The Human Factor in Transmission Network Expansion Planning: The Grid That a Sustainable Energy System Needs

The decarbonization of the energy sector puts additional pressure on the transmission network. The main cause for this is that renewable sources are often more abundant in geographical areas far away from the main demand centers, so new transmission lines are required to connect the new renewable energy capacity. In addition, by connecting different geographical zones, the transmission network could smooth the intermittency and the variability of renewable energy production. Thus, the changing energy landscape leads to a need to reinforce the transmission network through the Network Transmission Expansion Planning. Ideally, all the idiosyncrasies of the electricity system are considered in the operation and expansion planning process. However, several critical dimensions of the planning process are routinely ignored since they may introduce parameters that are difficult to quantify and complexity that state-of-the-art planning methods cannot handle. This paper identifies the most relevant elements related to the human factor, which have been grouped around the main topics: the human behind the technical, the human at the institutional level, and the human at the individual level. This paper also provides an additional formulation that can be used to upgrade existing models to include the human element and discusses the implications of these upgrades. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This research has been carried out thanks to the Spanish Ministry of Economy and Competitiveness MINECO through BC3 María de Maeztu excellence accreditation MDM-2017-0714 Maria de Maeztu Grant, and through the funding of openENTRANCE project (Open ENergy TRansition ANalyses for a low-carbon Economy) that belongs to LC-SC3-CC-2-2018—Modelling in support to the transition to a Low-Carbon Energy System in Europe

Levels, sources and seasonality of coarse particles (PM10-PM2.5) in three European capitals e implications for particulate pollution control

Coarse particles of aerodynamic diameter between 2.5 and 10 mm (PMc) are produced by a range of natural (windblown dust and sea sprays) and anthropogenic processes (non-exhaust vehicle emissions, industrial, agriculture, construction and quarrying activities). Although current ambient air quality regulations focus on PM2.5 and PM10, coarse particles are of interest from a public health point of view as they have been associated with certain mortality and morbidity outcomes. In this paper, an analysis of coarse particle levels in three European capitals (London, Madrid and Athens) is presented and discussed. For all three cities we analysed data from both traffic and urban background monitoring sites. The results showed that the levels of coarse particles present significant seasonal, weekly and daily variability. Their wind driven and non-wind driven resuspension as well as their roadside increment due to traffic were estimated. Both the local meteorological conditions and the air mass history indicating long-range atmospheric transport of particles of natural origin are significant parameters that influence the levels of coarse particles in the three cities especially during episodic events

Exploiting graphlet decomposition to explain the structure of complex networks: the GHuST framework

The characterization of topology is crucial in understanding network evolution and behavior. This paper presents an innovative approach, the GHuST framework to describe complex-network topology from graphlet decomposition. This new framework exploits the local information provided by graphlets to give a global explanation of network topology. The GHuST framework is comprised of 12 metrics that analyze how 2- and 3-node graphlets shape the structure of networks. The main strengths of the GHuST framework are enhanced topological description, size independence, and computational simplicity. It allows for straight comparison among different networks disregarding their size. It also reduces the complexity of graphlet counting, since it does not use 4- and 5-node graphlets. The application of the novel framework to a large set of networks shows that it can classify networks of distinct nature based on their topological properties. To ease network classification and enhance the graphical representation of them, we reduce the 12 dimensions to their main principal components. Furthermore, the 12 dimensions are easily interpretable. This enables the connection between complex-network analyses and diverse real applications

Estimativas de perdas de solo para sub-bacias hidrográficas do Estado do Rio de Janeiro.

O Estado do Rio de Janeiro apresenta uma diversidade de ambientes, baixadas litorâneas, Serras, Mar de Morros, e grandes vales, onde é possível encontrar usos da terra que variam da agricultura em larga escala (cana de açúcar), pecuária extensiva, pequenos pólos agrícolas, até grandes fragmentos conservados da mata atlântica. Para obter um diagnóstico da vuInerabilidade do ambiente que considere as características ambientais do terreno associadas a outros fatores ambientais e ao uso da terra, escolheu-se a Equação Universal de Perda de Solo. Este é um modelo usual para estimativa de erosão laminar, indicadora de vulnerabilidade do terreno, e que foi aplicada para todo o Estado do Rio de Janeiro. Para um melhor enfoque territorial relacionado à conservação ambiental as estimativas foram sumarizadas por sub-bacias hidrográficas. Verificou-se que 64% das terras apresentam perdas muito baixas, com valores inferiores a 10 ton/ha.ano; e aproximadamente 2% apresentam perdas extremamente elevadas, acima de 200 ton/ha.ano, e cerca de 21% das sub-bacias hidrográficas apresentam perdas médias muito baixas, com valores menores que 10 ton/ha.ano, e menos de 1% apresentam perdas muito altas, entre 100 e 131 ton/ha.ano

Estimativas de perdas de solo para microbacias hidrográficas do Estado do Rio de Janeiro.

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Vulnerabilidade ambiental em sub-bacias hidrográficas do Estado do Rio de Janeiro por meio de integração temática da perda do solo (USLE), variáveis morfométricas e o uso/cobertura da terra.

Watersheds are paths of environment management for hydrologic monitoring, soil conservation and land use restriction, because the product water in quality and quantity. The watersheds ofthe Rio Janeiro State was parameters with objective of indicate the agree vulnerability by multi-criteria evaluation (MCE). The result indicate that watersheds more vulnerability occur in northwest State. As one with more agree ofthe vulnerability occur at margin Paraiba do Sul, indicate ofthe areas for environment recuperation programs

Integrated geoinformation model for environmental planning in Rio de Janeiro, RJ, Brazil.

The design of an integrated geoinformation model was established to the environmental planning context, which is conduced by the Rio de Janeiro Municipal Secretariat for the Environment. Modelling boundaries were set from a semi-detailed soil survey executed by Embrapa Solos. This particular study aimed to evaluate the consistence of the GIS application as integrated part of the planning process. Therefore, the main objective was to identify weakness of existing procedures where the original data set could be revised by the proposed model. In addition, it was meant to explore object-oriented methodology applied to evaluate results from integrated spatial analysis according to existing products from survey methods. The methodological approach applies terrain object modelling standards in Molenaar (1996) and UML language for analysis and design (Rational, 1997). Yet, an integrated GIS environment supported by object-oriented technology (ILWIS 2.1 ®) was used to implement the conceptual model processes. Results are an updated semi-detailed soil map, at 1:75,000 scale, and derived information as land suitability for horticulture and reforestation, land vulnerability, and land environmental quality. Further spatial analysis were defined to support reclassification, aggregation, generalisation, and overlay processes for land suitability and land vulnerability interpretations. DTM analysis helped to review where the county area is classified either as highlands, due to erosion susceptibility, or as low lands, due to drainage conditions. Image analysis has considered supervised classification to extract update land cover information that helps to evaluate environmental quality of the lands

Aspectos climáticos do noroeste fluminense, RJ.

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