Buildings in Basel

This page is a knowledge crystal of subtype variable. The page identifier is Op_en7044
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Question

What is the building stock in Basel?

Rationale

Data

Detailed data can be found from heande:Buildings in Basel. This data is aggregated to the postal code level. The table uses Swiss Land Survey coordinates CH1903. [1] [2] Use this code in the ova2spat function:

proj4string = "+init=epsg:21781"

Renovations

Estimates from Laura Perez and Stephan Trüeb, unibas.ch N:\YMAL\Projects\Urgenche\WP9 Basel\Energy_scenarios_Basel_update.docx

Fraction of houses renovated per year(%)

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

Popularity of renovation types(%)

Obs	Renovation	Fraction	Description
1	None	0
2	Windows	65
3	Technical systems	30
4	Sheath reform	5
5	General	0

Emission locations

Where and how do the emissions of heating take place?

Emission locations(-)

Obs	Heating	Emission site	Emission height	Dummy
1	District	4056	High	4056 is the postal code of the heat and power plant IWB, Hagenaustrasse 40/70 4056 Basel.
2	Long-distance heating	4056	High
3	Electricity	4056	High
4	Geothermal	4056	High
5	Centrifuge, hydro-extractor	4056	High
6	Heating oil	At site of consumption	Ground
7	Wood	At site of consumption	Ground
8	Gas	At site of consumption	Ground
9	Coal	At site of consumption	Ground
10	Solar heater/ collector	At site of consumption	Ground
11	No energy source	At site of consumption	Ground
12	Other sources	At site of consumption	Ground

Locations of postal codes(epsg:21781)

Obs	Postal code	X	Y
1	4001	611296.55	267316.04
2	4051	611004.37	267137.18
3	4052	612735.06	266596.60
4	4053	611695.00	265635.41
5	4054	609694.31	266598.91
6	4055	609798.12	267812.13
7	4056	610271.78	268500.37
8	4057	611580.35	268976.81
9	4058	612781.70	268225.32
10	4059	611615.85	264689.04
11	4125	615721.84	269737.40
12	4126	617160.01	268852.20

Fuel use by heating type

Basel-specific data about connections between Heating and fuel usage. Generic data should be taken from Energy balance.

Fuel use by heating type(-)

Obs	Heating	Burner	Fuel	Fraction	Description
1	Long-distance heating	Large fluidized bed	Waste	0.5	The values are from Wikipedia for Basel. See below.
2	Long-distance heating	Large fluidized bed	Wood	0.1
3	Long-distance heating	Large fluidized bed	Gas	0.4
4	Long-distance heating	Grid	Electricity	0	This is geothermally-generated district heating. Note: the fraction you need electricity is ca. 0.3*the amount of geoheat produced.
5	Coal	Large fluidized bed	Coal	1

For guesstimates about Long-distance heating (which is used in Basel), see Climate change policies in Basel and de:IWB.

+ Show code- Hide code ## This code is Op_en7044/fuelShares on page [[Buildings in Basel]] library(OpasnetUtils) fuelShares <- Ovariable("fuelShares", dependencies = data.frame( Name = "fuelSharesgeneric", Ident = "Op_en5141/fuelSharesgeneric" # [[Energy balance]] ), formula = function(...) { dat <- EvalOutput(Ovariable("dat", ddata = "Op_en7044", subset = "Fuel use by heating type")) # [[Buildings in Basel]] colnames(dat@output) <- gsub("[ \\.]", "_", colnames(dat@output)) out <- combine(fuelSharesgeneric, dat, name = "fuelShares") out <- out * Ovariable(output = data.frame(Time = 1900:2080, Result = 1), marginal = c(TRUE, FALSE)) out <- unkeep(out, prevresults = TRUE, sources = TRUE) return(out) } ) objects.store(fuelShares) cat("Object fuelShares stored.\n")

Calculations

This code creates ovariables that are needed to run the Building model and its ovariables buildings and heatingEnergy.

+ Show code- Hide code library(OpasnetUtils) # [[Buildings in Basel]], building stock, locations by postal codes (in A Swiss coordinate system) stockBuildings <- Ovariable("stockBuildings", ddata = "Op_en7044.postal_code_areas") colnames(stockBuildings@data)[colnames(stockBuildings@data) == "Built"] <- "Time" colnames(stockBuildings@data)[colnames(stockBuildings@data) == "Postal code"] <- "City_area" # Construction rate is assumed to be 2 % /a from the year 2010 building stock. changeBuildings <- stockBuildings changeBuildings@name <- "changeBuildings" colnames(changeBuildings@data)[colnames(changeBuildings@data) == "stockBuildingsResult"] <- "changeBuildingsResult" changeBuildings@data$changeBuildingsResult <- changeBuildings@data$changeBuildingsResult * 0.02 changeBuildings@data$Time <- NULL changeBuildings@data <- merge(changeBuildings@data, data.frame(Time = 2015 + 0:7 * 5)) # Geolocations of the buildings for emission calculations. OLD VERSION # emissionLocations <- Ovariable("emissionLocations", ddata = "Op_en7044.locations_of_postal_codes") # colnames(emissionLocations@data)[colnames(emissionLocations@data) == "emissionLocationsResult"] <- "Y" # emissionLocations@data$emissionLocationsResult <- 1 emissionLocations <- Ovariable("emissionLocations", ddata = "Op_en7044", subset = "Emission locations") colnames(emissionLocations@data) <- gsub("[ \\.]", "_", colnames(emissionLocations@data)) emissionLocations@data$emissionLocationsResult <- 1 heatingShares <- 1 # This is already in the Basel data. renovationRate <- Ovariable('renovationRate', dependencies = data.frame(Name = "dummy"), formula = function(...) { temp <- tidy(opbase.data('Op_en7044', subset = 'Fraction of houses renovated per year')) temp$Age <- round(as.numeric(as.character(temp$Age))) out <- as.data.frame(approx( temp$Age, temp$Result, n = (max(temp$Age) - min(temp$Age) + 1), method = "constant" )) colnames(out) <- c("Age", "renovationRateResult") out$renovationRateResult <- out$renovationRateResult / 100 out <- Ovariable("renovationRate", output = out, marginal = c(TRUE, FALSE)) return(out) } ) renovationShares <- Ovariable("renovationShares", dependencies = data.frame(Name = "dummy"), formula = function(...) { out <- Ovariable("raw", ddata = 'Op_en7044', subset = 'Popularity of renovation types') out <- findrest((out), cols = "Renovation", total = 100) / 100 renovationyear <- Ovariable("renovationyear", data = data.frame( Obsyear = factor(c(2020, 2030, 2040, 2050)), Result = 1 )) out <- out * renovationyear # renovation shares repeated for every potential renovation year. out@output$Renovation <- factor(out@output$Renovation, levels = c( "None", "General", "Windows", "Technical systems", "Sheath reform" ), ordered = TRUE) return(out) } ) dummy <- 1 objects.store( stockBuildings, # Current building stock changeBuildings, # Building stock change per year emissionLocations, # Locations of buildings and emissions heatingShares, # Heating types of current buildings renovationRate, # Percentage of renovations per year renovationShares, # Fraction of renovation type when renovation is done. From [[Building stock in Kuopio]] dummy # Needed by renovationShares ) cat("Objects stockBuildings, changeBuildings, emissionLocations, heatingShares, renovationRate, renovationShares stored.\n")

See also

Urgenche research project 2011 - 2014: city-level climate change mitigation

Urgenche pages Urgenche main page · Category:Urgenche · Urgenche project page (password-protected) Relevant data Building stock data in Urgenche‎ · Building regulations in Finland · Concentration-response to PM2.5 · Emission factors for burning processes · ERF of indoor dampness on respiratory health effects · ERF of several environmental pollutions · General criteria for land use · Indoor environment quality (IEQ) factors · Intake fractions of PM · Land use in Urgenche · Land use and boundary in Urgenche · Energy use of buildings Relevant methods Building model · Energy balance · Health impact assessment · Opasnet map · Help:Drawing graphs · OpasnetUtils‎ · Recommended R functions‎ · Using summary tables‎ City Kuopio Climate change policies and health in Kuopio (assessment) · Climate change policies in Kuopio (plausible city-level climate policies) · Health impacts of energy consumption in Kuopio · Building stock in Kuopio · Cost curves for energy (prioritization of options) · Energy balance in Kuopio (energy data) · Energy consumption and GHG emissions in Kuopio by sector · Energy consumption classes (categorisation) · Energy consumption of heating of buildings in Kuopio · Energy transformations (energy production and use processes) · Fuels used by Haapaniemi energy plant · Greenhouse gas emissions in Kuopio · Haapaniemi energy plant in Kuopio · Land use in Kuopio · Building data availability in Kuopio · Password-protected pages: File:Heat use in Kuopio.csv · Kuopio housing City Basel Buildings in Basel (password-protected) Energy balances Energy balance in Basel · Energy balance in Kuopio · Energy balance in Stuttgart · Energy balance in Suzhou