Cold Weather Research Articles

Survival of Calliphora vicina (Diptera: Calliphoridae) embryos under cold temperature conditions: forensic implications.

Most blow flies (Diptera: Calliphoridae) species are sarcosaprophagous during the larval stage, primarily feeding on the soft tissues of carcasses during the early stages of decomposition, making them valuable forensic indicators for minimum post-mortem interval (minPMI) estimations. Like other insects, their developmental rates are strongly influenced by the environmental temperature. Although several studies have examined the influence of temperature on the development of different blow fly species, the impact of cold temperatures remains largely unstudied, despite its potential forensic implications. The present study investigates the effect of three cold temperatures (0, -2.5 and -5°C) on the survival of Calliphora vicina embryos of five different ages (0%, 20%, 40%, 60% and 80% of the total embryonic development) and two exposure times (6 and 24 h). Our results revealed significant differences in egg survival at the earliest embryonic stages (0% and 20% of the total embryonic development), resulting in high mortality rates. While at 20% of the total embryonic development high mortality was only observed under -5°C, at 0% of the total embryonic development high mortality rates were observed at all the temperatures tested. Although C. vicina embryos demonstrate tolerance to cold temperatures once they have completed the first 20% of the total embryonic development, potentially mitigating the impact of cold weather events, the possibility of minPMI underestimations due to the death of the first egg batches should not be disregarded. Additionally, considering that the embryonic development stages may last for several days under low temperatures, caution should be taken in the analysis of entomological evidence if a cadaver is discovered following cold weather episodes.

Investigating the impact of extreme weather events and related indicators on cardiometabolic multimorbidity

BackgroundThe impact of weather on human health has been proven, but the impact of extreme weather events on cardiometabolic multimorbidity (CMM) needs to be urgently explored.ObjectivesInvestigating the impact of extreme temperature, relative humidity (RH), and laboratory testing parameters at admission on adverse events in CMM hospitalizations.DesignsTime-stratified case-crossover design.MethodsA distributional lag nonlinear model with a time-stratified case-crossover design was used to explore the nonlinear lagged association between environmental factors and CMM. Subsequently, unbalanced data were processed by 1:2 propensity score matching (PSM) and conditional logistic regression was employed to analyze the association between laboratory indicators and unplanned readmissions for CMM. Finally, the previously identified environmental factors and relevant laboratory indicators were incorporated into different machine learning models to predict the risk of unplanned readmission for CMM.ResultsThere are nonlinear associations and hysteresis effects between temperature, RH and hospital admissions for a variety of CMM. In addition, the risk of admission is higher under low temperature and high RH conditions with the addition of particulate matter (PM, PM2.5 and PM10) and O3_8h. The risk is greater for females and adults aged 65 and older. Compared with first quartile (Q1), the fourth quartile (Q4) had a higher association between serum calcium (HR = 1.3632, 95% CI: 1.0732 ~ 1.7334), serum creatinine (HR = 1.7987, 95% CI: 1.3528 ~ 2.3958), fasting plasma glucose (HR = 1.2579, 95% CI: 1.0839 ~ 1.4770), aspartate aminotransferase/ alanine aminotransferase ratio (HR = 2.3131, 95% CI: 1.9844 ~ 2.6418), alanine aminotransferase (HR = 1.7687, 95% CI: 1.2388 ~ 2.2986), and gamma-glutamyltransferase (HR = 1.4951, 95% CI: 1.2551 ~ 1.7351) were independently and positively associated with unplanned readmission for CMM. However, serum total bilirubin and High-Density Lipoprotein (HDL) showed negative correlations. After incorporating environmental factors and their lagged terms, eXtreme Gradient Boosting (XGBoost) demonstrated a more prominent predictive performance for unplanned readmission of CMM patients, with an average area under the receiver operating characteristic curve (AUC) of 0.767 (95% CI:0.7486 ~ 0.7854).ConclusionsExtreme cold or wet weather is linked to worsened adverse health effects in female patients with CMM and in individuals aged 65 years and older. Moreover, meteorologic factors and environmental pollutants may elevate the likelihood of unplanned readmissions for CMM.

TRNSYS modelling and feasibility study of natural gas absorption heat pump (GAHP) for Canadian homes

An investigation was conducted to explore the potential use of a Natural Gas Absorption Heat Pump (GAHP) for heating and cooling. This investigation involved experiments and simulations using TRNSYS software. In the experimental and modelling study, a working fluid comprising a solution of 50% Propylene Glycol (PG) and water was utilized to prevent freezing in the system’s primary loop, which is exposed to extreme cold weather conditions. The data from the experimental study was utilized to develop performance curves used in the system simulations. TRNSYS simulations were conducted to predict the performance behaviour of the system under different operating and climatic conditions. The results of the analysis indicate that the GAHP can be a substitute in areas where natural gas is the primary heating fuel. However, it was noted that the GAHP’s capacity, Gas Utilization Efficiency (GUE), and Coefficient of Performance (COP) were significantly lower during the heating and cooling seasons. It was observed that the heating GUE values ranged from 0.53 to 0.64, and cooling GUEs ranged from 0.32 to 0.38. These GUE values are significantly lower than anticipated for this technology per system specifications. Furthermore, the lower performance of the GAHP operation in Canada is attributed to extremely cold conditions, excessive cycling, and part-load performance. It was concluded that optimizing the control system is necessary to improve the practicality of GAHP in Canada.

Characterizing Spatiotemporal Patterns of Disasters and Climates to Evaluate Hazards to Crop Production in Taiwan

Climate change causes frequent and severe disasters. A comprehensive assessment of disaster hazards is thus crucial to understanding variations in disaster patterns and planning mitigation and adaptation strategies. This study obtained information from a crop disaster dataset of Taiwan covering the period from 2003 to 2022. Additionally, principal component analysis and K-means clustering were used to create climate clusters to evaluate the effect of climate patterns on disaster hazards. The results revealed that tropical storm frequency substantially decreased, whereas rain disasters exhibited an increasing trend. The four regions of Taiwan exhibited variations in terms of hazards of various disasters. The cold wave hazard showed a significant upward trend in the central region. An upward trend of rain disaster hazards was only detected in the southern region. However, a downward trend in tropical storm hazards was detected across all regions. A distinct climate pattern was identified over the study period. After 2012, high temperature and dry climate were the primary climate patterns. These patterns exhibited a high hazard value for cold waves, droughts, and rain disasters. Hence, the present study’s findings indicate that managing cold waves and rain disasters is crucial to protecting crop production in Taiwan.

Extreme temperatures, PM2.5 and trajectories of impaired thyroid hormone sensitivity: A longitudinal study of patients with schizophrenia

BackgroundThe climate change scenario has witnessed an increase in extreme temperature events (ETEs), including heat waves and cold spells, and a heightened occurrence of compounding with fine particulate matter (PM2.5). However, the impact of this phenomenon on the sensitivity to thyroid hormones (THs) in humans is unclear, especially in a group as specific as schizophrenia. MethodsA longitudinal study was constructed using longitudinal measurements of thyroid function in schizophrenia in the Anhui Mental Health Center. The latent growth mixture model was applied to assess the optimal trajectory of change in impaired THs sensitivity. We then used logistic regression to explore associations between heat waves, cold spells, and PM2.5 with impaired THs sensitivity trajectories in the total population and different gender and age subgroups. Furthermore, the effect of the frequency, intensity, and duration of ETEs in the above associations was explored, as well as an assessment of the interaction between ETEs and PM2.5. ResultsAmong 931 participants, we identified two classifications of trajectories of impaired THs sensitivity: “Low-stable” (n = 836, 89.80 %) and “Rise-slight down” (n = 95, 10.20 %). Logistic regression showed significant associations between each additional day of heat waves (≥3 days with temperature thresholds above the 95th percentile) and cold spells (≥3 days with temperature thresholds below the 5th percentile) and “Rise-slight down” trajectory, with odds ratios (95 % confidence intervals) of 1.06 (1.02, 1.10) and 1.19 (1.14, 1.24), respectively, and the strength of this association increased with the intensity and duration of ETEs. Subgroup analyses indicated that the association was more pronounced in males and the age group above 40 years. Furthermore, PM2.5 was found to interact with heat waves, with high concentrations exacerbating the effects of heat waves. ConclusionsOur findings suggest that mitigating both ETEs and PM2.5 exposures may bring health co-benefits in preventing thyroid impairment in schizophrenia.

Body Mass Index as Effect Modifier of Heatwave and Cold Spell Mortalities: Longitudinal Study in China

Body Mass Index as Effect Modifier of Heatwave and Cold Spell Mortalities: Longitudinal Study in China

CRISPR/Cas9-mediated genome editing of OsCS511 enhances cold tolerance in Oryza sativa L.

The frequency of climate change is increasing globally, which makes predictions challenging. Cold spells during the rice seedling stage can significantly reduce yield, prompting a constant need for cold-tolerant cultivars, which is a major breeding goal. However, the traditional crossbreeding of rice cultivars requires substantial time and effort. Recently, the application of CRISPR/Cas9 to reduce defects in elite cultivars has become a more cost-effective and time-efficient method for breeding cultivars than cross-breeding methods and can alleviate food insecurity. In the present study, CRISPR/Cas9-mediated genome editing was performed for OsCS511 a gene involved in cold susceptibility, identified using quantitative trait loci (QTL) mapping in Ilmi (Oryza sativa L. spp. Japonica cv. Ilmi). In Ilmi, CRISPR/Cas9 tool-edited OsCS511 homozygous lines were used in T0 and advanced generations in the field. CRISPR/Cas9 induced variations in the DNA sequence and plants with insertions or deletions compared to OsCS511 of Ilmi were selected as genome-edited lines. Agricultural traits, reactive oxygen species scavenging capacity, and stress-tolerance-related gene expression levels were evaluated under normal and cold stress conditions. Under normal conditions, all traits evaluated in the Ilmi and OsCS511 genome-edited lines exhibited similar results; however, when subjected to cold stress, the cold tolerance of OsCS511 genome-edited lines improved or reached the same level as that of Ilmi. OsCS511 genome-edited lines recovered and survived. From a breeding perspective, we suggest that CRISPR/Cas9 technology can precisely reduce defects in existing superior rice cultivars with high efficiency and speed.

Temperature Control and Crack Prevention of High RCC Dam in Cold and Drought Area

A development process is introduced for a computation program to calculate the temperature and stress field of mass concrete based on the ANSYS® platform. The temperature control scheme of a high roller compacted concrete (RCC) dam in northern Xinjiang is optimized by using the simulation program. It is suggested that the concrete pouring temperature of the dam should not exceed 16°C and that water-pipe cooling should be adopted. The dam should be permanently heat preserved by 10 cm thick extruded polystyrene (XPS) extruded panels, and the top surface of the overwintering layer should be covered with an at least 14 cm thick thermal insulation quilt. During construction, the warehouse surface should be temporarily insulated with a 2 cm thick thermal insulation quilt. The causes of cracks in a particular dam section are simulated and analysed, and it is concluded that the cracks are mainly caused by the lack of thermal insulation of the warehouse surface during cold spells.

Increased Risk of Influenza Infection During Cold Spells in China: National Time Series Study.

Studies have reported the adverse effects of cold events on influenza. However, the role of critical factors, such as characteristics of cold spells, and regional variations remain unresolved. We aimed to systematically evaluate the association between cold spells and influenza incidence in mainland China. This time series analysis used surveillance data of daily influenza from 325 sites in China in the 2014-2019 period. A total of 15 definitions of cold spells were adopted based on combinations of temperature thresholds and days of duration. A distributed lag linear model was used to estimate the short-term effects of cold spells on influenza incidence during the cool seasons (November to March), and we further explored the potential impact of cold spell characteristics (ie, intensity, duration, and timing during the season) on the estimated associations. Meta-regressions were used to evaluate the modification effect of city-level socioeconomic indicators. The overall effect of cold spells on influenza incidence increased with the temperature threshold used to define cold spells, whereas the added effects were generally small and not statistically significant. The relative risk of influenza-associated with cold spells was 3.35 (95% CI 2.89-3.88), and the estimated effects were stronger during the middle period of cool seasons. The health effects of cold spells varied geographically and residents in Jiangnan region were vulnerable groups (relative risk 7.36, 95% CI 5.44-9.95). The overall effects of cold spells were positively correlated with the urban population density, population size, gross domestic product per capita, and urbanization rate, indicating a sterner response to cold spells in metropolises. Cold spells create a substantial health burden on seasonal influenza in China. Findings on regional and socioeconomic differences in the health effects of cold spells on seasonal influenza may be useful in formulating region-specific public health policies to address the hazardous effects of cold spells.

Assessing classroom ventilation rates using CO2 data from a nationwide study of UK schools and identifying school-wide correlation factors

Per-person ventilation rates were assessed from data measured in 322 UK schools throughout the Autumn term, 2023. It was found that the overall mean ventilation rate was 5.3 L s−1 p−1; rising to 6.8 L s−1 p−1 during warmer weather and falling to 3.8 L s−1 p−1 during colder weather. Daily mean CO2 levels recorded in the majority of schools consistently fell below the 1500 ppm threshold within government school ventilation guidance but the contribution of relatively few very high CO2 levels in some classrooms shows the need for targeted improvement and highlights the value of large-scale datasets. Exceedance of the 1500 ppm threshold rose to approximately 20% when the daily mean outdoor temperature fell to around 5 °C, indicating a barrier to ventilation. Controlling for outdoor temperature as a covariate, analysis of the CO2 measurements indicated schools in more-deprived regions, state-funded schools (relative to private), and secondary schools (relative to primary) exhibited statistically-significant higher CO2 concentration. Reassuringly, these findings remained unchanged when the analysis was deployed on estimated per-person ventilation rates; except that this enhanced analysis accounted for the greater CO2 production associated with older children and demonstrated that ventilation rates were not significantly different between primary and secondary schools.

Preparation and properties of an anti-icing and de-icing emulsified asphalt coating containing RTV and CNTs

In regions experiencing cold weather, road icing poses significant challenges to transportation safety. Traditional anti-icing or de-icing methods, such as salt spraying, have raised environmental concerns, prompting the exploration of more sustainable alternatives. This study introduces a novel approach by developing a hydrophobic coating for road surfaces. This method involves using room-temperature vulcanized silicone rubber (RTV) and carbon nanotubes (CNTs) for the hydrophobic modification of emulsified asphalt (EA), resulting in the preparation of modified emulsified asphalt (RCEA). This method does not cause environmental pollution and makes the road surface highly hydrophobic and effective at preventing ice formation. When the dosages of RTV and CNTs are 20 wt% and 4 wt%, respectively, the contact angle of RCEA reaches 118.6°, showing a significant increase of 73.4 % compared to EA. Comparative tests have revealed that RCEA extends the freezing time of water droplets by 66.7 % at −10 °C compared to traditional emulsified asphalt (EA). Furthermore, the adhesion force of ice on the RCEA surface is 58.2 % lower than on EA, indicating significantly improved de-icing efficiency. The results of ultraviolet aging and freeze-thaw cycle tests show that RCEA maintains its hydrophobicity, evidenced by only a slight reduction in the contact angle. Additionally, water seepage coefficient tests and anti-skid performance assessments confirm that RCEA meets the requisite standards for road performance. In summary, RCEA emerges as a promising anti-icing and de-icing material for asphalt roads, offering an environmentally friendly alternative to traditional de-icing methods.

Mortality risk and burden of sudden cardiac arrest associated with hot nights, heatwaves, cold spells, and non-optimum temperatures in 0.88 million patients: An individual-level case-crossover study

Sudden cardiac arrest (SCA) is a global health concern, imposing a substantial mortality burden. However, the understanding of the impact of various extreme temperature events, when accounting for the effect of daily average temperature on SCA, remains incomplete. Additionally, the assessment of SCA mortality burden associated with temperatures from an individual-level design is limited. This nationwide case-crossover study collected individual SCA death records across all (2844) county-level administrative units in the Chinese Mainland from 2013 to 2019. Four definitions for hot nights and ten for both cold spells and heatwaves were established using various temperature thresholds and durations. Conditional logistic regression models combined with distributed lag nonlinear models were employed to estimate the cumulative exposure-response relationships. Based on 887,662 SCA decedents, this analysis found that both hot nights [odds ratio (OR): 1.28; attributable fraction (AF): 1.32 %] and heatwaves (OR: 1.40; AF: 1.29 %) exhibited significant added effects on SCA mortality independent of daily average temperatures, while cold spells were not associated with an elevated SCA risk after accounting for effects of temperatures. Cold temperatures [below the minimum mortality temperature (MMT)] accounted for a larger mortality burden than high temperatures (above the MMT) [AF: 12.2 % vs. 1.5 %]. Higher temperature-related mortality risks and burdens were observed in patients who experienced out-of-hospital cardiac arrest compared to those with in-hospital cardiac arrest. This nationwide study presents the most compelling and comprehensive evidence of the elevated mortality risk and burden of SCA associated with extreme temperature events and ambient temperatures amid global warming.

Using computed tomography to diagnose chronic frontal sinusitis in the skeletal remains of a post-medieval Dutch rural community (AD 1829–1866)

Chronic frontal sinusitis (CFS) has afflicted humanity throughout history and continues to be a significant global health issue today. In bioarchaeology, sinusitis is often diagnosed through the identification of bone alterations within the maxillary sinus cavities by macroscopic and/or endoscopic examination. However, due to the inaccessible nature of frontal sinuses, CFS specifically has not been studied extensively archaeologically yet. This paper aims to demonstrate the effectiveness of diagnosing CFS through computed tomography (CT), highlighting the potential of radiographical imaging for future advancements in paleopathological research.We conducted a CT examination of 41 crania from the rural community of Middenbeemster, the Netherlands (AD 1829–1866) to assess the presence of CFS. Criteria for identifying CFS included bone formation and/or thickening of the sinus walls. Our analysis revealed that 14 individuals (34.1%) exhibited signs of CFS in one or both frontal sinuses. We found that males exhibited a slightly higher CFS prevalence (38%) than females (32%), although no significant correlation between sex and sinusitis occurrence was found. This lack of correlation suggests equal exposure to risk factors (e.g., indoor air quality, environmental pollution, allergens, and cold weather) among both sexes.To our knowledge, this study is the first of its kind to confirm the presence of CFS through CT scanning in an archaeological skeletal collection. It demonstrates that computed tomography allows for a straightforward and non-destructive detection of sinusitis in archaeological assemblages. Considering the currently limited bioarchaeological research on frontal sinusitis, our findings should be considered relevant and promising for future osteoarcheological studies on upper respiratory diseases.

Studies on Variation of Temperature and Rainfall using Climatological data for the Plain and Hill zones of Uttarakhand

The present study examines long-term annual, seasonal and monthly changes and short-term fluctuations in monsoonal rainfall and temperature over plain and hill zones of Uttarakhand. Both rainfall and temperature data for period of 1981-2020 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen’s slope estimator were used to examine and analyze the problems. The detailed analysis of the data for 40 years indicates that the annual range of temperature is increasing in the hill zone. In the context of agriculture, the observed trends in temperature and rainfall patterns pose significant implications for farming practices and crop yields in Uttarakhand. The increasing annual range of temperature, particularly in the hill zone, suggests a heightened risk of temperature extremes such as heat waves and cold spells. During the monsoon season, while rainfall levels may remain relatively stable or exhibit minor fluctuations, the variability highlighted by the box and whisker plots underscores the importance of preparedness for both excess and deficit rainfall scenarios.

Strategies of invasive snail Pomacea canaliculata during hibernation in rice fields of south China: effects of body size, sex, and soil depth.

The invasive freshwater snail Pomacea canaliculata is an agricultural pest with a certain level of tolerance to abiotic stress. After the harvest of late rice, the snails usually burrow themselves into the soil surface layers to overwinter and pose a renewed threatto rice production in the following year. Revealing the response of snails to environmental stresses is crucial for developing countermeasures to control their damage and spread. In this study, we conducted a 120-day in situ experiment during the winter to investigate the survival and physiological changes of hibernating snails in 0-5 and 5-10 cmsoil depths, aiming to explore their overwintering strategies. Our results showed that 73.61%, 87.50%, and 90.28% of male, female, and juvenile snails survived after hibernation for 120 days in 0-10 cm soil depth, respectively. The differences in survival rates based on sex and size of snailspotentially reflect the countermeasures of snails to rapidly reproduce after hibernation. Simultaneously, the hibernating snails exhibited the ability to maintain a certain level of body weight. During this period, the snails increased their antioxidant enzyme activities to cope with oxidative stress, and enhanced their lipid storage. The hibernation survival of snails was not significantly affected by different soil depths, indicating that they have the potential to hibernate into deeper soils. Furthermore, snails were capable of increasing their contents of bound water and glycerol to cope with sudden cold spells during hibernation. Our findings emphasize the adaptive changes of P. canaliculata snails overwintering in paddy soils. In future studies, the vulnerabilitiesof P. canaliculata during hibernation (e.g. shell characteristics, nutrient reserves, and dehydration tolerance, etc.,) should be investigated to develop effective control methods for this period. © 2024 Society of Chemical Industry.

Assessing the impacts of temperature extremes on agriculture yield and projecting future extremes using machine learning and deep learning approaches with CMIP6 data

Climate change, particularly extreme weather events, has significantly affected various sectors, including agriculture, human health, water resources, sea levels, and ecosystems. It is anticipated that the intensity, duration, and frequency of these extremes will escalate in the future. This study aims to discover the association between temperature extremes and agricultural yield and to project these extremes using machine learning (ML) and deep learning (DL) models with CMIP6 (Coupled Model Intercomparison Project Phase 6) data under two SSPs (Shared Socioeconomic Pathways). A bi-wavelet coherence technique is employed to investigate the association, providing detailed information in both the frequency and time domains for the period of 1980–2014. Various ML and DL models are trained and tested for the periods of 1985–2004 and 2005–2014, respectively, with gradient boosting machine chosen for projecting temperature extremes based on its superior performance. Mann-Kendall test is used for trend analysis in the projected temperature extremes. The results indicate strong negative and positive associations between TN10p (Cold nights) and TN90p (Warm nights), respectively, with wheat production. Additionally, there is a long-term negative association of CSDI (Cold Spell Duration Indicator) and strong positive association of WSDI (Warm Spell Duration Indicator) with rice yield. Projected results show an increase and decrease under SSP2-4.5 and SSP5-8.5, respectively, in DTR (Diurnal Temperature Range) at most stations. TN10p will increase in the future at most stations, with exceptions such as Muree station where it decreases during 2025–2049 and then increases under both SSPs. Projections show that TXn (annual or monthly minimum value of daily maximum temp) will increase in the future, with Muree station exhibiting the lowest value close to zero, while the average maximum value is around 20 °C at Khanpur station. Trend analysis reveals significantly increasing trend in TR20 (Tropical nights) and decreasing trend in CSDI in future durations under both SSPs. These findings hold implications for policymakers and stakeholders in various departments, including agriculture, health, and water resources management.

Cold Waves Accelerate the Spread of Infectious Diseases

AbstractClimate change is creating a new era of infectious disease crises, further exacerbated by extreme weather. However, the relationship between extreme weather and infectious disease remain unclear. Here, we provide a new quantitative study on the impact of cold wave on COVID‐19 as an example. We found that during cold waves, extreme cold temperatures coupled with rapid aerosol transport accelerated COVID‐19 outbreaks. It directly increased the number of COVID‐19 cases in Beijing by 28.1% in the winter of year 2022. More urgently, cold temperatures led to a higher risk of death during infectious disease outbreaks, with a 7.07% increase in confirmed deaths and a 16.61% increase in excess mortality. Our findings emphasize the urgent need to promote a synergistic policy for responding to infectious diseases during cold wave disasters in order to minimize the risk of death among the elderly and those with underlying diseases.

OSL re-dating and paleoclimate of Laoya Cave in Guizhou Province, southwest China

Laoya Cave is a significant prehistoric human site in Guizhou Province, Southwest China, and optically stimulated luminescence (OSL) and a Bayesian depositional model were used to update the chronology of the cave. Six OSL samples were dated to 16.7 ± 1.2, 18.0 ± 1.1, 28.8 ± 2.3, 32.1 ± 2.8, 57.7 ± 6.5, and 74.0 ± 5.9 ka, respectively, and the Bayesian deposition model has provided a coherent chronological framework, revealing boundaries with median ages of 18.5, 25.0, 27.5, 28.6, 29.9, and 74.4 ka for Boundaries 1/2, 2/3, 3/4, 4/5, 5/6, and 6/9, respectively. By comparing the new chronological framework with the related records of paleoclimate and human activities, we gain insight into the relationship between the environment and Paleolithic hominins at different times. During relatively warmer periods, humans tend to spread, while in relative colder climates, they tend to rely more heavily on caves and employ hunting strategies with an equal age distribution. These survival strategies help humans prevent the threats of cold weather. Additionally, the analysis of OSL dating results uncovers a discrepancy between OSL and accelerator mass spectrometry radiocarbon (AMS 14C) dating methods, with AMS 14C dates generally appearing older at later ages (<∼30 ka). This phenomenon may be due to disturbances caused by human activity, and OSL dating may recognize this to some extent.

The economics of home energy usage: Insights from urban economy

Recent regional investigations in the United States have revealed a thought-provoking perspective: household electricity consumption may act as an inferior commodity, displaying a negative correlation with wealth. This finding challenges the outcomes of various other econometric analyses and underscores the importance of scrutinizing power consumption patterns across different regional service areas. While it is commonly believed that home electricity usage decreases as income rises, this may not always hold true universally. This study focuses on power usage in Seattle, Washington households, a prominent urban economy in the Pacific Northwest. Employing dynamic error correction modeling techniques, the research demonstrates statistically significant fluctuations in domestic power usage attributed to variations in actual value, actual revenue, and cold weather. In the immediate future, energy for homes in this urban economy resembles any other commodity. However, investing in electricity for homes in Seattle may not be advisable in the long run. Home power usage in Seattle declines with each percentage point increase in actual per capita income over 1.2 %. This finding highlights the need for careful consideration and strategic planning in energy management policies for urban economies like Seattle.

Assessing the winter indoor environment with different comfort metrics in self-built houses of hot-humid areas: Does undercooling matter for the elderly?

Thermal comfort in housing is vital for well-being. Despite hot and humid regions experiencing shorter cold periods compared to heatwaves, vulnerable populations are susceptible to threats from cold snaps. However, existing research overlooks undercooling risks in hot regions during winter. This study examines self-built houses in densely populated, hot and humid areas, mainly occupied by elderly residents. We conducted an on-site measurement recording hourly indoor air temperature, humidity, and black globe temperature during wintertime. Two thermal comfort metrics (aPMV and adaptive regression model) and two resilience metrics (SET degree-hour, Hours of Safety) were used to quantify thermal conditions during cold periods under current and future climate conditions. The results show that undercooling hours in recent years exceed 90 % of wintertime using aPMV index and adaptive regression models. Under future climate scenarios (Representative Concentration Pathways), undercooling hours only decrease by 10 %–25 % from 2020 to 2100 across all metrics. Extreme cold events in 2018 saw SET degree-hours double the thermal resilience threshold, while they pose health risks to the elderly for up to 21 days according to the HOS metrics. This study aims to identify the importance of addressing winter thermal comfort in hot and humid regions and to assess the risk posed by cold snaps to vulnerable populations. By quantifying these risks, the study contributes to better decision-making regarding hot-humid region housing thermal retrofit strategies for architects, engineers, and other stakeholders.