  Smell has a huge influence over how we perceive places. Despite its
importance, smell has been crucially overlooked by urban planners and
scientists alike, not least because it is difficult to record and analyze at
scale. One of the authors of this paper has ventured out in the urban world and
conducted smellwalks in a variety of cities: participants were exposed to a
range of different smellscapes and asked to record their experiences. As a
result, smell-related words have been collected and classified, creating the
first dictionary for urban smell. Here we explore the possibility of using
social media data to reliably map the smells of entire cities. To this end, for
both Barcelona and London, we collect geo-referenced picture tags from Flickr
and Instagram, and geo-referenced tweets from Twitter. We match those tags and
tweets with the words in the smell dictionary. We find that smell-related words
are best classified in ten categories. We also find that specific categories
(e.g., industry, transport, cleaning) correlate with governmental air quality
indicators, adding validity to our study.
