Buildings in Hot Climate Zones—Quantification of Energy and CO₂ Reduction Potential for Different Architecture and Building Services Measures

Abstract

Reducing energy and associated greenhouse gas emissions in buildings is one of the key aspects of climate change on a global level. To put the building sector on a low carbon development path, policies and adequate financing play a crucial role in each region. In the global South, policies and regulations related to the decarbonization of the building stock are increasingly being implemented. For policy and decision makers, adequate data on the status quo of the building stock, as well as the quantification of energy reduction measures, are essential to make informed decisions on the building regulatory and funding framework. The objective of this study is to provide data-driven insights into the potential for energy and CO₂ reduction in buildings across various hot climate zones in the Global South. A simulation-based approach was employed to model five different building types, ranging from residential homes to office buildings, under a variety of architectural and building services scenarios. The simulations were conducted using the dynamic building energy simulation tool EnergyPlus, which assessed the impact of various energy-saving measures under both current and projected future climate conditions. This study concludes that optimizing passive design features, such as improved windows, solar shading, and reflective surfaces, in conjunction with active systems like decentralized cooling units and renewable energy integration, can result in a notable reduction in energy demand and emissions. Our findings provide a robust basis for policymakers to develop targeted energy efficiency strategies for buildings in hot climate zones, which will play a crucial role in achieving climate goals in the Global South.

1. Introduction

There is a worldwide effort to reduce greenhouse gas (GHG) emissions associated with the construction, use, and demolition of buildings. Adequate financing mechanisms, as well as policies and building regulations, are key factors for the improvement of standards towards higher energy and resource efficiency and subsequent lower emissions in the construction sector. Whilst the global North has had climate change measures on its agenda for the last decades, in the global South, emissions per capita tend to be lower than in the global North due to lower industrialization and modern construction methods in many regions. However, the proportion of emissions from the building sector is rising rapidly in many countries of the global South, as urbanization and population growth lead to an increase in construction activity.

This study places a significant emphasis on the Global South, given the accelerated urbanization that is occurring in these regions and the resultant surge in emissions associated with the building sector. Overall, the building sector in the global South still contributes less to global greenhouse gas emissions than in the global North, but growth rates are high, which underlines the importance of sustainable building and energy practices in these regions. A significant number of countries in the Global South lack comprehensive energy efficiency policies, which makes the implementation of targeted interventions a necessity. Furthermore, buildings in hot and humid climates are particularly vulnerable to climate change, which places additional strain on already inefficient energy systems. The resolution of these challenges offers substantial potential for emissions reduction and sustainable development in these regions.

In this context, the Sustainable Development Goals (SDGs) play a crucial role in identifying key drivers and measures towards a sustainable transformation. SDG7 (Affordable and Clean Energy) highlights the challenges and key goals that are strongly linked to the built environment as one of the key contributors to greenhouse gas emissions [1].

Reducing greenhouse gas emissions associated with buildings in the global South is a critical component of global efforts to combat climate change. The global South, which includes regions in Africa, Latin America, Asia, and the Middle East, faces unique challenges in reducing emissions due to factors such as rapid urbanization, economic development needs, and limited financial and technical resources. In a recent study, the trajectories of the key indicators of efficiency in the building sector have been analyzed and compared for emerging and developed regions. It highlights that since economic development will increase housing sizes and comfort demand in developing regions, efficiency improvements and relevant policies are needed to limit energy consumption [2]. In a recent meta-study by Kutty et al. [3], the authors concluded that buildings in hot and humid climate zones are especially vulnerable to the effects of climate change as any change would further impact the already strained energy systems, which are, in addition, still mostly based on fossil fuels.

There is still a disparity in policies related to the reduction of energy in buildings between the global South and the global North that stems from a combination of economic, institutional, and sociopolitical factors. The lower prevalence of energy reduction policies in buildings in the global South compared to the global North is a complex issue influenced by economic limitations, institutional weaknesses, lack of awareness, and global inequalities. Addressing these challenges requires tailored approaches that consider the specific socioeconomic and environmental contexts of these regions, along with increased international support and cooperation. Reducing GHG emissions in the building sector in the global South thus requires a multifaceted approach that combines technology, policy, and community engagement. By adopting sustainable practices and leveraging international support, these regions can build a low carbon future while improving living conditions and supporting economic development.

Several studies related to so called green policies have been undertaken in the past [4,5]. In general, it is argued that the effect of energy policies relies on efficiency, effectiveness, and legitimacy. In previous research, several developing countries have been investigated regarding energy and CO₂ intensity aspects [6], with more recent articles specifically focusing on the barriers [7] in the example of Brazil. A particular focus on improving the efficiency of the buildings lies in the local building codes. Examples can be taken from several programs that have the implementation and optimization of building codes in countries of the global South as a central focus [8]. A study by Gaum et al. [9] undertaken in 2022 concluded that approximately 47% of selected Global South countries are not implementing any form of building energy efficiency codes and thus recommended that mandatory regulations should be put in place.

To address a transformation of the built environment in hot climate zones, there are—in some respects similar to the colder climate zones—several key strategies that can be undertaken. Assessing autochthonous buildings in these regions delivers impactful strategies, as people have had to deal with overheating for hundreds of years without active cooling technologies. The use of shaded areas and courtyards are simple yet effective measures for the provision of comfortable building environments [10]. Local heritage buildings and the improvement of those buildings are a good source of information on how passive design strategies can impact indoor thermal comfort [11,12].

Measures to improve passive designs are key for a simple and highly effective reduction in heating or cooling energy demand [13]. To reduce overheating, strategies involving the utilization of thermal mass are highly effective in this context. There are several studies that have analyzed this effect with a focus on hot climates. In particular, Hu et al. [14] identified in a recent article a series of passive strategies related to design approach, building envelope, and passive cooling systems aimed at reducing indoor temperature and subsequent cooling loads. Several other studies in this context focus on thermal mass inertia [15] and other passive cooling strategies with a particular focus on hotter climates [16,17]. More advanced concepts focus on the improvement of the cooling effect of the thermal mass with phase change materials (PCMs) [18,19]; however, whilst the results are promising, the availability as well as the cost of these materials must be taken into account. In addition to the improvement of the thermal inertia of buildings, the most critical factor in the reduction of the cooling load remains building envelopes. Green envelopes using plants [20], as well as cool envelopes using particular reflective coatings [21], have been investigated in hotter climates.

The challenges posed by climate change in urban areas, particularly the rising temperatures due to the urban heat island effect, significantly increase the demand for cooling. This additional energy consumption results in elevated greenhouse gas emissions, underscoring the imperative for the implementation of energy-efficient measures. Targeted building renovations can markedly reduce energy consumption and emissions, which is of particular significance in urban areas. Enhancing energy efficiency through improved insulation, passive cooling, and the integration of renewable energy sources helps to mitigate climate change. Considering the rising urbanization and energy demand in cities, comprehensive renovation efforts are crucial to achieve climate objectives. For hotter climates, the challenge lies foremost in the adaptation of envelopes to reduce heating gains. Articles in this context highlight the importance of strategies for energy reduction [22,23], e.g., applying double skin facades. Once the passive design strategies have been exploited, active systems can be implemented to provide the necessary cooling. Foremost, ventilation is required to improve comfort, especially in humid regions. To increase efficiency, also hybrid systems can be applied in hotter climates as outlined in a study by Kabanshi et al. [24] as well as Kim et al. [25]. Other active technologies include solar cooling systems [26]. However, as with PCMs, it is important to assess whether these technologies are readily available and cost-efficient in their implementation in certain regions of the global South. Advanced simulation and thermal comfort models can provide meaningful assessments for the high variety of measures applicable to hotter climates [27,28].

Overall, it is clear that actions need to be both comprehensive and strategic. Thus, in recent years, a series of studies has been undertaken looking into scenarios for reducing energy demand in buildings in hot and humid climate zones [29,30,31,32], with some focusing, in particular, on assessments for retrofitting [33,34]. Overall, the goal is to also aim for net zero energy buildings (NZEBs) in hotter regions [35].

The German Agency for International Cooperation (GIZ) has been working to support, amongst others, countries in the global South in various programs and projects on relevant actions to reduce greenhouse gas emissions in buildings. In one of the recent activities, the GIZ implemented a program in collaboration with the National Secretariat of Housing (SNH) of the Ministry of Regional Development (MDR) called “Energy Efficiency in Sustainable Urban Development, Focus: Social Housing” (EEDUS) [36]. This program aimed to improve the energy efficiency in new social housing units in Brazil. Even though the program mainly focused on housing, other building types also have a significant reduction potential, especially when looking at the existing building stock. According to the Brazilian Energy Research Company (EPE), in 2018, 28.3% of the electricity produced in Brazil was consumed in residential and public buildings, and this trend is growing. In 2022, buildings in Brazil consumed 239 TWh, which represents 41% of the country’s electricity. Considering the share of electricity consumption in buildings, this sector can have the biggest potential for electrical efficiency [37].

In order to implement efficient policies and funding frameworks, adequate data on the status quo, as well as the expected impact of improvement measures related to energy efficiency, are a necessity. Out of this context, a study has been commissioned by the GIZ to provide assessments of adequate energy efficiency strategies related to various building types. The objective of this study was to develop both a reference system for calculations of energy demand and GHG emissions and the calculation and simulation of energy demand, GHG emissions, cost ranges, and thermal comfort for Baseline scenarios and for different energetic optimization scenarios. To apply these results not just to the Brazilian market but also to other regions where the GIZ is active, their analysis covered a series of different building types for several hot climate zones. The goals were to support the decision-making of policymakers in partner countries of the GIZ that are located in hot climate zones and to prepare proposals for climate financing using the generated energy and GHG emission data compiled by this assessment.

The overall results of the research have been published in the framework of GIZ reports [38,39]. This study is based on these reports, summarizes the key findings of their research, and provides a comprehensive analysis, methodology, and results on a multitude of simulated scenarios for energy efficiency measures related to the optimization of the architecture and building services of different building types in various hot climate zones. Whilst this paper is based on the above study, it provides a more comprehensive overview of the methodology applied and the specific findings for research purposes. Whilst the original report was mostly aimed at policymakers, the paper focuses more on the research aspect and the scientific goals of the selected approach. The aim of this paper is thus to present a methodological approach with its benefits and limitations to provide a basis for future work in this respect.

2. Methodology

Assessing a variety of scenarios for an outcome that should serve as a basis for policy decisions requires a highly structured and concise approach. Thus, our methodology comprises four consecutive steps to deliver meaningful results: (1) Baseline Model Definition, (2) Baseline Model Simulation, (3) Definition of Scenarios, and (4) Simulation of Scenarios. The primary focus of this methodology is logically simplifying each model, thoroughly defining, developing, and evaluating the Baseline models and their associated scenarios, and presenting the results in a clear and practical way.

2.1. Baseline Model Definition

In Step 1 of the process, the building types are defined in detail. This includes a description of the architecture, building systems, and internal conditions (depending on the building type). The design of the buildings has been compiled in a 3D model and subsequent architectural drawings, including floor plans, sections, and elevations. This includes the number, size, and area of transparent elements, the shape and compactness of the buildings, and the overall external envelope. In addition, orientation was defined as a fixed parameter. The buildings were situated within a theoretical urban context, free from any obstructions or shading caused by surrounding structures. Their designs were developed to be adaptable to diverse architectural and climatic regions. Consequently, the buildings are devoid of specific stylistic elements typical of various countries, serving instead as purely functional prototypes.

The building types are, therefore, entirely theoretical models that could be used in any climate zone. It should be noted that while it is understood that climate-adaptive architecture should and must focus on the specific conditions and context of a building to truly exploit efficiency measures, this study has been specifically designed to compare the same architecture with different materials and technical qualities. This represents a highly theoretical approach aimed at drawing conclusions about the most suitable solutions for specific climates, building types, and levels of quality enhancement.

2.1.1. Building Types

Overall, five types of buildings, including two types of single-family homes, have been analyzed as part of this study to cover a wide range of different buildings:

• Bungalow: Typical residential single-family home, 60 m²
• Townhouse: Typical residential single-family home, 80 m²
• Apartment: Typical residential multi-family home, ranging from 40 m² to 80 m²
• Hotel: Typical hotel building or student dormitory, 22 m² (average of a single room)
• Office: Typical office or government building, 450 m² (typical floor area)

As illustrated in Figure 1, this study employed standardized, theoretical building models to ensure direct comparability across different climate zones as well as standardized material properties across all building types for the Baseline models (

Table 1. Material properties for Baseline building types.

Component	U-Value [W/m2K]
External Walls	1.7
Window Glass	4.0 (g-Value: 80%)
Window Frame	1.8
Internal Walls to Staircase	2.4
Floor Slab	1.48
Roof Flat	0.99
Roof Slanted	1.19

). These models are intentionally simplified to clearly demonstrate the effects of architectural and technical measures on energy consumption and emissions.

2.1.2. Internal Loads

For the internal loads, all schedules for occupant presence, heating, and electrical loads are defined according to the standard values of the Swiss “SIA Merkblatt 2024 Raumnutzungsdaten für die Energie- und Gebäudetechnik” [40]. The building types “bungalow” and “townhouse” were considered single-family houses with a floor area of 30 m²/person. The building type “apartment” was considered as a multi-family house with the same occupancy rate. The building types “hotel” and “office” have different types of rooms inside; “office” has open spaces and individual offices as well as corridors and WCs, while “hotel” has hotel rooms, corridors, two small individual offices, reception, and restaurant. For each type of space, the corresponding space use data from the aforementioned SIA leaflet was used (see Figure 2).

For each building type, different measures for the architecture and building shell (i.e., thermal properties), as well as measures for the building energy systems and renewable energy, have been defined.

2.2. Baseline Model Simulation

In Step 2, the Baseline models incorporating five distinct building typologies were simulated. The thermal dynamic simulation environment EnergyPlus (v.9.5.0) [41] was employed for these simulations. EnergyPlus is an open-source, cross-platform, dynamic building energy simulation program that performs hourly calculations, allowing engineers, architects, and researchers to model energy consumption (such as heating, cooling, ventilation, lighting, and plug and process loads) as well as water usage in buildings. Funded by the U.S. Department of Energy’s Building Technologies Office, EnergyPlus serves as a valuable tool for building performance analysis. Each model is based on one of the five pre-defined building types and includes specific conditions for materials, technical building systems, and schedules for occupancy, lighting, and equipment.

2.2.1. Climate Data

In order to allow for a wide range of hot global regions to be covered by this study, five locations have been selected to represent five different regions, with four out of five selected cities located in Brazil. The climate data for the cities have been chosen to be representative of a series of other cities in similar climate zones (see Figure 3).

To also take future climate changes into account, two different datasets for climate data have been used for this study. Dataset 1 is a climate dataset of typical meteorological years (TMY), which results from averaging the datasets of the last 10 years (from 2006 to 2015). The TMYs were compiled by the “TMY Generator” Webserver, which is a part of the “EU Science Hub” from the European Commission’s science and knowledge service [42]. This dataset, therefore, presents results under the assumption that climate conditions will remain relatively stable over the coming years.

Dataset 2 is a future climate dataset that incorporates projected climate change scenarios, presenting results based on the assumption that climate conditions will shift over the coming years. To create Dataset 2, Dataset 1 was modified using the climate file generator “CCWorldWeatherGen”, developed by the University of Southampton in the United Kingdom [43]. Dataset 2 represents the future climate change scenario A2 of the time horizon 2050s. A comparative study of climate file generators, including “CCWorldWeatherGen”, is presented in Moazami, Amin et al. (2017): [44].

Despite certain limitations, Typical Meteorological Year (TMY) data are useful for global analyses due to their standardization and comparability across different regions. TMY data represent the mean weather conditions over multiple years, thereby ensuring reliability in the identification of long-term trends. Their extensive availability and coverage of diverse climate zones facilitate accessibility for large-scale studies. For global assessments, where macro-level trends are the focus, TMY data provide sufficient accuracy without necessitating the use of more complex and resource-intensive models. Ultimately, they offer a practical balance between precision and feasibility for global energy and emissions evaluations.

2.2.2. Emission Data

To calculate greenhouse gas emissions, emissions data based on IEA factors for total CO₂ emissions were used. All results were compiled using the following emissions data [45]: data for Brazil/Electricity 2019, emission factor Brazil Electricity 2019: 0.074 kg CO₂/kWh. It should be noted that although only four out of five locations for the weather dataset are in Brazil (Petrolina for C1 hot arid, Brasilia for C2 Savannah, Recife for C3 tropical, and São Paulo for C4 subtropical), the location Casablanca, MA for C5 Mediterranean was also calculated using the emission factor for Brazil. This is to ensure the comparability of results, as different emission datasets would distort the overview of the greenhouse gas emissions results.

2.3. Definition of Scenarios

In Step 3 of the process, three scenarios are established based on challenging yet regionally achievable measures. These measures are chosen to ensure that material properties and technical building systems are versatile enough for various applications and building types. Additionally, the selected measures are designed to be applicable across different climate zones and countries. The measures are categorized into architectural elements and those concerning technical building systems and renewable energy. The goal is to create accessible scenarios with high potential for replication.

2.3.1. Measures Architecture, Building Systems, and Renewable Energy

For the architecture and subsequent building envelope, the measures focus on passive design with the aim of reducing the cooling and heating energy demand. In the field of building systems, the measures relate to the supply of energy with technical building systems. Overall, there have been 11 different measures included in the architecture variations, seven different measures for the building energy systems and five different measures for the renewable energy systems. The combination of measures varies subsequently for each building type and each scenario.

In addition to the measures outlined in

Table 2. Overview of architecture, building systems, and renewable energy systems measures applied to the scenarios.

Measures Architecture	Measures Building Systems	Measures Renewable Energy
Standard building shell	Decentralized split units for cooling and heating	Domestic hot water solar thermal
Improved building shell low performance	Improved decentralized split units for cooling and heating	Photovoltaics
Improved building shell high performance	Central compression system (substituting split units)	Solar heating
Standard windows	Ceiling fan	Solar cooling
Improved windows low performance	Night cooling—natural	Heat pump (heating and cooling)
Improved windows high performance	Night cooling—mechanical
No external solar shading	Controlled ventilation with heat recovery
Fixed external solar shading
Flexible external solar shading/manual control
Flexible external solar shading/automated control
Light colored reflective surfaces on roofs and facades

, several other measures were tested in the simulations but were deemed unsuitable for the selected climates. These measures include evaporative cooling, earth ducts for preconditioning, and concrete core activation (see more detailed explanation in Section 3.1.4).

Different measures have been applied to different building types based on the need for heating (hot water) and cooling and the applicability of the passive, active, and renewable measures.

Table 3. Overview of measures applied to the different building types.

Building Type	Passive Measures	Active Systems	Renewable Energy	Energy [%]	CO2 [%]
Bungalow	Improved insulation, reflective surfaces, external shading	Night cooling, decentralized split units	Solar thermal	30–40	35–45
Townhouse	Improved windows, fixed external shading, thermal mass	Controlled ventilation with heat recovery	Photovoltaics, solar thermal	35–50	40–50
Apartment	Light-colored surfaces, adaptive shading	Centralized cooling system, hybrid ventilation	Photovoltaics	40–60	45–60
Hotel	Improved windows, solar shading, light-colored surfaces	Improved split units, controlled ventilation	Photovoltaics, solar thermal	35–50	30–45
Office	Reflective coatings, adaptive solar shading	Night cooling, centralized cooling	Photovoltaics, solar thermal	20–30	25.35

outlines the different building types and the respective measures and already provides an overview of the resulting energy performance impact (in column “Energy” as well as CO₂ emission reduction (in column “CO₂”).

2.3.2. Optimization Scenarios

The optimization from the Baseline to the three optimization scenarios focuses on measures related to the architecture (which only involve a change in material properties) and measures on building technology, including renewable energy systems. It is important to note that the overall architectural design does not change between the scenarios. This means that the number, size, and area of transparent elements, the shape and compactness of the buildings, and the overall external envelope and orientation remain the same in the Baseline and all scenarios. In addition to the Baseline, three optimization scenarios are defined to improve the Baseline (Figure 4).

Scenario 1 focuses on refurbishing a typical low-standard building, assuming that only buildings with improvement potential (as opposed to demolition) are considered. This scenario includes only measures that are feasible for refurbishment projects. Therefore, it involves a moderate enhancement of the building envelope (reduced U-values, added external shading) and improvements to the building’s energy system (upgraded technical systems and solar thermal for domestic hot water).

Scenario 2 involves a theoretical new building constructed to a higher standard than that in Scenario 1. The building envelope features significantly improved values compared to the Baseline and Scenario 1, with additional enhancements such as adaptable solar shading and reflective coatings on transparent surfaces. The technical building system mirrors that of Scenario 1 but includes a mechanical ventilation system instead of natural ventilation.

Scenario 3 incorporates the same architectural enhancements as Scenario 2 but with significantly higher quality in technical building systems and renewable energy integration. This includes both solar thermal and photovoltaic (PV) systems, making Scenario 3 a more ambitious yet attainable option within the targeted climate zones.

2.4. Simulation of Scenarios

In Step 4, the simulation of the three scenarios is carried out, and the various models are compiled for the five chosen building types, five different climate zones, and four scenarios, including the initially developed Baseline. Each of the Baseline models is altered based on the three defined scenarios for each climate zone and modeled in the thermal dynamic simulation environment EnergyPlus [41]. Using the respective climate data, building model, and other framework conditions (such as lighting and equipment schedules), hourly energy performance data are compiled over one year. This provides detailed insights into the building’s behavior under varying conditions throughout the year.

This results in 75 different models covering five building types by five climate zones by three scenarios (Scenarios 1, 2, and 3). With the previously simulated 25 Baseline models (five building types by five climate zones), the overall results comprise a summary of 100 models. When the climate Change Scenario is also included in the overall datasets, there are a total of 200 simulation models (Figure 5).

Each simulation is carried out for the following results:

• Cooling Demand [kWh/m²a]
• Heating Demand [kWh/m²a]
• Energy Demand Electrical [kWh/m²a]
• Total Electrical Demand from the grid [kWh/m²a]
• Total CO₂ [kg/m²a]

In total, each model then provides the above five results. This adds up to 500 results for a 2020 climate dataset alone. In the following section, the key results are summarized and put into context for the overall analysis of the various building types and subsequent scenarios.

3. Results

The objective of this publication is to facilitate a comparative analysis of the relative differences between scenarios rather than to provide precise predictions for real buildings. Given that theoretical models are employed to illustrate trends and potential outcomes, there is no requirement for absolute calibration with measurement data. The focus is on identifying relative improvements, and therefore, detailed calibration is not a pertinent consideration in the context of this study. Given the complexity of the overall analysis, which includes 100 models within a climate dataset and provides five results for each model (i.e., 500 results for a climate dataset), the results section summarizes the key findings that apply to the overall analysis. These findings are subsequently summarized from different perspectives: from the point of view of (1) measures, (2) scenarios, (3) climates, (4) climate change, and (5) zero-carbon buildings.

3.1. Perspective of Measures

The measures can be classified into three categories: architectural measures, building systems measures, and renewable energy systems measures. Together, they create a chain of interventions that are reflected in the scenarios.

3.1.1. Measures—Architecture (Primarily Scenario 1)

Passive measures aim to reduce the demand for heating and cooling energy by implementing enhancements such as an improved building envelope, upgraded windows, fixed and adaptive external solar shading, and light-colored reflective surfaces on roofs and facades. The most significant impact can be achieved through improved windows with low-performance glass. The use of external solar shading is also critical across all regions, as these measures help lower the cooling load within the building without consuming operational energy. In regions with a high sun elevation angle (C1 hot arid, C2 Savannah, C4 tropical, and C4 subtropical), fixed external shading or manually controlled shading is sufficient. However, in areas with a lower sun elevation angle (C5 Mediterranean), flexible external solar shading is necessary, and automatic control is recommended to optimize its performance.

3.1.2. Measures—Building Systems (Primarily Scenario 2)

Building systems measures concentrate on the efficient delivery of energy to building systems. These measures encompass decentralized split units, central compression systems, ceiling fans, night cooling, and controlled ventilation with heat recovery. The most significant impact can be achieved by utilizing improved split units or replacing them with a central compression system, particularly in conjunction with night cooling. Night cooling effectively lowers the cooling load within the space while enhancing the cooling equipment reduces operational energy consumption (electricity). However, the use of ceiling fans has been found to have a minimal effect on thermal comfort.

3.1.3. Measures—Renewable Energy Systems (Only Scenario 3)

Renewable energy system measures focus on integrating sustainable energy sources into buildings to fully or partially meet their electrical and heating demands. These measures include solar thermal systems for domestic hot water, photovoltaics, solar heating and cooling, and the use of heat pumps. Among these, solar thermal for domestic hot water has the most significant impact, particularly in buildings where domestic hot water is a key requirement, such as residential buildings and hotels. Another important measure is the implementation of photovoltaics in enhanced scenarios, especially when combined with heat pumps. The orientation of the solar modules is critical to ensure consistent energy production throughout the year, minimizing significant gaps or peaks in winter and summer. For the climate data collected from locations in Brazil (Brasilia, Petrolina, São Paulo, and Recife for Climate 1 hot arid, Climate 2 Savannah, Climate 3 tropical, and Climate 4 subtropical, respectively), the tilt angle for the PV systems and solar collectors is set to 0° (horizontal). In contrast, for Casablanca (Climate 5 Mediterranean), the tilt angle is set to 30°, with the azimuth angle oriented to 0° (south-facing).

3.1.4. Measures Without Essential Effect

Several measures were tested in the simulations but were deemed unsuitable for the selected climates. These include:

Evaporative Cooling: In the simulated climates, which are already humid, the impact of additional evaporation is negligible.

Earth Ducts for Preconditioning: The climates in all considered regions exhibit a small annual variation in air and soil temperatures, leading to poor efficiency of the earth ducts. The presence of the heat exchanger further diminishes the effectiveness of the ground loops.

Concrete Core Activation: In all considered regions, soil temperatures are significantly higher than those in Central Europe, where this system is typically applied. Consequently, the efficiency of this system is negligible.

3.2. Perspective of Scenarios

From the calculations, three clusters emerge: Baseline (Cluster 1), Scenarios 1 and 2 (Cluster 2), and Scenario 3 (Cluster 3). Based on the room energy, the ratio of the three clusters is roughly 100 to 60 to 40%. Figure 5 and Figure 6 show this as an example of the building types townhouse and office.

The biggest difference is between the Baseline and Scenarios 1 and 2. Scenario 1 is, therefore, a lower-cost alternative for retrofitting, while Scenario 2 is a good option for a cost-conscious new building. Scenario 3 is reserved for more ambitious new buildings. It can also be seen that the reduction in emissions between the Baseline and Scenario 1 is greater for the townhouse (between 35 and 50% across the different climate zones) than for the office building (between 20 and 30% across the different climate zones). This is primarily due to the high internal loads in the office building resulting from lighting and equipment. In the scenarios, the most significant absolute effects across all building types are observed in the warmest climate zones: hot, Dry, and tropical. An example of this effect is shown below for the apartment building and the hotel. As the efficiency of the scenarios increases, the climatic difference between the regions gradually disappears—the effect of internal loads increases. The ratios remain about the same but weakened by a factor of about 2 (see Figure 6 and Figure 7).

A more detailed example is shown in Figure 8, which depicts the electrical energy demand for the building type apartment building for the tropical climate zones. The energy demand for cooling can be reduced by almost 40% between the Baseline and Scenario 1 and over 60% between the Baseline and Scenario 2.

Given the high compactness of this building type, the efficiency measures applied can be translated directly into significant emission reductions. Because the measures related to Scenario 1 are mostly in the “same cost” or “low cost” range, the investment can lead to high emission savings.

3.3. Perspective of Building Types

The smaller residential building (bungalow) has an unfavorable cubature in terms of energy consumption. Like the hotel, it also has a high consumption of domestic hot water. Therefore, it has a high energy consumption per unit area in the Baseline and all scenarios. The increase in energy efficiency of these building types can be achieved on the one hand by passive architectural measures and on the other hand by using renewable energy for domestic hot water. Measures for active room cooling have shown to have less of an effect.

The office building has high internal loads due to equipment and lighting, while domestic hot water is of lesser importance. Beyond passive architectural measures, the energy efficiency of this building type can primarily be enhanced through more effective space cooling methods, such as night cooling and controlled ventilation with heat recovery, as well as the implementation of energy-efficient lighting. Measures aimed at utilizing renewable energy for domestic hot water have a limited impact on the overall energy demand of office buildings. Bungalows, townhouses, and apartment buildings are the building types that offer the largest savings in absolute terms. Figure 9 shows this as an example of the hot, arid climate. For the residential buildings, the savings between the scenarios are evident. This is also the case for the hotel, although the savings are significantly lower for the office as the building has larger internal loads and a higher demand for domestic hot water. This becomes even more evident when the different uses (electricity for lighting and small power, domestic hot water, heating, and cooling demand) are assessed separately, as shown in Figure 10 (Baseline) and Figure 11 (Scenario 1). The savings from Baseline to Scenario 1 result in a 26% reduction for the building type office but a 42% reduction for the building type bungalow.

3.4. Perspective of Climates

From a regional perspective, several key differences can be highlighted. In principle, three clusters of cooling energy consumption emerge in the Baseline scenario: low consumption in the subtropical and Mediterranean regions (100%), medium consumption in the savannah region (200%), and very high consumption in the tropical and hot arid regions (500%). The percentages refer to the Baseline cooling energy demand. Considering the resulting electricity consumption for cooling, the ratio between the subtropical and Mediterranean regions (100%), the average consumption in the savannah region (150%), and the very high consumption in the tropical and hot arid regions (200%). These last two regions are also expected to have the largest impact of the measures.

The total cooling demand then also dominates the total electricity demand from the grid. As shown in Figure 12, the tropical and hot, arid climates still result in the highest total electricity demand across all building types compared to the other climate zones.

In Figure 13, the bungalow building type is exemplary, as shown for the Baseline. It is clear that the cooling demand, and consequently the overall energy demand, is highest in the hot, arid, and tropical regions. In Scenario 2 (Figure 14), the difference is already less prominent, but there is still a significant gap between the cooling demand for the hotter and more moderate regions.

3.5. Perspective of Climate Change

To take into account future climate changes, two different datasets of climate data were used for the simulations: current climate data and future climate data considering the changing climate scenario A2 of the time horizon 2050. Projected climate change data for 2050 showed that cooling demand will continue to increase for all building types considered while heating demand will be negligible in Climate 4 subtropical and Climate 5 Mediterranean. The rate of increase in total electricity consumption in the periods “TMY-2020” and “2020–2050” remains stable and varies between 20 and 50% for 30 years. Overall, the differences between scenarios and building types remain similar to those for typical meteorological years. However, the largest increase in CO₂ emissions due to climate change will occur in the hottest regions, as shown below in the comparison of the hot, arid climate (Figure 15) and the Mediterranean climate (Figure 16).

3.6. Perspective of Zero Carbon Building

The building types of bungalows and townhouses are capable of achieving carbon neutrality in all climate zones under Scenario 3 without the need for any additional measures. Figure 17 shows this as an example of the bungalow.

The residential building type is close to neutral—but could be improved with further measures, such as making the earth ducts completely carbon neutral. The office building is the most challenging building type to achieve carbon neutrality, followed closely by the hotel. Compared to the baseline, the emissions of these building types are only around 30% (office building) and 20% (hotel), with the Mediterranean, subtropical, and Savannah climate zones being the most suitable. Figure 18 shows this for the office building as an example.

4. Discussion

Our study provides compelling evidence that adequate architectural optimization and building service measures can significantly reduce energy consumption and CO₂ emissions in buildings situated in hot climates. These findings substantiate the efficacy of passive architectural measures, such as enhanced windows and external shading, in markedly reducing cooling demand across diverse climate zones. The most pronounced effects were observed in hot, arid, and tropical climates, where solar shading and reflective surfaces had the greatest impact. These measures are of paramount importance in the mitigation of overheating and the reduction of reliance on active cooling systems, which have the potential to increase electricity consumption and CO₂ emissions.

Regarding building systems, it is evident that decentralized split units and night cooling strategies offer the most substantial benefits with respect to cooling energy efficiency. Nevertheless, more sophisticated solutions, such as centralized systems coupled with renewable energy sources (e.g., photovoltaics and solar thermal systems), demonstrate even greater reductions in energy demand and emissions, particularly in scenarios emphasizing high-performance buildings. The integration of renewable energy sources is most effective in buildings where there is a high demand for domestic hot water, such as residential and hotel buildings. The deployment of photovoltaics, in particular, is of paramount importance in offsetting grid electricity consumption, thereby reducing emissions to an even greater extent.

Our analysis also indicates that the building type and internal loads have a considerable impact on the efficacy of the measures. For example, residential buildings, particularly bungalows and townhouses, exhibit the highest relative potential for emission reductions due to their lower internal energy loads compared to offices and hotels, which have higher lighting and equipment usage. These findings highlight the necessity for tailored energy efficiency strategies that consider building typology and usage patterns.

Regarding climate scenarios, the findings of this study indicate that future climate change will intensify cooling demands across all building types, with the most pronounced increases anticipated in hot, arid, and tropical zones. This highlights the necessity of implementing robust energy-saving measures that are not only suitable for current climatic conditions but also resilient to future changes. Scenario 3, which incorporates the most comprehensive set of architectural and renewable energy measures, illustrates the feasibility of achieving near-zero carbon buildings, particularly in residential settings in the analyzed climate zones.

For an outlook and further development of this study, the framework of the assessment should be enlarged to consider bigger entities such as building districts and urban quarters. The current study has the individual building at the core of the analysis and, thus, the extent of the building as a system boundary. Our study is thus limited to the optimization of the individual building under different framework conditions. To enlarge the optimization potential, other considerations such as land use, density or flexibility should be considered. These aspects are largely connected to the larger district, city, or regional level. The results of this current study can subsequently form the basis for further investigations on a larger area level. From a methodological point of view, the enlargement provides more complexity and could develop different scenarios on a district scale that are optimized regarding the mix of uses. Optimized scenarios could then be defined as target functions that allow the integration of renewable energies and load shifting between different building types in an economically and ecologically adequate way. In addition, future climate change scenarios (i.e., with a large time horizon of 2020/2050/2080) could be analyzed, resulting in many variants and considering a more severe shift in climate change. The results of this enlarged viewpoint towards districts and cities could provide corresponding urban planning scenarios for a series of combinations that are calculated and evaluated as a whole system regarding energy and CO₂. This would allow a comparison of different urban planning approaches for various framework conditions, thus extending the building view to the district and city view.

Like this current study, the enlarged analysis could provide decision support for policy makers related to framework conditions for the development of refurbishment and new planning actions.

5. Conclusions

Our results highlight that tailoring passive measures to specific regional climates and building types, along with renewable energy integration, can greatly enhance energy efficiency and reduce CO₂ emissions across different climates.

In hot and arid climates, fixed or flexible solar shading, combined with reflective surfaces on facades and roofs, is highly effective in preventing overheating and reducing the need for active cooling. In tropical regions, where high humidity and frequent solar exposure are common, shading is crucial, and improved window technologies can significantly reduce heat gain. Natural ventilation and external shading devices further optimize cooling strategies, minimizing reliance on energy-intensive air conditioning. In subtropical and Mediterranean climates, adjustable shading systems are essential to adapt to varying sunlight throughout the year, ensuring better comfort. Automated shading and reflective coatings can be optimized based on building usage and orientation.

In conclusion, this study provides a comprehensive analysis of the potential for energy and CO₂ reduction in buildings across different hot climate zones, offering valuable insights for policymakers and stakeholders in the Global South. Our findings underscore the efficacy of passive design strategies in curbing cooling demand while underscoring the pivotal role of renewable energy in attaining more substantial emission reductions. These results demonstrate that, contingent on the specific building type, substantial reductions in energy demand and emissions can be attained, particularly in residential buildings. We also highlight that policies should be building type-specific, thus focusing on measures with the highest efficiency based on the specifics of the building type. The necessity for energy-efficient solutions is likely to become increasingly pressing in the future, particularly in the warmest regions. It is, therefore, evident that the implementation of bespoke energy policies and the promotion of renewable energy integration are essential for the realization of a low-carbon future in hot climate regions.