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Article

Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China

1
School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China
2
Department of Renewable Energy Generation System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
3
School of Mechanical Engineering, Tianjin University of Commerce, Tianjin 300134, China
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(8), 936; https://doi.org/10.3390/atmos15080936
Submission received: 20 June 2024 / Revised: 28 July 2024 / Accepted: 1 August 2024 / Published: 5 August 2024
(This article belongs to the Special Issue Science and Technology of Indoor and Outdoor Environment)

Abstract

:
Ground-mounted photovoltaic (GMPV) systems are a crucial component of photovoltaic (PV) applications, and their environmental impacts during large-scale development require thorough attention. This study conducted continuous observations at a GMPV plant in an arid region, employing a three-site comparative monitoring system to assess the environmental impact of both shaded and non-shaded areas within GMPV systems. The parameters measured included atmospheric temperature (AT), relative humidity (RH), soil temperature (ST), soil water content (SWC), and wind speed. The results revealed significant diurnal and seasonal variations in AT, with daytime warming and nighttime cooling ranging from 0.1 to 0.7 °C, with particularly large variations observed during high-temperature seasons. Shaded areas under the PV panels exhibited increased RH at night and decreased RH during the day, along with a cooling effect on ST, with a maximum reduction of 7 °C. SWC was higher in shaded areas during dry seasons but exhibited complex redistribution patterns during rainy seasons. Wind speed and direction were notably altered, demonstrating a corridor effect. These findings contrast with previous studies that only focused on the environmental assessment of non-shaded areas within PV systems and external areas using two-site monitoring. This study highlights the critical role of shaded areas in understanding the local environmental impacts of PV systems. This comprehensive approach offers deeper insights into how PV systems influence local meteorological and environmental conditions, suggesting that optimized design and placement of PV systems can enhance their ecological benefits and mitigate adverse environmental impacts in arid regions.

1. Introduction

Facing the growing energy crisis and the challenges of global climate change caused by the excessive consumption of fossil fuels, the development of clean and renewable energy is crucial for energy system transformation [1]. Solar energy, as a new approach to achieve dual positive environmental benefits, can help mitigate climate change by lowering greenhouse gas emissions [2] and can also achieve environmental friendliness during its construction and operation [3]. The advancement of photovoltaic (PV) technology continues to improve energy conversion efficiency and reduce power generation costs, enhancing PV energy’s competitiveness in the market [4]. The ground-mounted photovoltaic (GMPV) systems have become a crucial part of PV applications, accounting for 58.2% of the total installed capacity in China [5]. GMPV systems are primarily deployed in arid desert and Gobi regions, which have high solar irradiance and can promote efficient land use and economic development. Arid areas, with vast expanses of unused land, are ideal for large-scale GMPV installations without competing with agricultural or urban land use [6]. Deploying GMPV systems in these regions can stimulate local economies by creating job opportunities and promoting sustainable development in economically disadvantaged areas. However, the fragile natural environment in arid regions necessitates special consideration of environmental issues.
Because the GMPV systems cover a large area, the underlying surface structure is changed after the installation of the power station, which affects the surface energy balance and water cycle and brings changes in the local climate and ecological environment [7,8,9]. Many field observation studies have been carried out on GMPV systems in arid areas, covering atmospheric temperature, atmospheric humidity, soil temperature, soil humidity, and so on. Among these, research on atmospheric temperature is the most prevalent, and observation studies have been conducted in regions such as Qinghai and Xinjiang in China and Arizona in the United States. Typically, these studies involve selecting points both inside and outside the PV systems for continuous observation to analyze the differences. The results indicate that near-surface temperatures (1.5–2.5 m) in arid areas tend to be higher inside the PV systems during the day compared to outside, creating a photovoltaic heat island effect. At night, the temperature either rises or falls, depending on the location and environment. The temperature differences between inside and outside the PV system also show some seasonal correlation, with more pronounced differences during the high-temperature seasons. Barron-Gafford et al. [10] found that in a desert PV system in southern Arizona, nighttime temperatures at 2.5 m were 3–4 °C higher than the surrounding areas. During high-temperature seasons (spring and summer), the photovoltaic heat island effect was more significant than the urban heat island effect. Yang et al. [11] observed a large PV system in Qinghai, China, and found that at 2 m height, atmospheric temperatures inside the station in spring, summer, and autumn were higher than outside, with the largest increase in summer daytime temperatures, reaching 0.67 °C. Wu et al. [12] showed that the PV system in Qinghai, China, exhibited a cooling effect at night during all seasons, with seasonal differences in daytime temperatures. Nighttime temperatures decreased across all seasons, with the largest drop of 1.82 °C on winter nights. Chang et al. [13] also observed a cooling effect at night in desert GMPV systems.
In observational studies of relative humidity (RH) impacts of PV systems, some studies were carried out at the same time as atmospheric temperature studies. Wu et al. [12] conducted a year-long study in the PV system in Qinghai and revealed that RH within the power station generally increased, with the most significant increase occurring in winter, reaching a maximum increase of 5.00%. Observations by Fthenakis and Yu [14] also indicated that PV stations experienced an increase in daytime humidity in all seasons except summer, where a slight decrease was observed. Yin et al. [15] found that the establishment of PV stations in the desert areas of the Gonghe Basin increased RH by 3.93%. At a height of 2 m, relative humidity inside the station was significantly higher than outside at night.
The observational studies of soil temperature and soil humidity in desert or gobi GMPV systems are limited. Yue et al. [16,17] have monitored soil temperature and soil humidity in desert PV systems. Their results showed that the PV system increased the average soil temperature by 2.08 °C in winter while decreasing the average soil temperature during spring, summer, and autumn by up to 4.15 °C. The average soil humidity under the PV modules increased by 14.7%. The observed research by Wu et al. [18] also showed that the PV system acted as a cold source in spring, summer, and autumn, with the strongest cooling effect on soil in spring; in winter, it provided insulation to the soil. Broadbent et al. [19] indicated that shaded areas beneath PV panels keep the soil cooler during the day and warmer at night. The average shaded soil temperature at the PV site was 9.88 °C cooler than the average exposed soil temperature at the reference site during the day. Liu et al. [20] found through observational experiments at the edge of the Mu Us Desert that the average volumetric soil water content (~8%) at a 1 m profile beneath the PV array during the growing season was almost twice that of the area outside the PV site.
Despite numerous study areas mentioned above, existing research on atmospheric temperature (AT) and relative humidity (RH) in arid regions typically involves only two observation points positioned outside the PV system and in non-shaded areas between arrays. This approach fails to accurately assess the environmental impact of shaded areas, which is crucial for understanding the local meteorological and environmental effects of GMPV systems [21,22]. Additionally, monitoring studies on soil temperature (ST) and soil water content (SWC) in arid regions are limited. Given the minimal and seasonally concentrated rainfall in these areas, understanding moisture changes with precipitation is essential and requires further research.
In this study, we embarked on an extensive research effort at the Wuwei PV plant, a Gobi GMPV system located in Wuwei County, Gansu Province, China. Our approach differed from previous studies, which typically focused on a binary assessment of internal and external parameters at two sites. Instead, we implemented a comprehensive three-site comparative system to measure a range of environmental parameters, including AT, RH, ST, SWC, and wind speed. Monitoring sites were strategically placed at the below line (BL), interval (IT), and reference (REF) sites to allow for a sophisticated evaluation of the microclimate and soil characteristics influenced by both shaded and unshaded areas within the GMPV system.
In addition, to enhance our understanding of the hydrological cycle within the study area, we incorporated precipitation data from the NASA POWER Data Access Viewer. This additional dataset allowed us to explore the interplay between precipitation patterns and the observed changes in RH and SWC, providing a more holistic view of the environmental dynamics at play. Our research began with the establishment of a monitoring system, followed by continuous data collection over a period of more than a year. This baseline data collection was then followed by a meticulous analysis phase where we examined the diurnal and seasonal variations in the measured parameters. We then looked at the correlation between rainfall events and the soil’s ability to retain moisture, with the aim of uncovering the broader ecological implications of GMPV systems in arid regions.
Ultimately, our study aims to provide actionable insights into the microclimatic and soil impacts of GMPV systems, contribute to the optimization of their design and placement, and support the sustainable development of renewable energy infrastructure in arid climates. The overall structural framework of the article is shown in Figure 1.

2. Materials and Methods

2.1. Study Domain and Background

As shown in Table 1 and Figure 2a, GMPV system is located in Wuwei City, Gansu Province, China, at geographical coordinates of 102°13′3′′–102°22′23′′ E longitude and 38°04′40′′–38°07′12′′ N latitude. The region has a temperate continental arid climate characterized by distinct seasons, significant diurnal and annual temperature variations, low and unevenly distributed precipitation, high evaporation rates, dry conditions, and abundant solar radiation. The annual average temperature is 7.1 °C, with 2830 h of sunshine, an evaporation potential of 1996.6 mm, and 262.9 mm of precipitation. The study area, located in the Gobi Desert, primarily comprises loess soil rich in clay minerals, sand particles, and organic matter. Common grass species include Leymus chinensis, fescue, wolf tail, and ferns.
The GMPV arrays are oriented southward with a tilt angle of 32° relative to the ground. The row width of the PV array is 7 m, and the top and bottom edges of the PV panels are 2.75 m and 0.47 m above the ground, respectively, with a middle column height of 0.15 m. This configuration ensures adequate airflow, maintenance convenience, and minimal shading effects during peak daylight hours. The PV panels measure 1954 mm by 992 mm, with a power output of 295 W.

2.2. Data Monitoring and Analysis Methods

A three-site contrast monitoring system was deployed inside and outside the GMPV system (Figure 2). Two sites within the PV system were subdivided into BL and IT sites, while the site outside the PV system was defined as REF site. The BL site, located directly below the PV panels, better reflects the microclimate of shaded areas where solar radiation and rainfall are substantially blocked. The IT site, situated in the non-shaded areas between adjacent arrays, may be attributed to direct or indirect near-peripheral environmental effects of the PV arrays. The REF site provided the background climate characteristics of the study area.
Continuous observations were conducted at the three sites for over one year (January 2023 to May 2024), including measurements of AT, RH, ST, SWC, and wind speed. The AT, RH, and wind speed were monitored at a height of 1.5 m above ground level. The wind speed sensor was installed in June 2023, so the data acquisition period for wind speed is from June 2023 to May 2024. The ST and SWC were monitored using soil parameter sensors at depths of 5 cm, 10 cm, 20 cm, and 40 cm. Sensors at each depth capture soil temperature and moisture dynamics in response to precipitation, evaporation, and temperature changes [25]. Detailed performance indicators of the monitoring equipment are shown in Table 2. Data monitoring is self-powered by an independent solar panel (TR-SP25ZH, Truwel Inc., Beijing, China) and transmitted in real-time via the data collector (SD60, Truwel Inc., Beijing, China) [26]. Precipitation data were sourced from the NASA POWER Data Access Viewer v2.0.0, which provides statistically downscaled data from satellites and ground gauges. The raw data from the three-site contrast monitoring system were processed into hourly averages for comparative analysis in this study. Daily, monthly, and yearly scales were averaged from hourly data.

3. Results and Discussion

3.1. The Temperature

3.1.1. Atmospheric Temperature

The AT inside and outside the PV system show diurnal and seasonal variation (Figure 3). Compared to the REF site, the BL and IT sites within the PV system exhibit a pattern of warming during the day and cooling at night across all seasons. Our observations at the IT and REF sites are consistent with research conducted in Xinjiang, China, which did not include observations at the BL site. This research highlighted that the AT difference between IT and REF is primarily due to the installation and operation of the PV system altering the local thermal balance [28]. The warming period within the PV system during the day spans a longer duration in spring and summer (6 a.m.–7 p.m.) than in autumn and winter.
The AT from shaded and non-shaded areas within the PV system show significant seasonal differences. During the midday to afternoon in spring and winter (low-temperature seasons), AT in shaded areas (BL) is higher than non-shaded areas (IT), indicating that BL has a thermal insulation effect during the daytime in cold seasons. The AT at the BL site is primarily influenced by thermal diffusion, involving factors such as changes in surrounding AT, temperature fluctuations of the PV panels, ventilation conditions, and the roughness of the underlying surface. The elevated AT during daytime in cold seasons may be attributed to the heat generated by PV panels converting solar energy into electrical energy, which warms the panels and subsequently heats the BL area [28]. This heating effect is likely more pronounced in colder seasons. Analysis of wind speed (Section 3.4) indicates a reduction in wind speed at the BL site, which hinders heat dissipation and results in a thermal insulation effect. Also, this is consistent with Armstrong’s observational findings [29], which relied on a three-site monitoring method similar to our research. Conversely, in summer and autumn (high-temperature seasons), BL remains lower than IT throughout the day and night. This is primarily due to the shading by the PV panels, which reduces solar radiation and induces a cooling effect during the high-temperature seasons.
The PV system exhibits different temperature variation trends in shaded and non-shaded areas during low and high-temperature seasons ranging from 0.1 to 0.7 °C. Meanwhile, the AT inside and outside the PV system follow a consistent pattern throughout the whole year: during the day, the internal AT (BL and IT sites) is higher than the external reference (REF site), whereas at night, the situation reverses. This highlights the differential impact of PV systems on local AT, suggesting the need for targeted analysis and considerations for optimizing the ecological design of PV systems.

3.1.2. Soil Temperature

The vertical distribution of ST at depths ranging from 5 to 40 cm across the four seasons is illustrated in Figure 4. Combined with AT parameters (Figure 3), it is evident that ST generally increases and decreases significantly with AT changes over the months. During months with significant temperature differences (January, November, and December), the differences in ST at various depths become more pronounced.
Compared to the REF site, the BL site within the PV system generally exhibits a cooling effect, which differs from the trend in AT changes. This reflects the shading effect of the PV panels, which reduces solar radiation reaching the soil. This is consistent with the observational study by Lambert et al., which indicates that the PV system reduces soil temperature by 10% [30]. The cooling magnitude of the BL site shows seasonal variation, with a significant cooling effect in high-temperature seasons and a weaker cooling effect in low-temperature seasons. The maximum monthly average temperature reduction was 7 °C. The seasonal variation of the shaded area is also confirmed in the study by Broadbent et al., which demonstrates a significant cooling effect for BL areas during high-temperature seasons [19]. For the IT site, compared to the REF, there is an increase in deep soil temperature (20–40 cm depth) and a slight decrease in shallow soil temperature (5–10 cm depth) during high-temperature seasons. In low-temperature seasons, both shallow and deep soil temperatures exhibit a noticeable cooling effect in IT, which drops more than BL. So, the most obvious cooling effect occurs in shaded areas in high-temperature seasons and in non-shaded areas in low-temperature seasons in PV systems. The differential changes in ST at BL and IT sites illustrate the spatially differentiated impact of the PV system on soil temperature.

3.2. Relative Humidity

The diurnal variation of RH for three monitoring sites is shown in Figure 5, indicating that the humidity distribution is affected by the presence of PV panels. Compared to the IT and REF sites, the BL site exhibits a more pronounced humidity reduction during both daytime and nighttime, especially in summer when rainfall is more abundant. Based on Figure 2 and Figure 4, it can be observed that the BL site experiences daytime warming and humidity reduction, creating a high-temperature, low-humidity environment beneath the PV panels. Compared to the REF site, the IT site shows a slight humidifying effect (1% to 3%) during nighttime, with no significant seasonal difference.
This study’s observations on RH are largely consistent with the findings of Wu et al. [12] from a one-year study of a PV system in Qinghai Province, China. Wu’s study, which only included IT and REF sites, observed that RH generally increased at the IT site across all seasons, with the most significant increase in winter, reaching up to 5.00%. Due to differences in geographical location and climate, the observed RH increase in our study was smaller than that reported by Wu. However, the BL site showed the greatest reduction in humidity, exceeding 10%. This demonstrates the significant impact of the shaded area of the PV system on RH, which is a key area for future research.

3.3. Soil Water Content

According to Figure 6, the SWC at a depth of 40 cm is consistently highest at the IT site, indicating that the non-shaded areas of the PV system retain deep soil moisture most effectively. For shallow soil moisture variations, both sites inside the system (BL and IT) are generally higher than the REF site, though the differences between BL and IT vary across different months, likely due to seasonal precipitation. Thus, this study analyzes the soil moisture variations at different monitoring sites during the dry season (January to February 2023) and the rainy season (June to July 2023), as shown in Figure 7.
During the dry season (Figure 7a), the SWC at all three sites inside and outside the system is relatively low. Unlike RH, the SWC shows less noticeable changes with weak rainfall. Within the PV system, the SWC at 5 cm depth at the BL site is the highest, indicating a significant moisture retention effect in the shallow soil in the shaded area under the panels. This demonstrates the effective evaporation suppression by the panels during the dry season. In the rainy season (Figure 6 and Figure 7b,c), the SWC at a depth of 40 cm is less affected by rainfall and consistently shows that IT > BL > REF. In contrast, the SWC at a depth of 5 cm is more influenced by rainfall. Figure 7b indicates that June had less and more sporadic rainfall compared to July, which experienced higher and more concentrated rainfall. Consequently, July experienced an overall increase in SWC and a more rapid transfer of moisture from the IT area to the BL area. Additionally, the shading effect in the BL area reduced evaporation, resulting in higher SWC at shallower depths (5 cm) in July. Meanwhile, under heavy rainfall in July, the SWC at the BL site was higher and less variable, illustrating the redistribution of rainfall by the panels and leading to spatial differences in soil moisture within the PV system area.
For the shaded areas under the panels, significant moisture retention effects in the dry season and redistribution of rainfall in the rainy season are observed. PV panels can create temporal and spatial differences in soil moisture. This redistribution leads to changes in latent and sensible heat fluxes, which further affect surface air temperature and vegetation evapotranspiration [31]. Therefore, PV panels can impact vegetation growth. Makaronidou [32] observed that soil moisture was higher under PV panels compared to non-shaded areas, and soil moisture content was even higher during the growing season under the panels, thereby promoting vegetation growth. However, our research indicates that the SWC in the shaded area is higher from July to December, which could have a beneficial effect on vegetation growth in arid regions but warrants further research.

3.4. Wind Speed and Direction

As shown in Figure 8, the installation of PV plants significantly changes the wind speed and direction in both the shaded area (BL) and the non-shaded area (IT). For the shaded area (BL), the wind speed decreases mainly due to the obstruction of wind flow by the PV panels. The extent of reduction depends on factors such as the size, dip angle, and installation height of the panels, as well as terrain features. Moreover, since the PV panels are all oriented southward to maximize solar irradiation absorption, the wind direction at the BL site changes significantly compared to the REF site outside the system without panels. The wind direction at the BL site only comes from the north and does not vary with seasonal wind changes. However, for the non-shaded area (IT) in the PV system, the wind speed is higher compared to the REF site, and the wind direction is more uniform. This indicates that the corridor effect (Venturi Effect) formed by the gaps between PV panels significantly increases the wind speed. This result is similar to Jiang’s observational study at a height of 2 m [28]. However, since our study was monitored at a height of 1.5 m, which is closer to the ground and lower than the installation height of the PV panels, the corridor effect is more pronounced. Additionally, due to the arrangement of the PV arrays, the wind primarily flows along the direction of the panel corridors, resulting in a consistent east–west wind direction at the IT site.
These observations suggest that the PV system potentially causes a redistribution of local airflow, altering the original wind speed and direction patterns and minimizing their seasonal variations. These changes in wind speed and direction further influence local climatic conditions, such as temperature distribution and soil particle composition [33], and have the auxiliary function of sand prevention and control [34]. Therefore, further research on the impact of these wind changes should be conducted. This research could provide important references for wind erosion control and desertification prevention, as well as improving the Gobi ecosystem.

4. Conclusions

This study focused on the comprehensive analysis of the environmental impacts of GMPV systems in arid regions, specifically examining the Wuwei PV plant in Gansu Province, China. Over more than a year of continuous monitoring, we investigated the atmospheric temperature (AT), relative humidity (RH), soil temperature (ST), soil water content (SWC), and wind speed across three sites: under the PV arrays, between the arrays, and outside the system. Our findings underscore the significant microclimatic changes induced by PV systems and provide valuable insights for optimizing their eco-design and placement.
  • Atmospheric Temperature and Relative Humidity
The analysis revealed that PV systems significantly alter local AT and RH, especially for the shaded areas. The AT demonstrated a distinct pattern of daytime warming and nighttime cooling across all seasons, ranging from 0.1 to 0.7 °C. The most pronounced warming effect was observed during the high-temperature seasons (spring and summer), while the cooling effect at night was consistent throughout the year, with the largest decrease recorded during winter nights. The overall reduction in RH within the PV system appeared particularly in summer when rainfall was more abundant. The shaded areas experienced daytime warming and humidity reduction, creating a high-temperature, low-humidity environment beneath the PV panels. These combined effects on AT and RH highlight the unique microclimatic dynamics introduced by the PV infrastructure.
  • Soil Temperature and Soil Water Content
Soil temperature (ST) and soil water content (SWC) were significantly affected by the shading and structural characteristics of the PV systems. The shaded areas consistently showed a cooling effect on the soil, with the cooling magnitude varying seasonally—more pronounced during high-temperature seasons. The maximum monthly average temperature reduction was 7 °C. This cooling effect reflects the reduced solar radiation reaching the soil due to the panels’ shading. The SWC was higher in shaded areas during dry seasons, demonstrating effective moisture retention, but exhibited complex redistribution patterns during rainy seasons. Shaded and non-shaded areas exhibited dynamic changes in SWC in response to precipitation, indicating that the PV panels alter the natural processes of water infiltration and evaporation.
  • Wind Speed and Direction
Wind speed and direction were also significantly modified by the PV installations. The PV arrays reduced wind speed in the shaded areas, while the non-shaded areas between the arrays experienced increased wind speeds due to the corridor effect. The wind direction in shaded areas was notably altered, predominantly aligning with the orientation of the PV panels, which significantly affected local airflow patterns. These changes have broader implications for local climatic conditions, soil particle composition, and potential applications in sand prevention and control.
  • Implications and Future Research
The findings from this study underscore the critical importance of considering shaded and non-shaded areas in PV systems to fully understand their local environmental impacts. The differential impacts on AT, RH, ST, and SWC highlight the need for a nuanced approach to PV system design and placement, particularly in arid regions where water conservation and temperature regulation are vital. The observed changes in wind patterns further suggest potential benefits for wind erosion control and desertification prevention.
Regarding the limitations, since the data are derived from a single monitoring site, they may not fully represent conditions across all arid areas. Additional monitoring sites are needed for more comprehensive validation. So, expanding the scope of monitoring to include more diverse arid environments will enhance our understanding of the global applicability of these results. Furthermore, some analyses are based on certain assumptions and conjectures. Future research should focus on a more in-depth investigation of the variations and underlying mechanisms of the relevant indicators. Meanwhile, the long-term ecological impacts of PV systems, including their effects on local vegetation, soil health, and broader climatic patterns, should also be focused on in future research. Integrating these findings into climate models will improve the accuracy of environmental assessments and guide the development of more sustainable and efficient PV technologies.
In conclusion, this study provides a comprehensive assessment of the microclimatic and soil impacts of GMPV systems in arid regions. By highlighting the significant changes induced by the PV system, we emphasize the importance of optimized system design to maximize ecological benefits and mitigate adverse effects, ultimately contributing to more sustainable energy solutions and environmental stewardship.

Author Contributions

Conceptualization, J.Z.; methodology, J.Z.; software, Z.L.; validation, J.T. and J.Z.; formal analysis, Z.L.; investigation, Z.L. and Y.G.; resources, J.Z.; data curation, J.Z. and Y.Z.; writing—original draft preparation, J.Z.; writing—review and editing, Y.W. and B.Y.; visualization, Z.L.; supervision, Y.W.; project administration, Y.W.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Technologies Research and Development Program (No. 2023YFE0103100) and the International Partnership Program of the Chinese Academy of Sciences (No. 182111KYSB20200025).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.

Conflicts of Interest

The authors of this manuscript declare no conflicts of interest.

Abbreviations

Ground-mounted photovoltaicGMPV
Atmospheric temperatureAT
Relative humidityRH
Soil temperatureST
Soil water contentSWC
Below line siteBL
Interval siteIT
Reference siteREF
PhotovoltaicPV

References

  1. Wang, Y.; Wang, R.; Tanaka, K.; Ciais, P.; Penuelas, J.; Balkanski, Y.; Sardans, J.; Hauglustaine, D.; Liu, W.; Xing, X.; et al. Accelerating the energy transition towards photovoltaic and wind in China. Nature 2023, 619, 761–767. [Google Scholar] [CrossRef] [PubMed]
  2. Cherp, A.; Vinichenko, V.; Tosun, J.; Gordon, J.A.; Jewell, J. National growth dynamics of wind and solar power compared to the growth required for global climate targets. Nat. Energy 2021, 6, 742–754. [Google Scholar] [CrossRef]
  3. Hernandez, R.R.; Armstrong, A.; Burney, J.; Ryan, G.; Moore-O’Leary, K.; Diédhiou, I.; Grodsky, S.M.; Saul-Gershenz, L.; Davis, R.; Macknick, J.; et al. Techno–ecological synergies of solar energy for global sustainability. Nat. Sustain. 2019, 2, 560–568. [Google Scholar] [CrossRef]
  4. Jiang, J.; Gao, X.; Chen, B. The Impact of Utility-Scale Photovoltaics Plant on Near Surface Turbulence Characteristics in Gobi Areas. Atmosphere 2021, 12, 18. [Google Scholar] [CrossRef]
  5. National Energy Administration. Available online: https://www.nea.gov.cn/2024-02/28/c_1310765696.htm (accessed on 6 April 2024).
  6. Hua, Y.; Chai, J.; Chen, L.; Liu, P. The Influences of the Desert Photovoltaic Power Station on Local Climate and Environment: A Case Study in Dunhuang Photovoltaic Industrial Park, Dunhuang City, China in 2019. Atmosphere 2022, 13, 1235. [Google Scholar] [CrossRef]
  7. Hernandez, R.R.; Easter, S.B.; Murphy-Mariscal, M.L.; Maestre, F.T.; Tavassoli, M.; Allen, E.B.; Barrows, C.W.; Belnap, J.; Ochoa-Hueso, R.; Ravi, S.; et al. Environmental impacts of utility-scale solar energy. Renew. Sustain. Energy Rev. 2014, 29, 766–779. [Google Scholar] [CrossRef]
  8. Tsoutsos, T.; Frantzeskaki, N.; Gekas, V. Environmental impacts from the solar energy technologies. Energy Policy 2005, 33, 289–296. [Google Scholar] [CrossRef]
  9. Hernandez, R.R.; Hoffacker, M.K.; Murphy-Mariscal, M.L.; Wu, G.C.; Allen, M.F. Solar energy development impacts on land cover change and protected areas. Proc. Natl. Acad. Sci. USA 2015, 112, 13579–13584. [Google Scholar] [CrossRef]
  10. Barron-Gafford, G.A.; Minor, R.L.; Allen, N.A.; Cronin, A.D.; Brooks, A.E.; Pavao-Zuckerman, M.A. The Photovoltaic Heat Island Effect: Larger solar power plants increase local temperatures. Sci. Rep. 2016, 6, 35070. [Google Scholar] [CrossRef]
  11. Yang, L.; Gao, X.; Lv, F.; Hui, X.; Ma, L.; Hou, X. Study on the local climatic effects of large photovoltaic solar farms in desert areas. Sol. Energy 2017, 144, 244–253. [Google Scholar] [CrossRef]
  12. Wu, W.; Yue, S.; Zhou, X.; Guo, M.; Wang, J.; Ren, L.; Yuan, B. Observational Study on the Impact of Large-Scale Photovoltaic Development in Deserts on Local Air Temperature and Humidity. Sustainability 2020, 12, 3403. [Google Scholar] [CrossRef]
  13. Chang, R.; Shen, Y.; Luo, Y.; Wang, B.; Yang, Z.; Guo, P. Observed surface radiation and temperature impacts from the large-scale deployment of photovoltaics in the barren area of Gonghe, China. Renew. Energy 2018, 118, 131–137. [Google Scholar] [CrossRef]
  14. Fthenakis, V.; Yu, Y. Analysis of the potential for a heat island effect in large solar farms. In Proceedings of the Photovoltaic Specialists Conference, Tampa, FL, USA, 16–21 June 2013. [Google Scholar]
  15. Yin, D.Y.; Ma, L.; Qu, J.J.; Zhao, S.P.; Yu, Y.; Tan, L.; Xiao, J.H. Effect of large Photovoltaic power station microclimate of desert region in Gonghe Basin. Bull. Soil Water Conserv. 2017, 37, 15–21. [Google Scholar]
  16. Yue, S.; Guo, M.; Zou, P.; Wu, W.; Zhou, X. Effects of photovoltaic panels on soil temperature and moisture in desert areas. Env. Sci. Pollut. Res. Int. 2021, 28, 17506–17518. [Google Scholar] [CrossRef] [PubMed]
  17. Yue, S.; Wu, W.; Zhou, X.; Ren, L.; Wang, J. The Influence of Photovoltaic Panels on Soil Temperature in the Gonghe Desert Area. Environ. Eng. Sci. 2021, 38, 910–920. [Google Scholar] [CrossRef]
  18. Wu, W. Observational Study on the Impact of Large-Scale Photovoltaic Development on Soil Temperature. In Proceedings of the IOP Conference Series: Earth and Environmental Science, Nanjing, China, 25–27 June 2021. [Google Scholar]
  19. Broadbent, A.M.; Krayenhoff, E.S.; Georgescu, M.; Sailor, D.J. The Observed Effects of Utility-Scale Photovoltaics on Near-Surface Air Temperature and Energy Balance. J. Appl. Meteorol. Climatol. 2019, 58, 989–1006. [Google Scholar] [CrossRef]
  20. Liu, Y.; Zhang, R.Q.; Huang, Z.; Cheng, Z.; López-Vicente, M.; Ma, X.R.; Wu, G.L. Solar photovoltaic panels significantly promote vegetation recovery by modifying the soil surface microhabitats in an arid sandy ecosystem. Land Degrad. Dev. 2019, 30, 2177–2186. [Google Scholar] [CrossRef]
  21. Al-Rbaihat, R.; Alahmer, H.; Al-Manea, A.; Altork, Y.; Alrbai, M.; Alahmer, A. Maximizing efficiency in solar ammonia–water absorption refrigeration cycles: Exergy analysis, concentration impact, and advanced optimization with GBRT machine learning and FHO optimizer. Int. J. Refrig. 2024, 161, 31–50. [Google Scholar] [CrossRef]
  22. Ahmed, S.Y.; Al-Amir, Q.R.; Hamzah, H.K.; Ali, F.H.; Abed, A.M.; Al-Manea, A.; Egab, K.; Al-Rbaihat, R.; Saleh, K.; Alahmer, A. Investigation of natural convection and entropy generation of non-Newtonian flow in molten polymer-filled odd-shaped cavities using finite difference lattice Boltzmann method. Numer. Heat Transf. Part B Fundam. 2024, 29, 1–26. [Google Scholar] [CrossRef]
  23. Yuting, Z.; Zhen, Z.; Jihu, M. Spatial-temporal variation of vegetation coverage in Wuwei City from 2011 to 2020. Shelter. Technol. 2022, 1, 56–63. [Google Scholar] [CrossRef]
  24. Zhiguo, Z.; Hongjie, K. Spatial-temporal changes and driving forces of land use/cover in Wuwei City from 2000 to 2020. Sci. Technol. Eng. 2023, 23, 8579–8587. [Google Scholar]
  25. Wu, Z.Y.; Hou, A.P.; Chang, C.; Huang, X.; Shi, D.Q.; Wang, Z.F. Environmental impacts of large-scale CSP plants in northwestern China. Environ. Sci. -Process. Impacts 2014, 16, 2432–2441. [Google Scholar] [CrossRef] [PubMed]
  26. Teuwel. SD60/SDI12 Data Collector. Available online: https://www.truwel.com/truwel_Product_2062740003.html (accessed on 19 July 2024).
  27. Teuwel. Product Center. Available online: https://www.truwel.com/truwel_ProClass.html (accessed on 19 July 2024).
  28. Jiang, J.; Gao, X.; Lv, Q.; Li, Z.; Li, P. Observed impacts of utility-scale photovoltaic plant on local air temperature and energy partitioning in the barren areas. Renew. Energy 2021, 174, 157–169. [Google Scholar] [CrossRef]
  29. Armstrong, A.; Ostle, N.J.; Whitaker, J. Solar park microclimate and vegetation management effects on grassland carbon cycling. Environ. Res. Lett. 2016, 11, 074016. [Google Scholar] [CrossRef]
  30. Lambert, Q.; Bischoff, A.; Cueff, S.; Cluchier, A.; Gros, R. Effects of solar park construction and solar panels on soil quality, microclimate, CO2 effluxes, and vegetation under a Mediterranean climate. Land Degrad. Dev. 2021, 32, 5190–5202. [Google Scholar] [CrossRef]
  31. Seneviratne, S.I.; Hirschi, M.; Schwingshackl, C. Quantifying Spatiotemporal Variations of Soil Moisture Control on Surface Energy Balance and Near-Surface Air Temperature. J. Clim. 2017, 30, 7105–7124. [Google Scholar] [CrossRef]
  32. Makaronidou, M. Assessment on the Local Climate Effects of Solar Parks. Ph.D. Thesis, Lancaster University, Bailrigg, UK, 2020. [Google Scholar]
  33. Yun, J.D.; Cui, X.X.; Meng, Z.J. Study on Particle Size Characteristics of Surface Soil under Photovoltaic Panel in Kubuqi Desert. J. Inn. Mong. For. Sci. Technol. 2019, 45, 22–29. [Google Scholar]
  34. Chang, Z.; Liu, S.; Fu, J.; Wang, Q.; Wang, F.; Sun, T.; Liu, S.; Wang, F. Effect of desert photovoltaic on sand prevention and control—Taking Gansu Gulang Zhenfa photovoltaic DC field as an example. In Proceedings of the IOP Conference Series: Earth and Environmental Science, Weihai, China, 28–30 August 2020. [Google Scholar]
Figure 1. Methodological framework of the study outline.
Figure 1. Methodological framework of the study outline.
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Figure 2. Study domain of the PV system and allocation of the three monitoring sites. (a) The spatial location of the Wu Wei PV system; (bd) denote the real scenes of the surrounding situation of monitoring sites in BL, IT, and REF areas of the PV system.
Figure 2. Study domain of the PV system and allocation of the three monitoring sites. (a) The spatial location of the Wu Wei PV system; (bd) denote the real scenes of the surrounding situation of monitoring sites in BL, IT, and REF areas of the PV system.
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Figure 3. Diurnal variation of ΔAT in the three-site monitoring system in different seasons during the monitoring period from January 2023 to December 2023.
Figure 3. Diurnal variation of ΔAT in the three-site monitoring system in different seasons during the monitoring period from January 2023 to December 2023.
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Figure 4. Vertical distribution of monthly mean AT (a) and ST (b) at different soil depths at three sites during the monitoring period of 2023, where three sites on the line are BL, IT, and REF site data, respectively.
Figure 4. Vertical distribution of monthly mean AT (a) and ST (b) at different soil depths at three sites during the monitoring period of 2023, where three sites on the line are BL, IT, and REF site data, respectively.
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Figure 5. Diurnal variation of RH and ΔRH among three monitoring sites for different seasons during the monitoring period from January 2023 to December 2023.
Figure 5. Diurnal variation of RH and ΔRH among three monitoring sites for different seasons during the monitoring period from January 2023 to December 2023.
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Figure 6. Vertical distribution of monthly mean RH (a) and SWC (b) at different soil depths at three sites during the monitoring period of 2023.
Figure 6. Vertical distribution of monthly mean RH (a) and SWC (b) at different soil depths at three sites during the monitoring period of 2023.
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Figure 7. Day-to-day atmospheric RH and SWC (5 cm, 40 cm) during dry season (a) and rainy season (b,c).
Figure 7. Day-to-day atmospheric RH and SWC (5 cm, 40 cm) during dry season (a) and rainy season (b,c).
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Figure 8. Wind roses in different seasons at BL, IT, and REF sites during the monitoring period from June 2023 to May 2024.
Figure 8. Wind roses in different seasons at BL, IT, and REF sites during the monitoring period from June 2023 to May 2024.
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Table 1. Environmental characteristics of the monitoring site area [23,24].
Table 1. Environmental characteristics of the monitoring site area [23,24].
CategoriesDetailed Feature Description
LocationWestern Gansu Province, eastern end of Hexi Corridor
ClimacticThe average annual temperature: 7.8 °C
Annual precipitation: 60–610 mm
Evaporation capacity: 1400–3010 mm
Sunshine duration: 2200–3030 h
Solar radiation: 127–138 kcal/cm2
LandformThe southern Qilian Mountains, the central corridor plain, and the northern desert; elevation of 1020–4874 m
HydrologyYellow River Basin with a cross-border water flow of 23.15 billion cubic meters; Shiyang River Basin area: 29,100 square kilometers
BiodiversityHigh coverage areas mainly in the southern Qilian Mountain area, medium coverage areas mainly in the central oasis agricultural areas, low coverage areas mainly in the northern desert
Soil typeSandy soils with low moisture retention and high permeability
Table 2. Detailed performance indicators of the monitoring equipment.
Table 2. Detailed performance indicators of the monitoring equipment.
Parameter (unit)SensorHeight/
Depth
Working RangeAccuracyRate (min)
AT (°C)TRB3 a1.5 m−40 °C~ +70 °C±0.2 °C30
RH (%)TRB31.5 m0–100%±1.5%30
SWC (%)SM926 b5 cm, 10 cm, 20 cm, 40 cm0–100%±0.0330
ST (°C)SM9265 cm, 10 cm, 20 cm, 40 cm−40~55 °C±0.330
Wind speed & directionWXA
100-02S c
1.5 m0–60 m/s0.05 m/s30
Notes: a The TRB3 temperature, humidity, and pressure sensor is an integrated, simple digital signal for all-weather use. b The SM926 soil multi-parameter sensor belongs to the SWR (Standing Wave Ratio) measurement principle of the sensor. And the SM926 uses a 50 MHz signal source, and the probe adopts a four-claw structure distributed in a circular center, which can accurately measure multiple soil parameters. c The WXA100-02S anemometer is used to measure wind direction and speed with a digital interface for environmental measurement and can be connected to an external temperature or rain sensor [27].
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MDPI and ACS Style

Zhang, J.; Li, Z.; Tao, J.; Ge, Y.; Zhong, Y.; Wang, Y.; Yan, B. Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China. Atmosphere 2024, 15, 936. https://doi.org/10.3390/atmos15080936

AMA Style

Zhang J, Li Z, Tao J, Ge Y, Zhong Y, Wang Y, Yan B. Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China. Atmosphere. 2024; 15(8):936. https://doi.org/10.3390/atmos15080936

Chicago/Turabian Style

Zhang, Jia, Zaixin Li, Junyu Tao, Yadong Ge, Yuzhen Zhong, Yibo Wang, and Beibei Yan. 2024. "Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China" Atmosphere 15, no. 8: 936. https://doi.org/10.3390/atmos15080936

APA Style

Zhang, J., Li, Z., Tao, J., Ge, Y., Zhong, Y., Wang, Y., & Yan, B. (2024). Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China. Atmosphere, 15(8), 936. https://doi.org/10.3390/atmos15080936

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