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Coal will continue to be the main energy source in China for the immediate future, although the environmental pollution and ecological impacts of each stage in the full life cycle of coal mining, transportation, and combustion generate large quantities of external costs. The Late Permian coals in southwestern (SW) China usually contain high amounts of fluorine (F), arsenic (As), and ash, which together with high-F clays cause abnormally high levels of endemic fluorosis, As poisoning, and lung cancer in areas where coal is mined and burned. In this paper, we estimate the external costs of the life cycle of coal. The results show that the externalities of coal in SW China are estimated at USD 73.5 billion or 284.3 USD/t, which would have accounted for 6.5 % of the provincial GDP in this area in 2018. The external cost of human health accounts for 87.2% of the total external costs, of which endemic skeletal fluorosis diseases and related lung cancers have the most important impact. Our study provides a more precise estimate of externalities compared with its counterparts in other provinces in China. Therefore, several policy recommendations would be proposed to internalize the external cost.

In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project’s design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project’s market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources.

The nature of the electrode–electrolyte interface has an impact on the performance and durability of lithium-ion batteries (LIBs). The initial electrolyte’s thermodynamic instability at the anode–electrolyte interface in LIBs results in the formation of a passivation layer, called solid electrolyte interphase (SEI). The initial dense and intact layer allows Li+ transport and restricts electron tunneling, thus preventing electrolyte decomposition and ensuring the electrochemical stability of a battery. However, the growth of this layer can reduce the availability of active lithium and electrolyte, and ultimately lead to an irreversible battery capacity fade. Investigating the transport phenomena of lithium ions within SEI is crucial for understanding its formation and growth. Nonetheless, accurately describing all relevant mechanisms is challenging due to its complex and multiscale nature. An overview of current computational efforts to study Li+ transport within SEI is given in this article, ranging from electronic/atomistic scale simulations to macroscopic models. The drawbacks and advantages of the proposed numerical approaches are summarized along with the obstacles that need to be overcome to obtain accurate experimental data, identified on the basis of the most recent literature evidence. We highlight collaboration gaps between modeling and experimental approaches, as well as the urgent need for new multiscale models, to gain a better understanding of such a crucial transport phenomenon.

In this paper, a methodology for optimal decision making for electrical systems is addressed. This methodology seeks to identify and to prioritize the replacement and maintenance of a power asset fleet optimizing the return of investment. It fulfills this objective by considering the risk index, the replacement and maintenance costs, and the company revenue. The risk index is estimated and predicted for each asset using both its condition records and by evaluating the consequence of its failure. The condition is quantified as the probability of failure of the asset, and the consequence is determined by the impact of the asset failure on the whole system. Failure probability is estimated using the health index as scoring of asset condition. The consequence is evaluated considering a failure impact on the objectives of reliability (energy not supplied -ENS), environment, legality, and finance using Monte Carlo simulations for an assumed period of planning. Finally, the methodology was implemented in an open-source library called PywerAPM for assessing optimal decisions, where the proposed mathematical optimization problem is solved. As a benchmark, the power transformer fleet of the New England IEEE 39 Bus System was used. Condition records were provided by a local utility to compute the health index of each transformer. Subsequently, a Monte Carlo contingency simulation was performed to estimate the energy not supplied for a period of analysis of 10 years. As a result, the fleet is ranked according to risk index, and the optimal replacement and maintenance are estimated for the entire fleet.

If not properly designed, the adoption of large windows can sometimes have a negative impact on building energy demand. For this reason, aggravated by the outdated building envelope of the healthcare building stock, large fenestration systems are usually avoided in hospitals, especially in old structures. However, with appropriate glazing specifications, the adoption of wider openings can result into significant energy savings, lower costs and strong positive effects on patients and staff well-being. The present study investigates how different window sizes and types of glazing affect heating, cooling and lighting energy demand in a hospital patient room. The objective is to evaluate the energy savings that may be obtained when installing larger windows and to identify the glazing properties allowing one to reach the maximum energy reductions. Simulations were carried out using nine diverse glazing systems, already available on the market, and their energy performance was evaluated in relation to two different window areas: a common size opening, characterized by a 25% Window-to-Wall Ratio (WWR), and a floor to ceiling window, with 77% WWR. The analysis was conducted taking into consideration four different orientations in four Italian cities, supposing two artificial lighting control strategies. The results highlighted how the adoption of wider windows with appropriate glazings and a daylight-linked dimming lighting control strategy may lower the primary energy demand up to 17%.

Lithium titanium oxide (Li4Ti5O12, LTO) is an attractive negative electrode for the development of safe—next-generation—lithium-ion batteries (LIBs). LTO can find specific applications complementary to existing alternatives for LIBs thanks to its good rate capability at high C-rates, fast lithium intercalation, and high cycling stability. Furthermore, LIBs featuring LTO electrodes are inherently safer owing to the LTO’s operating potential of 1.55 V vs. Li+/Li where the commonly used organic-based electrolytes are thermodynamically stable. Herein, we report the combined use of water-soluble sodium alginate (SA) binder and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI)-tetraglyme (1m-T) electrolyte and we demonstrate the improvement of the electrochemical performance of LTO-based electrodes with respect to those operating in conventional electrolyte 1M LiPF6-ethylene carbonate: dimethyl carbonate (LP30). We also tackle the analysis of the impact of combining the binder/electrolyte on the long-term cycling performance of LTO electrodes featuring SA or conventional polyvinylidene fluoride (PVdF) as binders. Therefore, to assess the impact of the combination of binder/electrolyte on performance, we performed post-mortem characterization by ex situ synchrotron diffraction experiments of LTO electrodes after cycling in LP30 and 1m-T electrolytes.

The COVID-19 pandemic has had a huge impact on society. Scientists are working to mitigate the impact in many ways. As a field closely related to human life, building engineering can make a great contribution. In this article, we started with the concept of the smart building as our guide. The impact of COVID-19 on daily energy consumption, information and communication technology, the ventilation of the interior environment of buildings, and the higher demand for new energy technologies such as electric vehicles is an entry point. We discuss how the concept of the smart building and related technologies (refrigeration, measurement, sensor networks, robotics, local energy generation, and storage) could help human society respond to the pandemic. We also analyze the current problems and difficulties that smart buildings face and the possible future directions of this technology.

The magnitude of the impact of the pandemic on key variables, such as electricity demand, mobility of people and number of COVID-19 hospitalization cases, has been unprecedented. Existing economic models have not estimated the impact of sucokh events. This paper fills this gap, investigating the nexus among electricity demand elasticity, shifting behaviors of mobility and COVID-19 contagion with econometric estimation techniques. Firstly, using the single bids to purchase recorded in the Italian day-ahead wholesale electricity market in 2020, we estimate hourly electricity demand and price elasticity directly from short-run consumer behavior. Then, we analyze the effects of the main aspects of the pandemic, the health situation and the mobility contraction at the national level, on the estimated price elasticities. The period of heavy lockdown between 10 March and 3 June recorded a reduction in the price elasticity of electricity demand. However, when the pandemic broke out again at the beginning of October, elasticity increased, highlighting how companies and economic activities had adopted countermeasures to avoid the arrest of the economy and, consequently, the sharp contraction in electricity demand.