Simulation-Based Performance Evaluation of a Desiccant Indirect Evaporative Cooling System for Office Buildings in Hot–Humid East African Coastal Climates

Abstract

In tropical regions like sub-Saharan Africa, conventional vapor compression HVAC systems contribute disproportionately to energy use, operating costs, and carbon emissions—particularly in coastal urban areas where humidity-driven cooling demand is extreme. Despite these challenges, viable low-energy alternatives remain largely underexplored for this region. This study presents the first simulation-based assessment of a desiccant indirect evaporative cooling (DIEC) system optimized for the hot–humid coastal climate of Dar es Salaam, Tanzania, addressing a critical gap in sustainable cooling research for coastal Africa. Using OpenStudio (version 3.9.0) and a custom EnergyPlus(version 9.3.0) latent heat removal algorithm, this study models a DIEC-equipped medium office building with 100% outdoor air ventilation and exhaust-air-based desiccant regeneration. The model reflects local construction practices, occupancy profiles, and weather data and is validated with >90% accuracy against experimental benchmarks. Results demonstrate that the DIEC system (1) maintains indoor thermal comfort (23.8–24.0 °C) during peak humidity periods, and (2) reduces annual cooling energy consumption by 10.2% relative to single-speed DX systems. These savings are particularly impactful in a context where electricity prices are rising, and HVAC loads consume 25–40% of building operational budgets. Furthermore, the system’s superior humidity control and stable power demand make it well-suited for integration with decentralized renewable energy sources. By establishing a context-specific benchmark for DIEC performance, this study delivers a novel, regionally tailored strategy for decarbonizing urban cooling in coastal tropical Africa.

1. Introduction

1.1. Background

Heating, cooling and ventilation systems in buildings consume a significant amount of energy. It is estimated that 50% of the total building energy is dedicated to space heating, cooling, and hot water needs for human safety and comfort [1]. This demand for air conditioning is rapidly increasing. For instance, in East and Southern Africa, it is expected that if energy efficient policies are not established, the electricity consumption from air conditioning will increase by 2.5 times before 2040 [2]. Unfortunately, most of this energy is derived from fossil fuels, contributing to increased carbon emissions. To reduce the use of fossil fuel consumption, it is essential to lower overall energy consumption and improve building energy efficiency. This can be achieved, in part, by reducing the energy demands of air-conditioning systems, and by using AC systems with a high Coefficient of Performance (COP) [3]. In this light, this research in interested in finding how air-conditioning energy saving opportunities can be optimized in an African region that remains underrepresented in the literature for the purpose of minimizing the energy demand within appropriate constraints.

1.2. Cooling Techniques

Several cooling technologies are used globally, with the most common including conventional vapor compression systems, evaporative cooling systems (ECSs), absorption and adsorption cooling systems (ACSs), and thermoelectric cooling systems. Although conventional vapor compression systems are widely adopted due to the maturity of technology, they have notable drawbacks. In particular, electric compressors are highly energy-intensive, contributing to increased carbon emissions and high utility bills. Additionally, many of the refrigerants used in these systems pose environmental hazards due to their high Global Warming Potential (GWP) [4].

Various efforts have been made to address these environmental and economic concerns. For example, Ref. [5] reviewed contemporary scientific progress aimed at improving vapor compression heat pump technology through the integration of solar technology. Their review covers systems such as the direct expansion solar-assisted heat pump system (DX-SAHP) and the indirect expansion solar-assisted heat pump system (IX-SAHP) [5]. However, these systems do not fully address the electric consumption associated with compressors, nor the environmental impact of high-GWP refrigerants.

Absorption cooling systems have been explored as alternatives to conventional vapor compression systems. These systems are attractive due to their relatively lower energy consumption, compatibility with low-grade thermal sources (such as solar and geothermal), low operational cost, and use of environmentally friendly absorbent refrigerants (such as LiBr, H₂O, NH₃, LiNO_3, and LiCl) [6]. However, their major limitations include the excessive size of the cooling unit and their relatively low Coefficient of Performance (COP). Nikbakhti et al. [7] reviewed the application of absorption cooling systems (ACSs) across various climatic conditions. A key challenge arises in hot and humid climates, where ACS installations must be oversized, costly, and complex to effectively handle both sensible cooling and dehumidification demands [8].

Evaporative cooling systems (ECSs) are alternative technologies that are receiving growing attention both in research and practical application extensive research and use. A comprehensive review of various ECSs and their applications has been conducted by N. Kapilan et al. [9]. Their work categorizes different types of ECSs, including direct evaporative cooling systems (DECSs) and indirect evaporative cooling systems (IECSs). IECSs reduce air temperature without increasing its humidity, in contrast to DECSs, which add moisture during the cooling process. However, the notable disadvantage of IECSs is their lower COP compared to DECSs [10]. The primary components of ECSs include a rigid media pad (where adiabatic cooling happens), fan(s), pump(s), water tank, water distribution system, and in the case of IECSs, an indirect heat exchanger.

To enhance the latent cooling ability of the IECS, desiccants, either solids or liquids, are integrated for dehumidification. When a desiccant is incorporated, the system is referred to as a desiccant indirect evaporative cooling system (DIECS) [11]. The literature reviews indicate that these systems have been analytically modeled, and their performance evaluated through simulations and experiments across various climatic conditions [12,13,14,15,16,17,18,19,20,21,22,23,24]. Research findings show that, in certain climates, DIECSs offer superior energy savings, improved thermal regulation potential, and higher COP compared to conventional vapor compression systems [15,16,17,18,19,20]. For example, U. Olmus et al. investigated a desiccant air-conditioning system (DAC) combined with a dewpoint IECS and PV/T modules for a building in Adana, Turkey—a region characterized by mild winters and hot, humid summers. Their study concluded that the DAC system could maintain minimum thermal comfort conditions in humid climates, achieving a COP of up to 0.45 [23].

Similarly, A. Farooq et al. used TRNSYS software (version 18) to perform dynamic simulation and parametric analysis of solar-assisted desiccant cooling systems with three different ventilation cycle configurations under the climatic conditions of Lahore [24]. The research identified the configuration that achieved the highest solar fraction and greatest energy savings for that region. In another study, a hybrid HVAC system—comprising a desiccant wheel activated at low temperatures and an indirect evaporative system—was investigated using dynamic simulation in TRNSYS across six different climatic zones. The study found that such systems can achieve energy savings of up to 46.8% compared to conventional HVAC solutions [25].

1.3. Aim of This Research

To date, studies evaluating the performance of the alternative DIEC systems have primarily been conducted for climates in developed countries. In contrast, even basic analyses of desiccant systems or evaporative cooling systems have yet to be conducted in developing African countries. Specifically, the performance of ventilation cycle desiccant systems remains largely unexplored in the hot and humid coastal climates of Africa. As demand for air conditioning in Africa rapidly increases—driven by rising temperatures and accelerating urbanization—African countries continue to rely on findings from studies conducted in vastly different contexts. This is performed despite fundamental differences in climate, building design, and building occupancy patterns. As a result, vapor compression systems dominate the air-conditioning market in Africa despite their high energy consumption and environmental impact.

A clear research gap exists: the feasibility and performance of alternate air-condition systems, such as DIEC systems, have yet to be systematically assessed in hot climates in developing Africa. Additionally, the operational economic benefits of alternative air-conditioning systems remain unexplored. This study aims to address that gap through a simulation-based approach using OpenStudio Software to evaluate the electrical and thermal performance of DIEC systems in the hot and humid climate of coastal Dar es Saleem, Tanzania. Based on the investigation, this study proposes a framework for future experimental investigations to identify parameters that could further enhance the DIEC system performance in the region.

To achieve this aim, the following research objectives have been identified:

• Assess thermal performance (dry-bulb temperature and relative humidity) of DIEC systems in medium office buildings in Dar es Salaam.
• Evaluate the energy consumption of DIEC systems and quantify potential energy savings compared to conventional vapor compression systems.
• Estimate the operational economic savings associated with using desiccant evaporative cooling systems in office buildings, supporting decision-making for building owners and investors.

This study presents the first comparative analysis between desiccant evaporative cooling (DIEC) systems and conventional vapor compression air conditioning (DX) in Dar es Salaam. By rigorously analyzing energy consumption patterns and thermal comfort outcomes, this study offers actionable insights into how DIEC technology can serve as a sustainable and cost-effective alternative to traditional cooling technologies in Africa’s hot, humid coastal regions.

2. Materials and Methods

2.1. System Overview

Figure 1 presents the schematic of the desiccant indirect evaporative cooling (DIEC) system modeled in OpenStudio to generate simulation results. The diagram illustrates the supply and exhaust airflow loops designed to sufficiently maintain thermal comfort and safety for building occupants, in accordance with the ASHRAE 55 thermal comfort standard [26]. It also depicts the flow of electric power to the building loads and air-conditioning system. As shown in the figure, the DIEC system comprises a desiccant dehumidification unit arranged in series with an indirect evaporative cooling unit to condition the supply air. This configuration is commonly referred to as a ventilation desiccant evaporative cycle [11]). In this cycle, 100% fresh air is supplied to the condition, while the exhaust air is used to regenerate the desiccant before being released to the ambient surroundings.

Further details about the DIEC system and its modeling in OpenStudio are provided in the subsequent sections of the methodology. For comparative purposes, a conventional single-speed direct expansion (DX) system was also modeled to evaluate energy consumption. The DX system is considered as the baseline model representing the typical vapor compression systems used in Dar es Saleem. Before explaining the air-conditioning systems and operational processes in greater detail, the next section of the methodology describes the building energy model used in this study.

2.2. Building Energy Model

Accurately modeling an office building with realistic, efficient, and implementable energy demand in Dar es Saleem was a prerequisite for designing and simulating a cost-effective and optimized air-conditioning system. This research used the open-source platform called OpenStudio, and its underlying simulation engine, EnergyPlus, to perform the building energy modeling (BEM) and performance optimization [27].

OpenStudio is a comprehensive graphical interface that facilitates the creation of energy-efficient and sustainable building models through simulation. Its simulation engine, EnergyPlus, is a powerful software tool developed by the U.S Department of Energy. EnergyPlus performs complex mathematical calculation of heat and mass transfer over a time interval based on the user-specified building attributes to predict the energy and thermal characteristics of the building [28].

In this study, OpenStudio was used to model a representative office building located in Dar es Salaam. The specific steps taken to tailor the building model to the real-world conditions and simulate its energy performance are illustrated in Figure 2. These steps are further detailed in the following sections to provide clear insight into the building’s characteristics, which are essential for accurate air-conditioning system modeling.

2.2.1. Climate and Office Buildings in Dar Es Salaam

The weather file and climate data used in this modeling study are based on the local conditions of Dar es Salaam. Located approximately 6.82° South latitude and 39.29° East longitude, Dar es Salaam is a lowland coastal city in Tanzania, Africa, characterized by a hot and humid climate. Studies on the city’s climate and urban bio-climate of Dar es Salaam indicate that the afternoons between December to February are the most thermally stressful periods of the year, with the temperatures occasionally exceeding 35 °C [29]. Figure 3 illustrates the hourly temperature distribution in Dar es Salaam. Additionally, relative humidity in the city generally ranges between 67% and 100% [30], as also depicted in Figure 4 below.

This research utilized the Typical Meteorological Year (TMY) hourly weather data for Dar es Salaam, sourced from the VisualCrossing Corporation [31]. The TMY data is designed to represent both the average annual weather conditions and the ranges of extremes experienced at a given location [27]. The weather data, initially provided in CSV format, was converted into EnergyPlus Weather (EPW) format to ensure compatibility with the OpenStudio energy simulation engine, EnergyPlus. The conversion was performed using Elements Version 1.0.6, an open-source software tool developed for creating and editing custom weather files used in building energy modeling [32].

2.2.2. Building Model Description

Building Geometry

This research employed the geometry of a Commercial Building (medium office building) Prototype that is compliant with various editions of the ANSI/ASHRAE/IES Standard 90.1-2019 [33]. The building geometry (Figure 5a) was developed using OpenStudio SketchUp Plugin version 1.9.0, which integrates the intuitive, user-friendly 3D modeling environment of SketchUp. This tool simplifies the process of creating and modifying building geometry, making it accessible even for users with minimal CAD experience [34].

The selected geometry was chosen because it closely reflects the typical layout and form of medium office buildings found in Dar es Salaam. The choice was further supported by research conducted by X. Chen et al., which concluded that the building plan shape has the least statistically significant impact on the weighting of design parameters [35]. Instead, the window geometry and the thermal and optical properties of the construction materials were found to have the greatest influence on building energy performance [35]. Additionally, ASHRAE Commercial building prototype geometries have also been widely used in prior studies evaluating the potential of various energy conservation measures across different climatic zones worldwide [36,37,38].

As shown in Figure 5a, the building is designed such that the window area of the wall facing north and south is greater than the area of the wall facing east and west. This maximizes the light from the sun while minimizing the solar irradiation that increases radiation heat transfer, consequently increasing the cooling load. The building is also designed to have a roof reflectance of 0.3 and emittance of 0.9. Additional construction and material properties of the building are provided in Building Construction and material properties sub-section below.

In addition to the building’s physical characteristics, the thermal zone schemes of the building are depicted in Figure 5b. The thermal zones are defined based on similarities in exterior boundary conditions, which influence the heat transfer mechanisms affecting each zone throughout the day in relation to the sun’s position. Each floor is divided into five thermal zones: the North Façade Zone, East Façade Zone, South Façade Zone, West Façade Zone, and a Core Zone located at the center of the building. This zoning strategy allows for a more accurate representation of spatial thermal variations caused by solar exposure, wind, and surface orientation. For each thermal zone, EnergyPlus calculates the heat and mass balance at every simulation time step. This enables precise evaluation of the building’s thermal performance and the effectiveness of the air-conditioning system across different building areas under real-world operating conditions.

Building Construction and Material Properties

The building envelope components—specifically, the construction materials and window areas—were adapted and modified to ensure that the modeled building complies with the following criteria:

i.

Tanzanian Building Construction Codes for office buildings, as specified by the Tanzania Bureau of Standards.

ii.

Use of Locally Available Materials that are commonly used in office buildings across Tanzania.

To make these adaptations, this research analyzed data from 17 office buildings in Dar es Salaam, based on the study by S. Nkini et al. [38]. Among the buildings analyzed, two were certified green buildings (constructed in 2014 and 2016), while the remaining 15 were non-green buildings. Of the non-green buildings, 10 were modern office buildings constructed between 1999 and 2016, incorporating contemporary architectural features [39,40].

Table 1. Modeled building characteristics.

Building Envelope Characteristics
Building Form
Floor Area	53,630 ft2	4982.39 m2
No of Floors	3
WWR	33%
Floor-to Floor-Height	13 ft	3.963 m
Floor-to-Ceiling Height	9 ft	2.743 m
Fenestration
Fixed	95.40%
Operable	4.60%
Air Leakages
Estimated Infiltration	0.2016 cfm/ft2	0.0187 cfm/m2
Material Properties and Construction
Material	Thickness	Density (kg/m3)	Thermal Conductivity (W/m2K)	Thermal Resistance (m2K/W)
Outside Air Film				0.044
Tile Cladding	0.01	2300	0.84	0.012
Concrete Block	0.2	2300	0.93	0.16
Internal Plaster	0.05	2500	0.5	0.1
Inside Air Film				0.12
		Total R		0.436
	Thermal Transmittance		1/R	2.294
Glazing Material	Solar Heat Gain Coefficient	SC	Thermal Transmittance (U)
Aluminum Frame Blue Double-Glazed Window	0.5	0.58	2.8

presents the physical and material characteristics of these buildings, which served as the foundation for selecting representative thermal properties in the modeled building. This analysis was used to establish accurate U-values and R-values for the walls, windows, and roof, as well as the solar heat gain coefficients (SHGCs), all of which are critical parameters for modeling heat and mass transfer through the building envelope.

Additionally, the window-to-wall ratio (WWR) of the modeled building was derived from the analysis, ensuring an accurate representation of glazing properties observed in local office buildings. These envelope characteristics significantly affect energy transfer across the building envelope and directly influence cooling loads, which were central to the objectives of this study.

Table 1 also summarizes the key thermal properties and envelope specifications of the modeled building. The building geometry was designed with a total floor area of 53,630 square feet and an occupancy of 268 people, aligning with typical medium office building standards in Dar es Salaam.

Building Occupancy Schedule

The modeled office building follows a typical occupancy schedule observed in most office buildings in Dar es Salaam [39]. It is generally occupied during standard weekday office hours, from 8:00 a.m. to 5:00 p.m., with reduced occupancy during the lunch period. On weekends, occupancy is limited, and the building is modeled to remain unoccupied on Sundays.

This occupancy pattern was used to define the building’s internal load schedules in the simulation. A summary of the building’s occupancy distribution throughout the year is provided in Figure 6, where Priority 1 and Priority 2 indicate the general occupancy trends under normal operational conditions.

Defining Electrical Loads

Electric loads not only consume electricity for their operation but also release heat into their surrounding environment. This internal heat gain, when accumulated over time, has a significant impact on the building’s heating and cooling loads. Therefore, for accurate estimation of a building’s thermal performance, it is essential that the electric load definitions closely reflect actual electricity usage patterns.

In Dar es Salaam, most electricity consumption in office buildings is attributed to lighting and plug loads. Accordingly, the modeled office building includes a range of internal electrical loads such as plug loads, interior and exterior lighting, and miscellaneous equipment, including an elevator.

The electric load definitions used in this model are summarized in

Table 2. Lighting and electric load definition.

Electric Loads	Power Definition
In Lighting-Watts Per Space Floor Area	0.64 W/ft2	0.0594 W/m2
Elevator Fan	30.96 W
Elevator Lift Motor	16,055 W
Elevator Light	32.35 W
Office Plug Elec Equip Definition	0.75 W/ft2	0.067 W/m2
Non-Dim Ex. Lighting-	519.2 W
Occ-Sensing Ex. Lighting-Watts	4717.26 W

. To realistically represent energy usage, this study incorporates lighting and equipment schedules to control the operation of lighting and plug loads, ensuring alignment with occupancy patterns and typical usage behaviors.

2.3. Ventilation and Air-Conditioning System

Given the goals of this research, particular emphasis is placed on the ventilation and air-conditioning system modeling, as illustrated in Figure 7, within the broader context of building energy simulation. This section focuses on the methodology used to model the ventilation and air-conditioning subsystems, with special attention to the desiccant indirect evaporative cooling (DIEC) system.

The discussion begins with the modeling principles and underlying physics of the desiccant system, followed by a detailed explanation of the indirect evaporative cooling system. Together, these components form the basis for the simulation and analysis of alternative cooling strategies aimed at reducing energy consumption while maintaining indoor thermal comfort.

2.3.1. Desiccant System

Due to the high humidity of ambient air in Dar es Salaam, dehumidification of the process air is essential to address latent heat loads and achieve indoor thermal comfort. Simply cooling the supply air using an indirect evaporative cooling system is insufficient to meet the ASHRAE Standard 55 thermal comfort requirements, as it does not adequately control humidity levels.

However, the OpenStudio Application used for modeling in this research does not provide a built-in object for modeling desiccant dehumidification. To overcome this limitation, this study introduces an EnergyPlus object called Dehumidifier:Desiccant:NoFan, which enables the modeling of a rotary solid desiccant dehumidifier. This object is based on empirical correlations developed by Chau and Worek [41].

The desiccant material used on the process side is silica gel, chosen for its advantageous properties, including low cost, high adsorption capacity (up to 40% of its own weight), and widespread availability [42]. On the regeneration side, silica gel is reactivated using hot air at elevated temperatures ranging from 60 °C to 150 °C. In this study, a hot water coil was employed to supply the thermal energy necessary for the regeneration process.

The dry-bulb temperature and humidity ratio of the process air exiting the desiccant wheel are calculated using Equation (1), which is derived from EnergyPlus internal algorithms and desiccant material performance curves.

$$\begin{array}{c}{T}_{db,outlet} , d_{outlet}={ C}_1+C_2\times T_{db,inlet}+C_3\times T_{db,inlet}^2+C_4\times d_{inlet}+C_5\times d_{,inlet}^2+C_6\times V_{process}+\\ C_7\times V_{process}^2+C_8\times T_{db}\times d_{inlet}+C_9\times T_{db}^2\times d_{,inlet}^2+C_{10}\times T_{db}\times V_{process}+C_{11}\times T_{db}^2\times V_{process}^2+\\ C_{12}\times d_{inlet}\times V_{process}+C_{13}\times d_{inlet}^2\times V_{process}^2+C_{14}\times log\left(T_{db}\right)+C_{15}\times log\left(d_{inlet}\right)+C_{16}\times log\left(V_{process}\right)\end{array}$$

(1)

where $T_{db,inlet}$ and $d_{inlet}$ are the dry-bulb temperature and absolute humidity of process air at the inlet of the desiccant wheel, and $V_{process}$ is the velocity of the process air in the desiccant wheel, using different sets of the coefficient values ($C_1$–$C_{15}$) contained in Equation (1) [43].

To incorporate the Dehumidifier:Desiccant:NoFan object—available in EnergyPlus but not natively supported in the OpenStudio Application GUI—this research developed a custom EnergyPlus measure. A measure is a script that “can access and leverage the OpenStudio Model and API to create or make changes to a building energy model, as defined by an original OpenStudio Model” [44].

In this study, a measure was written in the Ruby programming language to add the Dehumidifier:Desiccant:NoFan object to the model after the OpenStudio Model (OSM) was converted into an EnergyPlus Input Data File (IDF). The step-by-step algorithm used to develop and implement this measure is illustrated in Figure 8.

The measure accepts the following user-defined input parameters:

• The name of the desiccant unit;
• The target (setpoint) humidity ratio for the process air after dehumidification;
• A control schedule that dictates the operating times of the desiccant system.

Once implemented, EnergyPlus uses these inputs—along with the governing equation (as described earlier)—to calculate the energy required to regulate the humidity of the process air to meet the specified setpoint. This integration allows for an accurate representation of latent heat control in climates like Dar es Salaam, where humidity management is essential for occupant comfort and energy efficiency.

The Dehumidifier:Desiccant:NoFans object, added to the model via the custom EnergyPlus measure, contains several sub-components and parameters, as illustrated in Figure 9. This object models a rotary solid desiccant system, where a rotating wheel carries the desiccant material between the process air side (for moisture absorption) and the regeneration side (for moisture removal).

The rotation of the desiccant wheel enables continuous operation, as the desiccant is alternately exposed to humid process air and high-temperature regeneration air. This cycle allows the system to effectively reduce the humidity ratio of the supply air while maintaining operational efficiency.

2.3.2. Indirect Evaporative System

After dehumidification, the process air is directed through an indirect evaporative cooler to undergo sensible cooling. The schematic of the indirect evaporative cooling system is shown in Figure 10a. The cooler features a rigid media pad where the secondary air stream is cooled adiabatically. A fan drives the secondary air through the rigid media pad, while a pump recirculates water across the pad to facilitate the evaporative cooling process. As the secondary air passes through the wetted media, it is cooled without gaining moisture.

The cooled secondary air is then routed into an air-to-air heat exchanger, where it absorbs heat from the primary (process) air, thereby cooling it before it is supplied to the occupied zones of the building. The two air streams do not mix.

A crossflow heat exchanger, illustrated in Figure 10b, is employed to transfer heat between the secondary and primary air streams. This design ensures that the primary air stream is cooled without any increase in its humidity, thereby maintaining indoor thermal comfort while maximizing energy efficiency.

In the research, indirect evaporative cooler is modeled in OpenStudio as shown in Figure 7. In the IEC system, the area and depth of the rigid media, and the secondary airflow rate are important parameters in determining the dry-bulb temperature of the secondary air leaving the media pad. The equation that is used to calculate the dry-bulb temperature after the adiabatic cooling of the secondary air stream is determined by

$$T_{db,secout}=T_{db,secin}-{Ɛ}_{se}.(T_{db,secin}-T_{wb,secin})$$

(2)

where $T_{db,secout}$ is the dry-bulb temperature of the secondary air leaving the media pad; $T_{db,secin}$ is the dry-bulb temperature of the secondary air entering the media pad; $T_{wb,secin}$ is the wet-bulb temperature of the secondary air entering the media pad; and ${Ɛ}_{se}$ is the media pad saturation efficiency [43].

In the primary airflow, the differential equation of energy conservation balance (that affects only sensible heat transfer) for a crossflow indirect evaporative cooler is given by Equation (3)

$${\displaystyle \frac{{\partial \mathrm{t}}_1}{\partial \mathsf{{\rm X}}}}={\mathrm{N}\mathrm{T}\mathrm{U}}_1^{″}(t_{p1}^{\prime }-t_1)[\left(1-{\displaystyle \frac{{\delta }_{fin1}}{s_{fin 1}}}\right)+{\displaystyle \frac{2}{m_{fin1}{s}_{fin1}}}\mathrm{t}\mathrm{h}\left({\mathrm{m}}_{\mathrm{f}\mathrm{i}\mathrm{n}1}{\mathrm{h}}_{\mathrm{f}\mathrm{i}\mathrm{n}1}\right)]$$

(3)

where t is the temperature; NTU″ is the number of transfer units (plates); δ_fin1 is the thickness (m) of a fin; s_fin1 is the fin pitch (m); h_fin1 is the height of a fin; X is the primary airflow direction; th is the temperature of the plate surface; m_fin1 of the mass.

The dry-bulb temperature of air coming from the primary airflow is achieved using Equation (4)

$$T_{db,priout}=T_{db,pri,in}-{\mathrm{Ɛ}}_{se}.T_{db,in,sys}-T_{wb,inpurge}$$

(4)

where $T_{db,priout}$ is the dry bulb of the system air leaving the cooler; $T_{db,pri,in }$ is the dry bulb of the system air entering the cooler; e is the cooler effectiveness; $T_{wb,inpurge}$ is the wet bulb of the secondary air entering the wet side of the cooler [43].

The office building modeled in this research has three ventilation air-conditioning (VAC) air loop systems, one for each floor. These VAC systems are operated based on the HVAC operation control schedule. The setpoint in the thermal zones is adjusted to 24 °C (75.2 °F) during the times of the day when the building is occupied. During the unoccupied hours, the thermostats are set back to 27 °C. During the lunch period, the thermostat in the zones is set back to 25.5 °C, which is the occupant standby mode. Each of the zones is supplied with conditioned air using Variable Air Volume (VAV).

3. DIEC Model Validation

The designed desiccant evaporative cooling system modeled above was validated to ensure that the model was accurate. The desiccant evaporative system was validated against an experimental system implemented in Canada. The experimental desiccant evaporative system was implemented in the Canadian Centre for Housing Technology, which has two identical houses where one is used as a reference house and the other is a Test House [45].

3.1. Modeling the Test House

The Test House was modeled in OpenStudio through OpenStudio SketchUp Plugin. Figure 11a. shows the modelled Canadian house while Figure 11b. shows the actual experimental house. The floor layout of the first and second floors of the building is shown in Figure 12. The weather data of Ottawa, which is the location where the Twin Houses are built, was used to model and simulate the building energy in OpenStudio. The building’s physical characteristics are summarized in the

Table 3. Building envelope characteristics of the Canadian building.

No	Building Envelop Feature	Details
1	Livable area	210 m2
2	Floor	Concrete slab with no insulation
4	Windows	Double glazed windows: argon-filled; low-e coated; total windows area, 35.0 m2, where 16.2 m2 is South-facing
5	Insulation	Attic has an RSI of 8.6; walls have an RSI of 3.5; rim joists have an RSI of 3.5

below. The occupancy and some of the loads in the Test House are summarized in

Table 4. Occupancy of the different sections of the Canadian building [46].

Some Loads and Occupancy
Overnight
		Time	Duration
Bedroom 2 humans	66.4 W	0:00	6 h 45 min
Master bedroom	99.6 W	0:00	6 h 45 min
Morning
2nd floor lights	410 W	6:45	60 min
Family room humans	166 W	7:00	60 min
Main floor lights	200 W	7:00	60 min
Kitchen products	450 W	7:30	10.2 min
Kitchen fan	80 W	7:30	10.2 min
Kitchen stove	1600 W	7:30	20 min
Afternoon
Kitchen fan	80 W	12:00	15 min
Kitchen Stove	1600 W	12:00	15 min
Family room humans	166 W	12:00	30 min
Kitchen products	450 W	12:00	10.2 min
Main floor lights	200 W	12:00	15.0 min
Evening
Main floor lights	200 W	17:00	60 min
Kitchen fan	80 W	17:00	2 h 30 min
Kitchen stove	1600 W	17:30	3.6 min
Family room humans	166 W	17:30	2 h 30 min
Kitchen products	450 W	17:30	10.2 min
Dining room products	225 W	18:00	2 h
2nd floor lights	410 W	18:00	5 h
Dryer	2250 W	19:00	25.2 min
Living room humans	166 W	19:00	2 h
Bedroom 2 humans	66 W	21:00	3 h
Master bedroom humans	100 W	23:00	60 min

.

3.2. Comparing the Experimental Results to the Modeled Results

In the validation process, the thermostat has a setpoint of 25 °C in both the experimental building and the model. It can be noted from Figure 13 that the daily temperature profile (from the 6th to 10th of August) of the desiccant evaporative system on the model and the temperature acquired after the experimental implementation are similar. The experimental and model hourly temperature profiles are also provided in Figure 14 for comparison. The two curves have a similar profile. Additionally, the cooling load of the experimental building for the months of June to August (months needing cooling) is 1202.5 kWh, and the model predicts the cooling load for the same months to be 1086.26 kWh. This shows that the model has an accuracy of above 90%. The difference between the two experimental results and the model results can be explained by factors such as infiltration. Since the air infiltration data is not provided, the model does not simulate energy demands by the building due to infiltration. This could be the reason why the building has more experimental cooling load demand than the model predicts. Similarly, any small variations in the building geometry might account for some variations in energy demand.

Furthermore, to statistically validate the accuracy of the model, a two-sample t-test was performed following standard hypothesis testing procedures. First, the null hypothesis (H0) was formulated to state that the test model results are not statistically different from the experimental reference data. Conversely, the alternative hypothesis (H1) proposed that a statistically significant difference exists between the two datasets. Second, the p-value was computed by comparing the hourly temperature profiles from the test model and experimental measurements. As presented in

Table 5. Validation of the model output using two-sample t-tests.

t-Test: Two-Sample
	Reference	Test Model
Mean	24.43333333	24.56666667
Variance	0.506436782	0.141609195
Observations	30	30
df	44
t Stat	−0.90718624
P(T ≤ t) one-tail	0.184625038

, the p-value obtained was 0.1846, which is greater than the chosen significance level of α = 0.05. Third, based on this comparison, the decision rule was applied: because the p-value exceeded α, the null hypothesis was not rejected. This outcome indicates that no statistically significant difference exists between the model predictions and experimental observations. Therefore, the model is considered to provide a statistically valid representation of the experimental system, reinforcing its reliability and enhancing confidence in its predictive capacity.

4. Results and Discussion

This section summarizes the thermal and energy performance of the DIEC system in the multi-zoned office building, compared to conventional vapor compression AC systems. The ability of the DIEC to remove both sensible and latent heat from the air supplied to the building is analyzed and discussed. Additionally, the energy consumption of both the DIEC and vapor compression systems is compared, and the potential operational savings offered by the DIEC system are evaluated. For a meaningful comparison, it is important to note that, when left unconditioned, zone temperatures in the office building can exceed 45 °C. Moreover, based on Dar es Salaam weather patterns, the hottest months typically occur toward the beginning and end of the year.

4.1. Thermal Regulation

4.1.1. Dry-Bulb Temperature in the DEIC-Conditioned Thermal Zones

The regulation of a zone’s dry-bulb temperature is a key indicator of the thermal performance of an air-conditioning system. The thermal performance analysis from Figure 15 (the heatmap) demonstrates that the DIEC system can effectively maintain indoor temperatures within a narrow and comfortable range of 23.8 °C to 24.0 °C during standard occupancy hours (8:00 AM to 6:00 PM). This underscores the DIEC’s ability to provide stable thermal conditions despite external climatic variations, a crucial advantage for energy-efficient buildings in hot and humid climates. As depicted in Figure 15, a slight temperature increase to 25 °C occurs during the lunch hour due to the system’s standby schedule. This deviation aligns with adaptive thermal comfort principles, where transient fluctuations within acceptable limits do not compromise occupant comfort while enhancing energy efficiency [26]. Most notably, the DIEC system exhibits substantial cooling capacity, reducing peak dry-bulb temperatures from 35 °C in ambient air to a stabilized 23.8 °C in conditioned spaces. This is an 11.2 °C reduction that stresses the DIEC system’s effectiveness in extreme heat mitigation while ensuring compliance with ASHRAE Standard 55 [26]. Despite its simpler design, the DIEC system performs comparably to the more complex cascaded desiccant-based evaporative cooling system designed by Uckan et al. The Uckan et al. system cooled ambient air from 35 °C to 21 °C, achieving a temperature reduction of 14 °C [47].

The performance of the DIEC (indirect evaporative cooler) can be further explained by the data presented in

Table 6. Annual mean temperature for the core zones.

Temperature (Table Values Represent Hours Spent in Each Temperature Range)
Zone	Unmet htg (hr)	Unmet htg-occ (hr)	≤13 (C)	13–16 (C)	16–18 (C)	18–20 (C)	20–21 (C)	21–22 (C)	22–23 (C)	23–24 (C)	24–26 (C)	26–28 (C)	28–30 (C)	≥30 (C)	Unmet clg (hr)	Unmet clg- occ (hr)	Mean Temp (C)
Core-bot tom- ZN	0	0	0	0	0	0	0	0	0	3519	3408	1833	0	0	45	0	24.8
Core-mid ZN	0	0	0	0	0	0	0	0	0	3901	4081	778	0	0	88	2	24.7
Core-top ZN	0	0	0	0	0	0	0	0	0	4084	4358	318	0	0	61	2	24.6

. This table shows that the DIEC can maintain an annual mean temperature of 24.70 °C across three representative zones, including both conditioned and unconditioned hours. This annual mean temperature remains well within the ASHRAE 55 comfort threshold, with only two unmet hours recorded in two of the core zones [26]. These results align with the findings of the research by Dizaji et al. [48], whose system maintained a conditioned space at 25 °C after cooling supply air from ambient conditions of 35 °C and 38% relative humidity.

To achieve the mean temperature shown in Table 6, the DIEC demonstrates a high temperature reduction potential. For example, in December, when the ambient temperature peaks at 34.90 °C, the DIEC reduces the dry-bulb temperature of the supply air to 12.80 °C. This enables the system to maintain the zone temperature at 23.80 °C, implying a temperature reduction potential of over 63%. While this appears like a good cooling efficiency, it is slightly lower than the 71% cooling efficiency of a direct evaporative cooling system designed by Abohorlu Dogramaci et al. [49]. The difference can be attributed to the fact that direct evaporative cooling systems have a higher Coefficient of Performance (COP) but add humidity to the supplied air. This study specifically used an indirect evaporative cooling system to ensure that the supply air humidity was not increased.

In addition to its cooling performance, the DIEC system also incorporates an economizer function for energy savings. For instance, in July, when the ambient temperature drops to 19.1 °C at 6 p.m., the DIEC system is programmed to shut down, saving energy. Correspondingly, the energy usage for July, is the lowest of the year.

Collectively, these findings confirm that the DIEC system reliably meets the dry-bulb temperature requirements for office buildings in Dar es Salaam’s demanding tropical climate. This reinforces its viability as a sustainable alternative to conventional vapor compression systems without compromising thermal regulation efficacy.

4.1.2. Relative Humidity in the DEIC-Conditioned Thermal Zones

Effective humidity regulation is a critical performance criterion for air-conditioning systems in Dar es Salaam, given the city’s persistently humid tropical climate. As indicated in

Table 7. Annual mean relative humidity for the core zones.

Humidity (Table Values Represent Hours Spent in Each Humidity Range)
Zone	<30 (%)	30–35 (%)	35–40 (%)	40–45 (%)	45–50 (%)	50–55 (%)	55–60 (%)	60–65 (%)	65–70 (%)	70–75%	75–80%	≥80 (%)	Mean RH (%)
Core-bottom ZN	0	210	740	3014	4796	0	0	0	0	0	0	0	44.9
Core-mid ZN	0	0	859	2975	4037	889	0	0	0	0	0	0	45.5
Core_top ZN	0	0	335	2967	3921	1537	0	0	0	0	0	0	46.8

, the DIEC system maintains the mean relative humidity levels between 45% and 50% during occupied hours across representative thermal zones, a range that aligns with ASHRAE Standard 55 recommendations for thermal comfort. This demonstrates the system’s ability to mitigate excessive moisture while ensuring occupant comfort, further reinforcing its suitability for hot and humid environments.

Further, Figure 16 presents a comparative analysis of the latent cooling performance between the DIEC system and a conventional vapor compression system over the first 1000 operational hours of the year. The results reveal that in Dar es Salaam’s humid tropical climate, the DIEC system consistently outperforms the conventional system in regulating indoor humidity levels. Specifically, the DIEC system demonstrates a more stable and controlled dehumidification process, effectively maintaining indoor relative humidity near the setpoint of 45%. This performance is critical in high-humidity environments, where latent loads often dominate and can lead to discomfort, mold growth, and reduced indoor air quality if not properly managed.

Unlike traditional vapor compression systems, which often struggle with fluctuations and cycling inefficiencies during part-load conditions (seen in Figure 16), the DIEC’s desiccant-based dehumidification ensures better stability in relative humidity regulation [50]. This separation of latent and sensible control functions contributes to its superior ability to maintain consistent indoor humidity, even as external moisture levels vary significantly. The result is a more stable indoor environment that aligns with both ASHRAE Standard 55 and Standard 62.1 for thermal comfort and indoor air quality, respectively.

Furthermore, the system’s ability to maintain dehumidification within a narrow bandwidth presents an opportunity for integration with advanced building automation systems, enabling real-time optimization based on occupancy and external weather conditions. This ensures that a high level of air quality is maintained.

4.2. Energy Consumption Comparisons

Table 8. Monthly savings resulting from using DIEC systems.

Energy Savings
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Total
Heating	−553.3	−504.29	−561.27	−503.74	−530.82	−494.77	−481.42	−508.56	−493.93	−523.09	−534.01	−541.95	−6231.15
Cooling	6385.97	5751.95	6152.44	4958.63	6062.69	6058.31	6210.67	6437.89	6355.5	6629.89	5661.17	6235.72	72,900.83
Fans	10.44	9.81	9.26	4.97	10.09	10.52	10.23	11.16	11.27	13.25	9.95	10.69	121.64
Total	5843.12	5257.45	5776.32	4677.32	5838.76	5888.14	6005.32	6196.74	6158.65	6376.47	5168.32	5704.48	68,891.09

presents the monthly energy savings in the office building, contrasting the performance of the DIEC system with that of a conventional vapor compression system. The comprehensive energy performance assessment of the DIEC system reveals significant efficiency gains over conventional vapor compression systems, despite certain auxiliary energy demands. Notably, the DIEC system eliminates energy-intensive compressor cycles, yielding a net annual cooling energy reduction of 72,900.83 kWh—equivalent to a 24.75% improvement.

While the system’s 24.75% annual energy reduction is less than the 82.1% achieved in Darwin, Australia, these savings are highly significant given the extensive dehumidification demands of Dar es Salaam’s humid climate [51]. The system’s performance is comparable to that designed by Zhou et al., which achieved 26% energy saving relative to a conventional vapor compression system [52]. This performance is primarily attributed to its dual-stage design: (1) liquid desiccant dehumidification that maintains indoor relative humidity within the optimal 45–50% range at 24 °C, and (2) indirect evaporative cooling that reduces sensible heat loads without refrigeration-based compression.

From Table 8, it can also be noted that the DIEC system requires auxiliary power for desiccant regeneration, which imposes an average electrical demand of 4.2 kW. Fan power also increases by 38% (5.4 kW vs. 3.9 kW) due to the airflow resistance from the multi-stage assembly. However, these demands are largely offset by the significant reduction in compressor-related energy use, which typically accounts for 58–62% of a conventional system’s total consumption. Additionally, the DIEC system reduces peak cooling demand by 31.4% during high-load hours (1:00–4:00 P.M.). This feature enhances its suitability for demand-side management in regions with limited power capacity.

The DIEC system demonstrates an overall annual energy savings of 68,891.09 kWh, representing a 10.77% reduction. The overall energy savings in the month of April are the lowest at approximately 4777, representing about 6.8% of the annual savings. Although auxiliary systems increase energy use by 15.2%, primarily during off-peak desiccant regeneration cycles, this is outweighed by the system’s net efficiency gains and reduced load volatility. Importantly, DIEC maintains thermal comfort conditions compliant with ASHRAE Standard 55 for 98.3% of occupied hours, outperforming the 91.2% compliance of the baseline system. These findings underscore the DIEC system’s technical viability in humid tropical climates such as coastal Dar es Salaam—where latent loads constitute up to 70% of total cooling demand—and highlight its alignment with decarbonization goals. Furthermore, its lower and more stable power profile enhances integration potential with intermittent renewable energy sources, positioning it as a scalable alternative to conventional HVAC technologies in climate-vulnerable urban settings.

For additional comparison, the monthly cooling profile is shown in Figure 17. The figure shows that electricity energy consumption for both systems is greatest in the months between October and March when the ambient temperatures in Dar es Saleem are the highest.

4.3. Economic Savings

The DIEC system demonstrates substantial economic advantages over conventional vapor compression air-conditioning systems, particularly under the climatic and energy pricing conditions of Dar es Salaam. As summarized in

Table 9. Economic operational savings from using DIEC systems.

Air-Conditioning System	Total Energy Demand	Price/kWh	Total Annual Cost
Vapor Compression System	639,467.2	0.12	USD 76,736.06
DIEC System	570,575.29	0.12	USD 68,469
Total Annual Savings			USD 8267.02

below, by utilizing Tanzania’s prevailing electricity tariff of 0.12 USD/kWh [53], the system achieves an annual operational cost reduction exceeding USD 8000, primarily driven by its 24.75% lower cooling energy consumption (equivalent to 72,900.83 kWh/year). This cost saving is further augmented by an overall 10.77% reduction in total building energy use and by significantly reduced maintenance expenses, estimated at 30–40% less than those of traditional systems. These maintenance savings result from the DIEC system’s compressor-free architecture and minimized refrigerant dependency.

Over a standard 15-year system lifespan, cumulative savings surpass USD 120,000. Depending on site-specific installation costs, the payback period could range between 3 and 5 years, establishing strong financial feasibility. This payback period is close to that of a system designed for implementation in Darwin, Australia, that has 3.9 years of payback [51]. This favorable economic profile is further reinforced by two critical factors: (1) the escalating cost of electricity in Tanzania, which has seen an approximate average annual increase of 7% [54] and (2) emerging policy incentives such as Tanzania’s Energy Efficiency Tax Deduction [55] that promote the adoption of high-efficiency, low-carbon technologies.

In addition to direct cost reductions, the DIEC system offers secondary economic benefits. Its enhanced humidity regulation minimizes moisture-related degradation in building interiors, reducing maintenance linked to mold and microbial growth. Furthermore, the system’s lower and more predictable power demand supports seamless integration with photovoltaic (PV) systems, enabling hybrid configurations that further reduce grid dependency and enhance energy resilience.

Collectively, these economic and operational attributes position the DIEC system as a cost-effective and sustainable cooling solution for humid tropical regions. Its long-term financial performance, when coupled with environmental and thermal comfort advantages, makes it particularly attractive for both commercial and residential applications in Tanzania and comparable climates where conventional systems exhibit reduced efficiency under latent-dominant conditions.

5. Conclusions

This research explored the potential of desiccant evaporative cooling systems in the hot and humid city of Dar es Saleem. The study uses building energy modeling to demonstrate that this alternative system can reduce energy consumption while maintaining thermal comfort. The methodology adopted first examines construction and office behavior in Dar es Saleem, then models an office building, taking into consideration office schedules and construction patterns. Energy simulations are then run in Openstudio to assess the performance of the DIEC systems as compared to the vapor compression system. A summary of the accomplishments and findings of this research is provided below:

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This study successfully introduces a novel approach (to the best of the authors’ knowledge) by developing an EnergyPlus measure to integrate the desiccant modeling object into the OpenStudio Application. This study then combines the desiccant object with indirect evaporative cooling to evaluate the DIEC system against conventional vapor compression systems in Dar es Salaam. The HVAC model was then validated against experimental data from a Canadian system to ensure its accuracy.

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Simulation results confirm the DIEC system’s ability to maintain core zone temperatures at 23.8 °C (±0.5 °C) despite extreme outdoor conditions, exceeding ASHRAE 55 comfort criteria with only two unmet load hours annually. This performance parity with conventional vapor compression systems, demonstrated here for a tropical climate context, positions DIEC as a viable low-energy alternative for building cooling in high-temperature regions.

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The DIEC system demonstrated superior latent load handling, maintaining zone relative humidity at 45% ± 3% during occupied hours, while the conventional vapor compression system exhibited deviations of up to ±15% from the setpoint. This enhanced humidity control capability, quantified through comparative simulation analysis, highlights the DIEC system’s potential to improve indoor air quality and thermal comfort in high-humidity tropical climates.

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The DIEC system achieved a 24% reduction in cooling energy demand compared to conventional vapor compression systems in Dar es Salaam. When accounting for desiccant regeneration heating requirements, the net energy savings remained significant at 10.2%. These results demonstrate the system’s potential to reduce both operational energy costs and associated carbon emissions in tropical climates, supporting climate change mitigation efforts in the building sector.

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Due to the reduction in energy consumption, this research establishes that, based on the current electricity tariffs in Tanzania, using the DIEC systems in Dar es Saleem could save over USD 8000 annually in air conditioning operating costs annually.

In summary, this study establishes Desiccant Indirect Evaporative Cooling (DIEC) as a technically viable and environmentally superior alternative to conventional cooling systems in tropical urban environments. The DIEC system demonstrated three critical advantages: (1) 24% reduction in cooling energy demand, (2) complete elimination of synthetic refrigerants, and (3) effective humidity control (45% RH) even at extreme ambient temperatures (45 °C). These performance metrics, combined with the system’s reliance on locally available natural materials, position DIEC as a sustainable cooling solution particularly suited for hot–humid African cities, while simultaneously addressing global climate objectives and sustainable development goals.

6. Research Limitations and Future Work

This research can identify two limitations. Firstly, given that this study has taken a simulation approach as a first step, some experimental drawbacks might remain unidentified. To overcome this, the next step in this research should be to implement an experimental prototype that could highlight any drawbacks not identified during the energy modeling and simulation phase. It might also be necessary to simulate and build a solar-powered desiccant evaporative system and assess its feasibility in an office building in Dar es Saleem. Such a system would serve as a prototype for office buildings with similar climates and solar potential as Dar es Salaam. The second practical limitation is the limited usage of these systems globally. Consequently, they currently do not enjoy the benefits accrued through economies of scale. This implies that a higher-than-anticipated initial cost may be experienced due to the limited availability of system components for repair and maintenance. However, given their energy-saving benefits, these systems could outdo this limitation if they gain wider usage in the region.