Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques
The rapid development of photovoltaic (PV) powerplants in the world has drawn attention on their climate and environmental impacts. In this study, we assessed the effects of PV powerplants on surface temperature using 23 largest PV powerplants in the world with thermal infrared remote sensing techni...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/11/1825 |
| _version_ | 1827715596189433856 |
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| author | Xunhe Zhang Ming Xu |
| author_facet | Xunhe Zhang Ming Xu |
| author_sort | Xunhe Zhang |
| collection | DOAJ |
| description | The rapid development of photovoltaic (PV) powerplants in the world has drawn attention on their climate and environmental impacts. In this study, we assessed the effects of PV powerplants on surface temperature using 23 largest PV powerplants in the world with thermal infrared remote sensing technique. Our result showed that the installation of the PV powerplants had significantly reduced the daily mean surface temperature by 0.53 °C in the PV powerplant areas. The cooling effect with the installation of the PV powerplants was much stronger during the daytime than the nighttime with the surface temperature dropped by 0.81 °C and 0.24 °C respectively. This cooling effect was also depended on the capacity of the powerplants with a cooling rate of −0.32, −0.48, and −0.14 °C/TWh, respectively, for daily mean, daytime, and nighttime temperature. We also found that the construction of the powerplants significantly decreased the surface albedo from 0.22 to 0.184, but significantly increased the effective albedo (surface albedo plus electricity conversion) from 0.22 to 0.244, suggesting conversion of solar energy to electrical energy is a major contributor to the observed surface cooling. Our further analyses showed that the nighttime cooling in the powerplants was significantly correlated with the latitude and elevation of the powerplants as well as the annual mean temperature, precipitation, solar radiation, and normalized difference vegetation index (NDVI). This means the temperature effect of the PV powerplants depended on regional geography, climate and vegetation conditions. This finding can be used to guide the selection of the sites of PV powerplants in the future. |
| first_indexed | 2024-03-10T19:22:08Z |
| format | Article |
| id | doaj.art-c64558a2f2f14ee3bbc21e1994314061 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:22:08Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c64558a2f2f14ee3bbc21e19943140612023-11-20T02:56:05ZengMDPI AGRemote Sensing2072-42922020-06-011211182510.3390/rs12111825Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing TechniquesXunhe Zhang0Ming Xu1Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Ministry of Education, Kaifeng 475004, ChinaKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Ministry of Education, Kaifeng 475004, ChinaThe rapid development of photovoltaic (PV) powerplants in the world has drawn attention on their climate and environmental impacts. In this study, we assessed the effects of PV powerplants on surface temperature using 23 largest PV powerplants in the world with thermal infrared remote sensing technique. Our result showed that the installation of the PV powerplants had significantly reduced the daily mean surface temperature by 0.53 °C in the PV powerplant areas. The cooling effect with the installation of the PV powerplants was much stronger during the daytime than the nighttime with the surface temperature dropped by 0.81 °C and 0.24 °C respectively. This cooling effect was also depended on the capacity of the powerplants with a cooling rate of −0.32, −0.48, and −0.14 °C/TWh, respectively, for daily mean, daytime, and nighttime temperature. We also found that the construction of the powerplants significantly decreased the surface albedo from 0.22 to 0.184, but significantly increased the effective albedo (surface albedo plus electricity conversion) from 0.22 to 0.244, suggesting conversion of solar energy to electrical energy is a major contributor to the observed surface cooling. Our further analyses showed that the nighttime cooling in the powerplants was significantly correlated with the latitude and elevation of the powerplants as well as the annual mean temperature, precipitation, solar radiation, and normalized difference vegetation index (NDVI). This means the temperature effect of the PV powerplants depended on regional geography, climate and vegetation conditions. This finding can be used to guide the selection of the sites of PV powerplants in the future.https://www.mdpi.com/2072-4292/12/11/1825photovoltaic powerplantsMODISeffective albedoconvective coolingNDVI |
| spellingShingle | Xunhe Zhang Ming Xu Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques Remote Sensing photovoltaic powerplants MODIS effective albedo convective cooling NDVI |
| title | Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques |
| title_full | Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques |
| title_fullStr | Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques |
| title_full_unstemmed | Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques |
| title_short | Assessing the Effects of Photovoltaic Powerplants on Surface Temperature Using Remote Sensing Techniques |
| title_sort | assessing the effects of photovoltaic powerplants on surface temperature using remote sensing techniques |
| topic | photovoltaic powerplants MODIS effective albedo convective cooling NDVI |
| url | https://www.mdpi.com/2072-4292/12/11/1825 |
| work_keys_str_mv | AT xunhezhang assessingtheeffectsofphotovoltaicpowerplantsonsurfacetemperatureusingremotesensingtechniques AT mingxu assessingtheeffectsofphotovoltaicpowerplantsonsurfacetemperatureusingremotesensingtechniques |