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Liu Z, Peng T, Ma S, Qi C, Song Y, Zhang C, Li K, Gao N, Pu M, Wang X, Bi Y, Na X. Potential benefits and risks of solar photovoltaic power plants on arid and semi-arid ecosystems: an assessment of soil microbial and plant communities. Front Microbiol 2023; 14:1190650. [PMID: 37588884 PMCID: PMC10427150 DOI: 10.3389/fmicb.2023.1190650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/07/2023] [Indexed: 08/18/2023] Open
Abstract
Exponential increase in photovoltaic installations arouses concerns regarding the impacts of large-scale solar power plants on dryland ecosystems. While the effects of photovoltaic panels on soil moisture content and plant biomass in arid ecosystems have been recognized, little is known about their influence on soil microbial communities. Here, we employed a combination of quantitative PCR, high-throughput sequencing, and soil property analysis to investigate the responses of soil microbial communities to solar panel installation. We also report on the responses of plant communities within the same solar farm. Our findings showed that soil microbial communities responded differently to the shading and precipitation-alternation effects of the photovoltaic panels in an arid ecosystem. By redirecting rainwater to the lower side, photovoltaic panels stimulated vegetation biomass and soil total organic carbon content in the middle and in front of the panels, positively contributing to carbon storage. The shade provided by the panels promoted the co-occurrence of soil microbes but inhibited the abundance of 16S rRNA gene in the soil. Increase in precipitation reduced 18S rRNA gene abundance, whereas decrease in precipitation led to decline in plant aboveground biomass, soil prokaryotic community alpha diversity, and dehydrogenase activity under the panels. These findings highlight the crucial role of precipitation in maintaining plant and soil microbial diversities in dryland ecosystems and are essential for estimating the potential risks of large-scale solar power plants on local and global climate change in the long term.
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Affiliation(s)
- Ziyu Liu
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Tong Peng
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Shaolan Ma
- No. 1 Middle School of Penyang, Guyuan, China
| | - Chang Qi
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Yanfang Song
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Chuanji Zhang
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Kaile Li
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Na Gao
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Meiyun Pu
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Xiaomin Wang
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Yurong Bi
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
| | - Xiaofan Na
- Key Laboratory of Cell Activities and Stress Adaptations, Ministry of Education, School of Life Sciences, Lanzhou University, Lanzhou, China
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Wu C, Liu H, Yu Y, Zhao W, Guo L, Liu J, Yetemen O. Ecohydrological insight: Solar farms facilitate carbon sink enhancement in drylands. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 342:118304. [PMID: 37276619 DOI: 10.1016/j.jenvman.2023.118304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/24/2023] [Accepted: 05/29/2023] [Indexed: 06/07/2023]
Abstract
Solar farms are critical to tackling climate change and achieving carbon neutrality. Besides producing renewable energy, a solar farm modifies microclimates and changes water distribution, consequently affecting local carbon sequestration capacity (CSC). Yet, how the CSC of an ecosystem responds to these changes after solar farm construction remains inadequately understood. Herein, the SOFAR model was adopted to reveal the effects of large-scale solar farms (LSFs) on CSC in arid northern China, with a series of numeric experiments along a climate gradient (with precipitation ranging from 70 to 500 mm yr-1). The results show that relative to pristine vegetation background, CSC was non-linearly increased by averages of 3.49-6.68%, 4.43-10.25%, 5.07-9.71% and 5.6% each year after the installation of LSFs in hyper-arid climates (with aridity index or AI = 0.04-0.05), arid climates (AI = 0.14-0.16), semi-arid climates (AI = 0.21-0.3) and semi-humid climates (AI = 0.55), respectively. The increase in available water for plants growing under the drip lines of photovoltaic panels (PVs) in LSFs is confirmed to be the overwhelming factor responsible for CSC enhancement. Although biases remain in the estimation of increased CSC in hyper- and semi-humid regions due to the high variability of climate (e.g., extreme drought events) and serious radiation reduction beneath PVs, it is certain that solar farms facilitate CSC without increasing external land use. These results will deepen our understanding of the feedback between solar farms and ambient environments and be meaningful for vegetation management in solar farms, especially in the context of climate change and carbon neutrality aims.
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Affiliation(s)
- Chuandong Wu
- Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100029, China
| | - Hu Liu
- Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100029, China.
| | - Yang Yu
- School of Soil and Water Conservation, Beijing Forestry University, Beijing, 100038, China
| | - Wenzhi Zhao
- Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Li Guo
- State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610000, China
| | - Jintao Liu
- State Key Laboratory of Hydrology-Water Resources & Hydraulic Engineering, Hohai University, Nanjing, 210098, China
| | - Omer Yetemen
- Eurasia Institute of Earth Sciences, Istanbul Technical University, Maslak, Istanbul, 34469, Turkey
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Zhang B, Zhang R, Li Y, Wang S, Xing F. Ignoring the Effects of Photovoltaic Array Deployment on Greenhouse Gas Emissions May Lead to Overestimation of the Contribution of Photovoltaic Power Generation to Greenhouse Gas Reduction. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4241-4252. [PMID: 36867117 DOI: 10.1021/acs.est.3c00479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Photovoltaic (PV) power generation is one of the world's most promising options for carbon emission reduction. However, whether the operation period of solar parks can increase greenhouse gas (GHG) emissions in hosting natural ecosystems has not been fully considered. Here, we conducted a field experiment to compensate for the lack of evaluation of the effects of PV array deployment on GHG emissions. Our results show that the PV arrays caused significant differences in air microclimate, soil properties, and vegetation characteristics. Simultaneously, PV arrays had more significant effects on CO2 and N2O emissions but a minor impact on CH4 uptake in the growing season. Of all the environmental variables included, soil temperature and moisture were the main drivers of GHG flux variation. The sustained flux global warming potential from the PV arrays significantly increased by 8.14% compared to the ambient grassland. Our evaluation models identified that the GHG footprint of PV arrays during the operation period on grasslands was 20.62 g CO2-eq kW h-1. Compared with our model estimates, GHG footprint estimates reported in previous studies were generally less by 25.46-50.76%. The contribution of PV power generation to GHG reduction may be overestimated without considering the impact of PV arrays on hosting ecosystems.
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Affiliation(s)
- Bin Zhang
- Key Laboratory of Vegetation Ecology, Institute of Grassland Science, Ministry of Education, Northeast Normal University, Changchun 130024, China
- Jilin Songnen Grassland Ecosystem National Observation and Research Station, Changchun 130024, China
| | - Ruohui Zhang
- Key Laboratory of Vegetation Ecology, Institute of Grassland Science, Ministry of Education, Northeast Normal University, Changchun 130024, China
- Jilin Songnen Grassland Ecosystem National Observation and Research Station, Changchun 130024, China
| | - You Li
- Key Laboratory of Vegetation Ecology, Institute of Grassland Science, Ministry of Education, Northeast Normal University, Changchun 130024, China
- Jilin Songnen Grassland Ecosystem National Observation and Research Station, Changchun 130024, China
| | - Shiwen Wang
- Key Laboratory of Vegetation Ecology, Institute of Grassland Science, Ministry of Education, Northeast Normal University, Changchun 130024, China
- Jilin Songnen Grassland Ecosystem National Observation and Research Station, Changchun 130024, China
| | - Fu Xing
- Key Laboratory of Vegetation Ecology, Institute of Grassland Science, Ministry of Education, Northeast Normal University, Changchun 130024, China
- Jilin Songnen Grassland Ecosystem National Observation and Research Station, Changchun 130024, China
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Xia Z, Li Y, Zhang W, Chen R, Guo S, Zhang P, Du P. Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 324:116338. [PMID: 36208517 DOI: 10.1016/j.jenvman.2022.116338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 08/28/2022] [Accepted: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Solar energy is considered one of the key solutions to the growing demand for energy and to reducing greenhouse gas emissions. Thanks to the relatively low cost of land use for solar energy and high power generation potential, a large number of photovoltaic (PV) power stations have been established in desert areas around the world. Despite the contribution to easing the energy crisis and combating climate change, large-scale construction and operation of PV power stations can change the land cover and affect the environment. However, few studies have focused on these special land cover changes, especially vegetation cover changes, which hinders understanding the effects of the extensive development of solar energy. Here, we used Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) based on Landsat images to monitor changes in vegetation abundance before and after the PV power stations deployment. To reduce the interference of PV shading on vegetation abundance estimation, we improved the vegetation (VG) fraction from SMA and developed the Photovoltaics-Adjusted Vegetation (PAVG) fraction for vegetation abundance measurements in PV power stations. Results show that PV power stations in China's 12 biggest deserts expanded from 0 to 102.56 km2 from 2011 to 2018, mainly distributed in the central part of north China. The desert vegetation in the deployment area of PV power stations presented a significant greening trend. Compared to 2010, the greening area reached 30.80 km2, accounting for 30% of the total area of PV power stations. Overall, the large-scale deployment of PV power stations has promoted desert greening, primarily due to government-led Photovoltaic Desert Control Projects and favorable climatic change. This study shows the great benefits of PV power stations in combating desertification and improving people's welfare, which bring sustainable economic, ecological and social prosperity in sandy ecosystems.
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Affiliation(s)
- Zilong Xia
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Yingjie Li
- Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, 48823, USA; Environmental Science and Policy Program, Michigan State University, East Lansing, MI, 48823, USA
| | - Wei Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Ruishan Chen
- School of Design, Shanghai Jiaotong University, Shanghai, 200241, China
| | - Shanchuan Guo
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Peng Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Peijun Du
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China.
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