Search Results (29)

Agro-photovoltaics (APV) or agrivoltaic systems integrate crop cultivation with solar energy production, offering a promising solution through the dual-use of land. This two-year study (2023 and 2024) examined the effects of an APV system on rice production. The results indicated that APV arrays created spatially variable light environments, with shadow lengths following predictable solar azimuth patterns and cloudy conditions mitigating shading effects through enhanced diffuse light. Compared with CK (non-shadow area), inter-panel plots (BP) maintained 77% photosynthetic efficiency and 85.4% plant height, whereas the areas beneath the panel showed a significant decrease in the relative chlorophyll content (SPAD values), photosynthesis rates, and yield. BP plots preserved a 78% fruiting rate through adaptive stomatal regulation, whereas LP zones (directly under the low eave) exhibited 35% higher intercellular CO₂ because of the limited assimilation in shading. Rice yield losses were correlated with shading intensity, driven by reduced panicles and grain filling. Moreover, the APV system achieved a high land equivalent ratio of 148–149% by combining 65–66% rice yield with 82.5% photovoltaics output. Based on the microenvironment created by the APV system, optimal crop types and fertilisation are essential for enhancing agricultural yields and improving land use efficiency. Full article

Protected structures with drip fertigation systems have allowed many countries around the world to grow high-value vegetables, such as tomatoes and bell peppers year round, particularly under adverse edaphoclimatic conditions. This paper evaluates the feasibility of tomato and bell pepper cultivation in Sunshine Pacific Limited. Farm in Tanumalala, a commercial farm in Samoa, under a protected cultivation system with drip fertigation. The yield, water use efficiency, establishment and maintenance costs, and the average return per hectare of production were analyzed. Additionally, economic feasibility indicators were estimated using the discount factors of 6.5% and 11%. Results showed that the annual yield of tomatoes (163,500 kg/ha) was higher than bell peppers (103,500 kg/ha). The water use efficiency (WUE) and product water use (PWU) of these two crops in this study were less efficient compared to what was observed in other countries, as indicated by the value of the respective WUE and PWU: 8.38 kg/m³ and 0.12 m³/kg for tomatoes while 5.31 kg/m³ and 0.19 m³/kg for capsicum. Despite the high initial establishment cost, all economic feasibility parameters indicated that the system is profitable, having a BCR ratio of more than 2, and feasible under Samoa conditions, mostly due to the high market price. Thus, this system of cultivation could be an option for growing high-value vegetables in Samoa. However, further research is needed to improve the yield and water use efficiency. Full article

The relationship between plants and their environment has always been a core issue in ecological research. This study about how plant architecture and leaf traits respond to environmental changes helps to more deeply understand the adaptive mechanisms of plants in diverse environments. Although there have been related studies, a systematic analysis on a China-wide scale is still lacking. To address this gap, we conducted a meta-analysis of 115 studies across China examining plant architectural and leaf trait responses to environmental changes. The dataset includes 849 observations across 11 ecological variables, such as the mean annual precipitation, mean annual temperature, soil type, and elevation, and evaluates their effects on seven key plant traits. The results indicated that variations in the plant height, diameter at breast height (DBH), and root-to-shoot ratio are primarily influenced by the soil type and mean annual precipitation. In contrast, the soil type and mean annual sunshine duration mainly affected the specific leaf area (SLA), leaf area, leaf thickness, and leaf dry matter content. Moreover, while the magnitude of trait responses varies across precipitation, temperature, elevation, and soil property gradients, the impacts of environmental change are particularly pronounced under more extreme conditions. This study provides robust scientific evidence for understanding the effects of environmental change on plant growth across China and offers valuable insights into ecological conservation and the sustainable use of plant resources. Full article

Solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to estimate the solar irradiance of typical irrigation areas. The relation between meteorological parameters and solar irradiance is studied, and four different parameter combinations are formed and considered as inputs to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as input parameters. In the model testing, the RMSE and MAE of WOA-XGBoost are 2.142 MJ·m⁻²·d⁻¹ and 1.531 MJ·m⁻²·d⁻¹, respectively, while those of XGBoost are 2.298 MJ·m⁻²·d⁻¹ and 1.598 MJ·m⁻²·d⁻¹. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model. The model developed in this study can be applied to forecast solar irradiance in different regions. By inputting the meteorological parameter data specific to a given area, this model can effectively produce accurate solar irradiance predictions for that region. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines. Full article

The aging of the population is not only a global challenge, but it is also a major concern in the research on environmental behaviors. Urban green spaces are regarded as crucial for the well-being of the elderly. However, there is still a lack of in-depth investigation into the effect of spatial factors on the public activities performed by the elderly in urban parks in cold weather. Therefore, this study is aimed at filling this gap, with Nankai Park in Tianjin as the research object. In order to achieve this purpose, the behavioral patterns of elderly park users are mapped in this paper, based on participatory observation in combination with the collection of spatial data through continuous photography. To begin with, the park space is divided into 23 areas for correlation analysis. UCL Depthmap software is then used for park space syntax analysis, with Tangent used to evaluate the sunshine (shadow) factors. Specific indexes are established to quantify the spatial factors in each area, such as the shortest distance to the exit, the green space ratio, and facility density. GIS (Geographic Information System) is applied for data integration, and SPSS is applied to reveal the correlation between the behavioral data and the selected spatial factors. The key findings are as follows. (1) There are four space syntax indexes closely correlated with the activities that the elderly participate in. (2) The solar (overshadowing) conditions play an important role in the distribution of elderly park users. (3) There is no definitive relationship exhibited by the pattern of activities performed by the elderly with various factors such as number and diversity of seating facilities as well as the quantity and diversity of seating facilities. Finally, this analysis aims to explore research methodology that extends from qualitative observation to quantitative analysis. Future research will focus on the shaping of aging-friendly urban communities, which is expected to deepen our understanding of public activities held within urban parks in cold weather across the northern cities of China. Full article

Ghana, being blessed with abundant solar resources, has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority (BPA) exemplifies the nation’s dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system’s performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one year’s worth of monitoring data for the climatic conditions at the facility and AC energy output fed into the grid. These data were used to analyze PV performance on each month’s sunniest and cloudiest days. The goal is to aid in predicting the system’s output over the next 365 days based on the system design and weather forecast and identify opportunities for system optimization to improve grid dependability. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between 16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analyses showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant’s performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant’s performance from deteriorating. Optimizing a solar PV system’s design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days. The study reveals the necessity of hydropower backup during cloudy days, enabling BPA to calculate the required hydropower for a consistent grid supply. Being able to predict the daily output of the system allows BPA to optimize dispatch strategies and determine the most efficient mix of solar and hydropower. It also assists BPA in identifying areas of the solar facility that require optimization to improve grid reliability. Full article

The potential of generalized deep learning models developed for crop water estimation was examined in the current study. This study was conducted in a semiarid region of India, i.e., Karnataka, with daily climatic data (maximum and minimum air temperatures, maximum and minimum relative humidity, wind speed, sunshine hours, and rainfall) of 44 years (1976–2020) for twelve locations. The Extreme Gradient Boosting (XGBoost), Gradient Boosting (GB), and Random Forest (RF) are three ensemble deep learning models that were developed using all of the climatic data from a single location (Bengaluru) from January 1976 to December 2017 and then immediately applied at eleven different locations (Ballari, Chikmaglur, Chitradurga, Devnagiri, Dharwad, Gadag, Haveri, Koppal, Mandya, Shivmoga, and Tumkuru) without the need for any local calibration. For the test period of January 2018–June 2020, the model’s capacity to estimate the numerical values of crop water requirement (Penman-Monteith (P-M) ETo values) was assessed. The developed ensemble deep learning models were evaluated using the performance criteria of mean absolute error (MAE), average absolute relative error (AARE), coefficient of correlation (r), noise to signal ratio (NS), Nash–Sutcliffe efficiency (ɳ), and weighted standard error of estimate (WSEE). The results indicated that the WSEE values of RF, GB, and XGBoost models for each location were smaller than 1 mm per day, and the model’s effectiveness varied from 96% to 99% across various locations. While all of the deep learning models performed better with respect to the P-M ETo approach, the XGBoost model was able to estimate ETo with greater accuracy than the GB and RF models. The XGBoost model’s strong performance was also indicated by the decreased noise-to-signal ratio. Thus, in this study, a generalized mathematical model for short-term ETo estimates is developed using ensemble deep learning techniques. Because of this type of model’s accuracy in calculating crop water requirements and its ability for generalization, it can be effortlessly integrated with a real-time water management system or an autonomous weather station at the regional level. Full article

This article compares the differences and similarities in residential layout and scale between Barcelona, Spain and Tianjin, a northern Chinese city, using Ladybug. We obtained sunshine simulation results under the same conditions in terms of building façades, lower floors, streets, courtyards and other aspects in two cities. Based on this, this paper draws on the advantages and disadvantages of the dense street network in the Eixample district of Barcelona and provides suggestions for the residential layout of cities in northern China. The aim of this study is to improve the residential layout of cities in northern China, while meeting the requirements of plot ratio and taking into account the favorable sunshine conditions in Barcelona. A key aspect of this study is the emphasis on the importance of capturing sunlight in future urban designs. Specifically, it highlights the potential for installing solar panels in areas with effective sunlight exposure of more than three hours daily such as streets, façades, rooftops and courtyards to harness solar energy and conserve resources. This paper compares the similarities and differences between the residence layout and scale in Barcelona, Spain and northern Chinese cities, regarding the overall façade of the building, the lower part of the building, and the streets and courtyards of the two coastal cities by using Ladybug to obtain sunshine simulation results under the same conditions and drawing lessons from the small block, dense street network of Barcelona’s Eixample district so as to put forward suggestions for the residential layout of northern Chinese cities. Research has found that the layout form of Barcelona housing is similar to the plot ratio of point and panel residential buildings in northern Chinese cities and has better hygiene conditions such as sunshine. Full article

To study the influence of multi-factors, such as long sunshine, sand erosion, and so on, in southern Xinjiang, we selected two kinds of composite insulators for the transmission lines in southern Xinjiang to study the aging characteristics of the umbrella skirt surface. The results of scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS) show that the surface roughness of the umbrella skirt is high and there are a large number of micron inorganic particles. The skirt has the characteristics of low C/O element ratio and high Al element content. The results of thermogravimetric analysis and micro infrared test show that the aging depth of the Myli Line skirt after 19 years of operation is 160~190 µm and that of Yuhe Line 1 after 14 years of operation is greater than 180 µm. The plasma discharge method was used to simulate the corona discharge in the actual operation to accelerate the aging of the surface of the umbrella skirt and the hydrophobic recovery of the umbrella skirt was investigated. The results show that the temperature has a great influence on the surface hydrophobic recovery performance after plasma treatment. These results may provide some theoretical guidance and technical support for the selection, operation, and maintenance of composite insulators in Xinjiang. Full article

The radiative budget is one of the key factors that influences climate change. The aim of this study was to analyze the radiative regime in Moscow using the RAD-MSU(BSRN) complex and to estimate the radiative effects of the main geophysical factors during the 2021–2023 period. This complex is equipped and maintained according to the recommendations of the Baseline Surface Radiation Network; however, it is not a part of this network. In cloudless conditions, the decrease in global shortwave irradiance (Q) is about 18–22% due to the aerosol content with a pronounced change in the direct to diffuse ratio. In winter, the increase in Q is about 45 W/m² (or 9%) at h = 30° due to a high surface albedo and reduced aerosol and water vapor contents, while the net shortwave irradiance (Bsh) demonstrates a significant decrease due to the prevailing effects of snow albedo. In cloudy conditions, a nonlinear dependence of Q and Bsh cloud transmittance on the relative sunshine duration is observed. The mean changes in Q for the 2021–2023 against the 1955–2020 period are characterized by negative anomalies (−22%) in winter and positive anomalies in summer (+3%) due to the changes in cloudiness. This is in line with the global tendencies in the long-term changes in shortwave irradiance in moderate climates in Europe in recent years. Full article

A 105-year chronology (AD 1917–2021) was developed from mountain birch (Betula pubescens Ehrh.) from beyond the coniferous treeline on the Kola Peninsula in Northwestern Russia (68.86 N, 34.69 E). A total of 22 trees were cored, including the oldest living mountain birch of 105 years old. The highest correlations occurred for the May temperature (r = 0.39, p < 0.01) and July sunshine duration (r = −0.39, p < 0.05). The increase in radial growth in May seemed to be caused by snowmelt giving rise to soil temperature, which can lead to a resumption in radial growth after winter dormancy. The negative correlation with the July sunshine duration seemed to be connected to changes in the spectral composition of solar radiation in the red to far-red ratio in the end of the polar day in July. The application of wavelet coherency revealed a significant (>95%) connection between the radial growth of B. pubescens, and solar activity in frequency bands encompassed the main solar cycles: 5.5 years (the second harmonic of the Schwabe cycle), 11 years (the Schwabe cycle) and 22 years (the Hale cycle). The results show that the northernmost birch trees in Europe are suited for tree-ring research. This allows us to expand the area of dendrochronological research further beyond the conifer treeline above the Polar Circle. Full article

The upper treeline ecotone is a global and typically climate-dependent phenomenon. Its elevation is usually coupled with the thermal limitations of tree growth. The air temperature rise connected with global warming is assumed as the main cause of treeline upslope shifts in the last century. It has been found that the treeline elevation also correlates with the distance from the coastline and the aridity or continentality of the climate or the mass elevation effect. However, previous and contemporary publications have not explained how the upper treeline position directly couples with climate parameters. Often, this has been restricted by a lack of climate measurements and spatial data. In our study, we obtained data from 339 regional weather stations for 1964–1974 and interpolated them to Altay and Western Sayan using regional DEMs and a specially developed regression model. Moreover, we semiautomatically identified the elevational position of the upper open forest boundary (OFB) (crown closure > 10%) on the slopes of 30 mountains in Altay and Western Sayan in 1960 and 2020. We took into account the slope aspect and edaphic constraints. The obtained data allowed us to undertake a regression analysis of the dependence of the OFB elevation on climatic parameters. As a result, we found that, in the 1960s, at OFB elevations rising from the outer to the inner parts of the study area to approximately 500–700 m, the summer air temperature and precipitation linearly decreased, but the summer sunshine duration increased. In the multiple regression analysis, including the climatic parameters as independent variables and the OFB elevation as a dependent variable, significant relations were found only for the combination of air temperature and sunshine duration. We assume that the OFB elevation is determined not only by the air temperature but also by the direct solar irradiation level, changing with latitude and cloudiness. We also found that the ratio between the OFB elevation on the northern and southern slopes varied with respect to latitude. The spatial analysis of OFB shifts in 1960–2020 revealed significant differences in its value in the central (80–90 m) and outer parts of the study area (110–130 m). We suppose that the OFB advance over the past 60 years has local specificity associated with the peculiarities of the climatic changes (summer temperature rise, precipitation decrease, and sunshine duration increase) in different parts of Altay and Western Sayan. Our results highlight the need to clearly determine climatic parameters when forecasting woody vegetation reactions to future climate changes. Full article

The release of toxic effluents and microfibers during the frequent washings of textiles poses a major threat to the environment. On the one hand, the detrimental effluents from detergents pose a threat to marine biota in peril, and on the other, microplastics have even been found in breastmilk. According to this study, functionalized metal-doped TiO₂ nanoparticles can be immobilized to create fabrics that are hygienic and antibacterial. There is a need to reduce the amount of different detergents, surfactants and chemicals used to remove stains. The manufacture of pristine and Cu-, Ag- and Zn-doped TiO₂ nanoparticles having trace molar ratios of dopant chosen with a simple sol–gel approach using pad–dry–cure silane coupling agents, firstly with the functionalization and then the immobilization of nanoparticles, was successfully performed on cotton fabric. The as-obtained fabrics were evaluated for their crystallinity, chemical functionalities, surface morphologies and elemental compositions. The photodegradation potentials of unfunctionalized materials were assessed in ambient sunshine against five commercial colors. Within three hours of sunshine exposure, according to color strength analysis and antibactericidal activities, 95–98% of the dye was degraded from the functionalized fabric surface. Additionally, the treated content kept its mechanical and comfort qualities. Full article

Preserving the authenticity of forest colors is essential to highlight regional characteristics and promote the sustainable development of forest landscapes. However, the factors and mechanisms influencing forest color remain unclear. We quantified 1422 forest color images from 43 parks across seven biogeographic regions in China to capture the forest color composition among regions. A generalized linear mixed-effects model was used to analyze the effects of meteorological and anthropogenic disturbance factors on forest color. Meteorological factors included accumulated sunshine hours, average temperature, accumulated precipitation, frost-free period, average wind speed, and average air quality index. Anthropogenic disturbance factors included park feature indicators (area, elevation, and perimeter-area ratio) and human activity indicators (distance to urban areas, building density, and road density). We calculated p-values and relative effect estimates to determine the sensitivity and degree of sensitivity of color to each factor. The results indicated the following: (1) forest color composition varied significantly among different regions in China with variations observed particularly in the proportions of primary (green), secondary (yellow and yellow-green), and accent colors (orange and blue-green); (2) forest colors were sensitive to all meteorological factors; (3) orange, yellow, purple, and red were all sensitive to anthropogenic disturbance factors; and (4) forest accent colors were more strongly influenced by anthropogenic disturbance factors, particularly park features. To protect the authenticity of forest colors, it is necessary to avoid excessive borrowing of forest color schemes from different regions, control park features, reduce building area within the park buffer zones, and optimize park tourism routes. Full article

The symbiotic photovoltaic (PV) electrofarming system introduced in this study is developed for the PV setup in an agriculture farming land. The study discusses the effect of different PV system design conditions influenced by annual sunhours on agricultural farm land. The aim is to increase the sunhours on the PV panel for optimized electricity generation. Therefore, this study combines the Taguchi method with Grey Relational Analysis (GRA) to optimize the two quality characteristics of the symbiotic electrofarming PV system with the best design parameter combination. The selected multiple quality characteristics are PV power generation and sunhours on farm land. The control factors include location, upright column height, module tilt angle, and PV panel width. First, the Taguchi method is used to populate a L9(3⁴) orthogonal array with the settings of the experimental plan. After the experimental results are obtained, signal-to-noise ratios are calculated, factor response tables and response graphs are drawn up, and analysis of variance is performed to obtain those significant factors which have great impact on the quality characteristics. The experiments show that the parameters which effects power generation are: location, upright column height, module tilt angle, and PV panel width. The ranking of the degree of influence of the control factors on the quality characteristics is location > PV panel width > module tilt angle > upright column height. By controlling these factors, the quality characteristics of the system can be effectively estimated. The results for PV power generation and sunhours on farm land both fall within the 95% CI (confidence interval), which shows that they are reliable and reproducible. The optimal design parameter realized in this research obtains a power generation of 26,497 kWh and a sunshine time of 1963 h. The finding showed that it can help to build a sustainable PV system combined with agriculture cultivation. Full article