Introduction

The preventive conservation of cultural heritage is defined as “measures and actions aimed at avoiding or minimizing future damage, deterioration and loss and, consequently, any invasive intervention”1. The definition implicitly includes the role of such measures in safeguarding collections from the impacts of the changing climate2,3. However, in the context of the achievement of the Sustainable Development Goals (SDGs) and the European Green Deal, it does not consider the challenges related to the energy efficiency of collections facilities, meant as all spaces housing, exhibiting, and storing cultural collections. The “European Cultural Heritage Green Paper”, issued by Europa Nostra and ICOMOS, has acknowledged the potential of cultural heritage as a vital resource to drive transformative climate action (SDG 13) and to influence energy patterns hence supporting the green transition2. However, the progress toward climate neutrality and sustainable goals has been slowed down by insufficient research on the impact of climate change4 on energy demand of collections facilities, and consequently, on their management strategies5.

Collections facilities and all their related activities might actively contribute to accelerate actions towards the SDG 11 (Target 11.4—Strengthen efforts to protect and safeguard the world’s cultural and natural heritage) and the energy efficiency through the implementation of building renovation and circular economy6. Nevertheless, a survey conducted by the Network of European Museum Organisations (NEMO) in 2022 has revealed that more than half of the 578 surveyed EU museums has not climate-friendly or neutral infrastructures7. It follows the need to establish heritage commons to support collections facilities in a sustainable decision-making process for the preventive conservation tailored to geographical and environmental contexts. This issue has been also discussed in the latest Business Plan edited by the Technical Committee 346 (TC 346 – Conservation of Cultural Heritage) of the European Committee for Standardization (CEN)8 and acknowledged in the standards: EN 16141:20129, EN 16883:201710 and EN 16893:201811. These standards are oriented towards interventions for planning for any new or refurbished collection facilities accounting for their potential energy use and maintenance costs over the whole building life. Additionally, the collections facilities’ sufficiency of use is another aspect that needs to be addressed to deal with the growing urgency of a sustainable climate action compatible with heritage conservation5.

The conventional practice to keep a tight microclimate control to limit damage to collections, together with the use of facilities for visits12 and users travelling to the location11, results in high energy demand and greenhouse gas emissions13. For collections preserved in inefficient collections facilities (i.e., not climate-friendly or neutral infrastructures), this practice further increases the energy demand, thus being incompatible with the targets of the Green Deal14. In this context, interventions for the energy efficiency of these facilities via short- and long-term measures (e.g., coupling passive technologies with renewable energy sources and natural-based solutions) can be a solution according to the current European directives15,16. However, their implementation is challenging for heritage at both building- and district-scale if they are protected by law17. Additionally, most of the research contributions have dealt with single case studies, providing building-scale solutions18,19,20,21 rather than local- and global-scale indications for the future management programming22,23. The lower attention paid to energy-efficiency measures at cultural district, city and regional stocks has also been highlighted by the review conducted by Lidelöw et al.24: solutions are mainly aimed at modifying building envelopes and/or other elements25,26 or at implementing renewable energy sources13 and heating, ventilation, and cooling systems27,28, but only at the building scale. Additionally, the effects on the acclimatisation of artworks to their historical climate conditions29 and the adaptation of such measures to future outdoor climate conditions are rarely discussed30. To cite but a few, the rise in air temperature associated with global warming may be responsible for the increase of summer cooling in southern latitudes30,31,32, making the use of the so-called “conservation heating” unfeasible for the indoor dehumidification in northern latitudes33,34. An alternative approach to responsibly consume energy in collections facilities goes through the reanalysis of the intervention measures and the possibility to rediscuss the operational management practices for the microclimate control according to the specific requirements of people and collections. For example, organic and hygroscopic collections preserved in historic buildings might suffer from mechanical degradation if they are moved to facilities differing from the historical microclimate to which they have acclimatised29,35,36. Kramer et al.37,38 and Kompatscher et al.39 have demonstrated that relaxing the microclimate thresholds in museums and archives from strict to wider thresholds is beneficial for energy savings without compromising the collection safeguard. Silva et al.14 have demonstrated that relaxing the temperature control during closing hours can be beneficial to energy savings, but further research should be performed to relative humidity control. Indeed, the current scientific understanding of how collection materials respond to microclimate fluctuations is based on degradation models, which could be employed to identify alternative microclimate thresholds. Although these results are encouraging, no research has focused so far on discussing the possibility to consider ‘not-standardised’ microclimate thresholds in the facility management. This approach can be complementary to the thresholds issued by norms to mitigate the energy demand of collections facilities while tackling the impact of future outdoor climate conditions4.

The research aims to discuss the energy implications in collections facilities to satisfy the thresholds for the microclimate control according to values suggested by the standard EN 16893:2018 and three degradation models. To this purpose, weather-based indices (i.e., degree-days and gram-days) were computed to estimate the energy consumption potential trend of collections facilities in three EU cities in different climate zones. Then, the influence of the outdoor climate scenarios on these indices was explored to understand future challenges in the microclimate control activities for different collections and possible implications towards pursuing SDGs. This has allowed to create a database that can be used to estimate the energy demand at urban level. The discussion of the results considers the role of thermal comfort for visitors and personnel, the preservation of collections, and the changing climate scenarios.

Materials and methods

Since one of the key contributors to climate change is the growing demand for energy, this research explores the potential energy implications in climate control for collections facilities (i.e., the collection-oriented microclimate control) in four cases of temperature (T) and relative humidity (RH) thresholds in different outdoor climate scenarios throughout the twenty-first century:

  1. 1.

    T-RH thresholds from EN 16893:2018 where thermal comfort of people in wintertime is neglected favouring a collection-oriented climatization;

  2. 2.

    T-RH thresholds from EN 16893:2018 where thermal comfort of people in wintertime is considered;

  3. 3.

    T-RH thresholds from EN 16893:2018 according to the vulnerability of selected materials where thermal comfort of people in wintertime is neglected favouring an individual collection with an oriented climatization;

  4. 4.

    T-RH thresholds from tailored degradation models of selected materials where thermal comfort of people in wintertime is neglected favouring an individual collection with an oriented climatization.

The evaluation is based on weather-based indices for estimating energy demand in three European cities located in Cfb, Csa and Dfb climate zones (Indices for microclimate control under different outdoor climate scenarios). Then, two comparisons are performed: case 1 versus case 2 to study the role of thermal comfort in wintertime, and case 3 versus case 4 to study different climate control opportunities for individual collection facilities. This makes it possible to identify the choices towards a more sustainable management of collections facilities, also in view of the achievement of the different SDGs.

Thermo-hygrometric thresholds for risk of damage

The EN 16893:2018, titled “Conservation of Cultural Heritage—Specifications for location, construction and modification of buildings or rooms intended for the storage or use of heritage collections”, aims at suggesting the most suitable strategies for managing collections facilities11. It addresses the criteria necessary to establish appropriate spaces for permanent exhibitions and provides four informative annexes devoted to the relative risk of damage and deterioration due to T and RH conditions. The standard recommends an initial assessment of the needs and vulnerability of the collections to define proper acceptability ranges to limit biological, chemical, and mechanical deterioration that could differently affect climate-sensitive materials (specifically reported in the informative annexes B and C). Annex B classifies materials based on their sensitivity to T: low (e.g., ceramic, glass), moderate (e.g., paper), and high (e.g., plastic, film). Additionally, Annex B provides the optimal range for human thermal comfort. Annex C involves mechanical stability, chemical sensitivity for materials sensitive to hydrolysis, and mould risk related to RH. Both the annexes include qualitative considerations on the energy demand associated with maintaining a particular T and RH range, allowing the set points to vary in specific ranges in different seasons. A note specifies that local climate will affect the energy considerations, thus leaving the decision up to each single facility.

Table 1 reports the first three cases of T and RH thresholds extracted from the Annexes B and C. As the energy demand for (de)humidifying is strictly related to the water vapour content in the air, the mixing ratio of moist air (MR) was computed as a function of the T and RH thresholds according to the equation reported in EN 16242:201240.

Table 1 T and RH thresholds (or setpoints) used for the estimation of energy demand in spaces exhibiting climate-vulnerable objects under three cases according to EN 16893:201811.
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Three degradation models developed and assessed in the framework of the European project CollectionCare (Grant n. 814624, 2019–2022), were used in this study to assess the climate-induced risks of canvas paintings41, wooden objects42 and cellulose-based objects43,44 and the related energy demands in spaces preserving heritage collections. All these models are dynamic, as they provide the evolution of specific parameters describing the materials to climate conditions over time. A detailed description of the three degradation models is provided in the Supplementary Information. T-RH thresholds extracted from the following degradation models are summarised in Table 2. It is worth noticing that the minimum T thresholds is set by default at 5 °C to reduce the occurrences of temperature responsible for the glass–rubber transition.

Table 2 Temperature (T) and relative humidity (RH) relative safe thresholds according to EN 1689311 and lowest risk provided by the selected degradation models tailored for canvas paintings, wood, and paper collections.
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Indices for microclimate control under different outdoor climate scenarios

Since both T and RH play a key role in cultural heritage preservation, energy demands in museums should be estimated while considering both T and RH setpoints of microclimate control systems (Table 1 and Table 2). For this reason, we have proposed an approach that is not limited to the energy refurbishment of collections facilities, but also includes the re-discussion of T-RH thresholds suggested by CEN standard combined with the outputs from degradation models. Our aim is to identify solutions for a sustainable facilities management taking into account both collections vulnerabilities and future climate scenarios, thus positively contributing towards achieving the SDGs.

The energy demand (ED) of a building required to control microclimate conditions is influenced by the difference between the outdoor climate variable and the corresponding expected indoor value. The larger the difference between outdoor climate conditions and the desired microclimate threshold, the higher is the energy needed for heating/cooling and/or (de)humidifying the collections facility. In this study, the index used for estimating thermal energy consumption (“degree-days”) is extended and applied to the mixing ratio of moist air (MR), being a conservative property. In this case we have called “gram-days” (GD). “Degree-days” represent the counts of °C that the T must increase or decrease to reach a specific threshold T value. Conversely, “gram-days” represent the counts of grams per kilogram (g·kg-1) that the MR must increase or decrease to reach the threshold MR value. Using this approach, four indices can be computed: heating degree-days (HDD), cooling degree-days (CDD), dehumidification gram-days (DGD), and humidification gram-days (HGD). Specifically, the computation of HDD and CDD is conducted independently on the season based on the equations reported by the UK Met Office45. To calculate DGD and HGD, daily outdoor average MR values were compared with a threshold MR computed for each combination of indoor T and RH thresholds. Note that DGD and HGD are computed considering the final indoor RH after the cooling or heating process: if the final indoor RH was within the RH thresholds, DGD and HGD are equal to zero; otherwise, DGD and HGD differ from zero. T-RH thresholds from Table 1 and Table 2 are taking into account. The use of climate variables makes it possible to potentially estimate the impact of outdoor climate scenarios on the energy demand31.

The evolution of the four indices is analysed in three European cities located along similar meridional direction: site A, Copenhagen (Denmark): Lat. = 56.1° N and Long. = 12.5° E; site B, Rome (Italy): Lat = 41.9° N and Long = 12.5° E; site C, Trondheim (Norway): Lat. = 62.7°N and Long. = 11.3° E. These three sites were chosen as representative of three climate zones in Europe according to the Köppen-Geiger classification46: Cfb (site A, temperate oceanic climate), Csa (site B, hot summer Mediterranean climate), and Dfb (site C, humid continental mild summer, wet all year).

Daily data of air T and MR related to the three cities were extracted from the Copernicus Climate Data Store. We used the outcomes from the Sixth Assessment Report (AR6) issued by the Intergovernmental Panel on Climate Change (IPCC), which reports five Shared Socio-economic Pathways (SSP) associated with different future emission scenarios 47. Each SSP provides a potential scenario that would be caused by different socio-economic conditions, land-use changes, and other human-caused climate drivers that influence greenhouse gas emissions (GHGs), thus also affecting the change in the net radiative flux. The Sixth phase of the Coupled Model Intercomparison Project (CMIP6) dataset used in this analysis was generated by Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC)48, providing data for recent past climate (RP, 1981–2010) and the intermediate scenario SSP2-4.5 and extreme scenario SSP5-8.5 for the near future (NF, 2021–2050) and far future (FF, 2071–2100). SSP2-4.5, called “middle of the road”, represents a development pattern like the current society development, in which radiative forcing is stabilised at approximately 4.5 W∙m-2 after 2100. Conversely, SSP5-8.5, called “fossil-fuelled development”, represents higher GHGs emissions for which radiative forcing reaches 8.5 W∙m-2 by 2100.

Then, the energy demands for thermal control (EDtherm), the energy demands for humidity control (EDhum) and the total energy demands (EDtot) in kWh∙m-3·year-1 were computed through Eqs. (1), (2) and (3), respectively:

$$E{D}_{therm}=\frac{A/V\cdot h\cdot {U}_{value}\cdot DD}{1000}$$
(1)
$$E{D}_{hum}=ACH\cdot h\cdot k\cdot {L}_{evap}\cdot \rho \cdot GD$$
(2)
$$E{D}_{tot}=E{D}_{therm}+E{D}_{hum}$$
(3)

where \(A\) is the total surface area of the building \(\left[{m}^{2}\right]\); \(V\) is the total volume of the building space \(\left[{m}^{3}\right]\); A/V is the surface-area-to-volume ratio \(\left[{m}^{-1}\right]\), i.e., the larger the A/V, the more surface area per unit volume, through which material can exchange heat; \({U}_{value}\) is the thermal transmittance of the building envelope \(\left[W\cdot {m}^{-2}{K}^{-1}\right]\); \(ACH\) is the air exchange rate \(\left[{h}^{-1}\right]\); \(h\) is the number of hour in a day (24 h); \(\rho\) is air density \(\left[kg\cdot {m}^{-3}\right]\); \({L}_{evap}\) is the latent heat of evaporation \(\left[J\cdot {kg}^{-1}\right]\); \(k\) is the conversion unit (2.78 10–7 s-1). The main advantage of this approach is that it is possible to change only the building features to estimate the potential energy demand in specific case studies.

Results

Estimation of f past and future energy demands: case 1 versus case 2

The evolution of the four indices (HDD, CDD, DGD, HGD) over a whole calendar year in the three European sites can provide an estimation of the magnitude of energy demands needed for accomplishing with the microclimate ranges suggested by the EN 16893 to limit relative risks of degradation for two cases of climate control.

Figure 1 shows the time evolution of degree-days (DD i.e., HDD and CDD) and gram-days (GD i.e., DGD and HGD) per day during the recent past (RP) period in case 1 (Fig. 1a–c) and case 2 (Fig. 1d–f). HDD values (orange lines) were highest between January and February and almost doubled from case 1 to case 2 (from 6 °C to 15 °C for Cfb and from 13 °C to 21 °C for Dfb), whereas the maximum HDD tripled from 2 °C to 9 °C in the Csa site. CDD (blue lines) were larger than zero only in the Csa zone and reached the maximum value of 5 °C at the end of July. DGD values (yellow lines) were always below 4 g∙kg-1 in all zones. In case 1, DGD values were higher than 0.5 g∙kg-1 throughout the year, except for the Dfb zone where it was null in wintertime. In case 2, DGD values were higher than 0.5 g∙kg-1 in summertime with a different duration: the longest for Csa (from April to November) and the shortest for Dfb (from June to September). HGD values (purple lines) were negligible in all zones, except for Dfb in wintertime in case 2, where the heating required to reach indoor minimum T threshold caused a drop of RH below the threshold of RH = 30%.

Figure 1
figure 1

Time evolution of degree-days (DD in °C) and gram-days (GD in g∙kg−1) in three sites corresponding to three different climate zones in the recent past (RP, 1981–2010) in case 1 (a-c) and 2 (d–f).

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For the sake of brevity, the time evolution of degree-days and gram-days for the two future scenarios are not reported, but they are briefly described as follows. In the far future of the extreme scenario SSP5-8.5, in case 2 it was observed that heating demands will decrease in frequency and duration, whereas the cooling and dehumidifying demands will increase with respect to the RP period and last for up to two months.

Figure 2 and Table 3 present the annual values of degree-days (HDD and CDD) and gram-days (DGD and HGD) from the recent past (RP) to the near future (NF) and far future (FF) periods in the intermediate SSP2-4.5 and extreme SSP5-8.5 scenarios. In both cases, HDD values tend to significantly decrease from RP to FF in all climate zones for both SSP scenarios. Conversely, CDD values tend to increase (Cfb from 2 °C to 96 °C in a year and Csa from 270 °C to 1000 °C in a year), except for the Dfb climate zone, where cooling will be negligible in all periods. Cooling to accomplish the Tmax threshold of EN 16893 will become a novel aspect to consider, especially in the Csa climate zone. In all climate zones, DGD values are higher in case 1 climate control than in case 2. Specifically, in the Cfb and Dfb climate zones, DGD is similar between case 1 and case 2, with a small difference between RP and the two NF scenarios: DGDCfb,1 = 447 ± 22 g∙kg-1, DGDCfb,2 = 158 ± 15 g∙kg-1, DGDDfb,1 = 384 ± 23 g∙kg−1 and DGDDfb,2 = 90 ± 20 g∙kg−1. In the FF scenarios, DGD is always higher than 250 g∙kg−1 with a maximum value of 639 g∙kg−1 according to SSP5-8.5. For the Csa climate zone, DGD increase from 600 g∙kg−1 in RP to 967 g∙kg−1 in FF for SSP5-8.5 in case 1, and from 295 g∙kg−1 in RP up to 815 g∙kg−1 in FF for SSP5-8.5 in case 2. Finally, HGD are always zero except for the Dfb climate zone in RP and NF scenarios in case 2.

Figure 2
figure 2

Bar plots of degree-days (HDD and CDD in °C) and gram-days (DGD and HGD in g∙kg−1) in three sites corresponding to three different climate zones from recent past (RP, 1981–2010) towards near future (NF, 2021–2050) and far future (FF, 2071–2100) based on SSP2− 4.5 and SSP5− 8.5 scenarios in case 1 (a–c) and 2 (d–f).

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Table 3 Summary of degree-days (HDD and CDD in °C) and gram-days (DGD and HGD in g∙kg-1) in three sites corresponding to three climate zones (Cfb, Csa, and Dfb) from recent past (RP, 1981–2010) towards near future (NF, 2021–2050) and far future (FF, 2071–2100) based on SSP2− 4.5 and SSP5− 8.5 in cases 1 and 2 climate control.
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Considering that all the reported values in Table 3 are proportional to the energy demands of buildings, it can be inferred that, compared to case 1, case 2 (tighter control) leads to a higher HDD to keep adequate indoor thermal comfort in wintertime for people (who require a narrow temperature range but are less sensitive to RH variation) and to a lower DGD to keep RH within the allowable thresholds for conservation. HDD increased up to 500 times with respect to their initial value (e.g., in SSP5-8.5 FF in Csa), while DGD lowered up to the 80% of the initial value (e.g., in SSP5-8.5 NF in Dfb). Figure 3 shows the time evolution of the degree-days (DD, left column) and the gram-days (GD, right column) in case 1 (first row) and case 2 (second row) from RP to FF.

Figure 3
figure 3

Time evolution of degree-days (DD, panels a and c) and gram-days (GD, panels b and d) in three sites corresponding to three different climate zones (Cfb, Csa, and Dfb) from recent past (RP, 1981–2010) towards near future (NF, 2021–2050) and far future (FF, 2071–2100) based on SSP2-4.5 and SSP5-8.5 scenarios in case 1 (a, b) and 2 (c, d) climate control.

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In case 1 (Fig. 3a,b), DD in RP were higher in Dfb (DD = 1933 °C) than those in Cfb (DD = 716 °C) and Csa (DD = 370 °C). GD in RP were higher in Csa (GD = 600 g∙kg-1) than those in Cfb (GD = 443 g∙kg-1) and Dfb (GD = 361 g∙kg-1). In NF and FF, DD tended to triple in Csa (from 370 °C to 1015 °C) and to decrease in Dfb (-50%) and Cfb (-60%); while GD is expected to increase in all climate zones, with a steeper positive change in SSP5-8.5 in Csa (+ 61%) and Dfb (+ 77%).

In case 2 (Fig. 3c,d), DD in RP were higher in Dfb (DD = 4463 °C) than those in Cfb (DD = 2644 °C) and Csa (DD = 1519 °C), with a future reduction in FF in Cfb (-37%) and Dfb (-34%) and a negligible change in Csa (-2%). GD in RP were higher in Csa (GD = 295 g∙kg-1) than those in Cfb (GD = 158 g∙kg-1) and Dfb (GD = 114 g∙kg-1), with a steeper increase in Csa and Dfb.

Starting from a basic knowledge of the building envelope features (e.g., ratio between surface area and building volume (A/V), thermal transmittance of building envelope (Uvalue), and air change rate (ACH)), it is possible to approximately estimate the energy demands (ED) of the spaces housing collections located in these specific sites. As an example, to estimate the possible ED over a calendar year to control the microclimate within the given T-RH window in cases 1 and 2, we performed calculations setting the following parameters: A/V = 1·m-1; Uvalue = 1.0 W·m-2·K-1; ACH = 1 h-1. Note that users can modify these parameters to estimate the total ED of different spaces housing collections starting from the DD and GD values reported in Table 3. In Fig. 4, it is evident that the total ED tends to double in Csa zone in case 1 (from 21 to 44 kWh·m-3) and to increase less than a third in case 2 from RP to FF in SSP5-8.5 scenario (from 42 to 52 kWh·m-3). In Cfb and Dfb zones, the total ED tends to decrease of 30% from RP to FF (SSP5-8.5) in both the cases, specifically:

  • Cfb: the total ED decreases from 26 kWh·m-3 in RP to 19 kWh·m-3 in FF in case 1 and in case 2 from 67 kWh·m-3 in RP to 46 kWh·m-3 in FF in case 2;

  • Dfb: the total ED decreases from 54 kWh·m-3 in RP to 36 kWh·m-3 in FF in case 1 and in case 2 from 109 kWh·m-3 in RP to 78 kWh·m-3 in FF.

Figure 4
figure 4

Annual energy demands in kWh·m−3 estimated in buildings located in three sites corresponding to three different climate zones from recent past (RP, 1981–2010, black bars) towards near future (NF, 2021–2050, solid bars) and far future (FF, 2071–2100, dashed bars) based on SSP2-4.5 (green bars) and SSP5-8.5 scenarios (red bars) in cases 1 and 2. Building features: A/V = 1·m−1; Uvalue = 1.0 W·m−2·K−1; ACH = 1 h−1.

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From the comparison between case 1 and case 2, it is possible to further discuss the expected total ED for different climate control strategies. Indeed, it was highlighted that, to shift from a strategy that did not consider comfort (case 1) to one that considered comfort (case 2), in RP site C (Dfb) and A (Cfb) would have spent about + 30 and + 55 kWh·m-3, respectively; on the contrary, to pass from case 1 to case 2, in FF the same sites will be spending approximately 25% less in terms of total ED. As already mentioned, site B (Csa) is the only site for which the total ED in FF is higher than in RP for both cases, with an expected increase of total ED of about + 50% in case 1 and 24% in case 2. The above results suggest that considering thermal comfort of the occupants is expected to become more feasible in climate classes such as Cfb and Dfb, while in view of global warming this change of strategy (case 2) will likely become less sustainable in climates with hot summers such as Csa, where the reduction of HDD will not compensate the increase of CDD.

Estimation of past and future energy demands: case 3 versus case 4

As degradation models are developed to support the identification of T-RH thresholds to limit the relative risks of damage, a comparison with respect to T-RH thresholds suggested by EN 16893 allows to evaluate if the use of degradation models outputs might affect the energy demands required for heritage collections preservation.

Figure 5 present a summary of T and RH thresholds with no relative risk of damage, as suggested by EN 16893 (green areas), and the lowest risk threshold provided by the three degradation models (i.e., T-RH values before any climate-induced deterioration might occur, depicted as white areas) for canvas paintings (a), wooden objects (b) and cellulose-based objects (c).

Figure 5
figure 5

Relative risk of degradation diagrams. RH versus T diagrams with the T and RH area without relative risk of damage, where the green area is related to EN 16893:2018 and the white area is estimated by the degradation models: (a) canvas paintings (considering an annual average RH = 65% of highly sensitive materials), (b) wooden objects and (c) cellulose-based objects (considering low-quality acidic paper with pH = 5 and DP = 600). The grey area indicates the T-RH relative risk of damage.

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Figure 5a shows that the T-RH safe thresholds (white area) as identified by the mechanical degradation model for highly sensitive materials (ΔRH = 10% and assuming a maximum allowable RH = 65%) are in line with those recommended by EN 16893. However, it is worth noting that EN 16893 might underestimate the actual mechanical stability in canvas paintings, as it explicitly refers to non-composite and non-constrained hygroscopic objects. The change in RH potentially causing cracks can substantially vary among paintings. Nevertheless, it is generally advised to keep the maximum fluctuation in RH below 40% for low sensitive objects and 10% for highly sensitive objects. When the RH fluctuations remain below the maximum ΔRH recommended threshold, it can be assumed that there is no immediate risk of cracks. Figure 5b shows that consistently maintaining RH values above 80% could put wooden art collections at risk of mould development within approximately 200 days, according to the mould growth isochrone defined through the VTT model. To minimise the risk of spore germination, it is advisable to always keep RH below 75% 49. Moreover, according to EN 16893 it is recommended to avoid RH values to exceed 55% to limit the risk of mould germination at 20 °C (Table 3). Understanding the risk level provided by the model allows the user of the model to benefit from the possibility to make gradual changes to climate conditions and avoid rapid changes in moisture content causing internal stresses in wood. Figure 5c highlights that the ranges without risk of damage suggested by EN 16893 for cellulose hydrolysis are narrower than those identified by the degradation model for low-quality acidic paper (pH = 5 and DP = 600) over a projected lifetime of 500 years. This indicates that the standard is very conservative and might be no longer sustainable in coping with the present challenges of global warming effect and energy consumption reduction. To limit the energy demand, a feasible strategy could be to use heavyweight buildings for archives and repositories, which have the potential to keep almost constant conditions without relying on energy-demanding systems50,51,52.

According to the procedure described in “Indices for microclimate control under different outdoor climate scenarios”, we computed the total ED taking the T-RH thresholds reported in Table 2. Table 4 and Table 5 summarise the key indices used in this study and their evolution in the near and far future. The preservation of paper collections from cellulose hydrolysis poses the greatest challenge compared to other materials, as it requires the highest energy demands and generates the most CO2 emissions. Both indices are expected to rise from RP to FF in the three cities, with a higher impact on climate zone Csa. A comparison between the thresholds outlined in EN 16893 and the degradation model reveals that following the former consumes significantly more energy than the latter. The preservation of canvas paintings from mechanical degradation does not show significant differences between the thresholds outlined in EN 16893 and the degradation model. Both indices are expected to decrease from RP to FF in the three cities, with a lower impact on climate zone Csa, as no heating and cooling demand are required. Finally, the preservation of wooden objects from the occurrence of mould growth has the higher energy demand if T-RH thresholds from EN 16893 are followed. In both Cfb and Csa climate zones, the energy demand will tend to increase from RP to FF, the opposite in the Dfb climate zone. The energy demand is significantly reduced when T-RH thresholds from the degradation model are followed.

Table 4 Database of the degree-days (HDD and CDD in °C) and gram-days (DGD and HGD in g∙kg-1) in three sites corresponding to three climate zones (Cfb, Csa, and Dfb) from recent past (RP, 1981–2010) towards near future (NF, 2021–2050) and far future (FF, 2071–2100) based on SSP2-4.5 and SSP5-8.5 for wood, canvas paintings and paper according to EN 1689311. In addition, the total energy demand is provided (Building features: A/V = 1·m-1; Uvalue = 1.0 W·m-2·K-1; ACH = 1 h-1.).
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Table 5 Database of the degree-days (HDD and CDD in °C) and gram-days (DGD and HGD in g∙kg-1) in three sites corresponding to three climate zones (Cfb, Csa, and Dfb) from recent past (RP, 1981–2010) towards near future (NF, 2021–2050) and far future (FF, 2071–2100) based on SSP2-4.5 and SSP5-8.5 for wood, canvas paintings and paper according to the degradation models described in “Thermo-hygrometric thresholds for risk of damage”. In addition, the total energy demand is provided (Building features: A/V = 1·m-1; Uvalue = 1.0 W·m-2·K-1; ACH = 1 h-1.).
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Discussion

To understand challenges and perspectives of different operational management in collections facilities while achieving SDGs, the outcomes of “Results” are discussed taking into account the roles of (a) visitors and personnel thermal comfort, (b) the collection-oriented microclimate control, and (c) the changing climate. Table 6 provides the list of the Sustainable Development Goals (SDGs) most relevant for this topic53 and the specific SDGs targets whose achievement can be influenced by different operational management of the microclimate control in collections facilities.

Table 6 Synthesis of the role of different management strategies for the microclimate control in collections facilities in accelerating (↑), unchanging ( ↔) and decelerating (↓) the achievement of the SDGs.
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Achieving thermal comfort in wintertime (case 2) doubles the energy demand needed to keep T-RH thresholds for mixed collections preservation (case 1) in all climate zones. Even though case 1 is more favourable for accelerating the building’s energy efficiency (SDG 9) and enhancing the preservation of collections (SDG 11), a side effect with respect to case 2 can occur in facilities located in Cfb and Dfb zones, where outdoor daily temperatures are on average below 8 °C for more than half of the year. Opting for case 1 (as well as for cases 3 and 4) could be responsible for a lower attractiveness of museums to visitors (negatively impacting the touristic flows) and worse working conditions for personnel (negatively impacting the accomplishment of SDG 8). Additionally, in the Dfb zone, winter heating should be coupled with a humidifying system to minimise too dry conditions, contributing to decelerating the achievement of more sustainable patterns in energy consumption (SDGs 9 and 12) and hampering resilience capacity (SDG 13) in the facility management. Some studies have already investigated how to dynamically set indoor T thresholds for thermal comfort with respect to outdoor climate conditions54 and how to combine them with T thresholds suitable for collections preservation55,56. They have demonstrated that the energy demand and relative costs of this option largely depends on the outdoor climate and, to a lesser extent, on the energy performance of the building. Moreover, a behavioural change of visitors and personnel based on an increased awareness of sustainability issues of facilities management and of conservation requirements of the collections might be key to foster energy savings57.

A collection-oriented climate control is preparatory in achieving SDG 11, as all the efforts are devoted to the collection’s preservation. The T-RH thresholds suggested by degradation models (case 4) need less energy to be hold if compared to those suggested by EN 16893 (case 3). The energy demand widely varies from collection to collection based on the specific vulnerability of each material. Since each facility can thus manage the most appropriate thresholds according to the collections it preserves, this allows to further improve the preservation of collections (SDG 11) and the responsible consumption of energy (SDG 12). The preservation of paper objects is the most energy demanding practice and it could not be environmentally and economically sustainable at the same time, especially in the Csa zone. It follows that in libraries and archives, which are the most susceptible facilities, keeping the T-RH thresholds can negatively impact the achievement of resilient (SDG 9) and adaptive (SDG 13) buildings being responsible for larger inequalities in facilities within and among countries (SDG 10).

The analysis of the energy implications in the near and far future climate scenarios has demonstrated that the energy demand for heating in wintertime will tend to significantly decrease, thus decreasing the demand for humidification (especially in northern latitudes). In turn, winter heating might also be responsible for an increase of the energy demand for the dehumidification in all climate zones. It follows that in the future it will be easier to accomplish thermal comfort of visitors and personnel in wintertime (i.e., better working place in accordance with SDG 8), thus reducing the risk of energy poverty and, hence the inequalities among facilities within and across countries (SDG 10). On the opposite, this positive effect does not counterbalance the drastic increased energy demand in the Csa zone for summer cooling and dehumidification, enhancing the risk of energy poverty in facilities located in similar climate zone. However, when standardised thresholds (case 3) are considered, global warming will contribute to exacerbate the environmental, economic and energy challenges in the facilities preserving paper collections. Such information on the energy implications of changing climate is fundamental in the early-stage design of adaptation interventions since it is possible to define indications at climate-zone level. Indeed, the future challenges for collections facilities involve making buildings more resilient to increasingly warmer outdoor conditions. The adaptive capacity of facilities will be more sustainable if the management for collections preservation is based on the use of the T-RH thresholds suggested by degradation models rather than on invasive energy refurbishment to keep standardised thresholds. Climate challenges vary across Europe according to the different impacts in individual areas, even within the same country. The main risk is that some museums or archives may be unable to address these challenges (i.e., inefficient historical buildings and/or located in low-resilient climate zones58, urban heat island and urban canyoning effects59,60,61, thus decelerating SDG 13), with an adverse side-effect on the energy poverty of facilities and on the preservation of collections. To reduce such risks, it may be worth considering a relocation of the collections in less challenging climate zones (e.g., those that are not expected to drastically change in the future) and higher scientific and technological capacity to move towards more sustainable patterns of consumption and production (SDG 12). On the other hand, such a solution could have dire consequences at the local level, potentially leading to job and cultural identity losses. To overcome such barriers, the implementation of collaborative actions based on a responsive, inclusive, participatory, and representative decision-making at all levels together with the investment promotion regimes for least developed countries can promote accelerating SDGs at regional level with positive impact on the single facility62. In Europe, this action can be guided by the CEN TC 346 regarding the definition of protocols and procedures to adopt in the preventive conservation of cultural heritage. In our opinion, the results of this paper could be leveraged in the upcoming revision of the EN 16893 standard as a preliminary step in this process. Indeed, the positive implications of case 4 open the opportunities to include further annexes devoted to the application of weather-based technical indices to support stakeholders in the early-stage decision-making to concurrently achieve sustainability and preservation goals.

Conclusions

This research provided a method for estimating energy demand in collection facilities since the early stages of the decision-making process, supporting the establishment of new European heritage commons, which is one of the primary challenges that heritage managers will face in the coming years. Our results demonstrated that adjusting the microclimate thresholds used in the operational management of collections facilities can be a valid alternative to energy refurbishment, especially when the facilities cannot sustain its elevated costs. The main advantage of our method is that it leverages solutions that do not require new costly infrastructures but can take advantage of the cooperation and alliance among similar facilities in the same climate zone, thus supporting the preservation of cultural objects. Therefore, it lays the ground for conservation policies based on sustainable management practices for the future programming at climate-zone level rather than at a building level. The results represent a valid support to understand how to achieve the SDG target 11.4 and the possible implications of different operational management strategies on the others (SDGs 8, 9, 10, 12 and 13). Additionally, the results can serve as basis for planning effective adaptation measures to the expected global warming, thus fine-tuning the microclimate control to safeguard heritage collections and thermal comfort while enhancing energy saving.

The discussion focussed on the future climate scenarios in three EU climate zones (Cfb, Csa, and Dfb) and on the role of collections facilities in achieving Sustainable Development Goals and climate-neutrality of the European Green Deal, paying attention to the implications of both the human thermal comfort and the collection-oriented climate control. The weather-based indices used are completely independent of the building performance and allow to estimate the potential energy demand of collection facilities according to different temperature and relative humidity thresholds resulting from the use of degradation models in the place of the ranges suggested in EN 16893. Additionally, they make it possible to estimate the potential energy demand in several collections facilities located at the same climate zone by simply changing the coefficients of the building features. Since the UNESCO Institute for Statistics oversees defining internationally comparable indices to monitor SDG target 11.4, these outcomes can effectively support this process. Additionally, the application of these weather-based indices can be included in the revision of the EN 16893, as an informative annex to estimate trends in the potential energy demand of a collection facility through a user-friendly method with a low computation effort. In this way, it would be possible to implement collaborative actions among collections facilities for a more integrated approach at regional level with a positive impact on facility level.

To conclude, the methodology and database provided in this article can be used also by non-experts to approximately estimate the energy demand of collections facilities in accordance with microclimate conditions limiting the relative risk of degradation, advantageously extending this application from a city scale to a regional scale.