[show] This page is a knowledge crystal of subtype method. The page identifier is Op_en5932
Moderator:Marjo (see all)

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Question

How to model the building stock of a city?

Answer

Calculate building stock into the future

The dynamics is calculated by adding building floor area at time points greater than construction year, and by subtracting when time point is greater than demolition year. This is done by building category, not individually.
Full data are stored in the ovariables. Before evaluating extra columns and rows are removed. The first part of the code is about this.

+ Show code - Hide code

library(OpasnetUtils)
library(ggplot2)

objects.latest("Op_en5932", code_name = "initiate") # Building ovariables
objects.latest("Op_en6007", code_name = "answer") # findrest

#################### Manage the data before calculating

# The building stock is measured as m^2 floor area.

openv.setN(1) # Set the number of iterations to 1.

####### Remove columns that are not needed.

buildings2010@data <- buildings2010@data[
	buildings2010@data$Observation == "AreaBR" , 
	colnames(buildings2010@data) != "Observation"
]

construction@data <- construction@data[
	construction@data$Observation == "Area" , 
	colnames(construction@data) != "Observation"
]

# The data is not yet specific to construction year, so remove index:
heatingTypeFuture@data <- heatingTypeFuture@data[colnames(heatingTypeFuture@data) != "Constructed"]

buildings <- buildings2010 * heatingType / 100
futureBuildings <- construction * 10 * energyClassesFuture / 100 # Construction in ten years multiplied by fraction of energy classes

year <- Ovariable(data = data.frame(
	Constructed = factor(
		c("2000-2010", "2011-2019", "2020-2029", "2030-2039", "2040-2049"), 
		ordered = TRUE
	), 
	Year = c(2005, 2015, 2025, 2035, 2045),
	Result = 1
))

energyClassesFuture <- findrest(energyClassesFuture, cols = "Emission class", total = 100)

construction <- construction * year

#addc ei mätsää buildingsin kanssa; edellisessä ei ole Heatingia. Samoin energialuokitus puuttuu molemmista
#vaikka pitäisi lisätä tiedot futureBuildingsistä.

ggplot(construction@output, aes(x = Year, y = Result)) + geom_point(aes(colour = Building)) + theme_grey(base_size = 24)

Plot results from this page

+ Show code - Hide code

library(OpasnetUtils)

library(ggplot2)      # A package with fancy graph formats

test <- Ovariable(
	name = 'test',
	dependencies = data.frame(
		Name = c('building.stock', 'energy.per.area', 'heating.fraction'),
		Ident = c('Op_en5932/initiate')
	),
	formula = function(...){

		building.stock@output <- building.stock@output[building.stock@output$Observation == "AreaHR" , ]		

		colnames(building.stock@output)[colnames(building.stock@output) == "Observation"] <- "building.stockObservation"


		energy.per.area@output <- energy.per.area@output[energy.per.area@output$Observation == observation , ]
		colnames(energy.per.area@output)[colnames(energy.per.area@output) == paste("energy.per.area", observation, sep = "")] <- "energy.per.areaResult"
		
		heating.fraction@output <- heating.fraction@output[heating.fraction@output$Observation == 'CorrFraction',c('Type','Heating','heating.fractionResult','heating.fractionSource')]
oprint(heating.fraction)
		out <- building.stock * heating.fraction / 100 * energy.per.area
		return(out)
	} 
)

test <- EvalOutput(test,N=1)

oprint(test)

oprint(summary(test))

ograph(test, x = "Constructed", fill = "Type")

ograph(test, x = "Heating", fill = "Type")

ograph(test, x = "Constructed", fill = "Heating", type = geom_bar())

Rationale

City-specific data

Building registry data

Building registry data(#,m2,m3,#)
Obs	Building	Constructed	Number	AreaBR	VolumeBR	AreaHR	VolumeHR	Description
1	Detached houses	2000-2010	756	386081	1633314	101479.9	324433.4	From building registry, except "AreaHR" and "VolumeHR" from heat registry
2	Detached houses	1990-1999	291	69238	244161	39061.7	124881.1	je
3	Detached houses	1980-1989	1332	436466	1578407	178797.9	571620.7
4	Detached houses	1970-1979	1153	533914	2135897	154770.3	494803.8
5	Detached houses	1960-1969	714	239478	825910	95842.12	306409.3
6	Detached houses	1950-1959	769	129148	400137	103224.9	330012.2
7	Detached houses	1940-1949	444	59420	199806	59599.3	190540.2
8	Detached houses	1930-1939	231	29492	117817	31007.75	991332.4
9	Detached houses	1920-1929	182	52362	209142	24430.34	78104.3
10	Detached houses	1910-1919	83	17141	63287	11141.31	35619.0
11	Detached houses	1900-1909	364	8583	26697	48860.69	156208.7
12	Detached houses	1799-1899	80	21416	90078	10738.61	34331.57
13	Row houses	2000-2010	35	4885	14776	14073.89	44638.6
14	Row houses	1990-1999	131	44673	155291	52676.57	167076
15	Row houses	1980-1989	215	53238	167371	86453.91	274208.7
16	Row houses	1970-1979	248	112504	388698	99723.58	316296.5
17	Row houses	1960-1969	169	59354	218500	67956.79	215540.8
18	Row houses	1950-1959	149	51992	181039	59914.57	190033
19	Row houses	1940-1949	150	24266	79655	60316.88	191308.4
20	Row houses	1930-1939	18	2109	6769	7238.002	22957.0
21	Row houses	1920-1929	50	6694	19447	20105.56	63769.5
22	Row houses	1910-1919	10	5649	31095	4021.112	12753.9
23	Row houses	1900-1909	60	1617	4770	24126.67	76523.4
24	Row houses	1799-1899	6	3075	12932	2412.667	7652.3
25	Apartment houses	2000-2010	101	19494	64499	167322.2	585906.9
26	Apartment houses	1990-1999	260	119428	487611	430730.5	1508275
27	Apartment houses	1980-1989	393	136886	479881	651065.8	2279816
28	Apartment houses	1970-1979	149	127426	429284	246841.7	864357.7
29	Apartment houses	1960-1969	122	114214	393011	202112	707729.1
30	Apartment houses	1950-1959	155	55041	236701	256781.7	899164
31	Apartment houses	1940-1949	73	17521	52956	120935.9	423477.3
32	Apartment houses	1930-1939	46	12122	47788	76206.17	266848.7
33	Apartment houses	1920-1929	51	6468	18829	84489.45	295854
34	Apartment houses	1910-1919	17	5361	16580	28163.15	98618
35	Apartment houses	1900-1909	77	3600	18943	127562.5	446681.5
36	Apartment houses	1799-1899	15	9190	37245	24849.84	87015.87
37	Leisure houses	2000-2010	129	27622	106034	27622	106034
38	Leisure houses	1990-1999	628	253150	959798	253150	959798
39	Leisure houses	1980-1989	312	106254	328436	106254	328436
40	Leisure houses	1970-1979	15	17313	61670	17313	61670
41	Leisure houses	1960-1969	23	41800	142756	41800	142756
42	Leisure houses	1950-1959	19	7727	24658	7727	24658
43	Leisure houses	1940-1949	32	6581	19417	6581	19417
44	Leisure houses	1930-1939	11	1671	4028	1671	4028
45	Leisure houses	1920-1929	3	496	1672	496	1672
46	Leisure houses	1910-1919	7	8345	30030	8345	30030
47	Leisure houses	1900-1909	25	8177	31580	8177	31580
48	Leisure houses	1799-1899	11	5187	21517	5187	21517
49	Offices	2000-2010	11	834	2513	24571.1	108975.1
50	Offices	1990-1999	30	5475	16512	67012.09	297204.7
51	Offices	1980-1989	15	15856	61168	33506.05	148602.4
52	Offices	1970-1979	5	8182	35146	11168.68	49534.1
53	Offices	1960-1969	14	12896	42267	31272.31	138695.5
54	Offices	1950-1959	11	4175	14891	24571.1	108975.1
55	Offices	1940-1949	26	5813	19002	58077.15	257577.4
56	Offices	1930-1939	6	7203	25634	13402.42	59441.0
57	Offices	1920-1929	6	18447	73484	13402.42	59441.0
58	Offices	1910-1919	3	7007	28393	6701.209	29720.5
59	Offices	1900-1909	11	1405	6658	24571.1	108975.1
60	Offices	1799-1899	10	8885	28766	22337.36	99068.2
61	Commercial buildings	2000-2010	3	1608	9750	6014.098	33975.3
62	Commercial buildings	1990-1999	90	27412	81016	180422.9	1019260
63	Commercial buildings	1980-1989	59	40501	135660	118277.3	668181.6
64	Commercial buildings	1970-1979	9	17990	66240	18042.29	101926
65	Commercial buildings	1960-1969	6	7613	25440	12028.2	67950.7
66	Commercial buildings	1950-1959	9	3992	17387	18042.29	101926
67	Commercial buildings	1940-1949	40	5824	16901	80187.97	453004.5
68	Commercial buildings	1930-1939	10	2962	12795	20046.99	113251.1
69	Commercial buildings	1920-1929	4	8512	27777	8018.797	45300.5
70	Commercial buildings	1910-1919	1	70	400	2004.699	11325.1
71	Commercial buildings	1900-1909	37	2511	9416	74173.87	419029.2
72	Commercial buildings	1799-1899	8	5221	27778	16037.59	90600.9
73	Health and social sector buildings	2000-2010	1	30	53	4225.8	16458.0
74	Health and social sector buildings	1990-1999	16	26529	174067	67612.8	263327.8
75	Health and social sector buildings	1980-1989	21	9354	27182	88741.7	345617.7
76	Health and social sector buildings	1970-1979	5	976	2743	21129.0	82289.9
77	Health and social sector buildings	1960-1969	3	237	943	12677.4	49374.0
78	Health and social sector buildings	1950-1959	7	793	2677	29580.6	115205.9
79	Health and social sector buildings	1940-1949	5	661	1695	21129.0	82289.9
80	Health and social sector buildings	1930-1939	2	66	147	8451.6	32916.0
81	Health and social sector buildings	1920-1929	0	0	0	0	0
82	Health and social sector buildings	1910-1919	0	0	0	0	0
83	Health and social sector buildings	1900-1909	2	149	487	8451.6	32916.0
84	Health and social sector buildings	1799-1899	2	30	70	8451.6	32916.0
85	Public buildings	2000-2010	0	0	0	0	0
86	Public buildings	1990-1999	17	10065	30863	22048	113251.8
87	Public buildings	1980-1989	8	948	3571	10375.5	53295.0
88	Public buildings	1970-1979	0	0	0	0	0
89	Public buildings	1960-1969	9	16153	58085	11672.5	59956.9
90	Public buildings	1950-1959	12	1716	4432	15563.3	79942.5
91	Public buildings	1940-1949	11	1774	4841	14266.4	73280.6
92	Public buildings	1930-1939	2	752	1328	2593.9	13323.8
93	Public buildings	1920-1929	6	5129	13639	7781.7	39971.2
94	Public buildings	1910-1919	1	31	78	1296.9	6661.9
95	Public buildings	1900-1909	5	375	1103	6484.7	33309.4
96	Public buildings	1799-1899	0	0	0	0	0
97	Sports buildings	2000-2010	3	1601	4892	5231.2	34573.8
98	Sports buildings	1990-1999	9	1330	3777	15693.5	103721.2
99	Sports buildings	1980-1989	23	3993	11721	40105.7	265065.4
100	Sports buildings	1970-1979	1	1010	2980	1743.7	11524.6
101	Sports buildings	1960-1969	4	326	970	6974.9	46098.3
102	Sports buildings	1950-1959	5	561	1421	8718.6	57622.9
103	Sports buildings	1940-1949	5	606	2467	8718.6	57622.9
104	Sports buildings	1930-1939	4	92	214	6974.9	46098.3
105	Sports buildings	1920-1929	1	128	368	1743.7	11524.6
106	Sports buildings	1910-1919	0	0	0	0	0
107	Sports buildings	1900-1909	0	0	0	0	0
108	Sports buildings	1799-1899	0	0	0	0	0
109	Educational buildings	2000-2010	10	965	3291	28041.9	118506.4
110	Educational buildings	1990-1999	35	12690	64092	98146.7	414772.4
111	Educational buildings	1980-1989	50	28242	83710	140209.5	592532
112	Educational buildings	1970-1979	24	24414	77939	67300.6	284415.3
113	Educational buildings	1960-1969	2	240	647	5608.4	23701.28
114	Educational buildings	1950-1959	4	3992	11602	11216.8	47402.6
115	Educational buildings	1940-1949	1	255	620	2804.2	11850.6
116	Educational buildings	1930-1939	5	1730	5190	14021	59253.2
117	Educational buildings	1920-1929	1	151	400	2804.2	11850.6
118	Educational buildings	1910-1919	0	0	0	0	0
119	Educational buildings	1900-1909	11	829	3384	30846.1	130357
120	Educational buildings	1799-1899	4	2129	7063	11216.8	47402.6
121	Industrial buildings	2000-2010	12	1403	4983	12303.7	67793.0
122	Industrial buildings	1990-1999	73	59828	259259	74847.7	412407.7
123	Industrial buildings	1980-1989	100	61742	213089	102531.1	564942
124	Industrial buildings	1970-1979	30	53533	245860	30759.3	169482.6
125	Industrial buildings	1960-1969	25	21774	78599	25632.8	141235.5
126	Industrial buildings	1950-1959	33	54513	171916	33835.3	186430.9
127	Industrial buildings	1940-1949	16	5991	18432	16405	90390.7
128	Industrial buildings	1930-1939	5	3774	16943	5126.6	28247.1
129	Industrial buildings	1920-1929	4	1012	2483	4101.2	22597.7
130	Industrial buildings	1910-1919	1	736	3800	1025.3	5649.4
131	Industrial buildings	1900-1909	8	78	210	8202.5	45195.4
132	Industrial buildings	1799-1899	5	1692	6530	5126.6	28247.1
133	Other buildings	2000-2010	1757	839469	3554193	85457.8	395141.1
134	Other buildings	1990-1999	848	368865	1353085	41245.4	190711.2
135	Other buildings	1980-1989	867	617201	2413346	42169.5	194984.3
136	Other buildings	1970-1979	395	666755	2847441	19212.2	88833.7
137	Other buildings	1960-1969	266	408885	1574959	12937.8	59822.2
138	Other buildings	1950-1959	310	474438	1656934	15077.9	69717.6
139	Other buildings	1940-1949	244	102298	352553	11867.8	54874.5
140	Other buildings	1930-1939	75	50759	187919	3647.9	16867.2
141	Other buildings	1920-1929	93	72101	278959	4523.4	20915.3
142	Other buildings	1910-1919	33	41916	150394	1605.1	7421.5
143	Other buildings	1900-1909	116	34061	120695	5642.1	26087.9
144	Other buildings	1799-1899	41	33680	137878	1994.2	9220.7

Fractions of houses according to heating type

Fractions of houses according heating type(%)
Obs	Building	Heating	Fraction	Old fraction	Description
1	Detached houses	District	68.36	82.5	City of Kuopio
2	Detached houses	Electricity	16.09	8.93
3	Detached houses	Oil	8.50	4.66
4	Detached houses	Wood	5.24	2.86
5	Detached houses	Geothermal	1.81	1.04
6	Row houses	District	100	100	Nearly correct
7	Apartment houses	District	100	100	Nearly correct
8	Leisure houses	Electricity	100	100	Assumption
9	Offices	District	100	100	Assumption
10	Commercial buildings	District	100	100	Assumption
11	Health and social sector buildings	District	100	100	Assumption
12	Public buildings	District	100	100	Assumption
13	Sports buildings	District	100	100	Assumption
14	Educational buildings	District	100	100	Assumption
15	Industrial buildings	District	100	100	Assumption
16	Other buildings	District	100	100	Assumption

Future heating types(%)
Obs	Building	Heating	Fraction
1	Residential	District	70-90
2	Residential	Geothermal	5-10
3	Residential	Electricity	10-15
4	Non-residential	District	100

Baseline energy consumption per area unit

----#: . Note that below numbers are very preliminary (esp. electricity)! --Marjo 16:49, 13 March 2013 (EET) (type: truth; paradigms: science: comment)

Baseline energy consumption per area unit(kWh/m2/a)
Obs	Building	Heating	District heat	Electricity for heating	User electricity	Oil	Wood	Total electricity	Year	Description
1	Detached houses	District	134.74		50			184.74	2010	Calculated from energy company´s data; Pöyry
2	Detached houses	Electricity	0	130	50			180	2010	Energiapolar; Pöyry
3	Detached houses	Oil	0		50	134.74		50	2010	Pöyry. Efficiency 90-95% (energiatehokaskoti.fi).
4	Detached houses	Wood	0		50		134.74	50	2010	Assumption. Efficiency of good kettles 80%(energiatehokaskoti.fi).
5	Detached houses	Geothermal	0		90			90	2010	Assumption
6	Row houses	District	168.88		73.5			73.5	2010	Calculated from energy company´s data
7	Apartment houses	District	172.31		41.7			41.7	2010	Calculated from energy company´s data
8	Commercial buildings	District	161.82		229.6			229.6	2010	Calculated from energy company´s data
9	Offices	District	161.07		93.1			93.1	2010	Calculated from energy company´s data
10	Health and social sector buildings	District	214.97		122.81			122.81	2010	Calculated from energy company´s data
11	Public buildings	District	165.47		110.4			110.4	2010	Calculated from energy company´s data
12	Sports buildings	District	121.38		85.9			85.9	2010	Calculated from energy company´s data
13	Educational buildings	District	170.00		116.4			116.4	2010	Calculated from energy company´s data
14	Industrial buildings	District	168.44		212.4			212.4	2010	Calculated from energy company´s data
15	Leisure houses	Electricity	0	2.4	1			3.4	2010	Calculated from energy company´s data
16	Other buildings	District	138.14		170.3			170.3	2010	Calculated from energy company´s data

Pöyry 2011. ^[1]

Energiapolar. ^[2]

Energiatehokaskoti.fi/Öljylämmitys ^[3]

Baseline energy consumption per volume unit

----#: . Note that below numbers are very preliminary (esp. electricity)! --Marjo 16:49, 13 March 2013 (EET) (type: truth; paradigms: science: comment)

Baseline energy consumption per volume unit(kWh/m3/a)
Obs	Building	Heating	Heat	Electricity for heating	User electricity	Oil	Wood	Year	Description
1	Detached houses	District	42.15		15.67			2010	Calculated from energy company´s data; Energiapolar
2	Detached houses	Electricity	0	40.66	15.67			2010	Energiapolar
3	Detached houses	Oil	0		15.67	42.15		2010	Energiapolar
4	Detached houses	Wood	0		15.67		42.15	2010	Assumption
5	Detached houses	Geothermal	0		34.23			2010	Assumption
6	Row houses	District	53.25		23.16			2010	From energy company
7	Apartment houses	District	49.20		11.90			2010	From energy company
8	Commercial buildings	District	28.65		40.64			2010	From energy company
9	Offices	District	36.32		20.99			2010	From energy company
10	Health and social sector buildings	District	55.20		31.53			2010	From energy company
11	Public buildings	District	32.21		21.49			2010	From energy company
12	Sports buildings	District	18.37		13.00			2010	From energy company; Electricity value comes from city´s renovation data
13	Educational buildings	District	40.23		27.54			2010	From energy company
14	Industrial buildings	District	30.57		38.55			2010	From energy company
15	Leisure houses	Electricity	0	0.68	0.29			2010	From energy company
16	Other buildings	District	29.88		36.83			2010	From energy company

Renovation data

Fraction of houses renovated per year(%)
Obs	Constructed	Result	Description
1	2000-2010	0	Assumption
2	1990-1999	0	Assumption
3	1980-1989	2	Assumption
4	1970-1979	8	Assumption based on Pöyry 2011 s.27
5	1960-1969	8	Assumption based on Pöyry 2011 s.27
6	1950-1959	2	Assumption
7	1940-1949	2	Assumption
8	1930-1939	2	Assumption
9	1920-1929	2	Assumption
10	1910-1919	1	Assumption
11	1900-1909	1	Assumption
12	1799-1899	1	Assumption

New buildings per year

Floor area of new houses and additional construction per year(#,m2,m3)
Obs	Building	Number	Area	Volume	Year	Description
1	Detached houses	244-271	35137-40041	120728-141108	2010-2012	From city supervision of buildings
2	Row houses	26-39	13120-18408	44141-62721	2010-2012	From city supervision of buildings
3	Apartment houses	21-31	34815-55460	128154-209340	2010-2012	From city supervision of buildings
4	Commercial buildings	9-14	9742-87323	49576-651239	2010-2012	From city supervision of buildings
5	Offices	3-6	235-23891	993-106590	2010-2012	From city supervision of buildings
6	Industrial buildings	14-23	2948-11638	13555-78906	2010-2012	From city supervision of buildings
7	Public buildings	2-5	313-2819	905-17470	2010-2012	From city supervision of buildings
8	Educational buildings	4-6	220-14730	1745-74718	2010-2012	From city supervision of buildings
9	Health and social sector buildings	2-8	17-28843	280-175064	2010-2012	From city supervision of buildings
10	Sport buildings				2010-2012	From city supervision of buildings
11	Leisure buildings	47-69	2859-3660	9909 12693	2010-2012	From city supervision of buildings
12	Other buildings	317-421	19849-36194	80607-123013	2010-2012	From city supervision of buildings

Removed buildings per year

Number of removed buildings has been 15-25 per year during 2009-2012 according dismantling permissions of the city. The actual number may be somewhat larger.

Energy saving potential of different renovations

Energy saving potential of different renovations(%,kWh/m2/a)
Obs	Energy class	Building2	Renovation	Relative	Absolute	Description
1	Old	Residential	New windows and doors	15	25	Pöyry 2011
2	Old	Residential	New windows, sealing of building's sheath, improvement of building's technical systems	50	75	Pöyry 2011
3	Old	Residential	New windows, sealing of building's sheath, improvement of building's technical systems, significant reform of building's sheath	65	100	Pöyry 2011
4	Old	Non-residential	General renovation	15	-	Pöyry 2011
5			None	0	0

Building type comparisons(-)
Obs	Building	Building2
1	Detached houses	Residential
2	Row houses	Residential
3	Apartment houses	Residential
4	Commercial buildings	Non-residential
5	Offices	Non-residential
6	Industrial buildings	Non-residential
7	Public buildings	Non-residential
8	Educational buildings	Non-residential
9	Health and social sector buildings	Non-residential
10	Sport buildings	Non-residential
11	Leisure buildings	Non-residential
12	Other buildings	Non-residential

Energy use by the energy class of a building

Energy use by energy class of building(kWh/m2/a)
Obs	Energy class	Heating energy	Property and user electricity	Service water	Description
1	Old	150		30	Pöyry 2011 s.28
2	New	70	50	40	Pöyry 2011 s.32 (2010 SRMK)
3	Low-energy	35	50	40	Personal communication
4	Passive	17.5 - 25	50	40	Pöyry 2011 s.33; Personal communication

Energy classes of new buildings in the future(%)
Obs	Energy class	Constructed	Fraction	Description
1	New	2020-2029	10-20
2	Low-energy	2020-2029		The rest
3	Passive	2020-2029	25-35
4	New	2030-2039	5-10
5	Low-energy	2030-2039	20-50
6	Passive	2030-2039		The rest
7	New	2040-2049	0-5
8	Low-energy	2040-2049	10-30
9	Passive	2040-2049		The rest

Old: old buildings to be renovated (or in need of renovation)
New: normal new buildings (no current need of renovation)
Low-energy: buildings consuming about half of the energy of a new building
Passive: buildings consuming a quarter or less of the energy of a new building

Data regarding indoor environment quality (IEQ) factors

IEQ factors(h-1,%,%,%,-,%,%,%,Bq/m3)
Obs	Building	Heating	Ventilation rate	Dampness%	Smoking%	In noise areas%	Radon	Description
1	Detached houses	District	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	15	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
2	Detached houses	Electricity	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	15	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
3	Detached houses	Oil	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	15	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
4	Detached houses	Wood	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	15	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
5	Detached houses	Geothermal	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	15	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
6	Row houses	District	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	21	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
7	Apartment houses	District	0.71 (0.3-1.12)	5-16.5	2.35 (1.4-3.4)	30	100 (95-105)	Gens, 2012; Turunen et al. 2010; Haverinen-Shaughnessy, 2012; Assumption based on city´s data; Kurttio 2006
8	Leisure houses	Electricity
9	Offices	District			0			Assumption
10	Commercial buildings	District			0			Assumption
11	Health and social sector buildings	District			0			Assumption
12	Public buildings	District			0			Assumption
13	Sports buildings	District			0			Assumption
14	Educational buildings	District		24	0			Haverinen-Shaughnessy et al. 2012; Assumption
15	Industrial buildings	District			0			Assumption
16	Other buildings	District

Gens 2012 ^[4]

Haverinen-Shaughnessy 2010 ^[5]

Haverinen-Shaughnessy et al. 2012 ^[6]

Turunen et al. 2010 ^[7]

Other potentially useful data

Regulations regarding energy consumption of buildings

Maximum allowed energy consumption per unit (= E-value)(kWh/m2/a)
Obs	Building	Year	E-value	Description
1	Detached houses	2012 forward	204	Heated net area <120 m2; Finland´s Environmental Administration
2	Row houses	2012 forward	150	Finland´s Environmental Administration
3	Apartment houses	2012 forward	130	Finland´s Environmental Administration
4	Shops and other commercial buildings	2012 forward	240	Finland´s Environmental Administration
5	Offices	2012 forward	170	Finland´s Environmental Administration
6	Health and social sector buildings: Hospitals	2012 forward	450	Finland´s Environmental Administration
7	Health and social sector buildings: Health care centers etc.	2012 forward	170	Finland´s Environmental Administration
8	Public buildings	2012 forward	240	Finland´s Environmental Administration
9	Sports buildings	2012 forward	170	Does not apply to swimming- and ice halls; Finland´s Environmental Administration
10	Educational buildings	2012 forward	170	Finland´s Environmental Administration
11	Industrial buildings	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration
12	Leisure buildings	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration
13	Other buildings	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration

Emission factors for wood heating

Emission factors for wood heating(PJ/a; mg/MJ)
Obs	Type	Observation	Result	Description
1	Residential buildings	34.2 (30.8-37.6)		Karvosenoja et al. 2008
2	Primary wood-heated residential buildings	20.2 (16.6-23.9)		Karvosenoja et al. 2008
3	Manual feed boilers with accumulator tank	5.42 (3.89-7.22)	80.0 (37.6-150)	Karvosenoja et al. 2008
4	Manual feed boilers without accumulator tank	2.67 (1.67-3.87)	700 (329-1310)	Karvosenoja et al. 2008
5	Automatic feed wood chip boilers	1.46 (1.01-2)	50.0 (23.5-93.9)	Karvosenoja et al. 2008
6	Automatic feed pellet boilers	0.102 (0.0693-0.142)	30.0 (14.1-56.3)	Karvosenoja et al. 2008
7	Iron stoves	0.142 (0.0976-0.196)	700 (329-1310)	Karvosenoja et al. 2008
8	Other stoves and ovens	10.2 (7.86-12.8)	140 (65.8-263)	Karvosenoja et al. 2008
9	Low-emission stoves	0	80 (37.6-150)	Karvosenoja et al. 2008
10	Open fireplaces	0.163 (0.111-0.224)	800 (376-1500)	Karvosenoja et al. 2008
11	Supplementary wood-heated residential buildings	14.0 (10.7-17.4)		Karvosenoja et al. 2008
12	Iron stoves	0.212 (0.135-0.316)	700 (329-1310)	Karvosenoja et al. 2008
13	Other stoves and ovens	13.6 (10.4-16.9)	140 (65.8-263)	Karvosenoja et al. 2008
14	Low-emission stoves	0	80 (37.6-150)	Karvosenoja et al. 2008
15	Open fireplaces	0.222 (0.14-0.332)	800 (376-1500)	Karvosenoja et al. 2008
16	Recreational buildings	5.00 (4.50-5.50)		Karvosenoja et al. 2008
17	Iron stoves	0.782 (0.372-1.37)	700 (329-1310)	Karvosenoja et al. 2008
18	Other stoves and ovens	3.96 (3.19-4.59)	140 (65.8-263)	Karvosenoja et al. 2008
19	Open fireplaces	0.262 (0.118-0.477)	800 (376-1500)	Karvosenoja et al. 2008

Karvosenoja et al. 2008 ^[8]

Calculations for ovariables

+ Show code - Hide code

library(OpasnetUtils)

buildings2010 <- Ovariable(
	name = 'buildings2010',
	ddata = 'Op_en5932',
	subset = 'Building registry data'
)

energy.per.area <- Ovariable(
	name = 'energy.per.area',
	ddata = 'Op_en5932',
	subset = 'Baseline energy consumption per area unit'
)

heatingType <- Ovariable(
	name = 'heatingType',
	ddata = 'Op_en5932',
	subset = 'Fractions of houses according heating type'
)

heatingTypeFuture <- Ovariable(
	name = 'heatingTypeFuture',
	ddata = 'Op_en5932',
	subset = 'Future heating types'
)

energy.per.volume <- Ovariable(
	name = 'energy.per.volume',
	ddata = 'Op_en5932',
	subset = 'Baseline energy consumption per volume unit'
)


renovation <- Ovariable(
	name = 'renovation',
	ddata = 'Op_en5932',
	subset = 'Fraction of houses renovated per year'
)


construction <- Ovariable(
	name = 'construction',
	ddata = 'Op_en5932',
	subset = 'Floor area of new houses and additional construction per year'
)


energyClassesFuture <- Ovariable(
	name = 'energyClassesFuture',
	ddata = 'Op_en5932',
	subset = 'Energy classes of new buildings in the future'
)


Maximum.allowed.energy.consumption.per.unit <- Ovariable(
	name = 'Maximum.allowed.energy.consumption.per.unit',
	ddata = 'Op_en5932',
	subset = 'Maximum allowed energy consumption per unit (= E-value)'
)

energy.saving.potential.of.different.renovations <- Ovariable(
	name = 'energy.saving.potential.of.different.renovations',
	ddata = 'Op_en5932',
	subset = 'Energy saving potential of different renovations'
)

energy.saving.potential.of.different.renovations <- Ovariable(
	name = 'energy.saving.potential.of.different.renovations',
	ddata = 'Op_en5932',
	subset = 'Energy saving potential of different renovations'
)


energy.classes.of.buildings <- Ovariable(
	name = 'energy.classes.of.buildings',
	ddata = 'Op_en5932',
	subset = 'Energy use by energy class of building'
)

buildingTypes <- Ovariable(
	name = 'buildingTypes',
	ddata = 'Op_en5932',
	subset = 'Building type comparisons'
)

objects.store(
	buildings2010, 
	energy.per.area,
	energy.per.volume,
	heatingType,
	heatingTypeFuture,
	renovation,
	construction,
	energyClassesFuture,
	energy.saving.potential.of.different.renovations,
	energy.classes.of.buildings,
	buildingTypes
)

cat("Objects buildings2010, 
	energy.per.area,
	energy.per.volume,
	heatingType,
	heatingTypeFuture,
	renovation,
	construction,
	energyClassesFuture,
	energy.saving.potential.of.different.renovations,
	energy.classes.of.buildings,
	buildingTypes
initiated!\n")

Other preliminary calculations

+ Show code - Hide code

library(OpasnetUtils)
library(ggplot2)

if(secret) {
	objects.get("ozJoC2EaIChFI0uC") 
	building.stock <- objects.decode(etable, key)
} else {
	building.stock <- Ovariable("building.stock", ddata = "Op_en5932", getddata = FALSE)@output
}

colnames(building.stock) <- as.vector(t(building.stock[1, ]))
building.stock <- building.stock[2:nrow(building.stock) , ]

for(i in c(1,3,4,5,7,8)) {
	building.stock[[i]] <- as.numeric(gsub(",", "", building.stock[[i]]))
}

building.stock <- dropall(building.stock)

cat("Mean floor area of buildings in Kuopio by heating type.\n")

oprint(as.data.frame(as.table(tapply(
	building.stock$kokonaisala, 
	building.stock[c("paaasiallinen_lammitystapa")], 
	mean, 
	na.rm = TRUE
))))

ggplot(building.stock, aes(x = paaasiallinen_lammitystapa, weight = kokonaisala, fill = kayttotarkoitus)) + 
	geom_bar() +
	theme_grey(base_size = 24) + 
	theme(axis.text.x = element_text(angle = 90, hjust = 1))

Keywords

References

↑ Pöyry 2011: Kuopion kasvihuonekaasupäästöjen vähentämismahdollisuudet v 2020 mennessä. [1]
↑ Energiapolar/Arvioi sähkönkulutus[2]
↑ Energiatehokaskoti.fi/Öljylämmitys[3]
↑ Gens 2012 [4]
↑ Haverinen-Shaughnessy 2010 [5]
↑ Haverinen-Shaughnessy et al. 2012 [6]
↑ Turunen et al. 2010 [7]
↑ Karvosenoja et al. 2008 [8]

Related files

[1] Pöyry 2011: Kuopion kasvihuonekaasupäästöjen vähentämismahdollisuudet v 2020 mennessä. [1]

[2] Energiapolar/Arvioi sähkönkulutus[2]

[3] Energiatehokaskoti.fi/Öljylämmitys[3]

[4] Gens 2012 [4]

[5] Haverinen-Shaughnessy 2010 [5]

[6] Haverinen-Shaughnessy et al. 2012 [6]

[7] Turunen et al. 2010 [7]

[8] Karvosenoja et al. 2008 [8]

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

Building stock in Kuopio

Contents

Question

Answer

Rationale

City-specific data

Building registry data

Fractions of houses according to heating type

Baseline energy consumption per area unit

Baseline energy consumption per volume unit

Renovation data

New buildings per year

Removed buildings per year

Energy saving potential of different renovations

Energy use by the energy class of a building

Data regarding indoor environment quality (IEQ) factors

Other potentially useful data

Regulations regarding energy consumption of buildings

Emission factors for wood heating

Calculations for ovariables

Other preliminary calculations

See also

Keywords

References

Related files

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