Environmental Assessment of Residential Space Heating and Cooling Technologies in Europe: A Review of 11 European Member States

Abstract

Greenhouse gas emissions have reached critical levels and climate change is threatening the globe. Thus, the space heating and cooling sector is striving to decarbonize assets through higher efficiency and renewable energy adoption for 2030 and 2050. This article reviewed data about the environmental impact and the primary energy consumption of 27 space heating and cooling technologies for the residential sector as if they were adopted in 11 different European member states: Austria, Cyprus, Denmark, Estonia, France, Germany, Italy, Poland, Romania, Spain, and Sweden. Direct emissions from the machineries and upstream indirect emissions from the energy carriers were considered. The analysis indicates that the adoption of renewable energy-powered technologies should be prioritized due to the significantly lower emissions related to these technologies. Notably, the emissions of electricity-powered technologies, if not driven by the direct self-consumption of renewable energy systems, highly depend on the region of adoption: in specific cases, such as in Poland, Cyprus, and Estonia, they can even exceed the emissions of coal-powered technologies. These countries should speed up the adoption of decarbonization policies regarding the residential sector to close the gap with the other EU member states and provide their contribution to the EU climate change goals.

1. Introduction

After the COVID-19 pandemic and just five years after the adoption of the Paris Agreement [1], global energy-related greenhouse gas (GHG) emissions have rebounded, rising by 6% in 2021 to about 36 billion tons, their highest level ever. In this growth, coal accounted for over 40%, while natural gas overtook its 2019 emissions, reaching 7.5 billion tons of CO₂. Still, in advanced economies such as the United States, Japan, and the European Union (EU), emissions did not rebound as sharply as in China, signaling an enduring trajectory of structural decline [2]. Indeed, via the Climate & Energy Package (2009), the EU Member States (MSs) had committed to reduce their GHG emissions by at least 20% by 2020 compared to 1990 levels. This Package also set two more targets: improving energy efficiency by 20% throughout the most energy-consuming technologies and making renewable energy reach a 20% share of the overall quantity of energy produced. The aforementioned targets have been reached and increased further as part of the European Green Deal [3]. With the European Climate Law [4], the EU has set itself a binding target of achieving climate neutrality by 2050, with the intermediate target, present under the proposed Fit for 55 [5] package, of also reducing net GHG emissions by 2030 by at least 55% compared to 1990 levels.

In 2021, the European Commission (EC) proposed to amend the Renewable Energy Directive (RED) [6] in order to increase the current target of 32% renewable energy sources in the total European energy mix to a minimum of 40% by 2030. In addition to this, the Russian invasion of Ukraine and the global energy market disruptions that it caused further showed the urgency to transform Europe’s energy system. An increase in Europe’s energy independence from volatile fossil fuels and unreliable suppliers was shown to be crucial, and the REPowerEU Plan represents the plan to reach this goal. The plan establishes a need to diversify energy imports, to reach energy savings of 13% and, finally, to once again raise the RED renewable energy target to 45% [7]. The progression of the aforementioned targets is illustrated in Figure 1.

It is worth mentioning that in 2018, the EU27+UK primary energy consumption (PEC) accounted for about 1600 Mtoe/year and the heating and cooling (H&C) section was the main base of energy consumption [9]. The latter, if we refer to the tertiary and residential sectors, is composed of space heating (SH), space cooling (SC), and domestic hot water (DHW), while it considers process heating (PH) and process cooling (PC) for the industrial branch. Overall, the sum of the above-mentioned sectors accounted for more than half of the entire PEC in 2018, with more than 800 Mtoe/year [10].

According to the above stated reasons, the European Commission has been paying great attention to the H&C topic and considers it a promising sector to be linked to renewable energy and optimized in terms of energy efficiency and decarbonization. Due to this, in the past few years, numerous studies have been supported for obtaining useful data and information for the European strategies, for example, through the Horizon 2020 Hotmaps project [11], EC [12], Directorate-General for Energy [13], and JRC [14,15]. Numerous scientific papers also tackled these themes but focused mainly on the H&C market or on a single type of building or technology: Pezzutto et al. [10], Ismail et al. [16], Fleiter et al. [17], and Scoccia et al. [18] are examples of them.

Our study was carried out in the framework of the ENER/2020/OP/0019 Pathways for Energy Efficient Heating and Cooling tender [19] and created a database containing information covering CO₂ equivalent emissions and the primary energy consumption of 12 end-use heating technologies, 12 district heating technologies, and 3 space cooling technologies. All of them were explored for each of the 11 European Member States investigated: Austria, Cyprus, Denmark, Estonia, France, Germany, Italy, Poland, Romania, Spain, and Sweden.

Table 1. The list of technologies in the scope of the analysis. Please note that CHP stands for combined heat and power plants.

End-Use Heating Technologies	District Heating Technologies	Cooling Technologies
Liquid fuel boilers	Coal-fired district heating plant (non-CHP)	Space cooling systems (air-conditioning)
Coal-fired boilers	Gas-fired district heating plant (non-CHP)	District cooling
Gas-fired boilers	Biomass-fired district heating plant (non-CHP)	Thermally driven heat pumps
Biomass boilers	Efficient district heating plant (Geothermal)
Combined solid fuel 1 boilers	Efficient district heating plant (Solar)
Solar thermal	Efficient district heating plant (using heat pump)
Solar PV-driven heat pumps	Efficient district heating plant (using CHP)
Geothermal installations	Efficient DH (using waste heat)
Heat pumps (HPs)	DHP utilizing thermal storage
Electric heating	Low-temperature district heating network (DHN)
Hydrogen boilers	High-temperature district heating network (DHN)
Micro-CHP (natural gas)	District heating plant (DHP) utilizing solid waste

¹ Combined solid fuel refers to biomass-based material, such as wood or pellet.

lists the technologies considered in this study.

The central research question of this study involves determining the emissions generated by the H&C technologies employed in 11 EU MSs, with a focus on identifying the technologies that may require prioritization in order to achieve the European climate objectives. This objective of this paper is to perform a comparative examination of the combination of technologies, energy sources and energy carriers, considering the potential impact of emissions and the consumption of renewable energy and fossil fuels. The results plan to provide precious insights into the most recent space H&C practices across Europe, enabling informed decision-making at the European, national, local, and individual levels to mitigate the current climate crisis and reach the EU climate targets.

Section 2 includes the materials and the methodology supporting the study, with detailed data and information gathering; Section 3 specifies the primary outcomes in findings and figures; Section 4 critically evaluates the top results; and Section 5 provides the conclusions with potential future implications and recommendations.

2. Materials and Methods

The aim of this section is to explain the methodology and materials used to create a comprehensive database of space H&C technologies, for which several parameters needed to be investigated concerning each technology for every building stock category, for all the EU11 countries.

2.1. Structure of the Dataset

The database structure was built by inspecting the space H&C sector for each EU11 MS (Austria, Cyprus, Denmark, Estonia, France, Germany, Italy, Poland, Romania, Spain, and Sweden), as presented in Figure 2 below.

Various factors were considered in the preparation of the assortment of the involved MSs in the current study: geographical areas, a great coverage of the European population, various needs of space H&C, and percentages of final energy consumption types. For this study, Southern Europe includes Cyprus, Spain, and Italy; Eastern Europe includes Estonia, Poland and Romania; Western Europe includes France, Central Europe includes Germany and Austria; and Northern Europe includes Sweden and Denmark. Moreover, the distribution of the EU11 MSs allowed the researchers to strengthen the data scouting of the technologies based on different energy needs due to the variety of climate zones covered. The EU11 zone collects more than 75% of the entire European population, which, according to Fleiter et al. [17], emerged as the most energy-intensive MSs of the EU27+UK aggregate. In addition to this, it is important to observe that the number of EU MSs analyzed in this study is 11 because it aligns with the criteria stipulated in the tender that served as the foundation for the research presented in this paper.

The collected data were divided into data on a national level and data on an average EU11-level scale. The latter was computed using an in-house Python program that calculates a weighted average based on the population of the EU11 MSs taken from Ref. [20].

Data were arranged by building type and sector, such as the residential and the service sector, by including the classes presented below [21].

The residential segment was organized according to the following building typologies:

• Single-family houses (SFHs—containing 2–3 floors);
• Multifamily houses (MFHs—containing 4–8 floors);
• Apartment blocks (Abs—containing >8 floors) [22].

Based on the following building typologies, the service portion was split among:

• Offices (composed of public and private offices and office blocks);
• Trade (department stores, shopping centers, individual shops, grocery shops, car sales and garages, bakeries, hairdressers, laundries, service stations, congress and fair buildings, and other retail and wholesale infrastructures);
• Education (primary, secondary and high schools—furthermore, universities, school dormitories, research centers/laboratories and infrastructure for professional training activities are included this section);
• Health (public and private hospitals, nursing homes and medical care centers);
• Hotels and restaurants (hostels, hotels, pubs, cafés, restaurants, canteens and catering in business);
• Other non-residential buildings (transportation and garage buildings, warehouses, agricultural buildings (greenhouses, farms), military barracks and sports facilities (e.g., swimming pools, sports halls and gyms) [23].

Since this scientific article will focus mainly on the SFHs, it should be clarified that the aforementioned subdivisions were created to fulfill the data needs of the ENER/2020/OP/0019 Pathways for Energy Efficient Heating and Cooling tender.

Moreover, it is crucial to specify that the space H&C technology sector was sorted into the three main categories, as presented below:

• End-use heating technologies;
• District heating technologies;
• Cooling technologies.

Overall, the end-use heating technologies and the district heating (DH) technologies are associated with the heating sector, while the cooling technologies involve the air-conditioning sector.

The examined technologies are presented for each category in Table 1 above. Twelve end-use technologies applied for space heating have been investigated, as well as another twelve DH technologies. Regarding the space cooling section, three types of technologies were explored.

Section 2.2.2 below reports all the sources containing information regarding the functioning and general characteristics of each specific technology mentioned in Table 1.

For each technology, several parameters were considered fundamental for the current data collection. They were divided and are presented as follows:

• Technical parameters;
• Environmental parameters.

In more detail,

Table 2. Environmental parameters for the investigated heating and cooling technologies.

Environmental Parameters
Factors	Description	Unit
CO2 equivalent	Measure used for the comparison of emissions of different GHGs based on their global-warming potential (GWP), by converting amounts of other gases to the equivalent amount of CO2 [24]. The indicator is calculated per 1 kWh of heat or cooling supplied.	g/kWh
Primary Non-Renewable Energy	Energy found in nature that has not been subjected to any human engineered conversion or transformation process, which will be required by the energy sector to generate the supply of energy carriers used by human society. Primary Non-Renewable Energy is related to oil, natural gas, coal and nuclear [25]. The indicator is calculated per 1 kWh of heat or cooling supplied.	MJprim per kWh
Primary Renewable Energy	Similar to above, but in this case, it is related to any form of renewable energy source, which are energy sources that naturally renew or replenish themselves on a human timescale. They include solar, wind, geothermal heat, waste heat, biomass energy and hydropower energy [25]. The indicator is calculated per 1 kWh of heat or cooling supplied.	MJprim per kWh

and

Table A1. Technical parameters for the investigated heating and cooling technologies.

Technical Parameters
Factors	Description	Unit
Energy source/s	They can be defined as sources such as oil, coal, air, groundwater, etc., which can be used to provide power for H&C types of machinery. The definition also involves alternative/renewable energy sources such as wind, waste heat, sun, geothermal heat, etc.	-
Energy carrier/s: input (fuel) output	It can be assessed as a transmitter of energy such as heat, cold and electricity as well as liquid, solid, gaseous fuels, etc. At the H&C machinery, the level occupies intermediate steps in the energy-supply chain between primary sources and end-use applications.	-
Efficiency	It can be defined as the ratio of the useful energy delivered by the H&C system to the energy supplied to it. It can be found as the Seasonal Performance Factor (SPF), Seasonal Energy Efficiency Ratio (SEER), Coefficient of Performance (COF), thermal efficiency, etc., depending on the technology type.	-

, in the Appendix A, present the investigated parameters per category for each space H&C technology and EU11 MS.

Overall, Table 2 and Table A1 have been combined with each EU11 MS building type and sector, creating as an outcome the template that is presented in

Table A2. Template structure utilized for data collection.

End-Use Heating/District Heating/Cooling Technology
EU11 Member State
Sector	Residential			Service
Building Type	SFHs	MFHs	ABs	Offices	Trade	Education	Health	Hotels and Restaurants	Public Buildings
Technical parameter
Energy source/s
Energy carrier/s: - input (fuel) - output
Efficiency (SEER, SPF, COP, etc.)
Environmental parameter
CO2 equivalent g/kWh
Primary Non Renewable Energy (MJprim per kWh)
Primary Renewable Energy (MJprim per kWh)

in Appendix A.

2.2. Literature Review, Data Collection, Processing and Validation

In this section, a literature review has been executed by examining relevant data/information sources. Data collection, processing, and validation phases are presented based on detailed relevant literature sources. Different aspects such as definition of the boundaries of the analysis to meet the comparability purposes of the evaluation, data inventory and collection, and data reliability have been considered in the current phase to ensure the quality of the gathered data/information.

2.2.1. Boundaries of the Evaluation (Data Comparability)

Even though most data providers adopt standardized data units and formats, this does not necessarily mean that data are fully comparable. Thus, attention attention has been given to data definition and comparability. Adjusting differences and inconsistencies among different measures, methods, assumptions, time references and specifications to improve data comparability is indeed one of the most meaningful aspects of the whole process of data elaboration. Data for the most recent year were collected for each country, with preference for data not older than 2018. The assembled data and information refer to the reference year by source. The developed datasets, including the documentation in this project, were expected to improve the data quality of existing data and provide the information required to track the development of space H&C technology utilization in various sectors and subsectors, respective energy carriers and sources, CO₂ emissions, etc., moving towards the realization of the decarbonization goals depicted by the EC for 2030 and 2050 and mentioned in the introduction.

Regarding the methodology for environmental parameters, the functional units of this study coincide with the unit of measure of the environmental parameters described in Table A2, and they are, respectively, gCO₂e/kWh and MJprim/kWh. It should be noted that “kWh” refers to the useful thermal energy generated for space H&C purposes. The definition of system boundaries has also been pivotal. The lifecycle phases included in this study are focused on the energy carriers used by the analyzed technologies. The extraction of raw energy carriers and their refining processes were included in the boundaries in order to consider the upstream supply chain. In addition to this, the use phase of the energy carriers in the space H&C technologies was also considered. The manufacturing, transportation and disposal of space H&C machineries and auxiliary components were thereby excluded by this study, together with biogenic carbon. Following the just-mentioned methodology, all the energy from renewable energy sources had zero CO₂ emissions. Waste heat, due to its “unavoidable” nature, was also considered to have zero emissions [26]. Figure 3 below illustrates the lifecycle phases included within the aforementioned boundaries.

2.2.2. Data Collection

The production of an exhaustive list of all existing data providers was one of the major challenges concerning the development of an inventory of data and information for space heating and cooling technologies with the respective characteristics in different sectors and subsectors per country for each technology. In more broad terms, the advantage of using data coming from EU27+UK projects and EU27+UK-wide information providers is that these are available for a large territory. Concerning the latter, HotMaps [27], Dittmann et al. [28], Danish Energy Agency [29], Invert/EE-Lab [30], EU Building Stock Observatory [31], Tabula [32], Statistics Estonia [33], Statistics Denmark [34], Foresight [35], INSEE [36], Statistics Sweden [37], Terna Driving Energy [38] and European Statistical System [39] were identified as exemplary sources. It is worth mentioning that the information inspected was never found to be fully detailed and complete. As a result, in order to increase data availability and coverage, it was necessary to scout data from national sources. In particular, in this section, we detailed the data utilized to fill the cells of Table A2 for EU11 MSs, space H&C category, sector, building type, and technology. Moreover, to fill data gaps and complete the data inventory, it was crucial to assemble and extrapolate data from the large aforementioned data tools and also to research data source-by-source from single scientific literature studies such as project deliverables, journal papers and conference proceedings. These have been properly referenced below. Moreover, one essential element of the data inventory was to ensure that the information could be interpreted and grasped accurately by any user. Therefore, a compilation of understandable metadata descriptions, annotations, contextual documentation, and information was required. Following these principles, this data collection subsection presents source-by-source data and information concerning the technical and environmental parameters.

For the current study, Fleiter et al. [17] has been a noteworthy source; this work provided data at the country level on the different capacities installed for certain end-use technologies, DH technologies and cooling technologies. The latter author was also useful for understanding the net total efficiency for technologies such as biomass-fired DHP (non-CHP), coal-fired DHP (non-CHP), DH utilizing urban solid waste, DHP utilizing thermal storage, efficient DH using waste heat, efficient DHP (geothermal), gas-fired DHP (non CHP) and high-temperature DHN. Again, from Fleiter et al. [17], other parameters such as energy efficiency, energy sources and energy carriers were identified. Dodds et al. [40] provided efficiencies for hydrogen boilers, and Lorenzo et al. [41] indicated the seasonal performance factor (SPF) for solar PV-driven heat pump installations in both the residential and service sectors. Olabarrieta et al. [42] and Naicker et al. [43] provided the efficiencies for machineries such as biomass boilers, combined solid fuel boilers, coal-fired boilers, liquid fuel boilers, gas-fired boilers, and hydrogen boilers. The Danish Energy Agency [44] provided information on the energy carriers of hydrogen boilers, coal-fired boilers, gas-fired boilers, liquid fuel boilers, combined solid fuel boilers and biomass boilers, both for the residential and service sectors. In the guide provided by Goetzler et al. [45], the energy carriers of all the space cooling systems were specified. The thermal efficiencies for liquid fuel boilers and gas-fired boilers were provided by Vakkilainen et al. [46]. Furthermore, Zukowsky et al. [47] and Redko et al. [48] provided the efficiency values for solar thermal technology. Most of the missing parameters for DH technologies were obtained from: Danish Energy Agency [29], Fan et al. [49], and IPCC [50]. Regarding the data collection for space cooling technologies, the most notable source was EC et al. [51], which provided data at the country level. Demirel et al. [52] provided the seasonal energy efficiency ratio (SEER) for the thermally driven heat pump (TDHP) technologies, while the remaining values were again provided by EC et al. [51]. Finally, concerning the energy sources, Goetzler et al. [53] and EUROVENT [54] specified the input required.

Regarding the environmental parameters, the Research Center for Energy Economics [55] was relevant for providing the input for the CO₂ calculation involving the residential and service sector for liquid fuel boilers, gas-fired boilers, coal-fired boilers, micro-CHP (natural gas), coal-fired district heating plant (non-CHP), gas-fired DHP (non-CHP), efficient DHP using CHP, DHP using thermal storage and high-temperature DHN. This source also specified the primary energy factors needed for the computation of the primary energy consumption for heat pumps, electric heating, space cooling systems (air conditioning—AC), district cooling (DC), TDHPs and efficient DHP (using heat pump). When considering the last-mentioned technologies, the AIB (Association of Issuing Bodies) [56] provided the data needed for the calculation of the CO₂e emissions. Furthermore, Balcombe et al. [57] revealed the CO₂ emissions of hydrogen boilers, while Dones et al. [58] detailed those coming from biomass boilers, combined solid fuel boilers, low-temperature DHN and biomass-fired DHP (non-CHP). Concerning DHN utilizing urban solid waste, Hast et al. [59] provided the data needed.

Expert interviews were carried out to complete missing data that were not available in the scientific literature. Ten experts in the fields of research, consultancy and public administration were consulted to integrate the missing information. The data that were retrieved using this methodology referred mainly to efficiencies and both input and output energy carriers at the country level for DC, low-temperature DHN, efficient DH using waste heat, micro-CHP (natural gas) and hydrogen boilers.

Lastly, to complete the data inventory and fill the data gaps, in the data processing subsection below we present how the calculations were performed in order to derive the data and any information that was deemed to be unavailable during the literature review.

2.2.3. Data Reliability

A literature review was crucial to obtain technical data: the sources cited in Section 2.2.2. were able to meet expectations, and when specific values happened to not be available, expert interviews with national contact people fulfilled the missing information. In general, the aforementioned sources provided straight-to-use data for our research needs. It should be recalled that the gathered material, in particular the efficiencies of the machineries, provided the necessary information for the processing of environmental data.

Furthermore, significant effort has been put into complementing the missing data gaps through in-depth investigations and assessing the reliability of the gathered data. To ensure data reliability, the indications obtained per space H&C technology, building type, sector, and EU11 MS, were subject to a periodically made quality-check control of the constructed dataset. According to the latter, a draft of the data and information on building type, sector, space H&C technology and EU11 MSs was circulated inside the consortium for corrections and review. In addition, expert questioning was conducted to provide further sources and possible methodologies for data computations, to fill the remaining data gaps. The authors acknowledge the potential uncertainties inherent in the utilization of such a vast dataset. Nonetheless, they emphasize that the statistical significance of the final results, particularly with regard to the average values, remains robust, despite the possibility of limited uncertain data points. The precision of the analysis aligns with the scope and objectives of the project for which this research was conducted.

According to everything that has been stated above, the explored sources were classified per technology type. In particular, the data and information were collected from scientific papers, national datasets, reports, conference proceedings, etc., on the available technologies, for EU11 MSs, building categories and sector. Based on the aforementioned procedures, the template presented in Table A2 in Appendix A was filled for space H&C technology and EU11 MS.

2.2.4. Data Processing

This subsection presents the data processing. It should be noted that data were refined in a comparable manner. Attention was paid to the same units among equal parameters.

The analytical methodology for the primary energy and CO₂ emissions parameters is described in the following paragraphs.

The procedure for the calculation of MJprim/kWh of useful energy is divided into two different methodologies, based on the type of energy directly used by the system.

It follows the equations applied to calculate the MJ of primary energy per kWh of useful thermal energy for machineries needing electric energy from the grid [55].

$${\mathrm{E}}_{\mathrm{primary}}\left[{\mathrm{kWh}}_{\mathrm{primary}}\right]={\mathrm{E}}_{\mathrm{electricity}} \left[{\mathrm{kWh}}_{\mathrm{electricity}}\right]\ast \mathrm{PEF}$$

(1)

$${\mathrm{E}}_{\mathrm{primary}} \left[{\mathrm{MJ}}_{\mathrm{primary}}\right]={\mathrm{E}}_{\mathrm{primary}} \left[{\mathrm{kWh}}_{\mathrm{primary}}\right]\ast 3.6\left[\frac{\mathrm{MJ}}{\mathrm{kWh}}\right]$$

(2)

$${\mathrm{E}}_{\mathrm{primary}} \left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{ele}}}\right]=\frac{{\mathrm{E}}_{\mathrm{primary}} \left[{\mathrm{kWh}}_{\mathrm{primary}}\right]\ast 3.6\left[\frac{\mathrm{MJ}}{\mathrm{kWh}}\right]}{{\mathrm{E}}_{\mathrm{electricity}} \left[{\mathrm{kWh}}_{\mathrm{electricity}}\right]}=\mathrm{PEF}\ast 3.6\left[\frac{\mathrm{MJ}}{\mathrm{kWh}}\right]$$

(3)

$${\mathrm{E}}_{\mathrm{primary}} \left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]={\mathrm{E}}_{\mathrm{primary}} \left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{electricity}}}\right]\ast \frac{1}{\mathsf{\eta }}\left[\frac{{\mathrm{kWh}}_{\mathrm{electricity}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]$$

(4)

$${\mathrm{E}}_{\mathrm{primary}\mathrm{renewable}\mathrm{energy}}\left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]={\mathrm{E}}_{\mathrm{primary}}\left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{electricity}}}\right]\ast \%\mathrm{RE}$$

(5)

$${\mathrm{E}}_{\mathrm{primary}\mathrm{non}\mathrm{renewable}\mathrm{energy}}\left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]={\mathrm{E}}_{\mathrm{primary}}\left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{electricity}}}\right]\ast \%\mathrm{NRE}$$

(6)

In Equation (1), PEF represents an acronym that refers to the primary energy factor of each specific country [55]. This factor is calculated as the inverse ratio between the amount of delivered energy and the primary energy required to provide it. PEFs can legitimately differ between MSs since the primary sources may vary, as well as the amount of energy required for transportation or processing.

When focusing on Equations (5) and (6), % RE and % NRE stand, respectively, for the percentages of renewable energy and non-renewable energy in the national electricity production mix [55].

The values corresponding to the previously mentioned factors and percentages can be located in

Table 3. Primary energy factors and percentages of renewable and non-renewable energy in the national electricity production mix utilized in (1), (3), (5) and (6) [55].

Country	PEF [-]	%RE	%NRE
Austria	2.96	78	22
Cyprus	3.12	9	91
Denmark	3.55	65	35
Estonia	3.30	14	86
France	3.33	17	83
Germany	3.12	30	70
Italy	2.90	39	61
Poland	3.08	14	86
Romania	3.57	40	60
Spain	3.11	36	64
Sweden	3.55	63	37

presented subsequently.

For energy carriers that differ from the electricity coming from the grid, the methodology to obtain the primary energy consumption is described as follows. Considering that the overall efficiency of the system is obtained as a ratio between the final thermal energy (that is, the useful effect) and the energy used (that is, the energy input (which could consist of combusted material)), the latter can be considered primary energy.

$$\mathsf{\eta }=\frac{{\mathrm{E}}_{\mathrm{thermal}}}{{\mathrm{E}}_{\mathrm{in}}}\left[\frac{{\mathrm{kWh}}_{\mathrm{thermal}}}{{\mathrm{kWh}}_{\mathrm{primary}}}\right]$$

(7)

Which means:

$${\mathrm{E}}_{\mathrm{primary}}\left[\frac{{\mathrm{MJ}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]=3.6\left[\frac{\mathrm{MJ}}{\mathrm{kWh}}\right]\ast \frac{1}{\mathsf{\eta }}\left[\frac{{\mathrm{kWh}}_{\mathrm{primary}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]$$

(8)

Considering that the technologies that do not use electricity coming from the grid only consume a single type of energy, whether fossil or renewable, a mathematical distinction of these two primary energy calculation methods is not needed.

As the primary energy consumption calculation, the quantitative calculation process for the CO₂ equivalent per kWh of useful thermal energy is also divided into two different methodologies, based again on the type of energy used by the system.

In the case of electric energy from the grid, the CO₂ intensity of the national residual mix (rmix) is used to avoid double counting. The residual mix of a country depicts the shares of electricity generation attributes available for disclosure after the explicit tracking systems, as guarantees of origin (GOs), have been accounted for. Without a residual mix, renewable electricity sold with GOs would be double counted; this happens because the same electricity would be disclosed to consumers buying “regular” electricity [56].

$${\mathrm{CO}}_2\left[\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]={\mathrm{CO}}_{2\mathrm{rmix}}\left[\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{{\mathrm{kWh}}_{\mathrm{electricity}}}\right]\ast \frac{1}{\mathsf{\eta }}\left[\frac{{\mathrm{kWh}}_{\mathrm{electricity}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]$$

(9)

For coal, natural gas, heating oil, hydrogen and urban solid waste, values regarding the CO₂ intensity covering the generation and supply chain of these energy carriers can be found in [55,57], but are related to the lower heating value (LHV). Resultingly, a methodology akin to the above one has been adopted.

$${\mathrm{CO}}_2\left[\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]={\mathrm{CO}}_{2\mathrm{LHV}}\left[\frac{{\mathrm{g}}_{{\mathrm{CO}}_2}}{{\mathrm{kWh}}_{\mathrm{LHV}}}\right]\ast \frac{1}{\mathsf{\eta }}\left[\frac{{\mathrm{kWh}}_{\mathrm{LHV}}}{{\mathrm{kWh}}_{\mathrm{thermal}}}\right]$$

(10)

In the case of hydrogen [57] and urban solid waste [59], an average value has been utilized due to an extremely wide range of emissions.

Regarding biomass, source [58] provided the information needed. For this energy carrier, net emissions were considered and an average value was adopted because investigating the immense variety of biomass fuels present in all the EU11 MSs exceeded the aim of this study.

Finally, as has already been mentioned in Section 2.1, weighted results were computed based on each country’s specific population [20] following Equation (11).

$$f=\frac{{{\displaystyle \sum }}_{i=1}^{11}{f}_i\ast PO{P}_i}{{{\displaystyle \sum }}_{i=1}^{11}PO{P}_i}{ }_{ }$$

(11)

$f_i$ and $PO{P}_i$ refer, respectively, to the parameter and to the population of the specific country i of each of the EU11 MSs.

3. Results

The outcomes of the processing of the gathered information according to the methodology provided in Section 2 are presented in this section.

All the following graphs represent results regarding the technologies used for the space H&C of SFHs. The country-specific data obtained with the aforementioned methodology were weighted using the population of each of the EU11 countries; because of this, the following graphs are not fully representative of country-specific results, and a deeper look at the full database is suggested. Furthermore, regarding the unit of measure, kWh refers to the heating or cooling power provided by the machinery.

3.1. Efficiencies

Considering that the main aim of this article consists of assessing the environmental impact of space H&C technologies, the technical parameters for data gathering and processing were entirely conceived to obtain the internal results needed for the environmental parameters calculations, as detailed in Section 2.2.4. In virtue of this and for transparency, this subsection merely displays, in Figure 4, the technical results obtained via the weighting of the data directly taken from the sources in Section 2.2.2.

Here, the different efficiencies of the H&C equipment are illustrated based on the color-coding defined in the legend. We note that generally the efficiency is related to the heating or cooling production unit only. In case of the DHNs, the efficiency considers both the production unit and the transportation unit.

3.2. Primary Renewable Energy

Looking at the results in Figure 5 below, it is worth noting that for electric technologies, primary renewable energy consumption is related to the primary energy factor, the share of renewable energy in the power mix, and the efficiency of the machine. For systems powered entirely by renewable energy, the latest factor is the only influencing parameter. In terms of primary renewable energy consumption, solar PV-driven heat pumps and conventional heat pumps, due to high values of SPF, are two of the end-use heating technologies consuming the lowest amount of primary renewable energy, with values lower than 1.5 MJprim per kWh, together with geothermal installations. On the opposite side, combined solid fuel boilers, solar thermal, biomass boilers and electric heating (especially in Denmark, Italy, Sweden, and Austria) have been identified as the most intensive primary renewable energy machineries. Focusing on DH, efficient DHP (using HP) was again one of the most efficient technologies in terms of renewable energy consumption, alongside efficient DHP (geothermal). In contrast, efficient DHP (solar) and low-temperature DHN were the most demanding overall. The most intensive cooling technology in terms of primary renewable energy was space cooling air-conditioning, followed by DC and TDHPs. In particular, the weighted consumption of TDHPs is 0.01 MJprim per kWh, an almost negligible value. Liquid fuel boilers, micro-CHP (natural gas), gas-fired boilers, hydrogen boilers, coal-fired boilers, high-temperature DHN, DHP utilizing thermal storage, gas-fired DHP (non-CHP), efficient DH using CHP, and coal-fired DHP (non-CHP) are technologies that depend only on non-renewable energy sources, so there is no primary renewable energy consumption.

3.3. Primary Non-Renewable Energy

As seen in Figure 6 below, in terms of primary non-renewable energy, electric heating represents the most demanding technology, requiring on average 7.41 MJprim per kWh; non-renewable energy-intensive countries (such as Poland, Estonia, Romania and Cyprus) highly influence this result because of their national electricity mix.

3.4. Carbon Dioxide Equivalent Emissions

A comparison between the carbon dioxide equivalent (CO₂e) emissions of all the explored technologies was carried out, as presented below in Figure 7. Both in the case of DH and end-use heating technologies, coal-powered heat-production units are those with the highest emissions. As opposed to fossil fuel-powered technologies, biomass- and renewable energy-powered technologies represent the least-emitting heating solutions; solar PV-driven heat pumps, solar thermal, geothermal installations, efficient DH using waste heat, efficient DHP (solar) and efficient DHP (geothermal) all have zero emissions, while low-temperature DHN, biomass-fired DHP (non CHP), biomass boilers and combined solid fuel boilers have CO₂e emissions of just 16 g/kWh, considering the boundaries of this assessment. It should be noted that the average value displayed for electricity-powered technologies does not fully represent their decarbonization potential; if adopted in countries with a high share of renewable energy in the electricity mix, these technologies have emissions even lower than biomass-powered technologies, as resulted in the case of Sweden with heat pumps. In Poland and Cyprus, on the other hand, electric heating was the most-emitting heating technology across the EU11 MSs. Country dependency is not so significant for fossil fuel-powered heat-production units. Regarding the cooling technologies, SC, DC and TDHPs are electrically driven technologies, which means that in this case SEER is the key technical parameter that determines the difference in emission values. In addition to this, the power consumption of TDHPs was only a few percentage points compared to the total cooling capacity provided. This means an emissions weighted value of 1.53 g/kWh, the lowest among the cooling technologies analyzed.

3.5. Comparison of Country-Specific Grid Electricity-Powered Heating Technologies

In order to have a clearer view of the environmental impact of the adoption of electricity-powered heating technologies across the EU11 MSs, a comparison is needed. To do so, country-specific data of both DH and end-use heating technologies powered by electricity coming from the grid were plotted in Figure 8 below, and each technology is preceded by the European country code to which it refers. The efficient DHP (using heat pump) of Austria, Cyprus, Germany, Estonia, France, Poland, and Romania is not shown because these countries have not adopted this technology [17]. Electric heating has an enormous range of CO₂e emissions that extends from 23.14 g/kWh in Sweden to 798.68 g/kWh in Poland. Heat pumps, due to their efficiency, have emissions that are on average three-times lower when compared to the electric heating ones. Efficient DHP (using HPs), with an average efficiency of 3.75 against the HP efficiency of 2.91, is the least-emitting heating technology powered by electricity coming from the grid. Still, it is impressive to note that Sweden occupies three out of the four places of the least-emitting technologies; again, this happens because of the electricity mix of Sweden, which is the one with the highest share of renewable energy between all the analyzed countries. Furthermore, heat pumps used in Poland emit more than electric heating in Spain, Romania, Austria, and Sweden; this fact indicates that the higher efficiency of heat pumps in specific cases is not enough to overcome the pollution coming from the centralized production of electricity.

4. Discussion

In this study, the environmental impact of space heating and cooling technologies in 11 European member states was assessed for the direct and indirect emissions of their energy carriers, following the boundaries described in the Materials and Methods section. In general, it has been observed that renewable energy- and biomass-powered technologies have clearly lower emissions than all the other technologies. The purpose of this study was also to examine and challenge the prevailing notion that traditional fossil fuel-based heating systems consistently result in higher levels of pollution compared to electricity-powered heating technologies. This conviction, often diffused among decision-makers, is mainly based on the absence of direct emissions from the latter technologies. However, when taking into consideration indirect emissions, the graphs representing the results regarding the carbon dioxide emissions of space heating and cooling technologies and country-specific CO₂e emissions from grid electricity-powered heating units were able to clarify that, in specific cases, electric heating and heat pumps have higher emissions, within the boundaries of this study. Electric heating was, on average, the third-most-polluting technology, preceded only by coal-fired boilers and coal-fired DHP (non-CHP). Furthermore, in Poland, Cyprus, Germany, and Estonia, electric heating emits significantly more than the average of all the fossil fuel-powered space H&C technologies of the EU11 MSs. The utilization of heat pumps in the aforementioned nations has been found to result in emission levels that are nearly equivalent to those produced by gas-fired boilers. Concerning primary energy consumption, despite renewable energy-powered technologies having a higher utilization of primary energy, this should not prevent their wider adoption, due to the definition of renewable energy itself.

The examined nations retain the potential to make a significant contribution to the ongoing energy transition taking place in the residential sector of Europe, thereby advancing towards the attainment of the European Union’s goals related to mitigating the impacts of climate change. According to literature works [60,61,62], indeed, achieving the climate change goals will require phasing out natural gas and fossil-based technologies as well as electrifying (on a long-term basis) a large share of the residential sector, whether on a single-house level or on a collective level in energy communities. To ensure the environmental competitiveness of this process, renewable energy sources need to be continuously integrated into electricity production and dispatched into increasingly decarbonized grids. Different authors [63,64] have specifically demonstrated that it is only while electricity grid are decarbonized that heat pumps can reach emission factors lower than the ones characterizing traditional gas boilers.

From a policy perspective, the incentivization of the energy retrofitting of the building stock represents the first strategy to be implemented to create the prerequisites for heat pump installation. The deployment of energy conservation measures has been demonstrated to be an effective strategy to lower buildings’ energy requirements and facilitate the adoption of electrical low-temperature generation systems.

This process is particularly challenging in countries where the building stock is highly energy-intensive and where there is a very low availability of renewable energy sources that can be exploited for electricity production. In instances where the baseline scenario is characterized by a significantly suboptimal envelope or ventilation performance (e.g., for the residential stock realized before the publication of the legislation about energy efficiency in buildings), the implementation of a comprehensive energy retrofit that involves the installation of fully electrical systems can prove to be a challenging endeavor. Regardless, there is still an untapped leeway in EU countries that are still at the beginning of the decarbonization pathway, as confirmed by Thomaßen et al. [65].

Moreover, the large-scale electrification of the heating and cooling residential sector could require the modernization of the electricity grids to avoid bottlenecks, congestion problems, and capacity deficiencies [66] and to enhance the flexibility and connectivity of networks [67,68]. The implementation of this necessity, of which the costs are difficult to estimate, would require strong political support towards the promotion of the infrastructure upgrades that will be necessary to address the needs of an evolving energy network. Overall, in order to follow properly the CO₂ emission reduction strategies and reach the 2030 and 2050 European goals, the heating and cooling sector should be targeted with deeper studies. Addressing the research gaps, which include the identification and application of country-specific emission factors for hydrogen, biomass, and urban solid waste, constitutes a necessary step in the field, to gain a more comprehensive understanding of their environmental impact as energy sources for space H&C applications. This research covered the emissions related to the generation and use of the energy carriers utilized by the technologies, but in order to have a more exhaustive view of the environmental impact of these technologies, embedded carbon should be taken into consideration. A lifecycle assessment approach is thus recommended for every space H&C technology in every MS; this represents the perfect solution for obtaining comprehensive results that not only cover GHGs emissions but the full environmental impact during each life phase of the machinery. This method is also recommended for applications in the future for the industrial branch and for process heating and cooling.

Finally, in order to evaluate the effectiveness of the retrofits aiming at the electrification of the construction sector, a building scale LCA should be performed to properly consider the coupling between the building envelope and energy generation systems and between local renewable generation systems and energy grids [69,70,71].

5. Conclusions

Extreme weather events related to climate change, such as heat waves, and the general temperature increase due to global warming, are increasing the need for cooling equipment in Europe. This reality will result in an overall increase in national electricity consumption. As has happened in Italy and Germany during the summer of 2022, droughts forced the peaks of electricity demands to be covered mainly by electricity generation coming from scheduled or already decommissioned coal and gas power plants that were given a new lease of life. Episodes such as this diminish Europe’s ability to accomplish its 2050 objectives.

Despite that, this research aligns with the strategy of the REPowerEU Plan. When focusing on the reduction of primary energy consumption to reinforce Europe’s energy independence, heat pumps, whose extensive adoption is one of the pillars of the aforementioned strategy, were demonstrated to have lower weighted primary energy consumption than other end-use and district heating technologies, considering a combination of both primary renewable and non-renewable energy. On the emissions side, the final data were again in line with the RepowerEU Plan: heat pumps are characterized by emissions that are below those of conventional district heating and end-use space heating and cooling technologies. This should culminate in an overall future reduction of emissions from the space heating and cooling sector, as appointed by the European Commission.

Still, while providing influential insights into the emissions of space heating and cooling technologies, this study aimed at highlighting the crucial attention that decision-makers must pay to the country-specific energy-mix situation. The increase in energy efficiency and renewable energy share must be set as a priority in order to significantly decarbonize and improve resiliency in the energy generation sector, together with the heating and cooling sectors.