For a long time neuroscientists believed that information about odors is relayed randomly through the brain. But new DNA-based brain mapping technologies enable researchers to track the connections of individual neurons in the olfactory cortex.
Cartographer Kate McLean leads smell walks in cities like Paris and Kyiv to document the olfactory landscapes of urban spaces. She then creates maps that visualize the odours she’s collected.
What is a Sniff Map?
There are plenty of ways to map a city, from basic street maps to neighborhood breakdowns by demographics. But researchers from the academic and technology worlds—including a team from Cambridge University and Yahoo Labs—are mapping cities by their smells.
Senior lecturer of graphic design Kate McLean conducts “smell walks” in places such as Amsterdam, Pamplona, Glasgow, Newport, and London. She leads small groups of people on guided tours through the city where they sniff around and take notes about what they’re noticing. Then, she creates a “smell map,” a colorful interpretation of the city’s scent hot spots.
These olfactory city maps highlight the fact that smells aren’t just in your nose, but also in the air, the sidewalks, and even the water. Humans can distinguish more than a trillion different smells, but many of them go unnoticed—unless you map them. The resulting data is helping to open a new stream of research that celebrates the role smell plays in a city’s life.
How do I make a Sniff Map?
Kate McLean is on a mission to map the smells of cities. As she walks the streets of Amsterdam or New York City, she sticks her nose into bakeries, subway cars and newspaper stands, logging scents with her olfactory app.
Humans can differentiate a trillion different odors, but many of them go unnoticed—especially when we are busy living our lives. That’s why McLean is leading small armies of urban explorers on “smellwalks” around cities. Then she turns their sensory perceptions into beautiful visualizations.
To get started, participants create what researchers call a “smell dictionary.” They walk the streets of their home cities or a new one, and note down all the distinct smells they encounter. Then they pick words that best describe them. From there, a list is created that can be used to generate the smell maps. The maps only represent a snapshot in time, since scents are fleeting, but they give a tantalizing glimpse into the hidden complexity of cities.
What are the benefits of making a Sniff Map?
Humans can potentially discriminate between a trillion smells, but much of what goes on around us can go unnoticed, including our urban smellscape. City officials often deal with only ten bad smells from a trillion and the positive role that smell plays in cities gets short shrift.
In an interview with Freethink, McLean explains that she and her collaborators, who include scientists from Cambridge University and Yahoo Labs, have asked people to conduct “smell walks” in their neighborhoods and then map the results online. The maps show at a street segment level the most characteristic smell perceived in an area. For example, one map shows that auto emissions smells—like gasoline and car exhaust—follow the highways of London while nature smells (like flowers, grass and soil) concentrate in parks and green areas.
The maps allow the user to view the odorous landscape of their neighborhood and can even be used to compare and contrast between different neighborhoods. But McLean stresses that the process is more important than the final product as smells are ephemeral, changing with the weather and influenced by personal biases.
How can I use a Sniff Map?
Sniff maps can be used to study smell preferences and perceptions in different neighborhoods. They can also be used to map a specific area’s olfactory ecology, which is useful for studying the effects of human development and environmental changes on local smells.
Schmuker, who was not involved in the original research, believes this is an important first step toward capturing and sharing smells, but further work will be needed to address areas such as smell intensity; mixtures and concentrations of multiple basic scent molecules; and digitizing real-world smells when their molecular structures aren’t a given. He hopes that future studies will make these smell models more accurate and readable.