework. Results: A total of 32 articles were included in the systematic review. Heatwave events increased mortality and morbidity incidence. Sociodemographic (elderly, children, male, female, low socioeconomic, low education), medical conditions (cardiopulmonary diseases, renal disease, diabetes, mental disease), and rural areas were crucial vulnerability factors. Conclusions: While mortality and morbidity are critical aspects for measuring the impact of heatwaves on human health, the sensitivity in the context of sociodemographic, medical conditions, and locality posed a higher vulnerability to certain groups. Therefore, further research on climate change and health impacts on vulnerability may help stakeholders strategize effective plans to reduce the effect of heatwaves. Full article

A heatwave (HW) is a spatiotemporally contiguous event that is spatially widespread and lasts many days. HWs impose severe impacts on many aspects of society and terrestrial ecosystems. Here, we systematically investigate the influence of the selected threshold method (the absolute threshold method ($ABS$), quantile-based method ($QTL$), and moving quantile-based method ($QT{L}_{mov}$)) and selected variables (heat index ($HI$), air temperature ($T_{air}$)) on the change patterns of spatiotemporally contiguous heatwave (STHW) characteristics over China from 1961–2017. Moreover, we discuss the different STHW change patterns among different HW severities (mild, moderate, and severe) and types (daytime and nighttime). The results show that (1) all threshold methods show a consistent phenomenon in most regions of China: STHWs have become longer-lasting (6.42%, 66.25%, and 148.58% HW days ($\mathrm{HWD}$) increases were found from 1991–2017 compared to 1961–1990 corresponding to $ABS$, $QTL$, and $QT{L}_{mov}$, respectively, as below), more severe (14.83%, 89.17%, and 158.92% increases in HW severity ($\mathrm{HWS}$) increases), and more spatially widespread (14.92%, 134%, and 245.83% increases in the summed HW area (${\mathrm{HWA}}_{\mathrm{sum}}$)). However, the HW frequency ($\mathrm{HWF}$) of moderate STHWs in some regions decreased as mild and moderate STHWs became extreme; (2) for threshold methods that do not consider seasonal variations (i.e., $ABS$ and $QTL$), the spatial $HI$ exceedance continuity was relatively weak, thus resulting in underestimated STHW characteristics increase rates; (3) for different variables defining STHWs, the relative changing ratio of the $HI$-based STHW was approximately 20% higher than that of the $T_{air}$-based STHW for all STHW characteristics, under the $QT{L}_{mov}$ threshold; (4) for different STHW types, the nighttime STHW was approximately 60% faster than the daytime STHW increase considering the $QTL$ threshold and approximately 120% faster for the $QT{L}_{mov}$ method. This study provides a systematic investigation of different STHW definition methods and will benefit future STHW research. Full article

Although extreme weather events have played a constant role in human history, heatwaves (HWs) have become more frequent and intense in the past decades, causing concern especially in light of the increasing evidence on climate change. Despite the increasing number of reviews suggesting a relationship between heat and health, these reviews focus primarily on mortality, neglecting other important aspects. This systematic review of reviews gathered the available evidence from research syntheses conducted on HWs and health. Following the PRISMA guidelines, 2232 records were retrieved, and 283 reviews were ultimately included. Information was extracted from the papers and categorized by topics. Quantitative data were extracted from meta-analyses and, when not available, evidence was collected from systematic reviews. Overall, 187 reviews were non-systematic, while 96 were systematic, of which 27 performed a meta-analysis. The majority evaluated mortality, morbidity, or vulnerability, while the other topics were scarcely addressed. The following main knowledge gaps were identified: lack of a universally accepted definition of HW; scarce evidence on the HW-mental health relationship; no meta-analyses assessing the risk perception of HWs; scarcity of studies evaluating the efficacy of adaptation strategies and interventions. Future efforts should meet these priorities to provide high-quality evidence to stakeholders. Full article