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Refrigerant Management: How Changes to Section 608 Impact Our Industry

JohnWallace_Blog_Image John Wallace | Director of Innovation, Retail Solutions

Emerson Commercial & Residential Solutions

I was recently interviewed for an article in ACHR’s The News magazine, “EPA’s Proposed Changes to Section 608 Cause Concern in the Industry,” where I provided my perspective on the current state of leak detection, repair and other provisions.

Refrigerant leak response and repair regulations have placed our industry in uncertain waters. As you may know, the Environmental Protection Agency (EPA) has proposed a new rule that rescinds some provisions of its Section 608 mandate, affecting equipment with 50 lbs. or more of hydrofluorocarbons (HFCs) or other substitute refrigerants. These best practices were developed in consultation with the HVACR industry to ensure safety, establish proper reclaim and recycling processes, and of course, reduce carbon emissions.

In November 2016, the EPA extended the scope of Section 608 — from refrigerants containing ozone-depleting substances (ODS) to nonexempt substitute refrigerants such as HFCs. Because the Court of Appeals ruled in 2017 that the EPA could not ban HFCs, the agency has decided that it also did not have the authority to regulate these refrigerants under Section 608.

Establishing best practices

Awareness of the importance of leak detection has grown exponentially in recent years. Today, most companies understand that implementing a leak response and repair program is simply a best practice. And for those companies that have already taken steps to comply with Section 608, the vacating of this rule will have little impact.

I stated in the article: “These procedures not only benefit the environment but also help ensure HVACR equipment operates at peak efficiency, including at the lowest overall cost. One of the benefits of the existing regulations has been to raise the awareness of best practices related to HVACR maintenance. Increased awareness generally leads to broader adoption by those in the industry, regardless of whether regulations are in place.”

Simply put, leak detection and repair programs make good sense, regardless of the regulations in place or the type of refrigerant being used. However, with the reversal of Section 608, equipment operators will no longer be under federal mandate to follow these widely adopted refrigerant management best practices:

  • Conducting leak rate calculations when refrigerant is added to an appliance
  • Repairing an appliance that leaks above a threshold leak rate
  • Conducting verification tests on repairs
  • Conducting periodic leak inspections on appliances that exceed the threshold leak rate
  • Reporting to the EPA about chronically leaking appliances
  • Retrofitting or retiring appliances that are not repaired
  • Maintaining related records
  • Overseeing technicians’ use of certified equipment and the reclamation process

These procedures are already considered to be the optimal standard practice, and end users who are focused on operational excellence are likely doing many (or most) of them today.

Maintaining other key program elements

The absence of a federal mandate for responsible HFC management creates a quandary for our industry. Currently, the EPA is seeking comments about the remaining provisions of Section 608, raising concerns about the potential for overturning other benefits of programs — specifically, guidelines for refrigerant reclaim procedures and technician certification and training programs.

Proper refrigerant reclamation reduces the likelihood of introducing impurities, which could lead to premature failures and increased maintenance costs for owners of HVACR equipment. What’s more, the certification program provides the vital information on how to deal with the ever-growing number of refrigerants. As I stated in the article: “One benefit of certification is that wholesalers are able to sell refrigerants to technicians who have a sufficient background and understanding of their liability under the Clean Air Act.”

Path forward

Already, several states are adopting standards for leak detection and control. Again, as I noted in the article, “We are already seeing some states such as California enact regulations that adopt many of the requirements in Section 608. Other states will likely step in, which may create more headaches for the industry. This could create problems for the industry and lead to a patchwork of inconsistent regulations that would be challenging for manufacturers and service providers to navigate.”

As always, Emerson will help you stay informed about further changes to Section 608. Regardless of the regulatory decisions, we’ll continue to provide guidance and expertise on how to design and implement refrigerant management programs.

Refrigerant Leak Detection and Regulatory Update

JohnWallace_Blog_Image John Wallace | Director of Innovation, Retail Solutions

Emerson Commercial & Residential Solutions

Proper refrigerant leak detection is essential for retailers, potentially saving them thousands of dollars annually and helping to meet regulatory requirements. For the full article, click here.

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Refrigerant leaks can cause both economic and environmental disruptions for retailers. Today, the average supermarket has two to four refrigeration racks charged with approximately 3,500 pounds of refrigerant. According to the Environmental Protection Agency’s (EPA) GreenChill research, about 25 percent (875 pounds) of that refrigerant is lost each year due to leaks. At $7 per pound, this loss equates to an annual expense of about $6,100 — more than $600,000 annually over a chain of 100 stores. And that’s just the financial aspect. In the same 100-store example, nearly 70,000 pounds of refrigerant are leaked into the atmosphere.

Introduced in the 1990s to address emissions of ozone-depleting substances such as chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigerants used in stationary refrigeration and air conditioning units, Section 608 of the Clean Air Act was revised in 2016 to include hydrofluorocarbon (HFC) refrigerants. This revision also introduced more stringent requirements for repairing leaks in larger appliances as well as new record keeping, reporting and disposal mandates.

Per the 2016 revision to Section 608, the next iteration of these requirements will take effect on January 1, 2019, and include the following changes:

Lower leak thresholds. The new thresholds are 30 percent (from 35 percent) for industrial process refrigeration (IPR), 20 percent (from 35 percent) for commercial refrigeration equipment (CRE), and 10 percent (from 15 percent) for comfort-cooling equipment.

Required inspection and monitoring. Section 608 now requires quarterly/annual leak inspections or the use of automatic, continuous monitoring devices for refrigeration and air conditioning equipment that have exceeded the threshold leak rate.

 New reporting requirements. Owners and operators must maintain hard or electronic copies of reports documenting the full charges of appliances and the types of automatic leak detection systems used. For chronically leaking appliances, owners/operators must also submit reports if their systems contain 50 or more pounds of refrigerant and leak 125 percent or more of their full charge in one calendar year.

 Disposal requirements. Technicians must keep a record of refrigerant recovered during system disposal from systems with charge sizes ranging from 5 to 50 pounds.

With all of these revisions on the horizon, it’s important to note that the EPA takes enforcement very seriously. The consequence of noncompliance can be significant: the agency is authorized to assess fines of $37,500 per day for violations.

We recommend that companies implement effective refrigerant leak detection programs to minimize refrigerant leaks and plan a response strategy in the event of a leak. Direct leak detection technology includes fixed or portable monitors installed on-site, which detect the concentration of refrigerants in the air. These can be set close to the anticipated leak airstream, in enclosed spaces and in areas near the floor where leaked refrigerants collect.

 The renewed regulatory focus on reducing refrigerant leaks has caused retailers to put more emphasis on developing efficient and effective leak detection strategies. Leak detection programs not only allow retailers to stay on top of regulations; they can potentially save costs associated with lost refrigerant, the degradation of refrigerated system performance and food loss.

Understanding Your EMS and Identifying Trends on the Horizon

JohnWallace_Blog_Image John Wallace | Director of Innovation, Retail Solutions

Emerson Commercial & Residential Solutions

Squeezing the most efficiency out of your energy management system (EMS) can be a pivotal part of your operation. Many store and franchise operators are only using around 10–20 percent of the overall power of their EMS. Optimizing your systems and getting your “money’s worth” out of your EMS can reduce energy and maintenance costs and potentially lower energy consumption.

Understanding Your EMS and Identifying Trends on the Horizon

To fully understand what an EMS does and how it can benefit you, a helpful comparison can be made by looking at the progression of automotive technologies. For example, today we are accustomed to our cars nearly being able to drive themselves (some can). That evolution began as industry leaders started incorporating electronics into vehicles to benefit drivers — things like an analog braking system that was connected to engine control modules which were connected to traction control systems. Manufacturers are blending these systems together, improving communication and thereby optimizing vehicles.

An EMS, essentially, follows the same sort of ideology, tying together key systems and the architectural layers of your operation. These start with the control layer, where electronics take sensor inputs and determine what actions to take with that information (turning on/off compressors, fans, etc.). Next, the supervisory layer handles things like data logging, bringing the data from different systems together and storing it for you to evaluate and analyze over a given time frame (days, weeks, months, etc.) — and generating alarms for anomalies and other problems.

Finally, the remote layer, or remote system, is a software platform (or something similar) that communicates with your on-site equipment and gathers data that you can view via a remote user interface to see trends in your operations. Obviously, this is key to your ability to manage all this information from a location away from your actual operation.

As your EMS continually collects data, it is important for you to make the most of that data and understand how your EMS can help you identify trends and improve the way your facility operates. Optimizing your EMS grants you visibility into what’s happening at any particular site within your building/enterprise. Average operational expenses for a supermarket are incredibly high, so knowing how to interpret data provided by an EMS allows you to solve your problems quickly and efficiently.

Several trends regarding smart buildings and EMS technology have emerged in recent years, including: building energy management hitting the “cloud,” increased demand for smart building products, the convergence of building communications protocols, and the blurring of the interface between smart buildings and the smart grid. These trends tend to drive innovation in four key areas: user interface and usability, integration, cloud connectivity, and extensibility and apps.

For a more in-depth look at what an EMS can offer your operation and to hear more trends, be sure to watch the full presentation here.

Modernizing the Middle of the Store

JohnWallace_Blog_Image John Wallace | Director of Innovation, Retail Solutions

Emerson Commercial & Residential Solutions

This blog summarizes an article from our E360 program, entitled Cooling the Middle of the Store to Heat up Sales.” Click here to read it in its entirety.

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The perimeter of most grocery chains has always been at the forefront of the customer experience, occupied by shopper-friendly delis, fresh produce and bakeries, among other things. The middle of the store? That’s where you’d find the less sexy necessities like canned goods and other grocery staples.

Emphasizing the perimeter and stockpiling the middle with necessities was a dependable strategy. But times are changing. Case in point: a major food retailer discovered that in recent years, as the middle of the store began to shrink, so did overall revenues, with some major brands seeing as much as 2.8 percent drops per quarter. It needed a way to boost profits in the middle of stores.

The solution was to add new, low-profile refrigerated units to showcase more exciting products and packaging, bringing the pizzazz and flair of the perimeters to the middle of stores. But keeping these units working properly and monitoring their performance in this central location was the real challenge.

The necessity of maintaining consistent temperatures in refrigeration units exposed to ambient air meant stores would have to hook up sensors to monitor and control the temperatures in free-standing cases. However, these sensors required wiring that would need to be encased inside the stores’ walls — which would disrupt customers and cost stores a decent amount of money.

Emerson Retail Solutions presented one client with another option, which required no wiring at all.

Emerson’s Wireless Sensor System allowed the grocery chain to connect temperature probes, product simulators and other refrigeration sensors in critical refrigeration equipment throughout their stores, running around the perimeter and filing into the middle. This system also allowed the chain to collect key data that helped store managers monitor perishables which, in turn, allowed for maximized shelf life, reduced shrinkage and ensured safety.

The wireless module inside the cases transmitted data from the probes, product simulators and other sensors to a remote wireless gateway overhead. That gateway then converts the wireless signals into usable, real-time information, allowing for constant monitoring and data that can be used for supervisory controls. The signal sent from the module is strong and reliable enough to reach up to a 100-foot radius, all while using a minimal amount of energy. Repeaters can boost this signal even more, allowing for reach across the entirety of stores.

The Emerson Wireless Sensor System can, oftentimes, be installed in just 3.5 hours, potentially accumulating a 70 percent savings in installation costs when retrofitting stores, and cutting construction costs on new retail stores by up to 15 percent. Savings continue after installation by allowing the grocery chain to avoid fluctuating temperatures and reduce energy costs with their highly efficient wireless systems.

This particular grocery chain firmly believes that maintaining food quality is their top priority. Recent changes in the Food Safety and Modernization Act establish that it should be every chain’s top priority. Solutions such as the Emerson Wireless Sensor System allow chains to monitor free-standing refrigerated equipment in their stores, ensuring proper merchandise temperatures and giving customers the confidence in the retailer’s ability to consistently provide fresh and nutritious products — regardless of where product is located.

 

 

 

 

How to Create a Machine-learning Model in Your Enterprise in Six Simple Steps

JohnWallace_Blog_Image John Wallace | Director of Innovation, Retail Solutions

Emerson Commercial & Residential Solutions

This blog summarizes an article from our most recent E360 Outlook, entitled Applying Machine Learning for Facility Management.” Click here to read it in its entirety.

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Machine learning is a subfield of computer science that refers to a computer’s ability to learn without being programmed. Although machines should be able to learn and adapt through experience, human interaction is still needed to produce desired results. Today, many facility management applications — for refrigeration and HVAC systems, for example — have taken a supervised learning approach that utilizes historical data to train an algorithm and predict an outcome from a series of inputs.

To create your own supervised-learning model, businesses can take these relatively simple six steps:

  1. Define the problem. It’s critical to have a keen idea of the problem you are trying to predict or solve, and establish well-defined goals of the application.
  2. Develop a data collection strategy. Data collection is achieved via inputs from a variety of information, including: temperatures, pressures, on-off activities (from motors, etc.) as well as the actions that result from these inputs. Your goal will be to predict the action that will occur for a given set of inputs. Data will be used to both train the learning model and validate the model’s performance.
  3. Create machine-learning models. Based on the training data collected and available inputs, you can create a machine-learning model that uses specific algorithms (math) to predict an action. Since different types of models may perform better or worse for a particular data set, you might need to create multiple models (different math) and then pick the one that performs best based on your data.
  4. Establish a standard. How closely does your model predict the action or result that came out of your training data? A perfect model would anticipate the result every time. While that usually doesn’t happen, the goal is to get as close as possible to achieving the desired results, and then use that model as a standard moving forward.
  5. Test the validation data. Based on the validation data from step two, evaluate the performance of your model. If the validation data doesn’t match up, you may need to step back and select a different training model, and then validate the data again. This is an intricate process. When and if the results do not match expectations, you may have to start from the beginning. Make sure you are collecting the right types of data before running the process again.
  6. Utilize the machine-learning model. Upon completion of your efforts, you should have a model that can be used to predict an action or result based on the available inputs. At some point, input parameters may change or another system modification may be required; in this event, you will need to go back periodically and update the model based on new data.
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