Temperature Scenarios Research Articles

Warming effects on a nonindigenous predator are not conserved across seasons

AbstractThe global proliferation of nonindigenous species remains a critical stressor driving both biodiversity loss and socioeconomic costs. These impacts frequently depend on environmental contexts, but few studies have investigated how seasonal variations coupled with climate changes, like warming, could modulate nonindigenous species ecological impacts. The Japanese brush‐clawed shore crab Hemigrapsus takanoi is a successful nonindigenous species in northern European waters and is currently spreading in the Baltic Sea. In this study, we used generalized linear models and the comparative functional response approach to examine the predatory impact of H. takanoi toward blue mussels Mytilus sp. across four seasons under current and future temperature scenarios (i.e., ambient and + 6°C warming). We further integrated H. takanoi Q10 values and field abundances across seasons to examine population‐level feeding impacts toward blue mussels. The nonindigenous species exhibited a consistent type II functional response (i.e., inversely prey density‐dependent response) across all seasons, temperatures and sexes, with males consistently consuming more mussels than females across all seasons. Warming generally decreased handling times and increased attack rates, but these effects varied by season and sex, with the most pronounced temperature responses observed in autumn and spring. Population‐level impact calculations integrating field abundance data of H. takanoi indicated that under ambient conditions, feeding impacts toward blue mussels currently peak in the summer months, but as temperature increases, this feeding impact is anticipated to shift later in the year into autumn. These findings underline the critical need for multifaceted research approaches to better understand and predict the context‐dependent ecological impacts of nonindigenous species, particularly in the face of ongoing climate change and shifting population characteristics.

Flexibility through power-to-heat in local integrated energy systems with renewable electricity generation and seasonal thermal energy storage

In heating dominated regions, the flexibility obtained through coupling heating and power sectors is particularly beneficial for the integration of high shares of variable renewable energy sources. This study concerns the design of an energy system for a new neighborhood in Norway, including a seasonal thermal energy storage storing excess heat from waste incineration, a seawater heat pump, and local power generation. Two supply temperature scenarios are considered for the local heating network: medium-temperature (70 °C), where all heating demands are covered through the network; and low-temperature (45 °C), where booster heat pumps are applied for hot water production. Both scenarios are more cost-effective than if heat demands were to be met through import from the district heating network, however, the difference between the two scenarios is small. The low-temperature scenario has the highest degree of self-sufficiency, and the advantage of additional flexibility gained through the local heat pumps with hot water storage. Cost-optimal charging strategy for the seasonal storage was highly dependent on the pricing of excess heat with respect to the electricity prices. Unlimited sharing of electricity among all users in the neighborhood should be promoted to gain full benefits of local flexibility.

Effect of Changing Temperature and CO2 Concentration on Weed Dynamics and Behaviour: A Review

Agriculture and climate change are interwoven with each other in various measures, as climate change is the main culprit of biotic and abiotic stresses, which has adverse impact on crops and weed flora and the effectiveness of weed management strategies. Indeed weed physiology and crop productivity has been greatly influenced by several means of climate variability. Climate change causes a shift in weed population dynamics by altering the physiological pathways with the changing temperature and CO2 conditions. Climate change can affect crop-weed interactions by favouring C4 weeds in increased temperature scenarios requiring adaptation and mitigation strategies. Weeds can also shift their range by invading into new areas and higher latitudes or altitudes due to climatic variability affecting weed diversity, establishment, and management. These factors helps in understanding the crop interactions, weed infestation and herbicide efficacy. This review paper summarizes the challenges that occur due to climate change in weed behaviour requiring more attention on sustainable agricultural production.

Precise three-diode photovoltaic model for photovoltaic modules based on Puma optimizer

The modeling accuracy of photovoltaic (PV) modules is essential nowadays due to the spread of PV power plant installation. Thus, precise PV modeling is vital as it ensures the optimal design, reliable performance prediction, and efficient energy management in solar power systems. The three-diode PV modeling is thus a suitable solution due to its precision and accuracy. However, it is complicated and includes nine unidentified parameters. The Puma optimization algorithm is presented in this paper for utilization in extraction and the optimization of nine unknown PV module parameters. The suggested methodology is applied to two commercial PV modules: the Kyocera KC200GT multi-crystalline and the Canadian PV monocrystalline modules CS6K280M. To ensure the superiority of the Puma algorithm, its results are compared with others resulting from more than four optimization algorithms, which include Artificial Electric Field Algorithm, Northern Goshawk Optimization, Grey Wolf Optimization, Coati Optimization Algorithm, and Particle Swarm Optimization algorithms. The Puma’s parameter extraction precision is further approved by the close agreement between the measured and estimated characteristics curves, extending its validation to variable temperature and irradiance level variations scenarios. The study establishes the Puma algorithm as a robust tool for parameter determination in the three-diode PV model. It opens new avenues for application in other complex optimization problems in renewable energy systems.

Research on optimizing the scope of impact considering decomposition products in the event of a nitric acid spill chemical accident

As the size of the chemical industry increases, chemical accidents continue to occur as the handling volume of chemicals also increases. Currently, in the case of a chemical accident, the prediction of the scope of influence mainly analyzes the scope of the impact on a single substance in the accident and does not consider the scope of the decomposition and reaction products. Nitric acid, one of the many chemical accidents, produces nitrogen dioxide, which is harmful when decomposed. In this research, we at first assumed an outflow accident of nitric acid. After conducting our research using the Chemical Accident Response Information System (CARIS), we discovered that the impact range and breakdown of nitric acid were comparable to that of nitrogen dioxide. Furthermore, we were able to identify the potential ramifications associated with such occurrences. In this study, the impact scenarios were evaluated according to the worst-case scenario, the alternative scenario, the size of the leak hole diameter, atmospheric temperature, atmospheric wind speed, and atmospheric stability. The results showed that the end point concentration distance of nitrogen in ERPG-1, 2 and 3 was larger than nitric acid in most conditions, with differences of up to 5.45 times in the worst-case scenario, 5.96 times in the alternative scenario, up to 6.952 times in the leak hole diameter scenario, up to 10 times in the atmospheric temperature scenario, up to 13 times in the wind speed-specific scenario, and up to 4 times in the atmospheric stability scenario. In the event of a nitric acid spill chemical accident, the response agency should set up a boundary area at a greater distance in consideration of the impact of nitrogen dioxide when setting up a boundary area such as the Hot zone and the Warm zone. Nitric acid handling sites should install additional detectors for nitrogen dioxide, which is decomposition products, to monitor the diffusion of decomposition products into the atmosphere when installing detection alarm equipment in preparation for leakage accidents. It is believed that the government should continuously secure and study data on other decomposable chemicals besides nitric acid to provide material information and disaster prevention methods to chemical accident response agencies and communities for effective and early treatment of chemical accidents.

Chlorophyll-a determinations in mesocosms under varying nutrient and temperature treatments: in-situ fluorescence sensors versus in-vitro measurements

Harmful algal blooms (HABs) are a significant threat to freshwater ecosystems, and monitoring for changes in biomass is therefore important. Fluorescence in-situ sensors enable rapid and high frequency real-time data collection and have been widely used to determine chlorophyll-a (Chla) concentrations that are used as an indicator of the total algal biomass. However, conversion of fluorescence to equivalent Chla concentrations is often complicated due to biofouling, phytoplankton composition and the type of equipment used. Here, we validated measurements from 24 Chla and 12 phycocyanin (cyanobacteria indicator) fluorescence in-situ sensors (Cyclops-7F, Turner Designs) against spectrophotometrically (in-vitro) determined Chla and tested a data-cleaning procedure for eliminating data errors and impacts of non-photochemical quenching. The test was done across a range of freshwater plankton communities in 24 mesocosms (i.e. experimental tanks) with a 2x3 (high and low nutrient x ambient, IPCC-A2 and IPCC-A2+50% temperature scenarios) factorial design. For most mesocosms (tanks), we found accurate (r2 ≥ 0.7) calibration of in-situ Chla fluorescence data using simple linear regression. An exception was tanks with high in-situ phycocyanin fluorescence, for which multiple regressions were employed, which increased the explained variance by >16%. Another exception was the low Chla concentration tanks (r2 < 0.3). Our results also show that the high frequency in-situ fluorescence data recorded the timing of sudden Chla variations, while less frequent in-vitro sampling sometimes missed these or, when recorded, the duration of changes was inaccurately determined. Fluorescence in-situ sensors are particularly useful to detect and quantify sudden phytoplankton biomass variations through high frequency measurements, especially when using appropriate data-cleaning methods and accounting for factors that can impact the fluorescence readings. Nevertheless, corroborating these data with in-vitro Chla assessments would provide additional validation for the early warnings provided by sensor data.

Varying photosynthetic quotients strongly influence net kelp primary production and seasonal differences increase under warming

Reliable net primary production (NPP) estimations of kelp forests are important to evaluate their C-fixation potential. Photosynthetic oxygen measurements can be converted to C-fixation using photosynthetic quotients (PQs). Although there is a known high variability in PQs, the extent and the consequences for NPP is understudied in kelp species. Thus, the present study aimed (i) to quantify the variability of PQs, (ii) to model NPP and (iii) to assess the impact of warming on both. The kelp, Laminaria hyperborea, was studied near the island of Helgoland (North Sea, Germany) along a depth gradient (2, 4, 6 m below mean low water spring tide) across all four seasons. Blade discs were cultivated during at least 6 days per season under simulated ambient photosynthetic photon flux density (PPFD) and temperature conditions and, in parallel, in a warming scenario (+ 4°C). PQs were calculated from parallel oxygen production and 14C-fixation measurements at saturating PPFD at the end of the incubation period. Seasonal PQs varied between 1.7 and 4.4, with highest values in summer due to increased oxygen production. The warming scenario stimulated C-fixation in most seasons, lowering the PQ in comparison to ambient temperature conditions, while collection depth had no significant effect on PQs. The seasonal PQs were used to model daily NPP rates for kelp standing stock at 4 m depth. These daily NPP rates were compared between temperature treatments and with daily NPP rates based on fixed PQs. The warming scenario had a stimulating effect on daily NPP rates in the high-light season spring. In the low-light season autumn, warming resulted in negative daily NPP rates, as the high respiration rates could not be compensated by gross photosynthesis. Overall, annual NPP rate under warming conditions (347 g C m–2 yr–1) was 14% higher than the annual NPP rate under ambient conditions (303 g C m–2 yr–1). Modelling daily NPP with fixed PQs, which neglects the seasonal variation of the PQs, led to a high overestimation of up to 255%. We, therefore, recommend modelling NPP rates not with a fixed PQ, but with seasonal PQs determined under different temperature scenarios in order to obtain reliable future predictions.

The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models

Process-based soil-crop models are becoming increasingly important to estimate the effects of agricultural management practices and climate change impacts on soil organic carbon (C). Although work has been done on the effects of crop type and climate on the root:shoot (biomass) ratio, there is a gap in research on the effects of specific environmental or management conditions such as drought, temperature, nutrient limitation, elevated CO2 or tillage on the root:shoot ratio and thus, atmospheric C sequestration. In this study, we quantified the effects of these factors on the root:shoot biomass ratio by reviewing the current literature, presented common simulation approaches and performed model simulations using different examples. Finally, we identified different research gaps with respect to the root:shoot ratio with the aim of better estimating and predicting atmospheric C sequestration. A predominantly positive response of the root:shoot ratio was observed in case of elevated CO2 (~12 %), low soil N levels (~44 %), and drought (~14 %). Soil tillage did not affect root:shoot ratio of the major field crops but increased it by ~15 % in case of wheat. There are only few field studies on air temperature increase and the results vary widely (mean − 48 %). The responses of tested models to the mentioned effects root:shoot ratio were slightly positive in case of CO2 elevation (0 to 2 %) and tillage (0 to 8 %), slightly to clearly positive in the case of drought and N limitation depending on the model (1 to 40 %), and very variable in case of the air temperature scenarios. Our study reveals large model uncertainty (especially on temperature effects), particularly for below ground processes that highlight knowledge gaps in simulating root:shoot ratio. We advocate for the need of more model-oriented specific experiments under abiotic stresses to help model improvement. Such research effort would enable more robust and reliable root:shoot ratio simulations.

Sensitivity of surface water and groundwater contributions to streamflow in a tropical glacierized basin under climate change scenarios

Abstract While mountain water faces threats posed by climate change, particularly in snow-dominated and glacierized systems, the role of groundwater in sustaining streamflow in these systems remains elusive. Changing mountain headwaters, marked by reduced snowpacks, retreating glaciers, shifting precipitation patterns, and rising temperatures, pose a crucial question: what is the resilience of streamflow in these mountains, and what role does groundwater play in this resilience? This is particularly uncertain in tropical high mountains where the seasonality of precipitation and glacier melt govern streamflow generation. A glacio-hydrological model was created using the Cold Regions Hydrological Modelling platform to investigate cryosphere-surface water-groundwater interactions in the Quilcayhuanca Basin, in Peru’s Cordillera Blanca. The model was forced by in-situ meteorological observations and parameterized using numerous data sources and process-based studies in the basin. Model results show that during the dry season, 37% of streamflow is generated from groundwater discharge, increasing to 56% during the lowest flows. Evapotranspiration is the largest mass flux from the basin at the peak of the dry season. Precipitation, temperature, and glacier change scenarios were used to assess the sensitivity of basin hydrology to climate change and glacier retreat. In a warmer, wetter, and nearly deglaciated future, Quilcayhuanca basin streamflow is expected to decrease by 4-19% annually, with a larger volumetric change in overland and vadose zone flow than in groundwater flow. The range in values is more closely linked to uncertainty in precipitation change than temperature change. Despite a strong reduction in snow and ice contribution to streamflow with warming and deglaciation, the concomitant increase in precipitation can limit the changes in streamflow and groundwater flow, showcasing the resilience of the system to shifts in climate and glacier cover.

Investigation of Salmonella enteritidis Growth under Varying Temperature Conditions in Liquid Whole Egg: Proposals for Smart Management Technology for Safe Refrigerated Storage

This study investigates the growth characteristics of Salmonella enteritidis (S. enteritidis) in liquid whole egg under both isothermal and non-isothermal storage conditions to understand the risks associated with inadequate temperature management in the egg industry. Using controlled laboratory simulations, liquid whole egg samples inoculated with S. enteritidis were stored under various isothermal (5, 15, 25, 35, and 45 °C) and non-isothermal conditions (5–10, 15–20, 25–30, 35–40, and 45–50 °C). The growth behavior of the S. enteritidis was analyzed using a two-step predictive modeling approach. First, growth kinetic parameters were estimated using a primary model, and then the effects of temperature on the estimated specific growth rate and lag time were described using a secondary model. Independent growth data under both isothermal and non-isothermal conditions were used to evaluate the models. The results showed that S. enteritidis exhibits different growth characteristics depending on temperature conditions, emphasizing the need for strict temperature control to prevent foodborne illnesses. To address this, a predictive growth model tailored for non-isothermal conditions was developed and validated using experimental data, demonstrating its reliability in predicting S. enteritidis behavior under dynamic temperature scenarios. Additionally, temperature management technologies were proposed and tested to improve food safety during refrigerated storage. This study provides a scientific basis for improving food safety protocols in the egg industry, thereby protecting public health and maintaining consumer confidence amid temperature fluctuations.

Quantitative assessment of the effects of rising temperature on the grain protein of winter wheat in china and its adaptive strategies

With advancements in genetics and technology, wheat yields have continuously increased, but grain quality has remained stagnant or even decreased in recent decades. The effects of temperature on the future grain quality of winter wheat in China are unknown. This study used an improved WheatGrow model, along with two future temperature scenarios, to quantify the regional impacts of temperature increases on grain protein in China and aimed to find effective strategies to adapt to the impact of temperature increases on quality. Compared with those in the baseline period, the protein concentration of wheat grains in the main winter wheat production region of China increased by 0.27% and 0.41% under the 1.5 ℃ and 2.0 ℃ temperature increase scenarios, respectively. However, the grain protein concentrations in the Sichuan Basin of Medium and Weak Gluten Wheat Subregion (Ⅴ) decreased. The temperature rise was estimated to increase the proportion of strong gluten-type wheat but reduce the proportion of medium gluten-type wheat, with the proportion of weak gluten-type wheat changing slightly. Advanced planting date was projected to increase the grain protein concentration in the Northern Strong Gluten Wheat Subregion (Ⅰ), the Northern of Huang-Huai Strong and Medium Gluten Wheat Subregion (Ⅱ), the Southern of Huang-Huai Medium Gluten Wheat Subregion (Ⅲ) and the Yangzi River of Medium and Weak Gluten Wheat Subregion (Ⅳ), whereas a delayed planting date reduced the protein concentration in subregions Ⅰ, Ⅱ, and Ⅲ. In addition, the grain protein concentration was not significantly affected in the higher high-temperature threshold varieties in the southern winter wheat production region under the global warming scenarios. However, if more strong gluten-type wheat is required in the northern China in the future, varieties with lower high-temperature thresholds can be selected without considering wheat yields. Moreover, increasing the nitrogen fertilizer application rate could further increase the wheat protein concentration under future warming scenarios, and the protein concentration of wheat was more sensitive to the nitrogen fertilizer application rate in the northern winter wheat production region than in the southern region. These findings are crucial for improving grain quality across different wheat production regions of China in the future.

An ensemble approach to downscale climatological variables via screening of clustered ANNs

ABSTRACT The statistical downscaling of global circulation models presents a significant challenge in selecting appropriate input variables from a vast pool of predictors. To address the issue, we developed ensemble approach based on the Combining Multiple Clusters via Similarity Graph (COMUSA), which integrates k-means and self-organizing maps (SOMs) methods with the mutual information (MI)-random sampling approach. This innovative feature extraction technique demonstrated a 21% improvement in the classification efficacy of large-scale climatic variables. When comparing feature extraction methods, the combination of MI-random sampling and ensemble clustering yielded more accurate results than SOM clustering alone. The most efficient artificial neural networks (ANNs)-based downscaling model was employed to project near- and mid-future precipitation and temperature (2025–2035, 2035–2045), revealing varied outcomes under different scenarios (SSP3-7.0 and SSP5-8.5). Under SSP3-7.0 and SSP5-8.5, annual mean precipitation values are projected to decrease by 2–3 and by 4–5%. Also, projected annual mean temperature values indicate an increase in 21-27 and 29-35% under SSP3-7.0 and SSP5-8.5 scenarios. Integrating COMUSA ensemble clustering with MI-random sampling enhances the estimation accuracy of the ANN downscaling model, contributing to accurate projections of future precipitation and temperature values.

Modeling the Effects of Temperature and Limiting Nutrients on the Competition of an Invasive Floating Plant, Pontederia crassipes, with Submersed Vegetation in a Shallow Lake.

The potential for a non-native plant species to invade a new habitat depends on broadscale factors such as climate, local factors such as nutrient availability, and the biotic community of the habitat into which the plant species is introduced. We developed a spatially explicit model to assess the risk of expansion of a floating invasive aquatic plant species (FAV), the water hyacinth (Pontederia crassipes), an invader in the United States, beyond its present range. Our model used known data on growth rates and competition with a native submersed aquatic macrophyte (SAV). In particular, the model simulated an invasion into a habitat with a mean annual temperature different from its own growth optimum, in which we also simulated seasonal fluctuations in temperature. Twenty different nutrient concentrations and eight different temperature scenarios, with different mean annual amplitudes of seasonal temperature variation around the mean of the invaded habitat, were simulated. In each case, the ability of the water hyacinth to invade and either exclude or coexist with the native vegetation was determined. As the temperature pattern was changed from tropical towards increasingly cooler temperate levels, the competitive advantage shifted from the tropical FAV to the more temperate SAV, with a wide range in which coexistence occurred. High nutrient concentrations allowed the coexistence of FAV, even at cooler annual temperatures. But even at the highest nutrient concentrations in the model, the FAV was unlikely to persist under the current climates of latitudes in the Southeastern United States above that of Northern Alabama. This result may have some implications for where control efforts need to be concentrated.

Split of the pseudocritical temperatures of chiral and confinement-deconfinement transitions by a temperature gradient

Searching of the critical endpoint (CEP) of the phase transition of quantum chromodynamics (QCD) matter in experiments is of great interest. The temperature in the fireball at a collider is location dependent, however, most theoretical studies address the scenario of uniform temperature. In this work, the effect of temperature gradients is investigated using lattice QCD approach. We find that the temperature gradient catalyzes chiral symmetry breaking, meanwhile the temperature gradient increases the Polyakov loop in the confined phase but suppresses the Polyakov loop in the deconfined phase. Furthermore, the temperature gradient decreases the pseudocritical temperature of chiral transition but increases the pseudocritical temperature of the confine-deconfine transition. It is also found that the temperature gradient can drive the system away from the singularity, implying that the CEP in the T−μ plane may move in the direction of the first-order phase transition in the phase diagram due to the temperature gradient. Published by the American Physical Society 2024

Impacts of Local Circulations on Ozone Pollution in the New York Metropolitan Area: Evidence From Three Summers of Observations

AbstractElevated surface ozone levels are often detected in the New York metropolitan area during summertime. Moreover, surface ozone in this region exhibits sharp spatial gradients and distinctive diurnal cycles under the influence of complex boundary layer circulations induced by the intricate coastal geometry. This study examines how surface ozone is impacted by local circulations spatially and temporally under different temperature scenarios (all summer days, hot summer days, and extreme heat days) with the help of cluster‐based meteorological conditions during the summertime of 2017–2019. The most polluted days are found to be highly associated with hot sea breeze days with weak background flow. When sea breeze development in the New York Bight is delayed and its penetration north is intercepted by the dominant westerlies during hot summer days, daily maximum 8‐hr average ozone (DMA8) in some ozone hot spots of New York City (NYC) and the south shore of Connecticut (CT) typically drops 9–10 ppb under comparable temperature levels. The average regional decrease of DMA8 for NYC and coastal CT is 6.7 and 8.3 ppb, respectively. Furthermore, we conclude that a change in early morning meridional wind direction is the most critical meteorological characteristic in controlling sea breeze onset type and helping modulate ozone exceedances in the region during extreme hot days when ozone exceedances are expected to be very common. The conclusion is further demonstrated with two case studies during the Long Island Sound Tropospheric Ozone Study 2018 field campaign.

Influence of stocking density and interaction variability on disease progression of white spot syndrome virus-infected shrimp under different risk scenarios

White spot syndrome virus (WSSV), the causative agent of white spot disease (WSD), is the most significant viral pathogen affecting farmed shrimp. As the culture model for whiteleg shrimp has evolved into a higher-intensity model, the need to study the influence of stocking density on disease progression in pond culture systems has been reinforced. Therefore, we assessed WSD progression by deriving a direct correlation between seasonal disease outbreak risk, stocking density, and viral shedding rate (WSSV genome copies/L/g) using three different stocking densities: high (210 shrimp/m2), medium (140 shrimp/m2), and low (70 shrimp/m2). In Experiment 1 (three stocking densities at 25 °C) and Experiment 2 (stocking density × temperature conditions), shrimp showed relatively high cumulative mortality within the temperature range of optimal WSSV replication (23–29 °C). Notably, the mortality trend, peak viral loads, and viral shedding of WSSV-infected shrimp occurred earlier under high-density conditions, regardless of temperature. Thereafter, this study established WSD risk scenarios based on water temperature conditions and confirmed a significant difference in mortality trends between vulnerable and less vulnerable water temperature scenarios under high- and low-density conditions. The vulnerable water temperature scenario included constant (25 °C), shifting-up (20 °C to 30 °C), and shifting-down (30 °C to 20 °C) conditions, whereas the less vulnerable water temperature scenario included constant 20 °C and 30 °C conditions. Based on mortality trends, the WSD risk scenarios revealed that the times to 50 % mortality for shrimp at high, medium, and low densities were 4, 5, and 6 days post-infection (dpi) in the vulnerable water temperature scenario, and 6, 7, and 9 dpi in the less vulnerable water temperature scenario. Viral shedding variability was evaluated based on the correlation between viral loads and viral shedding rate, and linear regression analysis revealed a significant positive correlation between viral shedding rates and viral loads in shrimp, regardless of WSD risk scenarios or stocking density conditions. Notably, a relatively enhanced viral shedding rate was observed at higher stocking densities (from low- to high-density conditions) and under vulnerable water temperature scenarios. This study suggests that increased stocking density and vulnerable water temperature scenarios could induce greater interactions among WSSV-infected shrimp. It also confirmed the potential role of risk scenarios, stocking density, and viral shedding in WSD progression, providing insights into the disease outbreak mechanisms on shrimp farms.

The potential burden from urbanisation on heat-related mortality in São Paulo, Brazil

Heatwave events are associated with increased hospital admissions and mortality rates worldwide. Heat exposure is often exacerbated by the Urban Heat Island (UHI) effect, especially in large cities. However, an accurate quantification of the additional burden related to heat from urbanisation is understudied in Latin American cities. Therefore, we used advanced meteorological modelling to simulate 2 m air temperature at 1 km spatial resolution across São Paulo, estimating UHI intensity attributing of all-cause mortality to heat and UHI during the 2014 heatwave. The Local Climate Zone classification system provided input land use parameters. Our model was validated against 31 weather stations and bias-corrected using linear regression. We calculated heat-related all-cause mortality, stratified by age, using the modelled temperature data, estimating 394 heat-related deaths. A counterfactual experiment, replacing urban areas with natural land, quantified the additional UHI burden. We found that the UHI may contribute to 69–70% of heat-related mortality (modelled temperature scenario). This work motivates the use of appropriate urban climate data, including careful model validation and bias correction, when assessing heat exposure and health risk assessment. It also highlights the health impacts from heatwaves in cities such as São Paulo, which are likely to increase due to climate change.

Design-Point Techno-Economics of Brayton Cycle PTES for Combined Heat and Power

Abstract Pumped thermal energy storage (PTES) systems are grid batteries that use heat pumps to create both hot and cold thermal energy stores when there is excess electricity and then use a power cycle to convert the thermal energy into electricity when there is demand for electricity. In normal operation, Joule-Brayton PTES discharges low-grade heat at temperatures useful for thermal energy consumers like district and industrial heating. Furthermore, PTES designs, like conventional combined heat and power (CHP) technology, can be modified to sacrifice some round-trip efficiency (RTE) to increase the temperature of heat rejection. This paper uses design-point performance and cost models that provide a detailed understanding of the efficiency and cost trade-offs of rejecting heat at various temperatures in ideal-gas Brayton PTES configurations. First, we keep the heat rejection in its nominal location in the PTES system. Next, we move the heat rejection to the discharge turbine exit. We define design-point metrics that isolate both the cost and performance penalty associated with the hotter heat rejection and attribute it exclusively to the heat economic metrics. We find that the levelized cost of heat, including the cost of thermal energy storage (TES) buffering the PTES and heat off-taker, compares favorably versus electric technologies and is less than the cost of natural gas for low temperature scenarios and competitive with the cost of natural gas in some regions of the contiguous United States in high temperature scenarios.

Effects of sunscreen exposure on Posidonia oceanica (L.) Delile under a perspective of increased seawater temperature scenario

The environmental risk of coastal sunscreen pollution and ocean warming to seagrass meadows seems to be greatly intensified in the Mediterranean basin, due to its semi-enclosed nature that limits water renewal and the high influx of tourists it receives every year. Both stress factors could be interacting synergistically, thus, contributing to the current decline of Posidonia oceanica meadows. Our study aimed to determine the response of P. oceanica to the combined effects of elevated seawater temperature and sunscreen addition in a short-term laboratory experiment, testing an environmentally relevant sunscreen concentration in Mallorca, Spain (20 mg L-1) and a control (0 mg L-1) with the ambient temperature in spring (15°C) and a worst-case scenario of estimated temperature increase by 2100 (ambient + 5°C). Sunscreen addition promoted net primary production rates in the seagrass under ambient temperature, possibly due to nutrient enrichment from the mixture. Alkaline phosphatase activity (APA) in young leaves was enhanced under increased temperature only. Early-warning signs of the impacts of combined elevated temperature with sunscreen exposure in P. oceanica were the drastic decrease in leaf chlorophyll concentrations and inhibition of the nitrogen fixation associated with rhizomes (more than 50%), along with greater oxidative stress biomarkers in leaves (i.e., catalase activity and polyphenols content) and APA in roots (4-fold increase). The current investigation has revealed how the negative effects of coastal sunscreen pollution in this seagrass species may be exacerbated under climate change factors, such as ocean warming, with possible implications in the nutrient cycling and photosynthetic process of the plant. Investigations focused on determining the impacts of these contaminants in P. oceanica meadows and their interaction with additional stress factors in the environment is of great relevance for the future management of this declining ecosystem.

Water Tales from Turkistan: Challenges and Opportunities for the Badam-Sayram Water System under a Changing Climate

The Badam River, a tributary to the Arys River located in the Syr Darya basin, is a crucial natural resource for ecological, social, and economic activities in the semi-arid region of southern Kazakhstan. The river basin is heavily influenced by manmade water infrastructure and faces water scarcity, particularly during summer, highlighting the importance of understanding its hydrological processes for effective water resource management. In this study, a semi-distributed conceptual hydrological model of the Badam River was implemented using the RS MINERVE hydrological software to evaluate the impacts of climate change on hydrology and to test the resilience of the water system. Connected HBV models were implemented for each of the hydrological response units that were defined as altitudinal zones. The hydrological model was calibrated using daily time steps between 1979 and 2011, and the resulting flow exceedance curves and hydrographs were used to assess the potential impacts of climate change on the basin, using CMIP6 precipitation and temperature scenarios. Future climate scenarios for the 2054 – 2064 period demonstrate that the peak discharge will be shifted to spring/late spring compared to the current early summer with no significant decrease in average discharge per day of the year. The insights gained from this hydrological-hydraulic model can be used to effectively manage the water system and inform future hydropower design decisions and serve as a blueprint for similar studies in the region and elsewhere.