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Degradation and longevity of solar photovoltaic modulesa??An analysis of recent field studies in Ghana
摘要： Solar photovoltaic (PV) technology has attracted an enormous amount of attention and investment in recent years—translating to record deployment levels. This is due in part to its potential role as a cleaner energy source in the emissions-constrained development agenda that is currently being pursued at both global and national levels. Solar PV has also been propelled to the forefront of today's menu of technological options by virtue of its attributes such as scalability, fast deployment lead times, and low operating cost. Substantial investments are needed in the coming years in order to accomplish climate targets and other goals set by various countries and regional/subregional blocs. In support of informed investment decision-making and ultimately, improved outcomes of solar PV projects, there has been an uptick in studies on operational performance of fielded PV systems across the globe. These studies are, however, geographically unbalanced, and there is the need for data from under-represented regions. This paper presents a synthesis of results obtained from recent seminal field studies on PV module performance degradation in Ghana. The studies altogether analyzed sixty-five (65) modules (mono- and polycrystalline silicon) from twenty-nine (29) installations across the country (1118 module-years). The field-aged modules were characterized in situ using current-voltage (I-V) curves, visual inspection checklists, and thermal imaging. Annual module performance degradation rates (peak power) of 0.8%-7%, 0.55%-2.07%, and 1.1%-2.4% were found for modules located in various climate subcategorizations.
关键词： module,degradation,photovoltaic,performance,Ghana
更新于2025-09-23 15:19:57
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Mapping the Leaf Economic Spectrum across West African Tropical Forests Using UAV-Acquired Hyperspectral Imagery
摘要： The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.
关键词： hyperspectral,spectroscopy,West Africa,tropical forest,UAV,Ghana,leaf traits,PLSR,leaf economic spectrum
更新于2025-09-10 09:29:36