Greenhouse gas emissions in Kuopio

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⇤--#: . Check the structure. Some subheadings are missing. Answer contains material that rather belongs to data. Check also categories and keywords. --Jouni 09:02, 7 February 2013 (EET) (type: truth; paradigms: science: attack)

⇤--#: . Use "ghg.emission" as the object name, not "GreenhousegasemissionsKuopio", in the Answer code. Then it should work. --Jouni 09:02, 7 February 2013 (EET) (type: truth; paradigms: science: attack)

----#: . Still the page lacks those subheadings --Sam0911 11:47, 17 February 2013 (EET) (type: truth; paradigms: science: comment)

What are the greenhouse gas and PM emissions in Kuopio?←--#: . The question is well defined and clear --Matthew 10:54, 31 January 2013 (EET) (type: truth; paradigms: science: defence)⇤--#: . However, there is no heading stating that this is the assessment question --Adedayo 21:18, 11 February 2013 (EET) (type: truth; paradigms: science: attack)

Answer

For calculating the emissions of district heating of buildings, following is needed:

• Heat consumption of buildings in Kuopio (Energy consumption of heating of buildings in Kuopio). Alternatively, heat production by Haapaniemi energy plant (Haapaniemi energy plant in Kuopio)
• Fractions of fuels used by Haapaniemi energy plant (Fuels used by Haapaniemi energy plant)
• Emission factors for CO2 and PM (Emission factors for burning processes)
• Scenario for heat consumption of buildings and fractions of fuels used by Haapaniemi in 2020 (Climate change policies in Kuopio)

⇤--#: . The answer only considers emissions from buildings and the power-plant, other emissions from the agriculture and traffic are not represented in the answer --Adedayo 15:22, 24 January 2013 (EET) (type: truth; paradigms: science: attack)

+ Show code- Hide code library(OpasnetUtils) # A package with Opasnet functionalities library(xtable) # A package with table formats library(ggplot2) # A package with fancy graph formats objects.latest("Op_en5483", "initiate") # Get the latest ovariables from code calculations on page Op_en5483. ghg.emission <- EvalOutput(ghg.emission) print(xtable(ghg.emission@output), type = 'html') # Show a result table ggplot(ghg.emission@output, # Show a bar chart aes(x = Sector, y = ghg.emission, fill = Year)) + geom_bar(position="dodge") + theme_grey(base_size = 24)

⇤--#: . There is a word case error in the code, an attempt to run the code after editing indicate an empty result set message error and this does not support graphs and chart display that could have indicated the GHG emissions from the various sources. --Matthew 11:24, 31 January 2013 (EET) (type: truth; paradigms: science: attack)

Rationale

Data

⇤--#: . The table is specific however, not clear enough to show the population of kuopio in 2010 that was used in the calculation for the description to ascertain the emissions from each sector --Matthew 11:12, 1 February 2013 (EET) (type: truth; paradigms: science: attack)

Greenhouse gas emissions in Kuopio(kton CO2e)

Obs	Sector	Year	Result	TonsPerCapita
1	Consumers' use of electricity	2010	126.96	1.31
2	Electric heating	2010	32.65	0.34
3	District heating	2010	321.18	3.31
4	Separate heating	2010	41.1	0.42
5	Traffic	2010	164.47	1.70
6	Agriculture	2010	24.36	0.25
7	Waste management	2010	20.55	0.21
8	Total	2010	731.27	7.54

Formula

←--#: . The code run was successful, the dependency table showing emission type and factor is well understood. The table showing GHG emissions in 2010 is aslo clear and definite with the highest emission from district heating. --Matthew 11:28, 1 February 2013 (EET) (type: truth; paradigms: science: defence)

+ Show code- Hide code library(OpasnetUtils) library(xtable) data <- tidy(op_baseGetData("opasnet_base", "Op_en5483"), objname = "ghg.emission", direction = "wide") data <- data[data$Sector %in% c("District heating"), ] dependencies <- data.frame( Name = c( "energy.balance", # [[Energy balance in Kuopio]] "emission.factor" # [[Emission factors for burning processes]] ), Key = c( "QZNNQL9ClAHO3COB", "QEq4AnzY04LXx3gX" ) ) formula <- function(dependencies, intermediates = FALSE, ...) { ComputeDependencies(dependencies, ...) emission.factor@data <- emission.factor@data[emission.factor@data[, "Fuel power (MW)"] %in% c("100-300", "-"), c("Fuel", "Emission type", "emission.factorUnit", "emission.factorResult") ] # The data.frame temp is needed to connect energy.balance and emission.factor. temp <- data.frame( Energy.class = c( "CHP peat", "CHP renewable", "CHP oil", "H biogas", "H oil", "Ind peat", "Ind oil", "Ind renewable", "Bought electricity"), Fuel = c( "Peat", "Wood", "Heavy oil", "Light oil", "Heavy oil", "Peat", "Heavy oil", "Wood", "Light oil" ) ) energy.balance@output <- merge(energy.balance@output, temp) # energy.balance@output$energy.balanceSource <- "Formula" # energy.balance@output$Unit <- "GWh" # #energy.balance <- convert.units(energy.balance, "GWh") if(intermediates) { print(xtable(energy.balance@output), type = 'html') print(emission.factor) } out <- energy.balance * emission.factor return(out) } ghg.emission <- new("ovariable", name = "ghg.emission", data = data, dependencies = dependencies, formula = formula ) ghg.emission <- EvalOutput(ghg.emission, intermediates = FALSE, N = 1) print(xtable(ghg.emission@output), type = 'html') objects.store(ghg.emission) cat("Object ghg.emission saved. Page: Op_en5483, code: initiate.\n")

The greenhouse gas emissions in Kuopio in 2010 (without industry)⇤--#: . the table is not properly labelled in the heading --Adedayo 21:23, 11 February 2013 (EET) (type: truth; paradigms: science: attack)

Sector	Greenhouse gas emission (kt CDE)	Emissions per resident (t CDE)
Consumers' use of electricity	126,96	1,31
Electric heating	32,65	0,34
District heating	321,18	3,31
Separate heating	41,1	0,42
Traffic	164,47	1,70
Agriculture	24,36	0,25
Waste management	20,55	0,21
Total	731,27	7,54

----#: . Assuming that CDE equals CO2e equals carbon dioxide equivalents. --Jouni 09:52, 8 February 2012 (EET) (type: truth; paradigms: science: comment)

The greenhouse gas emissions have grown in Kuopio from 1990. They're about the same as the emissions in other cities the same size. The most important sources of greenhouse gases are the district heating used to warm houses, other use of electricity, other use of fuels (the energy production of industry and fuels of construction vehicles) and traffic. The greenhouse gas emissions grow, if active operations to limit emissions from the traffic, the optimizing energy consumption and increasing the amount of renewable energy sources used aren't taken into action.

On EU-level the basisline is to reduce greenhouse gas emissions at least 20% from 1990 to 2020. During the same time period the portion of renewable energy sources is increased up to 20% and the related traffic biofuel use up to 10 %. On local level the energy efficiency agreements have a big effect. Along with the city of Kuopio different companies and other agents, such as farms and housing companies, have made these agreements. The energy efficiency agreement made by the city of Kuopio obligates the reduction in energy consumption by 9% (18.207 GWh) from 2005 to 2016.

The greenhouse gas emissions caused by the city's own actions are only 8% of the total. The whole city corporation, including Kuopion Energia Oy, produces a significant part of the greenhouse gas emissions of Kuopio. The city can affect the emissions from it's own actions and the emissions from traffic by land usage and traffic planning. With advising and announcements the city can contribute to the increasing of energy efficiency of households and buildings. With it's corporate governance the city can also affect the actions and emissions of the whole city corporation.

See also

• Energy balance in Kuopio
• Climate change policies 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

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