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Predicting energy consumption and savings in the housing stock: A performance gap analysis in the Netherlands
Get PDFThe research used several large datasets, about dwellings theoretical energy performance, most of which were related to energy label certificates. All the datasets containing theoretical performance were merged with actual energy data. In addition to that, some were also enriched with socioeconomic and behaviour related data from Statistics Netherlands (CBS) or from surveys which were designed for the purpose of this research. Simple descriptive statistics were used to compare average theoretical and actual consumptions. Advanced statistical tests were used for detecting correlations, followed by several regression analyses. In a separate scenario study, the resulting averages of both theoretical and actual consumptions were extrapolated nation-wide in order to be compared with the existing policy targets.
Due to low predictive power of the variables in regression analyses, a sensitivity analysis of the theoretical gas use was performed on six assumptions made in the theoretical calculation to show how an increment in one of the assumptions affects the final theoretical gas consumption and whether this can explain the performance gap.
Last but not least, longitudinal data of the social housing dwelling stock between 2010 and 2013 was analysed, focusing on dwellings that had undergone renovation. The goal was to find out whether the theoretical reduction of consumption materialised and to what extent. A comparison of the actual reduction of different renovation measures was made in order to show what renovation practices lower the consumptions most effectively. The discrepancies between actual and theoretical heating energy consumption in Dutch dwellings.
Discrepancies between theoretical and actual gas and electricity consumption
On average, the total theoretical primary energy use seems to be in accordance with actual primary energy consumption but when looking at more detailed data, one can see that the contribution of gas to the actual primary energy is much lower than in the theoretical primary energy and that the contribution of electricity is opposite — higher in the actual than theoretical primary energy. The two effects cancel each other out so that in terms of total primary energy, the theoretical consumption seems to be well predicted. Furthermore, the analyses showed that the variation in electricity consumption is marginal across label categories. This together with the fact that most Dutch dwellings are heated with gas made us focus exclusively on gas consumption in the rest of the thesis. Whereas it is clear that theoretical electricity consumption is much lower than actual since it does not account for appliances, however, it is much less obvious why gas consumption is on average so much lower in reality than according to theoretical calculation.
Performance gap in relation to energy label
The discrepancies in gas consumption were the largest in the poorest performing dwelling, where theoretical consumption surpassed the actual almost twice, which we also referred to as overprediction. On the other hand, well performing dwellings consume roughly 20% more gas than predicted. Theoretical electricity consumption was at least twice lower than actual in all label categories, due to the fact that actual consumption takes into account electricity use of appliances and theoretical does not. Actual and theoretical electricity consumptions seemed to be rather constant with regard to the label class. Primary energy consumption is a sum of consumption of gas and electricity in MJ for each label class where the efficiency of the electricity generation and of the network was taken into account as well as the heating value of gas burning. The theoretical primary energy use is dominated by gas consumption, since electricity is a relatively small fraction of primary energy use due to exclusion of the household appliances. The relation between actual and theoretical therefore remains similar as seen in gas consumption. For poor label classes, the theoretical consumption is overpredicted by about 30% and for good label classes it is underpredicted for roughly the same percentage.
Electricity consumption does not seem to depend on the energy performance of the dwelling. Moreover, the end uses of electricity included in actual and in theoretical consumption are different to an extent that renders a comparison meaningless (as the theoretical excludes appliances). Therefore the main focus of the thesis was gas consumption, which is also the predominantly used fuel for heating homes in The Netherlands.
Performance gap in different samples
The performance gap was analysed in four different datasets of varying size. All datasets provided very comparable results regarding average actual and theoretical consumptions across label categories. A closer analyses shows that the actual gas consumption has been dropping steadily within label categories A, E, F and G from 2010 till 2012. Theoretical gas consumption remained roughly the same in these years, which means that the performance gap has increased slightly.
Moreover, it was found that the dwellings which had no renovation measures applied and remained unchanged from year 2010 till 2012 still exhibit a 3,5% decrease in gas use between 2010 and 2012, which shows that the decrease detected in the fours studied samples is not due to sampling bias. This decrease could be a consequence of a changing household composition (smaller number of people per household) or a decreased use of gas for cooking, however, both these phenomena’s occur at a pace smaller than 3,5%. Other factors which could be responsible for this decrease could be the changing calorific value of gas and/or the method for the calculation of standardized annual consumption.
Performance gap in relation to dwelling type, floor area and installation types
The analyses showed that floor area does not affect the performance gap strongly. In terms of dwelling type, semi-detached houses have the highest performance gap, followed by flats with a staircase entrance, detached houses and finally, gallery flats. The performance gap differed also in dwellings with different installation types. Dwellings with a local heater in the living room (gas stove) had the highest performance gap, followed by a combined boiler with η<83%, and then each higher efficiency boiler had a smaller performance gap. Energy reduction targets for built environment and actual reduction potential of the dwelling stock and of the individual dwelling renovation measures
Theoretical and actual achievability of the current targets
A scenario analyses was conducted in the third chapter. The baseline scenario was the scenario described in Covenant Energy Savings Housing Associations Sector’ (Convenant Energiebesparing Corporatiesector, 2008), which aims is to save 20% gas consumption by 2018 by improving the dwellings to a B label or at least by 2 label classes. The refurbishment scenario of the mentioned agreement was one of the scenarios considered. Another, more radical refurbishment scenario was renovating the whole dwelling stock to label A. The two scenarios were tested on both baseline consumptions, actual and theoretical (Figure 4). It turned out that by using theoretical gas use as baseline, the least radical scenario is enough to ensure the potentials discussed in B.1 are fulfilled. However, if actual gas consumption is used as a baseline, most of these potentials seem unrealistic (exception is the 10% potential as defined by IDEAL project). This points to the fact that analysts as well as policy makers rely on theoretical gas consumption as a basis for future consumption estimates, which ultimately leads to unrealistic reduction targets and renovation plans.
Differences between the theoretical and actual reductions in dwellings where different renovation measures were applied
Longitudinal data of dwellings energy performance was used to identify renovated dwellings and analyse their energy consumption before and after the renovation. The results showed that most of the renovations are expected to yield larger reduction than what materialises, many times the realised saving is about half of the expected. On average in all renovated dwellings, actual gas reduction is about a third lower than expected, however, there are big differences in the reductions of individual measures. Improvements in efficiency of gas boilers (space heating and hot tap water) yield the biggest energy reduction, followed by deep improvements of window quality. Improving the ventilation system yields a relatively small reduction compared to other measures, however, it is still much larger than theoretically expected. The measures achieving the most reduction are drastic improvements of window quality and an improvement of the efficiency of heating and hot tap water system (not a replacement of a local system). These are averages and the reductions for specific changes vary considerably. Measures that achieve an actual reduction higher that the theoretical seem to mostly be very modest improvements of insulation or window quality. Also notable is the underprediction of the reduction in dwellings where natural ventilation was replaced by mechanical exhaust and it is questionable whether such dwellings still have a sufficient quality of indoor air after the renovation. Causes of the differences between actual and theoretical gas consumption
Explaining variation in gas use with dwelling, household and occupant characteristics
Regression based on socioeconomic data showed that explaining the actual gas consumption or the difference between the actual and theoretical with the publicly available variables yields a relatively low R2 value (in view of existing literature these R values are not low) of 50,5% and 44,0%, respectively, meaning that 50,5% of the variance could be explained by these factors. Since our dataset contained many records, this relatively low explanatory power was thought to be due to the fact that many factor that do influence actual energy use, such as indoor temperature or presence of occupants, were not included. In the regression based on the survey data, these factors were included, but still not much more variation could be explained, probably due to a smaller sample size than was the case with socioeconomic data. The total R2 values were 23,8% for actual gas use per m2 as dependent variable and 40,9% for DBTA (difference between the theoretical and actual consumption) per m2 as dependent variable. In both regression analyses, the majority of explanatory power for the DBTA came from dwelling characteristics. Household and occupant mattered less, although it was clear that the occupant behaviour data provided by the survey had a non-negligible predictive power for actual gas use per m2 of 9,1%. The fact that dwelling characteristics dominate the performance gap emphasises the importance of the assumptions made in the calculation method.
Besides the regression analyses for the total sample, the model was tested on under and for overpredictions separately, since the hypothesis was that these two phenomenon would be explained by different variables. There was a large difference in the amount of variation that could be explained by all available variables in these two samples. In the underpredicted set of data 19,9% of variation could be explained by occupancy presence patterns, presence of a programmable thermostat and water saving shower head. On the other hand, in overpredictions as much as 50,8% of variation was accounted for by dwelling and installation type, age of the building, floor area, and indoor temperature. Furthermore, reported comfort was a significant predictor only in overpredictions.
The results demonstrate the difficulty of finding the right predictors for actual
gas consumption. In the future both survey and socio demographic data could be combined to maximize the results, large samples should be used to ensure statistical significance and certain variables should probably be monitored in order to avoid survey bias. This includes variables like presence at home, indoor temperature an ventilation practices, since it seems that respondents might not be aware of their patterns well enough.
The relation between the performance gap and the normalised assumptions
Since the regression analyses did not cover the effect of variables such as indoor temperature, insulation quality, internal heat load etc. and this data was not available at that time, sensitivity of the theoretical calculation for certain parameters was conducted to fill this gap. Results showed, that an indoor temperature 2,7 degrees higher than assumed by the method currently (18 degrees) can explain the performance gap observed in label A and an indoor temperature 5,6 degrees lower than 18 degrees can account for the gap in label G. Both these temperature deviations are realistic, since people in well insulated dwellings probably heat their house more due to the small increment this causes in their monthly bill. Moreover, the installation system itself might be encouraging the occupants to heat more or less with for example low temperature floor heating installation in case of A labelled dwelling and with a local gas stove placed only in the living room in case of dwelling G. In the normalised calculation, all rooms are assumed to be heated. Heat resistance of the construction elements also had a big impact which demonstrates that in case of a poor inspection, the dwelling consumption could be very faulty due to an inaccurate estimation of insulation. This likely occurs in many old dwellings, where documentation is not available. Small increments in ventilation rates (up to 40% smaller or larger than current assumption) can also explain the performance gaps in label classes A to C. The two variables which had a smaller impact were the number of occupants and internal heat gains.
Longitudinal study confirmed the significant influence of insulation value by showing that the largest performance gaps appear in dwellings with poor envelope insulation, followed by those by poor window insulation. Considerable gaps appeared also in cases of heating installation of low efficiency.
A better model for theoretical gas consumption
Besides the exploratory regression analyses two other regression models were conducted in order to see whether the current theoretical consumption can be adapted with the new knowledge about the actual gas use. One model was made for under- and one for overpredicted consumptions. These models consisted of actual gas use as the dependent variable and theoretical gas consumption plus all other dwelling related features as predictors. The idea was to obtain the best possible theoretical consumption using only dwelling parameters so that the result could still be comparable among the dwellings. In the future, this could allow for determination of a more accurate dwelling consumption based only on dwelling parameters and average actual consumption data. For overpredictions, the model explained 33,8% of variation with installation and dwelling type being the significant variables (besides theoretical gas use). The explained variation was lower than for underpredictions, where it reached 60,0%, probably because the gap itself is much larger in overpredicted dwellings than in underpredictions.
The B coefficients obtained in these two models were then applied onto a different sample to see if a better predicted theoretical consumption could be obtained by adjusting the current theoretical use with the newly obtained parameters. The new theoretical consumption was indeed much closer to the actual gas use, which proves that this method could be used to obtain a better estimate of theoretical consumption.
Conclusion
There is a clear gap between actual and theoretical consumption in Dutch dwellings. Low performing dwellings tend to have a theoretical consumption much higher than actual, while high performing dwellings feature the opposite trend. These discrepancies are understandable at the level of individual dwellings and arise due to the standardizations made when calculating the theoretical consumption, however, on the level of the dwelling stock such a discrepancy is misleading and can lead to inaccurate policy reduction targets and sends wrong signals to several stakeholders (local governments, construction industry, renters and buyers etc.).
Regarding the causes of the discrepancies, they can party be explained by the features of the dwelling itself, meaning that the calculation model does not represent the reality accurately. However, a part of the discrepancy originates in the behaviour of the users and this part is difficult to quantify statistically. The results seem to indicate that underprediction is more difficult to explain and therefore probably more dependent on occupant practices than on the accuracy of the standardisation model. Overpredictions on the other hand, seem to have a lot in common with the fact that installation systems and the dwelling itself perform differently than expected. A methodological improvement seems to be more appropriate for the overpredicted cases while at the same time tackling the fact that occupants of these dwellings are likely to feel cold. For underpredictions on the other hand, changes to the methodology would mean accepting that a higher heating intensity is inevitable in efficient dwellings. While this should be further researched in the future, behaviour incentives that would encourage people to use their homes more wisely and not waste energy could be more successful.
The label calculation is easy to use and can be, as shown in the thesis, a very valuable tool for following the energy efficiency of the dwelling stock. Since the accuracy of theoretical gas and electricity calculations can easily be improved, it is a pity to miss the opportunity to do so. Several recommendations for further research and policy development were proposed regarding the methodology for the calculation of theoretical consumption. Examples of this are a revision of several standardised factors, revision of method for determining the insulation values on-site and introduction of correction factors based on actual consumption statistics. Moreover, labels that are issued should be accurate and reliable, meaning that more attention should be paid to the quality of inspections and the robustness of the software used for label calculation.
This thesis demonstrated that research on the relationship between policy instruments and their effects is crucial to ensure the effectiveness and a continuous improvement of these tools. Theoretical models, such as energy labelling, are often used to support policy decisions. As was shown, such models do not always provide results that correspond to reality, and in the case of dwellings a big reason for this is disregarding the user, who seems to adapt to the thermal quality of the house itself. However, as was demonstrated, there is a clear need for a more accurate estimation of consumption on a broader, dwelling stock level in order to enhance the effectiveness of the current renovation policies. moreover, showed that a better estimation is feasible. The thesis showed that using the current knowledge and data availability, there is few reason not to reduce the performance gap and predict the dwelling consumption more accurately
Energetic Communities: Planning support for sustainable energy transition in small- and medium-sized communities
Get PDFThe necessity for transition in the energy sector is beyond dispute and high on the political agendas. Climate change, the depletion of fossil fuels and the vulnerability of economies to resource speculation and unreliable political systems in the producing countries lay path for a broad implementation of smart alternative solutions. This means the integration of more sustainable renewable energy sources in the existing supply structures or the displacement of existing systems by new ones. Cities and communities are central players in the energy transition process. Energy demand is determined by the built environment. Renewable energy production needs space. The conflicts between different interest groups often break out in the context of local implementation measures that affect urban planning and the appearance of landscapes.
Small- and medium-sized communities might prove to be game-changers in the overall energy transition because many problems have to be solved within their ambit. Urban planning is dealing with the numerous processes of urban change. Energy is a fairly new task to be addressed and many stakeholders lack experience and criteria for strategic decision making. After a period of fierce determination to turn the wheel against climate change, it seems that there is a growing resignation among politicians, planners and the public because some things have not turned out the way we’d expected and the hope for quick solutions fades. Rebound-effects seem to eat up the savings to a good extent, and alternative ideas of how sustainable energy systems may be put into place have not yet been persuasive in many cases. Energy systems have proved to be complex. They are still perceived to be important but in practice there is a growing uneasiness about the right steps to take. The overarching research question of this thesis is: What do decision makers in smalland medium-sized communities need to become more successful in implementing energy transition processes? For the research project this general question was broken down into four primary research questions:
How can communities anchor and monitor long-term energy transition visions in their communal development plans?
What tools and models are available for urban energy system analysis?
How can tools and models be adapted to the specific demands and boundary conditions in the case study communities to ensure long-term implementation of appropriate technologies and measures?
How does the practical implementation of the adapted tools work in the case study and what barriers must be overcome for long-term success?
To answer these questions a combination of review of the current state of scientific literature of the thematic field with a practical application and evaluation of ‘real’ implementation projects was chosen. This appears to be a beneficial approach to scientific research in planning disciplines. The first research question is closely connected to urban planning and strategy. To anchor energy transition goals in these disciplines the potentials and consequences of political energy visions were studied. To monitor developments and progress existing indicator systems were reviewed and adapted to the needs of small- and medium-sized communities. For this overall target-definition the question of 'Exergy Thinking' in planning urban environments and energy systems was discussed. This basically means to create a deep understanding of the quality aspects in energy demand and supply systems and to be aware for better matching solutions. This approach opens many options for the integration of renewables in the heating and cooling supply. It showed that the definition of a clear long-term target or 'energy vision' supports the implementation of measures because it facilitates communication and controversy.
The large number of available tools and scientific methods for the analysis and optimization of communal energy systems was reviewed to answer the second research question. The results from this work mainly led to the one central challenge that has to be solved whenever complex modelling and strategic decision making are affected: Data. Data describes the status-quo and gives necessary information on the complex system interactions and influence factors. The options to create a concise data framework for the central objective were addressed in two steps. From literature, existing models and approaches general data frameworks were collected and summarized. Since the method was to be applied to the test case study the data was validated and tested under the case study conditions. This showed deviations and necessary specifications but as well a good analogy to the default data. From this a transparent and adjustable spreadsheet-model was developed to create scenarios for the case study and to answer the fourth research question. To create a holistic picture of the communal energy system and the effects of increased exploitation of renewables geographic information systems (GIS) show very valuable functionalities. Especially since the processing and interpretation of geographic information is anchored in urban planning disciplines and creates an easy access if energy system information is integrated. The open data architecture of GIS allows the integration of different data types as long as they have a spatial correlation. This enables to retrieve valuable results from a scenario model even with rather fragmented and incomplete data. To show the effects of different implementation strategies represented by the different 'energy visions' three energy scenarios were run for the case study. These three scenarios represent central 'beliefs' or ' approaches' in energy transition as well as overall development indicators and specific local aspects. Therefore the success of energy transition measures remains limited if not all essential development parameters take a favorable course.
The scenario evaluation shows some interesting results and shows the principal usability of the approach and the model. The base-case scenario shows that the community already reaches good results for the global energy indicators because of the existing measures. On a medium and long-term these measures are not sufficient though to stay on a good course. Especially the long-term developments in some cases produce unexpected results. For instance the rather unfavourable development of CO2-emissions in the renewable energies scenario was not a predictable result at first glance. Here the effects of the chosen technologies and the effects of superior developments show their impact. As well the huge impact of the assumed efficiency measures was somewhat unexpected. Even though the assumed refurbishment rates do not exceed national recommendations and the efficiency qualities are far from passive-house standard, the efficiency scenario shows the fastest and best results for the global environment indicators. This can be explained by the fact that the demand reduction optimally complements the existing renewable energy strategy and can show its full potential in this combination. The results of the smart-city scenario show the expected and desired trends of a moderate and balanced long-term strategy that leadsto a slower but continuous positive development in all the analysed energy system indicators. The long-term trends of the scenarios and the effects of following ‘plain’ strategies can be visualised well with the model and the developed scheme. Therefore the initial research questions can be answered positively. The framework gives good and useful results and offers many options for future extension. Certainly the next and most important aspect to include into the framework is the question of costs and economic effects. The overall investment and operational costs for the measures in the different scenarios will be very different. Efficiency measures especially in the existing building stock are costly while the costs for PV-plants will most probably further decline. This is certainly a shortcoming for the efficiency scenario. A future study could as well look at overall economic effects of the different strategies for the benefit of the community. Basic figures on the economic effects of renewable energy systems are already available (Hirschl et al. 2010) and could be implemented. This would certainly make the framework more beneficial for communal stakeholders. The model is transparent and simple enough to go this way in the near future and the achieved results of this thesis project are a good basis for this. The realisation of energy systems as sketched in the smart cities scenario still demands some changes in the regulatory boundary conditions and some new technologies mainly in the information and communication technologies. Smart and electricity grid compatible buildings which can contribute services in grid stability are an issue still to come and contribute to the integration of renewable electricity. The integration of renewable heat in communal supply systems is a big future opportunity to realise LowEx potentials in the heating and cooling sector. Stakeholders in small- and medium-sized communities should be encouraged by the outcomes of the thesis to take initial steps on the energy transition path, since the results that can be reached with state-of-the-art technologies are very encouraging. Energy transition on a large scale depends on the local implementation. Despite the fact that public and scientific focus and attention is mostly on the megacities, it will be the countless small initiatives that will turn the tide
Evidence-Based Design in Nederlandse ziekenhuizen: Ruimtelijke kwaliteiten die van invloed zijn op het welbevinden en de gezondheid van patií«nten
Get PDFSubject
Evidence-Based Design in hospitals.
Problem
What role can Evidence-Based Design have in the design of better hospitals?
Purpose
To determine spatial (or: concrete) qualities, scientifically proven to have a positive influence on the health and well being of patients and staff, in order to offer the architect a helping hand for designing better hospitals. These measures are drawn from research that has been done in the framework of Evidence-Based Design (EBD), which can be perceived as the scientific variant of the healing environment.
Relevance
In the Dutch media the term healing environment is often used by architects, representatives of hospitals and researchers. Everyone provides their own content (colour, nature, treatment, hospitality, etc.) to this collective concept. The determination of concrete design elements, with a proven positive effect for patients, can contribute to the design of better care environments.
Method and approach
Literature research and case studies.
EBD → elements → checklist → case studies in field research
↑ ---------- analysis ---------- ↑
Spatial measures were selected from scientific articles from Evidence-Based Design research that are applicable for an architect. Only those measures were selected for which the effect has been proven sufficiently. The selection was based on scientific articles that have been validated by EBD expert teams. The measures in this study cover waiting rooms, consultation rooms, nursing departments, patient rooms and day treatment areas.
The measures have an effect on:
A positive contribution to the health of patients (chapter 3);
A positive contribution to the well being (less anxiety, stress) of patients (chapter 4);
A positive contribution to the efficiency and effectiveness of staff (chapter 5).
The literature research gives information on how physical environmental interventions can contribute to the problems of the patient (such as lack of sleep). The selected measures are gathered in a checklist. This checklist gives an overview of all the validated spatial measures (from chapters 3, 4, 5). In the checklist it becomes clear which spatial measure can contribrute to which positive effects.
Some aspects are more significant than others because they contribute to many problems (such as the one-person patient room); others appear just once and contribute to just one aspect. The application of EBD in recently built Dutch Hospitals has been studied using this checklist in the case studies. In the field research (chapter 7) nine recently built Dutch hospitals (Orbis Medisch Centrum Sittard, Isala Klinieken Zwolle, Meander Medisch Centrum Amersfoort, Jeroen Bosch Ziekenhuis Den Bosch, Flevoziekenhuis Almere, Maasziekenhuis Boxmeer, Deventer Ziekenhuis Deventer, Bright Sites VUMC Amsterdam, Alexander Monro Kliniek Bilthoven) were visited. Using the checklist the analysis is carried out as to whether EBD elements are used and if so how they are applied.
The goals of the case studies are to gain understanding of:
The degree to which, and the way in which, the selected measures are applied;
The consequences for the architectonical quality.
The case studies want to answer the following questions:
Does the frequent use of terms such as healing environment indeed reflect the application of design elements that have been scientifically proven?
If certain aspects derived from EBD are applied, in which way is this done?
This study has disregarded the extent to which the aimed effects of the measures, as attributed in the literature, are evident when these measures are applied in reality in the hospitals.
A characteristic of this study is the fact that it has been done from the field of architecture.
Design qualities are studied. For each case study the design drawings from the architect were retrieved and studied, and the hospital was visited. Also for every case study an interview was held with a staff member of the hospital and with the architect. The media was searched for each hospital from the field research to determine whether the hospital or architect mentions the healing environment. In chapter 8 all the gathered data from the cases are compared.
The question about architectural quality is relevant from the perspective of the architect. EBD gives little information about the quality of the architecture for the architect. EBD states that there are too few research studies about design. Most starting points are found in the paragraph ‘interior’ (such as variation and differentiation). Roger Ulrich writes in a few articles about an aesthetically pleasant environment, a hotel-like interior and being well decorated. In this he understates the importance of the quality of the design.
Just sometimes he remarks about the use of colour, avoiding cheap furniture and the use of adequate lighting. For the architect design is important. For this reason, during the field research the design of the spaces was also observed: the analysis is not limited to the aspects derived from Evidence-Based Design. Therefore a professional analysis of architectural quality is possible. In chapter 9 the most significant aspects of architectural quality are described. In this part of the case studies vocabulary familiar in architecture and common architectural analytical methods are used. This part of the study gives information about the relationship between Evidence-Based Design and architectural quality.
In chapter 8 the conclusion is drawn if and how EBD is applied in recently built Dutch hospitals and the most significant results using the checklist are described.
Results
a checklist with all the physical measures together;
the findings of the case studies based on this checklist;
conclusions and recommendations.
The field research shows that EBD is sparely used in many spaces in hospitals:
Daylight and view. It was remarkable that in most hospitals many rooms are walled in, especially consulting rooms in outpatient areas. It also happens frequently that patients in rooms (for example day treatment), due to the interior design or the placement of furniture, cannot look outside.
Nature. In almost none of the case studies was there an easy accessible (patio) garden that staff and patients can use.
Patient room. More than half of the cases have the majority of patient bedrooms with shared bathrooms. Day treatment areas and multi occupancy patient bedrooms have, in almost all cases no design solutions that contribute to privacy, control, positive distraction or social support.
Interior. Many spaces in the hospitals from the field research where patients and staff stay a long time have an institutional character. Rooms with an institutional character do not offer the possibility for control or positive distraction to the patient due to a lack of variation and differentiation in colours, materials, lighting and furniture. Also there is in none of the hospitals any art in rooms where patients stay a long time and need positive distraction. It is frequently the case that equipment and necessities do not have an obvious location or that no possibility is offered for putting equipment etc. in a cupboard. This contributes to the fact that many rooms are chaotic and unattractive.
From the field research we can learn that EBD gives few concrete measures for design. A few EBD measures are important for architecture but they do not give actual rules for the design. The architect designs the totality of functional, programmatic and esthetic aspects of the brief of requirements. This study shows that the quality of the design is indeed important. EBD stands not in the way of architectural quality and architectural quality is no obstruction for the use of EBD.
Commentary and recommendations
The functional and programmatical measures from EBD provide the architect with information to design better hospitals. The recommendations that EBD provides for design are also valuable. The field research showed that still many measures from EBD are not applied in hospitals. It is recommended that hospitals and architects take note of EBD in order to realise the positive effects for patients.
In the field research an often-heard complaint was that the scientific basis of hospital design is insufficient: more EBD is needed. It is recommended that during the design and building process of a hospital attention is given to research (for example Post Occupancy Evaluation) in order to contribute to the body of knowledge of the positive effects of the 3. The field research showed that the quality of architecture is important in the experience of users and patients. It is recommended that more attention be given to architectural quality in the hospital environment. I also advise that the client gives more attention and is more involved in the design. The client can play a strong role in creating architectonical quality and making a better hospital environment
Technology campuses and cities: A study on the relation between innovation and the built environment at the urban area level
Get PDFThis thesis examines the development of technology campuses as built environments and their role in stimulating innovation. Technology campuses entail a variety of built environments developed to accommodate technology-driven research activities of multiple organisations. The science park is the most common type of technology campus. Other types include the campuses of universities of technology and corporate R&D parks.In industrialised countries, the demand for developing technology campuses to stimulate innovation has been growing in line with the attention given to knowledge in global, national and regional policies. There are over 700 technology campuses worldwide occupying hundred thousands of hectares in- and around cities. This type of built environments have emerged and developed during critical periods of technological advancements throughout the 20th century, to support technology-based development in industrialised countries. With the adoption of the knowledge- based economy, governments in many countries have encouraged research as an essential activity in their science, technology and innovation policies. The infrastructure that supports research is also gaining momentum. The number of registered science parks is steadily increasing since the late 1990s. The number of programmes supporting research infrastructure is growing in the European policy agenda. Municipalities are formally engaged with other public and private parties in the development of urban areas targeted to stimulate innovation. Governments, universities and R&D companies are investing billions of euros in developing the infrastructure that will not only support their core processes, but will help them to remain competitive by attracting and retaining the best talent. Part of these investments are targeted to develop new buildings or entire areas that often result in campuses as we know them: a concentration of buildings accommodating organisations, people, and their activities in a (green) field.The assumption that the concentration of research activities in one location stimulates innovation is promoting the development of technology campuses in many places. However, the capacity of these built environments to support the different processes associated with innovation is not well understood — i.e. Technology campuses are urban areas in the inner city and peripheral locations that have the capacity to support the processes of knowledge creation and diffusion, as well as of attracting and retaining knowledge workers. The existent knowledge about the relationship between the built environment and innovation at the area level is limited. This knowledge gap may lead to inefficient use of the resources employed to develop technology campuses including capital, land, and time. Also, this lack of understanding can have the opposite effect, because technology campuses could easily become problematic areas dealing with vacancy, poor spatial quality, and connectivity issues frustrating the societal goal of attracting and retaining talent in the knowledge economy. A potential way to address these problems is outlining the ways in which the built environment stimulates innovation in technology campuses.In this context, this research addresses as main question ‘How does the built environment stimulate innovation in technology campuses?’ This research is grounded in the field of corporate real estate management and its theoretical assumption that the built environment is a resource managed to support the goals of organisations. Research in this field has focused on the practice of real estate management from the end user’s view. Campus development is a comprehensive form of this practice, because it deals with activities that vary from developing real estate strategies, developing building projects, up to maintaining and managing the portfolio of an organisation. The relationship between innovation and the built environment has been addressed before in theories of corporate real estate management in a broad sense. Empirically, this has been explored on the supply side at the level of the workplace rather than at the urban scale. Although the contemporary discussion of innovation in complementary research fields focus on the urban level. Onthe demand side, the involvement of public and private parties in the development of these areas moves forward the organisational scope in corporate real estate management beyond the end-users in large scale built environments.This research provides an understanding of the relationship between the built environment and innovation at the area level. This research developed knowledge clarifying such relationship in the form of a conceptual model and recommendations for practitioners involved in the practice of campus development. This knowledge developed mainly throughout an inductive approach in two core studies. The first study is an exploratory research that uncovers and positions the link between innovation and the built environment by using inputs from theory (literature review) and empirical evidence (qualitative survey of 39 technology campuses). In this stage, the link between innovation and the built environment is provided in a form of a conceptual framework containing the proposition that the built environment is a catalyst for innovation. The second study is an explanatory research that clarifies the relationship between innovation and the built environment based on empirical evidence in the practice of campus development (theory building from case studies). In this stage, the theoretical constructs of the conceptual framework are applied and revised through the in- depth study of two cases in particular contexts (i.e. High Tech Campus Eindhoven in the Netherlands and the Massachusetts Institute of technology campus in the United States). As a result, the preliminary knowledge from the exploratory research was developed into a conceptual model bearing a hypothesis and five propositions closely linked to empirical evidence.The answer to the main research question is that the built environment is a catalyst for innovation in technology campuses demonstrated by location decisions and interventions facilitating five interdependent conditions required for innovation. The following propositions explain how the built environment facilitates each of the five conditions for innovation:
Location decisions and area development facilitate the long-term concentration of innovative organisations in cities and regions.
Interventions enabling the transformation of the built environment at area and building levels facilitate the climate for adaptation along changing technological trajectories over time.
Large-scale real estate interventions facilitate the synergy among university, industry and governments.
Location decisions and interventions supporting image and accessibility define the innovation area by emphasising its distinct identity, scale and connectivity features.
Real estate interventions enabling access to amenities increase the diversity of people & chances for social interaction regardless the distinct geographical settings in which the concentration of innovative activities takes place.
This research acknowledges that the location decisions of some technology-driven organisations have coincidentally determined the concentration of innovative research activities in particular places. Over the years, the accommodation of the research activities of these organisations has co- evolved with particular socio-economic processes in their hosting cities creating unique conditions for innovation. The concentration of innovative organisations can be considered as a primal condition enabling the co-existence of the other four conditions for innovation. Similarly, this research acknowledges the following interventions facilitating conditions for innovation at the area level and depending on the particular location characteristics in which each campus has developed:
Transforming areas through urban renewal and redevelopment,
Building, adapting and re-using flexible facilities,
Implementing the shared use of facilities accommodating different functions and users,
Developing physical infrastructure enabling access to amenities and connection between functions
Developing representative facilities and area concepts that support image.
The empirical evidence supporting the propositions in the model is structured and converted into information available to decision makers involved in the development of technology campuses in the form of tools. The so-called ‘campus decision maker toolbox’ provides instruments that can guide planners, designers and managers during different stages of campus development. The tool for planners comprises campus models to frame the campus vision during the initiation of the campus based on location characteristics. The tool for designers consists of alternatives to enhance the campus brief during the preparation of the campus. And the tool for managers contains an information map to steer the campus strategy during the use of the campus.This knowledge contributes to the existing understanding of the relationship between innovation and the built environment in theory and practice. In theory, this research adds to existing theoretical concepts connecting the fields of corporate real estate management, urban studies in the knowledge- based economy and economic geography. The conceptual model proposed a new combination of existing theoretical concepts addressing a new way to look at the relationship between innovation and the built environment. In practice, this understanding is expected to encourage the efficient and effective use of the many resources required to develop technology campuses. Particularly, by providing information that can help decision makers to steer such resources towards strategic decisions and interventions that -under certain conditions- facilitate innovation. The knowledge developed in this research clarifies a relationship between innovation and the built environment at urban area level, in which the built environment facilitates conditions for innovation
Imagine: Rapids
No full textProcesses of construction are related to available technologies of production and assembly. IT has made a deep impact on design possibilities and the control of production logistics, enabling feats such as freeform architecture and increasingly precise elaboration. Alternately, the idea of Rapid Prototyping and Rapid Manufacturing Technology provides the chance to create one-off components and elements for architecture. We now have the opportunity to design and construct without the disadvantages of production resistance and assembly needs - to realise genuine IT-driven architecture
AM Envelope: The Potential of Additive Manufacturing for facade constructions
Get PDFThis dissertation shows the potential of Additive Manufacturing (AM) for the development of building envelopes: AM will change the way of designing facades, how we engineer and produce them. To achieve today’s demands from those future envelopes, we have to find new solutions.
New technologies offer one possible way to do so. They open new approaches in designing, producing and processing building construction and facades. Finding the one capable of having big impact is difficult — Additive Manufacturing is one possible answer.
The term ‘AM Envelope’ (Additive Manufacturing Envelope) describes the transfer of this technology to the building envelope. Additive Fabrication is a building block that aids in developing the building envelope from a mere space enclosure to a dynamic building envelope.
First beginnings of AM facade construction show up when dealing with relevant aspects like material consumption, mounting or part’s performance.
From those starting points several parts of an existing post-and-beam façade system were optimized, aiming toward the implementation of AM into the production chain. Enhancements on all different levels of production were achieved: storing, producing, mounting and performance.
AM offers the opportunity to manufacture facades ‘just in time’. It is no longer necessary to store or produce large numbers of parts in advance. Initial investment for tooling can be avoided, as design improvements can be realized within the dataset of the AM part. AM is based on ‘tool-less’ production, all parts can be further developed with every new generation.
Producing tool-less also allows for new shapes and functional parts in small batch sizes — down to batch size one. The parts performance can be re-interpreted based on the demands within the system, not based on the limitations of conventional manufacturing. AM offers new ways of materializing the physical part around its function. It leads toward customized and enhanced performance.
Advancements can for example be achieved in the semi-finished goods: more effective glueing of window frames can be supported by Snap-On fittings. Solving the most critical part of a free-form structure and allowing for a smart combination with the approved standards has a great potential, as well.
Next to those product oriented approaches toward future envelopes, this thesis provides the basic knowledge about AM technologies and AM materials.
The basic principle of AM opens a fascinating new world of engineering, no matter what applications can be found: to ‘design for function’ rather to ‘design for production’ turns our way of engineering of the last century upside down. A collection of AM applications therefore offers the outlook to our (built) future in combination with the acquired knowledge.
AM will never replace established production processes but rather complement them where this seems practical. AM is not the proverbial Swiss-army knife that can resolve all of today’s façade issues! But it is a tool that might be able to close another link in the ‘file-to-factory chain’. AM allows us a better, more precise and safer realization of today’s predominantly free designs that are based on the algorithms of the available software. With such extraordinary building projects, the digital production of neuralgic system components will become reality in the near future — today, an AM Envelope is close at hand. Still, ‘printing’ entire buildings lies in the far future; for a long time human skill and craftsmanship will be needed on the construction site combined with high-tech tools to translate the designers’ visions into reality. AM Envelope is one possible result of this
Policies for Improving Energy Efficiency in the European Housing Stock
Get PDFAccording to EC forecasts, if energy efficiency could be increased 1% annually until 2010, two-thirds of the potential energy saving in the EU could be achieved. This would comply with 40% of the EU’s Kyoto obligation to reduce greenhouse gas emissions by 8% on the 1990 level by 2010-12, by cutting 200 million tonnes of CO2 emissions per year. Improving energy efficiency in existing buildings is often considered to be one of the most cost-effective ways of cutting carbon emissions. Current policy measures, however, seem to be decided with little reference to the specific needs of renovation in the housing sector instead of basing policy measures on detailed sets of requirements and actual costs. The research provides information for national governments in the EU on how to improve their sustainable building policies so as to increase carbon reductions in the existing housing stock. It addresses the question of the extent to which stronger government intervention is possible and necessary for circumnavigating barriers and the policy approaches that are likely to be feasible, effective cost-efficient and legitimate
Sustainable Solutions for Dutch Housing: Reducing the Environmental Impacts of New and Existing Houses
No full textSustainable housing construction and management has, to date, been primarily based on an intuitive approach. Numerous measures have been formulated to promote sustainable construction and to reduce the environmental impacts of the built environment. However, little is yet known about the extent of the environmental benefits thereof. Moreover, methods and tools are mainly directed to new construction. This publication makes clear that short-term environmental benefits in sustainable housing construction are rather limited. Renewal of the post-war housing stock offers excellent changes for improvement of the environmental performance of housing. With a newly developed method it is proven that renovation causes less environmental impacts than demolition followed by new construction. However, at the same time the usefulness of Life Cycle Assessment for buildings is doubted. This book is particularly interesting for scientists in the field of methods and tools for sustainable construction and management
Living with diversity in Jane-Fitch
Get PDFIn the past decades, diversity has become a popular catchphrase in theoretical, policy and public discourses in Canadian cities. Toronto is Canada’s most diverse city, wherein a long-standing immigration history coupled by the introduction of the Canadian Multiculturalism policy in the 1970s have rendered diversity a prominent value for the city’s inhabitants (Ahmadi and Tasan-Kok, 2014). Celebration of diversity has become a popular theme in Toronto’s policy and image making, such that many policy documents have proclaimed diversity as the city’s biggest strength. However, while the celebration of diversity has attracted funds and services to inner city Toronto, stereotyping based on different categories of diversity (particularly ethnicity and class) has resulted in the stigmatization and criminalization of poor racialised neighbourhoods located at the edges of the city.
Diversity in urban areas may derive from multiple factors such as behaviour, lifestyles, activities, ethnicity, age, gender and sexuality profiles, entitlements and restrictions of rights, labour market experiences, and patterns of spatial distribution. Research on diversity in the past decades has resulted in the creation of an extensive body of work on the notion. However, there are a few gaps in theory which the present study seeks to address, namely: (a) Research on diversity often overlooks the complexity and dynamic nature of diversity and maintains an overemphasis on ethnicity. (b) Despite plentiful evidence for the diversification of peripheral neighbourhoods, the available body of research focuses primarily on inner-city areas, leaving out the more remote rural and suburban areas (Humphris, 2014). (c) There is a tendency to present a ‘flat’ or ‘horizontal’ type of differentiation of diversity, which does not account for the various positions and hierarchies within and between different categories of difference.
In light of these gaps, this study seeks to add to our understanding of urban diversity, as perceived and experienced by those who inhabit, frequent and govern urban areas. It answers the following primary research question: How is diversity experienced at the neighbourhood level, as (a) discourse, (b) social reality, and (c) practice? Diversity as discourse refers to the public narratives around diversity, while diversity as social reality concerns the descriptive characteristics that render an area diverse. Diversity as practice refers to policies, programs and local practices that aim towards managing diversity (see also Berg and Sigona, 2013). The research question is investigated in four interconnected chapters, which engage with the three formerly mentioned dimensions to various degrees. The study further makes use of a variety of qualitative and participatory techniques (i.e. qualitative interviews, roundtable talks, participant observations, and focus groups) to gather rigorous empirical data on living with and managing diversity in an inner-suburban neighbourhood of Toronto, namely Jane-Finch
Balanceren tussen uitvoering en bewuste afwijking van beleid
Get PDFIn hun strategisch voorraadbeleid beschrijven woningcorporaties welke aanpassingen ze in hun woningbezit willen doorvoeren. Tegelijkertijd kan het in de praktijk soms verstandig zijn dat zij van hun beleid afwijken, bijvoorbeeld omdat er nieuwe inzichten zijn, of omdat er beren op de weg komen die je beter kunt mijden. In het proefschrift wordt ingegaan op de vraag hoe het implementatieproces van strategisch voorraadbeleid verloopt. Het bevat uitgebreide casestudies, uitgevoerd bij vier woningcorporaties, waarin meerdere uitvoeringsprojecten van begin tot eind zijn gereconstrueerd. Daarbij is in beeld gebracht welke middelen corporaties gebruiken om beleid en uitvoering met elkaar te verbinden. Ook is gezocht naar de balans tussen enerzijds het uitvoeren van voorgenomen beleid en anderzijds het bewust afwijken van voorgenomen beleid op basis van nieuwe ontwikkelingen en veranderende inzichten. De belangrijkste uitkomsten van deze studie komen samen in een balansmodel, waarmee gereflecteerd kan worden op implementatieprocessen bij woningcorporaties, andere maatschappelijke organisaties en overheden.