Building stock in Helsinki
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- During Decision analysis and risk management 2015 course, this page was used to collect student contributions. To see them, look at an archived version. The page has since been updated for its main use. Data in the archived tables was moved: Table 2. Energy parametres of buildings, Table 4. Energy sinks, Table 5. Changes in energy efficiency, Table 6. Important energy parametres. Tables 3, 7, and 8 did not contain data and were removed.
Question
What is the building stock in Helsinki and its projected future?
Answer
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Rationale
Data
Building stock
These tables are based on FACTA database classifications and their interpretation for assessments. This data is used for modelling. The data is large and can be seen from {{#opasnet_base_link:Op_en7115}}
(Stock details). Technical parts on this page are hidden for readability. Building types should match Energy use of buildings#Baseline energy consumption.
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----#: . Onko tää ok muodossa? Yhdistetyt luokat viittaa kaikkiin kyseisen luokan alapuolella oleviin luokkiin. Tässä on periaatteessa kolmiportainen jaottelu, mutta en tiedä, haluatteko sen jotenkin selkeämmin. --Signatiu (talk) 18:39, 20 August 2015 (UTC) (type: truth; paradigms: science: comment) You have error(s) in your data:You have invalid number of data cells in row 2 You have invalid number of data cells in row 3 You have invalid number of data cells in row 4 You have invalid number of data cells in row 5 You have invalid number of data cells in row 6 You have invalid number of data cells in row 7 You have invalid number of data cells in row 8 You have invalid number of data cells in row 9 You have invalid number of data cells in row 10 You have invalid number of data cells in row 11 You have invalid number of data cells in row 12 You have invalid number of data cells in row 13 You have invalid number of data cells in row 14 You have invalid number of data cells in row 15 You have invalid number of data cells in row 16 You have invalid number of data cells in row 17 You have invalid number of data cells in row 18 You have invalid number of data cells in row 19 You have invalid number of data cells in row 20 You have invalid number of data cells in row 21 You have invalid number of data cells in row 22 You have invalid number of data cells in row 23 You have invalid number of data cells in row 24 You have invalid number of data cells in row 25 You have invalid number of data cells in row 26 You have invalid number of data cells in row 27 You have invalid number of data cells in row 28 You have invalid number of data cells in row 29 You have invalid number of data cells in row 30 You have invalid number of data cells in row 31 You have invalid number of data cells in row 32 You have invalid number of data cells in row 33 You have invalid number of data cells in row 34 You have invalid number of data cells in row 35 You have invalid number of data cells in row 36 You have invalid number of data cells in row 37 You have invalid number of data cells in row 38 You have invalid number of data cells in row 39 You have invalid number of data cells in row 40 You have invalid number of data cells in row 41 You have invalid number of data cells in row 42 You have invalid number of data cells in row 43 You have invalid number of data cells in row 44 You have invalid number of data cells in row 45 You have invalid number of data cells in row 46 You have invalid number of data cells in row 47 You have invalid number of data cells in row 48 You have invalid number of data cells in row 49 You have invalid number of data cells in row 50 You have invalid number of data cells in row 51 You have invalid number of data cells in row 52 You have invalid number of data cells in row 53 You have invalid number of data cells in row 54 You have invalid number of data cells in row 55 You have invalid number of data cells in row 56 You have invalid number of data cells in row 57 You have invalid number of data cells in row 58 You have invalid number of data cells in row 59 You have invalid number of data cells in row 60 You have invalid number of data cells in row 61 You have invalid number of data cells in row 62 You have invalid number of data cells in row 63 You have invalid number of data cells in row 64 You have invalid number of data cells in row 65 You have invalid number of data cells in row 66 You have invalid number of data cells in row 67 You have invalid number of data cells in row 68 You have invalid number of data cells in row 69 You have invalid number of data cells in row 70 You have invalid number of data cells in row 71 You have invalid number of data cells in row 72 You have invalid number of data cells in row 73 You have invalid number of data cells in row 74 You have invalid number of data cells in row 75 You have invalid number of data cells in row 76 You have invalid number of data cells in row 77 You have invalid number of data cells in row 78 You have invalid number of data cells in row 79 Number of indices and result cells does not match
For residential buildings (classes A and B) the classification is kept more detailed than for other buildings. This is because residential buildings are the biggest energy consumers in Helsinki and different classes of residential buildings are examined separately. ←--#: . Tätä luokitusta ei siis käytetä. --Signatiu (talk) 18:46, 20 August 2015 (UTC) (type: truth; paradigms: science: defence)
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The structures of the tables are based on CyPT Excel file N:\YMAL\Projects\ilmastotiekartta\Helsinki Data Input Template - Building Data.xlsx.
Building | Baseline | 2020 | 2025 | 2050 | Year of baseline | Description |
Residential | 27884795 | 32472388 | 34890241 | 44069914 | 2014 | Building stock of Helsinki area, 2014 |
Public | 4537025 | 4764475 | 4945952 | 5855546 | 2014 | Building stock of Helsinki area, 2014 |
Industrial | 3277271 | 3306063 | 3360467 | 3640854 | 2014 | Building stock of Helsinki area, 2014 |
Other | 10861972 | 11406505 | 11840973 | 13806423 | 2014 | Building stock of Helsinki area, 2014 |
- Notes
- Estimates were based on
Siemens City Performance toolin seuraava kokous 2.2 and some derived calculations on
BUILDING STOCK CALCULATION 2015.
- How to get the numbers for the baseline floor area for residential, public, industrial and other: Residential floor area was named as residential together, public by summing the floor area of health care, education and common buildings, industrial buildings were as such and other buildings comprise of business, traffic, office and storage buildings.
- Ref. Helsinki master plan for 2050: there are 860 000 citizens living in Helsinki (ref. www.yleiskaava.fi, visio2050); Residental buildings => fast growth
- Prediction of citizen number in Helsinki in 2020, 2030, 2040 and 2050 was used for calculations (ref. Helsingin 30% päästövähennysselvitys).
- Helsinki’s climate policy: 30% reduction in emissions: In 2010 the proportion of jobs in services and public sectors was 94%, and in industry 6%. In 2020 the proportion of jobs in services and public sectors is estimated to be 96%, and in industry 4%. Public and other buildings => between fast growth option and basic option, Industry=> Basic option
- Prediction of job number in Helsinki in 2020, 2030, 2040 and 2050 was used for calculations (ref. Helsingin 30% päästövähennysselvitys).
Tables one and two The presentation of Tables 1 and 2
Technical notes:
- Sheet 4_Input Buildings (Area Demand). Priority 1. Auxiliaries PPT. Absolute increase/decrease rate will be based on the inhabitants projected in time.
- This is another list building types that was considered but rejected as too complex: Residential buildings, Government & public administration buildings, Commercial offices buildings, Data centers buildings, Education and K12 and universitiy buildings, Hospitals and healthcare buildings, Hotels and hospitality and leisure buildings, Exhibitions and fairs and halls buildings, Retail and stores and shops buildings, Warehouses & shopping mall buildings, Industrial buildings, Non residential buildings unspecified.
Construction and demolition
It is assumed that construction occurs at a constant rate so that there is an increase of 42% in 2050 compared to 2013. Energy efficiency comes from Energy use of buildings. It is assumed that no demolition occurs.
Heating type conversion
The fraction of heating types in the building stock reflects the situation at the moment of construction and not currently. The heating type conversion corrects this by changing a fraction of heating methods to a different one at different timepoints. Cumulative fraction, other timepoints will be interpolated.
Obs | Heating_from | Heating_to | Time | Result |
---|---|---|---|---|
1 | Oil | Geothermal | 2005 | 0 |
2 | Oil | Geothermal | 2015 | 0.5 |
3 | Oil | Geothermal | 2025 | 1 |
Renovations
Estimates from Laura Perez and Stephan Trüeb, unibas.ch N:\YMAL\Projects\Urgenche\WP9 Basel\Energy_scenarios_Basel_update.docx
Obs | Age | Result | Description |
---|---|---|---|
1 | 0 | 0 | Estimates from Laura Perez and Stephan Trüeb |
2 | 20 | 0 | Assumption Result applies to buildings older than the value in the Age column. |
3 | 25 | 1 | |
4 | 30 | 1 | |
5 | 50 | 1 | |
6 | 100 | 1 | |
7 | 1000 | 1 |
⇤--#: . Basel's data --Heta (talk) 12:30, 4 June 2015 (UTC) (type: truth; paradigms: science: attack)
Obs | Renovation | Fraction | Description |
---|---|---|---|
1 | None | 0 | |
2 | Windows | 65 | |
3 | Technical systems | 30 | |
4 | Sheath reform | 5 | |
5 | General | 0 |
⇤--#: . Basel's data --Heta (talk) 12:30, 4 June 2015 (UTC) (type: truth; paradigms: science: attack)
Construction year | Balcony glasses | Windows | Julkisivujen peruskorjaus | Vesikattojen peruskojaus | Lämmönvaihtimen uusiminen | Patteriverkoston säätö | Kylpyhuonekalusteiden vaihto | Patteriventtiilien vaihto | New balcony doors | LTO-laitteen asennus | Water consumption measurements |
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-20 | 0,0 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % | 1,1 % |
21-25 | 0,0 % | 10,3 % | 1,2 % | 11,1 % | 10,3 % | 10,3 % | 1,2 % | 10,3 % | 1,2 % | 10,3 % | 10,3 % |
26-30 | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 9,5 % | 0,0 % |
31-35 | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 0,0 % |
36-40 | 0,0 % | 0,0 % | 0,0 % | 0,0 % | 4,2 % | 4,2 % | 0,0 % | 0,0 % | 0,0 % | 4,2 % | 0,0 % |
41-45 | 0,0 % | 16,7 % | 0,0 % | 16,7 % | 16,7 % | 16,7 % | 0,0 % | 16,7 % | 0,0 % | 16,7 % | 16,7 % |
46-50 | 0,0 % | 5,2 % | 0,0 % | 7,4 % | 7,4 % | 7,4 % | 0,0 % | 7,4 % | 0,0 % | 5,2 % | 5,2 % |
51-55 | 0,0 % | 11,3 % | 0,0 % | 8,8 % | 8,8 % | 8,8 % | 0,0 % | 8,8 % | 0,0 % | 8,8 % | 16,2 % |
56-60 | 0,0 % | 5,4 % | 0,0 % | 4,9 % | 6,2 % | 7,1 % | 0,0 % | 6,2 % | 4,5 % | 4,5 % | 5,4 % |
61-65 | 0,0 % | 1,5 % | 1,3 % | 0,8 % | 2,9 % | 2,4 % | 1,0 % | 2,4 % | 0,9 % | 0,9 % | 2,9 % |
66-70 | 0,6 % | 2,9 % | 1,2 % | 2,8 % | 1,4 % | 2,3 % | 1,1 % | 1,1 % | 0,1 % | 1,1 % | 1,1 % |
71-75 | 3,2 % | 3,1 % | 3,4 % | 2,9 % | 3,1 % | 2,6 % | 0,2 % | 1,1 % | 0,2 % | 0,2 % | 0,2 % |
76-80 | 0,1 % | 2,7 % | 0,1 % | 0,7 % | 2,0 % | 1,7 % | 1,1 % | 1,2 % | 0,2 % | 0,4 % | 0,2 % |
81-85 | 1,0 % | 2,8 % | 0,7 % | 2,3 % | 3,3 % | 4,8 % | 3,5 % | 0,0 % | 0,0 % | 0,0 % | 0,8 % |
86-90 | 0,0 % | 1,3 % | 0,0 % | 2,1 % | 6,1 % | 1,6 % | 0,7 % | 1,8 % | 0,3 % | 0,3 % | 1,0 % |
91-95 | 0,6 % | 0,3 % | 0,0 % | 3,9 % | 8,6 % | 1,9 % | 5,1 % | 0,8 % | 0,2 % | 0,0 % | 1,3 % |
96-00 | 0,1 % | 0,0 % | 0,0 % | 0,6 % | 1,2 % | 1,0 % | 1,5 % | 1,0 % | 0,0 % | 0,0 % | 4,2 % |
01-05 | 2,9 % | 0,0 % | 0,0 % | 0,0 % | 1,2 % | 1,0 % | 0,0 % | 1,0 % | 0,0 % | 0,0 % | 0,7 % |
06-10 | 1,7 % | 0,0 % | 0,0 % | 0,0 % | 0,5 % | 0,5 % | 0,0 % | 0,5 % | 0,0 % | 0,0 % | 0,0 % |
←--#: . In the document there are similar tables for total renovations from 2010 onwards to years 2016, 2020 and 2050. --Heta (talk) 09:28, 16 June 2015 (UTC) (type: truth; paradigms: science: defence)
Toimenpide | Tarkasteltava ominaisuus | Muuttujan muutos | yksikkö | Huomautukset |
---|---|---|---|---|
Glass for balconies | U-value for windows | -0,3 | W/m2,K | Säästö 1-4% rakennustasolla |
Changing the windows | U-value for windows | -1 | W/m2,K | Vanhoista osa kaksilasisia ja osa kolmilasisia. Uudes 1,0 W/m2,K tai alle |
Julkisivun peruskorjaus | U-value of walls | -0,2 | W/m2,K | U-arvo puolitetaan eli n. 100 mm lisäeristys |
Vesikattojen peruskorjaus | Yläpohjan U-arvo | -0,15 | W/m2,K | Oletetaan 50% lisäeristys U-arvo puoleen eli n. 100 mm lisäerstys |
Balcony door change | U-value of doors | -0,5 | W/m2,K | Tiivistyminen tuo lisäsäästöä |
Construction decade | Thermal transmittance factors for building components (W/m2K) | Ventilation and leakage air rates (1/h) | |||||||
Floor | Roof | Walls | Windows | Outdoors | Supply air through the heat recovery unit | Supply air bypassing the heat recovery unit | Leakage air | ||
Before 1980 | Single family house | 0.52 | 0.32 | 0.54 | 2.14 | 1.18 | 0.30 | 0.05 | 0.20 |
Row house | 0.52 | 0.36 | 0.56 | 2.15 | 1.00 | 0.3 | 0.05 | 0.20 | |
Apartment building | 0.59 | 0.37 | 0.61 | 2.18 | 1.40 | 0.37 | 0.00 | 0.10 | |
1980's | Single family house | 0.30 | 0.21 | 0.28 | 1.70 | 1.00 | 0.30 | 0.05 | 0.15 |
Row house | 0.32 | 0.22 | 0.30 | 1.70 | 1.00 | 0.30 | 0.05 | 0.15 | |
Apartment building | 0.34 | 0.23 | 0.29 | 1.80 | 1.40 | 0.35 | 0.00 | 0.10 | |
1990's | Single family house | 0.25 | 0.20 | 0.25 | 1.70 | 1.00 | 0.30 | 0.05 | 0.15 |
Row house | 0.32 | 0.22 | 0.28 | 1.70 | 1.00 | 0.30 | 0.05 | 0.15 | |
Apartment building | 0.332 | 0.22 | 0.28 | 1.75 | 1.40 | 0.38 | 0.00 | 0.10 | |
2000's | Single family house | 0.24 | 0.17 | 0.24 | 1.40 | 1.00 | 0.30 | 0.05 | 0.13 |
Row house | 0.28 | 0.18 | 0.26 | 1.50 | 1.00 | 0.45 | 0.05 | 0.15 | |
Apartment building | 0.28 | 0.18 | 0.26 | 1.50 | 1.40 | 0.55 | 0.00 | 0.10 | |
2010's | Single family house | 0.16 | 0.09 | 0.17 | 1.00 | 1.00 | 0.30 | 0.05 | 0.10 |
Row house | 0.16 | 0.09 | 0.17 | 1.00 | 1.00 | 0.50 | 0.05 | 0.15 | |
Apartment building | 0.16 | 0.09 | 0.17 | 1.00 | 1.00 | 0.60 | 0.00 | 0.10 |
Locations of city areas
- Locations of city areas (hidden for readability).
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The positions listed here are used for exposure modelling. Area code matches with stock detail data on Building stock in Helsinki. The coordinates should be visually checked from http://www.karttapaikka.fi referencing picture X.
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See also
- Building stock in Helsinki metropolitan area
- Descriptions about the summary calculations on sheet Parameter Balance (not needed any more).
- Rakennustietoruudukko pääkaupunkiseudulta [1]
- Unit heat consumption of buildings in Finland
- Sitra, page 25
- Tee parannus pages 8-9, also 40-45
- VTT tiedotteet page 20-21, also 30, 80
- Heating consumption of buildings
- Lämmitystapavalintojen kehitys
References
- ↑ 1.0 1.1 HAESS Final report, Tampere University of Technology, 2010
- ↑ MK Mattinen, J Heljo, J Vihola, A Kurvinen, S Lehtoranta, A Nissinen: Modeling and visualisation of residential sector energy consumption and greenhouse gas emissions