Climate change policies and health in Kuopio

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Scope

Question

What are potential climate policies that reach the greenhouse emission targets in the city of Kuopio for years 2010-2030? What are their effects on health and well-being, and what recommendations can be given based on this? The national greenhouse emission target is to reduce greenhouse gas emissions by 20 % between 1990 and 2020; the city of Kuopio has its own, more ambitious target of 40 % for the same time period.

Boundaries

• Time: Year 2010 - 2030
• Spatial: Activities in Kuopio, Finland. Health and well-being effects due to policies anywhere, e.g. fine particle emissions in Kuopio increase cardiovascular mortality all over Finland.

Scenarios

• Two scenarios for each climate policy (which have not been defined yet): policy is A) implemented, B) not implemented.

Intended users

• The city of Kuopio.
• Other cities in Urgenche.
• Urgenche researchers are users from the methodological point of view.

Participants

• Main participants:
  • City of Kuopio: Erkki Pärjälä, Mikko Savastola
  • THL: Marjo Niittynen, Jouni Tuomisto, Matti Jantunen.
• Other participants:
  • University of Exeter
  • Universität Stuttgart
  • Other Urgenche research groups
  • Other Urgenche cities

Answer

Results

Not yet available.

Conclusions

The target of 40 % GHG reduction seems realistic.

Rationale

See other parts of the assessment:

• Climate change policies and health in Kuopio/Decisionmakers

This diagram is just a placeholder. A new file should be uploaded, because this is about another assessment.

+ Show code- Hide code library(OpasnetBaseUtils) library(xtable) n <- 5 names.Kuopio <- tidy(op_baseGetData("opasnet_base", "Op_en5461")) # Download the object names and identifiers. decisionmakers.Kuopio <- tidy(op_baseGetData("opasnet_base", "Op_en5583")) # Download the decisionmaker info. ccph.Kuopio <- new("oassessment", names = names.Kuopio, vars = init.vars(names.Kuopio), decisionmakers = decisionmakers.Kuopio ) ccph.Kuopio print(ccph.Kuopio)

Decision variables

• Plausible climate change policies in Kuopio can be found in detail at Climate change policies in Kuopio
  • Major policies/aims
    • Compared to 1990, 40% reduction in total GHG emissions in Kuopio by 2020.
    • Compared to 2005, 9% reduction in city´s own energy use by 2016.
• Specific actions
  • Energy production
    • New power plant unit in Haapaniemi: ability to use more biomass
  • Building stock
    • Energy efficiency of buildings is increased: new stricter building regulations in Finland (2/2013)
    • Education to building owners and managers: semblance of best practicies in heating and other use of energy. Possible reduction in energy use of building stock is about 10%, and mere beneficial health effects are expected.
  • Land use and transport
    • City of Kuopio finds out, whether it is possible to get an updated version of Kuopio´s traffic network
    • Alternatively, the effect of increased use of biofuels on GHG and CO2 emissions is evaluated.

Indicators

• Cardiovascular mortality
• Pulmonar mortality
• Well-being...

Assessment-specific data

Climate change policies and health in Kuopio: Difference between revisions(-)

Obs	Name	Identifier	Cell	Direction	Result
1	Climate change policies in Kuopio	Op_en5466		wide	decisions
2	Climate change policies in Kuopio	Op_en5466		wide	stakeholders
3	Climate change policies in Kuopio	Op_en5466		wide	probabilities
4	Energy consumption of heating of buildings in Kuopio	Op_en5699	Energy source:District heat	wide	heating.energy
5	Fuels used by Haapaniemi energy plant	Op_en5690		wide	fuel.fractions
6	Emission factors for burning processes	Op_en2791		wide	emission.factors
7	Haapaniemi energy plant in Kuopio	Op_en5688	Production type:Heat	wide	energy.production
8	Climate education in Kuopio	Op_en5582		wide	climate.education
9	Cost curves for energy	Op_en5478		long	cost.curve
10	Energy transformations	Op_en5472		wide	transformation
11	Energy balance in Kuopio	Op_en5469		wide	energy.balance
12	Greenhouse gas emissions in Kuopio	Op_en5483	Sector:District heating	long	GHG.emission
13	Building registry data
14	Use of electricity by building type
15	Use of heat by contract

+ Show code- Hide code cat("Functions initiated. Now starting model.\n") energy.production <- make.ovariable(fetch("Op_en5688"), name = "energy.production") fuel.fractions <- make.ovariable(fetch("Op_en5690"), name = "fuel.fractions") emission.factors <- make.ovariable(fetch("Op_en2791"), name = "emission.factors") print(emission.factors) print(fuel.fractions) print(energy.production) out <- fuel.fractions * energy.production * emission.factors print(out) plot(out) assessment <- make.oassessment("Op_en5461") print(assessment) plot(assessment)

Formula

Addition of biofuels in transportation (ktoe/a): How much energy is saved from the heating of buildings, compared with 2010? (%): + Show code- Hide code library(OpasnetBaseUtils) library(ggplot2) library(xtable) cat("Loading functions and data.\n") city <- "Kuopio" energy <- summary.bring("Op_en5473") # Category:Energy balance tran <- tidy(op_baseGetData("opasnet_base", "Op_en5472")) # Energy transformations classes <- tidy(op_baseGetData("opasnet_base", "Op_en5476")) # Energy consumption classes cat("Running model.\n") energy <- energy[energy$Place == city, ] energy$Amount <- as.numeric(energy$Amount) # The policy changes are implemented. energy.stra <- energy energy.stra$Amount <- ifelse(energy.stra$Transformation == "Traffic biofuel production" & energy.stra$Fuel == "Petrochemical products", energy.stra$Amount + biofuels, energy.stra$Amount) energy.stra$Amount <- ifelse(energy.stra$Process == "Heating" & energy.stra$Use == "Output", energy$Amount * (1 - heatsave / 100), energy.stra$Amount) energy <- rbind(data.frame(Action = "BAU", energy), data.frame(Action = "Policy", energy.stra)) #### The transformation processes are included. tran <- reshape(tran, idvar = c("Process", "Transformation", "Use", "Fuel"), timevar = "Observation", direction = "wide") colnames(tran) <- gsub("Result.", "", colnames(tran)) tran$Amount <- as.numeric(tran$Amount) # Calculate conversion factors. factors <- merge(tran, energy, by = c("Process", "Transformation", "Use", "Fuel")) mwh2ktoe <- 3600 / (35 * 1000) # 1 MWh = 3600 MWs / (35 MJ / kgoe * 1000 kgoe/toe) factors$Amount.x <- factors$Amount.y / (factors$Amount.x * mwh2ktoe) # Add conversion factors to the energy table. energy <- merge(tran, factors, by = c("Process", "Transformation"), all.x = TRUE) energy$Amount <- energy$Amount * energy$Amount.x energy <- energy[!colnames(energy) %in% c("Use.y", "Fuel.y", "Unit.x", "Amount.x", "Unit.y", "Amount.y")] colnames(energy) <- gsub(".x", "", colnames(energy)) # Convert energy values to ktoe. energy$Amount <- ifelse(energy$Unit == "MWh", energy$Amount * mwh2ktoe, energy$Amount) energy[energy$Unit == "MWh", "Unit"] <- "ktoe" fuels <- c("Coal and peat", "Crude oil", "Petrochemical products", "Gas", "Nuclear", "Hydro", "Geothermal solar wind", "Renewables and waste", "Electricity", "Heat") # Categorise energy to standard energy processes and calculate sums for each process. out <- merge(energy, classes, by.x = "Process", by.y = "Result") out <- as.data.frame(as.table(tapply(out$Amount, out[c("Class", "Fuel", "Use", "Action")], sum))) out <- out[!is.na(out$Freq) & out$Fuel %in% fuels, ] # & out$Use == "Input", ] print(xtable(out), type = 'html') # NOW how do we tell the energy need in the balance sheet? ggplot(energy[energy$Fuel == "CO2e", ], aes(x = Action, weight = Amount, fill = Process)) +geom_bar(position = "Stack") ggplot(energy[energy$Fuel == "PM2.5", ], aes(x = Action, weight = Amount, fill = Process)) +geom_bar(position = "Stack") ggplot(energy[energy$Fuel == "Ash", ], aes(x = Action, weight = Amount, fill = Process)) +geom_bar(position = "Stack") ggplot(energy[energy$Fuel == "Heat", ], aes(x = Action, weight = Amount, fill = Process)) +geom_bar(position = "Stack")

----#: . This is a city-specific copy of the original code: Energy balance. --Jouni 06:52, 27 January 2012 (EET) (type: truth; paradigms: science: comment)

Analyses

• Decision analysis on each policy: Which option minimises the health risks?
• Value-of-information analysis for each policy about the major variables in the model and the total VOI.

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

The average usage of firewood in certain types of houses according to the wain heating system in 2000-2001 in Finland (m^3/household/year)

Main heating system		Type of estate
		Detached house	Farm	Free-time place	Total
Stove heating		7.1	10	2	4.4
Central heating	Wood	13.7	25.6	..	18.4
	Oil	1.8	8.2	..	2.3
	Electricity	2.5	7.8	..	2.8
Straight electric heating		2.9	6.5	1.6	2.7
District heating		1.1	..	..	1.2
All		3.8	14.4	1.8	4.4

Related files

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