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Abstract During successive industrial revolutions, the objective has not only been for industry to improve and satisfy its direct needs, it has also been to improve society’s standard of living and make life easier for the consumer. Therefore, economic growth should always go hand in hand with each industrial revolution. The medical industry, energy conservation and, in particular, production technologies will be transformed through new value chain models. Globalization, urbanization, demographic change and energy transformation are the transforming forces estimating the technological impetus for a better identification of solutions for a world on the move. In recent years, successive revolutions have made remarkable contributions to a person’s quality of life, safety, industrial economy, comfort and health. This work aims at improving the energy consumption of buildings. To achieve this goal, we have created a Digital Twin that accurately reflects the behavior and characteristics of a future or existing building. To reproduce a copy of the future or existing building, we chose to use the Autodesk REVIT solution to meet several constraints. These have a significant influence on the energy behavior of the building.

Heating and cooling using aquifer thermal energy storage (ATES) has hardly been applied outside the Netherlands, even though it could make a valuable contribution to the energy transition. The Climate-KIC project "Europe-wide Use of Energy from aquifers" - E-USE(aq) - aimed to pave the way for Europe-wide application of ATES, through the realization and monitoring of six ATES pilot plants across five different EU countries. In a preceding paper, based on preliminary results of E-USE(aq), conclusions were already drawn, demonstrating how the barriers for this form of shallow geothermal energy can be overcome, and sometimes even leveraged as opportunities. Based on final pilot project results, key economic and environmental outcomes are now presented. This paper starts with the analysis of specific technological barriers: unfamiliarity with the subsurface, presumed limited compatibility with existing energy provision systems (especially district heating), energy imbalances and groundwater contamination. The paper then shows how these barriers have been tackled, using improved site investigation and monitoring technologies to map heterogeneous subsoils. In this way ATES can cost-efficiently be included in smart grids and combined with other sources of renewable (especially solar) energy, while at the same time achieving groundwater remediation. A comparative assessment of economic and environmental impacts of the pilots is included, to demonstrate the sustainability of ATES system with different renewables and renewable-based technologies. The paper concludes with an assessment of the market application potential of ATES, including in areas with water scarcity, and a review of climate beneficial impact.

EU Integration raises new requirements to energy sector, including municipal energy sector and improvement of local planning. Important role is assigned to development of energy infrastructure, use of renewable energy sources and energy efficiency. In order to use financial support from EU Structural funds for regional energy development, qualified applications will have to be developed in adequacy with the requirements for the use and control of EU Structural funds. The latter should be developed in the context of regional development programs (including energy sector development), which should be based on info systems. The Laboratory of Regional Energy Development at LEI is developing integrated info system "TAUSA" for this purpose. This info system is formed as server of data bases with respective bases and additional analysis modules. Information for the consumers of info systems could be available at Internet website. Besides indicators on district heating, "TAUSA" will accumulate data on distribution and end use of renewable energy sources at regional level, which permits to assess main macroeconomic indicators in the development of this economic activity. Matrix model for economic activity of preparing local fuel will enable to evaluate inter-branch links for district heating sector and the role of local fuel production in Gross Domestic Product (GDP) creating process. The macroeconomic model under development will help to assess economic benefit from the use of renewable energy sources in the region, including the facts that it improves employment, increases the flow of taxes to municipal budget, paid by the companies employed in this sector, give new business development opportunities.

Abstract Using a complicated stepped analysis, Ewing and Rong study the impact of sprawl on household energy use. They argue that dispersed land use brings about larger houses and more detached units, which consume more energy than the smaller houses and attached units typical of more compact communities. This comment suggests that their conclusions are intuitive and obvious, but that their complex methodology linking three unrelated data sets renders their quantitative conclusions suspect. Further, a simple engineering analysis can show more meaningful results, sprawl is more likely to affect energy use through increased vehicle miles traveled than house size or type, and household energy use can be mitigated by increasing the efficiency of the building envelope, heating/cooling system, appliances, and lighting. Still, combining the effects of compact urban development with the effects of energy‐efficient vehicles and housing unit design can be a real winner in our quest for more energy‐efficient communi...

To help policymakers form a judgment on inflation risks and the required monetary policy stance the OECD has developed an analytical framework based on a set of 'eclectic' Phillips curves estimated for the two largest OECD economies, the United States and the euro area, which is presented in this paper. This framework is used in the preparation of the Economic Outlook to explain recent developments in core inflation, excluding food and energy, based on developments in measures of economic slack (the output gap), spill-over effects from energy prices onto core inflation and lagged responses to past inflation via expectations formation. The fact that the knock-on effects from energy shocks onto core inflation appear small in comparison with the 1970s can be explained by the secular fall in energy intensity, a low and stable rate of 'mean inflation' -- to which observed inflation reverts after a shock has worked its way through -- and persistent slack in the aftermath of the bursting of the dotcom bubble.

The management of municipal solid waste (MSW) is a complex and expensive task. This is especially the case in developing countries, where waste generation rates are continuously increasing and where current MSW management strategies are focused on inadequate practices, such as landfilling and incineration, which result in numerous health and environmental problems. The anaerobic digestion (AD) of MSW has been implemented worldwide as a solution to decrease the amount of waste ending up in landfills. This process allows for the recovery of energy from the organic fraction of MSW (OFMSW) in the form of biogas, which is largely composed of methane. Therefore, the goal of the present study was to evaluate the biochemical methane potential (BMP) of the OFMSW generated within different socioeconomic strata of the Metropolitan Area of Guadalajara (MAG), Mexico. From a microscale perspective, the microbial communities within the experimental AD system were analyzed using high-throughput sequencing of the 16S rRNA gene to assess the relationship between these communities and the biogas composition. This microbial identification revealed a typical AD composition consisting of the following six phyla: Actinobacteria, Bacteroidetes, Chloroflexi, Euryarchaeota, Firmicutes, and Proteobacteria. Furthermore, through the identification of Methanobacterium and Methanosaeta, two methanogenesis pathways (hydrogenotrophic and acetoclastic) were pinpointed. From a macroscale perspective, a multi-stage Gompertz kinetic model was used to describe cumulative biogas production. This model considered the complex nature of the OFMSW substrate in order to estimate the potential level of biogas production in the MAG using a weighted average that was based on the size of the population in each socioeconomic stratum evaluated (732.8 mL⋅g−1 VS). This novel contribution to the literature provides an estimation of the potential economic, energetic, and environmental benefits of treating the OFMSW produced in the MAG through AD. Through this approach, an estimated 8.5 MWh·year−1 of electrical power could be produced, translating into 1.13 million USD of yearly revenue and resulting in reduced GHG emissions (10,519 tonne CO2eq⋅year−1).

Energy demand modelling has been widely applied in various contexts, including power plant generation, building energy simulation and demand-side management. However, it is still an ongoing research topic in terms of the choice of modelling method, feature engineering for data-driven methods, the application contexts and the type of data used. In the residential sector, survey-based and meter-based approaches are categorised according to the type of input data used, i.e. the activity records from the time use survey and energy consumption from meters respectively. These two paradigms are not necessarily easy to combine, which warrants the questions of when one may be preferred over the other and whether they need to be combined despite the significant data requirements. Other details also have a huge impact on the data structure and performance of the energy demand model, including the choice of influential factors, the historical time window of factors selected, the split between training and test data, and the choice of machine learning (ML) algorithm. There is a lack of comparative research to guide researchers and practitioners in developing energy demand modelling capability, specifically as it pertains to these issues. This study analyses three groups of test scenarios in a multi-household residential context based in the UK. Six ML algorithms (LightGBM, Random forest, ANN, SVM, KNN and LSTM), with eight sets of various influential features, at four different historical time window widths and two train-test splits were compared. An appropriate methodology was designed to capture the temporal impact of activities on energy demand and represent the overlap and interaction of activities. The results show that the combination of meter-based and survey-based energy demand models performs better in terms of modelling accuracy and robustness against sudden load variation. Particularly, integrating energy tariffs, household and individual attributes, appliance usage and general activity features can improve the energy demand model. Among the ML algorithms, LightGBM and ANN perform better than other algorithms while LSTM and SVM may not be suitable in this multi-household short monitoring context.

AbstractClimate change and environmental problems will force or induce millions of people to migrate. In this article, I describe environmental migration and articulate some of the ethical issues. To begin, I give an account of these migrants that overcomes misleading dichotomies. Then, I focus attention on two important ethical issues: justice and responsibility. Although we are all at risk of becoming environmental migrants, we are not equally at risk. Our risk depends on our temporal position, geographical location, social position, and the kind of society in which we live. We all contribute to environmental problems, but we do not contribute equally. About 11% of the world population is responsible for 50% of carbon emissions. These inequalities raise issues of justice because many of the people who are at high risk have contributed little to the problems. Since the issues of justice are relatively clear and compelling, I focus more attention on issues of responsibility. I use Iris Marion Young’s account of responsibility for structural injustice to address four key questions about moral responsibility and environmental migration.