Development of a Small Dual-Chamber Solar PV-Powered Evaporative Cooling System for Fruit and Vegetable Cooling with Techno-Economic Assessment

Abstract

This study evaluates a solar PV-powered evaporative cooling system for vegetable cooling. The system features dual cooling chambers with two different biomass pads, operating at different temperatures. To assess its potential, the research examines the evolution of temperature and humidity of the cooling chamber, evaporative effectiveness, cooling capacity, coefficient of performance (COP), energy metrics, greenhouse gas emissions, and overall cost. The results show that the system achieved a temperature depression range of 0.22 to 5.2 °C and 0.57 to 10.94 °C for wood shavings and polyurethane foam, respectively, under no-load conditions, while the values were 0.79 to 4.7 °C and 1.22 to 9.88 °C, with average values of 3.09 and 7.0 °C, for the same materials under loaded conditions. Loaded conditions also yielded a cooling capacity of 5.7 to 33.93 W for wood shavings and 8.13 to 75.55 W for polyurethane foam. The cooling efficiency ranged from 19.9 to 96.42% for polyurethane foam and 3.62 to 60% for wood shavings. The system’s COP was higher than that of solar-powered mechanical chillers, ranging from 2.37 to 22.92. The energy production factor was 2.3 to 2.4, with a lifecycle conversion efficiency of 0.5 and an energy payback time of 1.1 and 2.2 years for using polyurethane foam and wood shavings, respectively. The net present value was positive, and the levelized cost of energy was low, at 36.7 to 38.3 NGN/kWh (0.043–0.045 USD/kWh), making it a viable alternative to grid-based energy systems in Nigeria. Additionally, the system offers significant CO₂ mitigation potential, with estimated carbon credits of NGN 65,059 (USD 71.56) and NGN 98,576.49 (USD 108.43) over its lifetime.

1. Introduction

Cooling systems have been proven to reduce postharvest losses and improve the storage of fruits and vegetables [1]. Several methods, including mechanical refrigeration, controlled atmospheres, adiabatic cooling, and evaporative cooling, can extend the shelf life of perishable produce [2]. Nigeria’s tropical climate drives demand for cooling systems, as high temperatures necessitate cooling solutions. Furthermore, shifting consumer preferences for fresh produce in Sub-Saharan Africa have boosted the market potential of cooling systems in this region [3,4]. The literature shows that cold storage can increase agricultural profit margins by 40% through reduced postharvest losses [5]. As a result, the cooling system market has vast potential in densely populated developing countries like Nigeria.

Table 1. Cold storage market potential for Nigeria [5].

Market Segment	Annual Production (Metric Ton)	Price per Metric Ton (NGN)	Potential Annual Savings (NGN)
Cashew	960,000	525,000	201,600
Orange	4,160,000	25,000	41,600
Tomato	3,816,009	370,660	565,776
Milk	523,599,000	720,344	113,151,419
Fish	1,100,000	1,000,000	330,000
Total	534,581,704	--	110,776,845 (USD 121,854.53)

highlights the potential for cold storage of various products in Nigeria, with an estimated cost-saving potential of NGN 111 billion.

In Nigeria, researchers and farmers have explored various temporary storage methods for freshly harvested fruits and vegetables in rural areas [6]. However, power shortages and unreliable supply have hindered the use of conventional refrigerators, leading to chilling injuries due to excessive temperature reduction. This has prompted the search for cost-effective techniques to achieve suitable ambient conditions for preserving or cooling fruits and vegetables at optimal temperatures without chilling injuries. Evaporative cooling systems have emerged as a viable solution for removing field heat and preserving moderate-temperature produce. Evaporative cooling occurs when moisture is added to air with a relative humidity below 100%. The potential for evaporative cooling increases as relative humidity decreases, with the effectiveness of cooling dependent on the difference between air dry-bulb and wet-bulb temperatures. This technique reduces temperatures by absorbing energy from the surrounding environment as water evaporates. Evaporative cooling systems utilize mists, sprays, or wetted pads to lower air temperature, increasing relative humidity while cooling the air. The typical evaporative pad cooling system consists of a pad (wetting) medium, water supply line, water recirculation pump, water distribution header, fan or blower, gutter, sump tank, and bleed-off line (in some designs) [6]. As air flows past the wet pad surfaces, moisture acquires heat, evaporates, and removes heat energy from the air. This results in exhaust air with a lower temperature and elevated moisture content. Water is continuously recirculated over and through the wetting medium capillaries during operation. Evaporative coolers have been developed and deployed for domestic, agricultural, and industrial applications in recent years, with various sizes and capacities available [6]. For example, Dai and Sumathy investigated a cross-flow direct evaporative cooler using wet honeycomb paper and found an optimal air channel length for performance improvement [7]. Bowman et al. [8] studied passive downdraft evaporative cooling (PDEC) to reduce energy consumption in hot, dry climates. Jaber and Ajib [9] designed indirect evaporative air conditioning to reduce energy consumption without negatively affecting thermal comfort, with the goal of lowering the imported oil bill on the national level and reducing the emission of harmful gases to the environment on the international level. Despite their increasing performance and high energy efficiency, these systems have high electrical energy consumption and cause peak electricity loads because they depend on energy from the grid. Thus, they are most of the time not suitable for rural areas due to low electricity penetration density and the need to power fans and pumps. Furthermore, the increasing cost of energy over the past few years has made the energy-saving concept one of the most important research areas in the energy industry. Moreover, energy consumption is directly related to the greenhouse gas effect and environmental pollution, which is responsible for increased global temperature or global warming. The aforementioned problems have increased the desire to adopt renewable energy systems in energy devices. In most countries, available evaporative coolers are those that depend on natural wind flow [10], which is not reliable. A typical example is the pot-in-pot design or zeer pot design [11]. These designs have been adopted in rural areas, especially for cooling and short-term preservation of vegetables and fruits. The performance of these coolers is limited by low air flow rates and the need to manually re-wet the pads, which increases operational drudgery. To mitigate this and constantly maintain a steady air flow rate and water recirculation at reduced energy consumption for increased performance, Schulz [12] invented a new solar evaporative cooler retrofit kit to decrease the amount of electrical power supplied and the cost of operating such a common evaporative cooler. Solar energy is one form of renewable energy that is well distributed and available globally. In recent years, solar energy has been adopted as a cost-effective energy solution. It is clean, renewable, and environmentally friendly. Solar systems have been envisaged from an energy perspective for a sun-powered world [13].

Therefore, solar energy can be harnessed to various degrees to power the energy world, especially in rural areas with no electricity. This has been applied in the literature to power evaporative cooling systems. For example, Olosunde et al. [14] developed a solar-powered evaporative cooling system for preserving tomatoes, mangoes, bananas, and carrots in rural areas of Nigeria. The aim was to overcome the irregular power supply prevalent in rural areas. The designed evaporative cooling system had a capacity of about 0.39 m³ and delivered an exhaust temperature range of 7.8 to 15.4 °C and a relative humidity range of 44 to 96.8%, capable of preserving the products for 14 to 28 days. Saleh et al. [15] evaluated solar evaporative coolers for storing citrus and tomatoes for rural farmers in Nigeria, using charcoal as the wetting medium. They obtained an average temperature depression of 7 °C and achieved a storage life of 14 days with a saturation efficiency of 41%. Mekonen et al. [16] presented a two-stage solar-powered active evaporative cooling system in Ethiopia using activated carbon as the cooling pad. The cooler provided a temperature drop of about 9 to 15 °C under various operating conditions, with a relative humidity of up to 88% and a COP of 52.2 at a cooling capacity of 3653 W. Mansuri et al. [17] developed a solar-powered evaporative cooling system for storing fresh fruits and vegetables in India, using wet wool, khas, and CELdek as cooling pads. Under various operating conditions, they achieved a maximum relative humidity increase of 59% and a temperature drop of 14.6 °C. However, CELdek outperformed other cooling pads, with a cooling efficiency of 78.67%. Despite the above studies, research on evaporative cooling is ongoing. Various local materials, including biomass materials, have been tested as cooling pads due to the high cost of exotic pads [18,19]. The above assertions informed the design of the present solar evaporative cooler for cooling fruits and vegetables. Furthermore, noticing that fruits and vegetables require different cooling rates, the current research attempted to develop a novel evaporative cooler with dual cooling chambers capable of cooling concurrently at different temperatures. This was conceived by using different types of cooling pads or wetting media with different moisture absorption capacities, affecting the exhaust temperature range as shown in several studies in the literature [20]. Research has shown that different wetting materials can produce different cooling efficiency [21]. However, apart from energy demand, another challenge in adopting this cooler in most rural areas is the lack of techno-economic feasibility data on solar evaporative coolers, as the initial investment cost might seem high for farmers. This study will present a trade-off between the evaporative cooling system to be adopted and the energy sources for different countries [22]. This kind of study is lacking in Nigeria. Additionally, the energy pay-back time of PV-powered systems is a major concern, as it is a good CO₂ emission indicator [23]. Furthermore, although a solar evaporative cooler is renewable, the energy used in manufacturing most of the components represented in the embodied energy is not renewable, coming from electricity or fossil-based fuels. Thus, there is a need to study the impact of the embodied energy in the CO₂ emission, which will assist in reducing CO₂ emissions into the environment. Therefore, the present research aims to (1) develop and test a solar PV-powered evaporative cooling system with dual cooling chambers and biomass pads, (2) evaluate the system’s cooling performance, energy efficiency, and environmental impact, (3) assess the techno-economic feasibility of the system for smallholder farmers in tropical regions, and (4) compare the performance of different biomass pads (wood shavings and polyurethane foam) in the evaporative cooling system. However, the novelty of this research lies in developing a solar PV-powered evaporative cooling system with dual cooling chambers, utilizing biomass pads (wood shavings and polyurethane foam) as a sustainable and locally available solution and conducting comprehensive energy analysis and economic evaluation to assess its techno-economic feasibility and environmental impact in the tropical environment of Nigeria, where postharvest losses are significant and energy access is limited, making it an innovative solution for reducing postharvest losses and improving the cooling of fruits and vegetables while promoting sustainable energy and reducing environmental impact.

2. Materials and Methods

2.1. Sizing of Solar PV Module for Solar-Powered Evaporative Cooling

To determine the number of PV modules or size of the PV module and the battery capacity to power the evaporative cooling system, the daily energy requirement of the evaporative cooling system must be determined.

2.1.1. Power Requirement of the PV Module

Based on the design, the evaporative cooling system’s fan and water pump were rated at 25 W, but an allowance of three times more energy is needed to start the pump. Assuming the evaporative cooler will run for t hours in a day, the overall energy needed (in W per day) will be given as follows [22]:

$$E_C= P_i\times t\times 3$$

(1)

where P_i is the rated power of the fan and pump, and t is the maximum daily sunshine hours (11.41 h, the maximum value from Table 2 for Nigeria). Also, making provision for an energy loss of up to 30% (0.3) for the system [24], the overall energy needed to run the pump and fans for the evaporative cooling presented in Equation (1), will be raised by 30% (i.e., 0.3 E_c + E_c) as follows [24]:

$$E=1.3\times E_C$$

(2)

Therefore, the power requirement for the PV panel (W) needed is given by Opoku et al. [25] as follows:

$$\mathrm{W}={\displaystyle \frac{E}{{\eta }_{bat}{ \times \eta }_{reg}{ \times f}_{man} \times f_{tem} \times f_{dirt} \times t_{av}}}$$

(3)

where:

f_man: manufacturer’s tolerance for solar panel = 0.90 [25]

f_temp: temperature correction factor for solar panel = 1.04

f_dirt: derating factor for dirt on solar panel = 0.97

η_bat: efficiency of battery = 85%

η_reg: efficiency of regulator/charge controller = 85%

t_av: average sunshine hours per day in south-eastern Nigeria, taken as 7 h [26].

Table 2. Typical Nigerian weather by month [27].

Month	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Nov	Oct	Dec	Ave.
Recorded high, °C	39.5	41.2	41.9	42.6	42.8	40.2	36.0	33.4	36.37	38.7	37.8	38.2	42.8
Average high, °C	35.6	36.9	37.4	37.2	35.4	32.9	30.4	29.4	30.61	32.8	34.6	34.6	34.0
Daily average, °C	29.3	30.9	32.1	32.4	31.3	29.2	27.2	26.3	27.23	28.8	29.8	29.0	29.5
Average low, °C	20.3	22.4	24.6	25.7	25.7	24.4	23.1	22.5	22.94	23.6	23.1	21.0	23.3
Recorded low, °C	13.8	16.6	20.7	23.0	22.5	21.7	20.4	19.9	20.48	21.3	20.1	16.1	13.8
Average precipitation mm	16.9	39.2	68.0	95.2	151.1	190.8	277.5	31.9	285.5	17.6	61.2	15.0	141.3
Average precipitation days (≥1.0 mm)	3.2	6.7	10.9	13.3	17.7	19.9	24.7	25.3	23.67	18.0	9.1	3.3	14.6
Average relative humidity (%)	36.2	41.6	46.82	53.6	63.6	71.1	77.7	81.6	79.5	69.3	52.8	39.4	59.4
Mean monthly sunshine hours	11.4	11.3	11.0	11.1	11.0	10.4	9.5	9.0	9.6	10.3	10.5	10.9	10.5

Table 2. Typical Nigerian weather by month [27].

Month	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Nov	Oct	Dec	Ave.
Recorded high, °C	39.5	41.2	41.9	42.6	42.8	40.2	36.0	33.4	36.37	38.7	37.8	38.2	42.8
Average high, °C	35.6	36.9	37.4	37.2	35.4	32.9	30.4	29.4	30.61	32.8	34.6	34.6	34.0
Daily average, °C	29.3	30.9	32.1	32.4	31.3	29.2	27.2	26.3	27.23	28.8	29.8	29.0	29.5
Average low, °C	20.3	22.4	24.6	25.7	25.7	24.4	23.1	22.5	22.94	23.6	23.1	21.0	23.3
Recorded low, °C	13.8	16.6	20.7	23.0	22.5	21.7	20.4	19.9	20.48	21.3	20.1	16.1	13.8
Average precipitation mm	16.9	39.2	68.0	95.2	151.1	190.8	277.5	31.9	285.5	17.6	61.2	15.0	141.3
Average precipitation days (≥1.0 mm)	3.2	6.7	10.9	13.3	17.7	19.9	24.7	25.3	23.67	18.0	9.1	3.3	14.6
Average relative humidity (%)	36.2	41.6	46.82	53.6	63.6	71.1	77.7	81.6	79.5	69.3	52.8	39.4	59.4
Mean monthly sunshine hours	11.4	11.3	11.0	11.1	11.0	10.4	9.5	9.0	9.6	10.3	10.5	10.9	10.5

Therefore, the total number of panels required is given as follows [24]:

$$N.P={\displaystyle \frac{\mathrm{W}}{R}}$$

(4)

where R is the rated power (W) of a single solar panel.

2.1.2. Battery Capacity

The battery capacity (BC) for energy storage is calculated considering 15% loss. Thus, the battery capacity (Amp–h) is given as follows [25]:

$$B.C={\displaystyle \frac{E_c\times d_f}{V \times 0.85}}$$

(5)

where:

V is the nominal battery voltage (taking as 12 V)

d_f is the temperature correction factor (1.01).

2.1.3. Charge Controller Design

The controller rating is based on the PV specifications. It is calculated as follows [24]:

$$C.R=N.P\times I\times 1.3$$

(6)

where I is the short circuit current of the 250 W PV panel, taken as 2.4 A. The specifications of the solar module are presented in

Table 3. Calculated solar panel specifications for cooling systems.

Solar PV Parameters	Ratings
Rated input power of the evaporative cooler (W)	25
Maximum running time per day (h) for solar panel	11.41
Actual daily energy consumed (kWh) including losses	1.11
Rate power of PV	242 but 250 W selected
Number of panels	1 panel, 12 V, 250 W
Battery capacity (A-h)	30 AH, 12 V with 3 days’ autonomy, running 7 h
Controller rating (A)	4 A by 12 V

, while the cost is presented in

Table 4. Capital cost of the solar evaporative cooler.

Materials	Rating	Quantity	Price (NGN)
solar panel	12 V/250 W	1	80,000
Water reservoir	20 L	1	2000
Wood shaving	-	30 g	-
Pipe	6 m	1	1000
Jumper wires	60 × 14	1	1000
Battery	30 A-H	3	33,000
controller	4 A,12 V	1	10,000
DC water pump	12 V, 5 W, DC	1	7000
Plywood	-	4	7000
Aluminum sheet (scrap)	0.45 mm	1 m2	-
Wire mesh	-	0.00183 m2	4000
Suction fan	1.64 m3/s, 12 V, 0.3 A, DC	2	18,000
Polyurethane foam	-	20 g	300
Digital Temperature and humidity sensor	3 V, 0.1 °C, 1%RH,	2	10,000
Total			NGN 173,300 (USD 203.00)

.

2.2. Description of the Cooler

The schematic representative design of the solar evaporative cooling system (EVC) is shown in Figure 1. The solar evaporative cooling system (EVC) shown in Figure 1 consists of a submersible water pump (6 V DC, 5 W, Decdeal, China), two water tanks (40 × 40 cm, polycarbonate glass), two cooling pads or wetting media (polyurethane foam and wood shavings), a water distribution line, four axial fans (8 × 8 cm, 12 V, 0.3 A DC, ADDA), a solar panel (250 W, 1.5 × 0.67 × 0.035 m), and a solar control charger, all housed in a rectangular-shaped hood (0.42 × 0.42 × 0.50 cm) with a particle board exterior and aluminum sheet lining to prevent heat infiltration and rust, as seen in the fabricated cooling system pictured in Figure 1.

The hood (casing) is divided into two sections: Section A is at the back while Section B is at the front. Section A contains the water pump, two axial fans, cooling pads, water distribution header, wetting media, and two water reservoir tanks. The water pump recirculates water from the bottom tank to the top tank, which is connected to the water distribution line that supplies water to the wetting media. The water from the top tank is distributed by gravity to the pads through the water distribution header. The two wetting media, polyurethane foam and wood shavings, are separately placed in compartments located on each side of the hood, as shown in Figure 2. Each compartment is designed to hold one type of wetting medium, allowing for simultaneous testing of both materials. The two axial fans are located between the cooling chamber and the cooling pads, sucking cooled air through the wetting medium into the storage chamber. The operating air flow rate is approximately 3 m/s, which is effective for this small evaporative cooling system. Behind the cooling pad holder is an air channel that distributes inlet air to both pads, covered with a galvanized net at the back of the hood. The fan and pump are powered by a solar photovoltaic (PV) panel, which collects solar energy and converts it to electrical energy. A solar charge controller is used to control the power going from the solar panels to the accessories. The balance of the system (BOS) diagram of the PV system connection is presented in Figure 3.

Section B, which is the cooling chamber, is divided into two storage sections: Cooling Chamber A and Cooling Chamber B, which operate simultaneously. Cooling Chamber A uses polyurethane foam as the wetting material, while Cooling Chamber B uses wood shavings. The two storage chambers are designed to cool fruits and vegetables with different temperature needs simultaneously.

2.3. Cooling Efficiency

The effectiveness of the pad is based on the saturation efficiency. The saturation efficiency (η) of the cooling pad used was calculated using the formula by Harris [28] as:

$$\eta ={\displaystyle \frac{T_a-T_c}{T_a-T_w}}$$

(7)

where:

• T_a = dry-bulb inlet temperature, °C
• T_c = dry-bulb exhaust temperature, °C
• T_w = wet-bulb inlet temperature, °C given as follows.

The wet-bulb temperature is derived with Equation (8) as follows [18,19]:

$$\begin{gathered} T_w= T_{db}\times \arctan \left[0.151977\times \sqrt{R\mathrm{h}+8.313659}\right]+\arctan \left(T_{db}+R\mathrm{h}\right) \\ -\arctan \left(R\mathrm{h}-1.67633\right) \\ +0.00391838\times {\left(R\mathrm{h}\right)}^{3/2} \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\times \mathrm{a}\mathrm{r}\mathrm{c}\mathrm{t}\mathrm{a}\mathrm{n}\left(0.023101\times R\mathrm{h})-4.686035\right) \end{gathered}$$

(8)

where T_db is the dry-bulb temperature (°C), and Rh is the relative humidity (%).

2.4. Formulation of Energy Metrics

The flow chart of the energy analysis is shown in Figure 4. The figure depicts the energy flow of the solar evaporative cooling system, showcasing its potential for sustainable and energy-efficient cooling solutions. The input solar energy is the energy from the sun that drives the cooling process, while the embodied energy represents the energy invested in the system’s production and materials. Meanwhile, Energy Output represents the cooler cooling energy potential, illustrating the ultimate goal of the evaporative cooler to provide cooling energy.

2.4.1. Energy Payback Time (EPBT)

This is the time needed to recover energy input during the production of components. It is given as follows [29,30]:

$$EPBT={\displaystyle \frac{E_{emb}}{E_{out}}}$$

(9)

E_emb is the embodied energy (kWh) of the components presented in

Table 5. Estimated embodied energy for the solar evaporative cooler components [31,32,33].

Materials	Embodied Energy (kWh)
Solar panel (12 V, monocrystalline, 1.62 m2)	4084.6
Water reservoir (polycarbonate), 20 L, 0.2 kg	5.8
Charge controller	182.0
Wood shaving, hardwood (0.03 kg)	0.1
Pipe (rubber), 0.2 kg	5.0
DC water pump, 13 V, 5 W, submersible	0.4
Plywood, 4 kg	17.1
Polyurethane foam (0.02 kg)	0.6
Total solar PV operation and maintenance, electronic components, cables, and other miscellaneous components, etc., taking into account 10% extra [34]	1188.4
Total	5484

.

The energy output flow (E_out) of the system was deduced considering both electrical and thermal energy flows. In this case, these two energy flows include the solar gain expanded in the form of solar power output from the PV module and the energy output of the cold air utilized in cooling the product. Assuming that the solar PV-module-powered evaporative cooler runs for 20 h per day, the energy output per year (E_out) of the entire system (Wh) is the sum of the energy output by the solar PV module for powering the system per year (Wh/year) and the thermal energy extracted from the air and utilized in cooling load removal by the evaporative cooler per year (Wh/year), which was calculated as follows:

$$E_{out}=\left[({\dot{m}}_a\times C_{p,air}\times \Delta T)+\left(P\times 0.75\right)\right]\times t_{year}$$

(10)

where ${\dot{m}}_a$ is the airflow rate (kg/s), C_pair is the specific heat capacity of air (J/kg·K), ΔT is the average change in temperature (°K), P is the rated power of the PV module (W), and t_year is the total annual time of operation per year (h/year).

2.4.2. Energy Production Factor

The energy production factor is given in Equation (11) [34] as follows:

$$EPF={\displaystyle \frac{E_{out}\times n}{E_{emb}}}$$

(11)

where n is the lifetime of the cooling system (10 years).

2.4.3. Coefficient of Performance (COP)

The coefficient of performance (COP) is determined as the ratio of thermal cooling obtained to energy input [35]:

$$COP={\displaystyle \frac{{\dot{m}}_a\times C_{p,air}\times \Delta T}{Energy input}}$$

(12)

2.4.4. Life Cycle Conversion Efficiency (LCCE)

This is the ratio of the overall energy output by the system with respect to the energy input over the lifetime of operation of the evaporative cooler, adapted from Rajput et al. [34] as follows:

$$\mathrm{L}\mathrm{C}\mathrm{C}\mathrm{E}={\displaystyle \frac{E_{out}}{E_{in}}}\left(1-{\displaystyle \frac{E_{emb}}{E_{out}\times n}}\right)$$

(13)

where:

E_in is the annual energy input (kWh/year).

2.5. Greenhouse Gas Emissions

The benefit of using an evaporative cooler is its carbon emission mitigation potential. The environmental impact of using the cooler is assessed based on diesel- and electricity-powered systems. The greenhouse gas emission mitigation potential of the cooling system is determined as follows. For a diesel-powered cooling system, the energy consumed in running the fans and pump in kWh is determined as follows by Ndukwu et al. [33]:

$$E=v_d{k}_d{\eta }_d$$

(14)

where E is the overall energy consumed in cooling (kWh), η_d is the power efficiency of a diesel generator taken as 35%, k_d is the heating value of diesel, taken as 10.08 kWh/L, and v_d is the amount of diesel (L) consumed to produce the energy used to power the system.

Combining Equations (1) and (14), the volume of the diesel (v_d) is deduced. Thus, the mass of CO₂ mitigated per year is calculated as follows [32]:

$$m_{CO2}=v_d{k}_f$$

(15)

k_f is a constant given by Ndukwu et al. [35] as 2.63 kg/L.

For an electricity-powered cooling system, (Case 1) the CO₂ is determined as follows [36]:

$$M_{{CO}_2}= {\mathrm{E}\mathrm{F}}_{{\mathrm{C}\mathrm{O}}_2}x E_{ce}$$

(16)

where EF_CO2 is the country emission factor, which is 0.4392 kg of CO₂/kWh for Nigeria.

One of the benefits of evaporative cooling is the atmospheric mitigation of carbon dioxide. Thus, to encourage the adoption of green energy in the country’s energy mix, the carbon emission can be quantified monetarily as earned carbon credit, as in Equation (17) [37]:

$$E{CO}_2=\${CO}_2\times m_{{CO}_2}$$

(17)

where $CO₂ is the price of CO₂ taken as 14.5 USD per ton [36], and $m_{{CO}_2}$ is the mass of CO₂ emissions (tons) per year [37].

2.6. Life Cycle Cost Assessment

This involves the present and future cost of all the components of the evaporative cooling system, the net present values, the internal rate of return, and payback time. A typical cost analysis of a typical tomato farm in Nigeria was deployed for the cost inventory, as presented in

Table 6. Typical farm production data for tomatoes in Nigeria.

Farm	Cost Components
Product	Tomatoes
Durations for sales of cooled products per batch	3 days
Assuming a 2 kg capacity of evaporative coolers per batch, mass handled by the cooler per year	243 kg
Cost of production per kg of tomatoes	400 NGN (0.44 USD) per kg
Selling price of the preserved product per kg assuming 40% savings from postharvest losses (PHL) for Nigeria [5]	644 NGN (0.71 USD) per kg
Annual cost of production per year	NGN 97,200 (USD 106.92)
Annual selling price of preserved product assuming 40% × PHL savings	NGN 156,492 (USD 172.14)
Profit margin per year of preserved product assuming 40% × PHL savings	NGN 59,292 (USD 65.22) (61%)

It has been estimated that preservation can increase the profit margin by 40% by reducing storage risk [5].

.

2.6.1. Annualized Uniform Cost (AUC)

We first determine the annualized uniform cost (AC) of running each cooling and drying system as follows [38,39]:

$$AC=C_c+C_{rf}+C_{re}$$

(18)

where C_rf is the fuel running cost of fan and pumps, which is zero for solar systems [39], and C_re is the chargeable energy cost for running the electrical components, given as [38]:

$$C_{re}=t\times p\times C_e$$

(19)

where t is the equipment running time, p is the total input power, and C_e is the chargeable cost of electricity in a year. This value is taken as zero since the system is off-grid [38]. C_c is the uniform cost of equipment, given as follows [38,39]:

$$C_c=C_{cc}\times FR$$

(20)

$$RF={\displaystyle \frac{i{\left(i+1\right)}^n}{{\left(i+1\right)}^n-1}}$$

(21)

The capital cost (C_cc) is determined as follows [34]:

$$C_{cc}=P+P_{mr}+P_{rc}-P_s$$

(22)

P is the breakdown of all the various equipment component costs as presented in Table 4 for the cooling system.

$P_{mr}$ is the maintenance cost given in present value as follows [34]:

$$P_{mr}=m_{ce}\times \left({\displaystyle \frac{{\left(i+1\right)}^n-1}{{\left(i+1\right)}^n}}\right)$$

(23)

where:

i is the interest rate, n is the number of years, and m_ce is the annual maintenance and repair cost (2.5% of initial equipment cost).

The battery is the major component requiring frequent replacement for the system. Assuming a year’s replacement time of the entire duration of 10 years for the system lifetime, the net replacement cost (P_rc) is determined as follows [34]:

$$P_{rc}=R_5\times \left[{\displaystyle \frac{1}{{\left(i+1\right)}^5}}\right]+R_{10}\times \left[{\displaystyle \frac{1}{{\left(i+1\right)}^{10}}}\right]$$

(24)

where R is the replacement cost.

The net junk value at the end of the service life of the evaporative cooler is given as follows [34]:

$$P_s=S\times \left[{\displaystyle \frac{1}{{\left(i+1\right)}^n}}\right]$$

(25)

2.6.2. Net Present Value (NPV)

The net present value is determined as follows [40]:

$$\mathrm{N}\mathrm{P}\mathrm{V} = {\sum }_{\mathrm{t}=0}^{\mathrm{n}}{\displaystyle \frac{{\mathrm{X}}_{\mathrm{t}}}{{\left(1+\mathrm{d}\right)}^{\mathrm{t}}}}-\mathrm{A}\mathrm{C}$$

(26)

where:

X_t is the net cash flow, d is the discount rate per year taken as 2.7%, t is the total period count, and n is the number of years.

2.6.3. Internal Rate of Return (IRR)

The internal rate of return value is determined as follows [40]:

$$NPV=\sum _{i=1}^n\left[{\displaystyle \frac{{\mathrm{C}}_{\mathrm{i}}}{{\left(1+IRR\right)}^n}}\right]-AC$$

(27)

The payback period (PBP) is determined as follows [41]:

$$PBP={\displaystyle \frac{C_{cc}-P_s}{{AS}_{av}}}$$

(28)

where AS_av is the average annual saving on energy costs. A unit cost of energy in Nigeria is projected at 88 NGN/kWh in 2023 without subsidy.

2.6.4. Levelized Cost of Energy

To understand the benefit of solar-powered evaporative cooling, it is useful to consider the total energy output produced by the system including that of the PV module in terms of net present value of cost produced per unit of energy utilized in its lifetime. This is termed levelized cost of energy (LCOE), given as follows [24]:

$$LCOE={\displaystyle \frac{total life cycle cost}{ total lifetime cost of energy produced}}={\displaystyle \frac{\sum _{i=1}^n\left(\frac{P \times {\left(1 + i_{inf}\right)}^n}{\left(1 + d\right)}\right)}{\sum _{i=1}^n\left(\frac{{\left(1 + i_{inf}\right)}^n}{\left(1 + d\right)}\times E_o\times {\left(1-\zeta \right)}^n\right)}}$$

(29)

where:

P is the capital cost, i_f is the inflation rate, d is the discount rate (2% of NPV), and n is the number of years.

E_o is power produced in the first year, and $\zeta$ is the degradation rate of the solar PV module (0.05%).

2.7. Experimental Procedure

2.7.1. Pad Preparation

The evaporative cooling pad creates the environment required for exhaust air humidification, which provides the heat transfer dynamics. This lowers the exhaust air temperature and improves its humidity, which is required for vegetable cooling and preservation. Thus, the used biomass cooling pad materials, made up of polyurethane foam and wood shavings, were sourced from polyurethane waste from local furniture makers and timber processors. The selection of wood shavings and polyurethane foam as cooling pads in evaporative cooling was influenced by their favorable thermal properties. Wood shavings offer high specific heat capacity, porosity, and moderate thermal conductivity, allowing for efficient heat transfer and water absorption, as well as allowing air to pass through, which is one of the requirements for cooling pads. On the other hand, polyurethane foam boasts high porosity and water absorption, enabling effective heat dissipation through evaporation. Therefore, the thermo-physical properties of these materials leverage their synergistic effects, creating a cooling pad that excels at absorbing water and dissipating heat through moisture evaporation as the air flows through them. The cooling pads were processed by manually reducing their sizes to fit into the pad holder’s compartments, after which they were loaded into the cooling pad holder (Figure 5) at a thickness of 0.02 m. The pad holder with the cooling pad is slotted into position from the two sides of the first compartment of the housing, as described earlier.

2.7.2. Operation Loop and Field Measurements

The evaporative cooler was placed under an open field shaded beside a papaya tree. This action was performed to reduce the direct action of solar radiation and expose the evaporative cooling system’s inlet air and water tank to a cool ambience. The water tank (20 L) was initially left open to allow the prevailing wind to passively cool the water for about 5 min before opening the water header linking the tank with the spray header to allow water to be delivered to the pads from the edges of the pads. From the edges, the water drains down the cooling pads by both gravity and capillary action until the pad is saturated, as the water pump recirculates the water continuously. Next, the fans were switched on to deliver the inlet air towards the cooling pads. The air absorbs moisture and transfers some of its heat to the water and pad material before exiting into the cooling chamber at a lower temperature and higher humidity. The temperature of the cooling chamber was allowed to stabilize for 1 h before adding 200 g of fluted pumpkin leaves into it. For each cooling batch, the evaporative cooler can also handle 2 kg of products like tomatoes, oranges, and other vegetables. The temperature and humidity sensors attached to the body of the EVC automatically record the cooling chamber temperature (±0.01 °C) and humidity (±0.01%) as well as the ambient conditions through the k-type thermocouple and project it to the LED screen. These data were collected at 1 h intervals for three days (20–23 October 2023 for no-load condition and 24–26 October 2023 for load condition) and used for analysis. Figure 6 shows the operational loop of the evaporative cooling system.

2.8. Experimental Uncertainty

The uncertainty (Ux) in measuring temperature, relative humidity, and cooling efficiency is calculated as [42]:

$${\mathrm{U}}_{\mathrm{x}}={\left[{\left({\displaystyle \frac{\partial \mathrm{R}}{{\mathrm{z}}_1}}\right){\mathrm{w}}_1}^2+{\left({\displaystyle \frac{\partial \mathrm{R}}{{\mathrm{z}}_2}}\right){\mathrm{w}}_1}^2+\dots +{\left({\displaystyle \frac{\partial \mathrm{R}}{{\mathrm{z}}_2}}\right){\mathrm{w}}_{\mathrm{n}}}^2\right]}^{1/2}$$

(30)

where w₁, w₂, and w_n are the experimental uncertainties in the variables z₁, z₂, and z_n. For temperature, relative humidity, and cooling efficiency, the calculated uncertainties for their measurements were ca ±0.124%, ±1.02%, and ±0.34%, respectively.

3. Results and Discussion

3.1. Influence of Cooling Pads on Transient Response of the EVC to Weather Conditions

This cooler was developed to remove field heat acquired by vegetables and fruits before harvest and lower their temperature before packaging or shipping. It was assumed that the cooler can cool about 243 kg of products per year in batches of 2 kg, holding up to 3 days before sales or shipping. It was also assumed that cooling starts immediately after harvest. However, the cooler was tested with wood shavings and polyurethane foam as wetting media simultaneously without products (no-load conditions) and with products (load conditions). The evolution of ambient and relative humidity for two different cooling scenarios with wood shavings and polyurethane foam as wetting media are shown in Figure 7a, Figure 7b, Figure 8a, and Figure 8b, respectively, for the experiment. The lower cooler temperature (Figure 7a and Figure 8a) and higher humidity (Figure 7b and Figure 8b) were achieved with medium-density polyurethane foam for both no-load and load conditions compared to wood shavings, respectively. This might be due to a combination of factors, including higher porosity and moisture distribution rate of polyurethane foam compared to wood shavings. Materials with higher porosity provide better water distribution, greater airflow rate, increased surface area due to higher porosity, and increased evaporation rate, thus providing higher latent heat exchange between moisture and inlet air. Evaporative cooling depends on the evaporation of moisture from the pads; therefore, materials that are more porous with higher moisture absorption rates will quickly provide a larger body of water that will enable more water to evaporate faster, resulting in greater heat transfer from the air to the moisture. Therefore, it can quickly take full advantage of the evaporative cooling process. It will also reduce the possibility of hotspots due to dry-out of the pad surface with better humidity control. Additionally, polyurethane foam has higher thermal conductivity than wood shavings, allowing a faster heat transfer rate and cooling of the inlet air. However, by this variable degree of cooling and humidification, the system presents two different temperature ranges that could be deployed for cooling or preserving different kinds of fruits and vegetables based on their temperature sensitivities. This depends on the knowledge of cooling load requirements for different fruits and vegetables. Wood shavings and polyurethane foam provided temperature depression ranges of 0.22 to 5.2 °C and 0.57 to 10.94 °C, respectively, of inlet dry-bulb temperature for the no-load condition, as shown in Figure 7a, with average values of 3.46 and 7.04 °C. The values were 0.79 to 4.7 °C and 1.22 to 9.88 °C, with average values of 3.09 and 7.0 °C for the same materials for loaded conditions, respectively, as shown in Figure 8a. These values of temperature drop for wood shavings are very low compared to those obtained by some researchers [14,15,16,17,43]; however, the value for polyurethane foam is within the range of values in the literature. For example, Olosunde et al. [14] obtained an exhaust temperature of 7.8 °C, while Saleh et al. [15] obtained an average temperature depression of 7 °C. Similarly, Mekonen et al. [16] presented a temperature drop of about 9 to 15 °C for a two-stage cooler. The average difference for temperature depression between wood shavings and polyurethane foam was significant (p < 0.05). However, wood shavings and polyurethane foam provided average humidity increases of 15.85 to 38.63% and 28.18 to 51.78%, respectively, of inlet air for the no-load condition over the trial period, as shown in Figure 7b, while the values were 29.39 to 35.7% and 47.22 to 53.5% for the same materials for loaded conditions, respectively, as shown in Figure 8b.

3.2. Performance Analysis of the EVC

The major purpose of this work was to lower the temperature of the product without using grid or diesel-powered systems, and thus the availability of solar energy provides an advantage. First, the solar PV module was sized based on the fan and water recirculation pump capacity to provide the desired cooling load to be removed. To supply the electric energy, a 250 W solar photovoltaic cell and a battery of 30 Ah were needed to run the cooler for 20 h per day. This energy was supplied by a single solar photovoltaic cell of 250 W capacity.

Table 7. Cooling system parameters.

Parameters	Values
Average running time per day with battery (h)	20
Average running time per year (h/year)	7300
Equipment power source efficiency (%)	20% [44]
Rated power of evaporative cooler (kW)	0.025
Actual energy consumed per hour (kWh)	0.0975
Actual energy consumed per day (kWh/day)	1.95
Actual energy consumed per year (kWh/year)	711.75
Air flow rate	0.0072 kg/s

shows the energy consumption parameters of the solar-powered evaporative cooling system. Based on cooling demand, the evaporative cooler needed 711.75 kWh/year to produce the required cooling demand discussed above. However, this energy consumption produced different cooling capacities for the different cooling scenarios, as shown in Figure 9 and Figure 10, respectively, under no-load and loaded conditions. However, polyurethane foam produced higher cooling capacity than wood shavings in all cases due to its higher moisture absorption capacity compared to wood shavings, as stated earlier, which reflected in higher temperature reduction compared to wood shavings.

Under load conditions, the cooling capacity ranged from 5.7 to 33.93 W for wood shavings, while it was 8.13 to 75.55 W for polyurethane foam. In contrast, these values ranged from 1.6 to 37.63 W and 4.1 to 79.18 W for wood shavings and polyurethane foam, respectively, under no-load conditions. This shows the greater cooling effect of polyurethane foam, which resulted in a cooling efficiency of 19.9 to 96.42% and 14.14 to 82.86% compared to 3.62 to 60% and 8.98 to 35.93% for wood shavings under no-load and load conditions, as shown in Figure 11 and Figure 12, respectively. These results suggest that polyurethane foam is a more effective material for cooling applications, with higher cooling capacity and efficiency compared to wood shavings. The performance of polyurethane foam is consistently better under both load and no-load conditions, making it a more reliable choice as a wetting medium for cooling applications.

The COP of the solar PV-powered evaporative cooler ranged from 2.37 to 22.92 for load conditions and 0.52 to 25.37 for no-load conditions for the two cooling pads, as shown in Figure 13 and Figure 14, respectively. However, polyurethane pads consistently showed a higher COP compared to wood shavings in all conditions. This value is higher than the COP of a solar PV-powered chiller, which was deduced as 0.6 to 0.72 at a temperature of 70 to 110 °C [35]. Grossman [43] also reported a COP of 0.7 to 1.7 for solar absorption refrigeration. These findings suggest that the solar PV-powered evaporative cooler using polyurethane pad has a high COP, indicating efficient cooling performance. The comparison with other solar-powered cooling systems highlights the potential of this technology. However, the variation in COP values across different studies may be due to differences in system design, operating conditions, and materials used. The higher ranges of COP values achieved in this research demonstrate the potential of solar-powered evaporative cooling systems for efficient cooling applications, particularly in situations where traditional vapor-compression systems may not be feasible. Further research and development can focus on optimizing system design and materials to achieve even higher COP values and improve the overall performance of these systems.

3.3. Energy Metric Analysis

Table 8. Energy payback time, LCOE, energy production factor, and life cycle conversion efficiency.

Cooling Scenario	Energy Payback Time (Years)	LCOE (NGN/kWh)	Energy Production Factor	Life Cycle Conversion Efficiency
No-load wood shavings	2.18	38.26	2.3	0.51
No-load polyurethane foam	1.18	36.72	2.4	0.54
Loaded wood shavings	2.03	38.41	2.31	0.51
Loaded polyurethane foam	1.13	36.88	2.41	0.53

shows the energy metrics for different cooling scenarios based on energy input and output for each case. The average electrical and thermal energy output and the embodied energy were used to calculate the energy payback time under different cooling scenarios. The average energy payback time was calculated as 1.13 to 2.18 years for all the cooling scenarios, with the polyurethane wetting pad having the lowest energy payback time. This showed that polyurethane utilized lower thermal energy compared to wood shavings to produce a higher amount of cooling, since the electrical energy output for all the cooling scenarios was assumed to be the same. Thus, they had a higher energy production factor of 2.4 compared to wood shavings, which was recorded as 2.3, as shown in Table 8. However, the life cycle energy conversion efficiency for a 15-year period for each cooling scenario was not significantly different (p < 0.05), as can be seen in Table 8, with an average value of 0.5. However, with a very low levelized cost of energy ranging from 36.72 to 38.26 NGN/kWh (0.043 to 0.045 USD/kWh), which is far below the value of grid-based subsidized energy system cost in Nigeria (67 NGN/kWh), a user who has invested in the solar PV evaporative cooler will have a better energy investment. It is worth mentioning that the levelized cost of energy (LCOE) metric has some limitations, including adopting a very simple approach that assumes fixed costs over time, ignoring the impact of environmental and social conditions that might affect lifespan and technology-specific limitations like neglecting improvements or degradation over time, and assuming fixed capacity factors. Additionally, LCOE does not account for location-specific differences in costs, resources, and policies and assumes a fixed cost of capital. The metric also has timeframe limitations, typically evaluating costs over a fixed period like 20 years, which may not capture long-term costs or benefits. Finally, the choice of discount rate can significantly impact LCOE results, and different rates may be more appropriate for different technologies or locations. However, despite these limitations, LCOE can be used as a starting point for cost evaluation and can then be complemented by other cost analyses for a more comprehensive cost analysis.

3.4. Greenhouse Gas Emissions

Globally, the major issue is cutting down greenhouse gas emissions as a result of non-renewable energy generation [45]. Thus, the benefit of the solar PV-powered cooler is its greenhouse gas mitigation potential. The result was presented over the lifetime of the small solar PV evaporative cooler, taking 15 years. The mass of CO₂ mitigated was compared with diesel and grid-based electricity [46]. Equations (13) and (14) were used to calculate the mass of CO₂ generated from diesel and grid-connected systems using Nigerian emission factors, respectively, while the earned carbon credit was calculated with Equation (15).

Table 9. CO₂ emission potentials for different energy scenarios.

Energy Scenarios	Annual CO2 Emission (kg)	CO2 Mitigation per kWh	CO2 Emission over the Lifetime (kg)	Cost of Carbon Credit over the Lifetime (NGN)
Electricity	350.06	0.492 kg/kWh	5250.87	65,059.6 (USD 71.56)
Diesel	530.40	0.75 kg/kWh	7955.97	98,576.4 (USD 108.43)
Solar	119.59	0.168 kg/kWh	1793.97	22,214.7 (USD 24.43)

gives a breakdown of both the annual and lifetime CO₂ mitigation potential of the system. These values were 5.25 tons for grid-connected electricity and 7.955 tons for diesel generators over the lifetime. In terms of energy input, this will translate to 0.492 kg mitigated per kWh for grid electricity and 0.75 kg per kWh for diesel generators if the solar PV evaporative cooler is used instead of grid-connected systems or a diesel generator. Considering the above results compared to the embodied energy of the solar PV module, the lifetime CO₂ emission $\left({\displaystyle \frac{E_{in}\times {EF}_{{CO}_2}}{life time}}\right)$ of the PV module [47,48] was calculated as 1.79 tons, which is considerably lower than that of diesel and grid-based electricity as presented in Table 9. Furthermore, this comparatively will also translate to earned carbon credits of NGN 65,059 (USD 71.56), NGN 98,576.49 (USD 108.43), and NGN 22,214.73 (USD 24.43) for grid electricity, diesel, and the solar PV module, respectively, across their lifetimes.

3.5. Unit Cost Analysis

The analysis of cash flow and input assumptions is presented in

Table 10. Analysis of cash flow input assumptions for the year 2023, Nigerian case study.

Assumptions	Input	Source
The projected life of the evaporative cooler	15 years	Based on assumption
Projected life of PV panel	15 years
Battery (Lead-acid)	5-year replacement	Most acid batteries have a life duration of 5 years
Maintenance cost	2.5% of capital cost
Degradation rate of PV module	0.5%	[49,50]
Inflation rate	27.33%	[51]
The tax rate for Nigeria	24%	[52]
Interest rate	18.75%	[53]
Salvage value	15% of capital cost	Salvage values of most assets range between 0 and 20% of initial capital cost at the end of its service life [54]
Discount rate	2.7%	The discount rate of Nigeria ranged between 1.4 and 4.2% for [55]

. The cash flow analysis was conducted based on the production output cost of a typical farm in Nigeria presented in Table 6, assuming it adopted the evaporative cooling system to cool its product before sale. The payback period was deduced with Equation (25), relating to the annual cost of energy savings in Nigeria, if the cost of the cooler energy utilization is substituted with grid-based electricity cost with the project capital cost. The cost output generated includes the net present value, internal rate of return, and payback period for the small evaporative cooling system, as presented in

Table 11. Cost analysis results for cold storage.

Annualized Uniform Cost for Equipment (NGN)	NPV (NGN)	Net Cash Flow (NGN)	IRR (%)	Payback (Years)
251,919.2 (USD 277.11)	447,673.11 (USD 492.44)	618,880 (USD 680.77)	20.6%	2.4

. The annualized cost of the cooler is determined as NGN 251,919.2 (USD 277.11). The results showed a positive net present value and internal rate of return of 20.6% with a payback period of 2.4 years. This research involved a laboratory-sized evaporative cooling test bed, which was used for a small quantity of products. Thus, if the cooler is scaled up to cool a larger quantity of product, the internal rate of return will increase due to increased sales of a larger quantity of product. With investors recovering their initial investment in 2.4 years before financing, it is possible to lower the selling price of the products and still recover your investment.

4. Conclusions

The study on the techno-economic evaluation of a small twofold-chamber PV-powered evaporative cooling system for fruit and vegetable preservation was performed. The experimental evaporative cooler is a prototype that serves as a test bed, which can be scaled up to a larger scale. A comparative analysis of two cooling pads, including wood shavings and polyurethane foam, was presented. In terms of cooling efficiency, cooling capacity, COP, and energy payback time, the polyurethane foam presented better performance compared to wood shavings due to its higher moisture absorption capacity. Therefore, it is recommended as a better alternative cooling pad when exotic ones are not available. Moreover, the COP of the solar PV-powered evaporative cooler was higher than the COP of solar-powered mechanical chillers and ranged from 2.37 to 22.92 for load conditions and 0.52 to 25.37 for no-load conditions, thus showing lower energy consumption, higher efficiency, and lower operating cost. However, the cooling efficiency of 19.9 to 96.42% and 14.14 and 82.86% for polyurethane foam was achieved compared to 3.62 to 60% and 8.98 and 35.93% for wood shavings under no-load and load conditions. The average energy payback time was very short, ranging from 1.13 to 2.18 years for all the cooling scenarios, with the polyurethane wetting pad having the lowest energy payback time. The energy production factor of 2.4 for polyurethane foam compared to wood shavings, which was estimated at 2.3. However, the life cycle energy conversion efficiency for a 15-year period for each cooling scenario was not significantly different (p < 0.05). The net present value was positive, while the levelized cost of energy ranged from 36.72 to 38.26 NGN/kWh (0.043 to 0.045 USD/kWh), lower than the value obtained from the grid-based subsidized energy system cost in Nigeria (67 NGN/kWh). The avoidable CO₂ emissions were estimated at 5.25 tons for grid-connected electricity, 7.955 tons for diesel generators, and 1.79 tons for solar modules over their lifetimes, which translate to earned carbon credits of NGN 65,059 (USD 71.56), NGN 98,576.49 (USD 108.43), and NGN 22,214.73 (USD 24.43) for grid electricity, diesel, and solar PV modules, respectively, over their lifetimes. The net present values were positive, with an IRR of 20.6% and a payback period of 2.4 years. In the future, the exergy sustainability analysis of the system will be carried out, and the heat and mass transfer simulation models presented.