Effects of extreme climate events and child mortality on total fertility rate in Bangladesh.

Floods, storms, and temperature extremes are examples of extreme weather events that have a substantial influence on a country's demographic dynamics, including migration, fertility, and mortality. Changes in population size, composition, and distribution may result from these occurrences. This study, which spans the years 1966-2018, looks at how Bangladesh's total fertility rate (TFR) is affected by extreme weather events and child mortality, including neonatal, infant, male infant, and under-five mortality. We use data from secondary publicly accessible sources, such as the World Bank and The Emergency Events Database (EM-DAT), and we investigate the correlations using the autoregressive integrated moving average model (ARIMA), complemented by bivariate and multivariable analyses. Our findings from the univariate analysis are noteworthy. Total extreme climate events (ß = -0.345, 95 % CI: 0.510, -0.180), as well as individual extreme climate events, such as extreme temperatures (ß = -1.176, 95 % CI: 1.88, -0.47), floods (ß = -0.644, 95 % CI: 1.0729, -0.216), and storms (ß = -0.351, 95 % CI: 0.63159, -0.07154), exhibited negative associations with the TFR. Additionally, factors such as contraceptive prevalence rate (CPR) (ß = -0.085, 95 % CI: 0.09072, -0.07954) and gross national income (GNI) per capita (ß = -0.003, 95 % CI: 0.0041123, -0.0024234) were negatively correlated with the TFR. Conversely, various categories of child mortality, namely, infants (ß = 0.041, 95 % CI: 0.040474, 0.042748), males (ß = 0.038, 95 % CI:0.037719, 0.039891), and under-five (ß = 0.026, 95 % CI:0.025684, 0.026979) - are positively associated with TFR. Controlling for two pivotal confounding factors, time and GNI per capita, yielded consistent results in the multivariate analysis. These findings provide insight on the dual impact of extreme weather events, which can reduce TFR while also raising it through infant mortality. This phenomena may be due to the increased vulnerability of younger children in climate-event-prone areas, prompting parents to seek additional children as both a replacement for lost offspring and an insurance mechanism against future child loss.

Acclimation temperature influences the thermal sensitivity of injury accumulation in Folsomia candida at extreme low and high temperatures.

The importance of thermal acclimation for the Thermal Death Time (TDT) landscape of the common soil living springtail, Folsomia candida (Collembola, Isotomidae), was investigated. To this aim, we acclimated adult springtails at 10 °C (cold-acclimation) and 20 °C (warm-acclimation), respectively. In static thermal tolerance assays, we found the relationship between survival and exposure time at a number of stressful high and low temperatures. Using logistic modelling, we found, at each exposure temperature, the time until 50% mortality had been reached (Lt50). The exponential functions of TDT curves were found by linear regression of log10 Lt50 values against exposure temperature. Results showed that cold acclimation significantly increased cold tolerance and increased the temperature dependence of cold injury accumulation rate (increased the slope by 4 orders of magnitude) in F. candida. Hence, cold acclimation changed the status of this species from chill-susceptible to moderately chill-tolerant. The cellular injury accumulation at sub-zero temperatures was not related to freezing of body water in this study. Congruently, we found a significant negative effect of cold acclimation on heat tolerance and that cold acclimation decreased the thermal sensitivity of the heat injury accumulation rate. Different slopes of the TDT curves between acclimation groups indicated that acclimation shifted the proportional importance of cellular injury mechanisms or the nature of injury mechanisms. Finally, we compare and combine the TDT curves at extreme high and low temperatures with previously published results on longevity at benign temperatures (from 0 to 30 °C) and describe the full thermal niche of F. candida.

Interaction between Extreme Temperature Events and Fine Particulate Matter on Cardiometabolic Multimorbidity: Evidence from Four National Cohort Studies.

Accumulating evidence linked extreme temperature events (ETEs) and fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM); however, it remained unknown if and how ETEs and PM2.5 interact to trigger CMM occurrence. Merging four Chinese national cohorts with 64,140 free-CMM adults, we provided strong evidence among ETEs, PM2.5 exposure, and CMM occurrence. Performing Cox hazards regression models along with additive interaction analyses, we found that the hazards ratio (HRs) of CMM occurrence associated with heatwave and cold spell were 1.006-1.019 and 1.063-1.091, respectively. Each 10 µg/m3 increment of PM2.5 concentration was associated with 17.9% (95% confidence interval: 13.9-22.0%) increased risk of CMM. Similar adverse effects were also found among PM2.5 constituents of nitrate, organic matter, sulfate, ammonium, and black carbon. We observed a synergetic interaction of heatwave and PM2.5 pollution on CMM occurrence with relative excess risk due to the interaction of 0.999 (0.663-1.334). Our study provides novel evidence that both ETEs and PM2.5 exposure were positively associated with CMM occurrence, and the heatwave interacts synergistically with PM2.5 to trigger CMM.

The impact of intra-annual temperature fluctuations on agricultural temperature extreme events and attribution analysis in mainland China.

Daily temperature variations, which tend to exhibit non-constant and non-linear patterns, are often characterized by intra-annual fluctuations that cause severe and frequent extreme temperature events that have an enormous impact on agricultural production. However, the quantitative relationship between intra-annual temperature fluctuations and extreme agricultural temperatures remains unclear. We aimed to investigate intra-annual temperature fluctuation changes based on daily meteorological data in nine agricultural regions across China from 1960 to 2022 and quantify the impact of temperature fluctuations on extreme agricultural temperatures during crop growth periods. Moreover, an attribution analysis of intra-annual temperature fluctuations was performed using climate indicators. Main results showed: (1) intra-annual temperature fluctuations in each region exhibited a certain decrease, and the spatial distribution showed a significant decreasing trend from north to south. (2) Intra-annual temperature fluctuations have moderately exacerbated extreme agricultural hot and cold events during growth periods, which have brought serious challenges to agriculture owing to advances in phenology and unsynchronized rain heat compared to climate warming. The proportion of positive correlations between temperature fluctuations and extreme temperatures was much larger than that of the negative correlations in nearly all of China (percentage of stations: 20.5 %), and the negative correlation was concentrated only in southern China (percentage of stations: 3.7 %). (3) Hydrothermal coupling and elevation moderately affected intra-annual temperature fluctuations. Average temperature, relative humidity, and elevation had negative correlations with intra-annual temperature fluctuations, the correlation coefficients (R) were - 0.62, -0.42 and - 0.12, respectively; however, reference crop evapotranspiration (ET0) exhibited a positive correlation (R: 0.29), and all reached highly significant levels (P < 0.01). Climate indicators mainly affected intra-annual temperature fluctuations in eastern China. Specifically, the El Niño-Southern Oscillation (ENSO), unstable Asia Polar Vortex, and increased Western Pacific Subtropical High have enhanced temperature fluctuations. The deepened East Asian Trough and Arctic Oscillation of the negative phase weakened the intra-annual temperature fluctuations. This investigation highlights the crucial function of temperature fluctuation in intensifying extreme temperature occurrences and provides a more reasonable scientific foundation for extreme event prediction and agricultural planning.

Time-lag and accumulation responses of vegetation growth to average and extreme precipitation and temperature events in China between 2001 and 2020.

Climate change is often closely related to vegetation dynamics; time lag (Tlag) and accumulative effects (Tacc) are non-negligible phenomena when studying the interaction between climate and vegetation. But, amidst the escalating frequency of extreme climatic events, the quantification of temporal effects (Teffects) of such extremes on vegetation remains scarce. This research quantifies the Tlag and Tacc responses of China's vegetation to episodes of extreme temperature and precipitation since the early 2000s, utilizing daily meteorological data series. Overall, the precipitation in China has become wetter, and nighttime temperatures have risen significantly. The proportion of areas with Teffects ranged from 1.15 % to 15.95 %, and the correlation coefficient between the climate indices and the Normalized Difference Vegetation Index (NDVI) increased by 0.05 to 0.38 when considering the Teffects, compared to not considering it. The Tacc of vegetation had the strongest response (70.74-88.01 %) to extreme events among all the tested climate indices. Moreover, the Tacc of consecutive climate events had a greater impact on vegetation growth than individual climate event. The average Tacc for extreme temperature and extreme precipitation was 1.7-3.09 months and 2.17-3.25 months, respectively. Events like the over 95 % (R95p) and 99 % (R99p) percentile heavy precipitation and the maximum precipitation amount in one day (Rx1day) caused significant Teffects on NDVI. In addition, 90 % of grasslands exhibit Tacc, mainly contributed by the extreme precipitation indices (55.7 %), while the Teffects of forests were stronger than those of extreme temperature. Furthermore, NDVI was more affected by annual precipitation than by extreme precipitation, but the opposite was true for temperature. The results of this study highlight the importance of considering the Tlag and Tacc when predicting the effects of climate change on vegetation dynamics.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China.

Background: With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents. Methods: In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents. Results: The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days. Conclusion: Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

A dataset to measure global climate physical risk.

Extreme climate events have become more frequent and have had serious impacts on the global community. Consequently, the risk associated with climate change has gained increasing attention and has been considered as a new source of risk factors. To understand the socio-economic impacts of this new risk, systematically measuring risk around the world is critical for researchers and policymakers. Building on daily observations from meteorological stations, a Climate Physical Risk Index (CPRI) dataset is constructed for 170 countries, paying special attention to four extreme climate events: extreme low temperature (LTD), extreme high temperature (HTD), extreme rainfall (ERD), and extreme drought (EDD). A comprehensive index of climate physical risk for each country has also been constructed, covering the period from 1993 to 2023. The dataset will be updated regularly. Subnational indices or more detailed regional indices are available upon request.

Bivariate extreme value analysis of extreme temperature and mortality in Canada, 2000-2020.

Climate change increases the risk of illness through rising temperature, severe precipitation and worst air pollution. This paper investigates how monthly excess mortality rate is associated with the increasing frequency and severity of extreme temperature in Canada during 2000-2020. The extreme associations were compared among four age groups across five sub-blocks of Canada based on the datasets of monthly T90 and T10, the two most representative indices of severe weather monitoring measures developed by the actuarial associations in Canada and US. We utilize a combined seasonal Auto-regressive Integrated Moving Average (ARIMA) and bivariate Peaks-Over-Threshold (POT) method to investigate the extreme association via the extreme tail index χ and Pickands dependence function plots. It turns out that it is likely (more than 10%) to occur with excess mortality if there are unusual low temperature with extreme intensity (all χ > 0.1 except Northeast Atlantic (NEA), Northern Plains (NPL) and Northwest Pacific (NWP) for age group 0-44), while extreme frequent high temperature seems not to affect health significantly (all χ ≤ 0.001 except NWP). Particular attention should be paid to NWP and Central Arctic (CAR) since population health therein is highly associated with both extreme frequent high and low temperatures (both χ = 0.3182 for all age groups). The revealed extreme dependence is expected to help stakeholders avoid significant ramifications with targeted health protection strategies from unexpected consequences of extreme weather events. The novel extremal dependence methodology is promisingly applied in further studies of the interplay between extreme meteorological exposures, social-economic factors and health outcomes.

The effects of ambient temperature on road traffic injuries in Jinan city: a time-stratified case-crossover study based on distributed lag nonlinear model.

Objectives: The impact of climate change, especially extreme temperatures, on health outcomes has become a global public health concern. Most previous studies focused on the impact of disease incidence or mortality, whereas much less has been done on road traffic injuries (RTIs). This study aimed to explore the effects of ambient temperature, particularly extreme temperature, on road traffic deaths in Jinan city. Methods: Daily data on road traffic deaths and meteorological factors were collected among all residents in Jinan city during 2011-2020. We used a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the association between daily mean temperature, especially extreme temperature and road traffic deaths, and its variation in different subgroups of transportation mode, adjusting for meteorological confounders. Results: A total of 9,794 road traffic deaths were collected in our study. The results showed that extreme temperatures were associated with increased risks of deaths from road traffic injuries and four main subtypes of transportation mode, including walking, Bicycle, Motorcycle and Motor vehicle (except motorcycles), with obviously lag effects. Meanwhile, the negative effects of extreme high temperatures were significantly higher than those of extreme low temperatures. Under low-temperature exposure, the highest cumulative lag effect of 1.355 (95% CI, 1.054, 1.742) for pedal cyclists when cumulated over lag 0 to 6 day, and those for pedestrians, motorcycles and motor vehicle occupants all persisted until 14 days, with ORs of 1.227 (95% CI, 1.102, 1.367), 1.453 (95% CI, 1.214, 1.740) and 1.202 (95% CI, 1.005, 1.438), respectively. Under high-temperature exposure, the highest cumulative lag effect of 3.106 (95% CI, 1.646, 5.861) for motorcycle occupants when cumulated over lag 0 to 12 day, and those for pedestrian, pedal cyclists, and motor vehicle accidents all peaked when persisted until 14 days, with OR values of 1.638 (95% CI, 1.281, 2.094), 2.603 (95% CI, 1.695, 3.997) and 1.603 (95% CI, 1.066, 2.411), respectively. Conclusion: This study provides evidence that ambient temperature is significantly associated with the risk of road traffic injuries accompanied by obvious lag effect, and the associations differ by the mode of transportation. Our findings help to promote a more comprehensive understanding of the relationship between temperature and road traffic injuries, which can be used to establish appropriate public health policies and targeted interventions.

Temporal changes in temperature-related mortality in relation to the establishment of the heat-health alert system in Victoria, Australia.

Extreme heat alerts are the most common form of weather forecasting services used in Australia, yet very limited studies have documented their effectiveness in improving health outcomes. This study aimed to examine the temporal changes in temperature-related mortality in relation to the activation of the heat-health alert and response system (HARS) in the State of Victoria, Australia. We examined the relationship between temperatures and mortality using quasi-Poisson regression and the distributed lag non-linear model (dlnm) and compared the temperature-mortality association between the two periods: period 1- prior-HARS (1992-2009) and period 2- post-HARS (2010-2019). Since the HARS heavily weights heatwave effects, we also compared the main effects of heatwave events between the two periods. The heatwaves were defined for three levels, including 3 consecutive days at 97th, 98th, and 99th percentiles. We also controlled the potential confounding effect of seasonality by including a natural cubic B-spline of the day of the year with equally spaced knots and 8 degrees of freedom per year. The exposure-response curve reveals the temperature mortality was reduced in period 2 in comparison with period 1. The relative risk ratios (RRR) of Period 2 over Period 1 were all less than one and gradually decreased from 0.86 (95% CI, 0.72-1.03) to 0.64 (95% CI, 0.33-1.22), and the differences in attributable risk percent increased from 13.2 to 25.3%. The reduction in the risk of heatwave-related deaths decreased by 3.4% (RRp1 1.068, 95% CI, 1.024-1.112 versus RRp2 1.034, 95% CI, 0.986-1.082) and 10% (RRp1 1.16, 95% CI, 1.10-1.22 versus RRp2 1.06, 95% CI, 1.002-1.119) for all groups of people. The study indicated a decrease in heat-related mortality following the operation of HARS in Victoria under extreme heat and high-intensity heatwaves conditions. Further studies could investigate the extent of changes in mortality among populations of differing socio-economic groups during the operation of the heat-health alert system.

Triboelectric Basalt Textiles Efficiently Operating within an Ultrawide Temperature Range.

With the continuous upsurge in demand for wearable energy, nanogenerators are increasingly required to operate under extreme environmental conditions. Even though they are at the cutting edge of technology, nanogenerators have difficulty producing high-quality electrical output at very extreme temperatures. Here, a triboelectric basalt textile (TBT) with an ultrawide operational temperature range (from -196 to 520 °C) is created employing basalt material as the main body. The output power density of the TBT, in contrast to most conventional nanogenerators, would counterintuitively rise by 2.3 times to 740.6 mW m-2 after heating to 100 °C because the high temperature will enhance the material's interface polarization and electronic kinetic energy. The TBT retains ≈55% of its initial electrical output even after heating in the flame of an alcohol lamp (520 °C). Surprisingly, the TBTs output voltage may retain over 85% of its initial value even after submerging in liquid nitrogen. The TBTs exceptional resistance to heat and cold indicates its possible use in high and low latitudes, high altitudes, deserts, and even space settings.

Impacts of winter warming events on spruce budworm: the importance of timing.

Winter climate change constitutes not only a shift in chronic conditions (i.e., shorter length and warmer average temperatures) but will also influence the dynamics of extreme warming events. The latter may be particularly important for the performance and survival of insects, given their susceptibility to temperature variation. However, metabolic sensitivity changes over the course of winter diapause, and thus, insect responses to warming may vary depending on when the event occurs. To determine the influence of warm-up timing, we exposed the spruce budworm, Choristoneura fumiferana ((Clem.), Lepidoptera: Tortricidae), to acute warming events in early-, mid-, and late-dormancy and measured impacts on survival, performance, and biochemistry. While we did not observe any impacts of warm-up timing on performance, survival to the adult stage was significantly reduced in response to earlier warming. Additionally, glycogen concentration was significantly higher in response to early and late warming exposure. Collectively, these results suggest that the timing of extreme winter warming events matters, with consequences for both lethal and sublethal responses.

Assessment of historical and projected changes in extreme temperatures of Balochistan, Pakistan using extreme value theory.

The fundamental consequences of global warming include an upsurge in the intensity and frequency of temperature extremes. This study provides an insight into historical trends and projected changes in extreme temperatures on annual and seasonal scales across "Balochistan, Pakistan". Historical trends are analyzed through the Mann Kendal test, and extreme temperatures (Tmax and Tmin) are evaluated using generalized extreme value (GEV) distribution for historical period (1991-2020) from the observational data and the two projected periods as near-future (2041-2070) and far-future (2071-2100) using a six-member bias-corrected ensemble of regional climate models (RCMs) projections from the coordinate regional downscaling experiment (CORDEX) based on the worst emission scenario (RCP8.5). The evaluation of historical temperature trends suggests that Tmax generally increase on yearly scale and give mixed signals on seasonal scale (winter, spring, summer, and autumn); however, Tmin trends gave mixed signals at both yearly and seasonal scale. Compared to the historical period, the return levels are generally expected to be higher for Tmax and Tmin during the both projection periods in the order as far-future > near-future > historical on yearly and seasonal basis; however, the changes in Tmin are more evident. Station-averaged anomalies of + 1.9 °C and + 3.6 °C were estimated in 100-year return levels for yearly Tmax for near-future and far-future, respectively, while the anomalies in Tmin were found to be + 3.5 °C and + 4.8 °C which suggest the intensified heatwaves but milder colder extreme in future. The findings provide guidance on improved quantification of changing frequencies and severity in temperature extremes and the associated impacts.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study.

BACKGROUND: Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China. METHODS: A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects. RESULTS: Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26 °C (97.5th) and 27 °C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26 °C (1st) and - 23 °C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures. CONCLUSIONS: Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

Long-term effect of extreme temperature on cognitive function of middle-aged and older adults in China.

BACKGROUND: Several studies have explored the association between temperature and cognitive function. However, few studies have examined the effect of extreme temperature on cognitive function. In this study, we aimed to quantify the long-term effect of extreme temperature (e.g., heat waves, cold spells, and hot night excess (HNE)) on cognitive performance in middle-aged and older people in China. METHOD: We investigated 7915 aged >45 years people from the China Health and Retirement Longitudinal Study (CHARLS), surveyed in 2011 and 2015. A structured questionnaire was utilized to assess cognitive function, including four dimensions: episodic memory, attention, orientation, and visuo-construction. Hourly ambient temperature from the ERA5-Land datasets were used to calculate variables indicating extreme temperature. We performed difference-in-difference (DID) models to assess the potential causal relationship between extreme temperature and cognitive function. RESULTS: Non-linear analyses suggested that both sustained increases in temperature and excessive variability in temperature increased the risk of cognitive decline. Meanwhile, we observed the extra risk of global cognitive function decline was 2.3% (95% Confidence interval (95% CI): 0.2%, 4.4%) for heat waves (one unit increase) and 5.9% (95% CI: 0.6%, 11.6%) for HNE (one unit increase), while the association for cold spells was insignificant. Two cognitive dimensions, episodic memory and visuo-construction, were sensitive to these two heat-related factors. CONCLUSION: Extreme temperature was inversely related to cognitive performance in middle-aged and older adults, which was substantial for heat waves and HNE particularly. The effect size varied by cognitive dimensions.

Alpine grassland greening on the Northern Tibetan Plateau driven by climate change and human activities considering extreme temperature and soil moisture.

Alpine grassland is among the world's most vulnerable ecosystems, characterized by a high sensitivity to climate change (CC) and human activities (HA). Quantifying the relative contributions of CC and HA to grassland change plays a crucial role in safeguarding grassland ecological security and devising sustainable grassland management strategies. Although there were adequate studies focusing on the separate impacts of CC and HA on alpine ecosystem, insufficient attention has been given to investigating the effects of extreme temperatures and soil moisture. In this study, the spatiotemporal variations of alpine grassland were analyzed based on MODIS NDVI during the growing season from 2000 to 2020 in Naqu, using partial least squares regression and residual analysis methods to analyze the importance of climate factors and the impacts of CC and HA on grassland change. The results show that the NDVI during the growing season in Naqu exhibited an increasing trend of 0.0046/10a. At the biome scale, the most significant and rapid increase was observed in alpine desert and alpine desert grassland. Extreme temperature and soil moisture (SM) exerted a more significant importance on alpine grassland at whole scale. SM always showed a significant importance at biome and grid scale. The contributions of CC and HA to the change during the growing season were calculated as 0.0032/10a and 0.0015/10a, respectively, accounting for 68.05 % and 31.05 %. CC dominated the increase in NDVI during the growing season; HA contributed positively to NDVI in most areas of Naqu. The results are expected to enhance our understanding of grassland variations under CC and HA and provide a scientific basis for future ecological conservation in alpine regions.

Extreme temperature events and dementia mortality in Chinese adults: a population-based, case-crossover study.

BACKGROUND: The effect of exposure to extreme temperature events (ETEs) on dementia mortality remains largely unknown. We aimed to quantify the association of ETE exposure with dementia mortality. METHODS: We conducted a population-based, case-crossover study among 57 791 dementia deaths in Jiangsu province, China, during 2015-20. Daily mean temperatures were extracted from a validated grid dataset at each subject's residential address, and grid-specific exposures to heat wave and cold spell were assessed with a combination of their intensity and duration. We applied conditional logistic regression models to investigate cumulative and lag effects for ETE exposures. RESULTS: Exposure to ETE with each of all 24 definitions was associated with an increased odds of dementia mortality, which was higher when exposed to heat wave. Exposure to heat wave (daily mean temperature ≥95th percentile, duration ≥3 days (d); P95_3d) and cold spell (≤5th percentile, duration ≥3 d; P5_3d) was associated with a 75% (95% CI: 61%, 90%) and 30% (19%, 43%) increase in odds of dementia mortality, respectively. Definitions with higher intensity were generally associated with a higher odds of dementia mortality. We estimated that 6.14% of dementia deaths were attributable to exposure to heat wave (P90_2d) and cold spell (P10_2d). No effect modifications were observed by sex or age, except that the association for heat wave was stronger among women. CONCLUSIONS: Exposure to both heat wave and cold spell was associated with an increased odds of dementia mortality. Our findings highlight that reducing individual ETE exposures may be helpful in preventing deaths from dementia, especially among women in summer.

One hundred and six years of change in a Sonoran Desert plant community: Impact of climate anomalies and trends in species sensitivities.

A major restriction in predicting plant community response to future climate change is a lack of long-term data needed to properly assess species and community response to climate and identify a baseline to detect climate anomalies. Here, we use a 106-year dataset on a Sonoran Desert plant community to test the role of extreme temperature and precipitation anomalies on community dynamics at the decadal scale and over time. Additionally, we tested the climate sensitivity of 39 desert plant species and whether sensitivity was associated with growth form, longevity, geographic range, or local dominance. We found that desert plant communities had shifted directionally over the 106 years, but the climate had little influence on this directional change primarily due to nonlinear shifts in precipitation anomalies. Decadal-scale climate had the largest impact on species richness, species relative density, and total plant cover, explaining up to 26%, 45%, and 55% of the variance in each, respectively. Drought and the interaction between the frequency of freeze events and above-average summer precipitation were among the most influential climate factors. Increased drought frequency and wetter periods with frequent freeze events led to larger reductions in total plant cover, species richness, and the relative densities of dominant subshrubs Ambrosia deltoidea and Encelia farinosa. More than 80% of the tested species were sensitive to climate, but sensitivity was not associated with a species' local dominance, longevity, geographic range, or growth form. Some species appear to exhibit demographic buffering, where when they have a higher sensitivity to drought, they also tend to have a higher sensitivity to favorable (i.e., wetter and hotter) conditions. Overall, our results suggest that, while decadal-scale climate variation substantially impacts these desert plant communities, directional change in temperature over the last century has had little impact due to the relative importance of precipitation and drought. With projections of increased drought in this region, we may see reductions in total vegetation cover and species richness due to the loss of species, possibly through a breakdown in their ability to demographically buffer climatic variation, potentially changing community dynamics through a change in facilitative and competitive processes.

Direct Synthesis of Polyimide Curly Nanofibrous Aerogels for High-Performance Thermal Insulation Under Extreme Temperature.

Maintaining human body temperature is one of the basic needs for living, which requires high-performance thermal insulation materials to prevent heat exchange with external environment. However, the most widely used fibrous thermal insulation materials always suffer from the heavy weight, weak mechanical property, and moderate capacity to suppress heat transfer, resulting in limited personal cold and thermal protection performance. Here, an ultralight, mechanically robust, and thermally insulating polyimide (PI) aerogel is directly synthesized via constructing 3D interlocked curly nanofibrous networks during electrospinning. Controlling the solution/water molecule interaction enables the rapid phase inversion of charged jets, while the multiple jets are ejected by regulating charge density of the fluids, thus synergistically allowing numerous curly nanofibers to interlock and cross-link with each other to form porous aerogel structure. The resulted PI aerogel integrates the ultralight property with density of 2.4 mg cm-3, extreme temperature tolerance (mechanical robustness over -196 to 300 °C), and thermal insulation performance with ultralow thermal conductivity of 22.4 mW m-1 K-1, providing an ideal candidate to keep human thermal comfort under extreme temperature. This work can provide a source of inspiration for the design and development of nanofibrous aerogels for various applications.

Heatwave Definition and Impact on Cardiovascular Health: A Systematic Review.

Objectives: We aimed to analyze recent literature on heat effects on cardiovascular morbidity and mortality, focusing on the adopted heat definitions and their eventual impact on the results of the analysis. Methods: The search was performed on PubMed, ScienceDirect, and Scopus databases: 54 articles, published between January 2018 and September 2022, were selected as relevant. Results: In total, 21 different combinations of criteria were found for defining heat, 12 of which were based on air temperature, while the others combined it with other meteorological factors. By a simulation study, we showed how such complex indices could result in different values at reference conditions depending on temperature. Heat thresholds, mostly set using percentile or absolute values of the index, were applied to compare the risk of a cardiovascular health event in heat days with the respective risk in non-heat days. The larger threshold's deviation from the mean annual temperature, as well as higher temperature thresholds within the same study location, led to stronger negative effects. Conclusion: To better analyze trends in the characteristics of heatwaves, and their impact on cardiovascular health, an international harmonization effort to define a common standard is recommendable.