Exploring the Impact of Recycling on Demand-Supply Balance of Critical Materials in Green Transition: A Dynamic Multi-Regional Waste Input-Output Analysis.

Addressing our climate urgency requires various renewable and low-carbon technologies, which often contain critical materials that face potential supply risks. Existing studies on the critical material implications of green transition have used various methodologies, each with pros and cons in providing a system understanding. Here, we integrated the dynamic material flow analysis and input-output modeling principles in an integrated multi-regional waste input-output model to assess the demand-supply balance and recycling potentials for cobalt, lithium, neodymium, and dysprosium under various energy scenarios projected to 2050. We show that although all four critical materials are likely to face strong growth in annual demand (as high as a factor of 25 compared to the 2015 level), only cobalt has a higher cumulative demand by 2050 than the known reserves. Nevertheless, considering the sheer scale of demand increase and long lead time of opening or expanding new mines, recycling efforts are urgently needed to supplement primary supply toward global green transition. This model integration is proven useful and can be extended to more critical materials and green technologies.

A multi-disciplinary approach to estimate the medium-term impact of COVID-19 on transport and energy: A case study for Italy.

The aim of this paper is to estimate the potential impacts of different COVID-19 scenarios on the Italian energy sector through 2030, with a specific focus on transport and industry. The analysis takes a multi-disciplinary approach to properly consider the complex interactions of sectors across Italy. This approach includes the assessment of economic conditions using macroeconomic and input-output models, modelling the evolution of the energy system using an energy and transport model, and forecasting the reaction of travel demand and modal choice using econometric models and expert interviews. Results show that the effect of COVID-19 pandemic may lead to mid-term effects on energy consumption. The medium scenario, which assumes a stop of the emergency by the end of 2021, shows that energy-related emissions remain 10% lower than the baseline in the industry sector and 6% lower in the transport sector by 2030, when compared with a pre-COVID trend. Policy recommendations to support a green recovery are discussed in light of the results.

Advancing the representation of reservoir hydropower in energy systems modelling: The case of Zambesi River Basin.

In state-of-the-art energy systems modelling, reservoir hydropower is represented as any other thermal power plant: energy production is constrained by the plant's installed capacity and a capacity factor calibrated on the energy produced in previous years. Natural water resource variability across different temporal scales and the subsequent filtering effect of water storage mass balances are not accounted for, leading to biased optimal power dispatch strategies. In this work, we aim at introducing a novelty in the field by advancing the representation of reservoir hydropower generation in energy systems modelling by explicitly including the most relevant hydrological constraints, such as time-dependent water availability, hydraulic head, evaporation losses, and cascade releases. This advanced characterization is implemented in an open-source energy modelling framework. The improved model is then demonstrated on the Zambezi River Basin in the South Africa Power Pool. The basin has an estimated hydropower potential of 20,000 megawatts (MW) of which about 5,000 MW has been already developed. Results show a better alignment of electricity production with observed data, with a reduction of estimated hydropower production up to 35% with respect to the baseline Calliope implementation. These improvements are useful to support hydropower management and planning capacity expansion in countries richly endowed with water resource or that are already strongly relying on hydropower for electricity production.

The Exponential Phase of the Covid-19 Pandemic in Central Italy: An Integrated Care Pathway.

The Coronavirus Disease (Covid-19) pandemic is rapidly spreading across the world, representing an unparalleled challenge for health care systems. There are differences in the estimated fatality rates, which cannot be explained easily. In Italy, the estimated case fatality rate was 12.7% in mid-April, while Germany remained at 1.8%. Moreover, it is to be noted that different areas of Italy have very different lethality rates. Due to the complexity of Covid-19 patient management, it is of paramount importance to develop a well-defined clinical workflow in order to avoid the inconsistent management of patients. The Integrated Care Pathway (ICP) represents a multidisciplinary outline of anticipated care to support patient management in the Sant'Andrea Hospital, Rome. The main objective of this pilot study was to develop a new ICP evaluated by care indicators, in order to improve the COVID-19 patient management. The suggested ICP was developed by a multi-professional team composed of different specialists and administrators already involved in clinical and management processes. After a review of current internal practices and published evidences, we identified (1) the activities performed during care delivery, (2) the responsibilities for these activities, (3) hospital structural adaptation needs and potential improvements, and (4) ICP indicators. The process map formed the basis of the final ICP document; 160 COVID-19 inpatients were considered, and the effect of the ICP implementation was evaluated over time during the exponential phase of the COVID-19 pandemic. In conclusion, a rapid adoption of ICP and regular audits of quality indicators for the management of COVID-19 patients might be important tools to improve the quality of care and outcomes.