Climate change policies and health in Kuopio: Difference between revisions
(→Direct inputs: rcode DALYs created) |
(→Results: model version 1 copied to be the basis of version 2) |
||
Line 63: | Line 63: | ||
===Results=== | ===Results=== | ||
==== Model version 2 ==== | |||
:''This model version was used to produce the corrected manuscript in July 2015. | |||
<rcode graphics=1 store=0 variables="name:server|type:hidden|default:TRUE"> | |||
### THIS CODE IS FROM PAGE [[Climate change policies and health in Kuopio]] (Op_en5461, code_name = "") | |||
# Siirrä Kuopion-datat kässäristä linkin taakse Opasnettiin | |||
# KÄssäriin vain yhteenvetotaulukko joka kaupungista. | |||
# Mieti mitä sanotaan sisäilmasta. Perusmalli toimii ilmankin, ja Matin nostama miljoonan sisäilman hankaluus pitäisi lähinnä keskustella. Käytetäänkä ylileveitä jakaumia? | |||
# Onko järkeä yhdistää kaupungit? Silloin tulisi NA:ta eri päätösten kohdalle, ja tämä pitäisi huomioida kuvissa (muutenkin kannattaisi slaissata data ennen kuvien piirtämistä). | |||
# Tarkista iF jota käytetään: Mikä on iF-summary? | |||
library(OpasnetUtils) | |||
library(ggplot2) | |||
library(rgdal) | |||
library(maptools) | |||
library(RColorBrewer) | |||
library(classInt) | |||
#library(OpasnetUtilsExt) | |||
library(RgoogleMaps) | |||
openv.setN(0) # use medians instead of whole sampled distributions | |||
objects.latest("Op_en6007", code_name = "answer") # [[OpasnetUtils/Drafts]] findrest | |||
obstime <- data.frame(Startyear = (192:205) * 10) # Observation years must be defined for an assessment. | |||
## Additional index needed in followup of ovariables efficiencyShares and stockBuildings | |||
year <- Ovariable("year", data = data.frame( | |||
Constructed = factor( | |||
c("1799-1899", "1900-1909", "1910-1919", "1920-1929", "1930-1939", "1940-1949", | |||
"1950-1959", "1960-1969", "1970-1979", "1980-1989", "1990-1999", | |||
"2000-2010", "2011-2019", "2020-2029", "2030-2039", "2040-2049" | |||
), | |||
ordered = TRUE | |||
), | |||
Time = c(1880, 1905 + 0:14 * 10), | |||
Result = 1 | |||
)) | |||
BS <- 24 | |||
heating_before <- FALSE | |||
efficiency_before <- TRUE | |||
figstofile <- FALSE | |||
###################### Decisions | |||
decisions <- opbase.data('Op_en5461', subset = "Decisions") # [[Climate change policies and health in Kuopio]] | |||
DecisionTableParser(decisions) | |||
# Remove previous decisions, if any. | |||
rm( | |||
"buildings", | |||
"stockBuildings", | |||
"changeBuildings", | |||
"efficiencyShares", | |||
"energyUse", | |||
"heatingShares", | |||
"renovationShares", | |||
"renovationRate", | |||
"fuelShares", | |||
"year", | |||
envir = openv | |||
) | |||
############################ City-specific data | |||
####!------------------------------------------------ | |||
objects.latest("Op_en5417", code_name = "initiate") # [[Population of Kuopio]] | |||
# population: City_area | |||
objects.latest("Op_en5932", code_name = "initiate") # [[Building stock in Kuopio]] Building ovariables: | |||
# buildingStock: Building, Constructed, City_area | |||
# rateBuildings: Age, (RenovationPolicy) | |||
# renovationShares: Renovation | |||
# construction: Building | |||
# constructionAreas: City_area | |||
# buildingTypes: Building, Building2 | |||
# heatingShares: Building, Heating, Eventyear | |||
# heatingSharesNew: Building2, Heating | |||
# eventyear: Constructed, Eventyear | |||
# efficiencyShares: Time, Efficiency | |||
renovationRate <- EvalOutput(renovationRate) * 10 # Rates for 10-year periods | |||
#################### Energy use (needed for buildings submodel) | |||
####!------------------------------------------------ | |||
objects.latest("Op_en5488", code_name = "initiate") # [[Energy use of buildings]] | |||
# energyUse: Building, Heating | |||
# efficiencyShares: Efficiency, Constructed | |||
# renovationRatio: Efficiency, Building2, Renovation | |||
####i------------------------------------------------ | |||
###################### Actual building model | |||
# The building stock is measured as m^2 floor area. | |||
####!------------------------------------------------ | |||
objects.latest("Op_en6289", code_name = "initiate") # [[Building model]] # Generic building model. | |||
# buildings: formula-based | |||
# heatingEnergy: formula-based | |||
####i------------------------------------------------ | |||
buildings <- EvalOutput(buildings) | |||
buildings@output$RenovationPolicy <- factor( | |||
buildings@output$RenovationPolicy, | |||
levels = c("BAU", "Active renovation", "Effective renovation"), | |||
ordered = TRUE | |||
) | |||
buildings@output$EfficiencyPolicy <- factor( | |||
buildings@output$EfficiencyPolicy, | |||
levels = c("BAU", "Active efficiency"), | |||
ordered = TRUE | |||
) | |||
bui <- oapply(buildings * 1E-6, cols = c("City_area", "buildingsSource"), FUN = sum)@output | |||
ggplot(subset(bui, RenovationPolicy == "BAU" & EfficiencyPolicy == "BAU"), aes(x = Time, weight = buildingsResult, fill = Heating)) + geom_bar(binwidth = 5) + | |||
theme_gray(base_size = BS) + | |||
labs( | |||
title = "Building stock in Kuopio", | |||
x = "Time", | |||
y = "Floor area (M m2)" | |||
) | |||
if(figstofile) ggsave("Figure3.eps", width = 8, height = 7) | |||
ggplot(subset(bui, EfficiencyPolicy == "BAU"), aes(x = Time, weight = buildingsResult, fill = Renovation)) + | |||
geom_bar(binwidth = 5) + | |||
facet_grid(. ~ RenovationPolicy) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Building stock in Kuopio by renovation policy", | |||
x = "Time", | |||
y = "Floor area (M m2)" | |||
) | |||
ggplot(subset(bui, RenovationPolicy == "BAU"), aes(x = Time, weight = buildingsResult, fill = Efficiency)) + geom_bar(binwidth = 5) + | |||
facet_grid(. ~ EfficiencyPolicy) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Building stock in Kuopio by efficiency policy", | |||
x = "Time", | |||
y = "Floor area (M m2)" | |||
) | |||
ggplot(subset(bui, RenovationPolicy == "BAU" & EfficiencyPolicy == "BAU"), aes(x = Time, weight = buildingsResult, fill = Building)) + geom_bar(binwidth = 5) + | |||
theme_gray(base_size = BS) + | |||
labs( | |||
title = "Building stock in Kuopio", | |||
x = "Time", | |||
y = "Floor area (M m2)" | |||
) | |||
###################### Energy and emissions | |||
####!------------------------------------------------ | |||
objects.latest("Op_en2791", code_name = "initiate") # [[Emission factors for burning processes]] | |||
# emissionFactors: Burner, Fuel, Pollutant | |||
# fuelShares: Heating, Burner, Fuel | |||
####i------------------------------------------------ | |||
heatingEnergy <- EvalOutput(heatingEnergy) | |||
################ Transport and fate | |||
objects.latest("Op_en5813", code_name = "initiate") # [[Intake fractions of PM]], iF | |||
emissions <- EvalOutput(emissions) | |||
emissions@output$Time <- as.numeric(as.character(emissions@output$Time)) | |||
# Plot energy need and emissions | |||
ggplot(subset(heatingEnergy@output, EfficiencyPolicy == "BAU"), aes(x = Time, weight = heatingEnergyResult * 1E-6, fill = Heating)) + geom_bar(binwidth = 5) + | |||
facet_wrap( ~ RenovationPolicy) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Energy used in heating in Kuopio", | |||
x = "Time", | |||
y = "Heating energy (GWh /a)" | |||
) | |||
if(figstofile) ggsave("Figure4.eps", width = 11, height = 7) | |||
emis <- truncateIndex(emissions, cols = "Emission_site", bins = 5)@output | |||
ggplot(subset(emis, EfficiencyPolicy == "BAU" & RenovationPolicy == "BAU"), aes(x = Time, weight = emissionsResult, fill = Fuel)) + geom_bar(binwidth = 5) + | |||
facet_grid(Pollutant ~ FuelPolicy, scale = "free_y") + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Emissions from heating in Kuopio", | |||
x = "Time", | |||
y = "Emissions (ton /a)" | |||
) | |||
if(figstofile) ggsave("Figure5.eps", width = 8, height = 7) | |||
ggplot(heatingEnergy@output, aes(x = Time, weight = heatingEnergyResult * 1E-6, fill = Heating)) + geom_bar(binwidth = 5) + | |||
facet_grid(EfficiencyPolicy ~ RenovationPolicy) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Energy used in heating in Kuopio", | |||
x = "Time", | |||
y = "Heating energy (GWh /a)" | |||
) | |||
ggplot(subset(emis, EfficiencyPolicy == "BAU" & RenovationPolicy == "BAU"), aes(x = Time, weight = emissionsResult, fill = Fuel)) + geom_bar(binwidth = 5) + | |||
facet_grid(Pollutant ~ FuelPolicy, scale = "free_y") + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Emissions from heating in Kuopio", | |||
x = "Time", | |||
y = "Emissions (ton /a)" | |||
) | |||
ggplot(subset(emis, EfficiencyPolicy == "BAU" & FuelPolicy == "BAU"), aes(x = Time, weight = emissionsResult, fill = Emission_site)) + geom_bar(binwidth = 5) + | |||
facet_grid(Pollutant ~ RenovationPolicy, scale = "free_y") + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Emissions from heating in Kuopio", | |||
x = "Time", | |||
y = "Emissions (ton /a)" | |||
) | |||
ggplot(subset(emis, EfficiencyPolicy == "BAU" & FuelPolicy == "BAU"), aes(x = Time, weight = emissionsResult, fill = Fuel)) + geom_bar(binwidth = 5) + | |||
facet_grid(Pollutant ~ RenovationPolicy, scale = "free_y") + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Emissions from heating in Kuopio", | |||
x = "Time", | |||
y = "Emissions (ton /a)" | |||
) | |||
###################### Health assessment | |||
####!------------------------------------------------ | |||
objects.latest('Op_en2261', code_name = 'initiate') # [[Health impact assessment]] dose, RR, totcases. | |||
objects.latest('Op_en5917', code_name = 'initiate') # [[Disease risk]] disincidence | |||
directs <- tidy(opbase.data("Op_en5461", subset = "Direct inputs"), direction = "wide") # [[Climate change policies and health in Kuopio]] | |||
####i------------------------------------------------ | |||
colnames(directs) <- gsub(" ", "_", colnames(directs)) | |||
### Use these population and iF values in health impact assessment. Why? | |||
frexposed <- 1 # fraction of population that is exposed | |||
bgexposure <- 0 # Background exposure to an agent (a level below which you cannot get in practice) | |||
BW <- 70 # Body weight (is needed for RR calculations although it is irrelevant for PM2.5) | |||
population <- 1E+5 | |||
exposure <- EvalOutput(exposure, verbose = TRUE) | |||
ggplot(subset(exposure@output, RenovationPolicy == "BAU" & EfficiencyPolicy == "BAU" & FuelPolicy == "BAU"), aes(x = Time, weight = exposureResult, fill = Heating)) + | |||
geom_bar(binwidth = 5) + facet_grid(Area ~ Emission_height) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Exposure to PM2.5 from heating in Kuopio", | |||
x = "Time", | |||
y = "Average PM2.5 (µg/m3)" | |||
) | |||
exposure@output <- exposure@output[exposure@output$Area == "Average" , ] # Kuopio is an average area, | |||
# rather than rural or urban. | |||
ggplot(subset(exposure@output, EfficiencyPolicy == "BAU"), aes(x = Time, weight = exposureResult, fill = Heating)) + geom_bar(binwidth = 5) + facet_grid(FuelPolicy ~ RenovationPolicy) + theme_gray(base_size = BS) + | |||
labs( | |||
title = "Exposure to PM2.5 from heating in Kuopio", | |||
x = "Time", | |||
y = "Average PM2.5 (µg/m3)" | |||
) | |||
totcases <- EvalOutput(totcases) | |||
totcases@output$Time <- as.numeric(as.character(totcases@output$Time)) | |||
totcases <- oapply(totcases, cols = c("Age", "Sex"), FUN = sum) | |||
ggplot(subset(totcases@output, EfficiencyPolicy == "BAU" & FuelPolicy == "BAU"), aes(x = Time, weight = totcasesResult, fill = Heating))+geom_bar(binwidth = 5) + | |||
facet_grid(Trait ~ RenovationPolicy) + | |||
theme_gray(base_size = BS) + | |||
labs( | |||
title = "Health effects of PM2.5 from heating in Kuopio", | |||
x = "Time", | |||
y = "Health effects (deaths /a)" | |||
) | |||
DW <- Ovariable("DW", data = data.frame(directs["Trait"], Result = directs$DW)) | |||
L <- Ovariable("L", data = data.frame(directs["Trait"], Result = directs$L)) | |||
DALYs <- totcases * DW * L | |||
cat("Total DALYs/a by different combinations of policy options.\n") | |||
temp <- DALYs | |||
temp@output <- subset( | |||
temp@output, | |||
as.character(Time) %in% c("2010", "2030") & Trait == "Total mortality" | |||
) | |||
oprint(oapply(temp, INDEX = c("Time", "EfficiencyPolicy", "RenovationPolicy", "FuelPolicy"), FUN = sum)) | |||
ggplot(subset(DALYs@output, FuelPolicy == "BAU" & Trait == "Total mortality"), aes(x = Time, weight = Result, fill = Heating))+geom_bar(binwidth = 5) + | |||
facet_grid(EfficiencyPolicy ~ RenovationPolicy) + | |||
theme_gray(base_size = BS) + | |||
labs( | |||
title = "Health effects in DALYs of PM2.5 from heating in Kuopio", | |||
x = "Time", | |||
y = "Health effects (DALY /a)" | |||
) | |||
ggplot(subset(DALYs@output, Time == 2030 & Trait == "Total mortality"), aes(x = FuelPolicy, weight = Result, fill = Heating))+geom_bar() + | |||
facet_grid(EfficiencyPolicy ~ RenovationPolicy) + | |||
theme_gray(base_size = BS) + | |||
labs( | |||
title = "Health effects in DALYs of PM2.5 from heating in Kuopio", | |||
x = "Biofuel policy in district heating", | |||
y = "Health effects (DALY /a)" | |||
) | |||
######## Buildings in Kuopio on map | |||
# Calculate locations for Kuopio districts | |||
temp <- buildings | |||
temp@output <- subset(temp@output, | |||
Time == 2030 & EfficiencyPolicy == "BAU" & RenovationPolicy == "BAU" | |||
) | |||
temp <- unkeep(temp, sources = TRUE, prevresults = TRUE) | |||
temp <- oapply(temp, cols = c("Building", "Heating", "Efficiency", "Renovation"), FUN = sum) | |||
####!------------------------------------------------ | |||
districts <- tidy(opbase.data("Op_en5932.kuopio_city_districts"), widecol = "Location") # [[Building stock in Kuopio]] | |||
####i------------------------------------------------ | |||
colnames(districts) <- gsub("[ \\.]", "_", colnames(districts)) | |||
districts <- Ovariable("districts", data = data.frame(districts, Result = 1)) | |||
temp <- temp * districts | |||
MyRmap( | |||
ova2spat( | |||
temp, | |||
coord = c("E", "N"), | |||
proj4string = "+init=epsg:3067" | |||
), # National Land Survey uses EPSG:3067 (ETRS-TM35FIN) | |||
plotvar = "Result", | |||
legend_title = "Floor area", | |||
numbins = 8, | |||
pch = 19, | |||
cex = 2 | |||
) | |||
</rcode> | |||
==== Model version 1 ==== | |||
:''This model version was used to produce the submitted manuscript in spring 2015. | |||
[[heande:Kuopio housing]] | [[heande:Kuopio housing]] | ||
Revision as of 07:09, 17 July 2015
Moderator:Jouni (see all) |
|
Upload data
|
Main message: |
---|
Question:
What are the most beneficial ways from public health point of view to reduce GHG emissions in Kuopio? The target of 40 % GHG reduction seems realistic due to reforms in Haapaniemi power plant, assuming that GHG emissions for wood-based fuel is 0. Life-cycle impacts of the wood-based fuel have not yet been estimated. |
{{#display_map:
62.900223, 27.637482, Kuopio
| zoom = 11
}}
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.
Details of scoping |
---|
Boundaries
Scenarios
Intended users
Participants
|
Answer
Conclusions
The target of 40 % GHG reduction seems realistic due to reforms in Haapaniemi power plant, assuming that GHG emissions for wood-based fuel is 0. Life-cycle impacts of the wood-based fuel have not yet been estimated.
Results
Model version 2
- This model version was used to produce the corrected manuscript in July 2015.
Model version 1
- This model version was used to produce the submitted manuscript in spring 2015.
- 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.
- Also the renovation dynamics is built using event years: at an event, a certain amount of floor area is moved from one energy efficiency category to another.
- Full data are stored in the ovariables. Before evaluating, extra columns and rows are removed. The first part of the code is about this.
- Full model run with corrected table 13th March 2015
- Full model run 23 Feb 2015
- Old example model run (running the model takes more than 6 min, so use this ready-made result)
Rationale
Dependencies
- Building stock in Kuopio
- Intake fractions of PM
- OpasnetUtils/Drafts
- Energy use of buildings
- Kuopio energy production
- Emission factors for burning processes
- Population of Kuopio
- Building model
- Health impact assessment
- Disease risk
- ERFs of environmental pollutants
- Burden of disease in Finland
- Climate change policies and health in Kuopio DALY weights etc
Decisions
- Efficiency policy (index EfficiencyPolicy): Relates to the shares of efficiency types when new buildings are built (ovariable efficiencyShares).
- BAU: The shares are like in Energy use of buildings#Energy efficiency in heating
- Active efficiency: Passive buildings increase the market share by 25 and 10 %-units at the expense of low-energy buildings since 2020 and 2040, respectively.
- Biofuel policy (index FuelPolicy): Increase the share of biofuels in the Haapaniemi power plant (ovariable fuelShares).
- BAU: The shares are like in Emission factors for burning processes#Emission factors for heating (Fuel use in different heating types): Peat 84 %, wood 4 %, heavy oil 12 %.
- Biofuel increase: Peat 49.5 %, wood 49.5 %, heavy oil 1 %.
- Renovation policy (index RenovationPolicy): Existing buildings are renovated (typically after 25 years of age) for better energy efficiency. Different renovations produce different results (ovariables renovationRate, renovationShares).
- BAU: Default renovation rate is 3 % /a if the age of the building is >= 25 a. For renovation shares, see Building stock in Kuopio#Renovations.
- Active renovation: The renovation rate of all renovation types is 4.5 % /a.
- Effective renovation: The renovation rate is 3 % /a as in BAU, but all renovations are the most effective. i.e. sheath reforms.
Show details | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Direct inputs
Obs | Exposure agent | Response | Cases | DW | L | Description |
---|---|---|---|---|---|---|
1 | PM2.5 | Total mortality | 877 | 1 | 11 | Actually "Mortality (all cause)". In 2009 for Pohjois-Savo area 1090 / 100 000 from death cause registry. |
2 | PM2.5 | Work loss days (WLDs) | 323135 | 0.02 | 0.003 | |
3 | PM2.5 | Restricted activity days (RADs) | 31867 | 0.07 | 0.003 | 2.1 million in whole Finland |
4 | PM2.5 | Infant mortality | 3 | 1 | 81 | <1 year old 2009 data for Pohjois-Savo area 244 / 100 000 from death registry. In 2009 in Kuopio 1110 <1 year olds. |
5 | PM2.5 | COPD | 339 | 0.099 | 15 | Actually "Chronic bronchitis (>15 year olds)". Kelasto, includes astma cases too |
6 | PM2.5 | Cardiovascular hospital admissions (number) | 2109 | 0.253 | 0.017 | 21424 in year 2010 in Kuopio hospital. Hospital serves area with 817166 inhabitats. |
7 | PM2.5 | Respiratory hospital admissions | 1150 | 0.043 | 0.02 | In 2007 1429.55 hospital discharges for respiratory disease / 100 000 in whole Finland. http://data.euro.who.int/hfadb/ |
8 | PM2.5 | Asthma medication use (children aged 5-14) | 62 | 0.043 | 15 | Kelasto |
9 | Mold/dampness | Asthma development (>15 year olds) | 252 | 0.043 | 15 | Kelasto-database |
10 | Mold/dampness | Asthma development (5-14 year olds) | 62 | 0.043 | 15 | Kelasto-database |
11 | Noise | Highly annoyed | 0.02 | 1 | ||
12 | Noise | Sleep disturbance | 0.07 | 1 | ||
13 | Noise | Myocardial infarction | 1289 | 0.439 | 0.019663 | 13101 cases in Kuopio university Hospital in year 2010. Hospital serves area with 817166 inhabitats. |
14 | EC | Cardiovascular mortality | 366 | 0.043 | 0.02 | In 2009 for Pohjois-Savo area 455 / 100 000 from death cause registry. |
15 | Cardiopulmonary | 1 | 11 | Guesswork. The same as total mortality | ||
16 | Lung cancer | 1 | 11 | Guesswork. The same as total mortality. |
Specific actions - real and potential
- Energy production
- New power plant unit in Haapaniemi: ability to use significantly more biomass in the production of district heat (2014)
- Enhancement of dispersed energy production with biofuels
- Wide scale transition to renewable energy sources in heating
- 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
- If possible, PM emissions and noise are calculated based on updated version of Kuopio´s traffic network
- Alternatively, the effect of increased use of biofuels on GHG and CO2 emissions is evaluated.
- Possibilities of rail traffic in Kuopio
- Other...
Indicators
- Cardiovascular mortality
- Pulmonar mortality
- Well-being...
An archived version was planning to use Weighted product model to summarise results, but the idea was dropped.
- Stakeholders: City of Kuopio, Citizens, Budget office of Kuopio
Assessment-specific data
Received
- Building stock data
- Building registry
- Use of electricity by building type or type of activity
- Use of district heat by contract
- Amount of building stock renovated per year
- Amount of new building stock per year during 2010-2012
- Energy consumption in some of city´s own buildings before and after renovation
- Energy production
- Fuels and emissions of Haapaniemi CHP plant
- Traffic
- Regional plan on public transport
To be gathered
- Updated traffic network model?
- Estimates of the amount, area, volume and energy class of new buildings during next years (about 2014-2020)
See also
- Kuopion kaupunginhallitus 8.10.2012: Kuopion ja Siilinjärven joukkoliikennesuunnitelma (Kuopio public transport plan)
- Laskureita hiilijalanjäljen arviointiin ja seurantaan (Carbon footprint calculators): SYNERGIA, JUHILAS, Ilmastodieetti, KASVENER, KUHILAS, Y-HIILARI
- Millaisen tiekarten avulla hiilineutraaliin Suomeen 2050
- Climate policy of Kuopio 2009 - 2020
- DebattiBaari: energiakeskustelu
References
Keywords
Climate Change, Kuopio, Green house gas emissions, Health, Energy
Related files
<mfanonymousfilelist></mfanonymousfilelist>