Coal with Carbon Capture and Sequestration is not as Land Use Efficient as Solar Photovoltaic Technology for Climate Neutral Electricity Production

Forecasting meteorological impacts on the environmental sustainability of a large-scale solar plant via artificial intelligence-based life cycle assessment

Although large-scale solar (LSS) is a promising renewable energy technology, it causes adverse impacts on the ecosystem, human health, and resource depletion throughout its upstream (i.e., raw material extraction to solar panel production) and downstream (i.e., plant demolition and waste management) processes. The LSS operational performance also fluctuates due to meteorological conditions, leading to uncertainty in electricity generation and raising concerns about its overall environmental performance. Hitherto, there has been no evidence-backed study that evaluates the ecological sustainability of LSS with the consideration of meteorological uncertainties. In this study, a novel integrated Life Cycle Assessment (LCA) and Artificial Neural Network (ANN) framework is developed to forecast the meteorological impacts on LSS's electricity generation and its life cycle environmental sustainability. For LCA, 18 impact categories and three damage categories are characterised and assessed by ReCiPe 2016 via SimaPro v. 9.1. For ANN, a feedforward neural network is applied via Neural Designer 5.9.3. Taking an LSS plant in Malaysia as a case study, the photovoltaic panel production stage contributes the highest environmental impact in LSS (30 % of human health, 30 % of ecosystem quality, and 34 % of resource scarcity). Aluminium recycling reduces by 10 % for human health, 10 % for ecosystem quality, and 9 % for resource scarcity. The emissions avoided by the forecasted LSS-generated electricity offset the environmental burden for human health, ecosystem quality, and resource scarcity 12-68 times, 13-73 times, and 18-98 times, respectively. The developed ANN-LCA framework can provide LSS stakeholders with data-backed insights to effectively design an environmentally conscious LSS facility, considering meteorological influences.

An improved numerical model to predict the operating temperature and efficiency of solar photovoltaic systems

Solar photovoltaic (PV) technology has a huge potential for producing renewable energy and reducing greenhouse gas emissions. An increase in the PV cell temperature in real operating conditions reduces the actual output of a solar PV system. A 1D transient multi-layered model, based on the fundamentals of the finite difference method, has been developed to predict the operating cell temperature. Since a PV system operates in stochastic wind conditions and is not subjected to any predefined thermal boundary condition, several expressions of convection coefficient have been scientifically analyzed to determine the most suitable expression. The novel calculation approach assumes explicit radiation terms and implicit convection terms to linearize the equations and get rid of any iterative process. Comparison with experimental results shows that the convection coefficient derived from boundary layer theory corresponding to uniform heat flux predicts the cell temperature with the best accuracy showing a mean error of only [Formula: see text] and [Formula: see text]. Splitting the heat source across different solar PV layers produces a maximum change of [Formula: see text] only and can be avoided due to the involved complexity. The study proposes a new piece-wise function for PV efficiency in terms of cell temperature and irradiation. This novel function predicts PV efficiency on a sunny and a cloudy day with [Formula: see text] and [Formula: see text] mean errors, respectively, which are considerably lower than errors obtained using other popular functions in the literature. The model helps in predicting actual output from a PV system more accurately which should enable taking more informed decisions regarding the location of installation, PV technology, and the need for a cooling method.

Ecohydrological insight: Solar farms facilitate carbon sink enhancement in drylands

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.

Solar Photovoltaic Architecture and Agronomic Management in Agrivoltaic System: A Review

Agrivoltaic systems (AVS) offer a symbiotic strategy for co-location sustainable renewable energy and agricultural production. This is particularly important in densely populated developing and developed countries, where renewable energy development is becoming more important; however, profitable farmland must be preserved. As emphasized in the Food-Energy-Water (FEW) nexus, AVS advancements should not only focus on energy management, but also agronomic management (crop and water management). Thus, we critically review the important factors that influence the decision of energy management (solar PV architecture) and agronomic management in AV systems. The outcomes show that solar PV architecture and agronomic management advancements are reliant on (1) solar radiation qualities in term of light intensity and photosynthetically activate radiation (PAR), (2) AVS categories such as energy-centric, agricultural-centric, and agricultural-energy-centric, and (3) shareholder perspective (especially farmers). Next, several adjustments for crop selection and management are needed due to light limitation, microclimate condition beneath the solar structure, and solar structure constraints. More importantly, a systematic irrigation system is required to prevent damage to the solar panel structure. To summarize, AVS advancements should be carefully planned to ensure the goals of reducing reliance on non-renewable sources, mitigating global warming effects, and meeting the FEW initiatives.

Environmental impacts of solar photovoltaic systems: A critical review of recent progress and future outlook

Photovoltaic (PV) systems are regarded as clean and sustainable sources of energy. Although the operation of PV systems exhibits minimal pollution during their lifetime, the probable environmental impacts of such systems from manufacturing until disposal cannot be ignored. The production of hazardous contaminates, water resources pollution, and emissions of air pollutants during the manufacturing process as well as the impact of PV installations on land use are important environmental factors to consider. The present study aims at developing a comprehensive analysis of all possible environmental challenges as well as presenting novel design proposals to mitigate and solve the aforementioned environmental problems. The emissions of greenhouse gas (GHG) from various PV systems were also explored and compared with fossil fuel energy resources. The results revealed that the negative environmental impacts of PV systems could be substantially mitigated using optimized design, development of novel materials, minimize the use of hazardous materials, recycling whenever possible, and careful site selection. Such mitigation actions will reduce the emissions of GHG to the environment, decrease the accumulation of solid wastes, and preserve valuable water resources. The carbon footprint emission from PV systems was found to be in the range of 14-73 g CO₂-eq/kWh, which is 10 to 53 orders of magnitude lower than emission reported from the burning of oil (742 g CO₂-eq/kWh from oil). It was concluded that the carbon footprint of the PV system could be decreased further by one order of magnitude using novel manufacturing materials. Recycling solar cell materials can also contribute up to a 42% reduction in GHG emissions. The present study offers a valuable management strategy that can be used to improve the sustainability of PV manufacturing processes, improve its economic value, and mitigate its negative impacts on the environment.

Water Conservation Potential of Self-Funded Foam-Based Flexible Surface-Mounted Floatovoltaics

A potential solution to the coupled water–energy–food challenges in land use is the concept of floating photovoltaics or floatovoltaics (FPV). In this study, a new approach to FPV is investigated using a flexible crystalline silicon-based photovoltaic (PV) module backed with foam, which is less expensive than conventional pontoon-based FPV. This novel form of FPV is tested experimentally for operating temperature and performance and is analyzed for water-savings using an evaporation calculation adapted from the Penman–Monteith model. The results show that the foam-backed FPV had a lower operating temperature than conventional pontoon-based FPV, and thus a 3.5% higher energy output per unit power. Therefore, foam-based FPV provides a potentially profitable means of reducing water evaporation in the world’s at-risk bodies of fresh water. The case study of Lake Mead found that if 10% of the lake was covered with foam-backed FPV, there would be enough water conserved and electricity generated to service Las Vegas and Reno combined. At 50% coverage, the foam-backed FPV would provide over 127 TWh of clean solar electricity and 633.22 million m3 of water savings, which would provide enough electricity to retire 11% of the polluting coal-fired plants in the U.S. and provide water for over five million Americans, annually.