Summer Winter Research Articles

Shifting seasonality of annual growth through ontogeny for red deer at northern latitudes

AbstractLarge mammals at northern latitudes show annual cycles of body mass gain in summer and body mass loss in winter. The amplitude and seasonal timing of these cycles may vary through ontogeny depending on trade‐offs toward investments in structural growth versus fat storage, reproduction, and future survival. Despite this knowledge, there is no detailed model of how the seasonality of body mass develops through ontogeny. Here, we define a new seasonal growth model that accounts for shifting seasonality through two sine components: one included in the growth coefficient and the other on the asymptotic size. We fitted 12 candidate models to longitudinal data on body mass of captive male and female red deer (Cervus elaphus) in Norway, with different baseline growth structures (von Bertalanffy, Gompertz, and Brody) and including zero, one, or both of the seasonal components. The best fitting model was the Brody model with both seasonal components included, allowing the annual peak to shift through ontogeny: The annual peak occurred in December for calves, shifting to November in yearlings, and October in 2‐ and 3‐year‐olds, ending with September for adults. All age classes showed an annual minimum at the end of winter around March. Males and females showed similar seasonal peaks through ontogeny, although males grow bigger and have larger seasonal amplitudes. Our new growth model provides a flexible framework to model seasonal growth changing through ontogeny, applicable to different species.

LSVL: Large-scale season-invariant visual localization for UAVs

Localization of autonomous unmanned aerial vehicles (UAVs) relies heavily on Global Navigation Satellite Systems (GNSS), which are susceptible to interference. Especially in security applications, robust localization algorithms independent of GNSS are needed to provide dependable operations of autonomous UAVs also in interfered conditions. Typical non-GNSS visual localization approaches rely on known starting pose, work only on a small-sized map, or require known flight paths before a mission starts. We consider the problem of localization with no information on initial pose or planned flight path. We propose a solution for global visual localization on large maps, based on matching orthoprojected UAV images to satellite imagery using learned season-invariant descriptors, and test with environment sizes up to 100 km2. We show that the method is able to determine heading, latitude and longitude of the UAV at 12.6–18.7 m lateral translation error in as few as 23.2–44.4 updates from an uninformed initialization, also in situations of significant seasonal appearance difference (winter–summer) between the UAV image and the map. We evaluate the characteristics of multiple neural network architectures for generating the descriptors, and likelihood estimation methods that are able to provide fast convergence and low localization error. We also evaluate the operation of the algorithm using real UAV data and evaluate running time on a real-time embedded platform. We believe this is the first work that is able to recover the pose of an UAV at this scale and rate of convergence, while allowing significant seasonal difference between camera observations and map.

A CLINICAL STUDY OF INTUSSUSCEPTION IN CHILDREN

A CLINICAL STUDY OF INTUSSUSCEPTION IN CHILDREN

Different vertical heat transport induced by submesoscale motions in the shelf and open sea of the northwestern South China Sea

Submesoscale currents are known to be associated with strong vertical velocities (O (10) m/day), regulating the redistributions of energy and matter balances. The northern South China Sea (SCS) is fulfilled with submesoscale motions, which might induce strong vertical heat transport (VHT). We set up a 1-km horizontal resolution Massachusetts Institute of Technology General Circulation Model (MITgcm) to study the seasonal variations in submesoscale vertical heat transport in shelf regions and open seas. Spectrum analysis shows that the spatial scale separating submesoscale and mesoscale motions are 14 and 30 km for the shelf and open regions, respectively. The submesoscale VHT in the shelf region is one order of magnitude larger than that in the open ocean. The former has the largest value in summer and winter, which might be induced by summer upwelling and winter downwelling, while the latter is strongest in winter and weakest in summer in open regions. The submesoscale VHT also appears to have intra-seasonal variations and might be attributed to the disturbances of tropical cyclones and life stages of submesoscale eddies. The submesoscale VHT is strongest in the pregeneration phase of the eddies, and the maximum VHT belt has an entrainment type at the developing and mature stages. The chlorophyll-a concentration also has the same temporal variation as the different life-stage of eddies. This study provides local VHT induced by submesoscale motions, which is expected to improve our understanding of submesoscale air–sea interactions and their biological effects.

An observational study on the effect of seasonal variation on peritoneal dialysis patients.

Background: Seasonal variation has an impact on plants, wild animals, and also human beings. Data have shown seasonal variation has a significant impact on patients' fluid status, biochemistry results, and outcomes in hemodialysis populations. The relevant data on peritoneal dialysis is scant. Methods: This was a cross sectional study. All patients followed up in our center had a peritoneal equilibration test and PD adequacy test every 6months. All the peritoneal equilibration test and PD adequacy test data were collected during December 2019 to November 2020. The monthly delivery information of the whole center was collected from 2015 to 2019. Results: There were 366 patients and 604 sets of peritoneal equilibration test and PD adequacy test results in the study. Plasma albumin and phosphate levels were higher in summer. The monthly average outdoor temperature was positively correlated with plasma albumin. There was no seasonal difference in peritoneal dialysis ultrafiltration or urine volume. The percentage of low glucose concentration (1.5%) usage was higher in summer and lower in winter. Conclusion: Plasma albumin and phosphate levels were higher in summer in PD patients. Weaker glucose peritoneal dialysis dialysate was more widely used in summer. Understanding the seasonal variation of peritoneal dialysis is helpful in individualized treatment.

Impact of fossil and non-fossil fuel sources on the molecular compositions of water-soluble humic-like substances in PM2.5 at a suburban site of Yangtze River Delta, China

Abstract. Atmospheric humic-like substances (HULIS) affect the global radiation balance due to their strong light absorption at the ultraviolet wavelength. The potential sources and molecular compositions of water-soluble HULIS at a suburban site in the Yangtze River Delta from 2017 to 2018 were discussed, based on the results of the radiocarbon (14C) analysis and combining the Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) technique in this study. The 14C results showed that the averaged non-fossil-fuel source contributions to HULIS were 39 ± 8 % and 36 ± 6 % in summer and winter, respectively, indicating significant contributions from fossil fuel sources to HULIS. The Van Krevelen diagrams obtained from the FT-ICR-MS results showed that the proportions of tannin-like and carbohydrate-like groups were higher in summer, suggesting significant contribution of HULIS from biogenic secondary organic aerosols (SOAs). The higher proportions of condensed aromatic structures in winter suggested increasing anthropogenic emissions. Molecular composition analysis on the CHO, CHON, CHOS, and CHONS subgroups showed relatively higher intensities of high O-containing macromolecular oligomers in the CHO compounds in summer, further indicating stronger biogenic SOA formation in summer. High-intensity phenolic substances and flavonoids, which were related to biomass burning and polycyclic aromatic hydrocarbon (PAH) derivatives indicating fossil fuel combustion emissions, were found in winter CHO compounds. Besides, two high-intensity CHO compounds containing condensed aromatic ring structures (C9H6O7 and C10H5O8) identified in the summer and winter samples were similar to those from off-road engine samples, indicating that traffic emissions were one of the important fossil fuel sources of HULIS at the study site. The CHON compounds were mainly composed of nitro compounds or organonitrates with significantly higher intensities in winter, which were associated with biomass burning emissions, in addition to the enhanced formation of organonitrates due to high NOx in winter. However, the high-intensity CHON molecular formulas in summer were referring to N-heterocyclic aromatic compounds, which were produced from the atmospheric secondary processes involving reduced N species (e.g., ammonium). The S-containing compounds were mainly composed of organosulfates (OSs) derived from biogenic precursors, namely long-chain alkane and aromatic hydrocarbon, which illustrate the mixed sources of HULIS. Generally, different policies need to be considered for each season due to the different seasonal sources (i.e., biogenic emissions in summer and biomass burning in winter for non-fossil-fuel sources, traffic emissions and anthropogenic SOA formation in both seasons, and additional coal combustion in winter). Measures to control emissions from motor vehicles and industrial processes need to be considered in summer. Additional control measures on coal power plants and biomass burning should be applied in winter. These findings add to our understanding of the interaction between the sources and the molecular compositions of atmospheric HULIS.

Non-stationary large-scale statistics of precipitation extremes in central Europe

Extreme precipitation shows non-stationarity, meaning that its distribution can change with time or other large-scale variables. For a classical frequency-intensity analysis this effect is often neglected. Here, we propose a model including the influence of North Atlantic Oscillation, time, surface temperature and a blocking index. The model features flexibility to use annual maxima as well as seasonal maxima to be fitted in a generalized extreme value setting. To further increase the efficiency of data usage, maxima from different accumulation durations are aggregated so that information for extremes on different time scales can be provided. Our model is trained to individual station data with temporal resolutions ranging from one minute to one day across Germany. Models are chosen with a stepwise BIC model selection and verified with a cross-validated quantile skill index. The verification shows that the new model performs better than a reference model without large-scale information. Also, the new model enables insights into the effect of large-scale variables on extreme precipitation. Results suggest that the probability of extreme precipitation increases with time since 1950 in all seasons. High probabilities of extremes are positively correlated with blocking situations in summer and with temperature in winter. However, they are negatively correlated with blocking situations in winter and temperature in summer.

Post-occupancy evaluation for enhancing building performance and automation deployment

Building automation systems are building control and management systems that control/operate different systems in a building such as HVAC, lighting, safety systems, security and access control, surveillance, indoor air quality, and waste management. These systems manage, control, and integrate other building systems to enhance living experience and optimise energy use through a set of sensors and actuators that are deployed in the building to collect data and execute commands that are sent through a gateway. These management systems generate real-time commands and act or reacts to stochastic occupant behaviours. Buildings in Oman used to be built with burned clay mixed with date palm leaves, and wadi stones and date palm trunks are used for building structure. This architecture keeps the indoor environment warm in winter and cold in summer. However, with advancing technology there has been a shift in building towards using concrete and steel that have high thermal conductivity and pose some challenges for energy use. This paper will show that the main concern of occupants in Oman is indoor temperature control, especially during summer months. This has raised concerns for building performance in Oman and shows a need to review building materials, recommend sustainable alternatives, and more widely, implement sustainable building techniques. This paper seeks to develop recommendations to overcome these issues by exploring post-occupancy satisfaction measures and potential use of BAS and sustainable building materials to enhance building performance in Oman. Following on from this, this paper explores the motivations behind people's decision in Oman to deploy home automation and explore techniques to enhance building performance.

Comparisons of PM2.5 mitigation with stand characteristics between evergreen Korean pine plantations and deciduous broad-leaved forests in the Republic of Korea

Owing to industrialization and urbanization in recent decades, fine particulate matter (PM2.5) in the atmosphere has become a major environmental problem worldwide. This environmental issue pushed the use of forests as air filtering tools. However, there is a lack of continuous and long-term forest management to efficiently mitigate PM2.5. In this study, we assessed the potential of different forest types to control air pollution by measuring the seasonal PM2.5 concentrations inside and outside the forest for one year. In addition, the PM2.5 reduction efficiencies (PMREs) of two forest types were compared, and their relationship with stand characteristics was analyzed. The results showed that the average PMRE inside the forests was approximately 18.2%; the seasonal PMRE was highest in winter (approximately 28.1%) and lowest in summer (approximately 9.6%). The average PMRE of the Taehwa deciduous broad-leaved forest (TDF) (approximately 18.8%) was significantly higher than that of the Taehwa coniferous forest (TCF) (approximately 17.5%) (P < 0.001); differences were also observed seasonally. The PMRE in the TCF was higher in spring and summer (P < 0.001), while that in the TDF was higher in autumn and winter (P < 0.001). Furthermore, the PMRE in the TDF was negatively correlated with stand density (P = 0.003) and positively correlated with the average diameter at breast height (DBH) (P = 0.028). However, the PMRE in the TCF did not significantly correlate with stand characteristics. As such, the results of this study revealed the differences in PM2.5 mitigation according to stand characteristics, which should be considered in urban forest management.

Energy self-sufficiency and sustainability in a defined neighbourhood: Bio-methanation to green gas can outperform green hydrogen

In Europe, green hydrogen and biogas/green gas are considered important renewable energy carriers, besides renewable electricity and heat. Still, incentives proceed slowly, and the feasibility of local green gas is questioned. A supply chain of decentralised green hydrogen production from locally generated electricity (PV or wind) and decentralised green gas production from locally collected biomass and biological power-to-methane technology was analysed and compared to a green hydrogen scenario. We developed a novel method for assessing local options. Meeting the heating demand of households was constrained by the current EU law (RED II) to reduce greenhouse gas (GHG) emissions by 80% relative to fossil (natural) gas. Levelised cost of energy (LCOE) analyses at 80% GHG emission savings indicate that locally produced green gas (LCOE = 24.0 €ct kWh−1) is more attractive for individual citizens than locally produced green hydrogen (LCOE = 43.5 €ct kWh−1). In case higher GHG emission savings are desired, both LCOEs go up. Data indicate an apparent mismatch between heat demand in winter and PV electricity generation in summer. Besides, at the current state of technology, local onshore wind turbines have less GHG emissions than PV panels. Wind turbines may therefore have advantages over PV fields despite the various concerns in society. Our study confirms that biomass availability in a dedicated region is a challenge.

Study on the mechanisms of interannual variation in suspended sediment concentration in the Bohai Sea based on GOCI

The launch of the Geostationary Ocean Color Imager (GOCI) satellite has made it possible to observe suspended sediment concentration (SSC) in the Bohai Sea (BHS) over a long time and a large area. We utilized remote sensing data from GOCI from 2011 to 2021 to study the spatiotemporal variation characteristics of SSC in the BHS and identified the contribution of each oceanic element to the changes in SSC. Our findings indicate that SSC is high in winter and low in summer, and related to the southeastward winds in winter (>7 m/s) and northwestward winds in summer (<4 m/s), with a correlation coefficient of 0.634. The average annual increase in SSC is 0.07 g/m3 (an increase of 1.2% per year). In terms of spatial distribution, SSC is highest in Bohai Bay and Laizhou Bay, followed by the Liaodong Bay, and is greater than that in the Central Bohai Sea, which is related to multiple river estuaries in the three bays. Additionally, the Bohai and Liaodong Bay in the BHS are covered by sea ice during winter, which affects the response of waves and currents to wind and changes the ocean current field, thereby affecting the resuspension and transport of sediment. Our EOF analysis revealed that wind-induced changes are the dominant factors in the variations of SSC, while changes in river runoff, sediment discharge, and sea ice cover are also important factors influencing SSC changes.

Effect of different cold air intensities and their lagged effects on outpatient visits for respiratory illnesses in Handan in different seasons

The authors analyzed cold air processes of different intensities and their effect on the number of patients with respiratory illnesses visiting a hospital outpatient department in Handan City in different seasons from 2016 to 2019. For cold air events of the same intensity (apart from cold waves), the number of patients with respiratory illnesses visiting the outpatient department was highest in winter. During the cold waves, the number of patients increased sharply to greater than 55 patients per day, and the number of patients was higher in spring than in autumn. The probability density of the number of patients with respiratory illnesses visiting the outpatient department gradually changed to a positive skewness as the cold air intensity increased. Although the incidence of respiratory illnesses was the highest in winter and lowest in summer, the impact of cold air on respiratory illnesses was the largest in summer and spring, when the number of people with respiratory illnesses visiting the outpatient department increased by 18.4% and 13.3% two and five days after a cold air day. By contrast, the number people visiting the outpatient department with respiratory illnesses in winter only increased by 3.2% three days after a cold air day. The lag time of the health impact decreased with increasing cold air intensity in summer, autumn and winter, whereas the lag time was always long in spring. These findings provide a targeted basis for a scientific response to the risks to human health caused by global climate change.摘要本文利用2016年到2019年邯郸市气象要素和呼吸系统疾病门诊数据, 分析了不同季节不同强度的冷空气过程及其对呼吸系统疾病的影响. 结果显示: 尽管呼吸系统疾病在冬季高发, 夏季最低, 但冷空气对呼吸系统疾病的影响在夏, 春季最大, 就诊人数分别在冷空气日后两天和五天增加18.4%和13.3%, 而冬季就诊人数在冷空气日后三天仅增加3.2%.冷空气对疾病影响的滞后时间在夏, 秋和冬季随冷空气强度的增加而减少, 而春季的滞后时间总是很长. 这些发现可为科学应对气候异常导致的人群健康风险提供针对性依据.

Deciphering the Trend and Interannual Variability of Temperature and Precipitation Extremes over Greenland during 1958–2019

Abstract Greenland experienced multiple extreme weather/climate events in recent decades that led to significant melting of the ice sheet. However, how the intensity of extreme climate events over Greenland varied under recent warming has not been fully examined. Here, we collect 176 in situ observations over Greenland and demonstrate that the observed extreme temperature/precipitation events over Greenland are well captured by the RACMO2.3p2 model, in terms of climatological distribution, interannual variability, and long-term trend. Thus, we then investigate the spatiotemporal features of extreme events over Greenland during 1958–2019, using the daily model outputs at 5.5-km resolution. The simulated annual maximum temperature exhibits a significant increasing trend (∼0.13°C decade−1) during 1958–2019, whereas there is a weakening trend (−0.24°C decade−1) in annual minimum temperature over Greenland, especially after the 1990s (−1.24°C decade−1). For the interannual variability, changes in temperature extremes between warm and cold temperature years share large similarities with the distributions of long-term trends. The extreme precipitation events measured by annual maximum daily precipitation amount show a profound increasing trend (0.52 mm day−1 decade−1) over northeastern Greenland during 1958–2019, with large interannual variability in the ice-free coastal region and southern Greenland. Additionally, the changes in extreme warm and cold events are generally linked with the variation of Greenland blocking in summer and Arctic polar vortex in winter, respectively, in terms of favorable circulation background, and the extreme precipitation events are often associated with the position of the polar jet stream.

The Antarctic Amplification Based on MODIS Land Surface Temperature and ERA5

With global warming accelerating, polar amplification is one of the hot issues in climate research. However, most studies focus on Arctic amplification, and little attention has been paid to Antarctic amplification (AnA), and there is no relevant research based on MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature observations. Compared with 128 stations’ observations, MODIS can capture the variations in temperature over Antarctica. In addition, the temperature changes in Antarctica, East Antarctica, West Antarctica and the Antarctic Peninsula during the period 2001–2018 reflected by the MODIS and ERA5 are basically consistent, and the temperature changes in Antarctica are negatively correlated with the Southern Annular Mode. AnA occurs under all annual and seasonal scales, with an AnA index greater than 1.27 (1.31) from the MODIS (ERA5), and is strongest in the austral winter and weakest in summer. AnA displays regional differences, and the signal from the MODIS is similar to that from ERA5. The strongest amplification occurs in East Antarctica, with an AnA index greater than 1.45 (1.48) from the MODIS (ERA5), followed by West Antarctica, whereas the amplified signal is absent at the Antarctic Peninsula. In addition, seasonal differences can be observed in the sub regions of Antarctica. For West Antarctica, the greatest amplification appears in austral winter, and in austral spring for East Antarctica. The AnA signal also can be captured in daytime and nighttime observations, and the AnA in nighttime observations is stronger than that in daytime. Generally, the MODIS illustrates the appearance of AnA for the period 2001–2018, and the Antarctic climate undergoes drastic changes, and the potential impact should arouse attention.

Spatio-temporal variations of PM2.5 and O3 in China during 2013–2021: Impact factor analysis

Fine particulate matter (PM2.5) and ozone (O3) pollution are regarded as significant secondary air pollutants. The PM2.5 in most regions in China declined, and the decreasing rate in January was lower than the annual average. However, O3 concentration showed a steady increasing trend in most regions, and the increasing rate in July was slightly higher than the annual average. In particular, the annual average PM2.5 concentration and excess rate showed an increasing trend on the northern slope of the Tianshan Mountains. Conversely, O3 concentrations had shown a consistent increasing trend, exceeding the annual average limit of 100 μg/m3. Surface pressure exhibited positive correlations with PM2.5 in winter and O3 in summer across urban agglomerations. Moreover, soil temperature at different depths explained over 30% of the variations in PM2.5 and O3 in the Chengdu-Chongqing, Beijing-Tianjin-Hebei, and Lanzhou-Xining urban agglomerations. In winter, relative humidity demonstrated a positive correlation with urban agglomerations in northeast and northwest China, regions characterized by dry climates. During the COVID-19 period, the impacts of meteorological factors and soil temperature on PM2.5 and O3 differed significantly compared to preceding and subsequent periods. Notably, during the winter of 2020, the Harbin-Changchuan urban agglomeration exhibited a notable transition, as O3 and PM2.5 concentrations shifted from a strong negative correlation to a robust positive correlation. This remarkable shift, with deviations explained up to 60%, represents a unique phenomenon worth emphasizing in the study's findings.

Variations of Remote-Sensed Forel-Ule Index in the Bohai and Yellow Seas during 1997–2019

Water color, often quantified using the Forel-Ule Index (FUI), is a crucial parameter for assessing the water quality and ecological health of coastal waters. However, there is limited research on the spatiotemporal variations of FUI and the associated influencing factors in the Bohai and Yellow Seas. In this study, we utilized multi-sensor satellite datasets to retrieve monthly FUI products for the Bohai and Yellow Seas spanning the period from September 1997 to December 2019. Subsequently, we examined significant spatial disparities and variations across multiple timescales in the remotely sensed FUI time series. The climatological annual mean FUI map reveals a decreasing trend from nearshore to offshore regions, with similar spatial patterns observed in terms of overall and interannual FUI variability. The annual variations in wind field, sea surface temperature (SST), and ocean stratification play a key role in the seasonal dynamics of FUI by modulating the sediment resuspension process, resulting in low FUI values in summer and high FUI values in winter. Linear regression analysis of FUI anomaly indicates a long-term decreasing trend in FUI for the three bays of the Bohai Sea, while upward trends in FUI predominantly prevail in the central Yellow Sea. Factors related to interannual FUI variations, such as surface winds, SST, river outflow, rainfall, and anthropogenic activities, are qualitatively discussed. The findings of this study provide the first comprehensive evaluation of water color variations and their underlying mechanisms in the Bohai and Yellow Seas.

Seasonal variation in predialysis systolic blood pressure and cardiovascular events in patients on maintenance hemodialysis.

Predialysis systolic blood pressure (SBP) in patients on hemodialysis (HD) consistently followed a seasonal pattern, reaching a peak in winter and nadir in summer, similar to blood pressure in the general population. However, the relationship between seasonal variations in predialysis SBP and clinical outcomes is still under-investigated in Japanese patients on HD. This retrospective cohort study included 307 Japanese patients undergoing HD for >1 year in three dialysis clinics and evaluated the association between the standard deviation (SD) of predialysis SBP and clinical outcomes, including major adverse cardiovascular events (MACEs; cardiovascular death, nonfatal myocardial infarction or unstable angina, stroke, heart failure, and other severe cardiovascular events requiring hospitalization) with 2.5 years follow-up. The SD of predialysis SBP was 8.2 (6.4-10.9) mmHg. In the model fully adjusted for the SD of predialysis SBP, predialysis SBP, age, sex, HD vintage, Charlson comorbidity index, ultrafiltration rate, renin-angiotensin system inhibitors, corrected calcium, phosphorus, human atrial natriuretic peptide, C-reactive protein, albumin, hemoglobin, body mass index, normalized protein catabolism rate, and intradialytic SBP decline, Cox regression analyses showed that a higher SD of predialysis SBP (per 10 mmHg) was significantly associated with increased MACE risk (hazard ratio [HR], 1.89; 95% confidence interval [95% CI], 1.07-3.36) and all-cause hospitalization (HR, 1.57; 95% CI, 1.07-2.30). Therefore, greater seasonal variations in predialysis SBP were associated with worse clinical outcomes, including MACEs and all-cause hospitalization. Whether interventions to reduce seasonal variations in predialysis SBP will improve the prognosis of Japanese patients on HD must be investigated further.

Deepwater dissolved oxygen shows little ecological memory between lake phenological seasons

ABSTRACT Depletion of deepwater dissolved oxygen (DO) in lakes has become increasingly prevalent and severe because of many external stressors, potentially threatening human-derived ecosystem services ranging from drinking water quality to fisheries. Using year-round, high-frequency DO data from 12 dimictic lakes, we compared 3 measures of deepwater DO depletion during winter and summer: DO depletion rate, DO minimum, and hypoxia duration. Hypoxia (DO < 3 mg L−1) occurred in over half of the lakes and persisted an average of 83% longer in summer than in winter. While we found no difference in DO depletion rates between winter versus summer, these rates were significantly related to lake morphology in winter but trophic state in summer. In assessing cross-seasonal linkages, we found limited evidence for significant legacy effects in deepwater DO availability. Only fall mixing efficacy significantly responded to the previous summer’s minimum DO saturation, but it always reached moderate to high DO replenishment levels (>65%) regardless of the previous summer’s DO depletion severity. This lack of ecological memory in deepwater DO depletion across seasons suggests that deepwater DO largely resets during spring and fall mixing periods in most years in these dimictic lakes. Understanding the patterns and drivers in deepwater DO depletion in both winter and summer is a key step forward for predicting future chemical and biological consequences of seasonal DO depletion and managing lake ecosystem health, as well as the effects that climate change may have on these patterns.

Optimizing the operation of photovoltaic panels using mathematical regression models

Solar (PV) panel models are necessary for the implementation of solar panel control algorithms such as maximum power point tracking. If real-time control is required, these models will be used on microcontrollers and, therefore, will be subject to constraints of memory and execution time: the model implemented on the microcontroller must occupy a memory area as small as possible and the mathematical relationships it contains can be computed in the shortest possible time. Analytical models usually do not fit this criteria, therefore searching for equivalent models which do fit it is required. In this paper, equivalent mathematical models are determined in the MATLAB programming environment based on data obtained by simulating an analytical model in the LabVIEW programming environment. In this paper, the models were obtained by modeling the current distribution in the panel through regression methods, more specifically by using an optimal response surface which has been validated through the resolution of an optimization problem with restrictions. The optimal response surface was used to estimate the extreme values of the power produced by the panel for certain given weather conditions (maximum power in summer and minimum power in winter).

The heat transfer with nanomaterial enhanced phase change materials in different container shapes

The heat transfer is studied during the melting and solidification of sp11 and sp24 phase change materials in different container shapes. The materials are further mixed with nano-alumina and nano CuO enhancements. We aim to identify the most favorable phase change material for free-cooling in summer and free-heating in winter. Ansys Fluent 20.2 is used to analyze the 2D models for the melting and solidification mechanisms of the phase change samples in cylindrical, square, rectangular, and elliptical-shaped capsules. The nanomaterial-enhanced phase change material improves the melting and solidification behavior over the base phase change material by as much as 9.8%. It is further observed that the nanomaterial-enhanced phase change material particularly in the rectangular-shaped containers has faster melting and solidification rates by over 43% compared to the others. The material sp24 with 4% nano-alumina in a rectangular profile has the shortest melting times ~70-100 mins, when the inlet temperatures are 313 and 318 K. The same material has the shortest solidification time of 426 mins, two times faster compared to the 928 mins observed with the cylindrical capsule under the same conditions. The Sp11 with the nano-alumina in a rectangular capsule also has a short melting time of 134 mins. The rectangular profile is found capable of achieving the highest temperature drop about 3.3 K during free cooling of inlet air using nano-enhanced sp24. A progress is realized in unmasking the potential of the thermal energy battery using hybrid geometry and nanomaterial enhancements.