spiritus: Eco Guardians’ Report 4

Cleaning Up the Streets of Sinsa – A Day with Our Team

Last weekend, our team took part in a cleanup activity in the streets and back alleys of Sinsa-dong, Gangnam. This neighborhood is widely known for its fashionable streets, upscale cafés, and bustling nightlife. But once we stepped away from the main road, we saw a very different side of Sinsa — hidden piles of litter tucked behind buildings, overflowing bins, and trash scattered along narrow alleys that tourists and even many locals rarely notice.

We didn’t just come here to tidy up. Our goal was twofold:

1. Collect as much waste as possible to make the area visibly cleaner
2. Record and analyze detailed data about the waste we gathered so we could better understand what kinds of trash are most common and where they tend to accumulate. This way, we can design more targeted and effective cleanups in the future.

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📍 On the Ground – What We Found and Where

Armed with gloves, large trash bags, and a sense of teamwork, we divided the area into smaller zones so that we could cover more ground efficiently. We explored not only the main shopping streets but also service roads, parking lots, and even the narrow alleyways behind restaurants.

Along the way, we found:

• Plastic waste such as water bottles, food packaging, and snack wrappers.
• Aluminum cans — many from energy drinks and beer — often tossed near convenience stores.
• Paper cups from coffee shops, sometimes with leftover drinks still inside.
• General waste like used tissues, cigarette packs, and small plastic bags.

Interestingly, we noticed patterns:

• Delivery motorcycle waiting areas had a high concentration of drink containers and snack packaging.
• Corners near utility poles often had cigarette butts and crumpled receipts.
• Back entrances of buildings were hotspots for takeout containers and discarded straws.

By noting these details, we started to see not just what the waste was, but why it ended up there.

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The Data Behind the Cleanup

We didn’t want this to be “just” a trash pick-up. That’s why we used a tracking app to record the distance we covered, the number of items collected, and their types. In total, our team collected 138 pieces of waste along a 1.11 km route in just 26 minutes.

When we categorized the trash, the breakdown looked like this:

• Plastics: ~45%
• Cans: ~20%
• Paper: ~15%
• General waste: ~20%

This shows that plastic waste alone made up nearly half of everything we picked up — a clear signal that targeted action on single-use plastics could have a huge impact in this area.

Recording these numbers wasn’t just for curiosity — it means we can compare data from different cleanups over time, identify problem spots, and measure whether the situation improves after repeated efforts.

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The Power of Teamwork

This activity was truly a team effort, and that made all the difference. While one person focused on spotting hidden trash, another carried the collection bag, and another kept track of the data. Some team members even worked on sorting waste on the spot to speed up our post-cleanup process.

By sharing responsibilities, we covered more area in less time, avoided fatigue, and kept everyone motivated. There were also moments of laughter — like when two people raced to grab the same stray can — reminding us that even a physically tiring task can be fun when done together.

Teamwork also made it easier to stay committed. When someone’s energy dipped, others stepped in with encouragement, and before we knew it, the bags were full.

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📝 Reflections and Next Steps

Picking up litter might seem like a small act, but it’s a visible and immediate way to improve the community. Cleaner streets not only look better but also make people less likely to litter again, creating a ripple effect of positive behavior.

Our team believes that change starts small but grows through consistency. That’s why we plan to continue similar cleanups in Sinsa and expand to other neighborhoods. With each activity, we’ll keep collecting data so we can track patterns, focus on the biggest problem areas, and — hopefully — see the numbers go down over time.

At the end of the day, our mission is simple: leave every place cleaner than we found it, and use data to make each cleanup smarter than the last.