How Data Sharing Can Lead to Environment-Friendly Policies

Big data is making a big impact on the environment. Businesses and governments are using all kinds of data to track environmental issues and develop policies to make positive changes.

Examples include: data from GPS sensors that are tucked in trash are giving city planners a sense of how trash moves through a city, allowing them to optimize routes and collection sites; mobile phone location data is telling public transportation planners how riders are using the systems, allowing for better planning; and devices that monitor pollution that are scattered throughout cities indicate to planners which traffic routes need to be altered to decrease usage and pollution.

These streams of data are allowing government and business officials to strengthen and develop policies to make their cities, businesses, and communities more environmentally friendly. The data provides an overview of the issues needing to be tackled and often contains clues as to the best path forward.

Sebastian Castellanos, of the New Urban Mobility alliance (NUMO), works on micromobility issues with cities and helps cities articulate how certain data sets can help cities meet their environmental goals.

“It’s hard for every city to make the connection between the data and how the data is leading to these high-level goals with the environment,” says Castellanos.

In the world of micromobility in which scooters and electric bicycles are made available to the public, getting a handle on the carbon footprint of these systems can be challenging. In Portland, Oregon, city officials wanted to get a sense of the carbon impact of picking up scooters at the end of the day to charge them and then redistribute them. The servicing had been done by independent contractors working for the scooter company. The direct reduction in car usage due to scooter use was one data point, but figuring out how many car miles were needed to deliver and service the scooters was another. Portland asked for the miles logged from the scooter company. The figure was large, so the city worked with the company to develop a more environmentally friendly approach. Instead of having sole gig workers pick up the scooters, the company hired the workers and was thereby able to optimize pick-up routes and reduce miles. This is just one example about how diving into the data led to a more environmentally friendly approach.

Also in the arena of micromobility, the Copenhagen Wheel has received much attention for its ability to transform a bicycle into a hybrid ebike. But the Copenhagen Wheel also acts as a sensor, collecting data on air pollution, road conditions, and traffic congestion. The data doesn’t just inform the rider of better routes, it can be provided to cities anonymously so they may alter traffic patterns or routes to address the pollution and congestion.

Big data also is helping cities take a closer look at their biggest greenhouse gas emitters so they may develop plans to reduce those emissions. The Metropolitan Area Planning Council (MAPC), the regional planning agency for towns and cities around Boston, recently adopted a community greenhouse gas inventory tool that allows city staff across the region to enter emissions data and match it with publicly available datasets to calculate emissions across all sectors of the community. The data helps cities better understand their local primary sources of GHG so they can work to develop targeted climate action plans.

Big data from satellite images also is helping tackle environmental problems from deforestation to illegal mining. A non-profit called SkyTruth uses machine-learning technology to train computers to analyze satellite images. The computers can detect image features such as logging encroachment, or mining operations being conducted outside legal boundaries. Through a program called Conservation Vision, interested parties can be notified if an image has turned up a red flag. Other international projects track global forest change use high-resolution satellite imagery to calculate deforestation by counting trees.

The uses of data for protecting the environment – and people from environmental disasters – go on. Real-time monitoring of ocean data allows experts to predict tsunamis. Smart diagnostics in water treatment facilities detect leaks and allow for water savings, and complex algorithms of data are being used to develop predictive models of wind conditions to help determine how much wind power may be produced at a specific site.

In short, the power of data is only starting to be tapped to help solve some of the planet’s most vexing environmental problems. The uses of such data to solve environmental problems is expected to grow.