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Observational Study on the Impact of Large-Scale Photovoltaic Development in Deserts on Local Air Temperature and Humidity

Author

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  • Wei Wu

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

  • Shengjuan Yue

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China
    State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China)

  • Xiaode Zhou

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

  • Mengjing Guo

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

  • Jiawei Wang

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

  • Lei Ren

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

  • Bo Yuan

    (State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China)

Abstract

As an important form of clean energy, photovoltaic (PV) power generation is entering a rapid development phase. Qinghai, China is located on the Qinghai-Tibet Plateau. It has sufficient sunlight and rich heat and light resources, includes a large area of the Gobi Desert, and has become China’s largest base for PV power generation. However, large-scale PV development in deserts changes the local surface energy distribution and impacts local microclimates. This study considered the Gonghe PV Power Plant in Qinghai as an example. Three monitoring stations were set up in the PV power plant, transition, and reference areas, and the influence of large-scale PV developments on the local air temperature and humidity was studied based on long-term, multi-point field observation data. The results showed that the overall daytime air temperature in the PV power plant had changed slightly (increased and decreased), while the night-time temperature dropped significantly. Specifically, in spring and summer, the daytime temperature increased slightly, with a maximum increase of 0.34 °C; in autumn and winter, the daytime temperature decreased slightly, with a maximum decrease of 0.26 °C; in all seasons, the night-time temperature decreased, with a maximum decrease of 1.82 °C during the winter night. The relative humidity in the PV power plant generally increased; except for a slight decrease in summer, the daytime and night-time relative humidity in spring, autumn, and winter always increased. The humidification in winter was the most significant, with increases of 5.00% and 4.76% for the transition and reference areas, respectively. The diurnal air temperature and relative humidity ranges in the PV power plant were greater than those outside the PV power plant. The results obtained in this field observation study could serve as a basis for quantitative evaluation of the microclimate effects of large-scale PV development in deserts and provide technical support for guiding the future planning and development of the PV industry.

Suggested Citation

  • Wei Wu & Shengjuan Yue & Xiaode Zhou & Mengjing Guo & Jiawei Wang & Lei Ren & Bo Yuan, 2020. "Observational Study on the Impact of Large-Scale Photovoltaic Development in Deserts on Local Air Temperature and Humidity," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3403-:d:348799
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    References listed on IDEAS

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    1. Chang, Rui & Shen, Yanbo & Luo, Yong & Wang, Bo & Yang, Zhenbin & Guo, Peng, 2018. "Observed surface radiation and temperature impacts from the large-scale deployment of photovoltaics in the barren area of Gonghe, China," Renewable Energy, Elsevier, vol. 118(C), pages 131-137.
    2. Shuyu Dai & Dongxiao Niu & Yaru Han, 2018. "Forecasting of Energy-Related CO 2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability," Sustainability, MDPI, vol. 10(4), pages 1-17, March.
    3. Asl-Soleimani, E & Farhangi, S & Zabihi, M.S, 2001. "The effect of tilt angle, air pollution on performance of photovoltaic systems in Tehran," Renewable Energy, Elsevier, vol. 24(3), pages 459-468.
    4. Zhuoting Wu & Paul Dijkstra & George W. Koch & Bruce A. Hungate, 2012. "Biogeochemical and ecological feedbacks in grassland responses to warming," Nature Climate Change, Nature, vol. 2(6), pages 458-461, June.
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