Human exposure to indoor pollutant concentrations is receiving increasing interest in Life Cycle Assessment (LCA). We address this issue by incorporating an indoor compartment into the USEtox model, ...as well as by providing recommended parameter values for households in four different regions of the world differing geographically, economically, and socially. With these parameter values, intake fractions and comparative toxicity potentials for indoor emissions of dwellings for different air tightness levels were calculated. The resulting intake fractions for indoor exposure vary by 2 orders of magnitude, due to the variability of ventilation rate, building occupation, and volume. To compare health impacts as a result of indoor exposure with those from outdoor exposure, the indoor exposure characterization factors determined with the modified USEtox model were applied in a case study on cooking in non-OECD countries. This study demonstrates the appropriateness and significance of integrating indoor environments into LCA, which ensures a more holistic account of all exposure environments and allows for a better accountability of health impacts. The model, intake fractions, and characterization factors are made available for use in standard LCA studies via www.usetox.org and in standard LCA software.
Neglecting health effects from indoor pollutant emissions and exposure, as currently done in Life Cycle Assessment (LCA), may result in product or process optimizations at the expense of workers’ or ...consumers’ health. To close this gap, methods for considering indoor exposure to chemicals are needed to complement the methods for outdoor human exposure assessment already in use. This paper summarizes the work of an international expert group on the integration of human indoor and outdoor exposure in LCA, within the UNEP/SETAC Life Cycle Initiative. A new methodological framework is proposed for a general procedure to include human-health effects from indoor exposure in LCA. Exposure models from occupational hygiene and household indoor air quality studies and practices are critically reviewed and recommendations are provided on the appropriateness of various model alternatives in the context of LCA. A single-compartment box model is recommended for use as a default in LCA, enabling one to screen occupational and household exposures consistent with the existing models to assess outdoor emission in a multimedia environment. An initial set of model parameter values was collected. The comparison between indoor and outdoor human exposure per unit of emission shows that for many pollutants, intake per unit of indoor emission may be several orders of magnitude higher than for outdoor emissions. It is concluded that indoor exposure should be routinely addressed within LCA.
Benchmarking is a method that can be used to measure progress and create awareness about the performance of organisations. Benchmarking the housing stock energy performance of Dutch housing ...associations can be used to measure and assess progress towards the decarbonisation of the housing stock. A new national climate agreement was signed in 2019, and in 2021 a new method to determine the theoretical energy performance of dwellings came into force in the Netherlands. To benchmark energy performance, a set of indicators is created that adequately represents the performance of Dutch housing associations according to the changed policies. A process involving key stakeholders is presented here to identify, assess and combine possible indicators. These were then integrated into four integrated models, which led to a final benchmark model. A model was chosen that consists of three indicators covering the energy performance of Dutch housing associations. The process and arguments that led to this final model are presented. While applicable within the Dutch context, the method and research results provide generalisable insights for the creation of energy performance benchmarks for building stocks.Practice relevanceThis paper provides both researchers and policymakers with a practical approach to monitor and benchmark the energy performance of dwellings owned by organisations. An analysis of the Dutch policy context is presented. Examples of possible benchmark indicators are described and evaluated. A method is created to assess indicators and it is shown how to integrate indicators in different benchmark models. The final model consists of three indicators: (1) the average theoretical primary fossil energy consumption (energy label value); (2) the difference between the theoretical heating demand (quality building envelope) and the theoretical maximum heating demand of dwellings; and (3) the average actual CO2 emissions from gas consumption. Researchers and policymakers from other countries can adapt both the process and the final benchmark model to create similar benchmark models across housing stocks.
The Energy Performance of Buildings Directive (EPBD) enhanced the sustainable improvement of dwellings in the European Union. Member states formulated measurable goals to improve the housing stock, ...and monitoring systems were developed to give insights into the improvements. In the Netherlands, non-profit housing associations agreed to improve the quality of their housing stock to an average Dutch energy label B (energy index (EI NV) = 1.40) by 2020. Research assessing this progress over time is presented using an annual monitoring system based on 2.0 million energy performance calculations of 264 Dutch non-profit housing associations between 2017 and 2020. The assessment includes: a detailed description of the development of the state of the stock over time; the effect of changes to the stock (construction and demolition) and changes within the stock (different types of retrofit measures); and the different characteristics of non-profit housing associations. Insights from this research show which specific retrofit and other measures are adopted and have substantial impact over time. This provides a useful frame of reference for building stock analysis and accelerating the improvement of the building stock. It also creates a baseline of information for the future sustainable development of this particular stock.Practice relevanceThis research reveals which energy saving measures are most and least employed over time in Dutch non-profit housing associations sector. Large urban housing associations own a large share of the Dutch non-profit housing stock, and their dwellings have on average a lower energy rating. However, the improvement of their dwellings between 2017 and 2020 is higher than for smaller housing associations, which already have on average a higher energy rating. While the construction and demolition of dwellings contribute to 15.6% of the annual improvement, most of the improvement of the energy performance depends on retrofitting the existing stock. The trends are found to rely most on traditional measures (e.g. the installation of high-efficiency gas boilers and improved insulation). However, the rate of adding photovoltaic (PV) solar systems has increased rapidly in recent years, while futureproof systems (e.g. heat pumps and district heating) only have a steady adoption rate in this sector.
Thermal renovations are considered to be an effective measure to reduce residential energy consumption. However, they often result in lower-than-expected energy savings. In this paper, we investigate ...some parameters that influence the probability on lower-than-expected energy savings. We do this by comparing actual pre- and post-renovation energy consumption of 90,000 houses in the Netherlands. The results of this study confirm that the effect of the parameters differ per renovation measure. For every renovation measure, the energy performance gap post renovation plays a significant role. This implies that the use of actual energy consumption data to determine the potential energy savings could therefore help to reduce the number of renovations resulting in lower-than-expected energy savings. Also, the energy efficiency state of the building pre-renovation plays an important role. One should take into account that renovations of energy inefficient buildings more frequently result in lower-than-expected energy savings than renovations of relatively energy efficient buildings. For the type of house we found that multifamily houses more often result in lower than expected savings when building installations are improved, while single-family houses renovations more frequently result in lower energy savings than expected when the building envelope insulation is improved. These insights can contribute to the decision making process whether or not to take a certain renovation measures, they can also help to manage expectations on housing stock level and individual building level.
•A pre and post renovation energy use analysis of almost 90,000 renovated dwellings.•The (p)rebound effects explain only partly disappointing energy renovation results.•Effectiveness of renovations ...are dependent on state of building prior to renovation.•Effectiveness of renovations are dependent on type of occupant.•Deep renovations often save less energy than expected but are the most effective.
Energy renovations often result in lower energy savings than expected. Therefore, in this study we investigate nearly 90,000 renovated dwellings in the Netherlands with pre and post renovation data of actual and calculated energy consumption. One of the main additions of this paper, compared to previous studies on thermal renovation, is that it only takes dwellings into account with the same occupants before and after renovation, using a large longitudinal dataset. Overall this paper shows new insights towards the influence of the energy efficiency state of a building prior to energy renovation, the type of building, the number of occupants, the income level of the occupants and the occupancy time on the actual energy savings, the energy saving gap and on the probability of lower energy savings than expected. We also investigate if the influence is different per type of thermal renovation measure. Some of the findings are: it is impossible to conclude which single thermal renovation measure is the most effective because this is dependent on the energy efficiency of the building prior to the energy renovation, type of building, income level and occupancy; occupants with a high income save more energy than occupants with low income; dwellings with employed occupants benefit more from improved building installations than dwellings occupied by unemployed occupants; The prebound and rebound effects are only part of the explanations for lower than expected energy savings; Deep renovations result more often in lower than expected energy savings than single renovation measures but nevertheless they result in the highest average energy saving compared to other thermal renovation measures. The results could be used for more realistic expectations of the energy reduction achieved by thermal renovations, which is important for (amongst others) policy makers, clients and contractors who make use of energy performance contracting, home owners, landlords and (social) housing associations and as a starting point to improve the energy calculation method.
The difference between actual and calculated energy is called the 'energy-performance gap'. Possible explanations for this gap are construction mistakes, improper adjusting of equipment, excessive ...simplification in simulation models and occupant behaviour. Many researchers and governmental institutions think the occupant is the main cause of this gap. However, only limited evidence exists for this. Therefore, an analysis is presented of actual and theoretical energy consumption based on specific household types and building characteristics. Using a large dataset (1.4 million social housing households), the average actual and theoretical energy consumptions (gas and electricity) of different household types and characteristics (income level, type of income, number of occupants and their age) were compared for each energy label. Additionally, the 10% highest and lowest energy-consuming groups were analysed. The use of combinations of occupant characteristics instead of individual occupant characteristics provides new insights into the influence of the occupant on energy demand. For example, in contrast to previous studies, low-income households consume more gas per m
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(space heating and hot water) than households with a high income for all types of housing. Furthermore, the performance gap is caused not only by the occupant but also by the assumed building characteristics.
•Longitudinal analysis of heating consumption data from the Netherlands and Denmark.•Comparing variances in consumption of 887,685 moving and staying households.•Occupants and buildings each explain ...half of the variation in heating consumption.•The relative influence of occupants differs for different building characteristics.
It is commonly accepted that occupants have a significant influence on the variation in residential heating consumption. However, the scale of that influence lacks empirical investigation. The aim of this study was to distinguish which part of the variance in actual residential heating consumption can be attributed to the occupants, and which part to the building itself. This was achieved by applying and extending a method suggested by Sonderegger in 1978, using updated and significantly improved data from two different countries: the Netherlands and Denmark. These data contain different types of heating supply systems (district heating and natural gas) and different housing forms (multi and single-family social housing, and private detached single-family houses). For the studied databases, the results indicate that approximately 50% of the variance in heating consumption between houses can be explained by differences related to occupants. The other 50% can be explained by the characteristics of the building itself and other physical parameters, which are often not taken into account in simulation models of heat transmission within buildings. Additional analyses indicate that the relative influence of occupants on heating consumption differs depending on the building characteristics of the dwelling. For example, the influence of occupants is larger when the building is more energy efficient. Based on the research results, it can be concluded that it is unrealistic to aim for a building simulation model that perfectly projects residential heating consumption for individual cases. However, creating building simulation models and occupant consumption profiles that accurately represent average residential heating consumption should be possible.
The 2050 decarbonization goals coupled with the growing housing shortage in Europe intensify the pressure on new-build dwellings to enhance their energy performance. Beyond a zero operational energy, ...the focus has shifted towards reducing embodied carbon (EC). Against this backdrop, this study investigates the simultaneous impact of downsizing and the use of timber in new-build dwellings, EC reduction strategies seldom explored concurrently. Through partial life cycle assessments, three scenarios are modelled: the Small, Medium, and Large House, with two construction variations for each, comparing a modular timber design to a conventional concrete alternative. Designs are based on dwellings built in Almere, the Netherlands. Data is extracted from the Swiss Ecoinvent database using the TOTEM tool and the static −1/+1 approach for biogenic carbon accounting is adopted. Results show a total EC ranging from 42,608 to 70,384 kgCO2eq for the timber designs versus 54,681 to 91,270 kgCO2eq for their concrete counterparts. Findings suggest that the relationship between house size and EC is sublinear whereby a house twice the size entails less than twice the EC emissions. Only the simultaneous implementation of downsizing and the use of timber achieved 53% carbon savings. The discussion explores implications of outcomes across academic, industry and policy perspectives, challenges in implementing smaller timber dwellings, and study limitations and future research. Beyond its empirical contribution, this paper offers a practical contribution with its hierarchical data analysis approach covering building, element and component. This approach can be implemented by researchers and practitioners alike to inform their design process.
•Downsizing and timber are assessed in tandem as embodied carbon reduction strategies.•The embodied carbon of actual European housing scenarios is investigated.•A proposed hierarchical approach decomposes the house into elements and components.•The hierarchical analysis links architectural design choices to embodied carbon.•A small timber house consumes half the embodied carbon of a large concrete house.
Energy consumption in dwellings contributes significantly to their total negative environmental impact. This paper quantitatively assesses the environmental impact of building-related and ...user-related gas and electricity consumption in a Dutch apartment dwelling using life cycle assessment (LCA) methodology. Several scenarios for gas and electricity consumption are compared to assess what effect changes in building characteristics and user behaviour have on the environmental impacts of energy consumption. This study shows that gas consumption significantly contributes to four environmental impact categories, which can be most effectively countered by reducing the heat demand of the dwelling. A 23% reduction in gas consumption leads to up to 13% less overall environmental impacts. Particularly in buildings with low heat demand, electricity consumption dominates all environmental impact categories. These can most effectively be reduced by changing the electricity demand of the user: 47% less electricity consumption leads to a 9–45% reduction in the total environmental impact. However, since electricity consumption continues to rise, the environmental effects of electricity use may be better reduced by changing the environmental impact of the electricity supply. Theoretically, when electricity consumption remains the same, over 90% less environmental impact could be reached by using 100% wind power to generate electricity.
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