Stations In Region Research Articles

Performance Evaluation and Spatiotemporal Dynamics of Nine Reanalysis and Remote Sensing Evapotranspiration Products in China

Evapotranspiration (ET) is a critical component of the hydrological cycle. The eddy covariance data at 40 flux stations in different climatic regions in China were used to evaluate the accuracy of five reanalysis actual ET datasets (ERA5, ERA5-LAND, GLDAS-2.1, MERRA-2, TerraClimate) and four remote sensing estimation ET datasets (ETMonitor, GLEAM4.2a, PML_V2, SiTHv2), which are widely used by the hydrometeorological and climatological communities, in terms of the root mean square error, Pearson correlation coefficient, mean absolute deviation, and Taylor skill score. The results show that remote sensing products outperform reanalysis datasets. Among them, ETMonitor has the highest accuracy, followed by PML_V2 and SiTHv2. TerraClimate and MERRA-2 have the least agreement with the observations at flux sites across nearly all evaluation metrics. All products can capture the seasonality of ET in China, but underestimate ET in northwest China and overestimate ET in southern China throughout the year. We tried to merge three optimal data products (ETMonitor, PML_V2, and SiTHv2) using the triple collocation analysis method to improve the ET estimation, but the results showed that the improvement by the data fusion approach is marginal. The estimation of the multi-year average evapotranspiration during the period from 2001 to 2020 ranges from 397.8 mm/year (GLEAM4.2a) to 504.8 mm/year (ERA5-Land) in China. From 2001 to 2020, annual evapotranspiration in China generally increased, but with varying rates across different products. MERRA-2 showed the largest annual increase rate (3.71 mm/year), while SiTHv2 had the smallest (0.17 mm/year). There are no significant changes in the seasonality of ET by most ET products from 2001 to 2020, except for PML_V2 and SiTHv2, which indicate an increase in seasonality in terms of the evapotranspiration concentration index. This ET intercomparison addresses a key knowledge gap in terrestrial water flux quantification, aiding climate and hydrological research.

Positive soil responses to different vegetation restoration measures in desert photovoltaic power stations

Scientific and reasonable vegetation restoration plays a pivotal role in enhancing soil quality, boosting ecosystem services, and ensuring the long-term stable operation of photovoltaic (PV) power stations in desert regions. To elucidate the response mechanisms of soil under different vegetation restoration implemented in PV power stations located in sandy areas, this study selected the PV power plant in Duguitala Township of the Hobq Desert as a representative research site. A systematic evaluation was conducted on the effects of four artificial vegetation restoration strategies, namely, Leymus chinensis (LC), Glycyrrhiza uralensis (GU), Artemisia ordosica (AO), and Hedysarum scoparium (HS) under panels and between panels. This analysis aimed to clarify the influence of different vegetation restoration approaches on soil quality in sandy regions and their underlying mechanisms. The findings revealed that these vegetation restoration measures significantly impacted soil texture, bulk density (BD), soil porosity (SP), soil water content, and water retention capacity. Specifically, LC and GU markedly improved soil physical structure and water retention capacities. Vegetation restoration substantially enhanced soil nutrient accumulation, with LC achieving the highest levels of multiple soil nutrient indices (total nitrogen (TN), total phosphorus (TP), and available potassium (AK)), HS exhibiting the highest level of available phosphorus (AP), and GU demonstrating superiority in total potassium (TK). These diverse vegetation restoration strategies exhibited potential advantages in improving soil fertility and promoting nutrient cycling at locations under PV panels. The soil quality index (SQI) showed that the effectiveness of the different vegetation measures in enhancing soil quality was ranked GU>LC>HS>AO>CK. This study not only provides robust theoretical support for ecological restoration in desert PV plants, but also offers practical experience applicable to vegetation restoration efforts in similar ecological environments, thereby possessing significant ecological and practical value.

Reducing CO2 Emissions in Urban Infrastructure: The Role of Siliceous Fly Ash in Sustainable Mortar Design

The incorporation of industrial by-products such as fly ash (FA) into cementitious materials plays a vital role in promoting environmental sustainability during cement production. This study evaluates the feasibility of using siliceous fuel fly ash, sourced from thermal power stations in the Rhenish region of Germany, as a partial cement replacement in mortar formulations. Mortar specimens with FA replacement levels ranging from 5 wt% to 30 wt% were prepared and tested. Data were collected through standardized laboratory testing of mechanical properties (compressive and flexural strength), physical characteristics (porosity, sorptivity) and microstructural analysis via SEM and XRD. The results showed that increasing FA content generally led to reductions in strength and increases in porosity and sorptivity, due to the mineralogical composition and higher water demand linked to the porous FA structure. However, when FA was used at levels not exceeding 10 wt%, the physical and mechanical properties remained within acceptable limits for construction applications. Additionally, the use of plasticizing admixtures proved effective in mitigating workability and strength issues by reducing the water-to-binder ratio. These findings highlight that, despite certain limitations, siliceous FA can be safely and effectively used in low percentages, contributing to sustainable mortar production and reducing reliance on Portland cement. In addition, the use of fly ash contributes to reduced CO2 emissions and lower production costs, promoting sustainable and cost-efficient construction solutions.

Beidou UPD estimation and assessment based on LEO-assisted regional stations observations

Beidou UPD estimation and assessment based on LEO-assisted regional stations observations

Assessing the performance of multivariate data analysis for predicting solar radiation using alternative meteorological variables

This research analyses how well the Partial Least Squares Regression models could predict the monthly average daily global solar radiation for seven stations in the Mediterranean region of Türkiye. Five model scenarios were created with the SARAH-3 satellite dataset from 2005 to 2023 and using ERA5-AG meteorological variables. These included maximum and minimum temperature configurations, dew point temperature, precipitation, wind speed, and vapor pressure. Different models were examined for their prediction success by using different criteria and assessing the models with varying performance evaluation benchmarks. Based on the results, the models were accurate, mainly when all the predictor variables were used. The highest predictive performance was observed at Burdur station with KGE=0.937, NSE=0.901, and RSR=0.322. The greater regional variations showcased the specific meteorological parameters’ relevancy. The results also support the adequacy of the ERA5-AG dataset for climate modelling and resource evaluation purposes. Unlike traditional regression approaches, this study demonstrates the efficiency of PLSR in handling high-dimensional climatic datasets for solar radiation prediction. These findings support the reanalysis of data in renewable energy and agricultural applications, particularly in data-limited regions.

Investigating the Spatiotemporal Variation in Extreme Precipitation Indices in Iran from 1990 to 2020

This study examines the spatiotemporal characteristics of extreme precipitation indices in Iran. It analyzes data from 38 synoptic stations across the country, covering the period from 1990 to 2020, focusing on the 11 most common extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis employs the Mann–Kendall (M–K) trend test. The findings indicate that the indices PRCPTOT (annual total precipitation), R20 mm (very heavy precipitation days), R10 mm (heavy precipitation days), R25 mm (number of wet days), Rx1 day (maximum 1-day precipitation), Rx5 day (maximum 5-day precipitation), SDII (simple daily intensity index), R95p (very wet day precipitation), R99p (extremely wet day precipitation), and CWDs (consecutive wet days) showed the highest values in the northern and western regions of the country, particularly at stations like Ramsar, Hamedan, Ilam, Kermanshah, and Yasouj. Conversely, the eastern and southeastern parts of the country showed the lowest values for these indices. The Consecutive Dry Day (CDD) index exhibited the highest values at Zabol station (228 days) and Abadan station (193 days) in the southern region of the country. Generally, precipitation extremes in the western, northwestern, and Caspian Sea coasts showed an increasing trend, while the eastern, southeastern, and central parts of the country demonstrated a decreasing trend. The trend test results indicate significant mutations in all precipitation indices, except for SDII, with mutation points primarily occurring during the decade from 2000 to 2010. The magnitude of mutation for each index post-mutation is generally greater than before. This study provides valuable information for decision-makers in agriculture, food security, water, and the environment. It also serves as a resource for natural disaster prevention and mitigation.

Impact of Environmental Pollutants on Otorhinolaryngological Emergencies in the COVID-19 Era

Air pollution (AP) is a critical environmental factor influencing public health, with well-documented associations with upper respiratory tract (URT) diseases. This study investigates the relationship between ENT emergency department (ENT-ED) visits at Azienda Ospedale Università di Padova (AOPD) and daily concentrations of environmental pollutants during the first year of the COVID-19 pandemic (March 2020–March 2021), compared to pre-pandemic data from 2017. The study focuses on patients diagnosed with URT inflammatory diseases, excluding those with COVID-19 infection, who sought care at the AOPD ENT-ED. Environmental data, including meteorological variables, air pollutants, and major aeroallergen levels, were collected from regional monitoring stations. A total of 4594 patients were admitted in 2020/2021, marking a 37% reduction from 2017, with URT inflammatory admissions decreasing by 52%. A significant decline in PM10, NO2 and Alternaria levels was observed, whereas Betullaceae and Corylaceae concentrations significantly increased. Multivariate analyses revealed strong associations between aeroallergen exposure and ENT admissions, particularly for Alternaria, which had a notable impact on total admissions (p < 0.001) and was significantly linked to cases of otitis media and tonsillitis. PM10 concentrations on specific days preceding ED visits were associated with increased incidences of pharyngitis and rhinosinusitis (p < 0.05). These findings reinforce the connection between environmental pollutants and ENT emergency visits, highlighting the adverse effects of AP and climate variables on URT diseases, even during a pandemic when enhanced airway protection measures were in place. This study underscores the necessity of stringent air quality regulations and interdisciplinary strategies to mitigate environmental health risks and inform future public health policies.

Asessment of elite Indian wheat genotypes for drought tolerance

To understand the plasticity of adaptation to different environmental conditions, eighteen elite wheat genotypes were evaluated for two seasons (2017-18 and 2018-19) under water-stress and controlled environments at ICAR-Indian Agricultural Research Institute (IARI), Regional station, Indore, India. Combined analysis of variance for grain yield under both water regimes showed that effects due to the water regimes, environment and genotype all interactions were found to be significant. Genotypes viz., NI 5439, HI 8791and HI 1531 were found to perform stable under both water regimes with high mean yield. Based on PCA biplot and GGE biplot analysis it is evident that genotypes HI 8793, HI 8790 and HI 1619 were the highly adapted, most stable and high yielding genotypes. HI 8791, HI 1531, NI 5439, HI 8793, HI 8790 and HI 1619 were identified to be stable for grain yield and can be utilized further in the breeding program for climate resilient wheat varieties development. Keywords: Wheat, Drought, GGE biplot, PCA, yield

Nitrogen levels and growth regulators effect on wheat (Triticum aestivum) lodging, productivity and profitability under restricted irrigation in a Vertisols of Central India

The field experiment was carried out during rabi seasons of 2019–20 and 2020–21 at Research Farm of ICARIndian Agricultural Research Institute, Regional Station, Indore (M.P). A total nine treatments consisted of absolute control, 50%, 75%, 100%, 125%, 150% doses of recommended N, 100%, 125% and 150% N along with Growth regulators (Grs) spray were laid out in randomized block design with three replications under restricted irrigation condition. Pooled analysis revealed that spray of Grs along with 100 to 150% of recommended N significantly decreased the plant height and ultimately reduced lodging. However, maximum grain yield (4.40 t/ha) recorded with 100% N was statistically at par with 100 and 150% of N applied along with Grs but significantly higher over rest of the treatments. Wheat crop was lodged only in the plots, where nitrogen was applied @ 125 and 150% of the recommended N and lodging score was 5.23 and 12.53, respectively. Application of Grs recorded significantly higher wheat yields only when crop lodged or lower N levels. Highest values of net returns (` 85,114/ha), B:C ratio (2.73), energy productivity (256.9 g grain/MJ), energy responsiveness (7.84 MJ/Re), agronomic N-use efficiency (20.5 kg grain/kg-N applied), physiological N-use efficiency (38.5 kg grain/kg N uptake) and apparent recovery efficiency (66.5% N uptake/kg N applied) were recorded at 100% N, however, maximum values of energy ratio (9.46) was obtained with 100% N + Grs, partial factor productivity (68.0 kg grain/kg N applied) in 50% N, nitrogen harvest index (75.0%) under 75% N applied and total N uptakes (125.7 kg) as well as crude protein yield with 150% N + Grs. Overall, concluded that application of growth retardants, viz. 0.2% Chlormequat chloride + 0.1% Tebuconazole was found effective in shortening of wheat plant and reduced lodging but did not improve productivity and profitability under restricted irrigation condition in Vertisols of Central India.

A Device that Controls the Power Supply Sources of a Mobile Communication Base Station

In this research work, the classifications of the device that controls the energy supply sources of the mobile communication base station are presented. The device is used to automatically control the connection and disconnection of the next power source based on the status of the mobile communication base station power supply sources. This device was tested in real-world conditions at mobile communication base stations in the Khorezm region of the Republic of Uzbekistan, and the results were analyzed. The created device allows for rapid response to outages at base stations, management of supply sources based on their status, and monitoring of them, thereby increasing the reliability of energy supply sources and extending the life of backup energy supply sources.

Underestimation of Diurnal Variations in ERA5 Temperature and Relative Humidity over Tropical Indian Ocean

Significant upwelling in the equatorial ocean influences complex ocean–atmosphere interactions and contributes to diurnal variations in the lower troposphere. This study compares the temperature and relative humidity data from radiosonde observations over the tropical Indian Ocean with those from the ERA5, highlighting the underestimation of the diurnal variations in the ERA5. Radiosonde measurements were conducted at 3 h intervals for approximately 24 h, from 31 May to 1 June 2023, to investigate the diurnal variations in the lower troposphere at two fixed locations: (1) 65°E and 8°S in the upwelling region (Station 8) from 28 to 29 May 2023, and (2) 65°E and 4°S outside the upwelling region (Station 4). The radiosonde observations reveal pronounced diurnal variations in temperature and relative humidity between 950 and 650 hPa. The maximum diurnal range (maximum minus minimum) for temperature is observed above 800 hPa, with Station 8 exhibiting 4.7 °C and Station 4 exhibiting 2.7 °C. For relative humidity, Station 8 shows a diurnal range of 84%, while at Station 4, notable variations are observed only below 650 hPa, reaching 76%. However, the ERA5 underestimates the diurnal variations both within and outside the upwelling region. This underestimation is particularly evident between 850 and 750 hPa and is more pronounced within the upwelling region, where the diurnal range is larger. The diurnal ranges calculated from the ERA5 for 2004–2023 suggest that the reanalysis dataset exhibits limitations in capturing diurnal variations, particularly over the upwelling region. This report highlights the need for more in situ observations of the atmospheric variables to better represent diurnal variations in the tropical Indian Ocean.

Full-waveform earthquake source inversion using simulation-based inference

SUMMARY This paper presents a novel framework for full-waveform seismic source inversion using simulation-based inference (SBI). Traditional probabilistic approaches often rely on simplifying assumptions about data errors, which we show can lead to inaccurate uncertainty quantification. SBI addresses this limitation by learning an empirical probabilistic relationship between the parameters and data, without making assumptions about the data errors. This is achieved through the use of specialized machine learning models, known as neural density estimators, which can then be integrated into the Bayesian inference framework. We apply the SBI framework to point-source moment tensor inversions as well as joint moment tensor and time-location inversions. We construct a range of synthetic examples to explore the quality of the SBI solutions, as well as to compare the SBI results with standard Gaussian-likelihood based Bayesian inversions. We then demonstrate that under real seismic noise, common Gaussian-likelihood assumptions for treating full-waveform data yield overconfident posterior distributions that underestimate the moment tensor component uncertainties by up to a factor of 3. We contrast this with SBI, which produces well-calibrated posteriors that generally agree with the true seismic source parameters, and offers an order-of-magnitude reduction in the number of simulations required to perform inference compared to standard Monte Carlo sampling techniques. Finally, we apply our methodology to a pair of moderate magnitude earthquakes in the North Atlantic. We utilize seismic waveforms recorded by the recent UPFLOW ocean bottom seismometer array as well as by regional land stations in the Azores, comparing full moment tensor and source-time location posteriors between SBI and a Gaussian-likelihood approach. We find that our adaptation of SBI can be directly applied to real earthquake sources to efficiently produce high quality posterior distributions that significantly improve upon Gaussian-likelihood approaches.

The characteristics of motor vehicle technical tests on the example of selected vehicle inspection stations

In recent years, Poland has seen a dynamic increase in the number of vehicles on the road. Vehicles participating in road traffic come from both the domestic market, some registered as new, and are imported from foreign markets. The latter are mainly imported from Western Europe and from the American market. Vehicles imported onto the domestic market are several years old and quite often considerably worn out. On the other hand, vehicles from the American market are relatively new and sometimes damaged as a result of road incidents. The aim of this work is to perform a comparative analysis of the results of vehicle technical tests. Research was conducted at two regional vehicle inspection stations over three consecutive years. As part of this analysis, questions about the number of successful and unsuccessful technical tests were answered by the test type. In addition, the number of vehicles using the services of the various stations was evaluated, and the number of vehicle technical tests was analysed by the energy supply of those vehicles. This was followed by the comparison of the test results with the nationwide data in the Central Register of Vehicles and Drivers. A decrease in the number of unsuccessful vehicle tests was noted. Moreover, a greater number of tests of electric vehicles has been noted recently, which may be advantageous to the environment in the future.

Earthquake on January 12, 2025 at 14:49 in the Black Sea (in the Kerch Peninsula area), Mw=4.2, I0=3-4 points

Instrumental and macroseismic data are presented on two earthquakes that occurred on January 11, 2025, with epicenters in Krasnodar Krai (11 km from Sochi) at 01:47 and 17:43 with h=11 km Mw=3.0 and Mw=3.2, respectively. The earthquake parameters were determined based on instrumental data at the Central Branch of the GS RAS (Obninsk). The studied earthquakes occurred in the southwestern part of the Greater Caucasus structures in the Sochi-Krasnopolyanskaya zone within the Monastyrskaya zone of the ESZ with Mmax=6.0–6.5. Source spectra were calculated based on records from regional seismic stations of the GS RAS and spectral parameters were determined. Macroseismic data collection was carried out; the maximum intensity in the village of Verkhniy Yurt, the closest to the instrumental epicenter, was 4 points on the MSK-64 scale.

Earthquake on February 13, 2025 near Sochi with Mw=4.1, I0=4–5 points

The article presents instrumental and macroseismic data on the earthquake of February 13, 2025, with the epicenter in the Krasnodar territory (16 km from Sochi) at 12:12, with h=11 km, Mw=4.1. The earthquake occurred near the epicentral zone of two felt earthquakes that occurred on January 11, 2025 in the southwestern part of the Greater Caucasus structures in the Sochi-Krasnopolyanskaya zone within the Monastyrskaya zone of the ESZ with Mmax=6.0. Source spectra were calculated based on the records of regional seismic stations of the GS RAS and the spectral parameters of the studied source were determined. The focal mechanism was constructed, according to which the type of movement is a strike-slip with reverse fault components. Macroseismic data collection was carried out, the maximum observed intensity in the village of Solokhaul, the closest settlement to the instrumental epicenter, scored 4–5 on the MSK-64 scale.

Bolide Infrasound Signal Morphology and Yield Estimates: A Case Study of Two Events Detected by a Dense Acoustic Sensor Network

Abstract Two bolides (2016 June 2 and 2019 April 4) were detected at multiple regional infrasound stations, with many of the locations receiving multiple detections. Analysis of the received signals was used to estimate the yield, location, and trajectory, as well as the type of shock that produced the received signal. The results from the infrasound analysis were compared with ground-truth information that was collected through other sensing modalities. This multimodal framework offers an expanded perspective on the processes governing bolide shock generation and propagation. The majority of signal features showed reasonable agreement between the infrasound-based interpretation and the other observational modalities, though the yield estimate from the 2019 bolide was significantly lower using the infrasound detections. There was also evidence suggesting that one of the detections was from a cylindrical shock that was initially propagating upward, which is unusual though not impossible.

Optimizing light trap height and installation timing for effective monitoring of insect pests in rice field

The use of chemical pesticides in the agriculture are widely used but have harmful environmental and health impacts. However, it is hazardous to human health with the environment and is often used more than the prescribed amount. The solar light trap is a popular renewable and environment-friendly device. Although light traps are effective, their ideal height and deployment timing in rice fields remain not clear. This study was undertaken with a specific objective of selecting the appropriate installation height, and lighting time period of the solar light trap where LED bulbs were used in capturing insect pests and beneficial insects in rice fields in BRRI regional station Rajshahi, Bangladesh. The findings demonstrated significant variations in pest capture efficiency across different lighting durations. Early-night trapping recorded the highest captures of green leafhoppers (96.67 individuals) and rice bugs (39.67 individuals), while late-night trapping was most effective for stem borers (577.00 individuals) and rice leaf folders (35.33 individuals). The height of trap installation also influenced pest captures, with canopy-level traps (1.0 m) proving most effective for pests such as green leafhoppers and caseworms. Beneficial insects, including carabid beetles and earwigs, similarly exhibited a preference for traps set at higher positions. These results underscore the significance of optimizing operational parameters for light traps to improve their effectiveness in pest management. By minimizing dependence on chemical pesticides, the use of canopy-level (1.0 m) light traps supports sustainable rice cultivation and provides valuable guidance for integrating them into IPM programs tailored to specific agro-ecological conditions.

Activities of helminthological detachments in the North of the USSR under the leadership of Professor Elizaveta Vladimirovna Sorochenkova (in honor of the 110th anniversary of the scientist's birth)

In the mid-20th century, a high incidence of helminthiasis among the population was recorded in the European North of the USSR (Arkhangelsk Region and Nenets Autonomous Okrug), which served as a trigger for the formation of helminthological squads in 1961 to combat these diseases. The helminthological squads included medical workers, teachers of the Arkhangelsk State Medical Institute and students of this university who expressed a desire to help sick people. The squads were supervised by employees of the regional sanitary and epidemiological station, the activities of the squads were controlled by the head of the biology department of the Arkhangelsk State Medical Institute, Professor Elizaveta Vladimirovna Sorochenkova. The work of helminthological squads has proven its effectiveness, for example, in the village of Nelmin Nos in the Nenets Autonomous Okrug, the incidence of diphyllobothriasis among the population decreased from 44.7% in 1961 to 2.9% in 1986. Not only did the squads have the status of treatment and prevention, they were also engaged in research activities in the parasitological field. Upon completion of the squad's work, students wrote scientific articles on parasitology, spoke at conferences at various levels, and some of them devoted themselves to scientific work in their later lives. The squad movement in the helminthological profile existed for almost 30 years. A significant role in the organization of the squads belongs to Professor E.V. Sorochenkova, who would have turned 110 in 2024. She headed the Department of Biology at the Arkhangelsk State Medical Institute for 25 years (from 1957 to 1982). In 2023, the Department of Biology celebrated its 90th anniversary. The article shows the main stages of the development of E.V. Sorochenkova as a scientist and the development of the Department of Biology of the Arkhangelsk State Medical Institute, without which the organization of helminthological detachments in the European North of the USSR would not have taken place.

Two-Year Surveillance of Dengue, Zika, and Chikungunya Viruses Among Chinese Blood Donors - Guangxi and Yunnan PLADs, China, 2022-2023.

The transmission of emerging and re-emerging arboviruses represent a critical challenge to blood transfusion safety worldwide. This study established a comprehensive quality assurance system for Dengue virus (DENV), Zika virus (ZIKV), and Chikungunya virus (CHIKV) nucleic acid testing (NAT) blood screening. The system included external quality assessment (EQA) implementation across all participating central blood stations and performance evaluation of six domestic blood screening reagents. Surveillance conducted in Yunnan Province and Guangxi Zhuang Autonomous Region revealed no positive cases among 45,383 blood samples screened in 2022. In 2023, screening of 44,972 blood donors identified 9 NAT-reactive samples at the Xishuangbanna central blood station, with 6 confirmed as DENV-1 positive. Blood stations in border regions must implement comprehensive surveillance systems with enhanced detection sensitivity and robust early warning mechanisms to effectively address emerging disease threats and ensure transfusion safety.

Identification and land-Environment analysis of centralized photovoltaic stations in the arid northwest region of China

ABSTRACT This study investigates the distribution and impact of photovoltaic (PV) stations in the arid Northwest China, a crucial area for regional economic cooperation. A hierarchical extraction method combining RegNet and SAM models achieved 91.89% accuracy in PV station identification, while also showing a broader extraction coverage compared to existing datasets. In 2023, we identified 688 centralized PV stations, covering a total area of 719.28 km². Using the Continuous Change Detection and Classification (CCDC) algorithm along with Global Moran’s I, we observed significant development in PV installations between 2013 and 2021, with smaller stations being more spatially dispersed. Ecological analysis revealed that PV stations were predominantly situated within the Gobi area/desert, with a minor proportion located in low-coverage grasslands. The impacts of PV stations on local temperature exhibited both locational and seasonal variations. Temperature variations between PV stations and their 1 km buffer zones were significant, with over half of the PV stations contributing a cooling effect on their surroundings (50.78% in summers and 58.79% in winters). Additionally, vegetation coverage increased with distance from the PV stations, which indicated a substantial ecological interaction, underscoring the potential advantages and complexities associated with PV deployment in arid ecosystems.