In my last post, I talked about some of the pros and cons of both the “% discards recycled” metric and the “per-capita recycling metric”.
One of the biggest problems with recycling rates, and one of the reasons that has led to people to call for their demise has been their misuse.
In a previous post, I touched on my frustration that recycling rates are too often not used for benchmarking – which is their real value. Instead, too often they are misused for bragging purposes and artificial compliance goals. However, rather than continue to lament that form of misuse, let me focus on another: their misuse as a singular metric. At the risk of this sounding like a pun, the strength of these metrics is in their numbers. They are far more revealing when used in combination than when used individually.
For example, one of the strengths of the % discards recycled metric is that it is consumption neutral. The metric works no matter how much you consume or how little. If you envision a pie chart, the metric doesn’t care how big or how small the pie is, only the size of the recycling slice relative to the rest of the pie. The problem is that alone, it can be tricked by waste reduction efforts. Let’s say as an example that you are using the % discards model to evaluate your paper recycling program. Let’s further say that your paper recycling rate fell from 20% down to 16%. Is that a failure of the recycling program? It depends. The problem is that you need to combine that % discards with another metric to get more info in order to find out.
Using the falling paper recycling rate example from the previous paragraph, there are really two primary potential causes for the drop in recycling rate. One is that you are doing a worse job of collecting paper for recycling. The other is that you have a successful paper reduction program that is resulting in there being less available paper to be recovered for recycling. You may be getting all of the paper that there is to recycle, but if people are using less paper, say through double sided copying or web-based phone directories (and still using the same amount of everything else), your recycling rate could still drop.
So to get a better picture, take a complimentary look at your per capita trash number. If your recycling rate is dropping, but your per-capita trash number is increasing, you are likely looking at a situation in which your recycling program is suffering and more recyclables are ending up in the trash. If your recycling rate is dropping but your per-capita trash numbers are also decreasing, you are likely looking at a situation in which the drop is the result of waste reduction efforts.
Conversely, say you start by looking at your per capita numbers and see your per capita paper number increase. That could be the result of a few factors. If you look at your % discards recycled and find that they are also increasing, then chances are that your increases are due to an improvement in the recycling program. If your per capita numbers are increasing but your % discards recycled numbers are flat (or even decreasing), chances are that your per-capita increases are due to an overall increase in consumption rather than a specific improvement in recycling behavior.
The same thing is happening right now on the bottle & can side via package lightweighting. An aluminum can today has less aluminum and weighs less than it did 20 years ago. So too does a plastic bottle. Thus, if you collect the same number of cans and bottles that you did a decade or two ago, you could find your bottle & can recycling weights down at least 10-20%. If you see a drop in your bottle & can recycling numbers, check your per-capita trash tonnages. If they are going up, I’d start looking for places that people have started throwing recyclables into the trash. If the trash numbers are also going down, chances are that your issue is related to lightweighting.
If you are a college campus, a great way to use this combination of metrics is to look at yourself during different times of the year. If you look at per-capita generation of both waste and recycling, you will typically start to see a distinct seasonal flow. On a residential campus, you will typically see an increase in per-capita generation when the students move in and bring all of those cardboard boxes with them. In May, your per capita generation will likely go up as the students move out of their rooms and get rid of all of the stuff that didn’t fit into the trunk of the car or the move in bag when they go home for the summer. During the summer break and January break (if you have one), you will typically see a big dip in routine generation (though often a surge in project-related wastes). If you only used per-capita data to track your program results throughout the year, you would find yourself not as much tracking conscious behavior as you would just tracking the seasonal flow of a college campus. Combining that per capita metric with a % discards recycled metric will often reveal significant opportunities to improve your recycling program.
I used to work with a school that did a nice job of recycling throughout the fall. However, every year, I used to watch their % discards plummet during the winter and in May. Seeing that got me to investigate a little further. Come to find out, the Facilities folks used to pull that recycling crew all winter to do snow removal and every May to assist with student move-out and Commencement preparation. By the time they got back on the recycling truck to go around to pick stuff up, the custodians had gotten frustrated at the lack of pickups and started throwing everything into the trash (which was still being picked up daily even in the snow). By adjusting some schedules and investing in better collection equipment (that didn’t require as much manual lifting by a crew already exhausted from snow removal and end of year efforts), we saw huge improvements and their seasonal recycling percentages actually not only started to match, but even exceed the percent discards recycled during other periods of the year.
When it comes to using metrics to evaluate your recycling numbers, don’t choose just one. The strength of those metrics is in their numbers.