Daily Heat Research Articles

Abstract 4145877: Association of heat exposure with cardiovascular and all-cause hospitalizations among elderly adults in the United States

Background: Heat exposure is associated with an increase in cardiovascular mortality, particularly among older adults. Climate change has led to an increase in days with hot temperatures. The burden of hospitalizations associated with heat exposure is not well known. Methods: Data on all hospitalizations among Medicare beneficiaries 65 years of age and older in summer months (May through September) for 2016 to 2019 were obtained from Medicare Provider Analysis and Review (MEDPAR) files. Total daily cardiovascular and all-cause hospitalizations in each US county in the contiguous United States (US) were determined and daily county-level maximum heat index levels were obtained from the gridMET dataset. Counties with <100 elderly residents were excluded. The association between daily heat index and hospitalizations was quantified using the distributive lag non-linear framework, with a generalized linear regression model – assuming a quasi-Poisson distribution. The model accounted for the lagged association, for up to 10 days, for daily heat index as well as covariates (ozone, particulate matter, and precipitation levels). Estimates from this model were used to determine the number and fraction of hospitalizations attributable to high temperatures on hot days. Hot days were defined as those with a heat index level in the 90 th percentile based on a county-specific historical period (1979-2015). Results: A total of 2085 counties (out of 3108) were included. The median threshold for hot days was 90.2°F (IQR 84.8°F to 95.5°F) [32.3°C (IQR 29.3°C to 35.3°C)]. Between 2016 and 2019, hot days were associated with 3044.0 (95% CI 2641.5 to 3380.9) or 0.067% (95% CI 0.058% to 0.074%) of all cardiovascular hospitalizations. Hot days were associated with 42132.2 (95% CI 41159.9 to 43082.1) or 0.22% (95% 0.21% to 0.225%) of all hospitalizations among Medicare beneficiaries. Conclusions: Between 2016 and 2019 days with high heat index levels were associated with higher levels of cardiovascular and all-cause hospitalizations among elderly Medicare beneficiaries across the contiguous US. As the number of hot days continues to increase due to climate change, the burden of heat related hospitalizations is likely to continue to increase.

Foamed calcium sulfoaluminate cement with controlled porous network for daily or seasonal heat storage in ettringite

Calcium sulfoaluminate (CSA) cement-based materials have high ettringite content enables heat storage, enhancing the thermal inertia of buildings. This study aims to optimize the porous network of foamed CSA material in terms of porosity, permeability and mechanical strength so that they can be effective in building applications as supporting structures with heat storage capacity. To achieve these goals, a foaming process method using hydrogen peroxide (H2O2) and surfactant was used to control the porous network. The H2O2 and surfactant contents varied from 0.5% to 1.2% and 0.01% to 0.05%, respectively, and generated a wide range of material densities from 589 to 1184 kg/m3 - and hence a wide range of properties in terms of porosity (43 - 70%), permeability (2.6 10-13 - 7.1 10-12 m2) and compressive strength (0.8 -9.4 MPa). Then, an abacus correlating material properties, found by surface fitting, linking porosity, gas permeability and compressive strength, allowed the material to be optimized in accordance with the needs of each building application. The CSA paste consisting of 1% H2O2 and 0.03% surfactant, with 66% porosity, 4.1 10-12 m2 permeability, and 1.8 MPa compressive strength, was the optimal mix-design for solar storage box applications (for short-term storage). The CSA paste consisting of 0.5% H2O2 and 0.01% surfactant, with 43% porosity, 5.6 10-13 m2 permeability, 9.4 MPa compressive strength, appeared to be optimal for self-supporting wall storing solar heat (long-term storage).

Performance of bread wheat advanced lines under late sowing and hydric stress during the crop season 2020-2021

Thirty four advanced bread wheat lines and cultivar Borlaug 100 were sown on January 15 and 30, 2021, at the Norman E. Borlaug Experimental Station, in the Yaqui Valley, Sonora, México. Plots consisted of 1 bed 2 m long with two rows and 0.80 m apart with two replications, and a seed density of 100 kg ha-1 with two complementary irrigations. Average daily temperature (°C), maximum, minimum, relative humidity, rainfall, heat and cold units were recorded from January 1 to May 15, 2021. The average days for heading of the group was 69 for the first sowing date and 66 for the second one, while days for physiological maturity were 99 and 90, respectively. The average plant height of the group for the first date was 97.5 cm and 94 for the second one; the sister line SOKOLL/5/W15.92/4/PASTOR//HXL7573/2*BAU/3/ WBLL1/6/SOKOLL/3/PASTOR//HXL7573/2*BAU (PTSS12SHB00020T-0TOPB-099Y-099B-25Y-020Y-0B) consistently reached the maximum height with 107.5 and 110 cm in each date, respectively. The average grain yield per plot was 294 g; line BAJ #1*2/4/BETTY/3/CHEN/AE.SQ//2*OPATA showed the highest yield with 345.4 g which was above 4.3 t ha-1, followed by SOKOLL/3/PASTOR//HXL7573/2*BAU/4/ASTREB/5/PIHA//WORRAKATTA/2*PASTOR /3/PRL/2*PASTOR, also above 4.3 t ha-1. The average hourly temperature was 18.4 °C with a maximum of 40.8 °C and a minimum of 3.9 °C, and the number of heat and cold units was 203 and 393, respectively.

A Study of the Mixed Layer Warming Induced by the Barrier Layer in the Northern Bay of Bengal in 2013

Strong salinity stratification induced by large freshwater fluxes in the northern Bay of Bengal (BOB) results in the formation of a quasi-permanent barrier layer (BL) that covers almost the entire BOB and leads to a unique temperature inversion within the thick BL in winter. In the presence of temperature inversions, the entrainment process at the bottom of the mixed layer (ML) induces warming effects in the ML, but little is known about this. In this paper, we quantify the contribution of the entrainment process to the ML temperature (MLT) in the northern BOB during the winter of 2013 using monthly and daily data from the Ocean General Circulation Model for the Earth Simulator version 2 (OFES2). It is found that the warming effect of the daily entrainment heat flux (EHF), which resolved the high-frequency variations, is 4 orders of magnitude larger than the monthly EHF for most of the wintertime. This significantly enhanced warming effect in daily data offsets up to 87% of the surface cooling induced by net heat flux during wintertime. A further analysis reveals that the larger daily EHF warming effect compared to its monthly counterpart is closely related to the deepened ML, the larger temperature difference within the ML and vertical velocity at the bottom of the ML.

Investigation of a Novel Thermochemical Reactor for Medium- and Low-Temperature Heating Applications in Buildings

This research paper investigates a novel triangular honeycomb thermochemical energy storage reactor for low- and medium-temperature applications in buildings, emphasizing its potential to enhance sustainable heating. Using a validated 3D numerical model, the reactor’s performance is analyzed in depth across various configurations, focusing on key parameters such as energy storage density, pressure drop, internal air flow distribution, and round-trip efficiency. Results show that the reactor achieved an energy storage density of 872 kJ/kg and a round-trip thermal efficiency of 41.51% under optimal conditions. Additionally, the triangular honeycomb reactor (30°, 60, and 90°) configuration achieved the highest temperature lift of 48.7 °C. In a feasibility analysis for residential heating in northern China, the reactor with 30°, 60°, and 90° angles required 24.91% less volume to meet daily heating demands compared to other configurations. This study contributes valuable insights for the development of efficient, low-carbon heating solutions for low- and medium-temperature applications in buildings, offering interesting advancements in the field of thermochemical energy storage technology.

Experimental and numerical study of a novel interlayer ventilation phase change wall: Energy storage parameters and annual load characteristics

In subtropical regions, phase change walls tend to release heat into rooms during nighttime, reducing building energy efficiency. In this work, we proposed an interlayer ventilation phase change wall (IVPCW) to address this challenge. The thermal performance, thermal storage influencing factors, annual cooling and heating loads, and energy saving potentials of IVPCW were analyzed by experiment and numerical simulation. The results show that: (i) IVPCW has the best thermal performance under non-air-conditioning and air-conditioning among ordinary wall, phase change wall, and IVPCW. (ii) Increasing the density and latent heat of CPCM and decreasing the thermal conductivity of CPCM can reduce daily heat gain (DHG). Moreover, the density impacts DHG more than latent heat, while latent heat surpasses thermal conductivity in influencing DHG. (iii) The annual load of IVPCW is reduced by 62.8% compared with PCW. (iv)The annual load of IVPCW is reduced by 41.6% compared with insulation enhanced wall (IEW) in Ganzhou, and 39.2% lower than that of IEW in Guangzhou. The findings offer theoretical support to aid in the implementation and performance optimization of IVPCW systems

Matching analysis between the heating/cooling capacity of PVT heat pumps and the heating/cooling demand of residential buildings across various regions in China

PVT-HP (Photovoltaic-Thermal Heat Pump) is a novel type of energy saving technology. Existing researches on PVT-HP technology focuses only on its operating performance under some specific conditions, ignoring the matching of its energy supply capacity with the energy demand of buildings, which is very important for its engineering design and application. In this paper, the matching relationship between the heating/cooling capacity of the PVT-HP system and the heating/cooling demand of residential buildings in major cities of China has been analyzed. To achieve this goal, a novel prediction model used to calculate the heating/cooling performance of the PVT-HP system has been proposed. And the daily heating guarantee rate and daily cooling guarantee rate have been put forward to evaluate the matching relationship. Based on the evaluation indexes, the applicable matching relationship between the installed capacity of the PVT-HP system and the heating/cooling area of residential buildings has been analyzed. The result of case study shows that for the selected cities of Shenyang, Beijing and Wuhan, the heating/cooling area of residential building for PVT-HP system with installed capacity of 1hp should not exceed 17m2, 31m2 and 25m2, respectively. Further matching analysis of major cities in China shows that the PVT-HP system is more suitable for application in hot summer and cold winter zones of China, in where the suggested heating/cooling area for the PVT-HP system with installed capacity of one horse power is within the range of 30m2 to 37m2.

Predictive heating load management and energy flexibility analysis in residential sector using an archetype gray-box modeling approach: Application to an experimental house in Québec.

This paper presents a methodology to develop archetype gray-box models and use them in an economic model-based predictive control algorithm to simulate optimal heating load management in response to a newly-introduced static time-of-use tariff for Québec's residential sector, rate Flex-D. The methodology is evaluated through a case study, wherein in situ measurements from a two-storey unoccupied research house of Hydro-Québec are used to develop an 11R6C network with a heuristic zoning-by-floor approach and compute the sequence of optimal electric heating input for the next control horizon. Properly-tuned economic model-based predictive control under rate Flex-D shows potential for an approximately 30% reduction in daily heating cost compared to the reference operation, with a minimal average deviation of indoor air temperature from the reference setpoint. Also, the analysis of the response's sensitivity to weather forecast uncertainties indicates that the most influential uncontrolled input directing the performance of economic model-based predictive control is the structure price signal, rendering the impact of uncertainty in the weather forecast negligible.

A preliminary observational study on the characteristics of surface turbulent fluxes over the South China Sea Islands

AbstractIn recent years, there has been a rise in human activities in oceanic areas, making the land–atmosphere interactions over islands a major scientific concern on a global scale. Examining the observation data from offshore areas enables a more comprehensive understanding of the turbulent fluxes in offshore atmospheric environments, patterns of momentum, energy and material exchange between the atmosphere and underlying surface in an oceanic boundary layer, and development of a heterogeneous atmospheric boundary layer. The related findings will assist in developing theoretical models and parameterization schemes to simulate the influence of heterogeneous surfaces on land–atmosphere interactions on the South China Sea Islands. Existing studies on the turbulent fluxes over the South China Sea Islands were mainly conducted on the Nansha Islands, whereas studies on the waters of the South China Sea are scarce. In this study, we used 10 Hz high‐frequency turbulence measurements to calculate the latent and sensible heat fluxes over the South China Sea Islands using the eddy correlation method. These findings were then compared with data from the Dunhuang Gobi, Ordos desert, and Xilingol grassland regions in inland China, along with the observed net radiation and surface heat fluxes. The findings indicate that the energy fluxes over the South China Sea in summer exhibit prominent diurnal variations. The magnitude of either latent or soil heat flux is low, and the net radiation is predominantly transformed into sensible heat flux, which warms the atmosphere. Furthermore, the daily variation curves of sensible and latent heat fluxes are influenced by intermittent turbulence on the islands and reefs, resulting in a less smooth pattern compared with soil heat flux. Although the South China Sea Islands have small land areas and are surrounded by the sea, the land–atmosphere interactions over the underlying surface of this region are similar to those over the underlying surface of grasslands in inland China during summer. The daily mean sensible heat flux on the islands is higher than that in an inland area, and the time lag in its response to sunrise is longer than that in inland areas by approximately 1 h. The overall energy balance ratio is approximately 0.75, c which is in line with the average level, but an energy balance residual of approximately 25% still exists. Furthermore, extreme weather conditions, such as typhoons, can disrupt the diurnal variations of sensible and latent heat fluxes, and the cyclical patterns are subsequently restored.

Forecasting of Daily Heat Production in a District Heating Plant Using a Neural Network

Artificial neural networks (ANNs) can be used for accurate heat load forecasting in district heating systems (DHSs). This paper presents an application of a shallow ANN with two hidden layers in the case of a local DHS. The developed model was used to write a simple application in Python 3.10 that can be used in the operation of a district heating plant to carry out a preliminary analysis of heat demand, taking into account the ambient temperature on a given day. The model was trained using the real data from the period 2019–2022. The training was sufficient for the number of 150 epochs. The prediction effectiveness indicator was proposed. In the considered case, the effectiveness of the trained network was 85% and was better in comparison to five different regression models. The developed tool was based on an open-source programming environment and proved its ability to predict heating load.

Prioritizing social vulnerability in urban heat mitigation.

We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city's demographic composition and physical structure. The study results show that while urban trees may yield less cooling impact (0.27 K of Universal Thermal Climate Index in daytime) relative to cool roofs (0.30 K), the urban trees strategy can emerge as an effective approach for enhancing community resilience in heat stress-related outcomes. Social vulnerability-based heat mitigation was reviewed as vulnerability-weighted daily cumulative heat stress change. The results underscore: (i) importance of considering the community resilience when evaluating heat mitigation impact and (ii) the need to assess planting spaces for urban trees, rooftop areas, and neighborhood vulnerability when designing community-oriented urban overheating mitigation strategies.

High-resolution urban climate simulations for heat and health applications in Philadelphia

Stakeholders need high-resolution urban climate information for city planning and adaptation to climate risks. Climate models have too coarse a spatial resolution to properly represent cities at the relevant scale, and downscaled products often fail to account for urban effects. We propose here a methodological framework for producing high-resolution urban databases that are used to drive the SURFEX-TEB land surface and urban canopy models. A historical simulation is carried out over the period 1991–2020, based on a reanalysis of the city of Philadelphia (Pennsylvania, USA). The simulation is compared with observations outside and inside the city, as well as with a field campaign. The results show good agreement between the model and observations, with average summer biases of only −1 °C and + 0.8 °C for daily minimum and maximum temperatures outside the city, and almost none inside. The simulation is used to calculate the maximum daily heat index (HIX) and to study emergency heat alerts. The HIX is slightly overestimated and, consequently, the model simulates too many heat events if not bias corrected. Overall, HIX conditions at Philadelphia International Airport are found to be suitable proxies for city-wide summer conditions, and therefore are appropriate to use for emergency heat declarations.

Forecasting demand for air conditioning in the Brazilian residential sector

Brazil is among the ten largest air-conditioning consumers in the world. The estimated electricity demand for air conditioners in the residential sector has more than tripled in the last twelve years, while household air conditioner ownership increased by 9 % per year. This trend is expected to continue in the upcoming decades as a result of population growth rate, higher incomes, and individual preferences for thermal comfort. This work assess the current use of air conditioning in the Brazilian residential sector and attempts to forecast its future demand. Forecasting is based on a proposed methodology which includes weather data monitored by 265 meteorological stations during eight years. Empirical correlations are used to determine daily average indoor temperatures for typical residential buildings and the ANSI/ASHRAE standard for indoor thermal comfort is applied to estimate the average number of cooling days (CD) and heating days (HD). These two parameters indicate the yearly average number of days in which thermal comfort condition is not reached and consequently the use of air conditioning is necessary. Northern and Northeastern Brazil are the regions with the highest CD for masonry residential buildings, approximately 318 days annually. Efforts are made to project the electricity consumption by space cooling in the residential sector until 2035 considering several effects, such as population growth, ownership of ACs, cooling capacity, and equipment efficiency. Southeastern Brazil had the highest electricity consumption for space cooling in 2022, at 12.06 TWh. The research forecasts a rise to 44.77 TWh by 2035, though improved equipment efficiency could lower this to 33.51 TWh. Future energy policies should emphasize efficient AC usage and stricter EER standards.

A Waste Heat Assessment of a Manufacturing Facility With Consideration for Demand Matching Through Thermal Energy Storage

Abstract A waste heat assessment of a manufacturing facility was conducted. A physical survey identified potential waste heat sources. For these sources, the temporal fluctuations in temperature and flowrate, and the frequency of occurrence of the waste heat, were determined from measurements, calculations, and company records. The energy and exergy of the waste heat were calculated. The total annual waste heat is 36.5 TJ of energy, which represents 0.84 TJ of exergy. The boiler, plant vacuums, and chiller comprise 96% of the energy rejected and are the major contributors to the rejected exergy. Using the waste heat for space heating is evaluated. Based on fuel consumption in the boiler, the annual energy for space heating is estimated at 8.5 TJ. Theoretically, waste heat from the boiler flue, polypropylene dryers, and plant vacuums could meet up to 39% of this energy without storage. Simply allowing the vacuum exhausts to cool in the building could theoretically meet up to 27%. Models are developed to investigate using waste heat recovery and thermal energy storage (TES) to provide space heating for a prototype warehouse building, and estimates for the initial costs of the recovery system are developed. Modeling indicates that TES is highly beneficial for matching short-term demand fluctuations and for smoothing the temporal oscillations in the waste heat. A nine-month heating season is simulated to determine the fraction of the load met by the recovery system. A small amount of thermal storage, e.g., 12.5–25% of daily waste heat, improved the fraction of demand that could be met. Larger sizes had diminishing returns and significantly increased the initial cost and payback period. To reduce initial cost, a refined recovery system design that uses a TES as an intermediate and for storage is proposed. The study highlights the need to consider fluctuations in the waste heat supply and sink demand, for thermal storage, and to identify relatively simple modifications to recover waste heat.

Experimental and numerical investigation of the effects of passive radiative cooling-based cool roof on building energy consumption

Passive radiative cooling is an energy-efficient method that reduces indoor temperature and cooling load in buildings, thus contributing to significant energy savings. This study investigates the thermal performance of the passive radiative cooling-based cool roof (PRC-CR) based on experimental and numerical analysis in terms of indoor air temperature and space cooling load indicators. Two experiment rooms constructed from concrete are developed with an indoor air temperature control system. One is the PRC-CR room with the roof covered by a passive radiative cooling metamaterial and the other is the reference room with a concrete roof. Long-term testing results in Hefei show that the indoor air temperature of the PRC-CR room is 5.5 °C lower in maximal and 1.8 °C lower on average than that of the reference room in summer when the indoor air temperature control system is off. Besides, when the indoor air temperature control system is switched on, the PRC-CR room achieves a 29.1% reduction in daily cooling load in summer and a 4.1% increase in daily heating load in winter, which suggests that passive radiative cooling can indeed save energy in cooling season (i.e., hot season) but cause overcooling in heating season (i.e., cold season). In addition, a simulation building model is developed to further investigate the effect of the PRC-CR on the energy consumption of buildings in different locations. The predicted results show that PRC-CR reduces the total load of buildings in cooling load prevailing regions (e.g., tropical zones, subtropical zones, and the vast majority of warm temperate zones), while increasing the total load of buildings in heating load dominant regions (e.g., most middle temperate zones, cold temperate zones, and plateau climate zones). In summary, this work demonstrates both the positive and negative effects of PRC-CR, providing valuable insights into PRC-CR applications.

Measuring effects of insulation renewal on heating energy and indoor thermal environment in urban residence of hot-summer/cold-winter region, China

Optimizing thermal insulation in residential buildings is crucial for energy efficiency, especially in Hot Summer and Cold Winter (HSCW) region. Current research often neglects retrofitting and real-life measurements, relying instead on simulations. This study conducted insulation retrofitting on a Chengdu high-rise residential unit, focusing on the flexible heating habits locally. The insulation renewal work involved transforming the thermal insulation structure by adding insulation to all internal surfaces of the rooms' opaque structure, including external walls, internal walls, ceilings, and floors. Experiments based on residents' routines quantified energy savings and improved indoor thermal conditions under intermittent heating. Results showed a significant decrease in daily heating energy consumption by 45.10 % on average, with a maximum of 55.53 %. The retrofitted room's energy-saving rate stabilized between 50 % and 55 % after the second hour. Indoor temperatures in the retrofitted bedroom increased by 0.7 °C on average and up to 1.4 °C. Raising the heating set temperature by 2 °C resulted in a 1.1 °C increase in the retrofitted room, higher than in the non-retrofitted one. These findings provide practical insights for renovating existing residences to achieve energy efficiency in the HSCW region.

Performance of bread wheat advanced lines under late sowing and reduced irrigation

Twenty eight advanced wheat lines and cultivar Borlaug 100 were sown on January 15 and 30, 2020, at the Norman E. Borlaug Experimental Station, in the Yaqui Valley, Sonora, México. Plots consisted of 1 bed 2 m long with two rows and 0.80 m apart with two replications, a seed density of 100 kg ha-1 with two complementary irrigations. Average daily temperature (°C), maximum, minimum, relative humidity, rainfall, heat and cold units were recorded from January 1 to May 15, 2020. The average days for heading of the group was 67 for the first sowing date and 64 for the second, while days for physiological maturity were 103 and 95, respectively. The average plant height of the group for the first and second sowing dates was 83 cm; line SOKOLL/3/PASTOR//HXL7573/2*BAU/4/PARUS/ PASTOR/5/PIHA// WORRAKATTA/2*PASTOR/3/PRL/2*PASTOR consistently reached the maximum height with 92.5 and 95 cm in the first and second dates, respectively. The average a thousand grain weight of the group was 53.8 g for the first sowing date and 43.8 for the second; sister line SOKOLL/3/PASTOR//HXL7573/2*BAU/4/ SOKOLL/WBLL1/5/PIHA// WORRAKATTA/2*PASTOR/3/PRL/2*PASTOR (PTSS14Y00057S-0B-099Y-099B-43Y-020Y) showed the highest average weight with 57.07 g. The average grain yield per plot was 340 g; sister line WBLL4//OAX93.24.35/WBLL1 /5/CROC_1/AE.SQUARROSA(205)//BORL95/3/PRL/SARA//TSI/VEE#5/4/FRET2/6/D67.2/PARANA66.270//AE.SQUARROSA(320)/3/CUNNINGHAM/4/VORB (PTSS15Y00024S-099B-099Y-099M-10Y-020Y) showed the highest yield with 420 g which was above 5 t ha-1. The average temperature was 19.09 °C with a maximum of 36.3 °C and a minimum of 1.04 °C, and the number of heat and cold units was 229 and 227, respectively.

In-situ test and numerical investigation on the long-term performance of deep borehole heat exchanger coupled heat pump heating system

Given the substantial initial investment required by the drilling and implementation of the Deep Borehole Heat Exchanger (DBHE), it becomes imperative to quantitatively evaluate its long-term performance and sustainability. This work introduces a pilot DBHE project in Xi’an, along with the 500-h in-situ monitored data, which is used to validate the 3D numerical model established and simulated in the OpenGeoSys (OGS) software. Based on the validated model, a series of extended scenarios are executed to evaluate the influence of design and operational parameters on the long-term performance and sustainability of the DBHE system. The results show that the drilling depth is the most significant factor that influences long-term performance. On the contrary, pipe diameter and inner pipe thermal conductivity have a very limited impact. A comprehensive evaluation is suggested to determine operational flow rates in real projects while considering the energy consumption by the circulation pump. Moreover, the heat extraction performance and energy analysis of the DBHE coupled with a geothermal heat pump under intermittent operation are also investigated. With a fixed daily heating demand, a longer daily operating time results in lower circulating temperature drops, which is advantageous for the heat pump’s energy efficiency in long-term operation.

Association between summertime emergency department visits and maximum daily heat index in rural and non-rural areas of Virginia (2015–2022)

There is growing evidence that high ambient temperatures are associated with a range of adverse health outcomes. Further evidence suggests differences in rural versus non-rural populations' vulnerability to heat-related adverse health outcomes. The current project aims to 1) refine estimated associations between maximum daily heat index (HI) and emergency department (ED) visits in regions of Virginia, and 2) compare associations between maximum daily HI and ED visits in rural versus non-rural areas of Virginia and within those areas, for persons 65 years of age and older versus those younger than 65 years. Our study utilized 16,873,213 healthcare visits from Virginia facilities reporting to the Virginia Department of Health syndromic surveillance system between May and September 2015–2022. Federal Office of Rural Health Policy defined rural areas were assigned to patient home ZIP code. The estimated daily maximum HI at which ED visits begin to rise varies between 25 °C and 33 °C across climate zones and regions of Virginia. Across all regions, estimated ED visits attributable to days with maximum HI above 25.7 °C were higher in rural areas (3.7%, 95% CI: 3.5%, 3.9%) versus in non-rural areas (3.1%, 95% CIs: 3.0%, 3.2%). Patients aged 0–64 years had a higher estimated heat attributable fraction of ED visits (4.2%, 95% CI: 4.0%, 4.3%) than patients 65 years and older (3.1%, 95% CI: 2.9%, 3.4%). Rural patients older than 65 have a higher estimated fraction of heat attributable ED visits (2.7%, 95% CI: 2.2%, 3.1%) compared to non-rural patients 65 years and older (1.5%, 95% CI: 1.3%, 1.8%). State-level syndromic surveillance data can be used to optimize heat warning messaging based on expected changes in healthcare visits given a set of meteorological variables, and can be further refined based on climate, rurality and age.

Optimal design and thermal performance evaluation of phase change material filling position for solar air collectors

Unreasonable filling positions of phase-change materials (PCMs) significantly reduce the heat storage capacity, heat release time, output temperature difference, heat collection efficiency, and heat peak migration capacity of PCM-based solar–air collectors in building heating systems, thereby affecting the comprehensive heating requirements of building users. To solve this problem and obtain the optimal filling position of the PCM, four PCM filling schemes were designed in this experiment: Type I was a solar air collector with the PCM filled in the upper portion, Type II was filled in the middle portion, Type III was filled on both sides, and Type IV was filled in the bottom portion. Subsequently, the four models were compared. A comparative analysis of the thermal performance evaluation index showed that compared with the other three types of collectors, the heat storage layer of Type I stored 1.505 × 106J of heat in 1.42h, indicating that the Type I solar–air collector had the best heat storage speed rate. When the solar energy supply was terminated, the continuous heat release time of the Type I collector was 13.92h, and the ratio of the heat release time to the non-solar time was 96 %. The Type I collector had the lowest output temperature and the slightest temperature fluctuation, which could increase indoor thermal comfort. The average daily heat collection efficiency of the Type I collector was the lowest, at only 38.11 %, indicating that the Type I collector has the strongest “peak cutting and valley filling” ability, which allows for transferring more heat for nighttime release. Therefore, filling the upper portion is the optimal filling scheme that can provide technical benefits for the application and development of collectors.