Suburban neighbourhoods versus panel housing estates - An ecological footprint-based assessment of different residential areas in Budapest, seeking for improvement opportunities


165Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.DOI: 10.15201/hungeobull.73.2.4 Hungarian Geographical Bulletin 73 2024 (2)                            165–184.

Introduction

One of the most spectacular processes in 
the development of post-socialist cities has 
been the transformation of the inner-city 
neighbourhoods and the outskirts. Outside 
the core city, in the agglomeration zone sub-
urbanisation and urban sprawl have deter-
mined the development process in the last 
decades (Kubeš, J. and Nováček, A. 2019; 
Spórna, T. and Krzysztofik, R. 2020). With-
in the administrative boundaries of the city, 
fragmentation has progressed, with different 

neighbourhoods occupying different posi-
tion on the housing market. In Hungary, and 
also in other post-socialist countries, the po-
sition of housing estates has been changing 
recently due to modernisation and upgrad-
ing, as evidenced by the rising dwelling pric-
es and a growing demand for such dwellings 
(Kalm, K. et al. 2023).

There is a growing number of suburbanis-
ing towns and cities, which is significantly 
transforming urban land use, but urbanisa-
tion also happens at peri-urban areas. The in-
evitable corollary of decentralisation, on the 

Suburban neighbourhoods versus panel housing estates – 
An ecological footprint-based assessment of different residential 

areas in Budapest, seeking for improvement opportunities

Tamás EGEDY1, Cecília SZIGETI2 and Gábor HARANGOZÓ3

Abstract

In this study, the household consumption-related ecological footprint of lifestyles linked to panel housing 
estates and suburban neighbourhoods were compared in the case of Budapest and its suburbs. Our results 
show that the biggest parts of the ecological footprint are in both study areas the carbon, the cropland and the 
forest components, in line with earlier calculations. On the whole, the ecological footprint values are bigger 
in the suburban study area (2.63 gha/capita) compared to the panel housing estates (2.29 gha/capita), mainly 
because of the differences between the carbon uptake and the built-up land components. Beyond comparing 
the ecological footprint values of different residential areas, the study also contributes to the literature by 
addressing the improvement options of the respective areas through a rough model calculation on the reduc-
tion opportunities in both cases, resulting 36 percent in case of panel housing estates, and 47 percent in the 
suburban areas. Although these values have to be considered cautiously, they show significant opportunities 
in ecological footprint reduction in both types of residential areas supported by individual motivations, as 
well as by policy measures.

Keywords: suburbanisation, urban sprawl, sustainability assessment, housing estates, panel buildings, eco-
logical footprint, Budapest

Received February 2024, accepted April 2024.

1 Department of Tourism, Budapest Business University. Markó u. 29–31. H-1055 Budapest, Hungary; Geo-
graphical Institute, HUN-REN Research Centre for Astronomy and Earth Sciences. Budaörsi út 45. H-1112 
Budapest, Hungary. E-mail: egedy.tamas@uni-bge.hu

2 Sustainable Studies Institute, Budapest Metropolitan University. Nagy Lajos király útja 1–9. H-1148 Budapest, 
Hungary. Corresponding author’s e-mail: cszigeti@metropolitan.hu

3 Department of Sustainability Management and Environmental Economics, Corvinus University of Budapest. 
Fővám tér 8. H-1093 Budapest, Hungary. E-mail: gabor.harangozo@uni-corvinus.hu



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.166

other hand, is urban shrinkage (Champion, 
T. 2001), which has led to the re-emergence 
of the compact city concept in the EU’s cohe-
sion and social policy. Analysing the trends 
of the last almost four decades, a reversal to-
wards the compact city in the development 
of metropolitan regions can be expected and 
urban sprawl can be seen as an intermediate 
stage of long-term territorial development 
(Taubenböck, J. et al. 2019). The expected di-
rection of development is therefore not to-
wards further expansion of these areas, but 
rather towards networking between increas-
ingly compact, highly urbanised areas (Lang, 
R. and Knox, P.K. 2009). In this respect, the 
environmental characteristics of residential 
areas within the city and in the suburban 
zone are particularly important issues. Last 
but not least, there is much to be learned from 
the question of what ecological, architectural 
and lifestyle changes would be needed for 
the resident population to increase the sus-
tainability of cities. Based on Ferreira, J.P.  
et al. (2023), different types of urban structure 
and population are responsible for signifi-
cantly different levels of ecological impacts. 
According to Erdeiné Késmárki-Gally, Sz. 
and Neszmélyi, Gy.I. (2017), this is highly in-
fluenced by the significant differences in the 
level of urbanisation in the world.

Based on previous research, the aim of this 
study is to compare the ecological impacts of 
two very different types of urban structures, 
(1) densely populated panel housing estates 
in the compact city, and (2) sparsely populat-
ed suburban settlements outside the city, but 
still close the city boundary. This paper com-
pares two types of neighbourhoods through 
the example of Budapest, using the concept 
of the ecological footprint (Wackernagel, M. 
and Rees, W.E. 1996). The research questions 
are the followings:

 – RQ1. How do the ecological footprints of 
suburban settlements and panel housing 
estates differ from each other?

 – RQ2. Considering their different built-up 
characteristics, what are the opportunities 
to decrease the specific ecological footprint 
of these two different neighbourhoods?

The intended novelty and added value of this 
study is related to both research questions. In 
the literature review section, a research gap is 
detected. In spite there seems to be a consensus 
among academics that urban sprawl increases 
ecological footprint compared to compact cities, 
there is very little empirical research on com-
paring different types of residential areas, espe-
cially when ecological footprint of consumption 
habits of the respective lifestyles is also con-
sidered. Academic literature mainly focuses 
on the ecological footprint-based comparison 
of different construction technologies (Li, H.X. 
et al. 2014; Kumar, A. et al. 2021; Ottelin, J.  
et al. 2021), or macro-level (national or regional) 
comparisons (Kovács, Z. et al. 2020, 2022; Yang, 
Y. et al. 2022; Kuzyk, L.W. 2023; Zhang, H.  
et al. 2024), while ecological footprint literature 
lacks convincing studies comparing different 
residential areas (even Ottelin, J. et al. [2015] 
compares inner and outer urban areas in terms 
of carbon footprint).

The calculation presented related to RQ1 
contributes to fulfil this gap. The results not 
only help to better understand the differ-
ences between the overall ecological foot-
print values of the two study areas, but also 
highlight the key components contributing to 
both the indirect and the direct parts of the 
overall ecological footprint.

Another novelty value is the addressing 
and better understanding of the improve-
ment options in panel building estates and 
suburbs (related to RQ2, in the discussion 
section). This can contribute to the further 
development of both public policies and in-
dividual strategies aiming at decreasing eco-
logical footprint related to both study areas.

The rest of the study is structured as fol-
lows:

a) Literature review section provides a lit-
erature review of the major environmental 
challenges in residential areas, covering both 
suburban and densely populated prefab 
neighbourhoods, as well as a short overview 
of the concept of the ecological footprint with 
a special focus on the urban level. 

b) Methodology section introduces the study 
areas as well as the method of the ecologi-



167Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

cal footprint calculations mainly based on 
household consumption. 

c) Results section presents the results of 
comparing the two study areas.

d) Discussion section analyses the opportu-
nities of decreasing the ecological footprint 
of the different types of neighbourhoods. 
Finally, the last section concludes the main 
findings of the research and provides an out-
look for further research. 

Literature review

Environmental challenges in different residential 
areas

The environmental challenges of suburban 
neighbourhoods

Following the recession in the first half of 
the 1990s, cities of the Central and Eastern 
European countries have experienced a spec-

tacular development (Enyedi, Gy. 1998). Sub-
urbanisation and urban sprawl became one 
of the dominant spatial processes in the Bu-
dapest urban region, as in other large Central 
and Eastern European cities (Tammaru, T. 
et al. 2009; Roose, A. et al. 2013; Kocsis, J.B. 
2015; Csapó, T. and Lenner, T. 2016). Sub-
urbanisation and urban sprawl in the Buda-
pest agglomeration accelerated in the second 
half of the 1990s triggered by lower land and 
dwelling prices, lower densities, more attrac-
tive environment etc. The target settlements 
of the accelerating suburbanisation were 
mainly villages and small towns in the west-
ern and northern parts of the urban region, 
where the hilly and mountainous areas of-
fered an attractive natural environment for 
the newcomers (Photo 1). An uncoordinated 
and chaotic growth prevailed in the subur-
ban belt of Budapest significantly transform-
ing these areas (Egedy, T. 2012; Kovács, Z. 
and Tosics, I. 2014). Transport networks have 
not been developed in line with emerging 

Photo 1. Suburban neighbourhood in the Budajenő-Telki area. (Photo taken by the authors.)



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.168

needs, typically due to the lack of resources 
and a focused strategy (Erdeiné Késmárki-
Gally, Sz. et al. 2020).

Suburbanisation and urban sprawl have led 
to a dramatic increase in transportation need 
and the associated car use, and transport prob-
lems gradually became the biggest challenge 
for the city region (Austin, P. and Gregorova, 
E. 2015). Another major challenge for post-so-
cialist cities is the significant transformation 
of space and wasteful land use in city regions 
(Sýkora, L. 2014), as highlighted by Figure 1.

The statistics on commuting clearly show 
that in the post-1990 period, the spatial struc-
ture of the metropolitan region of Budapest 
has gradually transformed towards polycen-
tric development. This process has resulted in 
an increase in cross-commuting between cities 
and a sharpening urban-to-rural commuting 
due to the decentralisation of the economy. 

Meanwhile, in terms of land use, the mas-
sive conversion of former agricultural land 
into residential and commercial areas has 
commenced (Kovács, Z. and Tosics, I. 2014). 
The consequences of urban sprawl became 
visible in the region: the share of abandoned 
land increased, the proportion of agricultural 
land decreased, and the natural environment 

became fragmented. The growth of artificial 
surfaces has significantly accelerated. The 
post-socialist, post-industrial urban develop-
ment has increasingly become a victim of ad 
hoc decisions and development. Investments 
became often random, making spatial de-
velopment in the Budapest urban region 
unpredictable, it became difficult to predict 
and monitor land use changes. In the last 
two decades, development has been the re-
sult of market processes rather than of well-
established development policy interven-
tions (Fazekas, M. et al. 2015; Lang, T. 2015). 
Development has been organised along the 
lines of weaker resistance and stronger lob-
bies, reinforced by short-term political inter-
ests (Egedy, T. et al. 2017). As a consequence 
of the uncontrolled and unregulated spatial 
processes, the conflicts and negative envi-
ronmental and social effects associated with 
suburbanisation and urban sprawl have in-
tensified (Da Silva Machado, F. 2017).

The most common environmental chal-
lenges caused by the rapid development 
of suburban settlements include transport 
problems arising from commuting (with 
the ecological issues arising from car traffic 
being the main reason), land use problems 

Fig. 1. The interrelationship between mobility and spatial development in the Budapest metropolitan region. 
Source: Authors’ own design.

Mobility

Increasing suburbanisation after
regime change

Increased commuting due to
suburbanisation

New, complex forms of commuting

Spatial development

Spatial deconcentration of housing,
concentration of workplaces

Concentrated decentralisation of
workplaces, growing role of

suburban cities

Changing land use, increasing
environmental impacts

tim
e



169Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

linked to land conversion for housing (en-
croachment on natural landscapes, growth 
of artificial surfaces, illegal development and 
circumvention of regulations).

Challenges of panel housing estates from 
environmental and social perspectives

The reasons behind the construction of 
housing estates in both Western and East-
ern Europe were similar: on the one hand, 
they were an attempt to address the quan-
titative housing shortage by cost-effective 
means, while on the other hand, it was an 
attempt to fulfil social equality and/or egali-
tarian political ideology (communist Eastern 
Europe) based on the theory of modernist 
architecture (Benkő, M. 2015; Leetmaa, K.  
et al. 2018). One spectacular and – at the time 
– effective element of this was the emergence 
and spread of prefabricated housing estates 
in Europe and in other parts of the world.

The 1970s was the peak period for the con-
struction of prefab housing estates in East-

Central European countries (Ouředníček, M. 
and Kopecká, Z. 2023), including Hungary 
(Kovács, Z. et al. 2018). Only in Hungary, 
about 600,000 dwellings were built using pre-
fabricated technology (Benkő, M. and Egedy, 
T. 2023). Based on the authors, more than 
half of them has central heating and emerged 
in the form of greenfield investment. The lay-
out and architectural character of the 1970s 
housing estates was mainly determined by 
the Soviet type large-panel technology. Ten-
storey high strip houses (slabs) and 15-sto-
rey high towers became dominant, mostly 
with five, sometimes with ten staircases, as 
illustrated by Photo 2. The reduction of costs 
was only possible with the neglect of the 
construction of public services, and develop-
ment of green areas, which became the most 
serious deficiencies of these housing estates 
(Kolcsár, R.A. et al. 2022). These large-scale, 
land-intensive, densely built housing estates 
with medium- and high-rise buildings were 
usually built on the periphery of large cities, 
in isolated environments far from the city 
centre, on open urban land still available for 

Photo 2. Typical prefab building built in the 1970s. The “Village House” with 884 dwellings residing 
3,000 people built in 1970 in Budapest’s 3rd district. (Photo taken by the authors.)



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.170

large-scale construction (Petsimeris, P. 2018). 
The physical characteristics of housing es-
tates: size, design and construction have had 
a crucial impact on the long-term trajectory 
and performance of housing estates on the 
housing market, even if social and housing 
values have changed over time (Hess, D.B. 
et al. 2018). Monotonous high-rise housing 
estates located in the periphery with poor 
accessibility face higher risks for social and 
physical downgrading than smaller housing 
estates closer to the city centre (Andersson, 
R. and Bråmå, Å. 2018).

The 1970s also brought about changes in the 
social composition of housing estates. Poorer 
and less educated people got better access to 
public housing in housing estates, and the 
average social status of the new estates de-
creased accordingly. After the change of re-
gime, the wealthier strata who could afford 
better quality housing moved out of the panel 
housing estates, and today these neighbour-
hoods are mainly inhabited by the lower-mid-
dle class and the elderly (Egedy, T. et al. 2022). 
At the same time, due to the smaller average 
dwelling size, prefab housing estates have 
some potentials as in most European coun-
tries (and also in Hungary). They can attract 
small households composed of young singles, 
elderly, divorced people, foreign students and 
temporary workers who seek smaller housing 
units (Hess, D.B. et al. 2018). 

The challenges of prefab housing estates 
can be grouped into three categories: i) chal-
lenges caused by the built environment, ii) 
problems associated with the social envi-
ronment, and iii) challenges arising from 
the location (localisation) of the housing 
estates. The challenges of the built environ-
ment include problems of technological ori-
gin (problems due to the reinforced concrete 
construction, poor thermal and acoustic in-
sulation, the single-pipe heating system with 
its wasteful technology, which did not allow 
the individual metering and proportional ac-
counting of the energy used per apartment 
etc.), the lack of services and infrastructure 
(lack of institutions, shops, public services), 
the quality of green spaces and parking prob-

lems. The social challenges of prefab hous-
ing estates include the ageing of the local 
population, difficulties resulting from the 
co-existence of different generations (older 
original population and young newcomers), 
problems related to segregation, safety and 
crime. The location and localisation of hous-
ing estates (peripheral location in the case of 
panel estates) and their difficult accessibility 
often pose significant problems in terms of 
the lack of proximity and connectivity be-
tween the neighbourhood and the rest of the 
city. 

The concept of the ecological footprint in a 
regionally oriented framework

The ecological footprint indicator measures 
human demand on nature by showing how 
much biologically productive land and sea 
area is needed to sustain a given consump-
tion pattern. The magnitude of the demand, 
thus, can be compared with the available bio-
capacity on the supply side. If the demand 
for land in a certain area (country, region) 
exceeds the supply of biologically productive 
land, this results an ecological deficit indicat-
ing unsustainability at the longer term.

The concept was originally introduced in 
the 1990s (Wackernagel, M. and Rees, W.E. 
1996), but has since been further developed 
(Wiedmann, T. et al. 2006). The size of the 
ecological footprint is expropriated through 
consumption activities is calculated by di-
viding the amount of resources and services 
consumed by the yield of the type of land 
that produces those resources and services. 
The resulting values are then multiplied by 
equivalence factors and summed to pro-
duce the final ecological footprint values. 
Meanwhile, biocapacity measures the eco-
logical assets (including forest land, grazing 
land, cropland, fishing land and built-up 
land) available within the boundaries of the 
investigated territory and their capacity to 
produce renewable resources and ecologi-
cal services (Galli, A. et al. 2020). National 
footprint calculations are constantly improv-



171Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

ing as better data become available and new 
methodologies are developed (Kitzes, J. et al. 
2009). However, sub-national calculations are 
still relatively rare.

One direction for improvement in sub-na-
tional calculations is to develop a method 
to disaggregate national ecological foot-
prints by socio-economic groups or cer-
tain territories. This is done by combining 
existing National Footprint Accounts with 
input-output analysis (Wiedmann, T. et al. 
2006; Csutora, M. et al. 2011; Zhou, X. and 
Imura, H. 2011). One specific area of appli-
cation of the ecological footprint indicator 
is the calculation of the ecological footprint 
for cities and city regions, which became 
popular in the literature recently (Galli, A.  
et al. 2020; Kovács, Z. et al. 2020; Swiader, M.  
et al. 2020). The results of a recent publication 
regarding the ecological footprint calculation 
of Budapest provides the basis for our cur-
rent research (Kovács, Z. et al. 2022). The 
concept of ecological footprint has been the 
focus of much criticism (Galli, A. et al. 2016; 
Harangozó, G. et al. 2019), but its versatility 
has made it one of the most popular sustain-
ability assessment indicators, inspiring many 
creative applications to address spatial as-
pects (Kocsis, T. 2014).

Despite the popularity and the method-
ological development of ecological footprint 
calculations, there are surprisingly few stud-
ies aiming at comparing different types of 
built-up areas beyond the conventional ur-
ban-rural approach. Holden, E. (2004) com-
pared different types of residential areas in 
Norway and found that suburbs had higher 
footprint than city centres and argued for 
‘decentralised concentration’ as a future de-
velopment direction of urban areas, meaning 
smaller and more compact cities instead of 
urban sprawl. This study, however, mostly 
focused on the ecological footprint of hous-
ing and commuting, while embedded eco-
logical footprint of consumption (this may 
vary between different residential areas) 
was disregarded. There are studies compar-
ing the ecological footprint of different built 
structures, including prefab buildings (e.g., 

Solís-Guzmán, J. et al. 2013; Husain, G. and 
Prakash, R. 2019), but these still not cover 
the ecological footprint aspects of the life-
styles related to them. 

An interesting perspective is provided by 
Hurley, R.E. (2009), suggesting that brown-
field development of residential areas is pre-
ferred to greenfield ones. This sound to be 
logical (with the addition, that not exactly 
the ecological footprint is lower, but the need 
for – further – bio-capacity is less in case of 
brownfield investment), however, there is no 
empirical evidence provided for that. Indeed, 
Zhang, L. et al. (2016) could prove such rela-
tionship (brownfield investments are better 
than greenfield ones also from an ecological 
footprint perspective, in case of Chinese in-
dustrial areas), but not in residential areas. 

As existing research does not seem to cover 
the differences between ecological footprint 
patterns of various types of residential areas 
(especially considering respective consump-
tion habits), there is a research gap and need 
for more empirical studies in the field. 

Methodology

Delimitation of the study areas

In our study, the household consumption-re-
lated ecological footprint of lifestyles linked 
to panel buildings and suburban neighbour-
hoods were compared in the case of Buda-
pest. Following the scope of the research, two 
study areas were defined:

 – Prefab panel buildings within the city bor-
ders: these neighbourhoods include multi-
storey, land-intensive buildings with high 
population density and relatively low 
apartment sizes, with little or no green 
surfaces and with district-heating. On one 
hand, inhabitants of these buildings have 
limited individual options on energy ef-
ficiency improvement (e.g., insulation) 
or alternative energy sourcing (e.g., solar 
panels). On the other hand, panel neigh-
bourhoods are close to the compact city 
centre and supplied by public transpor-



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.172

tation. Altogether there are 57 housing 
estates within the city limits of Budapest 
with partly or fully prefab panel build-
ings. Based on the authors’ estimation, 
this means about 200,000 dwellings with 
approximately 460,000 residents.

 – Suburban neighbourhoods in the agglom-
eration of Budapest: these are villages and 
smaller towns, mostly with single fam-
ily homes with smaller gardens, the size 
of dwellings is bigger and they are sup-
plied with individual heating. There are 
more options regarding individual im-
provements for energy efficiency or use 
of alternative energy sources, however, 
such neighbourhoods have limited ac-
cess to public transportation. For the re-
search, the following seven municipalities 
were included in our sample: Budakeszi, 
Dunakeszi, Halásztelek, Pilisborosjenő, 
Szentendre, Telki and Vecsés. When com-
piling the suburban sample, villages, small 
and medium towns were considered, 
where relatively new and low-rise family 
house neighbourhoods are dominant. A 
further aspect was to include towns from 
various geographical sectors of the suburbs 
of Budapest. The total housing stock of the 
selected settlements is about 48,000 dwell-
ings, with a population of 130,000.
The study areas are overviewed by Figure 2.

Data and method

The process of calculating the household-
related ecological footprint (associated with 
both goods and services), was conducted 
using an input-output model, supplement-
ed with environmental data. Input-output 
models (based on the seminal work of Le-
ontief, W. in 1936) unveil the interdepend-
ence among sectors within an economy and 
quantify how a unit of output in one sector 
relies on resources drawn from various other 
sectors. To illustrate, consider the inputs re-
quired for the consumption of a kilogram of 
potatoes, including the agricultural, energy, 
transport, and retail sectors etc. 

The integration of environmental data 
into input-output models (environmentally 
extended input-output analysis – EEIO), it 
becomes possible to quantify the ecological 
footprint related to household consumption. 
This type of ecological footprint calculation 
is considered as a top-down approach. The 
input-output model was first used to calcu-
late the ecological footprint by Bicknell, K.B. 
et al. (1998), and Ferng, J.J. (2001). The first 
application in Hungary was by Csutora, M. 
et al. (2011), who used it to determine the eco-
logical footprint of household consumption. 
In this study, we extended the application of 
this methodology to a regional context, fol-
lowing the methodological guidelines set by 
Wiedmann, T. et al. (2006). Similar method-
ology was used by Córcoles, C. et al. (2024), 
using an environmentally extended multire-
gional input-output model and the Spanish 
Households Budget Survey to extract ex-
penditure microdata by municipality size.

The household consumption spending 
related methodology is highly appropriate 
to address micro-level differences between 
the study areas in many aspects. For exam-
ple, differences in household energy spend-
ing address the differences between prefab 

Fig. 2. Overview and location of the study areas. 
Source: Authors’ own compilation.

Szentendre

Pilisborosjenő

Telki

DunakesziDunakeszi

Vecsés

Budakeszi

Halásztelek

BUDAPESTBUDAPEST

Prefab housing estate

Suburban neighbourhoods



173Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

panel and suburban family house dwellings, 
spending on transportation and vehicle fuel 
address the spatial aspects of the study areas, 
while spending on various goods and servic-
es indicate the differences between lifestyles 
representing the study areas. The ecological 
footprint embedded in household consump-
tion can be expressed through the formula:

EF = EFdir · (I-A)-1 · FD,

where EF represents the ecological footprint, 
EFdir stands for the direct ecological footprint 
vector of specific sectors (in gha per million 
HUF). The term (I-A)-1 corresponds to the 
Leontief-inverse matrix derived from the in-
put-output model, showing the interdepend-
encies among sectors. Finally, FD stands for 
the household-related final demand vector 
indicating the extent of consumption along 
the products of various sectors during the 
study period.

The data for the EFdir vector were obtained 
from the Global Footprint Network (GFN) 
database, specific for Hungary, for 2019, the 
latest dataset provided by GFN. The house-
hold FD consumption vectors are calculated 
based on the EU Statistics on Income and 
Living Conditions (EU-SILC) database, data 
were obtained from the Hungarian Central 
Statistical Office (HCSO). Data were available 
for 2019, the last year before the Covid-19 
pandemic. For the first case area (Budapest 
panel building neighbourhoods) data on 
households from Budapest with district heat-
ing were used as a proxy, while for the ag-
glomeration case area, households from the 
respective municipalities in the Hungarian 
SILC database were used. Economy level 
input-output tables are developed in every 
five years for Hungary by the HCSO, so we 
applied the latest version, representing 2020. 

Beyond the ecological footprint of the em-
bedded consumption (indirect part), calcu-
lated as above based on Wiedmann, T. et al. 
(2006), we also estimated the direct compo-
nents, originating directly from households. 
These components have been quantified along 
two domains of the ecological footprint:

 – Carbon related component: This results 
from carbon emissions directly from resi-
dential heating and vehicle fuel usage. 
Examples include emissions from burning 
natural gas and gasoline or diesel during 
private car use. However, it excludes fac-
tors like electric heating, as electricity us-
age generates carbon emissions elsewhere 
(in power stations and during production 
and transportation of boilers, already cov-
ered by the EEIO-based calculation above). 
Similarly, the usage of bus transport ac-
counted when acquiring transport services. 
(The burning of firewood for home heating, 
relevant for the agglomeration is not quan-
tified in ecological footprint accounts, as it 
is considered as carbon neutral. However, 
in practice it is not necessarily the case 
[Gunn, J.S. et al. 2012], not considering ot-
her pollution caused by firewood heating.) 
Quantifying the household’s direct carbon 
footprint involves the following four steps:
a) Identifying expenditure on fuels (piped 

natural gas, bottled gas, liquid fuels, coal, 
briquettes, coke) and vehicle fuels (petrol, 
diesel) based on the HCSO consumption 
survey data.

b) Determining consumption quantities 
based on average prices.

c) Calculating annual per capita carbon-
dioxide emissions using calorific values (GJ/
unit of volume) and specific carbon-dioxide 
emissions (t CO2/GJ) of different fuels.

d) Deriving the carbon footprint per capita 
(gha/person) based on the coefficient of car-
bon dioxide from the (GFN data).

 – Built-up land related component: This is 
associated with the physical area of resi-
dential properties and roads, in proportion 
to household utilization. As a proxy, prop-
erties are estimated to cover 1,000 square 
metres per households in the agglomera-
tion (accounting for 0.25 gha – 0.12 gha/
capita – considering that both built-up land 
and arable land have an equivalence factor 
of 2.51 gha/ha). For panel building apart-
ments in multi-storey blocks, this compo-
nent was neglected. There was no proxy to 
estimate the household use related part of 

(1)



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.174

road surfaces, so this component is some-
what underestimated. 
Beyond comparing the per capita ecologi-

cal footprint values of the study areas, the 
study goes further. Based on literature and 
own considerations, specific improvement 
options are presented and discussed through 
a model calculation for the study areas.

Results

Table 1 provides an overview of the per capita 
household-related ecological footprint values 
for the two study areas, including both indi-
rect (in household consumption embedded) 
and direct components. 

Data show that the biggest components of 
the ecological footprint are in both study ar-
eas the carbon, the cropland, and the forest 
components, in line with earlier calculations 
(see Kovács, Z. et al. 2020, 2022). Altogether, 
the ecological footprint values are bigger in 
the suburban study area (2.63 gha/capita) 
compared to the panel housing estate neigh-
bourhoods (2.29 gha/capita), mainly because 
of the differences between the carbon uptake 
and the built-up land components. 

In spite of the clear differences between the 
two study areas (the overall per capita foot-
print value in the suburban sample is 15% 

higher than in the panel housing estate sam-
ple), there are major differences, if the direct 
and indirect parts of the ecological footprint 
values are considered. The indirect (embed-
ded in the life-cycle of purchased goods and 
services) part of the household consumption 
related footprint is 14 percent higher in case 
of panel housing estates (2.13 gha/capita ver-
sus 1.83 gha/capita in the suburbs) and the 
values of panel housing estates outnumber 
suburbs related all of the three most influen-
tial component (cropland, carbon and forest 
land). Indeed, the higher overall ecological 
footprint values of the suburbs emerge based 
on the major difference between the direct 
components (0.76 gha/capita in the suburbs), 
4.75 times bigger than the 0.16 gha/capita val-
ues of the panel housing estate sample. The 
respective carbon component is much larger 
in the suburban sample because of heating 
with natural gas. This component is not rel-
evant in the panel housing sample, because 
those households use district-heating (and, 
thus, count into the indirect component), 
their natural gas consumption is very low 
(used mainly for heating water and cooking) 
compared to suburban households. The di-
rect built-up land component is also bigger 
in the suburban sample (see the details of the 
respective methodological considerations in 
the previous section).

Table 1. Per capita household consumption related and total ecological footprint as well as bio-capacity by land use types*

Land use 
types

Household-related ecological footprint Ecological 
footprint 
(national, 

total)

Bio-capacity
(national)

Budapest panel buildings Suburbs

indirect direct total indirect direct total

Cropland 0.93 – 0.93 0.82 – 0.82 1.11 1.68
Grazing land 0.06 – 0.06 0.05 – 0.05 0.11 0.08
Forest 0.35 – 0.35 0.31 – 0.31 0,40 0.67
Fish 0.02 – 0.02 0.01 – 0.01 0.02 0,02
Built-up land 0.04 – 0.04 0.03 0.12 0.15 0.13 0.13

Carbon 0.73 0.04**
+0.12*** 0.89 0.65 0.48**

+0.15*** 1.28 2.23 –****

Total 2.13 0.16 2.29 1.87 0.76 2.63 3.97 2.57
*In gha/person, 2019, household related data. Source: Authors’ own calculation, national level data: GFN.
**Natural gas related (heating, cooking, hot water; only cooking and hot water in district heated panel buildings. 
***Transport related. ****As a fictive land type, not applicable in bio-capacity accounts.



175Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

Furthermore, there may be another 
element to be considered in the car-
bon component in the suburban study 
area, the impact of the firewood heat-
ing. In the ordinary ecological foot-
print accounts, biogenic emissions are 
not considered (based on the assump-
tion that dead wood would decom-
pose anyway), however, Gunn, J.S. et 
al. (2012) debate this approach. It is not 
the scope of this study to dig deeper 
in this debate, so a further 0.15 gha/
capita carbon uptake land component 
(based on firewood consumption) was 
not added to the suburban ecological 
footprint, but still mentioned as a po-
tential fictive element.

Household consumption-related 
ecological footprint data for both 
types of study areas are smaller than 
the national total values (but this is 
not very surprising as the latter also 
involves footprint components be-
yond the household consumption, 
such as governmental and third sector 
activities). If we, however, compare 
the results to the national bio-capacity 
(the ‘supply’ of biologically produc-
tive land), it is obvious that the house-
hold-related ecological footprint itself 
approaches (in case of the panel build-
ings) or even outnumbers (in case of 
the suburban study area) it, raising 
serious sustainability concerns.

Table 2 goes further and provides 
a summary on the ecological foot-
print data according to consump-
tion (COICOP – Classification of 
Individual Consumption According 
to Purpose, United Nations 2011 cat-
egories) (UN 2011).

If consumption categories are consid-
ered, the most important components 
are the food, housing (mainly heating) 
and transportation related ecological 
footprint components. The food com-
ponent is somewhat bigger in the panel 
housing neighbourhoods, that can be 
the result of higher spendings on food 

Ta
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Categories

01 – Food and beverages

02 – Alcohol, tobacco 
and narcotics

03 – Clothing and 
footwear

04 – Housing, water, 
electricity, gas, fuels

05 – Furnishings, 
household equipment

06 – Health

07 – Transport

08 – Communication

09 – Recreation and 
culture

10 – Education

11 – Restaurants and 
hotels

12 – Miscellaneous 
goods/services

Total

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da

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bu
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di
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87

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19 –

0.
19

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04 –

0.
04

0.
31

0.
04

0.
35

0.
05 –

0.
05

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03 –

0.
03

0.
18

0.
12

0.
30

0.
01 –

0.
01

0.
15 –

0.
15

0.
02 –

0.
02

0.
22 –

0.
22

0.
05 –

0.
05

2.
13

0.
16

2.
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0.
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0.
16 –

0.
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0.
04 –

0.
04

0.
31

0.
61

0.
79

0.
07 –

0.
07

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03 –

0.
03

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11

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15

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26

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01 –

0.
01

0.
09 –

0.
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02 –

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02

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25 –

0.
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1.
87

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Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.176

Discussion

Based on the results, it seems that compact, 
high density, high-rise housing estates are 
better than low-rise, sprawling, suburban ar-
eas, when ecological footprint is considered. It 
is important to note here, that results emerged 
as the aggregation of three major influencing 
factors, covered in the results section: building 
characteristics (influencing housing related 
footprint components), spatial aspects (re-
sponsible for commuting related footprint) 
and consumption patterns (influencing a ma-
jor share of indirect – in the supply chains of 
products and services consumed). 

Although the lack of extensive literature 
coverage of comparing the ecological foot-
print of specific residential areas, the results 
can still be discussed from different angles. If 
regional urban-rural aspects are considered, 
the current results are in line with recent cal-
culations (Swiader, M. et al. 2020; Kovács, 
Z. et al. 2022), however, the study areas in 
those calculations are not specified and ad-
dress only the differences between city and 
suburban neighbourhoods (disregarding the 
heterogeneity of those study areas). 

Literature focusing on the construction 
aspects of buildings from an ecological 
footprint perspective (Solís-Guzmán, J.  
et al. 2013; Husain, G. and Prakash, R. 2019) 
highlight the benefits of modern apartment 
blocks. This is partly in line with the results 
of this study, as panel building neighbour-
hoods seemed to have lower housing-related 
footprints, but this is not necessarily because 
of the modernity of those buildings, but rath-
er related to the lower per capita areas and 
the detached nature of such dwellings. 

The findings of Holden, E. (2004) – an ad-
vocate of ‘decentralised concentration’ based 
on a Norwegian case study – show similari-
ties with the results of this study, but the cur-
rent two study areas (panel building estates 
within a major city and suburbs out of the 
city, but still linked to it) are far from his ide-
al settlement, compact and small towns with 
low travel needs. Very few studies go beyond 
the aspects mentioned in this section so far 

product, which can be further decomposed 
along product categories using the coefficients 
of the Global Footprint Network Database 
(Table 3). The most dominant components are 
bread and cereals (because of their high quan-
tity consumed) and meat products (based on 
their per unit ecological footprint impacts). 
The biggest difference between the panel 
housing and the suburban neighbourhoods 
are related to the housing component, where 
the latter has more than double values (0.79 
gha/capita versus 0.35 gha/capita), mainly be-
cause of the larger average size of appartments 
and the individual buildings as opposed to 
panel apartments. The transportation related 
footprints are relatively similar (higher com-
muting impacts in the suburban lifestyle may 
be balanced by more leisure related monility 
among residents of panel buildings).

If differences between suburbs and panel 
housing estates are considered, it can be seen 
that footprint components related to most con-
sumption categories are smaller in case of sub-
urbs, but the large surplus related to housing 
(mainly related to energy consumption and 
physical land use) makes the overall value out-
number panel housing estates by 15 percent.

Results comparing the ecological footprint 
values of different residential areas are not 
only interesting in themselves, but also serve 
as the basis of our model calculation on how 
to reduce them, discussed in the following 
section. 

Table 3. Household-related food consumption footprint 
according to main food categories*

Food categories Panel 
buildings Suburbs

Bread and cereals
Meat
Fish
Milk, cheese, eggs
Oils/fats (plant-based)
Oils/fats (animal-based)
Fruit
Vegetables
Sugar, jam, honey, chocolate
Food n.e.c.
Total

0.240
0.180
0.023
0.064
0.100
0.037
0.078
0.077
0.039
0.022
0.870

0.210
0.160
0.020
0.054
0.089
0.032
0.066
0.066
0.033
0.018
0.740

*In gha/person, 2019. Source: Authors’ own calcula-
tion based on GFN coefficients. 



177Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

and consider general consumption patterns 
when comparing the ecological footprint 
values of different residential areas. Gao, X.  
et al. (2024) analysed Chinese households 
and found that footprint inequality increased 
both in urban and rural areas. The results are 
hard to be explicitly compared to this study, 
but it supports the current finding that foot-
print related to consumption patterns play a 
key role in the overall footprint. 

Based on the results, it seems that the geo-
graphical location of the dwelling, its size, 
architectural character, the basic communal 
infrastructure and the consumption patterns 
of residents are all key determinants of the 
magnitude of the ecological footprint and the 
potentials for reducing it. Beyond discuss-
ing the results of the two study areas of this 
paper, maybe an even more important field 
is to look for options decreasing ecological 
footprint specific for the different neigh-
bourhoods. In this section, some ideas are 
presented based on literature, with a special 
focus on the major footprint components. 

Literature differentiates top-down and bot-
tom-up measures to decrease ecological foot-
print in the different residential areas. The first 
follows a macroeconomic approach through 
policies developed and financed by the states 
or state-level authorities, while the latter, a 
microeconomic perspective, means locally 
initiated and realised interventions (Tilov, I.  
et al. 2019; Saunders, H.D. 2000). The mea-
sures themselves can cover several fields: ener-
gy consumption (housing and transportation), 
products related to housing and clothing and 
food consumption (Shinde. R. et al. 2022).

Su, B. et al. (2022) highlight the significant 
potential in reducing food-related footprint 
by consuming less meat or even going veg-
an. Vávra, J. et al. (2018) draw the attention 
to food self-provisioning, even though such 
opportunities seem to be limited even in sub-
urban conditions. There is a huge body of 
literature on how housing-related footprint 
can be radically decreased. Among them 
many researchers advocate refurbishing the 
buildings (Mir, A. et al. 2022; Kazemzadeh, 
E. et al. 2023), improving energy efficiency 

(Li, R. et al. 2022), promoting renewable en-
ergy in residential use (Shabir, M. et al. 2023), 
developing the electricity grid (Kuzyk, L.W. 
2023) or promoting low-carbon technology 
innovation already at the planning phase of 
buildings (Gao, X. et al. 2024).

Based on these ideas, as a basis of a mod-
el calculation, the following measures are 
quantified here: 1) going totally vegan by 
avoiding meat, fish and dairy product con-
sumption, 2) giving up totally harmful habits 
of smoking and alcohol consumption, and 3) 
transforming household-related energy use 
totally to renewable energy (and, thus, elim-
inating the indirect and direct carbon foot-
print elements) and giving up individual car 
usage with combustion engines(eliminating 
the direct carbon component of transporta-
tion related footprint). Based on the earlier 
outcomes of Table 2 and 3, this would result 
in decreased per capita ecological footprint 
values, as summarised by Table 4. 

Estimates based on Table 4 indicate a 0.83 gha/
capita (36%) reduction in the panel housing es-
tates and 1.25 gha/capita (47%) in the suburban 
sample area. An important insight is that sub-
urban neighbourhoods not only have higher 
potential for reduction, but if the total theoreti-
cal potential could be achieved, the remaining 
per capita ecological footprint would be even 
lower compared to panel building neighbour-
hoods (1.38 gha/capita versus 1.46 gha/capita 
respectively). Additionally, in case the fictive 
0.15 gha/capita firewood would also have been 
accounted, based on Gunn, J.S. et al. (2012), as 
derived in the method section) this could be a 
further reduction potential.

If our assumption for the number of resi-
dents of panel housing estates (450,000) 
holds true, the overall reduction potential 
accounts for 373,500 gha for this study area, 
8.4 percent of the total footprint value of 
Budapest based on the most recent related 
calculation (Kovács, Z. et al. 2022). The re-
spective reduction potential for the suburbs 
may vary between 10.9 and 15.9 percent of 
the total ecological footprint of the agglomer-
ation of Budapest. Although it is very hard to 
estimate the population in the suburbs living 



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.178

in similar neighbourhoods as in our 
respective study area (small towns 
that are different from urbanised sub-
urbs or rural areas in the suburbs of 
Budapest), the range estimated here 
is based on the assumptions that the 
whole agglomeration has the same 
amount (higher end of the range) or 
same ratio (lower end of the range) of 
residents falling into our suburban 
sample. However, as the considera-
tions of the decreasing potential ap-
ply also to the whole Budapest or 
agglomeration population, the num-
bers estimated in this passage can be 
understood as underestimation of the 
total reduction potential.

Although these estimations are 
very rough (not taking into account 
the emerging needs for additional ve-
gan food, public transportation etc.), 
clearly indicate huge opportunities for 
ecological footprint reduction. While 
current values are higher in the sub-
urban areas, the outcome of the reduc-
tion options also seems to be higher 
(also proportionally); this can also be 
considered when limited governmen-
tal resources or funding options are 
allocated for such purposes. The better 
understanding of the differences be-
tween core-periphery patterns (stud-
ied also from a different perspective 
by Péti, M. et al. (2024) can enable 
more case specific reduction actions.

In some cases, ecological footprint 
reduction does not need financial in-
vestment (in case of going vegan or 
giving up harmful habits. In other 
cases, however, improving the en-
ergy efficiency of buildings or trans-
portation, monetary resources are 
essential and modernisation funds 
indeed play a major role. According 
to Bajomi, A.Z. et al. (2022), in coun-
tries, like Hungary and others, where 
the state provides very little funding 
and support for modernisation and 
energy efficiency programmes of 

Ta
bl

e 4
. P

os
sib

ly
 a

ch
iev

ab
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 C

O
IC

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co
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um
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n 

ca
te

go
rie

s*

Bu
da

pe
st

 a
nd

 
ne

ig
hb

ou
rh

oo
ds

Categories

01 – Food and beverages

02 – Alcohol, tobacco and 
narcotics--

03 – Clothing and foot-
wear

04 – Housing, water, 
electricity, gas, fuels

05 – Furnishings, house-
hold equipment

06 – Health

07 – Transport

08 – Communication

09 – Recreation and 
culture

10 – Education

11 – Restaurants and 
hotels

12 – Miscellaneous goods/
services

Total

Bu
da

pe
st

 p
an

el
 

bu
ild

in
gs

in
di

re
ct

di
re

ct
th

eo
re

tic
al

 re
du

ct
io

n 
po

te
nt

ia
l

to
ta

l (
po

te
nt

ia
l)

0.
87 – 0.
27

0.
70

0.
19 – 0.
19 –

0.
04 – – 0.
04

0.
31

0.
04

0.
25

0.
10

0.
05 – – 0.
05

0.
03 – – 0.
03

0.
18

0.
12

0.
12

0.
18

0.
01 – – 0.
01

0.
15 – – 0.
15

0.
02 – – 0.
02

0.
22 – – 0.
22

0.
05 – – 0.
05

2.
13

0.
16

0.
83

1.
46

Su
bu

rb
s

in
di

re
ct

di
re

ct
th

eo
re

tic
al

 re
du

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io

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po

te
nt

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l

to
ta

l (
po

te
nt

ia
l)

0.
74 – 0.
23

0.
51

0.
16 – 0.
16 –

0.
04 – – 0.
04

0.
31

0.
61

0.
70

0.
22

0.
07 – – 0.
07

0.
03 – – 0.
03

0.
11

0.
15

0.
15

0.
11

0.
01 – – 0.
01

0.
09 – – 0.
09

0.
02 – – 0.
02

0.
25 – – 0.
25

0.
04 – – 0.
04

1.
87

0.
76

1.
25

1.
38

*I
n 

gh
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 in

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te
xt

. 



179Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

residential buildings compared to other EU 
member states, this is clearly a limiting fac-
tor. If the benefits of such programmes are 
highlighted from properly from multiple 
angles (including the results of this study, 
as well), more convincing recommenda-
tions for policymakers can be formulated. 
Furthermore, if also at an international con-
text, state subsidies are scarce or limited, 
even the disposable income and savings of 
the local residents can be a basis, when in-
vestment is needed for ecological footprint 
reduction measures (Shinde, R. et al. 2022). 
As the authors studied residential areas in 
Switzerland, the availability of financial re-
sources of local residents can also be a limi-
tation factor if major refurbishment of build-
ings is considered, even though this would 
pay back over time.

In case of both top-down and bottom-up 
measures to decrease ecological footprint, the 
rebound effect (savings and, thus, ecological 
footprint reduction achieved in one area can 
lead to increased spending, an again larger 
ecological footprint, in other fields) needs to 
be considered (Chitnis, M. et al. 2013). For 
example, savings on energy bills may be 
spent on larger distance driven as leisure ac-
tivity, partly or fully decreasing the achieve-
ment in ecological footprint reduction. This 
phenomenon draws the attention for the 
need of a complex, environmentally con-
scious approach, when promoting measures 
to decrease ecological footprint. Considering 
the results of this study as a rough model cal-
culation on how ecological footprint could be 
reduced in different types of residential ar-
eas, several limitations need to be mentioned:

Comparing two lifestyles is obviously ar-
tificial – in reality, there are many different 
lifestyles living side by side. The aim was to 
illustrate that different neighbourhoods with 
populations following different lifestyles 
have different potentials to reduce the level 
of the current ecological footprint.

This research is based on sample-based sta-
tistical data, from which individual differ-
ences cannot be identified due to the nature 
of the research.

The research relates to a single point in time, 
so comparisons over time, which would be 
the most meaningful application of ecological 
footprint calculations, are hence not possible.

The model calculation oversimplifies at 
some points (not considering the increased 
need for public transportation or vegan food if 
higher ecological footprint intensive patterns – 
such as carnivorous diet or individual driving 
of combustion-engine vehicles – are given up). 

The limitations suggest that the re-
sults have to be interpreted with caution. 
However, the results still show, that a more 
detailed understanding of ecological foot-
print of different urban neighbourhoods and 
related lifestyles can enable both individuals 
and policy makers to find alternative oppor-
tunities on how to launch programmes to 
decrease local ecological footprints. 

Conclusions and outlook

Central and Eastern European cities are under-
going concurrent processes of suburbanization 
and densification, characterized by ongoing 
urban sprawl alongside efforts to increase com-
pactness, particularly evident in major capital 
cities. This trend is particularly pronounced in 
cities experiencing a transition from a period 
of shrinking in the 1990s to a recent phase of 
growth, known as reurbanization. In such cit-
ies, strategies are needed to address challenges 
related to vacant properties, brownfield sites, 
transportation infrastructure, and overall qual-
ity of life for new residents (Wolff, M. 2018). 
Suburbs face various social and environmental 
issues, including inadequate infrastructure, in-
creasing social polarization, and growing com-
muting pressures, contributing to congestions, 
and impeding residents’ daily lives (Buzási, A. 
and Jäger, B.S. 2020; Mobolaji, D. et al. 2022). 
Therefore, it is key to better understand and 
measure the environmental challenges related 
to these areas. 

This study compares the ecological foot-
prints of two very different residential areas: 
panel building housing estates and suburban 
neighbourhoods through the examples of 



Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.180

Budapest. Based on the literature, this study 
not only contributes to the ecological foot-
print-based comparison of the study areas 
(RQ1), but also provides a novel model calcu-
lation to address the improvement potential 
specific to the study areas (RQ2). The find-
ings and the explicit answers to the research 
questions can be summarised as follows:

Panel housing estates exhibit a slightly 
lower per capita ecological footprint, attrib-
uted to building-related and spatial differ-
ences as well as assumably slightly lower per 
capita income compared to suburban areas, 
2.29 gha/capita versus 2.63 gha/capita respec-
tively. Beyond these factors, differences in 
food and transportation-related footprints 
were less pronounced (RQ1).

In addition to absolute footprint values, the 
study suggests a rough model calculation for 
estimating opportunities to decrease ecological 
footprint, as well. Findings show a 36 percent 
reduction potential for panel housing estates 
and 47 percent for suburban areas, meaning 
that suburbs may even achieve lower footprint 
values than panel housing estates (RQ2). 

Although these figures have to be inter-
preted cautiously, the specific details pre-
sented in this study indicate that numerous 
individual initiatives and policy interven-
tions can be suggested that align with both 
urban development and ecological objec-
tives. As a new insight offered by this study, 
such measures to decrease ecological foot-
print may be structured and scaled along 
the major aspects influencing the ecological 
footprint of the study areas: 

Related to the energy efficiency character-
istics improvement of dwellings, suburbs of-
fer a bigger and more flexible opportunity, 
as not only large-scale, policy driven refur-
bishment projects can be implemented, but 
smaller scale, individual, even do-it-yourself 
ones. However, newly built, or refurbished 
panel housing estates can provide comfort 
and high energy efficiency at the same time 
(Hess, D.B. et al. 2018), a major driver of con-
scious reurbanization. 

Regarding the spatial aspects, different 
pathways can target the idealistic ‘decentral-

ised concentration’ (Holden, E. 2004). Panel 
housing estates within the city perform already 
right well in this perspective, while the com-
pact municipality approach as a future devel-
opment stream could contribute to the reduc-
tion of ecological footprint in suburbs, as well.

The consumption patterns related to both 
study areas are important, also from an eco-
logical footprint perspective. To avoid the re-
bound effect (Shinde, R. et al. 2022), environ-
mental education and consciousness should 
be fostered, so that ecological and financial 
savings related to the previous aspects are 
not spent on further ecological footprint in-
tensive goods and services. 

Beyond these measures, the limitations of 
this study presented before also highlight 
new research directions:

As there are very few research and com-
parison of the ecological footprint of differ-
ent residential areas available at this time, 
further studies are needed to go beyond the 
urban-rural comparison and assess and com-
pare specific neighbourhoods. 

Beyond input-output modelling-based 
studies, bottom-up ecological footprint as-
sessment and comparisons would be very 
useful, considering local conditions even 
more specifically.

This study is based on a single point in 
time, but temporal comparisons, quantify-
ing the possible differences over time of dif-
ferent residential areas would also add new 
insights to the better understanding of the 
ecological footprint aspects of territorial de-
velopment. 

To overcome the simplifications used in 
this model calculation on the ecological foot-
print reduction potential of different residen-
tial areas, more research is needed to specify 
and quantify the trade-offs related to specific 
measures (e.g., switching between transpor-
tation modes, diets, habits), also from an eco-
logical footprint perspective.

Acknowledgement: The research was supported by 
the National Research, Development, and Innovation 
Fund of Hungary under Grant Nr. K-135546 and 
K-143542.



181Egedy, T. et al. Hungarian Geographical Bulletin 73 (2024) (2) 165–184.

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