Thermal Modernization for Sustainable Cities: Environmental and Economic Impacts in Central Urban Areas

Abstract

Maintaining a high-quality urban environment remains a critical yet challenging issue in modern cities, particularly in densely built and historically significant central areas. In response, the European Green Deal initiative aims to promote sustainable urban development. This study presents a multi-criteria assessment methodology for evaluating urban environments, with a focus on prioritizing thermal renovations of buildings to achieve substantial environmental improvements. The research adopts a centrifugal strategy, targeting buildings with the poorest energy performance for phased renovation efforts. Using the model city of Gubin, Poland, as a case study, the assessment proceeds through five stages: evaluating technical wear (Stages I–II), estimating replacement values and renovation costs (Stages III–IV), and finally, quantifying environmental benefits from energy efficiency upgrades (Stage V). Findings reveal that buildings in the lowest energy class (Class G) require investments of 111–193% of their replacement value but can deliver CO₂ emissions reduced to 1/6.2 of the original level (an approximate 84% reduction). The primary contribution of this paper is the development and application of a novel multi-criteria assessment methodology for evaluating urban environments, specifically designed to prioritize thermal renovations in central urban areas to achieve significant environmental and economic benefits. The study provides valuable economic and environmental indicators that can guide the formulation of pro-environmental urban policies and support strategic decision-making in cities with dense populations and aging infrastructure.

1. Introduction

1.1. Buildings, Energy Demand, and the Climate Challenge

Across the European Union (EU), buildings represent the most significant energy end-use sector, accounting for almost 40% of final energy demand and approximately 36% of energy-related CO₂ emissions [1]. Consequently, this sector occupies a pivotal position within the European Green Deal and the Fit-for-55 policy framework. Nevertheless, despite the pivotal role of the building stock in achieving climate neutrality, progress in renovation remains significantly below the requisite levels. Recent surveys conducted by the Buildings Performance Institute Europe (BPIE) indicate that the average annual rate of energy-related renovations in the EU is less than 1% of the total floor area, while the rate of deep renovations—those that deliver transformative energy savings—hovers around just 0.2% [2]. This stagnation signifies a pivotal structural dilemma, particularly given that the duration of building lifespans spans numerous decades. A considerable body of research has indicated that between 75 and 85 percent of the dwellings currently in use will be in continuous occupation until the year 2050 [3]. In the absence of accelerated upgrading, Europe’s “legacy fabric” is likely to constitute a significant impediment to the achievement of net-zero emissions targets [4]. Concurrently, the failure to curtail the operational energy demand of the built environment has been demonstrated to exacerbate household energy expenditures, to engender deteriorated air quality, and to contribute to health inequalities [5,6].

1.2. Regional Context: Central and Eastern Europe

The retrofit deficit is particularly acute in Central and Eastern Europe (CEE), where post-socialist urban housing estates are characterized by uniform prefabricated concrete-block architecture, thin insulation layers, and outdated heating systems [7]. The issue of inadequate investment, a phenomenon that has persisted since the 1990s political transitions, has led to numerous edifices characterized by high heat-loss indices and mounting maintenance backlogs [8]. Moreover, the transition from state-owned housing to fragmented private ownership has introduced governance complexities that complicate collective renovation decisions [9]. Empirical studies demonstrate that multi-family dwellings in the CEE region consume up to four times more heating energy than comparable units in Western Europe [10]. This inefficiency is concomitant with socio-economic vulnerabilities, giving rise to energy poverty hotspots where households face a dual burden of high energy bills and deteriorating indoor comfort [11]. The fiscal context further exacerbates the challenge, with national differences in property taxation, housing subsidies, and corporate tax regimes creating divergent climates for ESCO financing. While low-tax jurisdictions such as Ireland or Luxembourg experience capital flows, higher-tax CEE countries encounter difficulties in mobilizing comparable private investments [12,13]. Consequently, scholars have emphasized the importance of targeted incentives, including reduced value-added tax (VAT) rates for renovation materials, tax credits, and on-bill financing schemes, to support equitable access to retrofit benefits [5,14].

1.3. Policy Framework: EU and National Strategies

The EU has progressively strengthened its policy architecture with a view to accelerating the process of building renovation. The Energy Performance of Buildings Directive (EPBD) [2], revised in 2024, obliges Member States to guarantee that the least energy-efficient non-residential buildings attain a minimum energy rating of F by 2030, and that 26% of such buildings achieve a minimum rating of E by 2033 [15]. For residential properties, analogous minimum energy performance standards (MEPS) will be implemented, with the objective of propelling the least efficient homes towards efficiency classes F and E by the years 2030 and 2033. These measures have been designed to address the “policy gap” that was left by earlier instruments, such as Energy Performance Certificates (EPCs), which delivered only modest market signals [16,17]. Complementary strategies have been developed to reinforce this directive. The EU’s Renovation Wave initiative, established in 2020, aims to double the annual renovation rate over the forthcoming decade [18]. National long-term renovation strategies (LTRSs), such as Poland’s 2022 plan, commit to multi-million-scale thermal upgrades, including both shallow interventions (replacement of coal-fired boilers) and deep retrofits that comprehensively address insulation, windows, and systems. In Poland, for instance, the DSRB strategy anticipates 7.5 million renovations by 2050, of which 4.7 million are projected to be comprehensive [4]. Financial support mechanisms are offered by both the EU and national funds. At the EU level, cohesion funds and the Just Transition Mechanism allocate resources to regions with a long-standing reliance on coal [19]. At the national level, Poland’s Clean Air and Stop Smog funds deliver targeted subsidies for households, while the Thermal Modernisation and Renovation Fund leverages banking instruments for broader projects [20,21]. Despite these efforts, access for low-income owners remains limited without the implementation of tailored instruments, such as tax reductions, targeted grants, and inclusive pathways through public–private partnerships (PPPs) [12,13].

1.4. Social Dimensions: Energy Poverty and Health

The notion of buildings as mere technical or economic domains is a simplistic one; they are also a social determinant of health and well-being. The inhabitants of substandard housing frequently encounter suboptimal indoor thermal conditions, exposure to pollutants, and deficient ventilation, which exert a direct impact on respiratory and cardiovascular health [5,6]. Furthermore, energy poverty has been demonstrated to exacerbate social inequality by forcing households to expend a disproportionate share of their income on energy, often at the expense of food, healthcare, or education [6].

The correlation between substandard housing, stress, and mental health outcomes is a recognised phenomenon [22]. Research suggests that existential insecurity about energy bills and displacement due to urban redevelopment (also termed “renoviction”) contributes to heightened psychosocial stress among vulnerable groups [23,24,25].

1.5. The Economics of Renovation and Methodological Gaps

Conventional investment appraisals for renovation projects rely on net present value (NPV) calculations based primarily on fuel savings and maintenance cost reductions [26]. Nevertheless, this approach systematically underestimates broader non-market benefits. These include health cost savings from reduced air pollution [27], productivity improvements associated with better indoor environments [28], and societal benefits of carbon abatement [29]. In order to surmount these limitations, multi-criteria decision-making tools have been developed that incorporate economic, environmental, and technical (EET) indicators [30]. These frameworks account for life-cycle carbon, resilience against technical obsolescence, and welfare gains, offering a more holistic valuation of retrofit projects. Case studies demonstrate that projects classified as marginal or unattractive under conventional NPV appraisals become economically viable once externalities such as avoided healthcare expenditures and monetised carbon reductions are taken into account [31]. Nevertheless, methodological challenges persist, including the necessity for harmonized life-cycle assessment databases and standardised carbon pricing assumptions [32].

1.6. Governance and Participation

A growing body of literature emphasises the role of community participation in enhancing retrofit acceptance and equity. Participatory pilot projects in Poland, Hungary, and Romania demonstrate that residents involved in shaping the technical scope and financing options reported greater satisfaction and lower fears of displacement [33]. In a similar vein, governance structures that are co-created—such as neighbourhood energy forums and participatory budgeting—enable the customization of retrofit packages to local conditions [34,35,36,37]. These approaches have been shown to increase adoption rates among vulnerable households while concomitantly reducing the risk of gentrification-driven displacement [23,38]. The integration of participatory methods with EET evaluation ensures that equity metrics, such as the share of energy savings captured by low-income households, are explicitly considered [39,40]. This approach is consistent with the EU’s overarching Just Transition agenda, which aims to ensure that the transition to a climate-neutral economy does not intensify existing inequalities but rather generates societal co-benefits [20,21].

1.7. Challenges for Urban Policy and Regeneration

Urban areas with dense, older building stock present particular challenges. High-rise estates from the mid-20th century often coincide with fragile socio-economic conditions. Integrated urban regeneration strategies are required in such cases, combining physical retrofits with social and cultural investments [41]. In the absence of such comprehensive strategies, local authorities may find themselves perpetuating urban decline, outmigration from city centres, and the adoption of unsustainable suburbanization patterns. Spatial policy, heritage conservation, and public–private partnerships (PPPs) all interact with renovation goals [42]. The coordination of these domains requires both technical capacity and political will, particularly at the municipal level [43]. However, as highlighted by comparative studies, many local authorities face capacity deficits that hinder large-scale programmatic interventions. Furthermore, educational initiatives are being deployed to enhance environmental awareness of the benefits of modernization, complemented by technological assistance such as energy management systems and strategic investments designed to promote efficient energy use while simultaneously delivering social and environmental benefits [44].

1.8. Integrating Advances in Sustainable Urban Design

Recent research on sustainable urban design emphasizes the role of urban morphology in guiding energy efficiency, equity, and resilience. A typo-morphological framework links scales from building materials to city-wide street networks, showing how sustainable urban form depends on six parameters: efficiency, integrity, responsibility, acceptability, liveliness, and equity [45]. Efficiency is especially sensitive to material choice: high-performance insulation or low-carbon alternatives substantially reduce lifetime energy use and embodied emissions [45]. This approach suggests that sustainable renovation policies should integrate not only technical upgrades but also design strategies that reinforce social cohesion, accessibility, and urban vibrancy. At the same time, advances in sustainable construction materials—such as bio-based composites, recycled aggregates, and low-carbon concretes—are being applied to renovation and new builds [46]. These materials reduce embodied energy while improving thermal performance, directly supporting the EU’s Renovation Wave goals. When aligned with urban design frameworks, their use can amplify both micro-scale efficiency (at the building level) and macro-scale resilience (at the city level) [46].

1.9. Toward Integrated Assessment Tools

In view of the challenges identified, there is an urgent requirement for integrated assessment frameworks that can address the technical, economic, and environmental dimensions in a simultaneous and coordinated manner. The EET-based methodology presented in this study contributes to filling this gap. The objective of the present study is to quantify both costs and environmental co-benefits, thereby generating actionable evidence for policymakers and investors.

The case study of Gubin, Poland, provides a testbed for the application of this methodology to a medium-sized urban context characterized by a substantial presence of low-performance buildings. The analysis explores the potential for energy efficiency gains, the economic implications of deep renovation, and the associated environmental benefits. The primary contribution of this paper is the development and application of a novel multi-criteria assessment methodology for evaluating urban environments, specifically designed to prioritize thermal renovations in central urban areas to achieve significant environmental and economic benefits. The remainder of this paper is structured as follows: Section 2 presents the research purpose, methodology, and assumptions, including the ASEET multi-criteria assessment framework. Section 3 reports the results of the empirical case study of Gubin, Poland, with detailed technical, economic, and environmental evaluations across different building zones. Section 4 provides a discussion of the findings, highlighting the environmental and socio-economic benefits of thermal modernization and comparing alternative renovation scenarios. In Section 5, the focus is on the cumulative economic and environmental indicators for a selected group of buildings that have undergone thermal modernization, with limitations and future research.

2. Research Methodology and Assumptions

2.1. Research Objective

The primary objective of the research is to determine cumulative economic, energy, and technical (EET) indicators that reflect the technical and environmental performance of buildings within the study area. This economic assessment utilizes the EET indicators to identify the potential for energy improvement, focusing initially on buildings in the lowest energy efficiency classes (G-F) [2]. The ultimate goal is to quantify the investment costs associated with the energy modernization of individual buildings and complexes, thereby justifying environmental benefits such as reduction in CO₂ and other greenhouse gas (GHG) emissions.

An intermediate objective is to support the strategic management and control of expenditure and economic subsidies at national and European levels [47,48,49]. The study employs socio-economic indicators, benchmarked against carbon emissions in the analysed zones [30], to manage energy efficiency improvements in urban areas.

Effective management of urban energy efficiency yields multiple benefits:

• Reducing energy poverty: addressing the vulnerability of residents who cannot maintain adequate home temperatures [50,51];
• Mitigating financial burdens: reducing high heating and electricity costs, which disproportionately affect low-income residents, property owners, and local authorities [52];
• Improving public health outcomes: reducing excessive GHC emissions, PM10, and PM2.5 particulate matter; these emissions often stem from poor building technical conditions and outdated heating/ventilation systems, thus mitigating respiratory disease risks, especially for children and the elderly [53,54,55].

2.2. Research Methodology

The study employs a multi-criteria economic and environmental analysis focused on enhancing the energy efficiency of existing downtown built-up areas. This research represents a continuation of prior environmental work, specifically extending the climate assessment of CO₂ emissions by integrating the conceptual framework of the ASEET methodology [35], as shown in Figure 1. This approach identifies environmental data necessary for analysis and calculations, organized according to the following criteria: A—Architectural (design and construction); S—Social (impact on users and society); E—Economic (financial implications for owners and users); E—Energy (building energy efficiency); and T—Technical (technical condition). To enhance study transparency, we only operationalized the EET dimensions. The Architectural dimension serves solely as a checklist for typology/geometry and heat sources in Stage I and was not developed as an indicator or weighting factor for calculations. Conversely, the social dimension was entirely omitted. The current investigation concentrates on assessing the economic efficacy of improving the energy efficiency of buildings characterized by the lowest technical status. This approach is intended to provide a practical tool for conducting sustainable urban policy and serves as a participatory offer for residents by clearly outlining the investment costs associated with the thermal modernization of their properties.

The operational procedure, detailed in Figure 2, comprises five stages (I–V) designed to establish a direct link between building renovation costs and measurable environmental effects at the urban scale.

The methodological diagram (Figure 2) involves the following five stages:

• Stage I: architectural and technological inventory, including technical infrastructure and the building’s energy supply source;
• Stage II: determination of the technical wear degree (S_zt) of buildings within the selected city zone;
• Stage III: estimation of the existing building’s value based on architectural and technical data;
• Stage IV: determination of the costs associated with potential thermal modernization measures, according to the applicable energy standards for buildings in the analysed city zones;
• Stage V: discussion of the results, with an indication of derived environmental benefits.

Subsequently, the methodological procedures will be detailed, illustrating the study’s results based on the adopted calculation assumptions for both individual buildings and urban areas.

2.3. Methodological and Calculation Assumptions

For the purpose of this research, urban buildings in poor technical condition were defined as properties that are neglected, fail to meet modern standards, and exhibit existing technical infrastructure problems. These characteristics consistently translate into several negative outcomes:

• High Operating Costs: These buildings frequently utilize outdated heating and cooling systems, which substantially increases maintenance and operational costs.
• Low Energy Efficiency: A lack of adequate thermal insulation results in significant heat loss and a corresponding increase in overall energy consumption.
• Environmental Pollution: The prevalent use of outdated, high-emission energy sources, such as coal, contributes to increasing CO₂ emissions and local air pollution.

2.3.1. Research Area

The study is regionally focused on Poland, a European country facing significant energy and climate transformation requirements for its existing building stock. Poland plans 7.4 million thermal renovations by 2050, with approximately 30% of buildings currently classified as being in poor technical condition (Class G) [56].

2.3.2. Policy and Building Classification

Following the European Parliament and Council Directive on the Energy Performance of Buildings (EPBD), a classification system for buildings has been established, ranging from Class G (highest energy intensity and environmental impact) to Class A. Class G buildings are designated as those generating an annual energy performance (EP) greater than 150 kWH/m².

This research specifically targeted Class G buildings that rely on coal as the primary energy source. Consequently, the environmental analysis was primarily limited to carbon dioxide (CO₂), as it is the principal emission product of coal combustion. The use of the colour red for Zone I is consistent with the EPBD classification convention for Class G designation.

2.3.3. Model City and Economic Indicators

The proposed economic and environmental assessment aligns with recommendations for deep renovation policies [57]. We selected the city of Gubin, Poland (see Figure 3), as a model urban area. Gubin serves as an exemplary case study for the European green transformation, whose methodology could be adopted globally.

Previous studies have defined energy efficiency (EE) climate indicators for urban zones (j: I—red, II—yellow, and III—green) [30]. These indicators incorporate key factors: construction year, technology, heating systems, building surface parameters, operating costs, and energy consumption, and are utilized in stage V of the analysis.

The aim is to rapidly assess the economic and environmental performance of buildings on an urban scale. This is achieved by comparing the estimated value of existing buildings (W_GB) with the standard replacement value (K_RB) for new buildings that meet current standards. While this method, derived from real estate valuation, does not provide a detailed cost estimation (design, materials, labour, and energy certification), it allows the K_ST indicator to be used as a key tool for setting economic policy and investment priorities. The final step (Stage V) involves comparing the economic and technical indicators (K_ST and W_GB) with the ecological emission indicators (EE_j) across the city zones.

Based on empirical data, the built-up areas of Gubin were divided into four zones (S_I–S_IV) based on differences in environmental quality, which resulted from variations in technical condition, construction technology, main heat sources, and building typology. Zone S_IV, which comprises low-energy buildings compliant with contemporary environmental standards, was excluded from the study.

Following the data collection, the study zones were characterized by distinct CO₂ emission indicators:

• Zone I: average emission indicator EE_I = 33,899.0 MgCO₂/year;
• Zone II: average emission indicator EE_II = 12,167.0 MgCO₂/year;
• Zone III: average emission indicator EE_III = 2402.0 MgCO₂/year.

Emissions in each EE zone are significantly influenced by the technical condition of the buildings and the infrastructure for energy production and management (primary central heating (CO), domestic hot water (DHW), and air conditioning) [30].

The data collection and analysis efforts focused on buildings in Zones I, II, and III, which were designated as model objects for the socio-economic assessment of energy efficiency improvement.

At this stage of the study, it was assumed that residents would co-finance the thermal modernization of their own properties, supplemented by the participation of local authorities and EU subsidies [58,59]. This implementation strategy is projected to yield multiple long-term economic and environmental benefits:

• Lower operating costs: resulting from reduced energy consumption and heating/cooling costs;
• Lower emissions: achieved through the use of modern energy sources and improved building insulation, which can significantly reduce CO₂ emissions;
• Job creation: building modernization generates demand for skilled workers in the construction and energy sectors, supporting the local labour market.

3. Study Procedure and Results

The assessment of the urban area was structured into four distinct stages: Stage I (Inventory and Data Collection), Stage II (Determination of Technical Wear), Stage III (Valuation of Existing Buildings), and Stage IV (Economic Participation in Deep Thermal Modernization), ultimately addressing the currently required energy and technical standards.

3.1. Stage I—Data Inventory

Stage I involved collecting interdisciplinary inventory data for model buildings (R1-R6) [6] that represent specific development zones with similar typological characteristics. The gathered data encompassed construction technology, building function, year of construction, and operational costs. This information was primarily obtained through direct interviews with residents and owners.

The socio-economic data collected are essential for the fast-track thermal modernization path outlined in subsequent stages (II to V), particularly focusing on the economic, energy, and technical (EET) aspects of the ASEET methodology. Based on the inventory, a clear path for assessing the costs of energy and environmental improvement is presented (

Table 1. Number of buildings by construction period and zone.

Construction Year	No. of Buildings Zone SI	No. of Buildings Zone SII	No of Buildings Zone SIII
Until 1945–66	5	1	2
1967–92	1	5	2
1993–2008	-	-	1
Since 2009	-	-	1

). Note that Zone IV was excluded from this stage as it comprises only low-energy buildings already compliant with contemporary environmental standards.

Therefore, in accordance with the ASEET methodology, Stage I relied on empirical data gathered through surveys [30,60]. This involved the following factors:

• Inclusion of buildings with diverse social statuses, for which detailed technical and metric data were collected, including the year of construction, primary construction technology, type of heating system, number of stories, number of users, and total heated area ratio.
• Designation of surveyed areas that contain buildings exhibiting similar typological characteristics.
• Assignment of buildings to development zones based on the heat source criterion, which is directly related to the building’s emission profile [30].

The building data presented in Table 1 represent specific types used in the subsequent socio-economic assessment stages (II–IV). The analysis strategically focused on the oldest buildings within each given type.

3.2. Stage II—Technical Assessment of the Degree of Wear

The technical aspect of the ASEET assessment methodology requires calculating the degree of technical wear (S_zt) for buildings based on empirical data, including construction technology, age, heating system, and building function.

The foundation for assessing the technical condition of the analysed buildings with the lowest technical status (those located in zones I–III) is a calculation formula establishing the proportionality between the building’s age and its theoretical service life [61] as visually represented in Figure 4 (the S_zt formula is detailed below).

This linear formula is specifically applied to buildings identified as being in poor technical condition, typically characterized by 50–70% technical wear (S_zt). This high degradation is presumed to result from inadequate financing for regular renovations and unsystematic maintenance.

Consequently, the technical wear degree (S_zt) was calculated using the following linear relationship [61]:

$${\mathrm{S}}_{\mathrm{z}\mathrm{t}}={\displaystyle \frac{\mathrm{t}}{\mathrm{T}}} \mathrm{\ast } 100$$

(1)

where

• S_zt—degree of technical wear of the object [%];
• t—age of the object [years];
• T—expected service life [years], referenced in

  Table 2. Estimated service life (T) based on building type and construction technology.

  Building Type/Purpose	Wooden	Mixed	Massive
  Residential buildings	80–100	90–120	100–150
  Summer houses	Up to 40	Up to 60	Up to 80
  Farm/Utility buildings	60–70	70–90	80–100
  Livestock buildings	40–50	50–60	60–70
  Detached garages	None	50–80	80–100
  Repair workshops	40–50	50–80	Up to 100

  .

Table 2 presents the estimated service life (T) based on building type and construction technology, following the methodology concerning the determination of the technical wear (or degradation) degree of large-panel buildings [63].

The next step in the assessment is to calculate the combined technical and functional Degradation Factor (W_z or W_z (t,f)) [64].

This coefficient was initially calculated using the following formula:

$${\mathrm{W}}_{\mathrm{z}}\left(\mathrm{t},\mathrm{f}\right)=1-{\displaystyle \frac{({\mathrm{S}}_{\mathrm{z}\mathrm{t}}\times {\mathrm{S}}_{\mathrm{z}\mathrm{f}})}{100}}$$

(2)

where

• W_Z(t,f)—combined technical and functional Degradation Factor [%];
• S_zt—degree of technical wear [%];
• S_zf—degree of functional wear [%].

The analysed residential buildings largely fail to meet the requirements set by the Technical Conditions and contemporary resident expectations. Therefore, we assumed a complete functional obsolescence, setting S_zf = 100%.

Substituting this assumption into the equation, we derive the following simplifications:

$${\mathrm{W}}_{\mathrm{z}}\left(\mathrm{t},\mathrm{f}\right)=1-\left[{\displaystyle \frac{{\mathrm{S}}_{\mathrm{z}\mathrm{t}}}{100\mathrm{\%}}}\times {\displaystyle \frac{{\mathrm{S}}_{\mathrm{z}\mathrm{f}}}{100\mathrm{\%}}}\right]leadingto{W}_z\left(t,f\right)=1-\left[{\displaystyle \frac{{\mathrm{S}}_{\mathrm{z}\mathrm{t}}}{100\%}}\times {\displaystyle \frac{100\%}{100\%}}\right]$$

(3)

Based on this, the combined technical degradation factor (W_z) was ultimately calculated using the simplified linear relationship:

$${\mathrm{W}}_{\mathrm{z}}\left(\mathrm{t},\mathrm{f}\right)=1-{\displaystyle \frac{{\mathrm{S}}_{\mathrm{z}\mathrm{t}}}{100\mathrm{\%}}}$$

(4)

where W_z(t,f) represents the combined technical and functional degradation factor.

Initially, the technical wear of buildings in Zone I was examined (

Table 3. Technical wear parameters for traditional technology buildings in Gubin Zone S_I.

No.	Address	Heated Area [m2]	Building Age [Year]	Durability [Year]	Szt [%]	WZ
1	Gdańska 15 (KM *)	603.2	79	150	53	0.47
2	Bat. Chłopskich 6/8 (KM *)	221.4	79	150	53	0.47
3	Śląska 33 (KM *)	336.2	79	150	53	0.47
4	Kresowa 48 (School No. 3)	2676.0	60	120	50	0.50
5	Gdańska 17 (Clinic NFZ)	3444.0	49	120	41	0.59
6	Piastowska 20 (Kindergarten)	807.0	79	120	66	0.34

* KM—residential tenement house.

). This zone comprises the oldest buildings that form the city’s old town, primarily consisting of urban tenements built before 1945 using traditional technology.

Table 3 summarizes the calculated values of the technical wear degree (S_zt). The values range from 53–66%, which clearly indicates technical degradation. For planning purposes in subsequent economic analysis, the average wear index (S_zt) in Zone I can be assumed to be 50%, which will undoubtedly necessitate substantial renovation costs.

The degradation factor (W_z) is an auxiliary indicator. Therefore, even if its value is less than 0.5, cofinancing for modernization costs (K_st) may still be justified by other factors, such as historical status, location, or social and environmental benefits. The primary purpose of these economic indicators is to inform urban policy decisions.

For the yellow zone (S_II), the technical wear coefficients are summarized in

Table 4. Technical wear parameters for prefabricated buildings in Gubin Zone S_II.

No.	Address	Heated Area [m2]	Building Age [Year]	Durability [Year]	Szt [%]	WZ
1	Chrobrego 12	763.0	62	150	41	0.59
2	Roosevelta 11a	2380.0	54	150	36	0.64
3	Konopnickiej 1	1338.0	53	150	35	0.65
4	Westerplatte 10	1907.0	50	150	33	0.67
5	Emilii Plater 4	1151.5	54	150	36	0.64
6	Emilii Plater 9	3328.0	51	150	34	0.66

. This zone is characterized by monotype multi-family block flats or multi-family segmented buildings, typically reaching 3–5 stories in height.

Multi-family buildings constructed using the Żerań system were among the first in Poland to be built on a large scale during the 1960s and 1970s. Their estimated technical wear degree (S_zt) is relatively low, ranging from 33 to 41%, which positively influences the economic viability of adapting these buildings to contemporary energy requirements.

Buildings located in Zone III are supplied with natural gas and include structures of varying technology and age, ranging from pre-war (before 1945) to contemporary, as summarized in

Table 5. Technical wear parameters of mixed technology buildings in Gubin Zone S_III.

No.	Address	Heated Area [m2]	Building Age [Year]	Durability [Year]	Szt [%]	WZ
1	Piastowska 24 (A*)	2483.7	79	120	66	0.34
2	Rydla 2 (R*)	672.0	49	150	33	0.67
3	Racławicka 2 (School)	4284.8	49	120	41	0.59
4	Kresowa 122 (Hostel)	806.0	26	120	22	0.78
5	Gdańska 18a (R*)	245.0	24	120	20	0.80
6	Gdyńska 11 (R*)	197.4	15	120	13	0.88

A*—administration, R*—residential.

.

A characteristic feature of these buildings is their better technical condition, resulting from more frequent renovations and adaptations, as well as the inclusion of structures constructed using modern technologies, such as passive buildings. The measured technical wear degree (S_zt) exhibits a wide range, from 13 to 66%, depending on the specific type. This broad range requires an individualized approach when setting investment and environmental priorities.

3.3. Stage III and IV—Determination of Existing Building Value and Deep Thermal Renovation Costs

The technical condition of the buildings, as determined in Stage II, serves as the initial basis for assessing their economic value in the urban areas studied. These steps present the valuation of buildings in their existing condition (Stage III) and after adaptation to W_T (2024) requirements (Stage 4) [2]. Knowing a building’s value in its adapted condition allows us to determine the required level of economic participation for existing structures.

The authors’ goal was to adopt a method for economic and environmental assessment suitable for an urban scale. The chosen approach involves calculating the estimated value of existing buildings (W_GB) and comparing it with the standard replacement value (K_RB) of new buildings that comply with current standards. This method, rooted in real estate valuations, is used for macro-level assessment and does not constitute a detailed, design-specific cost estimation based on a procedure of design–technology–materials–labour, audit, and energy certification.

Conversely, the economic indicator for thermal modernization, K_ST (Modernization cost), can be used as a tool for economic policy when setting investment priorities across the city. Furthermore, the economic and technical indicators (K_ST and W_GB) can be compared with the ecological emission indicator (EE_j) for buildings in different zones, facilitating the creation of an environmental intervention map for the city.

Based on regulation [65], the replacement cost method was adopted pursuant to §3, p. 4. The results obtained via the index method are subsequently used to calculate the consumption costs of the facility as the initial state for the analysis, thereby determining the technical conditions, i.e., the wear of the building [66].

The methodology employed in this section, specifically the estimation of replacement costs using the index method, was guided by the methodological framework established by WACETOB and substantiated by pertinent external sources [67].

According to these principles, the technical wear of a building is understood as the depreciation of its value relative to the cost of constructing an equivalent new structure. In the process of determining the replacement value of buildings [68], the following calculation steps were adopted:

• Step 1—Determining the Replacement Cost of the Building (K_RB)

This step involves calculating the cost required to restore the building to its original condition, which simultaneously means adapting the structure to current technical and energy requirements, including the primary energy (EP) standard. This cost encompasses all necessary construction works and technical equipment. The calculation for the restoration cost, or standard replacement value (K_RB), is given as follows:

$${\mathrm{K}}_{\mathrm{R}\mathrm{B}}=\mathrm{Q}\times {\mathrm{C}}_{\mathrm{j}\mathrm{q}}$$

(5)

where

• K_RB—costs of restoring the building [PLN];
• Q—number of reference units, defined as the A_UH of heated usable floor space [m²] (assumed for this study) or V_H of cubic capacity [m³];
• C_jq—unit price index for a comparable facility. The unit price was adopted based on data from the Central Statistical Office (GUS) [68] as the average price index per 1 m² of usable floor space in the fourth quarter of 2024, which is 1788.14 USD/m2 (7162 PLN/m2, as of Q4 2024, using an exchange rate of 4.0 PLN per 1 USD).

• Step 2—Calculation of the Value of the Existing Building (W_GB)

The replacement value of existing buildings, calculated using the cost approach (replacement cost method, index method, and coefficient method), is determined by the following formula:

$${\mathrm{W}}_{\mathrm{G}\mathrm{B}}={\mathrm{K}}_{\mathrm{R}\mathrm{B}}\times {\mathrm{W}}_{\mathrm{z}}(\mathrm{t},\mathrm{f})$$

(6)

where

• W_GB—replacement value of the building in its current condition;
• K_RB—value of a new ‘replica’ building;
• W_z(t,f)—the combined technical and functional degradation factor.

Based on the simplified degradation factor (as derived in Equation (4)), the replacement value is thus obtained from the following formula:

$${\mathrm{W}}_{\mathrm{G}\mathrm{B}}={\mathrm{K}}_{\mathrm{R}\mathrm{B}}\times [1-\left({\displaystyle \frac{{\mathrm{S}}_{\mathrm{z}\mathrm{t}}}{100\mathrm{\%}}}\right)]$$

(7)

The W_GB value is an estimated value used for property valuation purposes and is adopted in these studies as a quantitative indicator on an urban scale.

• Step 3—Calculation of the Estimated Modernization Cost K_ST

The cost required to achieve the K_ST energy standard can be calculated using the difference between the standardized replacement value and the existing value:

$${\mathrm{K}}_{\mathrm{S}\mathrm{T}}={\mathrm{K}}_{\mathrm{R}\mathrm{B}}-{\mathrm{W}}_{\mathrm{G}\mathrm{B}}\left[\mathrm{U}\mathrm{S}\mathrm{D}\right]$$

(8)

This socio-economic assessment uses this formula to estimate the necessary costs of thermal modernization, derived from the difference between the value of a new building K_RB that meets current requirements (according to W_T (2024)) and the value of the existing building W_GB. This assumption allows for the strategic estimation of energy efficiency improvement costs across the study area.

In this research step, a parametric analysis is conducted to demonstrate the economic relationship between the technical condition and energy consumption of the buildings studied [30], thus indicating the economic potential for upgrading their standards. This socio-economic assessment does not exhaust the subject but serves as a crucial foundation for subsequent research on the long-term valuation of energy and climate benefits.

The economic indicators—K_RB (cost of a new building), W_GB (cost of an existing building), and K_ST (cost of thermal modernization to the current W_T (2024) energy standard)—are presented in

Table 6. Economic indicators for energy efficiency improvement investments in Gubin Zone S_I.

No.	Construction Year	Heated Area [m2]	KRB [USD]	Wz	WGB [USD]	KST [USD]	KST/WGB [%]
1	1945	603.2	1.08 × 106	0.47	5.11 × 105	5.68 × 105	111
2	1945	221.4	3.96 × 105	0.47	1.87 × 105	2.09 × 105	111
3	1945	336.2	6.01 × 105	0.47	2.85 × 105	3.17 × 105	111
4	1964	2676.0	4.79 × 106	0.50	2.39 × 106	2.39 × 106	100
5	1975	3444.0	6.16 × 106	0.59	3.64 × 106	2.51 × 106	69
6	1920	807.0	1.44 × 106	0.34	4.93 × 105	9.50 × 105	193

Note: The standard version is defined as the thermal modernization version compliant with the legal status as of the fourth quarter of 2024. The unit price index (C_jq) was adopted at 1788.14 USD/m², according to data from the Polish Central Statistical Office (GUS).

,

Table 7. Economic indicators for energy efficiency improvement investments in Gubin Zone S_II.

No.	Construction Year	Heated Area [m2]	KRB [USD]	Wz	WGB [USD]	KST [USD]	KST/WGB [%]
1	1962	763.0	1.36 × 106	0.59	8.00 × 105	5.64 × 105	70
2	1970	2380.0	4.26 × 106	0.64	2.72 × 106	1.53 × 106	56
3	1971	1338.0	2.39 × 106	0.65	1.55 × 106	8.45 × 105	55
4	1974	1907.0	3.41 × 106	0.67	2.27 × 106	1.14 × 106	50
5	1984	1151.5	2.06 × 106	0.64	1.32 × 106	7.41 × 105	56
6	1987	3328.0	5.95 × 106	0.66	3.93 × 106	2.02 × 106	52

Note: The standard version is the thermal modernization version as of the legal status in the fourth quarter of 2024. C_jq was adopted at 1788.14 USD/m2 according to the Central Statistical Office (GUS).

and

Table 8. Economic indicators for energy efficiency improvement investments in Gubin Zone S_III.

No.	Construction Year	Heated Area [m2]	KRB [USD]	Wz	WGB [USD]	KST [USD]	KST/WGB [%]
1	1920	2483.7	4.44 × 106	0.34	1.52 × 106	2.92 × 106	193
2	1975	672.0	1.20 × 106	0.67	8.09 × 105	3.93 × 105	49
3	1980	4284.8	7.66 × 106	0.59	4.53 × 106	3.13 × 106	69
4	1998	806.0	1.44 × 106	0.78	1.13 × 106	3.12 × 105	28
5	2000	245.0	4.38 × 105	0.80	3.50 × 105	8.76 × 104	25
6	2009	197.4	3.53 × 105	0.88	3.09 × 105	4.41 × 104	14

Note: The standard version refers to the thermal modernization compliant with legal status as of the fourth quarter of 2024. The unit price index (C_jq) was adopted at 1788.14 USD/m², according to data from the Central Statistical Office (GUS).

.

• Zone I—the historic center of the city (Old Town area)

For buildings in Zone I, as illustrated in Figure 5 (and detailed in Table 6), the average K_ST/W_GB ratio is greater than 100%. This ratio indicates that the costs of adopting the building to the K_ST standard exceed the discounted value of the existing property (W_GB). Consequently, in such cases, demolition or full reconstruction should be strongly considered.

Conversely, thermal modernization is economically justified for buildings where the K_ST/W_GB ratio is below 100%, as the costs of raising the K_ST standard are lower than the discounted value of the building. Furthermore, for buildings where the technical degradation factor (W_z) is near 0.5, thermal modernization may also be an alternative solution to increase the energy standard above class G, provided the K_ST costs remain below the building’s value. This comparative economic approach is crucial for planning municipal expenditure on improving the energy efficiency of built-up areas.

Buildings in Zone I are among the oldest in the city, with most constructed prior to 1945. Their technical degradation factor (W_z) ranges from 0.34 to 0.59, a clear consequence of their age and construction technology. This range places the analysed buildings in a critical decision space, balanced between options for demolition, major renovation, and thermal modernization.

Crucially, for these structures, the ratio of investment costs to achieve the K_ST energy standard (K_ST/W_GB) ranges from 111% to 193% of the existing building’s value. In contrast, younger buildings with similar technologies exhibit a significantly smaller share of K_ST costs, at only 69% of the base value.

• Zone II—buildings supplied from a central heating plant, primarily utilizing large-panel construction technology

In Zone II, a representative sample housing estate composed of multi-family buildings constructed using the prefabricated WK-70 large-panel technology was selected.

It is important to note the existence of many other construction systems originating in Poland in the 1960s. The mass production of prefabricated elements in systems such as Wk-70, WUF-T 67, OWT-75, WWT-69, the Szczecin System, and others [69,70,71] was widespread between the 1960s and 1980s, primarily in industrial cities. Currently, this type of building construction is beginning to reemerge after a long hiatus, as presented in Table 7.

In Zone II, as shown in Figure 6, the majority of the analysed buildings exhibit a technical degradation factor (W_z) between 0.59 and 0.67, which indicates a good potential for improving energy efficiency. Prefabricated buildings utilizing large-panel technologies are the most widespread type of multi-family housing in Poland and many other Eastern European countries. Notably, between 2000 and 2012, many of these buildings underwent an initial phase of thermal modernization. However, these older modernizations often no longer meet current energy requirements and necessitate further investment. The subsequent comparative analyses will assess the economic value of selected variants for these necessary thermal modernization projects.

For multi-family residential buildings in the Żerań and W-70 large-panel systems, the share of costs for adaptation to the K_ST/W_GB ratio energy standard, in accordance with the W_T (2024) technical conditions, is distributed at a level of 52–70% of the existing building’s value (W_GB). This percentage represents the required level of additional investment that will translate into significant long-term economic and environmental benefits for residents over the building’s remaining service life.

• Zone III—buildings supplied with natural gas, comprising structures of various technologies and ages

Among the surveyed buildings supplied with natural gas, we can distinguish between older structures built with traditional technologies, which typically exhibit a higher technical standard, and those recently constructed in accordance with contemporary energy standards (Table 8).

These buildings also exhibit the highest technical degradation factors (W_z), averaging above 0.5 and ranging from 0.34 to 0.88. This high W_z range indicates a good investment potential for improving their energy efficiency. The general trend shows that newer buildings possess greater potential, meaning the costs of energy improvement are proportionally lower (see Figure 7).

Research indicates that the percentage share of costs required to adapt buildings to the new energy requirements (K_ST/W_GB) in the zones exhibiting better technical standards is directly correlated with building age. Specifically, the ratio is highest for the oldest structures, reaching 193.0% for buildings constructed before 1945, but drops to less than 14% of the existing building’s value for structures built after 2009.

4. Discussion

In accordance with the research process in Figure 2, Stage V of the study focused on a cost–benefit analysis (CBA) of the environmental gains resulting from the costs required to raise the energy standards of buildings.

Each of the urban development zones studied has a distinct building typology, which was examined regarding the potential economic feasibility of deep renovation [72]. This feasibility is illustrated by the K_ST indicators calculated for current energy standards. The benefits of thermal renovation translate into: increased property value, lower operating costs and CO₂ emissions, and improved thermal and health comfort for residents.

Improving the energy efficiency of buildings directly impacts their certification class [2]. The K_ST costs for Zone I (red zone) primarily involve the transition from Class G to higher classes; however, achieving the B/A level may prove difficult and requires an individualized approach for each property.

When analysing environmental benefits across the urban development zones, the average CO₂ emission rates resulting from primary energy (EP) consumption were used. Environmental studies show the average primary energy consumption (EP_j) and carbon footprint (EE_j) of buildings in urban development zones are as follows [30,60,73]:

• Zone I: average EP of buildings (EP_I) = 433.93 kWh/m²/year, CO₂ emission factor (EE_I) = 0.129 Mg/m²/year;
• Zone II: average EP of buildings (EP_II) = 152.8 kWh/m²/year, CO₂ emission factor (EE_II) = 0.048 Mg/m²/year;
• Zone III: average EP of buildings (EP_III) = 97.79 kWh/m²/year, CO₂ emission factor (EE_III) = 0.031 Mg/m²/year.

Considering the objective of improving building energy efficiency to at least Class B (current requirement EP = 70 kWh/m²/year), in accordance with the EU directives (EPBD, EED) and with support from EU economic aid funds and public acceptance and partial participation, at least two possible environmental gain scenarios can be outlined.

• Scenario I

This scenario assumes full thermal modernization, or deep renovation, committing maximum financial resources (i.e., 100% K_ST) to achieve the greatest environmental gains. The resulting environmental effects for the individual zones in Scenario I are as follows:

• Zone I: The primary energy indicator (EP_I) will decrease from 433.93 to 70.00 kWh/m²/year. Correspondingly, the CO₂ emission factor for the zone (EE_I) will decrease from 0.1290 to 0.0208 Mg/m²/year, representing a reduction factor of 6.2 times.
• Zone II: The primary energy indicator (EP_II) will decrease from 152.8 to 70.00 kWh/m²/year. The CO₂ emission factor for the zone (EE_II) will decrease from 0.0480 to 0.0218 Mg/m²/year, representing a reduction factor of 2.2 times.
• Zone III: The primary energy indicator (EP_III) will decrease from 97.79 to 70.00 kWh/m²/year. The CO₂ emission factor for the zone (EE_III) will decrease from 0.0310 to 0.0221 Mg/m²/year, representing a reduction factor of 1.4 times.

• Scenario II

This scenario assumes partial thermal modernization aimed at meeting the minimum requirements of programs that finance the energy transition of buildings. This involves achieving an energy effect corresponding to a 30–50% reduction in primary energy (EP) indicators compared to the existing state [2,4,60,73,74].

Assuming a 50% reduction in EP_j for buildings across all zones (j), the resulting environmental effects are as follows:

• Zone I: The primary energy indicator (EP_I) will decrease from 433.93 to 216.96 kWh/m²/year. Consequently, the CO₂ emission factor (EE_I) will decrease from 0.1290 to 0.065 Mg/m²/year, achieving a reduction factor of 2 times.
• Zone II: The primary energy indicator (EP_II) will decrease from 152.8 to 76.40 kWh/m²/year. The CO₂ emission factor (EE_II) will decrease from 0.0480 to 0.0240 Mg/m²/year, achieving a reduction factor of 2 times.
• Zone III: The primary energy indicator (EP_III) will decrease from 97.79 to 48.90 kWh/m²/year. The CO₂ emission factor (EE_III) will decrease from 0.0310 to 0.0155 Mg/m²/year, achieving a reduction factor of 2 times.

The environmental benefits resulting from the thermal modernization of buildings in urban areas can be quantitatively assessed using the simple cost-effectiveness–environmental benefit (CEE_bj) indicator. This indicator compares the modernization costs K_STj with the final post-modernization emission indicators (EE_bj), assuming the transition from Class G to B:

$${\mathrm{C}\mathrm{E}\mathrm{E}}_{\mathrm{b}\mathrm{j}}={\displaystyle \frac{{\mathrm{K}}_{\mathrm{s}\mathrm{t}\mathrm{j}}}{{\mathrm{E}\mathrm{E}}_{\mathrm{b}\mathrm{j}}}}[\mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{M}\mathrm{g}/{\mathrm{m}}^2/\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}]$$

(9)

Figure 8 illustrates the optimal cost-effectiveness–environmental benefit (CEE_bj) for zone j = I.

An analysis of Scenario II indicates that a significant number of buildings, particularly those in Zone I, are unlikely to meet the Class D standard (150–200 kWh/m²/year). However, the remaining buildings are expected to fall within Classes B and A.

This outcome clearly demonstrates the need for EU economic support programs to raise the energy performance threshold requirements to a minimum EP improvement of 60% for existing Class G buildings.

The environmental benefits, as quantified by the cost-effectiveness–environmental benefit (CEE_bj) indicator (Figure 8), are derived from the transformation of buildings from energy Class G to Classes B and A, and in certain favourable cases, to Class A. These benefits also significantly impact the cost levels associated with CO₂ emissions in urban areas. The CEE_bj economic and environmental indicators can provide valuable insights to support the development of sustainable urban transformation policies [75,76,77,78]. Finally, research indicates a direct correlation between urban community economic disadvantage and the technical condition of the buildings they occupy [4,74,79,80,81].

5. Conclusions

In accordance with the ASEET assessment methodology, all procedures were successfully carried out, spanning from Stages I-II to Stages III-V of the study, as outlined in Figure 2. The key findings are summarized below:

1.

Technical Assessment (Stages I and II):

The technical wear of the buildings in the study zones (S_I-S_III) was assessed, and the results are as follows:

• Zone I: The technical wear degree (S_zt) of the surveyed buildings ranged from 53% to 66%, placing these structures in the category requiring the highest proportional renovation costs.
• Zone II: The S_zt indicators ranged from 33% to 41%. This range is significantly more favourable for renovation than Zone I, thus greatly increasing the cost-effectiveness of thermal modernization projects.
• Zone III: The S_zt for surveyed buildings was assessed across a broad range, from 13% to 66%, depending on the building type. Such a wide technical variation mandates an individualized approach when considering investment and environmental priorities.

Based on the S_zt results, the technical degradation factors (W_z) for the zones were calculated, which are essential inputs for determining the economic indicators of urban development.

2.

Economic Assessment (Stages III and IV):

The modernization cost (K_ST) economic indicators were calculated for building thermal modernization based on the determined data (K_RB and W_GB). The K_ST indicators, combined with the W_z factors, provide a clear analytical picture of thermal modernization costs:

• Zone I: Average K_ST costs for thermal modernization exceed 100% of the value of existing buildings (W_GB), suggesting that demolition or reconstruction should be considered.
• Zone II: Average K_ST costs range from 50% to 60% of the W_GB, indicating strong economic justification for deep renovation.
• Zone III: Average K_ST costs range from 10% to 50% of the W_GB, depending on the construction date. This zone generally possesses the best technical infrastructure.

3.

Environmental Assessment (Stage V):

An assessment of the impact of thermal modernization on the urban environment was conducted by comparing K_ST costs with the resulting emission reduction limits (EE_j). Two potential environmental scenarios were analysed:

• Scenario I (deep renovation): Assumes the use of 100% K_ST funds for deep thermal modernization, achieving the maximum environmental impact (a transition from Class G to Class B). For Zone I, this effect results in at least a six-fold reduction in EE_I emissions.
• Scenario II (partial renovation): Assumes K_ST costs are adjusted to meet minimum requirements (a 30–50% reduction in the EP indicator). The study assumed a 50% EP reduction, resulting in only a two-fold reduction in the EE_j emission indicator across the zones.

The study indicates that while adopting solutions from Scenario II is less costly for city budgets, more radical actions from Scenario I should be prioritized due to their significant positive impact on the environment and public health. The analysis confirms the utility of the cumulative cost-effectiveness–environmental benefit (CEE_bj) indicator (Figure 8) for illustrating K_ST costs as ecological benefits resulting from reduced EE_j emissions, thereby aiding in the management of public funds.

Limitations and Future Research

This study has several limitations, including its focus on a single case study in Gubin, reliance on survey and inventory data, partial quantification of non-market externalities, and assumptions regarding carbon pricing, resident participation, and policy stability. Future research should expand the methodology to diverse urban contexts, integrate high-resolution data (e.g., digital twins, smart meters), refine life-cycle and carbon accounting, and more deeply examine behavioural and governance barriers. Additionally, a supplementary analysis to encompass architectural and social benefits represents a potential avenue for research. Comparative studies across countries and the integration of circular economy principles and smart urban systems will further enhance the robustness and applicability of the framework.