# Storage conditions, energy consumption, and food safety implications of domestic refrigerators in Bangkok

Nattawut Chaomuang, Cheeraphat Potisuwan, Steven Duret, Evelyne

Derens-Bertheau, Yvanne Paviet-Salomon, Methawee Nukunudompanich,
Onrawee Laguerre

► To cite this version:

Nattawut Chaomuang, Cheeraphat Potisuwan, Steven Duret, Evelyne Derens-Bertheau, Yvanne Paviet-Salomon, et al.. Storage conditions, energy consumption, and food safety implications of domestic refrigerators in Bangkok. Applied Food Research, 2025, 5 (2), pp.101512. 10.1016/j.afres.2025.101512. hal-05463433

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# Storage conditions, energy consumption, and food safety implications of domestic refrigerators in Bangkok

Nattawut Chaomuang<sup>a</sup>, Cheeraphat Potisuwan<sup>a</sup>, Steven Duret<sup>b</sup>, Evelyne Derens-Bertheau<sup>b</sup>, Yvanne Paviet-Salomon<sup>b, c</sup>, Methawee Nukunudompanich<sup>c, *, d</sup>, Onrawee Laguerre<sup>b</sup>

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

### Keywords:

- Temperature control

- Food preservation

- Food safety

- Fridge

- Freezer

- Cold chain

- Predictive microbiology

## ABSTRACT

Domestic refrigeration plays a critical role in food preservation and safety by maintaining optimal storage conditions for perishable items. This study investigated the temperature and humidity conditions, as well as the energy consumption, of domestic refrigerators in Bangkok. Data were collected through on-site investigations of 123 refrigerators using data loggers to record temperature, humidity, and electrical consumption over a five-day period. In addition, a predictive microbiological model was used to assess the potential for microbial growth under the investigated storage conditions, specifically of *Listeria monocytogenes* and lactic acid bacteria (LAB). Results indicated that although the overall mean temperatures of chilling compartments (5.0 ± 2.5 °C) were within the recommended range for domestic refrigeration, only about 30–40 % of individual refrigerators consistently maintained temperatures at or below 5 °C on the top and middle shelves throughout the five-day monitoring period, where fresh and ready-to-eat products are typically stored. Electrical consumption analysis revealed significant differences across refrigerator types; appliances with two doors and bottom freezers exhibited the highest annual electrical consumption, while single door refrigerators recorded the lowest. However, the specific energy consumption (SEC) did not differ significantly among refrigerator types. The microbial exposure assessment based on a test product highlighted that for over 50 % of refrigerators, *L. monocytogenes* load exceeds the regulation safety limits (³ 10² CFU/g) within five days. These findings emphasize the need for improved temperature control, appliance design, and consumer education to ensure food safety and energy efficiency in domestic refrigeration.

## 1. Introduction

Refrigeration plays a crucial role in reducing post-harvest losses and preserving food products, ensuring that perishable items are maintained under optimal conditions to provide consumers with safe and healthy food. The integrity of the cold chain from production to consumption must be carefully controlled to prevent spoilage and foodborne illnesses. A review on temperature abuse in food cold chains revealed that much more is known about this issue in developed countries compared to developing ones (Ndraha et al., 2018). The Codex Alimentarius Commission (2014) states that insufficient food temperature control is one of the most common causes of foodborne illness, and the lack of an effective cold chain contributes to significant global food losses, reaching up to nearly 20 % of the total food supply, which could be reduced with

better temperature management (IIR, 2019).

Domestic refrigeration is an essential component of this cold chain. With an estimated 2 billion refrigerators and freezers worldwide (UNEP, 2019), consuming nearly 4 % of global electricity (IIR, 2019), it is clear that these appliances play a crucial role in food preservation. In domestic refrigerators, temperature is the main factors affecting the safety and quality of perishable commodities as it may exceed recommended limits (Hoffmann et al., 2021). Approximately 87 % of reported food-borne outbreaks occur at the household level, often due to improper handling, storage, and preparation (FSA, 2019). Additionally, fresh fruits and vegetables lose around 3 to 10 % of their mass through irreversible wilting and shrinkage, contributing significantly to food waste (Chaomuang et al., 2024; Lufu et al., 2020). Given that products remain stored in domestic refrigerators for longer periods compared to other

<footnote><sup>a</sup> Department of Food Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand</footnote>

<footnote><sup>b</sup> Université Paris-Saclay, INRAE, FRISE, 92761, Antony, France</footnote>

<footnote><sup>c</sup> Department of Industrial Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: methawee.nu@kmitl.ac.th (M. Nukunudompanich).</footnote>
steps in the cold chain (Derens-Bertheau et al., 2015), maintaining proper preservation conditions becomes even more critical. The growing demand for chilled convenience foods with extended shelf lives, up to several weeks, necessitates storage at appropriate temperatures, typically between 4 and 6 °C, to ensure both safety and quality until consumption (Daelman et al., 2013). Despite these requirements, many consumers maintain an optimistic bias, considering the domestic environment inherently safe (Byrd-Bredbenner et al., 2013; Taché &ARPENTIER, 2014), which emphasizes the need for a better understanding of food preservation and handling in households.

Although many countries recommend operating temperatures for domestic refrigerators, these guidelines are often not legally enforced. For instance, since 2002, the French government has required that all domestic refrigerators maintain a chilling compartment with a mean temperature below 4 °C and be equipped with a temperature indicator (Lagendijk et al., 2008). Monitoring, tracking, and measuring food temperatures provide essential information regarding real-time temperature abuse and help identify specific locations or stages in the cold chain where such issues occur. While major manufacturers and retailers typically maintain an effective cold chain, domestic refrigerators often exhibit problematic temperatures (van der Vossen-Wijmenga et al., 2024). Surveys conducted across various countries have demonstrated that domestic refrigerators in real-world use frequently operate at temperatures that are too high. Data compiled from 42 surveys in 19 Western countries, including the United States, Europe, Canada, Australia, Latin America, and New Zealand (Kurth, 2003), and from 5 surveys in 5 Eastern countries (cited in James et al. (2017) and Bonan-nom and Bergis (2021)) report overall temperatures measured over one or several days at various positions (top, middle, and bottom shelves). These measurements account for temporal fluctuations due to compressor on-off cycles and spatial temperature distributions, especially in refrigerators without fans, where natural convection causes warmer air to rise and cooler air to settle (Laguerre et al., 2010).

In Western countries, domestic refrigerators typically exhibit a mean temperature of around 6.0 ± 2.0 °C, with minimum and maximum temperatures of approximately 0.0 ± 2.0 °C and 11 ± 2.0 °C, respectively. About 54 % of these refrigerators operate at temperatures exceeding 5 °C, while around 66 % exceed 4 °C. In Eastern countries, the mean temperature is slightly lower at 5.0 ± 3.0 °C, with a minimum of -4.0 ± 1.5 °C and a maximum of 11 ± 3.0 °C, although these figures exclude refrigerators affected by electricity outages in Lebanon. However, the data from Eastern countries must be interpreted cautiously given that the number of surveys is about eight times lower than those from Western regions.

Overall, the global data indicate that consumer food safety remains a significant concern, particularly because many domestic refrigerators operate above the recommended 5 °C, exceeding the Food Standards Agency's guideline for domestic refrigerators (FSA, 2025). Under real-world conditions, average temperatures and fluctuations within refrigerators may not be adequately controlled, leading to operation outside intended parameters. Therefore, measuring temperatures under actual operating conditions is crucial for assessing refrigerator thermal performance, and field data on temperature and storage duration can support microbial risk assessments (Roccato et al., 2017; van der Vossen-Wijmenga et al., 2024).

Energy consumption in domestic refrigerators is also influenced by room temperature and relative humidity (Ghadiri & Rasti, 2014; Saidur et al., 2002), along with consumer habits such as thermostat settings, frequency of door openings, and the mass or volume of stored food (Belman-Flores et al., 2019; Bhatt, 2001; Saidur et al., 2002). Several studies have compared energy performance of domestic cold appliances under laboratory and household conditions, showing that real-life usage often results in higher energy consumption than reported by manufacturers (Biglia et al., 2020; Harrington et al., 2018). In recent years, substantial efforts have been made to enhance the energy efficiency of domestic appliances. Improvements in compressor, condenser, and

evaporator coil designs, enhanced thermal insulation, and reductions in refrigerant charge have all contributed to these gains (Ghadiri & Rasti, 2014; Pund, 2024). Furthermore, intelligent control systems that adjust parameters like compressor speed, thermostat set points, and defrost timing based on machine learning forecasts of door openings have demonstrated energy savings of 2.5-4.5 % while maintaining the desired temperature. An intelligent control system has been designed to regulate parameters like compressor speed, thermostat set point, and defrost timing by integrating machine learning-based forecasts of door openings (Kapici et al., 2022).

The present survey study was conducted to explore temperature and humidity conditions, and appliance electrical consumption in domestic refrigerators in Bangkok. The study aimed to explore whether domestic refrigerators represent a potential vulnerability in maintaining food safety once perishable products reach consumers' homes, to identify common characteristics among refrigerators that operate above recommended temperatures i.e., 5 °C. Surveys conducted in several countries, including France, the United Kingdom, Spain, Iran, and Lebanon (see Tables 1 and 2), have reported similar concerns, indicating that domestic refrigerators can be a weak link in the cold chain as the temperatures in refrigerators may exceed the recommended limit (van der Vossen-Wijmenga et al., 2024). A previous survey in Thailand conducted in 2007 confirmed this observation (Chantapiang et al., 2007). Given the economic growth over the past decade in Thailand, which has led to evolving consumer behavior and improved refrigerator technology, this updated study was undertaken to reassess domestic refrigerator performance and usage under current conditions. Additionally, the study also assessed the potential consumer risks using a predictive microbiological model and explored the possible relationship between temperature and electrical consumption and usage conditions (such as ambient temperature, refrigerator type, and age). The findings of this survey would provide insights into domestic storage conditions and support the development of consumer guidelines. The data on temperature distribution and storage duration could also assist food producers in adjusting product shelf life. Although a previous survey in Thailand by Chantapiang et al. (2007) was conducted, it did not include measurements of freezer temperature and appliance electrical consumption, highlighting the complementarity of the present work.

## 2. Materials and method

### 2.1. Participant recruitment

A linear snowball sampling approach was used to recruit participants for the study (Ovca et al., 2021). An online survey form (Google Forms) which included an invitation for an on-site investigation of refrigerators was initially distributed to acquaintances residing in Bangkok. These initial participants were then encouraged to forward the survey to additional potential participants at their discretion. First, all individuals were informed about the study's objectives, planned activities, and their rights regarding anonymity and withdrawal from participation. Those who agreed to take part completed the online consent form, and their responses were recorded anonymously. Upon acceptance, the research team scheduled appointments to visit their premises, where we observed the refrigerators and installed the instruments. A total of 145 participants permitted an on-site investigation of their appliances; however, only the results from 123 participants were included in the final analysis. The exclusions were due to participants residing outside Bangkok, measurement errors caused by instrument malfunction and/or accidental interruptions during data collection. The types of refrigerators (Fig. 1) owned by the considered participants included single-door (n = 41), two-door/top freezer (n = 77), and two-door/bottom freezer (n = 5).
<table><caption>**Table 1**
Surveys on domestic refrigerator temperature in Western countries.</caption><thead><tr><th>Country</th><th>Number of participants/ refrigerators</th><th>Main results</th><th>Reference</th></tr></thead><tbody><tr><td>Australia</td><td>57</td><td>Min 1.2 °C, mean 3.6 °C, max 7.5 °C<br>22.8 % > 5 °C</td><td>NSW Food Authority (2009)</td></tr><tr><td>Denmark</td><td>100</td><td>Min 0 °C, mean 6.2 °C, max 11.0 °C</td><td>Geppert et al. (2010)</td></tr><tr><td>France</td><td>119</td><td>Min 0.9 °C, mean 6.6 °C, max 11.4 °C<br>80 % > 5 °C</td><td>Laguerre et al. (2002)</td></tr><tr><td>France</td><td>100</td><td>Min 1.0 °C, mean 6.7 °C, max 12.0 °C</td><td>Geppert et al. (2010)</td></tr><tr><td>France</td><td>75</td><td>Product temperature (sliced ham): min 1.1 °C, mean 6.3 °C, max 10.7 °C<br>Storage duration: min 28 min, mean 6 days 6 h, max 33 days 14 h</td><td>Derens-Bertheau et al. (2015)</td></tr><tr><td>France</td><td>15</td><td>Min 4.0 °C, mean 6.4 °C, max 8.3 °C</td><td>Dumitraşcu et al. (2020)</td></tr><tr><td>Greece</td><td>110</td><td>26 % of domestic refrigerator operate with temperature < 4 °C, 28 % within 4–6 °C, 23 % within 6–8 °C, 15 % within 8–10 °C and 8 % operate within 10–12 °C</td><td>Bakalis et al. (2004)</td></tr><tr><td>Greece</td><td>250</td><td>Min –2.0 °C, mean 6.3 °C<br>50 % > 6 °C and 10 % > 0 °C</td><td>Taoukis et al. (2005)</td></tr><tr><td>Greece</td><td>100</td><td>Min –0.7 °C, mean 6.3 °C, max 13.0 °C</td><td>Koutsoumanis et al. (2010)</td></tr><tr><td>Greece</td><td>70</td><td>Min –0.1 °C, mean 8.9 °C, max 17.6 °C<br>68.6 % > 7 °C</td><td>Andritos et al. (2021)</td></tr><tr><td>Ireland</td><td>150</td><td>Min 0.8 °C, mean 6.5 °C, max 12.6 °C<br>71 % > 5 °C</td><td>Flynn et al. (1992)</td></tr><tr><td>Ireland</td><td>100</td><td>Min –1.7 °C, mean 5.4 °C, max 11.8 °C<br>59 % > 5 °C, 6 % > 10 °C</td><td>Kennedy et al. (2005)</td></tr><tr><td>Italy</td><td>106</td><td>Min –3.5 °C, mean 7.2 °C, max 15.2 °C</td><td>Roccato (2013)</td></tr><tr><td>Italy</td><td>84</td><td>Min 2.5 °C, mean 8.1 °C, max 15.9 °C<br>42.8 % > 4 °C and 51.2 % > 10 °C</td><td>Vegara et al. (2014)</td></tr><tr><td>Mexico</td><td>200</td><td>Mean 7.9 °C<br>11 % < 4 °C, 53 % > 7.1 °C, 14.5 % > 12 °C</td><td>Macias-Rodriguez et al. (2013)</td></tr><tr><td>Netherlands</td><td>125</td><td>30 % < 5 °C, 42 % within 5–7 °C, 26 % within 7–9 °C and 2 % > 9 °C</td><td>Lezenne (1994)</td></tr><tr><td>Netherlands</td><td>31</td><td>Min 3.8 °C, max 11.5 °C<br>68 % > 7 °C</td><td>Terpstra et al. (2005)</td></tr><tr><td>Netherlands</td><td>534</td><td>Min –1 °C, mean 5.7 °C, max 17 °C<br>33.2 % > 7 °C<br>Significant temperature difference between upper shelf and middle/ bottom shelves</td><td>van der Vossen-Wijmenga et al. (2024)</td></tr><tr><td>New Zealand</td><td>50</td><td>Min 0.8 °C, mean 4.9 °C, max 11 °C<br>60 % > 4 °C<br>88 % of participants did not know temperature range should be operating within.</td><td>O'Brien (1997)</td></tr><tr><td>New Zealand</td><td>127</td><td>Min –4.9 °C, mean 5.2 °C, max 18.0 °C<br>34 % > 6 °C, 55 % > 5 °C</td><td>Gilbert et al. (2007)</td></tr></tbody></table>

<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Country</th><th>Number of participants/ refrigerators</th><th>Main results</th><th>Reference</th></tr></thead><tbody><tr><td>Norway</td><td>46</td><td>20 % of refrigerators spent half or more of time above 7 °C<br>Min 1.3 °C, mean 5.6 °C, max 9.9 °C</td><td>Røssvoll et al. (2014)</td></tr><tr><td>Norway</td><td>13</td><td>Min 1.2 °C, mean 5.4 °C, max 8.8 °C</td><td>Dumitraşcu et al. (2020)</td></tr><tr><td>Poland</td><td>77</td><td>Min –1.2 °C, mean 5.1 °C, max 15.2 °C<br>49.35 % > 5 °C, 3.9 % > 10 °C</td><td>Stefanou et al. (2023)</td></tr><tr><td>Portugal</td><td>86</td><td>Min 0.9 °C, mean 7.3 °C, max 15.2 °C<br>70 % > 6 °C</td><td>Azevedo et al. (2005)</td></tr><tr><td>Portugal</td><td>51</td><td>Min –1.8 °C, mean 5.5 °C, max 11.9 °C<br>70 % > 6 °C</td><td>Galvão et al. (2017)</td></tr><tr><td>Portugal</td><td>15</td><td>Min 3.2 °C, mean 5.5 °C, max 9.1 °C</td><td>Dumitraşcu et al. (2020)</td></tr><tr><td>Romania</td><td>14</td><td>Min 1.7 °C, mean 5.3 °C, max 9.5 °C</td><td>Dumitraşcu et al. (2020)</td></tr><tr><td>Serbia</td><td>120</td><td>Min 0.1 °C, mean 7.7 °C, max 17.3 °C<br>82.5 % > 5 °C</td><td>Jovanovic et al. (2022)</td></tr><tr><td>Slovenia</td><td>50</td><td>Test product: min 1.0 °C, mean 6.0 °C, max 10.5 °C<br>Air: min –0.3 °C, mean 5.9 °C, max 9.6 °C<br>Ambient kitchen: mean 21.2 °C<br>20 % test product < 4 °C, 30 % = 4–6 °C, 50 % > 6 °C</td><td>Ovca et al. (2021)</td></tr><tr><td>Spain</td><td>30</td><td>Min –1.0 °C, mean 6.6 °C, max 16 °C</td><td>Carrasco et al. (2007)</td></tr><tr><td>Spain</td><td>100</td><td>Min 0 °C, mean 4.1 °C, max 10.0 °C</td><td>Geppert et al. (2010)</td></tr><tr><td>Spain</td><td>33</td><td>Min 0.6 °C, mean 7.9 °C, max 14.5 °C<br>No statistical difference between food and air temperatures.</td><td>Garrido et al. (2010)</td></tr><tr><td>Spain</td><td>160</td><td>Min 0.5 °C, mean 5.4 °C, max 12.2 °C<br>Significant impact of the seasons, insignificant impact of day and night and door opening</td><td>Jofré et al. (2019)</td></tr><tr><td>Sweden</td><td>102</td><td>Minced meat: mean 6.3 °C, max 11.3 °C<br>Ready-to-eat salad: mean 7.5 °C, max 18.3 °C<br>5–10 % > 10 °C</td><td>Marklinder et al. (2004)</td></tr><tr><td>UK</td><td>250</td><td>Min –0.9 °C, mean 6.0 °C, max 11.4 °C<br>23 % of domestic refrigerators operate with temperature > 7 °C<br>Min 2.0 °C, mean 5.9 °C, max 12.0 °C<br>50 % > 5 °C</td><td>James and Evans (1992)</td></tr><tr><td>UK</td><td>108</td><td>Min 3.0 °C, mean 5.2 °C, max 10.0 °C<br>Door location: Min –0.2 °C, mean 7.8 °C, max 17.9 °C, 67 % > 5 °C<br>Centre location: min –1.7 °C, mean 5.9 °C, max 16.9 °C, 40 % > 5 °C</td><td>Worsfold and Griffith (1997)</td></tr><tr><td>UK</td><td>43</td><td>Refrigerator: mean 5.3 °C</td><td>Geppert et al. (2010)</td></tr><tr><td>UK</td><td>998</td><td>Biglia et al. (2018)</td><td>Evans and Redmond (2016)</td></tr></tbody></table>

(continued on next page)
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Country</th><th>Number of participants/ refrigerators</th><th>Main results</th><th>Reference</th></tr></thead><tbody><tr><td>UK</td><td>13</td><td>17.4 % > 5 °C all operating time<br>Freezer: mean -20.3 °C<br>Ambience in kitchen: mean 18.5 °C<br>Electricity consumption: mean 354 kWh/year</td><td rowspan="2">Dumitraşcu et al. (2020)</td></tr><tr><td>USA</td><td>939</td><td>Min -0.1 °C, mean 5.0 °C, max 9.3 °C<br>Refrigerator: Product temperature: Min -6.1 °C, mean 3.9 °C, max 21.1 °C<br>8 % > 7 °C and 2 % > 10 °C<br>Freezer: Min -28.9 °C, mean -16.1 °C, max 8.9 °C<br>0.7 % > 0 °C</td></tr><tr><td>USA</td><td>200</td><td>Mean: 1.9 °C (top), 3.3 °C (bottom), 5.2 °C (door)<br>66 % > 4.4 °C (door for >8 h/day)</td><td>Godwin et al. (2007)</td></tr></tbody></table>

<table><caption>**Table 2**
Surveys on domestic refrigerator temperature in Eastern countries.</caption><thead><tr><th>Country</th><th>Number of participants/ refrigerators</th><th>Main results</th><th>Reference</th></tr></thead><tbody><tr><td>Iran</td><td>180</td><td>25.8 % < 5 °C, 22.7 % > 8 °C</td><td>Maktabi et al. (2013)</td></tr><tr><td>Korean</td><td>139</td><td>Min:5.1 °C, mean 3.5 °C, max 14.4 °C<br>23.6 % > 5 °C</td><td>Bahk (2010)</td></tr><tr><td>Lebanon</td><td>147</td><td>Min -5.9 °C, mean 8.0 °C, max 37 °C (electricity cut) 70 % > 6 °C<br>100 % surveyed fridges have no thermometer</td><td>Hassan et al. (2015)</td></tr><tr><td>Malaysia</td><td>26</td><td>Min -2.8 °C, mean 2.0 °C and max 7.5 °C</td><td>Rahman et al. (2005)</td></tr><tr><td>Thailand</td><td>55</td><td>Min -2.5 °C, mean 3.9 °C and max 13.0 °C<br>25.4 % > 5 °C</td><td>Chantapiang et al. (2007)</td></tr></tbody></table>

## 2.2. On-site investigation

This study measured four operating parameters: air temperature, relative humidity, product temperature, and appliance electrical consumption. Thermo-hygrometer data loggers (TagPlus-TH, Freshliance Electronics; ±0.5 °C temperature accuracy in the range of -30 °C to +70 °C and ±3 %RH humidity accuracy in the range of 0 %RH to 100 %RH) were used to measure air temperature and relative humidity). Fig. 1 illustrates the sensor positions in different types of refrigerators: one position in the freezer compartment (FC), three positions in the chilling compartment (TS, MS, and VD), and one position on the door shelf (DS). One data logger was installed outside the refrigerator to monitor ambient air temperature and relative humidity in the kitchen. These data loggers were set to record data every 5 min for at least seven days.

For product temperature measurement, a meat-like test product was prepared based on the formula proposed by Anderson and Singh (2005). The product was composed of 82 wt% Hydroxy-Ethyl-Cellulose (Shin-Etsu, Japan), 16 wt% distilled water, and 1.4 wt% antifungal agent Phenoxy-Ethanol (Knanze, Thailand). About 200 g of the test product was filled in a cylindrical aluminum container (Fig. 2). A temperature

recorder (iButton DS1922L-F5#, Analog Devices, USA, ±0.5 °C temperature accuracy in the range of -10 °C to +65 °C) was inserted into the geometric center of the test product to measure its core temperature. The test product was placed on the middle shelf of the chilling compartment (TP, Fig. 1). The temperature was recorded every 5 min for at least seven days.

Because a wide variety of foods are stored in domestic refrigerators (liquid and solid with differing moisture content and porosity), a test product was used as a food model to simulate the thermal mass and heat-transfer properties of meat during refrigeration. This model material (thermal conductivity = 0.45 W·m⁻¹·K⁻¹, density = 1032 kg·m⁻³, and specific heat capacity = 4.82 J·kg⁻¹·K⁻¹) is widely used in standard refrigeration tests to represent the thermal response of meat. Due to the high cost and practical complexity of conducting microbiological analyses in laboratory settings and as an initial approach, this food model was also used to support predictive microbial growth simulations. The advantage of using this model is to provide stable and repeatable temperature behavior while eliminating contamination risks associated with raw food products. Table 3 summarizes the thermophysical properties of the test product in comparison to those of minced beef. The density of the test product was determined by dividing the measured mass by the known volume of the container. The specific heat capacity was determined using a differential scanning calorimeter (DSC 3500, Netzsch, Germany). The thermal conductivity of the test product was measured using a TCi thermal analyzer (Trident, C-Therm Technologies, Canada) equipped with an MTPS sensor.

The refrigerator's electrical consumption was monitored using a wattmeter data logger (PR10, Shenzhen Zhurui Technology, China; ±5 % accuracy over the 0–4000 W range). Data was recorded daily in kilowatt-hours (kWh) for at least seven days.

## 2.3. Evaluation of microbial growth

A predictive microbiological model for *Listeria monocytogenes* and lactic acid bacteria (LAB) in preserved seafood and meat products was used to predict their simultaneous growth over five-day storage using the recorded time-temperature profiles of the test products. This model is implemented in Food Spoilage and Safety Predictor (FSSP version 4.0), developed by Dalgaard (2014) (http://fssp.food.dtu.dk). The primary and secondary models used in the FSSP were developed based on the logistic model and the cardinal parameter model, respectively. For full details, readers are referred to Giménez and Dalgaard (2004). Through comparisons between observed and predicted growth in naturally contaminated products, the model demonstrated good accuracy (Mejlholm & Dalgaard, 2007, 2015). It needs to be noted that *L. monocytogenes*, pathogenic bacteria, was studied because it can grow under low temperatures as observed in domestic refrigerator (4–5 °C) (Evans et al., 2021). LAB was selected for two reasons: it is often recognized as the most prevalent spoilage bacteria (Mataragas et al., 2006), and it exerts an antagonistic effect on the growth of *L. monocytogenes* (Mejlholm & Dalgaard, 2007).

The initial concentration of *L. monocytogenes* was set at 10 CFU/g considered as a detectable contamination level in cooked meat products (Kramarenko et al., 2013) and the initial concentration of LAB was set at 10² CFU/g. No lag time was considered for both bacteria. This assumption considers that the bacteria are already adapted to the food matrix environment by the time the product reaches the consumer home. To represent the test product, pH and salt content were set at 5.7 and 0.6 %, respectively (Zhao et al., 2020). All other input model parameters (e.g., phenol, CO₂, and nitrate) were set to zero for a simplification. The microbial safety limit for *L. monocytogenes* exceeding 10² CFU/g is defined as a regulatory critical value under Commission Regulation (EC) (2005), whereas LAB concentration above 8.6 log₁₀ CFU/g is considered indicative of spoilage, rendering the product unfit for consumption (Mataragas et al., 2006).
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Data logger positions in refrigerators (a) single door, (b) two-door/top freezer, and (c) two-door/bottom freezer. FC = freezer compartment, TS = top shelf, MS = middle shelf, VD = vegetable drawer, DS = door shelf, and TP = test product.</figcaption></figure>

Cross-sectional view at mid-height

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Meat-like test product used for product temperature representation.</figcaption></figure>

2.4. Statistical analysis

To account for the thermal inertia of the sensors and the test product, the mean values of each measured data (temperature, relative humidity,

<table><caption>**Table 3**

Thermophysical properties of the test product and minced beef.</caption><thead><tr><th rowspan="2">Property</th><th colspan="2">Test product</th><th colspan="2">Minced beef</th></tr><tr><th>Value</th><th>Measurement method</th><th>Value</th><th>Reference</th></tr></thead><tbody><tr><td>Density [kg/m<sup>3</sup>]</td><td>1032</td><td>Test product mass divided by container volume</td><td>1022</td><td>(Pan & Paul Singh, 2001)</td></tr><tr><td>Thermal conductivity [W/(m·°C)]</td><td>0.45</td><td>TCi thermal analyzer (Trident, C-Therm Technologies, Canada)<sup>2</sup></td><td>0.38</td><td>(Pan & Paul Singh, 2001)</td></tr><tr><td>Specific heat capacity [kJ/(kg·°C)]</td><td>4.82</td><td>Differential scanning calorimeter (DSC 3500, Netzsch, Germany)<sup>1</sup></td><td>3.48</td><td>(Tavman et al., 2007)</td></tr><tr><td>Thermal diffusivity [× 10<sup>-6</sup> m<sup>2</sup>/s]</td><td>0.09</td><td>Calculation</td><td>0.11</td><td>Calculation</td></tr></tbody><tfoot><tr><td colspan="5"><sup>1</sup>Sample mass 4.4 mg in a concave aluminum crucible with pierced lid.<br/><sup>2</sup>Ten repetitions at >20 °C and atmospheric pressure.</td></tr></tfoot></table>

and electrical consumption) were calculated from the recorded value over a five-day period (from 24 to 144 h). These mean values were then used for subsequent statistical analysis. As the temperature data exhibited a normal distribution, a one-way ANOVA was conducted, followed by Games and Howell multiple comparison test using IBM SPSS Statistics (version 29.0). However, the relative humidity and the electricity consumption data did not follow a normal distribution, a nonparametric approach was adopted using the Kruskal-Wallis one-way ANOVA coupled with Dunn's post hoc tests. In all cases, statistical significance was determined at the 95 % confidence level (p < 0.05).

3. Results and discussion

3.1. Storage conditions of domestic refrigerators

A total of 123 refrigerators were included in the analysis. As shown in Table 4, most of the investigated refrigerators were two-door models with a top freezer (62.6 %), followed by single-door refrigerators (33.3 %) and two-door models with a bottom freezer (4.1 %). Approximately 18.7 % of the refrigerators were 1–3 years old, and 15.4 % were >10 years old. Nearly equal proportions of refrigerators were aged 3–5 years and 5–10 years (30.1 % each).
<table><caption>**Table 4**

Characteristics of investigated refrigerators (n = 123).</caption><thead><tr><th>Category</th><th>Number of refrigerators (%)</th></tr></thead><tbody><tr><td><strong>Refrigerator type</strong></td><td></td></tr><tr><td>Single door</td><td>41 (62.6)</td></tr><tr><td>Two doors with a top freezer</td><td>77 (33.3)</td></tr><tr><td>Two doors with a bottom freezer</td><td>5 (4.1)</td></tr><tr><td><strong>Age of refrigerator</strong></td><td></td></tr><tr><td>&lt;1 year</td><td>7 (5.7)</td></tr><tr><td>1-3 years</td><td>23 (18.7)</td></tr><tr><td>3-5 years</td><td>37 (30.1)</td></tr><tr><td>5-10 years</td><td>37 (30.1)</td></tr><tr><td>&gt;10 years</td><td>19 (15.4)</td></tr></tbody></table>

### 3.1.1. Air and product temperature inside refrigerators

The recorded ambient conditions in the locations where the refrigerators were installed (e.g., kitchens or dining areas) showed a mean ambient temperature of 27.4 ± 3.2 °C (min 22.3 °C and max 33.0 °C) and a mean relative humidity of 70.2 ± 8.3 %RH (min 49.8 %RH and max 87.2 %RH). Lower ambient temperatures in some residences may be attributed to the use of air conditioning.

The mean air and product temperatures were calculated over a 5-day period, incorporating fluctuations due to compressor on/off cycles and defrosting. Fig. 3 illustrates time-temperature profiles for the air and product on the middle shelf, as well as the air in the vegetable drawer, highlighting these operational cycles. Since the mean air and product temperatures in the chilling compartment did not differ significantly among refrigerator types (p > 0.05), only the overall mean temperatures are reported and discussed.

Fig. 4 illustrates the distributions of mean air temperatures at various positions within the 123 refrigerators, along with the mean product temperature at the middle shelf. Considering all refrigerator types, the mean air temperatures on the top and middle shelves were significantly different (p < 0.05). In the chilling compartment, the top shelf had the lowest mean air temperature at 2.3 ± 3.6 °C (Fig. 4a), with approximately 20 % of refrigerators maintaining temperatures in the super-chilling range (–2 to 0 °C) and 20 % exhibiting temperatures above 5 °C (considered as abuse range since the safety of some foods like meat and fish cannot be assured). The middle shelf had a mean temperature of 3.9 ± 3.0 °C (Fig. 4b), which is 1.6 °C higher than the top shelf. At this position, about 42 % of refrigerators were within the optimal range (2–4 °C), while 27 % operated in the abuse range.

The study conducted in the Netherlands (van der Vossen-Wijmenga et al., 2024) reported that the lowest temperature occurred at the bottom shelf, which is opposite to the present findings. This difference reflects variations in temperature distribution patterns among refrigerator

models and households. These results suggest that temperature within a refrigerator is spatially heterogeneous and that relying on a single point thermometer measurement may not accurately represent the actual temperature conditions experienced by stored foods.

The mean product temperature at the middle shelf was 4.0 ± 3.0 °C (Fig. 4e). Despite fluctuations in air temperature due to compressor on/off cycles, the product temperature remained relatively constant and closely aligned with the mean air temperature at that position when a steady state was considered over the 5-day measurement period. Approximately 38 % of products were stored within the optimal temperature range, while about 30 % experienced conditions above 5 °C that could potentially compromise food safety.

The door shelf exhibited a mean temperature of 6.3 ± 3.2 °C (Fig. 4c), which is 4.0 °C and 2.4 °C higher than those of the top and middle shelves, respectively (p < 0.05). The vegetable drawer recorded the highest mean air temperature at 7.4 ± 3.3 °C (Fig. 4d). Although its temperature did not differ significantly from that of the door shelf (p > 0.05), approximately 72 % of refrigerators displayed temperatures above 5 °C in the vegetable drawer. This range may not be suitable for preserving certain fruits and vegetables (e.g., salad, carrot, strawberry, apple...), which ideally should be stored at 0–5 °C. Notably, one unit recorded a subzero reading in the vegetable drawer, potentially leading to chilling injury, particularly for leafy vegetables such as salad.

Considering the spatial and temporal temperature variations, the chilling compartment maintained a mean air temperature of 5.0 ± 2.5 °C in average, which falls within the recommended storage temperature ranges specified by national and international guidelines (FDA, 2017; FSA, 2025; WHO, 2006). However, only 37 % and 26 % of refrigerators maintained temperatures at or below 5 °C on the top and middle shelves, respectively, throughout the five-day monitoring period. The remaining appliances exhibited temperature fluctuations that periodically exceeded 5 °C at these positions.

As shown in Table 5, approximately 22 % of the top shelves recorded temperatures above 5 °C for >50 % of the five-day period, compared with 34 % on the middle shelves and 37 % for products placed on the middle shelves. In contrast, about 67–74 % of vegetable drawers and door shelves exceeded 5 °C for more than half of the monitoring period. Although higher temperatures in these areas are expected, as they are not typically designed for storing potentially hazardous foods, the data indicate that some refrigerators maintained temperatures above 5 °C continuously on the top (6 %) and middle (19 %) shelves, highlighting a potential risk to consumer health.

Overall, the results of this study appear less concerning than those reported by Evans and Redmond (2016), who found that none of the refrigerators evaluated in the United Kingdom (at both door and central locations) operated at or below 5 °C for an entire six-day period, with the

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Example of air and product time-temperature profiles in a refrigerator during normal compressor cycles and defrosting.</figcaption></figure>
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /><figcaption>**Fig. 4.** Distribution (column) and cumulative distribution (dash line) of mean air and product temperatures at different positions in the 123 investigated refrigerators: (a) air / top shelf, (b) air / middle shelf, (c) air / door shelf, (d) air / vegetable drawer, (e) product / middle shelf, and (f) air / freezer. The percentage of the refrigerators with different temperature range are presented in each chart. Means with a different uppercase letter indicate statistically significant differences between different positions (p < 0.05).</figcaption></figure>

majority of door storage areas (70 %) and central locations (40 %) consistently operating at unsafe temperatures. It should be noted that the exceedances above 5 °C do not necessarily indicate mechanical malfunction but rather reflect typical household operation under variable ambient conditions and usage behaviors in real conditions. From a food safety perspective, temperatures above 5 °C, even for short duration, can permit microbial growth and increase spoilage risk,

emphasizing the need for better consumer awareness and temperature management in domestic storage.

The temperature profiles reveal distinct gradients within chilling compartments. The top shelf, often used for storing highly perishable items such as meat, consistently maintained the lowest temperature. However, consumers may not know the cold position in their refrigerator because of the absence of indicative logo. The close correspondence
<table><caption>**Table 5**
Number (percentage) of refrigerators operating at and above 5 °C for different percentages of time over a 5-day period for 123 surveyed refrigerators.</caption><thead><tr><th rowspan="2">Percentage of time</th><th colspan="5">Number (percentage, 95 % confidence interval) of refrigerators operating at and above 5 °C for the specific percentage of time</th></tr><tr><th>Air on top shelf</th><th>Air on middle shelf</th><th>Product on middle shelf</th><th>Air in vegetable drawer</th><th>Air on door shelf</th></tr></thead><tbody><tr><td>0 (Never)</td><td>45 (37, 28–45)</td><td>32 (26, 18–34)</td><td>37 (30, 22–38)</td><td>10 (8, 3–13)</td><td>12 (10, 5–15)</td></tr><tr><td>1–25</td><td>36 (29, 21–37)</td><td>36 (29, 21–37)</td><td>34 (28, 20–36)</td><td>16 (13, 7–19)</td><td>22 (18, 11–25)</td></tr><tr><td>26–50</td><td>15 (12, 6–18)</td><td>14 (11, 6–17)</td><td>7 (6, 2–10)</td><td>7 (6, 2–10)</td><td>7 (6, 2–10)</td></tr><tr><td>51–75</td><td>10 (8, 3–13)</td><td>10 (8, 3–13)</td><td>9 (7, 3–12)</td><td>13 (11, 5–16)</td><td>13 (11, 5–16)</td></tr><tr><td>76–99</td><td>10 (8, 3–13)</td><td>8 (7, 2–11)</td><td>13 (11, 5–16)</td><td>11 (9, 4–14)</td><td>17 (14, 8–20)</td></tr><tr><td>100 (All the time)</td><td>7 (6, 2–10)</td><td>23 (19, 12–26)</td><td>23 (19, 12–26)</td><td>66 (54, 45–62)</td><td>52 (42, 34–51)</td></tr></tbody></table>

between air and product temperatures on the middle shelf suggests effective performance in keeping potentially hazardous foods below the safe threshold (< 5 °C) recommended by food safety guidelines. In contrast, the high temperatures on the door shelf are likely due to the heat transfer by conduction through walls, frequent door openings and obstructed airflow, while the higher temperature in the vegetable drawer can be explained by the heat released form condenser located at the rear. This design feature intended to preserve most fruits and vegetation while preventing chilling injury.

Fig. 4f presents the mean air temperature distribution in the freezer compartment, ranging from 6.0 °C to -25.1 °C, with an overall mean temperature of -12.2 ± 6.1 °C. This mean temperature is significantly higher than the recommended storage temperature for frozen food (-18 °C). Nearly 48 % of freezers maintained temperatures between -18 °C and -10 °C; although food safety may be maintained at -10 °C (James & James, 2023), organoleptic quality such as color and texture could be compromised (Deng et al., 2021). Additionally, five refrigerators (4 %) recorded temperatures above 0 °C, which are unsuitable for frozen food preservation. These elevated temperatures may result from inadequate defrost cycles, malfunctioning cooling components, or improper user settings, underscoring the need for regular maintenance and performance checks.

In contrast to the chilling compartment, based on the mean rank (data not shown), the mean freezer temperature in two-door refrigerators with top freezers (-13.4 ± 5.8 °C) was significantly lower than that in single-door refrigerators (-11.7 ± 5.5 °C) (p < 0.05). However, the mean freezer temperature in two-door refrigerators with bottom freezers (-11.2 ± 10.6 °C) did not differ significantly from that of the other appliance types (p > 0.05). This result should be interpreted with caution, as only five refrigerators with bottom freezers were included in the analysis, potentially affecting the reliability of the statistical comparison.

Although the mean freezer temperatures in all appliance types were above -18 °C, they remain within the acceptable range for short-term storage of most frozen products, as these temperatures do not promote the growth of pathogenic bacteria. However, food quality, nutrition, and palatability may degrade over time (James & James, 2023), highlighting a potential weakness in the domestic frozen food cold chain. Given that freezer temperature surveys are relatively rare compared to those of the chilling compartment (Biglia et al., 2018), these findings provide

valuable insights into domestic freezer performance and emphasize the need for improvements in maintenance and design to ensure both food safety and quality.

Considering the operation time, the mean air temperatures at different positions, as well as the mean product temperature at the middle shelf, did not differ significantly between day and night (p > 0.05) or between weekdays and weekends (p > 0.05). These results suggest that the refrigerators maintained stable temperatures regardless of the time of day or week, consistent with the findings of Jofré et al. (2019).

No clear relationship was observed between the mean ambient temperature and the mean air temperature in neither the chilling nor freezer compartments. Nonetheless, the calculated Pearson correlation coefficients (r = 0.20–0.36, p < 0.05) indicated a weak positive correlation between these two parameters. It leads to suppose that the refrigerators might be slightly influenced by normal daily and weekly variations in ambient conditions. These findings are consistent with previous studies reporting limited sensitivity of domestic refrigerator performance to typical ambient temperature fluctuations (Biglia et al., 2018; Evans & Redmond, 2016; Laguerre & Flick, 2010; Rahman et al., 2005).

Finally, the age and volume of the refrigerators appeared to have no relationship with the mean air temperatures at any position. However, these results should be interpreted with caution, as the age reported by participants reflects the year of purchase rather than the manufacturing date, and the volume values were approximated based on specification labels.

### 3.1.2. Air relative humidity distributions inside refrigerators

Fig. 5 shows the distributions of mean air relative humidity measured at various positions in 123 household refrigerators. In the chilling compartment, the average relative humidity ranged between 30 %RH and 40 %RH, corresponding to an absolute humidity of approximately 1.8 to 2.0 g of water vapor per kg of dry air, as estimated from a psychrometric chart.

Ambient relative humidity in Thailand typically varies from 50 % to 90 %RH (NSO, 2023), which aligns with our measured data showing a minimum of 49.8 %RH and a maximum of 87.2 %RH, corresponding to >15 g of water vapor per kg of dry air. This significant difference between the low humidity inside the refrigerator and the high ambient moisture content creates a strong driving force for moisture ingress. Such moisture penetration can lead to condensation and subsequent frost formation on the freezer walls and evaporator coils. The results suggest that more frost buildup can be expected in tropical climates, which can not only compromise the refrigerator's performance but may also increase energy consumption and necessitate more frequent maintenance.

Approximately 80–90 % of the refrigerators exhibited two distinct ranges of mean relative humidity on the top, middle, and door shelves (Fig. 5a-c): roughly half had values between 20–40 %RH, while about 30–40 % had values between 40–60 %RH. Based on the mean ranks, the mean relative humidity on the top shelf was not significantly different from that on the middle shelf (p > 0.05), but it was significantly different from that on the door shelf (p < 0.05). However, the mean relative humidity on the middle shelf was not significantly different from that on the door shelf (p > 0.05).

In the vegetable drawer (Fig. 5d), the mean relative humidity was 31.6 ± 9.6 %RH, corresponding to the absolute humidity of approximately 2.0 g of water vapor per kg of dry air at the mean air temperature of 7.4 °C. Based on the mean ranks, it was significantly higher than that on the top and middle shelves (p < 0.05), but not significantly different from that on the door shelf (p > 0.05). About 75 % of the refrigerators recorded relative humidity values between 20–40 %RH in the vegetable drawer. This value appears to be lower than the recommended range for the storage of fruits and vegetables, which is typically 90–95 %RH for 0–5 °C and 80–90 %RH for 6–13 °C (Thompson et al., 2002). Such low
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

**Fig. 5.** Distribution (column) and cumulative distribution (dash line) of mean air relative humidity at different positions in the 123 investigated refrigerators: (a) air / top shelf, (b) air / middle shelf, (c) air / door shelf, (d) air / vegetable drawer, and (e) air / freezer. The percentage of the refrigerators with different temperature range is presented on the side for each chart. Means with a different uppercase letter indicate that their mean ranks are statistically significant differences between different positions (p < 0.05).

relative humidity can result in a larger vapor pressure deficit, potentially accelerating moisture loss and negatively affecting food quality by dehydration and reducing produce freshness.

The freezer compartment exhibited a mean relative humidity of 69.7 ± 11.3 %RH (Fig. 5e), corresponding to an absolute humidity of approximately 0.9 g of water vapor per kg of dry air. The effect of relative humidity in the freezer compartment on food quality was insignificant since almost all frozen products are packaged.

These on-site humidity measurements, rarely reported in the literature for household refrigerators, highlight the importance of precise humidity control alongside temperature management. The observed differences in absolute and relative humidity across compartments

suggest that current refrigerator designs might not optimally balance the microenvironment needed to preserve food quality, particularly for fruits and vegetables. For example, the lower relative humidity in the vegetable drawer could lead to faster dehydration of fresh produce, compromising both quality and shelf life.

## 3.2. Electrical consumption

Annual Electrical Consumption (AEC, kWh·year⁻¹) was determined by averaging the daily electrical consumption measured over a 5-day period and then extrapolating this average to estimate consumption over 365 days. Table 6 presents the statistical results of the AEC across
<table><caption>**Table 6**
Statistical results of annual electrical consumption (AEC) and specific energy consumption (SEC) across different refrigerator types.</caption><thead><tr><th rowspan="2">Refrigerator type</th><th rowspan="2">N</th><th colspan="4">Annual Electrical Consumption (kWh·year<sup>-1</sup>)</th><th colspan="4">Specific Energy Consumption (kWh·year<sup>-1</sup>·m<sup>-3</sup>)</th></tr><tr><th>Mean<sup>*</sup></th><th>STD</th><th>Min</th><th>Max</th><th>Mean<sup>*</sup></th><th>STD</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td>Single door</td><td>41</td><td>330<sup>A</sup></td><td>214</td><td>135</td><td>945</td><td>1,821<sup>a</sup></td><td>1180</td><td>580</td><td>6070</td></tr><tr><td>Two doors / top freezer</td><td>77</td><td>407<sup>A</sup></td><td>216</td><td>62</td><td>1018</td><td>1,717<sup>a</sup></td><td>1047</td><td>342</td><td>5243</td></tr><tr><td>Two doors / bottom freezer</td><td>5</td><td>767<sup>B</sup></td><td>137</td><td>599</td><td>956</td><td>1,931<sup>a</sup></td><td>762</td><td>1240</td><td>3064</td></tr><tr><td><strong>All types</strong></td><td><strong>123</strong></td><td><strong>396</strong></td><td><strong>228</strong></td><td><strong>62</strong></td><td><strong>1018</strong></td><td><strong>1760</strong></td><td><strong>1078</strong></td><td><strong>342</strong></td><td><strong>6070</strong></td></tr></tbody></table>

different refrigerator types. Overall, the 123 investigated refrigerators had the mean AEC of 396 kWh·year⁻¹, with values ranging from 62 to 1018 kWh·year⁻¹. Among the refrigerator types, models with two doors and a bottom freezer exhibited the highest mean AEC (767 ± 137 kWh·year⁻¹), followed by those with two doors and a top freezer (407 ± 216 kWh·year⁻¹), while single-door refrigerators recorded the lowest AEC (330 ± 214 kWh·year⁻¹). Based on mean ranks, there was no significant difference in AEC between single-door refrigerators and those with two doors and a top freezer (p > 0.05); however, both groups differed significantly from refrigerators with two doors and a bottom freezer (p < 0.05). The higher electricity consumption observed in appliances with two doors and a bottom freezer can be attributed to their refrigeration cycle design, which typically comes with two separate evaporators for the chilling and freezer compartments. Moreover, the evaporator for the chilling compartment operates at a temperature slightly above 0 °C, this leads to reduce the temperature difference between the evaporator and condenser and thereby increasing the compressor work cycles and overall energy consumption (Visek et al., 2014).

These findings are consistent with a study conducted in England by Biglia et al. (2018), which highlighted that refrigerator configuration plays a significant role in electricity consumption. In that study, single door models (274 ± 159 kWh·year⁻¹) generally consumed less electricity than two-door fridge-freezer models (390 ± 190 kWh·year⁻¹). The consumption values reported in their study were somewhat lower than those observed in our study, which could be attributed to various factors, such as differences in ambient temperature (16–20 °C in England versus 22–33 °C in Thailand).

Specific Energy Consumption (SEC) was estimated by dividing the AEC by the volume indicated on individual refrigerator labels. The results are reported in Table 6. In contrast to the trend observed for the AEC, the SEC results indicate that two-door refrigerators with top freezers had the lowest SEC (1717 kWh·year⁻¹·m⁻³), followed by single door refrigerators (1821 ± 1180 kWh·year⁻¹·m⁻³), while refrigerators with bottom freezers had the highest SEC (1931 ± 762 kWh·year⁻¹·m⁻³). However, the mean ranks showed no significant differences in SEC among the refrigerator types (p > 0.05). Based on these results, it is not obvious to conclude that the type of refrigerator significantly affects energy efficiency per unit volume. The factors beyond refrigerator configuration such as ambient conditions, insulation quality, or consumer behavior (loading patterns, door-opening frequency, and thermostat settings) also play a crucial role in determining overall energy consumption. This observation is consistent with the large-scale UK survey by Biglia et al. (2020), which reported that 61 % of domestic refrigerators consumed more energy in households than under standard test conditions, primarily due to variations in user practices and environmental influences.

Although no clear relationship was observed between the mean ambient temperature and either the AEC or the SEC, the calculated Pearson correlation coefficients indicated modest positive correlations (r = 0.46, p < 0.05 for AEC and r = 0.28, p < 0.05 for SEC). From the recorded time-temperature profiles in the freezer compartment, the compressor on/off cycles were identified, and the mean compressor

power consumption was estimated. Again, no distinct relationship with ambient temperature was detected, although a weak positive correlation (r = 0.31, p < 0.05) was found. This result confirms the findings of Borikar et al. (2021) and Harrington et al. (2018). Overall, these modest correlations suggest that while ambient conditions influence energy consumption to some extent, modern domestic refrigerators remain relatively robust against typical variations in ambient temperature, likely due to improved insulation and system design.

Fig. 6 shows that the SEC increases with the age of the appliances. Refrigerators less than three years old had the mean SEC of under 1200 kWh·year⁻¹·m⁻³, which was significantly lower than that of refrigerators older than five years, whose mean SEC exceeded 2000 kWh·year⁻¹·m⁻³ (p < 0.05). However, these results should be interpreted with caution because the reported age reflects the year the participants purchased the refrigerator rather than its manufacturing date, and many participants provided only an approximate purchase year. Despite these limitations, the trend observed in this study is consistent with the findings from England (Biglia et al., 2018), where refrigerators less than four years old had a mean SEC of approximately 1500 kWh·year⁻¹·m⁻³, and those between five and eleven years old exhibited mean SEC values ranging from 1600 to 2000 kWh·year⁻¹·m⁻³.

### 3.3. Microbial risk implications of surveyed product temperatures

Fig. 7 presents the simulation results from the predictive

<figure><img src="image_17.png" /><figcaption>**Fig. 6.** Variations in mean specific energy consumption (SEC) with refrigerator age. Error bars represent standard variations. Different uppercase letters above each error bar indicate statistically significant differences in mean ranks (p < 0.05).</figcaption></figure>

<footnote>* Means with a different uppercase (for AEC) or lowercase (for SEC) letter indicate that their mean ranks are statistically significant differences (p < 0.05).</footnote>
<figure><img src="image_18.png" /><figcaption>**Fig. 7.** Distribution of total bacterial growth after 5 days of storage under the measured temperature of the test products: (a) L. monocytogenes and (b) LAB. The initial concentrations of L. monocytogenes and LAB were 10 CFU/g and 10² CFU/g, respectively.</figcaption></figure>

microbiological model for the simultaneous growth of L. monocytogenes and LAB. After five days of storage under the recorded temperature profiles, 64 out of 123 refrigerators (52%) exhibited products with potential consumer risks, as the contamination level of L. monocytogenes exceeded the regulation safe limit ( > 10² CFU/g) (Commission Regulation (EC), 2005). In addition, 10 of the 64 products (16%) tended to be spoiled because LAB levels almost reached the spoilage threshold ( > 10⁸ CFU/g). On average, it took 3.1 ± 1.2 days for the L. monocytogenes concentration to exceed the safe limit. With an initial concentration set at 10 CFU/g, no product spoiled before the pathogen reached the defined safety limit. This may result in consumers eating products containing L. monocytogenes at levels above 10² CFU/g, as the product may appear unspoiled.

Pouillot et al. (2024) classified L. monocytogenes strains into different virulence levels based on their median lethal dose (LD₅₀). The most virulent strains, with LD₅₀ values ranging from 2.57 to 3.67 log₁₀ CFU/g, can pose a health risk even at concentrations around 10² CFU/g, particularly for vulnerable groups such as the elderly or pregnant women. For less virulent strains (LD₅₀ 4.49 to 6.23 log₁₀ CFU/g), the simulation showed 9 out of 123 cases (7%) reached this contamination threshold of 10⁴ CFU/g.

Overall, based on the product temperatures, only 59 of 123 refrigerators (48%) could safely store products for more than five days, highlighting the potential for microbial growth that poses a consumer health risk.

It should be emphasized that the predictive microbiological model used in this study is based on conservative assumptions, including a fixed initial contamination level, the absence of an adaptation (lag) phase, and the omission of growth inhibitors. These simplifications were intentional, aiming to represent a worst-case scenario that ensures microbial risks are not underestimated under fluctuating domestic temperature conditions. The microbial results should be used as an indicator and must be interpreted with precaution. In fact, the purpose of the model was not to reproduce real contamination levels or specific product behavior, but to provide comparative risk indicators among refrigerators operating at different temperature ranges. Similar conservative assumptions have been commonly adopted in household food safety modeling studies (Jofré et al., 2019; Koutsoumanis et al., 2010; van der Vossen-Wijmenga et al., 2024).

## 4. Conclusions

This study investigated domestic refrigerators in Bangkok by evaluating temperature and humidity conditions and energy consumption as well as assessing microbial exposure using a predictive microbiological model. A total of 123 refrigerators were investigated and analyzed. The mean ambient temperature and relative humidity during measurement were 27.4 ± 3.2 °C (range: 22.3–33.0 °C) and 70.2 ± 8.3 %RH (range: 49.8–87.2 %RH), respectively.

In the chilling compartment, the mean air temperature was 2.3 ± 3.6 °C on the top shelf and 3.9 ± 3.0 °C on the middle shelf, while the mean product temperature at the middle shelf was 4.0 ± 3.0 °C. The door shelf and vegetable drawer exhibited higher mean temperatures of 6.3 ± 3.2 °C and 7.4 ± 3.3 °C, respectively, whereas the freezer compartment maintained a mean temperature of -12.2 ± 6.1 °C. Only 37% and 26% of refrigerators maintained mean temperatures at or below 5 °C on the top and middle shelves, respectively. In comparison with surveys conducted in European countries and the United States, the overall refrigerator temperatures in Bangkok were not significantly higher than those reported in Western countries.

The overall mean AEC was 396 kWh·year⁻¹ (range: 62–1018 kWh·year⁻¹ depending mainly on the refrigerator's volume). Single-door refrigerators consumed an average of 330 kWh·year⁻¹, two-door models with top freezers 407 kWh·year⁻¹, and those with bottom freezers 767 kWh·year⁻¹. Regarding the SEC, two-door models with top freezers showed the lowest SEC at 1717 kWh·year⁻¹·m⁻³, followed by single-door models at 1821 kWh·year⁻¹·m⁻³, while two-door models with bottom freezers had the highest SEC at 1931 kWh·year⁻¹·m⁻³. However, these differences in SEC were not statistically significant (*p* > 0.05).

The predictive microbiological model, which assumed no lag phase and a fixed initial contamination level, indicated that after five days, products in 52% of refrigerators reached L. monocytogenes concentrations exceeding the regulatory safety limit of 10² CFU/g. The average time to reach this value was 3.1 ± 1.2 days. In nine refrigerators, contamination levels exceeded 10⁴ CFU/g, representing a higher threshold used for modeling less virulent strains. In addition, 10 products nearly spoiled due to LAB levels considered indicative of sensory spoilage.

In summary, these findings emphasize that at least one in five surveyed domestic refrigerators operate at mean temperatures above 5 °C, which may compromise food safety at home. This highlights the need for
appliance indicators, such as a “cold region” logo, to help consumers correctly identify suitable storage zones for temperature-sensitive products (e.g., meat and fish). Furthermore, improvements in refrigerator design, regular maintenance, and enhanced consumer education are essential to ensure that domestic refrigeration systems consistently meet recommended safety guidelines. Addressing these issues is essential for reducing energy consumption, mitigating microbial risks, and ultimately improving food safety and shelf life in household environments.

It is to be emphasized that the sample primarily comprised urban residents. Future studies should expand the sampling framework to include households from suburban and rural areas to provide a more comprehensive understanding of domestic refrigeration practices across Thailand. In addition, the questionnaire, interview and measured data collected during this study will be further published in a data paper. These open access datasets would be useful to manufacturers and researchers on household refrigeration, food safety education, and energy use patterns in tropical environments.

## Studies on humans and animals

This study did not involve any experiments on human participants or animals. All participants who allowed on-site refrigerator investigations were informed about the study objectives, voluntary participation, and their right to withdraw at any time. No personal or identifiable information was collected and reported. Therefore, there are no ethical concerns related to human or animal subjects to declare.

## CRediT authorship contribution statement

**Nattawut Chaomuang:** Writing – original draft, Visualization, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Conceptualization.
**Cheeraphat Potisuwan:** Writing – original draft, Methodology, Investigation, Formal analysis, Data curation.
**Steven Duret:** Writing – review & editing, Validation, Supervision, Methodology, Formal analysis, Conceptualization.
**Evelyne Derens-Bertheau:** Writing – review & editing, Validation, Methodology, Formal analysis.
**Yvanne Paviet-Salomon:** Validation, Software, Methodology, Investigation, Data curation.
**Methawee Nukunudompanich:** Resources, Project administration, Funding acquisition, Formal analysis, Conceptualization.
**Onrawee Laguerre:** Writing – review & editing, Validation, Supervision, Methodology, Formal analysis, Conceptualization.

## Declaration of competing interest

The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript.

## Acknowledgements

This work was financially supported by King Mongkut's Institute of Technology Ladkrabang, Thailand (Grant No. 2567-02-01-003). The research was conducted as part of the INRAE-KU-KMITL-UPS Associated International Laboratory REWACT (REducing food WAs te in cold Chain of Tropical countries).

## Data availability

Data will be made available on request.

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