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• Causal relationship among waste generation, R&D intensity, and economic growth. • Panel vector error correction model is employed to study the causal relationship. • Regions of old and new EU countries are compared. • Bidirectional causality exists between waste generation and economic growth. • Bidirectional link among waste generation, heating energy, and R&D intensity. The relationship between economic growth and waste generation is a major global concern. Previous studies provided no conclusive evidence as to the causality between these two concepts, which can be attributed to at least two problems. First, R&D intensity is increasingly recognized as being an important determinant of environmental quality. Second, the regional level is considered to be important for the implementation of waste management policies, as regions and municipalities, among others, are responsible for separate collection systems and for establishing and managing treatment facilities. Previous studies failed to reflect the heterogeneity of the regions, which may lead to biased results. To address these problems, the panel vector error correction model was employed to examine the Granger causality in EU regions. The results provide empirical support for the existence of short- and long-run bidirectional causality between waste generation and economic growth in EU regions. A bidirectional link among waste generation, heating energy, and R&D intensity was also observed. The policy implication is that traditional economic development policies are not enough to reduce waste generation in EU regions. Economic tools, such as charges and incentives, and eco-innovation policies should be introduced to promote the region's shift towards a circular economy model. [ABSTRACT FROM AUTHOR]

• In the past 15 years, household energy costs in Canada have risen at a much faster pace than real income, particularly in low-income households. Within-the-home energy poverty rates, as determined by various metrics, have followed suit. • Low-income households across Canada consume the least amount of energy per year and per unit heated area. They also tend to live in smaller dwellings which require more energy per unit floor area. • Low-income households tend to live in older, rented dwellings which are retrofitted less often than owner-occupied dwellings and are the least exposed to energy-saving technology. • Other developed countries, particularly in Europe, have studied energy poverty and affordability across their populations and have used their results to analyse cases of freeloading and split-incentive and to optimize government subsidy programs. • Energy efficiency rating systems for dwellings have been designed in some countries to help manage subsidies and determine patterns contributing to energy inefficiency. • Energy rate increases across developed nations are part of a global trend which could be alleviated through sponsored retrofitting and income transfers. • Several solutions can assist in reversing the increasing rates of energy poverty in Canada, including reinstating non-profit housing programs, providing on-site renewable energy generation and defining energy as a basic need. Energy in households is explored in the context of households in the Canadian built environment, in which considerable amounts of energy must be consumed as heating energy over the winter months, particularly in older or low-income dwellings. Recent Canadian poverty trends are explored and are analyzed in conjunction to the country's rising energy rates and effects on affordability. Past and current measures aimed at improving the existing housing stock in Canada and in other countries are explored, including retrofitting, behavioural change and renewable energy generation. The issue of thermal comfort in social housing programs is discussed, with examples from both developed and developing countries. Potential remedies to energy poverty situations in Canada are presented by discussing similar programs from other countries, including classification techniques and data analysis measures. Results from other countries and potential benefits to Canada are demonstrated, and the Quebec model of socially mandated energy is highlighted as an example which can be adopted by other provinces. [ABSTRACT FROM AUTHOR]

An assessment of the potential economic, environmental, and health benefits of substituting firewood with charcoal briquettes as heating fuel in cities located in the Forestry Belt in Chile is conducted. Experimental results obtained by the authors allowed to determine production yields and energy packing of charcoal briquettes obtained from Eucalyptus globulus and radiata pine residues. Given the large annual harvested surface of these two species, large quantities of residual biomass are left available at very low cost. The technology proposed to produce these charcoal briquettes is based in the process of pyrolysis in retort kilns. These give better results than traditional methods used until now in Chile to produce charcoal, but a higher technology level is required. Retort kilns rendered yield ratios of 0.247 and 0.286 [kg of charcoal/kg feedstock] for eucalyptus and radiata pine respectively. Charcoal briquettes gave a LHV (lower heating value) of 7836 kcal/kg and 7975 kcal/kg for eucalyptus and pine forest residues feedstock respectively, about twice that of dry firewood. Our economics analysis renders a cost of 0.1059 USD/kWh, which is competitive against firewood and other fuel options. In terms of health and environmental impact it is estimated that using charcoal briquettes from eucalyptus and pine harvested residues would reduce PM2.5 (particle matter <2.5 μg) air pollution, the most critical source of contamination in this geographic region, around 7.96 %, saving annually an estimated 9376 tons from being delivered into the atmosphere. An estimated 8.3 % of the annual firewood consumption (966,656 m3/year of which 2/3 is native) would be saved, so that 2041 ha of native deforestation would be avoided. • Recycling of radiata pine end eucalyptus forest residues • Replacement of firewood with charcoal briquettes as a heating fuel • Air pollution reduction in urban sites in the Forestry Belt in Chile [ABSTRACT FROM AUTHOR]

Highlights • One-parameter-at-a-time (OAT) approach was used for the sensitivity analysis. • Default values of the CSHHEAT model are reasonably acceptable. • Heating demand is highly sensitive to the thermal properties of cover, thermal blanket, and greenhouse perimeter. • Small change of indoor temperature and RH have significant effects on the heating demand for the coldest months. Abstract The sensitivity of a heating simulation model (CSGHEAT) was performed for estimation of the time-dependent heating requirement in a Chinese-style solar greenhouse in cold region. Results showed that the constant value of air thermal conductance is the main default parameter of the model that significantly affected the model output. The results also indicated the heating requirement is highly sensitive to the greenhouse design parameters including the thermal properties of cover, thermal blanket, and greenhouse perimeter. The thermal blanket is the most important design parameter for the Chinese-style solar greenhouse, and the heating requirement could be increased between 32 and 41% during the coldest three months (January, February, and December) for changing the thermal conductivity from 0.01 to 0.05 W/m K. Increasing daytime indoor set-point temperature from 19 to 23 °C would increase the heating demand between 13 and 20%, whereas the heating demand could be increased by 9–18% for increasing the night-time temperature from 16 to 20 °C. Results also indicate the heating demand could be reduced up to 20% during the coldest period for increasing the indoor relative humidity from 70 to 90%. The results from this study could be useful for understanding the energy saving management of greenhouse operations and for designing the energy-efficient Chinese-style solar greenhouses in cold regions. [ABSTRACT FROM AUTHOR]

The domestic sector uses the majority of the energy consumed in Palestine. The Palestinian Central Bureau of statistics (PCBS) performs periodic statistics regarding the average energy consumption of the households, but there is no up to date breakdown of the energy consumption in the residential sector. The Palestinian energy sector main challenges are the high fuel prices, lack of sustainable consumption and energy insecurity. Developing energy policies and studying the potential of shifting towards more independent and sustainable energy sources need a clear understanding of the current energy consumption. A survey was used to collect relevant quantitative and qualitative data. The total number of households in Hebron who responded to the survey was 322 households. The survey covered physical characteristics of the dwellings, socioeconomic features of the households in addition to the pattern of heating the spaces, quantity and type of fuel used for heating. On average the households heated only 9.2% of the total area of their houses during the winter days. The survey revealed that households spend 3.5%–21.6% of their monthly income on space heating during winter. The main contribution to knowledge of this paper is a regression model to estimate energy consumption based on the data collected from the survey. The regression model is developed with an R 2 adjusted 0.606 indicating 60.6% accuracy of the predicted energy consumed for heating. The regression model depends on 14 parameters which include the type of settlement, physical characteristics of the dwelling that are housing typology, level of thermal insulation of the walls, the main building materials and the housing age. It also depends on socioeconomic parameters which are the family monthly income and the occupancy period. Moreover, the type of the heating system used, the number of heated months and the nominal heated area were influential parameters in this model. The significance of this paper stems from the methodology that propose an alternative to the energy audit and simulation methods. The proposed method can be used in contexts where a combination of energy resources is used with no proper metering system and with the absence of accurate data that is needed for simulation. [ABSTRACT FROM AUTHOR]

This study aims to investigate the effect of demand response (DR) actions on energy consumption and energy cost with two alternative heat generation systems in a detached house in a cold climate. The heat generation systems are a ground source heat pump coupled with a two-storage tank system (GSHP heating system) and a water-based electric heating system coupled with a similar storage tank system (storing electric heating system). Four rule-based DR control algorithms were applied and studied for two alternative heat generation systems. Two rule-based DR control algorithms from previous study were applied and investigated for these heat generation systems based on real-time hourly electricity price and future hourly electricity prices based on the blocking-maximum subarray method. Two new rule-based DR control algorithms based on future hourly electricity prices were developed and investigated for these heat generation systems based on the sliding-maximum subarray method and moving average method. This research was implemented with the validated dynamic building simulation tool IDA ICE. The obtained results show that the maximum annual savings in the heating energy and cost take place using the rule-based DR control algorithm based on the sliding-maximum subarray method. As well, these savings are about 10% and 15%, respectively, for the GSHP heating system; and about 1% and 8%, respectively, for the storing electric heating system. [ABSTRACT FROM AUTHOR]

Changes in weather conditions due to global warming affect the energy demand of buildings, resulting in changes in the installed heat capacity of district heating systems. The study provides a methodology for assessing the potential effects of climate change in combination with renovation of existing building stock on building heat demand. The system dynamics approach was used for investigation of the interlinkages and causality of energy efficiency, global warming, and total installed heat source capacity. Variations in the heating load of a district heating system due to improvements in building energy efficiency were studied in combination with three climate change scenarios. The optimal balance point between investment at the heat source side and at the heat consumers side was also investigated. The interaction of global warming, building heat demand and installed capacity of the district heating system was identified by the levelized investment approach. The study shows that global warming directly influences the heating degree-days and reduces the heat demand in the case study considered (part of the Riga city). A significantly higher impact on heat demand could be achieved by implementation of building renovation, however the funding available for this purpose is insufficient in the studied case. • The impact of global warming reduces heat demand by 13, 17, and 24% in low, medium, and high scenarios. • Provided methodology couples the system dynamic approach with the building heat balance model. • Investment in heat saving by the renovation of buildings and heat production technology are interlinked. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop an artificial neural network (ANN) model to predict the optimal start moment of the setback temperature during the normal occupied period of a building and to suggest an algorithm employing the developed ANN model to enhance indoor thermal comfort and building energy efficiency. To achieve this objective, three major steps were undertaken: the development of the initial ANN model, optimization of the initial model, and development of control algorithms and performance tests. The development and performance testing of the model and algorithm were conducted by employing numerical simulation methods using transient systems simulation (TRNSYS) and matrix laboratory (MATLAB) software. The results of the development and tests revealed that the indoor temperature, outdoor temperature, and temperature difference from the setback temperature were the three major variables predicting the optimal start moment of the setback temperature. Thus, these variables were used as input neurons in the ANN model. In addition, the optimal values for the number of hidden layers, number of hidden neurons, learning rate, and moment were found to be 4, 9, 0.6, and 0.9, respectively, and these values were applied to the optimized ANN model. Comparative performance testing of a conventional algorithm and two ANN-based predictive algorithms demonstrated that the ANN-based algorithms were superior in advancing indoor thermal comfort or building energy efficiency. [ABSTRACT FROM AUTHOR]

Energy performance simulation is a generally used method for assessing the energy consumption of buildings. Simulation tools, though, have shortcomings due to false assumptions made during the design phase of buildings, limited information on the building's envelope and installations and misunderstandings over the role of the occupant's behaviour. This paper presents the results of a Monte Carlo sensitivity analysis on the factors (relating to both the building and occupant behaviour) that affect the annual heating energy consumption and the PMV comfort index. The PMV results are presented only for the winter (heating) period which is important for energy consumption in Northern Europe. The reference building (TU Delft Concept House) was simulated as both a Class-A and a Class F dwelling and with three different heating systems. If behavioural parameters are not taken into account, the most critical parameters affecting heating consumption are the window U value, window g value and wall conductivity. When the uncertainty of the building-related parameters increases, the impact of the wall conductivity on heating consumption increases considerably. The most important finding was that when behavioural parameters like thermostat use and ventilation flow rate are added to the analysis, they dwarf the importance of the building parameters. For the PMV comfort index the most influential parameters were found to be metabolic activity and clothing, while the thermostat had a secondary impact. [ABSTRACT FROM AUTHOR]

Among all public buildings, on account of their educational purpose, school buildings have a major social responsibility. Therefore energy performance in this type of building is of great importance. The overall purpose of this research is to achieve a functional benchmarking, based on the real operation conditions of school buildings, by the exploitation of the results made public, through an intensive literature survey on energy consumptions in schools. The survey was made to gather data that is relative to energy consumption in school buildings, documented in the most diverse fields and units: global energy consumption values, electrical energy consumption; fuel consumption for heating, energy data consumption of schools expressed in annual cost per unit of heated/cooled surface area ($/m 2 ) or per unit of heated/cooled volume ($/m 3 ) or, finally, as the annual cost per student ($/student). The literature was analyzed to determine if a worldwide comparison among the published data could be established. The results suggest that when attempting to determine an energy benchmark some considerations should not be forgotten: standard indoor environmental conditions (IEC) for classrooms (set-point for indoor operative temperature of 20 °C in winter and 26 °C in summer as suggested in EN 15251:2007), electrical and heating consumption values should be kept separately, different education levels usually require different energy consumption values. A good way to normalize heating energy consumption is going through a climatic adjustment based on Heating Degree Days (HDD). For an impartial data comparison, based either on an operating rating or on a simulation carried out for reference conditions, benchmark reference values should be expressed in terms of billed energy data. [ABSTRACT FROM AUTHOR]

Highlight: [•] We analyzed heating energy consumption records of residential buildings. [•] Explanative parameters were analyzed by multivariate and regression analysis. [•] Energy classes were defined according to gas consumption per m2 of useful area. [•] Real energy consumption should be considered to label buildings heating efficiency. [Copyright &y& Elsevier]

Abstract: In this paper, we analyze the determinants of the demand for firewood by Norwegian households, focusing on intrinsic factors such as lifestyle and environmental attitudes, along with household socioeconomic characteristics. The data are from the Norwegian Consumer Expenditure Survey and a supplementary questionnaire on energy consumption and lifestyle. We apply a zero-inflated negative binomial model to correct for overdispersion and the excessive number of zeros in the data. The results indicate that an urban lifestyle and concerns for comfort are negatively associated with firewood demand. In addition, price has a strong negative effect on demand. However, the most important determinants of household firewood demand are the characteristics of the household residence, including location, and household characteristics such as age and income. [Copyright &y& Elsevier]

Abstract: An overview is presented on the last decade of geothermal heating by ground source heat pumps (GSHPs) in Europe. Significant growth rates can be observed and today''s total number of GSHP systems is above 1 million, with an estimate of about 1.25 million mainly used for residential space heating in 2011. These systems are counted among renewable energy technologies, though heat pump operation typically consumes electricity and thus only a fraction of the energy produced is actually greenhouse gas (GHG) emission free. Consequently, only in the most mature markets of the Scandinavian countries and in Switzerland, calculated emission savings reach more than 1% compared to standard heatings. However, Sweden shows that more than 35% is possible, with about one third of these systems in Europe concentrated in this country. Our calculations demonstrate the crucial role of country-specific heating practices, substituted heat mix and primary electricity mix for country-specific emission savings. For the nineteen European countries studied in 2008, 3.7Mio t CO2 (eq.) are saved in comparison to conventional practice, which means about 0.74% on average. This reveals that many countries are at an early stage with great potential for the future, but even if the markets would be fully saturated, this average would barely climb to about 30%. These numbers, however, take the current conditions as reference, and when extrapolated to the future can be expected to improve by greener electricity production and increased heat pump performance. [Copyright &y& Elsevier]

Abstract: Studies performed on the prediction of building energy consumption are increasingly important for selecting the best control strategies against the excessive energy consumptions. This paper presents Adaptive Network Based Inference System (ANFIS) model to forecast building energy consumption in a cold region. The objective of this paper is to examine the feasibility and applicability of ANFIS in building energy load forecasting area. Different combinations of building samples formed by using three different form factors (FF 1/2, FF 1/1 and FF 2/1), nine azimuth angles varied 0o–80o, three transparency ratios of 15%, 20%, 25% and five insulation thicknesses of 0, 2.5, 5, 10 and 15cm. Finally, it is observed that ANFIS can be a strong tool with the 96.5 and 83.8% for heating and cooling energy prediction in pre-design stage of energy efficient buildings for choosing the best combinations. [ABSTRACT FROM AUTHOR]

Abstract: In the current study the savings of CO2 emissions due to the use of ground source heat pump (GSHP) systems was investigated in comparison to conventional heating systems. Based on a subsidy program for GSHP systems in southwest Germany, the regional, average, and total CO2 savings of 1105 installed GSHP systems were determined on a regional scale. The emitted CO2 per kWh of heating demand for the studied scenario resulted in 149gCO2/kWh for GSHP using the German electricity mix and 65gCO2/kWh using the regional electricity mix, which results in CO2 savings of 35% or 72%, respectively. Similar CO2 avoidances of GSHP systems were found in American and European studies ranging between 15% and 77% strongly depending on the supplied energy for the heat pumps and the efficiency of installation. The resulting CO2 savings for one installed GSHP unit in the present study therefore range between 1800 and 4000kg per year. Nevertheless, the minimum average total annual CO2 savings of all installed GSHP systems due to the subsidy program amounted to 2000 tons per year. The maximum regional avoided additional CO2 emissions are primarily associated with the affluent suburbs of the most densely populated area in the region. In 2006 the total contribution of CO2 savings due to GSHP systems in Germany was only about 3.4% of the total renewable energies. However, continuously rising numbers of installed GSHP units and the increasing use of renewable electricity demonstrate that there is a fine opportunity to substantially avoid additional CO2 emissions associated with the provision of heating (and cooling) of buildings and other facilities. [Copyright &y& Elsevier]

Abstract: Energy efficiency is very important in school buildings as it is associated with comfort and air quality conditions in their interior and energy costs of these buildings are associated with their main operational costs. Moreover, school buildings differ from other types of buildings because they are the places where children are educated and have the opportunity to learn how to become environmentally-aware citizens. There is an increasing awareness throughout Europe for promotion of sustainable solutions in school buildings involving energy efficient technologies and measures. The aim of this article is to assess the energy performance, based on monitored data, of school buildings in the C′ climatic zone of Greece, a region with the lowest air temperature during winter period. It also demonstrates, through simulation studies, the potential for energy conservation of school buildings in this region. [Copyright &y& Elsevier]

Abstract: There is evidence from the International Panel of Climate Change that the UK will experience a mean rise in ambient air temperature over the coming years. Such a rise in temperature will change the requirements for heating and cooling of domestic buildings. This scoping paper explores this issue with respect to the housing sector in the Yorkshire Humber Region of the UK and comes to the conclusion that the regions domestic sector poses major problems with respect to the stated carbon savings required by the UK Government. [Copyright &y& Elsevier]

Abstract: The household energy end-use project (HEEP) has collected energy and temperature data from a randomly selected, nationally representative sample of about 400 houses throughout New Zealand. This database has been used to explore the drivers of indoor temperatures and heating energy. Initial analysis of the winter living room temperatures shows that heating type, climate and house age are the key drivers. On average, houses heated by solid fuel are the warmest, with houses heated by portable LPG and electric heaters the coldest. Over the three winter months, living rooms are below 20°C for 83% of the time—and the living room is typically the warmest room. Central heating is in only 5% of houses. Solid fuel is the dominant heating fuel in houses. The lack of air conditioning means that summer temperatures are affected by passive influences (e.g. house design, construction). Summer temperatures are strongly influenced by the house age and the local climate—together these variables explain 69% of the variation in daytime (9a.m. to 5p.m.) living room temperatures. In both summer and winter newer (post-1978) houses are warmer—this is beneficial in winter, but the high temperatures in summer are potentially uncomfortable. [Copyright &y& Elsevier]

Abstract: The potential impacts of climate change on heating and cooling energy demand were investigated by means of transient building energy simulations and hourly weather data scenarios for the Zurich–Kloten location, which is representative for the climatic situation in the Swiss Central Plateau. A multistory building with varying thermal insulation levels and internal heat gains, and a fixed window area fraction of 30% was considered. For the time horizon 2050–2100, a climatic warm reference year scenario was used that foresees a 4.4°C rise in mean annual air temperature relative to the 1961–1990 climatological normals and is thereby roughly in line with the climate change predictions made by the Intergovernmental Panel on Climate Change (IPCC). The calculation results show a 33–44% decrease in the annual heating energy demand for Swiss residential buildings for the period 2050–2100. The annual cooling energy demand for office buildings with internal heat gains of 20–30W/m2 will increase by 223–1050% while the heating energy demand will fall by 36–58%. A shortening of the heating season by up to 53 days can be observed. The study shows that efficient solar protection and night ventilation strategies capable of keeping indoor air temperatures within an acceptable comfort range and obviating the need for cooling plant are set to become a crucial building design issue. [Copyright &y& Elsevier]

The effects of heating energy and heating position on the conversion efficiency of an electrically heated catalyst of a four stroke motorcycle engine under cold start conditions were investigated in this study. In general, during cold start, the operating temperatures of a four stroke motorcycle engine and its catalyst would not be optimized. It was found in this paper that by applying heat to the catalyst however, the reaction of the catalyst could be promoted, which, consequently, improved the conversion efficiency.The experimented parameters were heating energy, heating position, heating temperature and the carbon monoxide (CO) setting level. The heating temperatures included 100, 140 and 180 °C, while three different heating powers and six different heating positions were used. The CO levels were set as 1.0%, 1.8% and 2.3%.The best CO conversion efficiency was obtained by applying heating at the inlet of the catalyst. It was revealed that a high heating power induced a high temperature rising rate and, consequently, a high CO conversion efficiency. In terms of energy economy efficiency, however, heating at the mid-section of the catalyst gave the best results and through a relatively low heating power. [Copyright &y& Elsevier]

This paper presents coherent 5-year measured data that have been gathered for analyses of building energy consumption and thermal performance of exterior walls. The data is also very suitable for calculations and simulations of heating and cooling energy need of buildings. The data was collected from six identical test buildings, having exterior walls that are constructed of different building materials. The data include the following: indoor–outdoors temperatures; temperatures at various depths within the northern, southern, eastern, and western exterior wall facades; indoor–outdoors relative humidity, heating energy, wind speed and direction; air tightness, infiltration, and horizontal global solar radiation. A computer system (data logger) was used to monitor, check, calculate, integrate, and save the data acquired from approximately 520 sensors in each test building. Measurements were taken with a time interval of 20 s. The 20 s values were then integrated over a time interval of 30 min and the minimum, maximum, and mean values were subsequently stored to a computer database. Analyses of the results indicated that temperatures within the buildings’ exterior walls are constantly changing and, that occasionally the flow of conduction heat is reversed (i.e. outside–inside) due to solar radiation. For accurate results of temperature distribution and the actual heat losses through building envelopes, none steady-state calculations are essential. Depending on the intensity of solar radiation and the material characteristics of the walls, temperature gradient at the inner surfaces of exterior walls may become milder compared to that of the outer surfaces. [Copyright &y& Elsevier]

Aquifer Thermal Energy Storage (ATES) is an open-loop geothermal system allowing long-term storage of thermal energy in groundwater. It is a promising technology for environmentally friendly energy generation that can reduce greenhouse gas (GHG) emissions. In the literature, there are few studies on the greenhouse gas emissions caused by ATES systems over their entire life cycle. Thus, this study presents a novel life cycle assessment (LCA) regression model that can be used for a wide range of ATES configurations due to its parametric structure. This model is a fast alternative to conventional time-consuming LCAs. Combined with a Monte Carlo simulation, it enables the analysis of the environmental impacts of a large variety of hypothetical ATES systems and therefore the evaluation of the technology as a whole. Compared to conventional heating systems based on heating oil and natural gas, the median value of the Monte Carlo simulation results in GHG savings of up to 74%. In comparison to cooling techniques using today's electricity mix, ATES can save up to about 59% of GHG emissions, while also being economically competitive. When considering a projected electricity mix for the year 2050, the GHG emission savings resulting from a second LCA regression model are as high as 97%. The findings of our sensitivity analysis show which ATES design parameters should be optimized when planning new systems. In particular, the most important design parameters operating time cooling and coefficient of performance (COP) of the heat pump should be carefully considered. • Novel life cycle regression model for aquifer thermal energy storage is developed. • Greenhouse gas emission (GHG) savings of up to 74% are possible. • Emission savings are even higher when using a renewable electricity mix. • The most important design parameters are identified. [ABSTRACT FROM AUTHOR]