Rubbish Litter Ocean Research Project

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My name is Bryan (I also go by Pocket), and I live in San Diego, California. I came across Rubbish on Reddit when they posted an AMA on Earth Day. During the start of quarantine, I was hoping to do something better with my time than staring at the wall and reached out to see if I could help with a project.

I used the Rubbish app to categorize the type and amount of litter I found diving in San Diego two river mouths over a period of 7 weeks. I found plastic to be the biggest culprit polluting our oceans. I plan to encourage others to help clean river mouths/beaches with my research.

One person can make a big difference, there was less average litter by the end of the 7 weeks in both beaches!

A student in diving gear underwater picking up floating trash. A student holding a small fish that he caught
Diving for “treasure”, and cleaner waters = cleaner food

Read my research below!

Litter Composition and Amount Entering Two River Mouths: Del Mar Dog Beach and Cardiff State Beach (San Diego, California)

Bryan “Pocket” Kaleta and the rubbish.love team, Jun 2020-Aug 2020

Abstract

Using the Rubbish.love app, my goal was to categorize the type and amount of litter going into two San Diego river mouths for 7 weeks. I found that the biggest contributor to litter in river mouths was plastic, followed by tobacco cigarettes. Both river mouths had less average litter by the end of the 7 weeks, from 18 total pieces to 6 total pieces. Some limitations in the experiment include the inability to fully identify every piece of litter due to wind and human activity causing shifts in the 150 m x 150 m quadrant.

Introduction

River mouths are a significant pathway for litter, channeling refuse toward the Pacific Ocean. Other significant sources include transportation by boat, shore littering, and fishing. Plastics and microplastics have gained much attention in marine conservation efforts. Even though plastic debris in the marine environment is widely documented, the quantity of plastic pollution entering oceans is unknown. A worldwide study estimated that “1.15 and 2.41 million tonnes of plastic currently flows from the global riverine system into oceans every year, with the top 20 polluting rivers locating in Asia” (Lebreton, Van der Zwet, Damsteeg, Slat, Andrady, Reisser).

In addition, surfactants (detergents, cleaning agents, foamers) are well-known sources of pollution in river mouths, from the farm and industrial runoff. With plastics, microplastics, and surfactants mixing together in rivers, the effect can be detrimental to the ecosystem. A study done with Daphnia Magna and surfactant-microplastic mixtures, concluded that microplastics form aggregates that affect the motility of those organisms — ultimately causing death. Additionally, different types of surfactants and microplastics have other observed toxic effects. This study showed the potential for marine mammals and humans to be negatively affected by the various types of pollution in the ocean. Finally, all other types of litter, especially those that have not broken down, have the potential to hurt the ecosystem.

Methods

The Rubbish app acts as a platform wherein litter cleanup and community come together. Using the app and my hands, I logged weekly data from Del Mar Dog Beach and Cardiff State Beach, San Diego, California. To eliminate further variables, I collected data on Mondays or Tuesdays within the range of 12:00–1:00 P.M. PST. The average data collection time for each session was around 11 minutes. The Rubbish app allowed me to time my collection and categorize/photograph each piece of litter that I picked up (Figure 1). It posts a GPS tag and provides a pie chart summary for my collection (Figure 2). The app provides a nickname for collecting litter as “Rubbish Runs”. Each piece of litter was to be bigger than 1.0 inches x 1.0 inches.

Interface of the Rubbish app, showing how to categorize litter
Figure 1: App interface (categorizing litter through the phone camera)
Examples of what the "Rubbish summary" of your trash pickup session
Figure 2: App summary of the “Rubbish Run”

Results:

Most of the trash picked up was plastic.

A pie chart that show the types of litter picked up at Del Mar Dog Beach. Most of the litter, 44%, is plastic, followed by paper at 23%
Del Mar Dog Beach Litter Composition over 7 weeks (73 pieces total)

We can see a general downward trend in the amount of litter at the Del Mar River Mouth.

A line graph showing the pieces of litter over time at the Del Mar River Mouth over 7 weeks. There is a overall decrease in trash
Del Mar River Mouth Amount of Litter over 7 weeks (73 pieces total)

Another data point that plastic is the most common litter type next to the ocean.

A pie chart that show the types of litter picked up at Cardiff State Beach. Most of the litter, 45%, is plastic, followed by paper at 21%, which is similar to the Del Mar Dog Beach.
Cardiff State Beach Litter Composition over 7 weeks (102 pieces total)

Similar to Del Mar, there is less litter over time at Cardiff Beach.

A line graph showing the pieces of litter over time at the Cardiff State Beach over 7 weeks. There is a overall decrease in trash, similar to the Del Mar Dog Beach
Cardiff State Beach Amount of Litter Over 7 weeks (102 pieces total)

Statistics

Analyzed the difference of mean plastic between Cardiff State Beach and Del Mar Dog Beach using a two tailed, t-test. Weekly samples are independent, random samples of litter. N= sample size of 7 (representing 7 weeks). Df= 6. The t-value is -2.56074. The p-value is .024968. Because the p value is under 0.05, there is a significant difference in the mean value of plastic between Cardiff State Beach and Del Mar Dog Beach.

Conclusion

The original questions asked were, “What type of litter is going into the ocean, and how does the total litter in the two beaches change over time?” Overall, plastic is the most abundant type of litter, with paper and tobacco the second and third, respectively. The major difference between Cardiff State Beach and Del Mar Dog beach is that the dog beach has more fecal content, which can be explained due to dogs being present on the beach. I chose to analyze the difference in the mean amount of plastic between the two beaches and the significance in this data can be attributed to more human activity within Cardiff beach. This explains the greater amount of plastic pieces. Variables that effect the result include wind patterns affecting the amount of litter over time and other humans picking up litter. If I were to further improve the research, it would include increasing the litter pick up to a 300 meter x 300 meter quadrant and to have multiple people picking up litter/using the app everyday for 1 year. This would allow for a greater insight into litter patterns.

References

  1. Rech, S., et al. “Rivers as a Source of Marine Litter — A Study from the SE Pacific.” Marine Pollution Bulletin, vol. 82, no. 1–2, 2014, pp. 66–75., doi:10.1016/j.marpolbul.2014.03.019. https://www.researchgate.net/publication/261607061_Rivers_as_a_source_of_marine_litter-A_study_from_the_SE_Pacific_Marine_Pollution_Bulletin_82_66-75
  2. Jambeck, J. R. et al. Plastic waste inputs from land into the ocean. Science 347, 768–771 (2015).https://www.iswa.org/fileadmin/user_upload/Calendar_2011_03_AMERICANA/Science-2015-Jambeck-768-71__2_.pdf
  3. Moore, C., Lattin, G. & Zellers, A. Quantity and type of plastic debris flowing from two urban rivers to coastal waters and beaches of Southern California. J. Integr. Coast. Zone Manag. 11, 65–73 (2011). https://www.cleanwater.org/files/publications/C%20Moore%20et%20al%202%20urban%20rivers.pdf
  4. Renzi, M., Grazioli, E. & Blašković, A. Effects of Different Microplastic Types and Surfactant-Microplastic Mixtures Under Fasting and Feeding Conditions: A Case Study on Daphnia magna. Bull Environ Contam Toxicol 103, 367–373 (2019). https://doi.org/10.1007/s00128-019-02678-y
Written by
Pocket Kaleta