A three-dimensional visualization tool that uses custom environmental IoT sensors to capture and visualize ground-level ozone and other atmospheric gasses in real-time. Through new forms of immersive representation and data collection techniques, the project seeks to employ a new approach to understanding the dynamic relationship between the ‘human', the ‘non-human’ and 'nature' that recognizes their deep interdependence and co-constitutive existence. We propose an alternative to tools developed to represent a world of static weight and solid substances and thus, are incapable of expressing the experiences of a world of dynamic lightness and relations that shape our immediate air milieu and is shaped by it. Hence, paving a shift in attitude that favors the conception of ourselves as atmosphere designers. The system is tested within three different site typologies, a neighborhood, a nature-infrastructure edge, and an urban center.

(designing) Atmospheric Matter

We developed a simulation system within the Unreal Engine that models four key gases present in the atmosphere: Carbon Dioxide, Carbon Monoxide, Nitrogen Dioxide, and Ozone. These gas digital twins are created through a combination of physical simulations and impact models. This system was designed to create connections between different simulations, including the gas simulation within the Unreal Engine, digital assets such as environment models and textures, and databases containing information on gas detection within a selected site area.

Sensing Artifacts

The information regarding air pollution and its correlation with mortality rates due to direct or indirect exposure underlines the intricacy of monitoring air pollution, specifically in terms of connecting standard measurement techniques with personal exposure. Since stationary sensors are not capable of accurately gauging individual exposure levels to nearby pollutants, an alternative solution is to create a network of inexpensive IoT sensors positioned throughout various sites. The development of the hardware component is aimed at addressing the dynamic challenges that arise when sensors are placed in a mobile context.

Site 1 / neighborhood

Our primary testing site for the project is Sumner Street, located in Cambridge, Massachusetts, USA. It is a small-scale neighborhood strip that connects several Harvard University buildings and centers, and features a mix of housing structures and academic centers. The site is situated near busy squares and has become an active line of transportation after the area was converted into single-way streets. As it is in close proximity to our base location, it serves as an ideal testing ground for both the development and product testing phases. The assumption for this choice is to understand how air quality is affected by the various times of the day, which dictate the traffic in and out of academic and office spaces in the area.

Site 2 / nature

The second site studied is situated at the edge condition, where nature and infrastructure meet. We have selected the east end of the Harvard Arnold Arboretum, adjacent to the bustling Forest Hills bus and train stations, separated by Washington Street. Along the strip being studied, three sensors have been placed in a linear manner, starting from the entrance and progressing deeper into the woods at forty meter intervals. The objective of this site is to investigate how the air quality varies between the entrance premises and the inner woods.

Site 3 / urban

Finally, we circle back to Dabberdt's 1973 study on Urban Diffusion Simulation for Carbon Monoxide in urban canyons, as we select a corner on Franklin Street in Downtown Boston for our final site. This corner features an intersection that connects the Norman B. Leventhal Park with high-rise residential and office towers. The movement of gas across the street is significantly different due to the cross-sections of the buildings, which makes this site distinct from our previous wider study areas. While architecture is shaped by the environment, it shapes it along the way.