For something as vitally important as air, rather few of us spend much time thinking about it. According to data furnished by the World Health Organization, air pollution and poor air quality result in 5.5 million unnecessary deaths in an average year. So, what are we doing to safeguard this vital, invisible resource?
One potential solution arrives by way of the “smart city” — those technologically-enhanced, sustainably-planned utopias that are springing up all over the world. By leveraging the power of the Internet of Things, the smart cities of the future will have better air pollution data than ever — and some actionable courses to pursue based on that data. Here’s how it all works.
How the IoT Can Gather Air Pollution Data
The Internet of Things is, of course, the name given to our vast web of millions of connected computers, machines and data-gathering devices. It only makes sense to turn the IoT toward the task of “crowd-sourcing” air quality data from the many types of sensors currently available.
The goal for a smart city, ultimately, is to use this “blanket” of sensor devices to accumulate much more detailed and nuanced information about changes in air pollution and quality over time, specific areas with higher concentrations of pollutants, and better insight into the source of contaminants. Once this data starts rolling in, it’s a matter of analyzing it and coming up with clear goals and action plans.
The technology involved can take several forms, including:
· Stationary Sensors: Some cities are retrofitting stationary sensors into existing city structures. Chicago’s “Array of Things,” which began rolling out in 2014, took a novel approach by attaching sensors to lampposts. Barcelona, Spain, pursued a similar track with smart lighting around the city that feeds data to government oversight offices, as well as a public portal.
· Mobile Sensors: For several reasons, smart cities might choose instead to implement a smaller number of mobile sensors that are not permanently attached to a structure. Pilot programs have piggybacked air quality sensors onto “street view” mapping cars, while others have even used bike-sharing programs to create a fleet of mobile sensors that spans the city.
· Cell Phone Sensor Data: With appropriate attention paid to the privacy implications, researchers at MIT and elsewhere have demonstrated the effectiveness of using anonymized sensor data from cell phones to determine which parts of the city are host to chemical contaminants and air pollution. In some respects, this type of data could be even more instructive than data gathered from stationary and mobile devices, since our smartphones are with us always, including where we live and recreate. Leveraging anonymous atmospheric readings from phones might yield the most “personal” air quality data we’ve seen yet.
No matter how they’re ultimately deployed, the value of this data is difficult to understate. Our cities and municipalities have never been in a better position to gather granular information on the presence of NO2 (nitrogen dioxide), CO2 (carbon dioxide) and black carbon, which is the unmistakable thick, sooty material fired into the atmosphere by combustion engines and coal-based power plants.
Black carbon is among the most significant contributors to air pollution in our metropolitan areas. It’s known to cause respiratory and cardiovascular problems as well as possible congenital disabilities.
Growing Pains and the Long Rollout Ahead
The need for scientifically duplicable and actionable information on the air quality within our cities has never been more apparent. In some parts of the developing world, like Delhi, the concentration of some types of pollutants increased by two-thirds over just three years.
But with strategic investments in commercial, off-the-shelf sensor equipment — much of which is appropriately ruggedized for use in challenging environments — and cloud service development to power it, the developed and developing worlds alike will soon have better tools to help curb the environmental impact of rapid industrialization and the rising global population.
Once they understand the concentrations and sources or air pollution, civil engineers and regulators will have a better idea of what types of structural and regulatory changes need to happen.
Naturally, there are advantages and disadvantages to each of the sensor types described above. Sensors installed on existing city infrastructure are some of the longest-lasting, but they’re also some of the most expensive. By the end of 2016, Chicago had established just one-tenth of the total number of sensors it intends to deploy — 50 against a goal of 500. The “map” of air quality in the city won’t be complete until the entire network of devices is brought online.
There is also the question of data integrity. Some cities might be tempted to pursue low-cost sensing equipment to reduce the expense. However, when compared with the much more sensitive material used in laboratories and by climatologists, making an early investment in less reliable technology won’t do much good.
The effectiveness of low-cost sensors that haven’t been subjected to peer review has, itself, been subjected to scientific scrutiny — and researchers doubt the usefulness of “bargain” solutions compared with more serious scientific apparatus.
Even with these warnings, however, the trajectory here is almost uniformly encouraging. Achieving this degree of transparency and insight into air pollution trends is the first step toward pursuing better public health in our shared spaces.