Unit Capacity Research Articles

Study on the carbon footprint of cold storage units using low-GWP alternative refrigerants

The increasing contribution of refrigeration systems to global warming has led to widespread demand for low global warming potential (GWP) refrigerants as alternatives. This paper proposed a comprehensive environmental assessment method for evaluating the carbon footprint of units charged with low-GWP refrigeration. Experimental and numerical studies were used to investigate the carbon footprint impact of using alternative refrigerants at different ambient temperatures in China. Initially, the model was validated through experimental case studies on the use stage of cold storage units. Subsequently, a comparison was made between the cooling capacity (CC) and energy efficiency ratio (EER) of cold storage units charged with different refrigerants. Additionally, the impact of alternative refrigerants in the use stage was analyzed by numerical calculations, and the adaptability of the cold storage unit to the ambient temperature and the national energy structure was also studied. The results indicate that among the four stages of the cold storage unit, the use stage is the hotspot of carbon footprint due to the large amount of energy consumption and the existence of refrigerant leakage and other behaviors. Utilizing low-GWP alternative refrigerants could significantly reduce the carbon footprint of the cold storage units' use stage by 10.56%–16.39%, thereby lowering the whole stage carbon footprint. Furthermore, the ambient temperature and national energy structure could also effectively reduce the carbon footprint of cold storage units' whole stage by 1%–27.17%. Furthermore, after adopting low GWP refrigerants, the life-cycle cost (LCC) of the units have also decreased by 6.1%–12%. Taking into account both environmental impact and economic considerations, it is recommended to directly replace R404A with R448A in the units in regions where the average ambient temperature is above 15 °C.

Almost disjoint paths and separating by forbidden pairs

By Menger's theorem, the maximum number of arc-disjoint paths from a vertex s to a vertex t in a directed graph equals the minimum number of arcs needed to disconnect s and t, i.e., the minimum size of an s-t-cut. The max-flow problem in a network with unit capacities is equivalent to the arc-disjoint paths problem. Moreover, the max-flow and min-cut problems form a strongly dual pair. We relax the disjointedness requirement on the paths, allowing them to be almost disjoint, meaning they may share up to one arc. The resulting almost disjoint paths problem (ADP) asks for k s-t-paths such that any two of them are almost disjoint. The separating by forbidden pairs problem (SFP) is the corresponding dual problem and calls for a set of k arc pairs such that every s-t-path contains both arcs of at least one such pair.In this paper, we explore these two problems, showing that they have an unbounded duality gap in general and analyzing their complexity. We prove that ADP is NP-complete when k is part of the input and that SFP is Σ2P-complete, even for acyclic graphs. Furthermore, we efficiently solve ADP when k≤2 is fixed and present a polynomial time algorithm based on dynamic programming for ADP when k is constant.

Hospital management of an epidemic in intensive care: a predictive tool for saturation

Abstract The COVID-19 epidemic has highlighted the importance of hospital resource management in exceptional health contexts. The hospital capacity of intensive care units has emerged as a determining factor in overall hospital management. The objective of this study is to create a tool for predicting the saturation status of an intensive care unit. The predictive model was developed based on a SIR compartmental model. The model was trained using hospitalization data (admissions, discharges, and capacity) from the Raymond Poincaré Hospital, AP-HP. The model parameters (transmission and recovery rates) were estimated using the least squares method. A web application, OHASiS® (Outil Hospitalier d'Analyse de Situations de Saturations), was developed using Shiny and embeds the model. The model provides a reliable prediction over 7 days of the evolution of the number of admissions and discharges in COVID-19 intensive care units. Information on capacity makes it possible to predict a possible saturation of the service. A sensitivity analysis of the model revealed no significant difference between predicted and observed attendance data. The OHASiS® tool allows for the visualization of epidemiological data and helps with medical decision-making as the epidemic evolves. It would be desirable to integrate this application into future hospital management plans. This tool could also be used during simulation exercises. Validation of the predictive model in the context of seasonal epidemics still needs to be conducted. Key messages • A SIR compartmental model was used to develop a tool for predicting the saturation status of ICU. • The web application OHASiS® can help with medical decision-making and should be integrated into future hospital management plans, though further validation is needed for use during seasonal epidemics.

Synergistic energy system [Sm3+-Eu3+-Tm3+]:CsPbI2.4Br0.6 designing and thermal optimization for photovoltaic and electrical applications

Current work, for the first time elucidates the fabrication and energy applications of the novel perovskite hetero-system formed by the ternary lanthanide doping of CsPbI2.4Br0.6 leading to formation of [Sm3+-Eu3+-Tm3+]:CsPbI2.4Br0.6 (SET:CPVSK). SET:PVSK was tailored for the band gap spanning over the range of 1.59–1.66 eV over the course of 28 days, exhibiting excellent stability. With the cubic crystalline geometry, the spin coated thin films expressed maximum coverage and profound binding to substrate. As a perovskite light absorber, SET:CVSK based solar cell gained an efficiency of 17 % with the 68.92 % of fill factor and an expanded open circuit voltage (Voc) of 1.08 V. As an electro-catalyst, SET:CPVSK expressed moderate oxygen generation. While it demonstrated magnanimous pure hydrogen generation showing impressively minimal overpotential and Tafel slope value of 142 mV and 122.7 mV dec−1, respectively. With an extended service life in the electrolyte medium, SET:CPVSK adorned nickel foam electrode was marked by superior unit capacity of 661.24 mAH g−1 while the equivalent series resistance (Rs) i.e. 0.67 Ω, which shows the minimal resistance and facilitated diffusion of ions.

Perspectives on Assessing the Flexibility of Hospitals for Crisis Mode Operations: Lessons From the COVID-19 Pandemic in the Netherlands.

The COVID-19 pandemic placed healthcare design at the heart of the crisis. Hospitals faced challenges such as rapidly increasing their intensive care unit capacity, enabling physical distancing measures, quickly converting to telehealth and telework practices, and above all, keeping patients and staff safe. Improving flexibility in hospital facility design and adaptability of hospital operations to function in "crisis mode" can be seen as ways of future-proofing for pandemics. In a design brief, flexibility is typically mentioned as an important target. Meanwhile, robustness of technical infrastructure is called for, and standardization at unit level with single-occupancy inpatient accommodation may be considered a way to enhance flexibility and adaptability in dealing with a surge in infectious patients. To future-proof facility design with pandemic preparedness and resilience in mind, this study evaluated what kinds of interventions were taken in Dutch hospital facilities and what perspectives need to be considered when hospitals operate in crisis mode. We have collected data from facility and estate professionals from 30 Dutch hospitals. Using a practice-based approach, in-depth interviewing helped uncover and compare successful operational strategies and design elements that provided the flexibility needed in the early stages of the recent crisis. As we looked at existing facilities and alterations made to allow hospitals to operate during the COVID-19 pandemic, we discovered that staff availability and adaptability were deemed crucial. We add the perspective of staff as an essential factor to be considered when future-proofing hospital facility desigr crisis mode operation.

Design of High Gain Luo Converter for PV System Applications

Photovoltaic (PV) power generation requires a bigger area per unit capacity than traditional power plants since it employs a limitless and clean energy source. As a result, installing floating PV systems (FPVs) on open sea surfaces is becoming more common in countries with tiny landmasses, such as South Korea, Japan, and Vietnam. For use in applications involving PV systems, this paper suggests a design for a high-gain LUO converter. This proposed system consists of a LUO converter for a PV system. A converter’s output voltage can be increased while staying constant throughout the system by using the proposed converter (a Luo converter). Step-up or boost converters increase the voltage from their input (supply) to their output (load) while converting DC to electricity. The PWM generator, which is connected to the power source and produces PWM pulses to modify the signal in the LUO converter, is used to produce PWM pulses.

Design and Frame Strength Evaluation of Salt Washing Unit Capacity 50 Kg/hour

The salt washing unit is part of the salt processing machine. This unit's function is to wash raw salt with brine. This unit has a motor, agitator blade, washing chamber, and frame. The frame structure strength of the salt washing unit needs to be evaluated to ensure safety. This research aims to design the salt washing unit and obtain simulation results of frame structure strength to ensure the safety of the salt washing unit. This research was carried out by simulation to look for stress, strain, and changes in the shape of objects (displacement). The frame strength simulation was carried out using Solidwork software. The salt washing unit with a 50 kg/hour capacity has been designed. It has a cylindrical shape with 990 mm in height and 680 mm in diameter. From the simulation results of strain, it can be concluded that the minimum point is 1.80 × 108 Mpa, and the maximum point is 1.63 × 105 Mpa. From the simulation results of displacement, it can be concluded that the minimum point is 0 mm and the maximum point is 2,296 mm. The maximum stress is 5.254×106 N/m2, and the minimum stress point is 1.803×106 N/m2.

Bidirectional pruned tree-based efficient minimum cut acceleration in dense graph

The minimum cut (min-cut) problem has been extensively investigated, and the corresponding algorithms have been used in many related problems. The recently proposed acceleration strategy based on tree-cut mapping has been shown to be an effective alternative, with a slight loss in acceleration accuracy. However, the existing method requires a large number of ineffective traversal passes in the high-overhead preprocessing step, which has the potential to be significantly improved in mapping effective graphs, i.e. dense graphs. To solve the problem, we propose to use bidirectional pruned tree for tree-cut mapping, which combines pruned depth-first traversal tree and bidirectional traversal paths to enumerate as many different tree instances as possible. Thus, it can help find the min-cut of any node pair efficiently. Theoretical analysis also shows its potential. For its serial implementation in a graph with M edges, after a preprocessing step with a time complexity as low as O(M), 99.9% of sampled node pairs can obtain their exact min-cut value in various types of dense graphs with degrees greater than 8 in experiments. In addition, the same precision can be obtained in sparse graphs in case of unit capacity. Per-pair running time in a million-node graph can be several orders of magnitude faster than existing methods and as low as several microseconds, so can be used as an effective complement to existing methods.

The Design of an Intelligent Lightweight Stock Trading System Using Deep Learning Models: Employing Technical Analysis Methods

Individual investors often struggle to predict stock prices due to the limitations imposed by the computational capacities of personal laptop Graphics Processing Units (GPUs) when running intensive deep learning models. This study proposes solving these GPU constraints by integrating deep learning models with technical analysis methods. This integration significantly reduces analysis time and equips individual investors with the ability to identify stocks that may yield potential gains or losses in an efficient manner. Thus, a comprehensive buy and sell algorithm, compatible with average laptop GPU performance, is introduced in this study. This algorithm offers a lightweight analysis method that emphasizes factors identified by technical analysis methods, thereby providing a more accessible and efficient approach for individual investors. To evaluate the efficacy of this approach, we assessed the performance of eight deep learning models: long short-term memory (LSTM), a convolutional neural network (CNN), bidirectional LSTM (BiLSTM), CNN Attention, a bidirectional gated recurrent unit (BiGRU) CNN BiLSTM Attention, BiLSTM Attention CNN, CNN BiLSTM Attention, and CNN Attention BiLSTM. These models were used to predict stock prices for Samsung Electronics and Celltrion Healthcare. The CNN Attention BiLSTM model displayed superior performance among these models, with the lowest validation mean absolute error value. In addition, an experiment was conducted using WandB Sweep to determine the optimal hyperparameters for four individual hybrid models. These optimal parameters were then implemented in each model to validate their back-testing rate of return. The CNN Attention BiLSTM hybrid model emerged as the highest-performing model, achieving an approximate rate of return of 5 percent. Overall, this study offers valuable insights into the performance of various deep learning and hybrid models in predicting stock prices. These findings can assist individual investors in selecting appropriate models that align with their investment strategies, thereby increasing their likelihood of success in the stock market.

Evolution trend analysis of carbon emissions in light industrial parks: A system dynamics approach

AbstractThe industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered.

Distributed Cooperative AGC Method for New Power System With Heterogeneous Frequency Regulation Resources

The inverter-interfaced renewable energy is increasing in future new power systems, both the system rotary inertia and frequency regulation capacity of traditional units are decreasing and becoming increasingly insufficient. It is urgent to explore various types of frequency regulation resources, especially for inverter-interfaced units that show fast response speed. The heterogeneous frequency regulation resources generally have different system models, capacities, and response speeds, which challenges the automatic generation control (AGC). In this paper, to make the heterogeneous frequency regulation resources provide improved frequency regulation performance, a novel distributed cooperative AGC method is proposed. Firstly, a distributed consensus-based area control error (ACE) discovery algorithm is proposed. Then, each frequency regulation unit can participate in the frequency regulation with an individual PI controller based on the discovered ACE information. Finally, by controlling the low-speed AGC units to generate more power, it can release the power capacity of the high-speed AGC units to prepare for the following round of AGC services. Furthermore, the communication delays are also considered for the proposed distributed AGC algorithm design. The improved performance of the proposed AGC method is verified based on the simulation study of a two-area power system with five different kinds of frequency regulation units.

Assessing the efficiency of ozone-based advanced drinking water treatment processes in removing antibiotics and antibiotic-resistant genes: Pilot-scale research

With the widespread use of antibiotics, the emergence of antibiotics and antibiotic resistance genes (ARGs) poses a potential threat to public health. Drinking water plants are both the source and sink of these pollutants. In this study, we investigated and analyzed the distribution of four major types of antibiotics and ARGs in a drinking water plant with advanced treatment processes (ozone and activated carbon units) located in the central region of China. Among these treatment processes, the ozone process had significant removal effects on antibiotics and resistance genes, ranging from 15.10–91.17 % and 0.07–1.27 log, (except for ermA and qnrD) respectively. A correlation analysis of the concentrations of antibiotics and ARGs revealed a significant correlation (0.95 < r < 1) between antibiotics and ARGs, as well as between different types of ARGs. Additionally, the mechanism of ozone in the lab- and pilot-scale tests was analyzed to improve the removal capacity of ozone units for target pollutants. The experimental results showed that the removal efficiency of antibiotics and ARGs by ozone could be effectively improved by increasing the ozone dosage (5 mg/L), pH (9), and reaction time (10 min). The removal efficiency of the pollutants ranged between 36.65 % and 96.01 %. Under optimal reaction conditions, the results of the pilot-scale ozone experiment were significantly better than the actual treatment effects in drinking water plants. Our findings provide a theoretical basis for the optimization of the ozone process in actual drinking water plants.

Linker Engineering for Reactive Oxygen Species Generation Efficiency in Ultra-Stable Nickel-Based Metal-Organic Frameworks.

Interfacial charge transfer on the surface of heterogeneous photocatalysts dictates the efficiency of reactive oxygen species (ROS) generation and therefore the efficiency of aerobic oxidation reactions. Reticular chemistry in metal-organic frameworks (MOFs) allows for the rational design of donor-acceptor pairs to optimize interfacial charge-transfer kinetics. Herein, we report a series of isostructural fcu-topology Ni8-MOFs (termed JNU-212, JNU-213, JNU-214, and JNU-215) with linearly bridged bipyrazoles as organic linkers. These crystalline Ni8-MOFs can maintain their structural integrity in 7 M NaOH at 100 °C for 24 h. Experimental studies reveal that linker engineering by tuning the electron-accepting capacity of the pyrazole-bridging units renders these Ni8-MOFs with significantly improved charge separation and transfer efficiency under visible-light irradiation. Among them, the one containing a benzoselenadiazole unit (JNU-214) exhibits the best photocatalytic performance in the aerobic oxidation of benzylamines with a conversion rate of 99% in 24 h. Recycling experiments were carried out to confirm the stability and reusability of JNU-214 as a robust heterogeneous catalyst. Significantly, the systematic modulation of the electron-accepting capacity of the bridging units in donor-acceptor-donor MOFs provides a new pathway to develop viable noble-metal-free heterogeneous photocatalysts for aerobic oxidation reactions.

Polycentric governance systems: addressing the power gap centered on climate entrepreneurs in Semnan Province of Iran

ABSTRACT Polycentric governance systems seek to solve environmental challenges through the involvement of diverse actors at different decision-making levels. However, previous studies did not confirm the positive performance of polycentric governance in social interactions with certainty. Therefore, the aim of the study was to identify the capacity and performance of current actors and units to understand their impact on the performance of polycentric governance systems perspective as a whole. For this purpose, this study investigated the theory of polycentric governance systems on a large scale in Semnan province of Iran. The social network analysis (SNA) and its 12 indices were used as a methodology of research, including 352 heterogeneous actors with different capacities, were interviewed and studied. The results showed that the power and leadership of key actors play an effective role in the stability and development of polycentric governance systems. The power sharing between decision-making centers is implemented through the interlevel communication of climate entrepreneurs. The comparison of performances showed that public management could not meet the leadership criteria as well as private actors. The final results showed that the total performance of the polycentric governance system of environment was positive and influenced by the performance of pioneer NGOs and climate entrepreneurs.

Nonlinear coupling vibration analyses of large-scale wind turbine system

With the development of wind energy, the unit capacity of wind turbine is becoming larger and the height of the support tower is getting higher. Limited by the transport conditions, the diameter of the tubular steel tower cannot further increase with the increase of the tower height, which results in the lower natural frequencies of the tower. The higher and more slender wind turbine towers are more sensitive to the external excitation and many tower collapses have occurred in recent years because of the interplay with the longer rotor blades. A 2 MW wind turbine system with a 120 m full steel tubular tower is taken as an example in this study to research the nonlinear coupling vibration mechanism under the normal operation case and the emergency shut-down case. An integrated model of large-scale wind turbine system including the tower, blades, hub, and nacelle is established by the open-source software FAST to study its nonlinear interaction vibration mechanism. Under the normal operation load case, the acceleration response of the steel wind turbine tower is greatly affected by the rotational frequency of the rotor. The maximum accelerations in the fore-aft and side-side directions both appear around the middle-upper height of the tower. Under the emergency shut-down load case, the maximum fore-aft acceleration response appears at the top of the tower, but the maximum side-side response still appears around the middle-upper height of the tower. The first-order vibration mode plays a dominant role in the top fore-aft acceleration and the second-order vibration mode has great contribution to the side-side acceleration under the emergency shut-down load case. The numerical results of this study can provide insight into the vibration control mechanism of the full steel tower.

Geochemical and H–O–Sr–B isotope signatures of Yangyi geothermal fields: implications for the evolution of thermal fluids in fracture-controlled type geothermal system, Tibet, China

High-temperature hydrothermal systems are mainly distributed in the north–south graben systems of southern Tibet as an important part of the Mediterranean–Tethys Himalayan geothermal belt in mainland China. As the largest unit capacity and second stable operating geothermal power station in China, Yangyi is the fracture-controlled type geothermal field in the center of Yadong–Gulu Graben. In this paper, hydrogeological and hydrochemical characteristics, isotope composition (δD and δ18O, 87Sr/86Sr and δ11B) of borehole water, hot springs, and surface river samples were analyzed. From the conservative elements (such as Cl− and Li+) and δD and δ18O values, the geothermal water of the Yangyi high-temperature geothermal field is estimated to be of meteoric origin with the contributions of chemical components of the magmatic fluid, which is provided by partially molten granite as a shallow magmatic heat source. According to logging data, the geothermal gradient and terrestrial heat flow value of the Yangyi high-temperature geothermal field are 6.48 ℃/100 m and 158.37 mW m−2, respectively. Combining the hydrothermal tracer experiment, 87Sr/86Sr and δ11B ratios obtained with gradually decreasing reservoir temperatures from the Bujiemu stream geothermal zone to Qialagai stream geothermal zone, we suggested the deep geothermal waters were mixed with local cold groundwater and then flow northeastward, forming the shallow reservoir within the crushed zone and intersect spot of faults in the Himalayan granitoid. Furthermore, in the process of ascent, the geothermal water is enriched in K+, Na+, and HCO3− during the interaction with underlying Himalayan granitoid and pyroclastic rocks that occur as wall rocks. The detailed description and extensive discussion are of great significance for the further exploitation and utilization of north–south trending geothermal belts in Tibet.

Environmental and economic impact assessment of synergistic organic-waste treatment strategies in eco-industrial parks: A pilot-scale case study in Shenzhen, China

The acceleration of urbanization has posed significant challenges for the urban organic-waste treatment in megacities and large cities of developing countries. Synergistic organic-waste treatment in eco-industrial parks is essential for achieving China's “zero-waste” and ambitious low-carbon targets. However, the environmental impact and benefit evaluation of synergistic organic-waste treatment in eco-industrial parks remain unclear. In this study, life cycle assessment methods were applied for the environmental management of a newly developed eco-industrial park for synergistic organic-waste treatment in Shenzhen city, China, with a population of 20 million. The synergistic eco-industrial park alleviated the direct and indirect environmental impacts of waste treatment and increased the profit, owing to the electricity recovery, fewer transportation activities, and co-composting treatment. A 38.8–88.2% decrease was observed in the environmental impacts of unit capacity in the synergistic mode compared to the independent mode. Moreover, the profit in the synergistic mode was 2 times higher than in the case with independent plants. Overall, synergistic organic-waste treatment facilities can be incorporated in industrial parks to treat organic waste in an effective and environmentally friendly manner. These findings can provide novel insights for understanding synergistic organic-waste treatment in eco-industrial parks and enhancing the low-carbon performance of megacities and large cities.

Critical Care Units in Malawi: A Cross-Sectional Study.

The global burden of critical illness falls disproportionately outside high-income countries. Despite younger patient populations with similar or lower disease severity, critical illness outcomes are poor outside high-income countries. A lack of data limits attempts to understand and address the drivers of critical care outcomes outside high-income countries. We aim to characterize the organization, available resources, and service capacity of public sector critical care units in Malawi and identify barriers to improving care. We conducted a secondary analysis of the Malawi Emergency and Critical Care Survey, a cross-sectional study performed from January to February 2020 at all four central hospitals and a simple random sample of nine out of 24 public sector district hospitals in Malawi, a predominantly rural, low-income country of 19.6 million in southern Africa. Data from critical care units were used to characterize resources, processes, and barriers to care. There were four HDUs and four ICUs across the 13 hospitals in the Malawi Emergency and Critical Care Survey sample. The median critical care beds per 1,000,000 catchment was 1.4 (IQR: 0.9 to 6.7). Absent equipment was the most common barrier in HDUs (46% [95% CI: 32% to 60%]). Stockouts was the most common barriers in ICUs (48% [CI: 38% to 58%]). ICUs had a median 3.0 (range: 2 to 8) functional ventilators per unit and reported an ability to perform several quality mechanical ventilation interventions. Although significant gaps exist, Malawian critical care units report the ability to perform several complex clinical processes. Our results highlight regional inequalities in access to care and support the use of process-oriented questions to assess critical care capacity. Future efforts should focus on basic critical care capacity outside of urban areas and quantify the impact of context-specific variables on critical care mortality.

The care of critically ill adults with COVID-19 in Ontario pediatric intensive care units.

To describe and review the experience of two pediatric intensive care units (PICUs) in Ontario, Canada, adapting and providing care to critically ill adults during the COVID-19 pandemic. At a time of extreme pressure to adult intensive care unit (ICU) capacity, two PICUs provided care to critically ill adults with COVID-19 pneumonia. Substantial yet rapid planning was required to facilitate safe delivery of critical care to adult patients while maintaining PICU services, including thoughtful development of care pathways and patient selection. To prepare clinical staff, several communication strategies, knowledge translation, skill consolidation, andsystem-adaptation mechanisms were developed. There was iterative adaptation of operational processes, including staffing models, specialist consultation, and the pharmacy. Care provided by the interprofessional teams was reoriented as appropriate to the needs of critically ill adults in close collaboration with adult ICU teams. Forty-one adults were admitted to the two PICUs over a 12-week period. In total, 36 patients (88%) received invasive ventilation, eight patients (20%) were supported with venovenous extracorporeal membrane oxygenation, and six patients (15%) received continuous renal replacement therapy. Four died in the PICU during this period. Feedback from staff included anxiety around reorienting practice to the care of critically ill adults, physical exhaustion, and psychological distress. Importantly, staff also reported a renewed sense of purpose with participation in the program. Though challenging, the experience has provided opportunity to enhance collaboration with partner institutions and improve the care of older children and adolescents in the PICU.

Daily rolling estimation of carbon emission cost of coal-fired units considering long-cycle interactive operation simulation of carbon-electricity market

The high overlap of participants in the carbon emissions trading and electricity markets couples the operations of the two markets. The carbon emission cost (CEC) of coal-fired units becomes part of the power generation cost through market coupling. The accuracy of CEC calculation affects the clearing capacity of coal-fired units in the electric power market. Study of carbon–electricity market interaction and CEC calculations is still in its initial stages. This study analyzes the impact of carbon emissions trading and compliance on the operation of the electric power market and defines the cost transmission mode between the carbon emissions trading and electric power markets. A long-period interactive operation simulation mechanism for the carbon–electricity market is established, and operation and trading models of the carbon emissions trading market and electric power market are established. A daily rolling estimation method for the CEC of coal- fired units is proposed, along with the CEC per unit electric quantity of the coal-fired units. The feasibility and effectiveness of the proposed method are verified through an example simulation, and the factors influencing the CEC are analyzed.