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[[Category:Climate change]]

:''This text is taken from the Aalto University doctoral dissertation by Jukka Heinonen "The Impacts of Urban Structure and the Related Consumption Patterns on the Carbon Emissions of an Average Consumer", 2012, ISBN 978-952-60-4536-8.<ref name="Heinonen"></ref>''

=Abstract=

Climate change, in the form of global warming, has been a hot topic throughout the present
millennium, and is currently becoming a more and more widely accepted phenomenon. Urban
areas hold a central position in the search for feasible climate change mitigation opportunities
as a signiﬁcant share of all the global greenhouse gas (GHG) emissions is closely related to
urban structures. Embracing the situation, cities worldwide are setting ambitious GHG
reduction targets. However, the strategies to attain these are still evolving. One explanation is
that the cities and urban areas in developed countries are demand and consumption centers
where the majority of all consumed goods are imported from outside of the city boundaries.
Thus, the traditional geographically restricted assessment methods cannot produce sufﬁcient
information for effective carbon management.

The dissertation argues that in order to create city level carbon mitigation strategies, which
would materialize the potential related to urban areas, it is necessary to identify and
understand the emissions caused by the consumers. Derived from this, the dissertation strived
to account for all the carbon emissions caused by the inhabitants in different types of urban
structures, i.e. their carbon consumption, including the upstream emissions of production and
supply chains. To create a clear understanding of the issue, a multiple case study approach was
chosen in the Finnish context with each of the individual studies reported in academic journals
or conference publications.

The studies employ a method based on hybrid life cycle assessment, along with an assessment
model developed to calculate city and sub-city level carbon consumption. The main argument
of the dissertation is that in the context of the study, the urban structure of an area per se seems
to have little effect on the carbon emissions of an average consumer of the area. Rather, the
overall consumption volume seems to affect the carbon consumption so strongly that a higher
consumption volume indicates higher carbon consumption regardless of the type of the urban
structure. The urban structure has a direct impact only on the emissions related to private
driving, whereas the emissions from other consumption activities closely follow the overall
consumption. Thus, while the environmental, social and functional importance of high urban
density and the building type have been demonstrated in a number of studies, from the climate
change perspective these factors are not decisive and they are not sufﬁcient measures for
effective city level carbon management.<ref name="Heinonen">J. Heinonen: The Impacts of Urban Structure and the Related Consumption Patterns on the Carbon Emissions of an Average Consumer [http://lib.tkk.fi/Diss/2012/isbn9789526045368/isbn9789526045368.pdf]</ref>

=Papers of the dissertation=

*Paper I: Heinonen, Jukka; Junnila, Seppo; Kuronen, Matti (2010): A Life Cycle Assessment of Carbon Mitigation Possibilities in Metropolitan Areas, SB10 Finland, Sustainable Community - BuildingSMART, Espoo, 22.-24.9.2010, Finnish Association of Civil Engineers RIL, Conference Proceedings. 
*Paper II: Heinonen, Jukka; Junnila, Seppo (2011): Case study on the carbon consumption of two metropolitan cities, International Journal of Life Cycle Assessment, 16, 569-579. 
*Paper III: Heinonen, Jukka; Junnila, Seppo (2011): Implications of urban structure on carbon consumption in metropolitan areas, Environmental Research Letters, 6, 014018. 
*Paper IV: Heinonen Jukka; Junnila Seppo (2011): Carbon Consumption Comparison of Rural and Urban Lifestyles, Sustainability, 3 (8), 1234-1249. 
*Paper V: Heinonen, Jukka; Kyrö, Riikka; Junnila, Seppo (2011): Dense downtown living more carbon intense due to higher consumption: a case study of Helsinki, Environmental Research Letters, 6, 034034.

=The author’s contribution in the papers=

*Paper I: The author is responsible for writing the paper.
*Paper II: The author is responsible for writing the paper.  
*Paper III: The author is responsible for writing the paper.  
*Paper IV: The author is responsible for writing the paper.  
*Paper V: The author is responsible for initiating the paper, conducting the assessments and writing the first manuscript of the paper as well as several parts of the final paper.

=Introduction=

Climate change, in the form of global warming, has been a hot topic 
throughout the present millennium. Despite some counterarguments [e.g. 
1, 2], the phenomenon has been widely accepted [3, 4] and it is often stated 
as the most severe global environmental problem of our age. Embracing 
this paradigm set the course for this dissertation.

The overall leading purpose of the dissertation is to analyze the climate 
change implications of different types of communities living in different 
types of urban structures. In other words, the aim is to integrate inhabitants 
into the analysis of the emissions of buildings and urban structures, with 
the idea that buildings are necessary goods for living, and the building, the 
urban structure and the location may all affect the lifestyle of the 
inhabitant. Based on these factors, the dissertation aims to account for all 
the emissions from consumption,  including the upstream emissions of 
production and supply chains.

The need for this type of consumption-based greenhouse gas (GHG) 
assessment approach, accounting  for all life cycle emissions from 
consumption, has been recently expressed by several authors [5, 6, 7, 8]. 
While some such approaches have also been reported in academic journals 
in the past years [5, 8, 9], space for new contributions is still ample. Within 
the field, this dissertation contributes especially to the area of city and subcity level GHG assessments, where the academic research tradition is thin 
[10]. However, the topic is important, as both cities and urban areas appear 
to be accountable for the majority  of all GHG emissions in developed 
countries [8, 11] and are important contributors in reaching carbon 
mitigation targets if willing to reduce their emissions [10-12].

While a variety of different calculation tools have been developed by 
academics and consultants, especially the techniques for a consistent 
consumption-based GHG assessment on a  city or sub-city level are still 
insufficient. Cities worldwide are setting ambitious GHG reduction targets, 
but the ways to attain these, and even to assess whether they are reached or 
not, are still under development. Cities and urban areas in developed 
countries are demand and consumption centers [5, 8, 13] where the 
majority of all consumed goods are imported from outside of the 
geographical city area. Thus, the traditional geographically restricted 
assessment methods cannot produce sufficient information for effective 
carbon management, mainly because the results  depend heavily on the 
presence or absence of heavy industries [37]. For example, the carbon 
footprint of an average resident of Helsinki, the capital of Finland as well as 
one of the case cities of this dissertation, has been reported in different 
publications to vary from roughly four tons of GHGs to almost 13. The 
minimum is reached with assessments limited in scope in both a geographic 
and a life cycle perspective [14], whereas the consumption-based approach 
of the dissertation, aiming to account for all life cycle emissions related to 
all consumption of goods and services of an average resident of the city, 
results in the highest figure. Neither of these can be claimed to be false as 
such, but the approach based on limited scopes can hardly be argued to 
produce sufficient data for efficient city-level management of the global 
phenomenon of climate change.

The dissertation consists of altogether five individual but interrelated 
studies reported in four academic  journal papers in 2011 and one 
conference proceeding in 2010. The studies analyze the consumption-based 
carbon emissions of the inhabitants in different types of urban structures in 
the Finnish geographical context, examining the impact of the structure and 
the consumption volume of the emissions. Thus, while the work with the 
assessment techniques contributes to the field of city-level consumptionbased GHG assessments, the key argument of the dissertation arises from 
the findings of the five studies. This argument, explained and discussed in 
detail throughout the dissertation, is that in the context of the study, the 
urban structure of an area per se seems to have little effect on the carbon 
emissions of an average consumer of the area. The key factors lie elsewhere. 
The overall consumption volume seems to affect the carbon consumption so 
strongly that a higher consumption volume indicates higher carbon 
consumption regardless of the type of the urban structure. Thus, while the 
environmental, social and functional importance of high urban density and 
the building type have been demonstrated in a number of studies, from the 
climate change perspective these factors are not sufficient indicators. 
However, the research also indicated means to break the connection 
between consumption volume and  carbon consumption, as will be 
discussed later.

The result contradicts with some earlier findings [15, 16], but the reasons 
for the contradiction have been found and reported in some earlier studies 
as well. For example, Sovacool and  Brown (2010) find that the carbon 
footprints of city residents are substantially higher than country averages in
many developing countries, whereas in the developed countries the 
situation is reversed in general [10]. They state the significantly higher level 
of the standard of living in the urban areas in the developing countries as 
one of the key reasons for the result.  According to this dissertation, the 
same argument may also apply in the context of a developed country when 
the consumption of all the goods and services and their life cycle emissions, 
which were excluded from the inventory of Sovacool and Brown, are 
included. City residents outsource a significant amount of their emissions, 
especially in the developed countries  where the heavy industry is often 
located outside of the cities and even the countries, and imports form a 
significant share of the overall supply. Thus, their per capita emissions may 
well be substantially higher than those of the surrounding areas when 
comprehensive consumption-based analyses are conducted.  
The results reported by Ramaswami et al. (2008) and Schulz (2007 & 
2009) on cities importing a significant  share of the goods consumed, and 
thus GHGs as well, also support the finding of city residents outsourcing 
their emissions [5, 8, 13]. Evidence for the outsourcing of the emissions 
taking place on an economy level has also been presented by Wagner 
(2010), who argues that  the energy embedded in the imports of the 
developed countries may cause  their per capita emissions to actually 
increase even when national inventories would seem to show decreasing 
patterns [17].

As said above, the argument of the  dissertation results from altogether 
five studies. In the studies, a comprehensive consumption-based 
assessment model is developed for  carbon consumption assessments in 
different types of areas. The papers present together a coherent set of 
multiple case studies, all producing similar outcomes. The overall key 
argument was initially reported already in Paper I of the dissertation. The 
latter studies, published in Papers II-V, all support the initial finding. In the 
five papers, the carbon effects of urban structure and consumption volume 
are analyzed in different types of urban structures and on different levels of 
urbanization: on the city level with multiple cases of different types of cities 
(Papers I and II), on the level of  metropolitan areas with two distinct 
metropolitan centers including several cities (Paper III), on a national level 
based on four types of urban structures (Paper IV), and finally on a sub-city 
level (Paper V).

The remainder of the dissertation is  structured as follows. Section 2 
presents the research problem and the context in which the problem is 
analyzed. Section 3 concentrates on the methodology, presenting first the 
methods employed in the different papers of the dissertation, and then the 
wider methodological context of the whole dissertation. In Section 4 the
contributions of individual papers are summarized and linked to the 
research problem as well as to the overall argument of the dissertation. 
Section 5 summarizes the results and the contribution of the dissertation is 
put together. Section 5  also evaluates the validity  and reliability of the 
research and assesses needs for future  development around the topics of 
the dissertation. Papers I-V follow the references in Section 6.<ref name="Heinonen"></ref>

==Terminology==

The dissertation aims at consistent and generally accepted use of terms. 
However, some terminology is employed in multiple meanings and some 
may be specific to the research. Short explanations are given below to 
clarify these.

'''Research'''

In the dissertation, the term “the research” refers to the entirety of the 
dissertation as a whole.

'''Study/studies'''

The dissertation consists of multiple interconnected but individual studies. 
The terms “the study” or “the studies” refer to the individual studies 
reported in the published papers of the dissertation. 

'''Carbon emissions'''

In the dissertation, including the individual publications, the term “carbon 
emissions” refers to all the included GHGs (CO2, CH4, N2O and HFC/PFCs) 
in carbon dioxide equivalents (CO2e).

'''Carbon consumption'''

The term “carbon consumption” is employed to indicate the GHGs released 
as a result of consumption, when a consumer responsibility perspective is 
utilized, that is, allocating to a consumer the life cycle emissions (including 
production and delivery chains) of all his/her consumption.<ref name="Heinonen"></ref>

=Research problem=

The dissertation had no explicit research problem to  begin with. Each 
individual study had their purposes, which resulted in the research problem 
of the dissertation in the course of the research. The field of research was 
familiar via previous literature on the subject, but no hypotheses were set a 
priori. When the research progressed, the prior stages were utilized to set 
working hypotheses for the next stages as well as to guide the case selection. 
However, the findings led early to the forming of the first version of the 
research question which, with minor modifications, is now expressed as:

'''What are the effects of urban structure and the related consumption patterns on the carbon emissions of an average consumer?'''

All the five papers of the dissertation  contribute to the research question 
above. The research question is examined from several perspectives 
utilizing multiple case studies that represent different contexts. The 
dissertation creates new knowledge on the carbon implications of the urban 
structure and the related consumption patterns of the inhabitants in 
different area types. The results, in addition to contributing to academic 
research, can be of high value in advancing the important topic of city 
carbon management, and should thus be brought into the awareness of 
urban policy makers alongside the academic community.

The broader context in all the papers of the dissertation is the Finnish 
economy. This limits the generalizability of the results, which is analyzed in 
more detail in the papers, especially in Paper V. However, as the 
perspective on the carbon emissions is global, a similar approach could be 
employed elsewhere as well, even if the results of this dissertation would 
not be directly applicable as such.<ref name="Heinonen"></ref>

=Methodology=

==Carbon consumption assessment methods==

The dissertation approaches the research question by utilizing a 
consumption-based assessment of the emissions, that is, allocating to a 
consumer the GHG emissions caused by his/her consumption regardless of 
the geographic location of the occurrence of the emissions. The method 
employed is life cycle assessment (LCA), which is capable of capturing the 
emissions of production and supply chains globally. More specifically, the 
research employs streamlined input-output (IO) and IO-based hybrid LCA 
approaches [18]. The approach is streamlined to concern only one impact 
category of global warming. In more detail, the carbon consumption is 
assessed on the level of annual per capita emissions. Paper I employs a 
direct IO LCA method. In Papers II to V, the assessment model is further 
developed into an IO-based hybrid LCA model according to the tiered 
hybrid LCA method [18, 19].

The selected methods were assessed as the most suitable due to the 
complex nature of the research object, the carbon emissions of private 
consumption. The IO LCA-based methods are especially suitable for 
analyses in the context of the built environment [18]. The method allows 
analyses of complex systems with much less labor than more traditional 
process LCAs as it utilizes monetary inputs to assess the GHG emissions 
based on output tables derived from the economic IO accounting of an 
economy [20].

The model exploited for the direct IO assessment and used as the basis for 
the developed IO-based hybrid LCA  model is the Carnegie-Mellon 
University economic input-output LCA (EIO-LCA), which is freely available 
in the Internet [21]. Although not based on the Finnish economy, the model 
was assessed as the most suitable one to be employed in the research. Indepth analyses on the applicability as well as the general strengths and 
weaknesses of the EIO-LCA model and the hybrid model developed are 
presented throughout Papers I-V of the dissertation.

The IO method in general was first  introduced by the Nobel laureate 
Wassily Leontief in the 1930s. In  the 60s the approach was extended to
cover the environmental perspective  [18, 22] as well  as regional, subeconomy, multi-regional, and multi-economy contexts [23-25]. More 
recently, city level assessment models have also been developed based on 
the IO method [e.g. 35].

The employed IO and IO-based hybrid LCA methods are in accordance 
with the ISO 14040 standard for conducting LCA analyses [18, 19]. In the 
dissertation as a whole, the goal and the scope are defined by the research 
question and they are described in more detail in the paragraphs above. An 
average consumer was chosen as the functional unit to allow comparisons 
between different types of consumers and to maintain the comparability of 
the results throughout the dissertation. The system boundary, set by the 
selected method, is infinite in the number of upstream processes included 
[e.g. 18, 26], but limited to the national economy in treating all products 
and the entire production and supply chains as domestic. The boundary is 
also economic, as the processes where a monetary transaction between two 
sectors occurs are included. Furthermore, according to Crawford (2011), the 
IO-based hybrid LCA approach provides the most comprehensive system 
boundary possible [18].

Viewed from another perspective, the assessment model developed in the 
dissertation is in accordance with  the definition of the WRI Scope 3 
standard [27]. The WRI Scope 3 standard  requires that the upstream life 
cycle emissions are taken into account for all the goods in the scope of the 
assessment, a quality rarely found in the assessment models presented in 
previous studies in the field [5].

Following from the qualities of the  assessment model presented above, 
the dissertation contributes to the field of city and sub-city level IO-based 
hybrid LCAs with regard to method by including all private consumption in 
the assessment. The problems and uncertainties related to the selected 
method and the consequences in interpreting the results are covered in 
detail in Papers I-V of the dissertation.<ref name="Heinonen"></ref>

==Methodological context==

The approach described above falls into a wider methodological context of 
mixed method studies [28]. The background is predominantly quantitative, 
the research data being entirely  quantitative. However, as many 
methodologists have stated [i.e. 29, 30], all findings, whether based on 
qualitative or quantitative data, must be interpreted by the researchers. In 
this dissertation, the emphasis is in fact on the interpretation of the results 
in which a qualitative analysis is utilized instead of a statistical approach.  
Another wider perspective on the methodological context is found from 
the case study approach. The five papers of the dissertation all contribute to 
the same research problem, creating a strong case-based theory as
described by Eisenhardt (1989) and Eisenhardt and Graebner (2007) [31, 
32]. According to Eisenhardt and Graebner, this type of theory can be 
“accurate, interesting and testable”. In addition, they state that “[the theory 
is] more accurate, and more generalizable (all else being equal) when it is 
based on multiple case experiments”  [32]. The papers have different 
contexts and present different cases, but all produce an outcome that 
verifies the findings of the earlier papers regarding the research question.

The setting of the dissertation follows the process of building a case study 
theory of Eisenhardt [31] in the research design, the setting and shaping of 
hypotheses as well as in employing literature to build higher validity. The 
research began without any set hypotheses about the outcome. The cases 
were selected along the progress of the research according to the theoretical 
sampling principle. The earlier cases and their results were utilized to set 
up hypotheses that were tested and  developed further by advancing the 
research around the identified phenomena using divergent cases. Existing 
literature was employed both to find support for the results and to analyze 
the reasons for the conflicts with findings reported earlier.

In Papers I and II the case study objects are cities, seven cities in Paper I 
and two in Paper II. Paper III consists of two cases: the two largest 
metropolitan areas in Finland, both consisting of several cities. Paper IV 
was set to test the results of the three earlier studies at the national level, 
and it leans more on national census data than specific case data. In Paper 
V the case study approach was employed again, but within a city context.

Due to the nature of the research objects described above, as well as the 
assessment method, the data collection and analysis differ somewhat from 
the type of case-based theory described by Eisenhardt [31]. The input data 
employed is predominantly statistical and collected by a third party, rather 
than being collected from within the case organizations. However, while the 
census data of Statistics Finland [33] is the primary data source in all of the 
studies, multiple other sources of data were utilized, such as data provided 
by the case organizations. The data  sources and their utilization are 
explained in detail in the papers.<ref name="Heinonen"></ref>

=Summaries of the research papers=

[[File:Distribution_of_carbon_consumption_in_Finland.png|thumb|400px|Figure 1: The distribution of the carbon consumption of an average resident in Finland]]

The papers of the dissertation form a very coherent body. They all deal with 
the same research question from slightly different perspectives, thus giving 
a basis for strong conclusions. In the course of the research, a 10-category 
distribution of the emissions was developed to allow the analyses of the 
effects of urban structure and consumption patterns on the emissions. The 
distribution was employed in Papers I-IV. For Paper V, the distribution was 
aggregated into five categories. The 10-category distribution of the 
emissions in Finland on average (from Paper IV) is shown in Figure 1.

As the figure depicts, 70% of the emissions in Finland on average come 
from sources very closely related to urban structure: 30% from Heat & 
electricity, 17% from Private driving, 12% from Building and property, 11% 
from Maintenance and operation (of  buildings) and 1% from Public 
transportation. Now, in all the five studies including roughly 20 areas, only 
the emissions in the category of  Private driving were found to decrease 
along with an increase in the density of the urban structure. In all the other 
categories, the relation observed is  the reverse or ambiguous in general.

The overall emissions  were found to increase (rather than decrease) 
following an increase in the density. However, the possible causality 
between the density and the emissions was not studied. The observations 
describe the current state of the issue, which is that the consumption 
volume tends to increase towards  denser structures, and this causes the 
emissions to increase in all but the category of Private driving. 
Some interesting findings were made concerning the differences between 
the areas studied. In the areas with higher consumption volumes, a larger 
share of the consumption is directed at consumption categories with lower 
carbon intensity, such as services, which might have a positive effect on the 
overall carbon consumption. However, the observed increase in the 
consumption in other categories as well hinders this positive effect and 
leads only to a further increase in the overall emissions.  
Next, the five individual papers and their findings are presented. Figure 2 
presents the overall setting, and the following chapters briefly describe 
Papers I-V and their key findings.<ref name="Heinonen"></ref>

[[File:Research_problem_purposes_key_findings.png|thumb|400px|Figure 2: The research problem, purposes and key findings of Papers I-V and conclusion.]]

==Paper I: A Life Cycle Assessment of Carbon Mitigation Possibilities in Metropolitan Areas==

The purpose of the first paper was to create a first picture about the 
feasibility of a consumption-based life cycle assessment in modeling the 
carbon emissions of different types  of urban structures. The paper 
examined the applicability of the  IO-based screening-LCA method in 
modeling GHG emissions from consumption. Moreover, the paper provided 
increased understanding of the possible future utilization of the method in 
urban development.

The study utilized the Consumer survey 2006 data from Statistics Finland 
[33] to assess the consumption-based carbon emissions of the average 
consumers of seven Finnish case cities from the Helsinki Region: Espoo, 
Helsinki, Hyvinkää, Kerava, Nurmijärvi, Porvoo and Vantaa. The cities 
represent a dense metropolitan core, the capital city Helsinki, and two 
circles of smaller and less dense cities around Helsinki. The paper followed 
the pure IO LCA method utilizing the Carnegie Mellon University EIO-LCA 
model [21]. With the paper, we thus also set the ground for the future 
utilization of the EIO-LCA model in the Finnish context.

For the purpose of revealing the connections between different types of 
urban areas and carbon emissions, we divided the overall consumption into 
10 consumption classes, namely Heat and electricity, Building and 
property, Maintenance and operation, Private driving, Public 
transportation, Consumer goods, Leisure goods, Leisure services, Travelling
abroad, and Health, nursing and training services. The study showed that 
the annual per capita carbon emissions tend to increase when the 
disposable income grows, when the living space per capita grows and when 
no commuter connections are available. Also, the study showed that a large 
share of the overall per capita emissions is attributable to the consumption 
of daily goods and leisure goods and services, which have often been left out 
of the carbon emissions assessments. Table 1 presents the LCA results 
divided into the 10 consumption categories.<ref name="Heinonen"></ref>

{|{{prettytable}}
|+ Table 1 (from Paper I): The annual consumption (€) and per capita carbon emissions (t CO2e.) in the seven Helsinki Region cities
!
! Hyvinkää
! Vantaa
! Kerava
! Porvoo
! Helsinki
! Espoo
! Nurmijärvi
|-----
| Private consumption
| 13.300
| 16.000
| 17.200
| 15.900
| 17.400
| 18.800
| 20.400
|-----
| Carbon footprint
| 12,1
| 13,8
| 14,6
| 15,1
| 15,3
| 17,3
| 18,4
|-----
| Building energy
| 5,56
| 5,62
| 5,78
| 6,18
| 6,13
| 6,87
| 7,43
|-----
| Building and property
| 1,21
| 1,34
| 1,18
| 1,40
| 1,36
| 1,71
| 1,70
|-----
| Maintenance & operation
| 1,03
| 1,30
| 1,51
| 1,46
| 1,64
| 1,27
| 0,99
|-----
| Private driving
| 1,19
| 1,54
| 2,08
| 2,17
| 1,42
| 2,16
| 3,11
|-----
| Public transportation
| 0,20
| 0,63
| 0,36
| 0,48
| 0,64
| 0,45
| 0,47
|-----
| Travelling abroad
| 0,48
| 0,50
| 0,89
| 0,68
| 0,89
| 1,45
| 1,09
|-----
| Consumer goods
| 1,23
| 1,33
| 1,26
| 1,39
| 1,61
| 1,56
| 1,49
|-----
| Leisure goods
| 0,32
| 0,45
| 0,38
| 0,41
| 0,34
| 0,45
| 0,78
|-----
| Leisure services
| 0,66
| 0,80
| 0,72
| 0,70
| 0,99
| 1,08
| 1,02
|-----
| Health, nursing and training services
| 0,26
| 0,26
| 0,46
| 0,17
| 0,29
| 0,31
| 0,28
|}

==Paper II: Case study on the carbon consumption of two metropolitan cities==

In the second paper, the model created in the first paper was developed 
further. The first study,  while demonstrating that the screening-LCA is 
efficient to use, revealed also sources  of bias that needed to be resolved. 
Thus, in the second paper we enhanced the model with Finnish process 
data on housing energy and fuel combustion of private driving according to 
the tiered hybrid LCA method [19]. In addition, we applied price level 
adjustment factors to property prices and disaggregated the housing 
charges to be able to assess the housing related emissions in detail.

The purpose of the second study was to validate and analyze further the 
findings of the first study. Furthermore, with the second paper we argued 
for the importance of the utilization of a consumption-based assessment in 
city level carbon management, as well as for the high value of the inclusion 
of all the emissions of private consumption into the assessment.

We selected the capital city Helsinki and the city of Porvoo, a smaller city 
about 50 kilometers away  from Helsinki, as the case cities of the study.
These two present interesting variation in the city structures while 
belonging to the same economic region. The city sizes, population densities, 
housing types and income  levels differ substantially on the city structure 
level. In addition, Porvoo  is dependent on Helsinki for workplaces and 
services, which generates a significant amount of commuting. And, even 
more importantly, the fuel mixes of  the local energy production differ 
significantly, as the production is predominantly based on renewable fuels 
in Porvoo and fossil fuels in Helsinki.

The key finding, supporting the result of Paper I with the more accurate 
hybrid version of the assessment model, was that the influence on the 
carbon consumption of the urban density and the dominant building type 
of the area may be negligible. The study showed that the carbon 
consumption is on a substantially higher level in Helsinki than in Porvoo. 
The impacts of a higher consumption volume and, especially in the case of 
this study, the fossil-based fuel mix in Helsinki overrule the effects of the 
higher level of private driving and larger average living space that increase 
the emissions in Porvoo. This, however, indicates that decreasing the 
emissions of local energy production would be very efficient city-level 
carbon management. According to the study, the annual carbon 
consumption of an average inhabitant of Helsinki is 13.2 t CO2e and 10.3 in 
Porvoo, as illustrated in Figure 3.<ref name="Heinonen"></ref>

[[File:Annual_per_capita_carbon_consumption_Helsinki_Porvoo.png|thumb|400px|Figure 3 (modified from Paper II): The annual per capita carbon consumption in Helsinki and in Porvoo together with the volume of private consumption.]]

==Paper III: Implications of urban structure on carbon consumption in metropolitan areas==

The third paper forms a continuum for the first two papers. The paper 
concentrated on analyzing the connection between urban structure and 
carbon consumption. In the study, the two largest metropolitan areas in 
Finland were analyzed: Helsinki with the surrounding cities of Espoo and 
Vantaa, and Tampere with the seven surrounding cities divided according 
to the level of urbanization into two  groups, urban cities in the Tampere 
Region (UCT) and rural cities in the Tampere Region (RCT).

The purpose of the third paper was to analyze the effects of density, 
dominant building type, private driving and income on the carbon 
consumption. In accordance with the first two papers, the study found no 
clear connection between  urban structure and carbon consumption. The 
shares of the total emissions of the consumption of tangible goods and 
services seem to be high enough, and have a high enough variation for the 
overall consumption volume of the average resident of an area to become 
the key factor in the carbon consumption, rather than the urban structure.

With regard to urban structure, the study showed that the dominant 
sources of carbon emissions are housing energy and the construction and 
maintenance of the residence. While it  is highly relevant for the urban 
authorities to understand the structure of the overall emissions, the highest 
mitigation potentials related to urban structure are related to these two 
sources. Figure 4 demonstrates the volume and division of the carbon 
consumption in the two metropolitan areas.<ref name="Heinonen"></ref>

[[File:Annual_per_capita_carbon_consumption_Helsinki_Tampere.png|thumb|400px|Figure 4 (modified from Paper  III): The annual per capita carbon consumption (t CO2e) together with private consumption (€) and net earnings per capita (€) in the two metropolitan areas.]]

==Paper IV: A Carbon Consumption Comparison of Rural and Urban Lifestyles==

All the first three papers indicated that, at least in certain conditions, the 
link between urban density and the carbon consumption of an average 
resident is weak or even negligible.  The housing type or differences in 
private car usage seemed to be easily overridden by the carbon emissions 
from the consumption of all other goods and services, making the 
consumption volume the decisive factor with regard to the differences in 
carbon consumption between the studied cities. However, none of the 
studies had a very diverse basis, being mere case studies.

This setting gave rise to the fourth paper, which focused on differences in 
carbon consumption in different area types in Finland as a whole. The study 
included four data samples representing four different area types in 
Finland: rural, semi-urban, city and metropolitan (Helsinki Metropolitan 
Area). For these, the carbon consumption of an average resident of each 
type was assessed. The results of the study were interesting, as according to 
the results, the carbon consumption grows along with the degree of 
urbanization, as Figure 5 shows.

[[File:Annual_per_capita_carbon_consumption_Finland.png|thumb|400px|Figure 5 (modified from Paper IV): The annual average per capita carbon consumption (t CO2e), private consumption (€) and disposable income (€) in the four area types in Finland.]]

When each of the 10 consumption areas utilized were analyzed separately, 
the result was that only the emissions related to private driving increase 
when the degree of urbanization decreases, as Figure 6 shows. One of the 
primary reasons explaining the findings is that in housing energy, no clear 
differences in the monetary consumption were found between the area 
types, but due to a better fuel mix, such as increased use of wood, the 
emissions are lower in rural and  semi-urban areas. In all other 
consumption areas the emissions were found to grow along with the degree
of urbanization. The key factor is the consumption volume, which increases 
on average as the scale of urbanization increases.<ref name="Heinonen"></ref>

[[File:Annual_per_capita_carbon_consumption_Finland_categorized.png|thumb|400px|Figure 6 (modified from Paper IV): The  average annual per capita carbon consumption within the 10 consumption areas in the different area types.]]

==Paper V: Dense downtown living more carbon intense due to higher consumption: a case study of Helsinki==

The fifth and final paper of the dissertation provides a continuum for the 
earlier papers, advancing both the method and especially the discussion of 
the third paper on the implications  of urban structure on the carbon 
consumption of the inhabitants. The purpose of the study was to analyze 
further the implications of income and area type on the emissions. The 
study moved into a sub-city context, analyzing the annual per capita carbon 
load on two different levels of urban density within Helsinki, the suburban 
regions (Helsinki SU) and the downtown core (Helsinki DT). The Finnish 
capital city Helsinki provides an  urban structure where the dense 
downtown area attracts wealthier residents and the less dense suburban 
areas attract lower income residents on average, although with the income 
level being well above the Finnish average in the suburbs, as well.

For the study, the hybrid LCA model for the carbon consumption 
assessment was developed further. The  aggregation of the consumption 
sectors was decreased, increasing the overall number of sectors up to 59 
from the 43 of the previous version of the model. Also, the number of the 
consumption categories to present the results was dropped down to five: 
Housing, Ground Transport, Tangible Goods, Services and  Air, Maritime 
and Package Travel to clarify the demonstration of the results.

The findings of the study  follow the pattern identified in the previous 
studies. The carbon consumption is on  a substantially higher level in the 
much denser downtown core following the difference in the income levels. 
In the downtown area, the figure is 14.7 ton CO2e per capita with the annual 
consumption volume of 19.800 €, but in the suburbia only 12.0 tons with
16.800 € in purchases. Carbon consumption seems to increase especially in 
the categories of Tangible Goods, Services and  Air, Maritime and Package 
Travel with the increase in the disposable income. As in the previous studies, 
the carbon consumption increases in each category but Ground Transport. 
Interestingly, the emissions increase also in almost each individual 
consumption sector, as Table 2 showing the three largest sectors of each 
category demonstrates.<ref name="Heinonen"></ref>

{|{{prettytable}}
|+ Table 2 (from Paper V): The largest emission sources in each sector and the respective consumption volumes.
! Sector/Category
! colspan="2" | Helsinki DT
! colspan="2" | Helsinki SU
! colspan="2" | Finland
|-----
! Housing
| 6.3 t CO<sub>2</sub>e
| 6,660 €
| 5.5 t CO<sub>2</sub>e
| 5,630 €
| 4.7 t CO<sub>2</sub>e
| 4,580 €
|-----
| Heat
| 2.3 t
| 6,440 €
| 3.0 t
| 4,670 €
| 2.8 t
| 4,240 €
|-----
| Electricity
| 0.7 t
| 220 €
| 0.8 t
| 250 €
| 0.9 t
| 330 €
|-----
| ''Other''
| 1.9 t
| 3,890 €
| 1.4 t
| 2,950 €
| 1.1 t
| 2,070 €
|-----
! Tangible goods
| 3.9 t
| 6,440 €
| 3.0 t
| 4,670 €
| 2.8 t
| 4,240 €
|-----
| Food
| 1.9 t
| 2,120 €
| 1.8 t
| 1,870 €
| 1.6 t
| 1,810 €
|-----
| Clothing
| 1.1 t
| 1,330 €
| 0.5 t
| 1,870 €
| 1.6 t
| 1,810 €
|-----
| Sports and leisure eqp.
| 0.5 t
| 300 €
| 0.5 t
| 270 €
| 0.5 t
| 290 €
|-----
| ''Other''
| 0.4 t
| 2,690 €
| 0.2 t
| 1,870 €
| 0.2 t
| 1,590 €
|-----
! Transport
| 1.6 t
| 1,730 €
| 1.7 t
| 2,070 €
| 2.1 t
| 2,170 €
|-----
| Fuel combustion
| 1.0 t
| 380 €
| 1.0 t
| 390 €
| 1.4 t
| 550 €
|-----
| Vehicles acquisition
| 0.2 t
| 570 €
| 0.4 t
| 920 €
| 0.4 t
| 1,070 €
|-----
| Public transport
| 0.3 t
| 350 €
| 0.2 t
| 320 €
| 0.1 t
| 140 €
|-----
| ''Other''
| 0.1 t
| 430 €
| 0.1 t
| 440 €
| 0.2 t
| 410 €
|-----
! Services
| 1.6 t
| 4,600 €
| 1.2 t
| 3,520 €
| 0.9 t
| 3,070 €
|-----
| Hotels and restaurants
| 0.7 t
| 1,230 €
| 0.5 t
| 820 €
| 0.3 t
| 600 €
|-----
| Recreation and culture
| 0.5 t
| 820 € 
| 0.3 t
| 490 € 
| 0.2 t
| 430 €
|-----
| Health care
| 0.2 t
| 590 €
| 0.2 t
| 620 €
| 0.2 t
| 500 €
|-----
| ''Other''
| 0.1 t
| 430 €
| 0.1 t
| 440 €
| 0.2 t
| 410 €
|-----
! Air, Maritime and Package Travel
| 1.4 t
| 740 €
| 0.7 t
| 380 €
| 0.5 t
| 280 €
|-----
| Package holidays
| 0.9 t
| 490 €
| 0.4 t
| 210 €
| 0.4 t
| 210 €
|-----
| Air and maritime overseas travel
| 0.4 t
| 220 €
| 0.3 t
| 150 €
| 0.1 t
| 60 €
|-----
| ''Other''
| 0.1 t
| 30 €
| 0.0 t
| 20 €
| 0.0 t
| 10 €
|}

=Discussion and conclusions=

This research was aimed  to analyze the GHG emissions caused by the 
inhabitants in different types of urban structures, i.e. their carbon 
consumption. One key finding early on in the research was that the urban 
structure, especially population density and the dominant building type, 
has little impact on the carbon consumption of the inhabitants. This lead to 
the formation of an early version of the research problem, which then 
during the course of the research developed into the present form: 

'''“What are the effects of urban structure and the related consumption patterns on the carbon emissions of an average consumer?”'''

As shown in Section 4, all the five papers returned the same outcome: The 
carbon consumption is defined largely by the overall consumption and only 
to a very limited extent by the urban structure. Throughout the research the 
results indicated that the urban structure has a  consistent direct impact 
only on the emissions from private driving, whereas the emissions from 
other consumption activities follow closely the overall consumption. 
Interestingly, even concerning the emissions of housing energy, the area or 
the building type seem to have little  influence as such, the per capita 
emissions being very similar on average in all types of buildings and 
structures. While contradictory to some results reported earlier, as well as 
to the prevailing belief, the arguments are clear. As analyzed in detail in 
Paper IV, smaller than average household sizes, energy use of common 
spaces in apartment buildings, emissions derived from secondary homes, 
all of which are mostly associated with to higher income city residents, 
significantly narrow down the differences between housing related 
emissions of city and rural area residents. Furthermore, the share of the 
carbon consumption of the goods and services categories outside of housing 
energy and transport was found to be significant enough to create an 
increase in the consumption in these categories to result in emissions large 
enough to easily hinder the potentially positive effect of urban density.

The dissertation strongly supports the findings also indicated earlier [5, 8, 
13, 35]. Cities may outsource such a high share of the emissions that the
GHG emissions may easily rise well  above those of the rural and semiurban areas. This is due to the tendency of production to be located outside 
of the cities, while the emissions are  allocated to the city residents if 
assessed from the consumption perspective. The results of Sovacool and 
Brown (2010) as well as those of Lenzen et al. (2004) would seem to depict 
the same phenomenon. If the consumption volume is on a higher level in a 
city, the result might be carbon consumption exceeding the country 
average. In addition, both studies bring up the significance of the income 
level and suggest that the GHG emissions may relate much more to 
purchasing power than structural features [10, 35]. Overall, two main 
characteristics would seem to largely explain the contradiction between the 
results of the dissertation with some findings reported earlier [12, 15, 16]. 
First, the rather large share of emissions derived from consumption not 
related to the residence, which is often left outside the scopes of the 
assessments, is included in the dissertation. Second, the dissertation is 
placed in the context of actual lifestyles. It would seem that, as discussed in 
more detail in Paper IV, for example theoretic differences in energy 
consumption between different  building types diminish when real 
consumption data is analyzed. In theory, increasing the living space per 
person naturally increases demand for heating and cooling (ceteris 
paribus), but it is by no means a new idea that the lifestyles and choices of 
the occupants may significantly change the outcome of the theoretic 
assessment [e.g. 38].

An interesting continuum indicated in Paper V, while not analyzed in 
detail, is that the same phenomenon of outsourcing the emissions seems to 
apply in a sub-city context as well. A higher consumption of services in the 
dense downtown area, especially in categories such as cafes, restaurants, 
hotels and movies, might decrease  the emissions from, for example, 
housing electricity use and food consumption. In more limited scope 
emissions assessments, this might also create a bias in the results.

Including altogether a reasonably high number of studied areas, around 
20, the reported findings seem robust. Even with the identified 
uncertainties, discussed in the papers, the overall arguments are strong. 
While IO-based LCA approaches in general are subject to potential biases, 
the identified increase in the consumption volume in monetary terms in 
almost each consumption category along with an increase in the income 
level strongly supports the leading argument.

This said, the studies also indicated ways to break the connection between 
the income level and emissions from consumption. First, a general pattern 
found was a decrease in the carbon intensity of consumption relative to the 
income level. It would seem that the share of the disposable income
consumed decreases as the income level increases. Similar, although much 
weaker, connection could also be  identified with the carbon intensity of 
consumption. On higher overall consumption levels, a larger share of the 
consumption is targeted to goods  and services with lower-than-average 
carbon intensity than on lower income levels. Second, the city of Porvoo, 
the case presented in Paper II, provides an example of the impact of low 
carbon local energy production on the carbon consumption of an average 
resident. The results of  Paper II indicate that cleaner local energy could 
reverse the situation of a specific city compared to the country average even 
with the income level higher than the country average. As the cleaner local 
energy would also affect the carbon load of all the consumption allocated to 
goods and services produced with the same energy, the potential impact is 
significant.

The arguments of the dissertation, while intended to be proved robust 
throughout this work, should be understood in their specific context. 
Whereas detailed discussion about the validity and the reliability of the 
arguments is provided in the next sections, and on the uncertainties related 
to the method and the specific findings in the published papers, some 
general level limitations are provided here as well. First, the arguments 
should only be applied to the level of an average resident of the area in 
concern. The method employed should not be reckoned to be applicable to 
the level of an individual. With individual choices, a person is able to affect 
his/her carbon consumption so significantly that the presented argument 
on the connection between the overall consumption volume and the carbon 
consumption would not apply. Second, the context of the study is Finland, 
and country specific factors may lead  to results contradictory to the 
situations in other geographical contexts, as is discussed in more detail in 
Section 5.1.

Furthermore, the place in which a certain individual resides does not 
define their carbon consumption in a  way that could be predicted by the 
average. For example, the depicted higher carbon consumption in a certain 
area compared to the surrounding area does not indicate a decrease in the 
carbon consumption if a person moved from the higher carbon 
consumption area to the surrounding area. In a city versus rural or 
suburban area comparison this would  most probably lead to a further 
increase in the carbon consumption, as the city lifestyle with the adapted 
consumption patterns would be likely to remain and the emissions from at 
least private driving would increase, unless the move would be 
accompanied with a decrease in the disposable income. Similarly, the, if a 
person were to move from a rural area to a city center, into a smaller 
apartment and close to divergent public transportation opportunities,
carbon consumption would likely decrease, assuming that the other 
consumption patterns would remain.

Finally, the dissertation also contributes to the methods of city and subcity level LCAs. As was brought up, the area is of high importance, with 
cities being accountable for the majority of the global GHG load. Similar 
approaches can be employed in other contexts to produce a more 
comprehensive understanding of how  carbon emissions are related to 
different types of cities and communities. If complementing the results with 
production-based assessments, the two together create a comprehensive 
basis for city level carbon management.<ref name="Heinonen"></ref>

==Validity of the research==

There are two different dimensions in  assessing the validity of the study. 
The concept of validity is divided into two perspectives: the internal validity 
and the external validity. In addition, concerning the dissertation, the 
validity assessment should cover both the research as a whole and the 
individual elements within the entirety. The validity assessment is 
conducted mirroring the guidelines of Ruane (2004) [29].

The internal validity refers to the results and conclusions involving 
causality assumptions [29]. The overall internal validity of the research 
arises from the selected method. The multiple case study method with such 
a high number of studied  areas as assessed in the dissertation provides a 
high degree of internal validity [31]. Furthermore, obeying the case study 
method in setting no a priori hypotheses for the research and following the 
selective sampling principle as the research advanced supports the 
argument of high internal validity, as very distinct cases produced similar 
outcomes.

Notwithstanding, as discussed in detail in the individual papers, the 
measurement employed can only produce estimates, not exact information. 
From the accuracy perspective, the deviation of the results from their true 
values [e.g. 34], there are numerous factors (aggregation of the input data, 
asymmetries between the data and the  LCA model, errors in the output 
vectors of the model, aggregation of  the output industry sectors) that 
decrease the accuracy of the results. Keeping this in mind, the high validity 
argued above is not compromised, however. The results are still good 
estimates and, as the internal validity is good, the conclusions are robust. 
On the level of the assessment methods, the concept of internal validity 
can be divided into two perspectives: the part of the independent variables, 
the causes for the outcomes, and the dependent variables, here the sectoral 
emissions factors. When the independent variables, here the input data, are 
concerned, the dissertation is assessed  as being of high validity. On the 
aggregate level where the research is positioned, an increase in the amount
of each consumed good or service  ceteris paribus increases the carbon 
emissions. The utilized numeric  input data, describing the average 
consumption in different areas, describes the consumption volumes and 
changes in them relatively well as long as average consumers purchasing 
average goods are considered.

More assumptions relate to the dependent variables, i.e. the output of 
carbon emissions caused by the purchases of goods and services. The 
uncertainties have been analyzed in Papers I-V, but in general there may be 
occasions where an increase in the consumption volume does not indicate 
higher emissions. This type of bias would occur if a low-carbon good was 
more expensive than the market  average. The increased consumption 
would incorrectly result in higher  carbon consumption in an IO-based 
assessment. However, it is very unlikely that the overall results would be 
compromised due to this uncertainty, as only average consumers are 
considered in the dissertation. In addition, the multiple study approach 
reduces the risk of this type of bias in the sense of the impact potential of 
individual abnormal consumption behavior. The probability is low with 
large sample sizes and decreases also if multiple cases produce similar 
outcomes. Furthermore, in Finland in general, the regional price 
differences are small, except for the  housing prices, for which a price 
correction factor was employed. Additionally, given the consistent results in 
all of the studies, the deviations from the average goods would need to be 
predominant, and lead consistently to either an increase or a decrease in 
the carbon consumption, in order to affect the results significantly. Finally, 
none of the samples represent extreme consumer types, where a possibility 
of deviations from average goods would be more likely.

Two inherent weaknesses of IO-based analyses, namely proportionality 
and homogeneity assumptions, describe the situation in general terms. An 
assumption that inputs to some sector of an economy would be linearly 
proportional to the output is referred to as the proportionality assumption, 
whereas the homogeneity assumption refers to the idea that price and 
sector outputs would have a consistently linear relation [e.g. 35].

The conclusions drawn from the results are also subject to potentially 
weak internal validity. They easily include causality assumptions that are 
not supported by the results [29]. The  research refrains from presenting 
strict causalities, but aims instead to understand the phenomena. Despite 
this, many conclusions  were narrowed down, focused better or argued 
through additional data during the review processes of the dissertation 
papers. In general, the context of all the studies is Finland, thus restricting 
the strongest and the most robust findings to Finland. Some estimations 
about the broader generalizability of the findings are presented in the
papers, but they also note the importance of sufficient similarity with the 
urban as well as socioeconomic structures. This level of generalization is 
strongly supported by the findings of Lenzen et al. (2004), who report 
increasing energy demands in the city center, and denote higher income 
levels as one of the primary reasons [36]. However, this also means that in 
some other context other factors may be dominating, as for example 
Crawford and Fuller (2011) and Fuller and Crawford (2011) demonstrate 
with regard to location, type and size of the residence in Australia [39, 40].

The generalizability also defines the external validity of the research. The 
power of the sample to represent a  larger population or different 
populations is an important perspective of the external validity of the 
dissertation. In the Finnish context this sample generalizability is assessed 
as high. Again, the multiple case study approach, representing altogether a 
diverse body of Finnish consumers,  makes this dimension of external 
validity within the Finnish context  fairly good. In broader contexts the 
external validity inevitably decreases. However, there are different levels of 
external validity. It is less risky to state that a similar method and model 
could be used globally, as has been argued, than to claim that the results 
would be the same. This distinction has also been made in the papers of the 
dissertation.<ref name="Heinonen"></ref>

==Reliability==

The reliability of the dissertation and the arguments arising from the 
results have been discussed in several  occasions above. When specifically 
considering the consistency of the measures in producing the same 
outcome each time [29], the measures utilized are of very high reliability. A 
key characteristic of the method, constant emissions vectors of the output 
matrices, makes it very consistent, thus allowing the repeatability of the 
research relatively easily concerning the measurement perspective.

When also considering the input data, the picture gets slightly more 
complex. As has been discussed in  the individual papers, the input data 
contains uncertainties that may affect the reliability of the research. 
Especially in Paper I of the dissertation, small sample sizes left room for 
errors arising from abnormal observations. However, as all of the cases 
later in the course of the research produced similar outcomes, the 
possibility of this kind of error related to the initial results was significantly 
reduced, as the multiple case study method suggests [31].

Notwithstanding, while the input data represent averages of the sample, 
they are probably not exact averages. If another sample of the same 
magnitude was taken, the figures would probably change. With sufficient 
sample sizes the variation would be small, but it would still exist. Given that 
the sample sizes are sufficient in the studies of this dissertation, as was
argued above, this kind of non-patterned error, called noise [29], does not 
compromise the results.

Another perspective to the reliability issue when the input data is 
considered is longitudinal reliability. Would the results change significantly 
if the input data was taken from another year? This perspective brings 
along new uncertainty issues related to currency fluctuations and inflation. 
In the early stage studies of the dissertation, this perspective of reliability 
was tested with a comparative longitudinal analysis of the same cases with 
input data from an earlier year. The results were very similar except for the 
magnitude, in which the difference was most likely due to the inflation and 
currency fluctuation issues mentioned. This was accepted as a sufficient test 
of the longitudinal reliability.

In a longer time span, longitudinal fluctuation is likely to occur due to 
changes in lifestyles. Moreover, production technologies will also change 
with time, which affects the carbon emissions. Thus, while the results seem 
robust from the reliability perspective, they are tied to the time of the 
measurement. Lifestyles as well as technologies change slowly in general, 
but in the context of the built environment, long time spans are often 
considered, calling for caution when the results are utilized in long-term 
planning.<ref name="Heinonen"></ref>

==Future research needs==

The research path started in this dissertation is but in the beginning. The 
findings of the dissertation open a variety  of directions to continue the 
work. Some steps have already been taken, while some still remain as mere 
ideas. The first early attempts have been made to merge the consumptionbased GHG assessment model with a  construction phase emissions 
assessment model to create a temporal LCA of a residential area. The idea is 
very interesting in its ability to demonstrate the effects of construction 
phase choices, but there are still plenty of difficulties especially with regard 
to the temporal perspective. On  the other hand, a study trying to 
incorporate new environmental impact categories into the assessment 
model is underway.

Another direction, important but still in an initial stage, would be the 
testing of the results in international contexts. The generalizability of the 
results of the dissertation is so far restricted to the Finnish economy and, 
with some degree of uncertainty, to other societies with similar structures, 
as argued earlier. Comparative  analyses would be very interesting and 
might produce important information from both academic and policy 
making perspectives.<ref name="Heinonen"></ref>

=Papers I-V=

Papers of the dissertation can be downloaded from the following sources:

*Paper I: Heinonen, Jukka; Junnila, Seppo; Kuronen, Matti (2010): A Life Cycle Assessment of Carbon Mitigation Possibilities in Metropolitan Areas, SB10 Finland, Sustainable Community - BuildingSMART, Espoo, 22.-24.9.2010, Finnish Association of Civil Engineers RIL, Conference Proceedings. 
*Paper II: Heinonen, Jukka; Junnila, Seppo (2011): Case study on the carbon consumption of two metropolitan cities, International Journal of Life Cycle Assessment, 16, 569-579. [http://www.springerlink.com/content/hm140801g7347246/]
*Paper III: Heinonen, Jukka; Junnila, Seppo (2011): Implications of urban structure on carbon consumption in metropolitan areas, Environmental Research Letters, 6, 014018. [http://iopscience.iop.org/1748-9326/6/1/014018]
*Paper IV: Heinonen Jukka; Junnila Seppo (2011): Carbon Consumption Comparison of Rural and Urban Lifestyles, Sustainability, 3 (8), 1234-1249. [http://www.mdpi.com/2071-1050/3/8/1234]
*Paper V: Heinonen, Jukka; Kyrö, Riikka; Junnila, Seppo (2011): Dense downtown living more carbon intense due to higher consumption: a case study of Helsinki, Environmental Research Letters, 6, 034034. [http://iopscience.iop.org/1748-9326/6/3/034034]

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