Climatic Conditions Research Articles

Selection and performance evaluation of roof materials in arid oasis cities: The advantages of white polymer materials

Selecting the appropriate roofing material is crucial for addressing the urban heat island effects. However, uncertainty remains regarding the best roofing material for improving subsurface cooling during hot summers in temperate continental arid climates. Comparative studies on different roof materials under various climatic conditions are essential to determine the most effective heat mitigation strategies for arid oasis cities. We present a conceptual model to examine the relationship between roofing materials and their thermal mitigation capabilities in arid regions during hot summers, while assessing the influence of climate factors on their cooling performance. An experiment in Urumqi evaluated the subsurface heat mitigation capabilities of four roofing materials: white polymer materials (WPM), sod (SOD), asphalt (ASP), and solar photovoltaic panels (SPP). The results showed that the WPM provided the most effective subsurface cooling. Compared with SOD, ASP, and SPP, WPM showed the lowest subsurface temperature. Notably, the subsurface temperature of the WPM was minimally affected by climatic factors and showed no correlation with solar radiation intensity, precipitation, and cloudiness (P > 0.05), highlighting its superior cooling performance. WPM roofs are recommended for heat mitigation during hot summers in arid oasis cities owing to their low maintenance costs, ecological benefits, and superior cooling performance. This study highlights the subsurface cooling capabilities of various roofing materials and their interaction with climatic factors and provides valuable insights for heat mitigation strategies in arid regions.

Land-use determines the distribution of large branchiopods in climatically homogeneous northern Pannonia

Large branchiopods are key biota of temporary pools in Central European lowlands. Due to land use changes, they are among the most threatened aquatic invertebrates in Europe. The lack of information on the main drivers of species distribution hinders effective protection and conservation prioritisation. We selected eight branchiopod species with representative data on their occurrence in the northern Pannonia to identify the most important drivers of their distribution and to predict their distribution in unexplored temporary pools across the Pannonian region of southern Slovakia, south-eastern Czech Republic, and eastern Austria. Data on pool size and isolation, soil characteristics, land use and climate were used to generate species distribution models using five modelling techniques and ensemble predictions. The distribution of species was mainly affected by the proportion of arable land within the pool (e.g. Triops cancriformis, Leptestheria dahalacensis), land use (e.g. Eubranchipus grubii, Lepidurus apus) and distance from the river (e.g. Branchinecta ferox and Chirocephalus carnuntanus). Wetland size and habitat isolation were also important for some species, mainly for Branchipus schaefferi and Imnadia yeyetta, respectively. As we focused on a climatically homogeneous area, climatic conditions only had the most important effect on the distribution of species that have their distribution limit in northern Pannonia (B. ferox, C. carnuntanus, I. yeyetta). Overall, the diversity of large branchiopods increased with pool size, while decreased with distance to a river and habitat isolation. As some distribution patterns emerged repeatedly in the models, the effective protection can be simplified to consider species that require contrasting conditions. Particular attention should be paid to ephemeral wetlands on arable land, crucial habitats for large branchiopods, yet lacking any protection. Our results can contribute to better conservation of large branchiopods by facilitating surveys of species in understudied areas and improving the knowledge on the species environmental niches.

A Comparative Study on the Performance of Ice-Source Heat Pumps Versus Other Heat Source Heat Pumps: A Case Study in the UK

Eliminating natural gas as a fuel for heating residential and industrial units is crucial for reducing environmental pollutants. The challenge lies in finding alternative heating systems and repurposing existing infrastructures, like gas pipes. This article presents a new approach to supplying energy to heat pumps in a post-natural gas era using repurposed gas pipes to transport water for ice-source heat pumps. It highlights the advantages of ice-source heat pumps and compares their thermal performance with other types. The proposed system integrates ice-source and geothermal heat pumps, offering space efficiency, compact design, cost-effective centralization, optimized subsidies, seasonal cooling, weather resilience, and eliminates the need for new piping.This study evaluates heat pump efficiency using various low-grade heat sources: ambient air, ground, domestic wastewater, river and lake water, piped water, and latent heat. It focuses on optimizing heat pump performance under the UK's climatic conditions, addressing efficiency challenges during peak cold periods. The research demonstrates the system's robust performance in cold, densely populated areas, potentially reducing water mass for energy supply by up to 95% with a 70% ice slurry concentration. Additionally, the ice-source heat pump requires about 36.7 times less water volume than traditional systems for residential heating.

The Factors Influencing Consumer Behaviour in the Purchase of Green Products in Windhoek, Khomas Region of Namibia

It is a global concern that environmental sustainability is in danger. Climate conditions in most parts of the world cannot sustain agriculture and livestock, while water and energy shortages remains a huge challenge. While enjoying products and services offered in the market, consumers should protect their environment and maintain a healthy life style by purchasing green products which are environmental friendly. Prospective green consumer’s expression of interest in green products is not converted into actual purchase. The objective of this study is to examine the factors that influence consumer behavior in the purchase of green products. The study adopted mixed methods and a sample of 120 respondents was considered. SPSS was used for analysis. Qualitative data was analyzed using thematic analysis. Statistical significant association was found between the purchases of green products with the eight main predictors which are; Environmental attitudes, perceived effectiveness of environmental problems, perceived environmental responsibility, green products labelling, green product features, green product certification, environmental benefits of green products, governments concern about the environment. The study found a negative association between purchase of green products and consumers knowledge about environmental benefits. By gathering this information, marketers would be able to understand the factors which influence consumers in the purchase of green products. They would also be able to formulate various strategies to effectively attract more green consumers to purchase green products as part solution for environmental protection. The legislators, national policy makers and environmental activists could utilize this information to promote a positive green consumerism.

Role of Tropical Disturbances along the South Asian Monsoon Trough in the 2022 Pakistan Floods and the Implications for Interannual Variability

Abstract This study examined the atmospheric circulation patterns that were responsible for the severe flooding that occurred in Pakistan in 2022. It focused on the role of westward-propagating tropical disturbances (TDs) along the South Asian monsoon trough, which are associated with flood-related precipitation events. The study also investigated the interannual precipitation variation in Pakistan over 23 years from 2000 to 2022, using satellite-derived precipitation and atmospheric reanalysis. The results showed high precipitation in southern and central Pakistan, implying tropical influences. The precipitation was the highest in the past 23 years. The massive rainfall was brought by several TDs under the highest water vapor conditions, although a TD of South Asia climatologically tends to weaken before affecting Pakistan. Enhanced easterlies along the Indo-Gangetic Plain, part of the enhanced monsoon trough, supported high water vapor conditions over Pakistan. The high water vapor was also partly supported by the long-lasting active phase of the South Asian monsoon intraseasonal oscillation in 2022. Moreover, the La Niña condition increased moisture transport as a background. On an interannual time scale, the enhanced moisture flux over the Indo-Gangetic Plain resulted in higher precipitation over Pakistan, as occurred in 2022. These high (low) water vapor and precipitation can be partly explained by La Niña (El Niño). However, La Niña and El Niño may not control the TD activity over South Asia. Thus, for 2022, the high water vapor is somewhat empirically predictable, but the active TD activity can be coincidental. Significance Statement In 2022, Pakistan was hit by catastrophic flooding that affected 15% of the population. The analysis of the atmospheric circulation associated with the flooding indicates that weak but rain-bearing tropical disturbances played a significant role in flooding. Several tropical disturbances stayed or moved into Pakistan, bringing massive rainfall although, usually, they tend to weaken before hitting Pakistan. In the past 23 years, La Niña–related weather patterns have partly explained the year-to-year precipitation variation in Pakistan. However, in 2022, the unusually heavy flooding was due to the combined La Niña effect and tropical disturbance activity. Because it is still difficult to predict the seasonal tropical disturbance activity from La Niña, El Niño, and other climatic conditions, seasonal prediction of these floods remains challenging.

Seasonal and diurnal variations in leaf aroma volatiles of Cinnamomum tamala (Buch.-Ham.) T. Nees & Eberm as evidenced from metabolite profiling, histochemical and ultrastructural analyses.

Though the leaves of Cinnamomum tamala is extensively employed in culinary applications due to its rich aroma and therapeutic properties, the produce exhibits variability in composition and contents of leaf essential oil due to fluctuations in climatic conditions and harvesting time. This work evaluated the impact of seasonal and diurnal variations on the composition and contents of aroma volatiles in the mature leaves of C. tamala. In summer, the profile of aroma volatile was dominated by phenylpropanoids (112.96±24.11μg/g of freeze-dried leaf tissue) while in winter monoterpenes (58.45±8.194μg/g of freeze-dried leaf tissue) acquired the dominance. The variability in the contents of primary metabolites was shown to be influenced by the harvesting season and time. Organic acids and sugars showed highest accumulation in leaves harvested during summer evening and winter morning, respectively. Histochemical study showed the presence of lipids and terpenes in the secretory cells as revealed through sudan III and NaDi staining. The ontogeny of secretory oil cells that accumulate essential oil were elucidated through ultrastructural study.

Fighting against forest fire: A lightweight real-time detection approach for forest fire based on synthetic images

Forest fires are known for their high level of randomness and unpredictability, which often lead to significant ecological damage and human life loss. Existing forest fire detection technologies are not capable of detecting small-scale flames or smoke in real time, thus failing to meet the demands of real-time detection of forest fires using Unmanned Aerial Vehicles (UAVs). To overcome these limitations, we propose an efficient and lightweight forest fire detection method that utilizes synthetic images and UAVs to achieve real-time and high-precision detection of forest fires against complex backgrounds. Firstly, we propose the Dilation Repconv Cross Stage Partial Network (DRCSPNet), which enhances the detection capabilities for multiscale flames and smoke using multi-branch parallel joint dilation convolution and batch normalization, while effectively extracting features from different stages of forest fires. Secondly, to mitigate challenges associated with extreme lighting in forest scenes and large contrast variation in fire images, we propose a Global Mixed-Attention (GMA) model across feature pyramids to enhance information lost in high-dimensional feature maps and increase the robustness of the model through a multiscale fusion strategy. Finally, we present the Lite-Path Aggregation Network (Lite-PAN) with varying scales to improve effective feature flow for multilevel forest fires, addressing challenges that arise from various climatic conditions. Furthermore, we employ Unreal Engine 5 to generate forest fire datasets in four scenarios to address the issue of relatively limited aerial forest fire datasets. According to the results of the experiment, our proposed method achieves 58.39% mAP(mean Average Precision) with 5.703 GFLOPs (Giga Floating Point Operations Per Second) while yielding a frame rate of 33.5 Frames Per Second (FPS) on NVIDIA Jetson NX. Extensive experiment results demonstrate our method has the advantage of being in real time, extremely accurate, and easily implementable compared to state-of-the-art techniques.

Spatial and temporal analysis of decomposition models in China

This study presents a comprehensive evaluation of 15 decomposition models (12 empirical and 3 atmospheric transmittance models) for estimating diffuse horizontal irradiance at 17 radiation sites in China, using hourly radiation data from 2011 to 2020. Our results show distinct patterns in model performance across different geographical regions, seasons, and sky conditions. The Liu model demonstrates the best overall performance with an RMSE of 78.20 W/m2, while model accuracy shows significant geographical variation, performing best in South and Southeast China (RMSE<70 W/m2) and worst in the Qinghai-Tibet Plateau and Northwest China (RMSE>90 W/m2). Seasonal analysis reveals better performance in winter than in summer, with RMSE differences approaching 40 W/m2, mainly due to the higher proportion of solar elevation angles exceeding 30° in summer. Under different sky conditions (classified by clearness index: 0–0.35 for overcast, 0.35–0.65 for partly cloudy, 0.65–1 for clear skies), most models follow an RMSE pattern of partly cloudy > clear sky > overcast. However, the Reindl2, Boland, DIRINT, and DIRINDEX models deviate from this trend due to their formula structure and sensitivity to atmospheric parameters. To reduce these regional disparities, we propose a new region-specific model selection strategy: the DIRINDEX model for eastern regions, DIRINT for central areas, and Karatasou for western regions. This combined approach reduces the overall RMSE to 73.17 W/m2. This research deepens our understanding of the application of decomposition models in China's complex geographical and climatic conditions, offering valuable references for solar radiation modeling and renewable energy forecasting in diverse climatic regions.

Influence of Lithology and Biota on Stream Erosivity and Drainage Density in a Semi‐Arid Landscape, Central Chile

AbstractDrainage density is a fundamental landscape feature that determines the length scale for hillslope sediment transport and results from the competition of diffusive hillslope and advective stream incision processes, whose efficiencies are known to vary with rock type but are notoriously difficult to quantify. Here, we present a comprehensive analysis of a catchment in semi‐arid Central Chile, where landscapes with different drainage densities, but equal tectonic and climatic conditions, have formed on three neighboring granitoid plutons (a monzogranite and two diorites). We combined topographic analysis of a 1‐m digital elevation model with 10Be‐derived denudation rates to estimate stream erosivity and soil diffusivity in the different landscapes. We find that the higher drainage density in the monzogranite is primarily due to higher stream erosivity, whereas soil diffusivity is similar between rock types. Remote sensing data from Landsat imagery confirm field observations of higher vegetation cover in the diorites, especially with regard to deeper‐rooted shrubs, which may result in increased infiltration. Based on geochemical and compositional analyses, we link vegetation differences to a relatively higher abundance of plant‐essential elements in the diorite bedrock. Additionally, the monzogranite's composition and crystal grain size supports more intense physical weathering and leads to a smaller observed hillslope grain size, which increases its erodibility. We conclude that subtle differences in composition and grain size can have a significant impact on stream erosivity and drainage density. Our results demonstrate the importance of taking lithology into account when interpreting fluvial networks and topographic metrics in slowly eroding landscapes.

Biogeography of Australian Camphorosmeae and Diversification in Climatic Space and Across Arid Habitat Types.

This study investigates the biogeography of the Australian Camphorosmeae (Amaranthaceae s.l.) lineage and how it relates to shifts in climatic niche and habitat types. Building on previous research and data resources, we integrate molecular phylogenetics, bioclimatic data and biogeographical models to deepen our understanding of the diversification and adaptation of this group across Australia's diverse landscapes in relation to palaeoclimatic changes. For 159 species representing 12 genera, georeferenced distribution points were used to define the most informative bioclimatic variables using principal component analysis. Evolutionary shifts in climatic niches and habitat types were analysed, revealing clade-specific shifts and adaptations to different habitats and climatic conditions. Biogeographical analyses allowed us to infer ancestral areas of Camphorosmeae in Australia and relate their expansion over evolutionary time to habitat shifts. Preadaptation of this group to warm and dry habitats coupled with key periods of aridification in Australia, particularly during the Late Miocene to Pliocene, were critical in driving its diversification through migration and local adaptation to varied habitats of arid Australia. Our analyses suggest that the 'Riverine Desert' habitat offered suitable conditions for ancestral Australian Camphorosmeae and facilitated their early widespread dispersal in the Western and Eastern Desert. We hypothesise that early diverging lineages such as Roycea adapted to the later emerging 'Desert Lake' habitat when it spread in Western Australia during the Early Pliocene. Further, habitat type shifts occurred from 'Riverine Desert' to 'Shield Plain', 'Karst Plain' and to 'Sand Desert' also during the Pliocene and Pleistocene once these habitat types emerged. This study illustrates the complex interplay between ecological flexibility and niche conservatism in shaping the biodiversity of Australian Camphorosmeae.

Assessing the performance of smart buildings and smart retrofit interventions through key performance indicators: Defining minimum performance thresholds

Smart technologies play a vital role in facilitating the response of buildings to the external conditions, including climate, grid, and the internal building requirements such as user needs. A salient concern lingers in relation to existing buildings due to their increasing energy consumption. Around 35 % of EU buildings are older than 50 years and 90 % are built before the nineties. In this sense, smart retrofitting represents a key step towards achieving energy-responsive flexible buildings. Quantifying building energy performance with appropriate Key Performance Indicators is a critical step towards achieving decarbonization goals in both existing and new buildings. In this paper a group of five representative indicators has been selected to measure the energy performance of smart features in retrofitted and new buildings, also identifying distinct performance thresholds. Therefore, each threshold defines minimum acceptable and top performing values for the indicators. Accordingly, thresholds are set first based on previous literature and performance data, then a Logical Evaluation Methodology is used to identify suitable range of thresholds. Results of this paper propose a quantified definition for smart retrofitting, which involves transforming an existing building into a Smart Building. A smart building is a nearly Zero Energy Building that achieves primary energy savings of 30 % to 80 % and can adapt to changing climate and grid conditions. It should communicate with users and predict operational failures using a Building Energy Management System. Additionally, it should enable load shifting in response to renewable energy source production and electricity prices by 30 % to 70 % annually, while minimizing grid interaction to 10 % to 30 % on an hourly basis throughout the year. Furthermore, it should allow for RES self-consumption of 30 % to 70 % and cover 20 % to 70 % of the load with RES annually. Finally, the indicators are tested on a case study in Italy within a Horizon 2020 project to validate the thresholds.

Life Cycle Assessment of an Avocado: Grown in South Africa-Enjoyed in Europe.

Food production is known to have significant environmental impacts, with the main contributors residing in the farming and transportation life cycle phases. Of the various food products transported around the world, avocados have increasingly gained attention as a high-commodity superfood. Avocados require specific climatic and agricultural conditions for farming, with the most fertile land and conditions located outside Europe. Consequently, most avocados consumed in Europe are imported over vast geographical distances, with little information available to quantify the environmental impacts of this imported superfood. This paper aims to present the most detailed life cycle assessment results of an avocado cultivated, grown and harvested in the Limpopo Province of South Africa and exported to the European market for sale and consumption. A life cycle assessment was developed for the farming, harvesting, handling, packaging, ripening, transportation, and carbon sequestration potential of the avocado, and it was used to conduct a holistic life cycle assessment. Input data was obtained through an 18-month data collection campaign across the relevant stakeholders. A baseline 'business-as-usual' scenario is focused on throughout this study, and scope for optimisation is identified for each life cycle phase where applicable, accompanied by uncertainty analyses. Results show a total carbon input of 904.85 kg CO2e/tonne. Mitigating this, 521.88 kg CO2e/tonne is offset, resulting in a net carbon footprint of 382.97 kg CO2e/tonne with uncertainty ranges of -23.22 to +58.69 kg CO2e/tonne, normalised to 57.45 g CO2e/avocado grown in South Africa and sold in Europe. The environmental impacts of the avocado industry under consideration are largely mitigated by the "nature first" philosophy of the farming and logistics enterprises, which have made significant investments in reducing emissions. Sensitivity analyses indicate that implementing large-scale renewable energy, using alternative packaging instead of cardboard, and selling avocados unripened could further enable the farming enterprise to achieve Net Zero objectives. These measures could reduce baseline emissions from 382.97 kg CO2e/tonne to a theoretical -68.54 kg CO2e/tonne, representing a 117.9% decrease. Although this study does not quantify climate change impacts, qualitative analyses suggest that climate change will have a net negative effect on the avocado industry in South Africa. These regions, typically located in micro-climates, are projected to become wetter and warmer, adversely affecting crop phenology, pest control, road conditions, management complexity, farmer livelihoods, and food security. The study recommends large-scale implementation of the optimisation strategies identified to achieve Net Zero objectives and the development of proactive climate change mitigation strategies to enhance the resilience of avocado supply chains to future stressors. These insights are crucial for policymakers, industry stakeholders, and consumers aiming to promote sustainability in the avocado market.

Understanding the effects of livestock grazing on dryland plant communities within the context of abiotic variability

AbstractDrylands, which cover more than 40% of the Earth's terrestrial surface, face rising agricultural demand and the influence of climate change. Understanding how livestock grazing pressure and local climate affect these environments is pivotal for informed land management. We studied big sagebrush plant communities in southwestern Wyoming over grazing gradients created by artificial livestock watering points. To explore the role of abiotic factors in shaping plant community response to grazing, we assessed the response of plant functional groups to grazing while accounting for soil texture variability across a precipitation gradient. Our models estimated that sagebrush cover responded positively to grazing intensity, with a 6% increase in cover with intensity when comparing the heaviest grazing treatment with the lowest grazing intensity. Perennial bunchgrass cover, the primary forage component, had a small negative response, a 3% decrease in cover from the lowest grazing intensity to the highest. Grazing intensity had no effect on bunchgrass density, perennial forbs, or rhizomatous grasses. Compared with abiotic factors, grazing intensity had a small effect on perennial bunchgrass and bare ground. We found that precipitation explained a 13% increase in perennial bunchgrass cover and a 34% decrease in bare ground cover compared with a 6% increase with increasing intensity across our grazing gradients. Sand content also had a larger effect on perennial bunchgrass cover and density than grazing. Increased sand content was associated with increased bunchgrass cover and density, supporting the inverse texture hypothesis. Our results show that while livestock grazing impacts sagebrush plant communities, its effect is small when compared with the effects of climate and soil. Our study contributes to a growing body of research emphasizing the need to contextualize plant community responses to grazing within specific climatic and edaphic conditions, which will promote effective land management in dryland ecosystems.

Nature vs. nurture: Drivers of site productivity in loblolly pine (Pinus taeda L.) forests in the southeastern US

Forest productivity is one of the most important aspects of forest management, landscape planning, and climate change assessment. However, although there are multiple elements known to affect productivity, most of them rely on the “nature” of the edaphic, climatic, and geographic conditions, and only some specific aspects can be modified through forest management or “nurture”. Through evaluation of site resource availability and an understanding of the main drivers of productivity, management can present solutions to overcome site resource limitations to productivity. Therefore, understanding the implications of a specific management regime requires understanding what drives productivity across large spatial extents and among different management regimes. In this study, we used data from over 1 million hectares of industrial forestland, covering over 6000 different soils and several management regimes of Pinus taeda L. plantations, as well as plot-based data from the Forest Inventory and Analysis (FIA) program, facilitating a comparison of planted and natural Pinus taeda stands. Combined with US Geological Survey LiDAR data, we computed site index and generated wall-to-wall productivity maps for planted Pinus taeda stands in the southeastern US, as well as point-based site index estimates for the FIA dataset. We modeled site index using a random forest algorithm considering edaphic, geologic, and physiographic province information based on the Forest Productivity Cooperative “SPOT” system, and also included climate and management history data. Our model predicted site index with an R2 of 0.701 and RMSE of 1.41 m on the industrial data and R2 of 0.417 and RMSE of 1.84 m for the FIA data. We found that year of establishment of the forest, physiographic province, and geology, were the most important drivers of site index. The soil classification modifier indicating root restrictions were the most important soil-specific variable. Additionally, we found an average increase in site index of 3.05 m since the 1950s for all FIA data, and an average increase of 4.73 m for all industrial data since the 1970s. For the latest period analyzed (2000–2012), average site index in planted FIA plots was 1.2 m higher than naturally regenerated FIA plots, and site index in all industrial forestland had a site index almost 3 m greater than planted FIA plots. Overall, we believe this work sets the foundation for better understanding of forest productivity and highlights the importance of intensive silviculture to improve productivity, and as an additional tool to achieve the economic, environmental, and social objectives.

Combined effect of gilsonite, sasobit, and soft binder on performance characterization of high RAP binder

The purpose of this research is focused on the performance evaluation of Gilsonite-modified binders (GMBs) and high-aged binder (HAB) content (more than 40 %) with and without the use of WMA additive. Accordingly, GMBs and GMB-WMA samples were prepared by combining PG52–28 softer binders and 4 %, 8 %, 12 %, and 16 % of Gilsonite with and without Sasobit. The results indicated that increasing the Gilsonite increases the viscosity, improves the rheological behavior, reduces the rutting, and increases the fatigue life Although higher Gilsonite content has performance advantages, it also has negative effects in terms of performance and low temperature/fatigue resistance. While the use of a composite-modified binder showed an effective way to overcome these limitations and optimize the overall performance characteristics of HAB. Adding 4, 8, 12, and 16 Gilsonite combined with Sasobit increased the rutting resistance by 46 %, 64 %, 80 %, and 87 % respectively, compared to the base binder. Combining Sasobit with 8 and 12 Gilsonite upgraded the performance of the base binder from PG58–22 to PG70–16 and PG76–10. The fatigue life of the AB/G+WMA containing 4, 8, 12, and 16 Gilsonite was 2.11, 2.25, 2.52, and 2.38 times greater than the base binder, respectively. Based on optimization results, Gilsonite/Sasobit combinations were recommended for different traffic conditions: G15.3+S1.8 for heavy traffic areas, G11.6+S1.9 for tropical regions, and G6+S2 for cold climates. The goal was to optimize the blends to leverage the benefits of Gilsonite while mitigating any drawbacks, depending on the specific climate and traffic conditions. The study demonstrates that the synergistic use of Gilsonite and Sasobit can significantly enhance the performance characteristics of asphalt binders, enabling tailored solutions for different applications and environmental conditions.

Collaborative water-electricity operation optimization of a photovoltaic/pumped storage-based aquaculture energy system considering water evaporation effects

The increasing global population, economic development, and urbanization trends have led to a heightened demand for seafood, presenting a significant challenge to the growth trajectory of the food industry. As the most rapidly expanding segment within the food industry, aquaculture presents a sustainable solution to mitigate the overexploitation of marine resources and address the growing demand for food. Aquaculture's sufficient aquatic expanses offer considerable potential for PV deployment, thereby relieving the demand for limited land resources. However, existing research rarely addresses the collaborative operation of water and electricity in aquaculture systems. The effects of water evaporation from PV panel-covered water surfaces on the collaborative water-electricity operation are generally neglected. Hence, this work proposes a collaborative water-electricity operation of a photovoltaic (PV)-pumped storage-based aquaculture energy system considering the water evaporation effects. This optimization method accounts for the reduced water evaporation due to PV panel shading. Water surface PV and pumped storage are integrated into the system to fulfill electricity needs, with pumped storage serving as a dual-purpose device for water and electricity supply. Environmentally sustainable water-electricity generation and aquaculture energy system requirements are established. Water surface PV electricity generation is modeled based on climate and engineering conditions, while aquaculture pond electricity requirement includes oxygenation, feeding, and water replenishment. Finally, a collaborative water-electricity operation model is introduced to optimize operation strategies for various devices. A case study on a fish-light complementation project demonstrates that this optimization method can reduce reliance on the utility grid and overall system operational costs.

Provenance and pretreatment effect on seed germination of twenty-six provenances of Xanthoceras sorbifolium

ABSTRACT Due to the long dormancy period and hard seed coat, the natural germination percentage of yellowhorn (Xanthoceras sorbifolium) seeds is low, which seriously hinders the large-scale cultivation of the yellowhorn. In this study, the seeds of 26 provenances with different climatic and geographical conditions were collected and the seed germination was tested, which was conducted to determine the effects of seed pretreatment methods on the germination of yellowhorn. This study showed that the germination percentage (GP), mean germination time (MGT) and germination index (GI) of 26 provenances of yellowhorn seeds in different pretreatment methods were highly significant (p < 0.01). The sand storage + clean water and sand storage + PEG almost significantly promote the GP and GI, and reduce the MGT of all provenances, while the pretreatments of warm water and cold water have almost no promoting effect on the GP and GI. In addition, this study indicates that provenances are as important as pretreatments in germination ability. Correlation between germination ability and geo-climatic data of provenances showed that low temperature can improve seed germination ability. This study showed that the seed germination ability of yellowhorn can be improved by using combined pretreatments for provenances with genetically low germination potential.

Geographical variability in hygrothermal simulation results of historical building envelopes with interior insulation in Belgium

Thermal retrofits of existing buildings offer a great potential to reduce Europe’s energy use and CO2 emissions. The impact of these retrofitting strategies on the risk for degradation in building envelopes is assessed through hygrothermal simulations. Due to the lack of long term climate data, hygrothermal simulations are performed for a certain location, and the results are generalised over a large region. However, this generalisation may not be valid, since the hygrothermal performance of building envelopes is highly influenced by local climate conditions. Therefore, we assessed the geographical variability on degradation risks in building envelopes. This paper presents the results of 34560 hygrothermal simulations of solid masonry walls, with and without interior insulation, and including a range of other parameter variations, for 20 synoptic weather stations across Belgium. Generally, the risk for degradation is higher at locations with a higher elevation above sea level. For Belgium, the elevation correlates well with the mean temperature (invers correlation), and the annual precipitation and wind-driven rain load. For a known wall orientation, the impact of interior insulation on the risk for freeze-thaw damage is most determined by the elevation above sea level. Also the mould index in uninsulated walls correlates best with the elevation. On the contrary, the brick type is more important than the location when considering wood decay of embedded beam heads in retrofitted walls. To conclude, the risk for degradation cannot be generalised, especially over areas with complex variations in orographic and climatological conditions.

Optimized design and comparative analysis of double-glazed photovoltaic windows for enhanced light harvesting and energy efficiency in cold regions of China

This study investigates the daylighting performance and energy efficiency optimization strategies of double-glazed photovoltaic windows (DS-STPV) in cold regions of China. By conducting a comprehensive comparative analysis with traditional and energy-efficient window systems, this research aims to identify high-efficiency building solutions tailored to extreme climatic conditions. Amidst the escalating global energy demand and the pressing need for energy conservation and emission reduction, Building-Integrated Photovoltaic (BIPV) technology is increasingly recognized for its potential and value as a critical method for harnessing green energy. However, the widespread adoption of BIPV technology faces several challenges, including cost-effectiveness, conversion efficiency, system stability, and architectural aesthetic integration. Utilizing the T&A House from the 3rd International Solar Decathlon as an empirical case study, this research employs Ecotect and DesignBuilder simulation software to systematically evaluate the daylighting effect and energy performance of DS-STPV. The analysis considers various key design parameters, including photovoltaic cell coverage, window orientation, and window-to-wall ratio. Through refined modeling and multi-dimensional analysis, this study aims to identify the optimal design configurations of DS-STPV windows in cold regions, with the goal of simultaneously achieving superior natural lighting quality and significant building energy efficiency. The findings indicate that a south-facing DS-STPV window design with approximately 30% photovoltaic cell coverage and a window-to-wall ratio of 30% effectively balances daylighting requirements and energy efficiency in cold regions of China. This design strategy not only ensures an abundance of natural light in the room, but also significantly reduces the building’s energy consumption, proving the superior performance of DS-STPV windows in cold climates. In addition, the unique optical properties of DS-STPV windows reduce glare, further improving the overall quality of the indoor environment. In summary, this study provides a robust scientific foundation for the application of DS-STPV windows in cold regions, offering practical guidance and reference for optimizing energy efficiency and facilitating green transformation in future building design.

Analysis of the influence of climate change on monthly energy consumption in Ireland

Abstract. This article focuses on the influence of climate change on energy consumption in Ireland. The purpose is to conclude this influence and give the Irish energy companies a better understanding of energy production. All the data sources were collected from the official websites of the Irish government. The article chose several climate factors such as wind speed and temperature etc. This paper especially concentrates on electronic power consumption. All these data were transformed into a monthly form. The author used linear regression models to analyse the relationships between climate factors and Energy consumption. The R studio is one of the most important tools for this research. The author creates many kinds of linear models to fit the data accurately. The main discovery of the research is that temperature has the most significant influence on energy consumption. They have a strong linear relationship. The Irish government might need to manage electricity production based on the temperature change to fit the citizens' needs and avoid risks of severe climate conditions in the future.