Waste minimization, reduction and management
Waste minimization, reduction and management
Plastic pollution is a growing source of emissions. By 2050, it's estimated that the emissions from the lifecycle of plastics could be equivalent to 615 large coal-fired power stations. Food waste is another significant source of emissions; it’s estimated that discarded food is responsible for six percent of global greenhouse gasses. Both plastic and food waste are growing problems in the Global South where waste management is underdeveloped and a large percentage of waste is mismanaged, particularly in urban settings, ending up in landfill unnecessarily or subject to open burning.
Plastics also contribute to emissions through their build up in marine and coastal environments. Marine litter, especially microplastics, can alter key species and habitats in coastal and marine environments, greatly reducing their carbon absorption capacity. Plastic pollution accumulates in oceans mainly due to poor waste management, littering and overconsumption. Countries in sub-Saharan Africa and South Asia figure prominently among those with the highest volumes of plastic in coastal areas.
Currently, effective waste management and cleanup operations are hindered by data gaps about the scale of the plastics problem, particularly in urban and coastal settings in the Global South. Collective intelligence initiatives are drawing on global crowdsourcing and hyperlocal citizen science initiatives to help fill these gaps on the precise location, quantity type and origins of plastic litter. Generating more granular data that captures these details could help to hold polluters accountable, tackling the problem at its source. Equally important is the standardization of data collection to ensure, for example, the use of the same categories of litter to allow for comparison across different locations and periods of time.
Collective intelligence efforts are also helping to fill doing gaps. Coastal crowdsourcing and citizen science projects help close the loop between collecting data and taking action through the organization of beach clean-ups. The success of these initiatives is often down to a critical mass of local participants motivated to improve their area after learning about the scale of the problem through data collection. A few initiatives have even helped to inform the redesign of collection, reuse and recycling programs, and the waste policy priorities of local decision makers. But it is rare that these projects have a direct impact on decision making.
Urban waste management systems rely on the streamlined activity of many actors to function efficiently. To date, the coordination at the scale required has been difficult to implement in cities in the Global South, resulting in mismanagement of waste that leads to unnecessary emissions. Collective intelligence can make a major contribution to addressing this issue. Several examples use digital tools to connect different parts of the waste management ecosystem, from waste producers (households and businesses) to individual service providers across the public, private and informal sectors. In these examples, collective intelligence emerges from the smart matching of supply and demand to address doing gaps of ineffective waste management.
Main collective intelligence methods being used
Crowdsourcing and combining datasets to monitor global waste
Remote sensing and citizen science to manage marine litter
Citizen generated data and coordinated actions to manage urban waste
Main climate action gaps being addressed
- Data gaps about the precise location, quantity, type and origins of plastic litter.
- Doing gaps around lack of accountability and persistence of behaviors that cause waste build up.
- Distance gap around lack of reliable open data about waste that can be compared between countries.
- Data gaps about the scale, types and origins of plastic litter on coastlines.
- Data gaps about hotspots where marine litter is concentrated.
- Doing gaps around accumulation of marine litter.
- Distance gaps around the consequences of plastic waste.
- Data gaps about the quantity of and categories of municipal waste at the street level, as well as hotspots of waste build-up.
- Data gaps around contributions of informal waste pickers.
- Doing gaps around how to prioritize limited waste services and waste mismanagement.
Crowdsourcing and combining datasets to monitor global waste
As waste production continues to escalate, it is more important than ever to keep better track of the rate and scale of the problem to target interventions. Collective intelligence helps to fill this data gap through crowdsourcing and/or combining datasets about location and types of waste, as well as documenting which brands contribute the most to plastic pollution. These data are increasingly shared through open databases that encourage their sharing and re-use for research and decision making.
The Waste Atlas is an interactive map that provides a reliable source of municipal solid waste management data, dumpsites and treatment plants across the world for comparison and benchmarking purposes. It combines datasets acquired through web-scraping and actively crowdsourced from more than 160 countries worldwide. Contributors, mostly scientists and official institutions, can submit data in many different formats including images or spreadsheets, but they have to follow a common data standard. All data is verified before being published to maintain quality and can be accessed through either a web-based interface or mobile apps. Other platforms, like OpenLitterMap, crowdsource data about litter and plastic waste from a wider pool of volunteers. It invites citizen scientists to upload geotagged photos and descriptions of litter, providing granular information about the location of the image with a timestamp of when it was created. They can also use the platform to organize local cleanups. The crowdsourced images are labeled with information about the quantity, category of waste and the brand that produced the original product. Similar to Waste Atlas, there is a quality assurance process before the data are integrated into the global map and made available as open data. Volunteers make their contributions through a gamified interface that includes a leaderboard and regular competitions to incentivize engagement.
Remote sensing and citizen science to manage marine litter
Despite increased awareness from policymakers and the public alike of the importance of marine litter as a key pollution challenge, there are still substantial data gaps about the scale, types and origins of plastic litter on coastlines. This is especially true for countries in the Global South. Hyperlocal citizen science projects are a good way to bridge between data collection and planning interventions to address the problem. They achieve this by sensitizing local communities to the issue and the scale of its impact, helping to close doing and distance gaps in the process.
The Citizen Observation of Local Litter in the coastal ECosysTems (COLLECT) project is a rare example of a pilot that aims to fill these gaps by standardizing data collection about marine litter in seven countries in West Africa and Southeast Asia. COLLECT has worked with young people to make observations and measure levels of plastic waste (macro- to micro-plastics) on beaches. Participating students were trained in sampling protocols using simple instruction manuals and YouTube videos available in multiple languages. This helped to ensure consistent data quality and promoted skills development among local young people. A key aim of the initiative is to increase awareness of the potential consequences of plastic pollution among local communities. The data from COLLECT contribute to establishing baseline information on coastal plastic pollution and help to identify hotspots of coastal plastic litter in participating countries.
In the Philippines, the UNDP Accelerator Lab is also trying to quantify plastic litter accumulation in Manila Bay. They are combining satellite imagery and citizen science to monitor the scale of the problem in Pasig City as part of a broader circular economy portfolio. They use satellite data to provide a baseline estimate of marine litter, which will be ground-truthed by local citizen researchers. This participatory approach to waste monitoring is part of an awareness-raising effort they hope will lead to changes in plastic disposal locally.
The Ghana Marine Litter project is another example of working with residents to fill significant data gaps on plastic waste. The initiative connected local grassroots groups with staff from the national statistics office from the outset. This helped to ensure that the data collected by locals would be useful for policy decisions and could contribute to the international monitoring commitments made by the Ghanaian government.
Citizen generated data and coordinated actions to manage urban waste
Urban waste management services in the Global South are often provided by a complex mix of official, private and informal actors. Mismanagement can be the result of individuals failing to separate waste or inefficient routing and coordination between the different parties involved in the production, distribution and treatment of waste. The absence of granular data about municipal waste at the neighborhood or street level also leads to doing gaps whereby different parts of the system are not optimized for coordinated action. One common oversight is the contribution made by informal workers, whose activities are important for diverting waste from landfill.
Collective intelligence initiatives in this space are using a combination of ethnographic methods and digital tools to connect the dots. Digital platforms and smartphone apps are helping to improve routing between waste producers and waste management services (both official and informal). Integrated payments and financial penalties that incentivize waste reduction at the level of individuals can result in a collective shift away from actions that increase emissions from waste when aggregated across the city. This also raises awareness about the consequences of mismanaged waste among local residents to help reduce the distance gap.
Clean City Africa is a Zimbabwean initiative to streamline waste collection and disposal services that divert recyclable waste away from landfills and prevent emissions from activities like the open burning of waste. Using a mobile app, households and businesses who generate waste are matched with waste collectors and aggregators, including informal workers. Clean City helped to consolidate this ecosystem by providing training and equipment that enabled informal workers to expand their operations. The Clean City initiative facilitates coordination between different stakeholders in the waste management ecosystem to improve environmental outcomes. Since its launch in 2019, over 50 illegal dump sites have been shut down across Harare city and over 10,000 households have started separating materials at source.
A similar example can be found in Bangalore, where 90 percent of litter is sent to landfill largely due to the failure of households to segregate their waste at source. The IGotGarbage project, which ran between 2014-2017 tried to address this through a digital platform that matched informal waste pickers with households and businesses that produced waste. Waste-pickers were trained to collect and manage different waste types, for example, sending recyclable dry waste to scrap dealers and ensuring that wet waste was sent to composting centers. Households had to pay for waste that still got routed to landfill, which led to increased recycling by residents. Over 10 million kgs of waste was recycled and composted while the platform was active.
Mismanagement and build up of waste designated for landfill can also be caused by limited municipal resources and insufficient data. The MOPA (Monitoria Participativa Maputo) platform in Mozambique uses a mobile app and citizen-driven data collection to help cities use limited services more efficiently. Citizens use a digital app to report waste issues like the build up of dumping sites or missed collections across their city. This helps to fill data gaps about where the urban waste system is under most pressure so service providers can prioritize those areas for cleanup. The data is aggregated on an open platform where city officials and citizens alike can monitor problems as they arise and monitor trends in service quality over time.
1 The evaluation survey results about the impact of the project on young people, including their awareness of plastic pollution as an issue and intentions to change behavior, are still due to be published.
2 Both household and business waste.