A PK _Sn,Pb /PK _Pb tandem was found to be the most promising PV technology for lowering the environmental impacts from solar PVs.

With solar photovoltaics (PV) playing an increasing role in our global energy market, it is now timely and critical to understand the end of life management of the solar panels. Recycling the panels can be an important pathway, possibly recovering a considerable amount of materials and adding economic benefits from currently installed solar panels. Yet, to date, the costs and benefits of recycling, especially when externality costs resulting from environmental pollution are considered, are largely unknown. In this study, we quantified the private and externality costs and benefits of recycling crystalline silicon (c-Si) PV panels. We found that the private cost of end-of-life (EoL) management of the c-Si PV module is USD 6.7/m² and much of this cost is from transporting (USD 3.3/m²) and landfilling (USD 3.1/m²), while the actual recycling process (the cost of consumed materials, electricity or the investment for the recycling facilities) is very small (USD 0.3/m²). We found that the external cost of PV EoL management is very similar to the private cost (USD 5.2/m²). Unlike the breakdown of the private costs, much of the externality costs (USD 4.08/m²) come from the recycling process, which suggests that more environmentally friendly methods (e.g., recycling methods that involve fewer toxic chemicals, acids, etc.) should be preferred. We estimated that the total economic value of the recycled materials from c-Si PV waste is USD 13.6/m². This means that when externality costs are not considered, the net benefit of recycling is USD 6.7; when the externality cost of recycling is considered, there is still a net benefit of USD 1.19 per m².

The rise of artificial intelligence (AI), blockchain (BC), and the internet of things (IoT) has had significant applications in the advancement of sustainability research. This review examines how these digital transformations drive natural and human systems, as well as which industry sectors have been applying them to advance sustainability. We adopted qualitative research methods, including a bibliometric analysis, in which we screened 960 publications to identify the leading sectors that apply AI/BC/IoT, and a content analysis to identify how each sector uses AI/BC/IoT to advance sustainability. We identified “smart city”, “energy system”, and “supply chain” as key leading sectors. Of these technologies, IoT received the most real-world applications in the “smart city” sector under the dimensions of “smart environment” and “smart mobility” and provided applications resolving energy consumption in the “energy system” sector. AI effectively resolved scheduling, prediction, and monitoring for both the “smart city” and “energy system” sectors. BC remained highly theoretical for “supply chain”, with limited applications. The technological integration of AI and IoT is a research trend for the “smart city” and “energy system” sectors, while BC and IoT is proposed for the “supply chain”. We observed a surge in AI/BC/IoT sustainability research since 2016 and a new research trend—technological integration—since 2020. Collectively, six of the United Nation’s seventeen sustainable development goals (i.e., 6, 7, 9, 11, 12, 13) have been the most widely involved with these technologies.