If I own 100 gas stations for 20 years, what is my Expected Environmental Loss (EEL)?
For an environmental consultant to provide some sort of measure of “expected” environmental risk and related financial loss, as opposed to the worst-case risk, is extremely valuable to real estate investors. Real estate investors constantly balance risk and reward. The environmental consultant tends to speak in worst-case-scenarios. Our clients need the worst-case-scenario, but would also greatly benefit from the most-likely-scenario—or the EEL.
Data exists to provide pretty good estimates, right? There is tons of data out there. For the gas station scenario, we could grab data from 1,000 State UST Fund Sites, add up the expenditure and divide by 1,000. I have been told by the California UST Fund that the result is $167,000. Can we call that the EEL?
One could argue that by definition these sites are sites with releases, so the derived EEL would be skewed too high, or that releases in the future should be less common and smaller than the past. Fair arguments, but I would argue that some quantitative measure is better than none.
Let me layout my definition of the EEL—I recently coined this term. The EEL is all potential environmental costs, multiplied by the percent likelihood of that scenario coming to pass. Here is an example of how to calculate it:
Let’s use the following site as a make-believe case study. A property was used as a gas station for the past 20 years, with no Phase II data, in a given state. In that state, we were provided the following loss data from a major oil company on 100 sites that they owned in this state:
30 Gas Stations: Zero Loss
30 Gas Stations: Minor Leak. Average loss for this bucket is $80,000
30 Gas Stations: Substantial Leak. Average loss for this bucket is $200,000
10 Gas Stations: Huge release. Big plume. Average Loss for this bucket is $800,000
Total Loss = (30x$0) + (30x$80,000) + (30x$200,000) + (10x$1,400,000) = $16,400,000
EEL = Total Loss/Sample Size =16,400,000 /100 = $164,000.
Realize that this math is on a make believe data set, but I think that we as an industry could do a few studies and define this word.
Now if you are working in this make believe state on the gas station with no existing subsurface data, you could site that the Average EEL for gas stations in this state is $164,000. Then just like structural engineers adjust PMLs for unique characteristics, the environmental professional could adjust the EEL up or down based on site specific data, such as groundwater, soil type, or proximity to sensitive receptors. The end result would be a bit inexact for sure, but would give clients a great order of magnitude appreciation of risk.
Gas stations often represent a bona fide recognized environmental condition, but consider how the data set looks for a much softer REC. For example, how might the buckets look if we are talking about a hydraulic lift? This data is harder to find, but any of us who have been in the business for 20 years might be able to offer a good guess or even a valuable data set. Just for fun let’s speculate what that example looks like:
Assume a guy owns 100 sites with 3 hydraulic lifts on each site. Assume for simplicity that he did not use other chemicals in the course of his business. I am guessing the data set would look like this:
50 Sites: Zero Loss
20 Gas Stations: Minor Leak. Average loss for this bucket is $5,000.
20 Gas Stations: Substantial Leak. Average loss for this bucket is $20,000
10 Gas Stations: Huge release. Big plume. Average Loss for this bucket is $100,000
Total Loss = (50x$0) + (20x$5,000) + (20x$20,000) + (10x$100,000) = $1,500,000
EEL = Total Loss/Sample Size =$1,500,000 /100 = $15,000.
So if I had these data sets available, I could give my clients far more quantitative advice that the binary REC / no-REC advice.
I would tell the gas station-buying client that the EEL is $164,000 and that the reasonable worst case scenario is $1,400,000.
I would tell the hydraulic lift-buying client that the EEL is $15,000 and the reasonable worst case scenario is $100,000.
Contact me with questions or for a consultation at 800-419-4923.