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air pollution , release into the atmosphere of various gases , finely divided solids, or finely dispersed liquid aerosols at rates that exceed the natural capacity of the environment to dissipate and dilute or absorb them. These substances may reach concentrations in the air that cause undesirable health, economic, or aesthetic effects.
Criteria pollutants.
Clean, dry air consists primarily of nitrogen and oxygen —78 percent and 21 percent respectively, by volume. The remaining 1 percent is a mixture of other gases, mostly argon (0.9 percent), along with trace (very small) amounts of carbon dioxide , methane , hydrogen , helium , and more. Water vapour is also a normal, though quite variable, component of the atmosphere, normally ranging from 0.01 to 4 percent by volume; under very humid conditions the moisture content of air may be as high as 5 percent.
There are six major air pollutants that have been designated by the U.S. Environmental Protection Agency (EPA) as “criteria” pollutants — criteria meaning that the concentrations of these pollutants in the atmosphere are useful as indicators of overall air quality. The sources, acceptable concentrations, and effects of the criteria pollutants are summarized in the table.
pollutant | common sources | maximum acceptable concentration in the atmosphere | environmental risks | human health risks |
---|---|---|---|---|
Source: U.S. Environmental Protection Agency | ||||
carbon monoxide (CO) | automobile emissions, fires, industrial processes | 35 ppm (1-hour period); 9 ppm (8-hour period) | contributes to smog formation | exacerbates symptoms of heart disease, such as chest pain; may cause vision problems and reduce physical and mental capabilities in healthy people |
nitrogen oxides (NO and NO ) | automobile emissions, electricity generation, industrial processes | 0.053 ppm (1-year period) | damage to foliage; contributes to smog formation | inflammation and irritation of breathing passages |
sulfur dioxide (SO ) | electricity generation, fossil-fuel combustion, industrial processes, automobile emissions | 0.03 ppm (1-year period); 0.14 ppm (24-hour period) | major cause of haze; contributes to acid rain formation, which subsequently damages foliage, buildings, and monuments; reacts to form particulate matter | breathing difficulties, particularly for people with asthma and heart disease |
ozone (O ) | nitrogen oxides (NO ) and volatile organic compounds (VOCs) from industrial and automobile emissions, gasoline vapours, chemical solvents, and electrical utilities | 0.075 ppm (8-hour period) | interferes with the ability of certain plants to respire, leading to increased susceptibility to other environmental stressors (e.g., disease, harsh weather) | reduced lung function; irritation and inflammation of breathing passages |
particulate matter | sources of primary particles include fires, smokestacks, construction sites, and unpaved roads; sources of secondary particles include reactions between gaseous chemicals emitted by power plants and automobiles | 150 μg/m (24-hour period for particles <10 μm); 35 μg/m (24-hour period for particles <2.5 μm) | contributes to formation of haze as well as acid rain, which changes the pH balance of waterways and damages foliage, buildings, and monuments | irritation of breathing passages, aggravation of asthma, irregular heartbeat |
lead (Pb) | metal processing, waste incineration, fossil-fuel combustion | 0.15 μg/m (rolling three-month average); 1.5 μg/m (quarterly average) | loss of biodiversity, decreased reproduction, neurological problems in vertebrates | adverse effects upon multiple bodily systems; may contribute to learning disabilities when young children are exposed; cardiovascular effects in adults |
The gaseous criteria air pollutants of primary concern in urban settings include sulfur dioxide , nitrogen dioxide , and carbon monoxide ; these are emitted directly into the air from fossil fuels such as fuel oil , gasoline , and natural gas that are burned in power plants, automobiles, and other combustion sources. Ozone (a key component of smog ) is also a gaseous pollutant; it forms in the atmosphere via complex chemical reactions occurring between nitrogen dioxide and various volatile organic compounds (e.g., gasoline vapours).
Airborne suspensions of extremely small solid or liquid particles called “particulates” (e.g., soot, dust, smokes, fumes, mists), especially those less than 10 micrometres (μm; millionths of a metre) in size, are significant air pollutants because of their very harmful effects on human health. They are emitted by various industrial processes, coal- or oil-burning power plants, residential heating systems, and automobiles. Lead fumes (airborne particulates less than 0.5 μm in size) are particularly toxic and are an important pollutant of many diesel fuels .
Except for lead, criteria pollutants are emitted in industrialized countries at very high rates, typically measured in millions of tons per year. All except ozone are discharged directly into the atmosphere from a wide variety of sources. They are regulated primarily by establishing ambient air quality standards, which are maximum acceptable concentrations of each criteria pollutant in the atmosphere, regardless of its origin. The six criteria pollutants are described in turn below.
The essay on environmental pollution explains how the earth and its natural resources are under the ever-increasing threat of pollution. All life on earth is threatened by this vicious process initiated by human intervention. The pollutants released from all kinds of human activity, including industrial processes, have had devastating effects on the delicate balance of nature. The most common forms of environmental pollution are air pollution, water pollution, and soil pollution. Environmental pollution has to be addressed as the most pressing problem facing humanity now, and solutions have to be implemented before it is too late. Pollution has been causing damage to natural resources in every corner of the world for decades, but it seems that we have been running away from taking any positive measures to mitigate its impact on the environment. This environmental pollution essay in English will help children realise these factors and instruct them to conserve the environment and handle natural resources with the care they deserve.
Environmental pollution is a significant problem in the world today. Some industries release chemicals into the air, which cause harm to the ozone layer that shields us from UV radiation. Some industries release harmful chemicals into water resources. These emissions will be carried by wind and rain and deposited on land or ocean surfaces.
Overpopulation is one of the primary reasons for massive environmental pollution. Besides, it has resulted due to improper waste disposal, hazardous chemical emissions, an increase in the number of factories, and overuse of natural resources.
Suggested Article: Causes of Environmental Pollution
With the use of renewable energy sources, such as solar and wind power, it is possible to limit global warming and reduce pollution at the same time. One of the leading causes of environmental pollution is the production, transportation and disposal of electronic waste. Companies should install recycling systems for computers and cell phones to reduce their need for landfills.
One of the measures to avoid pollution is to reduce the use of plastics. This includes using fewer disposable containers, choosing reusable bags, and reducing the use of plastics. Another way to avoid pollution is by recycling and disposing of waste responsibly.
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Essay on Environmental Pollution : All types of pollution are growing day by day and so environmental pollution also. An essay on environmental pollution is one of the most important essays for all students. Here, we have written an essay on environmental pollution for all the students. This essay on environmental pollution is about 500 to 1000 words .
The surroundings where all living and non-living components are residing is called environment. The growing demand for urbanization, industrialization, mining, exploration, etc. has disrupted the harmonious balance of the natural environment. Many unwanted man-made components are polluting the environment and so environmental pollution has now become a serious cause of concern.
Naturally, for a healthy environment, everything in the environment should be in proper ratio as per the natural occurrence. When something is pairs or impairs in the environment this changes the natural ratio of components in the environment and thus environment becomes contaminated. This contamination in the natural environment is called environmental pollution.
The main cause of environmental pollution is contamination in the natural environment which is mostly caused by human activities without caring for the environment. The situation has now reached at such a dangerous level that air and water without which we can't live, has been become polluted in a great extent. The most prevalent causes of environmental pollution are as under:
Industries have been polluting our environment since the beginning of the industrial revolution. The increasing use of fossil fuels in industries is one of the major causes of environmental pollution. Industries mainly cause air pollution, however, soil and water contamination also occur which results in soil and water pollution . Smoke from industries pollutes the environment and affects air quality badly. Waste material and garbage from industries and leakage of oils during transportation are major causes of water pollution .
With the advancement of technology, human abandoned animal power to travel. Pollution of the environment is growing day by day due to the prevalent transport system which is basically based on fossil fuels. As a medium of transport, we are using, scooters, cars, buses, trains, airplanes. These all modes of transport use fossil fuels as fuel and the smoke that comes from these modes of transports pollutes the environment.
Urbanization is a process of development of a place in such a way that converts a place into a city. In urban areas more and more people come for employment and residence. During the process of urbanization to convert a place into a city many industries are established that emits pollutants. Due to high population in the urban areas garbage has also become one of the major causes of pollution . Proper garbage and waste management system can be helpful in preventing environmental pollution in large extent.
Agricultural activities are mainly responsible for the contamination of water and soil. This is caused by the increased use of pesticides, chemical fertilizers for intensive production of crops. Initially, the chemicals used in pesticides and fertilizers go into the soil and make it polluted. During the irrigation, these chemicals are mixed up with water and make it contaminated.
To feed the growing population agricultural activities are extending day by day. More environments and ecosystems are destroyed to make space for the production of the crops to feed the entire world. Thus, water and soil which are components of environment become polluted by agricultural activities.
The growing level of environmental pollution is devastative for all human beings as well as all living creatures on the earth. It is time to understand the importance of healthy environment for living a happy and healthy life. We all should unitedly work together to protect our environment and stop environmental pollution.
Hope you like this essay on environmental pollution . Feel free to share your important feedback regarding this essay on environmental pollution in the comment box.
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Environmental Pollution refers to any addition of unwanted material in the environment due to human activities that lead to undesirable changes in the environment and ecology. For example, sewage water being released in clean water sources like tanks, rivers, etc. is an example of water pollution.
The different agents that cause environmental pollution are called pollutants . Pollutants can be chemicals, biological materials, or physical things that get added into the environment by accident that are directly or indirectly harmful to people and other living things.
: – They persist in the form in which they are added to the environment e.g. DDT, plastic. : – Formed by interaction among the primary pollutants e.g. is formed by interaction of and . | |
– Occur in and become when concentration reaches beyond a threshold level. E.g. . – These are man-made and do not occur in nature. E.g. fungicides, herbicides, DDT etc. | |
: – Waste products or the pollutants which are decomposed/ degraded by natural processes microbial action. E.g. sewage. : – The pollutants which don’t decompose naturally or decompose slowly e.g. DDT, Aluminium cans. | |
– These pollutants are released during natural processes, such as volcanic eruptions, forest fires, grass fires, etc. : – These pollutants are released during anthropogenic activities, such as CO emission from the burning of fossil fuels. |
Depending on the source as well as destination of the pollutants, there are various types of pollution. Some major of them can be seen as follows:
Water pollution refers to release of unwanted substances into subsurface groundwater or into water bodies like lakes, streams, rivers, estuaries, and oceans to a level which negatively impacts the beneficial use of the water or natural functioning of ecosystems.
When harmful chemicals or microorganisms contaminate a stream, river, lake, ocean, aquifer, or other body of water, the water’s quality deteriorates and it becomes toxic for both humans and the environment.
International measures to tackle water pollution.
1 | Dhaka | Bangladesh | 119dB |
2 | Moradabad | India | 114dB |
3 | Islamabad | Pakistan | 105dB |
4 | Rajshahi | Bangladesh | 103dB |
5 | Ho Chi Minh City | Vietnam | 103dB |
Thus, various types of pollutions being caused by different anthropogenic activities have the potential to cause damage to the existence of life on the earth. India and the world must adopt a “green vision” as part of the development agenda. The time has come to add “clean environment” to the list of basic necessities – “roti-kapada-makaan”.
Joint forest management (jfm): provisions, significance & more, social forestry: meaning, objectives, types & more, compensatory afforestation fund management and planning authority (campa), biological diversity act 2002 (bda 2002), ozone depleting substances (regulation and control) rules 2000, wetlands (conservation and management) rules 2010 & 2017, leave a reply cancel reply.
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Air pollution.
Air pollution consists of chemicals or particles in the air that can harm the health of humans, animals, and plants. It also damages buildings.
Biology, Ecology, Earth Science, Geography
Air pollution consists of chemicals or particles in the air that can harm the health of humans, animals, and plants. It also damages buildings. Pollutants in the air take many forms. They can be gases , solid particles, or liquid droplets. Sources of Air Pollution Pollution enters the Earth's atmosphere in many different ways. Most air pollution is created by people, taking the form of emissions from factories, cars, planes, or aerosol cans . Second-hand cigarette smoke is also considered air pollution. These man-made sources of pollution are called anthropogenic sources . Some types of air pollution, such as smoke from wildfires or ash from volcanoes , occur naturally. These are called natural sources . Air pollution is most common in large cities where emissions from many different sources are concentrated . Sometimes, mountains or tall buildings prevent air pollution from spreading out. This air pollution often appears as a cloud making the air murky. It is called smog . The word "smog" comes from combining the words "smoke" and " fog ." Large cities in poor and developing nations tend to have more air pollution than cities in developed nations. According to the World Health Organization (WHO) , some of the worlds most polluted cities are Karachi, Pakistan; New Delhi, India; Beijing, China; Lima, Peru; and Cairo, Egypt. However, many developed nations also have air pollution problems. Los Angeles, California, is nicknamed Smog City. Indoor Air Pollution Air pollution is usually thought of as smoke from large factories or exhaust from vehicles. But there are many types of indoor air pollution as well. Heating a house by burning substances such as kerosene , wood, and coal can contaminate the air inside the house. Ash and smoke make breathing difficult, and they can stick to walls, food, and clothing. Naturally-occurring radon gas, a cancer -causing material, can also build up in homes. Radon is released through the surface of the Earth. Inexpensive systems installed by professionals can reduce radon levels. Some construction materials, including insulation , are also dangerous to people's health. In addition, ventilation , or air movement, in homes and rooms can lead to the spread of toxic mold . A single colony of mold may exist in a damp, cool place in a house, such as between walls. The mold's spores enter the air and spread throughout the house. People can become sick from breathing in the spores. Effects On Humans People experience a wide range of health effects from being exposed to air pollution. Effects can be broken down into short-term effects and long-term effects . Short-term effects, which are temporary , include illnesses such as pneumonia or bronchitis . They also include discomfort such as irritation to the nose, throat, eyes, or skin. Air pollution can also cause headaches, dizziness, and nausea . Bad smells made by factories, garbage , or sewer systems are considered air pollution, too. These odors are less serious but still unpleasant . Long-term effects of air pollution can last for years or for an entire lifetime. They can even lead to a person's death. Long-term health effects from air pollution include heart disease , lung cancer, and respiratory diseases such as emphysema . Air pollution can also cause long-term damage to people's nerves , brain, kidneys , liver , and other organs. Some scientists suspect air pollutants cause birth defects . Nearly 2.5 million people die worldwide each year from the effects of outdoor or indoor air pollution. People react differently to different types of air pollution. Young children and older adults, whose immune systems tend to be weaker, are often more sensitive to pollution. Conditions such as asthma , heart disease, and lung disease can be made worse by exposure to air pollution. The length of exposure and amount and type of pollutants are also factors. Effects On The Environment Like people, animals, and plants, entire ecosystems can suffer effects from air pollution. Haze , like smog, is a visible type of air pollution that obscures shapes and colors. Hazy air pollution can even muffle sounds. Air pollution particles eventually fall back to Earth. Air pollution can directly contaminate the surface of bodies of water and soil . This can kill crops or reduce their yield . It can kill young trees and other plants. Sulfur dioxide and nitrogen oxide particles in the air, can create acid rain when they mix with water and oxygen in the atmosphere. These air pollutants come mostly from coal-fired power plants and motor vehicles . When acid rain falls to Earth, it damages plants by changing soil composition ; degrades water quality in rivers, lakes and streams; damages crops; and can cause buildings and monuments to decay . Like humans, animals can suffer health effects from exposure to air pollution. Birth defects, diseases, and lower reproductive rates have all been attributed to air pollution. Global Warming Global warming is an environmental phenomenon caused by natural and anthropogenic air pollution. It refers to rising air and ocean temperatures around the world. This temperature rise is at least partially caused by an increase in the amount of greenhouse gases in the atmosphere. Greenhouse gases trap heat energy in the Earths atmosphere. (Usually, more of Earths heat escapes into space.) Carbon dioxide is a greenhouse gas that has had the biggest effect on global warming. Carbon dioxide is emitted into the atmosphere by burning fossil fuels (coal, gasoline , and natural gas ). Humans have come to rely on fossil fuels to power cars and planes, heat homes, and run factories. Doing these things pollutes the air with carbon dioxide. Other greenhouse gases emitted by natural and artificial sources also include methane , nitrous oxide , and fluorinated gases. Methane is a major emission from coal plants and agricultural processes. Nitrous oxide is a common emission from industrial factories, agriculture, and the burning of fossil fuels in cars. Fluorinated gases, such as hydrofluorocarbons , are emitted by industry. Fluorinated gases are often used instead of gases such as chlorofluorocarbons (CFCs). CFCs have been outlawed in many places because they deplete the ozone layer . Worldwide, many countries have taken steps to reduce or limit greenhouse gas emissions to combat global warming. The Kyoto Protocol , first adopted in Kyoto, Japan, in 1997, is an agreement between 183 countries that they will work to reduce their carbon dioxide emissions. The United States has not signed that treaty . Regulation In addition to the international Kyoto Protocol, most developed nations have adopted laws to regulate emissions and reduce air pollution. In the United States, debate is under way about a system called cap and trade to limit emissions. This system would cap, or place a limit, on the amount of pollution a company is allowed. Companies that exceeded their cap would have to pay. Companies that polluted less than their cap could trade or sell their remaining pollution allowance to other companies. Cap and trade would essentially pay companies to limit pollution. In 2006 the World Health Organization issued new Air Quality Guidelines. The WHOs guidelines are tougher than most individual countries existing guidelines. The WHO guidelines aim to reduce air pollution-related deaths by 15 percent a year. Reduction Anybody can take steps to reduce air pollution. Millions of people every day make simple changes in their lives to do this. Taking public transportation instead of driving a car, or riding a bike instead of traveling in carbon dioxide-emitting vehicles are a couple of ways to reduce air pollution. Avoiding aerosol cans, recycling yard trimmings instead of burning them, and not smoking cigarettes are others.
Downwinders The United States conducted tests of nuclear weapons at the Nevada Test Site in southern Nevada in the 1950s. These tests sent invisible radioactive particles into the atmosphere. These air pollution particles traveled with wind currents, eventually falling to Earth, sometimes hundreds of miles away in states including Idaho, Utah, Arizona, and Washington. These areas were considered to be "downwind" from the Nevada Test Site. Decades later, people living in those downwind areascalled "downwinders"began developing cancer at above-normal rates. In 1990, the U.S. government passed the Radiation Exposure Compensation Act. This law entitles some downwinders to payments of $50,000.
Greenhouse Gases There are five major greenhouse gases in Earth's atmosphere.
London Smog What has come to be known as the London Smog of 1952, or the Great Smog of 1952, was a four-day incident that sickened 100,000 people and caused as many as 12,000 deaths. Very cold weather in December 1952 led residents of London, England, to burn more coal to keep warm. Smoke and other pollutants became trapped by a thick fog that settled over the city. The polluted fog became so thick that people could only see a few meters in front of them.
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Professor in Evolution and Behaviour, The University of Melbourne
PhD Researcher, Urban Light Lab, The University of Melbourne
Therésa Jones receives funding from the Australian Research Council.
Nikolas Willmott received funding from the Holsworth Wildlife Research Endowment, Ecological Society of Australia, and the Environmental Microbiology Research Initiative.
University of Melbourne provides funding as a founding partner of The Conversation AU.
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As darkness falls, the nocturnal half of the animal kingdom starts its day. Nocturnal species are perfectly adapted to navigate and survive the dark of night that has existed for countless millions of years.
What happens to these creatures when the darkness they call home is transformed by streetlights and other artificial night lighting?
In new research published in Biology Letters, we studied how light pollution affects the development of Australian garden orb weaving spiders. We discovered it makes their brains smaller, particularly in the regions devoted to vision – with unknown effects on their behaviour.
Artificial light is one of the fastest-growing ways humans are polluting the world, and it has a huge range of effects on animals, plants and ecosystems. Recent evidence suggests the stress of living with light pollution may impair the growth and development of the brain in some birds and mammals.
This may be catastrophic. To survive in novel environments where light pollution is most common, such as cities, animals may actually need larger and more complex brains.
But what about insects and spiders and other, smaller creatures that inhabit the night? Could light pollution similarly affect the growth and development of their brains?
Our study on the nocturnal Australian garden orb weaving spider suggests it does.
The Australian garden orb weaving spider is a perfect species to explore this question. It lives happily in cities and rural areas where it constructs its webs each night in wide open areas (even under streetlights).
In previous studies we found urban spiders that build webs under streetlights catch more insect prey . We also showed that light at night has a cost because it accelerates juvenile development resulting in smaller adults that produce fewer offspring .
In this current study we investigated whether developing under light at night also affects brain size in males and females.
To explore this question, we took late-juvenile spiders from relatively dark parks in Melbourne, Australia and reared them in the laboratory until they were adults.
During rearing we kept half the spiders under darkness at night and exposed the other half to nocturnal lighting equivalent to the brightness of a streetlight.
A few weeks after the spiders were fully grown we assessed whether light at night had affected the development of their brains. As a spider brain is around the size of the nib of a ballpoint pen (less than a cubic millimetre) we used micro-CT imaging technology to visualise what was inside.
We found that short-term exposure to light at night resulted in overall smaller spider brain volumes. The strongest effects were seen in the area of the brain linked to vision in the spider’s primary eyes.
These results are a first for invertebrates (animals with no backbone, such as insects and spiders), but they mirror what has been described in vertebrates. We can only speculate how these differences came about.
It is possible that the presence of light at night created a stressful environment that disrupted hormonal processes related to growth and development. However, if this was the case we might expect to see all parts of the brain affected, which was not the case.
An alternative explanation is that spiders forced to develop under light at night changed their “investment” in different parts of the brain. Proper brain function is essential for an animal to navigate its environment, so under stressful conditions, limited resources may be directed to the more important parts of the brain. For spiders that don’t rely on vision, like orb-weavers, they may compensate by reducing investment in the visual parts of the brain, as we found here.
Other invertebrates such as desert ants ( Cataglyphis fortis ) show similar “ neuroplastic shifts ” in the visual centre of their brain when they move from subterranean nest-tending to above-ground, vision-based foraging.
All this is quite interesting, but you might be wondering why we should care about light pollution affecting the size of a spider’s brain.
Well, spiders are very important in an ecosystem. They eat other invertebrates, including many pest species such as flies and mosquitoes. Spiders are also important prey for other predators, such as birds and lizards.
If spiders’ brains get smaller, it may affect their cognitive function and ability to perform these vital roles. We know from other species of birds and mammals that larger brains can help individuals survive in novel city environments and it is likely the same may be true for spiders.
This research also shows that the effects of light pollution on brain development extend to invertebrates as well as birds and mammals. The full effects of humanity’s love of artificial lighting are likely much bigger than we yet understand.
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Nature volume 633 , pages 101–108 ( 2024 ) Cite this article
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Negotiations for a global treaty on plastic pollution 1 will shape future policies on plastics production, use and waste management. Its parties will benefit from a high-resolution baseline of waste flows and plastic emission sources to enable identification of pollution hotspots and their causes 2 . Nationally aggregated waste management data can be distributed to smaller scales to identify generalized points of plastic accumulation and source phenomena 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 . However, it is challenging to use this type of spatial allocation to assess the conditions under which emissions take place 12 , 13 . Here we develop a global macroplastic pollution emissions inventory by combining conceptual modelling of emission mechanisms with measurable activity data. We define emissions as materials that have moved from the managed or mismanaged system (controlled or contained state) to the unmanaged system (uncontrolled or uncontained state—the environment). Using machine learning and probabilistic material flow analysis, we identify emission hotspots across 50,702 municipalities worldwide from five land-based plastic waste emission sources. We estimate global plastic waste emissions at 52.1 [48.3–56.3] million metric tonnes (Mt) per year, with approximately 57% wt. and 43% wt. open burned and unburned debris, respectively. Littering is the largest emission source in the Global North, whereas uncollected waste is the dominant emissions source across the Global South. We suggest that our findings can help inform treaty negotiations and develop national and sub-national waste management action plans and source inventories.
Plastic pollution is a global challenge requiring immediate action owing its environmental persistence and negative impact on ecosystems 14 , infrastructure 15 , society and the economy 16 . The importance of this burgeoning issue has recently been recognized by the ratification of a United Nations draft resolution to create an internationally legally binding instrument to end plastic pollution 1 , hereafter the ‘Plastics Treaty’. A global plastic pollution emissions inventory has been suggested as being critical to the success of the Plastics Treaty 17 and such inventories have already been applied in the climate change field 18 and as early evidence for a global legally binding agreement on mercury 19 , 20 —eventually the Minamata Convention 21 .
Previous efforts to model global plastic waste emissions and movement through the environment have demonstrated the scale of the issue, highlighting large macroplastic emissions from countries with extensive coastlines, large populations and insufficient waste management 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 . Yet there is a growing understanding that a much higher (sub-national) resolution is required, which identifies plastic pollution hotspots and accounts for specific local solid waste management, behavioural, cultural and socio-economic conditions 12 , 17 . We believe that the very concept of ‘emissions’ also requires clarification, owing to the complexity of the phenomena ( Methods and Extended Data Fig. 1 ). We use it here for clarity rather than the loosely defined terms of ‘leakage’ and ‘mismanaged waste’ described elsewhere 22 and we deliberately avoid the term ‘release’ suggested by the United Nations Economic Commission for Europe (UNECE) 23 , which could imply deliberate activity. We define plastic emissions as material that has moved from the managed or mismanaged systems (in which waste is subject to a form of control, however basic; contained state) to the unmanaged system (the environment; uncontained state) with no control. We further classify emissions according to two categories: (1) debris (physical particles >5 mm) and (2) open burning (mass combusted in open uncontrolled fires). For clarification, open burning emissions relate to the mass of material that is subjected to the practice, rather than the gaseous, liquid or solid matter emitted by the process. Further definitions and scope are in Supplementary Information Section S.2 .
Mapping and quantification of plastic waste material flows is hindered by the lack of sufficiently detailed and up-to-date records of waste management practices and quantities at a local level 24 , which prevents the complete assessment of emissions from human systems 25 . Although coordinated work is underway to remedy this data paucity 24 , a measurable baseline is urgently required to inform Plastics Treaty obligations 17 . As with greenhouse gas 18 or mercury 19 , 20 emissions inventories, this baseline would enable a more rational distribution of overseas development assistance, empower policymakers with scarce resources to develop evidence-based specialized national and sub-national strategies, action plans and targets 25 , and create a strong evidential basis for the reorganization of material systems that have been the focus of Plastics Treaty proposals 26 and negotiations 27 . Therefore, we created a macroplastic emissions inventory using a new methodology to quantify emissions for 50,702 municipality-level administrations from five land-based sources: (1) uncollected waste; (2) littering; (3) collection system; (4) uncontrolled disposal; and (5) rejects from sorting and reprocessing (Fig. 1 ). Unmeasured data were predicted using machine learning and flows were mapped using probabilistic material flow analysis (MFA) for the year 2020. See Methods and Supplementary Information for detailed methodology.
Key plastic pollution sources and generalized waste management and circular economy flows are shown in this explanatory framework. Detailed materials and methods are available in the Supplementary Information .
We estimate that 52.1 Mt year −1 [48.3–56.3] of macroplastic waste were emitted into the unmanaged system in 2020, representing 21% (wt.) of all the municipal plastic waste generated (251.7 Mt year −1 [233.1–272.4]) globally (statistics reported are the arithmetic mean of all iterations—simulation runs; the 5th and 95th percentiles are in square brackets). Approximately 43% (wt.) (22.2 Mt year −1 [20.6–24.0]) is unburned ‘debris’, meaning that it is no longer subject to any form of management or direct control and is at risk of transport across land and into the aquatic environment.
Most plastic pollution models do not report emissions in a way that is comparable with the present work, instead reporting emissions to ‘the aquatic environment’ 3 , ‘aquatic ecosystems’ 6 , ‘the ocean’ 8 , 28 , ‘mismanaged plastic waste’ 5 and ‘riverine outflows’ 29 . However, two studies report comparable data. Ryberg et al. 11 estimated macroplastic debris emissions to the environment at 6.2 Mt year −1 (confidence interval (CI): 2.0–20.4) in 2015. The upper end of the CI is within the range of our 5th percentile for debris emissions but the central estimate is approximately 3.5 times lower than our mean. The categories reported by Ryberg et al. 11 include sea-based, industrial and construction sources, which are all outside the scope of our model. Removing these would reduce their central estimate to 4.9 Mt year −1 , 4.5 times lower than our mean estimate. The sum of ‘terrestrial’ and ‘aquatic’ emissions estimated by Lau et al. 9 for 2016 was 29 Mt (95% CI: 22–39). This estimate includes microplastics and material emitted at sea but is otherwise congruent with our debris emissions category. Although the average reported by Lau et al. 9 is approximately 23% higher than our mean estimate, the lower CI is approximately the same as our mean debris emissions.
Our model improves on earlier works and provides new information in five ways: (1) in this model, we used a bottom-up approach rather than regional 10 and archetypal 9 averages distributed to finer resolution (top-down approach); (2) our finer resolution accounts for spatial heterogeneity in sub-national waste management data; (3) we modelled emissions from five separate downstream sources rather than the single homogenous source used in other models 3 , 4 , 5 , 6 , 7 , 8 , 28 —‘mismanaged (plastic) waste’ 22 , an umbrella term that encompasses a range of insufficiencies in waste management 12 ; (4) our definition of ‘emission’ includes waste that escapes from ‘dumpsites’ 24 (defined in Methods ) but excludes that retained within them because it is mostly buried beneath the waste mass 30 and poses a low risk of being blown or washed into the unmanaged system 31 . Only the ‘working face’ of these sites contains material at risk of transmission through the action of wind and surface water runoff 32 (Supplementary Information Section S.8.9 ). Conversely, it is self-evident that waste that is uncollected, scattered on land or accumulated in smaller ‘informal dumps’ has a much higher probability of being mobilized and transported across the terrestrial surface and into the aquatic environment; and 5) We account for the open burning of waste (Supplementary Information Section S.8.11 ), which is not specifically considered in most plastic pollution models 3 , 4 , 5 , 6 , 7 , 8 , 11 , 28 and which our results indicate contributes to 57% (29.9 Mt year −1 [27.6–32.4]) of all plastic waste emitted, resulting in widespread risk to human health and the environment 33 . As far as we are aware, only Lau et al. 9 report a comparable estimate of open burning of municipal solid waste plastic of 49 Mt year −1 (95% CI: 40–60) for 2016, two-thirds more than our estimate. The reason for this difference is the method of calculation. Whereas Lau et al. 9 used emission factors derived from expert assumptions published by the Intergovernmental Panel on Climate Change (IPCC) 18 and extrapolated from Wiedinmyer et al. 34 , our study uses census and survey activity data from 44 countries (Supplementary Information Section S.8.11 ).
On an absolute basis, we find that plastic pollution emissions are highest across countries in Southern Asia, Sub-Saharan Africa and South-eastern Asia (Fig. 2a–c ), with the largest amount (9.3 Mt year −1 [6.5–12.7]) emitted by India, equivalent to nearly one-fifth of global plastic emissions. In contrast to previous plastic pollution models that positioned China as the world’s highest plastic polluter 5 , 8 , it is ranked fourth in our results, with emissions of 2.8 Mt year −1 [2.1–3.7], less than Nigeria (3.5 Mt year −1 [2.6–4.6]) and Indonesia (3.4 Mt year −1 [2.5–4.3]). This lower contribution to plastic emissions from China reflects our use of more up-to-date data 35 that shows its substantial progress in adopting waste incineration and controlled landfill 36 . Conversely, India reports that its dumpsites (uncontrolled land disposal) outnumber sanitary landfills by 10:1 (ref. 37 ) and, despite the claim that there is a national collection coverage of 95%, there is evidence that official statistics do not include rural areas, open burning of uncollected waste or waste recycled by the informal sector 38 . This means that India’s official waste generation rate (approximately 0.12 kilograms per capita per day (kg cap −1 day −1 )) is probably underestimated and waste collection overestimated. Our model corrects for flows missing in officially reported statistics, resulting in a waste generation rate for India of 0.54 kg cap −1 day −1 [0.39–0.73], which is similar to and between other comparable estimates 38 , 39 , 40 .
a , Mean macroplastic emissions by country. Inset illustrates mean municipal-level emissions for India, from which the national results are calculated. Box plots show distribution of probabilistic material flow analysis results for the three highest macroplastic emitting countries in each United Nations sub-region. Box plot statistics: lower and upper hinges correspond to the first and third quartiles and the central line is the median. Whiskers extend to the data point no further than 1.5 times the interquartile range from the hinge, with outlier values beyond this denoted as dots. b , Emissions by United Nations sub-region and settlement typology 54 . Two groups of United Nations sub-regions are merged for simplicity into ‘Rest of Europe’ (Northern Europe, Southern Europe, Western Europe) and ‘Oceania’ (Polynesia, Australia and New Zealand, Melanesia, Micronesia). c , Mean emissions by United Nations sub-region and emission type. d , Mean proportion of macroplastic emissions by plastic format for the income categories of HIC and low-income or middle-income countries (LMIC).
Our data for India indicate a collection coverage of 81% [80–82], meaning that nearly 53% (wt.) [51–56] of the country’s plastic waste emissions (30% wt. [29–32] debris and 23% wt. [22–25] open burning) come from the 255 [241–270] million people (18% [17–19] of the population) whose waste is uncollected. Most of the remaining emissions (38% wt. [36–40]) are as a result of open burning on dumpsites, in which fires are reported to be common 38 . Overall, we estimate that 56.8 Mt year −1 [40.0–77.7] of municipal solid waste is open burned in India, of which 5.8 Mt year −1 [4.1–7.9] is plastic. This is within the lower end of the ranges modelled by Chaudhary et al. 38 of 74.0 Mt year −1 (uncertainty: 30–92) and Sharma et al. 39 of 68 Mt year −1 (range: 45–105).
Open burning rather than intact items (debris) is the predominant emission type across most United Nations sub-regions, except for those which are predominantly in the Global North (Northern America, Northern Europe, Western Europe and Australia and New Zealand) and Sub-Saharan Africa, in which debris emissions (7.4 Mt year −1 [6.7–8.2]) are slightly higher than open burning emissions (5.9 Mt year −1 [5.2–6.6]) (Fig. 2c ). This result is driven by data that indicate lower levels of open burning in the rural areas of low-income countries (LICs), of which there are many in the Sub-Saharan Africa region (Supplementary Fig. S.24d,f ).
Approximately 69% (35.7 Mt year −1 ) of the world’s plastic waste emissions come from 20 countries, of which four are LICs, nine are lower middle-income countries (LMCs) and seven are upper middle-income countries (UMCs). Despite high-income countries (HICs) having higher plastic waste generation rates (0.17 kg cap −1 day −1 [0.15–0.20]), none are ranked in the top 90 polluters, because most have 100% collection coverage and controlled disposal. Furthermore, our modelling accounts for the mitigating impact of street sweeping activity on emissions, which is greater in HICs (Supplementary Information Section S.8.5 ). We acknowledge that we may have underestimated plastic waste emissions from some HICs because we deliberately excluded plastic waste exports from our analysis. As explained in Supplementary Information Section S.2 , plastic waste exports from the top ten Organisation for Economic Co-operation and Development (OECD) exporters to non-OECD countries and Turkey have substantially decreased from nearly 5.4 Mt year −1 in 2017 to less than 1.7 Mt year −1 in 2022 (ref. 41 ), contributing approximately 0.03 Mt year −1 of emissions. Although this might affect some individual country results, the overall effect would be negligible in comparison with other sources.
Countries in low-income and middle-income categories have much lower plastic waste generation (LICs: 0.04 kg cap −1 day −1 ; LMCs: 0.07 kg cap −1 day −1 ; UMCs: 0.10 kg cap −1 day −1 ). However, in contrast to HICs, a large proportion of it is either uncollected (LICs: 55% wt.; LMCs: 26% wt.; UMCs: 11% wt.) or disposed of in dumpsites (uncontrolled disposal) (LICs: 36% wt.; LMCs: 57% wt.; UMCs: 19% wt.). The nine countries that make up the Southern Asia region emit a similar amount of plastic waste (15.1 Mt year −1 [12.1–18.7]) to the 51 countries in Sub-Saharan Africa (13.3 Mt year −1 [12.0–14.7]) (Fig. 2b,c ), with Nigeria contributing to approximately one-quarter (3.5 Mt year −1 [2.7–4.6]) of the Sub-Saharan African burden. Urban areas (cities, towns and semi-densely populated areas) account for most emissions in all regions (Fig. 2b ) because of low rural populations (Supplementary Information Section 7.1 ) and much lower plastic waste generation. However, we acknowledge that notable data gaps on solid waste management in rural communities exist and future efforts to address plastic pollution must include these often overlooked communities 42 .
Flexible plastic debris has a higher probability of being emitted into the environment in the Global South compared with rigid debris (mean ratio 56:44), driven by its greater prevalence (waste composition) and its propensity for mobilization under the action of wind and surface water (Fig. 2d ). In the Global North (for example, Northern America), the opposite is true (mean ratio 33:67) because rigid plastics are more prevalent in the waste and because emissions are driven by littering rather than meteorological forcing.
The contrast between absolute plastic waste emissions from the Global North and the Global South is stark (Fig. 3a,c ). However, on a per-capita basis, insufficiencies in local and national waste management systems are more apparent (Extended Data Figs. 2 – 6 ). For example, China, the world’s fourth largest absolute emitter, is one of the least polluting UMCs, ranked 153 of all countries on a per-capita basis (1.97 kg cap −1 year −1 [1.48–2.61]), and India, the world’s largest absolute emitter, is ranked 127 on a per-capita basis (6.64 kg cap −1 year −1 [4.66–9.08]). Conversely, Russia, the world’s fifth largest emitter on an absolute basis, also has high emissions on a per-capita basis (11.71 kg cap −1 year −1 [7.80–16.17]) because it is reported to have very low levels of controlled disposal 43 , 44 . Many countries in Sub-Saharan Africa that show low absolute plastic emissions are hotspots on a per-capita basis (Extended Data Fig. 4 ). Given the anticipated population boom in the region 45 , it is conceivable that, with an average emission rate of 12.01 kg cap −1 year −1 [10.83–13.25], Sub-Saharan Africa will become the world’s largest absolute source of plastic pollution within the next few decades.
a , Mean macroplastic emissions by country. b , Probability distributions of macroplastic emissions for six global cities >1 million population. c , Country-level macroplastic emissions by income category. Black dots are individual country results in each income category. The lower and upper hinges of the box plots correspond to the first and third quartiles and the central line is the median. Whiskers extend to the data point no further than 1.5 times the interquartile range from the hinge.
Municipal-scale probability distributions indicate substantial uncertainty within municipalities for some of our model outputs (Fig. 3b ). For example, the 5th and 95th percentiles of plastic emissions are 0.77–11.87 kg cap −1 year −1 (median 3.62 kg cap −1 year −1 ) for Agra (India) and 0.11–4.72 kg cap −1 year −1 (median 0.34 kg cap −1 year −1 ) for Maracaibo (Venezuela). The large ranges within many municipalities and relatively high kurtosis, for example, Shenzhen (42.3) and Maracaibo (19.9), are a consequence of our conservative application of probability density functions for many of the model’s input data, which have propagated through to the results.
Despite the wide uncertainty within each municipality, there are very large differences between many of them, enough to differentiate the most challenging locations from the least (Fig. 3b ). For example, median plastic emissions for Hamburg (Germany) are estimated at 0.02 kg cap −1 year −1 [0.01–0.06] compared with Mogadishu (Somalia), which has almost 680 times more (13.63 kg cap −1 year −1 [4.05–36.70]). Such large differences demonstrate that substantial reductions in plastic emissions are feasible, reiterating the importance of measuring sound solid waste management activity data. Continuing efforts to gather more reliable municipal-scale information 24 for SDG indicator 11.6.1 will gradually improve the accuracy of our model. However, much more comprehensive measurement and monitoring is required to improve the accuracy of flows that are rarely measured and that have been populated here using our conceptual sub-models.
Uncollected waste is the largest contributor to plastic pollution in the Global South, accounting for 68% (35.6 Mt year −1 ) of all plastic waste emissions and 85% (18.7 Mt year −1 ) of all debris emissions. On a per-capita basis, uncollected waste represents 69%, 66% and 80% (wt.) of emissions in UMCs, LMCs and LICs, respectively (Fig. 4b ). Approximately 56% (19.9 Mt year −1 [17.8–22.3]) of emissions from uncollected waste come from LMCs, in which the mean collection coverage is 74% [72–75] (Fig. 4a ). Uncollected waste in LMCs accounts for 38% of total global plastic emissions and 51% (11.3 Mt year −1 ) of debris emissions. As far as we are aware, none of the other global plastic pollution models 3 , 4 , 5 , 6 , 7 , 8 , 11 , 28 has explicitly highlighted uncollected waste as the main source of plastic pollution, instead grouping it in the ‘mismanaged waste’ category or, in one case 9 , together with disposal site debris emissions. Here we show that plastic waste emissions from uncontrolled land disposal sites (dumpsites), although important, contribute 25% (12.8 Mt year −1 [11.5–14.3]) of global plastic waste emissions, of which 98% (wt.) is open burned. This means that just 0.25 Mt year −1 is emitted from land disposal sites as debris, approximately 0.4% (wt.) of plastics deposited in uncontrolled disposal sites worldwide. This is substantially less than has been inferred elsewhere. For example, Lau et al. 9 estimated that between 1% and 1.5% of rigid plastics and 8% and 13% of flexible and multimaterial plastics deposited in uncontrolled disposal sites would reach the aquatic environment each year. The difference is that Lau et al. 9 used expert judgement to derive their transfer coefficients, whereas this work used a more detailed sub-model based on the surface area and runoff characteristics of dumpsites detailed in Supplementary Information Section S. 8.9 .
Shown by: a , absolute mass and income category; b , per capita and income category; c , absolute mass and United Nations sub-region; and d , per capita and United Nations sub-region. Absolute mass of emissions ( a , c ) has unit Mt year −1 , whereas per-capita emissions ( b , d ) has unit kg cap −1 year −1 . Two groups of United Nations sub-regions are merged for simplicity into ‘Rest of Europe’ (Northern Europe, Southern Europe, Western Europe) and ‘Oceania’ (Polynesia, Australia and New Zealand, Melanesia, Micronesia). LIC, low-income country; LMC, lower middle income country; UMC, upper middle income country; HIC, high-income country.
HICs contribute 0.3% (0.16 Mt year −1 [0.14–0.19]) of global plastic waste emissions. Among HICs, uncollected waste is the source of 21% [15–27] (0.03 Mt year −1 [0.02–0.05]) of plastic waste emissions, just 0.06% of the global emissions burden, largely because collection coverage is nearly 100%. The largest source of debris emissions in HICs is littering (see ‘Uncollected litter’ defined in Supplementary Table S.3 ), accounting for 53% of debris emissions and 49% (0.08 Mt year −1 , 0.06 kg cap year −1 ) of all plastic emissions in the Global North (Fig. 4a,b ). Of this, 0.03 Mt year −1 takes place in Northern America and 0.03 Mt year −1 in the Rest of Europe region (Fig. 4c ), representing 0.09 kg cap year −1 and 0.07 kg cap year −1 , respectively (Fig. 4d ). The behavioural nature of littering 46 contrasts with the underlying drivers of other emission sources, especially those in the Global South. This is because, although littering is negatively correlated with waste receptacle provision 47 , it is largely driven by the decisions of individuals 46 . By contrast, the 1.5 billion individuals whose waste is uncollected in the Global South have little choice but to self-manage it (defined in Supplementary Information Section S.4.1 ).
The mismanagement of rejects from plastics sorting and reprocessing (recycling system) in both the Global North and the Global South results in 1.0 Mt year −1 [0.9–1.1] of plastic waste emissions to the environment. These emissions have often been the focus of attention, particularly in relation to the transboundary trade (exports) in waste plastics 48 . However, here we show that the emissions burden from recycling macroplastic rejects is comparatively very small.
The purpose of our study was to create a macroplastic pollution inventory method for baselining and monitoring emissions at the local scale, at which on-the-ground actions can be applied. Such an emissions inventory, explaining the mechanisms for emission from the waste management and societal systems, could form a basis for a more detailed and comprehensive assessment of possible interventions. Once macroplastics have entered the environment, they are technically and economically challenging to remove 49 and, over time, will inevitably fragment into innumerable microplastics 50 , making clean-up efforts even more challenging. Minimizing plastic pollution at source by preventing the emission event in the first place must be a priority of the Plastics Treaty 17 and our insight indicates that tackling uncollected waste would have a bigger impact than mitigating all other land-based macroplastic sources combined. Notably, we already have a large global workforce of informal recyclers, entrepreneurs who our model shows collect more than 49.8 Mt year −1 [45.1–54.9] of waste plastics annually, much of which would otherwise be mismanaged.
We suggest that interventions to reduce uncollected plastic waste would focus on upstream material reduction to reduce waste generation and/or substantial improvement of waste collection services and infrastructure, and our emissions inventory sets a detailed basis for this. As highlighted elsewhere 9 , 51 , mitigating plastic waste emissions will require a multisectoral approach that includes addressing insufficiencies across the lifecycle, including redesign of product systems, source reduction and improving recycling systems worldwide. The plausibility of timely and at-scale deployment of such interventions needs to be carefully reassessed in the context of our new results.
The large mass of waste that is burned in open uncontrolled fires has not formed a central part of discussions at Plastics Treaty negotiations 26 , 27 . Yet, according to our model, more plastic waste is burned than is emitted as debris worldwide, releasing a cocktail of potentially hazardous substances and climate forcing emissions, which may have a substantial impact on human health and ecological systems 33 . An unintended consequence of interventions to mitigate the release of debris could result in an increase in emissions from open burning and vice versa 52 . Therefore, we propose that the inclusion of this phenomenon is a critical component of the forthcoming negotiations: clearly, choosing between two main forms of plastic pollution should not be an option.
We acknowledge that there is a dearth of robust, quality-controlled and verifiable waste management activity data. We have tediously screened, assessed, harmonized and corrected relevant data, incorporating uncertainty using a probabilistic approach. We have designed a conceptual framework that allows the model’s input data and structure to be continuously updated. As more quality-controlled locally obtained measurements from across the waste and resources system become available, and our understanding of release mechanisms improves, the model’s precision and accuracy can be ameliorated.
As with international climate change agreements 53 , signatories to the Plastics Treaty will require a method to calculate and baseline their plastic waste emissions so that they can compare them with others. Our emissions inventory enables them to carry out these estimates at high resolution by conceptualizing the mechanisms of emission, providing insights into the nature, extent and causes of plastic pollution and, therefore, enabling development of evidence-based national and sub-national action plans to eliminate plastic in our environment.
We created a macroplastic emissions inventory using a new methodology to quantify emissions from land-based sources for 50,702 municipality-level administrations 55 (see Supplementary Information for details on the method). We define plastic emissions as material that has moved from the managed or mismanaged systems (in which waste is subject to a form of control, however basic) to the unmanaged system (the environment) with no control. For example, open dumpsites, defined here as structures that contain concentrations of collected waste with only basic control to prevent its interaction with the environment, are a form of control, because most of the material buried beneath the waste mass is unlikely to undergo further movement into the environment.
Material was mapped through 81 downstream (after-use phase) processes to simulate the flow of municipal solid waste through globally diverse waste management systems (Fig. 1 and Supplementary Information Section 4 ). Emissions of land-based macroplastic debris (physical particles >5 mm) and open burning (combustion in open uncontrolled fires) from municipal solid waste (defined in Supplementary Information Section S.2 ) were quantified for flexible and rigid plastics (format). Activity data (the intensity of waste and resources recovery management activity) were obtained from four global 56 , 57 , 58 , 59 and two national 35 , 60 waste management databases. These were checked for errors, harmonized to a consistent basis and corrected if necessary, creating the first comprehensively quality controlled city-level solid waste management database with worldwide coverage (Supplementary Data 1 ). Our primary input data represent 12.2% of the 2015 global population, spanning each of the World Bank income categories (LICs: 12.0%; LMCs: 11.4%; UMCs: 13.5%; HICs: 11.2%). Further discussion on the representativeness of our input data is presented in Supplementary Information Section S.6.7 .
Quantile regression random forest models 61 predicted data for all global municipalities using national and sub-national socio-economic indicators. Waste management, circular economy and plastic waste emission characteristics, variables that are not commonly measured or reported, were estimated using data from the literature or through the creation of new conceptual models. These newly developed ‘sub-models’ (Supplementary Information Sections S.8.2 , S.8.3 , S.8.3.4 , S.8.5 , S.8.5.2 , S.8.8 , S.8.9 , S.8.11.1 and S.9.1.2 ) used data on human behaviour, material value, socio-economic development, population density and solid waste management performance, creating an explanatory framework through which to estimate unmeasured system characteristics. The use of ‘process-level sub-models’ to describe larger systems has recently been advocated for plastic pollution modelling 13 .
Probabilistic (Monte Carlo simulation) MFA mapped flows of municipal solid waste (5,000 iterations) throughout the system (Supplementary Information Section S.4 ), resulting in detailed information on municipal solid waste and plastic waste management for each global municipality (Supplementary Data 5 ). Emissions into the unmanaged system, defined here as uncontained waste that is no longer subject to any form of management or control, were estimated for five key sources: (1) uncollected waste; (2) littering; (3) collection system; (4) uncontrolled disposal; and (5) rejects from sorting and reprocessing (Extended Data Fig. 1 ). The probabilistic MFA used probability density functions from two sources: (1) the results of the machine learning predictions and (2) from the secondary data collection and processing step detailed in Supplementary Information Section S.8 . A full list of probability density functions used in our model is available in Supplementary Data 6 and the MFA equations are shown in Supplementary Data 2 .
These flows and their associated uncertainty were aggregated to the national scale (Supplementary Data 3 ) to align with reporting for SDG indicator 11.6.1 (ref. 24 ) and to the regional and global scales (Supplementary Data 4 ) to create a multiresolution global plastic emissions inventory (Fig. 1 and Extended Data Fig. 7 ). This inventory is the first-stage prerequisite for a second terrestrial transport model (not discussed further here), collectively named the ‘Spatio-temporal quantification of plastic pollution origins and transport’ model (SPOT). Although we acknowledge that upstream processes during the production, conversion and use phases result in a range of emissions from plastics, they are outside the scope of our modelling. We also exclude textiles, sea-based sources of plastic pollution and waste electrical and electronic equipment. To improve comprehension of proportionality, the results are reported as the mean of all iterations (simulation runs). Numbers in square brackets are the 5th and 95th percentiles of all iterations. As there are no datasets with which to validate our model outputs, we took the same approach as Lau et al. 9 and carried out global sensitivity analysis to assess the influence of the model inputs and structure on its results (Supplementary Information Section S.10 ).
We warn readers to consider the full uncertainty in our MFA results, particularly for municipal-scale outputs at which the ranges are generally much larger than national-scale or regional-scale aggregations. The origins of uncertainty in our model are discussed at length in Supplementary Information Section S.9.2.2 . We also explain in Supplementary Information Section S.9.1.1 a specific circumstance in which we decided not to quantify uncertainty for the uncontrolled disposal coefficient (tC3) owing to limitations of the quantile regression random forest predictive capability for that particular aspect of the system.
Supplementary Data 1 – 6 are freely available as part of the Supplementary Information and are available from Dryad: https://doi.org/10.5061/dryad.8cz8w9gxb . Administrative boundaries used for the maps were sourced from GADM version 3.6 and are available from https://gadm.org/ .
All code, model inputs and outputs are available from Dryad: https://doi.org/10.5061/dryad.8cz8w9gxb .
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We would like to thank Y. Gavish, data analyst, for comments on modelling uncertainty and machine learning; A. Savvantoglou for illustrations and graphic design; C. Gonzales and M. Harkness for data cleaning; K. Terzidis for collection and analysis of incineration data. For assistance in securing access to municipality-related primary data and assisting with comprehension of data collection and reporting methods used by the main international datasets: N. Takeuchi (UN-Habitat), A. Whiteman (Wasteaware), M. Newbury (United Nations Statistics Division) and S. Kaza (World Bank Group). Funding: this work was partly supported by the United Nations Human Settlements Programme (UN-Habitat), with further in-kind support by the University of Leeds. The views expressed in this article are those of the authors’ alone and do not necessarily represent the views or policies of UN-Habitat.
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Joshua W. Cottom, Ed Cook & Costas A. Velis
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J.W.C.: conceptualization; methodology; software; validation; formal analysis; investigation; data curation; writing – original draft; writing – review and editing; visualization. E.C.: conceptualization; methodology; validation; formal analysis; investigation; data curation; writing – original draft; writing – review and editing; visualization. C.A.V.: conceptualization; methodology; validation; formal analysis; investigation; data curation; writing – original draft; writing – review and editing; visualization; supervision; resources; funding acquisition.
Correspondence to Costas A. Velis .
Competing interests.
C.A.V. consults for organizations active in the waste, resources and circular economy sphere. He receives funding from UKRI, GCRF, NERC, ESRC, BBSRC, Royal Academy of Engineering, British Council, Innovate UK, EC H2020, World Bank Group, OECD, GIZ, UN-Habitat, UNESCAP, UNOPS, The Pew Charitable Trusts, IGES, ISWA, GRID-Arendal, Swedish EPA and SYSTEMIQ. He is affiliated with the International Solid Waste Association (ISWA), the Scientist’s Coalition for an Effective Plastics Treaty and the Innovation Alliance for a Global Plastics Treaty. The University of Leeds has memorandums of understanding with the Alliance To End Plastic Waste and the United Nations Environment Global Partnership on Plastic Pollution and Marine Litter (GPML), which refer to plastic pollution databases. E.C. has consulted for Tearfund.
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Extended data fig. 1 the point at which material passes from a contained to an uncontained state across the emission boundary is described here as an emission..
Emissions originate from five core emission sources and from three system parts (generated, managed and mismanaged), each of which exhibit different containment characteristics.
Countries in the Global South have high per-capita emissions compared with those in the Global North.
Hotspots for per-capita emissions include municipalities in Paraguay, Belize and Haiti, whereas municipalities in Uruguay and Chile have comparably lower emissions.
Per-capita emissions are high throughout the continent, with notable hotspots including municipalities in South Sudan, Angola and Namibia. Several megacities stand out as key hotspots, including Lagos (Nigeria), Juba (South Sudan) and Nouakchott (Mauritania).
Emissions on a per-capita basis are low for municipalities in HICs, such as Japan and South Korea, but high throughout much of South-eastern Asia, particularly Cambodia. Eastern China has low per-capita emissions owing to recent progress in solid waste management. However, emissions are marginally higher in Western China.
Per-capita emissions are high throughout the region, with the exception of municipalities in HICs on the Arabian Peninsula, such as Saudi Arabia, Qatar and United Arab Emirates. Municipalities in Kyrgyzstan, Kazakhstan, Iraq, Jordan and Syria have relatively high per-capita emissions. Although India has the highest absolute emissions of all countries, on a per-capita basis, most of its municipalities have between 5 and 10 kg cap −1 year −1 .
Municipal level data were cleaned, harmonized and used to train a quantile regression random forest machine learning model, which was used to generate core material flow data for 50,702 municipalities worldwide. These data, combined with explanatory conceptual submodels, were used to populate and define flows in a probabilistic material flow analysis model (Monte Carlo) with 81 processes. The results are presented at municipal level, which showed a large variations in emissions, and then as aggregations at national, income category and global levels. The majority of emissions come from uncollected waste, whereas litter accounts for a comparatively small proportion worldwide. Of the 52.1 Mt year -1 (mean) of emissions produced, approximately 57% wt. are burned in open uncontrolled fires.
Supplementary information.
This file contains Supplementary Methods, including Supplementary Figs. 1–30, Supplementary Tables 1–40 and Supplementary References. Further Supplementary Data for this article are available from Dryad at https://doi.org/10.5061/dryad.8cz8w9gxb .
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Cottom, J.W., Cook, E. & Velis, C.A. A local-to-global emissions inventory of macroplastic pollution. Nature 633 , 101–108 (2024). https://doi.org/10.1038/s41586-024-07758-6
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DOI : https://doi.org/10.1038/s41586-024-07758-6
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