Hourly marginal electricity mixes and their relevance for assessing the environmental performance of installations with variable load or power.

The ongoing energy transition is causing rapid changes in the electricity system and, in consequence, the environmental impacts associated with electricity generation. In parallel, the daily variability of generation increases with higher shares of renewable energies. This affects the potential environmental impacts or benefits of devices with variable load or power, such as electric vehicles, storage systems or photovoltaic home systems. However, recent environmental assessments of the actual benefit of such systems are scarce, with existing assessments majorly using average grid mixes that are frequently outdated and disregard the dynamic nature of renewable generation. This article provides detailed hourly average and marginal electricity mixes for each month of the year, determined for Spain as an illustrative country with a diversified (renewable) power generation portfolio that experienced a rapid change in the last years. These are combined with specific life-cycle emission factors for each generation technology. Main drivers for the impacts of the marginal mix turn out to be natural gas plants and imports, but also pumped hydropower due to its comparably low storage efficiency. Applied to a hypothetical photovoltaic rooftop installation, the differences between environmental assessments on hourly and on annual basis are found to be surprisingly low when assuming that the generated electricity replaces the average grid mix, but substantial when considering the marginal generation mix (i.e., the generation technologies that respond to a change in demand at a given time). This highlights the importance of considering the dynamics of the electricity system and the corresponding marginal electricity mixes when optimizing flexible load or generation technologies under environmental aspects.

Cancer de endometrio en grandes obesas: tratamiento quirurgico / Endometrial cancer in the severely obese: surgical management

Objetivo valorar la morbilidad de los diferentes abordajes quirúrgicos en mujeres con cáncer de endometrio e índice de masa corporal (IMC) superior o igual a 35kg/m2.Material y métodos se ha realizado un estudio descriptivo retrospectivo de 36 mujeres con cáncer de endometrio e IMC superior o igual a 35 kg/m2 tratadas quirúrgicamente en este centro desde 1996 hasta enero de 2007. Se han definido 2 grupos según el abordaje quirúrgico: laparoscopia (LPC) y laparotomía (LPM). Se han analizado diferentes factores como edad, IMC, cirugía previa, factores de riesgo, tipo de cirugía, duración, complicaciones, estancia media, tasa de conversión, transfusión, estadio según la Federación Internacional de Ginecología y Obstetricia (FIGO), tipo histológico y supervivencia. Resultados la edad media fue de 64,40±1,28 años (rango de 50 a 83) y el IMC fue de 39,94±0,73kg/m2 (rango de 35,1 a 55,3), sin que hubiera diferencias significativas. El 8,3% (3 mujeres) tenía algún tipo de cirugía abdominal previa; en el 69,4% (25 mujeres) había factores de riesgo de afección endometrial y el 8,3% (3 mujeres) había recibido tratamiento con tamoxifeno. El abordaje quirúrgico inicial fue LPC en 16 mujeres (44,4%) y LPM en 20 mujeres (55,5%). La realización de linfadenectomía fue posible en el 55% con LPM y en el 93,8% con LPC. La tasa de conversión a LPM fue necesaria en 3 mujeres (18,8%) debido a problemas de tratamiento anestésico. La estancia media y las cifras de hemoglobina media fueron mejores para la serie en la que se utilizó LPC (p<0,001). No hubo diferencias significativas en los ganglios extraídos. La tasa de supervivencia fue similar (p=0,29). Conclusiones el IMC elevado no puede considerarse una contraindicación para el abordaje laparoscópico. El tratamiento y la estadificación quirúrgica laparóscópica disminuye la morbilidad y la estancia mediab (AU)

Objective: To evaluate morbidity in distinct surgical approaches for the treatment of endometrial cancer in patients with a body mass index (BMI)¡Ý35(kg/m2).Material and methods: We performed a descriptive, retrospective study of 36 consecutive patients with a BMI >35 and endometrium cancer who underwent surgery from January 1996 to January 2007. The patients were classified into two groups according to whether the laparoscopic (LPS) or laparotomic (LPM) approach was used. The following factors were analyzed: age, BMI, previous surgery, risk factors, type of surgery, operating time, complications, mean length of hospital stay, conversion rate, transfusion rate, FIGO stage, histological type, and survival.Results: The mean age was 64.40¡À1.28 (50¨C83) years and the mean BMI was 39.94¡À0.73(35.1¨C55.3)kg/m2. A total of 8.3% (three patients) had previous abdominal surgery, 69.4% (25 patients) had endometrial risk factors and 8.3% (three patients) had received tamoxifen treatment. The initial surgical access was LPS in 16 patients (44.4%) and was LPM in the remaining 20 patients (55.5%). Lymphadenectomy was feasible in 55% of LPM and in 93.8% of LPS. Conversion to laparotomy was required in three patients (18.8%) due to anesthetic problems. The length of hospital stay and hemoglobin balance were more favorable in LPS (p<0.001). No differences were found in nodal extraction. The survival rate was similar with the two approaches (p=0.29).Conclusions: High BMI should not be considered as a contraindication for LPS. Successful laparoscopic management and staging reduces hospital stay and morbidity (AU)

Método de ajuste de riesgos para fallecimientos y consumo de estancias en un hospital de crónicos + software ad hoc para aplicar el modelo / Methods for adjusting the risk of deaths and length of hospital stays in a hospital for the chronically III. Ad hoc software for applying the model

Empleando una base de datos de 1.783 pacientes se realiza un modelo de ajustes de riesgos para fallecimientos y consumo de estancias. Las técnicas empleadas son la regresión logística y el análisis de supervivencia. Tras la validación del modelo se realizó un programa informático que permite la predicción de la estancia, tiempo de supervivencia o grado de efectividad del equipo sanitario (AU)

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