The international maritime traffic of people and goods has often contributed to the spread of pathogens affecting public health. The Maritime Declaration of Health (MDH), according to the International Health Regulations (IHR) (2005), is a document containing data related to the state of health on board a ship during passage and on arrival at port. It is a useful tool for early detection of public health risks. The main objective of our study was to evaluate compliance with the model provided in the IHR, focusing on the format and degree of completion of MDH forms received at Spanish ports. We reviewed the content of 802 MDH forms submitted to nine Spanish ports between October 2014 and March 2015. Study results show that 22% of MDH forms presented did not comply with the recommended model and 39% were incomplete. The proportion of cargo ships with correct and complete MDH forms was lower than passenger ships; thus, the nine health questions were answered less frequently by cargo ships than passenger ships (63% vs 90%, p value < 0.001). The appropriate demand and usage of MDH forms by competent authorities should improve the quality of the document as a tool and improve risk assessment.
Renewable energy communities (REC) are a valuable mean of combating climate change: they increase participant self-sufficiency, avert blackouts, minimize costs (and/or CO2 emissions), and improves the resilience of the community. The planning phase of an energy community requires an analysis of its performance and efficiency. Concretely, the calculation of optimized energy flows of each participant of the REC at each timepoint (and hence, the energy costs and/or CO2 emissions) is the objective of the analysis. The quality and accuracy of the analysis depend directly on the period of the analysis from one side, and on the modelling data from another. The most accepted period of the analysis of RECs (as a special case of micro-grids) comprises a whole year, to avoid seasonal effects. The necessary data for the analysis are energy consumption and production, trade prices and used technologies. Nowadays, most grid operators provide the values of energy flows with at least a 15-minute time resolution. It means each variable involved in the analysis will be represented as an array with 35 040 elements. Increasing the number of participants, technologies, and other involved variables, increases the amount of data, and consequently the complexity of the analysis. The main contribution of this paper is the comparison of different data reduction methods to handle this information and the validation of their results.
Energy Communities (EC) are an instrument to improve the efficiency and autarky of Smart Grids by increasing the local consume of the energy locally produced. Energetic (energy flows, CO2 emissions) and economic (operative costs, acquisition and maintenance of technologies) aspects of all components of the EC must be evaluated to quantify the participation of the EC to achieve the proposed goal. Effective analysis of EC must account for numerous complexities and uncertainties, requiring advanced computational tools. The main contribution of this paper is the introduction of a software package to analyze the viability of ECs focused on the particularities imposed by the new Austrian law for renewable energies, which optimizes the energy flows between all participants. The results of the test case show more than a 14.2% reduction of global cost. At the same time, all participants achieve better results operating inside of the EC than alone. The range of cost reductions varies between 2.75% and 51%. The spread of these reductions opens a question about a fair and optimal way to set trade prices inside of the EC for future works.
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