Building model

This page is a knowledge crystal of subtype method. The page identifier is Op_en6289
Moderator:Jouni (see all)
Upload data {{#opasnet_base_link:Op_en6289}}

Question

How to estimate the size of the building stock of a city, including heating properties, renovations etc? The situation is followed over time, and different policies can be implemented.

Answer

For examples of model use, see Building stock in Kuopio and Climate change policies and health in Kuopio.

Rationale

Causal diagram of the building model.

Calculations

+ Show code- Hide code library(OpasnetUtils) ########## Calculate all building events (constructions, demolitions, renovations) buildings <- Ovariable("buildings", dependencies = data.frame(Name = c( "stockBuildings", # Building stock given as an amount at given timepoints "heatingShares", # Heating types of current buildings "efficiencyShares", # Energy efficiency types of current buildings "changeBuildings", # Construction or demolition rate as floor-m2. Indices Efficiency and # Heating should be included here, if used. # "buildingTypes", # A dummy variable to combine two different indices: Building and Building2 "renovationShares", # Fraction of renovation type when renovation is done. "rateBuildings", # Percentage of renovations and other relative changes per year "year" # A data.frame of years for which observations are calculated. This requires timepoints function. )), formula = function(...) { ######## Current building stock stock <- stockBuildings * heatingShares * efficiencyShares # if(!"Startyear" %in% colnames(stock@output)) { # Make a duplicate of Time because Startyear is needed later. # marginals <- colnames(stock@output)[stock@marginal] # stock@output$Startyear <- stock@output$Time # stock@marginal <- colnames(stock@output) %in% c(marginals, "Startyear") # } #### Changes in building stock due to construction etc. # change <- changeBuildings change <- timepoints(changeBuildings, obsyear, sumtimecol = FALSE) # Cumulative changes at certain timepoints. nw <- stock nw@output$Time <- as.numeric(as.character(nw@output$Time)) nw@output <- subset(nw@output, Time == max(Time)) colnames(nw@output)[colnames(nw@output) == "Time"] <- "Startyear" changeBuildings@output$Startyear <- as.numeric(as.character(changeBuildings@output$Startyear)) nw <- unkeep(nw, prevresults = TRUE, sources = TRUE) nw@output <- orbind(nw, unkeep(1 * changeBuildings, prevresults = TRUE, sources = TRUE)) # nw <- # stock <- unkeep(change, cols = "Startyear") # change@marginal <- colnames(change@output) %in% c( # "Age", # colnames(stock@output)[stock@marginal], # colnames(changeBuildings@output)[changeBuildings@marginal] # ) # change <- unkeep(change, cols = "Startyear", prevresults = TRUE, sources = TRUE) ########### Floor area of renovations. Combine with continuous index Age. reno <- nw * renovationShares marginals <- colnames(reno@output)[reno@marginal] reno@output$Age <- as.numeric(as.character(reno@output$Time)) - as.numeric(as.character(reno@output$Startyear)) reno@marginal <- colnames(reno@output) %in% marginals reno <- reno * 0.03 # continuousOps(reno, renovationRate, '*') FIX continuousOps reno@output$Startyear <- reno@output$Time # Renovation is the new event. reno <- oapply(reno, cols = c("Age", "Time"), FUN = sum) reno <- timepoints(reno, obstime) reno@output <- reno@output[result(reno) != 0 , ] out <- reno * -1 # Equal amount stops being non-renovated. out@output$Renovation <- "None" out@output$Renovation <- as.factor(out@output$Renovation) out <- orbind(out, reno) # Temp2: Construction + renovation in data.frame for(i in colnames(reno@output)[reno@marginal]) { out[[i]][is.na(out[[i]])] <- "Not known" } return(out) } ) ### HeatingEnergy heatingEnergy <- Ovariable("heatingEnergy", dependencies = data.frame(Name = c( "energyUse", # Energy consumption per floor area "efficiencyRatio", # Relative energy consumption compared with the efficiency group Old. "renovationRatio", # Relative energy consumption compared with the Renovation "buildings", "buildingTypes" )), formula = function(...) { out <- buildings * buildingTypes * energyUse * efficiencyRatio * renovationRatio return(out) } ) ####### Calculate emissions emissions <- Ovariable("emissions", dependencies = data.frame( Name = c( "heatingEnergy", "fuelTypes", "emissionFactors" ) ), formula = function(...) { out <- oapply(heatingEnergy, cols = c("Building", "Efficiency"), FUN = sum) out <- out * fuelTypes * emissionFactors * 3.6 * 1E-9 # convert from kWh /a to MJ /a and mg to ton out <- unkeep(out * emissionLocations, sources = TRUE, prevresults = TRUE) out@output$Emission_site <- as.factor(ifelse( out@output$Emission_site == "At site of consumption", as.character(out@output$City_area), as.character(out@output$Emission_site) )) out <- oapply( out, cols = c("Heating", "Burner", "Fuel", "City_area"), FUN = sum ) } ) #"Emission_site", "Emission_height", exposure <- Ovariable("exposure", # emis is in ton /a # iF = conc (g /m3) * pop (#) * BR (m3 /s) / emis (g /s) <=> conc = emis * iF / BR / pop # conc is the exposure concentration dependencies = data.frame(Name = c("emis2", "iF", "pop")), formula = function(...) { BR <- 20 # Nominal breathing rate (m^3 /d) BR <- BR / 24 / 3600 # m^3 /s out <- 1E+12 / 365 / 24 / 3600 # Emission scaling from ton /a to ug /s. out <- (emis2 * out) * iF / BR / pop # the actual equation out <- unkeep(out, prevresults = TRUE, sources = TRUE) return(out) } ) objects.store(buildings, heatingEnergy, emissions, exposure) cat("Saved ovariables buildings, heatingEnergy, emissions, exposure\n")

Dependencies

• Exposure to PM2.5 in Finland
• OpasnetUtils/Drafts
• Energy use of buildings
• Ovariables used or produced and example pages where they are used:
  • Building stock in Kuopio
    • buildingStock, # Current building stock
    • renovation, # Percentage of renovations per year
    • renovationShares, # Fraction of renovation type when renovation is done.
    • construction, # Construction rate in the future
    • constructionAreas,
    • buildingTypes, # A dummy variable to combine two different indices: Building and Building2
    • heatingShares, # Heating types of current buildings
    • heatingSharesNew, # Heating types of the buildings in the future
    • buildings,
  • Energy use of buildings
    • energyUse,
    • efficienciesNew, # Energy efficiencies in the future
    • savingPotential,
  • Climate change policies and health in Kuopio
    • eventyear, # A dummy variable to combine time periods to numerical time axis.
    • efficiencies, # Energy efficiencies of current buildings
    • obsyear # Years for which observations are calculated. This requires timepoints function.

See also

• Building stock in Kuopio
• Building stock in Europe
• Building data availability in Kuopio
• Energy balance
• Greenhouse gas emissions in Kuopio
• heande:File:2013 10 29 - Exposure-Response Functions.xlsx
• heande:Health impact assessment framework
• heande:File:2013 10 29 WP6.2 Agreed ER.doc
• heande:Urgenche: Workpackage Exposure, Health, and Well-being
• heande:File:WP6 Deliverable 6 1.doc
• Land use in Kuopio

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