Temperature Scenarios Research Articles

Effects of Temperature Variation on Plant Growth in East African Countries

Purpose: The aim of this study was to explore the effects of temperature variation on plant growth in East African countries.
 Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The findings revealed that there exists a contextual and methodological gap relating to the effects of temperature variation on plant growth in east African countries. Preliminary empirical review revealed that temperature variation influences plant nutrient uptake, nutrient assimilation and utilization by plants, impacting their growth and nutritional status. The findings emphasize the need to consider temperature effects on plant nutrient dynamics in agriculture and ecosystem management. The effects of temperature on plant growth were found in most of the studies reviewed.
 Unique Contribution to Theory, Practice and Policy: The Optimal Temperature Theory, Temperature Stress Theory (Acclimation and Heat Shock Proteins), Photoperiodism and Vernalization Theory may be used to anchor future studies on the Effects of Temperature Variation on Plant Growth in East African Countries. Studying the molecular mechanisms underlying plant responses to temperature variation is essential. Uncovering the genetic and molecular pathways involved in temperature stress responses will enable the development of crops with enhanced temperature tolerance and resilience. Additionally, the development of robust predictive models that integrate climate data, physiological processes, and crop responses is crucial. These models will assist in assessing the potential impacts of future temperature scenarios on plant growth and enable the implementation of adaptive measures in agriculture.

Investigation of denoising autoencoder-based deep learning model in noise-riding experimental data for reliable state-of-charge estimation

State-of-charge (SOC) estimation plays a crucial role in battery management systems to ensure safe and reliable operation. However, SOC estimation remains challenging due to the dynamic nature of battery systems and varying ambient conditions. Data-driven methods have emerged as effective tools for analyzing nonlinear dynamical systems, but their performance heavily relies on data quality. In actual applications, data susceptible to distortions caused by external factors such as sensor failure, circuitry, and temperature variations, leading to degraded model performance. To address the performance degradation resulting from data quality deterioration, this paper introduces a denoising autoencoder is implemented as a stacked multi-layer perceptron, which learns to reconstruct distorted data. Furthermore, we propose the ensemble method that combines the autoencoder with an estimation model for SOC estimation in lithium-ion batteries. The effectiveness of the proposed model is demonstrated through tests conducted on a dataset comprising drive cycle profile of Panasonic 18650PF cells. The model validated under two ambient temperatures scenarios: identical and different, using a distorted dataset with added randomly added noise and dropout. The experimental results reveal that the proposed model achieved a 3 % error in training the drive profile relative to the actual values at different ambient temperatures. When compared to the plain model, the proposed ensemble model showed an increased RMSE of 4 %. Additionally, the performance of different estimation models was compared, with the LSTM model achieving an RMSE 0.67 at different ambient temperatures, outperforming the Support Vector Regression (SVR) with an RMSE 1.35 and the Extended Kalman Filter (EKF) with an RMSE of 0.87.

Design Optimization and Operating Performance of S-CO2 Brayton Cycle under Fluctuating Ambient Temperature and Diverse Power Demand Scenarios

Design Optimization and Operating Performance of S-CO2 Brayton Cycle under Fluctuating Ambient Temperature and Diverse Power Demand Scenarios

Variation of Mean Radiant Temperature in Rooms for Summer and Winter Conditions

The standard for ergonomics of the thermal environment provides information on the calculation of optimal thermal comfort. Operative temperature (OT) is one of the essential elements of thermal comfort and is a function of air temperature, mean radiant temperature (MRT), and air velocity. This paper investigates the impact of diverse influences on MRT in an office room based on occupant position and posture (seated and standing). A comparative simulation study of the varied thermal transmittance (U-value) of the only external wall with a window in an office room depending on the wide-ranging outdoor temperature is conducted in the MATLAB tool Simulink. The air temperature and air velocity are assumed according to the standards, and the MRT is simulated. The angle factors, U-value of walls/windows, occupant position, occupant posture, and outdoor temperature are the critical parameters that affect MRT. The results show varied responses from MRT for each of the five outdoor temperature scenarios simulated for three types of exterior walls. Seated occupants have equal MRT, whereas standing occupants have minor discrepancies when exposed to a window at the same distance in all outdoor scenarios. When the placement of occupants is not equally exposed to the window, the seated occupants have a higher MRT difference than the standing occupants.

Bioenergetic consequences of repeated catch-and-release fisheries interactions on adult steelhead across a range of ecologically relevant water temperatures

The biological consequences of catch-and-release angling have been studied for decades, yet little is known about the compounding effects of repeated recreational fisheries recaptures on the physiology and behaviour of angled fish. Using heart rate biologgers and behavioural assays, this study investigated the physiological and behavioural consequences of multiple simulated angling events (i.e., repeated stressors) on female steelhead (Oncorhynchus mykiss), under current (6 °C) and future (11 °C) water temperature scenarios. While steelhead in the warmer water temperature scenario demonstrated alterations in cardiac function (e.g., increases in maximum heart rate and scope of heart rate) and evidence of behavioural impairments (e.g., decreases in chase activity and landing time) over the course of two simulated angling events, cold water treated fish had negligible change. Fish subjected to two simulated angling events under warm water temperature conditions tended to demonstrate an increase in recovery time and scope for heart rate, and a decrease in resting heart rate. A second experiment was conducted to test for sex-specific differences in the heart rate response of steelhead subjected to an increase in water temperature. Females demonstrated a higher scope for heart rate when compared to males during the event and during recovery. More work is needed to better understand the interaction between multiple angling events and recovery from these events at various water temperatures, and the biological basis for sex-specific differences in cardiac function and response to challenges. This study contributes to a growing body of evidence on the effects of repeated stressors on wild fish.

Thermal performance investigation of a novel medium-temperature pilot-scale latent heat storage system at different charging and discharging temperatures

Large-capacity medium-temperature latent heat storage (LHS) systems have the potential to be extensively utilized for waste heat recovery and peak load shifting. However, the phase change behavior and mechanism of medium-temperature phase change materials (PCMs) in shell-and-tube LHS systems, as well as the impact of charging and discharging temperatures on the thermal performance, are still unclear. To address these issues and verify the reliability of the cylindrical pilot-scale LHS system, this article designed and constructed a novel cylindrical medium-temperature (up to 300 °C) LHS system with a large capacity (approximately 1 GJ) equipped with spiral and H-shaped fins. The research focused on investigating the impact of various charging and discharging temperatures on the thermal behavior of the LHS system to adapt different temperature scenarios in waste heat recovery while also analyzing the coupling effect of heat conduction and natural convection during charging and discharging and depicting the PCM liquidus based on thermocouple data. The experimental findings indicated that increasing the charging temperature could effectively shorten the charging duration, with a decrease from 5.99 h at 280 °C to 4.00 h at 300 °C, representing a reduction of 33.22%. In contrast, the impact of decreasing the discharging temperature on the discharging duration was less significant than that of increasing the charging temperature. Besides, the differences in heat transfer mechanisms between the charging and discharging processes were analyzed. In the charging process, the heat transfer was initially dominated by heat conduction, followed by natural convection. Conversely, heat conduction predominantly governed the heat transfer process in the discharging process. The heat transfer process dominated by heat conduction would increase the non-uniformity of PCM temperature on the horizontal plane, while the heat transfer process dominated by natural convection would alleviate this non-uniformity. Moreover, the accumulative stored energy under the charging temperature of 290 °C was 952.37 MJ, while the released energy under the discharging temperature of 160 °C was 648.72 MJ, which was approximately 10–200 times greater than those documented in existing studies.

Planning precision aquaculture activities in a changing and crowded sea

Extreme climate events are increasingly challenging the growth of the marine aquaculture sector, causing local influences on species performance and affecting production and yield - impacting where to locate cage aquaculture facilities. Here we produced scenario-based quantitative maps using modelled species-specific performance combined with predicted high-resolution future IPCC temperature scenarios. We ran a species-specific Dynamic Energy Budget mechanistic model for four model species, up to 2050, and mapped functional trait-based outcomes as: i) time to reach the commercial size, ii) feces produced and iii) uneaten food. A high spatial resolution suitability index allowed the sustainability of farming strategies for single- and multi-species to be identified across a 159.696 km2 surface extension (Italian Exclusive Economic Zone; 6% of the Mediterranean basin surface). Providing a good case study to shed light on difficult questions facing aquaculture planning around the world. Good future performance under both representative concentration pathway (RCP) scenarios were modelled for Sea bream and European seabass in inshore waters. Performance of Mediterranean mussels and Japanese oysters was found to decrease slightly when compared to the 2007–2010 time interval. Scenario-based quantitative maps represent a heterogeneous species-specific knowledge layer that is critical to better inform aquaculture management and development strategies. Yet this knowledge layer is missing from the process to develop climate-resilient risk maps and associated adaptation measures, as well as when informing stakeholders on potential site expansion and/or the establishment of nascent aquaculture industry sites.

Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S.

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.

How Could Increasing Temperature Scenarios Alter the Risk of Terrorist Acts in Different Historical Squares? A Simulation-Based Approach in Typological Italian Squares

Squares in the urban historical built environment are public open spaces prone to the risk of terrorist acts, essentially because they are ideal soft targets and attract significant user densities. Risk assessment methods should consider how users behave in them, both before and during an accident (i.e., the evacuation process). In addition to squares’ morphology and layout, and considering that urban areas are more and more prone to the effects of increasing temperatures, outdoor climate conditions can alter the initial scenario. In fact, such conditions can lead users to gather in specific outdoor areas, where they can look for shadows and shelter. This work hence proposes a simulation-based approach to assess how differences in users’ behaviours in response to increasing temperatures and squares’ morphology can alter the risk of terrorist acts in an emergency evacuation. An agent-based model is developed to simulate the interactions between users, hazards and the historical built environment. The work considers four typological squares prone to terrorist acts since they host a special building attracting users in front of it. These squares are derived from the analysis of Italian historical contexts within the BE S2ECURe project. Users are generated in the public open space (thus, before the terrorist act) depending on the intended uses of the square and on the outdoor temperature, which is affected by the square’s morphology. Three different users’ behaviours are modelled to consider (or not) the effects of the outdoor temperature on users’ thermal acceptability levels in an increasing temperature situation. Then, two evacuation scenarios are simulated: (a) a general evacuation process, without attackers, as the baseline for the risk assessment; and (b) an armed assault with cold weapons, to define one of the most probable attack situations in open spaces. Evacuation performance indicators are developed to assess users’ risk. Preliminary verifications demonstrate the capabilities of the approach. The results show that higher differences in evacuation indicators are noticed in large and asymmetric squares, since their conditions highly affect the variability of users’ behaviours in response to increasing temperatures. At the same time, stronger safety behaviours in response to increasing temperatures could reduce emergency issues because they allow users to be more dispersed and initially placed farther from the attack area. Decision-makers could take advantage of the proposed approach and simulation tool, moving towards an effectiveness analysis of solutions to increase the thermal comfort of users in respect of the risk levels during an evacuation. Finally, applications to real-world scenarios are thus encouraged to compare such idealized results with effective conditions.

The Reproductive Capacities of the Calanoid Copepods Parvocalanus crassirostis and Acartia pacifica under Different pH and Temperature Conditions.

The increasing atmospheric CO2 concentrations and warming of marine waters have encouraged experiments on multi-stressor interactions in marine organisms. We conducted a multigenerational experiment to assess reproductive capacities regarding egg production in calanoid copepods Parvocalanus crassirostis and Acartia pacifica under different pH and temperature conditions. The experimental set-up allowed assessing the tandem effect of warming and acidification on the number of eggs produced by healthy copepod pairs under two pH conditions of 8.20 and 7.50 (hard selection) as well as with a gradual reduction of 0.05 pH units at each generation (soft selection). The results are quite interesting, with very diverse performance across temperatures. The number of eggs produced under hard selection was higher at pH 8.20 compared to pH 7.50 for both species, with the maximum number of eggs produced at 24-28 °C, whereas under soft selection, there was no significant difference in the egg production rate at 24-28 °C across generations and there was an improvement in the number of eggs produced at 8-16 °C. The results provide evidence that in a future ocean scenario of lower pH and higher temperature, the two species, and possibly the copepod population at large, might not decrease. Copepod populations might be resilient, and the transcriptomic evidence of adaptation to increased temperature and lower pH is a ray of hope. We believe further studies are needed to provide more robust datasets to underpin the hypothesis of adaptation to climate change.

Designing a Solar PV-Battery based on Electric Vehicle Charging Station

Increasing transport demand necessitates higher oil consumption, resulting in an increase in carbon dioxide (CO2) emissions, which is a major cause of air pollution. The use of electric vehicles (EVs) is becoming more common around the world. Recent advancements in lithium-ion battery technology have increased the improvement of EVs. In this work, a solar photovoltaic (PV) battery-based EV charging station is designed. Meanwhile, the overall system comprises a battery energy storage system (BESS), solar PV module, grid and EV charging station. Thus, the primary source for the charging station is the PV source but due to less power during the night, we included battery storage as a backup. Grid source is also recommendable for an uninterruptable power supply. An artificial neural network strategy is developed in MATLAB/Simulink for proper power management of the solar PV-battery based EV charging station connected to the AC grid. Moreover, by employing an adaptive neuro-fuzzy inference system (ANFIS) and PI controller-based MPPT, the grid voltage and current, real/reactive grid power and the maximum output power are obtained. The overall system is evaluated under different scenarios of irradiance level and temperature with a state of charge (SOC) greater than 10 % for simulation purposes. The result shows that during the night hour due to less power from the PV source, an artificial neural network begins to regulate the grid power so that it supplies power to the stationary storage and EV battery.

Predicting the impacts of environmental variability on phytoplankton communities of a sub-tropical estuary

Phytoplankton are the floating microscopic organisms which form the base of aquatic food chain, and their ecology is controlled by biotic and abiotic variables. However, a little is known about the response of phytoplankton to changed environmental conditions especially in the sub-tropical regions. Therefore, this study aimed to understand the response of phytoplankton community in variable temperature and salinity conditions in the Naf River estuary of Bangladesh. Phytoplankton, temperature and salinity data were collected from the Naf River estuary of Bangladesh from February 2022 to December 2022. Predicted data of temperature and salinity under two climate change scenarios were also gathered from a hydrodynamic model. Response of phytoplankton to different temperature and salinity scenarios were then analyzed by using a logistic model. This study identified about 154 phytoplankton species from the study area. Temperature had significant negative impacts on the 50 phytoplankton species while 83% species were correlated to the change in salinity. About four phytoplankton species disappeared under the changed environmental conditions. Abundance of one species significantly reduced (50% reduction) while environmental conditions were changed. About 18 phytoplankton species responded positively to the changed environmental conditions. This study provides necessary insights to understand the consequences of climate change on phytoplankton ecology in the sub-tropical ecosystems.

Coupling habitat-specific temperature scenarios with tolerance landscape to predict the impacts of climate change on farmed bivalves

Due to climate change, heatwaves are likely to become more frequent, prolonged and characterized by higher peak values, compared with climatological averages. However, the thermal tolerance of organisms depends on the actual exposure, which can be modulated by environmental context and microhabitat characteristics. This study investigated the frequency of occurrence of mass mortality events in the next decades for two species of farmed bivalves, the mussel Mytilus galloprovincialis and the clam Ruditapes philippinarum, in a shallow coastal lagoon, characterised by marked diurnal oscillations of water temperature. The effect of heatwaves was estimated by means of tolerance landscape models, which predict the occurrence of 50% mortality based on the exposure intensity and duration. Scenarios of water temperature up to the year 2100 were modelled by combining two mechanistic components, namely: 1) monthly mean water temperatures, simulated using a hydrodynamic model including the heat budget; 2) daily oscillations, estimated from the harmonic analysis of a twenty year-long site-specific time series of water temperature. Scenarios of mean daily sediment temperature were estimated by means of a cross-correlation model, using as input the water temperature one: the model parameters were estimated based on a comprehensive set of site-specific water and sediment temperature observations. The results indicate that for both species the risk of mass mortality rapidly increases starting from the 2060s. Furthermore, the daily patterns of water temperature seemed to be relevant, as overnight it falls below the predicted mortality thresholds for a few hours. These findings suggest that further studies should address: 1) the improvement of tolerance landscape models, in order to take into account the integrated effect of repeated non-lethal stress events on mortality rate; 2) the prediction of environmental temperature in specific habitat, by means of both process-based and data driven models.

Generation of climate change scenarios for rainfall and temperature using SDSM in a Mediterranean environment: a case study of Boufakrane river watershed, Morocco

Climate change is the global phenomenon of climate transformation characterized by changes in the planet’s habitual climate. The main objective of this work is to assess and predict climate change for the 2015–2100 period, in the Boufakrane river watershed, Morocco. In this study, the Statistical DownScaling Model (SDSM) method has been used to generate the climate scenarios for rainfall and temperature related to Representative Concentration Pathway (RCP) scenarios such as RCP 2.6, RCP 4.5, and RCP 8.5. For this purpose, the region’s annual, monthly, and daily rainfall records were analyzed. A rainfall index was calculated to differentiate and distinguish between dry and humid years of the climate series, and a non-parametric Pettitt’s test has been applied to determine the trend of precipitation series for the projection period. The application of Pettitt’s test with a confidence interval of 99% and a significance level of 0.05 shows a break in the 1979/80 rainfall series, with an average of 675.78 mm and 511.94 mm respectively before and after the break. The combined application of the two approaches of SDSM, and the non-parametric Pettitt test for the period 2015–2100, showed a downward trend of annual rainfall with 17.29% for RCP 2.6. While no trend was recorded for the two scenarios RCP 4.5, and RCP 8.5. Therefore, this study highlighted the importance and urgent need for developing strategies and decision-making plans for climate change adaptation for sustainable water resources management.Graphical

Zooplankton community size structure across lakes within a semi-arid landscape: the effect of temperature and salinity

AbstractBody size is a master trait controlling biological communities and ecosystem functioning. Mean population size not only depends on the size of individuals, but also on the size distribution of individuals within the population. Mean community size is additionally influenced by the composition of species (larger- or smaller-sized species). Shallow lakes within semi-arid landscapes are prone to experience large changes in temperature and salinity, which affect the zooplankton size structure. Higher temperatures are expected to result in smaller average body size, while the effect of salinity appears to depend on the range under study. Here we analyze zooplankton body size patterns across shallow lakes from the semi-arid central region of Argentina. All community size descriptors point to decreasing size and a narrow size range at higher temperatures. On the other hand, the maximum average community body size occurred at intermediate (~30 gL−1) salinity levels. The combined effect of both variables resulted in a bell-shaped pattern, with maximum community body size toward lower temperatures and intermediate salinities. Based on future temperature scenarios, one may anticipate an overall decrease in community body size. But such prediction is strongly conditioned by regional and local trends in salinity.

Controlling internal nutrients loading at low temperature using oxygen-loading zeolite and submerged macrophytes enhances environmental resilience to subsequent high temperature

Nutrients releasing from anoxic sediment can be enhanced in summer because the dissolved oxygen (DO) consumption, nitrogen (N) and phosphorus (P) migration are susceptible to temperature. Herein, we proposed a method to hinder the aquatic environmental deterioration in warm seasons through consecutive application of oxygen- and lanthanum-modified zeolite (LOZ) and submerged macrophytes (V. natans) at low temperature scenario (5 °C, with depleted DO in water), and the effect was examined with drastic increasing the ambient temperature to 30 °C. The investigation was conducted in a microcosm scale including sediment cores (with a diameter of 11 cm, height of 10 cm) and overlying water (with depth of 35 cm). During the 60 days experiment, application of LOZ at 5 °C facilitated slower releasing and diffusion of oxygen from LOZ and the growth of V. natans. Thereby, when the temperature was increased to 30 °C and maintained for 35 days, the DO reached 10.01 mg/L, and the release of P and N from the sediment was reduced by 86% and 92%, respectively. This was achieved from the joint efforts of adsorption, biological conversion, chemical inactivation, and assimilation. Also, the LOZ inhibited 80% N2O, 75% CH4, and 70% CO2 emissions primary by promoting V. natans growth and reshaping microbiota. Meanwhile, the colonization of V. natans benefited the sustainable improvement in the water quality. Our results addressed the time that the remediation of anoxic sediment can be applied.

Recovery stress behavior of Fe-SMA under fatigue and thermal loading

The present paper investigates mechanical properties and recovery stress behavior of an iron-based shape memory alloy (Fe-SMA) with a special focus on the effect of fatigue and thermal loading. Change in recovery stress of activated Fe-SMAs subjected to fatigue at RT, −20 °C, 60 °C, and −20 to 60 °C was monitored. A second activation after fatigue was performed to investigate the retrievability of the lost recovery stress owing to fatigue. Coefficients of thermal expansion (CTEs) of the samples with different activation histories were also calculated. Results showed that the maximum reduction in recovery stress after two million cyclic loads of Δɛ=0.070% was approximately 20% under RT and −20 °C. A high temperature (60 °C) weakened such detrimental effect owing to higher critical stresses for martensitic transformation at higher temperatures, leading to only 10% reduction in recovery stress. Loss in the recovery stress due to fatigue was pronouncedly retrieved by a reactivation regardless of the temperature scenarios. This study extends understanding of recovery stress behavior of Fe-SMAs subjected to fatigue and thermal loading, and explores the retrievability of relaxed recovery stress by a second activation.

Sub-lethal effects induced in Mytilus galloprovincialis after short-term exposure to sodium lauryl sulfate: Comparison of the biological responses given by mussels under two temperature scenarios

Surfactants are among the most common PPCPs that reach coastal systems, being often used in large quantities in cleaning products such as detergents and soap powders. Sodium lauryl sulfate (SLS) is listed in this group of emerging contaminants. Previous studies have already demonstrated the presence of SLS in aquatic environments and the negative effects on organisms living there. However, with ocean acidification and warming predictions, SLS-induced impacts may differ from those currently known. In this context, the present study aimed to reproduce environmental conditions by assessing the release of substances over a short period and to understand the influence of a rapid increase in temperature on the impacts caused. The marine bivalve Mytilus galloprovincialis was exposed to 2.0 mg/L SLS at 17 °C and 21 °C for 7 days. To assess the possible biochemical changes resulting from the exposure of mussels to SLS, a series of biomarkers related to oxidative stress/damage, detoxification, and metabolic capacity were measured. The SLS accumulation in soft tissues was low (about 0.7 ng/g) at both temperatures. The results evidenced increased metabolic activity, especially in mussels exposed to SLS at 17 °C. An increase in protein content was also observed upon exposure to SLS and increased temperature compared to controls at 17 °C. Although no effects on antioxidant enzymes were observed, protein damage was recorded, especially at 21 °C. These findings confirmed that SLS induces toxic effects and predicted climate change factors may increase the impact on M. galloprovincialis.

Numerical assessment of the condensation phenomenon on a vehicle’s windshield

The energy consumption in buildings, transportation, services or processes has been raising constantly in the last years becoming top priority in research fields. As its impact on the environment has become more and more obvious, the transportation sector has been searching for solutions to lower its influence on future generations. Electric vehicles, proposed as an alternative to the internal combustion engine vehicles, still face some difficulties in driving range, cost, and for colder climates, passenger comfort conditions. As the HVAC system represents the highest energy consumption from the auxiliary systems in electric vehicles, this paper proposes to analyse to condensation phenomenon inside the vehicle’s cabin, especially on the windshield. The numerical approach assesses several scenarios of air velocities, temperatures, and thermal power inputs in order to establish the best configuration at the lowest energy cost.

Predicting the Growth of Vibrio parahaemolyticus in Oysters under Varying Ambient Temperature

Temperature is a critical factor that influences the proliferation of pathogens in hosts. One example of this is the human pathogen Vibrio parahaemolyticus (V. parahaemolyticus) in oysters. Here, a continuous time model was developed for predicting the growth of Vibrio parahaemolyticus in oysters under varying ambient temperature. The model was fit and evaluated against data from previous experiments. Once evaluated, the V. parahaemolyticus dynamics in oysters were estimated at different post-harvest varying temperature scenarios affected by water and air temperature and different ice treatment timing. The model performed adequately under varying temperature, reflecting that (i) increasing temperature, particularly in hot summers, favors a rapid V. parahaemolyticus growth in oysters, resulting in a very high risk of gastroenteritis in humans after consumption of a serving of raw oysters, (ii) pathogen inactivation due to day/night oscillations and, more evidently, due to ice treatments, and (iii) ice treatment is much more effective, limiting the risk of illness when applied immediately onboard compared to dockside. The model resulted in being a promising tool for improving the understanding of the V. parahaemolyticus–oyster system and supporting studies on the public health impact of pathogenic V. parahaemolyticus associated with raw oyster consumption. Although robust validation of the model predictions is needed, the initial results and evaluation showed the potential of the model to be easily modified to match similar systems where the temperature is a critical factor shaping the proliferation of pathogens in hosts.