Minimizing Environmental Impact of Urban Districts with Life Cycle Assessment - Berlin Tegel Airport Complex

HafenCity University Hamburg | REAP
Material Flow Analysis and Life Cycle Assessment | WS 2015/16
Minimizing Environmental Impact
of Urban Districts with Life Cycle Assessment
Berlin Tegel Airport Complex
Submitted to / on:
Professor Gregor C. Grassl
March 31st
, 2016
Contributing Authors:
Gabriel Nießen – 6029039
Heather Troutman – 6028601

_____________________________________________________________________________________________________
REAP-M-308-100| Nießen - Troutman 2
Abstract:
The life cycle assessment of single buildings but also of urban districts becomes
more valuable over time; particularly with recent challenges in regard of the predicted
climate change. The following paper determines certain potentials for more
sustainable quarters over a lifespan of 50 years along the case study of Berlin Tegel
Airport Complex which is being under soon refurbishment. It distinguishes between
solely material matters and district scale adjustments and discusses their respecting
influences on the performance. The DGNB-LCA-tool for urban districts served as an
example tool.
Table of Contents
1. Introduction.....................................................................................................................................................4
1.1. Berlin Tegel Airport Complex ...................................................................................................................4
1.2. Life Cycle Assessment...............................................................................................................................4
1.3. DGNB LCA Tool .........................................................................................................................................4
2. Criteria for Sustainable Urban Districts...........................................................................................................5
3. Analysis of Built Area .......................................................................................................................................5
3.1. Land Use ...................................................................................................................................................5
3.2. Built Area ..................................................................................................................................................5
3.3. Materials...................................................................................................................................................5
3.3.1. Proposition of Building Materials and Areas.....................................................................................5
4. LCA Results of Proposed Design......................................................................................................................6
5. Design Optimization for Enhanced Sustainability ...........................................................................................8
5.1. Material adjustments ...............................................................................................................................8
5.1.1. Optimization 1: Wooden Window Frames........................................................................................9
5.1.2. Optimization 2: as Optimization 0 substituting EPS with Mineral Wool ........................................10
5.1.3. Optimization 3: as Optimization 0 without Insulation....................................................................11
5.2. Adjustment of district parameters.........................................................................................................12
5.2.1. Optimization 4: District Heating......................................................................................................13
5.2.2. Optimization 5: 30% On-Site Renewable Energy Generation.........................................................14
5.2.3. Optimization 6: Increased Green Surfaces .....................................................................................15
5.3. Optimization 7: Wooden Window Frames, District Heating, On-Site RE-Gen. and Increased Green
Surfaces ................................................................................................................................................................16
5.4. Comparison of all Optimizations ............................................................................................................17
6. Conclusion and Recommendations...............................................................................................................17

_____________________________________________________________________________________________________
Diagrams, Figures and Tables
Figure 1: study area: Berlin Tegel Airport (Grassl 2016)............................................................................................4
Figure 2: DGNB criteria catalogue for urban districts (DGNB 2012)..........................................................................4
Figure 3: perspective of study area: built up space and open space (own depiction, based on design proposal....5
Table 2: energy and water benchmarks (Grassl 2016) ..............................................................................................6
Table 1: environmental impact factors according (own depiction based on DGNB-tool) ........................................6
Figure 5: environmental impact factors with district specific values (own depiction based on DGNB-tool) ...........7
Figure 4: environmental impact factors with standard reference values (own depiction based on DGNB-tool) ....7
Figure 6: Ratio of district specific values to reference values for optimization 0 (own depiction based on DGNB-
tool)......................................................................................................................................................................8
Figure 7: environmental impact factors with district specific values for optimization 1(own depiction based on
DGNB-tool)...........................................................................................................................................................9
Figure 8 : Ratio of district specific values to reference values for optimization 1 (own depiction based on DGNB-
tool)......................................................................................................................................................................9
Table 3: results of Optimization 2 relative to Optimization 0 (own depiction based on DGNB-tool).....................10
Figure 9: environmental impact factors with district specific values for optimization 2 (own depiction based on
DGNB-tool).........................................................................................................................................................10
Figure 10 Ratio of district specific values to reference values for optimization 2 (own depiction based on DGNB-
tool)....................................................................................................................................................................11
Table 4: comparison of EPS, mineral wool and no insulation (own depiction based on DGNB-tool).....................11
DGNB-tool).........................................................................................................................................................12
tool)....................................................................................................................................................................12
DGNB-tool).........................................................................................................................................................13
tool)....................................................................................................................................................................13
DGNB-tool).........................................................................................................................................................14
tool)....................................................................................................................................................................14
DGNB-tool).........................................................................................................................................................15
tool)....................................................................................................................................................................15
DGNB-tool).........................................................................................................................................................16
tool)....................................................................................................................................................................16
Figure 21: Ratio of district specific values to reference values, comparison (own depiction based on DGNB-tool)
...........................................................................................................................................................................17

_____________________________________________________________________________________________________
Figure 1: study area: Berlin Tegel Airport (Grassl 2016)
1. Introduction
This report aims to give a brief overview about the way how to perform a life cycle assessment along the
future project of the refurbishment of Berlin Tegel Airport. Subject is an excerpt of the study area around the
main terminal (s. Figure 1).
1.1. Berlin Tegel Airport Complex
The district around the airport Berlin Tegel has recently undergone an urban planning study to analyze the
potential for an after use after the regular routine will have ended. It is planned to install an innovation centre
intertwining innovation, production and energy whereas addressing sustainable requirements at the same time.
The urban quarter aims a mixed use with a projected balance of open and built up space as well as a good
integration into the remaining urban space and existing structures. (State of Berlin & reicher haase associierte
GmbH 2014)
1.2. Life Cycle Assessment
The instrument of a life cycle assessment aims to quantify the environmental impact of all constructed
buildings in a district including emissions, efficiency of appliances or impact of renewable energies (Bott, Grassl
und Anders 2013) (Huber 1995).
1.3. DGNB LCA Tool
The DNGB LCA tool for urban districts is the
only tool that equalizes ecological, economical,
socio-cultural and technical aspects. It
particularly concentrates on the location, the
open space and the infrastructure. It includes all
emissions and costs from claiming the resource,
producing the material, constructing the
building, using it until its end of life.
There are three different stages of
certificates and four different ratings; one in an earlier design phase, another one in the planning and
Figure 2: DGNB criteria catalogue for urban districts (DGNB 2012)

_____________________________________________________________________________________________________
developing phase and the third one for the completed district. The ratings are categorized into Bronze, Silver,
Gold and Platinum.
2. Criteria for Sustainable Urban Districts
The main criteria are of economic, ecological and socio-cultural manner. They aim to grant living comfort of
the users, environmental friendly and conscious use of natural resources as well as to reduce the occurring
costs over a lifecycle. All of them are being rated evenly with 22,5%. Another criteria is the technical quality
which also accounts to 22,5% as the aforementioned. The concluding item is the process quality which reflects
participatory and citizen integration, marketing and monitoring to mention a few ones.
3. Analysis of Built Area
3.1. Land Use
29% of the area is built space, 71% open space of which 62% is sealed and 9% green. Another 7% are
considered as an additional green space as every newly constructed building accommodates a green roof (own
mass estimations based on given aerial view).
3.2. Built Area
All new constructed buildings seem to be functioning as office or commercial buildings; there is no
residential use recognizable. The existing and refurbished terminals are intended as technology and research
development areas (customized docking zones) (Berlin 2013).
3.3. Materials
All buildings were considered as fully insulated (EPS) reinforced concrete skeleton buildings with a solid
technical concrete tower which equips stairs and piping. Concrete walls are coated with plaster, not load-
bearing walls consist of drywall. The façade layer is before the concrete columns. Windows were assumed as
double-pane with an aluminum frame (Reference value).
3.3.1. Proposition of Building Materials and Areas
A standardized medium standard office building accounts 87.2% of the gross area as net floor area and
12.8% as construction area (BKI 2015). The construction volume accounts to 10% of the gross building volume;
this value has been set up. The major construction material is reinforced concrete with 79% of the entire
Figure 3: perspective of study area: built up space and
open space (own depiction, based on design proposal

_____________________________________________________________________________________________________
construction volume (Pick und Streit 2011). 15% of construction volume is insulation material with a thickness
of 20 cm, 1% steel (Pick und Streit 2011), 2% masonry, 1% timber/aluminum, 0.8% glass, 0.2% plaster and 2%
drywall (ABW Recycling 2013).
4. LCA Results of Proposed Design
Following environmental impact factors were basis for the life cycle assessment of the district:
Abbreviation Name Unit Reference Unit
AP Acidification potential kg SO2-Equiv. kg
EP Eutrification potential kg Phosphate-Equiv. kg
GWP Global Warming Potential kg CO2-Equiv. kg
ODP Ozone Depletion Potential kg R11-Equiv. kg
POCP Photochemical Ozone Creation Potential kg Ethene-Equiv. kg
PE-NR Primary energy non-renewable MJ kg
PE-RE Primary energy renewable MJ kg
PE-Total Primary energy total MJ kg
The initial step was to determine the environmental impact according to standard reference values given by
ökobaudat-sheet for construction, energy, water and piping, using water and energy intensities specified by
Grassl (2016), as shown in Table 2.
Table 2: energy and water benchmarks (Grassl 2016)
Table 1: environmental impact factors according (own depiction based on DGNB-tool)

_____________________________________________________________________________________________________
Our second action was to set district specific values for water and energy intensities, shown as “TXL” in
Table 2, and assess the change in environmental impacts from reducing energy and water use in the district.
The optimized district (Optimization 0) results in 20 to 30% reductions in all environmental impact categories, as
shown in Figure 6. Additionally, the distribution (as a percent) of environmental impact categories relative to
district components (building construction, building operation, sealed surfaces, green spaces, media) shifted so
that building construction accounts for a larger share in each of the environmental impact categories than in the
reference scenario, as shown in Figure 5. This demonstrates decreased environmental burdens from building
operations, which is logical as Optimization 0 is an energy and water efficient urban district. As an example, in
the reference scenario, building construction and operations accounted for 12% and 87%, respectively, of
district total global warming potential (GWP); these values were shifted to 17% and 82% shares for building
construction and operations in Optimization 0.
Figure 5: environmental impact factors with district specific values (own depiction based on DGNB-tool)
0%
20%
40%
60%
80%
100%
GWP ODP POCP AP EP PE.nr PE.r PE.total
District Specific Values (unit/m2 GFA) | Reference
Building Construction Building Operations Sealed Surfaces Green Spaces Media
0%
20%
40%
60%
80%
100%
District Specific Values (unit/m2 GFA) | Optimization 0
Figure 4: environmental impact factors with standard reference values (own depiction based on DGNB-tool)

_____________________________________________________________________________________________________
Figure 6: Ratio of district specific values to reference values for optimization 0 (own depiction based on DGNB-tool)
5. Design Optimization for Enhanced Sustainability
The following optimization steps attempted to determine the most significant changes. Part One aims
adjustment in building materials, Part Two adjustment in district parameters. Part Three takes all together and
Part Four shows the overall performance relative to each other.
5.1. Material adjustments
Aluminum is known to be an energy intensive material to transform with harsh environmental impacts
associated to mining the raw resource. The first optimization reviewed the change in environmental impacts
from replacing all aluminum window frames with wooden frames, at an estimated 1,850 m length of window
frames in the entire district. As shown in Figures 7 and 8, Optimization 1 shows virtually no change in
performance or shift in environmental burdens from Optimization 0.
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
1,00
GWP ODP POCP AP EP PE.nr PE.re PE.total
Ratio of District Specific Values to Reference Values
(unit/m2 GFA) | Optimization 0

_____________________________________________________________________________________________________
5.1.1. Optimization 1: Wooden Window Frames
Figure 7: environmental impact factors with district specific values for optimization 1(own depiction based on DGNB-tool)
Figure 8 : Ratio of district specific values to reference values for optimization 1 (own depiction based on DGNB-tool)
0%
20%
40%
60%
80%
100%
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
1,00

_____________________________________________________________________________________________________
5.1.2. Optimization 2: as Optimization 0 substituting EPS with Mineral Wool
Expanded polystyrene (EPS) is a high performing insulation material. EPS is 98% by volume petroleum or
natural gas (EUMEPS 2014). This material, similar to concrete, has a large environmental footprint for the
production of the material (which is reflected in the building construction category of the DGNB District LCA
calculation tool) but then reduces the needed energy for thermal comfort in the building over its life (assumed
to be 50 years), which is reflected in the building operation category in the tool. Optimization 2 replaced all EPS
with mineral wool as an insulation material in the district under the assumption that mineral wool has a smaller
environmental footprint for production, and that the district LCA calculation tool is unable to reflect enhanced
building performance from a single material. It is assumed that approximately 16,500 m³ of insulation is used in
the total district. The 1% enhancement in GWP seems not to be much but for a single material with such a low
contribution it is worth mentioning it.
Results from Optimization 2 show significant changes in environmental footprint from Optimization 0,
reflected in Table 3, and shifts in environmental impacts relative to district category, as shown in Figure 9.
Ozone depletion potential (ODP) is reduced by 8%, and acidification potential (AP) is reduced by 42%.
Alternatively, Optimization 2 resulted in a 1% increase in GWP and non-renewable energy use (PEnon-renew),
and a 2% increase in photochemical ozone creation potential (POCP) and eutrophication potential (EP). The 8%
reduction in ODP, which reflects all of the building construction related emissions, is likely because EPS is
commonly treated with hexabromocyclodecane (HBCD) as a flame retardant (EUMEPS 2011). HBCD is an inert
molecule that has been shown destructive to tropospheric ozone (Jones 2013).
Table 3: results of Optimization 2 relative to Optimization 0 (own depiction based on DGNB-tool)
Figure 9: environmental impact factors with district specific values for optimization 2 (own depiction based on DGNB-tool)
0%
20%
40%
60%
80%
100%

_____________________________________________________________________________________________________
5.1.3. Optimization 3: as Optimization 0 without Insulation
The DGNB-tool calculates thermal performance of an urban district as an energy intensity measure
(kWh/m2
/a) and reflects this performance in the building operations category. Accordingly, optimizations of
materials in the tool can only reflect changes in environmental impacts in the building construction category.
Optimization 3 demonstrated this by removing any form of insulation as a building material. This optimization
resulted in the best performing building between the three insulation materials (EPS, mineral wool and no-
insulation), as shown in Table 4, because the total mass of materials was reduced and there forth all of the
associated environmental burdens. For example, Optimization 3 has a 29% reduction in GWP, 38% reduction in
ODP, 21% POCP, 54% reduction in AP, 21% reduction in EP and 27% reduction in total primary energy demand,
relative to the reference district, see Figure 10.
More information is needed concerning changes in thermal energy performance of the building during
operations between the three insulation scenarios in order to be able to accurately demonstrate changes in
environmental impact of the entire urban district over its anticipated functional life, 50 years.
Table 4: comparison of EPS, mineral wool and no insulation (own depiction based on DGNB-tool)
0,00
0,20
0,40
0,60
0,80
1,00

_____________________________________________________________________________________________________
Figure 12 Ratio of district specific values to reference values for optimization 3 (own depiction based on DGNB-tool)
5.2. Adjustment of district parameters
As previously discussed, the DGNB district LCA tool is most suited for demonstrating optimizations at
the district scale, rather than at the material level. This analysis optimized the urban district in three ways. First,
in Optimization 4, all thermal energy demands are met through a district heating grid. Optimization 5 reverts
back to the Optimization 0 energy mix for thermal heating, but displaces 30% of electricity supplied to the
district with on-site renewable energy generation. Optimization 6 reverts all energy supplies (electricity and
thermal) to Optimization 0 standard mixed values and increases the green surfaces in the district from 9% to
25%, thus reducing sealed surfaces.
0%
20%
40%
60%
80%
100%

_____________________________________________________________________________________________________
5.2.1. Optimization 4: District Heating
Although the thermal energy demand was is being entirely covered through a district heating grid, there is
no significant changes visible compared with other already made adjustments. The only remarkable spike
expresses the share of primary renewable energy sources. It remains on the table whether a district heating is
considerable as a renewable energy source.
Figure 14 Ratio of district specific values to reference values for optimization 4 (own depiction based on DGNB-tool)
0%
20%
40%
60%
80%
100%
0,67 0,67
0,74 0,75
0,79
0,69
14,00
0,69
0,00
0,20
0,40
0,60
0,80
1,00
(unit/m2 GFA) | Optimization 4 (adjusted)

_____________________________________________________________________________________________________
5.2.2. Optimization 5: 30% On-Site Renewable Energy Generation
Only a 30%-on-site energy generation results in starkly better performance of the district; particularly
regarding the Global Warming Potential and the Ozone Depletion Potential.ODP is reduced by half, GWP by
more than 40% after all. That reflects the high share of fossil fuels in the standard energy mix as well as the high
potential for CO2-reduction through renewables. R11, as the equivalent for ODP (United Environoment Nairobi
2000) resembles beside others the occurrence of NOx which is a byproduct at the combustion of fossil fuels in
order to generate energy.
0%
20%
40%
60%
80%
100%
0,00
0,20
0,40
0,60
0,80
1,00
(unit/m2 GFA) | Optimization 5 (adjusted)
3,00

_____________________________________________________________________________________________________
5.2.3. Optimization 6: Increased Green Surfaces
An increase of green space by almost 20% as compared to optimization 0 results in almost no improvement
of any of the environment impact factors whatsoever. The saved excavated soil underneath sealed surfaces or
even hazardously presumed aggregates for asphalt don’t have an influence here. Another explanation would be
the compensation of a comparatively small surface in regard of the energy consumption over time over the
operation of an entire district.
0%
20%
40%
60%
80%
100%
0,00
0,20
0,40
0,60
0,80
1,00
Ratio of Specific Values to Reference Values (unit/m2 GFA)
| Optimization 6

_____________________________________________________________________________________________________
5.3. Optimization 7: Wooden Window Frames, District Heating, On-Site RE-Gen. and Increased Green Surfaces
After all optimization steps has been taken together it results quite logically in the best performance of all
previously and individually performed optimizations. All environment impact factors show the largest reduction
where as the share of renewable energy rises alone ( s. Figure 21).
0%
20%
40%
60%
80%
100%
0,00
0,20
0,40
0,60
0,80
1,00
(unit/m2 GFA) | Optimization 7 (adujusted)
3,00

_____________________________________________________________________________________________________
5.4. Comparison of all Optimizations
Figure 21: Ratio of district specific values to reference values, comparison (own depiction based on DGNB-tool)
6. Conclusion and Recommendations
For future investigation and understanding of impacts of certain environment impact categories it is crucial
to analyze detailed data of respecting parameters. For a brief overview it was a good exercise but to merely
understand major impacts and utilize their potential could serve better for professional application of this tool.
In this sense it has not be
One thing that is worth of reconsidering is the lifetime of the district. 50 years should be an aimed ambition
but regarding the speed of technological advancements and the inevitable abundance of certain resources can
lead to an adjustment into longer time spans.
A given sample with comparable values and results would have had a deeper understanding and a more
sustainable learning effect.
-0,30
0,20
0,70
1,20
Ratio of District Specific Value to Reference Value
(unit/m2 GFA)
Ref. Op. 0 Op. 1 Op. 2 Op. 3 Op. 4 Op. 5 Op. 6 Op. 7

_____________________________________________________________________________________________________
References
ABW Recycling. "Vorlesung C/Kapitel 5: Bauwerksspezifische Kennzahlen." 2013.
Berlin, Senatsverwaltung für Stadtentwicklung und Umwelt. "Tegel Airport Future Use." Masterplan Berlin TXL.
Berlin, 2013.
BKI. BKI Baukosten Teil 1: Statistische Kennwerte für Gebäude 2015. 2015.
Bott, Helmut, Gregor Grassl, and Stephan Anders. Nachhaltige Stadtplanung. DETAIL, 2013.
DGNB. Handbuch für Nachhaltiges Bauen: Neubau Stadtquartiere. Stuttgart: DGNB, 2012.
EUMEPS – European Manufacturers of Expanded Polystyrene Association (2011) “Environmental Product
Declaration (EPD): Expanded Polystyrene (EPS) Foam Insulation (with infra red absorbers, density 20
kg/m3
)” Edited by Environmental Construction Products Organization (ECO)
Grassl, Gregor. 2016.
Huber, Joseph. "Nachhaltige Entwicklung." archplus, 1995: 79-81.
Jones, Philippa Nuttall (2013) “End in Sight for Flame Retardant HCBD?” Chemical Watch: Global Business
Briefing. Accessed online 28.03.2016 < https://chemicalwatch.com/16534/end-in-sight-for-flame-
retardant-hbcd>
Pick, Jürgen, and Wilfried Streit. "Kalkulation." In Zahlentafeln für den Baubetrieb, by Manfred Hoffmann.
Weisbaden: Vieweg+Teubner Verlag, 2011.
State of Berlin & reicher haase associierte GmbH. Städtebauliche Vorqualifizierung. Berlin: Tegel Projekt GmbH,
2014.

_____________________________________________________________________________________________________
Appendix 1: Building Volumes and Masses
Key

_____________________________________________________________________________________________________

_____________________________________________________________________________________________________
Appendix 2: Energy and Water Use

_____________________________________________________________________________________________________
Appendix 3: Optimizations and Results
Key

_____________________________________________________________________________________________________

Minimizing Environmental Impact of Urban Districts with Life Cycle Assessment - Berlin Tegel Airport Complex

Recomendados

Recomendados

Mais conteúdo relacionado

Destaque

Destaque (14)

Semelhante a Minimizing Environmental Impact of Urban Districts with Life Cycle Assessment - Berlin Tegel Airport Complex

Semelhante a Minimizing Environmental Impact of Urban Districts with Life Cycle Assessment - Berlin Tegel Airport Complex (20)

Mais de Heather Troutman

Mais de Heather Troutman (20)

Último

Último (20)

Minimizing Environmental Impact of Urban Districts with Life Cycle Assessment - Berlin Tegel Airport Complex