Cold Season Research Articles

LC3 cementitious binder incorporating microencapsulated phase change materials for self-defrosting traffic surfaces

Exposed surfaces of bridge decks, viaducts and pavements incur ice formation and accumulation of snow in cold seasons, which threatens traffic safety. Mitigating this problem using traditional methods such as deicing salts have caused ecosystem damage and inflicted substantial reinforcement corrosion and surface scaling to bridge decks and pavements, thus compromising their service life and causing colossal economic loss. This paper presents an alternative solution to overcome this problem through the development of a sustainable LC3 cementitious material incorporating micro-encapsulated phase change material (MEPCM) with low phase transition temperature to delay the surface temperature drop and mitigate snow accumulation and ice formation. MEPCM was incorporated in the cementitious matrix at 0 %, 10 % and 20 % by binder mass. Paste and mortar mixtures were prepared to investigate the microstructural, mechanical, physical, and thermal properties. Test results showed that incorporating MEPCM in the LC3 matrix achieved adequate compressive strength. Thermal simulations and visual observations conducted on mortar samples in the laboratory and outdoor exposure showed that MEPCM can effectively regulate the surface temperature of the LC3 matrix and mitigate temperature drops as well as snow accumulation. Analysis of temperature data in the 2023–2024 winter season of Hamilton, Ontario, Canada indicated that the MEPCM incorporated in mortar samples could effectively regulate 40 % of the total days considered and mitigate surface ice formation and snow accumulation, which provides both economic and environmental benefits.

Changes in the SST Seasonal Cycle in a Warmer North Pacific without Ocean Dynamical Feedbacks

Abstract Climate models project a significant intensification of the sea surface temperature (SST) seasonal cycle over the subpolar North Pacific due to global warming, with the shallower mixed layer widely recognized as the dominant factor. However, employing slab ocean experiments with only ocean–atmosphere thermal coupling, we find a substantial contribution from changes in surface heat flux to this seasonal cycle intensification. In particular, the stronger Newtonian cooling effect in winter acts as a more potent damping than in summer. This differential damping inhibits the warming in colder seasons, significantly contributing to the intensified SST seasonal cycle in the subpolar North Pacific. In addition, consistent phase shifts in the North Pacific are identified across CMIP6 models. In the northwest North Pacific, a phase advance is associated with anomalous heating in early spring, driven by enhanced warm atmospheric advection from lower latitudes and sea ice melting in marginal seas. In contrast, the southeast North Pacific exhibits a phase delay attributed to the anomalous cooling in spring relative to autumn. This cooling is due to weakened trade winds and increased presence of high clouds. The former leads to stronger evaporative cooling in spring, while the latter impedes shortwave radiation from reaching the ocean.

Seasonal Variation in Vascular Dehydration Risk: Insights from the KOBE Study

Abstract Objectives Dehydration, a risk factor for ischemic cerebrovascular diseases, is common in summer; however, the incidence of ischemic diseases is not necessarily higher in summer. The phenomenon may be influenced by the differences in the susceptibility to vascular dehydration based on the season. Therefore, this study aimed to distinguish types of dehydration in colder and warmer seasons by analyzing serum osmolarity, hematocrit, and daily non-alcohol drink (NAD) intake. Methods Participants in the Kobe Orthopedic and Biomedical Epidemiologic (KOBE) Study, consisting of healthy individuals, were categorized into two groups based on the examination month: the warmer and colder seasons. Multivariate analyses were conducted to examine disparities in serum osmolarity, hematocrit, and NAD intake between these two groups. Results Participant ratios by age group and the seasons (warmer season/colder season) were as follows: Women under 50 (35/62), 50-60 (77/126), 60-70 (123/170), over 70 (58/52); Men under 50 (14/17), 50-60 (22/36), 60-70 (57/71), over 70 (55/34). The colder season was found to be negatively correlated with serum osmolarity and NAD intake, but positively correlated with hematocrit, even after adjusting for relevant factors. Age was independently associated with serum osmolarity, but not with hematocrit and NAD intake. Conclusions This study highlights that vascular dehydration is more likely in the colder season despite lower serum osmolarity than the warmer season. Age-related increases in serum osmolarity without a corresponding rise in water intake may contribute to this. These findings emphasize the importance of addressing dehydration in the colder season, particularly in older adults. Key messages • The colder season showed a negative correlation with serum osmolarity and NAD intake but a positive correlation with hematocrit. • Raising awareness about the importance of hydration during winter may be essential.

Cold Season Cloud Response to Sea Ice Loss in the Arctic

Abstract Based on satellite observations, we investigate the cloud responses during the cold season, from October to the following March, to interannual fluctuations in Arctic sea ice concentrations during September and October. It is found that the cloud responses differ between the periods 2000-2018 and 1982-1999. From 2000-2018, increased Arctic Ocean cloud cover in October and November transitioned to significantly less cloud cover and cloud radiative forcing (CRF) from January to March, in response to lower sea ice concentrations in September and October. The lower CRF in January and March preconditions the sea ice and likely contributes to higher sea ice concentrations the following September. This suggests a negative cloud feedback on sea ice concentration, which may contribute to sea ice recovery after a dramatic decrease. In contrast, from 1982 to 1999, generally increased cloud cover and cloud radiative forcing persisted from October to March following lower sea ice concentrations in the preceding September and October. The cause of the different cloud responses to sea ice changes in these two time periods remains unclear and requires further investigation.

Effects of short-term exposures to lower air temperature and cold spells on myocardial infarction hospital admissions: a nationwide study in Sweden

Abstract Background Exposures to lower air temperature and cold spells have been associated with an increased risk of various diseases. However, the short-term effect of lower air temperature and cold spells on myocardial infarction (MI) remains incompletely understood. Purpose We aimed to evaluate the short-term effects of lower air temperature and cold spells on MI hospital admissions within the nationwide SWEDEHEART registry. Methods This population-based nationwide study included 120,380 MI cases admitted to hospitals in Sweden during the cold season (October to March) from 2005 to 2019. Daily mean air temperature was estimated at 1 km2 spatial resolution across Sweden using a three-stage machine learning approach and percentiles of daily temperatures experienced by individuals in the same municipality were employed as individual exposure indicators to account for potential geographic adaptation. Cold spells were defined as periods of at least two consecutive days with a daily mean temperature below the 10th percentile of the temperature distribution for each municipality. A time-stratified case-crossover design incorporating a conditional logistic regression model with distributed lag non-linear model using lag 0-1 and lag 2-6 days was employed to evaluate the short-term effects of lower air temperature and cold spells on total MI, non-ST-segment elevation MI (NSTEMI) and ST-segment elevation MI (STEMI). Results We found significant increases in risk for total MI, NSTEMI, and STEMI in association with a decrease of one percentile in temperature at a lag of 2-6 days, indicated by ORs (95% CI) of 1.099 (1.057-1.142), 1.110 (1.06-1.164), and 1.076 (1.004-1.153), respectively. Additionally, we found that cold spells were significantly associated with increased risks for total MI, NSTEMI, and STEMI at a lag of 2-6 days, with ORs (95% CI) of 1.077 (1.037-1.12), 1.069 (1.02-1.119), and 1.095 (1.023-1.172), respectively. Moreover, independent effects of lower air temperature and cold spells on MI occurrence were found after adjusting for each other. Conversely, we observed that lower air temperature and cold spells were associated with decreased risks for MI at a lag of 0-1 days. Conclusions This nationwide case-crossover study demonstrated a novel biphasic pattern in MI risk following exposure to lower air temperatures and cold spells, characterized by an initial transient reduction in risk at lags 0-1 day, followed by a significant increase in risk at lags 2-6 days. As climate change continues to induce complex shifts in regional weather patterns, enhancing protections to reduce future cold-related cardiac hospitalizations is crucial.

Monitoring of mosquito breeding sites in the municipality of Cascais, Portugal

Abstract Culex pipiens is the primary West Nile Virus vector in Portugal. Additionally, in 2017, Aedes albopictus, vector of various arboviruses, was detected in Northern Portugal. To mitigate viral transmission risks, effective surveillance is crucial, including monitoring egg, larva, and pupa stages. Located on the west of Lisbon, Cascais implemented a surveillance based on monitoring invasive species at Points of Entry and, complementarily, on detecting and intervening in breeding sites. Active searches for new breeding sites and monitoring those that were already identified are conducted weekly during the peak mosquito season (May to October) and biweekly during the colder season (November to April), following the methodology outlined below: • Upon detection, samples of immature stages are collected for submission to the National Institute of Health (INSA); • Corrective measures are requested to the managing entities of the locations where the sites are found; • Date of action, location, collection point, date of report, and status (pending or intervened) are recorded on a database; • Locations with pending status undergo continuous monitoring. In 2023, 16 artificial breeding sites were identified. These findings resulted from 23 actions conducted across 8 locations. 35 samples of immatures were collected, followed by their submission and notification to the respective managing entities. Recurrent detections were noted in 9 breeding sites. The managing entities implemented measures at 13 of the identified sites, leaving 3 with pending intervention. The identification of breeding sites demands continuous monitoring efforts and requires an effective coordination between the Public Health services and the management entities. Based on the achieved outcomes, it is evident that the implementation of corrective measures has been successful, making a significant contribution to reducing mosquito density. Key messages • Effective surveillance and intervention strategies are crucial in mitigating West Nile Virus and arbovirus transmission risks in Portugal. • Continuous monitoring and coordination between public health services and management entities are key for maintaining effective vector control measures.

Active offer of influenza vaccination during hospitalization: a multicenter study in Sicily (Italy)

Abstract Background Every cold season, the Italian health institutions strongly recommend influenza vaccination for categories at risk of complications, however influenza vaccination coverage is over and over far from the desirable target of 95%. After the pilot experience conducted in Palermo during the 2022-23 influenza season, the ‘Vaccinations in the ward’ project was extended to other Sicilian centers in order to evaluate the impact of the vaccination offer strategy in a broader territorial reality and to analyze the determinants of influenza vaccine acceptance among at risk people. Methods The project was conducted at the Umberto I Hospital in Enna and the University Hospitals of Messina and Palermo during the 2023-24 influenza season. A questionnaire was administered to the at risk hospitalized patients to investigate socio-demographic factors, behavioral habits, and clinical condition. Furthermore, influenza vaccination upon discharge was offered. Multivariable logistic regression was performed to identify the determinants of influenza vaccine acceptance. Results Overall, 374 patients with a median age of 65 years (IQR: 50-70) were recruited, of whom 36% had been vaccinated for influenza during the 2022-23 season (n = 136). The patients who accepted influenza vaccination in the ward were 57% (n = 214). The determinants of vaccination adherence were: age (OR: 1.03; p = 0.003); having quit smoking (OR: 2.68; p = 0.017); having received advice on vaccination from general practitioner (OR: 4.9; p < 0.001) and hospital healthcare workers (OR: 7.3; p < 0.001). Conclusions The offer of vaccination in the ward effectively increased influenza coverage among categories at risk of complications. Furthermore, the adoption of correct behavioral habits and the promotion of influenza vaccination by healthcare personnel have played a decisive role in the vaccine acceptance process. These findings could be useful for planning future influenza vaccination campaigns targeted to at risk people. Key messages • Vaccination strategies are needed to increase influenza coverage among at-risk categories. Active offer of influenza vaccine upon discharge can effectively increase vaccination compliance. • The adoption of correct behavioral habits and the promotion of vaccination by healthcare personnel play a decisive role in the influenza vaccine acceptance process among at risk people.

Analysis of Macro- and Microphysical Characteristics of Ice Clouds over the Tibetan Plateau Using CloudSat/CALIPSO Data

Utilizing CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2007 to 2016, this study analyzed the distributions of optical and physical characteristics and change characteristics of ice clouds over the Tibetan Plateau (TP). The results show that the frequency of ice clouds in the cold season (November to March) on the plateau is over 80%, while in the warm season (May to September) it is around 60%. The average cloud base height of ice clouds in the warm season is 3–5 km, and mostly around 2 km in the cold season. The average cloud top height in the warm season is around 5–8 km, while in the cold season it is mainly around 4.5 km. The average thickness of ice clouds in both seasons is around 2 km. The statistical results of microphysical characteristics show that the ice water content is around 10−1 to 103 mg/m3, and the effective radius of ice clouds is mainly in the range of 10–90 μm. Both have their highest frequency in the west of the TP and lowest in the northeast. A comprehensive analysis of the change in temperature, water vapor, and ice cloud occurrence frequency shows that the rate of increase in water vapor in the warm season is greater than that in the cold season, while the rates of increase in both surface temperature and ice cloud occurrence are smaller than in the cold season. The rate of increase in temperature in the warm season is around 0.038 °C/yr, and that in the cold season is around 0.095 °C/yr. The growth rate of thin ice clouds in the warm season is around 0.15% per year, while that in the cold season is as high as 1% per year. The results suggest that the surface temperature change may be related to the occurrence frequency of thin ice clouds, with the notable increase in temperature during the cold season possibly being associated with a significant increase in the occurrence frequency of thin ice clouds.

The Impact of Different Types of Trees on Annual Thermal Comfort in Hot Summer and Cold Winter Areas

Trees positively improve the annual thermal comfort of the built environment in tropical areas, where climate change is slight throughout the year. However, for areas with high changes in climate all year, the current studies have only explored the summer cooling performance of trees without the impact of different types of trees on annual thermal comfort, especially in cold seasons. Therefore, to quantify the impacts and scientifically guide the optimization of green space layout in hot summer and cold winter areas, this study selected Changsha City as the study area and analyzed how the annual thermal comfort is affected by evergreen trees and deciduous trees, which are two common types of trees in hot summer and cold winter areas. The analytical results indicated that the difference in the effect of deciduous and evergreen trees on outdoor thermal comfort was insignificant in summer, where the difference in the monthly mean PET for the three summer months was slight, being 0.28 °C, 0.14 °C, and 0.29 °C, respectively. However, evergreen trees greatly exacerbated winter cold compared to deciduous trees, with a monthly mean PET decrease by nearly 1.0 °C and an hourly PET reduced by up to 3.57 °C. The difference is mainly attributed to the absorption and reflection of solar radiation by the tree canopy, as well as the cooling and humidifying effect of the tree leaf. In hot summer and cold winter areas, outdoor thermal comfort is still in the “comfortable” and “slightly warm” acceptable stage despite the warming effect of deciduous trees in the spring and autumn seasons. Planting evergreen trees is an inevitable thermal mitigation choice for tropical areas. However, for the areas with high annual climate change, such as hot summer and cold winter areas in China, a change in empirical tree planting patterns and selecting deciduous trees where appropriate will improve year-round outdoor thermal comfort.

Seasonal influence on tomato fruit metabolome profile: Implications for ABA signaling in multi-stress resilience

The increasing effects of climate change are leading to an increase in the number and intensity of extreme events, making it essential to study how plants respond to various stresses occurring simultaneously. A crucial regulator of plant responses to abiotic stress is abscisic acid (ABA), as its accumulation in response to stress leads to transcriptomic and metabolomic changes that contribute to plant stress tolerance. In the present study, we investigated how ABA, stress conditions (salinity, water deficit and their combination) and seasons (autumn-winter and spring-summer) regulate tomato fruit yield and metabolism using tomato wild type (WT) and the ABA-deficient flacca mutant (flc) under stress conditions in cold and warm seasons. Our results showed that the applied stresses did not have the same effect in the warm season as in the cold season. In WT plants, the levels of other flavonoids, lignans and other polyphenols were higher in summer fruits, whereas the levels of anthocyanins, flavanols, flavonols, phenolic acids and stilbenes were higher in winter fruits. Furthermore, the significant increase in anthocyanins and flavonols was associated with the combination of salinity + water deficit in both seasons. Additionally, under certain conditions, flc mutants showed an enrichment of the superclasses of benzenoids and organosulphur compounds. The synthesis of phenolic compounds in flc fruits was also significantly different compared to WT plants. Thus, the metabolic profile of tomato fruits varies significantly with endogenous ABA levels, season of cultivation and applied stress treatments, highlighting the multifactorial nature of plant responses to combined environmental factors.

Spatial and temporal patterns of urban air pollution in tehran with a focus on PM2.5 and associated pollutants

Understanding the spatial and temporal dynamics of air pollutants is crucial for effective urban air pollution management. This study focuses on the temporal dynamics of air quality monitoring stations (AQMSs) and the association among air pollutants, particularly PM2.5, in Tehran, Iran. Using time series clustering and the Copula model, we analyzed data from 2019 to 2022. We found that the levels and dynamics of O3 and SO2 were similar across most AQMSs and unrelated to geographical positions. CO levels and dynamics were consistent among urban and border AQMSs, with higher concentrations in urban stations. NO2 levels and dynamics varied significantly among northern AQMSs with no relationship geographical positions. PM10 levels and dynamics had a relationship with geographical positions, with western clusters having the highest and northern clusters the lowest concentrations. The dynamics of PM2.5 showed significant relationship among AQMSs in the eastern, southern, and western regions, but not in the north. We also observed that PM10 and O3 levels were higher in warm seasons, whereas CO, SO2, NO2, and PM2.5 levels were higher in cold seasons. Most pollutants, except O3, peaked during traffic hours. Notably, the significant increase in PM2.5 since spring 2021 was primarily due to PM10. Policymakers should focus on these spatial and temporal variations to improve urban air quality and public health outcomes through targeted interventions.

Краткосрочный прогноз смерчеопасных ситуаций для прибрежной акватории Черного моря с использованием усовершенствованного индекса WRI

The paper considers the issues of improving the quality of short-term forecasts of waterspout-risk conditions for the Black Sea coastal water. The results related to the development of new versions for calculating the regional waterspout risk index (WRI) for both the warm (WRI21) and cold (WRIW) seasons are presented. The WRI is used to identify zones of high-risk waterspout formation and subsequent localization of waterspout-risk areas of the coast. Calculations of the WRI fields are based on the output of the COSMO-Ru2 mesoscale model with a grid spacing of 2.2 km. Calculations are carried out in real time within the technology for assessing the risk of waterspouts. The skill of forecasting new WRI versions for different periods is analyzed. It is shown that the probability of waterspout detection in the warm season can reach 82% on average. At the same time, there is also a high false alarm rate (about 70%), mainly due to the excessively predicted waterspout risk in certain areas of the coast (Sochi and Tuapse). In the cold season, as expected, a significantly smaller number of waterspout-risk days is predicted as compared to the warm period. Examples of forecasts for different seasons are presented. Recommendations on the use of forecasts for preparing storm warnings are given.

ҚАЗАҚСТАННЫҢ ШЫҒЫСЫНДАҒЫ КЛИМАТТЫҢ ЗАМАНАУИ ӨЗГЕРУЛЕРІ

Currently, the problem of climate change has not only alarmed meteorologists, but has also become a large-scale topic of public attention in general. One of the Sustainable Development Goals proposed by the United Nations is the Fight against climate change (SDG-13CIS-13), within the framework of which large-scale projects and a number of activities are being carried out in the country. Modern climatic changes in Kazakhstan lead to an increase in air temperature and precipitation, as well as the duration, intensity and frequency of hydrometeorological phenomena. It is important to understand the dynamics of their changes, to determine the patterns of occurrence. During the research in 1942...2022. The meteorological stations Ust-Kamenogorsk, Semey, Shemonaiha, Katon-Karagai, Kurchum, Zaisan, Aksuat in East Kazakhstan have a tendency to increase air temperature by 0,2...0,4 0C every 10 years. There was a tendency for precipitation to increase by 1,6...7,7 mm every 10 years at Zaisan, Shemonaiha and Semey stations, and by 4,1...5,9 mm every 10 years at other stations. Anomalies in air temperature and precipitation over the past decade have shown a positive trend.According to the Mann-Kendall test, the value of the air temperature change was higher at all stations in February-March and August. The value of precipitation changes in the spring and autumn months is small, and at Zaisan, Shemonaiha and Semey stations it was higher in the cold season.

Exergy based yearly performance analysis of a poly-generation system for a small-town application

The current study conducts a comprehensive year-round exergy analysis of an integrated system centered around a reversible solid oxide cell (RSOC), aimed at fulfilling the power and fresh water requirements of a small town, equivalent to 2.7 MW and 2000 m³/day, respectively. The integrated system encompasses four subsystems: the solar field, RSOC, organic Rankine cycle coupled with ejector cooling (ORC), and zero liquid discharge multi-effect desalination (MED-ZLD). The proposed system is analyzed using MATLAB. The annual exergy efficiency for each subsystem is examined, yielding average values of 11.9 %, 48.11 %, and 56.22 % for the solar field, ORC cycle, and MED-ZLD, respectively. Notably, the exergy efficiency of the Rankine cycle is higher in colder months compared to warmer ones. This phenomenon is attributed to the cycle's greater heat generation relative to the cooling it produces during the cold season. The RSOC exhibits noteworthy average exergy efficiencies of 93 % in electrolysis mode, 69.87 % in fuel cell mode, and an overall average exergy efficiency of 79.62 % throughout the year. The average exergy efficiency of the overall system is evaluated throughout the day, nighst, and the entire operational period. The results are values of 10.74 %, 34.31 %, and 23.34 %, respectively. This discrepancy is due to the primary energy supply source, which is solar energy during the day and input hydrogen during the night. The highest exergy efficiency is observed in December, while the lowest is in June. Furthermore, the study examines the distribution of exergy destruction and identifies cycles with significant impacts by analyzing the exergy destruction ratio across various months. The solar field is the primary contributor to daytime exergy destruction, peaking at 94.9 %. At night, the MED-SET cycle leads in exergy destruction, followed closely by the RSOC cycle operating as a fuel cell. The research also delves into exploring key contributors to exergy destruction in various cycles, shedding light on crucial insights into the intricate dynamics of the integrated system's performance.

Multi-omics insights into the energy compensation of rumen microbiota of grazing yaks in cold season.

The ability of yaks to adapt to the extreme environment of low temperatures and hypoxia at cold seasons on the Qinghai-Tibet Plateau (QTP) is related to the host genome; however, the convergent evolution of rumen microbiomes in host adaption is unknown. Here, we conducted a multi-omics study on the rumen fluid of grazing yaks from warm (July) and cold (December) seasons on the QTP to evaluate the convergent evolution of rumen microbiomes in the adaptation of grazing yaks to cold-seasons environments. The results showed that grazing yaks at cold seasons had higher fibrolytic enzyme activities and volatile fatty acids (VFAs) concentrations, and the relative abundance of Firmicutes and the ratio Firmicutes to Bacteroidetes was significantly higher than that of yaks at warm seasons. Macrogenomic analyses showed that genes involved in forming VFAs and arginine were significantly enriched in cold-season yaks. Transcriptome analyses of the rumen epithelium showed that 72 genes associated with VFAs absorption and transport were significantly upregulated in cold-season yaks. Metabolomic analyses showed that the levels of ornithine, related to efficient nitrogen utilization, were significantly upregulated in cold-season yaks. The synergistic role of rumen microbiomes in the adaptation of grazing yaks to extreme environments at cold seasons was revealed by multi-omics study.

Seasonal variation of antibiotic resistance genes in activated sludge of a full-scale municipal wastewater treatment plant: Contribution of activated sludge functional taxa and clinically relevant taxa

It has been demonstrated that antibiotic resistance genes (ARGs) exhibit seasonal variations in municipal wastewater treatment plants (MWTPs), but their relationship to bacterial phylogeny structure remains unclear. Using advanced metagenomic techniques and machine learning approach, the current study conducted a year-long investigation to explore the relationship between ARGs and the bacterial community of activated sludge in a full-scale MWTP in Beijing, where seasonal dynamics are remarkable. High abundance of ARGs, notably the clinically relevant high-risk ARGs, was observed in winter and spring, the cold season in Beijing. Seasonal patterns were also observed in the diversity of ARGs and the overall bacterial community. Machine learning-based random forest classification models were utilized to identify biomarkers for ARGs and bacterial genera as indicators of seasonal differences. Subsequent analysis of the relationship between ARGs and bacterial biomarkers was examined using random forest regression models. Results showed that the enrichment of potential pathogens such as Mycobacterium, Clostridium and Pseudomonas was high in winter and spring, strongly contributing to the abundance of high-risk ARGs (ermB, aac(6′)-I, tetM, blaTEM, and mefA) during cold season. Conversely, functional taxa associated with activated sludge, such as Thauera, displayed seasonal fluctuations and a preference for ARGs with minor clinical implications. Metagenomic binning further illustrated the contribution of Mycobacterium to ARG enrichment in cold season. Our findings highlight the collective impact of human-derived clinically relevant taxa and functional bacterial taxa in activated sludge on the seasonal dynamics of ARGs in MWTPs. Additionally, this study offers valuable insights into the safe disposal of the excess sludge from MWTPs.

Temperature variability and influenza incidence in China: Effect modification by ambient fine particulate matter

This study aims to examine the association between temperature variabilit (TV) exposure and influenza incidence in China, and the modification effect of PM2.5 levels. Data on daily influenza cases, weather conditions, and PM2.5 concentrations were collected from 339 cities across mainland China from 2014 to 2019. TV was computed as the standard deviation of daily maximum and minimum temperatures for the current day and the previous several days (i.e., TV0–1 to TV0–7). A space-time-stratified case-crossover design with conditional Poisson regression was employed. Overall, each 1 °C increase in TV0–6 was linked to 3.3 % (95 % CI: 3.1 %, 3.5 %) rise in influenza incidence, potentially attributing 14.73 % (95 % CI: 14.08 %, 15.37 %) of cases to this exposure. PM2.5 concentration showed substantial modification effect on the association, such that the relative risk (RR) of influenza incidence grew from 1.027 (95 % CI: 1.025, 1.029) to 1.040 (95 % CI: 1.038, 1.042) as PM2.5 levels increased from 15 to 75 μg/m³ . Females and individuals over 65 years old were more susceptible to TV exposure and the PM2.5 modification. Stronger effects were observed during cold season and in North region. The findings highlight the integrating considerations of TV and PM2.5 exposures into public health measures for influenza prevention and control.

The influence of specific weather types on stroke occurrence: an analysis of 23,000 patients from Augsburg, Germany

ABSTRACT For the first time, the relationships between large-scale weather types and local stroke events in the urban area of Augsburg, Germany are analyzed. Over 23,000 stroke cases (2006 – 2020) were standardized to account for long-term trends and seasonality. Using ERA5 reanalysis data, a composite analysis identified stroke-related atmospheric variables, while seasonal weather types were classified via the neural network algorithm of self-organizing maps. Cyclonic westerlies during the cold season, which transport warm air masses from the Atlantic Ocean to Germany, were a major risk factor for ischemic stroke, while colder easterly conditions reduced stroke incidence. In the warm season, both anticyclonic conditions and westerly/northerly air advection, leading to slightly warmer or distinctly colder temperatures, were linked to increased ischemic stroke risk. Additionally, hemorrhagic strokes in the cold season were triggered by weather conditions contrary to those associated with ischemic strokes and transitory ischemic attacks.

Massive Outbreak of Aurelia coerulea in Geoje Bay, Korea

This study was carried out to elucidate the causes of massive outbreaks of Aurelia coerulea in Geoje Bay, Korea, from November 2022 to October 2023. Adult medusae consistently spawn with planulae, and the populations of A. coerulea in Geoje Bay could be categorized into current-year and overwintering populations. The current-year population began with the emergence of ephyrae in February and grew until October, while the overwintering population comprised a mixture of surviving current-year population and additional individuals that joined during the warm season. The size of the planulae are significantly larger than the annual average during the cold season. These results appear to be the energy accumulation of planulae for polyp formation under low water temperatures. Planulae form polyps within a temperature range of 5–25 °C, suggesting the possibility of year-round polyp recruitment. In Geoje Bay, the highest appearance rate of A. coerulea was in April (8.71 ± 12.5 ind. m−3), with ephyrae experiencing higher growth rates up to the young medusa stage. However, from April, a decline in zooplankton biomass resulted in reduced growth rates in adults, indicating that jellyfish growth was primarily regulated by food availability. Additionally, submersed oyster shells in oyster farms served as the main habitat for jellyfish polyps. A. coerulea populations were also characterized by the continuous spawning of planulae throughout the year. In conclusion, this study suggests that stable polyp habitats, abundant food supply during the initial developmental period of the population, and suitable ranges of water temperature were significant factors inducing the massive outbreak of A. coerulea in Geoje Bay, Korea.

The weather of 1740, the coldest year in central Europe in 600 years

Abstract. The winter of 1739/40 is known as one of the coldest winters in Europe since early instrumental measurements began. Many contemporary sources discuss the cold waves and compare the winter to that of 1708/09. It is less well known that the year 1740 remained cold until August and was again cold in October and that negative temperature anomalies were also found over Eurasia and North America. The 1739/40 cold season over northern mid-latitude land areas was perhaps the coldest in 300 years, and 1740 was the coldest year in central Europe in 600 years. New monthly global climate reconstructions allow us to address this momentous event in greater detail, while daily observations and weather reconstructions give insight into the synoptic situations. Over Europe, we find that the event was initiated by a strong Scandinavian blocking in early January, allowing the advection of continental cold air. From February until June, high pressure dominated over Ireland, arguably associated with frequent eastern Atlantic blocking. This led to cold-air advection from the cold northern North Atlantic. During the summer, cyclonic weather dominated over central Europe, associated with cold and wet air from the Atlantic. The possible role of oceanic influences (El Niño) and external forcings (eruption of Mount Tarumae in 1739) are discussed. While a possible El Niño event might have contributed to the winter cold spells, the eastern Atlantic blocking is arguably unrelated to either El Niño or the volcanic eruption. All in all, the cold year of 1740 marks one of the strongest, arguably unforced excursions in European temperature.