The following text is an abridged and edited transcript of the video that follows at the end of this post.
Today we’re going to talk about why all emission factors aren’t the same and, more importantly, what you can do about that.
The Easiest and Cheapest Way to Determine an Emission Factor [00:25]
One of the easiest and cheapest ways to determine an emission factor is to simply look it up. As mentioned in a previous post, there are four ways to determine an emission factor:
- Look it up (See our post on where to find emission factors.)
- Conduct an engineering calculation
- Conduct a mass balance
- Conduct a direct measurement, such as a source test
However, although looking up an emission factor is usually the cheapest method, it’s also the least accurate. Let me explain why it’s so inaccurate — and what you can do about it.
The AP-42 Database [01:35]
The EPA’s AP-42 database is the go-to source for finding emission factors. However, as I’m about to explain, some of the emission factors may not work or may not be suited for use in your particular situation.
Potential Problems With Using AP-42 [02:18]
As a general rule, stay away from using AP-42 emission factors for permitting because you’ll sometimes be responsible for demonstrating compliance with an emission rate. Other times, the emissions calculated using an AP-42 emission factor may be higher or lower than the required emission limits within your air district.
And when it comes to filing your annual emission report (AER), the amount you emit is directly related to the fees you pay. If you have a high amount of emissions, you’re going to pay high fees. So, if you have an inaccurate emission factor, or one that’s not suited to your process, you could be throwing money down the drain.
Another reason is compliance. Air-quality rules and regulations are developed for a certain region of the country. The South Coast Air Quality Management District has some of the most stringent air-quality regulations in the nation, so you can expect your emission levels to be much lower than average. If you have a low emission limit noted on your permit and you then demonstrate compliance to that emission limit using an AP-42 emission factor that overestimates your emissions, you could find yourself in a compliance situation.
Why Does AP-42 Overestimate Emissions? [03:57]
There are a number of reasons that AP-42 emission factors overestimate emissions.
As a little bit of background, these emission factors are developed from source tests that are done in actual facilities. And the emissions coming out of the stack at the time of the test is dependent on weather, the process conditions, and the operating parameters, among others. So, testing at one plant may not produce the same emissions profile as that of another plant where conditions are different. This leads to variability between the emissions from different facilities within the same source type.
Because of the variability, the data used to develop a given emission factor tends to overestimate emissions factors — and that’s very important to keep in mind.
Ranking Emission Factors [05:17]
To account for the variability, the EPA ranks the emission factors found within the AP-42 database. This ranking serves as a guide to determine the suitability and the overall robustness of an emission factor to serve in a specific situation.
Ranking an emission factor is a two-step process that is largely dependent on professional judgment. The process involves first looking at the data quality and then giving the data set an overall appraisal as to the suitability of both the emission factor and the data set to serve as a standard for all of these facility types. It’s largely subjective. During the ranking process, the engineers look at the number of observations, the numbers of tests, and the test methods themselves. Then the engineers ask themselves such questions as:
- Are they reputable test methods?
- Are they one-off test methods?
- Are these test methods ones we’ve seen before?
- Were there any anomalies during the test?
There’s a lot of variability when doing a source test, and that too gets folded into the overall ranking process.
Be Cautious About Using an AP-42 Emission Factor [07:10]
You must exercise care when selecting an emission factor for your specific situation. First, look at the ranking, and then examine the specific data that was used to develop that emission factor. That way you’ll know that the data, or the situation for which this emission factor was developed, is similar to your situation.
Sometimes an emissions factor is determined by the results of a single source test. The source may not even be similar to yours, or it may be 20 or 30 years old, compared to your brand-new, technologically advanced equipment.
Now, without further ado, here are the five rankings for AP-42 emission factors.
Excellent (A) [10:02]
An excellent ranking means that the data used to produce the emission factor was good and robust. More importantly, it has lower variability, which means it’s a good example of a random facility or a random piece of equipment, and if we sample that one piece of equipment, its emissions are going to be somewhat similar to the situation used to develop that emission factor.
Above Average (B) [10:37]
You may have robust data, but there’s also a sense of some variability within the data set. It’s not entirely clear if this particular data set is a representative sample of the facilities out there. There could be variations because of anomalies, test data, weather, process operation, or operating parameters. When variability starts to occur, the ranking starts to drop.
Average (C) [11:14]
A C ranking means the data quality is poorer than that found in A or B, and it’s not entirely clear if the data represents a good example of a random facility. Again, as we move down the rankings, we see data quality degrading and, more importantly, variability increasing.
Below Average (D) [11:42]
A D ranking indicates problems with data quality, in which case there’s reason to believe that the data does not represent a random facility. Again, very high variability means that this data set may be specific to one facility in one part of the country, and then if we try to replicate that data in another part of the country, we may not get the same results. In that case, variability would start to increase.
Poor (E) [12:10]
An E ranking indicates unacceptable data quality. Not only is the data itself terrible, but it also doesn’t represent a random facility. That means that the emissions factor could have been determined from the results of a one-off test conducted 40 years ago. The EPA may have chosen to include it in its database because it was the only data they had.
In practice, high variability can also be present when you have “interesting” source types like deep fryers, which are notorious for their high variability. If you pick an emission factor out of AP-42 for a deep fryer, more than likely it will be of low quality, which means you’re likely to overestimate emissions.
What to Do If You Have a Low-Quality Emission Factor [13:28]
If you have low data quality but need to calculate emissions, you first need to determine what you’re using the data for. If it’s being used for an important reason, you’ll want to think twice about using an emission factor based on poor-quality data. Next, determine if you can conduct an engineering calculation using site-specific data to estimate the emissions from your process. Anytime you can use actual data from your facility, you’re already ahead of everyone else.
If that doesn’t work, consider source-testing the piece of equipment. Depending on your reason for needing the emissions, it could be a wise investment to have the most accurate results.
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Correction from the video: The abridged transcript has been updated to reflect the fact that the “poor” ranking is given an “E” instead of “F.”
