Building stock in Helsinki

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Question

What is the building stock in Helsinki?

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Rationale

Data

----#: . CHECK ALSO THIS DATA: --Jouni (talk) 12:53, 5 May 2015 (UTC) (type: truth; paradigms: science: comment)

• Unit heat consumption of buildings in Finland
• http://era17.fi/wp-content/uploads/2010/10/sitran_selvityksia_39.pdf page 25
• http://www.teeparannus.fi/attachements/2010-12-21T11-54-1114846.pdf pages 8-9, also 40-45
• http://www.vtt.fi/inf/pdf/tiedotteet/2007/T2377.pdf page 20-21, also 30, 80
• Heating consumption of buildings

Building stock

The structures of the tables are based on CyPT Excel file N:\YMAL\Projects\ilmastotiekartta\Helsinki Data Input Template - Building Data.xlsx.

Table 1. Effective floor area of buildings by building type.

Type of data:

• Average, City
• Example, city
• Average, city close by
• Example, city close by
• Average, national
• Example, country

Quality of data

• Statistics
• Extrapolated
• Calculated from statistics
• Calculated from stat. inc. assumptions

You have error(s) in your data:

Number of indices and result cells does not match

Effective floor area of buildings(m2)

Obs	Building	Baseline	2020	2025	2050	Year of baseline	Type of data	Quality	Description
1	Residential	28304514	31587862	34871210	39796232			Building block of Helsinki area, April 2015
2	Public	8507311	8586286	8656932	90018087			Building block of Helsinki area, April 2015
3	Industrial	3182152	3241232	3294568	3569457			Building block of Helsinki area, April 2015
4	Other	10699447	10798771	10887622	11341838			Building block of Helsinki area, April 2015

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).

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 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

Table 2. Existing situation of important energy parametres in the building stock.

Existing situation of total stock(%)

Obs	Property	Residential	Public	Industrial	Other	Description
1	Wall insulation	17				Default building data. excel/cyPT data collection
2	High efficient glazing	35				Energy performance class A in building automation/Simens pdf document searched in internet
3	Efficient lighting in baseline	1,4				Default building data. excel
4	Demand oriented lighting	26,9				Default building data. excel
5	Building Efficiency Monitoring
6	Building Remote Monitoring
7	Building Performance Optimization
8	Demand controlled ventilation	16,2or 22,4				Default building data. excel/cyPT data collection
9	Heat and Cold Recovery in ventilation	17,8
10	Efficient Motors
11	Building Automation BACS Class C
12	Building Automation BACS Class B
13	Building Automation BACS Class A
14	Room Automation HVAC	30				http://www.buildingtechnologies.siemens.com
15	Room Automation HVAC + lighting
16	Building Automation HVAC + lighting + blinds	60				www.buildingtechnologies.siemens.com

Notes

Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 1. Auxiliaries PPT.

Energy demand

Table 3. Total energy demand by energy type and building type.

Total energy demand by type(kWh /m2 /a)

Obs	Energy type	Residential	Public	Industrial	Other	Description
1	Electricity
2	Cooling
3	Heating

Notes

Heating includes warm water. Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 1. Auxiliaries PPT.

Table 4. Shares of different energy sinks by building type.

Share of energy demand by use type(kWh/m2a)

Obs	Energy type	Use	Residential	Other	Admin	Industry	Description	Auxiliaries
1	Cooling	Infiltration	0.0	0.0	0.0	0.0		PPT
2	Cooling	Ventilation	0.0	0.0	0.0	9.0		PPT
3	Cooling	Losses through walls through transmission	0.0	0.0	0.0	0.0		PPT
4	Cooling	Heat input by solar radiation through windows	0.0	0.0	0.0	0.0		PPT
5	Cooling	Losses through windows through transmission	0.0	0.0	0.0	0.0		PPT
6	Cooling	Other effects (e.g. people, electrical Appliances)	0.0	0.0	0.0	0.0		PPT
7	Heating	Infiltration	0.0	0.0	0.0	0.0		PPT
8	Heating	Ventilation	29.19	27.56	27.22	27.22		PPT
9	Heating	Walls	34.75	32.81	32.40	32.40		PPT
10	Heating	Windows	15.49	14.63	14.44	14.44		PPT
11	Heating	Floors	8.74	8.25	8.15	8.15		PPT
12	Heating	Roofs	9.33	8.81	8.70	8.70		PPT
13	Heating	Other	0.0	0.0	0.0	0.0		PPT
14	Heating	Warm water	1.89	0.0	1.76	1.76		Excel
15	Electricity	Lighting	2.82	20.05	49.68	8.67		Excel
16	Electricity	Appliances	24.84	18.74	14.19	13.00		Excel
17	Electricity	Ventilation	0	12.03	21.29	18.24		Excel
18	Electricity	Other	0.56	23.69	56.77	51.76		Excel

⇤--#: . The problem with your table is that you have changed the columns. You cannot do that, because the original classification is what we use in the model. Instead, you have to extrapolate from the existing numbers to those classes needed in the model. --Jouni (talk) 06:45, 29 April 2015 (UTC) (type: truth; paradigms: science: attack)

----#: . Use decimal points instead of decimal commas. --Jouni (talk) 06:45, 29 April 2015 (UTC) (type: truth; paradigms: science: comment)

----#: . Also include references and links so that the reader can go back to the original data and see where the numbers came from. --Jouni (talk) 06:45, 29 April 2015 (UTC) (type: truth; paradigms: science: comment)

Notes

Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 1. Auxiliaries: see table.

Data from Climate policies Helsinki additional data

We went through the data mentioned above and also the files given in "Climate policies Helsinki data" Climate policies Helsinki data but could not find the data for cooling, heating:infiltration, heating:other, heating:warm water:other and electricity:ventilation:resindential.

Total estimated amount of energy needed for cooling 23504480 kWh/a (whole Helsinki). Based on http://www.energiatehokashelsinki.fi/energiankulutus/Helsinki 14332 GWh/a for housing (total energy demand minus traffic 18 % [1] ) and http://www.korjaustieto.fi/pientalot/pientalojen-energiatehokkuus/energiatehokkuus-pientaloissa/pientalon-energiankulutus-ja-paastot.html 2 % of total energy demand of housing used for cooling. Total floor area of Helsinki needed (table 1).

Table 5. Changes in energy efficiency of different energy sinks.

Efficiency increase decreasing energy demand(% /a)

Obs	Energy type	Use	Residential	Public	Industrial	Other	Description
1	Electricity	Lighting /Lamp stock	0.6	0.6	0.6	0.6
2	Electricity	Appliances	0.6	0.6	0.6	0.6
3	Electricity	Ventilation	0.6	0.6	0.6	0.6
4	Electricity	Other	0.6	0.6	0.6	0.6
5	Cooling	Infiltration	2	0.6	0.6	0.6
6	Cooling	Ventilation	2	0.6	0.6	0.6
7	Cooling	Other (e.g. electric appliances, people)	2	0.6	0.6	0.6
8	Heating	Infiltration	0.6	0.6	0.6	0.6
9	Heating	Ventilation	0.6	0.6	0.6	0.6
10	Heating	Floors	0.6	0.6	0.6	0.6
11	Heating	Roofs	0.6	0.6	0.6	0.6
12	Heating	Other reasons	0.6	0.6	0.6	0.6
13	Heating	Warm water	1.1	0.6	0.6	0.6

Notes

Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 3. Auxiliaries Excel.

Estimated 3 % of houses renovated/year and 20 % increase in energy efficiency when renovated. [2] Data apart from 0.6% values from Climate policies Helsinki additional data

The presentation about tables 4 and 5 PresentationHW9

Table 6. Important energy parameters.

Energy parameters(-)

Obs	Parameter	Unit	Residential	Public	Industrial	Other	Description	Auxiliary
1	Ratio of wall area / effective area	-	0.00	0.00	0.00	0.00	0.00	PPT
2	Ratio of window/effective area	-	0.15	0.00	0.00	0.00	0.00	PPT
3	U-value of windows	W /m2 /K	1.0	1.4	1.4	1.4	1.6	PPT
4	Solar heat gain coefficient "G-Value" of windows	%	0,40	0.0	0.0	0.0	0.0	PPT
5	Efficiency increase of G-value of windows	% /a	0.0	0.0	0.0	0.0	0.0	Excel
6	Efficiency increase of U-value of windows	% /a	0.0	0.0	0.0	0.0	0.0	Excel
7	U-value of building walls	W /m2 /K	0.16	0.25	0.25	0.28	0.3	PPT

Notes

Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 3. Auxiliaries: see table.

Economidou, M., Atanasiu, B., Despret, C., Maio, J., Nolte, I., & Rapf, O. (2011). Europe’s buildings under the microscope. A Country-by-country review of the energy performance of buildings, 131.

Unit heat consumption, opasnet Kragh, J., Laustsen, J. B., & Svendsen, S. (2008). Proposal for Energy Rating System of windows in EU. DTU Civil Engineering-Report R-201.

http://www.ziegel.at/gbc-ziegelhandbuch/eng/ressourcen/energie/graue.htm

Lighting

Tables 7-8. Run times and shares of lamps by lamp type and building type.

Average run time of lamps per year(h /a)

Obs	Lamp	Residential	Public	Industrial	Other	Description
1	Incandescent lamps
2	Compact fluorescent lamps
3	Fluorescent lamps
4	Low voltage halogen lamps
5	Medium voltage halogen lamps

Shares of lamp types(%)

Obs	Lamp	Residential	Public	Industrial	Other	Description
1	Incandescent lamps
2	Compact fluorescent lamps
3	Fluorescent lamps
4	Low voltage halogen lamps
5	Medium voltage halogen lamps

Notes

Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 3. Auxiliaries Excel.

Other

Sheet 4_Input Buildings (Area Demand). Priority 1. Auxiliaries PPT. Nice to have specific factor otherwise we adapt standard data or other studies.

Possibly important information

Data	Result
Number of households
Number of persons per household

See also

• Descriptions about the summary calculations on sheet Parameter Balance (not needed any more).
• Rakennustietoruudukko pääkaupunkiseudulta [3]