Data

Probability of mismanaged plastic waste being emitted to the ocean

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What you should know about this indicator

  • These estimates come from a statistical model that combines location-specific data with environmental factors. They are not direct measurements for every country and river.
  • Mismanaged plastic waste is plastic that is littered or thrown away improperly. It is not securely contained in a landfill or properly managed facility, so it can escape into the environment.
  • The study uses location-specific data on mismanaged plastic waste and combines it with environmental factors. These factors include rainfall, wind, land use, terrain steepness, distance to rivers, river size, and distance to the ocean. This helps estimate how much plastic reaches the ocean through rivers.
  • The chance of plastic reaching the ocean depends on three things: first, whether it gets washed away by rain and wind; second, whether it travels from land into a river (affected by land use, slope, and distance); and third, whether it flows through the river network to the ocean (affected by river size and distance to the coast).
  • This probability shows the estimated chance that mismanaged plastic waste from a specific location will reach the ocean via rivers within a year. It is based on local environmental and geographic conditions.
  • These estimates focus on larger plastic items (typically bigger than 0.5 cm) that float on or near the water surface. They do not include tiny microplastics, plastic on riverbeds, or plastic stopped by dams.
Probability of mismanaged plastic waste being emitted to the ocean
Mismanaged plastic waste is plastic that is littered or thrown away improperly. It is not securely contained in a landfill or properly managed facility, so it can escape into the environment.
Source
Meijer et al. (2021)with minor processing by Our World in Data
Last updated
January 27, 2026
Date range
2019–2019
Unit
%

Sources and processing

Meijer et al. – More than 1000 rivers account for 80% of global riverine plastic emissions into the ocean

Supplementary materials from Meijer et al. (2021) including Table S8 with country-level statistics on plastic waste emissions into the ocean via rivers.

Retrieved on
January 27, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Meijer, L. J. J., van Emmerik, T., van der Ent, R., Schmidt, C., & Lebreton, L. (2021).
More than 1000 rivers account for 80% of global riverine plastic emissions into the ocean.
Science Advances, 7(18), eaaz5803.

Supplementary materials from Meijer et al. (2021) including Table S8 with country-level statistics on plastic waste emissions into the ocean via rivers.

Retrieved on
January 27, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Meijer, L. J. J., van Emmerik, T., van der Ent, R., Schmidt, C., & Lebreton, L. (2021).
More than 1000 rivers account for 80% of global riverine plastic emissions into the ocean.
Science Advances, 7(18), eaaz5803.

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To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Probability of mismanaged plastic waste being emitted to the ocean”, part of the following publication: Hannah Ritchie, Veronika Samborska, and Max Roser (2023) - “Plastic Pollution”. Data adapted from Meijer et al.. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/probability-mismanaged-plastic-ocean.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Meijer et al. (2021) – with minor processing by Our World in Data

Full citation

Meijer et al. (2021) – with minor processing by Our World in Data. “Probability of mismanaged plastic waste being emitted to the ocean” [dataset]. Meijer et al., “More than 1000 rivers account for 80% of global riverine plastic emissions into the ocean” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/probability-mismanaged-plastic-ocean.html (archived on March 4, 2026).

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/probability-mismanaged-plastic-ocean.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear