Activity and efficiency trends for the residential sector across countries

The residential sector is a major contributor to climate change, accounting for almost a quarter of global energy consumption and a fifth of CO2 emissions in 2019. Since 2000, residential consumption has grown at a sustained rate of 1%/year, driven by the development of emerging economies, despite stagnation in developed countries. The increasing demand for living space, energy services and comfort levels seems difficult to curb, especially in the developing world on its fair attempt to reduce inequality. To understand these trends, this paper analyses the trajectories of key indicators of activity and efficiency in this sector, for emerging and developed regions, as well as for major consuming nations, mainly China, United States, European Union, Russia, India, Japan and Brazil. Despite data limitations, meaningful cross-country comparisons are presented for fuel mixes, energy services and dwelling types. Heating, ventilation and air conditioning (HVAC) systems account for a third of residential consumption and will grow rapidly as increasing wealth in emerging economies allows for satisfying the thermal comfort demand. Economic development will naturally increase housing size and equipment level and reduce household size, and could close the per capita consumption gap between developing and developed regions. Efficiency improvements could reduce the energy use intensity to around 10 koe/m(2) but will not be enough to curb residential consumption. International cooperation, policy support and funding are essential to accelerate development and efficiency gains in developing countries without compromising environmental targets. In the meantime, politicians should focus on decarbonising the energy mix and promoting energy efficiency, while citizens focus on energy conservation to avoid irreversible environmental damage. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Connecting to smart cities : analyzing energy times series to visualize monthly electricity peak load in residential buildings

Rapidly growing energy consumption rate is considered an alarming threat to economic stability and environmental sustainability. There is an urgent need of proposing novel solutions to mitigate the drastic impact of increased energy demand in urban cities to improve energy efficiency in smart buildings. It is commonly agreed that exploring, analyzing and visualizing energy consumption patterns in residential buildings can help to estimate their energy demands. Moreover, visualizing energy consumption patterns of residential buildings can also help to diagnose if there is any unpredictable increase in energy demand at a certain time period. However, visualizing and inferring energy consumption patterns from typical line graphs, bar charts, scatter plots is obsolete, less informative and do not provide deep and significant insight of the daily domestic demand of energy utilization. Moreover, these methods become less significant when high temporal resolution is required. In this research work, advanced data exploratory and data analytics techniques are applied on energy time series. Data exploration results are presented in the form of heatmap. Heatmap provides a significant insight of energy utilization behavior during different times of the day. Heatmap results are articulated from three analytical perspectives; descriptive analysis, diagnostic analysis and contextual analysis

Fog paradigm for local energy management systems

Cloud Computing infrastructures have been extensively deployed to support energy computation within built environments. This has ranged from predicting potential energy demand for a building (or a group of buildings), undertaking heat profile/energy distribution simulations, to understanding the impact of climate and weather on building operation. Cloud computing usage in these scenarios have benefited from resource elasticity, where the number and types of resources can change based on the complexity of the simulation being considered. While there are numerous advantages of using a cloud based energy management system, there are also significant limitations. For instance, many such systems assume that the data has been pre-staged at a cloud platform prior to simulation, and do not take account of data transfer times from the building to the simulation platform. The need for supporting computation at edge resources, which can be hosted within the building itself or shared within a building complex, has become important over recent year. Additionally, network connectivity between the sensing infrastructure within a built environment and a data centre where analysis is to be carried out can be intermittent or may fail. There is therefore also a need to better understand how computation/analysis can be carried out closer to the data capture site to complement analysis that would be undertaken at the data centre. We describe how the Fog computing paradigm can be used to support some of these requirements, extending the capability of a data centre to support energy simulation within built environments

Optimal Control for Multi-mode Systems with Discrete Costs

This paper studies optimal time-bounded control in multi-mode systems with discrete costs. Multi-mode systems are an important subclass of linear hybrid systems, in which there are no guards on transitions and all invariants are global. Each state has a continuous cost attached to it, which is linear in the sojourn time, while a discrete cost is attached to each transition taken. We show that an optimal control for this model can be computed in NEXPTIME and approximated in PSPACE. We also show that the one-dimensional case is simpler: although the problem is NP-complete (and in LOGSPACE for an infinite time horizon), we develop an FPTAS for finding an approximate solution.Comment: extended version of a FORMATS 2017 pape

Virtual Sensor Based on a Deep Learning Approach for Estimating Efficiency in Chillers

P. 307-319Intensive use of heating, ventilation and air conditioning (HVAC) systems in buildings entails an analysis and monitoring of their e ciency. Cooling systems are key facilities in large buildings, and par- ticularly critical in hospitals, where chilled water production is needed as an auxiliary resource for a large number of devices. A chiller plant is often composed of several HVAC units running at the same time, be- ing impossible to assess the individual cooling production and e ciency, since a sensor is seldom installed due to the high cost. We propose a virtual sensor that provides an estimation of the cooling production, based on a deep learning architecture that features a 2D CNN (Convolu- tional Neural Network) to capture relevant features on two-way matrix arrangements of chiller data involving thermodynamic variables and the refrigeration circuits of the chiller unit. Our approach has been tested on an air-cooled chiller in the chiller plant at a hospital, and compared to other state-of-the-art methods using 10-fold cross-validation. Our re- sults report the lowest errors among the tested methods and include a comparison of the true and estimated cooling production and e ciency for a period of several daysS

Optimization Formulations for the Design of Low Embodied Energy Structures Made from Reused Elements

The building sector is one of the major contributors to material resource consumption, greenhouse gas emission and waste production. Load-bearing systems have a particularly large environmental impact because of their material and energy intensive manufacturing process. This paper aims to address the reduction of building structures environmental impacts through reusing structural elements for multiple service lives. Reuse avoids sourcing raw materials and requires little energy for reprocessing. However, to design a new structure reusing elements available from a stock is a challenging problem of combinatorial nature. This is because the structural system layout is a result of the available elements’ mechanical and geometric properties. In this paper, structural optimization formulations are proposed to design truss systems from available stock elements. Minimization of weight, cut-off waste and embodied energy are the objective functions subject to ultimate and serviceability constraints. Case studies focusing on embodied energy minimization are presented for: (1) three roof systems with predefined geometry and topology; (2) a bridge structure whose topology is optimized using the ground structure approach; (3) a geometry optimization to better match the optimal topology from 2 and available stock element lengths. In order to benchmark the energy savings through reuse, the optimal layouts obtained with the proposed methods are compared to weight-optimized solutions made of new material. For these case studies, the methods proposed in this work enable reusing stock elements to design structures embodying up to 71% less energy and hence having a significantly lower environmental impact with respect to structures made of new material

Species concepts in Calonectria (Cylindrocladium)

Species of Calonectria and their Cylindrocladium anamorphs are important plant pathogens worldwide. At present 52 Cylindrocladium spp. and 37 Calonectria spp. are recognised based on sexual compatibility, morphology and phylogenetic inference. The polyphasic approach of integrating Biological, Morphological and Phylogenetic Species Concepts has revolutionised the taxonomy of fungi. This review aims to present an overview of published research on the genera Calonectria and Cylindrocladium as they pertain to their taxonomic history. The nomenclature as well as future research necessary for this group of fungi are also briefly discussed

Estimating a threshold price for CO2 emissions of buildings to improve their energy performance level. Case study of a new Spanish home

Energy consumption in homes produces CO2. In many countries, building regulations are being set to enable energy efficiency performance levels to be issued. In Spain, there is a regulated procedure to certify the energy performance of buildings according to their CO2 emissions. Consequently, some software tools have been design to simulate buildings and to obtain their energy consumption and CO2 emissions. In this paper the investment, maintenance and energy consumption costs are calculated for different energy performance levels and for various climatic zones, in a single-family home. According to the results, more energy efficient buildings imply higher construction and maintenance costs, which are not compensated by lower energy costs. Therefore, under current conditions, economic criteria do not support the improvement of the energy efficiency of a dwelling. 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Fungal Planet description sheets: 1042–1111

Novel species of fungi described in this study include those from various countries as follows: Antarctica, Cladosporium arenosum from marine sediment sand. Argentina, Kosmimatamyces alatophylus (incl. Kosmimatamyces gen. nov.) from soil. Australia, Aspergillus banksianus, Aspergillus kumbius, Aspergillus luteorubrus, Aspergillus malvicolor and Aspergillus nanangensis from soil, Erysiphe medicaginis from leaves of Medicago polymorpha, Hymenotorrendiella communis on leaf litter of Eucalyptus bicostata, Lactifluus albopicri and Lactifluus austropiperatus on soil, Macalpinomyces collinsiae on Eriachne benthamii, Marasmius vagus on soil, Microdochium dawsoniorum from leaves of Sporobolus natalensis, Neopestalotiopsis nebuloides from leaves of Sporobolus elongatus, Pestalotiopsis etonensis from leaves of Sporobolus jacquemontii, Phytophthora personensis from soil associated with dying Grevillea mccutcheonii. Brazil, Aspergillus oxumiae from soil, Calvatia baixaverdensis on soil, Geastrum calycicoriaceum on leaf litter, Greeneria kielmeyerae on leaf spots of Kielmeyera coriacea. Chile, Phytophthora aysenensis on collar rot and stem of Aristotelia chilensis. Croatia, Mollisia gibbospora on fallen branch of Fagus sylvatica. Czech Republic, Neosetophoma hnaniceana from Buxus sempervirens. Ecuador, Exophiala frigidotolerans from soil. Estonia, Elaphomyces bucholtzii in soil. France, Venturia paralias from leaves of Euphorbia paralias. India, Cortinarius balteatoindicus and Cortinarius ulkhagarhiensis on leaf litter. Indonesia, Hymenotorrendiella indonesiana on Eucalyptus urophylla leaf litter. Italy, Penicillium taurinense from indoor chestnut mill. Malaysia, Hemileucoglossum kelabitense on soil, Satchmopsis pini on dead needles of Pinus tecunumanii. Poland, Lecanicillium praecognitum on insects' frass. Portugal, Neodevriesia aestuarina from saline water. Republic of Korea, Gongronella namwonensis from freshwater. Russia, Candida pellucida from Exomias pellucidus, Heterocephalacria septentrionalis as endophyte from Cladonia rangiferina, Vishniacozyma phoenicis from dates fruit, Volvariella paludosa from swamp. Slovenia, Mallocybe crassivelata on soil. South Africa, Beltraniella podocarpi, Hamatocanthoscypha podocarpi, Coleophoma podocarpi and Nothoseiridium podocarpi (incl. Nothoseiridium gen. nov.)from leaves of Podocarpus latifolius, Gyrothrix encephalarti from leaves of Encephalartos sp., Paraphyton cutaneum from skin of human patient, Phacidiella alsophilae from leaves of Alsophila capensis, and Satchmopsis metrosideri on leaf litter of Metrosideros excelsa. Spain, Cladophialophora cabanerensis from soil, Cortinarius paezii on soil, Cylindrium magnoliae from leaves of Magnolia grandiflora, Trichophoma cylindrospora (incl. Trichophoma gen. nov.) from plant debris, Tuber alcaracense in calcareus soil, Tuber buendiae in calcareus soil. Thailand, Annulohypoxylon spougei on corticated wood, Poaceascoma filiforme from leaves of unknown Poaceae. UK, Dendrostoma luteum on branch lesions of Castanea sativa, Ypsilina buttingtonensis from heartwood of Quercus sp. Ukraine, Myrmecridium phragmiticola from leaves of Phragmites australis. USA, Absidia pararepens from air, Juncomyces californiensis (incl. Juncomyces gen. nov.) from leaves of Juncus effusus, Montagnula cylindrospora from a human skin sample, Muriphila oklahomaensis (incl. Muriphila gen. nov.)on outside wall of alcohol distillery, Neofabraea eucalyptorum from leaves of Eucalyptus macrandra, Diabolocovidia claustri (incl. Diabolocovidia gen. nov.)from leaves of Serenoa repens, Paecilomyces penicilliformis from air, Pseudopezicula betulae from leaves of leaf spots of Populus tremuloides. Vietnam, Diaporthe durionigena on branches of Durio zibethinus and Roridomyces pseudoirritans on rotten wood. Morphological and culture characteristics are supported by DNA barcodes