Low-carbon transformation of power structure under the "double carbon" goal: power planning and policy implications.

The proposal of "double carbon" goal increases the pressure of power structure transformation. This paper sets up two scenarios according to the timing progress of realizing the "double carbon" goal and explores the transformation planning schemes of China's power structure. The conclusions are as follows: (1) Technological progress and policy support will greatly reduce the levelized cost of electricity (LCOE) of onshore wind power, offshore wind power, photovoltaic power, and photothermal power. The rapid rise in carbon price will lead to the LCOE of coal power in 2060 rising to 2 CNY/kWh. (2) The power consumption of the whole society in the baseline scenario can reach 17,000 TWh in 2060. In the acceleration scenario, this value may triple that in 2020 to 21,550 TWh. (3) The acceleration scenario will pay more newly added power costs and coal power stranded scale than the baseline scenario but can achieve carbon peak and negative emissions earlier. (4) More attention should be paid to the flexible level of power system, improve the allocation proportion and requirements of new energy storage on the power supply side, help the steady exit of coal power, and ensure the safety of low-carbon transformation of power structure.

Exploratory research on influential factors of China's sulfur dioxide emission based on symbolic regression.

The amount of China's sulfur dioxide emission remains significantly large in recent years. To further reduce sulfur dioxide emission, the key is to find out the leading factors affecting sulfur dioxide emission and then take measures to control it accordingly. In order to investigate the influential factors of sulfur dioxide emission of various provinces, the data of sulfur dioxide emission of 30 provinces in China from 2001 to 2020 were collected. We established the symbolic regression model to explore the relationship between the GDP (x1), total population (x2), total energy consumption (x3), thermal power installed capacity (x4), and sulfur dioxide emission (dependent variable) for each province. The results show that the amount of China's total sulfur dioxide emission and sulfur dioxide emission in most provinces meet the environmental Kuznets curve (EKC). The influential degree of the factors affecting China's sulfur dioxide emission are GDP, total energy consumption, thermal power installed capacity, and total population. The provinces with the primary factor of GDP have the lowest average total energy consumption and average thermal power installed capacity, and their average sulfur dioxide emissions are also relatively low. The provinces with the primary factor of GDP do not show obvious geographical characteristics, but the provinces with the primary factor of total energy consumption are all distributed in southern China. Based on the research results, some control measures are also put forward.

Examining the Effects of Installed Capacity Mix and Capacity Factor on Aggregate Carbon Intensity for Electricity Generation in China.

Promoting technological advancements and energy transitions in electricity generation are crucial for achieving carbon reduction goals. Some studies have examined the effectiveness of these measures by analysing the driving forces of "aggregate carbon intensity" (ACI) change. However, only a few studies have considered the effect of the installed capacity mix and capacity factor. Moreover, such analysis has never been applied at China's provincial level after 2015. To alleviate this gap, our study applied a temporal and multi-regional spatial IDA-LMDI model to analyse the driving factors of ACI changes and disparities among the provinces of China from 2005 to 2019. The model notably includes the effects of the installed capacity mix, thermal capacity factor, and overall capacity factor. The analysis revealed that the decline in China's ACI was diminished after 2015, while an ACI rebound was identified in five provinces. The changes in the ACI from 2015 to 2019 were mainly driven by the effect of the installed capacity mix rather than by the thermal efficiency and thermal capacity factor. The overall capacity factor was the only factor with a negative impact on the ACI change. We also found that its combined effect with the thermal capacity factor on increasing ACI can offset the effect of the installed capacity mix by reducing the ACI in provinces with significant additions of renewable energy installed capacity. The analysis of the influencing factors on the provincial ACI differences revealed that the share of hydropower installed capacity was significant. Moreover, the thermal efficiency and thermal capacity factor both played key roles in the ACI disparities in northeast, northwest, and central China. Overall, this study paves the way for data-driven measures of China's carbon peak and carbon neutrality goals by improving the capacity factor of wind and solar power, leveraging the critical impact of hydropower, and narrowing the differences in the thermal power sector among provinces.

Forecasting of China's solar PV industry installed capacity and analyzing of employment effect: based on GRA-BiLSTM model.

With the acceleration of China's energy transformation process and the rapid increase of renewable energy market demand, the photovoltaic (PV) industry has created more jobs and effectively alleviated the employment pressure of the labor market under the normalization of the epidemic situation. First, to accurately predict China's solar PV installed capacity, this paper proposes a multi-factor installed capacity prediction model based on bidirectional long short-term memory-grey relation analysis. The results show that, the MAPE value of the GRA-LSTM combined model established in this paper is 5.995, compared with the prediction results of other models, the prediction accuracy of the GRA-BiLSTM model is higher. Second, the BiLSTM model is used to forecast China's installed solar PV capacity from 2020 to 2035. The forecast results show that China's newly installed solar PV capacity will continue to grow and reach 2833GW in 2035. Third, the employment number in China's solar PV industry during 2020-2035 is predicted by the employment factors (EF) method. The results show that the energy transition in China during 2020-2035 will have a positive impact on the future stability and growth of the labor market in the solar PV industry. Overall, an accurate forecast of solar PV installed capacity can provide effective decision support for planning electric power development strategy and formulating employment policy of solar PV industry.

The Regionalization Process for Universal Health Coverage in Brazil (2008-2015).

The objective of this article is to analyze the development of the public and private offer for the universalization of health services, specifically, for the progression of the public network. The time period examined is from 2008 to 2015, when there was considerable economic growth and expansion of private health insurance and an unprecedented historical period with economic growth and reduction of social inequality. Across 5570 municipalities, the multivariate analysis model was used to estimate the level of concentration and the imbalance (heterogeneity) of installed health capacity of the network of health care services. Public spending on investment and human resources showed positive variation in all regions and in almost all population strata. The offer by the Unified Health System (public) of primary health care increased by 8000 new establishments in all regions, especially in previously uncovered cities and cities that had shortages of public health services. Public universalization almost reached its maximum, with about 70% of municipalities. The only setback was the significant reduction of 50% in the number of private establishments in primary health care services. The data suggest a positive movement toward the universalization of health services in Brazil, with the concentration of high-complexity care and the heterogeneity of the installed capacity being points for improvement.

Understanding the gap between formal and informal e-waste recycling facilities in India.

Nowadays, old electrical and electronic gadgets are being replaced constantly by newer versions resulting in huge amounts of waste electronic and electrical products that are collectively termed e-waste. It is estimated that 95% of e-waste recycling in India is done by the informal sector at the cost of their health and the environment. Very little data and no descriptions of recycling processes in the formal sector in India were available in the literature. The objective of this study was to evaluate the status of formal and informal e-waste recycling facilities in India. Seven authorized e-waste handling facilities in West Bengal, Maharashtra, Karnataka and Delhi were visited and most were involved in dismantling work only. In all cases, metals, plastic and glass are recovered from e-waste in compliance with environmental legislation. Challenges faced by the formal sector include lack of awareness among people and very few collection centers throughout the country. Quantification of e-waste generated in India was difficult as imported second-hand electrical and electronic gadgets cannot be separated for electronic waste. There is no mechanism for collecting data regarding e-waste generation in the states or at the Central government level. It is likely that published estimates are based on the indigenous production and import of electrical and electronic goods. The current installed e-waste handling capacity of 11 × 105 tons/year of e-waste in the country is woefully inadequate and needs to be enhanced as the minimum requirement is estimated to be 22 × 105 tons/year of e-waste.

Current Panorama and 2025 Scenario of Photovoltaic Solar Energy in Brazil

Abstract The photovoltaic solar energy in Brazil was boosted by Normative Resolution No. 482/2012 of ANEEL, which regulated the micro and mini generation in the compensation system, and by the specific auctions for photovoltaic plants carried out by the federal government. However, the country still has little representation of the solar energy in its electrical matrix, about 0.13%, with approximately 1% of the installed capacity of electric power generators considering all the sources, both values ​​refer to the year 2017. In the initial moments of a technology, its growth occurs irregularly and because there is little installed capacity, any added value can cause abrupt variations in the percentage from one year to another, that is, its growth still does not follow a sustainable standard, which should be regularized around the year 2025, following the worldwide trend of growth of approximately 30% each year. As a scenario for 2025, the total power of the PVSGC in Brazil will be approximately 75.6 GWp which will represent 98.3 TWh of electric energy produced by this source, considering the estimated electric energy demand for 2025 of 800 TWh, will result in the contribution of 12.3% of the energy by solar photovoltaic source.

Aproximaciones a un estimativo de la capacidad para formar el talento humano en el campo de la salud en un centro médico académico / Approaches to an Estimation of the Capacity to Form Human Talent in the Field of Health in an Academic Health Center

Uno de los mayores retos en la formación del talento humano en salud son los cálculos relacionados con la capacidad instalada de los centros de práctica para lograr la adecuada exposición al ambiente clínico y facilitar el logro de competencias. El artículo presenta un análisis desde la visión de un centro médico académico como es el Hospital Universitario San Ignacio en relación con la Pontificia Universidad Javeriana de Colombia.

One of the greatest challenges in the formation of human talent in health is the calculations related to the installed capacity of the practice centers to achieve adequate exposure to the clínica! environment and facilitare the achievement of competencies. We present an analysis from the visión of an Academtc Health Center such as the San Ignacio University Hospital in relation to the Pontificia Universidad Javeriana, Colombia.