Managing Waste Flow at Landfills

The Mississippi Basin Model (MBM) was a reproduction of the Mississippi River drainage basin, built at a horizontal scale of 1:2000 and a vertical scale of 1:100. During its years of operation, it was the largest small-scale working model in the world. Built near Jackson, MS, by the Army Corps of Engineers in the 1940s, the initial earthwork for the MBM was carried out by German POWs from nearby Camp Clinton. It was completed in 1966.

Using the MBM, engineers could simulate runoff from anywhere within the Mississippi River basin and then predict the impact at critical downstream locations, including dams, bridges, and levees. By the 1980s, the model was superseded by computer-modeling techniques, but it is widely agreed that the MBM had been a success, helping to solve numerous flood-control problems and thus saving lives.

The concept of tracking hydrologic flow from various watersheds to predict the flow at critical points along the route can be applied to other types of flow. Consider how trash, flowing to a landfill from within one or more waste sheds can affect the operation at critical downstream locations, such as the scale house, the tipping pad, or the daily cell. The ability to model the inbound wastestream is a vital step toward improving the efficiency of a landfill’s operation, and the results can help a manager efficiently schedule staffing, equipment, and materials for various locations throughout the day.

In a river drainage system, the flow capacity varies—some portions of the river can simply handle less flow than others. In the same way, a landfill’s flow capacity often varies at specific points along the way.

Let’s look at a typical example and then evaluate how the various flow capacities affect the overall operation.

Trash haulers arrive at the landfill entrance in a random but somewhat predictable pattern. During a peak period—late morning, for example, when route trucks complete their early runs—the flow of the inbound wastestream may exceed the production capability of the scale house. When that happens, vehicles will begin to stack up. Depending on the demographics of a landfill’s service area, significant stacking may also occur during the weekends when lots of self-haul vehicles arrive at the site.

Thus, from a “flow” perspective, the scale house is typically the first in a series of constraints on the inbound wastestream.

After passing the scale house, waste goes to the tipping pad (unloading area), where the next constraint often occurs. At this point, the width of the tipping pad usually limits the number of vehicles that can unload at a time. Once the tipping pad reaches capacity, vehicles must wait in line until the appropriate unloading slot is available.

When waste is dumped at the edge of the tipping pad, it faces a closely connected series of constraints. These, often unseen by the untrained eye, are perhaps the most critical ones in terms of overall landfill efficiency. They include pushing, spreading, compacting, and keeping the unloading area clear.

We’ll consider each of these constraints in detail, looking at how they can affect a landfill’s operation and exploring ways to increase the flow rate.

There are also many outside influences that can affect the flow rate of inbound vehicles. Such factors as traffic jams, construction projects or weather-related delays do have an impact, but here we’ll just be focusing on constraints at the landfill.

Scale house—The scale house is the first funnel point for inbound vehicles. And while vehicles might arrive at the landfill in a random pattern of singles and groups, they will leave the scale house at a more uniform rate.

The flow rate into the landfill can vary widely, depending on the type of load and the processing system used by the scale house. For example, self-haul vehicles that pay-as-they-throw, typically are slowest because of the need to evaluate and price the load (by weighing or measuring), process the payment, make change, and finally print a receipt. The time can be increased even more if vehicles are required to also weigh as they exit the landfill. These transactions can take two to four minutes each.

To shorten the transaction time for self-haul vehicles, many landfills assign a standard charge rate for specific types of self-haul vehicles in order to shorten the transaction time. For example, there may be a rate for small pickups, another for full-size pickups, and as many more as needed to cover the range of vehicle types. Those standard rates are often based on weight survey data and so provide an accurate estimate of inbound tonnage—without having to weigh every single load.

Faster processing generally occurs with commercial vehicles. Because their tare weight is known, these trucks must stop for an inbound weight only. Transaction time is also shortened because most commercial vehicles are billed against an account and the driver doesn’t have to stop and pay for each load.

The fastest processing occurs where a weigh-in-motion scale is combined with a scanning system to record every inbound commercial load. With these automated systems, the driver swipes a plastic ID card through a reader (like a credit card), or an electronic reader scans an ID unit on the truck. If the tare weight of the truck changes with each load (e.g., a rolloff truck with different boxes), each box may also have its own ID device. Some of the more sophisticated systems also include cameras allowing photos of the vehicle, the load, and the license plate to be attached to the invoice.

Every scale-house system, regardless of the type, causes some dampening of the inbound wastestream. Generally, the slower the transaction time, the greater the dampening effect. Slowing the inbound wastestream helps reduce the stress on the landfill crew by lessening the large swings in tonnage. On the downside, when transaction times are slow, vehicle stacking can become a problem.

As an example, let’s assume the scale house can perform one transaction per minute and each load weighs, on average, 5 tons. Based on these figures, the scale house could process approximately 300 tons per hour. If split into quarter-hour increments, the scale house production rate works out to 75 tons per quarter-hour. Thus, regardless of the inbound flow rate, the scale house can release vehicles at a maximum rate of 75 tons per quarter-hour.

Access Roads—The design and condition of a landfill’s access roads also affects the flow rate of inbound waste vehicles. And, whether intentional or not, narrow or poorly graded roads will slow traffic and further dampen peaks in the waste flow.

The effect of a landfill’s access roads on the overall flow rate is minimal. Generally, unless the access roads are in extremely poor condition, there is little additional dampening. Conversely, as vehicles leave the scale house on their way to the tipping pad, there may actually be some regrouping as faster vehicles catch up with slower ones.

In regard to our example, we’ll ignore any impact on production imposed by the access roads.

Tipping Pad—The tipping pad, also referred to as the unloading deck, is typically a major bottleneck to traffic flow. But this isn’t all bad. In fact, it can serve as an opportunity to regulate waste by type and quantity in order to improve the overall cell construction process.

Two opposing forces typically define the width of the tipping deck. The first of these is the need to keep the tipping pad as narrow as possible, thereby constraining the width of the active face and reducing litter and deck cleanup requirements. The second is the need to have it wide enough to accommodate all of the inbound vehicles as they arrive.

Typically, the tipping pad is kept to a relatively narrow width, closely matching the width of the face. This means that during peak periods, some vehicles may have to wait in line until a slot becomes available. The wait time may also be affected by a vehicle’s type of waste.

In most cases, daily cells are constructed in stages, with various types and amounts of waste contributing to each stage. For example, when portions of the cell are being completed, the operators look for wet, homogeneous trash—the kind normally found in packer trucks. Knowing this, a skilled traffic director, also known as a spotter, may bring a packer truck to the front of the line and allow it to unload before other vehicles, even if the other ones arrived first. This selective dumping will cause some dampening of the waste flow—sometimes along with some impatience by drivers who had to wait a few minutes.

Overall, the production rate on the tipping pad is defined by the following factors, shown with example values:

• Pad width (150 feet)
• Average unloading time (5 minutes)
• Width required per vehicle for dumping and buffer (30 feet) and
• Average tons per load (5 tons)

Thus, in our example, the throughput production rate of the tipping pad is approximately 272 tons per hour, or approximately 68 tons per quarter-hour.

Load checking—Depending on a landfill’s specific policy, load checking can affect the flow rate of inbound waste a lot or not at all. In most cases, the effect of load checking is insignificant.

Again, in regard to our example, we’ll ignore any impact on production imposed by load checking.

Dozer production rate—The flow capacity is, at every stage, based on the production rate, but like other activities, the dozer’s production rate is not set in stone. In fact, there is more flexibility in regard to dozer production than most landfill operators recognize. We’ll look at some of that flexibility; but first, let’s set a baseline production rate.

An empirical baseline is typically the easiest to obtain and usually reflects site-specific performance. Here’s a common approach: Observe the dozer as it pushes waste from the tipping pad to the cell. Record the time it takes for the dozer to make a complete cycle of gathering, pushing, spreading, and returning. Do this several times to get an average and then correlate that average to the rate of inbound tonnage. One easy method is to identify a specific truckload with the dozer’s push and then obtain that load’s tonnage from the scale-house records. The goal is to establish a production rate for the dozer measured in tons per hour.

As noted earlier, there are many variables that can affect the dozer’s production rate. These include the following:

• Dozer size and type—The size of the dozer is an obvious and significant factor in defining productivity. However, because trash is a relatively lightweight material, the size of the dozer’s blade is often a more important factor. Very often, a dozer’s productivity is limited not by how much weight it can push, but by how much trash (volume) it can gather and hold.
• Slope—Whether uphill, flat or downhill, the slope a dozer travels is in most cases the single most important factor in regard to dozer productivity. A dozer’s productivity can be cut in half when pushing up a 3:1 slope—or it can double when pushing down that same slope.
• Operator skill—The difference between a skilled operator and one who isn’t can often result in a variation in productivity of 20% to 40%.
• Operating method—An individual operator’s method of operation, or “style,” can have a tremendous impact on how productive he or she is. Generally, operators that are more aggressive will move continuously and at greater speed than operators with a quiet, passive personality. But in the long run, the operators who take time to think will generally outperform all others. Here’s an example: When pushing waste from the tipping pad to the face, some trash will inevitably fall from the load and be strewn along the push path. Some operators react to that spilled trash like Felix Unger would react to a dropped napkin: Messes drive him or her crazy. So for every individual production push, there may be two or more cleanup pushes. On the other hand, if Oscar Madison were running the dozer, that spilled trash would be seen as not problem. If you’re struggling to decide which half of this odd couple is best, consider the following analysis. Often, leaving that spilled trash alone until the end of the day offers some benefits. As the depth of the spilled trash increases, the dozer will begin to receive the benefits of slot dozing. When dozing in a slot, a dozer can push more material because material (i.e., trash) is less likely to spill from the edges of the blade. Also, by limiting the dozer’s pushes to production pushes and avoiding all of those wimpy cleanup pushes, the number of dozers can log fewer work hours—and still get the work done. When it comes to pushing trash, Oscar knows best: When pushing trash to the face, don’t be a clean freak. Let’s assume, for the sake of our example, the following in regard to the dozer’s productivity: Cycle time = 1.82 minutes per load; payload = 9 tons; cleanup pushes = three production pushes for every cleanup push. Based on these parameters, the dozer’s production rate in our example is 224 tons per hour, or 56 tons per quarter-hour.

Compactor Production Rates
As we’ve analyzed the waste flow through the system, you may have noticed a trend. From scale house to tipping pad to dozer, the wastestream becomes progressively more restricted. There are many variables, and this isn’t always the case, but it is common. Ask your crew members if they typically feel a crunch at the end of the day as they try to close up the operation. They’ll either laugh or cry, but either way the answer will likely be “Yes.”

But nowhere is the flow rate more critical than at this final box in the flowchart: the compactor. Because the compactor’s performance has such a direct bearing on airspace utilization, the flow at this stage should be steady and level. The optimum rate is based on many factors, but a ballpark estimate can be provided with the following equation:

T = (W – 20,000) ÷ 750
Where:
T = average tons of waste per hour
W = weight of compactor (in pounds)

Let’s suppose you are using the industry’s largest compactor, an Al-jon Impact 600, weighing 126,000 pounds. According to our equation, the machine could handle over 141 tons per hour. Again, breaking this into 15-minute increments yields a production rate of just over 35 tons per quarter-hour.

Summary
The production rates we’ve used in this example are shown in Table A.

Table B shows the inbound and outbound flow rates at several constraints including scale house, tipping pad, dozer, and compactor.

Whenever the waste flow exceeds the production rate (throughput) of a given constraint, the excess flow begins to build up. At 11 a.m., for example, when inbound traffic flow exceeds the processing capability of the scale house, vehicles will begin to stack. In extreme cases, a significant number of vehicles can be waiting in line. Please note that this table is expressed in tons, not number of vehicles. It’s vital that the landfill manager and staff understand the effects of these bottlenecks and then use that knowledge to plan and direct the operation.

Figure 1 shows graphically when bottlenecking occurs at certain points in the system. For example, at 11 a.m., the inbound wastestream exceeds the production capability of the scale house. As a result, the excess tonnage is deferred to the next hour, when the waste will be handled at the maximum rate until catching up with the backlog of waste. Like a wave, the same thing happens at each constraint. It is noteworthy that throughout the system, most constraints are “caught up” within an hour or two, but the compactor falls behind at 9:45 a.m. and doesn’t get caught up until 6 p.m. This is a common scenario, where the compactor is the critical bottleneck and is under unrealistic pressure to wrap everything up at the end of the day. Based on the same information, but showing the results in another perspective, Figure 2 shows the amount of trash (in tons) waiting at each point in the system. Again, while there is a backlog at all stations during the late-morning peaks, the compactor is clearly the main bottleneck, with a backlog of trash throughout most of the day.

Using this type of analysis, based on inbound tonnage and the production rate at each constraint, one can gain a clear understanding of the waste flow throughout the landfill operation.