Air Temperature Research Articles

Optimal Control of Air-Side Economizer

The economizer system is a method of improving energy efficiency through the operating method, which introduces outdoor air through dampers when the outdoor air temperature or enthalpy is lower than the that of the indoor air. The set values used for economizer control include the mixed air temperature and high and low limits. The set values are presented as fixed values in the relevant standards and are controlled to be fixed during actual operation, which may lead to issues such as indoor discomfort, poor indoor air quality, and energy wastage. Therefore, it is necessary to optimize economizer control by determining appropriate set values considering the indoor and outdoor environments. To this end, this paper reviewed the economizer system, control method, control set values, and prediction models in buildings. As a result, it was concluded that optimal economizer control is possible by utilizing a prediction model.

Device to Measure, Monitor and Control Variables for Agricultural Purposes

The measurement of meteorological variables is important for decision-making in the field. Accurate data can help farmers optimize their activities to improve food production. Traditional methods of monitoring variables can be expensive or complex for small-scale farmers to use. This indicates a need for low-cost and user-friendly devices. Currently, there is technology for developing these types of devices, which could be useful to automate processes based on variable monitoring and improve food production. Due to this, a device based on the Arduino Mega<SUP>TM</SUP> board was developed to monitor air temperature, relative humidity, rain, and soil moisture. In addition, equipment was developed to be controlled based on a rain gauge. The device has a TFT touch screen for easy-user interaction and 4 menus for information display (summary, floor, date-time and manual equipment control). The program of the device required more lines of code (59.65%) to establish user-device interaction compared to its internal processes (18.66%) and variable declarations (21.68%). A container was 3D printed to house all the integrated circuits and the device was tested under both indoor (Jun-10, 2024 to July-17, 2024) and outdoor (Jul-22, 2024 to Aug-18, 2024) conditions. Under indoor conditions, a 3% difference was found in the temperature measurements taken under the same conditions (using DS18B20 and MLX90614 sensors). Under outdoor conditions it was found that the air temperature decreased by an average of 2.33°C when increasing the height from 8ft to 16ft and the relative humidity decreased by an average 3.48% when increasing the height from 8ft to 16ft. There was a 3.4% difference in total rain measured by the rain gauges. Finally, the developed device performed adequately during the two months of testing in both conditions, measuring variables and controlling equipment (the equipment went from waiting mode to rain harvesting mode 92 times).

Anopheles gambiae Re-Emergence and Resurgent Malaria Transmission in Eastern Rwanda, 2010-2020.

Rwanda achieved unprecedented malaria control gains from 2000 to 2010, but cases increased 20-fold between 2011 and 2017. Vector control challenges and environmental changes were noted as potential explanations, but no studies have investigated causes of the resurgence or identified which vector species drove transmission. We conducted a retrospective study in four sites in eastern Rwanda that conducted monthly entomological surveillance and outpatient malaria care. We compared sporozoite rates, human blood index (HBI), and relative abundance of the primary vectors, Anopheles gambiae and Anopheles arabiensis, from 2017 to 2020. We then modeled the effects of vector control interventions, insecticide resistance, and temperature changes on species composition and reported malaria incidence. Sporozoite rates were 28 times higher and HBI was four times higher in An. gambiae compared with An. arabiensis. Insecticide-treated bed nets, first distributed nationally in 2010, were associated with decreased An. gambiae relative abundance. However, increased pyrethroid resistance was associated with increased An. gambiae relative abundance and malaria incidence. Epidemic malaria peaks corresponded to periods of model-predicted An. gambiae re-emergence, and increased regional air temperatures during the period were further associated with increased malaria incidence. Indoor residual spraying (IRS), implemented with non-pyrethroid insecticides later in the period, was associated with 86% reductions in An. gambiae relative abundance and 75% reductions in malaria incidence. These findings suggest that increased pyrethroid resistance and the re-emergence of An. gambiae were closely linked to the malaria resurgence in eastern Rwanda. Non-pyrethroid IRS or other control measures that effectively target An. gambiae may help prevent future resurgences.

The spatiotemporal and dependency analysis of selected meteorological parameters and normalized difference vegetation index with aerosol optical depth over east Africa

The unprecedented rise in atmospheric aerosols, coupled with their intricate interactions with the environment through a wide array of physical, chemical, and biological processes, has profoundly impacted global climate. Their presence in the atmosphere scatters and absorbs solar radiation, thus altering the amount of sunlight reaching the Earth's surface. These direct effects, along with the indirect effects of aerosols, have significantly altered atmospheric temperatures, land surface processes, global surface temperature, hydrological cycle, and ecosystems. Understanding the complex interplay between aerosols and climatic variables necessitates a multidisciplinary approach, such as dependency modeling. Addressing these challenges, the current study conducts a spatiotemporal correlational analysis of selected key meteorological parameters with aerosol optical depth over East Africa (EA) using multisensory data from Moderate-resolution Imaging Spectroradiometer (MODIS), Modern-Era Retrospective analysis for Research and Application (MERRA-2) model, and Tropical Rainfall Measurement Mission (TRMM). Employing a weighted least squares regression (WLS) model, the study quantifies trends in the time series of climatic variables and Normalized Difference Vegetation Index (NDVI), further utilizing a statistical dependency modeling technique for correlational analysis. The trend analysis reveals a significant decreasing trend in surface wind speed (SWS) in most months, with sporadic positive trends attributed to anthropogenic activities, notably biomass burning, observed in January. Spatial trend analysis of Precipitation Rate (PR) displays heterogeneity, with significant negative trends in January and March, and positive trends in February, April, November, and December. Negative trends during May to August are attributed to increased anthropogenic activities, while enhanced positive trends in May correlate with low aerosol optical depth (AOD) during this period. Surface air temperature (SAT) exhibits diverse variations across the region, with dry months recording higher averages and trends than wet months. The study notes heterogeneous correlations in NDVI over the study area, with positive and negative correlations observed in different regions. Specifically, positive correlations are noted along the coastal and Lake Victoria regions, attributed to improved PR enhancing vegetation cover in these areas.

Late-Holocene hydroclimatic change and its effect on human activity at Xiada Co on the western Tibetan Plateau

The scarcity of paleoclimate records in the western Tibetan Plateau (TP) hinders our understanding of how environmental evolution affects past human population, agriculture, and animal husbandry. Here, we utilized a range of materials to investigate the impact of climate change on human activities in the Xiada Co basin on the western TP during the Late-Holocene. We presented a continuous compound-specific hydrogen isotope record of sedimentary leaf waxes (δ2Hwax) from a sediment core of Xiada Co, and compared it to XRF core-scanning elements, brGDGT-based mean annual air temperature (MAAT) record, and fecal stanol-based human population proxy record from the same sediment core, as well as archeological evidence from the TP. The δ2Hwax exhibited a sustained increasing trend during the period from 4700 to 900 cal yr BP, followed by a generalized decrease in δ2Hwax values during 900–0 cal yr BP. The multi-proxy analysis of Xiada Co sediments revealed that the δ2Hwax values mainly reflect changes in the ISM precipitation, and are also influenced to some extent by glacier meltwater. Furthermore, a warm and humid climate condition was conducive to human habitation. Appropriate adaptation strategies, such as the herding of cold-tolerant and dry-tolerant sheep and the cultivation of barley in the western TP, led to a surge in population density during 3400–2900 cal yr BP, despite the slightly deteriorated climate background. This study confirmed the importance of choosing the right adaptive strategies to cope with climate change for human survival and development on the Tibetan Plateau.

Seasonal and Climatic Drivers of Wet Deposition Organic Matter at the Continental Scale

AbstractDissolved organic matter (DOM) concentrations and composition within wet deposition are rarely monitored despite contributing a large input of bioavailable dissolved organic carbon (DOC) and nitrogen (DON) to the Earth's surface. Lacking from the literature are spatially comprehensive assessments of simultaneous measurements of wet deposition DOC and DON chemistry and their dependencies on metrics of climate and environmental factors. Here, we use archived precipitation samples from the US National Atmospheric Deposition Program collected in 2017 to 2018 from 17 sites across six ecoregions to investigate variability in the concentration and composition of depositional DOM. We hypothesize metrics of DOM chemistry vary with ecoregion, season, large‐scale climate drivers, and precipitation geographic source. Findings indicate differences in DOC and DON concentrations and loads among ecoregions. The highest wet deposition concentrations are from sites in the Northern Forests and lowest concentrations from sites in Marine West Coast Forests. Summer and autumn samples contained the highest DOC concentrations and DON concentrations that were consistently above detection limit, corresponding with seasonality of peak air temperatures and the phenology of the growing season in the northern hemisphere. Compositional trends suggest lighter DOM molecules in autumn and winter and heavier molecules in spring and summer. Climate drivers explain 51% of variation in DOM chemistry, revealing differing drivers on the concentrations and loads of DOC versus DON in wet deposition. This study highlights the necessity of incorporating DOC and DON measurements into national deposition monitoring networks to understand spatial and temporal feedbacks between climate change, atmospheric chemistry and landscape biogeochemistry.

Influence of climate change on water quality in Terra Nova River basin, Pernambuco, Brazil

Climate changes tend to intensify water scarcity in arid and semi-arid regions, making water management in these areas more challenging, directly influencing hydrological dynamics, causing impacts on ecosystems and society. The Terra Nova River basin is crucial for the water security of the semi-arid region of Pernambuco, especially after the construction of the São Francisco River Integration Project (PISF), which saw the construction of six reservoirs to supply water for human consumption, agricultural, and industrial activities. Therefore, this study aims to analyzes the impacts of climate changes on water quality in the Terra Nova River basin in Pernambuco, using long-term data from the Hydrological Response Unit System for Pernambuco (SUPer). The ARIMA (Autoregressive Integrated Moving Averages) model is employed to predict water quality parameters in climate change scenarios, using data from the Intergovernmental Panel on Climate Change (IPCC) and the Oswaldo Cruz Foundation (Fiocruz). The variables include air temperature, precipitation, dissolved oxygen, nitrogen, and phosphorus. Simulated scenarios were compared with CONAMA No. 357/2005 limits, revealing potential decreases in dissolved oxygen and phosphorus concentrations, alongside an increase in nitrogen concentrations. Irregular rainfall rates, high air temperatures, and evapotranspiration, combined with conflicts by water resources, may exacerbate water access issues in the semi-arid region, worsening the water crisis and threatening water security.

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.

Nanoplastics Distribution during Ice Formation: Insights into Natural Surface Water Freezing Conditions.

The migration characteristics of nanoplastics (NPs) in the natural freezing process are complex and have attracted increasing attention in simulating natural freezing in recent years. However, simulated freezing conditions often fall short of replicating natural freezing processes, and studies on the vertical distribution of NPs remain inadequate. This study established a more realistic simulation of the natural freezing process in surface water by controlling both the air temperature (T1) and the water temperature (T2). Additionally, we introduced a new parameter, the local distribution coefficient (Kiw1), to compare with the effective distribution coefficient (Kiw2). The values of Kiw1 and Kiw2 for PS-500 nm were 0.18 and 0.21, respectively, at T1 = -20 °C and T2 = 1 °C. The results revealed the NPs concentration differed in ice, near-ice liquid, and far-ice liquid. Both properties of NPs and environmental factors could regulate the vertical distribution of NPs. The findings underscored the importance of freezing temperature regulated by T1 and T2, elucidating the roles of various influencing factors on the vertical distribution characteristics of NPs and unraveling the mechanisms of NPs distribution in the ice-water system. This study can provide valuable insights for understanding the migration of NPs in surface water in cold regions.

The Impact of Poor Air Quality on Hospitalisation of Multi-morbid Patients: A Systematic Review

Abstract Background Exposure to poor air quality worsen existing health conditions, particularly amongst vulnerable patients, leading to increased healthcare utilization. We conducted a systematic review to explore the impact of exposure to poor quality on healthcare requirements in multi-morbid patients. Methods We searched six major databases (Medline via Ovid, Embase via Ovid, Web of Science, CINAHL, Global Health, and Scopus) using search terms grouped into sets relating to ‘air pollution,’ ‘multimorbidity,’ “association” and ‘hospitalisation.’ We were interested in the impact of common air pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) and articles were screened independently by two researchers. The review was registered with The International Prospective Register of Systematic Reviews (CRD42022369757) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results A total of nineteen studies were included. All six air pollutants increased hospitalisation amongst multi-morbid patients, especially those with diabetes and cardiovascular comorbidity. Females and the elderly (>65 years old) were the most vulnerable to the effects of air pollution, with an increase in hospitalisations of 9.23% and 6.35% when exposed to PM2.5 and PM10, respectively. Patients >65 years had a higher likelihood of hospitalisation for ischemic and haemorrhagic stroke when exposed to PM2.5 or PM10 at warm season. Patients (≥70 years) who had cardiovascular and pulmonary comorbidity were 3.9% more likely to be hospitalised for a cardiopulmonary event with a rise in NO2 levels. We found an intersectional effect (referred to as “the CADC effect” - Climatic changes, Air pollutant, Demographics, Chronic conditions) that influenced the likelihood of hospitalisation. Conclusions Future research is required to further understand this CADC effect in other high-risk population. Key messages • Females, elderly, those with cardiovascular, and pulmonary comorbidity are at the highest risk of hospitalisation with poor air quality. • The CADC effect explains the intersectional effect between hospitalisation in multimorbid patients, patients demographics and chronic conditions, and air pollution and temperature effects.

Leveraging digital platforms to improve Public Health in hospital smart buildings

Abstract The integration of digital platforms into hospital infrastructure represents a significant leap forward in public health management. This session explores how smart hospital buildings, equipped with advanced digital technologies, can enhance public health outcomes through more effective disease surveillance, improved environmental controls and enhanced patient care management. Smart hospital buildings utilize a range of new technologies such as IoT sensors, AI-driven analytics and big data solutions to monitor and optimize various aspects of hospital operations and care. These technologies enable real-time data collection on environmental conditions, patient health metrics and resource utilization, creating an ecosystem that not only supports the immediate health needs of patients but also contributes to broader public health goals. The session will address four key areas where digital platforms can make an impact: -Disease Surveillance and Management: Digital tools can track health data trends and patterns within hospital settings, enabling early detection of infectious outbreaks and more precise tracking of patient outcomes. -Environmental Monitoring: IoT sensors can continuously assess conditions such as air quality, temperature and humidity, which are critical for preventing hospital-acquired infections and ensuring a safe environment for patients and staff. -Resource Optimization: AI algorithms can analyse data to optimize resource allocation, ensuring that medical supplies and human resources are used efficiently, which is crucial in health emergencies. -Patient-Centred Care: Digital platforms can facilitate personalized patient care through real-time health monitoring and data analysis, ensuring timely medical interventions and better health management. This session will highlight case studies demonstrating successful implementation of digital technologies in smart hospital buildings and discuss the challenges and lessons learned from these initiatives.

IoT-Based Connected Environmental Monitoring System Using NodeMCU

The Connected Environmental Monitoring System leverages the NodeMCU ESP8266 microcontroller in conjunction with various sensors, including the MQ-135, DHT22, BMP280, and a sound sensor, to enable real-time monitoring of critical environmental parameters. This project aims to provide comprehensive insights into air quality, temperature, humidity, atmospheric pressure, and noise levels, fostering awareness and informed decision-making regarding environmental conditions. Data collected by the sensors is transmitted wirelessly to the ThingSpeak cloud platform, where it is stored and visualized through user-friendly dashboards. The system also incorporates alert mechanisms to notify users when specific parameters exceed predefined thresholds, facilitating timely interventions. The modular architecture of the system allows for scalability and flexibility, making it adaptable for various applications, including urban management and smart city initiatives. Overall, this project demonstrates the efficacy of IoT solutions in addressing environmental monitoring challenges, contributing to the development of sustainable practices and enhanced community well-being.

A data-driven framework for the definition of heat in CV research for better comprehension of climate changes on human health

Abstract Background Recent literature has identified numerous combinations of meteorological indicators, methods and comparison thresholds to define heat in order to analyse its impact on adverse cardiovascular (CV) events. In fact, despite increasing attention to the issue due to ongoing climate change, there is no standardised definition of heat nor guidelines for its establishment, and in studies often little attention is given to the selected definition, despite its impact on the results. Purpose To fill this gap, our aim was to propose a data-driven framework for selecting the temperature threshold for defining heat in the context of studies on adverse CV outcomes, combining the most common approaches identified in the literature. Methods The following five-step framework is proposed: 1) Selection of temperature lags based on the contour plot obtained by the distributed lag non-linear model (DLNM); 2) Estimation of the relative risk (RR) of having a CV emergency in heat versus non-heat days by Poisson regression considering the 90th-99th percentile (%ile) of the temperature distribution for each lag; 3) Selection of the final lag based on the curvatures of the 10 included %iles; 4) Calculation of the % change in RR from %ile i to %ile i+1; 5) Selection of the heat threshold, defined as the %ile from which all the next %iles are associated with a higher % change, or, if not existing, the %ile preceding the one with the highest % change. We tested this framework, for each year, on retrospective CV emergencies in May-September 2017-2022 in Milan, Italy, using the apparent temperature data, accounting for air temperature, relative humidity and wind speed. Results The contour plot of the DLNM, controlled for air pollution, seasonality and long-term trend, showed that lags 0 and 1 were characterised by an increased RR for a CV emergency. The RR estimated for each %ile for each considered lag (i.e., heat on day i, heat on day i or on day i-1, and heat on day i and on day i-1), produced a similar curvature, so first lag option was arbitrarily selected. For Milan, the 95th %ile was the point from which all the subsequent %iles were associated to progressively higher % changes, resulting in a RR of having a CV emergency compared to non-heat days equal to 1.113 (95% CI: 1.087-1.139). The mean daily apparent temperature values associated to such %ile, varying from 27.7 °C to 29.9 °C depending on the year, should then be considered as the heat threshold in the examined context. Conclusion We proposed a flexible data-driven framework for the definition of heat that could easily be extended to similar scenarios. Although the framework still requires some arbitrary choices to be made, and the need of validation on other real-world data, it could provide a valuable guideline for relevant research, and could contribute to the standardization of heat definition for CV health research aiming at a better comprehension of climate changes on human health.

Numerical simulation of an innovative design of solar air heater using spiral duct inserts for enhancing thermal efficiency

ABSTRACT An innovative design of solar air heater (SAH) with spiral shape is numerically analyzed in this paper. The spiral-shaped SAH hydro-thermal performance is studied for different air mass flow rates using CFD COMSOL Multiphysics software. The outlet air temperature difference, thermal efficiency, flow structure, thermal field and pressure drop are the main parameters which are considered to estimate the fluid flow and heat transfer behaviors of the SAH. The simulation is realized for 1000 W/m2 of solar heat flux and 25°C of ambient temperature as typical climatic conditions in a middle day. The results show that the maximum outlet temperature difference of the SAH reached 93.08°C with 0.0083 kg/s of air mass flow rate. For the range of 0.0083–0.0332 kg/s, the thermal efficiency is varied from 91.41% to 99.01%. The ambitious percentage of the thermal efficiency of 99.01% was observed for 0.012 kg/s. The proposed design provides high thermal efficiency of SAH compared to other configurations of SAH.

Challenges posed by climate hazards to cardiovascular health and cardiac intensive care: implications for mitigation and adaptation.

Global warming, driven by increased greenhouse gas emissions, has led to unprecedented extreme weather events, contributing to higher morbidity and mortality rates from a variety of health conditions, including cardiovascular disease (CVD). The disruption of multiple planetary boundaries has increased the probability of connected, cascading, and catastrophic disasters with magnified health impacts on vulnerable populations. While the impact of climate change can be manifold, non-optimal air temperatures (NOTs) pose significant health risks from cardiovascular events. Vulnerable populations, especially those with pre-existing CVD, face increased risks of acute cardiovascular events during NOT. Factors such as age, socio-economic status, minority populations, and environmental conditions (especially air pollution) amplify these risks. With rising global surface temperatures, the frequency and intensity of heatwaves and cold spells are expected to increase, emphasizing the need to address their health impacts. The World Health Organization recommends implementing heat-health action plans, which include early warning systems, public education on recognizing heat-related symptoms, and guidelines for adjusting medications during heatwaves. Additionally, intensive care units must be prepared to handle increased patient loads and the specific challenges posed by extreme heat. Comprehensive and proactive adaptation and mitigation strategies with health as a primary consideration and measures to enhance resilience are essential to protect vulnerable populations and reduce the health burden associated with NOTs. The current educational review will explore the impact on cardiovascular events, future health projections, pathophysiology, drug interactions, and intensive care challenges and recommend actions for effective patient care.

Integrated Anomaly Detection and Early Warning System for Forest Fires in the Odisha Region

The present study aims to develop a random forest algorithm-based classifier to predict the occurrence of fire events using observed meteorological parameters a day in advance. We considered the skin temperature, the air temperature close to the surface, the humidity close to the surface level, and soil moisture as important meteorological factors influencing forest fire occurrence. Twenty additional parameters were derived based on these four parameters that account for the energy exchanged in sensible and latent forms and the change in parameters in recent trends. We used the mutual information approach to identify critical meteorological parameters that carry significant information about fire occurrence the next day. The top nine parameters were then fed as input to the random forest algorithm to predict fire/no fire the next day. The weighted data sampling and SMOTE techniques were employed to address the class imbalance in the fire data class. Both techniques correctly classified fire incidents well, given the meteorological input from the previous days. This study also showed that as the class imbalance increases to 1:9, the performance based on the precision, recall, F1 score, and accuracy are maximum, showing the model’s ability to perform with class imbalance. Both techniques helped the random forest algorithm forecast fire instances as the data sample size increased.

Mangrove freeze resistance and resilience across a tropical‐temperate transitional zone

Abstract Freeze events govern the distribution and structure of mangrove ecosystems, especially in tropical‐temperate transitional zones. Understanding mangrove responses to freezing is crucial for predicting their poleward expansion under climate change. However, there is a need for field‐based measurements of mangrove freeze resistance and resilience. After an extreme winter storm in December 2022, we measured mangrove post‐freeze damage and recovery (January and November 2023), building on a pre‐freeze baseline assessment conducted in July 2022 across 12 sites along the temperature gradient of Florida's Gulf of Mexico coast (USA). Low‐temperature thresholds for leaf damage to Avicennia germinans, Rhizophora mangle and Laguncularia racemosa were quantified near −6, −4 and − 4°C, respectively. Thresholds for mortality were found to be near −6 to −7°C for A. germinans and −4 to −5°C for R. mangle. A threshold for loss of reproductivity in A. germinans was identified near −6 to −7°C. Resprouting was observed in all three species but limited to just one individual for R. mangle. Surviving A. germinans resprouted vigorously and had the greatest number of resprout branches, which was proportional to leaf damage. Tall A. germinans had a higher resprout percentage than short trees. Strata‐specific differences in freeze damage were most pronounced for R. mangle, with higher damage in tall versus short trees, while no difference was found between A. germinans strata. These results suggest that R. mangle population recovery may depend on the growth of short trees, while A. germinans can recover from all strata. Minimum air temperature was strongly correlated with mangrove height and above‐ground biomass. Projections of future minimum temperature and species‐specific freeze degree days predict warming winters, suggesting further mangrove development and range expansion under climate change. Synthesis: Collectively, our study advances understanding of mangrove responses to freezing and identifies low‐temperature thresholds for each species, aiding predictions of mangrove range expansion.

Research on the Green Construction Technology of Stilt Houses Based on the Climate Adaptation of Transitional Seasons

Stilt houses are extremely adaptable to terrain and climate. However, current indoor thermal environment research in transitional seasons is not prominent. Therefore, in this research, a typical stilt house in southwest China was chosen as the research object and analyzed by combining Climate Consultant climate analysis software and field measurement data. The results showed that the indoor thermal stability of a stilt house was excellent during the transition season, and the attic had the most obvious climate regulation, with the maximum temperature difference between indoors and outdoors being 9 °C when the outdoor temperature was the highest. The difference between the mean radiant temperature and the average air temperature was only 0.04 °C, and the radiant effect of the enclosure on the interior was small. The indoor relative humidity ranged from 63.2% to 85.1%, showing high relative humidity, but the fluctuation was relatively stable. Stilt floors did not play a significant role in climate regulation during the transition season, and the semi-open space structure was more prone to moisture accumulation when the outdoor humidity was high. Regarding practical application, the climate adaptation strategies of shading, cooling, and dehumidification were applied in the transition season, but dehumidification was ineffective.

Detection of changes in local-scale statistical distribution of daily temperature and precipitation in dryland region: a case study of Ningxia, China

Identifying alterations in the local-scale statistical distributions of daily temperature indices and precipitation is crucial for adapting to climate change and combating desertification in arid regions. This study focuses on Ningxia, a representative dryland area in China, where we investigated changes in the statistical distributions of daily temperature and precipitation across ten weather stations over two 30-year periods: 1991–2020 compared to 1961–1990. From 1961 to 2020, annual air temperature indices (mean, maximum, and minimum) exhibited a significant upward trend at all ten weather stations (P < 0.05). Specifically, when comparing the decades of 1961–1970 with those of 2001–2020, annual air temperature indices increased by 1.2–2.2 °C for annual air temperatures, by 0.91–1.97 °C for maximum air temperature, and by 1.26–3.28 °C for minimum air temperature; these corresponded to rates of increase ranging from 0.20–0.40 °C per decade for mean air temperatures, from 0.15–0.33 °C per decade for maximum air temperatures, and from 0.21–0.55 °C per decade for minimum air temperatures, respectively during this period. The observed differences in the statistical distributions of daily temperature indices between the two periods were statistically significant (P < 0.05), indicating an increase rate of approximately 1 °C during the period from 1991 to 2020 relative to that from 1961 to 1990 across various weather stations. In contrast, there were no significant increasing or decreasing trends in annual precipitation (P > 0.05). Similarly, the changes in statistical distributions of daily precipitation also did not reach a significance level (P > 0.05) when comparing data from both periods within these stations. Furthermore, the correlation coefficients between daily temperature indices and daily precipitation have decreased across these stations during the later period compared to earlier years. These findings suggest that while there has been a notable shift toward higher values in the statistical distribution of daily temperature indices—indicating rising temperatures—the corresponding distribution patterns for daily precipitation have remained relatively stable between these time frames. Consequently, this research confirmed an escalation in localized drought conditions within certain dryland areas despite broader regional trends toward humidification observed over recent decades; thus implying an increased risk of desertification as aridity intensifies.

Climatic and edaphic controls of root-tip production and mortality in five temperate tree species

Root tips are the main components of absorptive fine roots, but their seasonal dynamics and relationship to environmental factors remain unclear due to the difficulties in methodology. In this study, we explored the temporal patterns of root-tip production and mortality in monoculture plantations of five temperate tree species at a common site in northeastern China, and identified the general environmental controls on such processes. We made monthly in-situ assessments of root tip length (RTL) production and mortality in two hardwood and three coniferous species with a minirhizotron (MR) method during the growing seasons of 2008 and 2009. Air temperature, rainfall, soil temperature and water content at 10 cm depth were determined concurrently. RTL production in all species exhibited consistent peaks in summer (June–August) in two growing seasons. RTL mortality showed substantial interannual and interspecific variability, with peaks in autumn and winter in 2008, but various patterns in 2009. RTL production positively correlated with monthly soil and air temperature across all species, and with monthly rainfall in three coniferous species. However, there was no significant correlation between RTL production and soil water content. By contrast, RTL mortality was weakly related to environmental factors, showing positive correlations with soil temperature in Korean spruce, and with rainfall in Korean pine and Korean spruce. Our findings suggest that the seasonal patterns of RTL production are convergent across the five temperate tree species due to the overlapped distribution of heat and rainfall, which can conduce roots to maximizing the acquisition of nutrient resources in the soil.