LEAKAGE ESTIMATION
Field researchers have undertaken several estimations to capture plastic leakage into the marine environment. Their results can differ depending on the scope and methodologies applied.
Land to Ocean Leakage
In 2010, Jambeck et al. (2015) estimated the leakage by calculating the amount of mismanaged plastic waste generated annually by populations living within 50 kilometres of a coast in 192 countries. The estimation framework included (1) annual waste generation per capita, (2) percentage of plastic waste, and (3) percentage of mismanaged plastic waste. The amount of mismanaged plastic waste was converted to the amount of marine plastic debris by applying a range of conversion rates.
Table 1 lists some countries that contributed the most leakage in 2010. Six Association of Southeast Asian (ASEAN) members (Indonesia, the Philippines, Viet Nam, Thailand, Malaysia, and Myanmar) were included in the top 20 countries. China topped the list. The global leakage estimation was 4.8 million–12.7 million metric tonnes/year (equivalent to 1.7%–4.6% of total plastic waste generated in those countries).
Table 1. Estimated Marine Plastic Debris Leakage in 2010
Scientific Knowledge : Leakage Estimation (Table 1)
Rank | Country |
Estimated Leakage in 2010
(million metric tonnes/year) |
Global (192 countries) | 4.8–12.7 | |
1 | China | 1.32–3.53 |
2 | Indonesia | 0.48–1.29 |
3 | Philippines | 0.28–0.75 |
4 | Viet Nam | 0.28–0.73 |
5 | Sri Lanka | 0.24–0.64 |
6 | Thailand | 0.15–0.41 |
7 | Egypt | 0.15–0.39 |
8 | Malaysia | 0.14–0.37 |
12 | India | 0.09–0.24 |
17 | Myanmar | 0.07–0.18 |
Source: Jambeck et al. (2015).
Land to River, Lake, and Ocean Leakage
Borrelle et al. (2020) update the annual amount of mismanaged plastic waste entering aquatic ecosystem (covering oceans, rivers, and lakes) from 2016 to 2030 in 173 countries. Applying a methodology similar to that of Jambeck et al. (2015), the estimation integrates expected population growth, annual waste generation per capita, as well as proportion of plastic waste and mismanaged waste. Those variables were integrated using a distance-based probability function, considering the spatially explicit waste generation and downhill flow accumulation.
The leakage in 2016 becomes the baseline estimation (Table 2), while the leakage in 2030 is estimated for three scenarios: (1) business as usual, in which waste generation and plastic production follow current trajectories; (2) ambitious, which draws upon existing global commitments in reducing the leakage; and (3) target (<8 million metric tonnes), estimated in 2010 by Jambeck et al. (2015). Russia tops the list, while two East Asia countries (China and Japan) and five ASEAN countries (Indonesia, Thailand, the Philippines, Myanmar, and Viet Nam) are included in the top 20. Under the business-as-usual scenario, the global estimated leakage will reach up to 90 million metric tonnes/year by 2030.
Table 2. Estimated Aquatic Ecosystem Plastic Waste Leakage in 2016 and 2030
Scientific Knowledge : Leakage Estimation (Table 2)
Rank in 2016 | Country |
Estimated Leakage in 2016
(million metric tonnes/year) |
Estimated Leakage in 2030
(million metric tonnes/year) |
||
Business as usual | Ambitious | Target | |||
- | Global (173 countries) | 19–23 | 35.8–90.0 | 19.8–53.3 | 3.4–12.0 |
1 | Russia | 2.99–3.40 | 4.72–10.46 | 1.32–5.43 | 0.02–2.63 |
2 | India | 2.51–3.21 | 4.74–13.93 | 2.50–7.28 | 0.49–1.42 |
3 | Indonesia | 1.55–1.83 | 2.83–6.42 | 2.04–4.71 | 0.40–0.90 |
4 | China | 1.41–1.74 | 2.46–7.12 | 2.03–5.87 | 0.04–0.11 |
5 | Thailand | 0.96–1.13 | 1.60–2.96 | 0.63–1.17 | 0.01–0.02 |
9 | Philippines | 0.46–0.52 | 0.88–2.48 | 0.49–1.37 | 0.10–0.27 |
11 | Myanmar | 0.33–0.39 | 0.61–1.39 | 0.47–1.13 | 0.23–0.54 |
15 | Viet Nam | 0.26–0.31 | 0.47–1.20 | 0.31–0.79 | 0.06–0.15 |
17 | Japan | 0.26–0.29 | 0.39–1.05 | 0.22–0.61 | 0.01–0.03 |
Source: Borrelle et al. (2020).
River to Ocean Leakage
Meijer et al. (2021) recently estimated that amongst 31,904 rivers in 163 countries, more than 1,500 rivers account for 80% of global plastic waste leakage. The global leakage of 0.8 million–2.7 million metric tonnes/year estimated by Meijer et al. (2021) is far below the amount estimated by Jambeck et al. (2015) in 2010. The reason behind the lower estimate is not the reduction of single-use plastics or the improvement of waste management systems but the estimation methodologies. In addition to common variables, such as population, waste generation per capita, and proportion of mismanaged waste, Meijer et al. (2021) utilised a probabilistic model that considered additional variables, including land use, terrain slope, wind, and precipitation. The model was then calibrated and validated against recent field observations from 2017 to 2020. Despite the difference, the results find that ASEAN countries remain as main contributors.
Table 3 lists five ASEAN countries as the top 10 contributors. Amongst these countries, the largest contributor is the Philippines, with seven rivers in the top 10 plastic-emitting rivers (Table 4), followed by Malaysia (3rd), Indonesia (5th), Myanmar (6th), Viet Nam (8th), and Thailand (10th).
Table 3. Recent Estimated Marine Plastic Leakage
Scientific Knowledge : Leakage Estimation (Table 3)
Rank | Country |
Recent Estimated Leakage
(million metric tonnes/year) |
Global (163 countries) | 0.8–2.7 | |
1 | Philippines | 0.356 |
2 | India | 0.126 |
3 | Malaysia | 0.073 |
4 | China | 0.071 |
5 | Indonesia | 0.056 |
6 | Myanmar | 0.040 |
7 | Brazil | 0.038 |
8 | Viet Nam | 0.028 |
10 | Thailand | 0.023 |
Source: Meijer et al. (2021).
Table 4. Predicted Top 10 Plastic-Emitting Rivers
Scientific Knowledge : Leakage Estimation (Table 4)
Rank | Catchment | Country |
Recent Estimated Leakage
(million metric tonnes/year) |
1 | Pasig | Philippines | 0.063 |
2 | Tullahan | Philippines | 0.013 |
3 | Ulhas | India | 0.013 |
4 | Klang | Malaysia | 0.013 |
5 | Meycauayan | Philippines | 0.012 |
6 | Pampanga | Philippines | 0.009 |
7 | Libmanan | Philippines | 0.007 |
8 | Ganges | India | 0.006 |
9 | Rio Grande de Mindanao | Philippines | 0.005 |
10 | Agno | Philippines | 0.005 |
Source: Meijer et al. (2021).
The results are consistent with Lebreton et al. (2017) and Schmidt et al. (2017), who found that 1.15 million–2.41 million metric tonnes and 0.41 million–4 million metric tonnes, respectively, of plastic flows from rivers to oceans annually. The top 20 polluting rivers were mostly in Asia (Table 5) and accounted for more than two-thirds (67%) of the global leakage (Lebreton et al., 2017). Amongst the top 20, seven rivers—Brantas (6th), Pasig (8th), Irrawaddy (9th), Solo (10th), Mekong (11th), Serayu (14th), and Progo River (19th)—are in ASEAN countries.
Table 5. Predicted Top 20 Polluting Rivers
Scientific Knowledge : Leakage Estimation (Table 5)
Rank | Catchment | Country |
Estimated Leakage
(million metric tonnes/year) |
1 | Yangtze | China | 0.333 |
2 | Ganges | India, Bangladesh | 0.115 |
3 | Xi | China | 0.074 |
4 | Huangpu | China | 0.041 |
5 | China | Nigeria, Cameroon | 0.040 |
6 | Brantas | Indonesia | 0.039 |
7 | Amazon | Brazil, Peru, Columbia, Ecuador | 0.039 |
8 | Pasig | Philippines | 0.039 |
9 | Irrawaddy | Myanmar | 0.035 |
10 | Solo | Indonesia | 0.033 |
11 | Mekong | Thailand, Cambodia, Lao People’s Democratic Republic, China, Myanmar, Viet Nam | 0.023 |
12 | Imo | Nigeria | 0.022 |
13 | Dong | China | 0.019 |
14 | Serayu | Indonesia | 0.017 |
15 | Magdalena | Colombia | 0.017 |
16 | Tamsui | Taiwan | 0.015 |
17 | Zhujiang | China | 0.014 |
18 | Hanjiang | China | 0.013 |
19 | Progo | Indonesia | 0.013 |
20 | Kwa Ibo | Nigeria | 0.012 |
Source: Lebreton et al. (2017).
Using underlying mismanaged plastic waste data similar to that used by Lebreton et al. (2017), Schmidt et al. (2017) concluded that 10 rivers (Table 6) account for 88%–95% of global leakage to the ocean. Eight out of the 10 rivers are in Asia, including the Mekong (10th), which flows through five ASEAN countries. The estimated leakage is higher because Schmidt et al. (2017) compiled a larger data set and treated microplastic and macroplastic separately. Reducing plastic leakage by 50% in the 10 top-ranked rivers would reduce total river-based leakage by 45%.
Table 6. Predicted Top 10 Polluting Rivers
Scientific Knowledge : Leakage Estimation (Table 6)
Rank | Catchment | Country |
Estimated Leakage
(million metric tonnes/year) |
1 | Yangtze | China | 16.884 |
2 | Indus | India, China, Pakistan | 4.809 |
3 | Huang He | China | 4.099 |
4 | Hai He | China | 3.448 |
5 | Nile | Egypt, Sudan, South Sudan, Ethiopia, Uganda, Congo, Kenya, Tanzania, Rwanda, Burundi | 3.293 |
6 | Meghna, Bramaputra, Ganges | Bangladesh, Bhutan, China, India, Nepal | 3.017 |
7 | Zhujiang | China, Viet Nam | 2.515 |
8 | Amur | Russia, China | 2.087 |
9 | Niger | Benin, Guinea, Mali, Niger, Nigeria | 1.990 |
10 | Mekong | Thailand, Cambodia, Lao PDR, China, Myanmar, Viet Nam | 1.931 |
Source: Schmidt et al. (2017).
Recent estimation by Meijer et al. (2021) shows a significant increase of leakage from several rivers in the Philippines, compared with the estimation by Lebreton et al. (2017). For instance, the amount of leakage from the Pasig River increases more than 60%, from only 0.039 million metric tonnes/year in 2017 (Table 5). Rivers in ASEAN countries, especially in the Philippines, have toppled rivers in China from the top spot as emitters of plastic to oceans since Meijer et al. (2021) considered spatial variability of the amount of mismanaged plastic waste within a river basin and utilised climate and terrain characteristics to differentiate the probability of leakage. With these assumptions, relatively small river basins, including those in ASEAN countries (e.g. the rivers in the Philippines), contribute proportionally more leakage than larger river basins, where the amount of mismanaged plastic waste is similar but located further upstream. Meijer et al. (2021) answer the limitation on Lebreton et al. (2017) and Schmidt et al. (2017), who overestimated the leakage from large rivers and underestimated the leakage from smaller rivers due to the exclusion of those important assumptions. The trend is a backstep and a warning that the region must reduce marine plastic debris.
Harmonised Methodology to Support Effective Countermeasures
Although several estimations have been undertaken to capture plastic leakage into the marine environment, more data should be estimated periodically. The results of estimations differ from one another depending on the scope and methodologies applied. To avoid any underestimation, harmonising the estimation methodologies is important. With harmonised methodology, data can be compared and validated against each other. Using a larger set of data, as done by Schmidt et al. (2017) and Borrelle et al. (2020), will further increase estimations’ accuracy. However, some countries might not have country-specific data, so that the data estimated using a proxy value with some assumptions and a certain level of uncertainties might lead to underestimation. For instance, Schmidt et al. (2017) extended by 41 countries the estimation of Jambeck et al. (2015) of mismanaged plastic waste generation rate from 192 coastal countries. The waste generation rate and plastic composition for these 41 countries were taken from Hoornweg and Bhada-Tata (2012) based on past regional estimation, while the mismanaged plastic waste was calculated based on average values for each World Bank economic classification (high income, upper middle income, lower middle income, or low income). In most developing countries, including India (Nandy et al., 2015), where plastic waste is mostly recovered by the informal sector, a significant amount of plastic waste is excluded in such estimation.
To address this issue, government shall support such research by monitoring leakage in rivers and providing valid waste management data regularly. The lack of actual waste management data, especially in ASEAN countries, might lead to lower or higher leakage estimations, depending on the proxy data. The lower estimation by Meijer et al. (2021) does not necessarily mean the reduction of leakage. By utilising the appropriate harmonised methodology and supported by valid data from the respective governments, various policies can be formulated and/or evaluated to create effective countermeasures against marine plastic leakage.
References
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Hoornweg, D. and P. Bhada-Tata (2012), What a Waste: A Global Review of Solid Waste Management. World Bank, Washington, DC. https://openknowledge.worldbank.org/handle/10986/17388 (accessed 6 September 2021).
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Lebreton, L., J. van der Zwet, J.W. Damsteeg, B. Slat, A. Andrady, and J. Reisser (2017), ‘River Plastic Emissions to the World’s Oceans’, Nature Communications, 8, pp.15611. https://doi.org/10.1038/ncomms15611
Meijer, L.J.J., T. van Emmerik, R. van der Ent, C. Schmidt, and L. Lebreton (2021), ‘More Than 1000 Rivers Account for 80% of Global Riverine Plastic Emissions into the Ocean’, Science Advances, 7, pp.eaaz5803. https://doi.org/10.1126/sciadv.aaz5803
Nandy, B., G. Sharma, S. Garg, S. Kumari, T. George, Y. Sunanda, and B. Sinha (2015), ‘Recovery of consumer waste in India – A mass flow analysis for paper, plastic and glass and the contribution of households and the informal sector’, Resources, Conservation and Recycling, 101, pp.167–81. https://doi.org/10.1016/j.resconrec.2015.05.012
Schmidt, C., T. Krauth, and S. Wagner (2017), ‘Export of plastic debris by rivers into the sea’, Environmental Science & Technology, 51, pp.12246–53. https://doi.org/10.1021/acs.est.7b02368