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Undergraduate Category: Engineering and Technology Degree Level: Bachelor of Science Abstract ID# 580
MantaRay: A Novel Autonomous MicroplasHc Sensor for Determining ParHcle ConcentraHons in Marine Ecosystems Ethan Edson and Mark PaSerson, Northeastern University, Boston, MA MicroplasHc polluHon in the open ocean is a rapid growing threat to marine organisms and human health. Studying deep ocean microplasHcs requires expensive and lengthy research cruises using tradiHonal research methods. A novel low-­‐cost oceanographic sensor has been designed that can determine the concentraHon of marine microplasHcs over large spaHal areas. This sensor can remove plasHc parHcles from seawater, archive them for later elemental analysis, determine microplasHc concentraHon for 28 discrete samples based on GPS posiHoning, and also record salinity and water temperature measurements. This sensor has been designed on the open-­‐source Arduino plaRorm, allowing for easy implementaHon of addiHonal systems in future prototypes, and can be aSached to a mooring, driTer, or Autonomous Underwater Vehicle (AUV) to gather diverse data. This sensor could drasHcally lower research costs associated with open ocean research cruises and greatly increase our understanding of dispersion and degradaHon rates of harmful marine microplasHcs. u 
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BaSery MicroplasHcs, defined as parHcles of plasHc tens of microns to millimeters in size (Figure 1), are becoming pervasive in the world oceans due to anthropogenic polluHon. The size of microplasHcs is of great concern because it results in physiological problems in a variety of marine organisms. PlasHc polymers have chemical structures that allow for the absorpHon of persistent organic pollutants (Fernandez 2012), transfer harmful chemicals to fish and other marine species (Rochman 2013), and are even creaHng unique habitats for harmful ocean bacteria (Figure 2) (ZeSler 2013). The ocean has spaHally diverse concentraHons of surface microplasHcs, so aSempHng to idenHfy trends in global dispersal paSerns is difficult and expensive using current research techniques. DetecLon Rate by ParLcle Size 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 5 4 3 2 1 0.7 100 90 80 70 60 50 40 30 20 10 0 0 20 40 60 80 MantaRay Temperature Measurement (C) Temperature Probe Performance • 
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Figure 3: An image of a Navis BCGI Autonomous Profiling Float, with a similar driTer design to what is planned for the MantaRay sensor. Study Area of Interest 100 •  ATer calibraHon, the MantaRay temperature probe had a near fit to a Sea-­‐Bird CTD temperature readout, showing a slope of 1.0086 and R2 fit of 0.998 • 
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GPS Performance Integrated Arduino GPS has accuracy of around 8 feet maximum driT, allowing for very precise samples Open ocean condiHons allow for liSle GPS interference and reliable data in Sargasso Sea Conclusion and Greater Impact The MantaRay has the potenHal to help supplement research cruises that study concentraHons and impacts of open ocean microplasHcs. Although An image of the SSV Corwith Cramer. SEA EducaHon AssociaHon holds the longest ongoing dataset looking at AtlanHc Ocean microplasHc concentraHons, and the MantaRay could help expand this dataset. Future Design Features Higher performance with smaller parHcle sizes Passive infrared opHcal sensor that will “fingerprint” and selecHvely remove plasHcs from flow through system Full pressure housing ready for deployment (Figure 3) Open-­‐source fluorometer for addiHonal data Open-­‐source salinity module for addiHonal data Smaller footprint design Easy soTware implementaHon for AUV connecHon or mooring implementaHon 0.3 y = 1.0086x + 0.0952 R² = 0.99838 • 
size, 88% of parHcles 3mm or over, and 95% of parHcles around 5mm in size. •  During sampling hours, the instrument pulls 300 ma of power, allowing for large sample volumes at sea. 1mm 0.7mm 0.5mm 0.3mm Water Temperature Performance •  The MantaRay was built completely open source around the Arduino plaRorm, allowing for maximum customizaHon through the soTware process, and in order to allow for the future implementaHon of various sensors as future prototypes progress. •  MantaRay uses the Arduino MEGA with many breakout boards, including the Adafruit GPS breakout, RioRand DC motor shield, Coleman Solar Charge Controller, and a Progressive AutomaHons linear actuator. The system is powered by several 12v Lead Acid baSeries, which double as ballast in the future buoyant pressure housing. •  The opHcal detector consists of a pair of laser diodes with beams bisecHng a quartz tube and himng a matching pair of digital photodiodes. A break in the laser beam can be read by the Arduino to divert the parHcles. •  A new filter is put into place by moving the filter stack a very finite distance with the linear actuator, with posiHoning relying on the internal potenHometer readings from the actuator. 0.5 ParLcle Sizes ParLcle DetecLon Performance 5mm •  ATer iniHal calibraHons, there was a 4mm decreasing capture rate associated with 3mm decreasing parHcle size. •  The MantaRay successfully captured 2mm 70% of parHcles larger than 1mm in ParLcle Size (mm) MantaRay Hardware Figure 2: ProporHons of Vibrio bacteria species on different substrates in the Sargasso Sea. Vibrio 12F11 is present in smaller proporHons on natural substrates but was the dominant species found on marine microplasHc, indicaHng that marine microplasHc clusters are becoming a novel emerging marine habitat. Research conducted by Ethan Edson et al. at SEA Educa7on Associa7on, Unpublished. Figure 1: Le<: Common millimeter sized microplas7cs pulled up in an open ocean net tow. Right: A map from Law et al. of SEA Educa7on Associa7on showing concentra7on trends in open ocean microplas7cs off the Atlan7c coast. Background The MantaRay is based on a flow through system that acHvely detects and removes parHcles from seawater samples. This is done by operaHng a primary flow through pump and a secondary pump that can “grab” parHcles out of the stream as they pass by. ATer disinfecHon, a seawater sample is drawn into the instrument through the intake by a pump and is passed through the opHcal sensor. If no parHcle is detected the primary pump conHnues to pump water through the instrument. If the opHcal sensor detects a parHcle by an interrupHon in the laser path on the photodetector, the secondary pump turns on and the primary flow through pump turns off. The secondary pump draws the water flow and parHcle into the filter column and over a 500um filter, where the parHcle is preserved. Once the parHcle is stored in the filter column, the primary flow through pump resumes operaHon and the instrument returns to acHvely looking for parHcles in the water. Using GPS triangulaHon, the pump rate of the pumps, and the number of parHcles stored in each discrete sample, we can back calculate microplasHc concentraHon over different spaHal areas. The MantaRay is capable of taking 28 discrete samples of customizable volume and also archiving miroplasHcs. Instrument Performance and Results Percent DetecLon Rate MantaRay Flow-­‐Through Design Exhaust Sea-­‐Bird CTD Temperature (C) Abstract Intake these research cruises are crucial to our understanding, they are very expensive and Hme consuming. A large fleet of MantaRay sensors could greatly increase study areas and have the ability to fit onto moorings, driTers, or even mobile plaRorms like Autonomous Underwater Vehicles (AUVs). With our current knowledge on the ecosystem impacts microplasHcs are having, it is clear that we need addiHonal data on how primary and secondary microplasHcs are produced and how they travel in the ocean. With a fleet of reliable MantRay units, this data could be achievable in the near future. Acknowledgements I would like to thank Mark PaSerson for the conHnuing guidance with this project and for uHlizaHon of the Field RoboHcs (AUV) Laboratory here at Northeastern, to the Office of the Provost whose research grant helped to fund this project, and to Erik ZeSler at SEA EducaHon AssociaHon for gemng me interested in microplasHcs and helping me with quesHons along the way.
References 1.  Life in the “PlasHsphere”: Microbial CommuniHes on PlasHc Marine Debris. Erik R. ZeSler, Tracy J. Mincer, and Linda A. Amaral-­‐ZeSler. Environmental Science & Technology 2013 47 (13), 7137-­‐7146 DOI: 10.1021/es401288x 2.  CalculaHng the Diffusive Flux of Persistent Organic Pollutants between Sediments and the Water Column on the Palos Verdes Shelf Superfund Site Using Polymeric Passive Samplers. LoreSa A. Fernandez, Wenjian Lao, Keith A. Maruya, and Robert M. Burgess. Environmental Science & Technology 2014 48 (7), 3925-­‐3934. DOI: 10.1021/es404475c 3.  Ingested plasHc transfers hazardous chemicals to fish and induces hepaHc stress. Rochman, C. M., Hoh, E., Kurobe, T., Teh, S. J.. ScienHfic Reports 3, 3263 (2013).