Tons of plastic waste enters the Great Lakes every year. So where does it end up?

The Chicago shore of Lake Michigan. Image: J. Crocker/Wikimedia Commons.

Awareness is rising worldwide about the scourge of ocean plastic pollution, from Earth Day 2018 events to the cover of National Geographic magazine. But few people realise that similar concentrations of plastic pollution are accumulating in lakes and rivers. One recent study found microplastic particles – fragments measuring less then five millimeters – in globally sourced tap water and beer brewed with water from the Great Lakes.

According to recent estimates, over 8m tons of plastic enter the oceans every year. Using that study’s calculations of how much plastic pollution per person enters the water in coastal regions, one of us (Matthew Hoffman) has estimated that around 10,000 tons of plastic enter the Great Lakes annually. Now we are analysing where it accumulates and how it may affect aquatic life.

No garbage patches, but lots of scrap on beaches

Plastic enters the Great Lakes in many ways. People on the shore and on boats throw litter in the water. Microplastic pollution also comes from wastewater treatment plants, stormwater and agricultural runoff. Some plastic fibres become airborne – possibly from clothing or building materials weathering outdoors – and are probably deposited into the lakes directly from the air.

Sampling natural water bodies for plastic particles is time-consuming and can be done on only a small fraction of any given river or lake. To augment actual sampling, researchers can use computational models to map how plastic pollution will move once it enters the water. In the ocean, these models show how plastic accumulates in particular locations around the globe, including the Arctic.

When plastic pollution was initially found in the Great Lakes, many observers feared that it could accumulate in large floating garbage patches, like those created by ocean currents. However, when we used our computational models to predict how plastic pollution would move around in the surface waters of Lake Erie, we found that temporary accumulation regions formed but did not persist as they do in the ocean. In Lake Erie and the other Great Lakes, strong winds break up the accumulation regions.

Three-dimensional transport simulations of particle movement in Lake Erie, based on water current models developed by the National Oceanic & Atmospheric Administration.

Subsequent simulations have also found no evidence for a Great Lakes garbage patch. Initially this seems like good news. But we know that a lot of plastic is entering the lakes. If it is not accumulating at their centers, where is it?

Using our models, we created maps that predict the average surface distribution of Great Lakes plastic pollution. They show that most of it ends up closer to shore. This helps to explain why so much plastic is found on Great Lakes beaches: in 2017 alone, volunteers with the Alliance for the Great Lakes collected more than 16 tons of plastic at beach cleanups. If more plastic is ending up near shore, where more wildlife is located and where we obtain our drinking water, is that really a better outcome than a garbage patch?

Average density of simulated particles in the Great Lakes from 2009-14. Notice that there are no patches in the middle of the Lakes, but more of the particles are concentrated near the shores. Image: Matthew Hoffman/creative commons.

Searching for missing plastic

We estimate that over four tons of microplastic are floating in Lake Erie. This figure is only a small fraction of the approximately 2,500 tons of plastic that we estimate enter the Lake each year. Similarly, researchers have found that their estimates of how much plastic is floating at the ocean’s surface account for only around 1 per cent of estimated input. Plastic pollution has adverse effects on many organisms, and to predict which ecosystems and organisms are most affected, it is essential to understand where it is going.

We have begun using more advanced computer models to map the three-dimensional distribution of plastic pollution in the Great Lakes. Assuming that plastic simply moves with currents, we see that a large proportion of it is predicted to sink to lake bottoms. Mapping plastic pollution this way begins to shed light on exposure risks for different species, based on where in the lake they live.

According to our initial simulations, much of the plastic is expected to sink. This prediction is supported by sediment samples collected from the bottom of the Great Lakes, which can contain high concentrations of plastic.

Three-dimensional transport simulation in Lake Erie. Particle color represents depth below the water surface: the bluer the particle, the deeper it is.

In a real lake, plastic does not just move with the current. It also can float or sink, based on its size and density. As a particle floats and is “weathered” by sun and waves, breaks into smaller particles, and becomes colonised by bacteria and other microorganisms, its ability to sink will change.

Better understanding of the processes that affect plastic transport will enable us to generate more accurate models of how it moves through the water. In addition, we know little so far about how plastic is removed from the water as it lands on the bottom or the beach, or is ingested by organisms.


Prediction informs prevention

Developing a complete picture of how plastic pollution travels through waterways, and which habitats are most at risk, is crucial for conceiving and testing possible solutions. If we can accurately track different types of plastic pollution after they enter the water, we can focus on the types that end up in sensitive habitats and predict their ultimate fate. The Conversation

Of course, preventing plastic from entering our waterways in the first place is the best way to eliminate the problem. But by determining which plastics are more toxic and also more likely to come into contact with sensitive organisms, or end up in our water supply, we can target the “worst of the worst”.

With this information, government agencies and conservation groups can develop specific community education programmes, target cleanup efforts and work with industries to develop alternatives to products that contain these materials.

Matthew J. Hoffman, Associate Professor of Mathematical Sciences, Rochester Institute of Technology and Christy Tyler, Associate Professor of Environmental Science, Rochester Institute of Technology.

This article was originally published on The Conversation. Read the original article.

 
 
 
 

The best bike maps are made by volunteers

A cyclist in Vancouver, Canada. Image: Getty.

Not all bike routes are equal. Some places that are marked as bike routes on a map feel precarious when traversed on two wheels, including shoulders covered in debris and places where you can feel the wind from speeding cars.

North American cities are building more bicycling routes, by adding on-street painted lanes, physically separated cycle tracks, bicycle-only or multi-use paths and local street bikeways. These different kinds of routes appeal to different types of users, from the interested but concerned cyclist to the keen road rider.

Despite this boost in biking infrastructure, a city’s website may not immediately reflect the changes or it may lack important information that can make cycling safer or more enjoyable.

Web-based maps that allow people to add information about bike routes give riders detailed data about the type of route, what it might feel like to ride there (do you have to ride close to cars?) and where it can take them (for example, shopping, work or school).

They can also tell us which cities are the most bike-friendly.

Measuring bike routes

We set out to assemble a dataset of bike routes in Canadian cities using their open data websites. But we found it was nearly impossible to keep it up-to-date because cities are constantly changing and the data are shared using different standards.

A physically separated cycle track in Victoria, British Columbia. Image: E. Gatti (TeamInteract.ca).

The solution was OpenStreetMap, which creates and distributes free geographic data. Anyone can add data or make edits to OpenStreetMap, whether they want to build a better bike map or make a navigation app.

We looked at OpenStreetMap data for three large cities (Vancouver, Toronto and Montréal) and three mid-sized cities (Victoria, Kelowna and Halifax) in Canada.

Not only did the data in OpenStreetMap agree reasonably well with the cities’ open data: in many cases it was more up-to-date. OpenStreetMap tended to include more local details such as where painted bike lanes ended and often marked the short cuts connecting suburban streets.

How did OpenStreetMap measure up?

Our analysis focused on how well different types of routes were mapped. We measured cycle tracks (which physically separate bikes from motorised traffic), on-street painted bike lanes (which use painted lines to separate bikes from motorised traffic), bike paths (which are located away from streets) and local street bikeways (which include traffic-calming features and where bicycling is encouraged).

Painted bike lanes are the most common type of route and also the most consistently well mapped. This makes sense, because the definition of a painted bike lane may be clearest across time and place. There is also a straightforward way for volunteers to tag it on OpenStreetMap.

But it was harder for us to distinguish cycle tracks from on-street painted lanes or paths (bicycle-only or multi-use) using OpenStreetMap. Local street bikeways were challenging to identify because of the wide range of ways cities design these kinds of routes along residential roads. Some use traffic-calming measures such as curb extensions, traffic islands, speed humps and raised traffic crossings to slow vehicle traffic and encourage safety, or greenery, reduced speed limits and bike-friendly markings on signs and the road surface.

Correspondence between OpenStreetMap and Open Data for categories of bicycling infrastructure. Image: author provided.

Bicycle routes that are physically separated from motor vehicles and pedestrians, like cycle tracks and bicycle-only paths, have the greatest benefits for bicycling safety and encourage bike use.

Ease of access to bicycle routes is important to a city’s overall bicycle friendliness, but there are other important things to consider including the distance to destinations, the number, slope and length of hills, number of riders and how the transportation culture of a city can influence its safety.


Bike-friendly Canadian cities

Our results showed that Montréal has the greatest total distance in cycle tracks in Canada. As cities continue building more bicycle routes, researchers and planners can use OpenStreetMap to measure these changes on the ground.

The perfect bicycle map is up-to-date, covers the entire globe and gives riders an idea of the kinds of experiences to expect on different trails, roads and paths. People cycling in cities can contribute to the high-quality geographic data needed to understand changes in bicycle friendliness.

But OpenStreetMap is only as good as its contributions. The exciting thing is that anyone who wants a better bike map — city planners, researchers and everyday riders — can join the bike-mapping revolution by logging in to OpenStreetMap and mapping the features that are important to bicyclists.

The Conversation

Colin Ferster, Post-doctoral fellow, University of Victoria and Meghan Winters, Associate Professor, Faculty of Health Sciences, Simon Fraser University

This article is republished from The Conversation under a Creative Commons license. Read the original article.