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7/31/2019 Research Paper 2 RevG
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With reference to a specific example or examples, critically assess the potential
for energy reduction in the built urban environment
Patrick Arnell
Introduction
This paper examines the potential for energy reduction in the built environment. Energy
production and consumption are closely linked to issues of sustainable development and
anthropogenicclimatechange(IPCC,2007;Goldembergetal,1987;Nissing&Blottnitz,2010).
Cities by association are linked to these issues; globally, cities represent the worlds biggest
consumersofenergy(IEA,2008).In2008,citiesaccountedformorethan66%ofglobalenergy
demandandby2030demandispredictedtoincreaseto73%(IEA,2008).Over85%ofthe
energy consumedbycities isderived from fossil fuel sourcesand projectionsto2030donotshowsignificantreductions(IEA,2008).Assessingthepotentialforenergyreductioninthebuilt
environment is therefore considered relevant, as measurable reductions in the energy
consumptionofcitieswouldgenerallybeexpectedtoproducecorrespondingimprovementsin
environmentalperformance.
Thecityscalewastheunitofanalysischosenforthispaper.Neighbourhoodsandbuildingsalso
represent acceptable scales for assessing the built environment (Williams & Dair, 2007).
However,theformofacityisconsideredtobeoneofthemajordeterminantsofhowenergyis
utilized(Steemers,2003;EPA,2001;Kenworthy&Laube,1999;Owens,1992),andthereforethe
city scale was considered most appropriate an assessment of energy reduction in the built
environment.
Toassess the potential for energy reduction at the city scale, a single planning strategywas
evaluated. Prior to focusing on this strategy, a review of alternative reduction schemes
(IPCC,2007)wasconducted.However,assessmentofasingleplanningstrategywaschosenas
planninghasbeenshowntobe asignificantdeterminantofurban formand thereforeenergy
consumption(Owens,1992).Inaddition,recenttrendsinNorthAmericaandEuropeindicate
planning movements based on sustainability principles are becoming more prevalent
(Williams&Dair,2007).Itisthereforeconsideredrelevanttoassesshowasustainableplanning
strategymayeffectacitysconsumptionofenergy.
The planningstrategyevaluated inthis paperisSmartGrowth (Smart Growth,2010). Smart
Growthisviewedasastrategyforreducingenergydemand(CityMayors,2010),andhasbeen
adopted by cities in both the US (EPA, 2010) and Canada (Smart Growth Canada, 2010).
Principles of Smart Growth include: increasing housing choices, creating walkable
neighbourhoods, mixing land-uses, increasing transportation choices, redeveloping existingcommunitiesandusingcompactbuildingdesign(SmartGrowth,2010).
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Toexamineinmoredetailthepotentialforenergyreductionatthecityscale,theCityofCalgary
wasselectedascasestudy.TheCityofCalgarywasselectedforthreereasons.Thefirstisthat
66%ofCalgarysecologicalfootprintisattributedtoenergyconsumptionand70%isconsidered
tobestronglyinfluencedbyCalgarysurbanform(CityofCalgary,2008).ThismakesCalgarya
goodcandidateforassessingtheeffectsofSmartGrowthonenergyusage.Thesecondisthatthe
Cityhasrecentlyintegrateditsplanningpoliciesforcommunitydevelopmentandtransportation
underasingleintegratedstrategywhichusesSmartGrowthprinciples(CityofCalgary,2007).
ThismakesanevaluationofthepotentialforenergyreductionusingSmartGrowthrelevant,as
theCitywillbeincorporatingtheseprinciplesintofutureplanningdecisions.Thethirdfactorfor
consideringCalgaryasacasestudyisproxydata(greenhousegasemissions,populationdensity
and transportation patterns) which provide converging lines of evidence suggesting that
characteristics of Calgarys urban form are similar to other North American cities. An
assessment into the potential for Smart Growth to reduce energy consumption in Calgary is
thereforeconsideredrelevantforothercitiesconsideringtheadoptionofSmartGrowth.
TocriticallyassessthepotentialforSmartGrowthtoinfluenceenergyreductionatthecityscale,
six neighbourhoods within the City of Calgary were evaluated to determine which one best
representedSmartGrowthprinciples.Eachprofileincludedanenergyaudit(NRC,2009)and
thereforepermittedanevaluationofthepotentialforenergyreductionbasedonurbanform.
TheenergyprofileoftheneighbourhoodbestrepresentingSmartGrowthwasthenextrapolated
acrosstheentirecity.Thedifferencebetweentheactualcalculatedenergybudgetforthecity
and the energy budget calculated from the extrapolated energy profile of the selected
neighbourhoodwasthencalculated.Usingthismethodology,thecalculatedenergysavingsforthecitywere62%(+/-2%)andthisresultisinterpretedtorepresentthepotentialforSmart
GrowthprinciplestoreducetheenergyconsumptionoftheCityofCalgary.
Basedon the results outlinedabove, this paper contends that the adoptionofSmartGrowth
principles has the potential to substantially reduce energy use for the City of Calgary. By
implication,citieswithsimilarlanduseandtransportationprofilesmayalsohavethepotential
forreducingenergyconsumptionbyadoptingSmartGrowthprinciples. Toprovidecontextual
informationonhowtheCityofCalgarycompareswithothercitiesthreemetricswerereviewed.
Thesewere:percapitagreenhousegas(GHG)emissions,urbanpopulationdensityandmodesoftransportation.ThesemetricsprovideconverginglinesofevidenceindicatingCalgaryspatterns
ofenergyuseandurbanformaresimilartootherNorthAmericancities.
Themajorsectionsofthispaperareorganizedasfollows.Section1presentstheobjectivesand
methods used to assess the potential for Smart Growth to influence energy consumption.
Section 2 presents data on the three metrics used to compare Calgary to other cities and
concludes with the profiles of the six Calgary neighbourhoods assessed for Smart Growth
principles.Section3presentstheresultsoftheanalysisandSection4presentsasummaryofthe
majorfindings.
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1. Objectives&Methods
The objective ofthis paperis tocritically assess the potential for SmartGrowth principles to
influence energy consumption at the city scale. To investigate this, the City of Calgarywas
chosenasacasestudy.Themethodsusedtoperformthecriticalanalysisarepresentedbelow.
Six neighbourhoods in Calgary were recently the subject of a study looking at energy
consumption patterns based on urban typology (NRC, 2009). Energy profiles for the six
communitieswere developed using The UrbanArchetypes Project Methodology (NRC, 2009;
method available at: www.canmetenergy.nrcan.gc.ca). The methodology allows for the
comparisonofenergybudgetsbetweenneighbourhoodsandaccountsforenergyutilizedbythe
dominanthousingtypesofaparticularneighbourhood.Includedineachprofileistheenergy
utilizedfor: spaceheating,hotwater, lighting and appliances. Energy consumedbypersonal
vehicleuseisalsoincludedineachprofile.Forthepurposesofthispaper,theaccountingoftheenergyexpendedfromtransportationandbuildingoccupancyisconsideredsuitablyrobustto
allowfortheprofilesdevelopedinthisstudytobeextrapolatedfortheentireCity.
Thesesixneighbourhoodprofileswerefirstassessedtodeterminewhichonebestrepresented
theprinciplesofSmartGrowth.Asimplemodelwasthenconstructedtoextrapolatewhateffect
theenergyconsumptionpatternsoftheselectedneighbourhoodwouldhaveifappliedacrossthe
entire City. To construct the model, the various housing typologies identified in the study
(NRC,2009)were firstmapped onto the types of housing stock tracked by the City (City of
Calgary,2010),withvehicleusageaveragedacrossallneighbourhoods.Acheckofthemodelwas then conducted by comparing the calculated GHG emissions (T CO2-eq/year), against
published and predicted GHG emissions for the City. The resulting error rate (difference
betweenobservedandcalculated)wasthenusedtoprovidetheconfidencelimitsforthemodel.
Energyusagedata,asmeasuredingigajoules(GJ)wasthenusedtoruntwosimulationsofthe
energy budget for thewholeof theCity of Calgary. The first run simulated the total energy
profileforthecityunderitspresentprofile.Thesecondrunconsideredwhattheenergybudget
for the city would look like if all neighbourhoods exhibited the same energy profile as the
neighbourhoodselectedtorepresentSmartGrowthprinciples.Thedifferencebetweenthese
twomodelrunswasconsideredtobethepotentialforSmartGrowthprinciplestoeffectenergy
usageatthecityscale.
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2. Background
EnergyProductionandConsumption
By 2030 global energy demand from cities is predicted to account for 73% of all energy
consumed(IEA,2008).Ofthetotalamountofenergyconsumedgloballybycities,over85%is
derivedfromnon-renewablefossilfuelsources(IEA,2008).Assumingcoal,hydro,gas,nuclear
andhydroarepredominatelyusedinbuildings(heating,cooling,lightingandappliances)andoil
consumptionreflectsvehicleusage,thetwomajorsourcesofenergyconsumptionincitiesare
buildingsat64%andtransportationat32%(IEA,2008).Thisissignificantinthatcityformis
considered to have a important effect on the balance of the energy used by buildings and
transportsystems(Steemers,2003).Chart1showsglobalenergyconsumptionbyfuelstock.
PercentagesoftotalfuelstocksusedbycitiesarepresentedinTable1.
Chart1:ProjectedGlobalEnergyConsumptionversesWorldPopulation
Notes: 1. Mtoe: Million tonne oil equivalent
2. Source for population data: U.S. Census Bureau, 2010.
3. Source for energy consumption data: IEA, 2008.
01,000,000,0002,000,000,0003,000,000,0004,000,000,0005,000,000,0006,000,000,0007,000,000,0008,000,000,0009,000,000,000
0500
10001500200025003000350040004500
2006 2015 2030Coal Oil Gas Nuclear
Hydro Biomass & Waste Other renewables World Population
P
opulation
M
toe
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Table1:PercentofTotalFuelStocksConsumedbyCities
2006 2015 2030Fuel Stock
Cities as % of World Cities as % of World Cities as % of World
Coal 76% 78% 81%
Oil 63% 63% 66%
Gas 82% 83% 87%Nuclear 76% 77% 81%
Hydro 75% 76% 79%
Biomass & Waste 24% 26% 31%
Other Renewables 72% 73% 75%
Total 67% 69% 73%
Source for percent of energy used by cities: EIA, 2008.
DataforcomparingcitiesonaktCO2-eq/capitabasishasrecentlybeenmadeavailablebythe
UNandWorldbank(Kennedyetal,2010).ThisGHGemissionsdatahasbeenusedasproxydata
tounderstandingeneraltermstherelationshipbetweencitiesintermsoftheiroverallenergy
budgets.Table2presentstherelativerankingofthetop25citiesinvolvedinthestudybasedon
ktCO2-eq/capita.
Table2:ComparisonofCitiesBasedonktCO2-eq/capita
Rank City Year
Total kt CO2-eq/capita (excluding
marine and aviation) Total kt CO2-eq/capita
1 Rotterdam 2005 29.8
2 Denver 2005 17.88 19.38
3 Washington DC 2000 19.3
4 Minneapolis 2005 18.34
5 Calgary 2003 17.7
6 Stuttgart 2005 16
7 Austin 2005 15.57
8 Frankfurt 2005 13.7
9 Seattle 2005 13.68
10 Los Angeles 2000 9.5 13
11 Portland 2005 12.41
12 Shanghai 2006 10.9 11.7
13 Toronto 2005 10.7 11.6
14 Cape Town 2006 7.8 11.615 Tianjin 1998 10.9 11.1
16 Bologna 2005 11.1
17 Bangkok 2005 8.8 10.7
18 New York City 2005 8 10.5
19 Athens 2005 10.4
20 Bijing 2006 9.6 10.1
21 Veneto 2005 10
22 Hamburg 2005 9.7
23 Torino 2005 9.7
24 London 2003 6.5 9.6
25 Ljubljana 2005 9.5Source: (Kennedy etal, 2010).
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TounderstandCalgaryshighpercapitaGHGemissions,areviewofregionalpowergenerationis
required.TheCityofCalgaryobtainsitspowergeneratingstationslocatedwithintheProvince
of Alberta. Generating capacity in the province includes: 5,971 MWof electrical generating
capacity from coal fire plants, 5,149 MW of capacity from gas fired plants (Government of
Alberta,2010),652.95MWof installedwindpower(CANWEA,2010),and869MWofinstalled
hydro power (Bell &Weis, 2009). An overview of Albertas energy profile is presented in
Figure1.
Figure1:2007ElectricalEnergyBudgetfortheProvinceofAlberta
Source: (Bell & Weis, 2009)
The City of Calgary uses two accounting schemes in its assessment of energy usage (City of
Calgary,2006).ThefirstschemeaccountsforenergyconsumedfromCityofCalgaryCorporate
(CCCORP)operationsandincludes:municipalandpublicbuildings,publictransit,streetlights,
waterandseweroperationsandothermiscellaneoussources(CityofCalgary,2006).TheSecond
schemeaccountsforenergyconsumedbytheCityofCalgaryCommunity(CCCOM)andincludes
anaccountingofthefollowing:electricity(lightingandappliances),heating(spaceandwater)
andvehicleusage(CityofCalgary,2006).
In both accounting schemes, results are reported on the basis of green house gas (GHG)
emissions.AseparatesummaryoftheenergyfeedstocksconsumedbyCCCOMisalsoavailable;
however,onlyaggregatedGHGdataispresentedforCCCORP.Thisaggregationandreportingof
energyuseintermsofGHGemissionsforCCCORPpreventsmeaningfulcomparisonofthetotal
energy utilized under the two systems. However, in a comparison of CCCORP emissions to
CCCOMemissions,CCCORPemissionsaccountforonlyabout3%oftheoverallenergybudgetfor
thecityandarenotthereforeconsideredasignificantportionoftheCitiesoverallenergybudget.
AsummaryoftheenergyfeedstocksusedbyCCCOMarepresentedinTable3.
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Table3:CCCOM2003EnergyConsumption
Coal & Gas Fired Electricity 7,869,085,000 kWh
Green electricity 59,215,000 kWh
Natural gas 77,000,000 GJ
Gasoline 1,372,929,000 litresDiesel 415,132,000 litres
Propane 196,272,503 litres
Natural gas (vehicles) 319,323 litres
Source: (City of Calgary, 2006)
Chart2presentsacomparisonofCCCOMGHGemissionsversespopulationgrowth.Projected
populationdatahasbeenaddedandfutureGHGemissionshavebeenextrapolatedforabusiness
asusual(BAU)scenariobasedonprojectedpopulationincreases.
Chart2:CityofCalgaryPopulationGrowthversesGHGEmissions
Notes: 1. GHG emissions Source: (City of Calgary, 2006a)
3. Future years of CO2-eq emissions calculated from projected population growth
AnitemizedcomparisonofGHGemissionsforCCCOMandCCCORParepresentedinCharts3and
4respectively.
0200,000400,000600,000800,0001,000,0001,200,0001,400,0001,600,000
0
5000
10000
15000
20000
25000
198
3
198
5
198
7
198
9
199
1
199
3
199
5
199
7
199
9
200
1
200
3
200
5
200
7
200
9
201
1
201
3
201
5
201
7
201
9
202
1
202
3
202
5
Population kt CO2-eq
BUA Forecast
ktCO2-eq
Population
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Chart3CCCOMGHGEmissionsprojected2010usingBUAForecast.
Notes: 1.FutureyearsofCO2-eqemissionscalculatedfromprojectedpopulationgrowth 2.Decreasein2004attributedtomildwintertemperatures 3.Sourceofemissionsdata:CityofCalgary2006StateoftheEnvironmentreport 4.Sourceofpopulationdata:CityofCalgary2010Census.
Chart4CCCORPGHGEmissions
Notes: 1.SourceGHGEmissions:CityofCalgary2008StateoftheEnvironmentreport. 2.Sourceofpopulationdata:CityofCalgary2010Census.
Charts3and4showthatwhiletheCityhasbeensuccessfulinreducingCCCORPGHGemissions,
itsinitiativestoreduceCCCCOMemissionshavenottodatemetwithsimilarsuccess.Withthe
exception of a slight dip in CCCOM GHG emissions for 2004, which was attributed to an
unseasonablywarmwinter,emissionsbetween1990and2005increased29%(CityofCalgary,
2006a).Theseresultsindicatethattherehasbeennosignificantpercapitareductioninenergy
consumptionbytheCityofCalgarycommunity.
020000040000060000080000010000001200000
02,0004,0006,0008,00010,000
12,00014,00016,00018,00020,000
19901997200020032004200520062007200820092010Waste Vehicles Natural gas Electricity Population
BUA ForecastCO2-eq
Pop
ulation
0200,000400,000600,000
800,0001,000,0001,200,000
0100200300
400500600
1990 2000 2003 2004 2005 2006 2007 2008Other Water treatment facilitiesStreet and traffic lights City fleetCity buildings Population
CO2-eq
Popu
lation
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PopulationDensity
ToexamineCalgaryspopulationdensityinrelationtootherUSandCanadiancitiesandevaluate
thepotentialeffectofdensityonpercapitaGHGemissions,datafromtheCityMayorswebsite
(2010)andKennedyetal (2010)wasused.TheaveragedensityofallUSandCanadiancities
withpopulationsover750,000was1,270people/km2(CityMayors,2010a).Incomparison,thedensityofCalgary(1250people/km2)isveryclosetotheaverage.Chart5presentspopulation
density verses GHGemission and two things are relevant to note. The first is a discernable
relationshipbetweenpopulationdensityandpercapitaCO2-eqemissions.Thesecondisthatthe
citiesclosesttoCalgaryonChart6areallUScities.Thisisinterpretedasanindicationthatthe
CityofCalgarysharesadensity/energyprofilecomparabletoseveralUScities.
Chart5:PopulationDensityversesGHGEmissions
Notes: 1. City of Calgary highlighted in red.2. Source for per capita CO2-eq data: Kennedy etal, 2010.
3. Source for population density: City Mayors, 2010.
DenverWashington DC
MinneapolisCalgary
Seattle
Shanghai
TianjinBejing
Seoul
R=0.33894
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
0 5 10 15 20 25 30 35
kt CO2-eq/capita
people/km2
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Transportation
Asnotedabove transportationrepresents amajorsource of energy usagebycities. Chart6,
belowpresentsthemodalsplitoftransportationtypesgroupedbyregion.
Chart6:ModalTransportationSplitofSelectCitiesGroupedbyRegion
Source: IPCC, 2007 p. 387
Within the City of Calgary dominant modes of transportation for 2010 included: motorized
vehicles(78%ofdailytrips),publictransit(15%),andwalking/cycling(7%)(CityofCalgary,
2010a).Chart7graphicallysummarizestherelationshipbetweenvehicleownershipinCalgary
versesotherCanadiancitiesandtheUnitedStates.Thedatapresentedhereareinterpretedto
indicate that the City of Calgary exhibits transportation patterns similar to other US and
Canadiancities.
0 20 40 60 80 100%
U.S.A.
Australia/New Zealand
Canada
Western Europe
High Income Asia
Eastern Europe
Middle East
Latin America
Africa
Low Income Asia
China
non motorised motorised public motorised private
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Chart7:Registeredvehiclesper1,000People
Source: City of Calgary, Feburary 2008. Mobility Monitor.
NeighbourhoodProfiles
ToassessthepotentialforenergyreductionintheCityofCalgaryusingSmartGrowthprinciples,
the profiles of six neighbourhoods were assessed. The neighbourhoods assessed were:
Britannia, Citadel,Rundel, Lake Bonavista,Mission and Tuscany. Dataused to construct the
profilesforeachofthesixneighbourhoodswastakenfrom2010censusdata(CityofCalgary,
2010)andanenergyprofilingstudyconductedbyNaturalResourcesCanada(NRC,2009).
Housing Stock in Calgary is categorized into one of five types (City of Calgary 2010 p. 120).
These are: single detached family dwellings (SF), semi-detached duplexes (DUP), apartments
(APT),rowortownhouses(TWN),andconvertedstructures(CNV),(typicallyhomeswhichhavebeensuited).ThepercentofeachhousingtypeintheCityofCalgaryfor2010was:SF59%,DUP
7%,APT21%,TWN10%andCNV3%.
Toassesseachofthe sixneighbourhoodsagainstSmartGrowthprinciplesaseries ofmetrics
were reviewed. These were adopted from the NRC study (NRC, 2010) and a summary is
presentedinTable3.Figure3presentsamapofCalgarywiththerelativelocationofeachofthe
sixneighbourhoodsshown.
0
100
200
300
400
500
600
700
800
900
1,000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
Re
gisteredvehiclesper1,0
00peo
ple
Montreal
Winnipeg
Calgary
Ottawa
United States
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Table3:MetricsUsedtoAssessNeighbourhoodsAgainstSmartGrowthPrinciples Britannia Citadel L. Bonavista Mission Rundle Tuscany
Vehicle km
traveled
40,000km/yr 42,300km/yr 45,600km/yr 16,200km/yr 36,200km/yr 36,500km/yrResident
Lifestyle
Average #
vehicles per
household
2.3 2.1 2.4 0.9 2.6 -
Density (units per
hectare)
6.43 14.87 7.02 55.5 11.61 14.9
Percent of single
detached homes
79% 93% 98% 4% 68% 91%
Land-use mix* 0.28 0.00 0.20 4.00 2.00 1.10
Neighbourhood
Design
Total road length 6.3 5.3 5.3 0.9 4.4 3.9
Location Distance to city
core
4.1km 13.2km 12.2km 1.6 7.2km 16.0km
Notes: 1. Source: NRC, 2009 p.10
2. *Land-use mix includes number of retail/commercial units, retail/commercial buildings, institutions and
municipal buildings. The higher the score, the more mixed the land use in the neighbourhood.
Figure3.CityofCalgaryShowingApproximateLocationsoftheSixNeighbourhoodsAssessed.
Sources: 1. Map from City of Calgary, 2010 Snapshots.
2. Neighbourhood Locations adapted from Natural Resources Canada, 2010.
Legend
Community Structure
CENTRE CITY
INNER CITY
1950s
1960s/1970s
1980s/1990s
2000s
BUILDING OUT
EMPLOYMENT
PARKS
UNDEVELOPED
OTHER
Transportation Utility Corridor
Lake Bonavista
Britannia
Mission
Rundle
Citadel
Tuscany
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3. Results
To critically assess the effect that the principles of Smart Growth could have on the energy
budgetfortheCityofCalgary,publisheddatacharacterizingtheenergyprofilesofsixCalgaryneighbourhoodswasused.ThedatawascollectedbyNaturalResourcesCanadausingtheUrban
ArchetypesProjectMethodology(NRC,2009).Themethodinvolvesthedevelopmentofenergy
profiles for the major housing typologies representative of each of the neighbourhoods and
accountsfortheenergyexpendedwithinbuildings(spaceheating,hotwaterandenergyusedfor
lightingandoperationofappliances)aswellenergyusedforpersonaltransportation(Natural
ResourcesCanada,2009).Thesixneighbourhoodsassessedinthestudywere:Britannia,Citadel,
LakeBonavista,Rundel,MissionandTuscany(Figure2).
Based on the data reviewed in Table 4, the neighbourhood of Mission was selected as best
representingtheprinciplesofSmartGrowth.TheprinciplesofSmartGrowthconsideredinthis
assessment included:housingchoice,walkableneighbourhood,mixed land-use,transportation
choices,redevelopmentofexistingcommunitiesandcompactbuildingdesign.Therationalefor
choosingMissionwas basedonthe number of theseSmartGrowth principles reflected in its
urbanform(Table4)versestheotherneighbourhoodsassessed.Asummaryofthisassessment
ispresentedinTable5below.
Table5: Summary of Assessment Criteria used to Select Neighbourhood Best RepresentingSmartGrowth
Housing Choices Percent of
single family
homes
Walkable
Neighbourhoods
Total road
length and
vehicle km
traveled
Mixed Land-use Land-use mix
Increasing
transportation
choices
Average
vehicles per
household
Redeveloping existing
communities
Distance to city
core
Compact Building
Design
Density
Note: * See Table 3 for details.
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ToestimatethepotentialenergysavingsfortheCityofCalgaryadoptinganeighborhoodprofile
similartoMissions,asimplemodelwasdevelopedbasedonhousingtypographiesandaverage
vehicleusage.Housingtypographiesidentifiedintheenergyauditstudy(NRC,2009)werefirst
mappedontothehousingtypographiestrackedbythecity(CityofCalgary,2010).Theresultsof
thismappingexercisearepresentedinTable6.
Table6:HousingTypesfromNRCStudyMappedontoCityofCalgaryHousingTypesCity of Calgary Housing TypesNeighbourhood Natural Resources Canada
Housing Types Single
Family (SF)
Duplex
(DUP)
Apartment
(APT)
Townhouse
(TWN)
Converted
Unit (CNV)
A. Single detached one storey B. Single detached two storey
Britannia
C. Single detached two storey
A. Single detached two storey
Citadel
B. Single detached two storey A. Single detached one storey B. Single detached two storey
L. Bonavista
C. Single detached two storey A. Apartment four storey B. Apartment six storey
Mission
C. Single detached two storey A. Single detached one storey B. Single detached one storey
Rundle
C. Row house two storey Tuscany A. Single detached two storey
Next,themodelwascheckedforaccuracybytestingitagainsttwodatapoints.Greenhousegasemissions for eachof theNRChousing typesweremapped onto the City of Calgary housing
types. Valueswere averagedbyhousing type and thesevalueswere thenmultipliedby total
dwellingcountsbasedonCitycensusdata.Vehicleemissionsforeachoftheneighbourhoods
wasalsoaveragedandthisvaluewasmultipliedbythetotalnumberofcitizens.Finallythese
twovalueswerethensummedandcomparedtoGHGemissiondata.Table7presentshowGHG
emissionsweremappedacrosshousingtypesandTables8aand8bpresentthe resultsofthe
GHGemissionscalculatedbytheModelagainst2003reportedCCCOMGHGemissionsand2010
projectedGHGemissions.
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Table7:GHGEmissions(TCO2-eq/yr)byHousingType+VehicleEmissions(TCO2-eq/yr)City of Calgary Housing TypesNeighbourhood Natural Resources Canada
Housing Types (SF) (DUP) (APT) (TWN) (CNV) Vehicle
A. Single detached one storey 15.5
B. Single detached two storey 17.2
Britannia
C. Single detached two storey 15.9
13.7
A. Single detached two storey 12.4Citadel
B. Single detached two storey 9.3
13.8
A. Single detached one storey 14
B. Single detached two storey 15.3
L. Bonavista
C. Single detached two storey 15.7
15.1
A. Apartment four storey 7.1
B. Apartment six storey 11.9
Mission
C. Single detached two storey 19.1
5
A. Single detached one storey 10.6
B. Single detached one storey 12.3
Rundle
C. Row house two storey 11 11 11
11.9
Tuscany A. Single detached two storey 11.2 11.3
Notes: 1. Vehicle column added. Values represent average T CO2-eq for transport by neighbourhood.
Table8a:2003ReportedGHGEmissionsversesGHGEmissionsCalculatedbyModel
2003 Total T CO2-eq/year Total kt CO2-eq/year
Population 922,315 11.8 10883
Housing Units* 371,756 12.2 4535
Total Calc. GHG Emissions 15418Total Reported CCCOM GHG Emissions 15748
Difference 329
Percent Difference -2%
Notes: 1. Housing Units by type not available for 2003. Average T CO2-eq/yr for all housing types used.
2. Source 2003 census data: City of Calgary, 2010.
3. Source total CCCOM GHG Emissions: City of Calgary 2006a.
Table8b:2010EstimatedCCCOMGHGEmissionsversesGHGEmissionsCalculatedbyModel
2010 Total SF DUP APT TWN CNV Vehicle Total kt CO2-eq/year
Housing units 440,856 257,854 28,507 93,730 45,543 15,222
Population 1,050,415
T CO2-eq/yr 14.4 11 9.5 11 11 11.8
Total kt CO2-eq/yr 3707 314 890 501 167 12395*
Total Calc. GHG Emissions 17974
Total Est. CCCOM GHG Emissions 18146
Difference 172
Percent Difference -1%
Notes: 1. * Value in this cell equals average Vehicle T CO2-eq/yr multiplied by total population.
2. Source 2010 census data: City of Calgary, 2010.
3. Total estimated CCCOM GHG Emissions based on population data.
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The results of these two data checks of themodel showed good agreementwith actual and
estimatedCCCOMGHGemissions.For2003thepercentdifferencebetweenthemodelandthe
reported CCCOM GHG emissions was 2%. A similar comparison to 2010 census data and
projectedGHGemissionsshowedthemodelunderestimatedGHGemissionby1%.Additional
testingwouldberequiredtoconfirmtherobustnessofthemodelbutbasedondatachecksat
tworeferencepoints(2003and2010)themodelestimatedGHGemissionswithinamaximumof
2%ofobservedGHGemissions.
GiventhemodelsaccuracyincalculatingGHGgasemissions,themodelwasrerunusingenergy
values(GJ).Table9presentshowtotalenergyvaluesweremappedontoHousingTypes.Table
10apresentsthecalculatedenergybudgetfortheCitybasedonaveragevaluesforhousingtype
an vehicle usage. Table 10b presents the calculated energy budget for the City assuming all
neighbourhoodsinCalgaryexhibitthesameenergyprofileasMission.
Table9:EnergyBudget(GJ)byHousingTypeCity of Calgary Housing TypesNeighbourhood Natural Resources Canada
Housing Types (SF) (DUP) (APT) (TWN) (CNV) Vehicle
A. Single detached one storey 246
B. Single detached two storey 279
Britannia
C. Single detached two storey 254
197
A. Single detached two storey 186Citadel
B. Single detached two storey 125
199
A. Single detached one storey 218
B. Single detached two storey 238
L. Bonavista
C. Single detached two storey 250
218
A. Apartment four storey 33
B. Apartment six storey 67
Mission
C. Single detached two storey 321
72
A. Single detached one storey 147
B. Single detached one storey 163
Rundle
C. Row house two storey 164 164 164
172
Tuscany A. Single detached two storey 163 163
Table10a:2010CalculatedEnergyBudgetforCityofCalgary(GJ)
2010 Total SF DUP APT TWN CNV Vehicle Total kt
CO2-eq/year
Housing
units
440,856 257,854 28,507 93,730 45,543 15,222
Population 1,050,415
GJyr 222 164 50 164 164 170
Total GJ/yr 57308052 4675148 4686500 7469052 2496408 178745619
Total Calc. Energy Budget for City of Calgary (GJ) 255380779
Notes: Table contains rounding errors for raw data set see Appendix B.
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Table10b:2010CalculatedEnergyReductionApplyingSmartGrowthforCityofCalgary(GJ)
2010 Total SF DUP APT TWN CNV Vehicle Total kt
CO2-eq/year
Housing
units
440,856 257,854 28,507 93,730 45,543 15,222
Population 1,050,415GJyr 50 50 50 50 50 170
Total GJ/yr 12892700 1425350 4686500 2277150 761100 75629880
Total Calc. Energy Budget for City of Calgary (GJ) 97672680
Notes: Table contains rounding errors for raw data set see Appendix B.
Thedifferencebetweenthe totalenergybudget inTable10aandTable10bisconsideredthe
potentialforenergyreductioninCalgaryusingtheprinciplesofSmartGrowth.Basedonthese
results,totalenergyreductionsof157,708,099GJor62%(+/-2%)wereachievable.
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4. Conclusions
Citiesgloballyarethelargestconsumersofenergyandthemajorityofthisenergyisderived
fromnon-renewablefossilfuels.Byextension,cityuseofenergyiscloselylinkedtoissuesof
sustainabledevelopmentandanthropogenicclimatechange.Strategiesforreducingtheenergy
consumptionofcitiesisthereforerelevantwhenconsideringpotentialsolutionsforimprovingtheenvironmentalperformanceofcities.
AnassessmentofhowtheprinciplesofSmartGrowthcouldinfluenceenergyconsumptionwas
completedusingtheCityofCalgaryasacaseStudy. TheCityofCalgarywaschosenbasedon
several factors including the contribution of its current urban form to the consumption of
energy,theCitysrecentadoptionofSmartGrowthprinciplesandconverginglinesofevidence
indicatingthatthecityexhibitscharacteristicstypicalofmanyUSandCanadiancities.
ToevaluatehowCalgarysbuiltenvironmentmightperformiforganizedaroundtheprinciplesofSmartGrowth, asimplemodelwasconstructed. Theusefulnessof themodelwascheckedby
comparing calculatedGHG emissions toobservedand predicted values. Themodelwas then
usedtocalculatetheenergybudgetfortheCityofCalgarygivenitspresenturbanformand
finally under the scenario that Calgarys urban formwas constructedusing the principles of
SmartGrowth.ThetotalcalculatedreductionfortheCityofCalgarysenergybudgetusingthis
methodwas62%(+/-2%).ThisresultisconsideredthepotentialforSmartGrowthtoreduce
energyconsumptionfortheCityofCalgary.
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