Mean Daily Temperature Research Articles

Impact of Ambient Temperature on Mortality Burden and Spatial Heterogeneity in 16 Prefecture-Level Cities of a Low-Latitude Plateau Area in Yunnan Province: Time-Series Study.

The relation between climate change and human health has become one of the major worldwide public health issues. However, the evidence for low-latitude plateau regions is limited, where the climate is unique and diverse with a complex geography and topography. This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions. We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors. The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0-21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14-615.18) and 247.83 (95% eCI 45.73-418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%-10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70-7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58-4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70-14.02) for heart disease, 11.12% (95% eCI 2.52-16.82) for respiratory disease, 10.85% (95% eCI 6.70-14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03-13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics. This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention.

Mortality risk and burden of aortic aneurysm and dissection attributable to low temperatures: A nationwide case-crossover analysis in Brazil, a predominantly tropical country

BackgroundLow temperatures are adverse contributors to cardiovascular diseases, but the associations between short-term exposure to cold and the risk of death from aortic dissection and aneurysm remain unclear, particularly in tropical regions. ObjectiveThis study was conducted based on 123,951 records of deaths caused by aortic dissection and aneurysms extracted from the national Mortality Information System in Brazil between 2000 and 2019. MethodsRelative risks and 95 % confidence intervals (CI) for the aortic-related deaths associated with low ambient temperatures were estimated using the conditional logistic model combined with the distributed lag nonlinear model. Subgroup analyses were performed by age group, sex, race, education level, and residential region. Furthermore, this study calculated the number and fraction of aortic-related deaths attributed to temperatures below the temperature threshold to quantify the cold-related mortality burden of aortic diseases. ResultsDuring the study period, aortic-related deaths and mortality rates in Brazil exhibited a steady increase, rising from 4419 (2.66/100,000) in 2000 to 8152 (3.88/100,000) in 2019. Under the identified temperature threshold (26 °C), per 1 °C decrease in daily mean temperature was associated with a 4.77 % (95 % CI: 4.35, 5.19) increase in mortality risk of aortic-related diseases over lag 0–3 days. Females, individuals aged 50 years or older, Asian and Black race, and northern residents were more susceptible to low temperatures. Low temperatures were responsible for 19.10 % (95 % CI: 17.71, 20.45) of aortic-related deaths in Brazil. ConclusionThis study highlights that low temperatures were associated with an increased risk of aortic-related deaths, with a remarkable burden even in this predominantly tropical country.

The impacts of global warming on climate zones over China based on CMIP6 models

AbstractClimate zones are expected to shift in response to climate change, which significantly influences vegetation distribution and provides essential guidance for human activities including production, lifestyle and economic development. Quantifying the shifts in climate zones due to global warming is therefore crucial. The primary metric for categorizing climate zones is the number of days with a daily mean temperature above 10°C (DT10). Utilizing DT10 and the ERA5 reanalysis data, it is observed that climate zones in China have gradually shifted northward over the past 65 years. Notably, the interdecadal changes in the climate zones differ between the eastern and western regions divided by the 110°E longitude. The western regions show minimal shifts, whereas the eastern regions, particularly the central and southern parts of Northeast China, exhibit obvious northward shifts. Consequently, the simulation capabilities of 41 CMIP6 models for Chinese climate zones were assessed, and it was found that 11 models demonstrated robust performance. These models were further used to analyse interdecadal variations and project future shifts in climate zones in China. The results show that the spatial pattern of climate zones in China can be well captured by the CMIP6 models, except for ACCESS‐CM2, FGOALS‐g3 and GFDL‐CM4. Each CMIP6 model seems to be more suitable for specific climatic zones concerning trends and decadal variations in China. By 2100, a northward shift is projected for all climate zones in the east of 110°E under SSP2‐4.5 and SSP5‐8.5 emission scenarios, particularly in northern China. It should be noted that the potential disappearance of the northern subtropical belt, likely to be replaced by the middle subtropical belt in the future.

Determination of occurrence of atmospheric blockings over the Caspian Sea region in winters of 1959–2022, and influence of them on the ice regime of the Northern Caspian Sea

The ice regime of the Caspian Sea has pronounced influence on the heat and moisture exchange of the reservoir with the atmosphere, the state of the ecosystem, as well as human marine activities, including shipping, fishing, construction of hydraulic structures, etc. Consequently, the development of existing ideas about the causes of changes in the characteristics of the ice regime of such water bodies is actual and socially significant problem of limnology, hydrometeorology, ecology, and navigation. This study was aimed at determination the frequency of occurrence of atmospheric blockings over the Caspian region with standings longer 5 days in winter period of 1959–2022, and investigation of influence of them on the ice regime in the Northern area of the Sea. The following information and data were used: changes in hourly mean values of atmospheric pressure at the sea level, geopotential of isobaric surfaces 850, 500 and 300 hPa, presented in the ERA5 reanalysis; and observational data on air temperature and ice cover from hydrometeorological stations located in the Caspian region of Kazakhstan and Russia. It has been established that in the winter during a long standing of atmospheric blockings the mean daily air temperatures noticeably drop. The values of all the studied characteristics of every atmospheric blocking which occurred in 1959–2022 were estimated as well the influence of them on the ice regime in the North of the Caspian Sea was analyzed. The relationship between a decrease in the frequency of atmospheric blockings (AB), sums of negative air temperatures on its coasts, and the ice cover thickness in the corresponding areas of coastal waters has been revealed in the region. The longer the total AB duration, the lower is the air temperature, and the ice thickness in February is larger.

Numerical modeling of microclimate of re-waterlogged lands of Belarusian Polesie

Based on the mesoscale hydrodynamic model WRF (Weather Research and Forecasting), the balance model of atmospheric moisture and the remote sensing data, we obtained the estimates of microclimate changes as a result of reswamping of lands in Belarusian Polesie. The calculations were performed on the example of the Khoiniki district of the Gomel region of Belarus. Numerical experiments considered the driest summer periods of the last two decades. Based on the modeling results, the maps of changes in mean daily temperature, amplitude of daily temperature variations, evapotranspiration and precipitation were constructed, which can be used to predict the consequences of land reclamation in different scenarios of adaptation to climate changes.

Risk Factors and Effects of Climate Lag on Vibrio Parahaemolyticus Infection in Eastern Coastal Cities of China: A Study Based on Hangzhou City.

Bacterial foodborne diseases caused by Vibrio parahaemolyticus pose persistent challenges to coastal cities in China. In this study, we employed multiple logistic regression analysis and distributed lag non-linear models (DLNM) to investigate the epidemiological characteristics and associated risk factors of vibriosis in the metropolitan area of Hangzhou from 2014 to 2018. Analysis of foodborne cases indicated that certain demographics and occupational factors, including age between 16 and 44 years; houseworkers or unemployed individuals; preference for aquatic and meat products; and dining in collective canteens or catering services contribute to an increased likelihood of V. parahaemolyticus infection. Moreover, a higher per capita GDP and exposure to high temperatures were identified as risk factors for vibriosis. This study highlights the significance of the daily mean temperature as a meteorological factor influencing V. parahaemolyticus infection, with varying lag effects observed depending on temperature conditions. At low temperatures, the risk of infection occurs after a lag of 21 days, whereas at high temperatures, the risk is highest on the same day, while the second infection risk period occurs after a lag of 21 days. These findings provide a spatiotemporal perspective of the risk analysis of foodborne diseases, with a daily timescale and street spatial scale, which contributes to the development of public health strategies and food safety protocols in coastal cities.

Association between heat and upper urinary tract stones morbidity and medical costs: A study in the subtropical humid climate zone

Urolithiasis is a heat-specific disease. Exploring heat-related urolithiasis susceptibility subtypes, economic burden, and modifying factors could assist governments in targeting interventions to reduce the heat-related health risks of urolithiasis morbidity. We collected data on 23,492 patients with upper urinary tract stones (main subtypes of urolithiasis) from 2013 to 2017 in Nanjing, China. We adopted generalized additive quasi-Poisson models to examine the associations between daily mean temperatures and morbidity of upper urinary tract stones, while generalized additive Gaussian models were used to explore the relationships between temperatures and log-transformed medical costs. We examined the modification effects of disease subtypes (kidney and ureteral calculus), sex, and age through stratified analyses and the modification effects of other meteorological factors by introducing interaction terms in the models. We found that short-term summer heat exposure has a statistically significant effect on ureteral calculus morbidity but not on kidney calculus morbidity. For ureter calculus, a 1 °C temperature increase was associated with a 4.36% (95% confidence interval [CI]: 1.94%, 6.83%) increase in daily hospitalization and a 5.44% (95% CI: 2.71%, 8.25%) increase in daily medical costs. The attributable fraction associated with heat (greater than the median value of daily mean temperature, 26.8 °C) was 7.85% (95% empirical confidence interval [eCI]: 3.64%, 11.44%) for hospitalization and 9.36% (95% eCI: 4.91%, 13.14%) for medical costs. The effects of heat on ureter calculus morbidity were significantly higher among the males and those with high sunshine duration than females and those with low sunshine duration. Short-term summer heat exposure was associated with increased morbidity and medical costs of ureteral calculus. Relevant government organizations should take effective intervention measures, including community health education, to reduce the health hazards and economic losses caused by heat.

The effect of ambient temperatures on hospital admissions for kidney diseases in Central Australia

This study aimed to quantify risk of hospitalisations for kidney diseases related to ambient temperature in Central Australia, Northern Territory (NT).Daily hospitalisation data were extracted for Alice Springs Hospital, Central Australia, 2010–2021. The association between daily mean temperature and daily hospital admissions for total kidney and specific kidney conditions was assessed using a quasi-Poisson Generalized Linear Model combined with a distributed lag non-linear model.A total of 52,057 hospitalisations associated with kidney diseases were recorded. In general, risk of specific kidney related hospitalisations was immediate due to hot temperatures and prolonged due to cold temperatures. Relative to the minimum-risk temperature (5.1 °C), at 31 °C, cumulative relative risk (RR) of hospitalisations for total kidney disease (TKD) was 1.297 [95% CI 1.164,1.446] over lag0-1 days, for chronic kidney disease (CKD) cumulative RR was 1.269 [95% CI 1.115,1.444] and for kidney failure (KF) cumulative RR was 1.252 [95% CI 1.107,1.416] at lag 0, and for urinary tract infection (UTI) cumulative RR was 1.522 [95% CI 1.072,2.162] over lag0-7 days. At 16 °C and over lag0-7 days, cumulative RR of hospitalisations for TKD was 1.320 [95% CI 1.135,1.535], for CKD was 1.232 [95% CI 1.025,1.482], for RF was 1.233 [95% CI 1.035,1.470] and for UTI was 1.597 [95% CI 1.143, 2.231]. Both cold and hot temperatures were also associated with increased risks of kidney related total hospitalisations among First Nations Australians and women. Overall, temperature attributable to 13.7% (i.e. 7138 cases) of kidney related hospitalisations with higher attributable hospitalisations from cold temperature.Given the significant burden of kidney disease and projected increases in extreme temperatures associated with climate change in NT including Central Australia there is a need to implement public health and environmental health risk reduction strategies and awareness programs to mitigate potential adverse health effects of extreme temperatures.

Short-term effects of fine particulate matter from biomass combustion and Saharan dust intrusions on emergency hospital admissions due to mental and behavioural disorders, anxiety and depression in Spain

Climate change is affecting both the frequency and scale of wildfires, as well as the increase in the number of days with Saharan dust intrusions. Traditionally, studies have focused on the extent to which the increase in fine particulate matter (PM) has had an impact on cardio-respiratory diseases, but (apart from PM) not on how the meteorological and pollution conditions in these situations affect other diseases, such as those linked to mental health.This study therefore sought to ascertain how daily mean PM10, PM 2.5, NO2, O3 concentrations and daily maximum temperature in heat waves influence daily emergency hospital admissions in Spain caused by mental and behavioural disorders, depression and anxiety on days with PM from biomass combustion and/or Saharan dust intrusions, as compared to days without such conditions, across the period 2009–2018.Our results indicate that on days on which there is biomass combustion, PM concentrations have a statistically significant effect on emergency admissions due to mental disorders, probably related with the toxicity of these particles. Yet on days with intrusions of Saharan dust rather than PM, it is the other variables considered in the analysis that are most closely linked to these types of admissions. The results of this study thus point to the need to implement public health prevention plans which take into account the joint effect of various environmental risk factors that act synergistically in given situations.

How does extreme heat affect carbon emission intensity? Evidence from county-level data in China

This study investigates the impact of increasingly frequent extreme heat events due to climate change on carbon emission intensities in China. Using spline regressions on county-level data from 2000 to 2019, we identify an asymmetric U-shaped relationship between daily mean temperatures and carbon intensities. Each additional day with temperatures above 33 °C in each location results in a 0.9% rise in the average annual carbon intensity, driven by higher energy consumption for cooling. We also explore the mitigating effects of China's low-carbon city initiatives and emissions trading scheme. By combining our estimation results with future temperature trajectories, we simulate that, in the long run, China's carbon intensity can increase by 8–13% under the SSP1-2.6 scenario and 24–51% under the SSP5-8.5 scenario. Our findings underscore the urgency for policymakers to thoroughly assess the socioeconomic impacts of heat waves and incorporate climate resilience into overall sustainable development plans.

Greening of Svalbard

Svalbard, located between 76°30′N and 80°50′N, is among the regions in the world with the most rapid temperature increase. We processed a cloud-free time-series of MODIS-NDVI for Svalbard. The dataset is interpolated to daily data during the 2000–2022 period with 232 m pixel resolution. The onset of growth, with a clear phenological definition, has been mapped each year. Then the integrated NDVI from the onset (O) of growth each year to the time of average (2000–2022) peak (P) of growth (OP NDVI) have been calculated. OP NDVI has previously shown high correlation with field-based tundra productivity. Daily mean temperature data from 11 meteorological stations are compared with the NDVI data. The OP NDVI values show very high and significant correlation with growing degree days computed from onset to time of peak of growth for all the meteorological stations used. On average for the entire Svalbard, the year 2016 first had the highest greening (OP NDVI values) recorded since the year 2000, then the greening in 2018 surpassed 2016, then 2020 surpassed 2018, and finally 2022 was the year with the overall highest greening by far for the whole 2000–2022 period. This shows a rapid recent greening of Svalbard very strongly linked to temperature increase, although there are regional differences: the eastern parts of Svalbard show the largest variability between years, most likely due to variability in the timing of sea-ice break-up in adjacent areas. Finally, we find that areas dominated by manured moss-tundra in the polar desert zone require new methodologies, as moss does not share the seasonal NDVI dynamics of tundra communities.

Ambient temperature and cardiovascular disease-related emergency room visits in Lanzhou, China from 2013 to 2019: A time-series study.

This study assessed the links between daily mean temperature and emergency room (ER) admissions for total and cause-specific cardiovascular diseases (CVD) in Lanzhou, China from 2013 to 2019. A quasi-Poisson Generalized Additive Model (GAM) and a Distributed Lag Non-Linear Model (DLNM) were used to determine the effects of temperature on total and cause-specific cardiovascular emergency visits. The relative risks (RR) at cold (hot) temperatures were calculated by comparing the 5th (95th) centile of temperature with the minimum morbidity temperature (MMT). Exposure-response curves demonstrating an inverted U-shape or an irregular M-shape association were observed between temperature and total and cause-specific CVD. The study found that both cold and hot temperatures had negative impacts on emergency room visits for various cardiovascular diseases. For people with total CVD, heart rhythm disturbances (HRD), or cerebrovascular diseases (CD), females were more sensitive to temperature than males, while for ischemic heart disease (IHD) and heart failure (HF), males were more vulnerable to temperature. The < 65 years old with total CVD, IHD, HRD, or CD was more susceptible to the effects of temperature. The results indicated that the relationship between temperature and total and cause-specific CVD was nonlinear, and susceptibility to temperature varied across disease subtype, gender, and age.

Implications of Ecological Drivers on Roan Antelope Populations in Mokala National Park, South Africa

Climate change has massive global impacts and affects a wide range of species. Threatened species such as the roan antelope (Hippotragus equinus) are particularly vulnerable to these changes because of their ecological requirements. Attempts to address concerns about the roan’s vulnerability have not been well documented in South African protected areas. This study identifies the landscape use and distribution of the roan as well as habitat and forage suitability changes to help inform management decisions for the conservation of roan. We used fine- and broad-scale data from Mokala National Park, South Africa that includes roan occurrence data, vegetation condition indices, vegetation (structure and plant species composition), elevation and temperature differences, and precipitation strata to construct a suitability framework using the Maximum Entropy (Maxent) and Random Forest statistical package. In Mokala National Park, roan occurred in the Schmidtia pappophoroides–Vachellia erioloba sparse woodland, Senegalia mellifera–Vachellia erioloba closed woodland, Senegalia mellifera–Vachellia tortilis open shrubland, Vachellia erioloba–V. tortilis closed woodland and Rhigozum obovatum–Senegalia mellifera open shrubland. The veld (vegetation) condition index (VCI) improved from 2019 (VCI &lt; 50%) to 2021 (VCI &gt; 60%), with the proportion of palatable grass species (Schmidtia pappophoroides and Eragrostis lehmanniana) also increasing. This study identified four key climatic conditions affecting roan distribution, namely annual mean daily temperature range, temperature seasonality, minimum temperatures of the coldest month, and precipitation of the wettest month. These results suggest that the conservation of roan antelope should consider these key variables that affect their survival in preferred habitats and foraging areas in anticipation of changing ecological conditions.

A hűtési és fűtési időszakot jellemző éghajlati klímaindexek változása Magyarországon

Összefoglalás. Az elmúlt évtizedekben a globális felmelegedés hatásai Európában, azon belül a Kárpát-medencében is nyilvánvalóvá váltak, s ez a hatás jelentős mértékű az energiaszektorra is. A kizárólag az időjárás által befolyásolt függő fűtési és hűtési energiaigényt leíró technikai klímaindexek alakulását mutatjuk be Magyarországon, nevezetesen a fűtési foknap (Heating Degree Days) és a hűtési foknap (Cooling Degree Days) paramétereket vizsgáljuk. A jelen klímát leginkább jellemző éves és havi normálértékek mellett a változásokat is elemezzük. A múlt század elejétől a fűtési foknapok egyértelmű csökkenése, míg a hűtési foknapok egyértelmű emelkedése figyelhető meg. Országos átlagban 314,6 foknappal [°C nap] csökkent a fűtési foknapok éves összege a lineáris trendmodell szerint 1901-től, míg ugyanerre az időszakra 79,4 ℃ nappal nőtt a hűtési foknap értéke. A legutóbbi három évtizedben, a legintenzívebb melegedés időszakában igen markánsak a változások, s ez a folyamat minden bizonnyal folytatódik a század végéig és azon túl is. Summary. In recent decades, the effects of global warming have become evident in Europe, including the Carpathian Basin, and this impact is significant for the energy sector. The most obvious impact of climate change in Hungary is the increase in extremes associated with high temperatures. Not only summer, but also winter and transition seasons show a warming trend, affecting all productive and service sectors. Rising temperatures could lead to shorter heating seasons and milder cold months, potentially reducing heating energy demand. However the heat waves have become more frequent and intense due to warming, leading to an increase in cooling energy demand. In the first part of this article, we present the evolution of heating degree-days from the beginning of the last century to the present day for the whole area of Hungary. The heating degree day is an indicator of the energy consumption for heating of buildings, which depends only on the weather. That is a temperature value, expressed in °Cday, which is proportional to the amount of energy required to heat the indoor environment to a given temperature on a given day, taking into account the daily minimum, maximum and mean temperature for a specific base temperature (15.5°Cday). Importantly, its value does not depend on the insulation of the buildings, economic indicators or the type of energy sources. Essentially, the colder the weather, the more the air temperature deviates from the base temperature of 15.5 degrees Celsius, the more energy is needed to heat the indoor environment and the higher the heating degree day value will be. In addition, we present the analysis of cooling degree days. The cooling degree day is derived in a similar way, following the logic of the heating degree day derivation. Therefore, the warmer the weather and the higher the air temperature is above the base temperature of 22°C, the more energy is needed to cool the indoor environment. Based on the results presented in the article, we can conclude that the annual as well as the monthly amounts of heating degree-days have decreased since the beginning of the last century, with the greatest decrease in mountainous areas and in Western Hungary. One of the few benefits of climate change is that less energy is needed to heat interiors, and this is particularly true for the last decades, when annual heating degree-day amounts were usually lower than normal. At the same time, as heating degree-days have decreased, as the heat waves have become more frequent and intense with warming, resulting in an increase in cooling degree-days. In Hungary, on average, the last 30 years have been characterised by the highest cooling degree-day values over the last century’s climate normal periods. On a national average, the annual amount of heating degree-days has decreased by 314.6°Cday according to the linear trend model since 1901, while the cooling degree-day value has increased by 79.4°Cday over the same period. During the period of most intense warming, the August weather-dependent cooling energy demand increased the most. Due to the urban heat island effect in the inner-city environment, cooling of buildings requires additional energy. The recent trends is likely to continue until the end of the century and beyond. Therefore important to monitor changes in climate parameters affecting energy security and to develop an effective strategy and action plans to address the climate risks for the energy sector.

“Observations stopped on the occasion of the cession of Alaska”: St. Petersburg academy of sciences’ magnetic and meteorological observatory in sitka (Alaska)

Based on the new archival materials from the Russian State Archive of the Navy, Russian State Historical Archive, and St. Petersburg Branch of the Russian Academy of Sciences Archive, the history of the organization and operations of the St. Petersburg Academy of Sciences’ Magnetic and Meteorological Observatory in Alaska (the city of Sitka / Sitkha) was analyzed for the first time. This Observatory operated from 1839 until the sale of Alaska in 1867. The themes from the history of the Observatory reviewed in the article are the background for its creation, the participation of the international scientific community (Royal Society of London) in its founding, and the contribution of the Russian-American Company and its leaders, primarily Arvid Adolf Etholén, to its construction and operations. The archival data relating to the observations conducted at the Observatory (mean daily temperature) are provided for the first time. The fact that the Observatory, being officially subordinate to the Mining Department of the Ministry of Finance, was scientifically managed by the Academy of Sciences, helps to better understand the specifics of interagency links and communication in the Russian Empire in the 19ʰᵗ century. The article also sheds light on the personal contribution of Director of the Central Physical Observatory, A. Ya. (Adolph-Theodor) Kupffer, to the formation of the Observatory in Sitka, briefly reviews the instruments and devices employed by the Observatory, and, for the first time, provides the names of its directors and other staff.

Urban-rural disparities in the short-term effects of cold and heat on myocardial infarction mortality in Anhui Province, China.

Non-optimal ambient temperatures are risk factors for myocardial infarction (MI) and urban-rural temperature differences in the context of climate change may have caused and will lead to differential association between temperature and MI. We collected daily mean temperature and daily MI deaths from 1 January 2016 to 31 December 2020 in Anhui Province, China. A distributed lag nonlinear model was performed to estimate the area-specific association of heat and cold (defined as the 2.5th and 97.5th percentile of the daily mean temperature) with MI mortality; the random-effects meta-analysis was then used to pool the effects of cold and heat. We found the risk of MI death due to cold was higher in rural areas [relative risk (RR): 1.13, 95% confidence interval (CI): 1.02-1.26, lag0) than in urban areas (RR: 0.99, 95% CI: 0.80-1.21, lag0), whereas the risk of MI death associated with heat was higher in urban areas (RR: 1.14, 95% CI: 1.03-1.27, lag0) than in rural areas (RR: 1.04, 95% CI: 0.99-1.10, lag0). Our findings may help to develop targeted protective strategies to reduce the adverse effects of cold and heat on cardiovascular disease.

Heat Metrics and Maternal-Child Health Diagnoses in Emergency Departments in the United States: A Scoping Review.

To summarize current research on associations between heat metrics and emergency department discharge diagnoses for US pregnant women and children from birth to age 18 via a scoping review. Climate change directly contributes to extreme weather conditions and environmental changes and indirectly affects health and the health care system. Pregnant women and children are believed to be more susceptible to extreme heat, but few empirical studies have been conducted evaluating effects of heat metrics on these populations. Ovid MEDLINE, CIHAHL, SCOPUS, Web of Science, JSTOR, and PsycINFO databases were searched using a combination of key words. Twelve studies were selected for this review. In pregnant women, positive associations were found between mean daily temperature and multiple subtypes of pregnancy complications, including threatened or spontaneous abortion, renal diseases, infectious diseases, diabetes, and hypertension. In children, positive associations were found with all-cause diagnoses; asthma; dehydration; electrolyte disorders; heat-related illness; infection; endocrine, nutritional, and metabolic diseases; injury; and otitis media and external emergency department discharge diagnoses and temperature or heatwave versus non-heatwave. By tracking associations between maternal-child emergency department discharge diagnoses and various heat metrics, researchers can contribute to better clinical practices that promote environmental justice and climate resilience.

Global variation in the preferred temperature for recreational outdoor activity

The impacts of climate change will depend on how human societies adapt to higher temperatures. In this study we report empirical evidence suggesting that people living in warmer places prefer a higher temperature for their recreational outdoor activities. To arrive at this conclusion we examine a novel global dataset of mobile phone usage in parks in more than 2500 locations across 77 countries. We examine this dataset with econometric methods to identify the relationship between outdoor recreation and temperature from daily variation in weather. Overall we find that for every increase in annual mean temperature by 1 degree Celsius, the preferred daily mean temperature for outdoor activity increases by about 0.5 degrees Celsius. We explain how these results can be interpreted as evidence for partial adaptation. We also illustrate how ignoring adaptation can bias projections of future responses to climate change.

Development of machine learning models for estimation of daily evaporation and mean temperature: a case study in New Delhi, India

ABSTRACT Accurate prediction of pan evaporation and mean temperature is crucial for effective water resources management, influencing the hydrological cycle and impacting water availability. This study focused on New Delhi's semi-arid climate, data spanning 31 years (1990–2020) were used to predict these variables using advanced algorithms such as Bagging, Random Subspace (RSS), M5P, and REPTree. The models were rigorously evaluated using 10 performance metrics, including correlation coefficient, mean absolute error (MAE), and Nash–Sutcliffe Efficiency (NSE) model coefficient. The Bagging model emerged as the best model with performance indices values as r, MAE, RMSE, RAE, RRSE, MBE NSE, d, KGE, and MAPE as 0.86, 0.76, 1.43, 32.70, 49.44, 0.03, 0.85, 0.96, 0.90, and 22.0, respectively, during model testing phase for pan evaporation prediction. In predicting mean temperature, the Bagging model reported the best results with performance indices values as r, MAE, RMSE, RAE, RRSE, MBE NSE, d, KGE, and MAPE as 0.86, 0.76, 1.43, 32.70, 49.44, 0.03, 0.85, 0.96, 0.90 and 22.0, respectively, during the model testing phase. These findings offer valuable insights for enhancing relative humidity prediction models in diverse climatic conditions. The Bagging model's robust performance underscores its potential application in water resource management.

Short-term exposure to ambient temperature and the mortality burden of suicide in Japan

Background. Previous studies suggest that temperature may trigger suicide, with higher ambient temperatures associated with increased risk globally. However, quantification of the attributable suicide burden due to non-optimal temperatures, particularly across specific subgroups like sex, age, and method of suicide, is limited. This study aimed to quantify this attributable burden across Japan and assess variations in these subgroups to enhance understanding and identify high-risk populations. Methods. Data on daily suicide counts and mean temperatures were collected for all 47 prefectures in Japan (1973–2015) for a comprehensive, nationally representative analysis. Using time-stratified case-crossover analyses and a distributed lag non-linear model (DLNM), we estimated temperature-suicide associations, accounting for long-term trends, seasonality, and day-of-the-week effects, and capturing both nonlinear and delayed impacts of temperature. Overall attributable fractions and fractions attributable to cold (0th-10th percentile), cool (10th-50th), warm (50th-90th), and hot (90th-100th) temperatures were computed. Subgroup analyses were conducted by sex, age (0 – 64 years and ≥65 years), and method of suicide (violent or nonviolent). Results. Approximately 19.9% of suicides (95% empirical confidence interval (eCI): 18.8, 20.9) could be attributed to non-optimal temperatures, representing the proportion of cases that would not have occurred under optimal temperature conditions, identified at the temperature corresponding to the minimum risk of suicide. The highest fraction (9.9%, 95% eCI: 9.4, 10.4) was observed for warm temperatures (50th-90th percentile). Higher burdens were observed in females (23.7%), individuals aged ≥65 years (31.9%), and violent suicides (22.4%). Conclusions. Nearly 20% of suicides in Japan are associated with non-optimal temperatures, particularly during warmer conditions. These findings highlight the importance of integrating temperature considerations into suicide prevention strategies, particularly for vulnerable populations such as the elderly. While focused on Japan, these results advocate future research to explore similar burdens globally, enhancing our understanding of environmental impacts on suicide and informing targeted public health interventions.