Project

MAS.552 Modeling Zero-Carbon Cities - Students projects - Fall 2021

 City Science

Groups

Climate change presents an existential threat to human civilization, and the IPCC report of August 2021 sounds like “a death knell for coal and fossil fuels before they destroy our planet."  With cities generating more than 70% of current global CO2 emissions, and with 90% of future population growth occurring in urban areas, it is a societal imperative that cities rapidly transition to a low-carbon future.

This workshop was a rapid-fire, high-level exploration of how to model urban interventions that could enable low-carbon (ultimately zero-carbon) cities, using the MIT-Kendall Square district as the case study.  We focused on two questions:

- What would be required for MIT-Kendall Square to achieve zero-carbon in 20 years?

- Can social performance be simultaneously increased to create a model entrepreneurship community?

Projects:

Climate change presents an existential threat to human civilization, and the IPCC report of August 2021 sounds like “a death knell for coal and fossil fuels before they destroy our planet."  With cities generating more than 70% of current global CO2 emissions, and with 90% of future population growth occurring in urban areas, it is a societal imperative that cities rapidly transition to a low-carbon future.

This workshop was a rapid-fire, high-level exploration of how to model urban interventions that could enable low-carbon (ultimately zero-carbon) cities, using the MIT-Kendall Square district as the case study.  We focused on two questions:

- What would be required for MIT-Kendall Square to achieve zero-carbon in 20 years?

- Can social performance be simultaneously increased to create a model entrepreneurship community?

Projects:

Walkability for All

Team members: Miguel Dávila Uzcátegui, Naksha Satish, Youngju Kim


Spatial patterns of sprawl are ubiquitous throughout American cities, which have increasingly become friendlier towards private vehicles and more hostile to pedestrians and multi-modality since the mid-century. Propelled by white flight, a decline in transit ridership, and homeownership subsidies, Americans moved farther away from each other but also from the jobs they could previously access without a car. Recently, the development patterns that were normalized have undergone significant scrutiny in the context of our climate emergency as transportation accounts for more than a third of climate-damaging emissions. This study explores and envisions walkable futures for the growing neighborhood of Kendall Square in Cambridge, MA by comparing existing incomes and possible rental costs of neighborhood commuters. Using an agent-based model architecture, the study introduces three different policy scenarios that could support the relocation of more than 6,000 Kendall Square workers who currently live outside the area – The incentives include: increasing residential density, providing tax incentives to developers, and providing direct subsidies to incoming tenants. The central question of this work pertains to whether neighborhood affordability and diversity can contribute to improved environmental outcomes. Using a basis rooted in existing conditions, the model can test the impacts of each of the policies in providing work-life symmetry to Kendall workers and transforming the neighborhood into a walkable and diverse community. Policy incentives are assessed and compared to our base scenario to achieve the best possible reductions in Co2 emissions.

Developing a data analysis tool to model and forecast community solar adoption as well as other key renewable technologies


Team members: Catalina Perez-Aguirre, Ellen Reinhard, Nile Berry and Paras Sethi

Solar panel efficiency has never been higher than it is today, while simultaneously, production costs have never been lower. However, there remains an information gap at the community level to fully grasp and forecast the benefits of implementing solar panel technology. The inability to predict solar on a macro scale limits many lawmakers to creating a hyper-local policy that could incentivize broad-based solar adoption.

When compared to other renewable energy technologies, solar energy production is unique. The physical placement of solar panels is directly correlated with the technology's overall efficacy. Neighboring building shadows, solar panel angle, and specific geographic location all play a key role in determining the technology's overall energy output and success.

Our research aims to close this information gap by creating a data model (using publicly available resources) to accurately and effectively forecast various solar adoption scenarios across a community. Our model focuses specifically on Kendall Square in Cambridge, Massachusetts, but could easily be adapted to another neighborhood of similar size.

Our goal is to provide policymakers with a simple forecasting tool that provides specific insights for their community to better understand the highest and best use of solar installation today and explore possible future scenarios. Beyond this, we incorporate additional calculations for other leading renewable energy technologies (geothermal, nuclear, etc.) to provide users with a broad understanding of how these technologies might factor in as well.

We hope that this research will provide community stakeholders with a key resource to better understand solar and other renewable technologies and empower them to think through adoption strategies that would lead to wide-scale decarbonization.

RetroScope

Team members: Xinzhu (Elence) Chen, Adam Yarnell, Allison Hyatt and Sihui (Iris) Chen

RetroScope is a python-based tool that uses Streamlit to visualize the environmental, economic, and health implications of diverse renovation strategies. Users select both the percentage of key building types and the retrofit scenario to apply, and the tool displays annotated maps and a radar chart displaying carbon emissions, indoor air quality, and cost-effectiveness. On the backend, RetroScope pulls data from EnergyPlus simulations run on MIT Sustainable Design Lab's Urban Modeling Interface (UMI), cost indices, and the results of a CO2-decay equation. Future iterations of the tool will deploy machine learning techniques for fast prediction so as to expand beyond Cambridge.

FlexiStreet

Team members: Yubo Zhao, George Guida, Mu (Clara) He and Elyjana Roach

The street is the primary urban public space of our cities. The COVID-19 pandemic has meant that our streets have been occupied in constant flux. From this, we have seen cities are much more open to these kinds of experimentations of using the street in various ways. However, the street continues to remain mono-functional in use. We envision the future of streets to be more flexible. Streets should be activated with a diversity of land uses of the street itself, and of modes of transport, and it should encourage social activities in order to promote continuous use by city members. 

 While city governments and planners seek to increase pedestrian activity on city streets within broader sustainability, community building, and economic development strategies, this project proposes a collaborative governance tool for simulating future street interfaces. The project uses scenario evaluation to quantify (four) metrics of environmental impacts from reduced carbon emissions, improved lightweight mobility through an increase of bicycle use and reduction on congestion, economic potential through increased foot traffic from potent street improvements and sociability which we are defining has a directly proportional relationship to the potential economic growth. 

 The project provides a platform that stimulates various datasets from the street ecosystem including traffic demands, pedestrian behaviors, and spatial usage of the street, analyzes flexibly different interventions under the framework of four metrics, and visualizes the outcomes where data can be collaboratively and interactively understood by multiple stakeholders to affect the urban decision-making process.

Kendall Life-Work Crescendo

Team members: Patrick Chwalek, Yoonjae Oh, Mirah Xu and Yuxin Yang

The past year's remote working experience, whether hybrid or fully remote, poses many design problems for existing office space culture. According to the Microsoft Work Index, 66% of leaders answered that their company are considering redesigning their office spaces for hybrid work. Global office leasing volumes in the last two years have dropped by half, and the US office vacancy rate (27%) has doubled from the previous year. According to the JLL Boston office insight report, total vacancy and average asking rent in Boston are rising. The projected office vacancy rate is 16.8%, 5% higher than the current rate.

In response to these issues, our project explores the possibility of office building conversions in the scope of Kendall Square. Our interactive statistical tool assists decision-makers in rethinking existing office buildings in Kendall and transforming them into spaces in need. Our tool guides users to understand three perspectives based on the rate of office transition: How much can we reduce building and transportation GHG Emissions? Is annual residential rent showing more financial improvement than annual office rent? Can we have more urban green space for increased well-being? Today, it is clear that the lack of housing stocks in Kendall Square has a severe adverse impact on housing affordability. By analyzing office-to-housing conversions, our vision is to gradually evolve Kendall into a more livable place where people can have better work-life symmetry.

Be-growth

Team members: Juan Villalon Hernando, Runke Luo, Sherry Lassiter, Zoe (Ziyao) Chen.

This is a tool to enhance sustainable urban agriculture production in urban areas. The main objective is to develop a policy approach that includes zoning explicitly to allow agricultural activities, and public health regulations to support and limit activities.