Forecasting the Impact of Climate Change on Energy Demand in High-Rise Office Buildings

Abstract

The objective of this analysis was to forecast the energy demand of a tall office building situated within a mid-rise urban context under future climate conditions. The research employed energy simulations conducted using OpenStudio v. 3.9.0 and EnergyPlus software v. 24.2.0, with weather data in TMY format. Climate projections for the years 2050 and 2080 were derived from the HadCM3 model. The morphing method was applied to generate climate data files in EPW format for integration into the building energy simulations. Based on these future weather files, the building’s performance was simulated, accounting for the operation of HVAC systems to determine energy consumption for heating and cooling. The results were compared against a baseline simulation representing contemporary climatic conditions, constructed from data covering the years 2004–2018. The findings indicate that cooling demand will play a decisive role in the total energy consumption of the building.

1. Introduction

One of the most significant challenges confronting contemporary civilisation is the issue of climate change and its impact on the planet. To mitigate the rate of these changes, a series of measures were initiated following the publication of the report prepared under the leadership of G.H. Brundtland in 1987. Despite the passage of several decades, the outcomes of these initiatives have proved unsatisfactory, and an increasing number of people recognise the necessity of complementing mitigation efforts with adaptive strategies. This challenge is particularly relevant to the construction industry, as the changing climate introduces new conditions affecting both the design and operation of buildings. Notwithstanding these transformations, buildings must continue to provide comfortable living and working environments while minimising energy consumption [1,2,3,4,5]. It is also essential that adaptation to evolving environmental conditions does not result in an increased carbon footprint. These issues have been examined for various global locations, with particular attention to energy consumption for building heating and cooling [5,6,7,8,9,10,11,12,13,14,15,16,17,18].

The authors of [1] emphasise the necessity of transforming material use and technological approaches within the construction sector, which accounts for approximately 40% of global energy consumption and associated CO₂ emissions. In [2], the authors measured air temperatures in selected rooms located on the uppermost and penultimate floors of both single-family and multi-family buildings and conducted simulation analyses to assess the effectiveness of wall systems in preventing excessive indoor heat gains. Based on these findings, they concluded that appropriate thermal insulation of building envelopes is essential to maintaining indoor air temperatures within a range acceptable to occupants. In [3], the influence of building partitions composed of different materials on their heat storage capacity and their role in creating a comfortable indoor microclimate was examined, using preschool buildings as a case study. Similar issues were addressed in [4], which highlighted the significant relationship between outdoor and indoor air temperatures, particularly during the summer period.

Climate change has become increasingly evident in recent years, raising the question of whether existing national outdoor climate design parameters remain adequate for contemporary building design, particularly in determining thermal loads. The author of [5] draws attention to this issue and proposes a revision of these parameters.

In recent years, energy efficiency has been considered within a much broader context, encompassing energy consumption across the entire life cycle of a building (LCA). In [6], global trends in greenhouse gas emissions throughout the building life cycle were analysed, and the findings indicate a tendency to reduce emissions through the appropriate selection of building materials and HVAC systems. In [7], the interplay between internal heat sources and the thermal properties of building envelope materials was emphasised, demonstrating their combined impact on the energy required for cooling in summer and heating in winter. The study was based on an analysis of four office buildings located in Vienna.

In [8], a two-storey single-family dwelling located in Tokyo was analysed. Energy simulations conducted for the projected 2030 climate indicate a 26% increase in energy consumption during August. The impact of climate change on energy consumption in office buildings located in China was examined in [9]. Across five climate zones, an increase in cooling energy consumption of between 11.4% and 24.2% was observed, while heating energy consumption decreased by between 13.8% and 55.7%. Reference scenarios in [10] demonstrate that climate change induces a greater rise in cooling energy consumption in China than in the United States. In [11], the primary focus was the assessment of the long-term impact of changing climatic conditions on the heat demand of renovated buildings in various climates. In every case, a reduction in heating energy demand was observed. Study [12] analysed the energy required to maintain thermal comfort in high-rise office buildings located in Tallinn. Overheating assessments were performed for five typical floors in each office building. The results indicate that it is possible to reduce maximum indoor temperature by 12% and cooling energy consumption by 14%, when accounting for locational conditions, climatic factors, and the specific characteristics of the urban environment. In [13], energy simulations were performed to evaluate the impact of climate change on the energy consumption of a standard single-family house in Tokyo for 2007 and the forecast year 2034. The findings show that an outdoor temperature increase of 1.52 °C would result in a 15% increase in energy consumption, primarily due to greater cooling demand. In [14], representative concentration pathways (RCP 2.6, 4.5, and 8.5) were considered to analyse the effectiveness of design strategies in the 21st century for France, Portugal, Spain, Argentina, Brazil, and Chile. The results confirm the continued relevance of passive heating and cooling strategies.

In [15], the impact of climate change on energy consumption in an office building located across five cities in the United States was analysed. The morphing method was applied using two general circulation models (HadCM3 and CESM1). The findings indicate that, in most cases, the cooling load would increase significantly, while the heating energy demand would decrease.

The results presented in [16] indicate that the use of Typical Weather Years (TWY) leads to an underestimation of the peak heating load by 12.5% and the cooling load by approximately 18% in a residential building located in Catania; for office buildings, this discrepancy may be even greater. The authors emphasise that when the objective of the simulation is to determine the capacity of heating and cooling systems, peak values derived from actual measurement data from the past 10–15 years should be preferred. In [17], results were presented for the years 2020, 2050, and 2080, illustrating the effects of climate change on average temperature, relative humidity, and energy consumption over the building life cycle. The findings show that climate change in southern Spain will result in increased building energy consumption, primarily due to higher cooling demand. In [18], the influence of various weather datasets on the energy demand for cooling and heating in a modern two-storey building located in Prague was analysed. The heating demand in the forecast years was shown to decrease by 3.95% compared with the Typical Reference Year (TRY), while the cooling demand increased by 3.96% relative to TRY. These results confirm that the observed warming trend in recent years has contributed to higher cooling energy demand.

Energy consumption in buildings is particularly sensitive to climate change due to the direct relationship between outdoor climate conditions and space heating and cooling. The authors of [19] considered the use of phase change materials (PCM) and double-layer facades (DSF) to optimize the energy efficiency of office buildings in Iran. They analyzed energy consumption trends in various climate scenarios over the period 1981–2030. The obtained results highlight the increasing energy demand caused by global temperature increase and prove that the integration of PCM and DSF can reduce energy consumption.

However, the authors of [20] showed that dry bulb temperature (DBT) is the dominant climatic parameter influencing the thermal loads of buildings in all three climatic zones in China during the heating period on a daily, monthly, and annual scale. The annual heating load showed a significant decrease in all three cities during heating periods over the last 50 years, from 1961 to 2010.

Although much research focuses on the efficiency of HVAC systems, there is little research on the relationship between building environment and energy consumption from the perspective of passive building design priority. In the work [21], 8 cases of typical high-rise office building plans in 6 categories are established in the city of Beijing, which is located in the cold climate zone of China. Among other things, the influence of the housing aspect ratio, communication location, and natural lighting on energy consumption was considered. Their simulation results show that the differences in energy consumption in all cases can be as much as 17%.

The authors of [22], regional-scale weather data from future climate scenarios were used and applied to a dynamic thermal simulation of nine example office buildings in Vienna, Austria. It has been observed that the heating demand decreases slightly, while the cooling demand generally increases significantly.

The paper [23] investigated the potential impact of climate change on the cooling and heating loads of offices located in Japan in three locations in three periods: 1981–2000, 2031–2050 and 2081–2100. Based on the obtained results, it was noted that by using selected adaptive measures, e.g., night cooling, glazing with better thermal insulation, and energy-saving lighting, the demand for heating/cooling can be reduced.

The authors of [15] conducted an energy simulation-based study to investigate the impact of climate change on energy consumption in an office building located in five different cities in the United States. This article highlights the importance of efficient operation of HVAC systems to ensure optimal heating and cooling energy demand.

In the article [24], a forecast of the future cooling load needed in 2000, 2020, 2050 and 2080 in the tropical zone was carried out. It turned out that compared to 2000, the maximum cooling load needed in 2020, 2050 and 2080 increases by 2.96%, 8.08% and 11.7%, respectively.

This paper [25] examines the impact of climate change on cooling energy consumption in office buildings in four major architectural climate zones in China. The results show that there are clear differences in the responses of monthly or annual cooling loads to climate change in different climates. The authors [25] emphasized the fact that to predict cooling energy consumption, the trend of humidity changes in the future must be taken into account.

In turn, the authors [26] analyzed the impact of climate change for 3 future time forecasts (2035, 2065 and 2090) for buildings located in Southern Europe. The results obtained in [26] show that in all scenarios there will be a steady and large increase in future air temperature, which will translate into an overall increase in total energy consumption with a relative decrease in heating demand and an increase in cooling demand. The authors emphasize that the annual demand for heating and cooling energy in 2090 is expected to increase in the range of +50.8–119.7% if measures to counteract and limit the effects of climate change are not planned.

The authors in the paper [27], based on energy audit reports on pre- and post-upgrade data for 56 office buildings located in Singapore (tropical climatic conditions), extracted a list of key variables influencing energy consumption in air-conditioned office buildings. This information can be used to explore the energy-saving potential of office buildings.

Interesting considerations were made by the authors [28] using fourteen global climate models and two representative concentration paths to account for the uncertainty of future climate forecasts in building energy simulations, using the example of an office in three different US cities (Boston, Miami, and San Francisco) and in three future periods (2030, 2060, and 2090). Driven by the increase in cooling energy, it was observed that annual primary energy consumption increased until 2090 for all tested predicted climatic conditions, which was due to the increase in cooling energy. The results varied significantly depending on location and forecasts, leading the authors [28] to emphasize the need for each model to support local design practices.

The article [29] assessed the influence of urban environmental geometry on the thermal load of office buildings in a city with a hot and humid climate. When urban development was included in the energy simulations, an average reduction in thermal load of 16–18% was observed, which highlights the influence of the geometry of the building environment on energy consumption.

Analyses of the impact of meteorological factors on energy consumption in high-rise office buildings in Hong Kong were also carried out in [30]. The obtained results indicate that in the case of office towers in Hong Kong, energy consumption is more sensitive to changes in temperature and humidity in hot and humid conditions than in cold and dry conditions.

In the paper [31], the authors conducted energy simulations for office buildings located in extremely cold, cold, and humid Canadian climate zones using climate forecasts for the period 2056–2075. The results quantify the expected decrease in heating and increase in cooling loads due to future higher temperatures across Canada. However, the scale of change differs significantly between the three selected climate zones.

Increasing population density and increasing urbanization have increased the need for high-rise buildings due to land scarcity. A number of analyses are being undertaken to design or modernize skyscrapers in an energy-efficient and sustainable manner to reduce their significant environmental impact. The results contained in [32] indicate that a reduction in energy consumption in skyscrapers can be achieved by improving the enclosure design parameters (up to 78.9%), optimizing the plan layout (up to 17%), using natural ventilation (up to 45%), and using renewable energy sources in HVAC systems.

In the article [33], the sensitivity of a wide range of design and operating parameters was investigated, including in terms of heating and cooling loads of multi-story buildings. The authors estimate that by 2050, multi-story buildings could save 28–44% of annual heating and cooling energy by using appropriate solutions in the field of building envelopes (e.g., type of glazing) or HVAC (mechanical ventilation with heat recovery) systems.

Energy conservation measures and appropriate operational parameters will be important issues in the future conditions of global climate change. Considerations in this regard were conducted by the authors of [34] for a newly renovated office building located in Chengdu. The optimization took into account the influence of set cooling and heating temperatures in the rooms, set supply/water return temperatures for the air conditioning system, night ventilation settings in summer, and renewable energy variables (photovoltaics). The simulation model was verified using monitored heating and cooling energy consumption. Analyses showed that the building’s energy system showed better performance when the cooling setpoint of the air source heat pump was increased from 7 °C to 9 °C. The optimal solution was to reduce the set heating temperature of the air source heat pump from 45 °C to 42.5 °C in 2030 and 2060 and from 45 °C to 40 °C in 2040 and 2050.

The considerations presented here do not encompass the identification of technical solutions for adapting buildings to changing external environmental parameters. Rather, they highlight the significance of the issues, while the development of potential solutions remains the subject of ongoing research. This pertains to a departure from current design standards concerning the use of glazing—depending on its construction and location (such as floor level or façade orientation)—as well as the implementation of controlled systems for regulating solar radiation. It may therefore be concluded that, through the application of appropriate adaptation measures, it is possible to maintain thermal comfort under projected climatic conditions while achieving low energy consumption within the building.

The studies cited above require climate change modelling for future decades. One of the main sources of information in the field of climate change is the work of the Intergovernmental Panel on Climate Change (IPCC). The projected evolution of the global climate is based on four scenarios of atmospheric CO₂ concentration change (RCP)—as shown in Figure 1—which are used, among other purposes, to estimate the average increase in the planet’s temperature. These scenarios correspond to the estimated levels of global radiative forcing in the upper layers of the atmosphere caused by greenhouse gases in the year 2100, amounting, respectively, to 2.6, 4.5, 6.0 and 8.5 W/m². This value is directly dependent on the concentration of greenhouse gases in the atmosphere, which reached approximately 410 ppm CO₂ in 2020.

Based on the literature review, the Authors stated that there is a lack of this type of research for the area of Poland, and, in particular, the region of Upper Silesia. Therefore, they attempted to fill the existing gap in this area and carried out energy demand forecasting for a tall office building, surrounded by medium-rise urban buildings, in the perspective of climate change. This study adopts the RCP 4.5 scenario to generate climate parameters for the years 2050 and 2080. The research was conducted through energy simulations using OpenStudio and EnergyPlus software Berkeley, CA, USA and Urbana-Champaign, IL, USA, with weather data in TMY format. Climate data for the years 2050 and 2080 were generated using the HadCM3 model, and the morphing method was applied. Based on the resulting weather files representing predicted future conditions, the building’s performance was simulated, taking into account the operation of HVAC systems to determine energy consumption for heating and cooling.

2. Materials and Methods

2.1. Subject of the Analyses

The subject of the study is a 19-storey high-rise building measuring 28.0 × 14.5 m, situated among typical city-centre buildings. The building is a virtual facility, the construction of which was modeled on the most frequently constructed facilities of this type in Poland.

The building was divided into temperature zones grouping rooms with the same design temperatures. In Figure 2 we have marked the analyzed offices on selected floors. Additionally, in purple you can see a separate temperature zone of the corridors. The simulation was conducted for the entire building model, taking into account the actual heat exchange between all adjacent interior zones (offices, corridors and floors). The surrounding development primarily comprises four-storey tenement houses (Figure 3 and Figure 4). The analyses focused on separate spaces within the building’s volume, configured as open-plan office spaces. Each office module was assumed to measure 18.0 × 5.0 m. The rooms under analysis are located on the 3rd, 6th, and 19th floors. The examined office spaces have external walls oriented towards the south (S) and north (N). In total, eight thermal zones were defined within the building: offices on the three selected floors and a corridor (communication zone) (Figure 2).

Design solutions that are typical of this type of facility were adopted. The proposed structural solution of the building is often found in Poland, where brick or concrete fragments of partitions are combined with system glazing. It is most often a frame structure filled with porous ceramics or aerated concrete blocks. The ceilings are a reinforced concrete slab.

The glazed façade comprises triple-glazed windows, with each glazing unit consisting of 3.0 mm thick panes separated by 13.0 mm inter-pane cavities filled with xenon gas. The inner surface of the innermost pane is coated with a low-emissivity (low-E) layer. The heat transfer coefficient of the glazing unit is U = 0.94 W/(m²·K). The total glazed area amounts to 31.5 m², representing 50% of the façade.

The analyzed building meets the Polish Technical Requirements for Buildings [36] in the field of thermal insulation. The heat transfer coefficients of the building envelope elements are as follows: external wall (U_SZ = 0.122 W/(m²·K) < 0.20), ground floor (U_PG = 0.130 W/(m²·K) < 0.30), and flat roof (U_ST = 0.124 W/(m²·K) < 0.15).

2.2. Assumptions of the Analyses

The building’s operation—including the functioning of the cooling and heating systems, occupant activity, lighting operation, and internal heat gains from installed equipment—was defined using daily schedules (Figure 5). Internal heat gains were assumed as follows: 8 W/m² from equipment, 132 W per person, 11 W/m² from lighting, with an occupant load of p = 45 and an air velocity of w = 0.1 m/s. Clothing insulation varied seasonally: 0.5 clo in summer (underwear, short-sleeved blouse/shirt, light trousers or skirt, tights or thin socks, shoes) and 1.0 clo in winter (underwear, long-sleeved blouse or shirt, skirt or regular trousers, tights or socks, shoes) [37].

The occupancy schedules were adopted based on the typical pattern of use of an office facility in Poland, i.e., work from 7:00 a.m. (9:00 a.m.) to 3:00 p.m. (5:00 p.m.). Surveys conducted among users of this type of building were partially used.

Internal heat gains were assumed as follows:

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132 W per person: according to [38] (work: light; sitting position: 120 W/person; standing position: 140 W/person);

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11 W/m² from lighting: according to [39]; office 500 lx ≈ 7–12 W/m²;

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8 W/m² from equipment: according to: [40].

Operative temperatures are based on [38] for a specific human physical activity: at a low metabolic rate (e.g., sewing, accounting or typing) the air temperature in rooms (in winter) is 20 ÷ 22 °C, and in summer: 23 ÷ 26 °C. During cooling periods, 24 °C was assumed during working hours and 27 °C for the remainder of the day. For heating, the corresponding values were 21 °C during working hours and 16 °C outside these hours.

In [38] for a specific human physical activity: at a low metabolic rate (e.g., sewing, accounting or typing) the air movement speed in winter is a maximum of 0.2 m/s and in summer—0.3 m/s. The authors assumed avoiding the draft phenomenon in office rooms, so they assumed an air flow speed of 0.1 m/s.

Ventilation air flow was taken as: 20 m³/h∙person according to Polish Technical Requirements for Buildings [36].

Heat gains from occupants were determined according to activity level—sedentary office work corresponding to 70 W/m² (1.2 met) [37].

For the building under study, the climatic parameters for the city of Katowice, represented by a Typical Meteorological Year (TMY), were used as the external thermal load. The dataset was derived from meteorological observations collected between 2004 and 2018 and was adopted as the reference year [41].

The climate of Katowice is a transitional temperate climate, combining features of a maritime and continental climate. Available reports characterize the climate of Katowice as [42,43,44]:

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average annual temperature: approx. 8–10 °C;

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summers: usually warm, with average temperatures of 18–20 °C;

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hot days (above 30 °C) appear every year;

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winters: mostly cool, but increasingly mild, with temperatures around −1 to 2 °C;

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episodes of severe frost still occur;

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lots of cloudy days, especially in autumn and winter;

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winds usually light to moderate, most often from the west.

Snow cover is variable, and in recent years there has been a tendency to maintain it for a shorter period. Heating is still an important element of energy demand. Transition periods (spring, autumn) are characterized by high variability of conditions: sometimes warm and sunny, sometimes colder, with precipitation. At these times of the year, you can mostly benefit from natural ventilation and lower heating/cooling demand. Summers are getting warmer: there are often days with temperatures exceeding 30 °C. Heat waves (i.e., days > 30 °C) are becoming more and more common, which poses challenges to well-insulated and tight buildings (risk of overheating).

For construction, this means that traditional heat loss reduction strategies must be combined with adaptation strategies: overheating protection, hybrid ventilation, cooling systems, and increased resistance to extreme weather conditions.

2.3. Methodology of the Analyses

The analyses were carried out using building energy modelling tool—OpenStudio v.3.9.0 [45]. Simulation studies were conducted using OpenStudio using EnergyPlus as the computational core. The calculations were performed according to the procedures suggested by the software authors. OpenStudio is an application that facilitates the energy modelling of buildings. Its computational engine is the EnergyPlus v. 24.2.0 program, while the building geometry is defined using SketchUp v. 2022. In addition to energy calculations, the software supports the analysis of thermal comfort and lighting conditions through interoperability with the Radiance program. The application also enables the import of results from external tools such as Window v. 7.8.57 and Therm v. 7.8.57, which determine the optical and thermal characteristics of windows, glazed façades, and thermal bridges. Beyond the energy analysis of building solutions, the platform allows for detailed modelling of technical building systems, including domestic hot water, ventilation, heating, cooling, and renewable energy sources. It is further possible to incorporate selected features of the building’s surroundings into the model. The analyses are based on the FEM (Finite Element Method), complemented by empirical equations for phenomena not otherwise described. Calculations are performed using a defined time step and climatic data corresponding to a Typical Meteorological Year (TMY) [45,46,47].

The authors assume that the CMIP5 model can be used in studies related to the assessment of the impact of climate change on buildings, taking into account certain limitations related to it. CMIP5 is the fifth phase of an international research and simulation project that aims to compare the results of different global climate models. CMIP5 models cover a wide range of simulations that take into account different greenhouse gas emission scenarios (so-called RCP—Representative Concentration Pathways). This model has a number of advantages, including: global scale and comprehensiveness, data for various scenarios, long-term forecasts or standardized approach. Certain restrictions include: spatial resolution, no regionalization, data complexity or usability in short-term forecasts.

According to the authors, the choice of the CMIP5 model over CMIP6 in the context of assessing climate change and its impact on buildings in temperate climates is justified in terms of data availability and the purpose of the study. The authors are aware that CMIP6 is a newer and more developed version, and in many cases its use is preferred. However, in certain situations the CMIP5 model may be more appropriate, especially in the context of comparisons and follow-up of previous studies. CMIP6 models introduce many new scenarios and parameters, but in some cases the availability of complete and consistent data from this phase is limited, especially in the context of long-term archives that rely on CMIP5. For researchers who need to relate to the results of reports or analyses based on CMIP5, it may make more sense to use this model to maintain continuity in research. There are many data processing, analysis, and visualization tools that are based on CMIP5 datasets and have been optimized for this data. In some cases, if research must be conducted using already existing computing resources, CMIP5 may be more compatible. While CMIP6 brings many new elements, such as more advanced emission models and socio-economic scenarios (SSPs), CMIP5 offers stability and consistency in long-term climate change analysis, especially for long-term construction projects. When using CMIP5, it is easier to compare and continue existing studies or implement new ones based on existing results. CMIP5 models have become the de facto standard in many scientific fields, including structural engineering, where climate change is important for building design and management. CMIP6 introduces more detailed data, but CMIP5 is sufficient when the aim of the study is to obtain preliminary, general results on climate change. CMIP5 models can provide robust climate predictions without the need for complex analyses related to new SSP scenarios.

While CMIP6 introduces many modern scenarios and technologies, CMIP5 still has its strengths in studying climate change in long-term construction projects, especially when the goal is: continuation of previous research, comparison with existing literature, use of already available tools and databases and performing analyses based on RCP scenarios.

Therefore, depending on the context and objectives of the study, CMIP5 may be a reasonable choice, especially when it comes to simpler predictions or analysis based on previous, well-documented data. The authors recognize that for more advanced analyses and more accurate forecasts, especially in the context of new greenhouse gas emission scenarios, CMIP6 may offer better options. At the same time, they note that the CMIP5 model can be used in studies on the impact of climate change on buildings, but it is important to be aware of the limitations related to spatial resolution, local climate effects, and specific construction requirements. If further research is needed and more accurate forecasts are needed for a specific area, it may be advisable to combine the results from the CMIP5 model with regional data or use higher-resolution models (e.g., RCM).

The authors adopted the projected trajectory of climate change in accordance with the HadCM3 model [48]. The HadCM3 model is a climate general circulation model developed by the Hadley Centre for Climate Prediction and Research in the United Kingdom. It is considered the reference model from which the era of modern coupled models began to be counted. It is used to simulate past, present, and future climate change—often within greenhouse gas emission scenarios (e.g., IPCC SRES, later RCP). Model elements include: HadAM3 (atmosphere model—dynamics, radiation, clouds, precipitation), HadOM3 (ocean model-currents, heat, salinity), sea ice model (ice thickness and extent, energy exchange), MOSES (land surface and vegetation model), Coupler (ocean-atmosphere coupling), and emission scenarios (external conditions-e.g., SRES (Special Report on Emissions Scenarios) A2, B1, or RCP (Representative Concentration Pathways) RCP4.5, RCP8.5, etc.). The HadCM3 model generates extensive climate data sets that can be analyzed regionally. The most important outcome elements of the scenario are: air temperature (average, min., max.), precipitation, atmospheric pressure, relative humidity, radiative fluxes (short-wave and long-wave), wind speed and direction, sea surface temperature, salinity and ocean circulation, snow cover, and sea ice.

Following a review of available methods for generating datasets representing future climatic conditions for building energy simulations, the authors selected the morphing and statistical approaches. Both methods enable the modification of existing TMY datasets while preserving the hourly resolution required for simulation studies. Therefore, the modification of climatic data was undertaken using the CCWorldWeatherGen v.1.1.2 program [49], which applies the morphing technique to adjust contemporary datasets [50]. This technique involves two principal operations on the input data: shifting, applied when the variable changes by an absolute difference in its mean value, and stretching or scaling, applied when the change in the mean value is expressed as a percentage. When projecting current climatic data onto future conditions based on the selected scenario, a combination of both operations is employed. The shift of the current climatic parameter value x_a by the monthly variation ${dx}_m$ for each month m is determined according to the following equation:

$$x=x_a+{dx}_m$$

(1)

where dx_m—absolute change in the average monthly value of the variable in a given month.

After this transformation, the monthly variance of the variable remains unchanged. The stretching by the s_m coefficient is performed based on the following formula:

$$x=s_m·x_a$$

(2)

where s_m—scale factor of the average monthly value for month m.

This transformation changes the variance value according to the equation:

$${〈{\sigma }^2〉}_m=s_m^2·{〈{\sigma }_a^2〉}_m$$

(3)

The combination of both operations is described by the equation:

$$x=x_a+{dx}_m+s_m·\left(x_a·{〈x_a〉}_m\right)$$

(4)

In this case, the variance is:

$${〈{\sigma }^2〉}_m=s_m^2·{〈{\sigma }_a^2〉}_m$$

(5)

3. Results and Discussion

As a result of the modelling process, a representation of the building’s performance under climatic loads was obtained for the base (reference) year and the projected years 2050 and 2080. Figure 6 illustrates the selected variable—air temperature—for the modified baseline climatic data. The results concerning energy performance for selected thermal zones are presented for January and July, as these months are the most representative for the purposes of the analysis.

Based on the results obtained, an increase in outdoor air temperature is evident in comparison with the current climate (Figure 6). The minimum value of the average daily outside air temperature is −8.9 °C, −5.4 °C and −3.2 °C for TMY, 2050 and 2080, respectively, so it increases by 2.5 °C in 2050 and by 5.7 °C in 2080 compared to the base year. The maximum value of the average daily outside air temperature is 28.3 °C, 32.3 °C and 35.1 °C for TMY, 2050 and 2080, respectively, so we observe an increase of 4 °C in 2050 and 6.8 °C in 2080 compared to the base year.

Considering the average daily outdoor air humidity, a decreasing trend is observed for all months in both forecasted years. During the autumn and winter months, values range from 72% to 90%, while in the spring and summer period they range from 58% to 78%. Analysis of wind speed indicates minimal variation, with prevailing directions remaining unchanged.

The situation differs somewhat in the case of total solar radiation intensity. For January, February, March, November, and December, the values decrease in the years 2050 and 2080 compared with the base year. However, during the remaining months (spring and summer), the relationship is reversed; in the projected future years, these values are higher than at present. Consequently, it can be inferred that the building in question will increasingly require cooling due to the potential for indoor overheating.

Analysing the annual final energy demand for individual office spaces reveals an increase in cooling energy demand for both forecast periods, accompanied by a reduction in heating energy demand across the building, irrespective of façade orientation. These variations are also influenced by the floor level on which the analysed space is located (Figure 7 and Figure 8). As anticipated, the geographical orientation of the façade exerts a significant impact on final energy demand: the south-facing façade exhibits almost twice the cooling demand of the north-facing façade. In contrast, the difference between the south and north orientations in terms of heating demand is less pronounced. Notably, these differences diminish by 2080.

The obtained results refer to one GCM climate model. This approach may raise some concerns among some researchers, but the authors consider this approach sufficient for the purposes of the analysis, especially if we take into account the following circumstances:

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less risk of extreme climate change in the short term

The temperate climate is characterized by relatively smaller fluctuations compared to tropical or Arctic regions. As a result of climate change, the temperature increase predicted in this region is relatively moderate, and for example: changes in rainfall may be less drastic in the short term (e.g., 20–30 years). In this case, if the climate model reflects these trends well, predictions about the future climate can be precise enough for building design purposes.

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stability of climate trends

In temperate climates, changes in temperature and precipitation over a long period (e.g., several decades) may be predictable and gradual. Unlike areas with more extreme conditions (e.g., subtropical or Arctic regions), where climate change can lead to more radical changes (e.g., melting glaciers, stronger hurricanes), in temperate climates, changes can take a more gradual form, meaning that a single model, especially for stable emission scenarios, may be sufficient.

In temperate climates, basic variables such as air temperature and precipitation are crucial for assessing a building’s behavior (its energy demand and thermal comfort). Climate models for this type of climate zone, even if they are only approximations, usually provide sufficient accuracy in predicting these basic parameters over the medium term (e.g., 30–50 years). In the context of construction, these forecasts may be good enough to conduct analyses related to the energy efficiency of buildings or insulation requirements.

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less uncertainty in forecasts

In temperate climates, changes in climate parameter forecasts are typically less divergent between different climate models than in regions with more extreme conditions. Climate models can make similar predictions when it comes to overall warming trends or changes in precipitation. The differences between them may be small, especially when it comes to the average forecast period (e.g., until 2080). In this case, the choice of a single model, based on robust data and forecasts, may be sufficient to perform analyses.

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long-term durability of buildings in temperate climates

Temperate buildings are typically designed for long lifespans (50, 100 years, and more), but climate change in this region can be relatively slow. This means that for the purposes of assessing a building’s energy performance, a model based on medium-term forecasts (e.g., by 2080) can provide sufficient precision in assessing the impact of climate change on the building. Even if climate change continues, its impact on buildings in temperate climates can be relatively easy to predict from a single model.

While the use of multiple climate models can improve forecast accuracy, in temperate climates where changes are relatively mild and climate variability is not as extreme as in other regions, using a single model may be sufficient, provided that the model is well-fitted to local conditions and takes into account important variables such as temperature, precipitation, humidity, and wind. Additionally, long-term changes in a temperate climate can be predicted within a single, robust model, making this approach practical and sufficient for assessing building behavior.

Analysing the final energy demand for heating in January reveals that the south-facing floors exhibit lower values than the north-facing floors (Figure 9). This is attributable to the greater number of sunshine hours received by the south-facing façade. The highest demand occurs on the lowest, north-facing floor. For both orientations, the 6th and 19th floors display very similar final energy demand values for heating, which can be explained by the absence of shading from neighbouring buildings.

4. Conclusions

The results of the analyses clearly indicate a shift in the prioritisation of final energy demand within buildings. As climate change progresses, the energy required for cooling is projected to become the dominant factor influencing total building energy consumption, while the demand for heating energy will decline.

The results indicate that, for the south-facing façade, the difference in final energy demand for cooling is Δ = +1.17 ÷ 1.22 GJ in 2050 and Δ = +1.78 ÷ 1.86 GJ in 2080. The greatest increase occurs on the 19th floor, which can be attributed to the absence of shading from adjacent buildings. For the north-facing façade, the difference is Δ = +0.86 ÷ 0.92 GJ in 2050 and Δ = +1.35 ÷ 1.44 GJ in 2080.

Considering the results for heating, it can be concluded that for the south-facing façade, the difference in final energy demand between individual floors is Δ = −0.54 ÷ 1.09 GJ in 2050 and Δ = −0.80 ÷ 1.23 GJ in 2080. The smallest difference occurs on the 19th floor, which can be attributed to the absence of shading from neighbouring buildings. For the north-facing façade, the difference between individual floors is Δ = −1.08 ÷ 1.09 GJ in 2050 and Δ = −1.47 ÷ 1.50 GJ in 2080.

Table 1. Differences in final energy demand for cooling and heating by each floor and elevation orientation.

Floor	Orientation	Differences in Final Energy Demand Compared to the Base (References) Year [GJ/Month]
		Cooling		Heating
		2050/July	2080/July	2050/January	2080/January
III	S	+1.18	+1.80	−1.08	−1.23
	N	+0.86	+1.35	−1.09	−1.50
VI	S	+1.17	+1.78	−1.54	−0.80
	N	+0.86	+1.36	−1.09	−1.48
XIX	S	+1.22	+1.86	−0.54	−0.80
	N	+0.92	+1.44	−1.08	−1.47

presents the differences in final energy demand for cooling (July) and heating (January) between the forecast years and the base year.

The magnitude of change in energy demand is markedly greater for cooling than for heating.

Another interesting conclusion that can be drawn from the obtained results concerns the differentiation of total energy consumption depending on the altitude at which the zone under consideration is located. In the case of heating (Figure 8 and Figure 9), the lowest floors are characterized by the highest energy consumption, which is due to shading of adjacent buildings, which limits solar gains. The highest part of the building has higher energy consumption than the central part due to extreme exposure to unfavorable weather impacts (e.g., wind).

Similar conclusions apply to building cooling (Figure 7 and Figure 10). In this case, heat accumulation in the highest parts of the building and heating of the roof surface with solar radiation play an important role.

In summary, it can be stated that a modern tall office building should have a differentiated design of external partitions in terms of thermal and optical parameters and an adaptive HVAC control system.

For each facility currently being designed, its energy parameters would need to be shaped, taking into account upcoming climate changes, making it possible to maintain low energy demand in changing external conditions.

The impact of the future climate, generated on the basis of RCP (Representative Concentration Pathways) scenarios for 2050 and 2080, on the energy consumption of a high-rise office buildings is innovative for several key reasons.

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A unique combination of local conditions and climate projections

Although research on the energy efficiency of buildings in the context of climate change is becoming increasingly common, it is rarely conducted in the context of a specific city, taking into account specific local conditions. In the case of Katowice, which is located in an urban zone with specific climatic and economic conditions, such a study is individual in nature and allows for drawing conclusions specific to this region. Climate forecasts for 2050 and 2080 are not yet widely used in local studies, and their inclusion in the context of office buildings in Katowice brings a new quality to existing knowledge.

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Adaptation to the specificity of the region

Studying energy consumption in buildings in the context of climate forecasts allows the creation of models that are not only general analyses but also adapted to the specific conditions of the region. Katowice’s climate is different from other cities, which means that a general approach alone is not enough. Such studies enable precise determination of how specific weather conditions may affect buildings’ energy systems and also allow the design of more sustainable and climate-resilient solutions.

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New directions in adaptation to climate change

While research on the energy efficiency of buildings in the context of climate change is indeed present in the literature, attempts are rarely made to comprehensively analyze adaptation to a changing climate in the long term (e.g., over a period of 50–60 years). Studies forecasting changes in energy consumption in office buildings by 2050 and even 2080 are unique in that they take into account not only current technologies but also changes in demographic, technological, and economic trends. This allows for the development of new business models that take into account long-term forecasts and ensure sustainable development.

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Response to specific urban development challenges

Katowice, as a city that is rapidly developing towards a „smart city” (smart city), must face challenges related to the growing number of office buildings, the changing urban landscape, and the growing demand for energy. Such research is therefore essential to appropriately adapt urban planning processes and urban infrastructure development, taking into account both the aspects of energy savings and adaptation to climate change.

In the context of the above arguments, the study of energy consumption in office buildings under the conditions of the forecast climate for 2050 and 2080 is an important research area that responds to current and future challenges in the field of urban sustainability and energy efficiency.

In the perspective of further research by the authors, issues include ways of adapting an existing building to changing climatic conditions. An attempt will be made to use available technical solutions, both passive and active. Perhaps it would be worth considering whether, when designing this type of facility, we should not take into account the differentiation of solutions in the field of transparent partitions depending on their location in relation to the cardinal directions or also in connection with the height of their installation and the shading of the surrounding buildings.