Where Is the Best Place to Live in the European Union? A Synthetic Assessment of External Residential Environmental Quality from a Sustainability Perspective by Degree of Urbanisation

Abstract

The contemporary approach to assessing the housing conditions of households requires taking into account not only the physical characteristics of dwellings but also the quality of their surroundings. From a sustainability perspective, the quality of the external residential environment constitutes a key dimension of sustainable living conditions, closely linked to environmental well-being, spatial equity, and the objectives of sustainable urban and territorial development in the European Union (EU). Despite the growing awareness of the importance of the living environment for residents’ well-being, this issue remains insufficiently represented in analyses addressing the territorial variations in household housing conditions in the EU countries. The scientific literature reveals a lack of comprehensive comparative studies that would link subjective assessments of external residential environmental quality with the level of urbanisation, enabling a more complete evaluation of the living environment and its spatial variability. The aim of the study was therefore to assess the perceived external residential environmental quality of households in EU countries, taking into account the level of urbanisation—differences between urban, town, and rural areas. The study aimed to test the hypothesis that “The external residential environmental quality in EU countries significantly varies depending on the level of urbanisation and regional affiliation, with the highest quality observed in rural areas, particularly in Western European countries.” The study was conducted based on data from the Eurostat database, which were processed using descriptive statistics, inferential statistics, and taxonomic methods. The results of the study confirmed that the external residential environmental quality of households in EU countries significantly differs depending on the level of urbanisation and regional affiliation. The highest level of residential environment quality for households is observed in rural areas of Northern and Eastern European countries. The greatest challenges occur in large cities, particularly in Western Europe, indicating the need to intensify efforts to improve the quality of the living environment in these areas.

1. Introduction

Housing conditions constitute one of the key factors shaping the standard of living and social well-being [1,2,3,4,5,6,7] and, as such, represent an important indicator of the socio-economic development of contemporary European societies. Their importance has been emphasised repeatedly both in international legal and policy documents, such as the Universal Declaration of Human Rights [8], the International Covenant on Economic, Social and Cultural Rights [9], the European Social Charter (as amended, 1996) [10], the Declaration on Social Progress and Development [11], and the Habitat II Conference Declaration in Istanbul [12], as well as in the scientific literature [13,14,15,16,17].

Housing, as a fundamental component of the material sphere of human life, satisfies basic subsistence needs by providing shelter, security, and conditions for rest. At the same time, it enables the fulfilment of psychosocial needs, related, among other things, to building relationships, a sense of stability, and personal development [17,18]. In recent years, increasing attention has been paid to deficits in housing conditions, which not only reduce quality of life but can also negatively affect health, education, employment opportunities, and social integration [15,19,20,21,22]. This issue became particularly visible during the COVID-19 pandemic, when mobility restrictions and the need for home isolation revealed the scale and consequences of housing deficits in Europe [22,23]. During this period, housing took on a multifunctional character—becoming simultaneously a space for private life, work, study, recreation, and physical activity—which highlighted the importance of the quality of both the dwelling itself and its immediate surroundings.

In the context of sustainable development, housing and its surrounding environment are increasingly recognised as fundamental components of sustainable living conditions. The quality of the external residential environment is closely linked to the objectives of sustainable cities and communities, as well as to broader goals related to environmental protection, social inclusion, and territorial cohesion within the European Union [24].

In this context, the literature increasingly focuses not only on the physical characteristics of the dwellings themselves but also on the conditions prevailing in their immediate residential surroundings. These factors affect residents’ quality of life, physical and mental well-being, as well as their subjective perception of housing conditions. This concept encompasses environmental, social, and functional factors. In the literature, key elements of the residential environment are identified as including noise levels, the presence of pollution and waste, the availability of green spaces, safety, the quality of public spaces, and access to essential services (such as transport, education, health) [14,17]. While the residential environment is a broad and multidimensional concept, this study focuses on a specific subset of its external and disturbance-related dimensions, namely perceived noise, environmental pollution, and crime, as reported by households. The measurement of residential environment quality can be both objective (e.g., based on statistical data or environmental measurements) and subjective (e.g., based on residents’ opinions and self-reports). From a sustainability perspective, these external residential environmental conditions play a crucial role in shaping long-term well-being, environmental justice, and the resilience of urban and rural settlements.

Despite the growing interest in this issue, the quality of the residential environment in EU countries remains insufficiently explored at the supranational level. Previous studies have primarily focused on nationwide analyses, overlooking internal territorial variations [25,26] or have been limited to case studies conducted in selected countries or regions [17,27,28]. What is lacking, however, are multi-aspect comparative studies that would take into account both residents’ subjective assessments and territorial variation according to the level of urbanisation—an aspect particularly important in the context of addressing spatial inequalities and implementing the EU’s socio-economic cohesion policy.

The significance of the place of residence—understood as the type of area: rural, urban, or intermediate (town)—is becoming increasingly important in the context of the European Union’s efforts to harmonise living conditions and reduce developmental disparities between regions. As previous studies indicate [29,30], the spatial determinants of quality of life result, among other things, from differences in access to services, the condition of housing infrastructure, the wealth level of local communities, and the effectiveness of actions undertaken within public policy and regional support frameworks.

The impact of the level of urbanisation on the quality of the living environment remains insufficiently explored—both from a spatial and a dynamic perspective. Meanwhile, the type of residential area can significantly differentiate the living conditions of households. Filling this knowledge gap is crucial for more effective design of housing, social, and regional policies, as well as for achieving the EU’s long-term objectives in terms of sustainable development, territorial equality, and social cohesion.

In response to the identified research gaps and the growing importance of sustainability-oriented spatial policies in the EU, the aim of the study was to assess the perceived external residential environmental quality of households in EU countries, taking into account the level of urbanisation—differences between urban, town, and rural areas. The study aimed to test the hypothesis that “The external residential environmental quality in EU countries significantly varies depending on the level of urbanisation and regional affiliation, with the highest quality observed in rural areas, particularly in Western European countries.”

The following research questions were posed as part of the analysis:

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Do factors that reduce the quality of the external residential environment for households (such as noise, air pollution, and crime) vary significantly depending on the level of urbanisation and regional affiliation in the EU?

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What is the level, 2014–2023 change, and spatial variation in the synthetic indicator of perceived external residential environmental quality of households in EU countries, broken down by level of urbanisation and regional affiliation? Do the results confirm the predominance of Western Europe in this regard?

2. External Residential Environmental Quality as a Component of Household Living Conditions: Theoretical Framework

Meeting basic human needs forms the foundation of sustainable social development, among which housing needs occupy a particularly important place [31,32,33,34]. Access to housing of an adequate standard is one of the key household needs, influencing quality of life, health, opportunities for social participation, and the overall well-being of the population [35,36,37,38]. Housing enables the fulfilment of basic physiological needs (such as sleep, food, and protection from weather conditions), provides a sense of security, and creates conditions for meeting higher-order needs—belonging, recognition, and self-actualisation [39,40].

“Residential environment quality” constitutes a key component of household living conditions and plays a significant role in shaping the well-being of individuals and local communities. In economic literature and interdisciplinary studies at the intersection of urban planning, social sciences, and public health, this concept is gaining importance as an integral element of spatial and social capital, influencing not only residents’ everyday experiences but also the socio-economic development of regions. In this study, particular attention is given to external residential environmental quality, understood as conditions prevailing in the immediate surroundings of the dwelling and experienced by households in their daily functioning. While the concept of residential environment quality is discussed here in a broad theoretical sense, the empirical part of this study focuses specifically on external residential environmental quality, operationalised through selected perceived environmental disturbances.

In this context, it is worth referring to Sen’s [41] concept of well-being, which holds that quality of life should not be assessed solely on the basis of income levels but through the lens of an individual’s real capabilities to lead a life they value. According to this approach, residential environment quality should be considered a condition that enables the fulfilment of higher-order needs—such as safety, social participation, personal development, and psychological well-being.

The empirical and theoretical significance of residential environment quality is confirmed by numerous studies. Van Kamp et al. [42] indicate that the quality of the environment—both in its physical aspect (e.g., infrastructure, pollution, access to green spaces) and social aspect (e.g., safety, community cohesion)—is one of the most important determinants of perceived quality of life and health. In a similar vein, Pacione [43] distinguishes two approaches to residential environment quality: an objective one, based on environmental data, and a subjective one, based on residents’ own assessments.

In urban planning and sociological approaches, residential environment quality is defined in a multidimensional way—encompassing both the physical characteristics of the space and social factors. Bonaiuto et al. [44] and Marans and Rodgers [45] indicate that both groups of indicators complement each other and influence the overall perception of the residential space. Sirgy et al. [46], in turn, emphasise that the subjective perception of residential environment quality is of significant importance for residents’ well-being and sense of local identity.

In economic literature, residential environment quality is increasingly regarded as a component of spatial capital [47,48]. It influences property values, migration decisions, and locational attractiveness, and thus—local economic development. In well-being models [41,49], residential environment quality affects the level of utility and the real capabilities of individuals, including educational, occupational, and social opportunities. Albouya’s [50] research further indicates that environment quality translates into the long-term productivity of human capital.

From a regional perspective, residential environment quality becomes a locational factor, attracting highly skilled personnel and investments. In this way, it supports the growth of social capital and regional innovativeness. Over the long term, this quality also affects territorial cohesion, counteracting marginalisation and depopulation of peripheral areas [47,48].

Empirical studies in EU countries [14,17] indicate that residential environment quality is highly spatially differentiated—both in terms of the level of urbanisation and regional conditions. The COVID-19 pandemic clearly highlighted the crucial role of the residential environment in situations of restricted mobility. As demonstrated by Ayala et al. [23] and Hick et al. [22], during lockdowns it was the immediate residential environment that determined opportunities for learning, remote work, and recreation. Although this study focuses on EU countries, it is worth noting that the issue of residential environment quality is also the subject of analyses in non-European countries. In the United States, Ellen & Turner [51] demonstrated a strong influence of neighbourhood conditions on social mobility and the long-term educational opportunities of children in cities with high levels of spatial segregation. In Canada, Fuller-Thomson et al. [52] indicated that the deterioration of the residential environment (particularly in the context of spatial poverty and service accessibility) is strongly correlated with the occurrence of mental and social problems.

In the international literature, residential environment quality is also analysed in the context of two important theoretical strands: the concept of neighbourhood effects and the environmental justice approach. The first emphasises that neighbourhood characteristics—such as crime levels, social cohesion, the quality of public services, and infrastructure—exert a long-term impact on residents’ health, educational attainment, social mobility, and well-being, regardless of their individual socio-economic characteristics [53,54,55]. In this perspective, the residential environment is treated as an independent factor shaping individuals’ life trajectories, with negative effects accumulating in areas of lower environmental quality and higher spatial segregation.

The second important strand is the concept of environmental justice, which draws attention to the unequal distribution of environmental burdens—such as air pollution, noise, or lack of green spaces—among different social and spatial groups. Researchers in this field point out that communities with lower material status and ethnic minorities more often reside in areas of poorer environmental quality, which affects their health, well-being, and development opportunities [56,57,58]. In this context, residential environment quality is not only an element of living conditions but also a matter of environmental and territorial justice. Both strands—neighbourhood effects and environmental justice—emphasise the importance of analysing the spatial variation in residential environment quality and highlight the need for comparative studies that take into account different area types, levels of urbanisation, and regional contexts, providing the theoretical justification for the analyses conducted in this study.

From a public health perspective, residential environment quality is therefore directly linked to residents’ physical and mental well-being. Van Kamp et al. [42] indicate that factors such as noise, air pollution, safety, and access to green spaces significantly affect stress levels, the incidence of cardiovascular diseases, and mental disorders. In recent years, the Anglo-Saxon literature has intensively developed this thread, particularly in the context of urbanisation and environmental health [43,44]. The subjective perception of these hazards often differs between urban, suburban, and rural areas, as confirmed by both quantitative and qualitative studies [22,23].

Despite the declared preference for living in a safe and green environment, residents’ actual location choices are strongly influenced by structural factors such as income, workplace location, and the availability of housing resources. Shucksmith [59] points out that spatial differences in residential environment quality reflect deeper social and economic inequalities.

It is worth noting that households’ ecological behaviours (e.g., using public transport, giving up car ownership) are often not the result of a conscious choice but rather the outcome of economic constraints [60,61]. At the same time, growing environmental awareness can lead to deliberate reductions in living space, which positively affects residential environment quality [62].

In summary, residential environment quality should be recognised as a key element in contemporary assessments of household living conditions. In the context of urbanisation, climate change, and growing regional inequalities, its importance extends beyond the housing sector, becoming a significant dimension of social, health, and regional policy. Integrating external residential environmental quality indicators into spatial analyses and public strategies can support residents’ well-being and territorial sustainable development. This theoretical perspective provides the foundation for the empirical analysis conducted in this study, which focuses on selected perceived environmental disturbances in households’ immediate residential surroundings and their differentiation by degree of urbanisation and regional context.

3. Research Materials and Methods

The study covered all EU member states as of 2023, excluding Malta (due to the lack of empirical data by level of urbanisation), i.e., a total of 26 countries. The assessment focused on the external residential environmental quality of households, taking into account the degree of urbanisation of the area of residence. Three categories of settlement were distinguished in accordance with the DEGURBA (Degree of Urbanisation) classification [63]:

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cities—densely populated areas where at least 50% of the population resides in an urban centre,

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towns and suburbs (towns)—areas of medium population density where at least 50% of the population lives in urban clusters but which are not classified as cities,

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rural areas—sparsely populated areas where more than 50% of the population lives in the countryside.

The variable degree of urbanisation (DB100) was defined according to the DEGURBA (Degree of Urbanisation) methodology, ensuring data comparability between EU member states.

The time frame of the study covered the years 2014 and 2023. The selection of these two time points was intentional and aimed at capturing long-term changes in the level of perceived external residential environmental quality, rather than short-term fluctuations. The use of distant benchmark years allows for a general assessment of change over a longer period, reducing the influence of temporary shocks and exceptional circumstances—such as the COVID-19 pandemic—that could significantly affect households’ year-to-year perceptions of their residential surroundings.

The source data came from the Eurostat database [64]. All indicators of external residential environmental quality used in the analysis are derived from the EU-SILC survey (European Union Statistics on Income and Living Conditions), which is Eurostat’s primary source of survey data on living conditions. Importantly, the indicators reflect households’ subjective assessments of selected environmental and social disturbances in their immediate external residential surroundings. Because the indicators are self-reported, cross-country differences may partly reflect variation in reporting behaviour, cultural norms, and tolerance thresholds (e.g., what respondents consider ‘noise annoyance’ or ‘safety problems’). Therefore, the results should be interpreted as differences in perceived residential disturbances rather than as strictly objective environmental conditions

The study was conducted in two stages, as presented in Figure 1. The first involved a unidimensional analysis of three partial indicators representing perceived external residential environmental disturbances, expressed as the percentage of households reporting specific problems in their place of residence: noise from neighbours or from the street (%) (x₁), pollution, grime or other environmental problems (%) (x₂) and crime, violence or vandalism in the area (%) (x₃).

Unit of analysis and interpretation. The indicators used in this study are derived from Eurostat/EU-SILC and are reported as country-level percentages by degree of urbanisation. Hence, the unit of analysis in the inferential comparisons is the country (and, in stratified comparisons, the country × degree-of-urbanisation cell), while the measured phenomenon refers to households (expressed as percentages). The applied non-parametric tests (Kruskal–Wallis and post hoc Mann–Whitney with Bonferroni correction) are used as exploratory tools to summarise cross-country differences between macroregions and settlement types; results should not be interpreted as household-level causal inference.

These analyses were carried out for the overall sample as well as separately for cities, towns and suburbs, and rural areas, using country-level percentages of households reported for each settlement category in EU countries. At this stage of the study, descriptive statistical methods (measures of central tendency, variability, and change dynamics) and non-parametric tests were used, including the Kruskal–Wallis test (for more than two groups) and post hoc Mann–Whitney tests with Bonferroni correction, employed to identify significant differences between groups. The data were compared across the following dimensions: by European regions (Western, Southern, Eastern, Northern) and by level of urbanisation (cities, towns and suburbs, rural areas). The following division into macroregions was adopted: Western Europe included Belgium, France, Germany, the Netherlands, Austria, and Luxembourg (n = 6); Southern Europe—Italy, Spain, Greece, Portugal, and Cyprus (n = 5); Eastern Europe—Poland, the Czech Republic, Slovakia, Hungary, Romania, Bulgaria, Lithuania, Latvia, Croatia, and Slovenia (n = 10); and Northern Europe—Sweden, Finland, Denmark, Estonia and Ireland (n = 5).

The second stage of the study involved a synthetic assessment of external residential environmental quality by degree of urbanisation in EU countries, using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) [14,17,65,66]. The values of the synthetic indicator of external residential environmental quality for urban, town and suburbs, and rural households in EU countries were estimated for 2014 and 2023, enabling a multi-aspect assessment of the level, dynamics of change, and spatial variation in the phenomenon within the EU. The units of analysis in this study were so-called “object-years” (cross-sectional-time units), totalling 156 (i.e., 26 countries × 3 levels of urbanisation × 2 years).

The construction of the synthetic indicator followed six sequential steps (

Table 1. Stages of constructing the synthetic indicator and identifying typological classes of external residential environmental quality in EU countries.

Specification		Details and Calculation Formulas
Step 1	Selection of simple features for the study	Criteria for feature selection: data availability (by degree of urbanisation), substantive criteria, and statistical criteria
Step 2	Normalisation of simple feature values	for destimulants: $z_{ik}={\displaystyle \frac{\mathit{max}\left\{x_{ik}\right\}-x_{ik}}{\mathit{max}\left\{x_{ik}\right\}-\mathit{min}\left\{x_{ik}\right\}}}$
		where: $x_{ik}$—value of the k-th feature in the i-th object, $min\left\{x_{ik}\right\}$—minimum value of the k-th feature, $max\left\{x_{ik}\right\}$—maximum value of the k-th feature.
Step 3	Determination of the coordinates of model objects—the development pattern and anti-pattern	$A^{+}=(\underset{i}{max}(z_{i1}),\hspace{0.33em}\underset{i}{max}(z_{i2}),\dots ,\underset{i}{max}(z_{ik}))=(z_1^{+},\hspace{0.33em}{z}_2^{+},\dots ,z_k^{+}),$ $A^{-}=(\underset{i}{min}(z_{i1}),\hspace{0.33em}\underset{i}{min}(z_{i2}),\dots ,\underset{i}{min}(z_{ik}))=(z_1^{-},\hspace{0.33em}{z}_2^{-},\dots ,z_k^{-})$.
Step 4	Calculation of the distance of each object (country) from the development pattern and anti-pattern using the Euclidean distance	$d_i^{+}=\sqrt{{\sum }_{k=1}^K(z_{ik}-z_k^{+}{)}^2}$, $d_i^{-}=\sqrt{{\sum }_{k=1}^K(z_{ik}-z_k^{-}{)}^2}$
Step 5	Calculation of the synthetic measure using the TOPSIS method	$q_i={\displaystyle \frac{d_i^{-}}{d_i^{-}+d_i^{+}}}$
Step 6	Identification of typological classes using a statistical approach (based on the mean and standard deviation of the synthetic measure values)	class I (high level): $q_i\ge \overline{q}+s_q$ class II (medium high level): $\overline{\mathrm{q}}+{\mathrm{s}}_{\mathrm{q}}>{\mathrm{q}}_{\mathrm{i}}\ge \overline{\mathrm{q}}$ class III (medium low level): $\overline{q}>q_i\ge \overline{q}-s_q$ class IV (low level): $q_i<\overline{q}-s_q$

Source: Own elaboration based on Wysocki [66].

). In the first step, indicators (so-called simple features) describing perceived external residential environmental perceived quality in EU countries were selected. In their selection, substantive and statistical criteria were applied, and data availability (by level of urbanisation) was taken into account. For the construction of the synthetic indicator, three indicators were considered, namely: noise from neighbours or the street (% of population), pollution, grime, or other environmental problems (%), and crime, violence, or vandalism in the area (%). All indicators were treated as destimulants, as higher values indicate a lower level of external residential environmental quality.

All three indicators were assigned equal weights in the aggregation process. This assumption reflects the absence of strong theoretical or empirical premises for prioritising any single dimension of perceived external residential environmental quality across countries and settlement types. Equal weighting allows for a neutral and transparent comparison and avoids introducing normative assumptions regarding the relative importance of specific environmental disturbances.

In the second step, a zero-unitarisation procedure was applied to normalise the values of the examined simple features, transforming all variables into a uniform [0, 1] range and ensuring their comparability. This procedure is particularly appropriate for destimulant variables and for distance-based methods such as TOPSIS, as it preserves relative differences between objects and ensures a consistent directional interpretation of the indicators. In the third step, the coordinates of the model objects—the pattern and the antipattern—were determined based on the maximum and minimum normalised values of the simple features, respectively. These coordinates were then used to calculate the Euclidean distances of the assessed objects from the pattern and antipattern of development (step IV). The procedure for normalising the values of the simple features, as well as the process of determining the coordinates of the model objects (pattern and antipattern of development), was carried out jointly for the 2014 and 2023 data (so-called object-years) to ensure the comparability of the obtained results across the analysed years and to indicate the developmental trend of the complex phenomenon under study.

In the final, fifth step, the values of the synthetic indicator (q_i) of external residential environmental quality for urban, town and suburbs, and rural areas in EU countries were calculated using the TOPSIS method. The obtained indicator values were used to develop a ranking of countries and their typological classification based on external residential environmental quality (Table 1).

4. Results

4.1. Noise, Pollution, and Crime in the Residential Environment of Households in EU Countries—Spatial Analysis by Level of Urbanisation

Social hazards—such as crime, vandalism, and violence—directly affect the sense of security, social relationships, and property values. At the territorial level, clear differences are observed in the perceived intensity of these burdens between urban areas, towns and suburbs, and rural areas [22,23].

Noise—whether originating from neighbours, streets, traffic, or commercial activities—remains one of the most significant factors reducing quality of life in urbanised environments. As numerous studies indicate [67,68], prolonged exposure to noise can lead to serious health consequences, including sleep disturbances, chronic stress, and an increased risk of cardiovascular diseases. From a BoD (burden of disease) perspective, traffic noise is considered one of the most significant environmental health hazards in Europe [69,70].

The conducted studies confirmed strong links between noise levels and the degree of urbanisation. In 2023, the highest share of households experiencing noise-related nuisances was recorded in cities (an average of 21.5% in the EU excluding Malta), compared to 15.7% in towns and 10.5% in rural areas. Compared to 2014, the values in cities remained practically unchanged, whereas small declines were observed in towns and rural areas, which may indicate the effects of infrastructure modernization and improvements in the quality of public spaces (

Table 2. Descriptive statistics of perceived noise from neighbours or from the street among households by degree of urbanisation in EU countries, 2014 and 2023 (%).

Specification	2014				2023
	Cities	Towns and Suburbs	Rural Areas	Overall	Cities	Towns and Suburbs	Rural Areas	Overall
Min	12.9	8.4	4.9	8.9	8.5	6.9	3.7	6.7
Q1	17.4	13.2	8.7	13.2	13.0	8.9	7.0	10.1
Median	20.2	14.9	10.4	15.6	20.5	14.3	10.1	14.9
Average	22.0	16.0	10.7	16.3	21.5	15.7	10.5	16.4
Q3	27.9	20.9	12.1	19.1	29.7	21.5	13.9	21.7
Max	33.8	26.2	17.2	25.9	42.4	32.5	19.8	30.2
Range	20.9	17.8	12.3	17.0	33.9	25.6	16.1	23.5

Source: Own calculations based on data from Eurostat [64].

).

The spatial variation in the phenomenon under study is very pronounced. In 2023, the highest levels of noise reported by households in cities were in Luxembourg (42.4%), the Netherlands (33.7%), Portugal (32.4%), and Greece (32.0%), with Luxembourg recording an increase of as much as 14.4 percentage points compared to 2014. The largest declines occurred in Italy, Poland, and Hungary—which may be the result of infrastructure modernisation and improvements in urban conditions. In towns and suburbs, the highest levels of the phenomenon were recorded in Luxembourg (32.5%), Portugal (29.6%), Germany (23.9%), and Greece (22.7%). At the same time, the largest declines occurred in Bulgaria, Lithuania, Poland, and Hungary, which may indicate improvements in public space quality and infrastructure in smaller urban centres.

In rural areas, noise remains the least burdensome; however, the data show that this is not a uniform phenomenon. In 2023, the lowest values of the indicator were recorded in Greece (3.7%), Bulgaria (4.1%), and Croatia (5.9%). Conversely, the highest values were recorded in Portugal (19.8%), Luxembourg (19.6%), and Germany (16.8%), where rural indicator values were noticeably above the EU average. Although rural areas are often perceived as spaces of quiet and tranquility, these data indicate that some rural areas—particularly in Western Europe—may experience an increase in environmental noise levels. This may be related to the process of suburbanisation, i.e., the spread of cities into peripheral areas, leading to increased development, higher traffic volumes, and the expansion of transport infrastructure [71,72]. High noise indicators may therefore result from increased urbanisation pressure in suburban areas and insufficient spatial planning, particularly regarding acoustic insulation and the location of major roads [73].

As Shucksmith [59] indicates, environmental problems in rural areas are increasingly the result of interactions between local conditions and broader metropolitan processes, including suburbanisation and increased commuting. In turn, Haarstad et al. [60] emphasise that a lack of coordination between spatial and transport planning can exacerbate environmental impacts, including noise, particularly on the outskirts of urban agglomerations.

From a national perspective, the data reveal a very strong urban–rural gradient in households’ perception of noise in their place of residence. In 2023, the largest differences between cities and rural areas were recorded, among others, in Greece (32.0% of households reporting noise in cities versus 3.7% in rural areas, a difference of 28 percentage points), Luxembourg (42.4% vs. 19.6%), as well as in the Netherlands, France, Germany, Portugal, and Romania (where the gap exceeded 12–15 percentage points). This indicates a strong concentration of noise-related nuisances in the major urban centres of these countries. Conversely, relatively small differences between urban and rural areas occur in Ireland, Sweden, Croatia, Hungary, Estonia, and Slovakia, where the gaps do not exceed a few percentage points. In some Central and Eastern European countries (e.g., Poland, Lithuania, Bulgaria, Hungary), the urban–rural gradient weakened noticeably over the studied years, whereas in others (Greece, Luxembourg, Spain, Finland) it deepened significantly. This indicates that the issue of noise has not only an international dimension but also a strong intranational dimension, closely linked to settlement structure and spatial policy in individual countries.

In addition to the differences between cities, towns, and rural areas within individual countries, it is also important to determine whether the observed patterns form broader regularities at the level of European macroregions in cross-country comparisons. Using country-level percentages for 2023 as the unit of analysis, the Kruskal–Wallis test indicated heterogeneity across macroregions in reported noise nuisances in cities (H = 12.08; p = 0.007), with the highest medians observed in Western Europe (30.0%) and Southern Europe (27.3%). Post hoc Mann–Whitney tests with Bonferroni correction (α = 0.0083) identified only one significant pairwise contrast: higher noise nuisance levels in Western Europe compared with Eastern Europe (p = 0.006). All other regional comparisons were non-significant after correction (Figure 2 and the last table in Section 4.1).

Similar conclusions were observed for towns and suburbs, where the Kruskal–Wallis test was significant (H = 11.64; p = 0.009), but none of the post hoc comparisons remained significant after correction. For rural areas, the Kruskal–Wallis test also reached significance (H = 7.90; p = 0.048), yet the pairwise comparisons did not reveal significant differences after correction. These results should be interpreted as exploratory cross-country comparisons rather than as strong population-level inference, given the limited number of countries and potential interdependence among EU Member States.

The study results indicate that settlement structure and regional affiliation influence the reported level of noise nuisances, with the largest differences observed in cities. In the case of towns and rural areas, the differences are less pronounced and may be explained, among other factors, by varying levels of suburbanisation, infrastructure development, and spatial planning policies.

In the analysis of perceived environmental problems, such as air pollution, grime, or other ecological nuisances, significant spatial differences and favourable changes over time were observed. In 2023, compared to 2014, the level of reported environmental discomfort among households decreased in cities, towns, and rural areas in most EU member states. The highest values were observed among city residents, where in 2023 the average level of nuisance was 15% (down from 18.6% in 2014), while in towns and suburbs it decreased from 12.8% to 9.8%, and in rural areas from 8.6% to 7.1%. These data confirm that less urbanised areas are characterised by relatively more favourable environmental conditions, as assessed by households (

Table 3. Descriptive statistics for perceived pollution, grime, or other environmental problems among households in EU countries by degree of urbanisation, 2014 and 2023 (%).

Specification	2014				2023
	Cities	Towns and Suburbs	Rural Areas	Overall	Cities	Towns and Suburbs	Rural Areas	Overall
Min	7.1	2.8	3.2	4.5	6.2	3.6	2.7	4.2
Q1	13.8	8.9	6.1	10.1	10.5	7.0	4.9	7.8
Median	17.2	13.1	8.9	13.7	13.5	9.1	6.9	10.6
Average	18.6	12.8	8.6	13.4	15.0	9.8	7.1	11.0
Q3	21.7	16.5	10.9	15.8	17.6	14.5	9.1	14.8
Max	36.3	24.9	17.6	23.2	35.3	17.1	12.3	20.5
Range	29.2	22.1	14.4	18.7	29.1	13.5	9.6	16.3

Source: Own calculations based on data from Eurostat [64].

).

In cities, the level of environmental nuisances, such as air pollution, grime, or other negative environmental factors, averaged 15% in 2023, representing a decline from 18.6% in 2014. In 2023, the highest values were reported by households in Malta (42.9%), Greece (35.3%), and Germany (22.3%). The lowest values, in turn, were recorded in Sweden (6.2%), Slovakia (7.6%), and Estonia (8.1%). Compared to 2014, the situation improved in many countries, for example in Italy (decline from 25.9% to 14.2%), Poland (from 17% to 11.8%), and Belgium (from 27.5% to 24.1%). In some countries, however, an increase was observed—particularly pronounced in Malta (from 39.8% to 42.9%) and Finland (from 10.6% to 13.3%). These changes may result from infrastructure development, environmental initiatives, and urban policies aimed at combating pollution.

In towns and suburbs, households reported an average level of environmental nuisance of 9.8% in 2023, down from 12.8% in 2014. In 2023, the most significant environmental problems in this category were reported by households in Malta (28.1%), Slovenia (17.1%), and Portugal (15.4%). The lowest values, in turn, were recorded in Croatia (3.6%), Bulgaria (8.4%), and the Czech Republic (7.1%). Compared to 2014, declines were particularly pronounced in Eastern European countries—for example, in Lithuania (from 17.3% to 9.2%) and Romania (from 18% to 8.9%). In turn, increases occurred, among others, in Ireland (from 2.8% to 9.5%) and Estonia (from 11.5% to 12.2%), which may result from changing perceptions of environmental perceived quality or heightened environmental awareness.

In rural areas, the average level of environmental nuisance was the lowest, at 7.1% in 2023, representing an improvement compared to 2014, when the average was 8.6%. In 2023, the highest indicator values were recorded in Slovenia (12.3%), Portugal (10.7%), and Finland (6.4%). The lowest values were observed in Croatia (2.7%), Greece (2.8%), and Sweden (3.4%). Compared to 2014, the most notable improvements were observed in Greece (from 9.1% to 2.8%), Bulgaria (from 9.7% to 5.2%), and Italy (from 6.5% to 4.7%). However, increases occurred in a few countries, for example in Finland (from 6.1% to 6.4%) and Denmark (from 3.2% to 6.3%). Overall, the data indicate relatively high environmental quality in rural areas, which may result from lower traffic intensity, lower population density, and a higher proportion of green spaces.

In the case of the indicator reflecting pollution, grime, or other environmental problems in the place of residence, a clear intranational urban–rural gradient is also evident. In 2023, the largest differences between cities and rural areas were recorded, among others, in Greece, Belgium, France, Germany, and Latvia, where the share of households reporting environmental problems in cities exceeded rural values by several percentage points, and in Greece by more than 30 percentage points. This indicates a strong concentration of environmental nuisances in the major urban centres of these countries. Conversely, relatively small urban–rural differences occur in the Nordic countries and in some Central and Eastern European countries (e.g., Denmark, Estonia, Croatia, Slovakia, Sweden, Austria), where the gaps are limited to a few percentage points. In many Central and Eastern European countries (e.g., Bulgaria, the Czech Republic, Lithuania, Poland, Romania, Slovakia), in 2023 compared to 2014, the indicator values declined simultaneously in both cities and rural areas, suggesting a gradual improvement in environmental quality and a partial reduction in intranational territorial disparities.

To deepen the analysis, statistical tests (Kruskal–Wallis test) were conducted to compare differences in country-level percentages across the four EU regions—Western, Southern, Eastern, and Northern Europe—separately for cities, towns, and rural areas. In cities, the Kruskal–Wallis test revealed differences close to conventional significance (H = 7.42; p = 0.0597). Descriptively, the median country-level shares tended to be higher in Western and Southern Europe than in Eastern and Northern Europe, which may be associated with higher population density, greater traffic pressure and more intensive use of urban space. For towns and suburbs, regional differences were not significant (H = 2.52; p = 0.4725), suggesting broadly similar distributions of the indicator across macroregions in this settlement category. For rural areas, no significant regional differences were found either (H = 2.52; p = 0.4712). Although the average values were higher in Western Europe, the between-region variation was not sufficient to be detected by the test. Overall, these findings point to relatively limited macroregional differentiation in this indicator outside large cities and should be interpreted as exploratory cross-country comparisons, consistent with previous evidence [22,44] (Figure 3 and last table in Section 4.1).

From a causal perspective, households’ perception of environmental problems depends not only on the actual state of the environment but also on its socio-economic context—such as the availability of municipal services, quality of spatial management, and individual sensitivity to ecological issues [42,43]. A reduction in nuisances may indicate the effectiveness of environmental policies and infrastructure investments, as well as an increase in civic awareness and social environmental responsibility.

Social problems in the residential environment, such as crime, vandalism, or violence, are a significant factor affecting residents’ quality of life and their subjective sense of security. Although crime indicators have an objective dimension, their perception is often shaped by social, spatial, and institutional factors, such as neighbourhood cohesion, the effectiveness of law enforcement, the level of social control, and the quality of public spaces. According to social disorganisation theory [74], crime is higher in environments characterised by poverty, population mobility, and a lack of stable social ties. These observations were further developed by Sampson and Groves [75], who emphasise the importance of so-called collective efficacy—the ability of a local community to act together toward common goals and address local problems, such as safety. In this context, urbanisation and population density can indirectly influence the perceived level of threat—through weakened local social control, greater anonymity, and increased social tensions. In contrast, in more cohesive communities (often in rural areas), lower levels of anonymity and greater social engagement can reduce both actual crime and its subjective perception.

Across the entire EU-27 (excluding Malta), crime, violence, or vandalism in the residential environment was most frequently reported by households living in cities—averaging 13.1% of households in 2023. Next were towns (6.9%) and rural areas (5.0%). This indicates that the level of urbanisation significantly affects the perceived level of threat—the larger the settlement, the more frequent the reports of social nuisances. This variation may result from a number of factors: greater anonymity in cities, weakened neighbourhood ties, higher population density, and a more complex socio-economic structure [74]. In rural areas, social control, neighbourhood vigilance, and mutual relationships are stronger, which may contribute both to lower levels of crime and to its reduced perception. Compared to 2014, however, a significant decline in the share of reported social nuisances is evident across all types of settlements. In cities, this indicator was 17.9% at that time, representing a decline of 4.9 percentage points. In towns and suburbs, the decrease was 5 percentage points (from 11.9% to 6.9%), and in rural areas 2.8 percentage points (from 7.7% to 5.0%) (

Table 4. Descriptive statistics for perceived crime, violence, or vandalism among households in EU countries by degree of urbanisation, 2014 and 2023 (%).

Specification	2014				2023
	Cities	Towns and Suburbs	Rural Areas	Overall	Cities	Towns and Suburbs	Rural Areas	Overall
Min	6.3	1.4	1.0	2.5	2.6	1.4	0.4	1.4
Q1	14.0	9.0	5.3	9.9	6.8	4.2	2.4	5.8
Median	17.5	11.3	7.5	12.7	11.3	6.5	4.1	7.0
Average	17.9	11.9	7.7	12.6	13.1	6.9	5.0	8.6
Q3	22.4	13.9	9.7	15.5	17.7	10.1	6.6	11.7
Max	33.4	25.8	19.9	26.8	26.9	16.7	16.4	20.9
Range	27.1	24.4	18.9	24.3	24.3	15.3	16.0	19.5

Source: Own calculations based on data from Eurostat [64].

). These data may indicate a general improvement in the subjective sense of security in EU countries, possibly resulting from the modernisation of public spaces, increased investment in social infrastructure, and enhanced effectiveness of law enforcement services.

In cities, the highest shares of households reporting crime, vandalism, or violence in 2023 were recorded in Greece (26.9%), France (23%), and Belgium (23%), indicating significant social problems in the major urban centres of these countries. Values above the EU average (13.1%) were also observed in the Netherlands (21.6%), Spain (16.6%), and Ireland (11.3%). Conversely, the lowest levels of reported crime were recorded by households living in Croatia (2.6%), Poland (6.1%), Slovakia (6%), and Romania (6.8%), which may indicate a higher subjective sense of security in the urban areas of these countries. In most countries, a decline in reported nuisances was observed. The largest declines occurred in Italy (from 23.6% to 10.6%), Poland (from 12.4% to 6.1%), Hungary (from 16.9% to 5.0%), and Slovakia (from 13.3% to 6.0%). Significant reductions in the perceived level of threat were also observed in Bulgaria and Romania. These changes may result from improvements in the quality of public spaces, enhanced effectiveness of preventive measures, and increased investment in safety and monitoring in cities of Central and Eastern Europe. It is worth noting, however, the increases in perceived threats in some Western European countries. In Greece, the level of reported threat increased by as much as 2.8 percentage points (from 24.1% to 26.9%), and in France by 1.8 percentage points (from 21.2% to 23.0%). These increases may be related to social tensions, migration, peripheral urbanisation, and a growing sense of insecurity in large metropolitan areas [75,76].

In towns and suburbs, the threat of crime, vandalism, or violence in the residential environment was generally lower than in cities but also clearly varied. In 2023, the highest shares of households reporting such nuisances were recorded in Greece (16.7%), France (13.3%), Ireland (11.8%), and Spain (10.9%). Average values were observed in the Netherlands (10.5%), Belgium (8.2%), and Germany (7.3%). The lowest levels of reported crime in the residential environment were recorded by households in Croatia (1.4%), Poland (1.8%), Lithuania (2.5%), and Slovakia (2.9%), which may indicate a relatively high level of perceived security in the smaller urban centres of these countries. Compared to 2014, most countries recorded a decline in the share of households reporting crime threats in towns and suburbs. For example, in Bulgaria the share declined from 25.8% to 11.0%, in Latvia from 11.3% to 3.4%, and in Poland from 5.3% to 1.8%. These declines may indicate an improvement in social conditions and safety in smaller urban centres, possibly resulting from investments in infrastructure, development of local services, and revitalisation efforts. On the other hand, in some countries—such as Greece (increase from 13.8% to 16.7%) and Spain (from 8.4% to 10.9%)—increases were observed. This may be related to intensifying social problems, the effects of economic crises, and migrant concentration in the peripheral districts of towns and suburbs.

In contrast, in rural areas, crime, vandalism, and violence in the residential environment were reported least frequently among all settlement types. This situation may reflect a higher level of social cohesion, stronger neighbourhood ties, and a limited presence of urban-specific threats, such as anonymity, social marginalisation, or high resident turnover. In 2023, the highest shares of households reporting these problems in rural areas were recorded in Greece (16.4%), Portugal (9.7%), and Bulgaria (9.3%). High indicators in these countries may result from persistent socio-economic tensions, less developed local governance structures, and the spillover of urban problems into peripheral areas due to suburbanisation and internal migration. The lowest levels of reported threats in 2023 were recorded by households in rural areas in Croatia (0.4%), Poland (1.0%), Lithuania (1.3%), the Czech Republic (2.6%), and Slovakia (2.6%). Low values may be associated with lower population density, greater transparency in social relationships, and reduced exposure to structural problems typical of urban environments, such as homelessness, drug abuse, or organised crime. Compared to 2014, the vast majority of EU countries recorded a decline in the share of households reporting crime threats in rural areas. The largest declines occurred in Bulgaria (from 19.9% to 9.3%, a decrease of 10.6 percentage points), Poland (from 2.5% to 1.0%), Hungary (from 13.2% to 6.3%), and Romania (from 12.2% to 4.9%). These declines may indicate more effective local policies, improvements in rural infrastructure, and integration efforts that strengthen social capital and reduce sources of conflict. It can also be assumed that, in some cases, the migration of lower-status populations to larger cities or suburban areas may have indirectly contributed to improved safety in rural areas. At the same time, in Greece, in contrast to the overall EU change between 2014 and 2023, the indicator of reported threats increased from 9.5% in 2014 to as much as 16.4% in 2023. This may be the result of intensifying social problems, limited access to public services, and insufficient institutional oversight in peripheral areas.

In the case of the indicator reflecting crime, violence, or vandalism in the residential area, a clear intranational urban–rural gradient also emerges, although its magnitude varies widely between countries. In 2023, the largest differences between cities and rural areas were observed, among others, in Belgium, France, Germany, Austria, the Netherlands, Luxembourg, and Bulgaria, where the share of households reporting threats in cities was about 12–17 percentage points higher than in rural areas. This indicates a clear concentration of social problems and perceived threats in the major urban centres of these countries. A different picture emerges in Central and Eastern European and Nordic countries, such as Croatia, Lithuania, Poland, Slovakia, Denmark, and Sweden, where both the level of reported threats and the urban–rural differences are relatively small. In some countries (e.g., Bulgaria, Romania, Poland, Hungary, Latvia, Estonia), in 2023 compared to 2014, a simultaneous decline in the indicator was recorded across all area types, indicating an improvement in the subjective sense of security and a reduction in intranational territorial disparities. Against this backdrop, Greece and Finland stand out, where the level of reported threats—particularly in cities—increased, and the differences compared to rural areas remained pronounced or even deepened.

In the division into European macro-regions, for cities, the Kruskal–Wallis test indicated significant regional differences (H = 10.90; p = 0.0123). The highest medians of urban crime occurred in Western Europe (23.0%) and Southern Europe (20.6%), which may result from greater migratory pressure, greater social polarisation, and greater urban planning challenges. The lowest medians were recorded in Eastern Europe (6.45%) and Northern Europe (11.30%). These descriptive differences may reflect, among other factors, higher urban density, greater social polarisation, and more complex urban governance and planning challenges in large metropolitan areas. In the case of towns and suburbs and for rural areas, the Kruskal–Wallis tests suggested some heterogeneity (H = 4.84; p = 0.1838 and H = 5.31; p = 0.1505, respectively); however, they were not statistically significant. Nonetheless, the observed variation may be related to differing patterns of suburbanisation, the quality of public space, and the availability of social infrastructure. In accordance with the theory of social disorganisation [74], the higher level of crime and its perception in large urban centres may be a consequence of greater anonymity, more frequent internal migrations, and weaker social control. Sampson and Groves [75] note that the lack of reciprocity and trust in urban communities may lead to the development of criminal behaviours and the devastation of public space (Figure 4 and Table 5).

The results of the study by Bąk and Szczecińska [76] show that the highest level of public safety in the EU in 2023 was recorded in Slovenia, the Czech Republic, and Poland, whereas the lowest—in Latvia, Bulgaria, and Belgium. These differences were correlated with the level of national income, the effectiveness of social policy, and the strength of state institutions. In turn, the study by Hummelsheim et al. [77] showed that the level of citizens’ safety in Western and Southern European countries is clearly linked to the quality of the welfare state—stronger institutions and higher expenditure on social policy contribute to reducing the fear of crime and improving residents’ quality of life. In countries where social inequalities are deeper, urban crime issues are more acutely felt and more frequently reported.

A limitation of this study is that inferential comparisons are based on country-level aggregates (n = 26), and the effective group sizes are further reduced by stratification by degree of urbanisation. Moreover, EU countries may not represent fully independent observations due to shared institutional frameworks, spatial proximity and historical trajectories. Therefore, the reported p-values should be interpreted cautiously and primarily as exploratory evidence of cross-country differences, complemented by descriptive patterns and the synthetic assessment (TOPSIS).

Table 5. Results of the Kruskal–Wallis Test for perceived noise, environmental problems, and crime by degree of urbanisation in European Regions in 2023.

List	Results of the Kruskal–Wallis Test	p-Value
Noise from neighbours or from the street
Cities	12.08	0.007
Towns and suburbs	11.64	0.009
Rural areas	7.90	0.048
Pollution, grime or other environmental problems
Cities	7.42	0.059
Towns and suburbs	2.52	0.473
Rural areas	2.52	0.471
Crime, violence or vandalism in the area
Cities	10.90	0.012
Towns and suburbs	4.84	0.184
Rural areas	5.31	0.151

Source: Own calculations based on data from Eurostat [64].

Table 5. Results of the Kruskal–Wallis Test for perceived noise, environmental problems, and crime by degree of urbanisation in European Regions in 2023.

List	Results of the Kruskal–Wallis Test	p-Value
Noise from neighbours or from the street
Cities	12.08	0.007
Towns and suburbs	11.64	0.009
Rural areas	7.90	0.048
Pollution, grime or other environmental problems
Cities	7.42	0.059
Towns and suburbs	2.52	0.473
Rural areas	2.52	0.471
Crime, violence or vandalism in the area
Cities	10.90	0.012
Towns and suburbs	4.84	0.184
Rural areas	5.31	0.151

Source: Own calculations based on data from Eurostat [64].

4.2. External Residential Environmental Quality of Households in EU Countries by Degree of Urbanisation—A Synthetic Assessment

The external residential environmental quality of households represents a specific and measurable dimension of residential living conditions, reflecting residents’ perceptions of selected environmental and social disturbances in their immediate surroundings. For its measurement and the assessment of spatial differentiation in EU countries by degree of urbanisation, the TOPSIS method was applied. Based on three diagnostic variables—i.e., the percentage of households indicating noise from the surrounding area (x₁), pollution, dirt and other environmental problems (x₂), and crime, vandalism and acts of violence in the neighbourhood (x₃)—synthetic indicator values of external residential environmental quality (q_i) were constructed for EU countries by degree of urbanisation in 2014 and 2023.

The conducted study showed that in 2014 and 2023, the level of external residential environmental quality of households was highest in rural areas, as confirmed by the highest median values of the synthetic indicator—amounting to 0.812 in 2014 and 0.829 in 2023, respectively. In turn, the lowest median values were recorded among cities—0.518 in 2014 and 0.616 in 2023—indicating that urban areas had the lowest average external residential environmental quality across the EU. The lowest level of external residential environmental quality in rural areas was recorded in Portugal (q_i = 0.733 in 2023). It is worth noting that only in eight EU countries was the indicator value for cities higher than this lowest value recorded in rural areas in Portugal. This confirms the relatively better situation regarding external residential environmental quality in rural areas on the EU scale (

Table 6. Typological classification results of level of external residential environmental quality of households in European Union countries by degree of urbanisation in 2014 and 2023.

Specification	Number/ Percentage	Typological Class/Level External Residential Environmental Quality				Overall
		I	II	III	IV
		High	Medium-High	Medium-Low	Low
		qi ≥ 0.858	0.694 ≤ qi ˂ 0.858	0.530 ≤ qi ˂ 0.694	qi < 0.530
2014
Cities	Number	0	3	9	14	26 countries/100%
	%	0.0	11.5	34.6	53.8
Towns and suburbs	Number	1	11	10	4
	%	3.8	42.3	38.5	15.4
Rural areas	Number	6	18	2	0
	%	23.1	69.2	7.7	0.0
2023
Cities	Number	1	7	9	9	26 countries/ 100%
	%	3.8	26.9	34.6	34.6
Towns and suburbs	Number	4	14	8	0
	%	15.4	53.8	30.8	0.0
Rural areas	Number	11	12	13	0
	%	42.3	46.2	11.5	0.0

Source: Own calculations based on data from Eurostat [64].

and

Table 7. Ranking of external residential environmental quality of households in European Union countries by degree of urbanisation in 2014 and 2023 ^{(a) (b)}.

Country	Cities								Towns and Suburbs								Rural Areas
	2014			2023			Change in Ranking Position	Change in Class	2014			2023			Change in Ranking Position	Change in Class	2014			2023			Change in Ranking Position	Change in Class
	qi	Position	Class	qi	Position	Class			qi	Position	Class	qi	Position	Class			qi	Position	Class	qi	Position	Class
Croatia	0.786	52	II	0.894	13	I	39	1	0.922	7	I	0.947	3	I	4	0	0.943	4	I	0.982	1	I	3	0
Poland	0.604	116	III	0.760	64	II	52	1	0.742	69	II	0.904	9	I	60	1	0.896	12	I	0.957	2	I	10	0
Italy	0.374	149	IV	0.686	93	III	56	1	0.619	113	III	0.841	30	II	83	1	0.838	32	II	0.936	5	I	27	−1
Slovakia	0.617	114	III	0.820	37	II	77	1	0.701	88	II	0.925	6	I	82	1	0.824	36	II	0.907	8	I	28	−1
Estonia	0.631	107	III	0.805	45	II	62	1	0.636	104	III	0.832	34	II	70	1	0.840	31	II	0.901	10	I	21	−1
Lithuania	0.625	111	III	0.742	70	II	41	1	0.747	68	II	0.862	22	I	46	1	0.843	27	II	0.899	11	I	16	−1
Czechia	0.525	132	IV	0.638	102	III	30	1	0.653	100	III	0.777	59	II	41	1	0.810	41	II	0.884	15	I	26	−1
Denmark	0.534	129	III	0.630	108	III	21	0	0.827	35	II	0.856	25	II	10	0	0.878	17	I	0.881	16	I	1	0
Sweden	0.628	110	III	0.739	71	II	39	1	0.779	57	II	0.857	24	II	33	0	0.874	19	I	0.868	20	I	−1	0
Ireland	0.711	82	II	0.757	65	II	17	0	0.810	40	II	0.729	77	II	−37	0	0.875	18	I	0.867	21	I	−3	0
Latvia	0.450	141	IV	0.575	123	III	18	1	0.665	98	III	0.763	62	II	36	1	0.708	84	II	0.861	23	I	61	−1
Bulgaria	0.405	147	IV	0.565	124	III	23	1	0.528	131	IV	0.791	50	II	81	2	0.677	95	III	0.846	26	II	69	−1
Belgium	0.284	153	IV	0.416	144	IV	9	0	0.707	86	II	0.785	55	II	31	0	0.709	83	II	0.843	28	II	55	0
Austria	0.442	143	IV	0.601	117	III	26	1	0.695	90	II	0.728	79	II	11	0	0.833	33	II	0.816	38	II	−5	0
Romania	0.365	151	IV	0.564	125	III	26	1	0.514	133	IV	0.729	78	II	55	2	0.692	92	III	0.809	42	II	50	−1
Hungary	0.537	127	III	0.737	73	II	54	1	0.665	99	III	0.734	74	II	25	1	0.721	80	II	0.806	44	II	36	0
France	0.501	137	IV	0.334	152	IV	−15	0	0.695	91	II	0.607	115	III	−24	−1	0.809	43	II	0.804	46	II	−3	0
Spain	0.595	120	III	0.529	130	IV	−10	−1	0.774	60	II	0.671	96	III	−36	−1	0.841	29	II	0.801	47	II	−18	0
Slovenia	0.511	134	IV	0.631	106	III	28	1	0.666	97	III	0.680	94	III	3	0	0.779	58	II	0.791	49	II	9	0
Finland	0.703	87	II	0.507	136	IV	−49	−2	0.796	48	II	0.696	89	II	−41	0	0.890	14	I	0.789	51	II	−37	1
Germany	0.240	155	IV	0.411	145	IV	10	0	0.555	126	III	0.628	109	III	17	0	0.732	76	II	0.782	56	II	20	0
Luxembourg	0.464	140	IV	0.409	146	IV	−6	0	0.444	142	IV	0.597	118	III	24	1	0.708	85	II	0.763	63	II	22	0
Greece	0.247	154	IV	0.187	156	IV	−2	0	0.498	138	IV	0.537	128	III	10	1	0.786	54	II	0.756	66	II	−12	0
Cyprus	0.636	103	III	0.643	101	III	2	0	0.584	122	III	0.786	53	II	69	1	0.769	61	II	0.750	67	II	−6	0
Netherlands	0.371	150	IV	0.392	148	IV	2	0	0.596	119	III	0.633	105	III	14	0	0.711	81	II	0.739	72	II	9	0
Portugal	0.468	139	IV	0.507	135	IV	4	0	0.620	112	III	0.590	121	III	−9	0	0.814	39	II	0.733	75	II	−36	0

^(a) Linear arrangement by non-increasing values of the synthetic indicator of external residential environmental quality (q_i) for households in rural areas in EU countries. ^(b) Typological class: I—high level, II—medium-high, III—medium-low, IV—low level of external residential environmental quality. Source: Own calculations based on data from Eurostat [64].

).

In terms of internal differentiation of the level of external residential environmental quality of households, the greatest variability was observed among urban areas. This is indicated by the highest values of both the classical range and the interquartile range for the synthetic indicator values. In 2023, the range in this group amounted to 0.707—it was almost three times higher than in the case of rural areas (0.266). The highest external residential environmental quality in cities was achieved in Croatia (q_i = 0.894), while the lowest—in Greece (q_i = 0.187) (Figure 5, Table 7).

The analysis of changes in the average value of the synthetic indicator of external residential environmental quality indicates an overall improvement in all three types of areas—urban, town, and rural. In each of these categories, an increase in the average value of the synthetic indicator was observed, which may reflect the combined effects of policies and investments aimed at reducing environmental and social disturbances in residential surroundings. The greatest increase in average values concerned cities, which may be the result of intensified efforts to improve air quality, reduce noise, and increase safety in large agglomerations. The next group were towns and intermediate areas, while the smallest changes were observed in rural areas, which already in 2014 were characterised by a relatively high level of external residential environmental quality. It is worth noting, however, that despite the overall improvement, internal differentiation among cities increased. This is evidenced not only by an increased range but also by a rise in the interquartile range, indicating deepening spatial inequalities in the external residential environment in large urban centres.

In order to deepen the analysis of the external residential environmental quality of households in EU countries by degree of urbanisation, a typological classification was conducted. Based on the synthetic indicator values external residential environmental quality, the surveyed units were arranged in a non-decreasing order. Next, ranks (position among the surveyed units) were assigned to them and a typological classification was conducted, distinguishing classes of units with high, medium-high, medium-low, and low levels of external residential environmental quality (Table 7 and Figure 6):

-

class I (high level of external residential environmental quality of households)—includes units in which the indicator reaches the highest values, which ow level of perceived environmental and social disturbances (noise, pollution, and crime) and a favourable quality of the external residential environment;

-

class II (medium-high level)—denotes moderately favourable external residential environmental conditions, with a limited impact of factors reducing quality of life;

-

class III (medium-low level)—indicates the presence of significant perceived environmental and social problems in the residential surroundings, which may affect the daily functioning of residents;

-

class IV (low level)—includes areas with the lowest indicator values, where the accumulation of unfavourable perceived environmental and social disturbances significantly reduces the perceived quality of the external residential environment.

In 2014, the highest values of the synthetic indicator representing the external residential environmental quality of households were recorded in rural areas. Almost one quarter of them (23.1%) were classified into class I (high level), and the vast majority (69.2%)—into class II (medium-high level). Only two units (7.7%) were classified in class III, while none were placed in class IV (low level), which indicates a relatively favourable living environment in rural areas in the Member States.

In the case of intermediate (town) areas, the distribution of classes was more varied. The largest share of units was located in classes II (medium-high level, 42.3%) and III (medium-low level, 38.5%), while a single case (3.8%) was classified in class I, representing a high level of external residential environmental quality of households (i.e., towns and suburbs in Croatia).

Urban areas, in turn, were characterised by a decidedly less favourable profile—over half of the units (53.8%) were classified in the lowest class IV (low level), and 34.6% in class III (medium-low level). At that time, no country achieved a synthetic indicator value that would allow urban areas to be assigned to class I, representing a high level of external residential environmental quality of households. This finding highlights the relatively less favourable conditions of the external residential environment in large urban centres compared to other types of areas in the EU.

In 2023, in relation to 2014, an improvement in the level of external residential environmental quality of households was recorded in all three area categories in the EU, although these changes varied in scale and pace. In rural areas, there was a significant increase in the number of units classified in class I—to 42.3% (+19.2 pp), which, combined with a decrease in the share of units in class II (–23.0 pp), confirms the strengthening of the position of rural areas as living spaces with the highest level of external residential environmental quality. The absence of cases classified in class IV in both analysed years suggests a lasting and stable qualitative advantage of these areas.

An exception was Finland, where the level of external residential environmental quality of households living in rural areas deteriorated over the analysed period (Table 7). In particular, a significant increase was recorded in the percentage of people complaining about noise from neighbours or from the street—from 8.3% in 2014 to 16.2% in 2023, whereas on average in EU countries this indicator for rural areas showed a slight decrease (from 10.6% to 10.5%). The increase in noise nuisance in the Finnish countryside may be linked to intensifying suburbanisation processes, dispersed development, and changes in the functional and spatial structure of these areas, which lead to increased road traffic and infrastructural pressure, and consequently—to a deterioration of acoustic living conditions [78].

Positive changes were also observed in towns and suburbs (intermediate areas) in terms of external residential environmental quality of households. The share of units classified in class I, indicating a high level of quality, increased from 3.8% in 2014 to 15.4% in 2023. At the same time, no unit was assigned to class IV, the lowest level of external residential environmental quality, whereas in 2014 this concerned 15.4% of cases (Table 6). This indicates a significant improvement in the living environment conditions in smaller urban centres, which may be the result of implementing local policies aimed at reducing noise, pollution, and perceived insecurity in residential surroundings.

An exception to this favourable pattern was observed for towns and suburbs in France and Spain, where the external residential environmental quality of households was lower in 2023 than in 2014 (Table 7). In both cases, a significant increase was observed in the percentage of households complaining about noise at their place of residence: in France from 16% in 2014 to 20.6% in 2023, and in Spain from 15% to 21.5%. This change contrasts with the EU average change between 2014 and 2023 in this settlement category, where the average for towns and suburbs in the EU decreased from 16% to 15.7%. These data may indicate increasing levels of acoustic nuisance in these countries, perhaps linked to uncontrolled suburbanisation, increased road traffic intensity, or insufficient adaptation of public spaces to the needs of residents of intermediate areas.

Despite the overall improvement in indicators, urban areas remain the most problematic type of area in terms of external residential environmental quality. In 2023, only one unit (cities in Croatia) was classified into class I (high level), while the share of units representing class II (medium-high level) increased to 26.9% (+15.4 percentage points compared to 2014). At the same time, in nine countries (34.6%), urban areas were classified in class IV, representing the lowest level of external residential environmental quality of households, which is the highest share among all analysed types of areas (Table 6).

In the case of most EU countries, urban areas showed higher external residential environmental quality in 2023 than in 2014 (Table 7, Figure 6). In 2023, in relation to 2014, as many as 14 countries had urban units classified in a higher class, which indicates a positive direction of change. In nine countries, the situation remained unchanged, which may indicate persistent stagnation or developmental barriers in improving the environmental conditions in the place of residence of urban households. An exception to this overall trend were cities in Finland, where a clear deterioration in the external residential environmental quality of households was observed. As a result of these adverse changes, in 2023 they were classified in the lowest class (class IV), whereas in 2014 they were in class II of the quality level of the residential environment. This decline was primarily associated with an increase in the share of the population experiencing negative environmental phenomena. The noise nuisance indicator (originating from neighbours or from the street) in Finnish cities increased from 17.5% in 2014 to 29.6% in 2023, which is one of the highest levels in the EU. At the same time, there was a significant increase in the percentage of residents experiencing problems related to crime, vandalism or lack of safety—from 10.0% to 16.7%. The deterioration in Finnish cities contrasts with the overall EU trend of improvement and indicates the need to intensify efforts in sustainable spatial planning and local policies aimed at improving external residential environmental conditions.

The persistently relatively low level of external residential environmental quality in large cities is a consequence of the accumulation of negative phenomena typical of highly urbanised environments—primarily excessive traffic noise, high levels of air pollution, limited access to green areas, and an increased sense of threat from crime. Additionally, intensive development and high population density promote the concentration of environmental and social problems, making it difficult to improve the external residential environment despite modernisation efforts and urban policies undertaken in many EU countries.

The results of the conducted typological classification clearly confirm that the type of residential area is a significant factor differentiating the quality level of external residential environmental quality of households in EU countries. Rural areas and smaller urban centres are far more frequently characterised by high or medium-high values of the synthetic indicator, which can be linked to lower levels of urbanisation, less infrastructural burden, better access to the natural environment (e.g., green areas), and relatively lower intensity of negative environmental factors, such as noise or air pollution. In turn, large cities, despite the improvement observed over the last decade, still exhibit structural deficits in the external residential environment. The accumulation of adverse phenomena—such as high population density, intense car traffic, limited access to recreational areas, and a higher sense of threat from crime—means that a significant proportion of urban areas remains classified in the lower classes of external residential environmental quality.

The conducted study showed that in some EU countries there are clear internal disparities in the level external residential environmental quality of households between cities, towns, and rural areas. Particularly large disparities occur between cities and rural areas in individual countries. In 2023, only in the case of two countries—Croatia and Hungary—was the quality of external residential environmental quality of households living in cities and rural areas at a similar level, which allowed them to be classified into the same typological class. In Croatia, the quality of the residential environment in these areas was assessed as high, whereas in Hungary it was assessed as medium-low.

In both 2014 and 2023, clear disparities (a difference in two typological classes) were observed in the level of quality of the residential environment of households living in cities and in rural areas in more than half of EU countries. In 2023, the countries where external residential environmental quality in rural areas was high (class I), while in urban areas it was medium-low (class III), included Italy, the Czech Republic, Denmark, and Latvia. In turn, the countries where the level of the analysed phenomenon in rural areas was medium-high (class II), while in urban areas it was low (class IV), included Belgium, France, Spain, Finland, Germany, Luxembourg, Greece, The Netherlands, and Portugal (Table 7).

Particularly large differences were observed in many Western European countries, i.e., e.g., Germany, France, Belgium and Austria. In these countries, the level of external residential environmental quality in large urban centres differed significantly from that observed in rural areas, which was reflected in their assignment to different typological classes (Table 7, Figure 6). For example, in Germany in 2023, cities obtained one of the lowest values of the synthetic indicator in the entire EU (q_i = 0.411, class IV), while rural areas achieved a result of 0.782 (class II), and towns—0.628 (class III). A similar situation occurred in France, where in 2023 cities achieved a very low result (q_i = 0.334, class IV), while towns and suburbs were classified in class III (q_i = 0.607) and rural areas in class II (q_i = 0.804). This type of arrangement may indicate limited effectiveness of environmental policies implemented in larger urban centres or neglect in the development of the urban living environment. In Belgium, strong differentiation was also recorded—in 2023, cities obtained a very low synthetic indicator score (q_i = 0.416, class IV), while the values for towns and rural areas amounted to 0.785 and 0.843, respectively, allowing them to be classified in class II. In Austria, the situation was analogous—in 2023, cities achieved a synthetic indicator score of 0.601 (class III), while towns and suburbs achieved 0.728 and rural areas 0.816 (both values corresponding to class II). Despite the overall improvement in 2023 compared to 2014, the spatial structure of external residential environmental quality still indicates a clear advantage of less urbanised areas. Such a considerable discrepancy results from the concentration of negative environmental factors in urban agglomerations, such as intensified traffic noise, higher air pollution, or a greater sense of threat from crime, while more favourable conditions are maintained in rural areas. As a result, smaller settlement units retain a lasting advantage over large urban centres in terms of external residential environmental quality, particularly in Western Europe.

On the other hand, there is a group of countries where the level of external residential environmental quality of households is not only relatively high but also relatively balanced across all types of areas—urban, town, and rural. This applies, for example, to Croatia, Poland, Slovakia, Lithuania and Sweden. For example, in Croatia, all three types of areas in 2023 achieved very high synthetic indicator values—above 0.89—with rural areas obtaining a score as high as 0.982, which was the highest value among all analysed territorial units. In Poland, however, cities, towns, and rural areas were classified into class I, indicating nationally favourable conditions of the external residential environment (Table 7).

The high and at the same time balanced level of external residential environmental quality in these countries may result from several co-occurring factors. Firstly, these are mostly countries with a lower level of urbanisation and lower population density compared to the highly urbanised countries of Western Europe. Such a settlement structure may foster a higher standard of the external environment—among others due to lower road traffic intensity, a larger share of green areas, and lower density of residential development. Secondly, in recent decades these countries have been intensively catching up on infrastructural and environmental shortcomings, often with the support of EU funds, which has translated into an improvement in the external residential environment.

The above results clearly indicate that the level of external residential environmental quality is not only spatially differentiated at the international level but also internally—within individual countries. In many cases, the disparities between cities and rural areas are significant and should constitute an important reference point for planning public policies aimed at sustainable territorial development and improving residents’ quality of life.

To deepen the assessment of the external residential environmental quality in EU countries, a comparison was made of the values of partial indicators illustrating the occurrence of negative environmental phenomena—such as noise, pollution, and crime risk—within the system of four typological classes of residential environment quality. The results clearly indicate the existence of a strong relationship between the typological class and the intensity of negative environmental phenomena—the lower the class (i.e., the poorer the overall level of quality of the residential environment), the higher the share of households reporting the nuisance of individual problems. This differentiation is particularly clear in relation to noise and crime, where the median value for class IV exceeds the median for class I more than threefold. In 2023, as many as 30.1% of households located in areas classified as class IV reported noise problems on average, whereas in class I it was only 7.7%. An even more pronounced contrast occurred in relation to crime—in the last class it was 19.5%, while in the first it was only 2.5%. Environmental pollution indicators also show clear differentiation, although their gradient is somewhat milder (

Table 8. Inter-class differentiation of the values of partial indicators illustrating the level of external residential environmental quality of households in European Union countries in 2014 and 2023 (class averages—medians).

Typological Class	Noise from Neighbours or from the Street (%)	Pollution, Grime or Other Environmental Problems (%)	Crime, Violence or Vandalism in the Area (%)
2014
I (high level)	8.4	4.4	4.0
II (medium-high level)	12.7	9.1	7.7
III (medium-low level)	17.3	14.7	13.5
IV (low)	24.2	20.6	21.6
Overall	15.0	12.5	11.6
2023
I (high)	7.7	5.4	2.5
II (medium-high level)	12.4	8.6	6.2
III (medium-low level)	22.2	14.5	10.9
IV (low)	30.1	17.4	19.5
Overall	13.5	9.2	6.7

Source: Own calculations based on data from Eurostat [64].

).

To verify the research hypothesis, Figure 7 presents the share of EU countries in the four classes of external residential environmental quality, differentiated by European macro-regions (Western, Eastern, Northern, Southern), types of areas (cities, towns, rural areas), and the years 2014 and 2023. In 2014, significant differentiation in external residential environmental quality was observed both between macro-regions and between types of areas. In urban areas, a particularly unfavourable situation was recorded in Western European countries, where all states were classified in the lowest class (IV). Likewise, in Eastern and Southern Europe, more than half of the countries were classified into the same category.

A different situation occurred in smaller urban centres (towns), where class II dominated across all macro-regions, with the most favourable class structure observed in Northern Europe—as many as five out of seven countries were in this class. The highest quality of external residential environmental quality in towns was recorded in only one Southern European country—Croatia. By far the most favourable situation was observed in rural areas. In 2014, in all macro-regions, most countries were classified in classes I or II, with a clear dominance of class I in Northern European countries.

In 2023, compared to 2014, the overall situation clearly improved, particularly in terms of the decline in the share of countries classified in the lowest class and the increase in the share of higher classes. In urban areas, the greatest improvement was observed in Eastern Europe, where the number of countries classified in class II increased by three (representing an increase of 43%), while the share of class IV decreased by four countries (−57%). In contrast, the situation in Western European cities remained unfavourable, with most countries still classified in the lowest class of external residential environmental quality

In turn, towns were characterised by the most positive change in class structure—class IV disappeared completely, and classes II and III dominated across all macro-regions. The increase in the share of class I was particularly noticeable in Eastern Europe, which may indicate the effectiveness of policies aimed at improving the quality of life in smaller centres. In rural areas, the generally high level of external residential environmental quality was maintained. In 2023, in all macro-regions, most countries were classified in classes I or II. Northern Europe continued to stand out with the largest share of countries in the highest class, while in Western Europe, despite favourable absolute values, the rate of improvement was somewhat lower than in other regions (Figure 7).

It is worth noting that Central and Eastern European countries, such as Poland, Slovakia, and Lithuania, achieved very high values of external residential environmental quality in rural areas in 2023—often surpassing Western European countries. Thus, they undermine the unequivocal nature of the initial hypothesis assumption regarding the dominance of Western Europe in this respect.

In towns (intermediate areas), a significant improvement was also recorded—the share of countries classified into higher classes increased, and class IV almost completely disappeared. The most positive changes were observed in Eastern and Northern Europe, where smaller urban centres increasingly achieved levels of external residential environmental quality comparable to those observed in rural areas. In Western and Southern Europe, the situation was more varied, and in some countries (e.g., France, Spain) there was even a deterioration in housing conditions, mainly due to an increase in noise nuisance.

Cities—despite some improvement—still remain the areas with the greatest differentiation and the lowest overall level of external residential environmental quality. In 2023, as many as one third of the countries of Southern and Western Europe were in the lowest class, and only a few cities achieved class I level (Figure 7). A positive exception were some Central and Eastern European countries (including Croatia and Poland), where even large cities achieved high indicator values. In turn, in Northern European countries—particularly in Finland—a clear deterioration in external residential environmental quality in cities was observed, which was linked to increased noise levels and a rise in the perceived threat of crime.

In summary, the research hypothesis regarding the differentiation of external residential environmental quality of households depending on the type of area and regional affiliation finds partial confirmation. The highest level of quality of the residential environment is indeed observed in rural areas, not in Western European countries, as originally assumed, but primarily in Northern and Eastern European countries. Empirical data also confirm that large cities still pose a challenge in the context of external residential environmental conditions, whereas towns and villages—especially in the eastern and northern regions of Europe—show the highest dynamics of improvement. These findings underscore the need for territorially differentiated environmental and urban policies in EU countries, with a particular focus on reducing environmental and social disturbances in large urban centres while sustaining favourable changes observed between 2014 and 2023 in smaller settlements and rural areas.

5. Summary and Conclusions

The conducted assessment of the external residential environmental quality of households in EU countries made it possible to capture the scale and direction of differentiation of the three key dimensions of the living environment—noise nuisance, exposure to pollution, and the perceived threat of crime—in 2014 and 2023. All examined elements showed clear and consistent relationships with the degree of urbanisation, and their cumulative effect was captured in the synthetic indicator of the quality of the residential environment.

Noise remains one of the most frequently reported environmental threats in the residential environment in Europe, particularly in urbanised conditions. The conducted analyses confirm a clear spatial relationship between the degree of urbanisation and the level of acoustic nuisance—the highest indicators occur in cities, medium in towns and suburbs, and the lowest in rural areas. This differentiation may reflect differences in traffic intensity, building density, or the quality of spatial planning. At the same time, significant differences are observed between European macro-regions—the highest medians of reported noise were recorded in Western Europe (e.g., Germany, the Netherlands, Belgium) and Southern Europe (including Spain, Portugal). In turn, the lowest noise levels occur in Eastern Europe (e.g., Poland, Croatia, Lithuania) and Northern Europe (e.g., Ireland, Estonia), which may result from lower infrastructural pressure, lower building intensity, and a higher share of green areas in the spatial structure. Such a clear territorial differentiation indicates that noise should be treated not only as a local nuisance but also as a spatial indicator of the quality of the residential environment, important for territorial development planning and the assessment of residents’ well-being on a European scale.

Between 2014 and 2023, households in the EU reported a lower prevalence of environmental problems at their place of residence, regardless of the degree of urbanisation. The highest level of nuisance consistently occurs in cities, confirming the strong link between the intensity of urbanisation and subjective environmental discomfort. Nevertheless, an improvement was recorded in all types of settlements—cities, towns, and villages—which may be the result of environmental policy measures, the development of municipal infrastructure, and growing ecological awareness. From a regional perspective, the highest intensity of such problems is observed in Western and Southern Europe, particularly in Greece, Germany, and Portugal, whereas the lowest levels are reported in Northern and Eastern Europe. This differentiation highlights the importance of a territorial approach to improving the quality of the residential environment in Europe.

The analysis of spatial differentiation in reported threats of crime, vandalism, and violence in households across EU countries indicates significant links between the level of urbanisation, regional context, and residents’ sense of security. In 2023, the greatest concerns occurred in cities—especially in Southern and Western Europe—whereas towns and rural areas were characterised by a lower level of reported problems. Between 2014 and 2023, the share of households reporting crime, vandalism, or violence decreased across settlement types, which may reflect improvements in social infrastructure, the effectiveness of security policies, and overall living conditions. At the same time, the variation between EU countries and regions suggests that factors such as institutional quality, social inequalities, suburbanisation, and migration pressures continue to strongly shape the perception of threats in the residential environment. Increases observed in some countries (e.g., Greece and France) may signal growing social challenges and the need for actions aimed at rebuilding social cohesion and trust in public institutions.

The synthetic assessment of the quality of the residential environment of households clearly confirmed the established spatial pattern in the EU. Its highest average level characterises rural areas, whereas the lowest is observed in urban areas. This result is consistent both cross-sectionally and over time, indicating that the type of residential area remains an important predictor of the quality of the residential environment of households. Contrary to initial expectations, it is not Western European countries but primarily Northern and Eastern European countries that achieve the highest values of the synthetic indicator of the quality of the residential environment of households. This reflects the growing role of small and medium settlement systems in ensuring a high quality of life, as well as significant infrastructural progress in some post-transition countries.

This unexpected macroregional pattern calls for a brief theoretical interpretation. The lack of confirmation of Western Europe’s predominance—despite the observed urban–rural gradient—suggests that macroregional differences in perceived residential environmental quality are shaped by structural and institutional mechanisms rather than by “development level” alone. In Western Europe, high metropolitan density and mature urbanisation trajectories are often accompanied by strong housing-market pressures, intensive transport flows and functional mixing, which can translate into higher exposure to noise and pollution and, in some contexts, greater perceived insecurity [73,79]. Moreover, higher environmental awareness and stricter expectations regarding residential comfort may also increase the propensity to report nuisances, reinforcing the observed pattern in perception-based indicators [42].

In Northern and parts of Eastern Europe, comparatively favourable rural outcomes may be linked to lower settlement density, a higher share of green space, and planning and infrastructure improvements that reduce everyday exposure to disturbances [79]. In several post-transition countries, long-term investments in local infrastructure and public-space upgrading—partly supported by EU cohesion policies—may additionally contribute to improved conditions in smaller settlements and rural areas. Overall, these findings indicate that territorial well-being is jointly shaped by welfare and governance capacity, housing and transport systems, and the spatial organisation of daily life, which calls for differentiated place-based policies aligned with the specific disturbances identified (noise, pollution/grime, and crime/violence/vandalism).

At the same time, the synthetic assessment of the external residential environmental quality revealed significant within-country variation, particularly in the highly urbanised countries of Western Europe, where differences between urban and rural areas reach as much as two typological classes. This indicates not only the spatial concentration of environmental problems in urban agglomerations but also the challenges in effectively implementing policies to improve quality of life under conditions of intensive urbanisation.

In 2023, compared with 2014, an increase was observed in the values of the synthetic indicator of household residential environment quality across all types of areas, which may be linked to the implementation of EU strategies on environmental protection, safety improvement, and the revitalisation of public spaces. However, this improvement did not occur evenly: the greatest progress was observed in cities, while in rural areas the increase in the indicator’s value was smaller, reflecting the already relatively high baseline level of the phenomenon under study.

The research findings fill an existing knowledge gap by providing a comparative and quantitative indication of how strongly the external quality of household residential environments in EU countries varies depending on the degree of urbanisation. They point to the simultaneous occurrence of two processes: the gradual convergence of household residential environment quality across EU countries, and the persistence of strong within-country differences, particularly between major cities and rural areas. These contrasting phenomena highlight the importance of a territorial approach to public policies and indicate that the key development challenges concern primarily the largest urban centres. This conclusion is consistent with broader macro-regional development assessments [80], which demonstrated that sustainable development and living standards across EU countries vary significantly by region and are shaped by long-term structural and institutional factors.

These conclusions are highly relevant for shaping public policies at both the national and EU levels. They point to the need for differentiated actions: improving the quality of urban spaces (e.g., through green infrastructure, noise reduction, and crime prevention) while simultaneously strengthening the potential of smaller centres as attractive places to live. Supporting sustainable territorial development should take into account not only income and technical infrastructure indicators but also the environmental conditions of residents’ immediate surroundings, as one of the foundations of their wellbeing.

These conclusions should, however, be interpreted with several limitations in mind. The study uses EU-SILC self-reports and therefore captures perceived disturbances; cross-country differences may partly reflect variation in reporting behaviour and cultural norms, despite the DEGURBA classification. The analysis is based on country-level percentages (no microdata), so comparative tests treat countries (and country × settlement-type cells) as the unit of analysis and should be interpreted as exploratory evidence rather than household-level causal inference; EU countries may also be interdependent. Finally, results compare two time points (2014 vs. 2023), which supports point-to-point change assessment rather than inference about continuous trends.

The synthetic indicator and the associated typological classification provide not only a comparative picture of residential environmental quality across EU countries and settlement types but also a practical framework for policy targeting. Since the indicator is constructed from three perceived disturbances—noise, pollution/grime and other environmental problems, and crime/violence/vandalism—its interpretation can be directly linked to dimension-specific interventions. In particular, the results suggest that cities require the most integrated policy packages due to the accumulation of disturbances and the lowest overall levels of residential environmental quality; towns and suburbs should be addressed with policies that prevent the spillover of urban burdens into intermediate areas, especially through coordinated transport–land-use planning; and rural areas, while generally characterised by higher residential environmental quality, may still require targeted actions in selected countries. Operationally, the typological classes (I–IV) may support prioritisation: units classified in class IV can be treated as priority areas for integrated interventions across the three dimensions, whereas classes I–II may focus on maintaining achieved levels and preventing deterioration. Overall, the findings underline the need for territorially differentiated, place-based policies aligned with the specific disturbances identified in each settlement type and macroregional context

In light of the analyses conducted, it appears appropriate to formulate territorially differentiated recommendations for public policy and spatial planning. In particular, it is essential to intensify efforts to improve the quality of external residential environments in cities, where problems related to noise, pollution, and the perception of threat are concentrated. At the same time, the potential of smaller centres and rural areas should be strengthened by supporting their access to infrastructure and countering marginalisation. It is also crucial to take residents’ subjective assessments into account when designing housing and environmental policies, as well as to integrate issues of residential environment quality with public health objectives. The study results clearly indicate the need for implementing an individualised, place-based policy that takes into account the diverse needs of residents depending on the degree of urbanisation and regional affiliation.