PLEA 2020 A CORUÑA
P la n ni n g P ost C ar b o n C it ie s
How much are initial design optimisations worth?
The importance of urban energy efficiency optimisations in early-stage design phase.
JULIA KUREK
,1JUSTYNA -MARTYNIUK-PĘCZEK
1Faculty of Architecture, Gdańsk University of Technology, Poland
2 Faculty of Architecture, Gdańsk University of Technology, Poland
ABSTRACT: In the context of predicted climate changes and shrinking natural resources there are growing appeals for most optimal energy and environmental resources management in the construction sector. However, far too little attention has been paid to urban design and comprehensive treatment of building structures, and their surroundings and lifestyle of inhabitants. The overall goal of this investigation was to find most optimal urban design solutions, lowering down energy consumption and negative environmental impact, but at the same time meeting other sustainable development and design composition goals. For this purpose, numerous design variants were created and analysed, based on collaborative work of joint international studio. Then the simulations were conducted according to the simulation tool for measuring urban energy efficiency and environmental impacts. Simulated and compared were CO2 lifecycle emissions, ecological footprint and total energy demand per capita. The results proved that in the most favourable scenario energy savings reached one thirds and the impact on the environment can be reduced by more than 70 percent. Such results translate directly into financial, environmental and qualitative benefits for potential residents. They also demonstrate the importance of optimizations performed at an early-stage conceptual design.
KEYWORDS: Urban planning, eco-cities, energy efficiency, carbon neutral cities, sustainability
1. INTRODUCTION
The goal of this research was to find the possibly carbon neutral urban design solution with minimal negative impact on the environment, meeting the criteria of affordability, energy efficiency and other aspects of sustainable development. The problem area was a district of Nowy Port located in the Polish city of Gdańsk, which is experiencing environmental, economic and social problems [1]. The district is located in the Pomeranian Voivodship, which is able to satisfy its heating energy needs only in 30 percent.
Additionally, in the district the permissible dust concentration in the air of PM10 and PM2.5 as well as sulfur dioxide [2] are regularly exceeded. Within this district dominates also low emissions - individual heating systems in the form of fireplaces and only a small number of buildings have a connection to the central heating system [3]. Due to the above facts and further planned development, this district required a special interdisciplinary design approach.
2. METHOD
The research was divided into four main stages.
The first stage concerned mainly the analysis of conditions and local problems in the project area.
These analyzes concerned on the aspects of Nowy Port and its surroundings, reconstruction,
infrastructure, land uses, development land uses, public life, characteristic local elements and possible design areas. They were presented in detail and published in Atlas 1 "Discovering of Nowy Port" [1].
Based on the results from numerous analyses, the students of architecture and spatial planning from HafenCity University Hamburg and Gdansk University of Technology created various urban design proposals as a part of international joint studio. Based on these proposals, design trends were determined with the overwhelming number of planning solutions in the given area - requiring special attention and future project engagement.
The process of classifying and selecting design trends and identifying students’ main design proposals was described in the article [4]. The most interdisciplinary spatial activities were proposed in the waterfront and port area therefore, this area became a focus of further research.
Among the proposals of both HCU and GUT students in the analyzed area dominated the housing function and broadly understood environmental activities. A lot of emphasis was also placed on services and public transport aspects. Therefore, four design solutions that met these criteria were selected for preliminary testing (Fig. 1.). In the second stage, these districts underwent preliminary calculations in
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the ELAS program. The goal of this stage was to select the most favorable design variant in terms of urban energy efficiency (energy consumption, ecological footprint and CO2 lifecycle emissions) for further simulations.
Figure 1. Stage 2: selected design variants for tests in ELAS calculator. Results of preliminary ELAS simulations.
The second stage was based on creating a series of design variants based on the international joint studio and checking their energy demand and environmental impact using the ELAS [5] simulation tool.
Then the most advantageous of the variants in terms of planning and environmental aspects was selected for further simulation.
Preliminary comparative simulations for 4 design variants were carried out assuming the passive building standard for all objects.
Figure 2. Scheme of research. Stages from 1 to 5.
The ELAS calculator measures urban energy efficiency for residential complexes expressed as total energy demand, ecological footprint, CO2 lifecycle emissions. In comparison with other techniques, this method had the advantage of respecting not only the parameters of the buildings themselves, but also their siting, infrastructure and mobility aspects along with other parameters of spatial energy efficiency.
The calculations considered the overall parameters of the building complex resulting from its functioning in the urban complex [6]. They were related to site specific data, buildings and household’s data, electricity data, municipality data and mobility data. Fig. 2 and Table 1.
Appropriate data was entered to the calculator (according to table 1), that differed depending on the adopted scenario
Figure 2: ELAS calculator scheme of work. Input and output data referring to the whole building complex.
The ELAS calculator includes interdisciplinary information about the entire building complex and its functioning in the city.
The variable was the number of buildings and their cubic capacity as well as the number of inhabitants, their life model and the type of energy used. In order to objectively compare the total energy demand, ecological footprint and CO2 lifecycle emissions results. Those results for the whole building complex were divided into the number of inhabitants. (fig. 1.)
Calibration data was an extensive part of this work due to the multitude of parameters analyzed. The main parameters analyzed are contained in table 1 below.
Table 1
ELAS input data for the parts 1,2,3,4 and 5.
PART 1. SITE SPECIFIC DATA Site Nation
Inhabita nts
• Number of inhabitants of municipality/city
• Number of inhabitants of district
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Degree of Centrality
From the locality as a starting point, the distance [in km] to the closest locality that provides at least one of the following facilities
Theater, concert hall, university
• Specialized shops, high school or vocational school
• Branch bank, medical specialist, secondary school
• grocery store, primary school
PART 2. BUILDINGS AND HOUSEHOLDS DATA
Building structure
• Building energy standard (i.e. passive house)
• Building type (i.e. multi-story building)
• Total living space [m2]
• Insulation (i.e. ecological/mineral/ fossil insulation)
• Number of buildings
• building lot area [m2]
Residents • Number of households
• Number of residents
• Age pattern of residents (according to national statistics)
Space Heating and Hot Water Supply
Space Heating
Energy rating of a building: number [kWh / (m2 · Year)]
Total space heating demand: number [kWh / Year]
Hot Water Supply
Hot water demand per person: number [kWh / Year]
Total water demand: number [kWh / Year]
technologies used to heat / provide DHW to the buildings to be constructed
Space heating supply
Hot water supply
Pellets, wood briquettes
0.00 % 0.00 %
Wood chips 0.00 % 0.00 %
Log wood 0.00 % 0.00 %
Solar thermal 4.00 % 4.00 %
Heat pump, compact heating unit for passive houses
4.00 % 4.00 %
Electric heating 1.00 % 1.00 % District heating
(biomass)
23.00 % 23.00 %
District heating (e.g.
gas, waste incineration, fossil oil)
24.00 % 24.00 %
Natural gas 23.00% 23.00%
Heating oil 21.00% 21.00%
Hard coal 0.00% 0.00%
Lignite 0.00% 0.00%
Sum 100% 100%
PART 3. ELECTRICITY DATA
Electricity demand
• Electricity demand of households [kWh / Year]
• Of that, used for space heating and hot water generation [kWh / Year]
Domestic electricity production
• Number of kWh that are annually produced de- centrally from renewable resources in the settlement resp. in the building
• Number of kWh electricity are provided from renewable resources [kWh / Year]
PART 4. MUNICIPAL SERVICES AND INFRASTRUCTURE DATA
Road Network
Internal development (streets within the settlement)
• Municipal road
• Country road
• Location within town/city center (compact settlement area with) : yes no)
Road services
Number of trips per years:
• Road cleaning
• Mowing and trimming
• Snow clearance
• Sanding
• Snow pole setting
•
Street lighting
Plans to provide the settlement with lighting:
• Number of lamps
• Total electricity consumption [kWh / Year]
Sewage Treatment
• Total annual wastewater [m3 / Year]
• Link to the sewer line (yes)
• Sewage treatment of the settlement is performed by a (Central sewage treatment plant)
• Type of the technology is applied in the sewage treatment plant (i.e. Two-stage (mechanical, biological/ three-stage (mechanical, biological, chemical)
• the length in km of the sewer line between the settlement and the sewage treatment plant
• number of kilometers of sewer line have to be additionally installed [km]
• the energy consumption of the sewer pumps (if installed) for the settlement per year [kWh / Year]
Waste collection
Public solid waste collection -Waste collection point: distance in km
-Fractions of solid waste that are collected by waste disposal companies or are collected at disposal points that may be reached by walking:
• Residual waste
• Plastic
• Glas
• Tree clipping,
• lawn clipping
• Bio-waste
• Used paper
• Used metal
• Bulky waste PART 5. MOBILITY DATA
Everyday Mobility
Means of transport/ everyday mobility:
consumption number in kWh/Year:
• Pedestrian
• Bicycle
• Electric bike
• Train / commuter train
• Tram / Metro
• Bus
• Bio-gas Bus
• Trolley Bus
• Moped / Motorcycle
• Car
• Hybrid car
• Electric vehicle
• E85 car
• Natural gas car ,
• Bio-gas car
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Vacation mobility
Means of transport for vacation mobility. Vacation mobility is divided for short break vacation and main vacation:
• Electric bike
• Train/ commuter train
• Bus
• Bio-gas bus
• Car
• Hybrid car
• Electric car
• E85 car
• Natural gas car
• Bio-gas car
• Aircraft
• ship
In the third stage, the selected design option was subjected to various energy scenarios. To prove what scenario is most beneficial and to which extent urban aspects may affect final results, a series of scenarios were conducted.
The first three scenarios tested the results dependent from heating demand. The following characteristics were tested:
▪ 95 kWh/m2Year-a current and commonly used energy characteristic in Poland
▪ 40 kWh/m2Year-recognized in Poland as energy-saving
▪ 15 kWh/m2Year -a passive-house standard In the fourth stage of investigation, two scenarios for the future were made – trend scenario and green scenario in order to check the future urban energy efficiency of the project, concentrating on ecological and non-ecological model of development in the perspective of 2050.
The housing complex will be subject to dynamic development in the future, therefore the purpose of the future scenarios (4 and five) was to show how much depends on aspects of energy efficiency, renewable energy applications and the lifestyle of residents.
Both scenarios 4 and 5 assumed the same heating demand as for passive construction – that is 15 [kWh/(m2·Year)], but other future development models of the district. Trend scenario (no. 4), assumed in terms of electricity consumption 2,2 percent increase per year along with change of the electricity provision mix. In terms of mobility it was simulated an increase of total mileage of everyday mobility by 25 percent together with increase of bio- gas cars (to 10 percent) and electric vehicles (to ca.
15 percent).
Green scenario was aimed at more balanced and ecological vision for future. development. In terms of electricity consumption, it assumed a decrease of total demand by 33 percent together with 100 percent eco-electricity (from hydro power, biomass, wind). Regarding mobility, an increase of total mileage like in trend-scenario was simulated (25 percent). Moreover, bio-gas cars (70 percent) and electric vehicles (30 percent) were foreseen as
providing individual mobility. Buses were simulated as running exclusively on biogas.
3. RESULTS
The first stage research results were summarised in the juxtapositions in the article [4] and allowed for the identification of the most problematic design intervention part - located in the current unused port.
This area has become the subject of further second stage research.
The second stage results are summarised on the figure number 2. The simulations were carried out for selected urban design variants – tested were carbon dioxide lifecycle emissions, ecological footprint and total energy demand per inhabitant. The calculations for individual design variants considered not only energy consumption and the environmental footprint of the buildings themselves, but also their surroundings - the impact associated with distances to public transport, distance from services, infrastructure and other aspects according to the ELAS tool [5], [7]. The most advantageous variant in terms of energy and environmental aspect, contrary to initial expectations, was not the variant with the lowest building intensity and the smallest number of inhabitants, but the balanced one (fig. 1.).
The results of third stage of the research included energy scenarios. The variant with most favourable results was project number 3. The results regarding the energy demand of the district and its environmental impacts depending on the adopted energy demand and the future way of development are presented on the figure 1.
Table 2
Elements and output parameters included in final simulations results according to areas and categories.
Areas Categories
Total energy consumption according to areas
Space heating, hot water supply
• Solar thermal
• Heat pump, compact heating unit for passive houses
• Electric heating
• District heating (biomass)
• District heating (e.g. gas, waste incineration, fossil oil)
• Natural gas
• Heating oil
Electricity • heating and hot water
• Provided by electrical grid
• Domestic Production Municipal services • Wastewater treatment
• Road services
• Street lighting
• Waste collection Mobility
(every day)
• Pedestrian
• Bicycle
• Train / commuter train
• Tram / Metro
• Bus
• Moped / Motorcycle
• Car Mobility
(leisure/vacation)
Main vacation
• Train /
Short trip
• Train / commuter
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commuter train
• Bus
• Car
• Aircraft
• Ship
train
• Bus
• Car
• Aircraft
• Ship Building measures • Demolition
• Building addition
• New construction
• Renovation Infrastructure
expansion
• Road construction
• Street lighting
• Sewer construction
CO2 lifecycle emissions
Space heating, hot water supply Electricity
Municipal services Mobility (every day) Mobility (leisure/vacation) Building measures Infrastructure expansion
Ecological Footprint (SPI) Space heating, hot
water supply
• Infrastructure
• Non-renewable resources
• fossil resources
• Renewable resources
• Emissions to air
• Emissions to water
• Emissions to soil Electricity
Municipal services Mobility (every day) Mobility
(leisure/vacation) Building measures Infrastructure expansion
Figure 3: Simulation results of total energy consumption, carbon dioxide lifecycle emissions and ecological footprint for respective scenarios.
The results regarding the energy demand of the district and its environmental impact depending on the adopted energy demand and the scenario of future development are presented in the summary [Figures 1 and 3.].
Between the commonly used energy standard in Poland (with heating demand 95 kWh) in scenario 1 and passive-house standard in scenario 2, the energy demand decreased by 27 percent. Scenario 2 also
reduced the negative environmental impact of CO2
lifecycle emissions and ecological footprint of respectively 17 and 12 percent.
Pure energy and environmental improvements are sometimes not a satisfying argument when talking about subsidized housing, low -income community.
Therefore, it was also important in stage 5 to calculate the financial difference between respective scenarios.
Comparing the annual energy consumption in scenarios 3 and 1, the annual energy expenses can be expected to be ca. 1.32 million Euro smaller.
As initially anticipated, the most favourable future scenario for the district's development was a combination of the passive house standard with other ecological optimisations: application of renewable sources of energy and more sustainable mobility of inhabitants. According to authors calculations, it can bring savings of over 1 million Euro annually, what is particularly important due to subsidized housing and not affluent residents [3]
predominating in this district.
In scenario 5, compared to scenario 1, there was a significant 33 percent reduction in energy demand and a reduction in CO2 lifecycle emissions by 69 percent, and a reduction in ecological footprint by 75 percent. At current electricity prices in Poland (in May 2020) 1kWh costs approximately 0.55 PLN ~ 0.13€.
The difference in energy consumption between the most favourable (scenario 3) and a less favourable scenario 1 is over 10 GWh per year. This translates into financial difference of ca. ~1.64 million Euro per year for the proposed district for 5409 inhabitants.
The differences in bigger scale districts can be imaginably greater.
The most puzzling were the results of the trend scenario (scenario 4) showing the possible future needs of the building complex in the perspective of 2050 with a non-ecological way of future development. It proved that even with the use of restrictive energy-saving parameters (passive-house standard) and several urban scale optimizations, in a situation where the residents do not change the lifestyle do not reduce the demand for electricity and do not turn to renewable energy sources in all sectors the results will worsen more than in any other variant. In trend scenario, the final ecological footprint parameters of the building complex turned out to be significantly worse even than those of ordinary energy-saving standards in scenario 1 - by 6 percent.
4. CONCLUSIONS
Applying the aspects of spatial energy efficiency and considering not only building parameters in environmental calculations, but also taking into account aspects of mobility, infrastructure and
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distance from services allows for a more accurate estimation of the real impact of a building complex on the environment than traditional approach based only on balanced energy characteristic of buildings.
It is important to continue deepening the knowledge about the relationship between the impact of a building complex on the environment including all urban aspects
In the future, it is essential to turn to the principles of spatial energy efficiency, considering not only the scale of individual buildings - but entire building complexes and their surroundings, infrastructure, transport and other aspects to create more sustainable carbon neutral cities and communities.
Based on the research, conclusions can be drawn regarding future planning on the project site.
Adhering to the aspects of spatial energy efficiency and respecting not only building parameters in environmental calculations, but also considering other aspects of spatial energy efficiency such as mobility, infrastructure and maintenance allows for a more accurate estimation of the real impact of a building complex on the environment.
Contrary to popular beliefs, condensed, extremely compact building variants with the highest density and intensity of buildings are not always the best solution in terms of urban energy efficiency - total dwelling energy demand, ecological footprint and carbon dioxide lifecycle emissions as it was proved in stage three. Therefore, the preliminary simulations should always look for a variety of most optimal density and intensity of buildings – that not necessary is always the most extreme one.
The results cast a new light on the importance of balanced ecological housing development and its maintenance in the future. Even with excellent energetical parameters at start, the end result parameters referring to whole urban complex can be worsened because of unecological way of development and behavior of inhabitants. These results were proved in trend scenario. It showed that even with the use of restrictive energy-saving parameters such as passive-house standard and many other improvements, in a situation with no change in the lifestyles of residents and the use of non- renewable energy sources, the predicted results will significantly deteriorate. The results occurred to be even less favorable than in standard non-energy- saving design models.
This conclusion can be key information, especially in communities and neighborhoods where financial and environmental aspects play a key role – such as Nowy Port.
Moreover, this conclusion demonstrates the great importance of maintenance and raising awareness
among citizens for shaping healthier and carbon neutral cities and communities for the future.
The research also demonstrates the importance of interdisciplinary optimization not limited to energy efficiency aspects in the early planning phase.
The most favorable scenario for the development of the housing complex was the combination of the passive-house standard with the green scenario of district development - high energy efficiency of buildings and application of renewable sources of energy. It is central to appreciate the importance of residents' lifestyles and to include urban energy efficiency components in early-stage research, planning and calculations. Only such optimization on an architectural and urban scale will be the most effective. Improving the energy efficiency of buildings and renewable energy applications alone may not be sufficient - as this study proved.
ACKNOWLEDGEMENTS
Special thanks to all contributors and supporters of international joint studio, especially to:
Prof. Dr. Michael Koch – originator and substantive leader of the cooperation project of HafenCity University Hamburg and Gdansk University Technology
Dr Gabriela Rembarz – substantive leader of Gdansk University of Technology
Prof. Piotr Lorens, Ph.D., D.Sc. Eng. Arch. – cooperation promoter
Dipl.-Eng. M.A. Florentine-Amelie Rost – cooperation assistant, project management
Dipl.-Eng. Architect Alexandra Schmitz – cooperation assistant, project management
REFERENCES
[1]M. Koch and F.-A. Rost, Atlas 1 Nowy Port Entdecken [Discovering Nowy Port]. Hamburg, 2018.
[2]M. Zgoda, D. Bielawska, and K. Szymańska, “Stan zanieczyszczenia powietrza atmosferycznego w aglomeracji gdańskiej i Tczewie w roku 2016 [Atmospheric air pollution in the Gdańsk agglomeration and Tczew in 2016],” Gdansk, 2017.
[3]Edyta Damszel–Turek, E. Pielak, W. Szermer, A. Przyk, and B. Zgórska, “Gminny Program Rewitalizacji Miasta Gdańska na lata 2017-2023 [Municipal Revitalization Program of the City of Gdańsk for 2017-2023],” Gdańsk, 2017.
[4]G. Martyniuk-Pęczek, Justyna Rembarz and J.
Kaszubowska, “Building smartslow_slowsmart in Nowy Port- the mulidisiciplinary educational experiment of joint design studio,” sgemsocial, vol. 2367–5659, no. 2367–
5659, pp. 53–60, 2018.
[5]I. und S. 2011. T. U. und G. IRUB, “ELAS – Energetische Langzeitanalysen für Siedlungsstrukturen.” [Online].
Available: http://www.elas-calculator.eu/.
[6]G. Stoeglehner, G. Neugebauer, S. Erker, and M.
Narodoslawsky, Integrated Spatial and energy planning.
SpringerBriefs in Applied Sciences and Technology, 2016.
[7]“Energetic Long Term Analysis of Settlement Structures FACTSHEET 1. ELAS-Point of Departure.”
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