Sustainability is more than just a trend – it’s a new perspective. According to Google, search interest for sustainability reached an all-time high across the globe in 2021. We need to find more circular ways of living, particularly in our metropolitan areas. This is paramount for a climate-friendly future.
Increasing recycling rates is a pivotal part of this circular way of life. According to the UN, our global “material footprint” increased by 70% between 2000 and 2017. 1 million plastic drinking bottles are purchased every minute and 5 trillion single-use plastic bags are thrown away every year. It’s clear that we need to redefine our waste and consumption patterns. Data-driven waste and resource management methods have the power to help us boost recycling rates so we can reduce these numbers and transition to a greener way of life.
In this article, we explore how smart sensors and data insights can help improve public recycling initiatives and transform our cities into smart and sustainable urban hubs.
Increasing Recycling Rates with Data
Plastic, paper, cardboard, food, metal, glass, batteries, and electronics can all be recycled into new products. But globally, we are still struggling to achieve high levels of participation in recycling and reuse schemes.
According to a report by the Federation of Canadian Municipalities (FCM) in 2009, around 80% of residential waste in Canada consisted of recyclable or organic materials, such as food and garden waste. The organization estimated that municipalities could work towards diverting approx. 50% of materials tossed in the trash away from landfills through reuse, recycling, and composting initiatives.
Some cities have had some success with diverting trash away from landfill. For example, San Francisco has an 80% diversion rate thanks to its recycling, composting, and reusing initiatives. But participation rates in recycling schemes remain low due to numerous factors. The convenience factor (bin locations and capacities) and a general lack of awareness and knowledge of recycling schemes play a key role in unlocking higher recycling numbers. And data can help municipalities address these two barriers.
Using Data to Understand Recycling Behavior
Installing smart sensors in your general waste and recycling bins provides a clear, digital overview of waste generation patterns. The data gathered by sensors enables you to set a clear baseline for current recycling levels, so you can effectively measure the impact of future changes and initiatives.
The data also provides a granular overview of recycling levels. Smart sensors enable you to dive into recycling differences and similarities in your local areas. This means that you can quickly identify which areas perform best in terms of recycling. This information can help you identify which areas need more help with recycling initiatives and which areas you can learn from.
Using Data to Improve Recycling Operations
Data doesn’t only help you understand citizen needs. It can also help you optimize your operations. Data gathered by smart sensors provides an accurate status of bins and fill levels in real time – and this information can help you drive effective waste collections and recycling programs.
Smart sensor data can help you tackle the unpredictable aspect of waste and resource management so you can maintain top efficiency. Traditional collection services are static and often pick up bins too early or too late. Early collections result in unnecessary services, carbon emissions, and costs. Late collections can mean overflowing bins and an increased risk of illegal dumping.
Static waste and recycling services that rely on historic waste generation patterns are inefficient. Our waste patterns are changing and unreliable. The collection services that worked last month, might not work this month. Data empowers you to stay one step ahead, so you can streamline your recycling operations and only schedule collections when needed.
In addition, a data-driven approach enables you to continually make operational improvements that make recycling easier for citizens. A digitalized overview of real-time recycling habits provides insights to help you increase bin capacity in hotspot areas or change bin locations to cater to the convenience factor.
Using Data to Improve Public Communication
Citizen engagement is the key to improving recycling participation levels. And more often than not, this comes down to clear communication from municipalities.
Studies show that transparency is essential to citizen involvement in waste management and circular economy programs. Clear communication builds trust between citizens and providers of waste services. Further research also demonstrates that citizens are more likely to participate in recycling schemes if they have a thorough understanding of the purpose: in particular why the schemes have been set up and why separating materials is important.
Municipalities can use this data to provide transparency to citizens. You can incorporate the data insights provided by smart sensors into communication materials. For example, you can provide information about current municipal waste and recycling levels and future goals as well as the reasons for new recycling initiatives. Municipalities can also include statistics on how well local areas are recycling different waste fractions – perhaps even as a gamification method to motivate and encourage individuals to comply with new initiatives.
A Data-Driven Approach to Municipal Recycling Initiatives
Transforming the world’s waste and resource management towards more circular avenues is one of the biggest challenges facing us today. And as our global material footprint reaches astronomical levels, increasing recycling participation is one way of tackling this. Data insights are crucial to accelerating our sustainability journey. A recycling program based on smart sensors and data will provide a better understanding of recycling behavior, help you optimize operations and collection services, and provide insightful information to the general public to motivate increased participation.