Strategic Evaluation of Sustainable Practices for HVAC Systems in Small- and Medium-Sized U.S. Manufacturers

Reducing energy usage, CO₂ emissions, and process costs became universal goals for industries due to global competitiveness, economic balance, and high atmospheric concentrations of greenhouse gases. Accounting for 24.4% of the total energy consumption in the United States [1], the industry sector contributes significantly to the attainment of these objectives. Furthermore, the total industrial energy consumption in the United States is projected to increase by approximately 36% by 2050 compared to 2020 [2,3].

Industries recognize the substantial influence of energy efficiency on their economic balance, profitability, and sustainable growth. According to the Energy Information Administration [4], 22% of the manufacturing establishments consider that energy consumption is becoming a high priority, and 39% of the management sections supported projects to improve energy consumption. In 2018, 48% of the U.S. manufacturing industries participated in general energy management activities. Additionally, all U.S. states have implemented various energy justice programs and policies [5]. Fitzgerald et al. [6] indicate that ISO 50001-certified facilities have an average annual energy improvement of 4.1% for the first year, and the rate continues to be 3.4%, after twelve years.

Small- and medium-sized manufacturing enterprises (SMEs) are often considered the backbone of the economy since they create jobs, drive innovation, and contribute to economic growth. The size of a company in the United States is defined by the number of employees, earnings, industry type, and ownership structure. The U.S. Department of Energy Industrial Assessment Center (IAC) program defines small- or medium-sized companies as having less than 500 employees and $100 million annual sales, and the annual energy cost ranges between $100,000 and $3.5 million [7]. The United States had 219,533 industries in 2020 [4], with an energy consumption of approximately 18,906 trillion Btu [8]. According to the US Census Bureau [8], SMEs consume 49% of their energy usage in the heating, ventilation, and air conditioning (HVAC) systems. In the pharmaceutical industry, the HVAC system contributes to about 65% of the energy use, while 10% of the energy is used for lighting and 25% for plug loads and processes [9]. Bengea et al. [10] state that 27% of the energy consumption and 45% of peak electrical demand are related to HVAC in commercial buildings. In the U.S. commercial buildings, the primary energy usage by end-use for the HVAC systems is 30%. Most of this usage is for heating (43%), while for space cooling and ventilation, the values are 28% and 29%, respectively [11]. It is noticed that HVAC systems have a notable influence on energy usage in the manufacturing industry, which is one of the main energy-consuming sectors in the United States.

Simple energy assessments related to HVAC systems, and their consequent improvements, have a great potential for energy savings, usually with a low implementation cost. The use of appropriate technologies results in 10% of energy reduction in HVAC energy consumption [11]. Due to the deterioration, inadequately preserved, and incorrectly controlled HVAC equipment, commercial buildings may waste from 15% to 30% of energy [12]. Moynihan [13] identifies some possible recommendations for the manufacturing industries such as implementing an HVAC unit maintenance program, installing an airside economizer, using programmable thermostats, applying a new roof coating, and adding insulation to the building. Norford et al. [14] attribute 12% of excess energy to the HVAC system due to design divergences and operations not as specified. Simple solutions such as applying optimal controls can reduce energy consumption by up to 10% [10]. The company Merck achieved an energy saving of 30,000 MMBtu/yr and a reduction of 1700 tons of CO₂/yr only by setting back the temperature in the nonproduction hours [9].

To assess the energy systems and recommend possible improvements, energy audits are necessary. The IAC program is created to help small- and medium-sized U.S. manufacturing companies in terms of energy efficiency [7]. Currently, 39 IACs exist, all supported and supervised by the Department of Energy. Outside of the United States, Price and Lu [15] demonstrate 22 industrial energy audit programs in 15 countries and the European Union. The majority of the programs focus on SMEs, because of their lack of resources. Particularly for SMEs, financial constraints can pose a significant barrier to their engagement in energy audits, which are vital for enhancing energy efficiency. SMEs may not have the necessary capital or may not prioritize energy audits in their resource allocation. Other significant elements for helping SMEs include manuals, databases, follow-ups after the assessment, standardized tools, case studies, and auditor training and certification. Sorrell [16] identifies potential barriers to implementing energy efficiency investments including financial and productivity risks, insufficient capital, and lack of technical and cost information about the implementation. According to Lung et al. [17], 50% of the companies in the Better Plants program that achieved the goals are large companies, planning to reduce their energy consumption. One of the main reasons behind this is that large companies often have an Environmental Health & Safety (EHS) department, which can focus on energy efficiency initiatives [17]. The EHS department plays a critical role in identifying, implementing, and monitoring energy-saving measures, ensuring compliance with environmental regulations, and promoting a culture of sustainability within the organization. This structured approach allows large companies to allocate resources effectively and achieve significant energy reductions [18]. These elements verify the relevance and importance of energy audit programs within SMEs.

The significance and outcomes of the IAC program are discussed in the literature. The majority of the studies describe local implementation and extrapolate their results to the region. However, a relatively small quantity of assessments and periods are analyzed. Table 1 demonstrates the location, period, number of assessments, the systems that are analyzed, and the main conclusions of each of the peer-reviewed papers published using the IAC database.

References [19–22] focus on Wisconsin and Refs. [23–26] focus on Ohio. These studies have an average of 122 recommendations analyzed in a maximum of 10-year period. Furthermore, they extrapolate their calculations by assuming that all the assessment recommendations (ARs) were implemented. Among all the listed literature, Shook and Choi [23] is the only paper that focuses on the potential of HVAC system; however, its central analysis is the Ohio state SMEs. The only study that has a national analysis is Ref. [27], whereas it has a general approach in terms of field of analysis and just focuses on energy savings.

This article investigates sustainable practices for HVAC systems in U.S. manufacturing SMEs. It provides a comprehensive examination of energy, environmental, and economic analyses of practices associated with HVAC systems. A total of 156,000 energy assessments are used in the analysis. The document quantifies the potential for substantial energy and cost savings, as well as a significant reduction in CO₂ emissions achievable through the adoption of energy efficiency measures in U.S. SME production facilities. Furthermore, by presenting case studies and common recommendations on HVAC systems, this document provides industries with practical information, enabling them to adopt energy-saving measures effectively.

The work is structured into three sections. First, the methodology employed for data analysis will be discussed and ARs will be described. Moving forward, the outcomes of the data analysis will be presented in the third section, and the energy and cost reductions achievable through ARs will be quantified alongside their associated implementation costs and implementation rate. Finally, some insights will be provided through the presentation of three case studies, selected due to their significance within the context of the data analysis. The case studies include detailed calculations, implementation costs, payback periods, energy and cost reductions, and the consequent reduction in CO₂ emissions.

Figure 1 shows that the methodology for analyzing the database containing the assessment information and recommendations data is divided into three parts: energy audit, filters applied to the database, and data analysis.

Energy audits involve a comprehensive examination of a facility or building, wherein the various energy-consuming systems, energy management practices, and potential avenues for energy savings are analyzed and assessed. A preliminary energy-use analysis needs to be conducted, including at least a one-year utility bill. On the assessment day, thermostat set points and types, nameplate data, input power, coefficient of performance (COP), airflow rate data in the duct system, operating schedule, building construction materials, sources of heat and potential losses, and usage factors are important parameters to be recorded and measured. With the data collected, the recommendations are done and reported, showing the energy, economic, and environmental analysis. Typically, energy savings, energy cost savings, CO₂ emissions reduction, and simple payback are calculated. Upon the completion of the report, the IAC uploads the energy data, the number of ARs, their associated savings, and implementation cost. In less than 1 year from the audit day, the company will be contacted regarding reporting the percentage of the ARs that are implemented and providing a reason for not implementing the other ones.

The data for the current analysis are collected from the IAC database [7]. The database has information on each energy assessment and associated ARs from 1981 to 2023 for all the centers around the country. The nature of each recommendation is indicated by the AR code (ARC). The code is composed of five numbers formatted as A.BCDE. For the present work, code 2.72DE is evaluated, which is related to the energy management group (2.BCDE), followed by the building and grounds subgroup (2.7CDE), and the space conducting subdivision (2.72DE). The codes 2.722E (operations), 2.723E (hardware—heating/cooling), 2.724E (hardware—air circulation), and 2.726E (controls) are chosen due to their relevance to the space conditioning ARs. Table 2 demonstrates a precise description for 21 AR codes.

To calculate energy savings, the proposed annual energy usage is subtracted from the calculated existing annual energy usage. The energy reduction can then be multiplied by the annual average facility electrical usage rate to find the total electrical energy cost savings. The total cost savings due to the implementation of the AR are calculated after considering other charges that the facility receives.

The simple payback period is calculated by dividing the implementation cost by the annual cost savings. The implementation cost includes both labor and equipment expenses on the implementation date. The energy cost savings are derived from reductions in electricity or natural gas usage, including any additional associated charges.

Given that this study focuses on a national analysis, the main comparable parameter is energy savings. Even for energy saving, different factors can play significant roles, including climate, building structure, human interaction, number of equipment, etc. Therefore, it is important to note that cost-related parameters may differ for different regions, industrial applications, etc.

The calculation for CO₂ emissions is based on the emission factor. For natural gas, 73.19 kg CO₂/MMBtu is used for all the U.S. states [30]. For electricity, the values of CO₂/kWh are different for each region [31].

In total, more than 156,000 ARs were evaluated, with an average of 7.49 ARs per energy assessment process. Figure 2 shows the total number of assessments and ARs/assessment per year. The number of assessments had its pick in 1995 with 879 assessments. The number of ARs/assessments does not witness significant changes throughout the years. However, after 2015, the ratio slightly decreased from 8.44 to 6.68 ARs/assessment, in 2022.

Energy management-related ARs account for 89% of all the recommendations, followed by waste minimization/pollution prevention with 7%, and direct productivity enhancements with 4%, as indicated in Fig. 3. Within energy management, 34% accounts for motor systems, 33% for buildings and grounds, 14% for thermal systems, and other types represent 19% of the ARs. Errigo et al. [25] studied the application of motor systems in medium- and small-sized companies. Additionally, Kapp et al. [24] demonstrate how the improvements in thermal systems save energy, CO₂, and cost, and potentially help the job market. The current work focuses on the building and grounds, which is the second most numerous topics.

The building and ground topic accounts for 45,377 ARs in the whole IAC history; Fig. 4 shows how the ARs are distributed. Seventy percent of these ARs are dedicated to lighting. On average, lighting ARs have an energy savings of 0.76% of the total energy cost savings of a facility, with a payback of 2 years. Fifty-four percent of the lighting ARs have been implemented. Shook and Choi [23] show how the implementation of lighting recommendations would be beneficial for SME companies around the United States. The building envelope is responsible for 8% of the building and ground topic ARs and has an average of 0.97% reduction on the total energy cost of a facility. Forty-three percent of these ARs are implemented, with an average of 1.8 years of payback period. The smallest number of recommendations is associated with ventilation ARs with 2% of the total number of building and grounds ARs, 46% implementation rate, and an average savings of the facility of 1.66%. Space conditioning accounts for 20% of the building and grounds AR and results in an average facility cost savings of 1.39% per AR type, with a payback period of 1.8 years. The implementation rate is 46% for the space conditioning ARs.

Four main categories of space conditioning-related ARs, associated with a total of 8565 recommendations since the IAC program establishment, are studied in this article. The operation-focused ARs with the code (2.722E) represent 32% of all ARs related to space conditioning, followed by controls (2.726E) with 26%, hardware—heating/cooling (2.723E) with 19%, and hardware—air circulation (2.724E) with 17%.

Table 3 presents the total savings per year, average payback, and implementation rate of the four main types of ARs in space conditioning. The hardware—heating/cooling has the highest values of savings with more than $32 million per year, followed by operation ARs with $28M, hardware—air circulation with $17M, and controls with $12M. However, the payback period for the control ARs is smaller than the other types, which also indicates the lower implementation cost, facilitating the implementation rate, resulting in 56% of the recommendations being implemented. Hardware—heating/cooling and hardware—air circulation have an average payback of 3.1 and 2 years, respectively. Note that the payback period has a meaningful impact on the implementation rate.

Table 4 shows the average cost savings of a specific AR in relation to energy cost, average simple payback, implementation rate, the ratio of number of each AR category to the total number of space conditioning (2.72DE) ARs, and the average annual energy savings for each AR of the operation, controls, hardware—heating/cooling, hardware—air circulation.

For the 2.722E (operations), the 2.7221 and 2.7224 ARs, described in Table 2, are the most common ones, and they result in the highest annual savings. Additionally, these two categories are the most implemented ones among operation ARs. The average simple payback of the 2.7224 ARs is small, with 0.4 year. The 2.7226 and 2.7229 ARs have the highest values of relative cost savings concerning the energy cost of the facility per AR, with 1.5% and 1.4%, respectively.

The largest energy for the 2.723E (hardware—heating/cooling) ARs resulted from 2.7233 and 2.7232, with 3787 MMBtu/yr and 2293 MMBtu/yr, respectively. Both types of ARs also have a high occurrence. The average payback for the 2.7231 is 1.9 year, which is lower when compared to the other 2.723E ARs. Note that the implementation rate for the 2.7232 and 2.7234 ARs are 42% and 41%, both higher than the others in the same category of ARs. Code 2.7233 has the largest average annual savings, followed by 2.7232 and 2.7231.

When comparing the 2.724E ARs, 2.7243 and 2.7241 play an important role with the highest occurrence. The 2.7242 ARs have an average annual energy savings of 2193 MMBtu/yr, followed by 2.7241 with 1688 MMBtu/yr. The most considerably beneficial AR in the 2.726E category seems to be 2.7261, which is related to installing and using programmable thermostats, with a relative energy cost savings of 1.7% of the total facility energy cost, a simple payback of 0.7 year, and an implementation rate of 56%.

Assessment recommendation 2.7261 considers installing timers and/or thermostats that can be programmed to set different temperatures during different seasons and nonworking hours. It is important to notice that this AR is closely related to ARs 2.7221 (Lower Temperature During the Winter Season and Vice-Versa) and 2.7224 (Reduce Space Conditioning During Non-Working Hours).

To gain a comprehensive understanding of the sustainable impact of HVAC ARs on small- and medium-sized companies in the United States, an extrapolation by assuming the implementation of ARs across the board was conducted. According to US Census Bureau data [8], in 2018, 219,533 SME companies existed in the United States, collectively consuming 18,906 trillion Btu of energy.

The current article analyzes 20,818 assessments, showing that the average annual energy cost per company amounted to $790,564 per year, with an associated energy usage of 155,774 MMBtu per year. When considering all SME companies evaluated, this is translated to $16.5 billion in annual energy costs and an energy consumption of 3.2 billion MMBtu per year.

The introduction of HVAC ARs is projected to yield a noteworthy impact, with an anticipated average reduction of 0.4% in energy consumption and 0.5% in energy costs, according to Table 4. Extrapolating these gains across all SME companies in the United States, we anticipate annual energy cost savings of $744 million per year and a substantial reduction of 71.9 million MMBtu in energy consumption per year.

As highlighted in Table 4, our analysis indicates that the average payback period for these ARs is approximately 1.8 years. The total investment of approximately $1.3 trillion is also needed. Importantly, this investment corresponds to a reduction of approximately 8.7 million metric tons of CO₂ emissions, annually. The implementation cost could be supported through government credits and rebates, along with other financial incentives. Therefore, the implementation of HVAC ARs not only presents a significant economic advantage for U.S. SME companies but also contributes to a meaningful reduction in carbon emissions, aligning with global sustainability objectives and policy goals. This information confirms the valuable impact that HVAC ARs on the U.S. SME sector, through improvements in energy efficiency, resulting in economic and environmental benefits.

It should be noted that not all HVAC practices are appropriate for all climates. Depending on the temperature and humidity levels, the energy reduction might have a significant impact. For instance, in cold climates (e.g., Alaska), windows with double or triple glazing and low-emissivity coatings can reduce heat loss [32]. In hot climates (e.g., Texas), cool roofs that reflect more sunlight and absorb less heat can reduce cooling loads [33].

This section presents three real case studies related to AR codes 2.7261 (Install Timers and/or Thermostats), 2.7232 (Replace Existing HVAC Unit with High Efficiency Model), and 2.7241 (Install Outside Air Damper/Economizer on HVAC Unit). The 2.7261 AR has significant importance among all space conditioning ARs, with a high number of repetitions, a high implementation rate, and a low simple payback. The 2.7232 is the most occurrence AR in the 2.723E category (hardware—heating/cooling) with high savings. The 2.7241 AR is one of the highly considered AR among the (2.724E) hardware—air circulation ARs with large savings and high average annual savings.

This section provides a comprehensive overview and a comparison of two methods of calculation used to estimate HVAC energy savings resulting from installing timers and/or thermostats. The input data are obtained from visiting a commercial printing company located in Alabama. The objective of this section is to showcase the detailed savings that can be achieved by installing programmable thermostats and assess the effectiveness of two common methods used for estimating those achievements.

Programmable thermostats are components essential for modern industrial climate control. Their features, such as scheduling, temperature control, and remote access, are crucial energy management systems. The user can create multi-level schedules, controlling the temperature set point during different periods of the day. Additionally, some advanced programmable thermostats have adaptive learning abilities, automatically controlling the schedule and temperature preferences of the users [34]. Some modern programmable thermostats also come with a wi-fi connection, which allows the user to control it remotely. Even many thermostats provide an energy report, assisting with the understanding of energy consumption.

The investigated methods include using openstudio and energyplus software versus the utilization of local bin-weather data. Through a comparative analysis of the results obtained using these two methods, the effectiveness of each approach in estimating energy savings will be evaluated. Additionally, valuable insights will be obtained toward the accuracy and reliability of the estimations.

The facility, with an area of 3716 m², is conditioned by a total of 14 HVAC units, with a combined capacity of 422.3 kW. The HVAC models installed are described in Table 6. The current temperature set point of the printing area, which operates for 5355 h/yr, equals 21 °C. The office area operates for 2295 h/yr, but the HVAC units run constantly with a temperature set point of 23 °C. It is estimated that 20% of the facility's energy usage is attributed to HVAC systems. The 12 cooling units used in the printing area consume 187,550 kWh/yr and the 2 cooling units supplying the office area consume 17,616 kWh/yr.

Installing and utilizing programmable thermostats throughout the facility is recommended. Programmable thermostats can raise or lower the set points for the air conditioning units automatically. For instance, the set point can be adjusted to a specified temperature higher than human comfort temperature during unoccupied periods in warm seasons. The appropriate use of programmable thermostats will reduce the energy consumption of air conditioning units by reducing their total operating hours.

The determination of the operational changes for the cooling system involves estimating the annual operating hours, while considering the desired set temperatures during periods of occupancy or vacancy. To allow sufficient time for the system to cool the space ahead of time and accommodate potential additional working hours, it is recommended to adjust the set points 1 h before and after the space is occupied. Furthermore, during weekends and sleeping hours, it is advisable to set the temperature to 27 °C for cooling. Throughout the workday, a cooling temperature of 23 °C is recommended. Table 5 outlines the proposed weekly set point schedule specifically calculated for each building.

Method 1 relies on local bin-weather data to determine the reduction in cooling hours of the building based on the occupancy hours of the building. By using the historical weather data specific to the location, the proposed cooling hours required to maintain the temperature set point can be determined. Implementing this new set point schedule is expected to yield 2177 annual cooling hours for the office, and 2602 annual cooling hours for the production area. The reduction in these hours, resulting from the installation of programmable thermostats, is calculated by taking into account the new temperature set points and specific HVAC system details.

The current energy usage of the space cooling system is estimated based on nameplate information and bin-weather data for the local area. The existing electrical energy usage for cooling is calculated by Eq. (1). Considering the operating conditions, the usage factor and load factor values are decided to be 1.00 and 0.33 for all HVAC units, respectively. Table 6 presents the rated capacity, COP_c, model, area where the system is used, and identification code for each evaluated HVAC unit. The identification code for each unit is designed for easy reference and is a combination of the rated capacity (in kW) and the COP_c. For instance, the model 4YCC4060A1090AB, which has a rated capacity of 17.6 kW and a COPc of 3.86, is assigned the code R17.6, C3.86.

Figure 5 shows the existing and proposed energy usage, which are based on the set point schedule. The proposed electrical energy usage for cooling is presented by an equation similar to Eq. (1), but the existing cooling hours will be replaced by the proposed cooling hours obtained from bin-weather data, which are 2177 h/yr and 2602 h/yr for the office and printing areas.

Method 2 for analyzing the HVAC unit savings involves the use of openstudio and energyplus software, industry-standard tools for building energy modeling and simulation. A virtual model of the building is created using openstudio, considering various factors such as building geometry, construction materials, occupancy schedules, and HVAC system characteristics. The model is then exported into energyplus to simulate the building's energy consumption patterns and estimate the potential energy savings. Parameters such as temperature set points, occupancy schedules, and HVAC system operation are considered in these calculations.

The existing energy usage of the space cooling system can be estimated based on nameplate information, as well as the weather TMY data file provided by energyplus [29]. energyplus and openstudio are used to create a model that replicates the HVAC system in use. Figure 6 shows the cooling loop in the printing area. The area is simplified and considered as one large area, and all the rooftop units were presented as a single unit with a COP equal to the average of all units.

The software openstudio and energyplus were used to change the temperature set point to 23 °C. This was done by changing the temperature schedule in the office and printing area. The estimated current electrical energy usage due to HVAC in the production area as predicted by the openstudio model is 184,246 kWh/yr. With the change in the temperature set point, the total energy usage can be reduced due to the space conditioning units running for a shorter period. This reduced usage is predicted to be 110,236 kWh/yr, based on TMY data for the local area.

To calculate the energy savings, the calculated existing annual energy usage is subtracted by the proposed annual energy usage. The energy reduction can then be multiplied by the annual average facility electrical usage rate to find the total electrical energy cost savings. The total cost savings due to the implementation of programmable thermostats are calculated after considering other charges that the facility receives. Furthermore, the reduction of CO₂ due to the decrease in electrical energy usage can be found by multiplying the amount of CO₂ produced per kWh of electricity generated by the energy reduction.

The comparison of the results obtained from the two calculation methods—method 1 based on local bin-weather data and method 2 utilizing openstudio and energyplus software—reveals that both methods demonstrate very similar energy and cost savings. Method 1 resulted in a total cost savings of $8162 per year, while method 2 resulted in a cost savings of $8266 per year, showing a minimal difference of only 1.26%. These cost savings were driven by a reduction in electrical energy usage. The calculations from method 1 show a 39% decrease in electrical energy usage, reducing from 187,550 kWh/yr to 114,472 kWh/yr. On the other hand, method 2 shows a slightly higher energy reduction, with a decrease of 40%, lowering the energy usage from 184,246 kWh/yr to 110,236 kWh/yr. This yields a 3.77% difference between the two methods. Additionally, the CO₂ reduction is 32 tons/yr for both methods.

The implementation cost of this recommendation includes the cost of purchasing programmable thermostats and the labor charges for a facility employee to install the thermostats and apply the mentioned scheduling to them. The average cost of a programmable thermostat is $70 [35], and it is recommended to have one for each HVAC unit. The total implementation cost for this example is approximately $1,440, considering twelve HVAC units and the labor cost. A simple payback of 0.18 years is resulted for both of the methods. Since the implementation costs are the same for both methods, the small difference in results between the two methods does not produce a significant disparity. Notice that the climate zones highly influence energy savings as can be seen in Ref. [36].

The similarity in the outcomes of the two calculation methods indicates a robust and consistent estimation of the proposed energy and cost savings achievable through the installation of programmable thermostats. These results provide strong evidence that implementing programmable thermostats leads to notable reductions in energy consumption and costs, contributing to the facility's sustainability goals while ensuring a comfortable working environment.

As HVAC units age, their efficiency degrades, and without scheduled maintenance, this loss in efficiency can dramatically increase the energy usage and cost of the HVAC system. The objective of this section is to show the calculations used to obtain projected energy savings from replacing older HVAC units located in a facility in Alabama. The facility is conditioned throughout the year by a total of 13 units ranging in size from 17.5 kW to 88 kW of capacity. According to the nameplate data gathered by AIAC personnel, these units range between 1 and 20 years old. Upon inspection, six HVAC units were observed to be older than 10 years. Considering the degraded HVAC efficiency, AIAC personnel estimate that these six HVAC units' usage accounts for approximately 60% of the entire HVAC system energy consumption, while the entire HVAC system consumes 34% of the total energy of the facility.

It is recommended to replace all the units over 10 years old (6 units out of 13), as they are nearing the end of their useful life. These six units consist of three 61.5 kW capacity TCH210C40BDA units and three 44.0 kW capacity TCH150D40BAA units. The estimated existing energy usage for the units being replaced is 611,372 kWh/yr for heating and 418,630 kWh/yr for cooling.

The initial COPs for each HVAC unit were determined using the manufacturer's specified data. Additionally, the usage and load factors of the units were estimated based on information collected by the AIAC during the plant tour. To assess the current cooling and heating hours, available bin-weather data for the local area were utilized.

To determine the degraded COPs, the initial COPs, estimated maintenance factors, and unit age were considered. The analysis revealed that the initial cooling and heating COPs for all six units were 2.87 and 3.87, respectively. However, after 20 years of use, the degraded cooling and heating COPs were calculated to be 1.56 and 2.11 [36], indicating a significant decline equal to 46% for both cooling and heating. Figure 7 shows the COP degradation and corresponding energy consumption over the course of 20 years.

It was found that increasing the HVAC unit's COP to that of which when it was new reduces the energy consumption by 46% for both cooling and heating. The restored efficiency of the units also leads to a reduction in demand, resulting in lower demand costs. Considering other charges incurred by the facility, such as taxes, surpluses, and incentives (TSI), it is estimated that the facility will experience a 10% decrease in annual electrical billing costs due to the improved efficiency of the HVAC units. Furthermore, the decrease in electrical energy usage also contributes to a reduction in CO₂ emissions. This reduction can be estimated by multiplying the amount of CO₂ produced per kilowatt-hour (kWh) of electricity generated by the energy reduction achieved, and results in a reduction of 203 tons CO₂/yr.

It is important to note the implementation costs associated with this recommendation as well. This implementation involves replacing 6 out of the 13 existing units. Estimated cost values for the implementation are obtained from the RSMeans cost catalog using linear regression. By considering the total cost savings and the implementation costs, a simple payback period of 3.9 years is calculated for this recommendation. Notice that the climate zones highly influence energy savings as can be seen in Ref. [37].

Installing airside economizers on production HVAC units is another way to improve energy efficiency and reduce operational costs. Table 6 shows the information for the HVAC units being analyzed. The purpose of using economizers is to take advantage of favorable outdoor conditions when the enthalpy, a measure of the total energy of air, is appropriate for cooling indoor spaces. When the enthalpy of the return air exceeds the enthalpy of the outdoor air, the economizer opens, allowing the outdoor air to be mixed with the return air and used for cooling purposes. This strategy enables the facility to utilize outdoor air as cooling air, reducing the cooling effort of the HVAC system and consequently saving energy. For heating, the method is similar but works in the opposite way. Figure 8 explains the logic of the economizer and Fig. 9 shows an illustration of the system. In these figures, T indicates temperature, h indicates enthalpy of the air, and subscripts in and amb stand for “inside air” and “ambient” characteristics, respectively.

To determine the hours of the year when outdoor conditions are suitable to be used as supply air for indoor conditioning, data from a TMY file provided by energyplus were used. The analysis, performed using energyplus and openstudio, aimed to simulate the HVAC system's behavior with the airside economizer in place.

The airside economizer used within the building model was a differential enthalpy economizer. Figure 6 shows the cooling loop in the office and production areas. The production and office areas are made up of two large areas. The several rooftop units that supply conditioned air to these areas were represented as a single unit of equivalent capacity for each area within the model.

The software openstudio and energyplus were used to estimate the impacts of installing an airside economizer on energy usage. This was done by performing two simulations: one with no airside economizer installed, and one with an airside economizer installed on all production rooftop units.

The estimated current electrical energy usage due to HVAC in the production area as predicted by the openstudio model is 184,246 kWh/yr, a difference of 1.76% between the model and the end-point analysis calculated through nameplate data. With the implementation of differential enthalpy airside economizers on the rooftop units, the total energy usage is predicted to be 164,822 kWh/yr, showing a 10% drop in energy usage. These calculations have been performed based on TMY data for Montgomery, AL. Considering other charges incurred by the facility, such as TSI, the 10% drop in energy usage results in a 5% reduction in the annual electrical billing costs. Furthermore, the decrease in electrical energy usage contributes to a reduction in CO₂ emissions. This reduction can be estimated by multiplying the amount of CO₂ produced per kWh of electricity generated by the energy reduction achieved, and results to 8 tons CO₂ reduced per year.

Many recent HVAC units contain built-in airside economizers, so only installation and labor costs are applicable. The cost of a new unit can be estimated using the RSMeans cost catalog and ranges from $3932 to $79,387 for a 7.0-kW and 52.75-kW capacity unit, respectively. The simple payback will vary based on local weather conditions and the capacity of the HVAC system. For Alabama, which is a hot and humid region, the airside economizer might have limited benefits. However, for the cold and dry climates, the energy savings are significantly high, as can be seen in Ref. [38].

Small- and medium-sized manufacturers play a substantial role, accounting for 50% of the total energy consumption in the United States. Remarkably, approximately half of this energy is attributed to HVAC systems within industrial settings, a section that is often overshadowed by the spotlight on process energy use. The IAC program has been essential in decreasing energy consumption by SMEs, with a focus on reducing their CO₂ emissions. Equally significant is the program's role in shaping future energy engineers and industry professionals, providing the foundational knowledge essential to address the climate crisis.

The means to achieve these laudable goals are embedded in precise energy assessments, producing detailed reports containing detailed calculated recommendations (ARs). Over the years, there has been a noticeable tendency to overlook building energy usage within industrial facilities. However, even considering the modest 10–20% energy savings typically offered by conventional energy assessments, the implementation of viable energy reduction measures linked to HVAC systems in U.S. SMEs presents a 0.4% reduction in energy consumption. Even in the current landscape which only a fraction of ARs target HVAC systems and 44% of these recommendations find implementation, the realized benefits are substantial. It includes a reduction of 71.9 million MMBtu of energy consumption annually, an annual reduction of 8.7 million metric tons of CO₂ emissions, and cost savings amounting to $744 million per year.

Three case studies were economically, energy, and environmentally evaluated. The first case study proposed the installation of programmable thermostats, which resulted in a 40% annual energy reduction, a simple payback of 0.18 years, and a CO₂ reduction of 32 tons/yr. The second case study recommends the replacement of degraded HVAC units, reducing the annual energy consumption by 46%, and 10% in annual electrical billing costs. The annual CO₂ emissions have a reduction of 203 tons CO₂/yr. The final case study investigates the installment of airside economizers in the HVAC units, achieving a 10% in the annual energy usage, 5% in the annual energy cost, and CO₂ reduction of 8 tons/yr.

This article offers a comprehensive overview of commonly recommended ARs. This helps industries by providing knowledge on available opportunities to initiate relevant energy-saving measures, even in the absence of detailed energy assessments. Key ARs related to HVAC systems, complete with payback periods, implementation rates, savings projections, and prevalence are provided. Additionally, three select case studies, distinguished by their substantial savings, minimal payback periods, and implementation rates, offer practical insights into ARs and associated calculations. This research investigates the role of HVAC systems in advancing sustainable manufacturing practices. It also highlights the importance of applying energy-saving measures to benefit the SME sector.

Financial support from U.S. Department of Energy (DOE) under the grant DE-EE0009715 through the Industrial Assessment Center program is gratefully acknowledged.

There are no conflicts of interest.

The data and information that support the findings of this article are freely available.²

N =

number of HVAC units

AR =

assessment recommendation

CO₂ =

carbon dioxide

COP =

coefficient of performance

DOE =

Department of Energy

EHS =

Environmental Health & Safety

EU =

energy usage

HVAC =

heating, ventilation, and air conditioning

IACs =

Industrial Assessment Centers

LF =

load factor

OH =

operating hours

RC =

rated capacity

SMEs =

small- and medium-sized manufacturing enterprises

TMY =

Typical Meteorological Year Data

UF =

usage factor