Dutch Housing Stock Research Articles

Evaluating building-level parameters for lower-temperature heating readiness: A sampling-based approach to addressing the heterogeneity of Dutch housing stock

The Dutch government aims to eliminate natural gas for residential heating in 1.5 million homes by 2030. One strategy is connecting existing dwellings to lower-temperature district heating (DH) systems, although these dwellings might require energy renovations. The heterogeneous dwelling stock causes varying renovation needs that complicate the energy transition. The present study addresses this issue by assessing the building-level parameters affecting the readiness of the Dutch terraced-intermediate and apartment types for lower-temperature heating (LTH) supplied by DH systems. A sampling-based approach was employed to capture variability within these dwelling types, addressing the limitations of archetype-based methods. The findings suggest a sample size of 1300 to represent the variations in these dwelling types. Parametric simulations and machine learning methods were used to identify significant building-level parameters for medium-temperature (MT: 70/50 °C) and low-temperature (LT: 55/35 °C) supply levels. These include heating setpoints (desired indoor temperature) and ventilation-related parameters (ventilation system type and air infiltration rate), followed by fabric-related parameters (roof, glazing, wall, ground, and door insulation) and geometric properties (orientation, compactness ratio, and window-to-wall ratio). Additionally, radiator oversizing also impacts LTH readiness. These results broadly apply to the studied dwelling types, although feature importance varies by supply temperature and dwelling type. The findings can guide stakeholders in assessing current conditions and prioritising renovation measures, aiding the development of targeted renovation solutions. Encompassing the representative variations within studied dwelling types enhances the robustness of the results. However, incorporating more refined data could improve the accuracy of the findings, better supporting the energy transition of these dwellings.

Discovering the Significance of Housing Neighbourhoods by Assessing Their Attributes With a Digital Tool

Much of the building stock subjected to the upcoming European Renovation Wave is neither listed as heritage nor considered valuable architecture. This also applies to Dutch housing built between 1965 and 1985, more than 30% of the Dutch housing stock, for which there is no consensus on their cultural significance. Their successful renovation process requires broad support. What attributes do citizens consider significant in their neighbourhood? How do we include a multitude of stakeholders? And can digital methods help collect and process responses? This article reveals significant attributes of residential neighbourhoods from 1965 to 1985, assessed by various stakeholders with a digital tool based on case studies in Amsterdam and Almere. A mobile application allowed individuals to identify significant attributes at various scales while visiting the neighbourhood. By qualitative data analysis of survey and interview results, groups of tangible and intangible attributes were deduced. Results show that identifying attributes by current stakeholders broadens existing expert-led assessments on 1965–1985 neighbourhoods by including, for example, generic attributes not originally intended by the designers. Asking open-ended questions is considered essential to identify undiscovered attributes by alternative stakeholders, although dealing with large numbers of responses is recognised as a challenge to cluster and classify. Lastly, the mobile application appears to be a useful digital tool, but integrating scientific consistency and usability is recommended for further development. Engaging multiple stakeholders with such mobile applications allows for collecting opinions, anticipating conflicts, or shared interests between stakeholders and integration into renovation designs. It can empower citizens to preserve the neighbourhood attributes that are most significant to them.

Heating the Dutch housing stock without natural gas

This paper studies the level of improvement of building envelopes required to heat the Dutch housing stock using an energy supply without natural gas, such as a district heating network at lower supply temperature or a heat pump. We identified 35 building types to represent the Dutch housing stock of single-family dwellings. A 4R2C building model was used to assess whether the dwellings could be heated at lower supply temperatures after they were renovated according to six renovation packages of different ambition level.

Heat pumps in the existing Dutch housing stock: An assessment of its Technological Innovation System

Heat pump technology has the potential to substantially increase the efficiency of domestic space heating which is currently based on boiler technology. Although the heat pump has reached technological maturity, its implementation remains hampered by numerous non-technological barriers in many countries. This paper presents an assessment of the barriers that hamper diffusion of heat pumps in the Dutch residential sector. For this purpose, the state of its Technological Innovation Systems (TIS) was assessed. Particular attention was thereby given to the role of the sectoral context as this is where the heat pump ultimately needs to fit in. The success of domestic heat pumps was found to be highly dependent on how developments within the sectoral context unfold. The findings not only present what is hampering domestic heat pumps in the Netherlands, but also show that the sectoral context can be much more dynamic than literature suggests.

Innovations for a carbon free Dutch housing stock in 2050

In 2019 the Dutch government agreed together with all relevant stakeholder organisations on a new Climate Agreement. This agreement combines high ambitions for the reduction of CO2 emissions with policies and measures to achieve these goals. In 2030 CO2 emissions have to be reduced to 49% compared to 1990. In 2050 we should have an CO2 emission free and energy neutral built environment. The existing housing stock plays a major role in the realisation of these goals. The Dutch housing stock comprises of 7.5 million dwellings. The majority of which has to be renovated to a nearly zero energy performance. In a few years’ time we will have to speed up the renovation rate to 200,000 carbon free renovations per year, a pace that is needed to make the entire stock of 6 million homes carbon free in the 30 years up to 2050. To support these goals a large innovation program is needed. Method: This paper will elaborate on the analyses of the current state and the needed innovations, hereby also referring to results of evaluation research of the progress in energy renovation in the recent years. Results: The required innovations will be presented in a systemic way. Furthermore, a model is presented of how to organize the innovation (research, applications in practices, pilots etc) in a long running, broad organization incorporating many stakeholders. For this purpose, a new platform, the BTIC (Building and Technology Innovation Center) has been developed. In BTIC all relevant research and innovation parties collaborate closely, like the Technical Universities and the national applied research institute TNO. The author is the scientific director of BTIC.

Innovations for a carbon free Dutch housing stock in 2050

In 2017 the new Dutch coalition government agreed on high ambitions for the reduction of CO2 emissions to meet the Paris agreement and policies to achieve this were detailed in a Climate Agreement between the government and many stakeholder organisation in June 2019. In 2030 CO2 emissions have to be reduced to 49% compared to 1990. In 2050 we should have a CO2 emission free and energy neutral built environment. The existing housing stock plays a major role in the realisation of these goals. The Dutch housing stock comprises of 7.5 million dwellings. The majority of which has a rather bad thermal energy condition and are mainly heated by natural gas. All these houses have to be renovated to a nearly zero carbon performance. By 2021 yearly more than 50,000 new homes per year will have to be delivered on nZEB level without a natural gas connection and at least 50,000 existing dwellings will have to be made gas-free per year. These are steps towards 200,000 zero carbon renovations per year, a pace that is needed to make the entire stock carbon free in the 30 years up to 2050. To support these goals a large innovation programme is currently being developed. This paper presents the required innovations. Research on the impact of the policies and measures applied in the recent years point to the challenges that have to be overcome. A particular challenge is to realize the intended performance and really save energy and reduce CO2 emissions on a large scale.

Analysing the Energy Efficiency Renovation Rates in the Dutch Residential Sector

The housing stock has a major share in energy consumption and CO2emissions in the Netherlands. CO2emissions increased 2.5% year-on-year in the first quarter of 2018. Higher CO2emissions were principally due to raised gas consumption for heating in the residential and service sector1. Energy efficiency renovations can contribute considerably in reducing energy consumption and achieving the EU and national energy efficiency targets. However, based on recent research2, the renovation rates in the Dutch social housing sector are not adequate to achieve the energy efficiency targets. Moreover, the deep renovation rates are almost negligible in this sector. The Dutch housing stock consists of the owner-occupied sector and rental sector (social housing and private rental houses) with shares equal to 69.4% and 30.6%, respectively. Considering the major share of the housing sector in energy consumption, the aim of the current study is to evaluate and compare the renovation rates in these sectors and the potential contribution of each one in achieving the energy efficiency targets. By renovation rate, we mean the percentage changes in the number of the identical houses moving from one energy label to the more efficient energy labels. The Netherlands Enterprise Agency (RVO) and Statistics Netherlands (CBS) databases are used to conduct the statistical analysis. The results show that the renovation rates are almost the same in these three sectors, despite the expectation of much higher renovation rates in the social housing sector.

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Evaluating the environmental adaptability of a nearly zero energy retrofitting strategy designed for Dutch housing stock to a Mediterranean climate

Users’ behaviour and indoor climate are two leading aspects that must be taken into account if we want the retrofitting of the housing stock to contribute to CO2 reduction, comfort improvement and reduction of living costs. The integrated facade module evaluated in this paper, which constitutes an approach to zero energy renovation, includes a preliminary study for the identification of target occupants and their characteristics and requirements that will guide the design decisions. The proposed strategy primarily focuses on the case of social rental multi-family housing stock in the Netherlands, but should provide insights in the application of the concept in Europe. This paper presents the analysis of the adaptability of this solution to the Mediterranean climate, taking into account the specific characteristics of the occupants of this climatic zone.The results showed an improved performance of building after the application of the evaluated solution in southern Spain, but with lower savings on the energy demand than in the Netherlands, so the economic investment should be reduced in this case. Also, the inclusion in the solution of some variables, such as the forced night-time ventilation for passive cooling and the insulation thickness reduction, were tested and proved to be an optimisation of its performance in the Mediterranean climate. Overall, the study concluded that the proposed refurbishment strategy has the potential to be implemented in different climates, particularly if certain modification in the facade operation is considered.

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

Occupant behavior and energy consumption in dwellings: An analysis of behavioral models and actual energy consumption in the dutch housing stock

Much is known about the increasing levels of energy consumption and environmental decay caused by the built environment. Also, more and more attention is shown to the energy consumption of dwellings, from the early design stage until the occupants start living in them. The increasing complexity of building technologies, the occupants’ preferences, and their needs and demands make it difficult to achieve the aimed energy consumption levels. The goal of reducing the energy consumption of dwellings and understanding the share of occupant behavior in it form the context of this research. Several studies have demonstrated the ‘energy performance gap’ between the calculated and the actual energy consumption levels of buildings, and have explored the reasons for it. The energy performance gap is either caused by calculation drawbacks, uncertainties of modeling weather conditions, construction defects regarding air tightness and insulation levels, or by occupant behavior. This research focuses on the last aspect, i.e. analyzing the relationship between occupant behavior and energy consumption in dwellings, understanding the determinants of energy consumption, and finding occupants’ behavioral patterns. There are several dimensions of occupant behavior and energy consumption of dwellings: dwelling characteristics including the energy and indoor comfort management systems, building envelope, lighting and appliances; occupant characteristics including the social, educational and economical; and actual behavior, including the control of heating, ventilation and lighting of spaces, and appliance use, hot water use, washing, bathing, and cleaning. Attempting to understand this complexity asks for a methodology that covers both quantitative and qualitative methods; and both cross-sectional and longitudinal data collection, working interdisciplinary among the domains of design for sustainability, environmental psychology, and building and design informatics.

Occupant behavior and energy consumption in dwellings: An analysis of behavioral models and actual energy consumption in the dutch housing stock

Much is known about the increasing levels of energy consumption and environmental decay caused by the built environment. Also, more and more attention is shown to the energy consumption of dwellings, from the early design stage until the occupants start living in them. The increasing complexity of building technologies, the occupants’ preferences, and their needs and demands make it difficult to achieve the aimed energy consumption levels. The goal of reducing the energy consumption of dwellings and understanding the share of occupant behavior in it form the context of this research. Several studies have demonstrated the ‘energy performance gap’ between the calculated and the actual energy consumption levels of buildings, and have explored the reasons for it. The energy performance gap is either caused by calculation drawbacks, uncertainties of modeling weather conditions, construction defects regarding air tightness and insulation levels, or by occupant behavior. This research focuses on the last aspect, i.e. analyzing the relationship between occupant behavior and energy consumption in dwellings, understanding the determinants of energy consumption, and finding occupants’ behavioral patterns. There are several dimensions of occupant behavior and energy consumption of dwellings: dwelling characteristics including the energy and indoor comfort management systems, building envelope, lighting and appliances; occupant characteristics including the social, educational and economical; and actual behavior, including the control of heating, ventilation and lighting of spaces, and appliance use, hot water use, washing, bathing, and cleaning. Attempting to understand this complexity asks for a methodology that covers both quantitative and qualitative methods; and both cross-sectional and longitudinal data collection, working interdisciplinary among the domains of design for sustainability, environmental psychology, and building and design informatics.

Behavioral patterns and profiles of electricity consumption in dutch dwellings

In EU member states, the consumption of electricity per dwelling has remained more or less constant, although the consumption of large appliances has decreased considerably in the last 2 decades. This stabilization is caused by the increased ownership, usage and consumption levels of Information, Communication and Entertainment (ICE) appliances. This paper aims to analyze electrical appliance use in the Dutch housing stock, and identify behavioral patterns and profiles of electricity consumption. The analysis is conducted by applying descriptive, correlation, and exploratory factor analyses on data collected from 323 dwellings in two neighborhoods in the Netherlands. Our results show that behavioral patterns could be found based on actual occupant behavior of lighting and appliance use, especially depending on household activities like cooking, (personal) cleaning, etc. Behavioral profiles could be determined based on household and dwelling characteristics, i.e. household size, income, education, dwelling type, age, hours of working outside. The 4 profiles set up in this research are explained as ‘family,’‘ techie,’ ‘comforty,’ and ‘conscious.’ These profiles showed statistically significantly differences in terms of their electricity consumption levels.

Occupant behavior and energy consumption in dwellings: An analysis of behavioral models and actual energy consumption in the dutch housing stock

Occupant behavior and energy consumption in dwellings: An analysis of behavioral models and actual energy consumption in the dutch housing stock

Work Floor Experiences of Supply Chain Partnering in the Dutch Housing Sector

Work Floor Experiences of Supply Chain Partnering in the Dutch Housing Sector

Upscaling Large Scale Deep Renovation in the Dutch Residential Sector: A Case Study

The 2014 carbon emission of the Dutch economy was estimated at 194.4 billion kg. Dutch households are responsible for a particular large part of the total emission, about 37.1 billion kg or 19% of the total emission in 2014. While society becomes aware of the negative side effects of carbon emission in terms of climate change, the government introduced environmental policies to diminish carbon emission by households in line with EU policies with respect to a ‘near zero’ build (nZEB) environment in 2050 (Directive 2010/31/EU). The government, together with the construction sector and social housing associations among others, attempt to face this challenge by developing and experimenting with innovative nZEB retrofit solutions in order to upgrade the outdated and energy consuming housing stock at large. Social housing associations are in this respect a particular important group of stakeholders while they own 30%, about 2,4 million, of the Dutch housing stock. A particular type of recently developed solutions in this respect can be characterized as modular, platform based retrofit concepts. These retrofit concepts are often referred to as transformation concepts while the overall performance with respect to energy consumption and indoor climate drastically improves while building aesthetics radically change. It has to be emphasized that governmental policies are considered to be the driving force behind the development and experimentation of transformation concepts by 1) stimulating housing associations to invest in a sustainable and affordable housing stock, and 2) pushing the construction sector to develop innovative transformation concepts. Moreover, the retrofit sector is still in its infancy and despite that these modular transformation concepts have been applied successfully in demonstration projects it is challenging to get them adopted beyond these single projects. This makes one wonder which mechanisms stimulate and hinder the adoption of innovative retrofit concepts. This paper contributes in three ways. First, this paper identifies which arguments suppliers tend to use to frame housing associations decision to adopt a particular transformation concept. Second, the mechanisms that affect adoption will be addressed, and in particular those mechanisms which hinder adoption. Finally, we present several suggestions to overcome the inertia which hinder adoption in order to increase the potential of transformation concepts taken into account the 2050 challenge of a near energy zero build environment.

Partnering for climate change adaptations by Dutch housing associations

Partnering for climate change adaptations by Dutch housing associations

Partnering for climate change adaptations by Dutch housing associations

Partnering for climate change adaptations by Dutch housing associations

Energy policy ambitions and allocation over investment types

Since a few years there is an intensified debate in the Dutch social housing sector about measures to improve the energy efficiency of buildings and individual dwellings. It is generally acknowledged that it is cost-efficient to combine physical measures to improve the energy performance of dwellings with maintenance or improvement activities. Most of these activities take place during void repairs, planned preventive maintenance and renovations. Each can be regarded as an investment opportunity. The allocation of energy improvements between these investment types influences the energy performance of a housing stock in the long term. The central question of this paper is to assess to which extent the energy performance of the Dutch housing stock improves combining these investment types.

Digital consultancy tool for ageing-in-place with dementia

Purpose In order to facilitate ageing-in-place (AiP) with dementia, a digital consultancy tool (DCT) was designed to facilitate modifications to the home environment. In the Netherlands, about 65% of the 270,000 older adults with dementia live in their own dwelling. At the same time, 40% of the Dutch housing stock is not appropriate for older adults to live independently1 . Admission to a nursing home is usually caused by stress and a straining of the family carers. Caring for a person with dementia requires constant vigilance. Although admission to a nursing home cannot always be avoided, admission may be postponed by modifying the dwelling and through the use of technology. At present, persons with dementia are not able to adjust their dwelling to suit their needs. Therefore, it is important that carers and installers have access to information on how to design a dwelling in a dementia-friendly way. Method Based on publications about housing facilities2 , thermal comfort3 and dementiafriendly space plan4 , the design for a DCT for AiP was made. The design of the DCT will be discussed in focus group sessions in Alzheimer Cafes with persons with dementia and their family carers. First, sessions will be held about the requirements for the web tool for dementia-friendly design. After gathering the requirements and verification to (inter)national guidelines concerning the accessibility of webpages, focus group sessions will be held with user groups in order to test the usability of the preliminary DCT. Results & Discussion Results of this process are a webpage with descriptions of how to create a dementia-friendly dwelling for AiP with dementia. On the webpage dementia-friendly modifications of the living environment will be ordered by problem/function or space. Problems are categorized by (I)ADL tasks, behaviour, or cognitive problems. Adjustments of spaces are categorized by the combined model of WHO’s ICF and the Model of Integrated Building Design3,5.