Average Daily Temperature Research Articles

Global Seasonal Activities of Respiratory Syncytial Virus Before the Coronavirus Disease 2019 Pandemic: A Systematic Review.

Varied seasonal patterns of respiratory syncytial virus (RSV) have been reported worldwide. We conducted a systematic review on articles identified in PubMed reporting RSV seasonality based on data collected before 1 January 2020. RSV seasonal patterns were examined by geographic location, calendar month, analytic method, and meteorological factors including temperature and absolute humidity. Correlation and regression analyses were conducted to explore the relationship between RSV seasonality and study methods and characteristics of study locations. RSV seasons were reported in 209 articles published in 1973-2023 for 317 locations in 77 countries. Regular RSV seasons were similarly reported in countries in temperate regions, with highly variable seasons identified in subtropical and tropical countries. Longer durations of RSV seasons were associated with a higher daily average mean temperature and daily average mean absolute humidity. The global seasonal patterns of RSV provided important information for optimizing interventions against RSV infection.

Seasonality of Infections Caused by Respiratory Viruses in Newborns and Their Relation to Meteorological Factors

Objectives − Most viral respiratory tract infections (VRTI) are seasonal diseases and frequently severely affect public health by causing seasonal epidemics and pandemics, also in newborns. The objective of this study was to analyse the relation of meteorological factors to the occurrence of neonatal VRTI and to estimate their predictive role for VRTI seasonality.Patients and methods − The retrospective observational cohort study enrolled 228 newborns (56% male and 29% preterm) aged up to 44 postmenstrual weeks, hospitalized due to acute VRTI between January 2015 and December 2020 in the central Slovenian region. The meteorological data for the same geographical region and time period were assessed, and correlation, multiple regression and cut-off values were analysed. Results − A typical seasonal distribution of VRTI from December to March was observed and the large majority of cases were due to respiratory syncytial virus (RSV) infection. Low air temperature, high relative humidity, shorter daily solar radiation and increased cloud cover were associated with an increased risk of neonatal, either RSV or non-RSV VRTI.Conclusions − Meteorological factors, particularly air temperature and relative humidity, were associated with neonatal VRTI occurrence in the temperate climate of central Slovenia. The average daily air temperature below 4.9 and 3.8 °C could predict the onset of the VRTI and RSV VRTI season, respectively. These factors could be used as real-time predictive warning, especially for RSV season onset and the need to begin RSV immunoprophylaxis in vulnerable newborns.

Assessment of Tropospheric Radio Refractivity and Its Variation with Climatic Variables Over Zaria, Nigeria

To achieve optimal performances, radio link/system planning and design must take radio refractivity estimation very seriously. This study utilizes measured average daily temperature, relative humidity, and atmospheric pressure for forty-one-year period (1981–2021) obtained from the National Aeronautics and Space Administration (NASA) archives for Zaria (latitude 11.100 N, longitude 7.680 E) strategically located in Nigeria’s midland climate zone to calculate the monthly tropospheric radio refractivity and look into how it varies with other meteorological factors and radio refractive index. The percentage of the contribution of dry term (Ndry) and wet term (Nwet) to radio refractivity and refractivity gradient were investigated. The findings indicated that radio refractivity was higher during the rainy season (August) and lower’during the dry season (February), with a maximum mean value of 350.8733 N-units and a minimum mean value of 284.1975 N-units, respectively, found in those months. The wet term contributes to the significant fluctuation of the radio refractivity, whereas the dry term makes up 76.03% of the total value. The gradient of mean refractivity estimated for Zaria was found to be – 43.8709 N – units/km indicating super-refraction propagation condition.

Nasal oxidative stress mediating the effects of colder temperature exposure on pediatric asthma symptoms.

Colder temperature exposure is a known trigger for pediatric asthma exacerbation. The induction of oxidative stress is a known pathophysiologic pathway for asthma exacerbation. However, the role of oxidative stress in linking colder temperature exposure and worsened pediatric asthma symptoms is poorly understood. In a panel study involving 43 children with asthma, aged 5-13 years old, each child was visited 4 times with a 2-week interval. At each visit, nasal fluid, urine, and saliva samples were obtained and measured for biomarkers of oxidative stress in the nasal cavity (nasal malondialdehyde [MDA]), the circulatory system (urinary MDA), and the oral cavity (salivary MDA). Childhood Asthma-Control Test (CACT) was used to assess asthma symptoms. When ambient daily-average temperature ranged from 7 to 18 °C, a 2 °C decrement in personal temperature exposures were significantly associated with higher nasal MDA and urinary MDA concentrations by 47-77% and 6-14%, respectively. We estimated that, of the decrease in child-reported CACT scores (indicating worsened asthma symptoms and asthma control) associated with colder temperature exposure, 14-57% were mediated by nasal MDA. These results suggest a plausible pathway that colder temperature exposure worsens pediatric asthma symptoms partly via inducing nasal oxidative stress. The role of oxidative stress in linking colder temperature exposure and worsened asthma symptoms is still poorly understood. Lower temperature exposure in a colder season was associated with higher nasal and systemic oxidative stress in children with asthma. Nasal MDA, a biomarker of nasal oxidative stress, mediated the associations between colder temperature exposures and pediatric asthma symptoms. The results firstly suggest a plausible pathway that colder temperature exposure worsens pediatric asthma symptoms partly via inducing oxidative stress in the nasal cavity.

Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years

In the past 10 years, extreme weather phenomena have increased, and global warming has markedly advanced; moreover, the intensity of human activity has gradually increased. These have an impact on the growth of global vegetation. Related studies have focused on the Tibetan Plateau and some northern provinces of China to estimate grassland AGB at a large scale but a low resolution. Hulunbuir Grassland is an important supplier of livestock products, and therefore, it is important to precisely map AGB and explore the response of Hulunbuir Grassland AGB to climate change and human activities at a high resolution to identify complex spatial details. In this study, we selected vegetation indices from Landsat 8 OLI and topographic indices and used multiple linear regression and machine learning algorithms to estimate the spatial distribution of AGB from 2013 to 2022. Then, we analyzed the correlations between AGB and cumulative precipitation and daily average temperature in summer and between population density and livestock density at the pixel level. Our results demonstrated that the RF model performed well, with an RMSE of 28.23 and R2 value of 0.74; the AGB was positively correlated with the cumulative precipitation in summer in 94.45 % of the area and negatively correlated with the daily average temperature in summer in 96.32 % of the area. We suggest that it is necessary to reduce grazing activities in future warm and drought years and to adjust sources of income to adapt to the decrease in AGB under global warming conditions. This study will provide reference for the countries or regions that depend on temperate grasslands for husbandry.

Energy-saving regulation methods and energy consumption characteristics of office air-conditioning loads in hot summer and cold winter areas

The air-conditioning system of an office building may have much higher operational energy consumption than its designed value due to the actual use behavior which significantly deviates from the predicted one. To precisely analyze the actual air-conditioning energy consumption, in this paper, based on the impact of occupant air-conditioning behavior on the energy consumption of air-conditioning systems, a Supply-Side Cooling Load Regulation Method (SSRM) is proposed, and its air-conditioning energy consumption analysis model is established. The energy consumption characteristics of the air-conditioning system under SSRM were analyzed, with the assumption that the example office building is located in a hot summer and cold winter areas. The results indicate that the indoor air conditioning set temperature and the actual fresh air volume are important factors affecting the variation of the air conditioning system cooling load under the Demand-Side Cooling Load Regulation Method (DSRM) method, whereas under SSRM, the air conditioning system cooling load is not affected by the variation of the indoor set temperature and the fresh air volume; meanwhile, regulating human air-conditioning use behaviors is the key point of reducing air-conditioning cooling load. The increasing fresh air volume from 30 m3/(p∙h) to 90 m3/(p∙h) can result in about a 5°C increase in the average daily indoor air temperature in the rooms used by SSRM, and it also causes an increase in the total air-conditioning load in the rooms under DSRM by more than 45 kWh/day. Further, compared to the DSRM, the SSRM can well regulate occupant air-conditioning use behaviors, which reduces energy consumption by more than 35% in the summer.

Analysis of market risk volatility and warning in carbon trading market

A good risk warning model is an effective way to guarantee the stable operation of the carbon market and exert its emission reduction function. This paper takes the China's pilot carbon market as the research object and measures the carbon market risk by ARMA-GARCH-VaR. Then, influential factors are selected as non-market characteristics from the perspective of causality and incorporated into the risk warning model, and SMOTE and SMOTEENN are introduced to deal with the unbalanced samples. Results show that (1) The risk fluctuations of Beijing and Shenzhen carbon market are large, and the risk fluctuations of Guangdong carbon market are relatively smooth in the early period and larger in the recent period. (2) Air quality, average daily temperature, CSI 300, power coal, natural gas, European carbon market, exchange rate, and Baidu index are all important factors in the risk volatility of carbon market. (3) The Classification Decision Tree (CDT) has the best performance. CDT has the best performance in Guangdong carbon market, SMOTE-CDT has the best performance in Hubei carbon market, and SMOTEENN-CDT has the best performance in Shanghai carbon market, in which SMOTEENN-CDT has a 76% Recall. The non-equilibrium treatment improves the overall Recall, and the risk warning model after non-equilibrium treatment can avoid missing important risk points. This paper can provide a certain degree of reference for the improvement of carbon trading market and risk management.

Responses of phenology to preseason drought and soil temperature for different land cover types on the Mongolian Plateau

Drought and heat caused major disturbance in nature by interfering with plant phenology, and can also alter the vulnerability and resilience of terrestrial ecosystems. Existing research on the Mongolian Plateau has primarily focused on studying the response of the start (SOS) and end (EOS) of the growing season to drought and heat variations. However, there is still a lack of comprehensive understanding regarding the coupled effects of drought and heat on phenology across different land cover types. In this study, we retrieved SOS and EOS based on 34-year (1982–2015) normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). Results showed that grasslands and the Gobi-Desert show rapid advancement in SOS, and forests presented the slowest advancement in SOS, but SOS in croplands were delayed. EOS across four land cover types advanced, with the Gobi-Desert showed the highest rate of advancement and forests the lowest. Using the Palmer Drought Severity Index (PDSI) and soil temperature as the indicators of drought and thermal conditions, the responses of SOS and EOS to these two climate variables were evaluated. The advanced SOS driven by lower drought severity was detected in forests, grasslands, croplands and the Gobi-Desert. The dominant response of EOS to drought severity was positive in croplands, grasslands and forests, except for the Gobi-Desert, where drought severity had negative effects on EOS. Compared with the daily average soil temperature (STmean), the daily maximum soil temperature (STmax, daytime), and the daily minimum soil temperature (STmin, nighttime), the daily diurnal soil temperature range (DSTR, where DSTR = STmax − STmin) between night and day were the most suitable indicators for assessing the response of SOS and EOS to soil temperature. Strong negative correlation between SOS and the preseason DSTR was pronounced in all land cover types on the Mongolian Plateau. However, EOS was negatively correlated with the preseason DSTR only in the Gobi-Desert. Last but not least, normalized sensitivity assessments reveal that the negative impacts of DSTR on SOS and EOS were the main controlling factors on the Mongolian Plateau phenology, followed by the couple negative effects of drought severity and DSTR.

Change and influence of agroclimatic conditions on oat yield in Yakutia

The results of the dynamics analysis of multi-year meteorological indicators and study of their influence on the yield of the released oat varieties in different agroclimatic zones of Yakutia are presented. It is shown that in the period from 1960 to 2021 the mean annual air temperature in Central Yakutia (Pokrovsk meteorological station) increased annually by 0.045 °C, from 1999 to 2021 – by 0.088 °C, the number of dry years in June increased from 67 to 92% due to a 21% increase in years with medium (HTC = 0.41-0.60) and very strong (HTC < 0.21) drought. In July, drought was recorded in 50% of the years, in August – in 38%. In all agroclimatic zones in the period from 2014 to 2021 for June – August the average daily air temperature annually increased by 0.16...0.34 °С and their sum by 14...28 °С, with precipitation decreasing by 3-16 mm and HTC value by 0.04-0.12 units. Climate change from 2014 to 2021 was 3 to 8 times more intense than from 1999 to 2022. There was a strong variability of yields of the released oat varieties in each agroclimatic zone: Central – from 0.38 to 2.14 t/ha (V = 60–73%), Zarechnaya – from 0.31 to 3.55 t/ha (V = 41–49%), Srednelenskaya – from 1.51 to 4.66 t/ha (V = 30–36%). The greatest annual decrease in grain yield of oat varieties (by 0.25–0.26 t/ha) was observed in arid agroclimatic zones – Central (Yakutsk SCTS) and Zarechnaya (Megino-Kangalassky SCTS) – compared to the wetter Srednelenskaya zone (Olyokminsky SCTS – by 0.10 t/ha). More significant influence on the yield in the Central and Zarechnaya zones was made by precipitation and HTC of the growing season (r = 0.77...0.84), in the Srednelenskaya zone – by temperature (r = – 0.79). Negative effect of temperature on the yield in the Central zone was observed in June (r = – 0.83), Zarechnaya zone - in July (r = – 0.83), in the Srednelenskaya zone – in August (r = –0.86). Precipitation and HTC had the greatest influence on the yield in the Central zone in June and July (r = 0.56...0.59), Zarechnaya zone – July and August (r = 0.60...0.76). In the Srednelenskaya zone the relationship of the yield with precipitation and HTC in June and July was positive (r = 0.23...0.37), in August – negative (r = – 0.57...– 0.71). Significant variability in grain yields of the released oat varieties indicates the variability of weather conditions and the need to cultivate oat varieties that provide a more stable yield in different agroclimatic zones of Yakutia.

Yield Gap Analysis of Super High-Yielding Rice (>15 t ha−1) in Two Ecological Regions

Super high-yielding rice (SHYR) (>15 t ha−1) plays a crucial role in global food production and security. We hypothesized that the external environment of different ecological regions could improve biomass accumulation in different periods and thus increase the rice yield. Two SHYR varieties, i.e., Xiangliangyou900 (XLY900) and Yliangyou900 (YLY900), were cultivated in the YONGSHENG and LONGHUI ecoregions, China. The results indicated that the average yield of the two SHYRs in the LONGHUI ecological region was 15.27–15.45 t ha−1 and 18.81–20.10 t ha−1 in YONGSHENG. The high grain yield in the YONGSHENG ecoregion was mainly due to the increased number of spikelets per panicle, crop growth rate, and total biomass during the transplanting–heading stage (TP-HS) and heading–maturity stage (HS-MS), and harvest index. The yield of SHYR was significantly correlated with external environment conditions, i.e., average minimum temperature, average daytime, and night-time temperature, and average daily temperature at the TP-HS, HS-MS, and transplanting–maturity (TP-MS) stages. The rice yield was significantly and positively correlated with the cumulative daily radiation. Therefore, it can be concluded that the final yield of super high-yield rice is closely related to the utilization of temperature and radiation resources during the growth process in the ecological environment.

Betaine addition to the diet alleviates intestinal injury in growing rabbits during the summer heat through the AAT/mTOR pathway

BackgroundThe aim of this experiment was to investigate the effect of different levels of betaine (Bet) inclusion in the diet on the intestinal health of growing rabbits under summer heat. A total of 100 weaned Qixing meat rabbits aged 35 d with body weight of 748.61 ± 38.59 g were randomly divided into 5 treatment groups: control group (basal diet) and Bet groups (basal diet + 0.75, 1.0, 1.5 or 2.0 g/kg Bet). The average daily temperature in the rabbitry during the experiment was 30.48 °C and the relative humidity was 69.44%.ResultsDietary addition of Bet had no significant effect on growth performance and health status of growing rabbits (P > 0.05), but it increased ileal secretory immunoglobulin A content compared to the control under summer heat (P < 0.05). Addition of 0.75 g/kg Bet up-regulated jejunal IL-4, down-regulated ileal TNF-α expression (P < 0.05). The addition of 1.0 g/kg Bet increased the villi height (VH) in the jejunum (P < 0.05). Serum glucose levels were reduced, and the expression of SLC6A20 was up-regulated in jejunum and ileum of rabbits fed with 1.5 g/kg Bet (P < 0.05). When added at 2.0 g/kg, Bet reduced serum HSP70 content, increased jejunal VH, and up-regulated duodenal SLC7A6, SLC38A2, mTOR and 4EBP-2 expression (P < 0.05). Correlation analysis revealed that intestinal mTOR expression was significantly and positively correlated with SLC7A6, SLC38A2, SLC36A1 and IL-4 expression (P < 0.05).ConclusionsDietary addition of Bet can up-regulate the expression of anti-inflammatory factors through the AAT/mTOR pathway, improve the intestinal immune function, alleviate intestinal damage in growing rabbits caused by summer heat, and improve intestinal health.

Physical and mechanical properties of grain of spring barley varieties in the conditions of Tatarstan

The aim of the work is to analyze the physical and mechanical properties of grain of spring barley varieties cultivated in the conditions of the Predkamsk zone of the Republic of Tatarstan. The research was conducted in Tatarsky Research Institute of Agriculture FRC of Kazan Research Center RAS in 2015–2022. In the conditions of the Predkamsk zone, on average over the years of research, the late maturing variety Endan was characterized by reliably high values of 1000 grain weight (48.5 g), the early maturing variety Kamashevsky – reliably high values of natural grain weight (686, 3 g/l), convergence from 2.8 x 20 mm sieve (33.9 %) and coarseness (70.02 %), medium maturing variety Raushan – higher variability in 1000 grain weight (18.6 %), convergence from 2.8 and 2.5 x 20 mm sieves (55.6 and 29.7 %, respectively) and coarseness (39.5 %). The direct dependence of the mass of 1000 grains, runoff from the sieve 2.8 x 20 mm and coarseness on the sum of precipitation (r = 0.41/0.58/0.56, respectively), GTC (r = 0.40/0.58/0.55, respectively) and inverse dependence of these physical and mechanical properties on the average daily air temperature (r = -0.51/-0.62/-0.63, respectively) of the interphase period "earing-full ripeness" were established at 1% significance level. Judging by the value of the coefficient of determination (r2), the most closely related to the average daily air temperature are the signs "mass of 1000 grains", "drift from the sieve 2.8 x 20 mm" and "coarseness". The analysis of path coefficients revealed a high direct positive contribution (0.87) of 2.8 x 20 mm sieve runoff and an average direct positive contribution (0.43) of 2.5 x 20 mm sieve runoff to grain yield. Under the conditions of the Predkamsk zone, the prevailing contribution to the total variance of the traits "drift from the sieve 2.8 x 20 mm", "coarseness", "weight of 1000 grains", "bulk grain weight", "drift from the sieve 2.5 x 20 mm" was made by the factor "year", which accounted for (in descending order) 81.7...80.3...76.6...76.2. 68.7 %, respectively.

Seasonal Variations in the Toughness of Leaves: A Case Study Using Griselinia littoralis.

Potential effects of climate change include greater extremes of temperature and increased severity of storms. Many plants have evolved to resist the challenges of winter (freezing, dehydration, and wind) in a process known as cold hardening. Sensing reducing temperatures, they make structural changes at the cellular level to increase their mechanical resistance and prevent damage. Previous work on this topic, though extensive, has been conducted under laboratory conditions rather than in the field, and while many workers have observed changes to cell wall thickness and composition, which imply increased mechanical strength, few have actually measured strength or any other parameter describing structural integrity. This paper describes experiments on a model system designed to measure the structural integrity of leaf laminae from plants growing naturally in the field over extended periods, allowing seasonal variations to be captured. Standard engineering properties-tensile strength and fracture toughness-were measured for leaves of Griselinia littoralis on 19 separate occasions over a 12-month period. Toughness (rather than strength) was found to be the controlling mechanical property. Toughness values were found to change significantly during the year, by more than a factor of 2. Toughness correlated strongly with average daily soil temperature, but with a lag of about 1-2 weeks, suggesting that this is the time needed for structural adjustments to take place. Highest toughness values occurred in winter, confirming cold hardening. Increasing temperature in the spring was associated with decreasing toughness, but in the summer, when highest temperatures occurred, toughness increased again. This apparent "hot hardening" may be a response to dehydration. Results imply that a given leaf is able to both increase and decrease its toughness in response to temperature changes, demonstrating excellent plasticity of response. This case study of a single species establishes a method of reliably measuring changes in a plant's structural integrity due to cold hardening and other seasonal variations, which may be used to investigate the effects of climate change and other variables.

Composting reduces the risks of resistome in beef cattle manure at the transcriptional level.

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in terms of the abundance of antibiotic resistance genes (ARGs), the number of ARG subtypes, and the prevalence of high-risk ARGs (i.e., mobile ARGs associated with zoonotic pathogens). DNA and transcript contigs show that the pathogen hosts of high-risk ARGs included Escherichia coli O157:H7 and O25b:H4, Klebsiella pneumoniae, and Salmonella enterica. Although the average daily temperatures for the entire composting pile exceeded 55°C throughout the field study, more ARG and ARG transcripts were removed at the center of the composting pile than at the surface. This work demonstrates the advantage of composting over stockpiling in reducing ARG risk in active populations in beef cattle manure.IMPORTANCEProper treatment of manure before land application is essential to mitigate the spread of antibiotic resistance in the environment. Stockpiling and composting are two commonly used methods for manure treatment. However, the effectiveness of composting in reducing antibiotic resistance in manure has been debated. This work compared the ability of these two methods to reduce the risk of antibiotic resistance in beef cattle manure. Our results demonstrate that composting reduced more high-risk resistance genes at the transcriptomic level in cattle manure than conventional stockpiling. This finding not only underscores the effectiveness of composting in reducing antibiotic resistance in manure but also highlights the importance of employing RNA analyses alongside DNA analyses.

УРОЖАЙНОСТЬ СРЕДНЕСПЕЛЫХ СОРТОВ ЯРОВОЙ МЯГКОЙ ПШЕНИЦЫ В РАЗЛИЧНЫХ ПРИРОДНО-КЛИМАТИЧЕСКИХ ЗОНАХ КРАСНОЯРСКОГО КРАЯ

The objective of the study is to investigate the yield of mid-season varieties for the period 1999–2000 in different natural and climatic zones of the Krasnoyarsk Region, to identify its relationship with meteorological factors. The yield of 44 mid-season varieties of spring soft wheat was analyzed for the period 1999–2020 on variety plots of the Krasnoyarsk Region in 6 natural and climatic zones: III – lowland sub-taiga (Kazachinsky variety plot), IV – foothill sub-taiga (Dzerzhinsky, Sayansky), V – Kansk-Krasnoyarsk forest-steppe (Sukhobuzimsky, Uyarsky), VI – Prichulymye forest-steppe (Nazarovsky, Uzhursky), VII – southern forest-steppe (Karatuzsky), VIII – foothill steppe on ordinary and southern chernozems (Minusinsky, Krasnoturansky). Only in zone VI, over this period of years, a trend of yield growth was noted from 3.83 (1999–2003) to 4.30 t/ha (2016–2020). Yield fluctuations in the study period were observed in the Kansk-Krasnoyarsk forest-steppe (zone V), with a sharp increase in 2016–2020 (4.80 t/ha) from 2.38 t/ha (2013–2015). The increase in yield here can be explained by the cultivation of intensive varieties in compliance with all technology elements. Instability of yield without a significant increase is typical of the foothill subtaiga (zone IV). Yield growth occurred in natural zone III (lowland subtaiga) from 2008–2012 to 2016–2020 from 1.25 to 2.22 t/ha. Natural zones make the greatest contribution to yield variability – 59.0–74.8 %, while the “years” factor is much less – 1.0–15.0 % and the “genotype” factor is 1.5–5.8 %. A correlation between yield and plant height (r = 0.462–0.552), and 1000-grain weight (r = 0.435–0.650) (Kazachinsky, Karatuzsky, Nazarovsky, Sukhobuzimsky, Uyarsky) was revealed on many variety plots of the region (Kazachinsky, Sayansky, Karatuzsky, Minusinsky, Uzhursky, Sukhobuzimsky). An unequal dependence of the yield of the studied variety plots by ten-day period of the vegetation period on the average daily air temperature, precipitation amount, and relative air humidity was revealed.

Heat and cold waves on the Crimean Peninsula and their impact on population health

BACKGROUND: Climate change has a significant impact on the population health including morbidity and mortality. The studies presented in this paper present characteristics of heat and cold waves on the Crimean Peninsula.&#x0D; AIM: To assess the heat and cold wave characteristics, identify differences in the wave characteristics depending on the coastal and mainland location of climatotherapeutic centers on the Crimean Peninsula.&#x0D; MATERIAL AND METHODS: In our research we used standard statistical data treatment methods. Moreover, data visualization techniques allowed identifying zones of maximum temperature values. Heat and cold waves were defined using the 3rd and the 97th percentiles of the average daily air temperatures. This approach allows considering the intensity and duration of the events under study. Measurements of the surface air temperature included eight observations per day at 19 stations on the Crimean Peninsula for the period from 2006 to 2021. Distribution of the permanently residing population in the Crimea and the city of Sevastopol by age and gender was analyzed using the Rosstat data.&#x0D; RESULTS: As many as 43.5% of the population of the Crimean Peninsula have increased risk of exposure to extreme air temperatures. Having applied the threshold values of the 3rd and the 97th percentiles of the temperature, we identified the periods of heat and cold waves at each station. Even though the Crimean Peninsula has a warm and humid climate, 1 to 4 cold and heat waves have been observed at each station per year. At the same time, the total intensity of cold waves was more than twice the total intensity of heat waves.&#x0D; CONCLUSION: The presented assessment of heat and cold wave characteristics on the Crimean Peninsula, using 3% and 97% percentiles of the distribution of the average daily air temperature over several years, provides the evidence for developing the measures to reduce the negative impact of extreme temperatures on human health on the Crimean Peninsula.

Impact of Temperature and Atmospheric Pressure on Hospitalizations of Patients Presenting With Acute Coronary Syndrome.

This study aims to investigatethe impact of temperature and atmospheric pressure on hospitalizations of patients with acute coronary syndrome (ACS). This is a retrospective, observational, analytical study conducted in a single center, University Hospital Center "Mother Teresa," Tirana, Albania, in the period January-December 2018. This study included 1,165 patients with ACS, who performed urgent coronary angiography, from January 2018 to December 2018. Patients were diagnosed withACS based on clinical and examination findings. The data were collected retrospectively using patient files. Baseline demographic, clinical, and procedural characteristics were collected. Data on atmospheric parameters, measured at the weather monitoring station, were obtained from the National Meteorological Service database. Measurements from the meteorological service provided values ​​for each parameter: average daily temperature and atmospheric pressure in each country district. Atmospheric data measurements were taken for the day under review. The number of inhabitants for the respective districts is taken from the National Institute of Statistics (INSTAT). The study involved 1,165 patients, with a mean age of 63.1 years, ranging from 27 years to 89 years old. The majority of patients (78.6%) were male, while 21.4% were female. A statistically significant relationship was observed between seasonal changes in temperature and atmospheric pressure concerning the number of cases with ACS; the autumn season prevails with 27.9% of the total cases, followed by the spring season with 25.6%, the summer season with 24.2%, and winter season with 22.3% (p = 0.04). Additionally, significant changes in the average monthly values ​​of temperature and atmospheric pressure were accompanied by a statistically significant increase in the number of cases as occurred in March-April and October-November (p ≤ 0.05). Most cases in the cold period (November-March) occurred on days with a change in temperature or atmospheric pressure with a statistically significant value of p < 0.05. An important relationship between seasonal, monthly, and daily changes in temperature and atmospheric pressure concerning the frequency of cases with ACS was observed.

An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems

AbstractDeep Reinforcement Learning (DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers (RBCs), but it still lacks scalability and generalisation due to the necessity of using tailored models for the training process. Transfer Learning (TL) is a potential solution to address this limitation. However, existing TL applications in building control have been mostly tested among buildings with similar features, not addressing the need to scale up advanced control in real-world scenarios with diverse energy systems. This paper assesses the performance of an online heterogeneous TL strategy, comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and Python. The study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage (TES). The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems, different building envelope features, occupancy schedule and boundary conditions (e.g., weather and price signal). The TL approach incorporates model slicing, imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target buildings. Results show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL controllers. Moreover, online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to RBC. Conversely, online TL achieves worse performance compared to offline DRL in either transductive or inductive settings. However, offline Deep Reinforcement Learning (DRL) agents should be trained at least for 15 episodes to reach the same level of performance as the online TL. Therefore, the proposed online TL methodology is effective, completely model-free and it can be directly implemented in real buildings with satisfying performance.

Climate Adaptation through Trade: Evidence and Mechanism from Heatwaves on Firms' Imports

Firms can adapt causally to heat waves by altering their import behaviors. Utilizing matched data from the China Customs Database, the China Industrial Enterprise Database, and the China National Meteorological Science Data Center, this paper investigates variations in firm-level imports on days marked by extreme heat. The study robustly establishes that, in comparison to the temperature range of [12 °C, 15 °C), extreme heat leads to increased imports by industrial firms. Additionally, for each additional day within a month featuring an average daily temperature falling within the ranges [24 °C, 27 °C), [27 °C, 30 °C), or [30 °C, +∞), monthly imports for firms increase cumulatively by 0.35%, 0.57%, and 0.56%, respectively. Notably, the impact of hot weather on non-state-owned labor-intensive firms is particularly pronounced. Our mechanistic analysis suggests that firms resort to heightened imports as a strategy for adapting to the warming climate, mitigating the elevated domestic production costs identified in existing studies. These findings bear relevance to the formulation of future “bottom-up” climate adaptation policies.

Responses of Yield and Photosynthetic Characteristics of Rice to Climate Resources under Different Crop Rotation Patterns and Planting Methods.

Climate is the most important environmental factor influencing yield during rice growth and development. To investigate the relationships between climate and yield under different crop rotation patterns and planting methods, three typical rotation patterns (vegetable-rice (V), rape-rice (R), and wheat-rice (W)) and two mechanical planting methods (mechanical transplanting (T1) and mechanical direct seeding (T2)) were established. The results showed that compared to the V rotation pattern, the average daily temperature (ADT) during the sowing to heading stage increased under both R and W rotation patterns, which significantly shortened the growth period. Thus, the effective accumulated temperature (EAT), photosynthetic capacity, effective panicle (EP), and spikelet per panicle (SP) under R and W rotation patterns significantly decreased, leading to reductions in grain yield (GY). VT2 had a higher ratio of productive tillers (RPT), relative chlorophyll content (SPAD), leaf area index (LAI), and net photosynthetic rate (Pn) than those of VT1, which significantly increased panicle dry matter accumulation (DMA), resulting in an increase in GY. Although RT2 and WT2 had a higher RPT than those of RT1 and WT1, the GY of RT1 and WT1 decreased due to the significant reductions in EAT and photosynthetic capacity. Principal component analysis (PCA) showed that the comprehensive score for different rotation patterns followed the order of V > R > T with VT2 ranking first. The structural equation model (SEM) showed that EAT and ADT were the most important climate factors affecting yield, with total effects of 0.520 and -0.446, respectively. In conclusion, mechanical direct seeding under vegetable-rice rotation pattern and mechanical transplanting under rape-rice or wheat-rice rotation pattern were the rice-planting methods that optimized the climate resources in southwest China.